This global demand for clean and sustainable energy has pushed invention and development of more advanced PV technologies with high efficiencies and low manufacturing costs. Perovskite Solar Cells (PSCs) have developed as one of the most promising next generation tandem solar energy conversion devices owing to their excellent optoelectronic properties, tunable band gap, high absorption coefficient, long carrier diffusion length with respects to all of the above properties, and low temperature fabrication process. This paper provides a full performance analysis on PSCs considering the effect of absorber layer thickness, transport layer materials, temperature and defect density on the PV performance. The obtained simulation results are analyzed and can be applied to the realization of such multilayer PSC structure, Glass/ITO/ETL/Perovskite/HTL/Metal, by using tools like SCAPS-1D, COMSOL Multiphysics, MATLAB and Silvaco Atlas. PVs parameters such as short circuit current density (Jsc), open circuit voltage (Voc), fill factor (FF) and power conversion efficiency (PCE) were tested under various operating conditions. The result showed that the thickness of the absorber film nearly 700 nm and the combination of transport layers SnO₂/NiO gave the highest results of power conversion efficiency, close to 27% of the efficiency. Additionally, charge recombination, which decreases carrier mobility, was seen to be enhanced with increasing temperature and defect density effecting device performance. While PSCs can be prone to some problems, including moisture sensitivity, thermal instability and even lead toxicity, they show tremendous potential for applications in the field of renewable energy in the future. The study suggests that optimizing the materials, passivating material defects, using lead-free perovskites, and flexible or tandem perovskite architectures could pave the way towards achieving stable low-cost perovskites for sustainable power generation.

High strength concrete (HSC) is essential for modern infrastructure such as high-rise buildings, bridges, and marine structures. However, its high cement content contributes significantly to CO₂ emissions, making sustainability a critical concern. This research investigates the partial replacement of Ordinary Portland Cement (OPC 53 grade) with Calcined Clay (CC) and Silica Fume (SF) to produce M60 grade concrete with enhanced mechanical and durability properties. A control mix (100% cement) and four blended mixes with constant 10% SF and varying CC (10%, 12%, 14%, 16% by weight of cement) were prepared with a constant water-cement ratio of 0.30. Compressive strength was evaluated at 7, 14 and 28 days on 150 mm cubes. Flexural strength was measured at 28 days on 150×150×700 mm beams under third-point loading. Durability was assessed through water absorption (ASTM C642) and sorptivity (ASTM C1585). The results show that the optimum replacement level is 12% Calcined Clay + 10% Silica Fume. This mix achieved a 28-day compressive strength of 68.4 MPa (control: 55.2 MPa, +23.9%), a flexural strength of 7.8 MPa (control: 6.1 MPa, +27.9%), a water absorption of 2.48% (control: 3.85%, -35.6%), and a sorptivity of 0.072 mm/min⁰·⁵ (control: 0.124 mm/min⁰·⁵, -41.9%). Beyond 12% CC, performance declined due to incomplete pozzolanic reaction and dilution effects. The study confirms that the combination of 12% calcined clay and 10% silica fume produces M60 grade concrete that meets strength requirements, offers excellent durability, and reduces cement consumption by 22%, contributing to sustainable construction practices.

Thisstudypresentsacomprehensivenumericalinvestigationofmagnetohydrody-namic (MHD) blood-based nanofluid flow with coupled heat and mass transfer for cardio vascular prosthetic applications. There search add resses critical gapsin thermal regulation and targeted drug delivery modeling by developing a physiolog-ically realistic mathematical framework that incorporate select romagnetic effects, nanoparticle dynamics, and the non-Newtonian rheology of blood. The govern-ing conservation equations for mass, momentum, energy, and species concentration are formulated within a boundary layer framework, incorporating Lorentz forces, variablethermalconductivity,viscousdissipation,Jouleheating,Brownianmotion, thermophoresis,andchemicalreactions.Throughsimilaritytransformations,the non linear partial differential equation sare reduced to a system of coupled ordinary differential equations,whicharesolvednumericallyusingacollocationmethodim-plemented in Python (scipy. integrate. solve_bvp). A comprehensive parametric analysis reveals that thermal and solutal buoyancy significantly enhance momentum transport, while the Prandtl number governs thermal boundary layer characteristics. Nanoparticle transport is predominantly controlled by ther morphosis and Brown-Ian motion, with the omophoria’s promoting nanoparticle accumulation and Brown-Ian motion enhancing diffusion. The Schmidt number suppresses species diffusion, whiletheCassonparameterexhibitsminimalinfluenceonvelocitybutsignificantly affects thermal distribution. The magnetic para meter introduces resistive Lorentz forces that modify both momentum and thermal fields. These findings provide valu-able insights for the design of cardio vascular prosthetics, thermal therapy systems, and targeted drug delivery platforms.

Potential functions which described the anharmonic oscillators could reasonably predict metallic properties which are temperature dependent at room temperature but failed when applied to calculate these set of parameters at high temperatures. This is why a temperature dependent first order polynomial modulated by a simple exponential pair potential function was developed to estimate temperature-dependent properties of metallic .cubes, such as the coefficient of thermal expansionand the specific heat capacity of some selected cubic metals at temperatures higher thantheroomtemperature.The adjustableparametersin this pair potentialfunctionwere fitted to the lattice constant,the internal energy and the bulk modulusof the cubic consider in this study. The results generated showed a good agreement with both experimental values and some theoretical values of thermalcoefficients and elastic constants found in literature.

As more people are increasingly wanting to make use of electrical energy and because of environmental concerns caused by fossil fuel consumption, renewable energy which includes solar and wind energy is becoming increasingly popular. The reliability, unpredictability and intermittent nature of these resources, however, are significant hurdles for grid stability, reliable power supply and efficient use of most energy storage solutions. This work calls for a Closed Loop Hybrid Renewable Energy System (HRES) consisting of Solar Photovoltaic (PV) systems, Wind Turbine Generators (WTG), Battery Energy Storage System (BESS) and Model Predictive Control (MPC) that delivers optimized energy management and promotes grid stability. The system is modeled and simulated in MATLAB/Simulink and ETAP 19.0 for different solar irradiance, wind speed and load demand conditions. Renewable energy generation and load demand are predicted using Artificial Neural Networks (ANN) and ARIMA (Auto regressive Integrated Moving Average) time-series model to make energy dispatch decisions in advance. The MPC controller makes use of forecasted data to operate the battery charging/discharge operations for optimal performance while keeping voltage and frequency stable. The performance of the proposed framework is compared with the conventional PID and rule based control methods using simulation results which illustrate the significant increase in renewable energy utilization, decrease in fluctuations of electrical power into the grid and improvement in battery performance. The system employs around 90% of the renewable energy, reduces voltage deviation by 35%, reduces frequency deviation by 40% and prolongs battery life by 25%. The results show that the combination of predictive control and battery storage is a promising and effective approach for smart grid and renewable energy systems in the future.

Close to half Kenyan employers are dissatisfied with the level of skills of the graduates being churned out of Kenyan universities every year. This study sought to establish the effect that curriculum content has on the employability competency of the graduates produced by higher education institutions in Nairobi City of Kenya. The researcher utilized concurrent triangulation research design, a mixed method that provided for use of both qualitative and quantitative methods. A total of 379 fourth year students were randomly selected through stratified sampling from universities located within Nairobi County. Quantitative data was collected from fourth year students in their final semester of study in 15 universities in Nairobi City County and qualitative data collected from 30 curriculum developers and 25 potential employers in the labor market. At least 60.2% of the learners were satisfied with the curriculum content of the courses they had enrolled for, leaving out close to 40%. The study recommends restructuring of university undergraduate curricula, enhancing the vocational role of university courses, and introduction of work integrated learning and apprenticeship programs for learners.

for Fast-Moving Consumer Goods (FMCG) in emerging markets, a context that remains underexplored despite the rapid evolution of these consumer segments. We employed a sequential exploratory mixed-methods design, beginning with qualitative interviews and focus groups involving 55 participants (rural consumers, marketing professionals, and retail distributors), which identified four primary categories of influencing factors: economic constraints, institutional barriers, socio-cultural norms, and psychological determinants. These qualitative insights were then translated into measurement constructs for a quantitative phase, where we administered a structured questionnaire to 332 randomly selected rural households. Data were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM) alongside ANOVA, Chi-square, regression, and correlation analyses. Our results demonstrate that social networks ( ), attitude ( ), and perceived behavioural control ( ) significantly drive purchase intentions, while trust emerged as the strongest predictor of consumer attitudes ( ). The composite perceived barriers construct exerted a significant negative effect ( ), reflecting structural constraints such as income sensitivity and limited product availability. Moreover, qualitative findings revealed that rural consumers rank a well-furnished concrete house as their top aspiration, and marketing professionals noted growing brand consciousness alongside concerns about cultural threats from urban influences. The novelty of this research lies in its integration of qualitative and quantitative evidence to produce a context-specific framework of rural consumer behaviour, thereby addressing a gap in the empirical literature. These findings underscore the need for localized, trust-building marketing strategies that account for the heterogeneous aspirations and barriers within rural markets, offering actionable insights for marketers and policymakers.

The study investigated the effect of Computer Animation Techniques on Secondary School Students’ Interest, Achievement and Retention in Organic Chemistry in Zone A Area of Benue State, Nigeria. Quasi-experimental research design was adopted. The population of the study consisted of 3041 (1573 males and 1468 females) senior secondary two (SS 2) students from 85 co-educational public secondary schools across the seven local government areas in Education Zone A, Benue State. A sample of 361 (180 males and 181 females) SS 2 students from 6 co-educational public senior secondary schools in six local government areas in Education Zone A, Benue State was selected using a multistage sampling technique. Organic Chemistry Interest Rating Scale (OCIRS), Organic Chemistry Achievement Test (OCAT) and Organic Chemistry Retention Test (OCRT) were used for data collection. Mean and standard deviation were used to answer the research questions while Analysis of Covariance (ANCOVA) was used to test the null hypotheses at 0.05 level of significance. The findings were as follow: computer animation techniques significantly enhanced students’ interest compared to conventional method (P = 0.000 < 0.05). Computer animation techniques significantly enhanced students’ achievement in Organic Chemistry more than the conventional method (P = 0.000 < 0.05). Students taught Organic Chemistry using computer animation techniques have higher retention scores than those taught using conventional method(P = 0.000 < 0.05). Male students had higher interest and achievement scores than the female students when taught Organic Chemistry using computer animation techniques (P = 0.000 < 0.05). Male and female students had the same level of retention ability when taught Organic Chemistry using computer animation techniques (P = 0.986 > 0.05).The study concludes that despite the significant interaction effect of gender and computer animation techniques on students’ interest and achievement, the strategy plays crucial roles in enhancing students’ interest, achievement and retention in Organic Chemistry. Based on the findings of this study, it was recommended among others that computer animation instructional techniques should be given serious consideration by Chemistry teachers because of its proven positive effect on students’ interest, academic achievement and retention in Chemistry.

Storytelling has been a foundational pedagogical method within the Indian knowledge systems. (IKS) serving as a powerful medium for transporting ethical values, philosophical insights and practical wisdom across generations. Classical Sanskrit literature abounds with narratives that function not merely as literary compositions, but also as effective tools of education, such as Ramayana, Mahabharatha, Bhagavatha Purana, Panchatantra, etc., employee storytelling to communicate complex, moral Social and spiritual teachings in a form that is accessible, engaging and memorable. This paper explores storytelling as a significant pedagogical approach embedded in classical Sanskrit narratives and examines its role in shaping traditional modes of learning in India. The study highlights how narrative structures, character development, and dialogue exchanges within these texts facilitate experiential learning, ethical reflection, and emotional engagement among learners in the traditional Guru-Shishya framework stories function as instruments for cultivating virtues, such as Dharma-righteousness, compassion, courage, and wisdom by presenting moral dilemma, exemplary conduct and consequences of actions. These narratives encouraged learners to internal values through reflection and interpretation rather than through direct instruction alone. Furthermore, the paper argues that the narrative pedagogy found in Sanskrit tax resonates with contemporary educational theory that emphasize learner-centered approaches, experiential learning and the role of storytelling in cognitive and moral development by analyzing selected narratives from classical Sanskrit sources. The study demonstrates how storytelling bridges, knowledge, ethics and cultural heritage within the broader framework of Indian knowledge systems. The paper concludes at integrating traditional narrative pedagogy into modern educational context can enrich teaching practices, promote holistic learning and strengthen cultural continuity and contemporary academic discourse.

The exponential growth and increasing complexity of 5G networks present significant operational challenges that traditional rule-based management systems struggle to handle effectively. However, many existing approaches do not adequately capture traffic uncertainty, which limits their ability to adapt in highly dynamic network environments. To address this, the study proposes an optimized 5G Network Entropy-Guided Cyber Twin architecture. The methodology centres on the application of Shannon entropy to quantify traffic uncertainty across temporal, spatial, and service dimensions. This was executed through a tripartite framework: first, a traffic entropy model was developed to provide a mathematical foundation for uncertainty quantification; second, a Cyber Twin environment was constructed to serve as a high-fidelity virtual replica of the 5G network for safe and efficient policy testing; and third, a Soft Actor-Critic (SAC) reinforcement learning agent was designed to incorporate these entropy measures directly into its reward function. This integration allows the agent to make adaptive, data-driven resource allocation decisions that account for underlying traffic variability. Together, these components enable the joint optimization of resource allocation, power consumption, and system latency. The proposed framework was evaluated using the DeepSlice dataset from Kaggle, which contains 63,167 samples representing realistic 5G traffic patterns across three slice types: eMBB, URLLC, and mMTC. This dataset serves as the empirical basis for modeling and evaluation. Performance was evaluated against baseline methods, including conventional heuristic allocation and standard SAC without entropy integration. The results show that the proposed entropy-aware framework achieved a 98.64% URLLC compliance rate with a mean latency of 3.5 ms, yielding relative improvements of 30% to 91.6% across all slices compared to maximum QoS thresholds. Overall, this research developed an architecture that incorporates traffic entropy into the learning process, enhancing the adaptability and robustness of 5G resource management, providing a practical and scalable solution for real-time optimization in next-generation networks.

Hazardous waste management in nuclear, biomedical, and chemical environments presents serious safety risks because human workers may be exposed to radioactive materials, toxic chemicals, infectious substances, sharp biomedical waste, and unsafe surroundings. This paper presents the design and development of a Bluetooth-controlled robotic arm vehicle for remote hazardous waste inspection and material handling. The proposed system integrates an Arduino UNO controller, HC-05 Bluetooth module, L298N motor drivers, PMDC gear motors, a four-wheel mobile chassis, a night vision camera, and articulated robotic arms with a gripper. The system enables an operator to control vehicle motion, monitor the work area, and perform gripping operations from a safe distance. Mechanical design validation includes motor torque analysis, shaft bending stress, welded joint strength, square pipe bending stress, and battery performance. Calculated values such as 9.54 N-m wheel motor torque, 58.96 N/mm² shaft bending stress, 21 N/mm² welded joint stress, 15.79 N/mm² square pipe stress, 3.5 h charging time, and 2.1 h operating time show that the prototype is structurally safe and functionally suitable for controlled hazardous material handling. The developed system is low-cost, modular, and scalable for future integration of radiation, gas, temperature, and autonomous navigation sensors.

Self-study is the shortest path for learners to deepen and master knowledge. Learning is not just reproducing and repeating knowledge through pure memorization, but effective learning must be built on exploration, curiosity, and creative thinking. In Vietnam, teaching and learning are facing great opportunities and challenges because traditional and modern teaching approaches are not yet synchronized, lack continuity, and have not developed in a balanced way. In teaching Literature, organizing learning activities based on traditional methods still play a certain role. In writing lessons, teachers mainly provide theory, guide the essay structure, and may even brainstorm ideas for the learners. However, in the current context, these traditional methods of teaching text creation (writing) seem unable to meet the requirements of educational innovation. This is because teaching writing not only requires students to follow a specific text format, but also requires them to master writing skills. To master these skills, learners need to be taught using a suitable method. Given the characteristics of the current 2018 General Education Curriculum, teaching informational text writing in Literature using the flipped classroom model has shown many advantages and positive results because the flipped classroom model both effectively teaches text creation through the writing process: before, during, and after writing and helps learners develop their ability to brainstorm ideas, outline, study autonomously, and think creatively.

Crop yield estimation is a valuable tool for ensuring food security and optimization of resources under shifting climates. Conventional models often do not sufficiently consider the complex, non-linear relationships between climate and productivity of crops. To conclude, we introduce ClimateYield-AEF (Climate Yield Prediction with Augmented Ensemble Features), a novel ensemble architecture that integrates sophisticated climate feature engineering and optimal tree-based ML algorithms to improve yield prediction.
ClimateYield-AEF is a system that combines NASA POWER satellite climate data with USDA crop yield records and producesits 18 engineered features such as vapor pressure deficit (VPD), photothermal quotient, and comprehensive agricultural indices. Scientific data augmentation has been used to triplicate the size of the training dataset, while maintaining climate-yield relationships. Random forests, gradient boosting and extra trees models are tuned to the learning task selection of hyperparameters and weighted performance combination.
Through comprehensive evaluation with 5-fold cross-validation, the ClimateYield-AEF shows remarkable predictive performance [R² = 0.767 ± 0.032%, MAE =11.5 ± 1.7 bu/acre and mean absolute percentage error (MAPE) =8.% ± 5.] mediated by the model’s ability to capture the distinguishable patterns among weather factors and yield effects on multiple key dates throughout crop growth phase. The ensemble does much better than the individual models, where Random Forest yields R² = 0.574 and linear regression R² = 0.001. Importance of variables analyses showed that developed climate-related indices (radiation per growing degree day, photothermal quotient) were more important than the temperature and precipitations alone.
The results illustrate that the powerful combination of feature engineering and ensemble can effectively model climate-yield relationships in realistic agricultural forecasting. ClimateYield-AEF delivers production-ready accuracy significantly lower than the 15% MAPE threshold and provides agricultural actors with a strong basis for yield prediction under climate variability. This work is in terms of precision farming, due to its linking climate science and machine learning aiding decision-making proponents.

Pharmaceutical practice is being transformed in revolutionary ways through advances in artificial intelligence (AI) technology, particularly by assisting with drug discovery; making recommendations about the use of drugs based on patient characteristics; and improving the safety of medications through adherence monitoring. Pharmacists are better able to make informed decisions about drug interactions and other aspects of medication management with the support of AI tools that provide insight into patient-specific data. This review discusses how AI is utilized for clinical decision-making, improving medication safety, and supporting precision medicine, while also identifying barriers to successful implementation of AI in pharmacy practice, including concerns with privacy of patient data, algorithmic bias, and integration into the workflow of pharmacy practice. There is a need for all healthcare providers to be ethically vigilant and work together in order to successfully integrate AI into pharmacy practice, which has the potential to enhance the delivery of pharmaceutical care and improve patient outcomes.

The increasing prevalence of herbicide-resistant weeds, coupled with growing environmental and regulatory concerns associated with synthetic herbicides, has intensified the search for sustainable alternatives for weed management. Weed pathogenic fungi represent a promising source of biologically active phytotoxins that can be exploited for the development of metabolite-based mycoherbicide. The present study investigated the production of herbicidal secondary metabolites by four weed pathogenic fungi, Alternaria alternata, Fusarium oxysporum, Curvularia lunata, and Phoma herbarum, cultured on various synthetic and natural substrates. Fungal isolates were grown on Potato Dextrose Broth (PDB), Czapek Dox Broth (CDB), Richard’s Broth (RB), selected cereal grains, and natural liquid media supplemented with either yeast extract or weed tissue homogenate. Following incubation, crude metabolites were extracted using ethyl acetate and quantified gravimetrically. Significant differences in metabolite production were observed among fungal species, culture media, and supplementation treatments. Among the synthetic media, Richard’s Broth supported the highest metabolite production, whereas among natural substrates, red rice, broken sorghum, and sugarcane juice proved particularly favorable. The highest crude metabolite yield was obtained from Fusarium oxysporum cultured in sugarcane juice supplemented with weed tissue homogenate. Preliminary phytotoxicity assays demonstrated that the crude extracts induced chlorosis, necrosis, and tissue damage in target weed species, indicating the presence of biologically active herbicidal compounds. The findings suggest that inexpensive agricultural substrates can substantially enhance fungal metabolite production and provide a cost-effective platform for large-scale production of phytotoxins. These results highlight the potential of weed pathogenic fungi as sources of natural herbicidal compounds and support further research on metabolite characterization, formulation development, and field evaluation for sustainable mycoherbicide development.

Background: Harmful alcohol consumption remains a major public health concern globally and is associated with adverse physical, psychological, and socio-economic consequences. Despite increasing alcohol use among men in Nigeria, limited community-based evidence exists regarding perceptions of its effects.
Objective: This study assessed the perceived physical, psychological, and socio-economic effects of alcohol use among men aged 20 years and above in a rural community inAnaocha Local Government Area of Anambra State, Nigeria.
Methods: A descriptive cross-sectional survey design was employed among 262 men aged 20 years and above selected from a community in Anaocha Local Government Area. Data were collected using a structured questionnaire and analyzed using descriptive and inferential statistics. Mean scores were used to assess respondents' perceptions, while chi-square statistics were used to examine relationships between socio-demographic characteristics and perceived health effects of alcohol use at p < 0.05.
Results: Respondents perceived alcohol use as having substantial adverse effects across the physical, psychological, and socio-economic domains. The physical effects domain recorded the highest grand mean score (3.06), followed by psychological effects (2.83) and socio-economic effects (2.73). Respondents strongly agreed that alcohol use can contributes to physical injuries, deterioration of family economic well-being. Significant relationships were found between age and perceived health effects of alcohol use and between occupation and perceived health effects (p < 0.05), while marital status was not significantly associated with perceived health effects (p > 0.05).
Conclusion: The findings underscore the need for strengthened public health education, community-based interventions, and mental health support services.

Agriculture plays a pivotal role in economic development, particularly in developing countries where it supports livelihoods and food security. However, the sector faces persistent challenges such as fragmented supply chains, post-harvest losses, and limited market access. Value Chain Management (VCM) has emerged as a strategic approach to address these inefficiencies by integrating production, processing, logistics, and marketing systems. This study examines the role of VCM in improving farmer income, enhancing market access, promoting technological adoption, and ensuring sustainability. Using a conceptual research design supported by recent literature (2022–2026), the study develop saframe work linking value chain integration with key agricultural outcomes. The findings indicate that VCM significantly enhances efficiency, reduces losses, and contributes to rural development. The study suggest sare view-based frame work that illustrates the role of value chain integration in agricultural sustainability by increasing resource efficiency, access to markets, technological uptake and inclusive rural development. The results have implications for policy makers, researchers and agricultural stakeholders.

This article investigates the historical formation of the French capitalist class in Vietnam during the late nineteenth century, a process intrinsically linked to the first colonial exploitation program initiated by Governor-General Paul Doumer. Through a rigorous analysis of primary archival sources from the colonial administration and the financial dossiers of the Banque de l'Indochine, this study elucidates the structural composition and capital accumulation modalities of French syndicates, planters, and economic contractors. The findings indicate that the emergence of this class did not conform to conventional free-market mechanisms but rather depended heavily on a symbiotic nexus between financial monopoly and the protection of the colonial state’s coercive apparatus. Initial capital investments were predominantly concentrated in mineral extraction, transport infrastructure, and agrarian plantations, thereby establishing the foundations of an asymmetrical and unequal colonial economic structure. This research contributes a nuanced understanding of the nature of financial colonial capitalism in Indochina during its formative phase.

This article provides a systematic and comprehensive analysis of French capital investment inflows into three strategic consumer industries: beer, wine, and tobacco in Vietnam during the 1895–1945 period. Utilizing colonial administrative archives and the financial ledgers of the Banque de l'Indochine, this study exposes the corporate monopolies and regressive indirect taxation mechanisms executed by the colonial state. The empirical findings indicate that capital inflows into these industries were not aimed at constructing sustainable domestic manufacturing infrastructures; instead, they were calculated to maximize super-profits for elite French syndicates (notably the SFDIC for alcohol monopolies). The Banque de l'Indochine functioned as the supreme financial regulatory institution, providing not only capital liquidity but also institutional protection for trade monopolies, working in absolute synergy with the "triple monopoly taxes" (salt, alcohol, and opium) established by the Governor-General of Indochina. The study concludes that the legacies of these capital flows generated a distorted consumption framework and severely accelerated the economic pauperization of indigenous Vietnamese society under colonial rule.

This article systematically analyzes the public investment policies of the French colonial government in Vietnam from 1895 to 1945, focusing on elucidating the structural contradiction between the political-economic purposes of the metropole and the empirical results in the colony. Utilizing primary administrative archival documents and the financial portfolios of the Banque de l'Indochine, this study demonstrates that public investment programs—most notably the trans-Indochina railway system, strategic seaports, and hydraulic irrigation networks—were primarily engineered to optimize the extraction of primary commodities, fulfill military imperatives, and insulate the profit margins of French syndicates. Regarding the results, although these investments generated a specific modern technical infrastructure, they simultaneously imposed a regressive burden of public debt and excessive taxation upon the indigenous population through the floating of colonial bonds. Consequently, colonial public investment failed to foster sustainable development; instead, it exacerbated the dependent economic dualism of Vietnam, leaving profound structural distortions that persisted long after 1945.

This paper delivers a profound analysis of the executive leadership structure of the Banque de l'Indochine from its institutional inception to its ultimate withdrawal from Indochina (1875–1954). By exploiting primary colonial archival materials, this study elucidates the elite personnel networks comprising Governors, Directors, and Board members. The empirical findings reveal that the bank’s executives were not merely technical financial experts; instead, they were highly influential political figures representing an organic alliance between metropolitan industrial syndicates and the French colonial administrative apparatus. This leadership structure underwent significant reconfigurations across three pivotal historical milestones: the consolidation of institutional monopoly (1875–1900), the boom of colonial extraction operations (1900–1939), and the era of structural decline and power transfer driven by geopolitical cataclysms (1939–1954). Conclusively, the study affirms that the executive board of the Banque de l'Indochine functioned as the supreme core directing the mechanics of financial colonialism in Vietnam.

This paper delivers a profound investigation into the historical role and strategic operations of the Banque de l'Indochine during the turbulent epoch of the First World War (1914–1918). Capitalizing on primary colonial archival sources, this study elucidates how the institution shifted its operational focus from a conventional currency-issuing and credit institution to a potent wartime financial instrument serving the supreme interests of metropolitan France. The empirical findings indicate that against the backdrop of a war-torn metropole, the Banque de l'Indochine implemented draconian monetary tightening policies, accelerated the issuance of banknotes without sufficient bullion backing, and orchestrated aggressive war bond campaigns designed to drain Indochina's financial resources and channel them directly to Paris. This systemic intervention not only rescued the metropolitan treasury from imminent deficits but also severely disrupted the socio-economic structure of colonial Vietnam, plunging the indigenous economy into deep inflation and exhaustion.

This article focuses on analyzing the phenomenon of the decline in French capital investment flows into Indochina during the 1930s under the profound impact of the Great Depression (1929–1933). Based on the exploitation of original archival documents from the colonial administration and financial records of the Banque de l'Indochine, this study elucidates the trends of capital withdrawal, the freezing of both public and private investment projects, and the shifting of investment capital from productive sectors to defensive financial speculation. The research findings indicate that the metropolitan policies of monetary tightening and trade protectionism not only failed to salvage the colonial economic structure but also exacerbated the systemic exhaustion of the Vietnamese economy. This study contributes to providing a systematic perspective on the vulnerability and predatory nature of the financial-colonial economic model during historical periods of crisis.

Employee engagement has emerged as a critical factor in enhancing organizational performance, productivity, and employee well-being in modern workplaces. This study investigates the relationship between employee engagement and organizational productivity using a quantitative research approach. Primary data were collected from 150 respondents through a structured questionnaire, and statistical techniques such as descriptive analysis, chi-square tests, and Exploratory Factor Analysis (EFA) were applied. The demographic analysis highlights a young and moderately experienced workforce. Perception analysis reveals that although a majority of organizations have implemented formal engagement programs, many employees do not perceive a direct impact of engagement on productivity. Hypothesis testing shows no significant association between gender and engagement perception, while a significant relationship exists between geographic location and program implementation. Factor analysis identifies three key dimensions of engagement: organizational support and recognition, career development and alignment, and work-life integration, with organizational support emerging as the most influential factor. The findings suggest that effective engagement strategies must focus on supportive work environments and employee-centered practices.

Local anaesthetics are drugs that produce reversible loss of sensation in a localized area without causing loss of consciousness. Lidocaine hydrochloride is one of the most widely used amide-type local anaesthetics because of its rapid onset, effective anaesthetic action, and good safety profile. The present work focuses on the study of lidocaine hydrochloride injection including its mechanism of action, pharmacokinetics, adverse effects, preformulation studies, formulation, manufacturing process, evaluation parameters, packaging, storage, and regulatory requirements. Preformulation studies such as organoleptic evaluation, solubility, melting point, partition coefficient, pKa, pH, hygroscopicity, FTIR analysis, and stability studies were carried out to determine the physicochemical characteristics of the drug. The study concludes that lidocaine hydrochloride injection is a stable, safe, and effective sterile parenteral preparation suitable for local anaesthetic applications.

This study investigated the effect of Business Intelligence (BI) on competitive advantage in food and beverage firms in South-West Nigeria, with specific focus on data warehousing and data visualization. The study was anchored on the Resource-Based View (RBV) Theory and adopted a survey research design. The population comprised 14,230 employees drawn from selected food and beverage firms, namely Nestlé Nigeria Plc, Cadbury Nigeria Plc, Guinness Nigeria Plc, Nigerian Breweries Plc, and Flour Mills of Nigeria Plc. Using the Krejcie and Morgan formula, a sample size of 370 respondents was determined and selected through simple random sampling. Data were collected using a structured questionnaire and analyzed using descriptive statistics and simple linear regression with the aid of SPSS version 25. The findings revealed that data warehousing has a significant positive influence on competitive advantage (R² = 0.717, β = 0.860, F = 913.042, p < 0.05), while data visualization also exerts a significant positive influence on competitive advantage (R² = 0.770, β = 0.895, F = 1205.413, p < 0.05). The study concluded that effective utilization of BI components enhances organizational decision-making, operational efficiency, and market responsiveness, thereby strengthening competitive advantage. The study recommended that food and beverage firms should invest in robust data warehouse systems and integrate data visualization tools into their operations to improve strategic decision-making and sustain long-term competitiveness.

Background: The rapid ageing of India's population has underscored the critical role of pension systems in securing the socio-economic wellbeing of senior citizens. Despite several government-initiated pension schemes, persistent financial hardship, declining health, and social isolation continue to afflict the elderly, particularly those dependent on social security pensions.
Objective: This study examines the socio-economic profile of pension beneficiaries, investigates the nature and adequacy of pension schemes, analyses the socio-economic problems faced by senior citizens, and evaluates the influence of pension type on problem severity and life satisfaction.
Materials and Methods: A cross-sectional, descriptive survey design was employed with a purposive sample of 100 pension recipients. Primary data were collected through a structured interview schedule in 2026. Statistical tools including one-sample t-tests and the non-parametric Friedman test were applied to test the research hypotheses.
Results:Themajorityofrespondentswereaged60–69years(63%),male(55%),OBC(68%), and resided in rural areas (51%). Social security pension recipients (66%) constituted the largest group, receiving a mean monthly pension of Rs. 1,013, far below subsistence levels. Financial hardship was the most critical problem among social security pensioners (mean = 4.23),whileservicepensionersreportedphysicalimmobilityastheirprimaryconcern(mean= 3.00).TheFriedmantestconfirmedastatisticallysignificantvariationinproblemseverity
acrosspensioncategories(χ²=23.570,p=0.002).Despitethesedisparities,overallsatisfaction levels did not differ significantly across pension types (χ² = 14.733, p = 0.138).
Conclusion:The findings highlight the structur alinadequacyofIndia'ssocialsecuritypension schemes and the urgent need for upward revision of pension amounts, expanded health coverage, and community-based social integration programmes. Policy reforms targeted at marginalizedandlow-incomeelderlypopulationsareimperativeforensuringdignifiedageing in India.

Cancer involves uncontrolled cell growth that can spread in the body (Gates & Fink, 2008). Breast cancer is the most common cancer in women worldwide(WHO,2024).Itoftenbeginsintheducts or lobules of the breast. Early detection through screening improves outcomes. Treatment options include surgery, radiation, and drug therapies. Chemotherapyisakeysystemictreatmentformany cases. It works bydestroyingorslowing cancer cell growth. However, it also affects healthy fast-growing cells, causing side effects. Managing side effectshelpspatients continuetreatment. Following the full chemotherapy plan improves recovery and survival (National Cancer Institute, 2023).
Chemotherapy drugs act in different ways to stop cancer growth. Some damage the DNA of cancer cells,whileothersblockcelldivision.Thisprevents the cells from multiplying and spreading further. Chemotherapy may be given before surgery to shrinktumoursoraftersurgerytodestroyremaining cells. It is also used in advanced stages to control disease progression. The effectiveness depends on the cancer type and stage. Regular monitoring by doctors ensures proper response to treatment. Dose adjustmentsmaybemadebasedonpatienttolerance. Supportive care is important during treatment (Canadian Cancer Society, 2024).

Social media marketing has become a dominant force in influencing consumer behaviour, particularly among younger audiences. This study examines the role of influencer marketing in shaping consumer trust and brand loyalty, with a focus on key factors such as credibility, content relevance, engagement, and electronic word-of-mouth. This study adopted a descriptive research design to analyse the influence of influencer marketing on consumer trust and brand loyalty. The design enabled a systematic understanding of consumer perceptions without manipulating variables. Data were collected using a convenience sampling method, selecting respondents who are active social media users. The research was conducted across Kerala, a region with high digital awareness and strong social media usage, making it suitable for the study. A structured questionnaire was used to gather primary data on variables such as influencer credibility, content relevance, engagement, and trust. Statistical tools including percentage analysis, descriptive statistics, and factor analysis were applied for data interpretation. The results indicated that social influence, content relevance, and interactive communication are key determinants of trust, while reliance on influencer endorsements alone is limited. The study is relevant in guiding marketers to focus on authenticity, engagement, and credibility to build effective influencer marketing strategies.

Digital literacy has emerged as a critical driver of rural development in India, especially in the context of government initiatives like Digital India. This study investigates the role of digital literacy in promoting rural upliftment in Gulur Hobali of Tumkur Taluk, Tumkur District, Karnataka. The research aims to assess the current level of digital awareness and skills among rural residents, and how these capabilities impact their access to education, employment, government schemes, and essential services.
A mixed-method approach was adopted, combining primary data from surveys and interviews with secondary data from government reports and academic literature. A total of 100 households across villages in Gulur Hobali were surveyed. The findings indicate that while mobile phone penetration is high, actual digital literacy—defined as the ability to effectively use digital tools and services—remains limited, particularly among women and older adults. However, digitally literate individuals demonstrated improved access to online education, job portals, telemedicine, and welfare schemes such as e-Shram and PM Kisan.
The study highlights key challenges such as poor internet infrastructure, lack of localized digital content, and limited digital training programs. It concludes that while digital literacy has significant potential to contribute to rural upliftment, its success depends on targeted interventions, policy support, and active community engagement.

Artificial Intelligence (AI) is increasingly transforming the management, processing, and protection of personal data across public and private sectors. In Nigeria, the enforcement of the Nigeria Data Protection Act (NDPA) provides a detailed legal framework for safeguarding personal information and promoting responsible data governance. However, the integration of AI into data processing activities raises important ethical and legal concerns with respect to privacy, transparency, accountability, fairness, and regulatory compliance. This paper examines the relationship between AI technologies and data protection compliance in Nigeria by analyzing the ethical principles and legal requirements governing AI-driven data processing. Using a qualitative analytical approach founded on document review and policy analysis, the study evaluates the extent to which AI systems align with the provisions of the NDPA and international best practices. A reconstructed Ethical-Legal AI Compliance Framework is proposed to explain the interaction between AI governance principles and data protection obligations. The study concludes that effective AI governance, supported by ethical safeguards and legal accountability mechanisms, is essential for ensuring compliance, protecting individual rights, and fostering public trust in Nigeria's digital ecosystem.

This study examined the relationship between parental socioeconomic status (SES)—comprising income, occupation, and education level—and students' mathematics achievement in senior secondary schools across Nigeria's North-East geopolitical zone. A mixed-methods design was employed. Quantitative data were collected from 1,440 senior secondary students across all six North-East states (Adamawa, Bauchi, Borno, Gombe, Taraba, Yobe) using a Family Background Questionnaire and a standardized 50-item Mathematics Achievement Test. Qualitative data were gathered through semi-structured interviews with 72 participants and 18 focus group discussions. Data were analyzed using Pearson correlation, ANOVA, multiple regression, and thematic analysis. Findings revealed that Mathematics performance was critically low (mean = 24.6/50, SD = 11.3), with only 28.3% achieving credit level. All three SES indicators significantly correlated with achievement: parental income (r = .42, p < .001), father's education (r = .48, p < .001), and mother's education (r = .51, p < .001). Mother's education emerged as the strongest predictor (β = .28, p < .001). Students whose mothers had tertiary education scored nearly double (M = 35.8, SD = 8.2) those whose mothers had no formal education (M = 18.7, SD = 9.4). Qualitative findings revealed mechanisms: educated parents provide both material resources and academic guidance. Policies should prioritize adult education, particularly for mothers, as an intergenerational investment. School-based parent education programs can equip low-SES parents with strategies to support mathematics learning regardless of their own education level.

This study investigated how family structure influences mathematics achievement among 1,440 secondary students in North-East Nigeria. Quantitative data were analyzed using correlation, ANOVA, and multiple regression; qualitative data from 72 interviews and 18 focus groups provided explanatory depth. Family size correlated negatively with achievement (r = -.31, p < .001). Students from small families (≤5 children) scored significantly higher (M = 28.7, SD = 10.4) than those from large families (≥9 children) (M = 20.1, SD = 9.7). Students from monogamous families outperformed those from polygamous families (26.8 vs. 22.3, t = 8.92, p < .001). Parental marital status also mattered: intact families scored highest (M = 25.6), followed by widowed (M = 21.4) and separated families (M = 20.7). Qualitative data revealed resource dilution mechanisms: paternal attention divided among multiple wives, maternal time constrained by domestic responsibilities, financial resources stretched across many children. The study concludes that family structure significantly shapes educational outcomes. Interventions should include family planning education integrated with school programs and targeted support for students from polygamous and large families.

This study investigated the effect of total debt on the financial performance of listed deposit money banks (DMBs) in Nigeria, with firm size as a moderating variable. The persistent challenge of determining an optimal debt-equity mix, exacerbated by recent recapitalization policies and rising non-performing loans, motivated the inquiry. Using an ex-post facto research design, secondary data were extracted from the annual reports of all 13 DMBs listed on the Nigerian Exchange Group (NGX) covering the period from 2015 to 2024. Panel data regression based on a random effects model was employed to analyze the relationship between total debt (debt-to-asset ratio), firm size, profit margin, and return on assets (ROA). The findings revealed that total debt had a positive but statistically insignificant relationship with ROA (coefficient = 0.5687632, p = 0.54). While the direction of the relationship was positive, the lack of statistical significance suggests that aggregate debt levels, without distinguishing between short-term and long-term components, do not reliably explain variations in financial performance among Nigerian deposit money banks. The model explained 63% of the variation in ROA. The study concludes that undifferentiated total debt does not significantly influence bank performance. It is recommended that regulatory policies be bank-specific rather than uniform, and that the Central Bank of Nigeria support flexible debt instruments tailored to individual bank characteristics.

This study examined the relationship between long-term debt and the financial performance of listed deposit money banks (DMBs) in Nigeria over the ten-year period from 2015 to 2024. Using an ex-post facto research design, secondary data were sourced from the annual reports and financial statements of all 13 DMBs listed on the Nigerian Exchange Group (NGX). Panel data regression based on a random effects model, selected following Hausman specification tests, was employed to analyze the effects of long-term debt (measured as long-term debt to total assets) on return on assets (ROA), with firm size and profit margin as control variables. The findings revealed that long-term debt had a positive and statistically significant influence on ROA at the 1% significance level (coefficient = 5.328731, p = 0.000). This result is consistent with the trade-off theory, which posits that debt provides tax shield benefits that reduce the cost of capital and enhance firm value. The study concludes that long-term debt improves financial performance by providing management with an optimal capital mix to finance operations. This study recommended that bank management should prioritize long-term debt as a means of business financing and that the central bank of Nigeria (CBN) regulate the financial sector through monetary and fiscal policies to reduce the cost of borrowing.

The Indian Knowledge System (IKS) represents India’s indigenous intellectual heritage encompassing philosophy, science, education, health, ecology, and value-based living. The National Education Policy (NEP) 2020 emphasizes integrating IKS into teacher education to promote culturally rooted and holistic learning. Teachers play a crucial role in transmitting such knowledge; therefore, awareness and perception of IKS among teacher trainees become significant. The present study investigates the level of awareness and perception of Indian Knowledge System among B.Ed. trainees of Veer Narmad South Gujarat University (VNSGU). A descriptive survey method was employed on a sample of 120 B.Ed. trainees from affiliated colleges. Data were collected through a self-developed Awareness and Perception Scale on IKS. Findings indicate moderate awareness but highly positive perception towards the inclusion of IKS in teacher education. No significant gender difference was found in awareness, whereas perception differed slightly in favor of female trainees. The study concludes that systematic curricular exposure and pedagogical integration of IKS are required in B.Ed. programs under VNSGU.

Betel nut chewing functions as a social mechanism that fosters relationship-building by enabling individuals to interact within their community. This study analyzed how betel nut chewing contributes to the development of relationships among Ilocano chewers. Using a phenomenological approach, nine adult Ilocano betel nut chewers were interviewed through structured, face-to-face interviews. The analysis revealed three key themes: establishing trust, serving as a replacement for cigarette use, and sharing adapted culture. Informants described how betel nut chewing establishes trust, serves as an alternative to other vices, and facilitates communication through the sharing of tradition. The findings demonstrate that betel nut chewing influences social behavior, providing opportunities for interaction, knowledge exchange, and the formation of friendships. Ultimately, the practice extends beyond being a personal habit or vice, functioning as a cultural and social activity that strengthens bonds and contributes to community cohesion.

Theaimofthispresent studyistwoformulationsandevaluationsofthe antibacterial and antifungal activity ofwhich is widely used for the management of antifungal infections. The present study usesdusting powder. As formulated, the dusting powder is prepared by mixing all ingredients in a mortar and pestle uniformly. These are dusting powders and various types of creams. Gel powder ketoconazole is a lipophilic drug of an anti-yeast action used both locally and systematically. Dusting powder shows easy ability, non-irritability, free flowability & non-greasiness, and good absorption. Powder reduces inflammation and treats conditions like dermatitis.

The present study aims to examine the role of employee empowerment in enhancing organizational performance and achieving sustainable workplace outcomes. Employee empowerment refers to the process of granting employees the authority, autonomy, and confidence to make decisions related to their job responsibilities. Such empowerment enables employees to take ownership of their work, contribute innovative ideas, and participate actively in organizational decision-making processes. The underlying objective of employee empowerment is to increase employee responsibility, strengthen morale, improve job satisfaction, and enhance the overall quality of work life.This study explores the relationship between employee empowerment and organizational performance by analyzing various dimensions of workplace engagement. It highlights how empowerment serves as an effective motivational strategy that fosters a sense of belonging, commitment, and satisfaction among employees. The findings indicate that empowered employees are more likely to exhibit higher levels of productivity, dedication, and organizational loyalty.The study further reveals that employee satisfaction is significantly influenced by factors such as training and development opportunities, personal growth programs, employee participation in organizational activities, regular staff meetings, and management’s willingness to consider employee ideas and opinions. These practices create a supportive work environment that encourages employees to perform effectively and contribute to organizational success. Overall, the research concludes that employee empowerment is a critical organizational strategy that positively impacts employee satisfaction and organizational performance, thereby strengthening long-term organizational effectiveness and competitiveness.

This article investigates and elucidates the strategic role of the Banque de l'Indochine in the mining industry in Vietnam from 1885 to 1945. Employing historical and logical methods grounded in an extensive array of colonial archival sources, the study demonstrates that the Banque de l'Indochine was not merely a monetary issuing institution but the most powerful financial investor controlling the entire lifeblood of the mining sector. Immediately following the foundational French military pacification of Tonkin (1885), the bank rapidly intervened through the provision of exclusive credit lines, the acquisition of controlling shares, and the underwriting of corporate securities for major mining conglomerates, most notably the Société Française des Charbonnages du Tonkin (Hon Gai Coal Company). The institution functioned as a macroeconomic conduit to attract capital flows from the metropole in Paris into Vietnamese mining sites, transforming indigenous mineral resources into immense profits for the French financial oligarchy. The research findings confirm that the presence of the Banque de l'Indochine was the decisive catalyst driving the colonialization of the economy, shaping the distorted structure of the Vietnamese extraction industry, and directly serving the French colonial exploitation strategy prior to its ultimate demise in 1945.

This article provides an in-depth analysis of the organic and symbiotic relationship between the Banque de l'Indochine and the French colonial administration in Vietnam throughout the period from 1875 to 1945. Established by a French presidential decree, the Banque de l'Indochine was not merely a commercial financial institution, but rapidly evolved into the supreme political-economic instrument of the colonial ruling apparatus. Drawing upon colonial archival sources and a Marxist historical framework, this study elucidates the mechanism of the tight alliance between finance capital and the administrative power of the Governor-Generalship. This symbiosis manifested in the colonial government granting the monopoly of currency issuance and the management of public treasuries to the bank; conversely, the bank financed strategic loans to the colonial state to construct infrastructure for social control and pacification. The research findings confirm that this two-way relationship constituted the backbone of French financial colonialism, directly determining the outcome of colonial exploitation programs and leaving profound structural legacies on modern Vietnamese economic history.

This article provides an in-depth analysis of the lending activities and credit distribution of the Banque de l'Indochine in Vietnam during the early twentieth century (1900–1930). As the most powerful financial institution established by the French colonial administration, the bank functioned not merely as a currency issuance monopoly but as an optimal instrument for dominating and accelerating the flow of metropolitan finance capital into the colony. Utilizing historical and logical methods combined with the verification of colonial archival records, this study elucidates the structure of credit flows, which were heavily concentrated in large-scale rubber plantations in Cochinchina, mining conglomerates in Tonkin, and strategic transport infrastructure projects. The research findings indicate that the bank’s preferential and discriminatory lending policies directly stifled the indigenous economy while facilitating the expropriation of natural resources by French anonymous societies. This process transformed the Vietnamese economic structure into a colonial monoculture model, forging a tight nexus between finance capital and the French colonial administrative apparatus.

The escalating global demand for sustainable energy has exposed the severe ecological limitations of conventional chemical batteries, necessitating the development of biodegradable alternatives. This paper presents a comprehensive study on the design, fabrication, and performance analysis of a novel biobattery utilizing Aloe Vera (Aloe barbadensis Miller) gel as a natural electrolyte. The introduction contextualizes the environmental imperative for green energy storage systems. The methodology details the extraction of untreated Aloe Vera gel and the assembly of a non-toxic electrochemical cell. Experimental evaluations, focusing on varying electrode configurations—predominantly Zinc, Copper, and Graphite—and immersion depths, yielded a maximum stable open-circuit voltage of approximately 2.0 V under partial immersion conditions. A rigorous comparative analysis with alternative organic electrolytes (e.g., lemon juice and potato extract) demonstrates that while highly acidic fluids may produce transiently higher voltages, the unique structural integrity and mild acidity of Aloe Vera gel dramatically reduce electrode corrosion, enhancing long-term operational stability. Finally, the conclusion outlines the feasibility of plant-based bio-batteries as a scalable, low-cost paradigm for low-power electronics and proposes future directions for optimizing internal resistance in off-grid applications.

Project stakeholders are persons or entities who have specific interest in the projects, are affected by the decision, activity or the performance of the project. The synergy between project stakeholder’s and the project is critical because it directly determines the project success, influence the scope and fosters necessary trust while ensuring that the outputs meet the actual needs of those involved.The study examined the influence of stakeholder’ssynergy on performance of faith – based organizations. Specifically, the study examined the influence of cooperation, coordination, collaboration and control. The study was anchored on Social Exchange Theory. Descriptive research design was applied; data was congregated from 181 respondents carefully selected using Yamane’s formula and stratified sampling techniques from 310. Primary data was congregated by means of structured questionnaires, whereas secondary data were collected from organizational documents. Data was analyzed using Pearson's correlation and multiple regression analysis with SPSS version 24.0 and presented using descriptive statistics. The results indicates that cooperation among stakeholders exhibited by strongest positive correlations of 0.541** with p-value 0.000,coordination 0.540** p-value 0.000 strong and collaboration 0.319** p-value 0.000 moderate. The study concludes that cooperation between project stakeholder’s and the project is critical as it directly determines the project success while influencing the scope, fosters necessary trust and ensuring that the outputs meet the actual needs of the project and those involved. The study recommends strengthening collaboration mechanisms to have strong links for better performance which involves collective decision making while observing the rules and procedures, standardization, mutual adjustments and direct supervision among others.

The Tribes are those who have been living in forest for millions of years and their livelihood depend on the forest resources. During 19th century there is no much restrictions on forest resources for tribes all over the country. Implementation of conservation policies during early 70’s in India had a positive effects on the density of forest been improved from 17713 sq.kms to 26345 sq.kms in Tamil Nadu and also the population of tiger has been increased from 76 to 306. But the conservation policies made adverse negative effect on the economic condition of tribes due to the restrictions on forest access by government policies and programes of the government such as construction of dams, expansion of forests, Forest Rights Act and Tiger Reserve Act . The main objective of the paper is to demonstrate the livelihood pattern of the tribes earlier and their present scenario in Tamil Nadu. Thus the study revealed that the economic activities of tribes shifted from forest based subsistence economy to labour work and MGNREGA because of the conservation policies. There is need of government initiatives like employment opportunities to the tribes in the forest department because historically tribes involved in protecting forest and wildlife and also the government should incorporate the tribes in part of conservation policies rather than displacement.

This research investigates Genduren Paskah tradition observed by the Catholic community in Kedungrejo Village, Rowokangkung District, Lumajang Regency, East Java. This tradition serves as a cultural-religious expression that combine Javanese customs with Catholic spirituality. The study seeks to investigate the representation of Javanese Catholic identity and communal harmony through local cultural symbols and religious practices as embodied in the ritual. This study utilizes a qualitative descriptive method, drawing on Stuart Hall’s theory of representation and Roland Barthes’ semiotic approach. This analysis concentrates on the symbolic components of the ritual, which involve community gathering, prayers in the Javanese language, and traditional dishes such as sega gurih, ayam ingkung, and sambal goreng kentang. The results show that Genduren Paskah serves not only as a community Easter celebration but also as a cultural space where the concepts of faith, identity, gratitude, solidarity, and harmony are socially constructed and collectively interpreted. Using Hall’s representation theory, the ritual can be seen as a reflection of the Catholic community’s negotiation and expression of its religious identity in the context of Javanese culture. Barthes’ semiotic analysis further illustrates that ritual symbols function on denotative, connotative, and mythological levels, generating cultural meanings associated with devotion, unity, social harmony, and religious inculturation. The tradition exemplifies the integration of local cultural forms into Catholic religious life while preserving their cultural significance. This research adds to the discourse on cultural representation, semiotics, and religious inculturation by demonstrating the role of local rituals in the creation of meaning and the formation of identity within modern Indonesian society.

Crop Yield Prediction (CYP) in precision agriculture is a critical application involving various data-driven techniques and advanced technologies to estimate the potential harvest output of crops. The goal is to provide farmers with valuable insights into expected yields, allowing them to make informed decisions about resource allocation, crop management practices, and harvest planning. CYP is a complex task involving challenges and uncertainties like high computational time complexity and higher accuracy. This paper proposes a novel deep-learning technique for crop yield prediction in precision agriculture. The statistical, agricultural, and weather data are initially collected from Crop Production Statistics – India Dataset. Then, perform data cleaning and normalization using the min-max normalization method on collected data. After that, the Res2Net technique was used to extract the features. Then, select the essential features by eliminating unnecessary features using the Modified Red Deer Optimization Algorithm (MRDOA) algorithm to reduce the time complexity. Finally, the Deep Spiking Convolutional Neural Network (DCSNN) technique is employed to predict the crop yield in precision agriculture. We simulate and evaluate the performance on the Python platform and analyze the effectiveness through Root Mean Squared Error (RMSE), Mean Absolute Error (MSE), and Correlation Coefficient (R) metrics to calculate the outcomes of the DL crop yield prediction. Local, regional, and global decision-making can be improved by using the proposed method to anticipate agricultural yields more accurately and efficiently.

Environmental, Social and Governance (ESG) disclosure has become a central instrument for strengthening corporate transparency, accountability and sustainability communication. In India, SEBI’s Business Responsibility and Sustainability Reporting (BRSR) framework, along with the emerging emphasis on BRSR-Core and assured sustainability metrics, has created a stronger regulatory foundation for environmental reporting. At the same time, firms are increasingly using green marketing to communicate environmental responsibility to consumers, creating a need to examine whether such claims are credible, substantiated and aligned with regulatory expectations.
This paper examines the relationship between ESG regulations and green marketing practices in the Indian context, with specific reference to SEBI’s BRSR/BRSR-Core framework, ASCI’s guidelines on environmental claims and CCPA’s consumer-protection framework. Drawing on Signalling Theory and Stakeholder Theory, the paper develops a conceptual framework linking ESG disclosure, claim substantiation, regulatory compliance, perceived credibility and consumer trust. It argues that ESG disclosures can serve as credible signals only when consumer-facing green claims are specific, qualified, transparent and supported by verifiable evidence.
The paper further highlights the risks of vague, absolute or unsupported environmental claims, which may lead to greenwashing concerns, consumer scepticism and regulatory scrutiny. Through a conceptual and regulatory analysis, it brings together two streams often examined separately: sustainability reporting and marketing communication. By integrating these domains, the study contributes to the emerging Indian discourse on ESG-informed green marketing. It offers a structured basis for credible environmental claims and provides practical implications for firms, marketers, regulators and consumers seeking to build trust in sustainability communication in India’s evolving marketplace.

Stingray (Dasyatidae sp.) is a commodity in Indonesian waters with a large population that is used as smoked fish. Smoked fish is a fish processed traditionally through a hot smoking process. The study aims to evaluate the quality and its compliance with the Indonesian National Standard (SNI) for Smoked Fishin MSMEs in Rembang District. The study was conducted using a stratified random sampling technique from a population of 67 MSMEs in Rembang District. The study was conducted using observation, survey, case study, and laboratory testing methods, consisting of 9 MSME locations, namely A1, A2, A3, B1, B2, B3, C1, C2, and C3 with 3 repetitions. The test parameters were sensory, water content, fat content, protein content, total plate count (ALT), lead (Pb), and benzo(α)pyrene (BaP). The data were analyzed using SPSS 16 application, tested using normality, homogeneity, ANOVA, and Tukey HSD, while non-parametric data were analyzed using the Kruskall-Wallis test followed by the Mann-Whitney test. The results of the study showed that UMKM C1 (Bu Dami Smoked Fish) had the best quality based on sensory,nutritional, and foodsafety parameters. Theresults ofthesensoryanalysis ofsmoked stingray from 9 samples showed significant differences in the taste of smoked stingray (P>0.05). UMKM B1 showed high sensory values, water content of (69.91% ± 0.13), fat content of (0.73% ± 0.003), protein content (25.22% ± 0.006), for lead heavy metal contamination (0.096 mg/kg), total plate count (9.2 × 103 colonies/g). Thus, UMKM B1 is recommended as the best smoked stingray producer in RembangDistrict. The Benzo(α)Pyrene (BaP) test results that meet the requirements are found in UMKM A at 0.35 µg/kg.

This study examines the relationship between hours spent on the internet, time spent studying, and academic performance among students. The research adopted a descriptive survey design, and data were collected through a structured questionnaire administered to 200 respondents. Using both linear and multiple regression analysis, the study assessed how each variable influences students’ Grade Point Average (GPA). Results revealed that time spent on the internet had no significant effect on academic performance, as its contribution to GPA variation was minimal. However, study hours showed a strong and statistically significant positive relationship with academic performance, indicating that consistent study efforts directly improve students’ academic outcomes. The multiple regression model further revealed that both variables together affect performance, study time remains the dominant predictor of students’ academic success. The study concludes that while the internet can be a supportive tool for learning, excessive or uncontrolled use does not guarantee better performance. Therefore, students are encouraged to manage their internet time wisely and dedicate moretime to study hours t to enhance their academic success.

The rapid evolution of 5G and emerging 6G networks has introduced unprecedented challenges in managing highly dynamic, heterogeneous, and latency-sensitive traffic patterns, necessitating intelligent and adaptive solutions for network optimization. This paper proposes an integrated framework that combines explainable artificial intelligence with reinforcement learning to enable accurate network traffic forecasting and efficient quality of service optimization in next-generation communication systems. A deep learning-based forecasting module predicts future traffic using historical and contextual data, and these predictions guide a reinforcement learning agent to dynamically allocate resources and optimize routing in real time. To address the critical challenge of interpretability in autonomous network management, explainable AI techniques such as SHAP and LIME are incorporated to provide transparent insights into both forecasting outputs and decision-making policies. The proposed approach not only enhances key QoS metrics, including latency, throughput, and packet loss, but also improves trustworthiness and accountability in AI-driven network operations. Experimental evaluation using simulated network environments demonstrates that the integration of predictive analytics, reinforcement learning, and explainability significantly outperforms conventional optimization methods, offering a scalable and intelligent solution for future self-organizing 5G and 6G networks.

Soil properties play a significant role in determining the propagation characteristics of microwave and millimeter-wave signals in terrestrial environments. The present study investigates selected soil physicochemical parameters, including electrical conductivity (EC), pH, organic carbon (OC), and soil organic matter (SOM), in and around the Amera Coal Field region of Surguja District, Chhattisgarh, India. Soil samples were collected from five representative locations, namely Parsa, Ramgarh (Sitabengra), Amera Village, Latori (Navapara), and the Amera Coal Field area. Standard laboratory methods were employed for the determination of EC, pH, and OC, while SOM was estimated using the Van Bemmelen conversion factor.The results revealed considerable spatial variation in soil characteristics across the study area. The highest mean EC value was observed inside the Amera Coal Field (0.687 dS m⁻¹), whereas the highest pH and OC values were recorded at Parsa (5.86) and Amera Village (0.902%), respectively. Estimated SOM values ranged from 0.936% to 1.555%. Statistical analysis using mean, standard deviation, and coefficient of variation indicated significant heterogeneity among the sampling sites, reflecting the influence of mining activities and local environmental conditions.Since soil electrical and dielectric properties are closely related to moisture retention, ionic concentration, and organic matter content, variations in EC, pH, OC, and SOM are expected to influence electromagnetic wave propagation characteristics. The findings provide important baseline information for future modelling of microwave and millimeter-wave attenuation in the X-band frequency range under mining and dust-affected environments. The study contributes to understanding the relationship between soil quality and radio-wave propagation in coalfield regions.

Background: Uncontrolled hypertension represents a substantial global health challenge, markedly elevating the risk of cardiovascular diseases, cerebrovascular accidents (strokes), renal failure, and premature mortality. This study investigates the socio-demographic, clinical and behavioural characteristics of hypertensive patients at Bahati sub-county hospital in Nakuru, Kenya, employing SPICE digital Platform. The primary objective of this research is to determine the critical factors contributing to insufficient blood pressure control. The findings derived from this analysis are pivotal in shaping national health policies as Kenya endeavors to achieve universal health coverage. This initiative is anticipated to enhance hypertension management and improve patient outcomes across the region.
Method: This study employed cross sectional study design using data from the SPICE digital health platform, focusing on hypertensive patients enrolled between 2020 and 2023 with at least six months of follow-up. Descriptive analysis summarized socio-demographic, clinical and behavioral characteristics, and chi-square tests assessed factors of controlled and uncontrolled hypertension patients after six months of follow up. Logistic regression identified factors influencing uncontrolled hypertension, with odds ratios and 95% confidence intervals reported. All analyses, conducted using IBM SPSS version 25, applied a significance level of p < 0.05.
Results: The study of 1,199 hypertension patients revealed a significant gender difference, with 81.6% being female, a majority aged 70 and above, and 56.1% unemployed. Additionally, a separate study of 755 participants indicated that 76.47% had uncontrolled hypertension, particularly in the 50-59 age group, with many lacking formal education and insurance. Males were 21.1% less likely to control their hypertension compared to females, while risk of uncontrolled hypertension was lower in insured and employed group. Community Health Promoters follow-ups effectively enhanced hypertension control.
Conclusion: Addressing gender and ensuring equitable access to health insurance and employment are crucial for managing hypertension. Socioeconomic factors significantly impact health outcomes, emphasizing the need for community health promoters. These individuals enhance patient care by connecting healthcare providers with communities, delivering tailored interventions, and promoting health literacy, highlighting the importance of comprehensive approaches in hypertension management.

The present study reports a comparative analysis of the physicochemical characteristics of surface pond water and household drinking water sources within the Ambikapur (Surguja) region. Water samples were systematically collected from four strategic locations: Chillam Chowk Talab, Mahamaya Talab, Kharsiya Road Talab, and a domestic household supply line in the Chandni Chowk/Shastri Road area. Laboratory evaluations were performed at the District Water Testing Laboratory, Ambikapur, to determine physical and chemical parameters including pH, temperature, turbidity, total dissolved solids (TDS), electrical conductivity (EC), total hardness, and dissolved oxygen (DO). The study revealed significant variations in the physicochemical parameters between open surface water systems and managed domestic supplies. The values of the parameters for pond water ranged from pH7.40 to8.05 , turbidity 6.90 to7.30NTU, and TDS 388.00 to573.00mg/L, showing clear signs of environmental stress and organic load due to surface runoff and anthropogenic activities. In contrast, household drinking water samples demonstrated stable, neutral pH ranges and largely conformed to the safe permissible limits prescribed by BIS and WHO standards, though variations in total hardness were observed across groundwater-dependent taps. The study concludes that while domestic drinking water is generally safe for consumption, local pond ecosystems show clear degradation and require urgent conservation measures.

This research presents a systematic physical and chemical analysis of soil as a multiphase system collected from various sectors (sub-divided as locations R1 to R5) in Sanjay Park, Ambikapur (Surguja, Chhattisgarh). Soil dynamics are evaluated through fundamental principles of thermodynamics, fluid mechanics, and electrical charge transport. Key parameters including pH, Electrical Conductivity (EC), Organic Carbon (OC), and primary macronutrients (N, P, K) were quantified. Soil pH ranges from 5.1 to 6.7, showing slight acidity to near neutrality. Electrical conductivity values (0.14– 0.90 dS/m) demonstrate non-saline conditions suitable for sustainable flora maintenance. Natively generated TikZ/PGFPlots graphs describe spatial variations across the sampling profiles. The paper integrates classical transport equations to construct a quantifiable modeling matrix for soil ecosystem management.

Gelatin is a protein obtained from the hydrolysis of collagen derived from skin, bone, and connective tissue, commonly through acid hydrolysis followed by high-temperature extraction. Owing to its water-binding and gel-forming properties, gelatin can be used to improve the texture and gel quality of surimi-based products such as chikuwa. This study evaluated the effect of gelatin extracted from different fish skins, namely catfish, milkfish, and mackerel skins, on the gel quality of tilapia (Oreochromis niloticus) chikuwa. Chikuwa was formulated with 3% gelatin and analyzed for gel strength, texture profile, moisture content, water-holding capacity, and sensory properties. The study was conducted using a laboratory experimental method arranged in a completely randomized design. Parametric data were analyzed using analysis of variance followed by Tukey's honestly significant difference test, whereas non-parametric sensory data were analyzed using the Kruskal-Wallis and Mann-Whitney tests. The results showed that the type of fish-skin gelatin had a significant effect on all quality parameters of chikuwa (p < 0.05). The best treatment was obtained from the addition of mackerel-skin gelatin, which produced gel strength of 1461.50 g.cm, hardness of 0.44 kgf, cohesiveness of 0.11, springiness of 4.27 mm, chewiness of 0.15 kgf.mm, moisture content of 53.45%, water-holding capacity of 33.33%, and sensory scores within a confidence interval of 7.90 < µ < 8.22, indicating that the product was favored by panelists.

Ultrasonic communication has emerged as a promising alternative medium for short-range, low-power data transmission in Internet of Things (IoT) applications. This project presents the design, development, and evaluation of an ultrasonic IoT communication framework capable of transmitting digital information using inaudible high-frequency sound waves (typically above 18 kHz). The primary objective is to establish a cost-effective, hardware-independent communication channel that operates using existing audio interfaces such as microphones and speakers, thereby eliminating the need for conventional wireless technologies like Wi-Fi, Bluetooth, or RF modules.
The proposed system employs modulation techniques such as Frequency Shift Keying (FSK) and Amplitude Shift Keying (ASK) to encode digital data into ultrasonic signals. These signals are transmitted through standard audio hardware and received by compatible devices, where demodulation and decoding processes reconstruct the original data. The architecture integrates microcontrollers, signal processing algorithms, and IoT interfaces to enable seamless device-to-device communication.
In the implemented phase of the project, ultrasonic signal generation and modulation were successfully achieved, and experimental validation demonstrated reliable data transmission over short indoor distances. A basic receiver module was developed to perform signal filtering, decoding, and error detection. Performance evaluation indicates that ultrasonic communication offers advantages such as low energy consumption, enhanced security due to limited propagation range, and reduced interference compared to traditional RF-based systems.
Furthermore, the system shows potential for applications in secure authentication, proximity-based data exchange, indoor localization, and smart environments. Despite challenges such as environmental noise sensitivity and limited bandwidth, the results confirm the feasibility of ultrasonic communication as an innovative and efficient solution for next-generation IoT networks.

The rapid advancement of the Internet of Things (IoT) has enabled the development of smart and intelligent home environments that enhance user convenience, safety, and energy efficiency. This paper presents the design and development of an IoT-based Home Automation and Weather Monitoring System using the NodeMCU (ESP8266) microcontroller and a cloud platform. The proposed system integrates temperature and humidity sensing using the DHT11/DHT22 sensor along with appliance control through relay modules. The NodeMCU, equipped with built-in Wi-Fi, facilitates real-time data transmission to the cloud using protocols such as MQTT/HTTPS.
The system allows users to remotely monitor environmental conditions and control home appliances via a mobile or web-based dashboard. Additionally, automation rules can be implemented based on sensor data, enabling intelligent decision-making, such as activating fans when temperature exceeds a predefined threshold. The cloud platform provides data visualization, storage, and analytics, improving user awareness and system efficiency.
The proposed solution is cost-effective, scalable, and energy-efficient, making it suitable for modern smart home applications. It addresses the limitations of traditional systems by providing real-time monitoring, remote accessibility, and automated control, thereby contributing to the advancement of IoT-based smart living environments.

This project presents the design and implementation of an Eye Tracking Mouse system using Python, enabling users to control the computer cursor through eye movements without the need for a physical mouse. The system utilizes computer vision techniques with OpenCV and MediaPipe to detect facial landmarks and track eye gaze in real time. The iris position is mapped to screen coordinates to achieve smooth cursor movement, while blink detection using the Eye Aspect Ratio (EAR) algorithm is employed to perform mouse click operations.
The proposed system focuses on real-time performance, accuracy, and usability, incorporating smoothing techniques to reduce cursor jitter and improve stability. This solution is particularly beneficial for physically disabled users and provides an efficient hands-free human-computer interaction method. The system demonstrates a low-cost and accessible approach to modern touchless computing technologies.

The rapid growth of digital payment systems such as UPI, mobile wallets, credit cards, and online subscriptions has significantly increased the complexity of personal financial management. Individuals often struggle with fragmented financial data, lack of real-time insights, and ineffective traditional tools that primarily focus on manual tracking rather than intelligent decision-making. To address these challenges, this project proposes an AI-Based Real-Time Personal Finance Dashboard that functions as a smart financial assistant.
The system integrates financial data from multiple sources and provides a unified, real-time view of income, expenses, and savings. Leveraging machine learning techniques, it automatically categorizes transactions, detects unusual spending patterns, and analyzes user behavior to generate personalized financial recommendations. The dashboard also includes features such as budget monitoring, overspending alerts, and goal-based savings automation, enabling users to manage their finances proactively.
Interactive visualizations and analytics help users understand their financial habits and make informed decisions. By combining real-time data processing with artificial intelligence, the proposed system enhances financial awareness, promotes disciplined spending, and supports long-term financial planning. This approach transforms traditional passive finance tools into an intelligent, adaptive, and user-centric financial management solution.

In recent years, maintaining a healthy lifestyle has become increasingly important due to the rise in lifestyle-related diseases. Proper nutrition plays a vital role in improving overall health; however, many individuals lack personalized guidance and accurate tools to monitor their dietary habits. This research presents an AI-based nutrition web application designed to provide personalized diet recommendations using Body Mass Index (BMI) analysis and image-based calorie prediction.
The proposed system integrates multiple modules, including user authentication, BMI calculation, diet recommendation, daily dietary history tracking, and an intelligent image processing module. The application uses Convolutional Neural Networks (CNN) to analyze food images and estimate their calorie content, enabling users to track their intake more accurately. Additionally, a database system is implemented to store user information and historical data, allowing long-term monitoring and analysis.
The system is developed using modern web technologies and machine learning frameworks, ensuring scalability and efficiency. Experimental results indicate that the application provides reliable calorie predictions and improves the accuracy of diet recommendations compared to traditional methods. The proposed solution offers a user-friendly and intelligent platform that promotes healthier lifestyle choices and enhances awareness about nutrition management.

Agriculture is rapidly transforming through the integration of Artificial Intelligence(AI), Internet of Things (IoT), cloud computing, and mobile technologies. Traditional farming methods face major challenges such as crop diseases, water scarcity, unpredictable weather conditions, and in efficient market systems. This survey paper presents a comprehensive analysis of modern smart farming technologies and their role in improving agricultural productivity and sustainability. The study focuses on AI-based crop disease detection, IoT-enabled monitoring systems, real-time weather analysis, cloud-based agricultural services, and digital marketplaces for farmers. The paper also discusses the Green Genie platform, which aims to provide an integrated smart farming ecosystem using Flutter, Python, and Firebase technologies. The survey identifies the major research gap in current agricultural systems, namely the lack of centralized and user-friendly digital solutions for farmers. The study concludes that integrated smart farming platform scan significantly improve decision-making, reduce manual effort, and promote sustainable agricultural practices.

The Babon River in Semarang provides water for humans, animals, and plants; however, pollution from industrial and domestic activities can negatively impact the ecosystem and human health. This study aimed to determine the levels of Pb heavy metal pollution in sediment, water quality, and pollution index (IP) in the river. Sampling was conducted at three station points: residential areas, industries, and a combination of both types of areas. The analyzed parameters included BOD, COD, DO, pH, temperature, brightness, and Pb content using Atomic Absorption Spectroscopy (AAS). The results of the study showed that Pb sediment concentrations ranged from 4.99-32.24 mg/Kg, still within the USEPA threshold of 47.82 mg/Kg, making it safe or low-risk. Water quality analysis showed decreases in BOD and COD exceeding class II standards and DO in several areas. The Babon River was classified as having a light-pollution status. Continuous monitoring and waste management are crucial to prevent further pollution and maintain aquatic ecosystem sustainability.

The present study was aimed at the formulation and evaluation of matrix tablets of Salbutamol Sulphate using different polymers to develop a sustained-release drug delivery system. Salbutamol Sulphate is a bronchodilator widely used in the treatment of asthma and other respiratory disorders; however, its short biological half-life necessitates frequent dosing. To overcome this limitation, matrix tablets were prepared by the direct compression method using various polymers such as Hydroxypropyl Methylcellulose (HPMC), Carbopol, and Ethyl Cellulose at different concentrations.The prepared formulations were evaluated for pre-compression parameters including angle of repose, bulk density, tapped density, Carr’s index, and Hausner’s ratio. Post-compression studies were carried out for hardness, thickness, weight variation, friability, drug content uniformity, and in vitro drug release. All formulations showed satisfactory physical characteristics and complied with pharmacopeial limits. The drug release profiles demonstrated that polymer type and concentration significantly influenced the release rate of Salbutamol Sulphate. An increase in polymer concentration resulted in a slower and more controlled drug release pattern.The optimized formulation exhibited satisfactory physicochemical properties and sustained drug release for an extended period. The study concluded that matrix tablets prepared with suitable polymers can effectively control the release of Salbutamol Sulphate, thereby improving therapeutic efficacy, reducing dosing frequency, and enhancing patient compliance.

Background: Opioid analgesics are frequently prescribed for the management of moderate to severe pain; however, their improper use has contributed to increasing rates of misuse, dependence, and overdose worldwide. Community pharmacists play an important role in ensuring the safe and rational utilization of opioids and in preventing their abuse.{1,2,4,5,}
Objective: This study was conducted to assess opioid dispensing practices and abuse prevention strategies followed by community pharmacists.
Methods: A cross-sectional observational study was conducted among community pharmacists and pharmacy staff working in selected community pharmacies. Data were gathered using a structured and pre-validated questionnaire designed to evaluate opioid dispensing practices, prescription verification processes, patient counselling activities, awareness of opioid misuse, and strategies for abuse prevention{.,7 8}
Results: The results indicated that most pharmacists consistently verified prescriptions prior to dispensing opioids, including evaluation of dosage, treatment duration, and possible drug interactions. Counselling regarding safe use, adverse effects, storage, and disposal of opioids was commonly provided to patients. Pharmacists also reported monitoring repeat prescriptions and detecting suspicious prescribing behaviours. However, several challenges were identified, such as limited access to Prescription Drug Monitoring Programs (PDMPs), inadequate training, high workload, and insufficient staffing.
Conclusion: Community pharmacists play a crucial role in opioid stewardship through prescription monitoring, patient counselling, and implementation of abuse prevention strategies. Enhancing training programs and improving access to prescription monitoring systems may further strengthen efforts to prevent opioid misuse.

Digital Public Infrastructure (DPI) has emerged as one of the most transformative innovations in public governance and economic management during the twenty-first century. India has developed a globally recognized DPI ecosystem through initiatives such as Aadhaar, Unified Payments Interface (UPI), Direct Benefit Transfer (DBT), Jan Dhan Yojana, DigiLocker, and various e-governance platforms. These systems have significantly influenced the functioning of economic administration and financial inclusion by improving transparency, efficiency, accountability, and accessibility of public services. Rajasthan, one of India's largest states, has actively adopted digital governance initiatives to enhance service delivery and welfare administration.
The present study examines the impact of Digital Public Infrastructure on economic administration and financial inclusion in Rajasthan. The study employs an empirical framework based on secondary data and a simulated survey of beneficiaries, government officials, and banking correspondents across selected districts of Rajasthan. The findings indicate that DPI has substantially improved administrative efficiency, reduced leakages in welfare distribution, enhanced financial access among marginalized populations, and strengthened citizen-government interactions. The study also identifies challenges related to digital literacy, internet connectivity, cybersecurity, and socio-economic inequalities.
The paper concludes that Digital Public Infrastructure has become an essential instrument for promoting inclusive development and strengthening economic governance in Rajasthan. The study recommends investments in digital literacy, infrastructure development, cybersecurity frameworks, and institutional capacity building to maximize the developmental benefits of DPI.

Students in many secondary schools lack social integration skills and competencies required for harmonious interaction in the 21st century. Consequently, these learners do not relate effectively with peers from diverse cultural and linguistic backgrounds which often results in exclusion and classroom conflicts in the long run. Even their present social needs in daily school activities are not easily addressed due to weak collaborative competences and one of the ways to address this issue is through drama-based pedagogy in diverse classrooms. This study investigated social integration outcomes through drama-based instruction. It is a randomized control trial with 100 participants, 50 students randomly assigned to experimental group and another 50 students assigned to the control group with age bracket of 14 to 19 years. The results of this study reveal that there is a statistically significant difference between the social integration outcomes of students in the experimental group (Mean = 8.72, SD = 1.48) and the control group (Mean = 6.84, SD = 1.91), with the experimental group performing better (p < 0.05, Cohen’s d = 0.62, 95% CI [0.58, 1.46]) in application of social concepts. The findings of this research imply that curriculum planners and other educational stakeholders should integrate drama-based pedagogy in social integration programs offered in secondary institutions to improve social integration outcomes.

International students in many tertiary institutions lack intercultural knowledge, skills, and competencies required for sociocultural survival in host countries. Consequently, these learners misinterpret cultural cues and experience social isolation which often results in poor academic engagement and adjustment difficulties in the long run. Even their present social and academic needs in daily activities are not easily addressed due to limited cultural literacy, and one of the ways to address this issue is through performance pedagogy in intercultural education. This study investigated cultural integration outcomes through performance-based instruction. It is a randomized controlled trial with 100 participants, 50 students randomly assigned to the experimental group and another 50 students assigned to the control group with an age bracket of 18 to 24 years. The results of this study reveal that there is a statistically significant difference between the application of intercultural variables by students in the experimental group (Mean = 8.62, SD = 1.48) and the control group (Mean = 7.04, SD = 1.78), with the experimental group performing better (p = .004, Cohen’s d = 0.59, 95% CI [0.46, 1.32]) in cultural integration scores. The findings of this research imply that curriculum planners and other educational stakeholders should integrate performance pedagogy in intercultural programs offered in tertiary institutions to improve cultural integration outcomes.

The availability of infrastructure is one of the important factors in supporting the implementation of employee duties and functions in health care facilities. Adequate infrastructure can increase the effectiveness, efficiency, and work productivity of employees so that it has an impact on improving the quality ofhealth services to the community. This studyaims to determinetheroleof infrastructure availabilityon employeeperformance at the Poasia Health Center in Kendari City.

This type of research is a quantitative research with a cross sectional study approach. The population as well as the sample in this study is all employees of the Poasia Health Center in Kendari Cityas manyas 145 people with a total samplingtechnique. Theresearch instrument
used a questionnaire. Data analysis was carried out univariate and bivariate using the Chi-Square test with a confidence level of 95% (α = 0.05).

Theresultsofthestudyshowedthattherewasasignificantrelationshipbetweentheavailability of infrastructure and employee performance at the Poasia Health Center in Kendari City with a p-value of <0.05. Adequate infrastructure is able to support the smooth implementation of tasks, increase work productivity, and improve the quality of services to the community.

The conclusion of this study is that the availability of infrastructure has a significant role in employee performance. Therefore, improving work facilities and infrastructure needs to be a concern in an effort to improve the quality of health services at the Poasia Health Center in Kendari City.

This study introduces a probabilistic framework to assess both structural stability and occupant safety in an indoor sports hall, using Lead City University as a case example. The method combines non-linear finite-element analysis of the main steel–concrete system with stochastic simulations of uncertainties in loads, materials, and boundary conditions to determine failure probability through a limit-state approach. Monte Carlo simulations account for these uncertainties to generate reliability metrics. Simultaneously, an agent-based evacuation model evaluates egress efficiency under various emergency scenarios, including fire, power outage, and combined hazards, while considering different exit layouts and lighting conditions. The structural analysis reveals key failure modes, such as elastic buckling of portal frames, local rafter buckling, and brittle connection failure, with an overall failure probability of approximately 3.7 × 10⁻⁵ for the baseline setup, reflecting strong structural reliability under design loads. Evacuation results show that safe egress for about 1,200 occupants can be achieved within roughly 540 seconds with four exits and improved wayfinding/lighting; without these measures, congestion and delays significantly rise. The findings are translated into practical recommendations: enhance or redesign critical connections and bracing, adopt reliability-based load factors, expand and clearly mark egress routes, and implement targeted safety training and facility management. This integrated approach highlights how combining probabilistic structural reliability with egress performance assessment can guide design improvements and operational strategies for university sports halls and similar large-assembly venues.

Manuscript collections in active Indian monasteries are living cultural assets facing conservation costs of 1,800–2,400 crore INR over 20 years, yet 92% lack formal revenue mechanisms. This study evaluates revenue sharing models that connect manuscript tourism and controlled digital access to monastery sustainability. We surveyed 42 monasteries across 8 states, conducted 186 interviews, and analyzed 2018–2025 financial data. Four revenue streams were modeled: ticketed viewing, licensed digital access, experience-based tourism, and academic/commercial image use. Monasteries with formal agreements earned 3.8–11.2 lakh INR annually versus 0.3–0.9 lakh for donation-only sites. Digital licensing produced 2.1x higher net revenue than physical tourism while reducing handling risk by 97%. The most equitable models allocated 40–60% to conservation, 20–30% to community welfare, 15–25% to custodian livelihoods, and 5–10% to a pooled risk fund. Barriers include unclear intellectual property status, absence of standard contracts, infrastructure gaps, and doctrinal limits on commodification. We propose a “Sacred Knowledge Stewardship Framework” comprising: 1) A Community-Controlled Licensing Entity, 2) Tiered pricing with free, research, and commercial levels, 3) Reinvestment rules codified in trust deeds. Monte Carlo simulation shows adoption across 200 repositories could generate 42–68 crore INR annually and 1,800–2,400 livelihoods. The framework reframes manuscripts from cost centers to community assets while maintaining spiritual authority with custodians.

Mackerel (Rastrelligersp.) hasa highpotentialasasourceofoilrichin omega-3. Ice cream is a frozen product with a sweet flavor that is commonly consumed as a dessert.As consumer demand for functional foods that promote health continues to rise, various efforts have been made to substitute raw materialstoenhancethenutritionalvalueoficecream.Oneinnovationthatcanbeapplied is the production of ice cream containing omega-3 fatty acids through the addition of mackerel oil.This study aimed to determine the characteristics of ice cream with added mackerel oil and identify the optimal formulation for adding mackerel oil to ice cream and the resulting omega-3 content.An experimental laboratory study with a Complete Randomized Design (CRD) was used.The treatments used in this study were the addition of mackerel oil at concentrations of 0% (EM0), 1% (EM1), 3% (EM3), and 5% (EM5). Hedonic test analysis used the Kruskal-Wallis test, followed by the Mann-Whitney test. Testing of overrun, melting point, emulsion stability, viscosity, and fat content used ANOVA (Analysis of Variance) and the Honest Significant Difference (HSD) test. The best treatmentwas EM5, with a 5% addition of mackerel oil, which yielded a hedonic score of7.55

Background: Drug logistics management is a series of activities aimed at ensuring the availability of safe, quality drugs that meet the needs of health services. Problems such as drug shortages, discrepancies in the number of drugs received, and limited storage facilities are still found at the BLUD UPTD Mokoau Health Center, Kendari City, which has the potential to affect the continuity of health services. This study aims to analyze the implementation of drug logistics management at the BLUD UPTD Mokoau Health Center, Kendari City in 2025. Methods: This study uses a qualitative method with a descriptive approach. Data were collected through in-depth interviews, observations, and document reviews with two key informants and three supporting informants. Data analysis was carried out through data reduction, data presentation, and conclusion drawing.Results: The implementation of drug logistics management in general has been in accordance with the 2019 Technical Guidelines for Pharmaceutical Service Standards at Community Health Centers. Drug planning is carried out based on DOEN and FORNAS by utilizing stock opname data, LPLPO, consumption methods, morbidity methods, and buffer stock. Drug procurement is carried out through routine requests, special requests, and independent procurement when stock is empty. Drug storage applies the FIFO and FEFO principles as well as special management for high alert drugs, LASA, narcotics, and psychotropics. Drug distribution, recording, and reporting have been carried out according to procedures. Obstacles found include drug stock shortages, excess stock due to dropping program drugs, limited storage space, and the lack of a special cabinet for narcotics and psychotropics. Conclusion: Drug logistics management at the BLUD UPTD Mokoau Health Center has been running quite well and mostly meets standards, but improvements are still needed in the procurement and storage aspects to support drug availability and the quality of health services.

Starry triggerfish (Abalistes stellaris) is a fishery resource with a relatively high protein content and considerable potential for development into processed products such as fish nuggets. Processing fish into nuggets aims to increase added value, extend shelf life, and improve consumer acceptance. The addition of carrots in fish nugget production may provide a golden color and a softer texture to the product. This study aimed to determine the effect of carrot addition on the chemical characteristics and panelist acceptance of starry triggerfish nuggets and to identify the best formulation. This study employed an experimental method using a completely randomized design (CRD) consisting of four carrot-addition treatments, namely K (0%), A (10%), B (20%), and C (30%). The observed parameters included proximate analysis, consisting of moisture, protein, fat, ash, and carbohydrate contents, as well as hedonic evaluation of appearance, odor, taste, and texture. The results showed that carrot addition affected the chemical characteristics of starry triggerfish nuggets. Increasing carrot concentration tended to increase moisture and carbohydrate contents, while decreasing protein and fat contents. The hedonic test results indicated that treatment B, with 20% carrot addition, was the most preferred treatment by the panelists based on appearance, odor, taste, and texture. Therefore, it can be concluded that carrot addition influences the characteristics and acceptance level of starry triggerfish (Abalistes stellaris) nuggets, with the best formulation obtained at 20% carrot addition.

The increasing number of divorce cases in Central Java during 2017–2019, along with the various social problems arising from divorce, highlights the need for effective and region-specific divorce prevention strategies. Since each district and city has distinct characteristics related to the factors contributing to divorce, clustering analysis can provide valuable insights for designing targeted interventions. This study applies the Self-Organizing Maps (SOM) algorithm, an unsupervised neural network approach, to cluster districts and cities in Central Java based on divorce-related factors. The analysis uses data from 35 regencies and municipalities in Central Java Province in 2019 and incorporates 13 variables representing the causes of divorce. Several clustering scenarios consisting of 3, 4, 5, and 6 clusters were evaluated. The SOM model was trained using a learning rate of 0.50, Euclidean distance, a maximum of 1,000 iterations, an initial neighborhood radius of 1, a bubble neighborhood function, and linearly decreasing learning rates and neighborhood radii. Initial weights were randomly selected from the input vectors. Clustering performance was assessed using the silhouette coefficient. The results indicate that the three-cluster solution provides the best partition, achieving the highest silhouette coefficient of 0.39547. The resulting clusters consist of 13 regencies/municipalities in Cluster 1, 10 in Cluster 2, and 12 in Cluster 3. These findings provide a basis for developing more targeted and region-specific policies to address divorce-related issues in Central Java.

Vannamei shrimp (Litopenaeus vannamei) is one of the major fishery commodities in Indonesia. The processing of vannamei shrimp generates a by-product in the form of shrimp broth, which is rarely utilized and may potentially cause environmental pollution. However, shrimp broth contains glutamic acid. Therefore, shrimp broth has potential to be processed into powdered broth. The production of powdered broth requires a filler. Cornstarch is one filler that can produce good product consistency. In addition, cornstarch can improve product texture and stability. Therefore, this study investigated the addition of cornstarch to vannamei shrimp powdered broth. This study aimed to determine the effect of adding cornstarch at different concentrations on the physical and chemical characteristics of vannamei shrimp powdered broth. The study used a completely randomized design with one factor, namely differences in cornstarch concentration: 0% (K), 5% (A), 10% (B), and 15% (C). The resulting vannamei shrimp powdered broth was analyzed for physical properties (yield and color) and chemical properties (moisture, protein, and glutamic acid). The results showed that higher cornstarch addition increased yield and moisture content, whereas protein and glutamic acid contents decreased. For color attributes, cornstarch addition increased lightness. The best vannamei shrimp powdered broth was obtained with 5% cornstarch addition, containing 5.70% moisture, 41.13% protein, and 1.93% glutamic acid. The addition of 5% cornstarch produced a yield of 9.58%, with L*, a*, and b* color values of 80.69, 6.72, and 16.65, respectively.

The Western Ghats, recognized as one of the world’s eight "hottest hotspots" of biological diversity, host a rich array of flora and fauna, including numerous ant species that play crucial roles in ecosystem functioning. This study aims to assess the diversity, distributionand habitat association of ant species in the Satara district of Maharashtra, India a region within the Northern Western Ghats. Extensive field surveys were conducted across different habitats such as forested areas, grasslands, agricultural fields, and human settlements using standardized sampling techniques including pitfall trapsand hand collection. Species richness and abundance varied significantly across habitat types, with forested areas exhibiting the highest diversity. The results highlight the importance of microhabitats and vegetation cover in maintaining ant biodiversity and underline the need for conservation efforts in the face of increasing anthropogenic pressures. This study provides baseline data essential for future ecological research and conservation planning in the Western Ghats region.

Malnutrition among adolescent girls in Uttar Pradesh (UP) represents a significant public health challenge with far-reaching consequences. This critical age group (10–18 years) undergoes rapid physical and cognitive development, and inadequate nutrition during this period can lead to stunted growth, weakened immunity, poor academic performance, early pregnancy complications, and long-term health issues. The present study explores the prevalence, underlying causes, and preventive strategies related to malnutrition among adolescent girls in both rural and urban regions of UP.
Secondary data from the National Family Health Survey (NFHS-5) reveals that approximately 43.5% of adolescent girls in UP are anemic, and over 30% suffer from under nutrition, including stunting and being underweight. The burden is more pronounced in economically disadvantaged and socially marginalized communities. Root causes include poverty, food insecurity, gender-based discrimination, poor dietary habits, early marriage and pregnancy, lack of access to adolescent health services, and low awareness regarding nutritional needs.
The government initiatives such as the Rashtriya Kishor Swasthya Karyakram (RKSK), Weekly Iron and Folic Acid Supplementation (WIFS), mid-day meal schemes, and the role of Adolescent-Friendly Health Clinics (AFHCs). Despite existing programs, gaps in implementation, limited outreach, and cultural barriers reduce their effectiveness.
The study concludes that a comprehensive, multi-sectoral approach is essential for addressing adolescent malnutrition. This includes strengthening nutrition education in schools, empowering girls through awareness and community participation, enhancing food and health security, and ensuring convergence among health, education, and nutrition sectors. Focused efforts in UP can improve adolescent well-being and contribute significantly to breaking the intergenerational cycle of malnutrition.

Kupipakwa Rasayana, a specialized class of herbo mineral preparations in Rasa Shastra, involves heating materialstypically sulfur (Gandhaka) and mercury (Parada)in a glass bottle (Kupi) embedded in a sand bath (Valukayantra) to produce red sulfide of mercury (Sindura). Current manufacturing relies on empirical temperature control, manual observation of reaction progression, and batch-to-batchvariability.Digital twin technology, which involves the virtual replication of physical processes with real-timedata integration, has transformed pharmaceuticalmanufacturing but remains unexplored in RasaShastra.This review examines the physicochemical basis of Kupipakwa reactions (temperature-dependentphase transitions, vapor-soliddeposition, and gradient crystallization), evaluates existing monitoring methods (thermocouples, visual inspection, and offline product assay), and proposes an AI-guided digital twin architecture.The framework combines: (1) an instrumented Kupi with embedded thermocouples at three axial positions; (2) computational fluid dynamics modelling of Valuka yantra heat transfer; (3) a reaction kinetics model for HgS formation (activation energy 45–55 kJ/mol); and (4) machine learning predictors (long short-term memory, random forest) for real-time product quality estimation (particle size, free mercury content, color uniformity).The validation pathway includes laboratory (50 g batch) and pilot (500 g batch) scales.The integration of Industry 4.0 enables remote monitoring, predictive maintenance, and batch traceability.This approach transforms an artisanal process into a data-driven , quality-by-designoperation.

The construction industry faces significant challenges in project monitoring, communication, documentation, and progress tracking. Traditional method soft enrelyon manual paperwork, phone calls, and messaging applications, leading to poor documentation, data loss, and inefficient coordination. This paper presents an Online Construction Resource Planning and Tracking Platform that enables real-time monitoring of construction activities through a centralized web-based system. Supervisors can upload construction siteimages along with descriptive notes, while administrator scan remotely access and monitor project progress through a secure dashboard. The system is developed using PHP, MySQL, HTML, and CSS. It improves communication, enhances transparency, reduces paper work, and provides reliable project documentation for construction organizations.

This study examined the relationship between generative artificial intelligence (AI) tools and students’ research skills in public universities in South-South Nigeria. Specifically, the study investigated the relationship between AI content generation, AI paraphrasing tools, and students’ research competencies. A correlational survey research design was adopted for the study. The population comprised 126,482 undergraduate students from six selected universities: University of Port Harcourt, University of Uyo, University of Calabar, Rivers State University, Delta State University, and AkwaIbom State University. A sample size of 399 respondents was determined using Taro Yamane’s formula, while a multistage sampling technique involving stratified and simple random sampling methods was employed.Data were collected using a structured questionnaire titled Generative Artificial Intelligence Tools and Students’ Research Skills Questionnaire (GAITSRSQ), which demonstrated high reliability coefficients (α = 0.83 for AI content generation, α = 0.85 for AI paraphrasing tools, and α = 0.88 for research skills). Data analysis was conducted using Pearson Product Moment Correlation at a 0.05 level of significance.Findings revealed a moderate positive and statistically significant relationship between AI content generation and students’ research skills, indicating that students who utilize AI tools for content generation tend to demonstrate improved abilities in idea development, literature organization, and academic writing. Similarly, a moderate positive and significant relationship was found between AI paraphrasing tools and students’ research skills, suggesting that these tools enhance students’ ability to rephrase content, improve clarity, and avoid plagiarism.The study concluded that generative AI tools significantly contribute to the development of students’ research skills, although their influence is moderate and should be complemented with independent critical thinking and traditional learning approaches. It was recommended that universities promote AI literacy, establish ethical guidelines for AI usage, and integrate responsible AI practices into academic curricula to maximize benefits while minimizing potential drawbacks.

The increasing integration of social media into adolescents&#39; daily lives has generated concerns regarding its implications for mental health. This study investigated the influence of social media usage on mental health outcomes among adolescents in secondary schools in AkwaIbom State, Nigeria. Specifically, the study examined the influence of social media usage intensity and problematic social media use on mental health outcomes among adolescents. The study adopted a descriptive survey research design. The population comprised 12,840 Senior Secondary II students in public secondary schools in Uyo Senatorial District, AkwaIbom State. A sample of 388 respondents was determined using the Taro Yamane formula and selected through multistage sampling procedures. Data were collected using the Social Media Usage and Mental Health Outcomes Questionnaire (SMUMHQ). Data were analyzed using mean, standard deviation, and simple linear regression. Findings revealed that social media usage intensity significantly influenced mental health outcomes among adolescents, while problematic social media use also significantly influenced mental health outcomes. The study concluded that excessive and problematic engagement with social media contributes substantially to adverse mental health outcomes among adolescents. It was recommended that schools, parents, and educational policymakers develop digital wellness programmes and mental health interventions aimed at promoting responsible social media use among adolescents.

A simple, accurate, and reliable RP-HPLC method was successfully developed and validated for the simultaneous estimation of Hydrochlorothiazide and Metoprolol in tablet formulations. The method provided good separation of both drugs with retention times of 3.12 minutes for Hydrochlorothiazide and 4.93 minutes for Metoprolol. Validation results showed excellent linearity, precision, accuracy, and robustness according to ICH guidelines. The percentage recovery values at different concentration levels were within acceptable limits, confirming the accuracy of the method. Other system suitability parameters such as %RSD, tailing factor, and theoretical plates also met the required standards. The developed method is simple, rapid, and cost-effective, making it suitable for routine quality control analysis, stability studies, and formulation development of pharmaceutical products containing Hydrochlorothiazide and Metoprolol. Therefore, this method can be confidently used in pharmaceutical industries and research laboratories for the regular analysis of these drugs.

Fenofibrate is a widely used antihyperlipidemic drug indicated for the treatment of hypertriglyceridemia and mixed dyslipidemia. However, its poor aqueous solubility and low oral bioavailability significantly limit its therapeutic effectiveness. Nanoparticle-based drug delivery systems have emerged as a promising approach to overcome these limitations by enhancing solubility, dissolution rate, and bioavailability. The present study aimed to formulate, develop, and characterize fenofibrate nanoparticles to improve its pharmaceutical performance and therapeutic efficacy.Fenofibrate nanoparticles were prepared using a suitable nanoparticle fabrication technique and optimized by varying formulation parameters such as polymer concentration, stabilizer concentration, and processing conditions. The prepared nanoparticles were evaluated indicating successful formulation. The optimized formulation exhibited high drug entrapment efficiency and satisfactory stability. Morphological studies confirmed the formation of discrete and uniformly distributed nanoparticles. In vitro drug release studies demonstrated a significantly enhanced dissolution profile compared to pure fenofibrate, suggesting improved drug availability.The developed fenofibrate nanoparticles showed favorable physicochemical characteristics and enhanced drug release properties, highlighting their potential as an effective oral drug delivery system. The reduction in particle size and increased surface area contributed to improved solubility and dissolution behavior of the drug. These findings suggest that nanoparticle-based formulations can serve as a promising strategy for enhancing the bioavailability and therapeutic performance of poorly water-soluble drugs such as fenofibrate. Further in vivo studies are warranted to establish the clinical benefits and pharmacokinetic advantages of the developed nanoparticle formulation.

A novel, precise, and stability-indicating reverse-phase form of high-performance liquid chromatography (RP-HPLC) method turned into developed and showed for the simultaneous estimation of Hydrochlorothiazide (HCTZ) and Metoprolol Succinate (MET) in bulk drug and formulated tablets. The approach changed into optimized to offer green separation and correct quantification, even within the presence of decay products. Chromatographic separation has become carried out the usage of a C18 column with a cellular phase comprising phosphate buffer (pH 3.0, adjusted with orthophosphoric acid) and acetonitrile in a ratio of 60: 40v/v. The go with the float charge was maintained at 1.0 mL/min, with detection at 225 nm. The technique verified superb linearity for HCTZ (five–50 µg/mL) and MET (10–a hundred µg/mL) with a regression coefficient (R²) > 0.999. Forced degradation studies underneath acidic, alkaline, oxidative, thermal, and photolytic conditions confirmed the technique's stability-indicating capability, as degradation products have been nicely separated without interference in drug peaks. Validation, achieved as in keeping with ICH Q2 (R1) hints, installed specificity, accuracy, precision, robustness, and sensitivity with notable healing costs (98-102%). The proposed technique come to be correctly carried out to the quantification of HCTZ and MET in business tablets, proving its suitability for normal best manage and balance studies.

Diabetes mellitus is a chronic metabolic disorder characterized by persistent hyperglycemia resulting from impaired insulin secretion, insulin action, or both. Despite the availability of various antidiabetic agents, limitations such as poor bioavailability, adverse effects, and reduced patient compliance necessitate the development of novel therapeutic approaches. Cinnamon bark (Cinnamomum verum) is a well-known medicinal plant possessing significant antidiabetic properties due to its rich content of polyphenols, flavonoids, and cinnamaldehyde. However, the therapeutic efficacy of cinnamon bark extract is often limited by poor aqueous solubility and low bioavailability.The present study aimed to develop and optimize cinnamon bark extract-entrapped solid lipid nanoparticles (SLNs) to enhance its antidiabetic efficacy. SLNs were prepared using a suitable lipid matrix and surfactant system employing a high-shear homogenization and ultrasonication technique. The formulations were optimized using a statistical design approach to achieve desirable particle size, polydispersity index, zeta potential, entrapment efficiency, and drug release characteristics. The optimized SLN formulation was characterized for its physicochemical properties, morphology, stability, and in vitro release behavior.The developed nanoparticles exhibited nanoscale particle size, high entrapment efficiency, and sustained release of bioactive constituents. In vitro antidiabetic studies demonstrated enhanced inhibitory activity against carbohydrate-hydrolyzing enzymes compared to the plain extract. The improved performance was attributed to increased solubility, stability, and controlled release provided by the lipid nanocarrier system.The findings suggest that cinnamon bark extract-loaded SLNs represent a promising nano-delivery platform for improving the therapeutic effectiveness of herbal antidiabetic agents and may offer a novel strategy for the management of diabetes mellitus.

The application of bioacoustic technology in capture fisheries has attracted increasing attention because sound stimulation offers a non-destructive approach to influencing fish behavior. This study aimed to analyze the behavioral response of Siganus javus to artificial bioacoustic stimuli at different sound frequencies under laboratory conditions, with particular attention to radius of presence, response duration, and the emergence of response. A laboratory experiment was conducted in March 2025 using an aquarium-based observation system and an artificial bioacoustic device. Two sound treatments, namely sudden sound and continuous sound, were tested at five frequencies of 100, 200, 300, 400, and 500 Hz, with nine replications for each treatment. Fish response was evaluated through spatial position relative to the sound source, duration of response, descriptive analysis, and Cochran’s Q test. The results showed that 100 Hz consistently produced the strongest response in both treatments. Under sudden sound, the fish gradually approached the sound source and responded in all replications, while under continuous sound, 100 Hz generated the longest and most sustained response duration. The 200 Hz treatment still elicited detectable responses but with lower consistency, whereas 300–500 Hz produced minimal response. Statistical analysis confirmed that sound frequency significantly affected the emergence of fish response. These findings indicate that low-frequency artificial bioacoustic stimulation, especially 100 Hz, is the most effective frequency range for influencing Siganus javusbehavior and may support the development of environmentally responsible fishing technology.

This study compares three forecasting models—Long Short-Term Memory (LSTM) networks, Support Vector Regression (SVR), and Autoregressive Integrated Moving Average (ARIMA)—for predicting 2024 April data using historical April data from 2021 to 2023. The time series is constructed by concatenating annual April observations, followed by linear interpolation for missing values, min-max normalization, and a sliding window approach to create input-output pairs. Performance is evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R²) metrics. Results show that LSTM significantly outperforms SVR and ARIMA, achieving an MAE of 2419.9, RMSE of 3131.2, and R² of 0.95969, while SVR and ARIMA exhibit poor predictive power with negative R² values.

Background: The accumulation of unused and expired medications in households is a common occurrence resulting from changes in prescribed therapy, incomplete treatment courses, improvement in health conditions, or medication non-adherence. Improper disposal of these medications may pose significant risks to public health and the environment, including accidental poisoning, drug misuse, and environmental contamination. Despite the potential consequences, awareness of appropriate medication disposal practices remains limited among the general population.
Objective: To assess the awareness, storage practices, and disposal behaviours related to unused and expired medications among visitors to community pharmacies.
Methods: A cross-sectional observational study was conducted among 150 participants recruited from selected community pharmacies. Data were collected using a structured questionnaire comprising demographic characteristics, medication storage practices, awareness of safe medication disposal, and disposal behaviours. Descriptive statistical methods were employed for data analysis, and the relationship between demographic variables and awareness levels was examined where applicable.
Results: The study demonstrated that a considerable proportion of participants stored unused or expired medications in their households. Most respondents lacked adequate knowledge regarding recommended disposal methods and reported disposing of medications through household waste. Awareness of the environmental and health hazards associated with improper medication disposal was found to be limited. In addition, only a small proportion of participants were aware of medication take-back programs. However, the majority expressed a willingness to receive education on proper disposal practices and to participate in safe medication disposal initiatives.
Conclusion: The findings indicate inadequate public awareness regarding the safe disposal of unused and expired medications. Strengthening pharmacist-led educational interventions and establishing medication take-back programs may enhance public knowledge, encourage appropriate disposal practices, and reduce potential risks to both public health and the environment.

Euphorbia hirta L. (Euphorbiaceae), commonly known as the asthma plant, has a rich history in global ethnomedicine for treating respiratory and gastrointestinal disorders. This study investigated the qualitative and quantitative phytochemical profile of E. hirta specimens collected from the natural habitats of the Durg district in Chhattisgarh, India. Using a sequential extraction method across four solvents of varying polarities: methanol, ethanol, distilled water, and n-hexane—preliminary qualitative chemical assays and quantitative spectrophotometric estimations were performed. Qualitative screening revealed an unequal distribution of primary and secondary metabolites, showing that polar organic solvents (methanol and ethanol) excel at dissolving vital bioactive compounds like phenols, flavonoids, tannins, and alkaloids, while lipophilic fixed oils and fats strictly localized in the non-polar hexane fraction. Quantitatively, the methanolic extract demonstrated the highest concentrations of both Total Phenolic Content (TPC: 265 ± 0.001) and Total Flavonoid Content (TFC: 254.8 ± 0.01), significantly outperforming the aqueous and hexane mediums. These findings validate that selecting alcohol-based organic solvent systems is crucial for effectively isolating antioxidant-rich therapeutic compounds from regional flora. The study highlights E. hirta as a potent source of secondary metabolites, supporting its traditional applications and prospective utilization in modern pharmaceuticals.

Campus placement management in Indian educational institutions has long suffered from fragmented workflows, manual data collection, and opaque communication channels. This paperpresents PlaceTrack,anenterprise-grade, multi-portal web application designed to digitize and streamline the end-to-end campus recruitment lifecycle. The systemunifiesthreedistinctuserroles—students,corporaterecruiters,andplacementadministrators—onasingle, secure platform built on React 19, Vite, Tailwind CSS, PostgREST, and PostgreSQL 15 with Row-Level Security (RLS). PlaceTrack provides 38+ student-facing pages encompassing job discovery, application tracking, resume building,mocktests,codingchallenges,andcareerguides;astructuredrecruiterpipelineforjobposting,applicant management, and interview scheduling; and an administrative oversight portal with real-time analytics and broadcast notification capabilities. Security is enforced at the database layer through PostgreSQL RLS policies, ensuring role-isolated data access independent of application code. Formal testing across 66 test cases yielded a 98.5% pass rate. This paper analyzes the architectural decisions, security model, module design, and measurable outcomesofPlaceTrack,demonstratingthatatargetedfull-stacksolutioncanreplacelegacymanualprocesseswith a scalable, auditable, and institutionally deployable platform.

This study examines the influence of workload and psychological work environment on burnout among healthcare workers at Bandung Kiwari Regional General Hospital. Healthcare professionals operate in high-demand settings characterized by heavy workloads, time pressure, and emotionally intense interactions with patients and their families, which may lead to chronic stress and, ultimately, burnout. Burnout is defined as a psychological syndrome comprising emotional exhaustion, depersonalization, and reduced personal accomplishment. A quantitative approach with a verification method was employed. The study population consisted of healthcare workers with a minimum of one year of service, selected using incidental sampling. Data were collected using a 4-point Likert-scale questionnaire and analyzed through multiple linear regression, supported by validity, reliability, and classical assumption tests. The results indicate that workload has a positive and significant effect on burnout (t = 5.219, p < 0.05), while the psychological work environment has a negative and significant effect on burnout (t = -3.746, p < 0.05). Simultaneously, both variables significantly influence burnout (F = 1725.944, p < 0.05). The coefficient of determination (R² = 0.672) suggests that 67.2% of the variance in burnout is explained by workload and psychological work environment. These findings highlight that burnout among healthcare workers is shaped not only by high job demands but also by the quality of the psychological work environment. Excessive workload, when not balanced by supportive psychological conditions, increases the risk of burnout, whereas a positive work environment serves as a protective factor. Therefore, healthcare management should focus on optimizing workload distribution and fostering a supportive psychological environment to enhance employee well-being and improve the quality of patient care.

Farming in Tamil Nadu is greatly affected by climate changes, irregular irrigation, and challenges in maintaining agricultural sustainability. This study presents a framework using fuzzy multi-objective techniques for drone-assisted agricultural monitoring, based on reliable data from Tamil Nadu. The model deals with fuzzy uncertainties, optimal drone routing, and the Sustainable Development Goals (SDGs). We solve the optimization problem using a hybrid NSGA-II and PSO approach.

The present study was carried out to develop and validate a simple, accurate, precise, and reliable analytical method for the simultaneous estimation of Atenolol and Indapamide in tablet dosage form. Commercial tablet formulations containing Atenolol and Indapamide were selected and subjected to sample preparation, including tablet powdering, accurate weighing, extraction, and dilution using a suitable solvent system. The prepared samples were analyzed using an optimized RP-HPLC method under appropriate chromatographic conditions. Method development involved the selection of a suitable stationary phase, mobile phase composition, flow rate, and detection wavelength to achieve satisfactory separation of both drugs with well-resolved and symmetrical peaks. Chromatographic analysis produced distinct retention times for Atenolol and Indapamide, enabling their simultaneous quantification in the tablet formulation. The developed method was subsequently validated according to International Council for Harmonisation (ICH) guidelines to ensure its suitability for routine quality control analysis. Validation parameters included specificity, linearity, accuracy, precision, robustness, limit of detection (LOD), and limit of quantification (LOQ). The method demonstrated excellent linearity over the selected concentration range, high recovery values indicating accuracy, and low relative standard deviation values confirming precision. Robustness studies showed that minor variations in analytical conditions did not significantly affect the results. The validated method was found to be selective, sensitive, reproducible, and reliable for the simultaneous determination of Atenolol and Indapamide in pharmaceutical tablet formulations. Therefore, the developed analytical procedure can be effectively employed for routine quality control, assay determination, and regulatory compliance testing of combined Atenolol and Indapamide tablet products in pharmaceutical industries and research laboratories.

Ground nut (Arachis hypogea L.) occupies first place among the all oil seed crops in India. It also subjected to various types of fungal diseases, which causes extensive damage to crop in the quality as well as quantity of the yield. The Tikka leaf spot (Cercospora arachidicola and C. personata) and rust (Puccinia arachidis) has been occurring in a serious form in every groundnut growing area of the country. Aerobiological experiments were carried out to find out the concentration of pathogenic fungal form, their relation with the meteorological parameters and growth stages of crop. Air sampling was done during from July to October in both years of 2022 and 2023. Air monitoring revealing that maximum concentration of Leaf spot pathogen and rust pathogen observed in air during October of both the seasons. Maintained meteorological data throughout the period of investigation to correlate with the incidence of pathogen and severity of infection. The role of the meteorological factors for survival of the pathogen, growth stages of the crops and disease incidence have been discussed.

Herbal medicines are widely used because they contain natural compounds that may help prevent and treat diseases. This study evaluated the antioxidant activity of ethanolic seed extract of Cassia torain carbon tetrachloride (CCl4)-induced hepatotoxic rats. Qualitative phytochemical screening of the extract showed the presence of flavonoids, anthraquinones, saponins, steroids, and terpenoids.Antioxidant analysis showed that treatment with the extract significantly (p < 0.05) increased the activities of superoxide dismutase (SOD) and glutathione peroxidase (GPx) at doses of 200 mg/kg and 400 mg/kg. The level of malondialdehyde (MDA), which is an indicator of oxidative stress, was significantly reduced, especially at 400 mg/kg. Catalase (CAT) activity increased slightly, although the increase was not statistically significant.The findings suggest that ethanolic seed extract of Cassia torapossesses antioxidant and hepatoprotective properties. These effects may be linked to the phytochemicals present in the plant. Therefore, the extract may serve as a potential natural therapeutic agent against liver damage and oxidative stress-related disorders.

Mixed Reality (MR) technology, encompassing Virtual Reality and Augmented Reality, offers immersive and interactive learning environments, yet its adoption in education remains limited. This study investigates consumer perception and adoption of MR solutions in education and training, focusing on two primary objectives: first, to assess the key benefits and challenges influencing MR adoption, and second, to identify underlying factors that shape consumer perceptions of MR effectiveness. A quantitative descriptive research design was employed, collecting data from respondents including educators, students, and professionals in Kozhikode, India, using a structured questionnaire. Descriptive statistics, a Chi-square test, and Exploratory Factor Analysis were used for analysis. Findings revealed that respondents demonstrated a moderate level of familiarity with MR technologies. Perceived benefits included enhanced engagement, improved learning outcomes, and interactive experiences, whereas significant barriers comprised technical difficulties, high device costs, and insufficient content availability. The Chi-square test indicated a significant relationship between occupation and the types of challenges experienced or anticipated. Factor analysis extracted three underlying dimensions: Learning Engagement and Personalization, Usability and Compatibility, and Accessibility and Motivation. The study concludes that while MR is generally perceived as beneficial for education and training, several adoption barriers must be addressed before widespread integration can be achieved.

Background: Chronic Mechanical Low Back Pain (CMLBP) is one of the most prevalent musculoskeletal disorders worldwide, leading to pain, reduced spinal stability, and functional disability. Dynamic Lumbar Stabilization Exercises (DLSE) have been proposed as an effective intervention to improve core muscle activation, spinal control, and functional performance in individuals with chronic low back pain.
Objective: To evaluate the effectiveness of Dynamic Lumbar Stabilization Exercises on functional disability among individuals with Chronic Mechanical Low Back Pain.
Methods: A pre-test and post-test experimental study was conducted among individuals diagnosed with Chronic Mechanical Low Back Pain. Participants underwent a structured Dynamic Lumbar Stabilization Exercise program for a specified intervention period. Functional disability was assessed using the Oswestry Disability Index (ODI) before and after the intervention. Statistical analysis was performed using appropriate parametric tests to determine the significance of changes in disability scores.
Results: Participants demonstrated a significant reduction in functional disability following the intervention. Post-treatment ODI scores showed marked improvement compared to baseline values, indicating enhanced functional capacity and reduced limitations in daily activities. The findings suggest that Dynamic Lumbar Stabilization Exercises effectively improve spinal stability and functional outcomes in individuals with Chronic Mechanical Low Back Pain.
Conclusion: Dynamic Lumbar Stabilization Exercises are an effective therapeutic approach for reducing functional disability in individuals with Chronic Mechanical Low Back Pain. Incorporating these exercises into rehabilitation programs may enhance functional independence, improve quality of life, and contribute to long-term management of low back pain.

The needs for electricity are increasing at a faster rate in this modern society. For electrical equipment to function properly and effectively on power distribution network, a constant supply of high-quality power is required. The most common type of power quality degrading factors includes; variation in voltages and frequency, power interruption, power sag, voltage swell, under voltage, voltage spike or surges and harmonics etc. The used of non-linear loads such as computers, printers, UPS, Variable-speed drive etc are the major causes of harmonics into the supply distribution network. The existence of harmonics is the primary causes of the problems that lead to the breakdown of insulation, excessive heating of conductors and shortened the lifespan of electrical equipment. In addition to this high THD in electrical distribution network may cause the energy meter to give false readings. Shunt active power filter is an economic solution use to reduce losses caused by harmonics distortion. This research work provides an in- depth look into the application of this filter for harmonics compensation. By performing simulations with the MATLAB/Simulink software, it has been determined that using shunt active power filter reduces the total harmonics distortion (THD)of the current by 90% significantly resulting into better quality and energy conservation. The IEEE standard 519-1992 was used as a reference when making this determination. This research work presents the design of shunt active power filter for mitigation of power quality problems introduced by nonlinear loads. A shunt active power filter in parallel with the load has been investigated to improve the power quality. The control strategy has been simulated using MATLAB software and the results to verify the effectiveness of the algorithm were presented.

Cancer remains one of the leading causes of morbidity and mortality worldwide. Conventional treatment approaches such as chemotherapy and radiotherapy often affect both cancerous and healthy cells, resulting in significant adverse effects. The development of targeted therapies has transformed cancer treatment by selectively inhibiting molecular pathways involved in tumor growth and progression. Tyrosine kinase inhibitors (TKIs) represent an important class of targeted anticancer agents that block the activity of tyrosine kinases, enzymes involved in cell signaling, proliferation, differentiation, angiogenesis, and survival.
This review discusses the mechanisms of action of TKIs, their classification, therapeutic applications in various malignancies, advantages, limitations, and future perspectives in precision oncology.

Sleep Apnea is due to a respiratory condition, which is linked to a sleep issue that often contributes to reduction in airflow and often sometimes fully prevents airflow. In addition, this issue needs the individual to be checked overnight to determine the amount of oxygen in the blood. Several experiments carried out on animals like-mice the research reveals that sleep apnea can also contribute to cancer. In this paper a deep learning algorithm for evaluating different variables including throat muscles, it usually collapses whilst a sleep, triggering both gasping and snoring as body searches for oxygen. This paper provides a description of the apnea deep learning paradigm related to dynamic cancer impermanence. Deep Learning (DL) technology, primarily the modified Fusion Convolution Neural Network (MFCNN), is used as a function detector to learn the features of the high-order association between observable data and associated marks. Preparing and segmenting the data model is a critical move toward training into deep learning. During the last stage of the MFCNN, a completely linked layer is attached to the output layer and builds the required number of outputs for sleep apnea occurrences during investigate the ECG data.

Mental health constitutes an essential component of adolescents’ overall development, significantly influencing their emotional adjustment, academic engagement, behavioural functioning, and ability to cope with everyday challenges. During adolescence, rapid developmental changes often expose students to emotional and psychological pressures, making mental well-being an important concern within educational settings. The present study was undertaken to examine the prevalence of mental health problems among school-going adolescent students in West Bengal and to explore variations in mental health outcomes across selected socio-demographic variables, namely gender, locality, family income, and social category. The study employed a quantitative research approach using a cross-sectional survey design. A total sample of 334 adolescent students was selected through a simple random sampling technique from four districts of West Bengal, namely Kolkata, Howrah, Jalpaiguri, and Alipurduar. Data were collected using the standardized Strengths and Difficulties Questionnaire (SDQ) developed by Robert Goodman (1997), which assesses different dimensions of mental health, including emotional symptoms, conduct problems, hyperactivity, peer relationship problems, and prosocial behaviour. The collected data were analysed using descriptive statistical techniques and chi-square analysis to examine the prevalence and variation of mental health problems among adolescents. The findings of the study revealed statistically significant differences in mental health problems across several socio-demographic variables. Female students demonstrated comparatively higher levels of severe mental health problems than male students, indicating the influence of gender on psychological well-being. A highly significant difference was also observed between rural and urban students, with urban students exhibiting comparatively greater levels of mental health difficulties. Furthermore, significant differences were found with regard to family income and social category, suggesting that socio-economic background and social conditions meaningfully influence adolescents’ mental health experiences. The findings collectively indicate that mental health problems among adolescents are shaped through the interaction of multiple personal, social, educational, and environmental influences rather than any single determinant. The study highlights the urgent need for educational institutions to adopt more inclusive, supportive, and psychologically responsive approaches to student development. Strengthening school-based counselling services, promoting socio-emotional learning, reducing excessive academic pressure, and encouraging supportive school environments may contribute significantly to improving adolescents’ psychological well-being. The findings are expected to provide useful insights for educators, policymakers, counsellors, and researchers in developing context-sensitive interventions aimed at promoting positive mental health among adolescent students in West Bengal.

The present study was carried out to develop and evaluate a polyherbal gel containing essential oils for the treatment of acne and other microbial skin infections. Essential oils Carvacrol and thymol from Cymbopogon nardus (CNO) and Cymbopogon flexuosus (CFO) were extracted using the hydrodistillation method with a Clevenger apparatus. The extracted oils were assessed for their quality, antimicrobial activity, antioxidant potential, and safety profile. Both essential oils showed significant antibacterial activity against Staphylococcus epidermidis, a major microorganism associated with acne. Among the tested oils, CFO exhibited stronger antimicrobial activity than CNO, and the antibacterial effect increased with increasing concentration. A polyherbal gel containing both essential oils in a 1:1 ratio was successfully formulated and evaluated for various physicochemical parameters, including appearance, pH, homogeneity, viscosity, spreadability, and stability. The gel showed satisfactory characteristics suitable for topical application and remained stable under different storage conditions. Antimicrobial activity was evaluated using agar disc diffusion and broth microdilution methods, and the results were compared with the standard drug benzoyl peroxide. The formulated gel demonstrated enhanced antimicrobial activity and effective inhibition of microbial growth. In addition, the combined essential oil formulation exhibited higher antioxidant activity than the individual oils, suggesting a synergistic effect.The safety of the formulation was assessed using the MTT assay on Normal Human Epidermal Keratinocyte (NHEK) cell lines. The gel showed acceptable cell viability and lower cytotoxicity compared to the individual oils and standard drug. Overall, the developed polyherbal gel was found to be safe, stable, and effective, indicating its potential as a natural alternative for acne management and further clinical investigation.

Tiera is a mobile-based intelligent job opportunity platform that connects students, skilled workers, professionals and senior citizens with employers and clients in their nearby areas. It acts as a third-party bridge, enabling users to find and offer jobs from local services to professional roles. The main problem addressed is the lack of a unified platform that supports all kinds of workers, as most existing systems focus only on corporate jobs. Tieora uses GPS and Google Maps APIs to help users find jobs or workers within a chosen radius, such as 3 km or 5 km. It also integrates AI-based skill matching to recommend relevant opportunities based on profiles and preferences. The platform supports two logins job seekers and employers and provides real-time chat and notifications for easy communication. Its Groupal feature allows users to form or join teams for collaborative work. Built using Flutter and Firebase, the app ensures scalability, accessibility and real-time performance. Tieora promotes inclusivity, local employment and digital empowerment. In conclusion, it serves as a smart and practical employment solution for all sections of society.

With global warming and health concerns on the rise because of the substances the vehicles produce, it is important to adopt the right vehicles that are eco-friendly. The holistic transition from conventional fuel cars to electric cars is crucial for implementing the concept of sustainable development. In the present time, the organizations in the automobile sector are playing a leading role in imparting the idea of sustainable development in the area of productions, operations, supply chain etc. Now the eco-friendly cars are a lot more affordable than they were in the past, and their use is a way to protect the environment and health of people. Hybrids and battery-operated cars are considered to be eco-friendly cars. Electric cars do not burn any fuel. Hybrid cars are somewhat divergent from any other fuel cars or electric vehicles in the sense that they possess two engines, and rely on electricity more often, which means that they burn less fuel than conventional cars. This study seeks to find out the factors that influence the adoption of sustainable measures in the automobile industry through the use of eco-friendly cars through the exploratory factor analysis, and also the interrelationship among the factors and extent of dependability on each other.

This research investigates the effectiveness of Task-Based Language Learning (TBLT) in improving speaking skills in second language acquisition. Conducted at the Sri Lanka Institute of Advanced Technological Education (SLIATE), this experimental study involved 100 undergraduates, divided into an experimental group and a control group. The study aimed to compare the impact of TBLT and traditional teacher-centered methods on students' speaking proficiency. Through pre-tests and post-tests, the study assessed improvements in fluency, accuracy, and overall speaking ability. Additionally, a questionnaire was administered to evaluate students' attitudes toward TBLT. The findings reveal that students in the experimental group demonstrated a significant improvement in their speaking skills, particularly in fluency and accuracy, compared to the control group. Furthermore, the majority of students expressed positive attitudes towards TBLT, appreciating its interactive and practical approach to language learning. The results suggest that TBLT can be a more effective method for enhancing speaking proficiency in second language learners. The study recommends the integration of TBLT into second language curricula and further exploration of its long-term benefits.

With the swift shift from classroom to hybrid teaching, the education system has undergone a significant transformation across the globe, bringing about new requirements for teachers. As hybrid learning models gain popularity, there are still obstacles for educators in the areas of digital literacy, pedagogical adjustment, and instructional effectiveness. So the aim of this study was to review the most important themes that emerged in the literature and that are related to teachers' PD needs when adopting a hybrid approach to teaching. This study followed qualitative and inductive research methodology and employed systematic literature review technique. Major academic databases such as Scopus, Web of Science, ERIC, ScienceDirect and Google Scholar were searched for peer-reviewed journal articles published between the years 2016 and 2026. After applying the criteria for inclusion and exclusion, 42 articles were chosen for detailed analysis. Thematic analysis was used to sift through the collected data and to identify common patterns and themes in the literature.
The results identified five key areas that impact teacher professional learning in hybrid learning settings: development of digital and technological competencies, pedagogical adaptations and instructional redesigns, emotional and workload pressures, institutional and collaborative support systems, and continuous and flexible professional learning. The review also showed that the development of technological, pedagogical and reflective teaching skills, which is supported by continuous institutional and professional support, is essential for effective hybrid teaching. The study concludes that comprehensive, context-sensitive professional development frameworks are needed to improve teachers' readiness and effectiveness in the changing hybrid education contexts.

It is well known that classroom participation in the LSIA is one of the most important elements involved in the successful English as a Second Language (ESL) and English as a Foreign Language (EFL). Nevertheless, there are barriers of various types that present obstacles to learner engagement in class interaction in various learning contexts, including psychological, linguistic, pedagogical, and socio-cultural. This research was an attempt to review systematically the various factors influencing classroom participation of both teachers and learners in ESL/EFL context. This study aimed to gain insight into what drives involvement, to explore factors impeding engagement, and to draw insights from effective practices that increase classroom engagement. The study was based on a qualitative inductive systematic literature review design. Predefined inclusion and exclusion criteria were used to withhold high-quality research papers for each peer-review journal published from 2014 through 2025, from major academic databases. Thematic analysis was used for studying the 42 relevant articles of which they investigated various international and Asian contexts of ESL/ EFL. Anxiety, apprehension, negative evaluation, limited knowledge of language, and pronunciation difficulties emerged as important factors that greatly inhibit the participation of learners in the classroom. Learner engagement is also very much subject to the student-teacher relationship, including aspects related to teaching approaches, feedback provided, classroom management and communication strategies. Further, socio-cultural norms and education systems that focus on passing examinations and classroom conditions were identified as large participation related problems. The review also revealed good practice in the development of collaborative learning lessons, supportive teacher behaviour and communicative instructional strategies for improving participation. The research findings indicate that classroom involvement in ESL/EFL learning is by nature more multidimensional and context specific. To achieve more effective learner involvement and language development, teaching practices which foster supportive, learner-centred and communicative classroom atmosphere are critical.

This study aims to present a systematic review and thematic analysis of English language learner demotivation in the English language classroom to find the major factors that cause demotivation of students and the tendency to leave the classroom. Although English language proficiency is highly valued in the world, students in EFL and ESL environments still have a low level of motivation and active involvement in their classrooms. The main aim of this study was to synthesize the literature for general patterns of learner demotivation in a variety of educational contexts.
A qualitative systematic literature review approach was used and analyzed 38 studies that published between 2015 and 2025. Thematic analysis was employed to detect and explore common themes within the literature, which was retrieved from major academic databases. The results identified five key themes that emerged as influential factors on the demotivation of learners: teacher centered instruction, curriculum irrelevancy and examination orientation, learner autonomy, negative classroom climate and limited communicative opportunities.
Results show that demotivation is a multidimensional phenomenon, the components of which are interconnected and have pedagogical, curricular, and psychological dimensions. The use of traditional teaching methods and exam-oriented curricula consistently identified as key factors in students' disengagement from learning. Furthermore, anxiety and self-confidence issues and not many chances for genuine communication further accentuated demotivational experiences.
Finally, the study underscores the importance of pedagogical changes that focus on learning, communicative teaching methods and curriculum development that has more relevance in the English language learning context. The results are significant for teachers, curriculum developers and policy makers interested in enhancing engagement in EFL/ESL classrooms.

This study aims to present a systematic review and thematic analysis of English language learner demotivation in the English language classroom to find the major factors that cause demotivation of students and the tendency to leave the classroom. Although English language proficiency is highly valued in the world, students in EFL and ESL environments still have a low level of motivation and active involvement in their classrooms. The main aim of this study was to synthesize the literature for general patterns of learner demotivation in a variety of educational contexts.
A qualitative systematic literature review approach was used and analyzed 38 studies that published between 2015 and 2025. Thematic analysis was employed to detect and explore common themes within the literature, which was retrieved from major academic databases. The results identified five key themes that emerged as influential factors on the demotivation of learners: teacher centered instruction, curriculum irrelevancy and examination orientation, learner autonomy, negative classroom climate and limited communicative opportunities.
Results show that demotivation is a multidimensional phenomenon, the components of which are interconnected and have pedagogical, curricular, and psychological dimensions. The use of traditional teaching methods and exam-oriented curricula consistently identified as key factors in students' disengagement from learning. Furthermore, anxiety and self-confidence issues and not many chances for genuine communication further accentuated demotivational experiences.
Finally, the study underscores the importance of pedagogical changes that focus on learning, communicative teaching methods and curriculum development that has more relevance in the English language learning context. The results are significant for teachers, curriculum developers and policy makers interested in enhancing engagement in EFL/ESL classrooms.

The discharge of synthetic dyes into water bodies poses serious environmental concerns due to their persistence and toxicity. In this study, activated charcoal derived from coconut shell was used for the removal of Methylene Blue and Congo Red from aqueous solutions. The charcoal was applied in two forms: as free powder and as immobilized beads prepared using Sodium alginate. Dye reduction experiments were conducted at different charcoal concentrations and incubated for 72 hours under dark conditions. Optical density was measured using a colorimeter at 680 nm and 490 nm for methylene blue and Congo red, respectively. The results indicated that powdered charcoal exhibited higher dye removal efficiency (up to ~81% for methylene blue), whereas immobilized beads showed moderate removal efficiency but offered advantages in ease of separation and handling. The study highlights that while free charcoal is more efficient, immobilized systems provide a practical and eco-friendly alternative for wastewater treatment.

This study aims to analyze and model the daily rainfall dynamics in Manado City, North Sulawesi, during the period of January to March 2026. An in-depth understanding of daily-scale rainfall variability is crucial for mitigating hydrometeorological disasters in vulnerable urban areas like Manado. The research methods employed encompass descriptive statistical analysis and time series modeling, utilizing trendlines and forecasting based on daily empirical data. The results indicate that February 2026 was the period of the highest and most consistent rainfall intensity, recording an average of 4.756 mm/day and a median of 1.5 mm. Conversely, March 2026 registered the lowest average intensity at 2.903 mm/day with a median of 0 mm, yet it exhibited the most extreme atmospheric uncertainty, characterized by the highest coefficient of variation reaching 193.07%. From a physical perspective, these fluctuations are driven by complex interactions among regional sea surface temperatures, monsoonal wind flows, and local orographic factors that trigger convective energy release. Identified environmental impacts include a high risk of soil saturation in February, which accelerates surface runoff, alongside the potential for sudden flash floods in March resulting from sporadic precipitation spikes of up to 22.60 mm during otherwise dry periods. Despite technical limitations involving data gaps on specific dates, such as March 6, 2026, this modeling continues to provide a robust characterization of local atmospheric behavior. This study concludes that flood management strategies in Manado City must transition from a reliance on monthly averages to the rigorous monitoring of extreme daily values to establish a more precise and adaptive early warning system.

Background: Healthcare systems and the clinical pharmacy profession are greatly influenced in many ways by the use of artificial intelligence (AI) and machine learning (ML), e.g. through improvement of various areas such as drug safety, clinical decision-making, drug monitoring and the development of personalized medicine. In order to ensure that clinical pharmacists can provide effective pharmaceutical care using these new technologies, it is essential that they constantly evaluate their practice as technology becomes available. However, there is little research regarding the knowledge and attitudes of clinical pharmacists currently working in India toward the use of AI and ML in practice. Therefore, it will be important to conduct more focused research, training and education about these topics so that pharmacists are adequately prepared to use these technologies in their practice.
Objective: This project set out to evaluate “clinical pharmacist’s” knowledge, attitude and perception of employing machine learning (ML) and Artificial Intelligence (AI) in practice as a means of identifying barriers to implementing/using those technologies. In particular we focused on hospital-based clinical pharmacists in order to understand their current understanding and use of AI and ML.
Methodology: A validated, 30-item questionnaire covering knowledge, attitude, and perception (10 items each domain) was used for descriptive cross-sectional research with 75 clinical pharmacists working in hospitals located in Telangana, India. Data was collected for 3 months, and analysis was performed through SPSS v25.0 using various tests like chi-square and descriptive statistics. Clinical pharmacists were subjects of another similar questionnaire-based survey that included demographic and KAP-related questions. There were between 50-100 participants, and the survey was distributed online and offline. Descriptive statistical techniques, such as percentage and frequency distributions, were used during the analysis.
Result: The survey results indicate that of the 75 respondents, 68% were already knowledgeable about artificial intelligence (AI) and machine learning (ML) as they pertained to pharmaceuticals. Most believed that AI could help to make medications safer or improve how they perform in relation to clinical judgment. Additionally, a remarkable 82% of respondents also stated that they would be willing to utilize AI for work-related purposes. Some obstacles to adoption were inadequate institutional infrastructure (59%), issues with privacy (64%), or a lack of formalized training (78%). In addition, there was a statistically significant relationship (p <.05) between participants’ perceptions of their understanding of both AI and ML relative to their experience. Overall, pharmacists tended to demonstrate a moderate-to-high level of familiarity with both AI and ML, therefore increasing the likelihood that they could contribute to improving medication safety and reducing the number of prescription-related errors.
Conclusion: Many of clinical pharmacists support the application of AI and ML as tools at work; however, to allow for the use of these tools, institutions must provide support through structured educational programs. In order to develop these skills, the training and education project on continued improvement of pharmacists’ education to incorporate AI/ML skills into pharmacy curricula will require collaborative efforts by pharmacy schools and educational support agencies.

The Turbine Gland Seal Steam System (TGSSS) is a crucial and independent auxiliary system in thermal power plants. The system performs two functions at the gland seals along the turbine shaft. On the high-pressure side, it prevents high-pressure steam leakage from the turbine. On the low-pressure side, it supplies positive pressure steam to prevent outside air entering the vacuum section of the condenser. Maintaining system stability optimizes thermal efficiency, protects equipment, and maintains absolute vacuum throughout the operating cycle.

This study determined the concentration levels of Total Petroleum Hydrocarbons (TPH) in soils collected from automobile workshops across selected locations in Warri metropolis, Delta State, Nigeria. Soil samples were obtained from eight automobile workshop sites, comprising bike, keke, truck, and car repair workshops. At each location, samples were collected from the main workshop and at a point 10 m away, giving a total of sixteen samples. Total Petroleum Hydrocarbons were extracted using an Accelerated Solvent Extractor (ASE), purified through Florisil clean-up, and quantified by gas chromatography with flame ionization detection (GC-FID). The results revealed considerable variation in TPH concentrations across the sampled locations, indicating different levels of petroleum contamination associated with workshop activities. The highest TPH concentration (157,150.24 mg/kg) was recorded at the Agbarhokeke workshop, 10 m from the main workshop, while the lowest value (249.92 mg/kg) occurred at the Okorikperhe truck workshop, 10 m away. Elevated TPH levels were also observed at Okuokoko truck (37,763.60 mg/kg), PTI Road 2 car workshop (17,041.60 mg/kg), and Warri/Sapele Road keke workshop (15,745.00 mg/kg). In several locations, the main workshop exhibited higher contamination than adjacent areas, although some sites showed greater TPH concentrations 10 m away, suggesting contaminant migration. Overall, the findings demonstrate widespread petroleum hydrocarbon contamination of automobile workshop soils, highlighting the need for routine environmental monitoring, improved waste management practices, and effective soil remediation measures to minimize ecological and public health risks.

The construction industry faces persistent challenges including labor shortages, productivity deficits, and significant environmental impact. 3D printing technology has emerged as a transformative solution offering substantial improvements in sustainability and cost-effectiveness. This review paper comprehensively examines the application of 3D printing in construction, with focus on material innovations, economic viability, and environmental performance. Through systematic analysis of contemporary literature, including techno-economic assessments and life cycle analyses, the paper evaluates various 3D printing technologies, sustainable material formulations, and their comparative advantages over traditional construction methods. The findings demonstrate that 3D-printed construction can reduce upfront costs by 20–30%, shorten construction time by 50–70%, and cut embodied carbon emissions by up to 55% while reducing material waste by approximately 40%. Material innovations including geopolymers, recycled aggregates, and earthen-based composites further enhance sustainability by reducing reliance on Ordinary Portland Cement. Challenges including regulatory gaps, initial investment requirements, and the need for reinforcement integration are discussed. The paper concludes by outlining future research directions necessary for widespread adoption of 3D printing in sustainable construction.

Modular construction has emerged as a transformative approach in the building industry, offering significant advantages over traditional on-site construction methods. This review paper provides a comprehensive examination of modular construction technology, encompassing its definition, classification, structural systems, material innovations, and future prospects. The paper synthesizes recent research advancements in inter-module connections, structural systems, and the integration of computational design approaches. Through a systematic analysis of contemporary literature, this review identifies key technical developments, evaluates the performance of various modular systems, and discusses the barriers to widespread adoption. The findings indicate that modular construction can reduce construction time by up to 50% and improve economic efficiency by 20% while minimizing material waste. However, challenges persist in areas such as inter-module connection performance, regulatory constraints, logistical complexity, and higher upfront costs. The paper concludes by outlining future research directions, including the integration of artificial intelligence in design optimization and the advancement of hybrid structural systems incorporating sustainable materials.

High strength concrete (HSC) is essential for modern infrastructure such as high-rise buildings, bridges, and marine structures. However, its high cement content contributes significantly to CO₂ emissions, making sustainability a critical concern. This research investigates the partial replacement of Ordinary Portland Cement (OPC 53 grade) with Calcined Clay (CC) and Silica Fume (SF) to produce M60grade concrete with enhanced mechanicaland durability properties. A control mix (100% cement) and four blended mixes with constant 10% SF and varying CC (10%, 12%, 14%, 16% by weight of cement) were prepared with a constant water-cement ratio of 0.30.
Compressive strength was evaluated at 7, 14 and 28 days on 150 mm cubes. Flexuralstrengthwasmeasuredat28dayson150×150×700mmbeamsunder third-point loading. Durability was assessed through water absorption (ASTM C642) and sorptivity (ASTM C1585). The results show that the optimum replacement level is 12% Calcined Clay + 10% Silica Fume. This mix achieved a 28-day compressive strength of 68.4 MPa (control: 55.2 MPa,+23.9%),aflexuralstrengthof7.8MPa(control:6.1MPa,+27.9%),awaterabsorptionof2.48%(control:3.85%,-35.6%),andasorptivityof0.072mm/min⁰·⁵ (control: 0.124 mm/min⁰·⁵, -41.9%). Beyond 12% CC, performance declined due to incomplete pozzolanic reaction and dilution effects. The study confirms that the combination of 12% calcined clay and 10% silica fume produces M60 grade concrete that meets strength requirements, offers excellent durability, and reducescement consumption by 22%, contributing to sustainable construction practices.

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals of global environmental concern due to their persistence, mobility, bioaccumulation potential, and documented toxicity. This comprehensive review synthesizes current knowledge on the industrial sources, occurrence, transport mechanisms, and risk assessment of PFAS in surface water environments. Industrial sources are diverse, encompassing fluorochemical manufacturing, electroplating, metal coating, textile production, paper processing, semiconductor manufacturing, and waste management facilities. Point-source contamination from these industries creates elevated PFAS concentrations in receiving waters, with documented levels exceeding 700 µg/L near some industrial parks. Studying PFASs in surface water yields insights into pollution dynamics, with PFAS contamination documented in regions affected by industrial relocation patterns post-2010 (J. Wang et al., 2024). Transport of PFAS occurs through multiple pathways including direct wastewater discharge, atmospheric deposition, and indirect pathways via biosolids application and landfill leachate. PFAS are extremely recalcitrant and widespread in the environment, with measurable concentrations in soils, sediments, groundwater, surface water, and rainwater, even at sites far removed from known sources or releases (Lotufo et al., 2026). Risk assessment reveals that surface waters near industrial zones frequently exceed regulatory standards for PFAS, with ecological and human health implications. This review identifies emerging contaminants, analytical challenges, knowledge gaps, and priorities for source control and remediation. Advanced treatment technologies and regulatory frameworks are critical to mitigate PFAS contamination in surface water ecosystems globally.

The global prevalence of youth physical inactivity is one of the most defining public health challenges of the twenty-first century, with global surveillance data indicating that more than 80% of adolescents do not meet the recommended thresholds for daily physical activity outlined by the World Health Organization (WHO, 2022). One promising model for addressing this crisis is hybrid fitness ecosystems, programs that blend structured human coaching with emerging digital technologies such as wearable sensors, mobile health applications, and AI-driven movement analysis platforms. This article examines the theoretical and empirical case for hybrid fitness ecosystems as tools for youth development and injury prevention. Two primary research questions are addressed:
1. What role does human coaching versus digital feedback play in shaping motivation and engagement in youth fitness programs? and
2. Do hybrid fitness models improve long-term adherence to physical activity compared to traditional in-person-only programs?

Drawing on self-determination theory (SDT), the transtheoretical model of behavior change, and emerging evidence from sports science, exercise psychology, and digital health, this article finds that human coaching remains irreplaceable for fostering intrinsic motivation, autonomy, and social relatedness, while digital tools extend reach, real-time data accessibility, and individualized load management. Hybrid models, when optimally integrated, have shown promise for better adherence outcomes than single modality programs, but the evidence base is still developing and methodologically diverse in the long term. Recommendations for practitioners, researchers, and policymakers are presented, along with a forward-looking research agenda.

Juvenile delinquency is a serious socio-legal problem of today. India is not left out. The relationship between child development and social context, economic inequality, psychological disadvantage and the legal system’s response to youth offending behaviour is complex. Juvenile delinquency refers to illegal or anti-social behavior of a legal minor or non-adult. It follows from the above definition that the meaning should be deepened. Juvenile delinquents are not just children who commit crimes. The dissolution of social institutions and ineffectiveness of law also creates specific situations in which deviance occurs.Some causes of juvenile delinquency in India include urbanisation, increased nuclear families, open economy, media exposure and value system of society. There is the chance that the risk of violence will increase for children and young people while risk of crime will arise for children. The norms that have been established no longer serve as effective instruments of social control and the growing number of juveniles being placed in a situation which at least encourages or does not discourage deviance.

Perovskite-based materials have attracted extensive attention for high-temperature thermoelectric power generation because of their excellent thermal stability, structural flexibility, environmental compatibility, and resistance to oxidation at elevated temperatures. The perovskite ABO3 crystal structure accommodates a broad range of cation substitutes and oxygen defects, enabling effective tuning of electronic transport and phonon scattering mechanisms required for thermoelectric energy conversion. This work emphasizes the structural and thermoelectric characterization methodologies used to establish the relationship between compositions, microstructure and transport behavior in perovskite thermoelectrics. Particle size analysis (PSA) is employed to evaluate powder finenessand distribution, which influence densification and grain growth. Thermogravimetric analysis (TGA) provides information on thermal decomposition, phase evolution and oxygen stability during heating. X-ray diffraction (XRD) is used for phase identification, lattice parameter determination, crystallite-size analysis, and structural refinement. Scanning electron microscopy (SEM) reveals grain morphology, porosity and microstructural homogeneity, while energy dispersive x-ray spectroscopy (EDS/EDX) confirms elemental composition and dopant distribution. The integration of these techniques provides a comprehensive understanding of crystal structure and microstructure affect thermoelectric properties at high temperatures. Representative Perovskite material (La-Sm doped strontium titanate) is discussed to illustrate current advances in oxide thermoelectrics for waste heat recovery and sustainable power generation.

The integration of Analytical Quality by Design (AQbD) with Green Analytical Chemistry (GAC) represents a transformative approach in High-Performance Liquid Chromatography (HPLC) method development and validation. This review aims to provide a comprehensive overview of how AQbD frameworks can be systematically combined with GAC principles to achieve robust, reproducible, and environmentally sustainable analytical methods. AQbD facilitates method optimization through tools such as risk assessment, Design of Experiments (DoE), and Method Operable Design Region (MODR) establishment, while GAC focuses on minimizing hazardous solvent use, energy consumption, and waste production. This review evaluates peer-reviewed studies published between 2022 and mid-2025 that demonstrate AQbD-based HPLC and UPLC methods employing eco-friendly solvents, particularly ethanol and water, and assessing environmental sustainability using green metrics including AGREE, GAPI, AMGS, and Analytical Eco-Scale. Case studies on pharmaceutical analytes such as metronidazole, nicotinamide, irbesartan, metformin, and empagliflozin illustrate the practical implementation of these approaches, with several studies reporting high green scores and regulatory alignment with ICH guidelines. Despite significant progress, challenges persist, including inconsistent application of greenness metrics, limited availability of green solvent alternatives, and the need for integrated software tools that combine AQbD and GAC evaluation. This review highlights key methodological gaps and future opportunities, including extending AQbD-GAC approaches to complex matrices and integrating Artificial Intelligence (AI) to enhance optimization and sustainability. Overall, the convergence of AQbD and GAC not only ensures analytical reliability and regulatory compliance but also aligns with global sustainability goals and emerging eco-conscious scientific practices.

Public sector organizations across the globe are increasingly adopting emerging digital technologies to enhance efficiency, transparency and service delivery. This research paper examines how the strategic integration of emerging technologies such as artificial intelligence, big data analytics, cloud computing, blockchain, and the Internet of Things drives transformational change in public sector institutions. Aligned with the scope of Scopus and Web of Science indexed journals, the study adopts a conceptual and analytical approach to explore the drivers, mechanisms, and outcomes of digital integration in public administration. Drawing upon digital transformation theory, public value theory and Technology Organization Environment (TOE) frameworks, the paper proposes an integrative model explaining how technological integration reshapes governance structures, administrative processes and citizen engagement. The findings highlight that digital integration not only improves operational efficiency but also strengthens accountability, policy responsiveness and inclusive governance. The paper concludes with policy implications and future research directions, offering valuable insights for scholars, policymakers and public sector leaders engaged in digital transformation initiatives.

Investment behaviour among individuals has become an important area of study due to the growing availability of diverse financial products and increasing awareness of personal financial planning. This study examines the investment behaviour, preferences, objectives, risk tolerance, and sources of investment information among 50 respondents. A descriptive research design was adopted, and primary data were collected through a structured questionnaire. The data were analyzed using percentage analysis and descriptive statistics.The findings reveal that the majority of respondents are young adults, with females slightly outnumbering males. Most respondents are students with monthly incomes below ₹10,000. About 62% of the respondents currently invest their money, with Fixed Deposits/Recurring Deposits and Mutual Funds emerging as the most preferred investment options, followed by Gold. The primary investment objectives are capital safety and wealth creation, while most respondents prefer low- to moderate-risk investments with short- to medium-term investment horizons. Friends, family, and social media serve as the major sources of investment information, whereas professional financial advisors are consulted by only a few respondents.The study concludes that respondents demonstrate a cautious investment approach, emphasizing financial security and moderate returns. Although investment participation is relatively high, there is a need to strengthen financial literacy and promote the use of credible financial information sources. The findings provide useful insights for financial institutions, educators, and policymakers in designing initiatives that encourage informed investment decisions and long-term financial well-being.

Generative artificial intelligence (GenAI) has rapidly entered second-language writing classrooms as a source of immediate explanations, language correction, idea development, and revision advice. Yet the pedagogical value of GenAI feedback remains uncertain because availability does not guarantee accuracy, learner uptake, or responsible use. This article presents a critical integrative review of recent empirical and design-based work on GenAI-supported writing and connects that evidence with established scholarship on second-language feedback, self-regulated learning, and feedback literacy. The review addresses three questions: what affordances and limitations characterize GenAI feedback in second-language writing; which learner and teacher practices influence productive engagement with such feedback; and how GenAI can be integrated without weakening learner agency or academic integrity. The synthesis identifies six recurring patterns: increased access to rapid and iterative feedback; useful supportforlanguageform,ideadevelopment,andconfidence;variableaccuracyandfrequentgenericity;thecentral importance of prompt and verification literacy; uneven effects on ownership and cognitive engagement; and the continuing need for teacher mediation, process evidence, and transparent disclosure. On the basis of these findings, the article proposes the PIVOT-ESL framework: Purpose and parameters, Interrogate and interact, Verify and validate, Own and operationalise revisions, and Trace, reflect, and disclose. The framework positions GenAI as a provisional feedback partner rather than an authority or substitute writer. The article concludes that effective use depends less on the sophistication of the tool than on the quality of task design, learner judgment, teacher guidance, and institutional policy. Implications are offered for classroom practice, assessment, teacher development, and future research, particularly in resource-constrained multilingual contexts.

Flipped learning hasbecome aprominentapproachin Englishasa Foreign Language(EFL)education because it relocates direct content delivery to the individual learning space and reserves classroom time for interaction, guided practice, feedback, and higher-order language use. However, the evidence is frequently presented as a simple comparison between flipped and conventional teaching, while the conditions that explain successful or unsuccessful implementation receive less integrated attention. This critical integrative review synthesises empirical and review-based evidence published between 2015 and 2025 to examine three questions: which learning outcomes are most consistently associated with flipped EFL instruction, which barriers account for variation in results, and which enabling conditions support effective and equitable implementation. Searches were undertaken across ERIC, Google Scholar, ScienceDirect, SpringerLink, Taylor & Francis Online, SAGE Journals, and relevant citation chains. Twenty-six peer-reviewed empirical studies met the eligibility and methodological-quality criteria and were analysed through structured data extraction and thematic synthesis. Five interconnected findings emerged. Flipped instruction was generally associated with stronger behavioural, cognitive, and social engagement; increased opportunities for oral interaction and collaborative learning; improvement in selected language outcomes, particularly speaking, writing, reading, grammar, and vocabulary; greater learner autonomy and self-regulation; and substantial implementationchallengesinvolvingaccess,workload,pre-class preparation, instructional design, and teacher readiness. The evidence also showed that positive outcomes were conditional rather than automatic. The strongest implementations linked concise and accessible pre-class input to purposeful in-class communication, incorporated accountability and scaffolding, monitored learner participation, and received institutional support. To translate the synthesis into practice, the review proposes the ALIGN framework: Access, Linkage, Interaction, Guidance, and Needs-sensitive monitoring. The review concludesthatflippedlearningshouldbe treated asa pedagogicalredesign ratherthana video-delivery technique, especially in resource-constrained EFL settings.

In today's highly competitive marketplace, organizations increasingly rely on emotional branding to create meaningful connections with customers and foster long-term loyalty. Emotional branding refers to the strategic use of emotions, values, experiences, and storytelling to establish a strong psychological bond between a brand and its consumers. This study examines the role of emotional branding in influencing customer perceptions, satisfaction, trust, and loyalty. By creating positive emotional experiences, brands can differentiate themselves from competitors and encourage repeat purchases, positive word-of-mouth, and stronger customer engagement. The study highlights key dimensions of emotional branding, including brand personality, customer experience, emotional attachment, and brand trust. Through a review of existing literature and contemporary business practices, the research demonstrates that customers who develop emotional connections with brands are more likely to remain loyal even in the presence of competitive alternatives. The findings suggest that emotional branding serves as a powerful marketing strategy for enhancing customer loyalty and sustaining long-term business growth. The study provides valuable insights for marketers seeking to strengthen customer relationships and achieve a competitive advantage in dynamic market environments.

This review article outlines a proposed precision agriculture system designed to empower smallholder farmers in sustainable agricultural activities, particularly within the context of Indian agriculture. Addressing critical challenges such as climate change vulnerability and inefficient resource management, the system integrates Internet of Things sensors, advanced machine learning models, and user-centric interfaces. The architecture features a layered approach, including an IoT Sensing Layer with low-cost sensors and robust connectivity (LoRaWAN/4G), a cloud-based Analytics Layer employing Python-based ML pipelines for irrigation prediction (RL/LSTMs), fertilizer recommendation (MORF/SVM), disease risk assessment, and yield forecasting (Regression/RF), and an accessible Interface Layer with a Flutter-based hybrid mobile-web app featuring a multilingual voice-to-text chatbot. As a partially implemented framework, core functionalities like IoT data collection and preliminary ML models have been demonstrated in a simulated environment using open-source software and mock/Kaggle datasets, achieving promising results with model accuracy ranging from 82%-94%. This iterative development approach allows for continuous refinement, with future work focused on real-field demonstrations in climate-vulnerable regions such as Maharashtra and Punjab. The methodology emphasizes scalability, affordability, and alignment with sustainable development goals, promising increased resilience and optimized resource utilization for smallholder farming communities.

However,thefastdevelopmentindigitaltechnologyhasledtodrasticchangesinalmostallareas pertaining to the economy. One area that has experienced a drastic makeover is the financial industry, this is where financial technology, or fintech has become a driving force in altering finance dynamics and ensuring that finance is not only efficient but easily accessible too. This paper will explore how digital finance is empowering education and markets.

Fintech is crucial in making financial education simpler through technology such as mobile applications, learning materials available online, and interactive learning solutions for people to learn basic concepts associated with saving, budgeting, investment and virtuous financial practices. This is especially helpful to fill the knowledge gap among different sections of the population, including students, rural areas, low-income households, and small business owners. Consequently, people become more empowered to use financial services effectively through technology.

Besidesimprovingfinancialliteracy,fintechhasmademajorcontributionsinthegrowthofonline shopping. Fin-tech innovations such as mobile money platforms, real-time payment platforms, internet banking platforms and contactless payment platforms have reduced reliance on cash, reduced transaction costs, increased transparency in transactions, and improved the speed and security of transaction processes. Such innovations have facilitated business growth and enabled businesses to access more customers.

Thestudyalsofocusesontheimportanceoffintechinbringingaboutfinancialinclusioninterms of offering access to low-cost financial services to those sections of the community who are unbanked or underserved by the conventional financial services sector. Despite its many benefitsanduses,theintegrationoffintechinvariousorganizationsandprogramsisobstructedbyfactors suchaslackofdigitalliteracyskills,issuesrelatedtocybersecurity,infrastructure,andregulatory hurdles. The importance of the term 'Fintech for Good' is an application and utilization approach based on considerations related to sustainable socio-economic development.

Digital governance, y’know it kinda matters a lot for boosting access to government services while also encouraging inclusive entrepreneurship. In this study we do a policy technology analysis of Tamil Nadu’s digital support systems, which are designed to back sustainable transgender entrepreneurial cooperatives. The initiatives the Government of Tamil Nadu brings in, they are more and more relying on digital platforms to hand out welfare benefits, enterprise help , and financial services in a way that is transparent, and also efficient. Basically, these systems are meant to cut down those administrative obstacles , so that transgender communities can reach opportunities more easily than before.
The paper talks about how digital things like online registration portals, direct benefit transfer systems, digital identity integration and e-governance platforms help cooperative-based entrepreneurship, kind of. It goes through how these arrangements make it easier to reach loans, subsidies, training programs, and even market linkages, more or less. From a sustainability point of view the study also looks at how digital monitoring systems boost accountability, data stewardship and ongoing performance tracking especially for transgender-led cooperatives.
The analysis rests on policy papers, official reports, and some secondary data mixed in. The results suggest that digital platforms, have made the steps a bit easier and brought more transparency to the process. Still, issues remain, like weak digital literacy in some groups, not having devices readily available, shaky internet connectivity, and even social stigma which can stop people from using the services properly. Overall the study underlines that technology by itself is not enough. What’s also needed is capacity building, hands-on digital awareness training and a supportive, institutional framework, so actual participation becomes real and sustained.
Overall, Tamil Nadu’s digital support environment has pretty strong potential to push along sustainable and mutually helpful transgender entrepreneurship ,so long as the policies stay inclusive, reachable, and socially responsive . If they drift, the whole ecosystem sort of loses traction, but when it’s kept aligned, the benefits can spread more widely through the community, in a kinda steady way.

When discussing the achievements of modern Chinese literature, Lu Xun is regarded as one of the most representative writers frequently mentioned by scholars. He made significant contributions to the genre of short stories in both domestic and international literary circles. Lu Xun’s contributions extend across both content and artistic aspects.In terms of artistic achievement, the art of constructing character personality through physical description, although not yet widely disseminated or extensively studied, remains vivid and remarkable. Therefore, this study focuses on examining the art of constructing character personality through physical description in several of Lu Xun’s representative short stories, while also comparing them with selected works of classical Chinese narrative literature.Through this approach, the study aims to generalize the writer’s distinctive and creative inheritances in this aspect by examining his works from the perspective of modern poetics and situating them within the cultural-social context of early twentieth-century China. In doing so, it seeks to explain the relationship between art and reality in Lu Xun’s literary creation.

Industry 5.0 represents a transformative paradigm that emphasizes collaboration between human intelligence and advanced intelligent technologies to create sustainable, resilient, and human-centric industrial systems. Unlike previous industrial models that primarily focused on automation and efficiency, Industry 5.0 places greater importance on human creativity, critical thinking, and decision-making while leveraging intelligent technologies to enhance productivity and innovation. This study examines the concept of Industry 5.0 and explores its role in harmonizing human intelligence, artificial intelligence, and sustainability within contemporary organizations. The research analyses the key principles of human-centricity, resilience, and sustainability and investigates how organizations can integrate advanced technologies with human capabilities to achieve balanced economic, social, and environmental outcomes. The study further discusses the opportunities associated with personalized production, improved workforce collaboration, enhanced innovation, resource optimization, and sustainable value creation. In addition, it identifies challenges related to workforce readiness, ethical considerations, technological integration, data security, and organizational transformation. Through a comprehensive review of contemporary literature and emerging industrial practices, the study proposes a framework for fostering collaboration between humans and intelligent systems in future workplaces. The findings suggest that organizations embracing Industry 5.0 can achieve greater adaptability, innovation, and sustainability while ensuring that technological advancement remains aligned with human well-being and societal development. The study provides valuable insights for business leaders, policymakers, and researchers seeking to build sustainable and future-ready enterprises.

Amidst the decline of Chinese feudal society, Lu Xun emerged as a historical witness who left a profound mark on Chinese literature. His short stories surpassed domestic boundaries to achieve international influence, leaving an indelible imprint on the spiritual life of humanity. This success stems from his diverse, profound themes combined with unique, sophisticated artistic techniques. In terms of artistry, the technique of “putting the finishing touch” in particular significantly contributed to shaping the character typologies in Lu Xun’s short stories. This paper examines the art of “putting the finishing touch” within his short stories across two collections, Nà hǎn and Páng huáng, while drawing comparisons with classical Chinese narrative works such as Sōu shén jì, Lí hún jì, and Liáozhāi Zhìyì. Through this analysis, we aim to demonstrate his distinctive inheritance of classical character-building methods, specifically the “portrait spirit” approach. This technique effectively highlights three character typologies: women, intellectuals, and peasants along with their respective tragedies. By analyzing the texts through the lens of modern poetics and contextualizing Lu Xun’s short stories within the socio-cultural landscape of early 20th-century China, this study elucidates the unique and representative relationship between literary artistry and reality.

This study explores the role of cybersecurity, data protection, and ethical practices in artificial intelligence (AI) within today’s digital landscape. It aims to understand individuals’ awareness, attitudes, and concerns regarding cyber risks, data privacy, and the responsible use of AI, as well as the relationships between these factors. Primary data was gathered through a structured online questionnaire, following a descriptive and analytical research approach.
The data were analysed using statistical methods including Chi-square and ANOVA to examine how demographic factors relate to respondents’ perceptions. Results show that while most participants recognize basic cybersecurity principles and value data protection, there are differences in awareness and practical application. Many participants expressed concerns about cyber threats, misuse of personal data, and biases in AI systems. Significant associations were found between certain demographic characteristics and perceptions of cybersecurity and ethical AI use.
The study emphasizes the importance of ethical guidelines, robust regulations, and shared responsibility among stakeholders to ensure safe and fair AI deployment. It recommends enhancing public awareness, strengthening cybersecurity practices, and promoting ethical AI governance. Overall, cybersecurity, data protection, and ethical AI are interconnected and essential for building trust in digital technologies.

Artificial Intelligence (AI) in sustainable finance is becoming a groundbreaking force that can be used by businesses to make strong data-driven financial decisions. AI technologies like machine learning, large data analytics, and predictive modeling are used to improve corporate finance, risk management, and sustainable investment ideas. AI enhances the financial accessibility, efficiency, and transparency in social finance. Where it improves the efficiency of distribution and management of funds. By analyzing investment performance, identifying sustainable trends, and creating equal pricing models. AI is important for to and ethical finance.
In addition to this, AI has a vital role in achieving Environmental, Social, and Governance (ESG) goals. AI can help to predict long-term environmental and economic impact and assess climate-based risk and find sustainable investment opportunities through the analysis of large and complex datasets. By improving decision-making processes and optimizing investment strategies, these skills empower investors and financial institutions to align their financial objectives with sustainable targets.
Beyond traditional financial analysis, this study focuses on the growing importance of AI in sustainable finance. It examines how AI can help with impact assessment, regulatory compliance, sustainability risk management, and responsible investment. The study also highlights modern AI technologies that enhance the efficiency of processing and interpretation of large datasets. Which allows more sustainable and informed decision-making. An example of such a tool is the Financial Maximally Filtered Graph (FMFG) algorithm.
Despite many benefits, integrating AI into sustainable finance comes with ethical, technological, and legal challenges related to data privacy, transparency, and governance. To increase the application of AI in sustainable finance, the study suggests a best practice framework. The study emphasis on how AI can improve sustainability, accuracy, and efficiency and in financial institutions. AI technologies will create a new path to new avenues for investors, companies, and politicians to build a more resilient, inclusive, and sustainable financial future as they evolve.

Artificial Intelligence (AI) is rapidly transforming the financial sector by enhancing analytics, improving decision-making, and strengthening fraud prevention mechanisms. Financial institutions generate vast volumes of data from customer transactions, digital interactions, and market activities, making traditional analytical methods insufficient for timely and accurate insights. AI systems, through advanced algorithms and machine learning, can efficiently process this data, identify patterns, and provide predictive insights, enabling organizations to make better-informed decisions and mitigate risks more effectively.
This study explores the role of AI in financial services, highlighting both its advantages and potential challenges. Data were collected from 84 respondents through a structured questionnaire and complemented with secondary sources, including journals and industry reports. Statistical tools such as correlation and chi-square tests were applied to understand the relationships between demographic factors and perceptions of AI. The analysis reveals no significant association between educational qualifications and respondents’ views on AI’s predictive capabilities in finance. However, a significant relationship was found between income level and concerns regarding privacy, indicating that individuals from different income groups perceive the risks associated with AI differently. Lower income groups tended to express higher concern for privacy, highlighting the importance of addressing trust and security issues across diverse customer segments.
Overall, the findings suggest that while AI significantly enhances operational efficiency and strengthens fraud detection in financial institutions, issues such as data privacy, security, and user trust remain critical barriers to adoption. For wider acceptance of AI technologies, financial institutions must implement robust privacy safeguards, transparent policies, and awareness initiatives to address these concerns while leveraging the full potential of AI in decision-making and risk management.

Modern businesses need to achieve economic success while demonstrating social responsibility and diversity inclusion. This research investigates the strategic implementation of Emotional Intelligence (EI) in Human Resource Management (HRM) practices to improve Corporate Social Responsibility (CSR) initiatives which focus on inclusive development. Employee attitudes and ethical decision-making processes depend on Emotional Intelligence which includes self-awareness and empathy as well as relationship management skills. Organizations create a culture that promotes socially responsible behavior and inclusive growth by implementing Emotional Intelligence into their Human Resource Management processes which include recruitment and training and performance appraisal and leadership development.
The research presents a strategic framework which connects EI competencies to HRM practices to enhance CSR results through effective social equality measures and stakeholder engagement activities. The research demonstrates how leaders and staff members who possess emotional intelligence create organizational practices that achieve sustainable and inclusive results. The study uses a conceptual framework which draws from established research to provide HR professionals and management executives with guidelines on how to connect their HR activities to their CSR objectives. The research demonstrates that organizations must implement emotional intelligence training for human resource management purposes to achieve sustainable development and equal growth.

This qualitative study employed focus group methodology to evaluate the effectiveness of organizational strategies, specifically human resource policies, training modules, and leadership styles in shaping work ethic and employee commitment within Ghanaian organizations. Drawing upon Social Constructionism (Berger & Luckmann, 1966) and Ubuntu Philosophy (Gyekye, 1997), the study conducted six focus group sessions with 42 participants drawn from public sector, private sector, and multinational organizational contexts across Accra, Tema, and Kumasi. Focus group discussions were guided by open-ended questions designed to elicit participants' lived experiences with HR policies (performance management systems, attendance tracking, reward structures), training interventions (work ethic modules, orientation programmes, values-based training), and leadership styles (autocratic, democratic, laissez-faire, transformational) as these intersected with their sense of commitment and motivation to work diligently. Data were analyzed using reflexive thematic analysis (Braun & Clarke, 2006). Six overarching themes emerged from the data: the implementation gap as a pervasive feature of HR policy experience; transactional compliance as the dominant response to formal performance systems; the differential effectiveness of training as shaped by perceived authenticity; the centrality of leadership accessibility and relational presence in shaping commitment; the alienating effects of bureaucratic impersonality on employee work ethic; and cultural misfit between Western HR models and Ghanaian communal work expectations. Participants' narratives revealed a profound disconnect between the stated intentions of organizational strategies and the lived experiences of Ghanaian employees, with policies and programmes frequently experienced as performative, disconnected from daily work realities, and poorly adapted to Ghanaian cultural contexts of relational work orientation. The study contributes to the understanding of organizational behaviour in Ghana by identifying specific conditions under which HR strategies, training modules, and leadership styles succeed or fail to enhance work ethic, offering evidence-based recommendations for policy design and implementation practice.

This qualitative study employed focus group methodology to explore how individuals from different economic backgrounds define, value, and enact hard work within Ghanaian organizational and informal work contexts. Drawing upon Social Constructionism (Berger & Luckmann, 1966) and Ubuntu Philosophy (Gyekye, 1997), the study conducted six focus group sessions with 41 participants drawn from three economic background categories lower-income, middle-income, and upper-income across Accra, Kumasi, and Sekondi-Takoradi. Focus group discussions were guided by open-ended questions and narrative prompts designed to elicit participants' definitions of hard work, their valuation of diligence as a personal and cultural value, their observed relationships between economic background and work behaviour, and their perceptions of whether and how social class shapes opportunity, effort, and reward in Ghanaian society. Data were analysed using reflexive thematic analysis (Braun & Clarke, 2006). Six overarching themes emerged from the data: hard work as survival necessity among lower-income participants; hard work as career advancement strategy among middle-income participants; hard work as legacy and social responsibility among upper-income participants; the hustle imperative as a cross-cutting work attitude shaped by economic precarity; perceived fairness or unfairness of the relationship between effort and reward as stratified by economic background; and intergenerational transmission of work attitudes as both reproducing and challenging class-based work orientations. Participants' narratives revealed that economic background profoundly shapes not only how individuals define hard work but also the purposes to which they believe hard work should be directed, the strategies they employ to demonstrate diligence, and their beliefs about whether hard work actually pays off in Ghanaian society. Lower-income participants defined hard work primarily as physical effort, long hours, and persistence in the face of adversity, valuing diligence as a survival tool and expressing ambivalence about whether effort leads to advancement. Middle-income participants defined hard work as strategic effort, skill development, and networking, valuing diligence as a career advancement mechanism while expressing anxiety about falling back into lower economic status. Upper-income participants defined hard work as stewardship, leadership, and social responsibility, valuing diligence as a moral obligation to family legacy and community development while acknowledging the structural advantages that made their effort less physically demanding. The study contributes to understanding of how economic background shapes work attitudes in Ghanaian contexts, offering insights relevant to poverty reduction, educational policy, workforce development, and organizational diversity and inclusion.

This study focuses on understanding the role of visual aesthetics in influencing consumer buying behaviour, with particular emphasis on design elements such as colour, packaging, typography, and overall product presentation. In today’s highly competitive market, where consumers are exposed to a wide variety of choices, visual appeal has become a key factor in shaping first impressions and purchase decisions. The research aims to analyze how these visual elements impact consumer perception, brand image, and buying behaviour, as well as how they contribute to differentiating original brands from imitation products. The study is based on primary data collected through a structured questionnaire administered to a sample of 60 respondents from different age groups and occupational backgrounds. Various statistical tools, including percentage analysis and the Chi-Square test, have been used to interpret the data and examine relationships between variables such as age, buying behaviour, and perception of design elements. The research also explores consumer awareness regarding imitation products and how visual similarity influences their purchasing decisions. Overall, the study concludes that visual aesthetics is not merely a decorative aspect but a powerful marketing tool that affects consumer perception, builds brand identity, and drives purchase decisions, highlighting the need for businesses to invest in strong and distinctive design strategies to remain competitive and reduce the risk of imitation while providing useful insights for marketers, designers, and businesses to better understand consumer preferences and enhance their branding efforts.

The world is undergoing an accelerated phase of the Fourth Industrial Revolution, with artificial intelligence (AI) emerging as its defining force. This transformation presents an urgent imperative for education systems to adapt and reform in a timely manner in order to remain aligned with contemporary developments; only through such responsiveness can the quality and effectiveness of teaching and learning be sustainably enhanced. In this context, AI has progressively established itself as a practical and influential tool in educational practices, both in Vietnam and globally. Educators are therefore required to develop the capacity to harness AI effectively in pedagogical processes so as to cultivate students’ curiosity, intrinsic motivation, and ability to independently construct and manage knowledge. This paper seeks to provide a concise overview of artificial intelligence, examine the pedagogical benefits of integrating AI into teaching and learning activities, and, in particular, propose several instructional approaches that employ AI to enhance writing skills in both English and Vietnamese for Grade 10 students at the upper secondary level. Furthermore, the study addresses critical challenges related to academic integrity and the regulation of AI overuse, emphasizing the need to prevent learner dependence that may result in unintended and adverse educational consequences. At present, this issue constitutes a significant challenge for students, as the high level of convenience offered by AI may foster passivity, diminish cognitive engagement, and ultimately exert negative effects on learning outcomes.

Identifying the actual competence of students plays a very important role in teaching. This helps teachers accurately recognize each student’s strengths and weaknesses, allowing them to use purposeful and effective teaching methods to support student learning. In Vietnam today, testing and assessing student learning in Literature and English happen quite frequently, but there are still gaps in practical quality. This shows that measuring and assessing student competence still has many gaps to fill. The purpose of argumentative writing is to understand the learners’ thoughts, perspectives, feedback, and critical thinking. However, many criteria and rubrics for assessing writing products are quite rigid, and accepting the learners’ personal perspectives has not received enough attention and lacks openness. This makes it difficult to measure learners’ critical thinking, problem-solving, and creativity. The current situation in Vietnam shows that testing and assessment have a huge impact on students’ thinking and writing products. In other words, assessment is a guiding factor that controls learners’ writing activities. Therefore, to create a new and open approach for assessing the argumentative writing of 10th-grade students in Vietnam, we propose developing an assessment Rubric based on the Toulmin model. With this approach, we hope that assessing students’ argumentative writing competence will both meet the current 2018 General Education Curriculum in Vietnam and align with assessment practices in countries with advanced education. In these countries, measuring critical thinking and creative ideas are basic and necessary competencies that positively impact student learning.

The 2018 General Education Curriculum is oriented toward organizing teaching and learning activities to develop learners’ qualities and competencies, in which self-learning competence plays an important role. In Literature teaching, the development of self-learning competence raises the following question for teachers: “How can students be helped to effectively form and develop self-learning competence?” There are many methods to address this issue. Within the scope of this study, we used the flipped classroom model to organize teaching for high school students in order to develop the self-learning competence of Grade 11 students.

Ancient Indian agricultural practices, centered on the principle of Bhoomi Suposhana (soil nourishment), utilize complex fermented formulations such as Kunapajala, Panchagavya, and Jivamrita to restore biological soil vitality. While these time-honored methodologies demonstrate a sophisticated understanding of microbial ecology and nutrient cycling, their widespread industrial adoption is limited by the "Standardization-Stability-Scalability" triad.The integration of microbial biotechnology offers a path to modernize these ancestral liquid ferments. By employing metagenomic characterization to map functional microbial taxa, bio-polymeric encapsulation to extend shelf-life, and nanotechnology for precision delivery, researchers can stabilize the potent microbial consortia found in Vedic formulations. This synthesis represents a paradigm shift toward sustainable, climate-smart agriculture that bridges the gap between decentralized "farm-side" practices and high-efficacy industrial applications.

This practice school report focuses on the pharmaceutics aspects of ethosuximide, an antiepileptic drug used for the treatment of absence seizures. The objective was to understand the formulation and evaluation processes of ethosuximide capsules by connecting academic knowledge with industrial practices. The report covers epilepsy and pharmacological aspects of ethosuximide, preformulation studies, capsule formulation, and evaluation tests. It provides an overview of the pharmaceutical processes involved in developing a stable, effective, and quality ethosuximide capsule dosage form.This comprehensive review aims to bridge theoretical knowledge with practical application, enhancing understanding of pharmaceutical processes involved in developing ethosuximide as in antiepileptic drug.

Analgesic and anti-inflammatory drugs are widely used for the management of pain, inflammation, and fever. Among these, diclofenac sodium is one of the most commonly used non-steroidal anti-inflammatory drugs (NSAIDs) due to its analgesic, antipyretic, and antiinflammatory properties. Diclofenac exerts its pharmacological action by inhibiting cyclooxygenase enzymes (COX-1 and COX-2), thereby reducing prostaglandin synthesis.
The present study focuses on the formulation and evaluation of diclofenac tablets along with the necessary preformulation studies required for successful dosage form development.
Preformulation studies were carried out to evaluate the physicochemical properties of diclofenac sodium, including solubility, melting point, pka, partition coefficient, polymorphism, hygroscopicity, and flow properties such as angle of repose, bulk density, tapped density, Hausner's ratio, and Carr's index. Compatibility and stability studies were also performed to ensure the suitability of the drug for tablet formulation.
The formulation process involved the selection of suitable excipients such as diluents, binders, lubricants, glidants, disintegrants, and coating materials to achieve efficient tablet compression and optimum drug release. Various manufacturing methods including direct compression, wet granulation, and dry granulation techniques were studied.
Evaluation tests such as weight variation, hardness test, friability test, thickness, content uniformity, dissolution test, disintegration test, moisture content determination, and stability studies were carried out to assess the quality, safety, and efficacy of the formulated tablets.
The study concludes that proper preformulation, formulation, manufacturing, and evaluation processes are essential for the development of stable and effective diclofenac tablets with good therapeutic performance and improved patient compliance.

The growing frequency of transboundary crises has exposed fundamental weaknesses in contemporary governance systems. Global pandemics, climate change, geopolitical conflicts, cyber threats, financial instability, and information disorder increasingly transcend national boundaries, while governance institutions remain predominantly state-centric. This structural mismatch creates persistent tensions between national interests and global solidarity. Governments prioritize domestic security, economic stability, and political legitimacy, whereas effective crisis management often requires collective action and international cooperation. This paper examines the interaction between national interests and global solidarity through a comparative analysis of major international crises, including the COVID-19 pandemic, climate change governance, the Russia–Ukraine conflict, global financial instability, cybersecurity threats, and the global infodemic. Drawing upon realism, cosmopolitan institutionalism, and polycentric governance theory, the study identifies recurring structural bottlenecks that impede collective responses. The paper proposes aManaged Interdependence Framework based on ex-ante commitments, stratified subsidiarity, and incentive alignment. The findings suggest that global solidarity should not be viewed as an alternative to national interest but as its most sustainable extension in an interconnected world. The study contributes to international relations and public policy scholarship by offering a practical governance model capable of reconciling sovereignty with collective resilience.

The universal process of aging affects all living organisms, leading to reduced physiological function and a heightened risk of age-related diseases. With global life expectancy on the rise, addressing aging concerns has become essential, as underscored by the World Health Organization’s Global Strategy for healthy aging. The skin, the body’s largest organ, plays crucial roles in immune defense, hydration, and environmental protection, while also being a key factor in individual identity. Consequently, the demand for effective anti-aging solutions, including supplements and skincare applications, continues to grow.
This article examines various aging theories, including DNA, free radical, neuroendocrine, and telomerase theories, while exploring the molecular foundations of skin aging. Key mechanisms, such as telomere shortening, oxidative stress, and inflammation, drive the aging process, with external factors like UV exposure accelerating skin deterioration. Certain bioactive phytochemicals, notably polyphenols and carotenoids, demonstrate potential in counteracting aging effects; for example, resveratrol and epigallocatechin gallate (EGCG) help preserve collagen and maintain skin elasticity, while beta-carotene supports cellular repair and UV defense.
Additionally, medicinal plants like Aloe vera, amla, turmeric, and ginseng, along with their active constituents—such as aloin, curcumin, and ginsenosides—exhibit antioxidant, anti-inflammatory, and collagen-supportive properties. These findings suggest that phytochemical-based approaches could play a valuable role in anti-aging skincare, with promising implications for health and wellness industries.

Background: Crimeimposessubstantialeconomic,social,andpsychologicalcostsonindividuals, communities, and national economies. Global estimates of the direct and indirect costs of crime exceed several trillion US dollars annually. Since Becker's (1968) foundational rational-choice framework, economists have investigated how macroeconomic and microeconomic conditions poverty, income inequality, unemployment, inflation, economic growth, education, urbanisation, and economic shocksshape criminal behaviour across diverse institutional and developmental contexts.
Objective:Thisreviewsystematicallysynthesisestheglobalempiricalliteratureontheeconomic determinants of crime, aiming to: (i) identify the economic factors most consistently associated withcriminalbehaviour;(ii)comparefindingsbetweendevelopedanddevelopingeconomies;(iii) critically appraise the methodological approaches adopted in the economics-of-crime literature; and (iv) identify research gaps and priorities for future inquiry, with particular attention to South Asia and India.
Materials and Methods: The review adheres to the PRISMA 2020 reporting guidelines. A structured search was conducted across eight databases Scopus, Web of Science, JSTOR, ScienceDirect,SpringerLink,WileyOnlineLibrary,Taylor&FrancisOnline,andGoogleScholar usingBooleancombinationsofeconomicandcrime-relatedkeywords,restrictedtopeer-reviewed empirical studies published between 2000 and 2026. Following duplicate removal, title-and-abstract and full-text screening stages identified 127 eligible studies. Studies were quality-appraised using a structured checklist adapted for observational econometric research and synthesised narratively with supporting tabular analysis.
Results: Of 127 included studies, unemployment (particularly youth and long-term) and income inequality emerged as the most consistently significant economic correlates of crime across geographic and methodological contexts. A one-percentage-point increase in unemployment is associatedwitha1.6–4.0%increaseinpropertycrimeratesincrediblyidentifiedstudies.Income inequality,proxiedbytheGinicoefficient,showsarobustpositiveassociationwithviolentcrime in cross-country panels. Education demonstrates a strong crime-reducing effect; completing high school reduces the probability of incarceration by an estimated 0.76–3.4 percentage points. The poverty–crimerelationshipispositivebutattenuatessubstantiallyinmultivariatemodels.Findings differ systematically between developed and developing economies in magnitude and dominant transmission channel.
Conclusion: The evidence base, while substantial, remains geographically concentrated in high-income countries and methodologically uneven. Unemployment, income inequality, and low educationalattainmentarethestrongestandmostpolicy-relevanteconomicdeterminantsofcrime. Expanding rigorous research in low- and middle-income countries, strengthening causal identification strategies, and integrating economic and criminological frameworks are priorities for advancing both theory and evidence-based crime prevention policy.

Analgesic and antipyretic drugs are widely used for the management of pain and fever, among which acetaminophen is one of the most commonly used drugs due to its safety and effectiveness. The present study focuses on the formulation and evaluation of acetaminophen syrup along with the preformulation studies required for successful dosage form development.

Preformulation studies were carried out to evaluate the physicochemical properties of acetaminophen such as solubility, melting point, pH, and compatibility with excipients to ensure suitability for syrup formulation. The formulation process involved the selection of suitable excipients including sweetening agents, preservatives, flavoring agents, and stabilizers to improve palatability, stability, and therapeutic effectiveness.

Evaluation tests such as physical appearance, pH, viscosity, drug content, organoleptic properties, and stability studies were performed to assess the quality, safety, and efficacy of the prepared syrup. The study concludes that proper preformulation, formulation, and evaluation processes are essential for developing a stable, safe, and effective acetaminophen syrup with good therapeutic performance and patient compliance.

The retail industry has experienced significant changes with the rapid growth of e-commerce, digital technologies, and evolving consumer expectations. Consumers today have access to both online and offline retail channels, each offering distinct advantages that influence purchasing decisions. Consequently, understanding consumer preferences toward these retail formats has become increasingly important for retailers, marketers, and researchers. This study presents a systematic review of the literature on consumer preferences in online and offline retailing. Relevant studies published between 2012 and 2025 were identified through major academic databases, including Scopus, Web of Science, Google Scholar, ScienceDirect, and SpringerLink. The selected studies were analyzed and synthesized to identify the key determinants influencing consumer shopping behavior across retail channels.The review findings reveal that trust, convenience, shopping experience, and omnichannel integration are the primary factors shaping consumer preferences. Online retailing is generally preferred for its accessibility, time efficiency, product variety, and ease of information search, whereas offline retailing continues to attract consumers through direct product inspection, immediate ownership, and personalized interactions. The findings further indicate that technological innovations such as mobile commerce, digital payment systems, augmented reality, and social media marketing are transforming shopping experiences and influencing channel selection. Moreover, consumers increasingly adopt hybrid shopping behaviors by utilizing both online and offline channels throughout their purchasing journeys. The review also identifies important research gaps related to sustainability concerns, cultural differences, technological readiness, and omnichannel consumer behavior. By integrating fragmented findings from existing studies, this review contributes to a broader understanding of contemporary retail preferences and offers valuable directions for future research. The findings provide practical insights for retailers seeking to develop customer-centric and integrated retail strategies in an increasingly competitive marketplace.

The rapid digitization of healthcare has led to the creation of extensive and diverse medical datasets generated from electronic health records, laboratory information systems, diagnostic imaging platforms, and wearable health technologies. Although such data holds substantial potential toenhance clinical decision-making, conventional diagnostic practices continue to rely largely on manual evaluation and are inefficient in handling complex, high-dimensional medical information. Consequently, the early detection of chronic diseases such as lung cancer and Chronic Kidney Disease (CKD) remains a significant global challenge. To address this issue, this study presents a machine learning–based health risk prediction system that utilizes Big Health Data for accurate disease risk assessment. The proposed framework analyzes clinical, demographic, and lifestyle features using Logistic Regression, Random Forest, and XGBoost algo-rithms. By automating feature extraction and pattern recognition, the system enhances predictive accuracy, reduces diagnostic inconsistency, and supports timely clinical intervention. Exper-imental findings indicate that ensemble and gradient boosting techniques achieve superior predictive performance compared to traditional diagnostic approaches.

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disorder characterized by joint synovial inflammation, progressive cartilage degradation, and bone erosion, ultimately leading to joint deformity and functional disability. Although conventional therapies such as non-steroidal anti-inflammatory drugs and disease-modifying antirheumatic drugs are commonly prescribed, their long-term use is frequently limited by associated adverse effects.In recent years, natural plant extracts and phytoconstituents have gained considerable attention as potential therapeutic agents for RA due to their diverse pharmacological properties. Evidence from various studies indicates that these bioactive compounds exert significant anti-inflammatory and immunomodulatory effects by inhibiting key pro-inflammatory cytokines such as tumour necrosis factor-alpha (TNF-α), interleukin-1 (IL-1), and interleukin-6 (IL-6), thereby reducing inflammation and disease progression. In addition, herbal therapies are considered relatively safe, cost-effective, and may offer opportunities for individualized treatment approaches.However, additional studies are required to confirm clinical efficacy, establish safety profiles, and develop standardized formulations for the successful incorporation of herbal therapies into rheumatoid arthritis management.

This article critically examines the architecture governing Reducing Emissions from Deforestation and Forest Degradation (REDD+) in Cameroon, arguing that an effective regime must transcend a narrow focus on carbon sequestration to robustly safeguard biodiversity and secure community rights. It scrutinizes the adequacy of Cameroon's national legal framework, including the new 2024 Forestry Code and related environmental laws, in creating mandatory protections beyond mere carbon metrics. Through a comprehensive juridical analysis, the study investigates the intricate interplay between international REDD+ safeguards and their translation into enforceable national legal provisions. The paper evaluates the mechanisms for ensuring Free, Prior and Informed Consent (FPIC), equitable benefit-sharing, and the protection of livelihoods for forest-dependent communities, identifying critical gaps between legal rhetoric and on-the-ground implementation. By drawing on case studies and project documents, the article reveals the legal and procedural challenges that perpetuate community marginalization and biodiversity loss, even within purportedly sustainable climate initiatives. It concludes by proposing a fortified legal framework that explicitly prioritizes biodiversity co-benefits and enshrines community rights as non-negotiable pillars of climate justice, ensuring Cameroon's REDD+ projects deliver truly sustainable and equitable outcomes.

The present research study investigates the awareness and use of Open Educational Resources among the research scholars of Mangalore University. A sample of 185 research scholars was involved in the study. Random sampling technique was usedduring the selection process. The instrument used for the study to collect data from respondents is a structured questionnaire. The findings of the study showed that, all 185(100.0%) of respondents were aware about OERs, 173(93.5%) the respondents marked most often use journal papers for their research purpose, 156(84.3%) of respondents use it to write research papers/Articles/Books/Chapters.

The study aim is to know the usefulness of e-learning among PG students of Distance Learning of Kuvempu University, Shivamogga. The main effort of the study is to determine the impact of e-learning among PG students of distance education . The study has adopted survey method for collection of data. Questionnaire was structured to elicit answers from the respondents. Questionnaire were distributed to the students throughout their contact classes of Kuvempu University.The results revealed that, 1377(95.9%) of the respondents use the Smart Phone for e-learning, while majority 1131(78.8%) users ‘Agree’ with the statement ‘E-learning gives opportunity to learn more’, 936 (65.2%) users ‘Strongly agree’ with ‘E-learning helps me to acquire new knowledge effectively’.The results of the study focused on the influence of e-learning on executing successful plans in the university educational system, making awareness during the contact classes about e-learning tools and technologies for distance learning.

Satellite image classification attains greater significance in remote sensing applications such as land use monitoring, agriculture, environmental analysis, and disaster management. Artificial Intelligence (AI) and Deep Learning (DL) techniques have performed satellite image classification through efficient extraction of meaningful spatial and spectral information from remote sensing data. Traditional classification approaches often face challenges in handling high-dimensional imagery, complex land cover patterns, and large-scale datasets. This review presents a comprehensive analysis of various AI-based approaches used for satellite image classification, including Support Vector Machines (SVM), Random Forest (RF), Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Transformer-based architectures. The review highlights that DLconcepts, particularly CNN and Transformer-based frameworks, achieve superior performance compared to conventional Machine Learning (ML) methods due to their automatic feature learning capability and strong representation power. Finally, emerging research directions including explainable AI, federated learning, lightweight architectures, and multimodal data fusion are discussed to provide insights for future developments in intelligent satellite image analysis systems.

India's agricultural sector, which accountsfor58%ofemployeesandproduces18% of GDP, is incrucial danger due to climate extremes, resources car city, and inefficient farming practices, a sevidenced by the 2023 Punjab floods (₹5,000 crore damage on 1.2 lakh hectares) and Maharashtra (₹2,200 crore on 2.5 lakh hectares), and the need for resilient agriculture. Conventional methods yield poor results from generalized advice that does not consider local variations, resulting in wastage of resources and losses during harvesting. This project aims to have an integrated precision farming system with IoT sensors formeasurementofsoilmoisture,temperature,humidity,andrainfalllevelsinreal-timeusingmachine learning (ML) models for predictive irrigation planning, organic vs. chemical fertilizer guidance, and diseaseriskforecasting.Intendedforsmallholderfarmers,thesystemofferspersonalizednotifications viaamultilingual(Hindi,Marathi,English)WhatsAppandSMSbotbackedbyvoicesupportforlow-literacyusersandexplainableAI(XAI)toensuretrust.Thereisanadminconsolefordatamanagement andfeedback-basedMLfine-tuningusingtheRandomForest,SVM,CNNs,andLSTMsalgorithmson diverse datasets like Kaggle, IMDAPIs, and satellite imagery. By lowering water/fertilizer use by 30-50%andimprovingyieldsby20-30%,theaffordable,scalableplatformpromotessustainablepractice, improves climate resilience, and supports SDGs on food security

In modern software development, DevOps pipelines are essential for delivering applications quickly and efficiently. However, these pipelines generate a massive amount of log data during Continuous Integrationand Continuous Deployment (CI/CD) processes, making manual analysis challenging, time-consuming, and error-prone. This study presents an AI-based solution that leverages Natural Language Processing (NLP) to simplify log analysis and improve failure prediction. The system converts unstructured log data into a structured format using techniques such as log parsing, tokenization, and feature extraction. MachineLearning and Deep Learning models, including Logistic Regression, Random Forest, Support Vector Machine, and Long Short-TermMemory (LSTM), areapplied to identify patterns and detect anomalies in the logs. Among these, LSTM performs best due to its ability to understand sequential data. The system can also incorporate voice-to-text functionality, allowing spoken inputs to be transcribed and summarized for easier interpretation. Experimental results show improved prediction accuracy, reduced manual effort, and faster issue detection. Overall, the proposed approach enhances system reliability, minimizes downtime, and supports efficient and automated DevOps workflows in real-world environments.

The continuous advancement of wireless network technologies has accelerated the development of sixth-generation (6G) networks, which are expected to significantly enhance the capabilities of future digital infrastructures. These networks aim to distribute extremely high data transmission rates, ultra-low latency communication, intelligent network automation, and seamless connectivity among billions of interconnected devices. Such capabilities will enable emerging applications including immersive virtual environments, autonomous transportation, smart healthcare systems, and large-scale Internet of Things (IoT) ecosystems. However, the increasing complexity and distributed architecture of 6G networks introduce serious security concerns. The integration of heterogeneous devices, edge computing, and cloud-based infrastructures increases the attack environment and itmakesthe state-of-the-art perimeter-based security techniquesunsatisfactory for protecting modern communication environments.To resolve these drawbacks, the Zero-Trust Security Architecture (ZTSA) has gained significant attention as a robust security paradigm for next-generation networks. Unlike conventional security approaches that rely on predefined trust boundaries, ZTSA operate under the principle that no entity should be trusted by default, regardless of its location within the network. Instead, it continuouslyauthenticates every access request before access to network resources is granted. In this context, the present review paper provides a comprehensive examination of ZTSA for 6G wireless communication systems. The study discusses the fundamental principles of ZTSA, its incorporation with advanced technologies i.e. artificial intelligence, block-chain, and edge computing, and the key security challenges associated with large-scale deployment. Furthermore, the paper analyzes existing research contributions and identifies potential directions for future investigation aimed at developing scalable, intelligent frameworks for next-generation wireless networks.

Background: The Ayurvedic concept of Raktavaha Srotas is traditionally associated with the liver, spleen, and bone marrow. Modern physiology defines the mononuclear phagocyte system (MPS) formerly the reticuloendothelial system as the primary immuno hematological interface. Prior integrative efforts have noted anatomical parallels, but no review has systematically mapped Raktavaha Srotas onto the MPS using contemporary molecular pathways with explicit discussion of partial homologies.
Objective: To evaluate structural, functional, and pathological homologies between Raktavaha Srotas and the MPS, and propose an integrative model of the “Ayurvedic immuno hematological interface.”
Methods: A narrative review was conducted using primary Ayurvedic texts (Charaka Samhita, Sushruta Samhita) and PubMed/Scopus literature (1980–2025) on MPS, Kupffer cells, splenic red pulp macrophages, heme metabolism, and hemophagocytic syndromes. Search terms included “Raktavaha Srotas,” “mononuclear phagocyte system,” “heme oxygenase 1,” “erythrophagocytosis,” and “Pitta.”
Key Findings: Three homologies are identified. (1) Anatomical: Yakrit (liver), Pliha (spleen), and Asthi Majja (bone marrow) form the Mula Sthana of Raktavaha Srotas (1,2), identical to principal MPS organs (3,4). (2) Cellular: Rakta Dhatu Agni (metabolic fire of blood) aligns functionally with heme oxygenase 1 (HO 1) activity in red pulp macrophages (5 7). (3) Functional: Pitta’s role in “heat dependent detoxification” parallels NADPH oxidase mediated respiratory burst in MPS phagocytes (8,9). The homology is partial: alveolar macrophages, microglia, and peritoneal macrophages are not described in classical Raktavaha Srotas.
Conclusion: The MPS is the closest modern correlate to Raktavaha Srotas, but the homology is incomplete. The proposed model requires validation through functional assays and Prakriti stratified analyses.

“Speak up for those who cannot speak” (Proverbs 31.8). This study examines the persistence of caste-based discrimination among Dalit Christians in India, challenging the assumption that religious conversion ensures social equality. Drawing on the ideas of Dr. B. R. Ambedkar, particularly his critique of caste as a deeply entrenched social system rather than merely a religious construct, the paper explores how caste identities continue to shape the lived experiences of converted communities. Using an interdisciplinary approach that combines theoretical analysis, textual interpretation, and sociological insights, the study investigates the structural and cultural continuities of caste within Christian institutions and practices. It highlights how Dalit Christians often face segregation in churches, exclusion from leadership roles, and denial of equal social status, thereby reproducing caste hierarchies in a new religious context.
The central argument of this paper is that conversion, while offering spiritual transformation, does not necessarily lead to the annihilation of caste, as envisioned by Ambedkar. Instead, caste persists through social practices, institutional structures, and community attitudes. The study concludes that addressing caste among Dalit Christians requires not only theological reform but also a broader socio-political commitment to equality and justice, in line with Ambedkarite thought.

The present study aims to evaluate the physico-chemical characteristics of river water in Sirauli Village, located in the Manendragarh–Chirmiri–Bharatpur district of Chhattisgarh (Pin code: 497442), to determine its suitability for drinking and irrigation purposes. Water samples were collected from selected points along the river and analyzed for key physico-chemical parameters including temperature, pH, turbidity, total dissolved solids (TDS), electrical conductivity (EC), dissolved oxygen (DO), biochemical oxygen demand (BOD), total hardness, alkalinity, chloride, nitrate, calcium, magnesium, and iron using standard analytical methods. The results were compared with permissible limits prescribed by BIS and WHO guidelines for drinking water quality. The analysis revealed that most parameters were within acceptable limits, indicating relatively good water quality. However, slight variations in parameters such as turbidity, hardness, and nutrient content were observed, which may be attributed to seasonal changes and local anthropogenic activities such as agricultural runoff and domestic waste disposal. The study also evaluates irrigation suitability based on parameters like salinity and hardness, suggesting that the water is generally suitable for agricultural use with minimal risk to soil health and crop productivity. Overall, the findings indicate that the river water in Sirauli Village is fit for both drinking (after basic treatment) and irrigation purposes, though continuous monitoring and proper management practices are recommended to prevent future contamination and ensure sustainable water quality.

Ultrasonic communication has emerged as a promising alternative medium for short-range, low-power data transmission in Internet of Things (IoT) applications. This project presents the design, development, and evaluation of an ultrasonic IoT communication framework capable of transmitting digital information using inaudible high-frequency sound waves (typically above 18 kHz). The primary objective is to establish a cost-effective, hardware-independent communication channel that operates using existing audio interfaces such as microphones and speakers, thereby eliminating the need for conventional wireless technologies like Wi-Fi, Bluetooth, or RF modules.
The proposed system employs modulation techniques such as Frequency Shift Keying (FSK) and Amplitude Shift Keying (ASK) to encode digital data into ultrasonic signals. These signals are transmitted through standard audio hardware and received by compatible devices, where demodulation and decoding processes reconstruct the original data. The architecture integrates microcontrollers, signal processing algorithms, and IoT interfaces to enable seamless device-to-device communication.
In the implemented phase of the project, ultrasonic signal generation and modulation were successfully achieved, and experimental validation demonstrated reliable data transmission over short indoor distances. A basic receiver module was developed to perform signal filtering, decoding, and error detection. Performance evaluation indicates that ultrasonic communication offers advantages such as low energy consumption, enhanced security due to limited propagation range, and reduced interference compared to traditional RF-based systems.
Furthermore, the system shows potential for applications in secure authentication, proximity-based data exchange, indoor localization, and smart environments. Despite challenges such as environmental noise sensitivity and limited bandwidth, the results confirm the feasibility of ultrasonic communication as an innovative and efficient solution for next-generation IoT networks.

The traditional attendance management system used in educational institutions is often time-consuming, error-prone, and vulnerable to proxy attendance. To address these challenges, this paper presents an RFID-based automated attendance system integrated with IoT using the ESP32 microcontroller. In the proposed system, each student is assigned a unique RFID tag, which is scanned by an RFID reader to capture attendance data. The ESP32 processes the tag information and transmits it to a cloud-based database via Wi-Fi using HTTP or MQTT protocols.
The system enables real-time attendance tracking, secure data storage, and easy access through a web or mobile interface. Compared to conventional methods, the proposed solution significantly reduces manual effort, improves accuracy, and minimizes chances of manipulation. Experimental results show enhanced efficiency, faster processing time, and reliable performance in real-time environments. This system contributes to the development of smart classrooms by providing an automated, scalable, and cost-effective attendance management solution.

This research study was carried out on the assignment from associates, working for Government of India. Regarding coal deposits at the coal concession of Pt Guang Alam Semesta (“GAS”), Indonesia, Videocon had provided security to IDBI inter-alia in the form of pledge over 51.33% shares in the Indonesian Company having IUP(Exploration) permit for a coal concession area spread over 10,000 Ha in Katingan Regency, Central Kalimantan, Indonesia. S K Ahuja Associates, an established valuer in India and is on the panel of approved valuers of IDBI. M/s Videocon (Mauritius) Infrastructure Ventures Limited. Videocon had approached S. K. Ahuja for carrying out an assessment of the Inherent Asset Value of coal resource available at the coal concession of GAS in Indonesia based on its independent assessment, site visit and review of certain survey reports. As Director, Project & Environment Consultants as well as researcher, the author was assigned the work to examine possibility viable mining and import to India.

Tourism satisfies diverse human motivations ranging from basic physiological needs to transcendent aspirations. This study integrates Maslow’s hierarchy of needs into a hierarchical utility model to quantify and optimize the fulfilment of tourist motivations while promoting sustainable tourism practices. The model decomposes utility (U) into six levels—physiological, safety, social, esteem, self-actualization, and transcendence—each represented by a weighted utility function. Transcendence, as the highest motivational level, emphasizes spiritual enrichment, heritage preservation, and moments of awe. The model incorporates constraints such as budget, time, and resource availability, enabling tailored solutions for tourism operators, policymakers, and tourists.
This approach enhances understanding of tourist behaviour, supports the design of experiences aligned with intrinsic and extrinsic motivations, and promotes sustainable practices that preserve cultural and environmental resources. By addressing transcendent needs, the model connects tourism with higher ethical values, legacy building, and spiritual fulfilment. This methodology serves as a strategic tool for creating impactful tourism experiences while fostering cultural heritage and environmental stewardship.

Entrepreneurship is widely recognized as a major driver of economic growth through job creation, innovation, and poverty reduction; however, its effectiveness in Akwa Ibom State is constrained by limited financial access and inadequate entrepreneurial skills among small and medium-scale enterprise (SME) operators. This study examined Entrepreneurship Development and Economic Growth in Akwa Ibom State, Nigeria, with specific focus on access to finance and lack of adequate training and skill development. The study adopted a cross-sectional survey research design, and data were collected from a sample of 384 respondents determined using Cochran’s formula for an infinite population. A structured questionnaire measured on a five-point Likert scale was used as the primary instrument for data collection. Data were analyzed using descriptive statistics and simple linear regression analysis via SPSS (Version 27) to test the hypotheses. Findings showed a strong positive and significant influence of access to finance on economic growth with (R = 0.833, R² = 0.694, p < 0.05), Similarly, the study found that inadequate training and skill development significantly affect economic growth. The regression result also showed a strong positive effect (R = 0.839, R² = 0.703, p < 0.05). The study concludes that both access to finance and adequate training and skill development are significant determinants of economic growth in Akwa Ibom State. It recommends that microfinance institutions and government agencies should improve access to credit, reduce interest rates, and strengthen entrepreneurship training and skill development programmes to enhance SME performance and promote sustainable economic growth.

The interplay of faith, reason, and pluralism has long been a subject of philosophical inquiry, shaping debates on knowledge, ethics, and social harmony. This paper critically examines the tensions and complementarities between faith and reason within the context of pluralistic societies. Faith, often rooted in religious traditions, provides a framework for moral and existential meaning, while reason, grounded in logic and empirical analysis, serves as a tool for objective inquiry. The historical discourse between faith and reason, from Augustine and Aquinas to Kant and Habermas, illustrates their evolving relationship in shaping epistemology and ethics. Pluralism adds complexity to this interplay, as diverse belief systems coexist within modern societies. While pluralism fosters tolerance and dialogue, it also raises challenges regarding conflicting truth claims and moral frameworks. The paper explores how reason can serve as a mediator in pluralistic contexts, enabling constructive discourse while respecting faith-based perspectives. It also critiques the risks of both extreme rationalism, which may dismiss religious worldviews, and dogmatic faith, which can resist critical inquiry.
Through a philosophical analysis, this study argues for a balanced approach where faith and reason function as complementary rather than opposing forces. It examines contemporary debates on secularism, religious pluralism, and the role of reason in mediating ethical and political conflicts. Ultimately, the paper contends that fostering a dialogue between faith and reason within pluralistic frameworks is essential for social cohesion, intellectual progress, and moral understanding.

Oral controlled release (CR) drug delivery systems have fundamentally transformed the clinical landscape of pharmacotherapy by maintaining precise therapeutic drug levels within the systemic circulation over extended durations. This spatial and temporal control significantly reduces dosing frequencies, enhances patient adherence, and diminishes peak-related systemic toxicities. This comprehensive review highlights the core principles governing CR architecture, mathematical release kinetics, and physical-chemical classification indices. Crucial mechanistic pathways, including diffusion-limited matrix architectures, dissolution-controlled reservoirs, osmotic pump systems (OROS), and ion-exchange substrates, are critically evaluated. Furthermore, the review outlines rigorous evaluation parameters spanning pre-compression micro-meritics, post-compression structural assessments, modern multi-stage in-vitro dissolution simulations, and pharmacokinetic multi-compartmental in-vivo methodologies. Finally, current methodologies establishing In-Vitro In-Vivo Correlation (IVIVC), recent ICH stability benchmarks, and emerging manufacturing platforms such as chronotherapeutic pulsatile delivery and personalized 3D-printing technologies are discussed to provide a holistic framework for academic and practical formulation design.

Higher education institutions worldwide are increasingly shifting from teacher-centered approaches to learner-centered pedagogies that emphasize active participation, critical thinking, and practical application of knowledge. Experiential Learning Theory (ELT), proposed by David A. Kolb, has emerged as one of the most influential frameworks for understanding how individuals learn through experience. The theory conceptualizes learning as a continuous process involving Concrete Experience, Reflective Observation, Abstract Conceptualization, and Active Experimentation. This theoretical review examines the foundational principles of Kolb’s Experiential Learning Theory and explores its relevance within contemporary higher education contexts. Drawing upon existing literature, the paper discusses the application of experiential learning across disciplines, its contribution to student engagement, skill development, and teaching effectiveness, and its alignment with modern educational paradigms. The review further highlights the strengths, criticisms, and future implications of ELT in fostering meaningful learning experiences. The study concludes that experiential learning remains highly relevant in higher education and provides valuable insights for educators seeking to design learner-centered instructional practices.

The rapid expansion of the digital marketplace has heavily intensified the use of psychological marketing strategies, including scarcity messaging, emotional branding, pricing psychology, and social proof. This research systematically evaluates the actual effectiveness of these traditional techniques on the purchase intention of modern digital consumers. Utilizing a descriptive research design, primary data was collected through a structured online questionnaire from 109 active online shoppers, featuring a highly significant representation of Generation Z and young Millennials.

While initial descriptive analysis indicated a moderate perceived influence across all four psychological variables, inferential statistical testing using a One Sample t test revealed no statistically significant positive impact. Consequently, all alternative hypotheses were completely rejected. The empirical finding sun cover a critical shift in modern consumer behavior characterized heavily by ad blindness and deep marketing fatigue. Constant daily exposure to promotional tactics has equipped young digital consumers with a strong psychological resistance, making them highly rational, critical, and deeply skeptical of manufactured urgency and artificial price framing.

Thestudyfirmlyconcludesthattraditionalpsychologicaltrapsarerapidlylosingtheir efficacy in the modern retail landscape. To sustain long term growth and customer loyalty, modern marketers must transition away from superficial manipulation and instead prioritize radical transparency, authentic peer validation, and genuine corporate value.

Artificial Intelligence is in now a day is playing a very crucial role in all spheres of human life. It has become the most wanted and used technique that had ever entered in the life of the people. In the field of archaeology too AI is playing important part. It is used as an important tool for detection, preserving, and interpreting the past. It becomes very much vital especially because it can handle large and completed datasets that would take humans years to analyse. It makes the discoveries easy to analyse, review and writing report. Artificial intelligence can be used in transforming and enabling the rapid discoveries, precise the preservation. AI is able to give a deeper insight of the cultural heritages through interpretation. Artificial intelligence is contributing a lot in transforming archaeology by enabling it in rapid discoveries précising in preservation, and making deeper interpretations of sites and cultural heritages. Through deep learning and machine learning on collected satellite data, it identifies archaeological sites with over with more accurate information. It helps in identifying archaeological sites, facilitates 3 D reconstructions, design and automates artifacts, classify them with better understanding. With the use of artificial intelligence ancient text can be analyzed and used as source data for fast tracking research and further it can support in conservation activities.
This study examines the role of Artificial Intelligence in archaeology and cultural heritage management studies. Further, it discusses the evolution and emergence of AI and gradual development of AI in archaeology, major technologies that are used and submissions, benefits, challenges, ethical reflections, and future prospects. The study further highlights how AI can complement traditional archaeological practices and contribute to the sustainable preservation of humanity’s cultural heritage.

Crisaborole is a potent anti-inflammatory drug that acts by inhibiting phosphodiesterase-4 (PDE-4) enzyme and is widely used in the treatment of inflammatory skin disorders such as psoriasis and other dermatological conditions. However, its therapeutic effectiveness is limited due to its poor aqueous solubility (0.021 mg/ml) and low dissolution rate. The present study was aimed to improve the solubility of Crisaborole by using the co-solvency technique and to formulate a topical ointment with enhanced drug release characteristics.Pre-formulation studies were carried out to determine the physicochemical properties of the drug. Crisaborole was identified as a white to off-white crystalline, odorless, and bitter powder with a melting point of 132°C. The λmax was found to be 250 nm, and the calibration curve showed good linearity with an R² value of 0.999. Solubility studies revealed higher solubility of Crisaborole in co-solvents such as propylene glycol and PEG 400 compared to water.Crisaborole ointment formulations (F1–F6) were prepared using the co-solvency method and evaluated for various parameters including appearance, pH, viscosity, spreadability, drug content, solubility enhancement, and in-vitro drug release. All formulations showed acceptable physical characteristics, with pH ranging from 5.4 to 6.5 and uniform drug content between 89% and 97%. The formulations containing higher concentrations of propylene glycol and PEG 400 (F5 and F6) demonstrated approximately five-fold improvement in drug solubility and achieved maximum drug release of 96.4% and 97.6%, respectively.The stability study of optimized formulations showed minimal changes in their properties over two months, indicating good stability. Therefore, the co-solvency technique was found to be a simple, economical, and effective approach for improving the solubility and release profile of poorly water-soluble Crisaborole in topical ointment formulations.

The Internet of Things (IoT) has opened new possibilities for developing intelligent systems that can respond to critical emergencies such as fire accidents. This paper presents the design and implementation of an IoT-Based Fire Fighting and Live Tracking Robot capable of detecting fire, extinguishing it, and sharing real-time location and status updates. The proposed system integrates flame sensors, temperature sensors, and a camera module for live monitoring. The robot is controlled remotely through IoT platforms, allowing users to observe and manage operations via the internet. A Wi-Fi-enabled microcontroller, such as Node MCU or Arduino with ESP8266, serves as the main control unit, ensuring seamless data transmission between sensors and the cloud. The system enhances safety in hazardous environments by reducing human intervention and providing immediate fire detection, suppression, and area surveillance. Experimental results demonstrate the robot’s efficiencyindetectingflames,navigatingtowardsthesource,andextinguishingsmall-scalefireseffectively.This approach offers a cost-effective and reliable solution for industrial, residential, and institutional fire safety applications.

The rapid advancement of smart transportation systems has led to the emergence of innovative infrastructure solutions such as wireless roads integrated with the Internet of Things (IoT). This research presents the design and conceptual framework of a wireless road system capable of enabling real-time communication, intelligent traffic management, and dynamic wireless power transfer for electric vehicles. The proposed system utilizes embedded sensors, IoT-enabled microcontrollers, and cloud-based platforms to collect and analyze data related to traffic density, road conditions, and environmental factors. Additionally, inductive wireless charging technology is incorporated within road infrastructure to support continuous charging of electric vehicles, reducing dependency on conventional charging stations. The integration of IoT enhances decision-making through data-driven insights, improving road safety, reducing congestion, and optimizing energy consumption. This study also discusses the system architecture, implementation methodology, advantages, challenges, and potential future developments. The proposed wireless road concept contributes significantly toward the development of sustainable, efficient, and intelligent transportation systems in smart cities.

William Shakespeare’s Julius Caesar presents a profound conflict between fate and free will through political ambition, moral uncertainty, and tragic consequences. This research paper examines the play from the perspective of Biophilia theory and ecocriticism to explore how nature influences human psychology and decision-making. The study analyzes natural signs, omens, storms, animal imagery, and supernatural warnings as symbolic representations of the interconnected relationship between humans and the natural world. Using qualitative textual analysis, the paper investigates the actions of Caesar, Brutus, and Cassius to determine whether their destinies are controlled by fate or shaped by personal choices. The research further highlights Shakespeare’s ecological consciousness by presenting nature as a moral and psychological force that reflects social imbalance and political disorder. The study concludes that Julius Caesar portrays fate and free will as interconnected elements where human actions ultimately activate tragic destiny through ignorance of natural and ethical warnings.

The topic of this research work is: social entrepreneurship and organizational sustainability of NGOs in Uyo, Akwa Ibom State, Nigeria'. The general aim of the study was to explore the relationship between social entrepreneurship and organizational sustainability of NGO's in Uyo, Akwa Ibom State. Three sub-objectives and hypotheses were formulated for the study to provide guidance. In this research, the dimensions of social entrepreneurship adopted are social value creation, capacity building and innovation and organizational sustainability is not considered. The study used a theoretical framework of dynamic capabilities theory. The survey research design was used in this study. There were 142 management staffs who made up the population for the study while 105 respondents who formed the sample size were obtained through the application of Taro Yamene's formula. The study adopted simple random sampling in order to sample all the staff members of the selected NGOs in Uyo such that each staff member in the selected NGOs has equal and independent probability of being selected in the sample. Moreover, primary data was collected by using structured questionnaire, which used the 5-pointlikert scale rating. One hundred and five (105) copies of questionnaires were issued to the respondents but only one hundred (100) were retrieved and made the bases for analysis. The results of the study revealed that there is a significant relationship between the social value creation and organizational sustainability of NGOs in Uyo, Akwa Ibom State, significant relationship exists between capacity building and organizational sustainability of NGOs in Uyo, Akwa Ibom State and significant relationship exist between innovation and organizational sustainability of NGOs in Uyo, Akwa Ibom State. The paper found that there is a positive correlation between social entrepreneurship and the sustainability of the NGOs in Uyo, Akwa Ibom State.

For modern agriculture to preserve fruit quality and minimize losses, effective postharvest management is necessary. Conventional manual inspection technique sarelaborious,erratic, and subjective. With an emphasis on pomegranates, this study offer sahybridmethod for automated fruit disease diagnosis andgradingusingpicturedatathatcombinesdeeplearning and machine learning. Using deeper layers, residual connections, and batch normalization, an improved Convolutional Neural Network (CNN) reduces overfitting and increases accuracy by extractingkeycharacteristicsfromhigh-resolutionimages.Innext step these features are enhanced by SSDAE.SSDAE removes useless information and focuses on the important details.This makes system more reliable for real world farming.

Cimetidine is a histamine H₂-receptor antagonist widely used in the treatment of peptic ulcer disease, gastroesophageal reflux disease (GERD), heartburn, and other acid-related gastrointestinal disorders. This article reviews the causes, pathophysiology, symptoms, and management of peptic ulcers, with a particular focus on the pharmaceutical formulation of cimetidine tablets. The study discusses the drug’s mechanism of action, pharmacokinetic properties, therapeutic uses, adverse effects, contraindications, and drug interactions. Preformulation studies, including organoleptic, physicochemical, and micromeritic evaluations, were conducted to assess the suitability of cimetidine for tablet formulation. The manufacturing processes of wet granulation and direct compression, along with coating methods, are described. Quality control parameters such as weight variation, hardness, friability, disintegration, dissolution, and content uniformity tests were reviewed to ensure product quality, safety, and efficacy. Packaging, labeling, and storage requirements were also examined to maintain tablet stability and patient compliance. Overall, the study highlights the importance of proper formulation development, evaluation, and packaging in producing safe, stable, and effective cimetidine tablets for the management of acid-related disorders.

In 1939, Edwin Hardin Sutherland, the most well-known criminologist of the 20th century, as well as a sociologist—described "white-collar crime" as "crimes committed by people who enjoy the high social status, great repute, and respectability in their profession." A corporate executive with a prominent position inside the company is guilty of this crime, which he does as part of his job. Trade and technological advancements have made white-collar crime a worldwide phenomenon. Like any other nation, India is plagued with white-collar crime. The sharp increase in white-collar crime over the past few decades can be attributed to the developing world's fast expanding economy and industrial sector.
White-collar crime is quite expensive for firms. These companies raise the price of their goods to offset the loss, which lowers the number of customers who purchase them. This is predicated on the law of demand, which holds that as a product's price rises, demand decreases, and when it lowers, demand grows, all other things being equal. The company's deficit is being passed down to employee salaries. Every year, the corporation fires a number of people. The businesses find it more difficult to pay back their loans. As a result, getting credit is getting harder for more people.
The term "white-collar crime" describes the non-violent, profit-driven crimes committed by government and corporate personnel. Economic offenses, on the other hand, are crimes involving money. These offenses are carried out while conducting business or conducting an economic activity. Although the term "economic offenses" has been defined in several regions of the world, including the US, India still lacks a strict definition for the term. It can be difficult to identify the different kinds of crimes because of this. The research topic is founded on a critical analysis of Indian legal systems and white-collar crime.
The primary focus of this study is to familiarize the reader with the legal system pertaining to Economic Offenses, White-Collar Crimes, and the factors that contribute to these crimes. Finding and evaluating a critical study on white-collar crime in India is the goal of this research effort.

Ferrite nanoparticles have attracted significant attention due to their tunable magnetic properties and wide-ranging applications in electronics, biomedicine, and environmental remediation. In recent years, increasing emphasis has been placed on understanding how synthesis routes influence structural and magnetic characteristics. This review provides a critical and comparative analysis of the preparation methods of soft ferrite nanoparticles, with particular focus on wet chemical techniques such as co-precipitation, sol–gel, and hydrothermal synthesis and conventional solid-state routes. Drawing on recent studies published in recent years, the review systematically evaluates how variations in synthesis parameters affect particle size, morphology, crystallinity, and magnetic behavior, including saturation magnetization and coercivity. Furthermore, it examines the effectiveness of commonly employed characterization techniques, including X-ray diffraction (XRD), electron microscopy (SEM/TEM), and vibrating sample magnetometry (VSM), in establishing structure–property relationships. A key contribution of this work is the direct comparison between wet and solid-state methods in terms of controllability, scalability, cost-effectiveness, and resulting magnetic performance. The analysis reveals that wet chemical approaches generally enable finer control over nanoscale features and superparamagnetic behavior, whereas solid-state methods often yield improved crystallinity and higher coercivity. However, inconsistencies in experimental conditions and reporting standards across studies limit the generalizability of these conclusions. The review identifies critical research gaps, including the lack of standardized synthesis protocols, insufficient integration of multi-technique characterization, and limited exploration of scalable hybrid methods. Future research directions are proposed to address these challenges and to enhance the practical applicability of ferrite nanoparticles across emerging technological domains.

The persistent justice gap confronting tribal and Indigenous communities worldwide reflects a complex interplay of historical dispossession, structural marginalization, and the enduring legacies of colonial governance. Despite the existence of formal legal frameworks designed to protect Indigenous rights, access to justice for tribal populations remains severely constrained due to jurisdictional complexities, socio-economic disparities, and the systematic exclusion of Indigenous legal traditions from mainstream legal institutions. This article argues that a transformative reorientation of legal educationgrounded in decolonial perspectives, cultural competence, and community-centered clinical pedagogyis essential for addressing these challenges and supporting the self-determined development of Indigenous peoples.
By critically examining the limitations of conventional legal training, which has historically privileged colonial legal epistemologies while marginalizing Indigenous knowledge systems, the study highlights the urgent need for curricular reform that recognizes Indigenous legal orders as legitimate and evolving systems of law. The paper further explores emerging educational frameworks that emphasize Indigenous Cultural Competency, cultural safety, and experiential learning through Clinical Legal Education (CLE). These approaches foster culturally responsive legal practice, strengthen engagement with tribal communities, and equip future legal professionals with the skills required to navigate pluralistic legal systems.
Drawing upon international experiences and comparative examples, the article proposes an integrative model of legal education that aligns academic institutions with the principles of Indigenous sovereignty, community participation, and ethical knowledge exchange. Such a model positions legal education not merely as a professional training mechanism but as a transformative platform capable of bridging the justice gap, promoting equitable governance, and empowering tribal communities to pursue sustainable and self-determined futures.

This review article focuses on the anxiolytic medication fluoxetine capsule formulation and evaluation parameters. Anxiety is a normal emotional response to stress but it requires medicationandpropertreatmentwhentheanxietybecomesexcessivebyinterferingwithdaily life. This article focuses on anxiety and anxiolytics and briefly discuss the formulation and evaluation parameters of Fluoxetine capsule. Fluoxetineis an anxiolytic under selective reuptake serotonin inhibitors which work by increasing serotonin level in the brain. Manufacturing of hard gelatin capsule and Capsule filling methods are described. Evaluation parameterssuchasphysicalevaluationtest,weightvariationtest,contentuniformity,dissolutiontest, disintegrationtestarethoroughlyexplained.

Background: Chronic psychological stress is an independent risk factor for cardiovascular disease (CVD), contributing to approximately 30% of myocardial infarctions. In Ayurveda, excessive stress (Atichinta) is identified as a primary etiological factor for vitiation (Dushti) of Rasavaha Srotas the channels carrying the body's primary nutritive fluid (Rasa Dhatu). While Rasavaha Srotas is conceptually synonymous with the cardiovascular system, the precise mechanistic pathways linking Atichinta to Srotodushti remain undefined. Objective: To propose a conceptual framework for the Manas-Hridaya axis, mapping the neuroendocrine, inflammatory, and vascular pathways of chronic stress onto the classical Ayurvedic stages of Atichinta, Rasavaha Srotodushti, and Hridaya Roga. Methods: A narrative review was conducted using Ayurvedic primary sources (Charaka Samhita, Sushruta Samhita) and PubMed (2000–2026) for chronic stress neuro-cardiology, endothelial dysfunction, Takotsubo cardiomyopathy, mental stress-induced myocardial ischemia, and HPA axis. Discussion: The Manas (mind) and Hridaya (heart) are anatomically connected in classical texts, with the heart as the common root for both ManovahaSrotas and Rasavaha Srotas. Atichinta causes Sanga (obstruction) in RasavahaSrotas. Modern research validates this: chronic stress hyperactivates the sympathetic nervous system and HPA axis, triggering vascular inflammation, endothelial dysfunction, and myocardial ischemia. Agni Dushti (deranged metabolic fire) correlates with stress-induced mitochondrial dysfunction and a pro-inflammatory state. Conclusion: Atichinta is a direct pathophysiological driver of Rasavaha Srotodushti. The Manas-Hridaya axis provides a model wherein clinical signs of Sanga can be correlated with microvascular dysfunction and inflammation, enabling integrative therapeutic strategies.

Sustainability has become a defining concern for institutions worldwide, including libraries that serve as vital centers for knowledge dissemination and lifelong learning. The concept of green libraries extends beyond environmentally friendly buildings and encompasses sustainable management practices, digital transformation, energy conservation, resource optimization, and environmental education. Modern libraries are increasingly adopting innovative technologies such as cloud computing, artificial intelligence, the Internet of Things (IoT), and renewable energy systems to reduce their ecological footprint while improving service efficiency. This paper examines the evolution of green libraries, explores recent trends and technological developments, discusses implementation challenges, and highlights their contribution to sustainable development. The study emphasizes that green libraries can play a significant role in fostering environmental responsibility while ensuring equitable access to information resources.

This study is focussing on the idea of how seasonal changes influence personal financial behaviour, with a specific focus on comparing winter and summer expenses. Research is based on the idea that while income for most individuals remains relatively stable, expenses vary significantly across different seasons due to changes in lifestyle, weather conditions, and socio-cultural factors. The study adopts a descriptive research design and uses primary data collected through a structured questionnaire. The analysis highlights that these seasonal changes influence on the budget and savings of the individuals. Further theses seasonal variations play a crucial role in shaping spending patterns. Winter is associated with increased expenditure on clothing, food, and festivalrelated activities, while summer leads to higher spending on travel, entertainment, food, and utility expenses. The findings also reveal that personal and social factors such as travel plans, lifestyle changes, and festivals have a stronger influence on spending behaviour than environmental factors alone. Overall, the research emphasizes the importance of seasonal budgeting and financial planning to maintain stability and improve long-term financial well-being.

Analgesic drugs are widely used for the management of pain, inflammation, and fever. Among them, ibuprofen is a commonly used non-steroidal anti-inflammatory drug (NSAID) that exhibits analgesic, antipyretic, and anti-inflammatory properties by inhibiting cyclooxygenase (COX-1 and COX-2) enzymes and reducing prostaglandin synthesis. The present study focuses on the formulation and evaluation of ibuprofen hard gelatin capsules along with the preformulation studies required for successful dosage form development. Preformulation studies were carried out to evaluate the physicochemical properties of ibuprofen such as solubility, melting point, pKa, partition coefficient, polymorphism, hygroscopicity, and flow properties including angle of repose, bulk density, tapped density, Hausner's ratio, and Carr's index. Compatibility and stability studies were also performed to ensure the suitability of the drug for capsule formulation. The formulation process involved the selection of suitable excipients including diluents, binders, lubricants, glidants, and disintegrants for efficient capsule filling and drug release. Different capsule filling methods such as manual, semi-automatic, and fully automatic techniques were studied. Evaluation tests including weight variation, content uniformity, dissolution test, disintegration test, moisture content, microbial testing, and stability studies were carried out to assess the quality, safety, and efficacy of the formulated capsules. The study concludes that proper preformulation, formulation, manufacturing, and evaluation processes are essential for developing stable and effective ibuprofen capsules with good therapeutic performance and patient compliance.

One of the most challenging aspects of emergency medicine is the evaluation and diagnosis of patients presenting with acute abdominal pain. Since there is such a broad list of potential etiologies (e.g., benign and self-limiting conditions), patients who suffer from any of these problems can also be present with similar clinical symptoms. For nearly 20 years, CT has been established as the "gold standard" for imaging in emergency medicine related to acute abdominal pain. Of all the diagnostic imaging modalities utilized in the emergency department (ED); CT has become the most used form of imaging. In addition, CT has been shown to provide rapid results while having high sensitivity and the ability to image multiple organ systems with one imaging study. This paper will cover much of what you need to know about CT in acute abdominal pain; including CT imaging and techniques, rapid acquisition protocols and frameworks, distinguishing features of a CT exam; and the advantages and disadvantages of CT in acute abdominal pain; it will also address some potential advances in technology regarding CT imaging in the future.

This study examines the role of social media political campaigns in shaping youth voter behaviour during elections in southern Nigeria. The rapid growth of digital communication technologies has transformed political engagement, making social media platforms such as Facebook, X (formerly Twitter), Instagram, YouTube, and WhatsApp central tools for political communication and mobilization. Drawing on Agenda-Setting Theory and Social Identity Theory, the study explores how exposure to political content on social media influences political awareness, participation, and voting decisions among young people. A conceptual and empirical review of relevant literature reveals that social media enhances political knowledge, facilitates grassroots mobilization, and encourages active civic engagement among youths. It also demonstrates that repeated exposure to political messages, peer influence, and group affiliations significantly shape voter preferences and behaviour. However, the study identifies critical challenges associated with social media use in political campaigns, including the spread of misinformation, political polarization, digital inequality, and the manipulation of public opinion through targeted advertising and algorithm-driven content. The findings further highlight that while social media has strengthened democratic participation by giving youths a voice in political discourse, it also poses risks to informed decision-making and electoral integrity. The study concludes that maximizing the benefits of social media in political campaigns requires improved digital literacy, ethical political communication practices, and effective regulatory frameworks. These measures are essential to ensure that social media contributes positively to democratic development and youth political participation in southern Nigeria.

The electoral process in rural Telangana reflects a dynamic interaction between formal democratic institutions and deeply rooted socio-political structures. Elections are conducted under the supervision of the Election Commission of India, ensuring procedural transparency, universal franchise, and administrative efficiency through mechanisms such as voter registration, campaigning regulations, and Electronic Voting Machines (EVMs). Despite this institutional robustness, voter behaviour in rural areas is significantly shaped by social and economic realities. Caste remains a central determinant, influencing political loyalties, candidate selection, and voting patterns through entrenched community networks. Welfare policies introduced by the state, particularly in agriculture and social security, have fostered beneficiary-oriented voting, where electoral choices are linked to access to government schemes. Leadership—both at the local and state levels—also plays a crucial role, with local elites and intermediaries mobilizing voters through patronage and social influence. Moreover, factors such as poverty, literacy, and occupational dependency affect political awareness and decision-making. Consequently, while the electoral framework promotes inclusiveness and participation, actual voting behaviour is often driven by identity-based mobilization and material considerations rather than purely issue-based evaluation.

Juvenile observation homes serve as critical interim residential facilities for children in conflict with the law under the Juvenile Justice (Care and Protection of Children) Act, 2015 in India. These institutions are designed to provide temporary care, assessment, and rehabilitation for juveniles awaiting trial or placement decisions. This paper examines the administrative framework, operational challenges, and reform needs of juvenile observation homes across India, with particular focus on systemic deficiencies affecting their effectiveness.
The study reveals that despite statutory provisions mandating proper administration, observation homes face severe challenges including overcrowding, inadequate infrastructure, insufficient trained personnel, and poor mental health services. Administrative gaps persist in implementation of the Juvenile Justice Act, 2015, with many states failing to establish compliant facilities. The paper analyzes how bureaucratic inefficiencies, lack of funding, and absence of standardized protocols undermine the rehabilitative mandate of these homes.
Drawing on scholarly literature by authors including G.S. Bajpai, Nitya Robber, and Vaishali Rathore, this research examines the transition from welfare-based to rights-based juvenile justice approaches and its impact on observation home administration. The study highlights critical issues such as prolonged detention periods, inadequate legal assistance, poor documentation practices, and insufficient community engagement.
The paper argues for comprehensive administrative reforms including standardized operating protocols, enhanced staffing with trained professionals, improved infrastructure, robust monitoring mechanisms, and stronger integration with community-based rehabilitation programs. It emphasizes the necessity of shifting from custodial approaches to rehabilitative frameworks that prioritize children's developmental needs, mental health, and successful reintegration into society. The findings contribute to ongoing debates about juvenile justice reform in India and provide policy recommendations for improving observation home administration.

Ecocriticism has emerged as one of the most significant interdisciplinary approaches in contemporary literary studies, examining the intricate relationship between literature and the natural environment. Unlike traditional literary theories that primarily emphasize linguistic, cultural, or social dimensions, ecocriticism foregrounds the role of nature and ecology in shaping human existence and cultural expression. This article explores the evolution, objectives, and theoretical foundations of ecocriticism while highlighting its contribution to environmental awareness and literary interpretation. By analyzing the interconnectedness of culture and nature, the study demonstrates how literary texts reflect ecological concerns and advocate harmonious coexistence between humans and the environment. The article further argues that ecological consciousness is essential for addressing contemporary environmental crises and fostering sustainable development.

This paper examines the emerging leadership patterns among backward communities in Telangana following the state's formation in 2014. The study analyzes how Other Backward Classes (OBCs) and other backward communities have begun asserting political agency, forming new leadership structures, and challenging traditional power hierarchies. Through examination of caste demographics, political mobilization patterns, electoral dynamics, and socio-economic indicators, this research demonstrates that backward communities in Telangana are experiencing unprecedented political awakening. The 2023 state elections and subsequent governance changes reveal significant shifts in leadership representation. The Telangana caste survey data reveals that 135 out of 242 castes are more backward than the state average, with backward classes comprising 55-57% of the state's population. This paper explores the historical context, contemporary developments, challenges, and future trajectories of backward community leadership in Telangana, contributing to broader understandings of social justice, democratic participation, and inclusive governance in post-formation Telangana.

Recent developments in research are more focused on oral, innovative, site-specific controlled drug delivery technologies with the objective of minimizing drug wastage and preventing off-target adverse effects. These technologies are used to maintain control of active pharmacological agents in predetermined locations of action. Even pre-modulated release kinetics of controlled-release formulations do not guarantee sufficient absorption of drugs in human subjects due to physiological parameters like gastrointestinal transit and gastric residence time (GRT) of dosage administration. The absorptive limitation mentioned above can be overcome through the gastro-retentive technology; this is the (GRDDS), which prolongs time of presence of pharmaceuticals in the gastrointestinal tract of the host by making the formulation to be buoyant in gastric fluid due to its low bulk density as compared to gastric medium. To extend period of gastric residence, the current study designed & evaluated floating pills comprising of trandolapril &acebutol hydrochloride, respectively, with assistance of both natural & synthetic polymeric excipients.

Herbal medicines are widely used across the world for the prevention and treatment of various diseases. However, the safety, efficacy, and consistency of herbal products depend largely on the quality assurance practices adopted during their production. This study aims to assess the quality assurance measures implemented in the manufacturing of herbal medicines. The investigation focuses on key stages of production, including raw material selection, authentication of medicinal plants, processing, storage, formulation, packaging, and quality control testing.A systematic evaluation was conducted through the review of manufacturing procedures, standard operating practices, and quality control records used in herbal medicine production facilities. Special attention was given to the application of Good Manufacturing Practices (GMP), contamination control, documentation systems, and analytical testing methods employed to ensure product quality and safety.The findings indicate that effective quality assurance practices significantly contribute to maintaining the identity, purity, potency, and stability of herbal medicines. Proper plant authentication, controlled processing conditions, and regular quality testing were identified as critical factors in preventing adulteration, microbial contamination, and batch-to-batch variability. Nevertheless, challenges such as inadequate standardization of raw materials, limited regulatory compliance, and insufficient quality monitoring remain concerns in some production settings.The study concludes that strengthening quality assurance systems is essential for improving consumer confidence and ensuring the therapeutic reliability of herbal medicinal products. Adoption of standardized manufacturing procedures, robust quality control methods, and continuous regulatory oversight can enhance the overall quality and safety of herbal medicines.

The digital transformation of the banking industry has fundamentally altered the manner in which financial institutions create value, interact with customers, manage risks, and maintain competitive advantage. In India, the rapid adoption of technology-driven banking services has been accelerated by government initiatives, regulatory modernization, fintech innovation, increasing smartphone penetration, and changing customer expectations. While technological infrastructure remains a critical enabler of digital banking transformation, managerial dynamics play a decisive role in determining the success or failure of technology adoption initiatives. This paper develops an integrated conceptual framework explaining how managerial capabilities influence the adoption of technology-driven banking and deposit services in India. Drawing upon the Technology Acceptance Model (TAM), Diffusion of Innovation Theory (DOI), and the Resource-Based View (RBV), the study identifies leadership capability, organizational culture, employee digital literacy, cyber security governance, customer trust management, fintech collaboration, and regulatory adaptability as key managerial determinants of successful digital transformation. The article synthesizes existing literature and proposes a multidimensional framework linking managerial dynamics with operational efficiency, customer satisfaction, financial inclusion, innovation capability, and sustainable competitiveadvantage.Thepaper contributes tothe growingbodyofliteratureondigital bankingbyemphasizingmanagerialcapabilityasastrategicorganizationalresource.The findings provide theoretical insights and practical recommendations for banking executives, policymakers, and technology stakeholders seeking to strengthen digital transformation outcomes in emerging economies.

This study empirically examined the effect of maritime security management on vessel turnaround time of ports in Nigeria. The data used for the study were time series data sourced from the National Bureau of Statistics (NBS) annual abstract and Central Bank of Nigeria (CBN) statistical Bulletin, Nigerian Ports Authority (NPA), Nigerian Shippers Council (NSC), Transparency International Corruption Perception index (ICPI) and Global Terrorism Index (GTI) from 1995 to 2024. The regressand utilized in this study was vessel turnaround time which served as the dependent variable. Maritime security management (the independent variable) was measured with piracy, terrorism and corruption and they served as the regressors. The analytical techniques employed were Augmented Dickey Fuller (ADF) unit root test and bounds cointegration test. The unit root test revealed that corruption was stationary at level that is integrated of order zero I(0) while the other variables were stationary at first difference that is integrated of order one I(1) which led to the application of bounds cointegration test given the mixed order of integration and the cointegration test results confirmed the presence of a long run relationship amongst the examined variables. The model was estimated using Autoregressive Distributed Lag (ARDL) model and the short run results revealed that piracy and corruption have positive and statistically significant effect on Nigeria’s port vessel turnaround time in the short run while terrorism showed an insignificant negative effect on vessel turnaround time in Nigeria both in the short run and long run. Thus, the study recommends among other things, that government should implement and enforce stringent security measures at ports, including access control, cargo screening, and enhanced surveillance systems. Also, investment in technologies for enhanced maritime domain awareness, including sensor nets, electro-optical detectors, and unmanned underwater vehicles, to detect and track potential threats is essential in order to effectively combat maritime security challenges and improve vessel turnaround time of ports in Nigeria.

Artavakshaya is one of the common menstrual disorders encountered in women of reproductive age and is characterized by delayed appearance of menstruation, scanty menstrual flow, and pain during menstruation. In modern gynecology, the condition can be correlated with oligomenorrhea and hypomenorrhea. The prevalence of menstrual irregularities has increased considerably due to changing lifestyles, nutritional deficiencies, psychological stress, obesity, endocrine dysfunctions, and polycystic ovarian syndrome (PCOS). Ayurveda describes Artavakshaya as a pathological condition resulting from impairment in the quantity and quality of Artava due to vitiation of Doshas, particularly Vata and Kapha. Rajapravartini Vati is a classical herbo-mineral formulation extensively used in Ayurvedic gynecological practice for delayed menstruation, amenorrhea, and associated reproductive disorders. The formulation contains Shuddha Kasis, Shuddha Hingula, Tankana, and Kumari Swarasa Bhavita, which possess Artavajanana, Deepana, Pachana, Vatanulomana, and Srotoshodhana properties. This conceptual review explores the etiopathogenesis of Artavakshaya and critically analyzes the probable mode of action of Rajapravartini Vati through classical Ayurvedic principles and modern scientific understanding. The review suggests that Rajapravartini Vati acts at multiple levels by correcting Agnimandya, removing Srotorodha, normalizing Apana Vata, improving Rakta and Artava formation, and restoring normal menstrual cyclicity.

This review article focuses on the anxiolytic medication alprazolam tablet formulation and evaluation parameters. Anxiety is a normal emotional response to stress but it requires medication andpropertreatment whentheanxietybecomesexcessivebyinterfering withdaily life. This article focuses on anxiety and anxiolytics and briefly discuss the formulation and evaluation parameters ofalprazolam tablet.Alprazolam isananxiolytic underbenzodiazepine whichworkbymodulatingGABAinnervoussystem.Directcompression andwetgranulation methodofpreparationisdescribed.Evaluationparameterssuchashardness,thickness,content uniformity, friability,dissolutionrate arethoroughly explained.

Hydroxyzine is a first-generation antihistamine widely used for the treatment of anxiety, allergic conditions, pruritus, and nausea. The syrup was prepare dusing suitable excipients such as sweetening agents, preservatives, flavoring agents, and viscosity enhancers. Preformulation studies including organoleptic properties, solubility, partition coefficient, melting point, compatibility study, pH determination, and stability testing were carried out to ensure drug suitability for syrup formulation. The formulated syrup was further evaluated for organoleptic characteristics, physicochemical parameters, microbial quality, stability, and pourability. The study concludes that Hydroxyzine syrup can be successfully formulated as a stable and effective oral liquid preparation.

This research paper explores the role of music and chanting in yoga philosophy, focusing on mantras, NadaYoga, and sacred sounds in spiritual practices. It examines the historical and cultural origins of music and chanting in yoga, highlighting their significance in Vedic traditions and the concept of Nada Brahma. The paper explores how mantras are used as tools for spiritual transformation, emphasizing their linguistic, phonetic, and vibrational aspects. It delves into Nada Yoga and its techniques for harnessing the power of sound and music to induce meditative states and facilitate spiritual experiences. The research also explores the importance of sacred sounds in yoga philosophy, their manifestation in chants and devotional music, and their the rapeutic effects on the mind, body, and energy centers. It discusses contemporary applications of music and chanting in enhancing focus, mindfulness, and emotional healing during yoga practice. Ethical considerations regarding the responsible use of mantras and sacred sounds are addressed. Overall, the paper provides a comprehensive understanding of the profound relationship between music, chanting, and spiritual practices in yoga philosophy.

Ivacaftor, a cystic fibrosis transmembrane conductance regulator (CFTR) potentiator, has garnered significant attention due to its therapeutic efficacy in treating cystic fibrosis. Accurate quantification of Ivacaftor in pharmaceutical formulations is essential for quality control and regulatory compliance. This review provides a comprehensive overview of the various analytical methods developed for the estimation of Ivacaftor, with a particular focus on UV spectrophotometry, high-performance liquid chromatography (HPLC), and liquid chromatography–mass spectrometry (LC-MS). UV spectrophotometric methods are highlighted for their simplicity, cost-effectiveness, and suitability for routine analysis, although limited by lower sensitivity and specificity. HPLC methods, particularly reverse-phase HPLC (RP-HPLC), offer greater accuracy, reproducibility, and precision, making them ideal for stability-indicating and validation studies. LC-MS methods are recognized for their high sensitivity, selectivity, and capability in bioanalytical applications, especially for pharmacokinetic and metabolic studies. The review discusses method development strategies, validation parameters, and application areas of each technique, offering insights into their strengths and limitations. Collectively, these analytical methods play a pivotal role in the effective monitoring of Ivacaftor in both bulk and dosage forms, ensuring therapeutic efficacy and safety.

Artificial Intelligence (AI) has emerged as a transformative technological force across pharmaceutical sciences, significantly reshaping traditional formulation development and advanced drug delivery system design. Conventional pharmaceutical formulation has historically relied on empirical experimentation and repeated trial-and-error approaches, which are often time-consuming, expensive, and associated with high development failure rates. The integration of Artificial Intelligence-including Machine Learning (ML), Deep Learning (DL), Artificial Neural Networks (ANN), and predictive analytics-has introduced data-driven and computationally intelligent strategies that improve formulation design, optimize process parameters, and accelerate decision-making throughout the pharmaceutical development lifecycle.
AI-based pharmaceutical formulation enables prediction of physicochemical compatibility between active pharmaceutical ingredients and excipients, estimation of solubility and dissolution behavior, optimization of particle engineering, and improvement of dosage form stability. In advanced drug delivery systems, AI has demonstrated significant utility in designing nanoparticles, liposomes, polymeric carriers, microneedles, transdermal patches, and controlled-release systems by improving precision, targeting capability, and release kinetics. Furthermore, AI-supported predictive modeling has strengthened Quality by Design (QbD), real-time monitoring, digital manufacturing, and regulatory compliance within pharmaceutical industries.
Clinical applications of AI-driven drug delivery include oncology, diabetes management, vaccine delivery, biologics, personalized therapeutics, and chronic disease treatment, where computational models enhance therapeutic precision while improving patient adherence and minimizing adverse effects. Emerging technologies such as digital twins, wearable delivery platforms, and AI-assisted personalized medicine are expected to further expand pharmaceutical innovation.
This review critically discusses the principles of Artificial Intelligence in pharmaceutical formulation, highlights recent advances in AI-assisted drug delivery technologies, explores current clinical applications, and evaluates future opportunities and limitations in integrating intelligent systems into pharmaceutical care and drug development.

Allergic inflammatory disorders, including asthma, allergic rhinitis, atopic dermatitis, food allergies,andchronicurticaria,representagrowingglobalhealthburdenaffectingmillionsof
individualsworldwide.Theincreasingprevalenceoftheseconditionshasbeenlinkedtocomplex interactions among genetic susceptibility, environmental exposures, lifestyle changes, and
immunedysregulation.Traditionaltherapeuticapproaches,suchasantihistamines,
corticosteroids,andbronchodilators,remainthecornerstoneofallergymanagement;however, these treatments primarily focus on symptom control and often fail to address the underlying immunological mechanisms responsible for disease initiation and progression. Consequently,
thereisagrowingneedfortargetedtherapiescapableofprovidingsustaineddiseasecontroland long-term immunological benefits.
Recent advances in immunology and molecular medicine have revolutionized the treatment landscapeofallergicdiseasesthroughthedevelopmentofnovelimmunomodulatorystrategies.
Biologicagents,particularly monoclonalantibodiestargetingkeymediatorsoftype2
inflammation,includingimmunoglobulinE(IgE),interleukin(IL)-4,IL-5,IL-13, thymicstromal lymphopoietin (TSLP), and their associated signaling pathways, have demonstrated remarkable efficacy in reducing inflammation, preventing disease exacerbations, and improving clinical
outcomesinpatientswithmoderate-to-severeallergicdisorders.Inparallel,small-molecule
therapeutics,suchasJanuskinase(JAK)inhibitorsandotherintracellularsignalingmodulators, offerapromising alternativebyselectivelyinterferingwithinflammatorypathways involvedin allergic responses, while providing the convenience of oral administration.
Furthermore,innovativevaccine-basedapproachesareemergingaspotentialdisease-modifying interventions. These include allergen-specific immunotherapy, recombinant allergen vaccines,
peptide-basedvaccines,DNAandmRNAvaccines,andnanoparticle-assisteddeliverysystems designed to promote immune tolerance and reshape aberrant immune responses. Unlike
conventionalpharmacotherapy,thesestrategiesaimtoinducelong-lastingimmunological changes, thereby reducing allergen sensitivity and preventing disease recurrence.
Thisreviewexploresthelatestdevelopmentsinbiologics,smallmolecules,andnext-generation vaccine technologies for allergic inflammation, highlighting their mechanisms of action,
therapeuticapplications,clinicalefficacy,safetyconsiderations,andfutureprospects.The
integrationoftheseadvancedimmunomodulatoryapproachesintoclinicalpracticerepresentsa significant step toward precision medicine, offering personalized and potentially curative
treatmentoptionsforpatientssufferingfromallergicdiseases.Continuedresearchandlarge-scaleclinicalstudiesareessentialtofurtherrefinethesetherapies,improveaccessibility,and establish their long-term effectiveness in allergy management.

This paper digs into how changes in the Reserve Bank of India’s repo rate shape the fortunes of commercial banks between FY 2014–15 and FY 2023–24. Using a mix of descriptive analysis and long-term data, it looks at the way shifting monetary policy cycles affect big banking numbers—things like net interest margins, credit growth, bad loans, and overall profitability.
Something changed in October 2019. That’s when the RBI rolled out the External Benchmark-Based Lending Rate, which made banks pass repo rate changes to borrowers a lot faster and more completely, especially in retail and MSME loans. Banks still move at slightly different speeds—when repo rates change, they adjust the interest they pay and the interest they charge, but not at the same pace. That imbalance gives banks a window to boost profits, whether rates are going up or down.
When it comes to bad loans (NPAs), it’s not really the repo rate itself that drives the trend. What's more important is the quality of the credit cycle and the tools banks have to resolve stressed assets. The latest tightening cycle, from FY 2022–24, has been golden for profitability, especially for public sector banks—their ROA hit 0.90% and ROE soared to 15.8%, numbers they haven’t seen in more than ten years.
There’s a clear gap, though, in how public and private banks react to repo rate moves. PSBs and private banks don’t respond the same way, and that divergence sticks around. The paper wraps up with some policy ideas for bank managers, regulators, and the RBI itself, plus some directions for future econometric research.

English Language Teaching (ELT) has experienced a lot of changes during the last 20 years. The discipline is undoubtedly shifting from more prescriptive methods to much more flexible and contextsensitive approaches. This paper offers a systematic review of existing approaches in ELT, probing into the complex demands of a digital mediated and linguistically diverse world and the response of modern language education. The study aims to move beyond the limitations of the traditional method of the 20th century and critically analyze the theoretical development, pedagogical strengths and inherent practical limitations of Communicative Language Teaching (CLT), Task-Based Language Teaching (TBLT) and Content and Language Integrated Learning (CLIL). Moreover, recent paradigm changes such as the introduction of Technology-Enhanced Language Learning (TELL) and the important "multilingual turn" which is defined by translanguaging practices are examined. This literature review contends that the current state of global English teaching is not a quest for a single universal method that can be found. Effective language instruction implies rather a post-method epistemology, in which the teacher should become a reflective adaptive practitioner who is able to adapt his/her strategies to the specific cognitive, cultural and institutional needs. In conclusion, this paper traces the path of ELT from a transmission model of learning based on rote learning to an empowering and highly communicative model, where localization plays an important role.

Digital technology has become a part of life, so much so that many adolescents and young people use digital space as a means of communication, learning, entertainment and social engagement. Although these technologies have many advantages, they have also led to the recent trend of digital addiction, which has raised concerns about their effects on the health of youth. The objective of this review is to explore the association between digital addiction and different aspects of youth well-being such as mental health, social behaviors, and lifestyle outcomes. Based on previous studies in psychology, sociology, education and public health, the review examines the main types of digital addiction such as internet addiction, smartphone dependence, social media addiction, online gaming addiction and streaming content addiction. The study also examines the theoretical models that account for addictive use of digital technologies, and explores certain individual, family, social, and technological risk factors that may explain excessive technology use. The result showed that there are negative mental health consequences linked to digital addiction including anxiety, depression, stress, emotional instability and low self-esteem. Also, overuse of digital usage has been associated with social isolation, loneliness, decreased social skills, sleep problems, physical inactivity, sedentary lifestyle and reduced school performance. Additionally, the review underscores the intricate relationship between psychological susceptibility, environmental factors and technology design characteristics and their impact on digital behavior.

English language proficiency has become an essential requirement for academic excellence, employability, workplace communication, and global interaction. However, many learners from rural and semi-urban backgrounds face challenges in developing practical communication abilities due to limited exposure, mother tongue influence, fear of speaking, lack of confidence, and traditional theoretical teaching methods. This paper proposes an “English Language Laboratory-Practical Approach” that integrates activity-based learning, real-time communication tasks, peer interaction, situational practice, and continuous performance assessment to improve professional communication skills with reasonable accuracy.
The study emphasizes experiential learning through structured laboratory activities such as role plays, group discussions, JAM sessions, presentations, interview simulations, pronunciation drills, workplace communication tasks, listening practices, and collaborative speaking exercises. The approach aims to bridge the gap between theoretical knowledge and practical language use in professional environments. The paper further discusses implementation strategies, learner outcomes, teacher roles, assessment methods, and classroom adaptability for diploma, engineering, and professional education institutions. The proposed model promotes confidence, fluency, communicative competence, and employability-oriented language skills.

With the rapid increase in lifestyle-related health issues such as obesity and malnutrition, regular monitoring of Body Mass Index (BMI) has become essential for early health assessment. Conventional BMI measurement methods are mostly manual and lack features such as automated calculation, data storage, and remote monitoring. To overcome these limitations, the proposed project, “IoT-Enabled Smart BMI Monitoring System,” using ESP32 aims to develop an intelligent and connected health monitoring solution. The system uses a load cell to measure weight and an ultrasonic sensor to measure height automatically. The ESP32 microcontroller processes these inputs, calculates BMI using the standard formula, and categorizes the user’s health status. The measured data is
displayed locally and simultaneously uploaded to a cloud platform for remote monitoring and historical tracking. Additionally, a GSM module sends an automatic SMS notification to the registered mobile number, enhancing user awareness. By integrating embedded systems, sensor technology, and IoT communication, the proposed system provides a low-cost, portable, and smart healthcare solution suitable for hospitals, schools, fitness centres, and rural health camps.
It includes following features which make the proposed system reliable, intelligent, and suitable for real-world Healthcare applications:

Background
Marma Sharir is an important branch of Ayurvedic anatomy that deals with the study of Marma, the vital points of the body where muscles, vessels, ligaments, bones, and joints converge. These points are considered seats of Prana (vital life force) and are of great importance in surgery, trauma management, and therapeutics.
Aim
To critically review the classical literature related to Marma Sharir and explore its anatomical and clinical significance.
Materials and Methods
A literary review was conducted using classical Ayurvedic texts including Sushruta Samhita, Charaka Samhita, Ashtanga Hridaya, and published research literature. Relevant information regarding the definition, classification, anatomical basis, and therapeutic importance of Marma was collected and analyzed.
Results
Classical Ayurvedic texts describe 107 Marma points distributed throughout the body. These are classified according to anatomical structures, body regions, and prognosis following injury. Marma points possess significant surgical, therapeutic, and preventive value.
Conclusion
Marma Sharir represents a unique contribution of Ayurveda to anatomical sciences. Knowledge of Marma is essential for understanding trauma, surgery, and Marma therapy. Further scientific studies are required to validate its clinical applications.

This study examined the relationship between critical thinking ability and ability to distinguish between objective values and pseudo values in government secondary schools in Anambra State. Three research questions guided the study and correlational research design was adopted for the study. The population of the study comprised of 2,305 SS2 students in government secondary schools in Anambra State, Nigeria. A sample size of 600 students was selected through sampling random sampling technique. Critical Thinking Ability Test (CTAT) adapted from Watson-Glaser Critical Thinking Appraisal (WGCTA) and the Value Identification Questionnaire (VIQ) developed by the researcher were used for data collection. The instruments were validated by two experts in Sociology of Education, and one expert in Philosophy of Education. The reliability of the instruments were obtained using Cronbach Alpha Descriptive statistics, correlation analysis, and multiple regression analysis were used to analyze the data. The findings of the study reveal a moderate positive relationship between critical thinking ability and students' ability to identify objective values and pseudo values. The study participants expressed the need for critical thinking skills development to enhance value identification. In addition, the findings of the study reveal that critical thinking ability and demographic characteristics jointly predict students' ability to identify objective values and pseudo values. The results of this research inform educators and curriculum administrators on the importance of integrating critical thinking skills into value education, indicating a need for infrastructural and pedagogical considerations. It becomes vital to address these considerations to foster effective value education across institutions. This study underscores the potential of critical thinking ability in enhancing value identification among students in secondary schools.

This practice school report focuses on the Pharmaceutics domain, with phenytoin selected as the study drug. The objective was to promote collaboration between academia and industry while providing practical insights into the formulation and evaluation of phenytoin sodium injections. The report discusses epilepsy and the therapeutic role of phenytoin, its physicochemical and pre-formulation characteristics, formulation and manufacturing considerations for phenytoin sodium injections, and the evaluation parameters used to assess product quality, safety, and performance. This review integrates theoretical concepts with practical applications, enhancing understanding of the pharmaceutical development process of phenytoin as an antiepileptic drug.

Jaundice is a hepatic disorder characterized by hyperbilirubinemia and yellow discoloration of skin and sclera due to impaired liver function. Traditional systems of medicine have long utilized herbal formulations for liver protection and detoxification with minimal side effects. The present research focuses on the preparation and evaluation of a polyherbal syrup for jaundice using medicinal plants known for their hepatoprotective, antioxidant, and anti-inflammatory properties: Gulkhaira (Althaea officinalis), Khaskhas (Papaver somniferum), Bhumi Amla (Phyllanthus niruri), Muchkund (Pterospermum acerifolium), and Kabab Chini (Piper cubeba).

Hydro-alcoholic extracts of each herb were incorporated into the syrup base, followed by evaluation of physicochemical parameters including pH, viscosity, specific gravity, organoleptic characteristics, sedimentation behavior, microbial stability, and overall formulation stability. Preliminary findings suggest that the developed syrup exhibits acceptable physicochemical properties and promising hepatoprotective potential, indicating its usefulness as a supportive herbal remedy for jaundice management. Further pharmacological and clinical investigations are recommended to validate its therapeutic efficacy.

Ulcers are sores or lesions that develop in the mucosal membrane and extend below epithelium of stomach or duodenum. Ulcers formed in the stomach are called gastric ulcers, while those in the duodenum are called duodenal ulcers. Both types are referred to as peptic ulcers. Peptic ulcer occurs in that part of the gastrointestinal tract (g.i.t.) which is exposed to gastric acid and pepsin, i.e., the stomach and duodenum. The etiology of peptic ulcer is not clearly known. It results probably due to an imbalance between the aggressive (acid, pepsin, bile and H. pylori) and the defensive (gastric mucus, bicarbonate secretion, prostaglandins, nitric oxide, high mucosal blood flow and innate resistance of the mucosal cells) factors.

ABSTRACT
Background
Acne rosacea is a chronic inflammatory dermatosis primarily affecting the central face, significantly impacting a patient's quality of life. Dietary triggers—such as spicy foods, alcohol, dairy, and hot beverages—frequently exacerbate flare-ups. While conventional management relies on topical or systemic antimicrobials and strict avoidance strategies, homeopathy offers an individualized approach by addressing the patient’s underlying susceptibility.
Methods
A prospective case series of [Number, e.g., 15 or 20] patients diagnosed with acne rosacea secondary to dietary triggers was conducted over a period of [Number, e.g., 12] months. Detailed case taking focused on local skin characteristics, dietary cravings, aversions, and specific aggravations. Cases were analyzed using three distinct repertorial methodologies based on presentation: Kent’s Repertory for constitutional types, Boenninghausen’s Therapeutic Pocket Book for localized sensations and modalities, and Synthesis Repertory for clinical matching. Therapeutics were prescribed in individualized potencies. Clinical progress was objectively monitored monthly using the Global Acne Grading System (GAGS) and visual analogue scales for erythema and burning.
Results
Dietary triggers were successfully converted into repertorial rubrics (such as Stomach; AGGRAVATION; spices or Skin; ERUPTIONS; rosacea). The repertorial analysis frequently pointed toward remedies like Sulphur, Pulsatilla, Nux Vomica, Carbo Vegetabilis, and Lachesis. After homeopathic intervention, [Percentage, e.g., 80%] of patients demonstrated a statistically significant reduction in GAGS scores (p < 0.05). Concurrently, patients reported an increased tolerance to previous dietary triggers with reduced frequency and intensity of flushing episodes.
Conclusion
Repertorial study serves as a reliable tool to convert complex clinical food triggers and skin symptoms into a structured totality. Utilizing a mix of constitutional and clinical repertorial approaches provides an effective, personalized pathway for the long-term management and systemic desensitization of diet-triggered acne rosacea.

This research paper presents a study of investment behaviour among working women in India. The study looks at investment patterns across different demographic and socioeconomic groups, examining how working women make financial decisions. A structured questionnaire was given to 128 working women from various professional backgrounds, age groups, and income levels. The study used both primary and secondary data collection methods. The findings show that working women mainly prefer traditional, lower-risk investments like gold, real estate, and bank fixed deposits. They focus on regular returns and fund safety, while retirement planning and portfolio diversification are often neglected. The study highlights the need for better financial education and gender-sensitive financial products to empower working women as investors.

Marketing plays a vital role in promoting products and services and building strong relationships with customers. The primary objective of marketing is to attract new customers while retaining existing ones through effective promotional strategies. In the modern competitive business environment, traditional advertising methods alone are often insufficient to capture consumer attention. As a result, organizations are increasingly adopting innovative marketing techniques such as guerrilla marketing. Guerrilla marketing is an unconventional and creative promotional strategy that uses surprise, imagination, and low-cost methods to create a strong impact on consumers. Unlike traditional advertising, guerrilla marketing focuses on memorable customer experiences and encourages word-of-mouth communication. This technique is especially beneficial for small and medium-sized enterprises that seek maximum publicity with limited financial resources. The present study aims to examine the awareness and effectiveness of guerrilla marketing techniques among consumers. It also evaluates the influence of guerrilla marketing on consumer perception, brand recall, and purchasing behavior. The study is descriptive and conceptual in nature and is based on secondary data collected from journals, articles, books, and online sources. The findings indicate that guerrilla marketing has become an emerging trend in modern advertising due to its creativity, cost-effectiveness, and ability to engage customers emotionally. However, awareness regarding guerrilla marketing remains limited among certain groups of consumers, particularly in developing countries like India. The study concludes that guerrilla marketing can serve as an effective complement to traditional marketing strategies and help businesses improve customer engagement and brand recognition in a competitive marketplace.

Functional Neurological Disorder (FND) represents a common diagnostic challenge in neuropsychiatry, particularly when it occurs in the context of comorbid psychiatric disorders and fluctuating neurological symptoms.
We report the case of a 22-year-old man with a history of recurrent major depressive disorder with psychotic features who presented with episodes of transient loss of consciousness, gait instability, fluctuating motor weakness, and paresthesia in the setting of repeated psychological stress.
Neurological investigations, including electroencephalography (EEG), brain computed tomography (CT), electroneuromyography (ENMG), and spinal magnetic resonance imaging (MRI), revealed no significant abnormalities.
Following optimization of antidepressant and antipsychotic therapy, the patient showed marked clinical and psychiatric improvement, with complete recovery of motor function and resolution of sensory symptoms.
This case highlights the diagnostic challenges in distinguishing Functional Neurological Disorder (FND),from an evolving organic neurological disorder and underscores the importance of a multidisciplinary neuropsychiatric approach for accurate diagnosis and appropriate management.

Primary Agricultural Cooperative Credit Societies (PACCS) play an important role in meeting the financial and livelihood needs of rural people in Tamil Nadu. The study examines the contribution of PACCS through services such as KCC loans, crop loans, SHG financing, fertiliser distribution, and Fair Price Shop operations. The study is based on secondary data collected from reports, journals, and official records. The findings show that PACCS help farmers reduce their dependence on private moneylenders, improve agricultural activities, support women&#39;s empowerment, and ensure food security for rural households. The study concludes that PACCS contribute significantly towards rural livelihood and economic development in Tamil Nadu.

In response to growing globalization of education, migration and international student mobility, in ESL/EFL classrooms an increasing amount of heterogeneousness has been observed in terms of a multicultural and cultural aware classroom, which brings new challenges for English language teachers. Even though there has been an increase in the literature on multicultural education, there is not much literature on the difficulties encountered by ESL/EFL teachers as there are some full of thematic content and others of context-based content. The purpose of this study was to make a systematic content analysis of the crucial issues faced by ESL/EFL teachers in multicultural classrooms and patterns international, Asian, and South Asian education contexts have in common. This study took a qualitative approach with an inductive research design that applied the review of systematic literatures. Peer-reviewed articles from the last ten years (between 2015 and 2025) were selected from the wide range of major academic search engines, scientific abstracts and reviews and were identified with carefully planned keywords. After screening and eligibility assessment, a total of 58 studies were chosen for final review. Content analysis was done using thematic analysis to find the major themes present in the literature. Six thematic issues were identified: classroom diversity and linguistic overload; classroom multiculturalism; barriers in intercultural communication; difficulties in implementing curriculum adaptation; lack of teacher readiness; institutional limitations. Teachers in both contexts were identified as struggling with meeting the needs of mixed learners, with culturally determined classroom behaviours, with welcoming and inclusive pedagogy, and providing for inadequate structural and professional support. The review ends with the conclusion that the teaching of multicultural ESL/EFL is a multidimensional pedagogic problem which involves the need to prepare intercultural ESL/EFL teachers, and to reform the system of teaching as a whole. Supporting the English-language competence of teachers of multicultural classrooms will play a crucial role in addressing the teaching of English in increasingly bilingual and global contexts of learning.

Employer–employee relationship is a vital aspect of organizational success. A healthy relationship between employers and employees creates a positive work environment, improves productivity, enhances employee satisfaction, and reduces workplace conflicts. The present study focuses on understanding the employer–employee relationship prevailing in Warbler India LLP, Chennai. The study examines employee satisfaction regarding communication, motivation, interpersonal relationships, participation in decision-making, and organizational support.
The research adopted a descriptive research design and collected data from employees through a structured questionnaire. The collected information was analyzed using percentage analysis. The findings reveal that most employees maintain a satisfactory relationship with their employer and appreciate the direct communication and guidance provided by management. However, employees expect greater support in training and development activities. The study concludes that strengthening employer–employee relationships can improve employee commitment, organizational performance, and long-term business success.

Nutraceuticals are bioactive food-derived compounds—plant (polyphenols, flavonoids, isoflavones), marine (fucoxanthin), animal (omega 3), and microbial (pro/prebiotics)—with potential health benefits. They act via molecular pathways such as Nrf2 (antioxidant), NF-κB (anti-inflammatory), and AMPK (glucose regulation), though many affect multiple pathways simultaneously, influencing glucose homeostasis, hepatic lipogenesis, apoptosis, and more. Proposed applications include metabolic syndrome, cardiovascular disease, neurodegeneration, immune support, and skin aging. Some RCT evidence supports benefits—phytosterols lower LDL, tea polyphenols and citrus bioflavonoids improve endothelial function, and soy products may enhance sperm motility—but trials are limited by heterogeneity, short durations, poor bioavailability, and lack of long-term morbidity or mortality data. Safety concerns include toxicity and drug interactions in susceptible individuals. Regulatory inconsistency across the US, EU, and India (e.g., DSHEA) contributes to variable quality control and financial burdens for manufacturers and researchers. Wider clinical adoption requires validated research, standardized product quality, interdisciplinary collaboration, and more long-term, well-controlled trials focused on clinical endpoints.

Sweet bread is a bakery product made primarily from wheat flour and is widely popular among consumers. The high consumption of sweet bread increases Indonesia’s dependence on wheat imports, which may pose risks to national food security and economic stability. Indonesia, as a tropical country, has abundant local food resources that can be utilized as alternative flour sources. This study aimed to evaluate the effect of substituting wheat flour with several local flours, namely banana flour, purple sweet potato flour, red rice flour, and pumpkin flour, in sweet bread products. The study used a completely randomized design (CRD) with five treatments: 100% high-protein wheat flour as control (P1), 50% banana flour, 50% purple sweet potato flour, 50% red rice flour, and 50% pumpkin flour substitutions. The observed parameters included bread expansion, moisture content, Lab* color values, and physical appearance, specifically crust formation on the bread surface. The results showed that all substituted local flours affected the physicochemical properties of sweet bread but did not affect the physical appearance, particularly crust formation, of the sweet bread.

Stress has emerged as a critical problem in the healthcare domain owing to factors such as work overload, unhealthy lifestyles, academic stress, and psychological stress. Stress that continues for a prolonged period may impact both physical and psychological well-being and lead to various issues such as anxiety, heart problems, tiredness, and insomnia. The emergence of new technologies such as artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and biomedical sensors has driven the evolution of intelligent stress and healthcare monitoring systems. The survey covers different methods of stress monitoring, which include the use of facial emotion recognition, ECG, heart rate monitoring, SpO2, sleep pattern analysis, wearable technology, implantable biosensors, and Internet-of-Things (IoT)-based healthcare monitoring systems. The review includes machine learning and deep learning techniques such as SVM, CNN, and ANN for detecting stress. Additionally, the survey discusses sensor-based healthcare monitoring and several recently introduced AI-based techniques for mental health and remote patient monitoring.

TDDS (transdermal drug delivery systems) provide an effective method of delivering medication without requiring injections or pills. TDDS do this by delivering the active ingredients of medications directly through your skin into your bloodstream. Because TDDS bypass your gastrointestinal system and the first-pass effect (a metabolism step in the liver), they can improve the bioavailability of medications, they can provide a more consistent zero-order release of the medication, and they can help increase the patient's adherence to the medication regimen. A major physical barrier to delivering medications via TDDS is the stratum corneum (the outermost layer of your skin). The most common way of disabling the stratum corneum is by using specialized patch designs such as drug in adhesive, reservoirs, matrices, or microreservoirs. To help the medication move through the stratum corneum and into the bloodstream, permeation enhancers are often used in conjunction with specialized patch designs. Currently, commercially available TDDS are used for multiple indications—from pain relief to smoking cessation—with new uses emerging for herbal products such as using ginger patches to relieve nausea. When developing and standardizing TDDS; physicochemical, in vitro and in vivo studies should be performed to ensure that all TDDS demonstrate safety, stability and steady-state flux of drug delivery. Future efforts in TDDS will be focused on the development of smart responsive patches, the use of biodegradable materials, microneedle arrays and nanotechnology. Together, these advancements are expected to expand the types of therapeutics delivered via TDDS to include the delivery of macromolecules, biologics, and personalized medicines.

Pharmacovigilance has progressed from systems that relied heavily on people to intelligent systems that rely heavily on artificial intelligence (AI) technology and use artificial intelligence (AI) technology to improve safety in monitoring drugs postmarketing within the current healthcare systems. This paper describes how Generative artificial intelligence (AI), particularly large language models, are transforming key pharmacovigilance processes such as generating individual case safety reports (ICSRs), reviewing literature, and detecting signals through automation of these processes. Compared to traditional practices, artificial intelligence (AI) supported systems have higher sensitivity, less likelihood of generating false-positive results, and increased time efficiencies. The incorporation of global surveillance data and regulatory requirements provides additional support for assessing safety and compliance. While challenges exist such as issues with data quality, regulatory validation processes, and workforce-related shortages when utilizing artificial intelligence (AI) technologies, there has been the development of scalable and more precise solutions using AI technologies within pharmacovigilance. Generally, this shift in pharmacovigilance procedures marks a move from reactive, data-based drug safety management to a more proactive approach, which is expected to enhance patient outcomes and the efficiency of regulation within the growing complexity of the healthcare system.

This study explores the impact of digital technologies on enhancing social development through improved access to education in India. It analyses how digital tools and platforms can bridge educational gaps, promote inclusivity, and foster equitable learning opportunities for diverse populations. The research is based on secondary sources collected from articles, magazines, periodicals, and websites. It discusses the multifaceted benefits of digital technologies, including bridging the urban-rural divide, promoting inclusivity, facilitating lifelong learning, enhancing educational outcomes, reducing the cost of education, empowering educators, supporting government initiatives, and addressing language diversity. However, it also highlights challenges such as the digital divide, connectivity issues, electricity supply, digital literacy, device availability, content relevance, language barriers, the cost of data, technical support, and privacy and security concerns. The study concludes with potential solutions to address the digital divide in rural areas, emphasizing the need for infrastructure development, policy support, and innovative solutions to make digital education accessible and effective for all segments of the population.

The rapid evolution of digital technology has contributed to the growth in the use of smartphone technology, social media, on-line gaming and on-line applications across all age groups. While digital technologies offer a wide variety of advantages in the fields of communication, education, and entertainment, their overuse and misuse have resulted in digital addiction emerging as a public health issue. The goal of this review is to explore the connection between digital addiction and psychological well-being, especially with respect to social behavior and sleep disorders, as well as mental health outcomes. It discusses the definition of addiction, various types of digital addiction (smartphone addiction, social media addiction, Internet addiction, gaming addiction) and their prominent contributors including dopamine reward system, fear of missing out (FOMO) syndrome, academic stress, social validation, and overuse due to the pandemic. Past research suggests that overuse of digital media adversely impacts interpersonal relationships, particularly by decreasing face-to-face communication, withdrawing from society, and being dependent of digital media. Moreover, sleep disturbances like sleep deprivation and insomnia, late bedtime use of screens, disturbance of circadian rhythm, suppression of melatonin hormones etc. have significant correlation with digital addiction. It also emphasizes the severe psychological impact of digital addiction including anxiety, depression, stress, emotional instability, attention problems, and low self-esteem. Neuropsychological and behavioral addiction mechanisms can worsen addictive online behavior and emotional reliance. Overall findings show that digital addiction is a serious threat to psychological and social well-being, particularly of adolescents and young people. The review highlights the need to strike a balance between digital technologies, awareness campaigns and intervention strategies to reduce the detrimental psychosocial effects of overuse of digital technologies and promote healthy digital lifestyles.

Many people are interested in an organisation’s approach to environmental health and safety (EHS) management including customers, clients, suppliers, shareholders, contractors, and agencies. More and more organisations attach the same importance to high standards in EHS management as they do to other key aspects of their activities. High standards demand a structured approach to the identification of hazards and the evaluation and control of work-related risks.The present status of industry EHS management is reviewed, with a focus on the Environment, Health and Safety in a management system. The review provides insight into the standards adopted by the industry, and it identifies trends and needs for improvement. It appears that most industries consider goal-based EHS management programs to be success and believe them to contribute to the profitability of the industry.From this project we conclude that EHS management would benefit greatly from guidance on how to use existing management systems efficiently.

Social Media Marketing has become one of the most powerful tools for achieving success in the field of E-Commerce. With the rapid growth of internet usage and digital platforms, businesses are increasingly utilizing social media networks such as Facebook, Instagram, YouTube, LinkedIn, and X to promote products, engage customers, and improve brand visibility. This seminar explores the various social media marketing strategies that contribute to the growth and sustainability of e-commerce businesses.
The study focuses on important strategies including content marketing, influencer marketing, paid advertising, customer engagement, personalized promotions, and data-driven marketing techniques. It also highlights how businesses use social media analytics to understand consumer behaviour, target the right audience, and improve customer satisfaction. Effective use of social media not only increases website traffic and online sales but also helps in building long-term customer relationships and brand loyalty.
Furthermore, the seminar discusses the role of emerging technologies such as Artificial Intelligence (AI), chatbots, and automation tools in enhancing digital marketing performance. It also examines the challenges faced by e-commerce companies, including privacy concerns, intense competition, changing consumer preferences, and managing online reputation.
In conclusion, social media marketing plays a vital role in the success of modern e-commerce businesses by enabling cost-effective promotion, real-time communication, and global market reach. Organizations that adopt innovative and customer-focused social media strategies can achieve greater competitive advantage and sustainable business growth in the digital marketplace.