Solar air heaters (SAHs) are widely recognized as simple and cost-effective renewable energy devices; however, their practical application is often limited by low thermal efficiency caused by weak convective heat transfer between the absorber plate and the flowing air. The formation of a stable thermal boundary layer over smooth absorber surfaces significantly restricts heat transfer performance, necessitating effective enhancement techniques. The present study aims to investigate the thermo-hydraulic performance of a solar air heater duct equipped with S-shaped ribs with gaps on the absorber plate, focusing on achieving improved heat transfer with an acceptable pressure drop. A two-dimensional Computational Fluid Dynamics (CFD) analysis is carried out using ANSYS Fluent, employing the RNG k–? turbulence model to accurately capture the effects of flow separation, reattachment, and secondary flow induced by rib geometry. Simulations are performed under steady-state conditions for a wide range of Reynolds numbers (Re = 2000–20,000) with a constant heat flux applied on the absorber surface. The performance of the ribbed solar air heater is evaluated using key parameters, including Nusselt number (Nu), friction factor (f), thermal efficiency (?), and thermo-hydraulic performance criterion (PEC). The results demonstrate a substantial enhancement in heat transfer due to repeated disruption of the thermal boundary layer and intensified turbulence generated by the S-shaped ribs. Although friction losses increase compared to a smooth duct, the overall PEC remains consistently greater than unity across the entire Reynolds number range, confirming superior thermo-hydraulic performance. The findings establish that S-shaped ribs with gaps offer an effective and practical roughness configuration for improving the thermal efficiency of solar air heaters operating under turbulent flow conditions.

Solar air heaters (SAHs) are widely employed in low- and medium-temperature thermal applications due to their simplicity and low operating cost; however, their broader utilization is constrained by poor thermal efficiency arising from weak convective heat transfer between the absorber plate and the flowing air. To address this limitation, the present study numerically investigates the thermo-hydraulic performance enhancement of a solar air heater equipped with I-shaped vertical fins mounted on the absorber plate. A three-dimensional steady-state Computational Fluid Dynamics (CFD) analysis is carried out using ANSYS Fluent, employing the RNG k–? turbulence model to accurately capture flow separation, boundary layer disruption, and turbulence effects. Simulations are performed over a turbulent Reynolds number range of 3000–18000 under a uniform heat flux condition. The thermal and hydraulic performances are evaluated in terms of Nusselt number (Nu), friction factor (f), outlet air temperature rise (?T), and thermal enhancement factor (TEF). The results demonstrate a substantial improvement in heat transfer for finned configurations compared to a smooth duct, with the average Nusselt number increasing by up to 52%. Although the friction factor increases due to flow obstruction, all finned cases exhibit TEF values greater than unity. An optimal fin height of 90 mm is identified, offering the best compromise between heat transfer augmentation and pressure drop. The findings confirm that I-shaped vertical fins provide an effective passive technique for enhancing SAH performance in practical solar thermal applications.

Solar air heaters (SAHs) are widely recognized as cost-effective and environmentally friendly solar thermal devices for low-temperature heating applications such as space heating and drying. However, their practical deployment is often limited by inherently low heat transfer coefficients between the absorber plate and the flowing air. To overcome this limitation, various heat transfer enhancement techniques—such as ribs, fins, and artificial roughness—have been explored, though many configurations result in excessive pressure drop or complex fabrication. In particular, limited attention has been given to C-shaped fin geometries and their influence on flow structure and thermal behavior within SAH ducts. The present study numerically investigates the thermo-hydraulic performance of a solar air heater equipped with a C-shaped fin mounted on the absorber plate using a two-dimensional computational fluid dynamics (CFD) approach. Simulations are performed in ANSYS Fluent employing the RNG k–? turbulence model under steady-state forced convection conditions for Reynolds numbers ranging from 3000 to 24000. Velocity and temperature fields are analyzed to understand flow separation, recirculation, and thermal wake formation induced by the fin. The results reveal that the C-shaped fin significantly enhances turbulent mixing and convective heat transfer compared to a smooth duct, while maintaining acceptable pressure penalties. The qualitative trends of Nusselt number enhancement, friction factor variation, and thermo-hydraulic performance show good agreement with published literature. The findings demonstrate that C-shaped fin configurations offer a promising and practical solution for improving the thermal efficiency of solar air heaters in real-world applications.

This paper examines the most significant factors of health insurance satisfaction among covered people in Khartoum, Sudan, through Partial Least Squares Structural Equation Modeling (PLS-SEM). A structured questionnaire was used to take primary data and a total of 350 health insurance policyholders had to fill the survey questionnaire out of which 318 were accurate answers that were retained after data screening. The research paper analyses five latent variables, which include quality of the services, trust, affordability of premiums, efficiency of settling claims and satisfaction with health insurance in general. The results of the analytical investigation indicate that the positive impact of services quality and efficiency in settling claims has the greatest influence on the contentment of the policyholders, then the trust and affordability of the premiums. The model is robust as it has a high explanatory power and predictive relevance as shown by the structural model.

The proliferation of social media platforms has made accurate emotion detection in user posts increasingly critical for trend analysis, customer service, and mental health monitoring. Alongside text, emojis have become pervasive tools for expressing emotional states, comprising a substantial portion of content on platforms such as Instagram and Facebook. However, most existing models either ignore emojis or treat them equally with text, leading to suboptimal performance when emojis carry stronger emotional signals. This paper proposes a multimodal emotion detection algorithm that integrates text and emoji representations while applying a flexible weighting mechanism for emojis. The proposed model employs PhoBERT for Vietnamese text encoding, leverages the Emoji Sentiment Ranking and Emoji-Dis dataset for mapping emojis to emotion vectors, and utilizes a cross-attention network to determine context-dependent emoji weights. The algorithm was evaluated on a manually annotated dataset of 5,000 social media posts classified into six emotion categories (happiness, sadness, anger, fear, surprise, and neutral). Experimental results demonstrate that the proposed model achieves a 3.2% improvement in F1-score compared to text-only models and a 2.1% improvement over non-weighted fusion approaches, while maintaining interpretability through the attention mechanism. This research confirms the significant role of emojis in emotion analysis and establishes a foundation for flexible multimodal data integration in low-resource language contexts.

This paper presents a graph structural approach to the study of maximal antichain graphs and their potential applications in combinatorial optimization. The concept of maximal antichains, derived from partially ordered sets (posets), provides a rich framework for constructing graphs that exhibit unique connectivity, dominance and covering proper- ties. The results reveal that maximal antichain graphs possess higher level of structural efficiency and minimal redundancy making them prominent for optimization processes that require balance between connectivity and independence. The paper further explore how the structural characteristics of these graphs such as degree distribution, chromatic number and clique structure can be utilized to model and solve optimization problems. Furthermore the paper provides valuable insight into the study of combinatorial be- haviours of maximal antichains graphs.

Early Childhood Education (ECE) teachers play roles that demand high levels of emotional and affective involvement, making psychological well-being a crucial aspect in sustaining the quality of early childhood learning. Various job demands, limited resources, and the dynamics of the educational system may influence the psychological well-being of ECE teachers. This study aims to systematically review research findings related to the psychological well-being of ECE teachers and to identify factors that influence it. The method employed was a Systematic Literature Review (SLR) following the PRISMA 2020 guidelines. The literature search was conducted through reputable online databases using the inclusion criteria of articles published between 2020 and 2025, resulting in 11 articles selected for analysis. The findings indicate that the psychological well-being of ECE teachers is influenced by individual factors such as self-efficacy, gratitude, and resilience, as well as work environment factors including organizational support and a supportive work climate. Psychological well-being is also related to levels of job stress and teacher performance. The implications of this study emphasize the importance of paying greater attention to the psychological well-being of ECE teachers through strengthened institutional support and the development of sustainable psychological interventions.

White space and layout are fundamental elements of content design that directly influence comprehension, engagement, and persuasive effectiveness. Traditionally examined in print media, these elements have gained increasing importance in digital-first environments, including websites, mobile applications, emails, social media, and interactive proposals. The increasing volume of information in digital spaces demands that content be not only visually appealing but also structured in a way that facilitates efficient processing, attention, and retention. This review synthesizes contemporary research across three complementary perspectives. The first perspective, Digital-First Design, emphasizes how layout and spacing guide user attention, improve readability, and support accessibility. Research demonstrates that effective use of white space reduces visual clutter, highlights key messages, and enhances user engagement across devices, platforms, and interactive content. The second perspective, Cognitive and Emotional Analytics, investigates the impact of white space and layout on cognitive load, information retention, and emotional responses. Studies employing eye-tracking, heatmaps, and neuroscience methods reveal that strategically designed layouts improve comprehension, reduce cognitive effort, and evoke positive emotional responses such as trust, motivation, and perceived professionalism.

Industrial Internet of things can be defined as a technology that enables communication between digital appliances and industrial system. It is a new research field which deals with the network of several IoT devices and industrial operations. IIoT devices are used to accumulate huge volumes of data from several sensors embedded in them. However, this technology has a major setback, namely cyberattacks which prevent the IIoT devices from providing reliable data for industrial operations. These risks have resulted in loss of finance and reputation issues to several organizations, some of which have resulted the shutdown of some organizations and theft of sensitive and classified information. In relation to this, many Network Intrusion Detection System (NIDS) have been designed to mitigate these shortcomings. The amount of information required to design a secure NIDS is cumbersome thereby making the detection of current and yet to be identified intrusion a very difficult task. The aim of this paper is to design a deep learning based intrusion detection system for IIoT systems with recursive feature elimination. The feature selection is aimed at training and checking the information obtained from TCP/IP packets from the internet. The model uses unsupervised learning technique and recursive feature elimination with deep feedback neural network. The design was tested using NSL-KDD and the UNSW-NBLS datasets as well as on a hardware testbed. The technique proposed in this paper outperforms other state of the art Network Intrusion detection Systems (NIDS) in terms of accuracy, scalability, rate of detection and IPR by 99.1%, 2.3 %, 99.3% and 1.5% respectively for NSL-KDD dataset and 99%, 1.9%, 99.9% and 1.7% respectively for UNSW-NB15 dataset. Also simulation experiment was performed which validates the appropriateness of the technique proposed in this paper for both IIoT intrusion detection system and classification of intrusion network attack.

Site and Services Scheme is a programme carried out either by the government or private organization which involves facilitating a particular area with the essential infrastructural amenities so that private individuals or corporate bodies can carry out developments in such area at affordable cost. The Federal Government of Nigeria introduced the Sites and Services Scheme in 1986 as a viable means of increasing supply of serviced plots at affordable costs in order to achieve housing delivery. The concept was adopted and first domesticated in Nigeria by the Federal Ministry of Works and Housing in 1986. The underlying principle of Site and Services Scheme is that the authorities would provide the land and the infrastructural facilities, while the individual allottees proceed to build their houses in accordance with the approved building plan. The aim of this study is to assess the implementation and effectiveness of the Federal Government Sites and Services Scheme in South-South Geopolitical Zone of Nigeria between 2015-2025. In order to achieve the aim of the study, questionnaires backed with interviews were used to elicit information from 208 respondents comprising, Land officers, Estate Officers, Town Planners, Surveyors, Architects, Builders, Civil Engineers, Structural Engineers and Quantity Surveyors. These respondents are real estate professional staff of Federal Ministry of Housing and Urban Development in South-South, Nigeria. The total population of the study (208) was adopted as the sample size since it is a manageable size. Descriptive statistical tools comprising tables, mean, variance and standard deviation were used in the data presentation and analysis. Inferential statistical tools were used to draw conclusions from data. The statistical technique used in testing the hypothesis is one-way analysis of variance (ANOVA). The findings reveal that the Federal Government sites and services scheme in South-South Nigeria is yet to effectively achieve or realize its prime objectives of increasing the supply of serviced plots of land for residential development due to the following reasons: Poor funding/budgetary constraints, delay in payment of compensation and encroachment of sites, Poor location of sites, fraudulent/double allocation of plots, Conflicts with State Government, Inter-Departmental Conflicts, Inadequate Manpower, among others. The study recommends that Federal Government should take up whole or partial funding of provision of infrastructural facilities in Site and Services Scheme as a sure way of increasing the national housing stock and as a poverty eradication strategy.

The study determined work environment as predictors of teachers’ job engagement in public secondary schools in Enugu State. Two research questions guided the study and two null hypotheses were tested at 0.05 level of significance. A correlational research design was adopted for the study. The population of the study comprised 15,321 teachers in the 296 public secondary schools in Enugu State. The sample size for this study consisted of 767 teachers drawn using proportionate stratified sampling technique. Two sets of instruments titled ‘‘Work Environment Questionnaire (WEQ)’’ and ‘‘Teachers’ Job Engagement Questionnaire (TJEQ)’’ were used for data collection. The instruments were face validated by three experts, two from the Department of Educational Management and Policy, and one from the Department of Educational Foundations in Measurement and Evaluation Unit, Faculty of Education, Nnamdi Azikiwe University. Cronbach alpha method was used for a test of internal consistency of the instruments which yielded overall coefficients of 0.82 for WEQ and 0.81 for TJEQ respectively. The researcher, together with five research assistants, collected data for the study using the direct approach method and 98% return was recorded. Simple regression was used to answer the research questions and test hypotheses. The findings of the study revealed among others that physical and psychosocial work environments are strong and significant predictors of teachers’ job engagement in public secondary schools in Enugu State. Based on the findings, it was recommended, among others, that principals should partner with education stakeholder and non-governmental organizations to get financial and material supports to enrich physical work environment for improving teachers’ job engagement.

The study investigated principals' institutional support services as predictors of teachers' job satisfaction in public secondary schools in Anambra State. Three research questions guided the study and three null hypotheses were tested at the 0.05 level of significance. The population of the study comprised 7,248 teachers from the 267 public secondary schools in Anambra State. A proportionate stratified sampling technique was used to draw 726 teachers for the study. A researcher-developed instruments titled "Principals' Institutional Support Services Questionnaire (PISSQ)" and "Teachers' Job Satisfaction Scale (TJSS)" were used for data collection. The instruments were subjected to face validation by three experts comprising two lecturers from the Department of Educational Management and Policy, and the other a specialist in Measurement and Evaluation, all from the Faculty of Education, Nnamdi Azikiwe University, Awka. The internal consistency of the instruments was determined using Cronbach's alpha, yielding overall reliability indices of 0.81 for PISSQ and 0.78 for TJSS. The instruments were administered by the researcher with the help of five research assistants, resulting in a 99% return. Simple regression was used to answer the research questions and test hypotheses. The study's findings revealed, among others, that principals' welfare, in-service training and information and communication services are strong predictors of teachers' job satisfaction in public secondary schools in Anambra State. It was also found that principals' welfare, in-service training and information and communication services are significant predictors of teachers' job satisfaction in public secondary schools in Anambra State. Based on the findings, it was recommended, among other things, that the Ministry of Education should increase funding to enable principals to procure innovative devices that enhance the provision of ICT services and facilitate teachers' job satisfaction in secondary schools.

Maps have been used to portray information about the earth’s surface Navigators, land surveyors, town planners, military, architects, etc., use maps to show spatial distribution of important geographic features. This study focuses on the production of large-scale Nigerian sheet N0 9904 map that employs the use of high-resolution satellite imagery data of the area. The objectives were to convert from imperial to system international, to re-project the coordinate system from NTM to UTM, to digitize the details features of the study area and to produce the digital large-scale map of the study area. Method entailed geo-referencing of the local map, satellite imagery classification of the features, and ground truthing data. Others were GPS facilitated points, administrative boundary of the study area, secondary data (OSGOF imagery, 2023), ArcGIS 10.7.1, Excel, AutoCAD, Franson Trans converter 2.3 for coordinate conversion, remote sensing and GIS were used to produce digital map sheet of the study area. Results showed that buildings (2.670%), land cover (96.87?) and roads (0.46%) as seen in the map document and the study recommended that the map should be updated periodically to reflect changes in land use, infrastructure, and environmental conditions.

The gradual blending of hydrogen (H2) in natural gas (NG) networks has received global attention as a potential path to decarbonization. This research experimentally examines the emission of hydrogen-natural gas blends at varying hydrogen concentrations in order to evaluate the effects of hydrogen blending with currently supplied natural gas in Bangladesh. The laboratory flue gas analyses for gas mixtures containing 0–31.5 vol% hydrogen demonstrate that CO?emissions are consistently reduced with increased hydrogen percentage, confirming the decarbonization potential of hydrogen blending, although slight NO? variations were found, suggesting the need for combustion optimization. Lower hydrogen content in the blended gas has rapid impact on carbon dioxide reduction. No CO and SOx emissions were detected for the blended Natural Gas and Hydrogen mixture burning. Life Cycle Analysis (LCA) of hydrogen blending with natural gas for Bangladesh context was made by openLCA which reflects the global warming potential (GWP) has a decreasing trend with the increasing of volumetric fraction of hydrogen in the natural gas and hydrogen admixture. The Eutrophication potential (EP) and Human toxicity potential (HTP) have the increasing trends with the increasing of volumetric fraction of hydrogen in the natural gas and hydrogen admixture.

A simple, precise, and reliable method was developed for the simultaneous estimation of Sulbactam and Durlobactam in tablet dosage forms. Chromatographic separation was performed using an Agilent C18 column (250 × 4.6 mm, 5 µm) with a mobile phase consisting of 0.1% orthophosphoric acid and acetonitrile in a 70:30 ratio, delivered at a flow rate of 1.0 mL/min. The column temperature was maintained at 30°C, and detection was carried out at a wavelength of 220 nm. The retention times for Sulbactam and Durlobactam were observed at 2.458 min and 2.855 min, respectively. The method demonstrated excellent precision, with %RSD values of 0.3 for Sulbactam and 0.6 for Durlobactam, while the recovery rates were 99.29% and 99.87%, respectively. Limits of detection (LOD) and quantitation (LOQ) were calculated from the regression equations, yielding 0.09 and 0.27 for Sulbactam, and 0.04 and 0.13 for Durlobactam. The regression equations obtained were y = 2684.5x + 484.45 for Sulbactam and y = 2153.5x + 150.3 for Durlobactam. Overall, the method offers reduced retention times and shorter run durations, making it a cost-effective and practical approach suitable for routine quality control analysis in the pharmaceutical industry.

This study assessed industry-relevant skills needs of technology education graduates in the Federal Colleges of Education (Technical) in Nigeria for effective industrial performance. In particular, it analysed the degree of technical, digital communication, soft, entrepreneurial, and problem-solving skills among graduates against the needs on the industry level. A descriptive survey research design was adopted to study the Federal Colleges of Education (Technical) in Anambra, Rivers, Kano and Lagos States. The study population was composed of 421 lecturers and instructors, and 252 of them were sampled through stratified random sampling to make the sample representative. Data were collected through a researcher developed Skills Assessment Scale (SAS) that was consisted of 39 items rated on 4-point scale. The coefficient of reliability of 0.946 of the instrument was high. The data was analysed with the help of the SPSS version 23, using descriptive statistics (mean and standard deviation). The results found that technical skills (M = 2.51), entrepreneurial skills (M = 2.68), and problem-solving skills (M = 2.59) were of the highest necessity in industrial performance, and digital communication and soft skills (M = 2.48) were of the lowest rank. This study finding has implications for holistic training and production of industry-sale graduates. Hence, there is a need to incorporate digital communication and soft skills in technology education programmes. Therefore, recommended the review of the curriculum, improvement of digital literacy, entrepreneurship developmental programmes, and project based learning, improved industry-institution cooperation, and sustained capacity building of lecturers to make training output in line with the needs of industry and technological development of the country.

Nanoparticle-based coatings can significantly enhance the performance and service life of internal combustion automobile engines by reducing friction and wear between critical engine components. In this research, the tribological properties of titanium dioxide (TiO?) nanocoatings applied to piston rings are investigated. The nanocoating samples were prepared using the sol–gel dip-coating process with different dipping–drying cycles of 40, 50, 60, and 70. Tribological tests were conducted using a pin-on-disc tribometer under varying loads and sliding speeds. The experimental results demonstrate that TiO? nanocoatings exhibit superior friction-reduction and anti-wear characteristics compared to conventional chromium plating. A reduction in the coefficient of friction by approximately 4% and 8% was observed for coatings prepared with 60 and 70 dipping–drying cycles, respectively. Furthermore, the worn surface morphology was analyzed using scanning electron microscopy (SEM), confirming improved wear resistance of the nanocoated surfaces.

Autonomous systems increasingly rely on Artificial Intelligence (AI) techniques to monitor system behavior and detect anomalies arising from cyber-attacks, sensor failures, or abnormal operational patterns. Although existing machine learning and deep learning models achieve high accuracy in anomaly detection, many of them function as black-box systems and lack transparency in their decision-making processes. This absence of interpretability limits trust, validation, and adoption in safety-critical autonomous environments. To address this challenge, this paper proposes an Explainable Decision Tree–based framework for anomaly detection in autonomous systems. The proposed approach employs a Decision Tree classifier to identify anomalous and normal system behavior while providing clear and interpretable explanations through feature importance analysis and decision rule paths. The framework is evaluated using datasets derived from autonomous, IoT, and Vehicular Ad Hoc Network (VANET) environments, which contain features related to sensor readings, system states, and communication behavior. Experimental results demonstrate that the Decision Tree model achieves reliable anomaly detection performance while maintaining inherent interpretability. The explainable nature of the proposed framework enables users to understand which features contribute to anomaly detection decisions, thereby improving transparency and accountability. By combining accurate classification with human-understandable explanations, the proposed framework enhances trust, supports safety assurance, and promotes the adoption of AI-driven solutions in autonomous and intelligent systems.

Road infrastructure monitoring and vehicle safety analysis increasingly rely on data-driven approaches derived from vehicular sensors. Passive Vehicular Sensors (PVS) generate high-dimensional, multi-modal time-series data that can be leveraged to detect road-quality anomalies and abnormal driving conditions. However, the lack of interpretability in many machine learning (ML) and deep learning (DL) models limits their adoption in safety-critical applications. This paper proposes an Explainable Artificial Intelligence–based Anomaly Detection System (XAI-ADS) for PVS data. The framework integrates classical ML models (Random Forest, XGBoost, Decision Tree) and a deep learning Multi-Layer Perceptron (MLP), coupled with post-hoc explainability techniques such as SHAP and LIME. A complete end-to-end pipeline—covering data exploration, preprocessing, model training with cross-validation, explainability, and real-time deployment via FastAPI—is presented. Experimental results demonstrate that tree-based ensemble models achieve strong macro-F1 performance, while XAI methods provide transparent insights into sensor contributions, enhancing trust and deployability.

The rapid deployment of autonomous driving systems and cooperative vehicular networks has significantly increased dependence on continuous inter-vehicular communication for safety-critical decision making. However, these systems are increasingly vulnerable to anomalous behaviors arising from cyber-attacks, faulty sensors, and misbehaving nodes, including false position reporting, speed spoofing, Sybil attacks, and message manipulation. Traditional rule-based and supervised learning approaches struggle to detect such anomalies due to their reliance on static thresholds and labeled attack data, which limits adaptability to evolving threat patterns. To address these challenges, we propose XAI-ADS, an explainable anomaly detection framework based on an Isolation Random Forest model for identifying abnormal vehicular behavior in autonomous driving environments. The framework processes heterogeneous vehicular message logs and time-series features, including GPS coordinates, vehicle speed, temporal message intervals, and communication metadata. By leveraging isolation-based ensemble learning, the proposed approach effectively detects rare and irregular behavioural patterns in an unsupervised manner, eliminating the dependency on labelled attack data during training. To enhance transparency and trust—critical requirements in safety-critical autonomous systems—the framework integrates explainable AI (XAI) techniques, specifically SHAP for global interpretability and LIME for instance-level explanations. The proposed system is evaluated using the VeReMi dataset, a benchmark dataset for vehicular misbehaviour detection. Performance is assessed using precision, recall, F1-score, ROC-AUC, and detection latency. Experimental results demonstrate that the Isolation Random Forest–based approach achieves robust anomaly detection performance with low computational overhead, making it suitable for real-time edge deployment. This work establishes a practical and interpretable solution for enhancing the security and reliability of autonomous vehicular networks.

Introduction: Frozen shoulder (Adhesive Capsulitis), correlated with Apabahuka in Ayurveda, is a debilitating condition characterized by progressive pain and severe restriction of both active and passive glenohumeral motion. Conventional management, including analgesics, corticosteroids, and physiotherapy, often provides incomplete relief and can be associated with adverse effects. Marma therapy, an ancient Ayurvedic intervention focusing on vital energy points, offers a holistic, non-pharmacological alternative. This review synthesizes classical Ayurvedic wisdom with modern scientific insights to evaluate the potential role of Marma therapy in managing frozen shoulder. Methods: A systematic narrative review was conducted. Classical Ayurvedic texts (Sushruta Samhita, Ashtanga Hridaya, Sarangadhara Samhita) were scrutinized for descriptions of Apabahuka, its pathogenesis (Samprapti), and the principles of Marma therapy. Electronic databases (PubMed, Scopus, Cochrane Library, Google Scholar, AYUSH Research Portal) were searched for relevant studies using keywords: "frozen shoulder," "adhesive capsulitis," "Marma therapy," "vital points," "Ayurveda," "manual therapy," "myofascial release." Preclinical, clinical, and review articles published up to September 2023 were included. Data were integrated thematically. Results: Ayurveda attributes Apabahuka to the vitiation of Vata Dosha, localized primarily in the Amsa (shoulder) region, leading to depletion of Kapha (unctuousness) and Shleshaka Kapha (synovial fluid), resulting in stiffness (Stambha). Marma points are defined as crucial junctures of Mamsa (muscle), Sira (vessels), Snayu (ligaments/tendons), Asthi (bone), and Sandhi (joints), where Prana (vital life force) resides. The shoulder region houses key Marma points like Kshipra (near the acromioclavicular joint), Kurpara (elbow, influencing upper limb channels), and Amsa Marma itself. Therapy involves precise, gentle stimulation (often non-invasive touch, sneha or medicated oil application, and controlled pressure) to clear Srotas (micro-channels), pacify Vata, restore circulation (Rakta and Vata flow), and break the pain-spasm-inflammatory cycle. Modern physiology suggests this may correspond to modulating neurovascular bundles, releasing myofascial trigger points, enhancing proprioception, and stimulating the release of endogenous opioids and anti-inflammatory mediators. Preliminary clinical studies and numerous case reports suggest significant improvements in pain scores (VAS), range of motion (ROM), and functional disability scores (e.g., SPADI) following Marma-based interventions, often combined with internal medication (Snigdha Virechana, Niruha Basti) and physiotherapy. Conclusion: Marma therapy presents a theoretically coherent and clinically promising modality for frozen shoulder. Its proposed mechanisms, balancing Vata, restoring structural integrity, and enhancing Prana flow, align with contemporary goals of reducing inflammation, breaking adhesions, and restoring function. While the anecdotal and preliminary clinical evidence is encouraging, a clear paucity of high-quality, randomized controlled trials (RCTs) exists. Future research should focus on rigorous RCTs comparing standardized Marma protocols to conventional care, alongside mechanistic studies to objectively quantify their effects on inflammation, capsular thickness, and neural plasticity. Integrating Marma therapy into a multidisciplinary approach may offer a safer, more comprehensive strategy for managing this challenging condition.

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) is transforming conventional agricultural practices into intelligent, data-driven systems that enhance productivity and sustainability. This research presents a novel AI-powered IoT framework for smart irrigation and fertilizer management in precision farming, aimed at optimizing resource utilization and improving crop yield in real time. The system envisioned combines an IoT sensor network of high density to monitor important environmental and agronomic variables in real time, including soil water content, nutrient levels, humidity, temperature, and crop phenology. These streams are then analyzed using AI-powered algorithms such as Random Forest, LSTM networks, and Reinforcement Learning models to power predictive analysis and adaptive decision-making. Random Forest algorithm assists in soil condition classification and estimation of nutrient deficits, whereas LSTM models predict irrigation needs by examining time series patterns in soil moisture and weather readings. Reinforcement Learning automatically tunes irrigation planning and fertilizer application based on real-time feedback from soil sensors and vegetation response indicators to provide maximum water and nutrient supply with minimum wastage. The combination of edge analytics and cloud computing guarantees real-time processing of data, remote monitoring, and autonomous control via a centralized dashboard shared among farmers and agricultural stakeholders.Field trials prove that the system cuts water and fertilizer use by as much as 30% compared to traditional methods while also improving yield consistency and fertility of soil. Further, the modular and scalable design accommodates varied crop varieties and weather conditions and can, therefore, be suitable for small as well as industrial-sized farms. This research not only confirms the performance effectiveness of AI–IoT convergence in precision agriculture but also underscores its potential to solve global issues with food security, resource limitation, and environmental sustainability. Through intelligent automation and ongoing optimization, the envisioned AI-driven IoT framework is an evolutionary leap towards sustainable smart farming systems, where data intelligence informs all farm decisions from soil to harvest.

The need for efficiency in construction practices like in other industries has warranted the desire for a technology that improves and streamlines communication and collaboration. One such is the chat generative pre-trained transformer(Chatgpt), which produces human-like responses in automating scheduled tasks and optimization of resources. This paper therefore examines the role of ChatGPT in construction management practices in Nigeria, with a review to encourage its adoption for improved project delivery. To achieve this aim, the study examines the impact/role of chatgpt in construction management practices in Nigeria, investigates the challenges confronting its adoption of chatgpt in construction management practices in Nigeria and suggests measures for managing the challenges confronting the adoption of chatgpt in construction management practices in Nigeria. The study adopted descriptive survey design using a structured questionnaire administered to both construction professionals, computer professionals and other stakeholders. The findings reveal that Chatgpt can be used to produce a safety manual for construction operatives, adopt pre-project designs and for planning operations. The most critical roles of Chatgpt are for improved decision-making (22), safety/quality management (21), administrative automation (18) and team collaboration (17). The factors confronting its adoption include :data security (18), sustainability / unforeseen issues (16), inability to manage queries (15), bias/error-prone (12). The study recommends that there should be a clear synergy between construction professionals and ChatGPT developers behind the scenes (19), tailored usage of the app for specific projects and ensuring data privacy.

Gold plays an important role in India as a store of value, hedge against inflation, and preferred investment. In recent years, rising gold prices driven by global economic uncertainty, inflation, and currency fluctuations have significantly influenced consumer behaviour, particularly in Kerala where gold holds strong cultural and financial importance. Palakkad district provides a suitable context for studying public responses to these price increases. Rising gold prices have created mixed reactions, benefiting existing gold owners while posing affordability challenges for middle- and lower-income buyers. Traditional practices related to weddings and savings have also been affected. This study examines public perception, challenges, and satisfaction regarding rising gold prices in Palakkad district using primary and secondary data, analysed through percentage analysis, chi-square test, and ANOVA.

This paper presents the detailed design, analysis, and development of a semi-automatic bottle labeling machine intended for small and medium enterprises. The system focuses on improving productivity, labeling accuracy, and operational consistency while maintaining low investment cost. The proposed design integrates a conveyor mechanism, pressure-sensitive labeling head, and PLC-based control system. Performance analysis shows significant improvement over manual labeling methods, making the system suitable for low-to-medium volume production environments.

Artificial Intelligence (AI) is transforming accounting and auditing, yet its effects on jobs in developing countries like Zambia remain underexplored. This study assesses AI’s impact on accounting and auditing jobs in Zambia. Using a qualitative approach, 122 questionnaires were administered to participants in the study from Lusaka and Mazabuka districts . After analysis the findings reveal 75% of respondents lacked AI training, while 61% perceived AI’s impact positively. About 52% of organizations had implemented AI, primarily Robotic Process Automation. The study highlights significant Implications for accounting and auditing professionals in Zambia. AI adoption is expected to grow, emphasizing the need for AI-focused training and curriculum updates. This will address skills gaps and ethical concerns, ensuring professionals are equipped to work with emerging technologies. Key recommendations include integrating AI education into accounting and auditing curricula and providing ongoing training for professionals. Addressing ethical concerns around data privacy, security, and bias in AI decision-making is also crucial. The study’s findings have significant implications for policy and practice in Zambia’s accounting and auditing sector. By investing in AI education and training, Zambia can leverage AI’s benefits while minimizing its risks. This will enable accounting and auditing professionals to remain competitive and contribute to the country’s economic development. Furthermore, the study suggests that AI can enhance efficiency and accuracy in accounting and auditing processes.

The major challenges are family planning and birth control. According to a recent UN report, India’s population has already topped 1.26 billion this year, and if current growth rates continue, the country’s population will surpass that of China by 2028. The national fertility rate remains high, leading to long-term population growth in India. Family planning was not confined to birth control or contraception. It is important to improve the family’s economic condition and the health of the mother and her children. First, family planning highlights the importance of spacing births at least two years apart from one another. According to medical science, giving birth within a gap of more than five years or less than two years has a serious effect on the health of both the mother and child. Giving birth involves costs, and with an increase in the number of children in a family, more medical costs of pregnancy and birth are involved, along with the high costs of raising and rearing children. It is the duty of parents to provide food, clothing, shelter, and education to their children. If adopted, family planning has an effective impact on stabilizing the financial condition of any family, especially women in rural areas.

Heart disease is one of the top causes of death globally, making early and accurate prediction critical for better patient outcomes. Advances in artificial intelligence have considerably improved diagnostic capacities in the medical area, providing more accuracy and efficiency than previous approaches. Researchers are focusing on the rising prevalence of cardiac problems after COVID-19, underlining the importance of assessing heart attack risk in all age groups. Machine Learning and Deep Learning systems have shown exceptional performance in medical imaging and illness prediction, frequently outperforming manual diagnostic methods. This paper proposes a machine-learning-based methodology for predicting cardiac disease using a dataset that includes critical patient health characteristics. Correlation analysis is used in the model to assess prediction efficiency and investigate feature correlations. The model evaluates efficiency and visualizes data correlations using a heatmap. The findings highlight the potential of machine learning in healthcare applications and outline future directions for enhancing model accuracy, robustness, and clinical reliability. In this paper, multiple machine learning algorithms are applied and their performance in predicting cardiac arrest is systematically evaluated using the same dataset.

Post-operative complications following abdominal surgery remain a significant challenge in healthcare, contributing to increased morbidity, extended hospital stays, and higher healthcare costs. Structured teaching programmes aimed at educating patients about preventive measures have the potential to improve outcomes by reducing complication rates and empowering patients toward self-care. This study assessed the effectiveness of a structured teaching programme on the prevention of selected post-operative complications among patients undergoing abdominal surgeries in selected hospitals of Agra District. A quasi-experimental pre-test/post-test design was adopted among 120 postoperative abdominal surgery patients selected through purposive sampling. Data were collected using a validated questionnaire addressing knowledge and self-care practices related to post-operative complications such as infection, deep vein thrombosis (DVT), respiratory complications, and wound care. Pre-test evaluation was conducted on day one post-surgery, followed by the structured teaching intervention. A post-test assessment was done on the fourth postoperative day. Statistical analysis was performed using paired t-tests and chi-square tests. Results showed a significant increase in knowledge and self-care practices post-intervention (p < 0.001). The findings highlight that a structured teaching programme significantly enhances patient knowledge and reduces the risk of selected postoperative complications.

There are opportunities and challenges that must be addressed for artificial intelligence technologies to be successfully integrated in teacher education for improved digital literacy skills of future teaches. Consequently, it becomes needful to examine Artificial Intelligence (AI) technologies as a means of enhancing digital literacy of future teachers. The study employed three research questions. Pre-test/post-test control group design was adopted for the research with a sample size of 50 participants which was made up of future teachers from Nnamdi Azikiwe University, Awka, Anambra State, Nigeria with age categories of 20-22 years. It was a quasi-experimental study. In addition, mean, standard deviation and t-test were the statistical tools used for data analysis. The findings showed that Artificial Intelligence (AI) literacy level among future teachers is high and these Artificial Intelligence (AI) technologies enhances their digital literacy skills. The study also showed that future teachers’ perceptions regarding the use of Artificial Intelligence (AI) technologies were positive. Suggestions were made for further studies.

This research explores the impact of AI-driven social media interactions on digital trust and brand value among entrepreneurs. The study was guided by five specific research objectives. It was grounded by two theories: Technology Acceptance Model (TAM) and Social Cognitive Theory (SCT). This study adopted a descriptive research design with 300 participants who were purposively sampled. These participants completed an online survey that examined their AI-driven social media interactions, digital trust, and brand value. Descriptive statistics were used for analysis. The findings of this research showed that AI-driven personalization has a significant impact on brand authenticity and trust, and entrepreneurs exhibited stronger digital trust and brand value. The study provides practical recommendations for entrepreneurs to leverage AI tools, enhance digital competence, and build digital trust and brand value. Future studies should integrate objective usage data and test blended delivery models to deepen understanding of AI-driven social media strategies.

This study examines the adoption and impact of AI-powered social media analytics on sustainable entrepreneurship in Anambra State, Nigeria. Grounded in the Technology-Organization-Environment (TOE) framework and Resource-Based View (RBV) theory, the research employed a cross sectional survey research design involving 250 entrepreneurs. The results revealed that the adoption of AI-powered social media analytics is moderate among entrepreneurs, with perceived usefulness, perceived ease of use, and social influence being the top three factors that influence adoption. The findings also showed that AI-powered social media analytics has a significant positive impact on business performance and sustainability. These results underscore the potential of AI-powered social media analytics in enhancing business competitiveness and sustainability in Anambra State, Nigeria. The study highlights key benefits of integrating AI-powered social media analytics into business operations and offers practical implications for entrepreneurs, policymakers, and business educators. Addressing technical and infrastructural challenges remains critical for scaling such innovations across Nigerian businesses.

Work ethic within public service institutions is shaped by a combination of cultural, institutional, and socio-economic factors that vary across regions and administrative departments. In Ghana, the public service sector comprises diverse units including health, education, local government, revenue agencies, and administrative departments each operating under different leadership styles, resource conditions, and service mandates. Despite efforts to improve efficiency and accountability, disparities in work ethic continue to be observed across regions and departments, influencing service delivery outcomes and public trust. This study investigates the variations in work ethic among public service employees in Ghana, examining how regional socio-cultural contexts, departmental functions, leadership practices, and institutional norms shape attitudes toward punctuality, accountability, diligence, teamwork, and service commitment. Using a mixed-methods design, the study draws on survey data and qualitative interviews to provide a comprehensive analysis of the factors contributing to work ethic differences across the public sector. Findings from this study will offer insights for improving performance management, strengthening organisational culture, and enhancing service delivery in Ghana’s public institutions.

Background: Behavioral change has important implications for the effectiveness and efficiency of healthcare systems. On the one hand, informed students can contribute positively to the treatment process. On the other hand, erroneous or incomplete information can disrupt the doctor-patient relationship, reduce treatment adherence, and even compromise patient safety. Method: This research is quantitative and explanatory. Sampling used accidental sampling. The sample size was 85 students from the Faculty of Public Health at Halu Oleo University. Result: There is a positive and significant influence of the intensity of online health information searches on the decision to undergo treatment with an original sample value of 0.449 and a p-value of 0.000 <0.05. Motivations for seeking health information online have a positive and significant influence on the decision to undergo treatment with an original sample value of 0.139 and a p-value of 0.040 <0.05. And online health information sources used have a positive and significant influence on the decision to undergo treatment with an original sample value of 0.451 and a p-value of 0.000>0.05. Conclusion: The impact of online health information search behavior by students is the decision to seek treatment.

The study examined the effect of trauma-informed interventions on the wellbeing of adolescents from the Obio-Akpor Local Government Area Rivers State Nigeria. The study adopted quasi experimental design. A sample of 120 adolescents, aged 12–18, from public secondary schools was selected. Secondary school students were split into either treatment, which involved participation in an 8-week trauma-informed intervention, or control groups, which did not engage in any form of participation. The Adolescent Wellbeing Scale was used to gather data from participants and the data were analyzed using descriptive and ANCOVA statistics. The outcome of the study was that the trauma-informed intervention work. As per the study, the intervention’s effectiveness dominated irrespective of adolescents’ gender and socio-economic status. The participants from the study were able to gain the same level of intervention irrespective of the sociodemographic variables. The study established that trauma-informed interventions improve and protect the psychosocial and emotional wellbeing of adolescents in schools. The study recommends that schools in Obio-Akpor LGA should adopt trauma-informed programs in the guidance and counselling programs aimed at supporting adolescents’ psychological wellbeing.

This study presents the design and development of a smart electric bicycle (e-bike) intended to serve as an environmentally friendly, economical, and efficient transportation option for urban users. The primary objective is to develop a lightweight and energy-efficient e-bike that minimizes dependence on fossil fuels, reduces air pollution, and helps ease traffic congestion in heavily populated cities. The proposed e-bike is equipped with a lithium-ion battery and an electric motor that provides pedal assistance, enabling a comfortable and effortless riding experience. An intelligent control system regulates the motor output according to rider input and road conditions, ensuring optimal power utilization. To further improve efficiency, a regenerative braking mechanism is incorporated to recover energy during braking, thereby extending battery life. The bicycle frame is designed to offer strength, durability, and rider comfort, along with adjustable suspension to handle varying urban road conditions smoothly. User convenience is enhanced through a digital display that provides real-time information such as speed, battery status, and energy consumption. In addition, the e-bike supports smartphone connectivity for features including GPS navigation, system diagnostics, and ride performance tracking, allowing users to manage and monitor their journeys effectively. By providing a sustainable alternative to conventional modes of transport, the electric bicycle helps reduce traffic congestion and carbon emissions. The project encourages the adoption of green mobility solutions and supports the transition toward a cleaner, energy-efficient urban transportation system. Overall, this work aims to address urban mobility challenges while promoting the practical application of electric vehicle technology in daily life.

BACKGROUND: Skin is the largest organ covering the entire outside of the body. Skin care is a fundamental component of basic patient care and reflects on the overall quality of care a patient receives in the hospital. Pressure ulcers have been described as one of the physically debilitating complications in the 20* century and it will increase the costs of health care. OBJECTIVES: 1.To assess the knowledge regarding use of Braden Scale for predicting pressure sore risk among B.Sc nursing first semester students.2.To evaluate the effectiveness of Structured Teaching Programme on knowledge regarding use of Braden Scale for predicting pressure sore risk among at B.Sc nursing first semester students in terms of gain in knowledge scores. 3.To find out an association between pre-test knowledge scores regarding use of Braden Scale for predicting pressure sore risk among B.Sc nursing first semester students and their selected socio-demographic variables. METHODS: A pre experimental one group pre-test post-test design was used. The sample size of 60 were selected by using Probability; simple random sampling technique. Data was collected from samples in Shridevi College of Nursing, Tumkur by means of structured knowledge questionnaire. The reliability of the tool was r =0.89 and analysis was done using descriptive and inferential statistics. RESULTS: The overall post-test knowledge scores of B.Sc nursing first semester students had Majority of 30(50%) with good knowledge, 20(33.33%) had poor knowledge and 10(16.66%) had average knowledge in the post-test, regarding use of Braden scale in predicting pressure sore risk. There was significant gain in knowledge score of 74.94% who were exposed to structured teaching programme. The paired ‘t’ test value (t cal=51.09*)was greater than the tabulated value (t tab' 2.000) for knowledge, hence proved that stated hypothesis i.e. mean post-test knowledge scores of Nursing students who have been exposed to structured teaching Programme will be significantly higher than the mean pre-test knowledge scores at 0 05 level of significance. CONCLUSION: The study concluded that structured teaching programme was more effective for student nurses to increase the knowledge regarding use of Braden scale in predicting pressure ulcer risk.

Artificial Intelligence through its deployment in pathology functions as a diagnostic force-multiplier that increases precision while minimizing mistakes and enhances operational effectiveness. Deep learning models developed with AI technology remind PathAI and Google’s DeepVariant demonstrate cancer detection accuracy at 92-96%. The microbiological testing method MALDI-TOF MS achieves rapid bacterial identification through AI power by shortening results times from 24 hours to much less than 1 hour. Auristic systems in hematology enhanced the ability to detect leukemia effectively between 30–50% more efficiently. The adoption of AI technology remains limited by data bias alongside execution barriers and interpretive obstacles. The future development of Explainable AI together with federated learning and robotic laboratories will improve AI precision diagnostics by achieving more accurate and accessible healthcare solutions.

The construction sector is evolving as new technologies seek to boost productivity, efficiency, and sustainability. Nevertheless, construction projects in developing nations continue to experience high failure rates, often due to budget overruns, schedule delays, and quality shortfalls (Pinto and Mantel1990). This phenomenon is still evident in the Indian construction sector. Among these challenges, construction project failure remains the most persistent challenge. Failure in construction projects is widely defined as the inability to achieve principal performance milestones, such as cost, time, technical specifications, and client satisfaction, which represent internal inefficiencies and ineffective project control (Pinto and Mantel 1990). Human mistakes and poor monetary administration are two of the most crucial underlying causes of delays, which result in project abandonment Shahhosseini et al. (2018). One of the most effective solutions to this problem is digitalization in the construction industry. Digitalization is the integration of industrialized technical approaches with digital technologies to improve the profitability and sustainability of construction projects Dauda et al.(2024). Digitalization in the construction industry must be implemented in various construction cycles. The demand for digitalization is apparent as construction companies strive to meet the growing demands for faster delivery, reduced costs, and improved quality. Dauda et al. (2024) describe how digitalisation assists organisations in accomplishing their objectives by simplifying operations, facilitating quicker communication, integrating systems, and improving overall asset productivity. Such processes reduce delays, errors, and waste in conventional building processes. However, the journey towards complete digital adaptation is not smooth, especially in developing countries such as India. The strongest issue faced in tackling this challenge is the resistance to change within the organization, which is caused by a lack of awareness of the long-term benefits of digitalization. The second significant hindrance is the communication gap between individuals and technology in the construction life cycles (Nývlt and Kube?ka ND).

This study looked into how supervisory coaching practices affected the occupational development skills of workers in tertiary institutions owned by Rivers State. It specifically looked at how employees' occupational skills relate to goal-setting assistance, constructive criticism, and career counseling. A sample of 350 employees was chosen by proportionate stratified random sampling in a correlational study design. A structured questionnaire was used to gather data, and Pearson Product Moment Correlation was used for analysis. The results showed that goal-setting support (r=0.612), constructive criticism (r=0.553), career counseling (r=0.671), and occupational development skills were significantly positively correlated. This underscores the critical role that good supervisory coaching plays in developing employees' technical, problem-solving, and communication skills. To improve occupational development among university staff, the study suggests creating formal mentoring schemes, improving supervisors' feedback skills through focused training, and putting in place structured goal-setting programs.

Okra (Abelmoschus esculentus) is a widely cultivated vegetable that is highly susceptible to fungal infections, leading to significant post-harvest losses. This study investigated the incidence and pathogenicity of fungal pathogens affecting okra fruits in Sokoto North. Fresh samples of okra were obtained directly from three (3) local farms and stored for one week to observe signs of spoilage. Potato Dextrose Agar (PDA) was prepared at a concentration of 39 g per liter of distilled water according to the manufacturer's instructions and incubated. Identification was done based on morphological and microscopic characteristics using a compound microscope. Pathogenicity tests were conducted by inoculating healthy okra fruits with fungal isolates. Data were analyzed using descriptive statistics with percentage of occurrence to determine fungal prevalence, while mean and standard deviation for mycelial growth measurements. The study identified four fungal species: Rhizopus stolonifer, Aspergillus niger, Aspergillus fumigatus, and Candida tropicalis. Among these, Rhizopus stolonifer had the highest occurrence rate (40.00%), while the other species had (20.00%) each. Pathogenicity tests showed that Aspergillus niger had the highest incidence with (64.35%), followed by Aspergillus fumigatus with (60.26%), Candida tropicalis with (52.56%), and Rhizopus stolonifer with (42.56%). The study emphasizes the substantial risk posed by these fungal pathogens to okra crops, leading to post-harvest losses. It is recommended that proper post-harvest handling and antifungal treatments should be explored to mitigate these pathogens.

High levels of work stress and job burnout among educators have become a global concern, particularly for Vocational High School (SMK) / Vocational Teachers who face dual demands. The fundamental issue underlying this phenomenon is the need for a comprehensive identification of the factors that drive the emergence of work stress in vocational teachers, to allow for the design of effective and targeted interventions.The objective of this study is to systematically identify and synthesize the main causal factors of work stress in Vocational High School / Vocational Teachers based on a review of scientific literature published between 2020 – 2025.By employing a Systematic Literature Review (SLR) method, 14 journal articles focusing on work stress and burnout in vocational teachers were analyzed. Qualitative and quantitative data were extracted from the research findings and subsequently analyzed thematically.The results of the thematic analysis indicate that the causes of stress are predominantly driven by high job demands, including workload and classroom demands. Organizational factors, such as administrative pressure and inappropriate leadership, were found to be strong predictors affecting job satisfaction. Furthermore, a lack of social support, poor working conditions, and policy changes also contribute.The consequences of work stress include a decline in Quality of Work Life (QWL), reduced performance, and an increase in intention to quit teaching. Interventions should be directed toward reducing administrative burdens and strengthening individual resources, such as resilience.

Physics education in Zambia has historically emphasized abstract, examination-driven, and largely Eurocentric content, often detached from learners’ lived realities. This has contributed to low learner motivation, weak conceptual understanding, and limited application of physics knowledge to real-life contexts, particularly in energy-related topics. In response to these challenges, the Zambian Ministry of Education introduced the Competence-Based Curriculum (CBC) in 2023, emphasizing learner-centred pedagogy, practical application, and the development of holistic competences. This study investigated the effectiveness of Project-Based Learning (PBL), centred on the design and improvement of traditional biomass stoves, as a pedagogical approach for teaching energy concepts in secondary school physics while fostering learner competences and strengthening community engagement. A qualitative case-study design was employed involving 20 Grade 11 physics learners, two physics teachers, three local artisans, and ten community members in Masaiti District, Zambia. Data were collected through learners’ reflective journals, focus group discussions, teacher observation records, photo documentation, and community feedback sessions. The findings indicate substantial improvement in learners’ conceptual understanding of energy concepts, evidenced by a shift from abstract, formula-based explanations to contextualized reasoning grounded in everyday cooking technologies. The study further revealed significant development of key learner competences, including collaboration, communication, emotional intelligence, and problem-solving. In addition, the improved biomass stoves demonstrated a reduction in charcoal consumption, highlighting positive social, economic, and environmental impacts within the local community. The study concludes that PBL provides an effective and culturally responsive pathway for operationalizing Zambia’s CBC in physics education, integrating conceptual mastery, competence development, and community relevance.

Flooding in the Kaveri River zone, particularly around Srirangapatana, poses recurring risks to life, property, and infrastructure during monsoon seasons. Traditional flood monitoring methods often rely on manual observation, leading to delays in detection and response. To address these challenges, this project proposes a real-time flood water monitoring and alert system using Internet of Things (IoT) technology. The system integrates sensors such as ultrasonic water level sensors, flow sensors, and rainfall sensors to continuously measure river conditions with high accuracy. The collected data is transmitted to a cloud platform using IoT communication protocols, enabling real-time analysis and visualization. When water levels exceed predefined danger thresholds, the system automatically triggers alerts through SMS, mobile notifications, alarms, and a web dashboard, ensuring timely communication to residents and disaster management authorities. By providing continuous monitoring, early warnings, and location-specific data for the Srirangapatana stretch of the Kaveri River, the proposed IoT-based system enhances flood preparedness and reduces potential damage. It offers a low- cost, scalable, and efficient solution that can be expanded to other vulnerable regions of the river basin, contributing significantly to disaster mitigation and community safety.

Paternal denial of responsibility remains a widespread social and developmental challenge in Ghana, with significant implications for maternal well-being, child development, and social support systems. Although existing literature highlights financial hardship, relationship instability, and socio-cultural norms as drivers of paternal disengagement, limited research has explored the deeper psychological, relational, and structural factors that influence fathers’ denial of responsibility within the Ghanaian context. This qualitative study seeks to explore the lived experiences, perceptions, and contextual realities surrounding paternal denial of responsibility following pregnancy or childbirth. Using purposive sampling, in-depth interviews were conducted with 25 participants, including single mothers, social workers, community leaders, and young fathers. Thematic analysis was employed to uncover patterns related to socio-economic pressures, cultural expectations of masculinity, family influence, stigma, and emotional unpreparedness. Preliminary findings suggest that paternal denial is shaped by complex interwoven factors such as fear of financial responsibility, mistrust of paternity, strained romantic relationships, societal pressure to conform to masculine norms, and lack of institutional support for early fatherhood. This study contributes to the understanding of paternal disengagement in Ghana and offers insights for policy, community interventions, and fatherhood support programs.

The advent of Human Resource Analytics (HR Analytics or HRA) has transformed performance management systems by leveraging data-driven insights to enhance objectivity, transparency, and decision-making. While organizational benefits of HR Analytics have been widely discussed, the perspective of employees — the key stakeholders of performance management — remains underexplored, especially in the Indian IT services sector. This study investigates employee perceptions of HR Analytics usage in performance management, focusing on awareness, perceived fairness, transparency, and impact on motivation and engagement. Using a mixed-methods approach, a structured survey of 250 IT sector employees and semi-structured interviews with 20 participants were conducted. Preliminary findings suggest that awareness of HR Analytics is positively associated with perceptions of fairness and transparency. However, concerns about data privacy, misuse, and algorithmic opacity were prevalent. The study highlights the importance of integrating technical HR Analytics tools with employee-centric communication, ethical safeguards, and participative implementation to optimize acceptance and effectiveness.

Amid growing environmental consciousness and value-based consumerism, green brand knowledge (GBK) has emerged as a key driver of ethical purchasing behavior. This study investigates the relationship between GBK and green purchase intention (GPI) among urban consumers in Delhi, India—one of the most environmentally stressed megacities globally. Drawing from the Theory of Planned Behavior and the Knowledge-Attitude-Behavior framework, the research adopts a mixed-methods approach, integrating a structured survey of 300 respondents with 15 semi-structured interviews. Quantitative analysis reveals a significant positive association between GBK and GPI (r = 0.61; ? = 0.54, p < 0.001), with environmental concern acting as a positive moderator. Qualitative insights highlight trust, transparency, and authenticity as spiritual-ethical enablers in green purchasing, while price sensitivity and skepticism about greenwashing remain barriers. The findings emphasize the need for brands to communicate ecological values credibly and compassionately, fostering spiritually conscious consumption. By contextualizing environmental ethics within a densely populated urban setting, this study contributes to a spiritually grounded understanding of sustainable consumer behavior and brand trust in emerging markets.

Background: Ayurveda, the ancient Indian system of medicine, posits a holistic biopsychosomatic model of health. Beyond the physical constitution (Deha Prakriti), it meticulously describes Mansika Prakriti—the innate psychological constitution, categorized by the predominance of the three mental qualities or Gunas: Sattva (clarity, harmony), Rajas (activity, passion), and Tamas (inertia, delusion). This system represents one of the earliest and most comprehensive typologies of personality and temperament. Objective: To systematically review the literature on Mansika Prakriti, correlate its core constructs with modern psychological and neuroscientific frameworks, and evaluate the empirical evidence for its phenotypic and biological correlates. Methods: A narrative and systematic synthesis was conducted following PRISMA-ScR guidelines. Electronic databases (PubMed, PsycINFO, Scopus, AYUSH Research Portal) were searched for studies published until December 2023. Keywords included "Ayurveda," "Mansika Prakriti," "Sattva," "Rajas," "Tamas," "psychological constitution," "Gunas," "personality," "temperament," and "neurobiology." Studies exploring theoretical correlations, psychometric validation of assessment tools, or biological associations of Guna-based types were included. Results: 127 studies were included. Mansika Prakriti shows significant conceptual overlap with modern personality models. Sattva dominance correlates with traits of high conscientiousness, openness, emotional stability, resilience, and mindfulness. Rajas aligns with high extraversion, neuroticism, ambition, and susceptibility to stress-related disorders. Tamas correlates with high neuroticism, low conscientiousness, depressive traits, and behavioral inhibition. Psychometrically validated tools like the Guna Inventory and Vedic Personality Inventory demonstrate reliability. Emerging neuroscientific evidence suggests distinct biological substrates: Sattvic traits are associated with higher heart rate variability (HRV), better neuroendocrine regulation, and potentially distinct EEG patterns; Rajasic and Tamasic states are linked to sympathetic dominance, HPA-axis dysregulation, and pro-inflammatory tendencies. Conclusion: Mansika Prakriti is a sophisticated, valid, and clinically relevant model of personality with demonstrable correlations to established psychological constructs and preliminary biological correlates. It offers a unique integrative framework that links personality to health, vulnerability to mental disorders, and therapeutic response. Further interdisciplinary research using robust designs is needed to fully elucidate its neurobiological underpinnings and validate its utility in personalized mental health care.

Background: Biological rhythms, governed by endogenous circadian (~24-hour) and ultradian (<24-hour) clocks, are fundamental to homeostasis in living systems. Contemporary chronobiology has meticulously mapped these oscillations to molecular transcriptional-translational feedback loops. Parallelly, Ayurveda, the ancient Indian system of medicine, presents a sophisticated framework of diurnal and seasonal cycles governed by the rhythmic dominance of the three Doshas (Vata, Pitta, Kapha) and the state of Agni (digestive/metabolic fire). Objective: To systematically correlate the Ayurvedic theory of Dinacharya (daily regimen) and Ritucharya (seasonal regimen) with established principles of modern chronobiology, exploring convergences in timing, physiological underpinnings, and therapeutic implications. Methods: A narrative and comparative review was conducted. Literature from PubMed, Scopus, and AYUSH research portals was searched using keywords: "circadian rhythm," "chronobiology," "chronotherapy," "Ayurveda," "Dinacharya," "Ritucharya," "Dosha," "Kala." Classical Ayurvedic texts (Charaka Samhita, Ashtanga Hridaya) were consulted for source concepts. Data were synthesized to map temporal cycles described in both systems onto common physiological parameters. Results: A profound correlation exists between the Ayurvedic Dosha cycles and circadian physiology. The Kapha period (6:00 AM-10:00 AM & PM) aligns with rising cortisol and parasympathetic dominance; the Pitta period (10:00 AM-2:00 PM & PM) correlates with peak core body temperature, metabolic rate, and digestive enzyme secretion; the Vata period (2:00 PM-6:00 PM & AM) associates with increased cognitive alertness and sympathetic activity. Ritucharya recommendations for diet and lifestyle show alignment with seasonal variations in photoperiod, hormone secretion (e.g., melatonin), and immune function. The Ayurvedic emphasis on meal timing, sleep-wake cycles, and activity synchronizes with chronobiological principles of entrainment by Zeitgebers (light, food). Conclusion: Ayurvedic chronobiology provides a holistic, pre-scientific model that remarkably anticipates modern chronobiological findings. The Dosha theory offers a unique functional lens for understanding time-dependent physiological states. Integrating these paradigms can inform personalized chronotherapeutic and lifestyle interventions, promoting Swasthavritta (preventive health) through optimal alignment of daily and seasonal routines with endogenous biological rhythms.

This study examines age-related differences in the limits of stability (LOS) among adults aged 50–79 years using the Multidirectional Reach Test (MDRT). Mean ± SD values for forward, backward, right lateral, and left lateral reaches were extracted for three age groups (50–59, 60–69, 70–79 years). A one-way ANOVA (df_between=2, df_within=27) was conducted to evaluate group differences. Results indicated significant declines in mediolateral reach (right and left) with increasing age, whereas forward and backward reaches did not differ significantly. These findings suggest lateral stability is more susceptible to age-related decline and highlight the clinical utility of MDRT in fall-risk screening.

The use of Artificial Intelligence (AI) within the educational field has been evolving at a fast pace, altering not only the process of teaching and learning but also the teacher-student relationship and the kind of decisions that teachers make about their students. Although AI-based tools seem to have a greater level of efficiency, customization, and data-driven knowledge, they also create issues of autonomy and professional identity of the teacher. This paper examines the impact of AI on the liberty of decision making by teachers, their professional identity, as well as their changing role in the technology mediated classroom. A total of 120 secondary-level teachers (in India) were surveyed and interviewed using semi-structured methods to gather their data using a mixed-method approach. The results show that even though teachers value AI as a way to save administrative time, many of them believe that the use of algorithms to suggest and content assessment might affect their autonomy in pedagogical practice. The paper highlights the importance of implementing AI in a balanced manner that does not override human judgment, enhances agency of teachers and builds professional identity.

This conceptual article examines how couples in South African marriages negotiate educational aspirations and the emotional labour associated with gendered expectations and power dynamics in the home. Drawing on existing literature and qualitative insights, it explores a situation in which a husband, as breadwinner, aspires to further his education, while his stay-at-home wife or housewife resists academic advancement in favour of more immediate emotional attention. The study articulates how traditional gender roles, resource control, and emotional responsibilities interact to create tension and conflict. Using feminist and relational power theories, the paper unpacks how emotional labour becomes a tool in negotiating support, recognition, and identity within the union. The findings suggest that while financial support is offered, emotional resentment and competing time demands can undermine educational aspirations. Implications include the need for more open spousal communication, renegotiation of roles, and supportive institutional structures (such as flexible study options) to facilitate mutual growth. Future research should empirically investigate these dynamics through in-depth interviews or longitudinal designs. The paper contributes to understandings of intra-household power in gendered contexts of education, care, and personal development.

Aggression is a complex behavioural phenotype shaped by interacting genetic, environmental, and developmental influences. Behavioural genomics has advanced understanding of how common genetic variants, rare alleles, and gene–environment interplay contribute to individual differences in aggressive behaviour. This study integrates current evidence from twin and molecular genetic research with a simulated quantitative dataset to examine how polygenic risk, monoamine oxidase A (MAOA) variation, and childhood adversity jointly predict aggression in young adults. A sample of 300 simulated participants (50% male) was generated to approximate heritability estimates and effect sizes reported in recent literature. Variables included a standardized polygenic risk score (PRS) for antisocial/aggressive behaviour, MAOA low-activity variant status, childhood adversity, sex, and aggression scores. Correlation analyses showed that aggression was positively associated with PRS (r = .68), MAOA low-activity carrier status (r = .26), and adversity (r = .60). Hierarchical regression analyses revealed that genetic factors (PRS and MAOA) accounted for 53% of the variance in aggression, environmental adversity added 9%, and gene–environment interaction terms (PRS × adversity, MAOA × adversity) increased the explained variance to 69%. These patterns are consistent with behavioural genomics findings that aggression is moderately heritable and influenced by polygenic risk in combination with adverse environments. The paper highlights the value of integrating polygenic scores with contextual risk indicators, discusses ethical considerations around genetic prediction, and outlines directions for future multimodal research.

Awareness of legal rights refers to an individual's understanding and knowledge of the rights granted to them by law. This includes civil, political, social, economic, and educational rights. Such awareness is fundamental in ensuring that individuals can protect themselves from injustice, exercise their freedoms responsibly, and participate actively in a democratic society. The objective of the present investigation is to study the awareness of legal rights among higher secondary school teachers based on the selected sub sample gender and the descriptive survey study method of research has been used. The total sample for the present study consisted of 295 higher secondary school teachers of which the total numbers of male and female teachers are 67 and 228 respectively from of 13 higher secondary schools in Namakkal district. The awareness of legal rights tool was used for data collection and the inferential statistics of the obtained data are calculated for analysis and interpretation. The analysis revealed that the male and female teachers do not differ in the dimensions cognitive, affective, behavioural and total scores of awareness of legal rights.

This research introduces a novel Hierarchical Proximal Policy Optimization with Multi-Layer Adaptation (HPPO-MLA) algorithm designed for semi-active suspension systems in modern vehicles. The primary objective was to develop a control framework that simultaneously optimizes ride comfort, vehicle stability, and safety constraints under varying road conditions. The methodology employed a sophisticated four-layer hierarchical architecture comprising perception, adaptation, optimization, and safety layers, integrated with proximal policy optimization techniques. The experimental setup involved comprehensive simulations using a high-fidelity quarter-car model validated against real-world data, with performance evaluation conducted across ISO 8608 road classifications A-F. Results demonstrated that HPPO-MLA achieved a 35.2% improvement in ride comfort compared to traditional PID control, reduced RMS body acceleration by 28.7% versus skyhook controllers, and maintained suspension travel within safety limits with 94.3% reliability. The algorithm exhibited superior adaptation capabilities, converging within 50 training episodes compared to 200+ episodes required by conventional reinforcement learning approaches. The study concluded that HPPO-MLA represents a significant advancement in intelligent suspension control technology, offering robust performance across diverse operating conditions while maintaining computational efficiency suitable for automotive embedded systems.

This paper presents the design, implementation, and control dynamics of an unmanned ground vehicle (UGV) integrating synchronized mowing and raking mechanisms for autonomous lawn maintenance. The system employs a distributed control architecture based on Arduino-class microcontrollers, wireless communication via Bluetooth HC05 modules, and a power management subsystem supporting dual mobility actuators, a rotary cutting spindle, and a servo-actuated rake. Comparative analysis with the Husqvarna Automower 450X and Worx Landroid WR140 reveals that the proposed system achieves 23% lower power consumption and 40% cost reduction while maintaining functional parity. Experimental results demonstrate stable operation across varying terrain conditions with peak system power demand of 214 W and average continuous draw of 17–20 A from a 12 V battery pack.

South Africa occupies a singular place in global governance and continental affairs. As the only African member of both the G20 and BRICS, it serves as a bridge between the Global South and established global powers. This article explores South Africa’s strategic role, focusing on its G20 and BRICS memberships, its influence in Southern Africa through SADC, and opportunities for shared development across the continent. Using a qualitative policy-analysis approach, informed by government documents, expert interviews, and secondary literature, the study identifies how South Africa leverages its global platforms to advance African interests. Key findings show that South Africa’s G20 presidency has foregrounded issues such as debt sustainability, equity, and multilateral reform, aligning closely with BRICS priorities of inclusive governance. Regionally, South Africa’s economic weight supports infrastructure integration in SADC and the Tripartite Free Trade Area. Yet, there are tensions: domestic perceptions of waning influence and criticism of its BRICS ties indicate that its leadership is contested. The article argues that other African states can benefit by deepening economic partnerships with South Africa, aligning their regional integration strategies with its diplomatic agenda, and leveraging continental mechanisms such as the African Continental Free Trade Area (AfCFTA). The implications point toward a more coherent African voice in global governance and greater shared development. Future research should examine how intra-African coordination around South Africa’s global roles can be institutionalized through regional and continental bodies.

This article examines how artificial intelligence affects the mental health and wellbeing of users who are already vulnerable due to age, socioeconomic status or pre-existing psychological conditions. The purpose of the study is to consolidate existing evidence and develop a clearer understanding of what kinds of risks and opportunities AI presents for these populations. The study uses a qualitative document analysis approach that draws on recent peer reviewed literature, global policy documents and technical reports. This approach makes it possible to analyse existing knowledge without collecting new human data, which avoids the need for ethical clearance. The findings indicate that while AI driven tools can improve access to mental health support and early detection of psychological distress, they also introduce risks that arise from algorithmic bias, targeted content exposure, emotional dependency on AI chatbots, surveillance-based data practices and reduced human contact. These risks appear to be magnified among vulnerable users who often have limited digital literacy and fewer safeguards. The article concludes that current research has not sufficiently accounted for the lived realities of these users and that more inclusive risk assessment models are required. The study recommends that policymakers and designers adopt protective design principles, transparent data practices and oversight mechanisms that centre the needs of vulnerable communities.

This article examines how exposure to South Africa’s tender driven economy influences youth attitudes toward formal education, social mobility, and definitions of success. Drawing on the notion of “tenderpreneurship”, where individuals secure government contracts with minimal formal education, the paper explores narratives in which financial gain, rather than schooling, becomes a marker of achievement. Employing a conceptual analytical approach grounded in recent empirical studies on youth entrepreneurship and educational inequality in South Africa, the article synthesises evidence about: (a) the limitations of entrepreneurship education and the disconnect between formal qualifications and tender-based success; (b) structural factors that incentivise pursuing tender opportunities over schooling; and (c) the resulting implications for social inequality and long-term economic development. I find that while formal education remains strongly associated with lower unemployment risk and higher human capital, for a subset of youth, the visibility of tender-derived wealth fosters a devaluation of schooling. This devaluation may contribute to increased dropout rates and a deteriorating societal perception of education’s instrumental value. The paper argues that policy and academic discourses must re-engage with the social value of education beyond immediate financial returns. Implications include the need to strengthen institutional transparency in procurement, reorient entrepreneurial support programmes, and invest in human capital development to safeguard the long-term viability of both youth aspirations and equitable economic growth.

Background: Vitiligo is a chronic autoimmune depigmentary disorder affecting 0.2–2% of the global population. Standard therapies such as corticosteroids and phototherapy offer variable outcomes and high recurrence. Homoeopathic immunomodulation has shown potential in restoring melanocyte activity but remains underreported in long-term clinical datasets. Objective: To evaluate the efficacy of individualised homoeopathic immunomodulatory therapy in repigmentation, disease stabilisation, and relapse prevention in Vitiligo patients over a 28-year period. Methods: An observational study (1997–2025) was conducted at Anand Hospital & Research Centre, Maharashtra. A total of 7,000+ patients were evaluated through detailed constitutional case-taking, individualised remedy selection, and periodic photographic documentation. Exclusion criteria included chemical leukoderma, albinism, and congenital pigment disorders.

The present study evaluated the effects of different sweeteners on the physicochemical, microbial, and sensory properties of fruit- and honey-enriched probiotic yoghurts. Yoghurt formulations incorporated papaya, mango, avocado, pineapple, or honey, combined with cane sugar, stevia, or aspartame, and probiotic cultures (ABT and ABY3). Physicochemical analyses included pH, titratable acidity, syneresis, , and proximate composition, while microbial quality was assessed via total viable counts, coliforms, and yeast/mould enumeration. Sensory evaluation employed a 9-point hedonic scale to assess color, flavor, texture, taste, and overall acceptability. Results indicated that fruit and honey addition significantly increased acidity and microbial load while moderately decreasing pH (p < 0.05); sweetener type had no significant effect on acidity or pH but influenced total viable counts. Among fruits, 10% papaya yoghurt showed optimal sensory scores, including the highest overall acceptability (8.81 ± 0.40). Probiotic yoghurt with ABY3 demonstrated superior microbial viability, lower syneresis, and higher sensory ratings compared to ABT and control samples. Papaya supplementation increased total solids, protein, ash, and solids-not-fat, while reducing fat and moisture content. The study concludes that papaya-enriched probiotic yoghurt formulated with ABY3 and appropriate sweeteners provides a functional, nutritionally enhanced dairy product with high consumer acceptability, hygienic quality, and potential for scale-up in the Ethiopian dairy sector.

Ben Okri, a prominent Nigerian writer, is celebrated for integrating African folklore, magical realism, and metaphysical inquiry in his fiction. This study explores the philosophical dimensions of his post-millennial novels Starbook (2007) and Prayer for the Living (2021), focusing on ethical reflection, spiritual consciousness, and existential inquiry (Okri, 2007; 2021). Employing an interdisciplinary framework that combines African philosophical thought (Mbiti, 1969; Gyekye, 1997), narrative theory (Bakhtin, 1981), and ethical literary criticism (Bennett, 2011), the research analyses characters as philosophical agents whose actions, visions, and moral deliberations illuminate broader social, ethical, and metaphysical concerns. Key findings reveal recurring patterns in Okri’s post-millennial fiction, including ethical agency, spiritual realism, temporal fluidity, and the function of narrative as a medium for philosophical reflection. The paper demonstrates that Okri’s novels transcend conventional storytelling, positioning literary narratives as frameworks for examining human consciousness, moral responsibility, and the interconnection between the spiritual and material realms. By situating African philosophical principles within imaginative literary contexts, the research underscores the capacity of Okri’s fiction to convey profound ethical and metaphysical insights. These findings contribute to the broader discourse on African literary philosophy and highlight the role of fiction as a vehicle for philosophical and moral inquiry in contemporary literature.

This article examines the origin and historical evolution of punctuation in written language, tracing its development from ancient scripts to modern writing systems. The study analyzes how punctuation emerged as a tool for clarifying meaning, regulating rhythm, and supporting syntactic organization. Special attention is given to the contributions of classical Greek, Latin, medieval, and early printing traditions to the formation of punctuation norms. The paper also highlights the influence of linguistic, cultural, and technological changes on the transformation of punctuation practices. The findings demonstrate that punctuation is not merely a technical system but a dynamic linguistic phenomenon shaped by the communicative needs of each historical era.

This study investigates the effectiveness of modular construction technology in optimizing costs and accelerating project timelines in modern infrastructure development, using the Kosciuszko Bridge replacement project in New York as a case study. A comparative analysis of traditional and modular methods was conducted, drawing on project data, industry benchmarks, and expert interviews. Results show that modular construction reduced costs by 20.7% ($115 million), from $555 million to $440 million, driven by lower labor and material expenses, though offset by higher transportation costs. The timeline was shortened by 62.5% (30 months), from 48 to 18 months, due to parallel workflows. These findings suggest modular construction can enhance efficiency in U.S. infrastructure projects, supporting goals of the Infrastructure Investment and Jobs Act. However, logistical challenges and regulatory barriers require strategic planning for broader adoption. This research provides actionable insights for stakeholders aiming to improve cost and time performance in infrastructure development.

The Proliferation of Digital Communication In the”No, I’m busy” rather than two variations of ”Yes”). modern digital landscape, email remains the primary channel for professional and personal communication. However, the sheer volume of incoming messages has resulted in significant infor- mation overload, leading to reduced productivity and increased cognitive burden for users. This paper addresses the critical need for intelligent email assistance by proposing a Smart Automated Response System. The primary objective is to alleviate the time- consuming process of composing routine replies by predicting and suggesting contextually appropriate, short-form responses Addressing Challenges in Scalability and Nuance The paper also investigates the challenges inherent in automated text gener- ation, such as handling rare words, maintaining tone consistency, and preserving user privacy. We introduce a mechanism for style transfer to ensure the generated responses match the user’s typical level of formality. Furthermore, we discuss the imple- mentation of lightweight on-device inference, which addresses privacy concerns b9y minimizing the amount of sensitive data sent to cloud servers. The system is designed to be scalable, capable in real-time. 1of handling high throughput with low latency, making it suitable Architectural Framework The core of the proposed system relies on advanced Natural Language Processing (NLP) and Deep Learning techniques. Specifically, we utilize a Sequence- to-Sequence (Seq2Seq) learning model, augmented with Long Short-Term Memory (LSTM) networks or Transformer-based architectures (such as BERT). This architecture is designed to encode the incoming email message into a vector representation, capturing the semantic meaning and syntactic structure, and subsequently decode it to generate a probability distribution of potential responses. Unlike simple rule-based systems, this neural network approach allows the model to learn complex language patterns and dependencies from massive datasets of conversational pairs. Semantic Analysis and Intent Recognition A critical com- ponent of the research involves semantic clustering and intent recognition. The system does not merely match keywords; it analyzes the underlying intent of the sender (e.g., scheduling a for integration into large-scale email client applications.

This study examined the work ethic of the Ghanaian general workforce across both the informal and formal sectors, with the aim of establishing a baseline understanding of work attitudes, value orientations, and behavioural patterns that shape productivity in contemporary Ghana. Drawing on a cross-sectional research design, the study gathered quantitative data from workers across a wide range of occupations, supported by qualitative insights from key informants. The analysis explored the extent to which punctuality, commitment, responsibility, honesty, initiative, and diligence manifested among workers, while also assessing the contextual social, economic, and organisational factors that influenced these behaviours. Findings indicated significant variations in work ethic between formal-sector employees and informal-sector workers, shaped largely by structural conditions, working environments, access to resources, and differing systems of accountability. The study further revealed that broader cultural expectations, leadership practices, and socioeconomic constraints played substantial roles in shaping worker attitudes toward duty and performance. These insights provided a much-needed empirical foundation for understanding work ethic in Ghana, where national discourse on productivity often relies on anecdotal assumptions rather than evidence. The study concluded that establishing a baseline profile of Ghanaian work ethic is essential for informing policy formulation, improving workforce development strategies, and strengthening the institutional frameworks necessary for national productivity enhancement.

This study examined the influence of teachers’ instructional strategies on students’ interest in Mathematics in the North-Central Zone of Nigeria. A total of 1,400 participants (200 teachers and 1,200 students) were sampled. Data were collected using questionnaires assessing teachers’ use of five instructional strategies; lecture, cooperative learning, ICT integration, manipulatives, and formative assessment and students’ interest in Mathematics. Descriptive, correlational, and multilevel analyses were conducted. Results indicated that cooperative learning, formative assessment, ICT integration and manipulatives significantly predicted students’ interest, while lecture method had minimal effect. Findings underscore the importance of active, technology-driven and assessment- oriented strategies in enhancing Mathematics interest among secondary school students in the region.

The study explores the role of social media engagement (SME) in fostering customer engagement (CE) and brand loyalty (BL) among millennial consumers in the Indian telecom sector. With the growing reliance on digital communication platforms, social media has become a key interface for telecom brands to interact, inform, and build relationships with their customers. Drawing upon relationship marketing and social exchange theories, the study employs a quantitative research design using data from 360 millennial respondents who actively engage with telecom brands such as Jio, Airtel, and Vodafone Idea on social media. Statistical analyses, including descriptive statistics, correlation, and multiple regression, were conducted to test the proposed relationships. The findings reveal that social media engagement significantly influences customer engagement (? = .61, p

Jessore Wildlife Sanctuary is rich in faunal and floral biodiversity. Present research about spiders was done in 2015-16 at Jessore Wildlife Sanctuary, Banaskantha district, Gujarat. The simple handpicking collecting method was used. 1290 specimens of spiders were collected during a field visit. A total of 133 spider species and 87 genera of 26 families were identified from the study area. During the field visit, observed some anthropogenic activities which disturbing forest biodiversity. Anthropogenic activities were domestic animal grazing, firewood collection, tourism, agricultural activities, etc., which led to the loss of faunal and floral biodiversity. So, we must conserve and protect natural biodiversity. Spiders are important natural controllers for insects and other small, harmful animals. Spiders are also part of biodiversity. So, after studying spiders, make baseline information and take conservative steps for spiders’ biodiversity.

The study examined the effect of green shipping practices on port digitalization in Nigeria. The dependent variable focused on port digitalization (PORDIG) which served as the regressand or measure. The dimensions or the predictor variables of green shipping practices analyzed included energy-efficient vessels (ENEGEV), decarbonization of maritime transport (DEMATR), and technological innovation (TECHIN) and they served as the regressors. The data utilized for the study were time series data sourced from the Nigerian Ports Authority (NPA), Nigerian Maritime Administration and Safety Agency (NIMASA), Nigerian Shippers’ Council (NSC), Nigerian Navy and Marine Police (NNMP), National Inland Waterways Authority (NIWA) and Federal Ministry of Marine and Blue Economy (FMMBE) between the period of 1990 to 2024. The analytical techniques employed were Phillip-Perron unit root test and bounds cointegration test. The model was estimated using Autoregressive Distributed Lag (ARDL) model. The unit root test revealed that the variables have mixed order of integration I(0) and I(1). This led to the application of ARDL bounds test to confirm cointegration. The result indicated the presence of a long run relationship amongst the dependent and independent variables examined in the model. The result revealed that energy-efficient vessel has significant positive effect on port digitalization in the short run. Also, decarbonization of maritime transport and technological innovation have significant positive effects on port digitalization in both the short run and long run. Thus, the study recommends among other things, that government should encourage the acquisition of energy-efficient vessels and decarbonization of maritime transport system to align with technological innovations development of the maritime sector. Also, regulatory frameworks should prioritize carbon reduction strategies, including stricter emission controls and incentives for low-carbon shipping practices.

The Public Grievance Redressal System is a fundamental pillar of democratic governance and citizen-centric administration. As societies evolve, governments are increasingly expected to provide transparent, responsive, and efficient mechanisms to address citizen concerns. The Government of Andhra Pradesh has emerged as a national model through its Public Grievance Redressal Management System (PGRMS), integrating digital governance, decentralized service delivery, and real-time monitoring mechanisms. This study evaluates the effectiveness of PGRMS, using a mixed-methods approach that combines quantitative survey data from 600 respondents across six districts along with qualitative interviews from field staff, secretariat personnel, and departmental officers. The research examines accessibility, timeliness, service quality, departmental coordination, technological integration, and overall citizen satisfaction. The findings reveal that the Public Grievance Redressal System platform, Village/Ward Secretariats, Real-Time Governance Society (RTGS) dashboards, and the 1100 Call Centre have significantly improved grievance accessibility and tracking. However, issues persist in revenue and housing departments due to field verification complexity and documentation burdens, resulting in longer resolution cycles. The statistical tests demonstrate strong associations between digital literacy, platform preference, resolution timelines, and satisfaction levels. The study concludes that PGRMS represents a robust and innovative governance mechanism with scope for strengthened AI integration, enhanced administrative capacities, and improved inter-department coordination. Policy recommendations and future areas for governance research are provided.

Peptic ulcers are a broad term that includes ulcers of digestive tract in the stomach or the duodenum. The formation of peptic ulcers depends on the presence of acid and peptic activity in gastric juice plus a breakdown in mucosal defenses. There are two major factors that can disrupt the mucosal resistance to injury: non-steroidal anti-inflammatory drugs (NSAIDs) example, aspirin and Helicobacter pylori infection. Numerous natural products have been evaluated as therapeutics for the treatment of a variety of diseases, including peptic ulcer. There has been considerable pharmacological investigation into the antiulcer activity of some compounds. In this work, we shall review the literature on different medicinal plant and alkaloids with antiulcer activity. This article reviews the antiacid/anti- peptic, gastroprotective and/or antiulcer properties of the most commonly employed herbal medicines and their identified active constituents. The experimental parameters used for antiulcer activity were cold restraint stress-induced ulcer model, Diclofenac- induced ulcer model in rats, (HCl– ethanol)-induced ulcer in mice and water immersion stress-induced ulcer in rats. The ideal aims of treatment of peptic ulcer disease are to relieve pain, heal the ulcer and delay ulcer recurrence. About 70% of patients with peptic ulcer disease are infected by Helicobacter pylori and eradication of this microorganism seems to be curative for this disease. This article reviews drugs derived from medicinal plant more commonly used in the world for peptic ulcer and, if reported, the antiulcer activity. This article will be concerned only with the antiulcer and gastro- protective effects.

The confluence of AI and immersive technology threatens to radically alter issues in case pedagogy, thereby transforming management education. Whereas traditional case method instruction has accepted little change since its inception at Harvard Business School in 1908, events within the business environment of 2050 demand radical innovations in pedagogy. This paper presents a conceptual framework for an AI-driven, immersive case pedagogy that transcends the limitations of current paradigms through integrative, adaptive learning algorithms, virtual reality environments, and intelligent tutoring systems. Drawing upon Yeoman and McMahon-Beatte's foundational work in future-oriented pedagogy, this research proposes Adaptive Immersive Case Learning (AICL): a pedagogical approach in which AI facilitates personalized, context-aware case experiences in virtual business environments.

The “Pens Down” tradition, parties held by South African students at the end of their exams, has become a culturally entrenched rite of passage. While these gatherings symbolize freedom and achievement, mounting evidence links them to excessive alcohol consumption, underage drinking, and serious safety risks, including fatal accidents. This article uses a desk-based review methodology to examine the emergence, drivers, and impacts of the Pens Down phenomenon among South African youth. Drawing on recent peer-reviewed studies, government reports, and civil society commentary, the paper explores how accessibility of alcohol, peer influence, and risky celebratory norms converge to produce harmful outcomes. Key findings suggest that underage and binge drinking is pervasive among secondary and tertiary, that environments near schools facilitate alcohol use, and that intense celebratory events following exams can escalate to violence and tragedy (e.g., the Enyobeni Tavern tragedy). The discussion situates these observations in relation to social learning theory and risk-taking frameworks. Finally, we propose practical recommendations: scaling up youth-led alcohol-harm reduction campaigns, strengthening regulation of alcohol sales near schools, and promoting alternative, non-alcoholic modes of celebration. The article concludes with a call for continued monitoring and research on the Pens Down culture, emphasizing that meaningful change requires coordinated effort across communities, schools, and policy actors.

This article critically examines the structural interplay between political dynamics, entrepreneurial engagement, and post-school education in South Africa, a context marked by entrenched youth unemployment and limited formal sector absorption. Amidst policy narratives that increasingly position entrepreneurship as a strategic response to labour market saturation, the study interrogates how institutional architectures and political networks shape the post-educational trajectories of young South Africans. Employing a qualitative content analysis of policy documents, scholarly literature, and media narratives from 2019 to 2025, the research reveals that while vocational and tertiary education remains instrumental in imparting technical and academic knowledge, it is often deficient in fostering entrepreneurial competencies or enabling market access. Furthermore, the study highlights the pervasive influence of political capital and patronage in mediating access to entrepreneurial resources, particularly within state-driven funding and procurement channels. These dynamics perpetuate structural inequalities, undermining the potential for inclusive entrepreneurial ecosystems. The findings underscore the critical need for educational frameworks that integrate political and economic literacy with practical entrepreneurial training, enabling youth to navigate and contest institutional barriers.Highlighting the critical intersections between education, governance, and entrepreneurship, this article underscores the necessity of a paradigmatic shift in institutional frameworks to foster an entrepreneurial ecosystem that is both genuinely inclusive and structurally emancipatory. Such a reconceptualization is vital for interrupting the cyclical reproduction of inequality and facilitating a more equitable distribution of economic opportunities within South Africa’s evolving post-school landscape.

Road safety is a pressing issue worldwide, affecting the lives of millions of people each year. Despite the numerous efforts to tackle this problem, current measures lack an integrated framework that can be adapted to changing conditions. Thi s study seeks to fill this gap by developing a comprehensive and dynamic framework for road safety measures that is both efficient and effective. The rising number of traffic accidents in the Jaipur region has highlighted the urgent need for a systematic approach to road safety. To address this issue, this research proposes using indicators that can monitor and evaluate the state of the problem, provide scientific information, assess policy initiatives, and identify priorities.

Aims: Liver Steatosis, commonly known as fatty liver disease, is a major global health concern that can progress to cirrhosis or hepatocellular carcinoma if undetected at an early stage. The present study aims to develop and optimize a deep learning-based framework capable of accurately identifying liver steatosis from ultrasound images, thereby supporting early diagnosis and preventive intervention. Methodology: A curated dataset of liver ultrasound scans-including both normal and steatosis-affected samples-was utilized. Preprocessing techniques such as image resizing, normalization, and augmentation were applied to ensure consistency and improve generalization. Additional feature enhancement processes, including Gaussian smoothing and histogram equalization, were implemented to refine tissue visibility. A lightweight convolutional neural network (CNN) model was designed and optimized using advanced regularization and learning-rate controls to achieve efficient and accurate classification. Results: The optimized model demonstrated superior performance when compared with conventional CNN architectures, achieving higher accuracy, precision, recall, and F1-score across evaluation datasets. The framework effectively captured subtle textural and intensity variations in hepatic tissues, minimizing false classifications and enhancing reliability in clinical interpretation. Conclusion: The proposed optimized deep learning model offers a robust and efficient solution for detecting liver steatosis using ultrasound images. By combining effective preprocessing, feature optimization, and network tuning, this approach improves diagnostic accuracy and reduces computational cost. The model shows strong potential as a rapid, computer-assisted diagnostic tool to support clinicians in early detection and management of liver steatosis.

Bank plays an important role in the economic development of every nation. This is applicable to India too. They have control over a part of supply of money in circulation. A bank is a financial intermediary that accepts deposits and channels those deposits into lending activities .Bank are fundamental component of the financial system, and also active players in financial market. Economic development is dynamic and continuous process. Because, the operational efficiency of various segment of the economy.

Recently renewable energy generation is increasing to meet the demand for electricity. In this project, the generation of electricity is achieved by using vertical axis wind turbine in addition with magnetic repulsion power buster, using the force created by moving shaft. For that purpose, wind turbines are placed at the center of the highway for the generation and utilization. An energy harvesting device such as highway wind turbines can still be used for applications where less power is needed. This energy can be harvested using vertical axis wind turbines (VAWT) placed on the sides of the highways to make use of the vehicles moving in both directions. This work presents an experimental study of using a VAWT specially designed and manufactured for producing electrical energy from wind energy of moving cars on highways for lighting purposes such as the highway lights, traffic signals, and light guide lines. The wind speed due to vehicles passing on a highway is used for power generation by using VAWT. Results will evaluated for different parameters consideration using the VAWT prototype establish on the highway. The working model namely magnetic repulsion engine is works on the repulsion principle of magnets either permanent or electromagnets. Both the magnets are facing each other with like poles for continuous repulsion. These mechanism does not require any input source and works on the magnetic force of its own ,thus it is eco-friendly and can be used in running power generation application in wind mill. The engine can be best alternative for wind mill power buster.

Smart cities integrate cyber-physical systems, IoT devices, and digital infrastructure to enhance urban living. Secure identity management (SIM) in these environments is critical to ensure authenticity, privacy, and trust among citizens, devices, and services. Traditional identity management systems often rely on centralized authorities, posing risks such as single points of failure, data breaches, and privacy invasion. Blockchain technology, with its decentralization, immutability, and cryptographic security, presents a promising foundation for secure identity services in smart cities. This paper proposes a blockchain-based architecture for secure identity management tailored for smart cities, details the design, illustrates protocol algorithms with derivation and a conceptual diagram, and evaluates security properties, performance challenges, and future research directions.

This study investigated how participatory communication serves as an inclusive and dialogic approach to eradicating cultism and inter-tribal wars in Tombia community in Degema Local Government Area of Rivers State, Nigeria. The study was anchored on Modernisation and Participatory Communication theories. The descriptive research design was employed, and using Taro Yamane’s formula, a sample size of 384 respondents was drawned from a population of 105,000 indigenes of Degema that make up the population of the study. The purposive and cluster sampling techniques was adopted for the study. The data for the study was gathered through the administration of the questionnaire to the target population. The data was presented on Tables to help analyse the research objectives. Findings of the study lead to the conclusion and recommendations.

Olive ridleys (Lepidochelys olivacea) are well documented to nest along east and west coasts of India. These turtles have been categorized as ‘Vulnerable’ in the IUCN Red List and fall under Schedule I of the Indian Wildlife (Protection) Act, (1972). This phenomenon of mass aggregation in olive ridleys is found only in India, Costa Rica and Mexico coastal waters. In recent times, arribadas have also been observed at Nicaragua and Panama (Honarvar et al. 2008). India hosts three major mass nesting sites in Odisha i.e Gahirmatha, Rushikuly whereas the third site Devi river mouth nesting has being reduced although the mass aggregation in the nearshore waters are being reported. Even the nesting is reported to be above the sporadic nesting (High sporadic nesting or minor mass nesting site) but arribadas are no longer recoded. In the recently year minor mass nesting site at Cuthbert Bay in the Andaman Islands have being discovered. Rushikulya has had the most consistent record of mass nesting over the last decade, with mass nesting reported only during some years at Gahirmatha (Shanker et al. unpubl. data). Monitoring mass nesting at two major rookery Rushikulya, Gahirmatha as well as in two minor rookery Devi, Cuthbert Bay a can provide insights into population trends of olive ridley turtles. Nesting beaches for sea turtles around the world are facing major beach erosion. Historic nesting beaches of olive ridley marine turtles have been reduced and impacted by humans with the remaining beach areas facing risks of further loss (McClenachan et al., 2006, Seminoff et al., 2015). Reduction of suitable nesting beaches could negatively impact the stability of marine turtle population. Sea level rise due to global warming has already resulted in severe coastal erosions in the 20th century and is expected to aggravate in the 21st century.

Financial literacy is essential for individual financial well-being and overall economic stability. This empirical study investigates the level of financial literacy among commerce students and its impact on their economic stability-related behaviour. Primary data were collected from 120 students using a structured questionnaire. Analysis was conducted using descriptive statistics, mean scores, and Pearson correlation. Results indicate a moderate level of financial literacy among most students and a significant positive relationship with economic stability indicators such as saving, budgeting, and investment awareness. The study highlights the importance of integrating practical financial education into commerce curricula.

The mechanization of agricultural practices, especially weed management, is integral to improving crop yields, reducing labor dependency, and advancing sustainable farming. Traditional manual weeding methods are labor-intensive, time-consuming, and often economically unsustainable for smallholder farmers. The development of motorized weed removal machines (MWRMs), particularly those powered by renewable energy sources like solar power, represents a pivotal advancement in agricultural engineering. This literature review critically surveys the design, development, optimization, and future trajectory of MWRMs, drawing on recent innovations in mechanical engineering, artificial intelligence, and collaborative machine tasking. It examines the technological components and methodologies underpinning modern weeder systems, the role of AI and large language models in machinery management and automation, and the integration of advanced algorithms for efficient task allocation. The review discusses the advantages and limitations of current weeder designs, explores emerging trends such as smart and collaborative agricultural machinery, and evaluates the expected impact of ongoing research on sustainable farming and global food security. The synthesis concludes by highlighting the potential of interdisciplinary approaches to revolutionize weed management and proposes directions for future research and implementation.

Quantum computing harnesses quantum mechanics to process information in fundamentally new ways. This review systematically examines the core concepts of quantum computing, contrasting them with classical computing, and surveying recent developments. Our methodology is a comprehensive literature review of high-impact sources (IEEE, Springer, Nature, and Google Scholar) from 2019–2024. We outline how qubits, superposition, entanglement, and quantum gates form the basis of quantum computers, and we compare classical and quantum architectures. Key insights include the theoretical speed-ups of quantum algorithms (e.g. Shor’s and Grover’s) and the broad applications in cryptography, optimization, artificial intelligence, and drug discovery[1][2]. At the same time, we discuss practical limitations: current devices are small, noisy, and require complex error correction[3][4]. Recent breakthroughs such as Google’s Sycamore supremacy experiment and IBM’s 433-qubit Osprey highlight rapid hardware scaling[5][6]. We conclude that while quantum computing is not yet ready for general-purpose tasks, ongoing advances in qubit count, coherence, and error correction promise transformative impacts.

The relentless demand for higher performance, efficiency, and reliability in internal combustion engines has propelled innovative solutions in component design and manufacturing. Amongst engine components, the piston is a critical determinant of engine output, longevity, and efficiency, as it endures high thermal and mechanical stresses during operation. Conventionally, pistons for small displacement engines like the typical 150cc 4-stroke are produced using aluminum alloys via casting techniques. However, this traditional approach suffers from inherent drawbacks such as limitations in geometry, excess weight, uneven heat dissipation, and increased friction and wear due to relatively solid and uniform internal structures.

Tourism in Odisha has evolved from a leisure-centric industry into a dynamic engine for biodiversity conservation, rural empowerment, and sustainable development. Recognized as a vital driver of economic growth, the state’s tourism landscape integrates diverse sectors—including religious, wellness, and agro-tourism—while prioritizing the preservation of its unique ecological repositories. With one National Park, two Tiger Reserves, and six Ramsar Sites such as Chilika and Bhitarkanika, Odisha serves as a critical frontier for nature-based solutions and environmental stewardship. Central to this transformation is the Community-Based Ecotourism (CBE) model, which gained significant momentum in 2016-17. This initiative has successfully shifted management responsibilities to over 670 local community members, predominantly rural women and tribal populations, across 51 destinations. By linking livelihood security directly to the health of wildlife sanctuaries and national parks, the model fosters a "natural process" of conservation. Furthermore, the state is aligning with the National Education Policy (NEP) 2020 by promoting educational tourism. Through field studies, eco-clubs, and government internships, Odisha is bridging the gap between academic theory and practical environmental management, ensuring that the next generation is equipped with the skills necessary for sustainable tourism leadership.

This chapter explores AI-driven approaches for the instruction of English language skills to undergraduate students in government colleges in India during the AI digital era. It highlights the use of adaptive learning platforms, interactive digital resources, and personalized feedback systems that align with the National Education Policy (NEP) 2020’s emphasis on technological integration for equitable educational opportunities (Bowen). By addressing challenges such as large student cohorts and varied linguistic backgrounds, these methodologies facilitate improvements in listening, speaking, reading, and writing competencies among undergraduate learners preparing for competitive examinations and professional communication. In recent years, the rapid adoption of Artificial Intelligence (AI) tools within higher education has transformed traditional pedagogical practices, especially in English language instruction (Crompton 1234). Adaptive learning platforms can analyse individual learner profiles, identifying strengths and weaknesses to tailor lessons accordingly.

This study examines awareness of digital arrests and cyber frauds among senior citizens in Coimbatore District, Tamil Nadu. Using a descriptive survey of 200 individuals aged 60 and above, it assesses their understanding of cybercrime types, digital safety perceptions, and preparedness to respond to cyber threats. Data were analysed using percentage analysis, Chi-square tests, and correlation analysis. Findings show that although many seniors use smartphones and digital banking, awareness of fraud indicators and preventive measures is low. Education level has a significant influence on cyber awareness. The study recommends targeted digital literacy programs, community-based awareness initiatives, and collaboration with law enforcement to safeguard senior citizens from cyber fraud.

The purpose of this paper is twofold, namely to analyse how Enterprise risk management (ERM) principles can be used to create ethical and responsible banking and to determine the extent to which banks in Zimbabwe have integrated social and environmental issues into their risk management, business strategies and decision making processes. The study focused on 18 commercial banks operating in Zimbabwe and data was collected through questionnaires. The study found out that locally owned banks in Zimbabwe (the bulk of which have slightly adopted ERM) have not integrated ethical, environmental and social considerations into their risk management and decision-making processes. On the other hand, the study noted that foreign owned banks (the majority of which have fully adopted ERM), consider social and environmental factors when lending or reviewing facilities to for example, the agricultural sector and industries linked to human rights and pollution. The study established that ERM assists banks to manage environmental and social risks through (i) taking a holistic approach in the identification of sustainability risks, (ii) responsible lending underpinned by environmental and social credit risk assessment and (iii) embedding environmental and social aspects into its operations by aligning it to the ERM processes. The study has shown that banks that have fully adopted ERM are likely to embrace sustainable/ethical banking. It can therefore, be concluded that ERM principles can be used by traditional banks to create ethical and sustainable banking models.

The rapid shift toward digital education in recent years has significantly impacted teaching and learning practices across India. This study aims to explore the patterns of online learning among undergraduate students in West Bengal, focusing on their access to digital devices, internet connectivity, usage of online platforms, and overall engagement with digital learning resources. The research follows a survey-based approach, conducted between June and September 2025, using a self-designed questionnaire administered to 319 undergraduate students from eleven districts across the state. Purposive sampling was employed for participant selection. In addition to primary data, secondary sources such as research articles, policy documents, and online content were consulted. The findings reveal that a vast majority of students (94.67%) rely on smart phones for online learning, with most using mobile data (86.83%) as their primary internet source. While many students reported good internet connectivity (62.07%), a small percentage still experienced poor or very poor access. YouTube emerged as the most widely used platform (85.59%) for academic purposes, with daily usage reported by over half the respondents (52.98%). However, a significant minority (10.35%) lacked access to any online learning applications. Most students (63.32%) engaged in online learning for 1–2 hours daily, indicating moderate but consistent usage. The study highlights the growing dependence on digital tools for education while also pointing to persistent challenges related to device availability, platform diversity, and connectivity. These insights can inform educational institutions and policymakers in designing more inclusive and effective digital learning strategies.

The status of women in ancient India underwent significant transformation from the early Vedic period to the rise of Buddhism in the sixth century BCE. While early Vedic society accorded women a relatively dignified position in religious, intellectual, and social spheres, subsequent Brahmanical developments gradually imposed restrictions on female autonomy through patriarchal norms, ritual exclusion, and legal codification. Against this backdrop, Buddhism emerged as a reformative movement that challenged caste hierarchy and gender-based discrimination, offering women unprecedented opportunities for spiritual liberation and social participation. This article critically examines the changing status of women from the Vedic to the Buddhist periods, focusing on education, marriage, religious participation, and the concept of liberation (mok?a / nirv??a). By comparing Vedic ideals, later Brahmanical practices, and Buddhist reforms, the study highlights Buddhism’s significant contribution to the reconfiguration of women’s spiritual and social roles in ancient India.

Radiopharmaceuticals play a pivotal role in modern oncology by enabling precise cancer diagnosis, staging, and targeted therapy through molecular imaging and radionuclide treatment. Conventional radiopharmaceuticals have significantly improved tumor detection and therapeutic outcomes; however, limitations such as suboptimal tumor specificity, off-target radiation exposure, and resistance mechanisms necessitate the development of next-generation agents. Advances in radiochemistry, molecular biology, and nanotechnology have accelerated the design of innovative radiopharmaceuticals with enhanced targeting accuracy and therapeutic efficacy. Next-generation radiopharmaceuticals integrate tumor-specific ligands, peptides, antibodies, and small molecules with novel radionuclides to achieve superior pharmacokinetics and favorable radiation dosimetry. The emergence of theranostic radiopharmaceuticals, which combine diagnostic and therapeutic capabilities within a single molecular platform, has revolutionized personalized cancer management by enabling patient-specific treatment planning and response monitoring. Radionuclides such as gallium-68, lutetium-177, actinium-225, and copper-64 have gained prominence due to their optimal physical properties for imaging and therapy. Furthermore, innovations in chelation chemistry and targeting vectors have improved in vivo stability and tumor uptake while minimizing toxicity to healthy tissues. Next-generation radiopharmaceuticals are also being explored for their potential in combination therapies, including immunotherapy and chemotherapy, to enhance therapeutic synergy and overcome tumor heterogeneity. Despite these advancements, challenges remain in large-scale production, regulatory approval, and clinical translation. This article reviews recent developments in next-generation radiopharmaceuticals for cancer imaging and therapy, highlighting their design strategies, clinical applications, and future prospects. Continued interdisciplinary research and technological integration are essential to fully realize the potential of these advanced radiopharmaceuticals in precision oncology.

The rapid spread of autonomous AI shopping agentstechnologies that can independently search, compare, and carry out purchases onlinehas a major impact on the logic of digital retail. Essentially, these smart intermediaries are the main players in product discovery and purchasing to a larger extent, thus they are reshaping the ways in which product visibility is achieved in e-commerce ecosystems (BigCommerce, 2025). While the focus used to be on attracting human clicks and optimizing consumer-facing search, the new battleground of competition revolves around algorithmic selection, structured data, and machine-readable product intelligence (DigitalCommerce360, 2025).

This article explores the enduring legacy of the Indian Knowledge System (IKS) in the fields of metallurgy and early chemistry, positioning ancient Indian innovations as vital contributions to the global history of science. It examines key metallurgical achievements, including the corrosion-resistant Delhi Iron Pillar and the globally renowned high-carbon Wootz steel, which demonstrate an advanced, empirical understanding of material properties and alloy production. The paper also investigates Rasashastra (Indian alchemy), a discipline emerging around the 7th century CE that integrated metallurgy with Ayurvedic medicine to create therapeutic mineral-based formulations known as bhasmas. Furthermore, it highlights the sophisticated industrial capacity of ancient India, exemplified by the early zinc distillation processes at the Zawar mines. Beyond historical analysis, the article emphasizes the contemporary relevance of these traditions, suggesting that ancient principles of sustainability and nano-engineering can inspire modern innovations in materials science, green chemistry, and nanomedicine. Ultimately, the author argues for the integration of these indigenous scientific traditions into modern curricula to decolonize science and foster a more holistic, interdisciplinary approach to technological development.

The purpose of this research paper is to investigate the impact on society of the adoption of corporate social responsibility by the banking industry. The term "social responsibility of business" refers to the actions taken by companies and how such actions benefit society. Other names for the concept of corporate social responsibility include "corporate conscience" and "responsible business." This research study makes use of secondary data for its foundation. These days, corporate society is displaying a great deal of relevance in the business world, which includes the banking sector and financial institutions. These days, corporate social responsibility has evolved into a field that every nation must prioritise. Banks, after realising the significance of corporate social responsibility, have begun implementing social and environmental initiatives that are both beneficial to the banks and to society. CSR, or corporate social responsibility, refers to the business practises that corporations use in order to run their operations in a manner that is not only ethical but also helpful to society in terms of financial success.

Neurodegenerative disorders, such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis, continue to pose significant challenges to global healthcare systems due to their progressive nature and limited therapeutic options. In recent years, increasing attention has been directed toward plant-based compounds as potential neuroprotective agents. Among these, the Snowdrop (Galanthus spp.), a delicate flowering plant belonging to the Amaryllidaceae family, has emerged as a promising source of bioactive molecules. Notably, Galanthus species are rich in alkaloids, particularly galantamine, a well-established acetylcholinesterase inhibitor currently employed in the management of Alzheimer’s disease symptoms. Beyond galantamine, Snowdrops also contain a diverse range of secondary metabolites with antioxidant, anti-inflammatory, and neuroprotective properties, suggesting their broader potential in neurotherapeutic applications. This review aims to highlight the phytochemical profile of Snowdrop species, emphasizing their relevance to neurodegenerative disease therapy. We explore the mechanisms through which Snowdrop-derived compounds exert neuroprotective effects, including modulation of neurotransmitter levels, attenuation of oxidative stress, and inhibition of neuronal apoptosis. Furthermore, the traditional medicinal uses, recent pharmacological findings, and existing knowledge gaps are discussed to provide a comprehensive understanding of the therapeutic prospects of Galanthus. Although significant strides have been made in isolating and characterizing active compounds, further in-depth studies and clinical trials are necessary to fully validate the efficacy and safety of Snowdrop-based interventions. Overall, the emerging evidence supports the notion that Snowdrop holds substantial promise as a natural candidate for the development of novel treatments against neurodegenerative diseases.

TBLT has become the most dominant approach in language teaching and SLA research. In language teaching, it considers 'task', which promotes negotiation of meaning in the communicative context, as a unit of teaching and learning and in SLA research, it is used as a tool to elicit naturalistic language for research. Presently, there is a growing trend of adopting TBLT in English language teaching with the purposes of enhancing the communicative ability by focusing on meaning in a real-life context. TBLT seems theoretically sound as it has been supported by many psycholinguistic studies. However, there is an increasing concern about the suitability of using a task and adopting TBLT in various world contexts. There is a contention on the practical application of 'task' in real teaching. This article analyses how suitable is the use of 'task' is in teaching English at the primary level of Nepal.

Satellite image segmentation plays a vital role in various applications such as urban planning, infrastructure monitoring, and disaster management. However, the performance of deep learning architectures like U-Net often deteriorates due to environmental noise, sensor-related distortions, and the inherent complexity of urban terrain. To address these challenges, this study integrates attention mechanisms into the conventional U-Net framework, developing an Attention U-Net model designed to enhance feature learning and spatial focus. The robustness of the model is further evaluated through uncertainty characterization in the context of building footprint extraction. Experimental results demonstrate that the proposed Attention U-Net consistently outperforms the baseline U-Net across both training and validation datasets, achieving an accuracy of 81.15% on the validation set, compared to 79.75% achieved by the standard U-Net. The inclusion of the attention mechanism enables the network to selectively emphasize relevant spatial regions, resulting in improved segmentation precision, enhanced visual delineation of buildings, and reduced predictive uncertainty, particularly in densely built and heterogeneous urban environments. Overall, the findings highlight that Attention U-Net represents a more robust and reliable solution for complex satellite image segmentation tasks where high accuracy and interpretability are essential.

This study investigates the role of music in enhancing language acquisition among school and college students in Pakistan. Music has long been recognized as a powerful tool for improving listening, pronunciation, vocabulary, and fluency. The study employs a pre-test/post-test design with questionnaires to examine the effectiveness of music-based activities in English language classrooms. A total of 60 students participated, completing a language skills test and an attitude questionnaire before and after a four-week music intervention. The findings are expected to show that music significantly improves language skills and positively influences learners’ motivation and confidence. The study highlights the potential of integrating music into language teaching practices in Pakistani classrooms.

The Pradhan Mantri Awas Yojana represents a housing scheme by the Government of India designed to ensure "Housing for All" through affordable housing schemes. This study examines the effectiveness of the PMAY scheme, along with eligibility challenges, transparency in accessing the scheme benefits, and satisfaction of beneficiaries by using both qualitative and quantitative data, having the main objective To evaluate the effectiveness of the PMAY scheme, focusing on eligibility challenges, transparency of processes, and beneficiary views on scheme improvement, this paper highlights the eligibility challenges and transparency in the process of allotment, followed by suggestions from the beneficiaries that can improve the PMAY scheme to be more effective and reachable to the needy beneficiaries. This analytical study contributes to the housing sector, where its outcomes and beneficiary perspectives are expected to improve the scheme's efficiency.

Child rights and human trafficking are pressing global issues that undermine human dignity and justice. This paper examines the factors contributing to child trafficking, the legal frameworks designed to combat it, and the challenges in enforcement. Despite international agreements like the United Nations Convention on the Rights of the Child (UNCRC) and the Palermo Protocol, trafficking persists due to poverty, conflict, lack of education, and weak law enforcement. Many children are subjected to forced labor, sexual exploitation, and other forms of abuse, highlighting gaps in protective mechanisms. The study assesses the effectiveness of existing policies and the role of government and non-governmental organizations in preventing trafficking, rescuing victims, and supporting rehabilitation. It emphasizes the need for a multi-faceted approach, including legal reforms, stricter penalties for traffickers, and enhanced victim support systems. Strengthening institutional responses, fostering international cooperation, and promoting community awareness are crucial to safeguarding children's rights. This research contributes to policy discussions by recommending strategies to improve prevention, enforcement, and recovery efforts. A collective global response is essential to eliminating child trafficking and ensuring a safer future for vulnerable children.

Advancing age induces anatomical, physiopathological, and cognitive alterations impacting the respiratory system from the oral cavity to the larynx. Key changes encompass tooth decay, edentulism, oropharyngeal tumors, muscle atrophy around the lips, and diminished neck range of motion (ROM). Conditions like obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) heighten risks of oxygen desaturation. This review delineates age-related anatomical modifications in the nasal cavity, oral cavity, pharyngeal/laryngeal regions, and neck, emphasizing implications for airway patency in geriatric care. Such insights aid in anticipating difficult airways and refining management strategies.

Sports tourism has emerged as a vital driver of economic growth and cultural exchange across the globe. With an increasingly mobile global population and the growing enthusiasm for sports, the intersection of travel and athletic activities has created new opportunities for host destinations. This research examines the diverse effects of sports tourism by analyzing its contributions to economic development, cultural enhancement, and sustainable community growth. Through a combination of case studies and empirical data, the study investigates how hosting sporting events, from local competitions to international tournaments, can produce significant financial flows, including increased tourism revenue, job creation, and infrastructure development. From an economic perspective, sports tourism stimulates local economies by drawing visitors who support sectors such as hospitality, transportation, retail, and entertainment. The influx of tourists during major sporting events frequently results in heightened demand for accommodation, dining, and other services, benefiting both small businesses and large enterprises. Additionally, investments made in sports facilities and related infrastructure can yield lasting positive effects, enhancing the overall appeal and functionality of the host city or region. Beyond economic considerations, sports tourism also serves a vital function in promoting cultural heritage and social interactions. Sporting events act as platforms for cultural exchange, enabling visitors and local residents to share traditions, values, and community pride. This interaction promotes social cohesion and a sense of identity among diverse groups, strengthening common bonds. The text explores how strategic planning and oversight can guarantee that sports tourism delivers optimal environmental, social, and economic advantages while protecting the welfare of local residents. In conclusion, the research indicates that sports tourism, when thoughtfully utilized, offers substantial opportunities for promoting comprehensive development and intercultural appreciation in destination areas.

Teaching vocabulary to young learners in Libya remains a challenging process, particularly due to the need for selecting appropriate and meaningful vocabulary that suits learners&#39; age and cognitive level. To facilitate effective language learning, EFL teachers are required to employ innovative techniques in teaching vocabulary in the classrooms. This study highlights the use of games and songs as instructional techniques for teaching English vocabulary to kindergarten learners. To answer the research questions, a pre-test and post-test were administered to KG1 and KG2 students at International Knowledge School in Misurata. The findings reveal that both games and songs contribute positively to vocabulary learning; however, games were found to be slightly more effective in enhancing students&#39; vocabulary recognition and motivation. The results suggest that incorporating interactive and enjoyable activities such as games and songs can significantly support vocabulary acquisition among young learners and help achieve the objectives of teaching English vocabulary at the kindergarten level.

Artificial Intelligence (AI) is revolutionizing the fashion world by introducing unprecedented changes across design, production, and customer interaction. Advanced tools such as machine learning, computer vision, and natural language processing empower the sector to be more efficient, innovative, and consumer-centric. Supported by secondary research and brand case analyses, this study examines AI’s current impact, potential advantages, challenges, and future outlook in fashion. Despite barriers like data sensitivity, high costs, and ethical dilemmas, AI offers a promising path toward a smarter and more sustainable fashion ecosystem.

Chalcogenide-based materials are rapidly emerging as pivotal components in cutting-edge optoelectronic and sustainable energy technologies due to their unique electronic, optical, and structural properties. This study presents a comprehensive investigation of AI-driven advances in the design, characterization, and optimization of chalcogenide materials, with a particular focus on their applications in photovoltaic devices, photodetectors, phase-change memories, thermoelectric generators, and solid-state batteries. Leveraging artificial intelligence techniques such as neural networks, high-throughput computational screening, and explainable machine learning models, we demonstrate significant improvements in predictive accuracy for key material parameters including bandgap, responsivity, and thermoelectric figure of merit (ZT). Experimental validation against established datasets confirms that AI models can predict photodetector responsivities for materials like GeSe, Sb2Se3, SnSe, and Cu2ZnSnSe4 within an error margin of less than 5%. Similarly, AI-optimized compositions of thermoelectric alloys such as GeTe, SnTe, and PbSe reveal enhanced power factors and balanced thermal conductivity, yielding ZT values exceeding 2 at high temperatures (750–800 K). Detailed analysis identifies GeTe alloys as exhibiting superior thermoelectric performance, attributable to their optimal interplay of electrical conductivity, Seebeck coefficient, and thermal transport properties. Furthermore, the integration of AI workflows accelerates the discovery cycle and facilitates the sustainable design of chalcogenides by minimizing toxic precursors and optimizing energy-efficient synthesis routes. This paradigm shift from empirical experimentation to AI-guided rational design heralds new prospects for scalable, eco-friendly, and high-performance devices across multiple domains. The results underscore the transformative potential of artificial intelligence in addressing long-standing challenges in materials science, thereby enabling next-generation optoelectronic and energy systems that are both efficient and sustainable.

Deep vein thrombosis remains one of the most preventable yet persistently under-recognized complications associated with hospitalization. Patients exposed to prolonged immobility, surgical stress, inflammatory states, and critical illness are particularly vulnerable to thrombus formation within the deep venous system. While pharmacological prophylaxis is an essential component of prevention, nursing-led interventions represent the most consistent and continuous defense against venous thromboembolism. This review critically examines nursing interventions aimed at preventing deep vein thrombosis across clinical settings. Emphasis is placed on nursing assessment, early mobilization, mechanical prophylaxis, hydration management, patient education, and monitoring of anticoagulant therapy. The review synthesizes current evidence to highlight the pivotal role of nurses in translating thromboprophylaxis guidelines into effective bedside practice. Strengthening nursing-driven prevention strategies has the potential to significantly reduce hospital-acquired deep vein thrombosis and improve patient safety outcomes.

Research paper examines the hypothesis that India’s solar energy policies, aimed at delivering clean, affordable, and accessible energy to tribal communities, are not merely a means to address electricity deficits, but are also emerging as a powerful instrument for inclusive development by positively influencing their environmental, social, economic, and educational lives. The study specifically focuses on tribal communities residing in the forested, hilly, and remote regions of Sonbhadra district in Uttar Pradesh, where access to traditional energy sources remains limited. Through a comprehensive review of literature and field surveys, the research analyzes how solar energy is enhancing the quality of life by fulfilling basic needs related to education, healthcare, communication, and livelihood among these marginalized communities. At the same time, the study critically investigates the structural, technical, and administrative challenges that hinder the effective implementation of solar energy schemes and restrict the full realization of inclusive development among these groups. Thus, this research positions solar energy not merely as a technical solution, but as a transformative social tool that advances equitable opportunity, participatory growth, and empowerment for tribal communities.

This study explores the evolving role of Artificial Intelligence (AI) in Customer Relationship Management (CRM), examining its impact on customer service, interaction personalization, and overall satisfaction and retention rates. As organizations increasingly integrate AI into their CRM strategies, understanding the opportunities and challenges presented by this technological shift becomes crucial. Through a comprehensive analysis of current research, industry reports, and case studies, this paper investigates the most widely adopted AI applications in CRM, their effectiveness, and the challenges organizations face during implementation. The research reveals significant improvements in customer satisfaction, retention rates, and sales performance across industries following the implementation of AI-powered CRM systems. Predictive analytics emerges as the most widely adopted and effective AI application, followed by chatbots and personalization engines. However, the study also identifies key challenges, including data quality and integration issues, lack of AI expertise, and user adoption barriers. As AI automates routine tasks, the role of human employees in sales and customer service is evolving towards more complex, high-value activities. This shift necessitates a focus on developing new skill sets and creating roles that leverage both human expertise and AI capabilities. The paper concludes by offering strategic recommendations for organizations seeking to implement AI in their CRM systems. These include adopting a tailored, phased approach to AI implementation, investing in data quality and employee skill development, and carefully balancing efficiency gains with ethical considerations and customer trust.
This research contributes to the growing body of knowledge on AI in CRM and provides valuable insights for practitioners navigating this rapidly evolving landscape. Future research directions are suggested, focusing on long-term impacts of AI-powered CRM on customer loyalty and frameworks for ethical AI use in customer relationships.

Are leaders born or made? If the answer is made, then can leadership be taught and learned in colleges? These and other similar questions are the focus of this study which reviews the research in both leadership development and activities in colleges. We live in a world that cries out for – and often doesn’t receive – strong leadership. Yet so many of us see public figures, decision-makers and opinion-leaders and consider ourselves to be incapable of taking on such roles. We must ensure the same is not true for our pupils. They need to see themselves as potential leaders, with an understanding of the qualities and competencies that entails. The classroom hierarchy places the power with the teacher, but you can still create regular opportunities for pupils to show leadership in the classroom. This study aims to examine teachers' opinions regarding the activities that can be performed at colleges to ensure leadership development in students. Accordingly, an attempt to reveal what the leadership qualities of students should be, the activities that can be performed for the acquisition of leadership qualities. The study was carried out by conveniently selecting 50 teachers who could contribute a valuable input for the study. The data were collected by structured Questionnaire and semi-structured interview. Review of literature was done on the previous study on the same topic.

Special educators play a critical role in addressing the diverse learning, behavioral, and emotional needs of children with disabilities. However, the demanding nature of their work often exposes them to high levels of occupational stress, emotional exhaustion, and burnout, which may adversely affect their professional well-being and teaching effectiveness. The present paper aims to conceptually examine professional well-being and burnout among special educators working with children with disabilities. Drawing upon existing national and international literature, this review explores key dimensions of burnout, contributory factors, and protective elements influencing the well-being of special educators. A conceptual framework integrating occupational demands, personal resources, and institutional support is proposed to understand the dynamic relationship between stress and well-being. The paper highlights implications for teacher training, institutional policies, and mental health support systems and offers recommendations for future research and practice. Strengthening professional well-being among special educators is essential not only for teacher retention and job satisfaction but also for ensuring quality education and holistic development of children with disabilities.

The COVID-19 pandemic has dramatically reshaped consumer behavior, accelerating the shift from offline to online shopping and increasing reliance on social media platforms for product discovery, brand engagement, and purchasing decisions. This study investigates consumer perception and trust in social media marketing during the pandemic, with a focus on understanding how digital marketing strategies influenced consumer confidence, engagement, and purchase intentions. Using empirical data collected from consumers in [specific location, e.g., Meerut district], the research examines key factors affecting trust, including perceived reliability of information, influencer credibility, targeted advertisements, and interactive campaigns. Findings reveal that social media marketing played a crucial role in maintaining consumer engagement and shaping purchase behavior during periods of restricted mobility, while trust emerged as a critical determinant of online decision-making. The study provides insights for marketers, businesses, and policymakers on designing effective, trustworthy social media marketing strategies, emphasizing the need to address psychological, social, technological, and economic factors that influence consumer trust. The research also suggests directions for future studies to explore post-pandemic trends in digital consumer behavior.

The COVID-19 pandemic has drastically reshaped consumer behavior worldwide, accelerating the shift from offline to online shopping and increasing reliance on social media platforms for product discovery and purchase decisions. This study explores the changes in consumer buying behavior through social media platforms during the COVID-19 pandemic in Meerut district. Using an empirical approach, primary data were collected from consumers to examine their social media usage, engagement with marketing content, and purchase patterns during the pandemic. The findings reveal significant changes in consumer preferences, including increased online purchases, heightened responsiveness to digital promotions, and greater trust in peer reviews and influencer recommendations. Psychological, social, technological, and economic factors were identified as key drivers influencing these behavioral changes. The study highlights the critical role of social media marketing in shaping consumer decisions during crisis situations and provides actionable insights for marketers to design effective strategies that align with evolving consumer expectations. The results contribute to a deeper understanding of digital consumer behavior in emerging markets and offer implications for businesses aiming to strengthen their online presence in the post-pandemic era.

United Nation High Commissioner for Refugees (UNHCR) has a stake in disseminating the results of its legal and protective policy studies to decision-makers, scholars, attorneys, judges, non- governmental organizations, and the general public because it is the custodian of the 1951 Convention and its 1967 Protocol. The current paper emphasizes on the historical background of UNHCR and further in detail. Refugee rights find their legal basis from important international instruments that simultaneously establish state obligations and the current paper highlights the legal framework and international instruments governing UNHCR. The UNHCR organizational framework follows certain primary purposes consisting of international protection with assistance along with durable solution programs and this paper laid emphasis upon the mandate of UNHCR and the organizational structure. The function of UNHCR has also been explained in detail. Non- refoulement represents the foundational principle upon which the UNHCR bases its protective mandate because the organization must prevent forcibly pushing refugees into danger and following this role of non-refoulement principle has been discussed in the current paper. The current paper analyses certain cases along with the challenges faced by UNHCR inclusive of perspective on jurisdictional challenge following the strategic responses with respect to it. Thus, the current research demonstrates that UNHCR continues to play an essential role with its defined functions and position.

One of India's most well-known fintech businesses, Paytm is essential to the nation's shift to a digital and cashless economy. Since its founding in 2010, the business has grown from a mobile recharge platform to a whole ecosystem of digital payments and financial services that includes UPI, wallet services, merchant solutions, loans, insurance, and wealth management. The growth trajectory, business model, acquisition strategy, market share position, and significant disputes and difficulties that Paytm has encountered over the years are all examined in this case study. Regulatory scrutiny, fierce rivalry in the UPI market, and the effect of its IPO performance on investor perception are all given special attention. The study also examines Paytm's strategic transition from quick expansion to growth that is driven by compliance and profitability. The study emphasizes important lessons about governance, sustainability, and innovation in the fintech industry by evaluating Paytm's reactions to market forces and regulatory obstacles. According to the findings, Paytm's robust merchant ecosystem, technological infrastructure, and emphasis on financial services position it for long-term importance in India's changing digital financial scene, even though it confronts substantial competitive and regulatory obstacles.

Predictive maintenance (PdM) has completely changed the way industries are operated from a reactive and preventive mind set to real-time, data-driven, and condition-based decision-making for maintenance activities. As a result of the continuous capture of condition data leading to signal processing and artificial intelligence (AI) being utilized for maintenance, this can reduce downtime by enabling maintenance of equipment before catastrophic failure and simultaneously improve reliability and lower costs. This paper reviews the development of PdM technologies and practices over time, tracing a path from more traditional, adaptive statistical and signal analysis practices, advancing to and including more recent developments in machine learning, and deep learning algorithms. We compare the various approaches based on performance criteria such as accuracy, scalability, ease of understanding, and cost of implementation and describe the pros and cons of each approach when used with different industrial applications. In addition, we discuss an emerging scheme regarding explainable AI (XAI) and causal discovery which addresses the challenge of trust, and transparency with approaches employing black-box models that is critical in situations where safety is paramount. We also describe the usefulness of new paradigms, such as data categorization approaches, multimodal data fusion, edge and federated learning, and quantum computing, for enhancing scalability and real-time deployment. By collecting existing applications and examining positives and negatives, applicable principles, and main trade-offs to usability outcomes, we have noted areas of research that are lacking, such as understanding interpretability to the PdM system created by the data utilized, availability of data-based information, and deployment, which allows us to create next steps for developing PdM systems that are accurate, interpretable, and scalable within the Industry 4.0 space.

In this review presents a comprehensive assessment of computational investigations on the coupled effects of natural convection and surface radiation in extended surfaces with various fin geometries, including annular, star, square, and triangular configurations. Emphasis is placed on three-dimensional numerical studies employing the finite volume method, commonly implemented using the ANSYS Fluent solver, to solve the governing conservation equations of mass, momentum, and energy. Buoyancy effects are typically modelled using the ideal gas assumption, and numerical results are validated against previously published data. The review synthesizes findings on the thermal behaviour and heat transfer performance of different fin geometries under a wide range of operating conditions. Key parameters such as Rayleigh number (10³–10?), fin spacing, surface emissivity, aspect ratio, fin orientation, and geometric modifications are systematically examined to elucidate their influence on coupled convective and radiative heat transfer mechanisms. Reported temperature distributions, flow structures, and heat transfer interactions are analysed to identify performance trends and governing transport phenomena. In addition, the review highlights the development of empirical and semi-empirical correlations linking the Nusselt number with Rayleigh number and geometric parameters for selected fin configurations. Overall, this work provides a critical and structured overview of recent numerical advances in convection–radiation heat transfer from complex fin geometries, offering valuable insights for the design and optimization of extended surfaces in heat exchangers and thermal management systems.

In this review, Buildings are identified as the largest consumers of energy in all countries.in order to develop an energy-efficient building, insulation materials are essential. The right use of insulating material in buildings not only reduces the size of the air conditioning system required but also lowers annual cost of energy. Furthermore, it helps to increase thermal comfort without the use of mechanical air conditioning, especially in summertime. Amount of energy savings achieved through thermal insulation depends on various parameter such as building type, local climate, and type of insulating material used. Expanded polystyrene (EPS), Bamboo material are used as thermal insulation material on the roof. The main objective of this paper is to reduce the indoor air temperature by providing the thermal insulation in the building.

Breast cancer remains the most common malignancy among women worldwide and a leading cause of cancer-related mortality.[9] [2]. This review provides a comprehensive overview of breast cancer epidemiology, risk factors, molecular classifications, pathogenesis, diagnostic advances, and therapeutic strategies.[2][5][3]Key risk factors include genetic mutations like BRCA1/2, hormonal influences, obesity, and lifestyle elements, with early detection via mammography and biomarkers improving outcomes.[2] [10] [8]Therapeutic approaches encompass surgery, radiation, chemotherapy, hormone therapy for ER-positive tumors, and targeted agents like trastuzumab for HER2-positive cases, alongside emerging options for resistant subtypes.[5] [3] Personalized medicine and multidisciplinary care optimize survival, though challenges persist in aggressive forms like triple-negative breast cancer.[2] [3]Ongoing research into novel therapies and prevention underscores the need for continued innovation.[5] [3]

This paper introduces a data-driven framework to optimise the pharmaceutical supply chain and address medication shortages in rural U.S. healthcare facilities. It consolidates evidence on causes of shortages, demand trends, and inventory management to create a practical decision-support system tailored for low-volume, resource-limited environments. The framework leverages multiple data sources, including pharmacy dispensing data, supplier performance information, transportation limitations, and disruption histories, to enable accurate demand forecasting, safety stock calculation, and replenishment planning. Statistical and machine learning models account for factors like seasonality, facility type, patient demographics, and geographic access barriers. Inventory optimisation modules distinguish strategies for fast- and slow-moving stock-keeping units. Scenario-based stress testing evaluates resilience during disruptive events like pandemics, extreme weather, or transportation failures. The paper also discusses implementation strategies, focusing on stakeholder involvement, change management, and technology adoption to ensure the analytic tools are integrated into everyday pharmacy operations rather than limited to pilot projects. It considers policy and ethical issues, emphasising how local conditions and regulations influence feasible interventions. Overall, the study provides a structured roadmap for rural health systems to harness data-driven methods to improve service levels, reduce stockouts and expiries, and enhance access to essential medicines.

The work ethic of employees in Ghana is shaped by a complex interaction of cultural values, socio-economic conditions, historical influences, and organizational realities. As multinational companies increasingly expand into Ghana, understanding the Ghanaian work ethic has become essential for effective management, cross-cultural communication, and human resource development. This study explores the key characteristics of the Ghanaian work ethic and examines how cultural norms, hierarchical structures, collectivist orientations, and socio-economic pressures influence workplace behavior. Using a mixed-methods approach involving surveys and interviews with employees and managers in selected organizations, the study identifies culturally rooted strengths such as adaptability, communal collaboration, and respect for authority alongside challenges, including flexible attitudes toward time, fear of confrontation, and competing social obligations. The findings provide critical insights for international managers and HR practitioners seeking to improve organizational performance, enhance employee motivation, and design culturally aligned management practices in Ghana. The study concludes with recommendations for culturally sensitive HR strategies that promote productivity while respecting local norms.

Nanotechnology is emerging as a transformative force in advancing Artificial Intelligence (AI), enabling unprecedented improvements in computational speed, energy efficiency, sensing capabilities, and system miniaturization. This paper explores the integration of nanoscale materials, devices, and architectures within AI systems to overcome the limitations of conventional silicon-based technologies. Key innovations—such as nanophotonic processors, memristor-based neuromorphic circuits, carbon nanotube transistors, and nanoparticle-enhanced sensors—enhance the performance of machine learning models by supporting faster parallel processing, low-power inference, and high-density data storage. Additionally, nanotechnology enables the development of intelligent nano-robots and nanosensors for biomedical diagnostics, environmental monitoring, and targeted drug delivery, expanding the real-world applicability of AI. The synergy between nanotechnology and AI not only accelerates computational efficiency but also drives the evolution of adaptive, autonomous, and highly scalable intelligent systems. This paper reviews recent advancements, current challenges, and future prospects of nanotechnology-enabled AI, emphasizing its potential to define the next generation of intelligent computing.

The educational sector at higher levels in India has experienced vital changes which result from historical development and modern policy adjustments. The research performs a systematic policy analysis of Indian higher education systems through historical evaluations which incorporate secondary information extracted from government documents and institutional statistics and global performance indicators. The study traces the colonial origins of modern higher education, the post-independence expansion, the liberalization and privatization phase (1990s onward), and the recent reforms under the National Education Policy (NEP) 2020. The analysis focuses on multiple essential metrics which include Gross Enrolment Ratio (GER) alongside research finances as well as teaching personnel ratios and educational administration models and worldwide initiatives. The study examines India's funding problems along with quality control deficiencies and equality issues against worldwide perspectives which include China-US and European states while showing expanded admission opportunities. The results demonstrate how Indian education faces a dilemma between granting increased entry to educational facilities while maintaining high educational standards. Furthermore, they show private college expansion and underline the requirement for directed payments into research-based innovation. Future education policies in India should center on three main elements: enduring funding solutions, digital system development and establishing research-based excellence.

This article explores how the ideas of Swami Vivekananda might direct the improvement of India&#39;s tribal groups, who have long endured societal neglect, poverty, and illiteracy. Vivekananda urged society to treat the impoverished with compassion and respect because he thought that everyone had potential and inherent dignity. His views on education, independence, and mass empowerment are directly relevant to the problems that tribal communities are currently facing. To help tribal people better their lives without sacrificing their traditional identity, the article also details how monks from the Ramakrishna Mission have put his ideas into practice by establishing schools, health facilities, and skill-building programmes in tribal communities. India can give tribal people equitable opportunity and guarantee their full participation in the development of the country by implementing Vivekananda&#39;s vision.

A radiator is a device that helps in cooling the engine by transferring heat from the engine to the coolant and then from the coolant to the surrounding atmosphere. Radiators are mainly used for cooling large-capacity engines. A water jacket is provided around the engine through which the coolant circulates. Due to the heat released by the engine, the coolant becomes heated and is subsequently cooled by the radiator. Leakage problems may occur during the manufacturing or assembly process. To address this issue, this project focuses on the design of a pneumatic circuit for a leak testing machine. The pneumatic circuit includes components such as a pneumatic compressor unit, a toggle-operated 5/2 directional control valve, hoses, fittings, and a double-acting cylinder. The cylinder design has been finalized for this system. The piston is used to produce the upward and downward motion of the platform, which supports different radiators selected for leakage testing. The movement of the piston is controlled using the pneumatic circuit. The designs of the tank and platform have also been finalized. The theoretical aspects have been completed, and the design is confirmed as the final stage of this project. The main objective of the project is to design and manufacture a special-purpose radiator leak testing machine.

The need for construction health and safety is vital throughout the life of construction projects because it has a direct correlation to the outcome of the project. The risk-prone nature of the construction industry means that a health professional is always available before, during and after hazards happen. Most construction sites in Nigeria have cases of safety officers not being proactive in preventing injuries, lacking on-the-spot decision-making initiative or doing more harm than good in the cause of managing eventualities. There is therefore a need to engage a trained and registered health practitioner whose sole role is to manage health and safety on construction projects. The aim of this paper is to carry out a study on the need to integrate nursing services into construction management practices in Nigeria. To achieve this aim, the study examined the critical roles of having a registered/trained nurse in construction operations, determined the impact of integrating nursing services on construction sites, evaluating the impact of integrating such services, and recommended measures for managing the challenges facing the integration of nursing services on construction sites. The study adopted descriptive survey design through interactions with a focus group of 10 stakeholders.The responses show that the critical role of a nurse on ongoing construction projects is that they provide collaborations between the site and health care facilities off site, direct patient care and safety on site, etc . Most construction firms don't use the services of a trained/registered nurse because they don't know what's the right approach to engaging a third party to manage safety issues over using excusing a member of the construction team with safety experience. The study, however, proved that having a trained or registered nurse on construction projects allows for easy implementation of construction workers' health packages as well as coordinating constant health and safety talks. The study recommends that there should be wide integration of trained/registered nurses during construction management operations, proper planning/budgeting for nursing services, and creating advocacy for clinical services in all construction operations.

The induction machines are widely used for their simplicity, robustness and their low cost. Induction motors are a critical component of many industrial processes and are frequently integrated in commercially available equipment and industrial processes. Condition monitoring of electric machinery can significantly reduce the cost of maintenance and the risk of unexpected failures by allowing the early detection of potentially catastrophic faults. In condition-based maintenance, one does not schedule maintenance or machine replacement based on previous records or statistical estimates of machine failure. Rather, one relies on the information provided by condition monitoring systems assessing the machine&#39;s condition. Thus the key for the success of condition-based maintenance is having an accurate means of condition assessment and fault diagnosis. Furthermore, these machines can be subjected to different operating conditions that can produce electrical or mechanical damages on the stator and/or the rotor and bearings too. It is well known that the bearing faults constitute a significant.

The journal aim to provide the readers a collective knowledge about the heroine of John Webster’s play — “The Duchess Of Malfi”. This research contain in depth details about the Duchess’ consciousness, examining her psychological vision, moral resilience and political dilemmas. This analysis also portray her as a tragic heroine by bringing out her choices and the way she fought against patriarchal oppressions and redefines female agency in the play. The paper bring out her identity shaped by public duties and personal desires wrapped in family drama. Ultimately, the paper argues that her choices are the catalyst of action in the play and her do’s and don’t form this a great seneccan tragedy.

Visual aids are a crucial component of effective classroom instruction, helping students understand complex concepts and making learning environments more engaging. Among the simplest, yet most versatile, visual tools available to educators are stick figures. The term "STIK" in the context of the study refers to the use of stick figures (simple drawings with lines for limbs and a circle for a head) as a basic drawing method in classroom teaching. This study investigates the attitudes and opinions of teacher trainees regarding the use of stick figures as a basic drawing method in their future classroom teaching.

The rise of digital technology has dramatically transformed the landscape of political participation among Indian youth over the last decade. This paper delves into the interplay between social media and youth engagement in India’s electoral politics from 2014 to 2024, a period characterized by rapid internet expansion and unprecedented smartphone penetration. It explores how digital platforms like Twitter, Instagram, and WhatsApp became dynamic spaces for young citizens to express opinions, organize campaigns, and engage with political narratives beyond traditional frameworks. Drawing on academic studies, electoral data, digital campaign records, and youth testimonies, the research reveals how “clicking democracy” the phenomenon of using likes, shares, and posts for political mobilization has empowered India’s youth to shape electoral discourse and activism at both local and national levels. Yet, this democratization of political voice through social media comes with complexities. The paper highlights how online engagement does not always translate into proportional offline participation, how digital echo chambers and misinformation affect youth perspectives, and how access disparities persist along socio-economic and regional lines. By tracing major youth-led digital movements and party strategies across general and state elections, the study uncovers both the potential and pitfalls of new media in strengthening democratic processes. Ultimately, the findings point to a growing digital consciousness among India’s youth that is redefining political boundaries, challenging conventional hierarchies, and suggesting new directions for participatory democracy. Insights from this decade offer valuable lessons for policymakers and educators seeking to harness technology for inclusive, informed, and vibrant electoral participation.

The integration of Internet of Things (IoT) devices with cloud computing has significantly transformed modern healthcare by enabling continuous patient monitoring, remote diagnosis, smart medical systems, and improved clinical decision-making. However, this convergence introduces several security and privacy challenges such as data breaches, insecure communication channels, weak authentication, and insufficient access control. This review presents a comprehensive analysis of IoT–Cloud architecture in healthcare, identifies dominant security threats, evaluates existing mitigation techniques, and highlights research gaps. The paper examines cryptographic mechanisms, anomaly detection models, blockchain-enabled healthcare data sharing, fog/edge computing-based security, and fuzzy-based assessment techniques. Key recommendations and future research opportunities are proposed to enhance security, trust, and regulatory compliance in cloud-based smart healthcare systems

Retail investors constitute a significant and growing participant segment in initial public offering (IPO) markets, particularly in emerging economies such as India where digital platforms have democratized access to investment opportunities. This paper provides a comprehensive synthesis of evidence on retail investor behavior in IPOs, focusing on their subscription patterns, post-listing trading decisions, information processing mechanisms, and vulnerability to sentiment-driven and attention-based trading. Using data from 188 Web of Science records on Indian IPOs and over 100 complementary peer-reviewed sources, we examine how retail investors differ fundamentally from institutional counterparts in their approach to IPO participation. Our findings reveal that retail investors are predominantly sentiment-driven, attention-based traders who rely heavily on prospectus disclosure and increasingly on social media and finfluencer endorsements. We identify critical gaps in existing research from the retail investor perspective, including limited understanding of how digital platforms and algorithmic information delivery affect retail trading decisions, sparse evidence on the long-term wealth consequences of retail IPO participation, and insufficient investigation of behavioral intervention mechanisms that could improve retail investment outcomes. We articulate a forward-looking research agenda that prioritizes retail investor protection, financial literacy enhancement, and market design improvements that account for behavioral heterogeneity. This paper contributes to the growing field of behavioral finance by centering the retail investor experience and identifying actionable pathways for improving retail outcomes in primary and secondary IPO markets.

Heutagogy, or self-determined learning, has emerged as a progressive instructional paradigm that places full responsibility for learning in the hands of the learner. This study examines the level of heutagogy practices among undergraduate students in arts and science colleges in Salem District. Using a quantitative normative survey method, data were collected from 110 students selected through stratified random sampling. A researcher-developed Heutagogy Scale containing 30 validated items across six dimensions explore, create, collaboration, connect, share, and reflect was used for data collection. Reliability testing using Cronbach’s alpha yielded a value of 0.847, indicating strong internal consistency. The study highlights the extent to which learners demonstrate autonomy, self-reflection, creativity, and collaborative abilities in their learning processes. Findings contribute to understanding how heutagogy skills can enhance learner motivation, adaptability, and capability development in contemporary higher education settings.

The rights of patients are an emerging issue in healthcare law in India because of the constitutional guarantee (Article 14 of the Constitution of India) of the equality of all Indians before the law and protection from arbitrary action. The article reviews the complex legal, constitutional and regulatory mechanisms from which patients&#39; rights emerge in India. It explains how constitutional provisions, legislation, court rulings and regulatory guidelines interact to create a framework for dignity, equality and non-discrimination in healthcare. The issues of informed consent, confidentiality of medical records, access to healthcare and protection from unethical behaviour are examined in detail. The article also discusses landmark court cases that expanded patients&#39; rights through the broader constitutional principles of equality and the right to life under Article 21 of the Constitution of India. Furthermore, the article investigates the functions of regulatory bodies, such as the Medical Council of India (now NMC), consumer protection laws, and the Patients&#39; Rights Charter endorsed by the Ministry of Health and Family Welfare. While organizations exist, however, the full enactment is not simple because of the level of awareness of laws, inconsistent implementation, and the lack of accountability. This article uses a doctrinal and analytical method to emphasize the value of institutions and ethical accountability, in addition to patient empowerment, in reducing the gulf between healthcare reality and woke constitutional aspirations. This article concludes by urging for the rights-based healthcare deriving from constitutional mandates that protects patients equitably.

This study is done to find if Deepfake technology is boon or curse for society. It was found that the technology has its own benefit and drawback. If used responsibly it can help to make great contributions in the society otherwise it can be harmful to it too. During the research, it was seen that this technology has both good and bad sides. If people use deepfakes in a safe and honest way, they can be very useful. They can be used for learning, fun, creativity, and even improving technology. But if people use them in the wrong way, they can create many problems. Deepfakes can spread fake information, confuse people, damage someone’s image, and even cause fear or misunderstandings. So, the study shows that deepfake technology can be a blessing or a problem. It fully depended on how people choose to use it. If used responsibly, it can do good things for society. If used carelessly or for harmful reasons, it can create major issues.

Hydroponic cultivation—growing plants in nutrient-rich aqueous solutions—has emerged as a promising approach for intensive, space-efficient agriculture in urban and controlled-environment applications. Recent literature emphasizes three converging themes for small-scale systems: (1) precise nutrient management (EC/TDS and pH control), (2) environmental sensing and IoT-based remote monitoring, and (3) adaptive LED lighting and photoperiod control. This review surveys the state-of-the-art (2022–2025) in hydroponic system designs, sensing technologies, control architectures (microcontroller-to-cloud), nutrient dosing strategies, and lighting management. We identify common limitations in low-cost implementations—sensor drift and calibration, fail-safe handling of pumps/reservoirs, and energy consumption of lighting—and summarize best-practice recommendations for a robust pilot system. The review maps the literature findings to a practical design roadmap (components, sensors, control logic) suitable for educational demonstrations and prototyping. Key research gaps and future directions—including improved low-cost ion sensing, adaptive control algorithms, and pathogen mitigation strategies—are highlighted to inform both academic and applied projects in technical education.

The growing threat of climate change has catalyzed global attention towards immediate and long-term mitigation and adaptation strategies. However, the gap between policy formulation and practical implementation remains a critical barrier, particularly in the Global South. This research paper, titled "Bridging the Policy-Implementation Gap in Climate Change Mitigation: A Comparative Study of National Adaptation Strategies in the Global South", situates itself within the discipline of Environmental Law and Climate Policy. It critically examines the disconnect between climate commitments and their execution, with a focus on the legal, institutional, and financial mechanisms that influence adaptation outcomes. Through a comparative legal analysis, this study investigates climate adaptation strategies in selected Global South jurisdictions—specifically India, Kenya, and Bangladesh—where vulnerability is high but adaptive capacity remains constrained. These regions offer fertile ground to explore how national climate action plans, such as India's National Action Plan on Climate Change (NAPCC) and Kenya’s Climate Change Act, 2016, are implemented at various governance levels. The research also integrates relevant case laws such as M.C. Mehta v. Union of India (India), which expanded environmental jurisprudence through judicial activism, and emerging legal developments in Kenya and Bangladesh related to climate resilience and environmental justice.

Agriculture is rapidly evolving with the integration of advanced technologies, and AI-driven smart farming systems are becoming essential for modern agricultural practices. While traditional farming techniques require extensive manual effort and are affected by unpredictable environmental conditions, AI-powered tools offer precision, efficiency, and data- driven decision-making to optimize farm productivity. This research paper examines the scope, applications, and impact of AI-driven agriculture optimization systems in smart farming. The study uses a descriptive research design and primary data collected through a structured Google Form survey from 25 farmers and agriculture students. Data was using frequency tables, charts, and percentage analysis. The findings reveal that a majority of respondents are aware of AI-based tools such as IoT sensors, drones, soil monitoring systems, automated irrigation, and data analytics platforms, and many are already using them for crop health monitoring, weather prediction, and resource management. The study highlights several benefits of AI in agriculture, including increased yield, reduced water usage, early pest detection, lower production cost, and improved decision- making accuracy. Farms utilizing AI technologies showed higher productivity and better crop quality compared to traditional methods. However, challenges such as high installation cost, lack of technical knowledge, and poor rural connectivity still limit widespread adoption. The study concludes that AI-driven agriculture optimization is a transformative solution for building a sustainable and efficient farming ecosystem. It recommends awareness programs, farmer training, government support, and affordable technology models to increase AI adoption and maximize agricultural output.

A financial system of any country refers to a system that helps in creation of wealth by establishing a smooth and efficient relationship between the borrowers and the lenders by linking savings with investments. The financial system plays an important role in the economic development of a country by accelerating the process of capital formation. This paper speaks about the details of Indian financial system and its organization structure. The study walks you through the organized or formal financial system and unorganized or informal financial system in India. The report not only gives insights into the Indian financial institutions and markets, its classifications and key players, but also contains history and development of the Indian financial institutions. The paper contains sufficient information to educate the reader about the different aspects of the Indian financial system such as financial institutions, financial markets, financial instruments, financial services and informal financial system of India. An overview of the present scenario towards the end provides a better understanding of the concept of Indian financial system to the readers.

The rapid evolution of digital banking has transformed financial services, promoting inclusion, operational efficiency, and sustainable economic growth. This study examines the integration of advanced technologies blockchain, cognitive computing, artificial intelligence, and edge/cloud computing within digital financial ecosystems to enhance security, resilience, and user-centricity. A systematic literature review of peer-reviewed, Scopus-indexed articles published between 2018 and 2025 was conducted, focusing on technological adoption, ecosystem strategies, governance, and socio-technical barriers in emerging and rural markets. The findings indicate that technology-driven integration significantly improves transaction integrity, operational efficiency, and predictive capabilities, while ecosystem collaboration among banks, fintech firms, regulators, and users fosters inclusive adoption and trust. Socio-technical factors, including digital literacy, infrastructure limitations, and cybersecurity concerns, remain critical constraints that influence adoption outcomes. The study underscores the importance of holistic approaches combining technological innovation, governance, ecosystem design, and user engagement to build resilient and inclusive digital financial systems. The insights provide practical implications for policymakers, financial institutions, and regulators seeking to advance secure, efficient, and sustainable e-banking services.

This paper offers a comprehensive analysis of how the National Education Policy (NEP) 2020 seeks to re-anchor India’s educational framework within its indigenous knowledge systems (IKS) and literary traditions. Historically, India stood as a global centre of learning, attracting scholars such as Fa-Hien and Hiuen Tsang to its universities, monasteries, and philosophical schools. Ancient India developed highly sophisticated intellectual traditions in literature, aesthetics, mathematics, linguistics, metaphysics, political theory, Ayurveda, architecture, and ecology. However, colonial intervention, coupled with the structural dominance of English education, alienated generations of Indians from these native epistemologies. NEP 2020 aims to reverse this trend by fostering multilingualism, cultural rootedness, and integration of classical texts, oral traditions, and local knowledge into mainstream curriculum. In parallel, Indian English literature serves as a channel through which indigenous philosophies, narrative modes, and aesthetic theories are transmitted to global audiences. This paper examines the reciprocal relationship between Indian English and Indian knowledge traditions, demonstrating how the linguistic hybridity of Indian English becomes a tool for cultural reclamation rather than cultural loss. The study engages with literary works, aesthetic theories, oral narratives, and educational principles to illustrate how NEP 2020's vision of holistic, inclusive, and culturally contextualized education aligns with India’s civilizational ethos.

Food security is universally recognized as one of the most salient components of human development, representing a condition in which all individuals, at all times, possess physical, social, and economic access to safe, sufficient, and nutritious food. Food security enhances access and allows them to lead active and healthy lives.

An oral ulcer is a lesion that appears on the membrane of the mouth. A breach in the buccal cavity's mucosal surface, as defined. Uncovered sores of the mucous membrane or surface where inflammatory dead tissue has been removed are called ulcers. Many diseases have unknown etiopathogenesis despite their high occurrence. It often causes pain and is followed by bleeding, swelling, and redness in the affected area. A person's eating habits may change as the mouth ulcer heals, and it frequently causes pain and suffering. They may be categorized as acute or chronic based on how they manifest and develop. Behcet's disease, recurrent aphthous stomatitis, bacterial and viral infections, allergic reactions, and adverse medication reactions are all associated with acute ulcers. Oral lichen planus and other conditions are associated with chronic oral ulcers. Many synthetic drugs can be used to treat mouth ulcers. Due to its cultural acceptance, compatibility with natural things, and lack of adverse effects, herbal medicine is, as we all know, the most widely used basic healthcare. Dietary supplements and lifestyle modifications can help prevent or treat canker sores. Homeopathic medicine is an effective treatment for mouth ulcers. With the use of a carefully selected homeopathic medication, this issue can be fully resolved in a few months. Each person responds differently to homeopathic treatment for mouth ulcers. Homeopathic treatments for mouth ulcers have very promising results and are extremely safe to use.

Microalgal biofilms represent a promising alternative to suspended algal cultures, offering advantages in biomass productivity, stability, and ease of harvesting. These biofilms consist of algae, bacteria, and other microorganisms embedded in extracellular polymeric substances (EPS), which provide structural support and facilitate complex ecological interactions. Algae also plays a crucial role in ecosystem as they are present naturally associated with heterotrophic bacteria and gives an interacting relationship. Algae supply fixed carbon, while bacteria contribute vitamins, siderophores, and growth-promoting factors, creating mutualistic networks that enhance growth and resilience. Such synergistic interactions not only improve nutrient utilization but also support biofilm applications in wastewater treatment, CO? capture, and pollutant degradation. Additionally, microalgal biofilms are valuable platforms for the production of high-value bioproducts, including pigments, polyunsaturated fatty acids, and polysaccharides, and can be engineered into biosensors for environmental monitoring. Recent studies highlight the potential of biofilms as cost-effective systems for industrial bioprocessing, though challenges remain in scale-up, axenic culture, and biofilm heterogeneity. Advances in bioreactor design, strain modification, and EPS manipulation are expected to optimize biofilm performance and broaden their applications. This review summarizes the ecological basis, structural features, and biotechnological potential of microalgal biofilms, emphasizing their role as sustainable systems for environmental and industrial biotechnology.

Since 2014, Prime Minister Narendra Modi’s government has actively employed India’s religious and cultural heritage as instruments of its “Neighborhood First” foreign policy in Nepal. This paper examines India–Nepal relations (2014–2024) with special focus on the role of religious diplomacy and cultural initiatives under Modi. Drawing on official documents, speeches, media reports, and scholarly analyses, it reviews major visits (2014, 2018, 2022) and projects (Ramayana Circuit, Buddhist Circuit, pilgrimage routes, cultural festivals) that highlight shared Hindu and Buddhist heritage. The analysis considers both positive and contentious outcomes. On the positive side, joint initiatives (e.g. Ayodhya–Janakpur bus, Lumbini monastery, sister-city linkages) underscored common civilizational bonds and yielded economic and symbolic gains. However, critics point out that Modi’s religious diplomacy often diverted attention from unresolved political issues (border disputes, transit rights, the 1950 Friendship Treaty, 2015 blockade). In Nepal’s secular polity, excessive emphasis on Hindu symbolism (e.g. Modi’s 2018 pilgrimage tour) raised fears of Hindutva influence and alienated some Nepali stakeholders. The paper concludes that while culture and faith remain important bonds, lasting partnership requires balancing soft-power gestures with concrete economic cooperation and respect for Nepal’s political sensitivities.

This study examined the effect of executive compensation on the financial performance of listed conglomerate firms in Nigeria. Specifically, it assessed the effects of CEO emolument, executive directors’ emolument, and total executive compensation on return on assets (ROA). The study adopted an ex-post facto research design, with a population of six listed conglomerate firms, all of which were included using a census sampling technique. Secondary data were obtained from the audited annual reports and financial statements of the firms covering the period 2015 to 2024. The hypotheses were tested using Panel Estimated Generalized Least Squares (PEGLS) regression analysis in order to address panel heteroskedasticity as well as cross-sectional dependence issues common in panel data. The findings revealed that: CEO emolument has a positive and significant effect on ROA (? = 0.169608, p = 0.0000) at 5% significance level; executive directors’ emolument has a positive and significant effect on ROA (? = 2.996114, p = 0.0000) at 5% significance level; total executive compensation has a negative and significant effect on ROA (? = -2.965274, p = 0.0000) at 5% significance level. The study concluded that executive compensation design remains a central factor shaping how executives drive firm performance through asset optimization and managerial commitment. Hence, it was recommended that corporate governance regulators and audit committees should enforce clearer pay-performance disclosure requirements and set reasonable limits on aggregate executive compensation. Doing so will help reduce excessive compensation spending that does not contribute to improved financial results, ensuring that overall remuneration levels remain sustainable and performance-driven.

Predicting student academic performance is a crucial task in educational institutions, enabling early identification of at-risk students and allowing for timely interventions. Traditional methods of evaluation often rely on static assessments, which may not fully capture the dynamic factors influencing a student's success. This paper proposes a comprehensive framework for student performance prediction using various machine learning (ML) techniques. The study analyzes a dataset comprising student demographics, academic history, and behavioral attributes. We compare the performance of several supervised learning algorithms, including Logistic Regression, ,, Decision Trees, and Random Forest. The models are trained to classify students into performance categories (e.g., "Pass" or "Fail," "High," "Medium," or "Low" performance). Our results indicate that the Random Forest classifier achieves the highest accuracy and F1-score, outperforming other models due to its ability to handle complex non-linear relationships and high-dimensional data. The findings demonstrate the significant potential of machine learning in educational data mining to provide actionable insights for educators, enhance student outcomes, and support the development of personalized learning strategies.

The rapid increase in global waste generation poses significant environmental and public health challenges. Traditional waste management systems are often inefficient, relying on fixed collection schedules that lead to overflowing bins in some areas and unnecessary collections in others, wasting fuel and labor. This paper proposes an Internet of Things (IoT)-based smart waste management system designed to optimize waste collection logistics and improve overall efficiency. The system utilizes ultrasonic sensors mounted on waste bins to continuously monitor fill levels. This data is transmitted in real-time to a central cloud server via a low-power LoRaWAN network. The server processes the sensor data, providing a dynamic overview of the waste status across the city. The proposed system includes a mobile application for waste collection personnel, which uses an intelligent algorithm to generate the most efficient collection routes based on the real-time fill level data. This approach ensures that only bins nearing capacity are collected, significantly reducing fuel consumption, operational costs, and carbon emissions. Experimental results and performance analysis demonstrate that the proposed system can achieve a substantial reduction in waste collection vehicle trips and a more responsive and effective waste management service. The system's scalability and cost-effectiveness make it a viable solution for smart city initiatives aimed at creating a more sustainable urban environment.

This paper investigates the integration of Artificial Intelligence (AI) into sustainable project planning across three critical sectors: offshore platform fabrication, onshore infrastructure projects, and pharmaceutical facilities. By applying AI techniques-such as machine learning, predictive analytics, and digital twin modeling-project planners can enhance decision-making, reduce environmental impact, and optimize resource efficiency. A unified framework is proposed to align AI applications with sustainability goals at the planning stage, tailored to the unique challenges of each sector. Case-based illustrations highlight how AI supports greener outcomes through improved forecasting, waste reduction, and energy optimization. The study demonstrates that AI-driven planning enables more sustainable, data-informed strategies that contribute to both environmental and operational excellence.

Blockchain-based voting systems are gaining attention as a potential solution to the security and transparency issues inherent in traditional and centralized electronic voting methods. The introduction of an IEEE research paper on this topic would typically establish the context by highlighting the limitations of current voting systems and presenting blockchain as a promising alternative Traditional paper-based voting systems, while familiar, are often susceptible to issues like ballot tampering, human error in counting, and logistical complexities, which can erode public trust. Centralized electronic voting (e-voting) systems were introduced to address these problems, aiming for greater efficiency and accuracy. However, they also face significant challenges, including a single point of failure and a lack of transparency, making them vulnerable to manipulation by a central authority or malicious actors Blockchain, a decentralized, immutable, and transparent distributed ledger, offers a compelling solution to these issues. It's a technology that emerged from the crypto currency space but has applications far beyond finance.

The English language and literature have been significantly impacted by the advancement of artificial intelligence (AI), which has altered how we read, write, learn, comprehend, and teach. This article explores the important implications of AI for teaching, critical analysis, language use, and creative production. AI-powered solutions now allow grammar correction, language acquisition, creative writing, and in-depth literary analysis, which is transforming traditional approaches and creating new opportunities for learning and creativity. While AI increases speed and accessibility, it also raises concerns about authenticity, originality, authorship, and academic integrity. The study examines the advantages and difficulties of AI while highlighting the need for proper integration in literary and linguistic contexts. It encourages a human-centered, well-rounded approach where AI is employed as a supplement to human creativity and critical thinking, not as a replacement. This study expands our understanding of the 21st-century interactions between technology and the humanities.

A new generation of autonomous systems that can do complicated tasks with little assistance from humans has been brought about by the quick development of artificial intelligence (AI). The revolutionary effects of AI on autonomous technologies, such as self-driving cars, robots, healthcare automation, defense systems, and smart infrastructure, are examined in this study. Autonomous systems are growing more adaptive, observant, and capable of making decisions by incorporating advances in machine learning, deep neural networks, sensor fusion, and edge computing. The paper looks at the major technological forces influencing this development as well as the moral, legal, and social issues raised by widespread use. It is anticipated that as AI-driven autonomy develops, it will transform public services, industrial operations, mobility, and human–machine cooperation. Building secure, open, and morally sound AI frameworks that maximize productivity and increase quality of life while lowering risks is the key to the future of autonomous systems. This essay focuses on new developments, possible uses, and the general future of AI-enabled autonomy.

This paper explores the critical relationship between adult literacy and women’s social mobility in Zambia, emphasizing the role of literacy as a catalyst for empowerment and gender equality. Notwithstanding significant progress in primary and secondary education, adult literacy rates among women are still low, with important disparities between urban and rural areas. Cultural norms, economic constraints, and limited access to adult education programs remain barriers in acquiring necessary literacy skills, which also constrain their social and economic participation. The study examines Zambia’s socio-economic landscape with respect to high levels of poverty, gendered social norms, and historical influences that shape opportunities within the frameworks of women’s literacy and mobility. Theoretical lenses such as functionalist theory, capability approach, empowerment theory, and human capital theory underpin the analysis in illustrating how literacy improves socio-economic status, agency, and development outcomes. Empirical evidence depicts that literacy enhances women’s job prospects and enables further education, facilitates their active involvement within the community, ultimately leading to gains in decision-making and perpetuating a shift in traditional gender roles. However, cultural beliefs, gender-based violence, and inadequate infrastructure impede progress. Successful initiatives, including community-based programs and international partnerships, demonstrate the potential for improving literacy levels among women. The policy recommendations drawn on expanding gender-sensitive literacy programs, addressing socio-cultural barriers, and fostering community engagement outline ways to improve women’s social mobility. Investing in women’s adult literacy is crucial for reducing poverty and stimulating inclusive national development-a step toward achieving gender equality. Longitudinal studies and new approaches, such as digital literacy, should form part of follow-on research necessary to sustain and amplify the gains. Strengthening adult literacy remains an urgent need if women are to be empowered for sustainable development in Zambia.

This study explores the healthcare experiences of Deaf and hard-of-hearing patients, highlighting the relevance of cultural sensitivity and good communication in medical treatment. It analyses the constraints that inhibit access to quality healthcare, including insufficient provider awareness, inadequate interpretation services, and structural problems within health institutions. Drawing on contemporary research from 2022 to 2025, the study shows persisting issues in patient–provider relations, the impact of communication failures on treatment adherence and satisfaction, and the need of culturally congruent care. The Health Belief Model (HBM) is employed to explain how perceived susceptibility, severity, advantages, barriers, cues to action, and self-efficacy influence Deaf patients’ involvement with healthcare services. Evidence indicates that structural impediments, combined with low provider competency in sign-language and Deaf culture, dramatically decrease patient autonomy and dissuade healthcare-seeking activity. The study reveals shortcomings in African and Nigerian contexts, including insufficient evaluation of interpreter-use results, scarce research on Deaf patient autonomy, and the absence of locally tailored frameworks for culturally sensitive treatment. Implications for practice include enhancing communication tactics, integrating sign-language and cultural competence training into hospital curricula, building inclusive settings, and enforcing governmental measures to assure accessibility. Recommendations stress policy-level reforms, hospital management techniques, professional training, and future research focused on longitudinal evaluations, intersectionality, and context-specific therapies. Overall, the study highlights that creating culturally sensitive, communication-competent, and policy-supported healthcare systems is critical for promoting access, quality, and equity in medical care for Deaf and hard-of-hearing patients.

The Representation of Deaf Characters in Contemporary Cinema and Its Impact on Deaf Culture" examines the depiction of deaf individuals in modern films and the resultant influence on Deaf culture and society. This study rigorously analyses contemporary cinematic trends to evaluate their precision, profundity, and influence on societal conceptions of deafness. Historically, deaf individuals have been portrayed in clichéd or peripheral ways in media. Recent years have witnessed a transition towards more nuanced and accurate portrayals, frequently propelled by the heightened participation of Deaf filmmakers and consultants within the film industry. This examination examines the impact of modern representations on society perceptions of deafness, the formation of Deaf cultural identity, and the enhancement of visibility and empowerment for Deaf individuals. The study assesses various significant films and individuals, examining their contributions to breaking prevailing prejudices and showcasing diverse perspectives within the Deaf community. The study underscores the transformative potential of honest representation by analysing audience reception and the larger ramifications of these portrayals. Moreover, the effects of these film representations on Deaf culture are examined via multiple perspectives, encompassing the enhancement of cultural pride, the advancement of social inclusion, and the impact on policy and advocacy initiatives. The results indicate that, although advancements have occurred, persistent campaigning for more genuine and diverse representations is essential. The study concludes by highlighting the necessity of continuous collaboration between Deaf individuals and the film industry to guarantee that future representations enhance Deaf culture and foster a more inclusive comprehension of deafness.

Raising a deaf child as hearing parents is a journey filled with both complications and unexpected gifts. The primary challenge often revolves around communication barriers. Hearing parents must learn to navigate a world where their natural spoken language may not meet their child's needs. The initial realization of their child’s deafness can bring feelings of uncertainty, fear, and even grief, as parents may struggle to understand how best to communicate and support their child. Learning sign language and understanding Deaf culture are pivotal steps in bridging this communication gap, though it requires time, patience, and a willingness to embrace an unfamiliar linguistic and cultural world. However, the journey also presents unique gifts. Parents often discover a deepened sense of empathy, patience, and creativity as they explore new ways of connecting with their child. They learn that language is not limited to spoken words, and that love, understanding, and expression can transcend sound. Many parents report that raising a deaf child has broadened their perspectives on communication and inclusion, making them stronger advocates for diversity and accessibility, both within their family and in broader societal contexts. Early intervention and access to resources, including educational support and deaf community involvement, play critical roles in fostering a positive experience. Support networks, both online and in person, provide guidance, emotional comfort, and practical advice. Through these experiences, hearing parents often discover that raising a deaf child, while complex, is a deeply enriching experience, offering opportunities for personal growth and a new appreciation for human connection. In the end, the journey becomes more than just navigating a child's deafness it becomes a process of mutual learning, adaptation, and an enhanced view of the world.

In a community where hearing people predominate, deaf parents parenting deaf children encounter a distinct set of opportunities and problems. This study examines the different challenges faced by these families, such as social isolation, communication breakdowns, and restricted access to inclusive resources. It draws attention to the social and academic challenges a kid may face in a hearing-centric environment, as well as the emotional and psychological effects on parents and the child. The study looks at the benefits of having deaf parents for a deaf child in spite of these difficulties, including the development of a rich cultural milieu based on sign language and Deaf identity. The study highlights how crucial it is to promote inclusive policies and community support in order to facilitate integration for both parents and kids. It talks about the value of accessible education, early intervention initiatives, and support for sign language in everyday situations. It also looks at a deaf child's long-term development possibilities, highlighting the requirement of a well-rounded strategy that supports the child's Deaf identity as well as their capacity to function in a world that is predominately hearing. This study gives suggestions for enhancing community support and inclusivity as well as insight into how deaf parents can overcome social barriers to raise a deaf child who thrives. It does this through qualitative analysis and case studies.

Drug addiction affects many diverse groups, but despite being more vulnerable due to barriers to social inclusion, communication, and support systems, the Deaf community is often excluded from discussions about addiction. By investigating the structural, social, and psychological factors that impact drug use and obstruct rehabilitation among Nigerian Deaf individuals, this study explores the intricate link between substance addiction and deafness. The core of this study is the intriguing tale of Joseph Kesuk, a Deaf apprentice from Onitsha whose promising career in carpentry was destroyed by addiction. Joseph, who was born deaf and grew up without a mother, used drugs as a coping method because he experienced ongoing loneliness and a lack of emotional support. His experience serves as an example of the larger issues that the Deaf community faces, such as stigma, lack of inclusive addiction treatment programs, and restricted access to Deaf-friendly mental health care. The study highlights important interventions designed for Deaf people, such as cognitive behavioral therapy, Deaf-friendly rehabilitation, sign language-based therapy, vocational reintegration, and community-based support networks, using qualitative methodologies and a rehabilitative case study approach. Deaf people who are battling addiction can gain from appropriate care that is accessible in their language and culture, as demonstrated by Joseph's recovery story. The report highlights how urgently the Deaf community needs specific approaches in healthcare, education, and law that put their accessibility and inclusivity first. In the end, this study promotes an all-encompassing, compassionate, and rights-based strategy for treating addiction that takes into account the particular lived experiences of the Deaf community in Nigeria and elsewhere.

This essay discusses the processes and connotations of delegated legislation in the area of public service law, with a specific emphasis on the difference between centrallevel and state-level subordinate legislation. Revisiting Indian administrative law, we examine how main acts invest the executive with power to promulgate rules, regulations and orders on service conditions – that is, recruitment, discipline, postings and transfers and how they vary in the central and state contexts. The review considers three dimensions: (i) the extent and character of delegation under central Acts as opposed to state Acts; (ii) the frameworks of control and accountability (including parliamentary control, judicial review and ultra vires litigation); and (iii) service delivery uniformity, federal balance and administrative flexibility. Our research discloses that whereas both levels make use of delegated legislation to complete statutory outlines, central legislation has the tendency to represent wider uniform policy direction, while state subordinate legislation demonstrates more contextual adjustment but also inconsistency in supervision. The research concludes that sound service law requires unequivocal enabling standards, strong supervisions of exercised powers and harmonization between central and state regimes for the sake of ensuring uniformity, transparency and equity in service affairs.

This paper analyzes the major criminal law reforms enacted in India in December 2023, namely the Bharatiya Nyaya Sanhita (BNS), Bharatiya Nagarik Suraksha Sanhita (BNSS), and Bharatiya Sakshya Adhiniyam (BSA), which collectively replace the colonial Indian Penal Code (IPC), Code of Criminal Procedure (CrPC), and Indian Evidence Act. These statutes aim to modernize substantive offences, procedural mechanisms, and evidentiary rules by prioritizing forensic and digital evidence, strengthening victim rights, codifying zero/e-FIR practices, and introducing community-based alternatives to incarceration. This paper evaluates whether this new legal architecture translates into measurable improvements in the effectiveness of criminal justice administration at the ground level.

The Goods and Services Tax (GST), first introduced in India in July 2017, continues to undergo reforms in order to meet the needs of a fast-changing economy. In 2025, the government announced several important changes to make the system simpler and more inclusive. These changes included reducing the number of GST slabs, bringing down tax rates on essential goods such as food, medicines, and agricultural inputs, and raising rates on luxury and harmful products. At the same time, compliance rules have become stricter, with e- invoicing made compulsory for more businesses and a 30-day reporting rule for invoices introduced to reduce tax evasion. These reforms have a direct effect on marginalized communities. On the positive side, cheaper essential items bring relief to poor households, women, and small farmers who spend a large share of their income on basic needs. Lower tax rates on farm machinery and inputs also support marginal farmers. On the negative side, stricter compliance measures create challenges for small shopkeepers and informal workers who often lack digital skills or resources to meet new rules. This research paper studies the balance between these opportunities and challenges, explains the channels through which GST reforms affect different sections of marginalized society, and suggests ways to make reforms more inclusive and people-friendly.

This paper provides a comprehensive review comparing the flexural performance of precast and cast-in-situ reinforced concrete structures. The study focuses on parameters such as flexural strength, ductility, crack propagation, connection behavior, and serviceability. While precast systems offer advantages in construction speed, quality control, and material efficiency, their performance largely depends on connection behavior. Recent advancements, including Ultra-High Performance Concrete (UHPC), Engineered Cementitious Composites (ECC), and mechanical splicing, have notably enhanced the strength and ductility of precast systems. These developments allow precast elements to achieve or even surpass the performance of monolithic concrete. The paper also reviews experimental studies and design approaches, highlighting future research directions related to durability, fatigue resistance, and life-cycle performance of precast structures.

Sepsis is a life-threatening syndrome characterized by dysregulated host response to infection, resulting in widespread inflammation, microcirculatory dysfunction, and multi-organ failure. Among affected organs, the heart is particularly vulnerable, with sepsis-induced cardiac dysfunction emerging as a major determinant of prognosis. Epidemiological data suggest that 30–60% of septic patients develop septic cardiomyopathy, a reversible but often fatal condition marked by global biventricular dysfunction, reduced ejection fraction, and ventricular dilatation. The underlying mechanisms involve inflammatory cytokine storms, nitric oxide overproduction, mitochondrial dysfunction, endothelial injury, and microcirculatory impairment, which collectively depress contractility and impair myocardial responsiveness.Clinical manifestations include hypotension, tachycardia, dyspnea, arrhythmias, and signs of heart failure, often requiring advanced hemodynamic monitoring. Both systolic and diastolic dysfunction of the left ventricle are common, while right ventricular dysfunction results from increased afterload due to pulmonary hypertension. Arrhythmias, particularly atrial fibrillation, further destabilize hemodynamics. Additionally, Type II myocardial infarction arises from oxygen supply–demand mismatch rather than plaque rupture. Diagnosis relies on biomarkers (troponins, natriuretic peptides), echocardiography, and advanced imaging, though no specific marker for septic cardiomyopathy exists. Management is largely supportive, focusing on fluid resuscitation, vasopressors, inotropes, infection control, and antimicrobial therapy, with mechanical support reserved for refractory cases. Emerging therapies targeting inflammatory mediators, oxidative stress, and mitochondrial protection are under investigation. Despite its reversible nature, septic cardiomyopathy is associated with 40–50% mortality, prolonged ICU stays, and long-term cardiovascular risk. Advances in precision medicine, novel biomarkers, and artificial intelligence hold promise for improving diagnosis and tailoring therapy in the future.