संस्कृति किसी समाज की उस सामूहिक जीवन-दृष्टि का नाम है जो सदियों के अनुभवों, परंपराओं और मूल्यों के प्रवाह से निर्मित होती है। इतिहास, कला, भाषा, साहित्य, धर्म और सामाजिक व्यवहार, सब इसके अंतर्गत समाहित होते हैं। संस्कृति स्थिर नहीं, प्रवाहमय है; वह अपने दोषों का त्याग कर नए प्रगतिशील तत्वों को स्वीकार करती चलती है। समकालीन हिंदी कविता इसी सांस्कृतिक प्रवाह की साक्षी है। प्रस्तुत शोध-आलेख में समकालीन हिंदी कविता के सांस्कृतिक एवं धार्मिक संदर्भों का विश्लेषण किया गया है। अरुण कमल, कुमार अंबुज, सत्यपाल सहगल, कुमार विकल और मंगलेश डबराल की चयनित कविताओं के आधार पर यह अध्ययन करता है कि कवियों ने भारतीय संस्कृति की समन्वयकारी एकता, पाश्चात्य संस्कृति के अंधानुकरण, धर्म की विकृति, सांप्रदायिकता, बाजारवाद तथा भूमंडलीकरण जैसे प्रश्नों को किस प्रकार अभिव्यक्त किया है।
आलेख में सबसे पहले भारतीय संस्कृति के महत्व को रेखांकित किया गया है। अरुण कमल की 'हाट' और कुमार अंबुज की 'चँदेरी' जैसी कविताओं में बाजार तथा परंपरागत शिल्प के चित्रण के माध्यम से संस्कृति के जीवंत स्वरूप को देखा गया है। इसके पश्चात पाश्चात्य जीवन-शैली के अंधानुकरण पर सत्यपाल सहगल जैसे कवियों के व्यंग्य का विवेचन किया गया है। धर्म की विकृति और सांप्रदायिकता के प्रश्न पर कुमार विकल, कुमार अंबुज और सहगल की कविताओं का विश्लेषण यह दर्शाता है कि धर्म के नाम पर स्वार्थी तत्व समाज को बाँटते हैं, जबकि हिंसा में बहने वाला रक्त किसी धर्म या जाति का नहीं होता।
अध्ययन से स्पष्ट होता है कि समकालीन कवि संस्कृति को स्थिर धरोहर नहीं, बल्कि प्रवाहमय जीवन-पद्धति मानते हैं। वे धर्म के नाम पर होने वाले शोषण, पहचान-आधारित पूर्वाग्रह और सांप्रदायिक हिंसा का प्रखर विरोध करते हैं तथा बाजार की चकाचौंध में हाशिये पर धकेले गए छोटे व्यापारियों, मजदूरों, किसानों और स्त्रियों के पक्ष में खड़े होते हैं। मंगलेश डबराल और कुमार अंबुज की कविताएँ दिखाती हैं कि बाजारवाद ने चमत्कारों के उत्पादन को सबसे बड़ा व्यापार बना दिया है और उसकी चकाचौंध में साधारण कामगार उपेक्षित हो गए हैं। 1991 के बाद के भूमंडलीकरण ने जहाँ विकास के नए मार्ग खोले, वहीं मनुष्य को परिवार, समाज और स्वयं से विच्छिन्न भी किया, जिसे कवियों ने गहरी संवेदना के साथ दर्ज किया है।
इन कवियों की दृष्टि न परंपरा के प्रति अंध-मोह की है, न आधुनिकता के प्रति अंध-विरोध की। वे संस्कृति के विकृत तत्वों की आलोचना करते हुए सत्य, अहिंसा, समानता और मानवीयता जैसे मूल्यों को बचाए रखने का आग्रह करते हैं। निष्कर्षतः समकालीन हिंदी कविता सौंदर्यबोध की अभिव्यक्ति मात्र नहीं, बल्कि सामाजिक-सांस्कृतिक चेतना जगाने वाला सशक्त माध्यम है, जो पाठक को अपने समय की विसंगतियों के प्रति सजग, संवेदनशील और विवेकशील बनाता है।

Scalp disorders and hair shaft degradation caused by environmental pollutants, microbial dysbiosis, oxidative stress, and harsh synthetic cleansing agents represent a major global dermatological and cosmetic challenge. Conventional shampoos rely heavily on anionic petrochemical surfactants such as sodium lauryl sulfate (SLS) and sodium laureth sulfate (SLES), alongside synthetic preservatives, silicones, and alkanolamides. While effective at rapid sebum emulsification, prolonged exposure to these synthetic excipients strips the protective 18-methyleicosanoic acid (18-MEA) lipid monolayer, alkalinizes the scalp acid mantle, denatures cuticular alpha-keratin, and triggers corneocyte inflammation, contact dermatitis, and ocular irritation. In recent years, polyherbal shampoos rooted in classical Indian Ayurvedic pharmacognosy (Keshya rasayanas) have attracted significant scientific interest as biocompatible, biodegradable, and multifunctional alternatives. Botanical surfactants rich in triterpenoid and steroidal saponins—principally derived from Sapindus mukorossi (Reetha) and Acacia concinna (Shikakai)—reduce interfacial tension and solubilize sebum via micellar encapsulation without disrupting cuticular integrity. Concurrently, polyphenolic, alkaloid, and mucilage-rich botanicals such as Phyllanthus emblica (Amla), Eclipta prostrata (Bhringraj), Azadirachta indica (Neem), Hibiscus rosa-sinensis (Japa), Lawsonia inermis (Madayanti), Trigonella foenum-graecum (Methika), Wrightia tinctoria (Indrayava), and Nardostachys jatamansi (Jatamansi) exert potent antioxidant, anti-Malassezia, 5-alpha-reductase inhibitory, and dermal papilla proliferative effects.

The contemporary media environment has transformed government communication from a largely centralised process into a complex and continuously contested communicative activity. Government press secretaries are consequently required not only to source and disseminate official information but also to employ strategic communication techniques and respond to misinformation, hostile media narratives, public backlash and institutional constraints that may affect government reputation. This study examines the role of government press secretaries in reputation management in selected South-South Nigerian states, focusing specifically on how they source and disseminate government information, techniques employed in managing government representations across media forms, and the challenges encountered in their day-to-day reputation management activities. The study adopted a descriptive survey design and was anchored on Image Restoration Theory and Reputation Management Theory. The population comprised 122 press secretaries attached to governors, deputy governors and commissioners in Bayelsa, Rivers, Akwa Ibom and Delta States. Findings show that press secretaries obtain government information predominantly through official memos, briefings, directives and government documents, while dissemination occurs through press releases, interviews, social media and other formal communication channels. The findings further reveal that clear and audience-tailored messaging, visual communication, media training, regular updates and feedback engagement constitute important reputation management techniques. However, misinformation and fake news, limited resources, the tension between transparency and confidentiality, rapidly changing media environments, public backlash and negative media coverage constitute major challenges. The study concludes that effective government reputation management requires accurate and timely information sourcing, ethically grounded strategic communication, continuous feedback and adequate institutional and technological support. It recommends clearer information-verification procedures, integrated traditional-digital communication strategies, professional capacity development, stronger fact-checking mechanisms and greater strategic autonomy for press secretaries.

This study investigated performance appraisal systems and recognition practices as correlates of teachers' work motivation in public secondary schools in Rivers State, Nigeria. A correlational research design was adopted, guided by four research questions and four corresponding null hypotheses. The population comprised 5,676 teachers across 367 public senior secondary schools, from which a sample of 400 teachers was drawn using a multistage sampling procedure. Data were collected using three researcher-developed instruments: the Performance Appraisal Systems Scale (PASS), Recognition Practices Scale (RPS), and Teachers' Work Motivation Scale (TWMS). The instruments were validated by experts, and Cronbach's alpha reliability coefficients were 0.86 (PASS), 0.83 (RPS), and 0.82 (TWMS). Pearson Product-Moment Correlation (PPMC) answered research questions 1–4, while the t-test for Pearson r tested hypotheses 1–4 at the 0.05 significance level. Findings showed that classroom observation, structured feedback mechanisms, commendation letters and awards for outstanding performance had significant positive relationships with teachers' work motivation. The study concluded that effective implementation of performance appraisal systems and recognition practices enhances teachers' work motivation, and recommended that school administrators institutionalise objective appraisal systems and strengthen recognition practices to sustain motivation and improve educational outcomes.

This study presents these challenges in Telangana through documentary socio-legal research. This looks into the shift from Dharani and the 2020 record-of-rights legislation to the Telangana Bhu Bharati Act, 2022 and related judicial pronouncements, national modernisation policy and scholarship. The study distinguishes between digitisation, registration, mutation, cadastral identification and title. The argument presented in this paper is that while technology may enhance administrative coordination, it cannot independently resolve either conflicts of ownership or historical exclusions. There are various legal issues that arise mainly in connection with electronic evidence, procedural fairness, privacy, and access to correction. Specially noted is the effect of wrong entries in the case of women, tenants, disadvantaged claimants and recipients of land-linked benefits. The paper advocates reliance on verified source records, auditable amendments, accessible remedies, proportionate disclosure, secure infrastructure, and independent evaluation. The conclusions are on institutional design, documented legal matters, rather than measured outcomes statewide or original fieldwork.

Zero Trust Architecture (ZTA) replaces implicit, location-based trust with explicit access decisions that are re-evaluated as conditions change. Research on the topic has spread quickly across enterprise migration, Zero Trust Network Access (ZTNA), cloud-native systems, the Internet of Things (IoT), software-defined networking (SDN), blockchain and 5G/6G networks. Existing surveys map this breadth, but they seldom ask how well the published claims are actually supported. This review examines how recent ZTA research is distributed, what evidence stands behind its security and performance claims, which suspected research gaps survive scrutiny, and how studies can be appraised on a common footing.
Following PRISMA 2020 reporting guidance, we re-verified the 15 studies of an earlier survey and screened 97 new records, which gave 35 included studies published between 2021 and 2026 (21 primary, 14 secondary). Primary studies were profiled with a proposed four-dimension Zero Trust Evidence-Appraisal Framework (ZT-EAF) covering security effectiveness, operational performance, deployment feasibility and evidence quality, deliberately without an aggregate score. Only nine primary studies reported any operational cost, and just three measured both a security outcome and its overhead; all three are non-peer-reviewed preprints. Metrics, environments and baselines differed too much to pool, public artefacts could be confirmed for a single study, and none evaluated failure of the policy engine. Where both were measured, stronger enforcement came at the price of extra latency or resource use.
The field's main shortfall is therefore comparable evidence rather than new architectures. We offer ZT-EAF and a nine-item minimum reporting checklist to make future ZTA evaluations reproducible and comparable.

There is a significant relationship between pornography and the violation of human rights in the adult film industry. This paper proposes that policies should be introduced in accordance with the view to protect the violation of human rights in the film industry. However there are certain factors to be considered like the literacy rate of the people and the awareness among the people about the issue. The main objective of the study is to analyze the major reasons for violation of human rights in the adult film industry and it focuses on the concept of entertainment and profit from cinematic production and artistic production at the expense of human rights and it also analyses the role of internet in the violation of human rights in the adult film industry.The researcher has followed the empirical research method using convenient sampling method. The sample size of the study is 200. The result observed from the study is that the majority of the sample respondents agree that the internet is a major source for violation of human rights in the adult film industry and there is a significant relationship between pornography and violation of human rights in the adult film industry.

Nigerian tertiary institutions are rapidly adopting Artificial Intelligence (AI) tools such as CCTV analytics, facial recognition, and predictive policing software to address rising security threats including cultism, kidnapping, vandalism, and civil unrest. Yet, two persistent challenges undermine effectiveness. First, technological determinism leads many institutions
to treat AI as a substitute for human security personnel, resulting in over-reliance, system failures, and diminished trust among staff and students. Second, most AI models are imported without adaptation to Nigeria’s resource constraints, socio-political realities, and gaps in human capacity, creating a contextual mismatch. As a result, there remains limited empirical evidence on how human security managers and AI systems should interact the human-AI nexus to produce security outcomes that are effective, ethical, and sustainable.
This study seeks to develop and validate a Hybrid Intelligence Framework for managing security apparatus in Nigerian tertiary institutions. Anchored in Human-AI Interaction Theory, Institutional Theory, and the Resource-Based View, the research employs a sequential explanatory mixed-methods design. Phase one involves a survey of security managers, ICT directors, and administrators across 15-20 public and private universities to map current AI adoption, assess levels of trust in AI, and examine perceived security effectiveness. Phase two uses in-depth interviews and focus groups in four case-study institutions to explore lived experiences of human-AI collaboration, decision conflicts, and failure points. Insights from both phases will inform the construction of a Hybrid Intelligence Framework specifying roles, decision-sharing protocols, and training requirements. The framework will be validated through expert panels and a Delphi study involving security professionals and education policymakers.
The study extends Human-AI Interaction Theory to resource-constrained educational contexts in Africa and offers Nigerian universities, the National Universities Commission, and the Ministry of Education actionable guidelines for integrating AI in campus security without displacing human judgment. By centering the human-AI nexus, this research contributes both theoretical insight and practical tools for sustainable security management in the digital age.

In contrast to traditional immediate-release formulations, modified-release medications are pharmacological dosage forms intended to regulate the rate, time, or location of drug release in order to enhance therapeutic performance. Extended-release, sustained-release, delayed-release, controlled-release, and other cutting-edge drug-delivery techniques are examples of these systems. Careful integration of formulation design, drug characteristics, excipient selection, manufacturing procedures, and pharmaceutical quality assessment is necessary for the creation of modified-release medications. To guaranty consistent product performance, factors including dissolving behaviour, drug-release kinetics, content homogeneity, assay, stability, and mechanical qualities are crucial.
Additionally, a formulation's in-vitro release properties can alter pharmacokinetic parameters such drug exposure, peak plasma concentration, and duration of action, which in turn can impact clinical efficacy and safety. Current developments in multiarticulate systems, osmotic delivery, polymeric systems, nanotechnology, and customized medication distribution have
increased modified-release therapy's potential. With a focus on the connection between formulation design, product quality, and therapeutic outcomes, this review addresses the principles, formulation strategies, pharmaceutical quality requirements, release evaluation, clinical performance, advantages, limitations, and regulatory considerations of advanced modified-release medicines.

This investigation delineates the intricate nexus between artificial intelligence (AI) infusion and sustainable innovation within multidisciplinary research institutions, addressing the fragmented comprehension of how AI adoption influences cross-sectoral research outcomes. Analysing secondary panel data from the Scopus and Web of Science repositories for 450 research institutions spanning 2018 to 2024, the inquiry reveals a statistically significant positive relationship between AI integration profundity and sustainable innovation output (β = 0.72, p < 0.01), while institutional collaboration exhibits a lagged moderating effect (β = 0.34, p < 0.05). The findings suggest that strategic AI adoption, coupled with interdisciplinary collaboration, significantly enhances research impact. This inquiry concludes that targeted AI integration policies are indispensable for advancing global academic excellence and provides a robust framework for future multidisciplinary investigations. The study contributes to theoretical discourse by refining the Resource-Based View and Dynamic Capabilities Theory within academic contexts.

Small-scale rice farmers in Pakistan operate under seasonal cash-flow constraints, volatile input costs, weak market integration and recurrent climate-related risks. Agricultural microfinance is frequently proposed as a mechanism for strengthening rural livelihoods, yet empowerment is broader than access to credit alone. This study profiles multidimensional economic empowerment among small-scale rice farmers using a structured questionnaire designed for rice-growing communities in Pakistan. The survey targeted 400 farmers in Punjab, Sindh, Balochistan and Khyber Pakhtunkhwa, following a 15-farmer pilot test. Economic empowerment was summarized through six five-point indicators covering business decision-making confidence, social recognition, household decision-making power, regular saving, spending on technology, health and education, and access to local markets. Each dimension was normalized to a 0-1 scale using the stated min-max transformation. The aggregate index derived from the reported component means was 0.590. Social recognition recorded the highest mean score (3.71), followed by household decision-making power (3.46), welfare-related spending (3.42), business confidence (3.40) and regular saving (3.32). Local market access was the weakest dimension (2.86), and its 95% confidence interval remained below the neutral midpoint of 3.0. The results indicate that empowerment among rice farmers is uneven: social and household-level capabilities appear stronger than market integration. Agricultural microfinance programs should therefore move beyond loan disbursement toward crop-cycle-aligned finance, productive input access, market linkages, practical financial capability and climate-risk protection. The study offers a multidimensional framework for designing rural finance around the capabilities that farmers need to convert financial access into more resilient livelihoods.

Artificial intelligence has become a defining driver of regional economic competitiveness, innovation, and industrial transformation. India's AI landscape, however, is highly uneven, with a small number of metropolitan clusters capturing the majority of investment, talent, and institutional capacity. This paper presents a comparative analysis of the artificial intelligence ecosystems in Belagavi, an emerging tier-two city in Karnataka, and Bangalore, an established global technology hub. Using a conceptual framework supported by real secondary data from government, industry, and international sources, the study examines six dimensions: technological infrastructure, innovation capacity, talent availability, institutional support, industry adoption, and regional development determinants. A composite Regional AI Ecosystem Index is proposed and applied to structure the comparison. The analysis shows that Bangalore possesses mature infrastructure, dense talent pools, strong venture capital access, and globally connected research institutions, while Belagavi offers lower operating costs, emerging industrial clusters, and growing academic capacity, but faces deficits in specialized AI talent, high-speed connectivity, research funding, and startup financing. The paper argues that Belagavi's AI trajectory depends on deliberate policy intervention, industry-academia linkage, and regional specialization rather than replication of Bangalore's model. The findings have implications for policymakers, universities, and firms seeking to build inclusive and distributed AI ecosystems in India.

Electrical machines remain among the most failure-prone assets in industrial settings, and the cost of unplanned downtime keeps pushing engineers toward earlier, more granular fault detection. Conventional condition monitoring tends to be reactive: faults are confirmed only after symptoms surface, by which point efficiency has often already degraded. Digital twin technology offers a way to close that gap, yet much of the published work treats fault diagnosis and performance optimization as separate problems rather than as stages of one continuous loop. This study addresses that separation directly. It pursues two objectives: first, to design a four-layer digital twin framework architecture for real-time condition monitoring of electrical machines, and second, to evaluate, through software-in-the-loop simulation, the intelligent control mechanisms that allow the framework to act on what it detects. A Python-based synthetic data generator produced time-series signals for stator current, vibration, temperature, and voltage under one healthy and four faulty conditions; the stream was ingested into InfluxDB and queried by a fault-classification model linked to a rule-based control layer. Under simulated load the pipeline sustained an ingestion throughput of 10,000 records per second while classifying every window (95th-percentile detection latency 145 ms) and saturated near 35,700 records per second; in sequential operation the median end-to-end detection latency was 99 ms. Five-class classification accuracy was 97.0% under five-fold cross-validation, with bearing wear and mechanical misalignment separated without error and the remaining errors confined to the boundary between healthy operation and winding overheating. In a 120-second closed-loop scenario, the load-adjustment response held simulated winding temperature to a peak of 87.3 °C, where the same fault without a response reached 100.5 °C. These figures describe the software architecture’s behavior under load, not the physical response of a deployed motor. The framework demonstrates that monitoring and optimization can be unified within a single orchestrated pipeline, and it points toward hardware validation as the logical next step.

The setting for this research and experiment is Abia State University, and the work discuss the development of an IoT-based smart irrigation system for the promotion of sustainable and efficient farming practices at Abia State University. The issue of watering, inaccuracy, and a lack of irrigation control through irrigation was addressed through IoT-based water conservation and the maintenance of optimal soil moisture levels. The capacitive soil moisture sensor and the soil water level sensor are used to track the soil condition and the irrigation water available at real time. These sensors are used to feed the data necessary for smart irrigation. An ESP32 is the brain of the whole setup, which has Wi-Fi built into it, transmitting the data received from the sensors to a mobile app, which can remotely display the data. Watering is done through a solenoid valve and a relay. Flexibility will be automatic or manual. For the automatic mode, the system will irrigate the plot whenever the soil moisture level falls below set ranges and will control the system as soon as the soil moisture level returns to normal. Manual control allows the farmer to irrigate the plot through the Blynk app whenever they want. The Blynk app will enable the farmer to monitor the soil moisture level and control the system through the remote control system offered by the app. The Blynk app will display the readings from the sensors and the status of the system.The test results reveal that the system adapts to a change in soil moisture level and makes a significant reduction in water consumption compared to traditional methods. The system is designed with low-cost components that are easily available, meaning that it can be scaled up for use in several plots or even fields. In conclusion, this smart irrigation system, which is based on IoT technology, is an appropriate approach to precision irrigation that improves agricultural productivity in university campuses and nearby agricultural communities.

The effectiveness of financial management practices in Urban Local Bodies (ULBs) of Tamil Nadu has become increasingly critical for sustainable urban development and governance. This study examines the current financial management systems, revenue generation mechanisms, expenditure patterns, and fiscal accountability measures across selected ULBs in Tamil Nadu. Through a mixed-methods approach combining quantitative analysis of financial data from 2019-2024 and qualitative interviews with key stakeholders, the research evaluates the strengths and weaknesses of existing financial practices. The findings reveal significant variations in financial performance across ULBs, with particular challenges in revenue collection efficiency, budget utilisation, and implementation of accrual-based accounting systems. While some ULBs demonstrate innovative practices in resource mobilisation and expenditure management, others struggle with basic financial management functions. The study identifies key factors influencing financial management effectiveness, including institutional capacity, technological adoption, and governance structures. Based on these findings, the research proposes a framework for enhancing financial management practices, emphasising the need for capacity building, technology integration, and strengthened accountability mechanisms. These recommendations aim to improve the financial sustainability and service delivery capabilities of Tamil Nadu's urban local bodies.

The article provides a comprehensive analysis of academic definitions of demogeographic concepts and offers a theoretical and methodological substantiation for their formation in the 8th-grade geography course under educational modernization. Based on a multi-level comparative analysis, a significant conceptual gap is identified between dynamic academic discourse and the simplified, static interpretations of "migration" and "depopulation" definitions embedded within the current model curricula of the New Ukrainian School (NUS). The methodological toolkit for navigating "definition pluralism" in classroom instruction through interactive technologies, Comparative Concept Matrices, population pyramid analysis, demographic modeling, and signal outlines is substantiated. Particular attention is paid to the integration of the regional component using the case study of the Chernihiv region as a strategic border territory undergoing severe geodemographic deformations. The spatial-temporal transformations of human capital in the region induced by military aggression are characterized, specifically focusing on the intense population outflows from the vulnerable northeastern border zones toward the relatively safer regional economic axis. It is demonstrated that integrating local contexts that link forced migration to cascading socioeconomic and ecological consequences serves as an effective instrument for cultivating students' critical thinking and spatial awareness.

Choosing skincare and makeup products that suit an individual’s skin usually relies on manual research, trial and error or generic advice, and questionnaire-based applications rarely analyse the face directly or consider several skin attributes together. This paper presents DermaVision, an AI-powered web application that estimates skin type, skin tone and acne concern level from a user’s selfie and recommends skincare and makeup products matched to the resulting skin profile. The analysis pipeline uses face-api.js for browser-side face detection, OpenCV for image preprocessing, EfficientNet-B0 convolutional models for skin-type (Dry, Normal, Oily) and acne-severity classification, and a K-Nearest Neighbors (KNN) classifier on skin colour values for skin-tone classification. Products are ranked by cosine similarity between the user’s skin profile and product feature vectors. The application is built with React.js, Node.js and Express, and Python AI services, with product recommendation data stored in CSV format and application data in MongoDB. On validation data, the project reports an accuracy of 80% (precision 82%, recall 80%, F1-score 80.5%) for skin type, 84% (precision 83%, recall 82%, F1-score 82.5%) for acne severity and 81% accuracy for skin tone. Dataset sizes, the validation protocol and independent test results are not fully specified, so these figures are indicative only. DermaVision supports product discovery and does not provide a medical diagnosis. Planned work covers e-commerce integration with price comparison, weekly routine tracking and skin progress monitoring.

Visually impaired people face daily difficulty in handling money, avoiding obstacles and asking for help in an emergency. This project presents a low-cost smart glasses system that supports these needs through an ESP32-CAM module mounted on a spectacle frame and a companion Android application. The ESP32-CAM captures images and streams them over Wi-Fi to the smartphone, where the processing is done. A TensorFlow Lite image-classification model, trained with Google Teachable Machine, recognises Indian currency notes of ₹10 to ₹500 and announces the value through text-to-speech. An ultrasonic sensor detects nearby obstacles and warns the user with a buzzer or vibration that gets faster as the distance decreases. A single push button controls the system: a press starts the currency reader, and a long press triggers an SOS alert. When SOS is triggered, the app gives a short cancel window, obtains the GPS location, and sends an SMS with a Google Maps link to a registered caregiver. The prototype is built on a budget of about ₹2000 using commonly available components, and it is intended as an affordable assistive aid that improves safety and independence for visually impaired users.

Background: Teaching homoeopathic repertory has traditionally relied on didactic instruction focused on the mechanical structure of books. Evaluating how different philosophical methodologies—such as Boenninghausen’s macro-reconstructive approach (combining fragments into a complete symptom) and Kent’s deductive approach (general symptoms down to particulars)—are taught using modern interactive methods is essential for clinical competence.
Objectives: To evaluate the educational efficacy of Case-Based Learning (CBL) in teaching Boenninghausen’s versus Kent’s repertorial methodologies to third-year Bachelor of Homoeopathic Medicine and Surgery (BHMS) students.
Methods: A prospective, comparative educational trial was conducted with 100 third-year BHMS students randomized into two parallel arms: Group K (Kentian CBL framework, n = 50) and Group B (Boenninghausen CBL framework, n = 50). Both groups received identical clinical case profiles over an 8-week period but processed them using their respective methodology via structured group workshops. Academic output was evaluated using a blind-vetted multi-component clinical assessment (0–100 marks) and a Repertorial Confidence Survey (1–5 Likert scale).
Results: Group K demonstrated significantly higher proficiency in initial case synthesis and hierarchical ranking of symptoms (82.4 ± 6.8 vs. 74.1 ± 8.2; \(p < 0.001\)). Conversely, Group B excelled significantly in extracting pathological generals and managing complex, structurally incomplete chronic cases (79.8 ± 7.1 vs. 68.5 ± 9.4; \(p < 0.001\)). Subjective confidence in cross-repertorisation advanced by two Likert steps in both cohorts.
Conclusion: Case-Based Learning effectively bridges classical repertorial philosophy and clinical practice. While Kentian methodology taught via CBL enhances deductive logic, Boenninghausen’s framework adapts better to challenging cases lacking clear mental characteristics. Both should be integrated into interactive BHMS curricula.

Small and Medium Enterprises (SMEs) often manage employees, attendance, projects, meetings and reports in separate tools, which leads to manual data entry, data silos and slow managerial decisions. This paper presents AURA (Artificial Unified Resource Analytics), a web-based, AI-enabled Enterprise Resource Management System designed for SMEs. AURA centralises employee, department, attendance, project, meeting and report management in a single Flask application backed by a SQLite database, and applies role-based access control through separate manager and employee interfaces. Real-time executive dashboards, automated PDF and CSV reports and a deterministic Business Health Overview, a score from 0 to 100 that combines attendance consistency, project milestones and meeting discipline, give managers an integrated view of organisational performance. Two pretrained foundation models extend the platform: Amazon Chronos-2 for attendance forecasting and TabPFN for employee risk classification. Project Delay Prediction, Employee Workload Prediction and a WhatsApp Business Health Summary are identified as Phase 2 work and are not presented as operational. The contribution of the paper is a system design and implementation that combines transactional SME operations with lightweight embedded analytics, positioned against a survey of the literature on AI adoption, project management, business intelligence and ERP in SMEs. No accuracy, efficiency or user-study results are reported because none were available; the AI components are described as integrated rather than experimentally validated, and quantitative evaluation with authorised SME data remains future work.

Background: Contact dermatitis is a highly prevalent inflammatory skin condition characterized by localized pruritus, erythema, and eruptions triggered by exogenous allergens or irritants. In homoeopathy, Boger Boenninghausen’s Characteristics and Repertory (BBCR) is uniquely structured to handle such presentations, as it prioritizes pathological generals, localized tissue changes, and causative factors over mental rubrics to find the constitutional similimum.
Objective: To evaluate the clinical utility of Pathological Generals and Causation rubrics from the BBCR in the homoeopathic management of contact dermatitis.
Methodology: A randomized, clinical study was conducted involving 60 patients diagnosed with contact dermatitis. Patients were selected based on well-defined inclusion and exclusion criteria. Case taking emphasized the exciting cause (chemical, occupational, or environmental exposures) and pathological generals (nature of skin lesions, modalities, and characteristic discharges). Repertorization was strictly performed using the BBCR framework. Assessment was carried out at baseline and during follow-ups using the Dermatological Life Quality Index (DLQI) or Severity Score of Contact Dermatitis scales over a period of 6 months.
Results: Out of [60] patients, statistically significant improvement was observed in 75% of cases. The utilization of BBCR rubrics from the Skin, Sensations and Complaints in General, and Causation chapters led to high accuracy in remedy selection. The most frequently indicated remedies were Rhus Toxicodendron, Graphites, Sulphur, and Arsenicum album. The paired t-test showed a statistically significant reduction in symptom scores post-treatment (p < 0.05).

The phrase "Media Trial" refers to journalistic media coverage that goes beyond reporting confirmed facts and instead presents unverified allegations, disputed evidence or explanatory commentary in a way that leads the public to believe an accused person is guilty before a legal determination. Within India's constitutional framework, this incident creates a fundamental tension between the constitutional right to freedom of speech & expression guaranteed under Article 19(1) (a) and the Indian constitutional protection of life, dignity, and procedural fairness in criminal cases. The examination examines the definition and implications of media trials, relevant constitutional and legislative provisions, and the way Courts reconcile Press freedom with judicial administration. Using a principled analytical approach based on constitutional text, statutory law and significant judicial precedent, the research study argues that journalism serving public interest and investigative reporting warrants ongoing legal protection while false allegations, unauthorized disclosure of confidential identities, prejudicial statements The present research study proposes measures including accurate source attribution, clear demarcation between unsubstantiated allegations and substantiated facts, protection of individuals at risk, timely remediation, enhanced editorial protocols, and appropriately calibrated judicial remedies. The conclusion of the study emphasizes that the proper aim is not to restrict media coverage of judicial matters but to ensure that media reporting does not replace the formal legal decision-making process.

The rapid advancement of generative AI has led to the emergence of full-body deepfakes synthetic videos that manipulate not only faces but also entire body movements, gestures, and postures. Traditional deepfake detection methods focus primarily on facial artifacts (e.g., inconsistent eye blinking, unnatural skin texture) and fail when the manipulation extends to the body or when faces are occluded. This research paper presents a novel pose-aware hybrid deep learning framework for full-body deepfake detection that integrates a Pose Estimation Module (PEM) with a dual-stream architecture combining a Residual Network (ResNet-50) and a Vision Transformer (ViT). The system first extracts 2D skeletal keypoints (17 body joints) from each video frame using a pre-trained pose estimator (OpenPose). These keypoints are fed into a temporal Graph Convolutional Network (GCN) to capture pose dynamics, while the RGB frames are processed by ResNet-50 (for local texture artifacts) and a ViT (for global spatial inconsistencies). A cross-attention fusion layer integrates the three feature streams (ResNet, ViT, pose GCN) to produce a final classification (real vs. fake). The model is trained and evaluated on two large-scale datasets: the Full-Body Deepfake (FBD) dataset (50,000 real and 50,000 fake videos, including full-body manipulations generated by PoseGAN, Liquid Warping GAN, and diffusion-based models) and the DeepFake Detection Challenge (DFDC) extended with body annotations. The proposed hybrid model achieves state-of-the-art performance: 98.4% accuracy, 0.99 AUC, and 96.7% F1-score, outperforming single-stream baselines (ResNet only: 91.2%, ViT only: 93.5%, pose GCN only: 87.3%). Ablation studies show that pose awareness contributes a 5.2% absolute improvement in accuracy. The system also generalises to unseen manipulation methods (zero-shot setting) with 84.6% accuracy. The paper discusses the importance of pose consistency for deepfake detection, the computational overhead of pose extraction, and robustness against adversarial attacks. Future directions include real-time detection, cross-dataset generalisation, and integration with audio-visual synchronisation.

The COVID-19 pandemic has increased awareness and the importance of hand hygiene, with frequent use of disinfectants potentially causing dryness and increasing the demand for hand creams. While handwashing and disinfectant use are essential to reduce the spread of viruses and bacteria, they can damage the skin, causing dryness, cracking, and sores. Excessive use alters the skin's pH and causes loss of natural hydration, making users more vulnerable to viral and bacterial infections as a result of this water loss. Therefore, this research aims to produce a natural product with moisturizing potential for hands, evaluating its moisturizing power in vitro. For this purpose, sugarcane molasses was chosen, associated with hydroxy ethyl cellulose and low molecular weight (HMW) sodium hyaluronate. The results demonstrate the potential use of Sugar Cane Molasses as an occlusive and moisturizing agent, compared to formulation components and industrial products.

The increasing adoption of artificial intelligence in e-commerce has created opportunities for virtual try-on systems that enable users to visualize different clothing items on their own photographs. However, integrating generative artificial intelligence through application programming interfaces (APIs) can introduce significant operational costs due to image input processing, token consumption, and repeated image-generation requests. This paper proposes a cost-efficient AI-based virtual try-on framework designed to support multiple clothing categories while reducing API usage costs without unnecessarily compromising visual quality. The proposed system accepts a user's photograph and a selected garment image and processes these inputs before forwarding them to a generative AI model for virtual garment visualization. Image resizing, compression, and prompt optimization are explored as cost-reduction strategies to minimize unnecessary input data and improve resource utilization. The system employs a React.js and Vite-based frontend and a FastAPI backend to manage user interactions, image preprocessing, and API communication. The framework aims to preserve important visual characteristics, including garment color, texture, patterns, and design details, while maintaining the user's facial identity and body appearance. Unlike approaches that focus exclusively on visual generation, the proposed framework emphasizes the relationship between image preprocessing, API consumption, generation efficiency, and output quality. Its effectiveness can be evaluated by comparing API usage costs, input token consumption, image-generation latency, and visual fidelity before and after optimization across different clothing categories. The proposed work seeks to provide a practical foundation for developing economically sustainable, AI-powered virtual try-on applications for online fashion retail.

In the digital era, organizations generate enormous volumes of data through business transactions, digital platforms, information systems, sensors, and customer interactions. Extracting meaningful insights from this data has become essential for effective and timely decision-making. Data analytics provides a systematic approach to collecting, processing, analyzing, and interpreting data to support strategic, tactical, and operational decisions. This article examines the role of data analytics in smart decision-making, focusing on analytical techniques, technological developments, practical applications, implementation challenges, and future research opportunities. It discusses descriptive, diagnostic, predictive, and prescriptive analytics and explains how artificial intelligence, machine learning, big data technologies, and data visualization contribute to decision processes. Applications in business management, healthcare, education, finance, and public administration are explored. A conceptual framework is proposed to integrate data collection, preprocessing, analytical modeling, insight generation, decision implementation, and continuous evaluation. The article also highlights challenges associated with data quality, privacy, security, algorithmic bias, interpretability, and organizational readiness. It adopts a conceptual research approach supported by existing literature rather than claiming new experimental findings. It concludes that analytics can improve the quality, consistency, and timeliness of decisions when supported by reliable data, appropriate analytical methods, human judgment, and responsible data governance.

ParkEase is a proposed web platform that connects drivers seeking parking with land owners offering vacant spaces for short-term rental. The system enables users to discover listed parking spaces within a configurable radius, initially 500 metres, compare prices, check booking availability, and reserve a suitable space for an hourly or daily duration. Owners can publish location details, photographs, access conditions, space dimensions, and optional electric vehicle (EV) charging facilities. Vehicle brand, model, and verified dimensions support preliminary checks of whether a vehicle can fit within the offered space. An EV filter presents connector type, charging power, and availability when supplied by the owner or a connected charging service. Customer, owner, and administrator dashboards support booking management, listing verification, subscription plans, and issue reporting. The design combines location-based discovery with time-slot booking and controlled contact sharing. This paper presents the proposed architecture, methodology, data model, and evaluation plan; no measured deployment results are claimed.

The AI-Powered Application Security Testing and DevSecOps Platform is an intelligent security platform designed to improve application security through automated vulnerability detection, analysis, and secure deployment. The platform combines Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) to analyze application source code and running applications for vulnerabilities such as SQL Injection, Cross-Site Scripting, Command Injection, Broken Access Control, hardcoded secrets, and security misconfigurations. A key feature of the system is its vulnerability correlation mechanism, which compares SAST and DAST findings to identify related security issues and reduce duplicate results. Detected vulnerabilities are classified into Critical, High, Medium, and Low-priority levels with supporting evidence such as source-code locations, endpoints, parameters, and runtime behavior. An AI-based analysis module explains the detected vulnerabilities and provides suitable remediation guidance to help developers fix security issues. The system also includes a CI/CD Security Gate that evaluates security results based on predefined policies and can block vulnerable applications from deployment. By integrating automated security testing, vulnerability correlation, AI-assisted remediation, and secure deployment, the proposed platform aims to provide continuous application security throughout the software development lifecycle.

Passengers in rural areas often wait at bus stops without knowing whether a bus is coming, how far away it is, or when it will arrive. Commercial vehicle-tracking solutions depend on dedicated GPS hardware and subscriptions, which small rural operators cannot afford. This paper presents the Smart Rural Bus Tracking System, a low-cost, real-time tracking platform that needs no dedicated GPS device: the location of the driver&#39;s own Android smartphone is used instead. A driver application written in Kotlin reads the phone&#39;s GPS through the Fused Location Provider about every ten seconds and sends it to a Django backend over a secured REST API. A trip is started only when the driver enters a unique, single-use 8-digit activation code generated by the administrator, which links the driver, bus and route for that trip alone and becomes invalid when the trip ends. Because rural mobile coverage is unreliable, every reading is first saved in a local Room database and is deleted only after the server has confirmed it, so locations recorded without internet are uploaded later and not lost.

Parkinson’s disease (PD) is a progressive neurological disorder associated with motor and non-motor symptoms, including tremor, bradykinesia, gait changes, and speech impairment. Early recognition and ongoing monitoring are important, yet clinical assessment can be complex and symptoms may vary across individuals. Deep learning (DL) offers a promising research direction for analyzing patterns in voice recordings, gait signals, handwriting, and other digital measurements. This article reviews the role of deep learning in Parkinson’s disease prediction and proposes a conceptual framework that combines data collection, preprocessing, representation learning, model evaluation, and clinically supervised interpretation. Convolutional neural networks (CNNs), recurrent neural networks such as long short-term memory (LSTM), and multimodal architectures are discussed in relation to different data types. The article also considers public voice datasets, evaluation metrics, data leakage, class imbalance, explainability, privacy, and clinical validation. Existing literature suggests technical promise, but reported performance varies and can be inflated by small datasets or unsuitable validation procedures. Accordingly, this article does not report new experiments or claim an achieved prediction accuracy. It proposes a reproducible evaluation plan using participant-level data separation, external validation, and sensitivity, specificity, F1-score, and area under the ROC curve. Deep learning should be treated as a decision-support research tool rather than a replacement for neurologists or a stand-alone diagnostic test.

सम्राट अशोक की धम्मनीति प्राचीन भारतीय राजनीतिक एवं नैतिक चिंतन की एक महत्त्वपूर्ण उपलब्धि है। उनकी धम्मविजय, अहिंसा और धार्मिक सहिष्णुता की अवधारणाएँ शासन, सामाजिक सद्भाव तथा अन्य राज्यों के साथ शांतिपूर्ण संबंधों के संदर्भ में विशेष महत्त्व रखती हैं। कलिंग युद्ध के पश्चात् अशोक ने सैन्य विजय की अपेक्षा धम्मविजय को प्राथमिकता प्रदान की। उनके तेरहवें प्रमुख शिलालेख में युद्ध से उत्पन्न पीड़ा के प्रति पश्चात्ताप और नैतिक विजय की भावना अभिव्यक्त होती है। इसी प्रकार, बारहवें प्रमुख शिलालेख में विभिन्न धार्मिक संप्रदायों के प्रति सम्मान, सहिष्णुता और पारस्परिक सद्भाव पर बल दिया गया है। ये अभिलेख अशोक की नैतिक दृष्टि को समझने के प्रमुख ऐतिहासिक स्रोत हैं।
प्रस्तुत शोध का उद्देश्य सम्राट अशोक की धम्मविजय, अहिंसा और धार्मिक सहिष्णुता के सिद्धांतों का अध्ययन करना तथा वर्तमान भारतीय विदेश नीति के संदर्भ में उनकी प्रासंगिकता का विश्लेषण करना है। आधुनिक भारतीय विदेश नीति में शांतिपूर्ण सह-अस्तित्व, संवाद, अंतरराष्ट्रीय सहयोग, सांस्कृतिक संबंधों और वैश्विक शांति जैसे विषयों का महत्त्वपूर्ण स्थान है। भारत की बौद्ध सांस्कृतिक विरासत भी विभिन्न देशों के साथ ऐतिहासिक एवं सांस्कृतिक संबंधों को सुदृढ़ करने में सहायक है। इस अध्ययन में ऐतिहासिक, वर्णनात्मक एवं विश्लेषणात्मक पद्धति के माध्यम से अशोक के प्रमुख शिलालेखों, ऐतिहासिक ग्रंथों तथा भारतीय विदेश नीति से संबंधित स्रोतों का अध्ययन किया जाएगा। शोध में प्राचीन धम्मनीति और आधुनिक कूटनीति के बीच समानताओं के साथ-साथ उनके ऐतिहासिक, राजनीतिक और व्यावहारिक अंतर को भी स्पष्ट किया जाएगा। यह अध्ययन इस तथ्य को रेखांकित करता है कि अशोक के नैतिक आदर्श आधुनिक भारतीय विदेश नीति के शांतिपूर्ण, सहिष्णुतापूर्ण और सहयोगात्मक आयामों को समझने के लिए एक महत्त्वपूर्ण वैचारिक आधार प्रदान करते हैं।

Battery health matters a great deal in electric vehicles (EVs) because it affects safety, driving range, and when a pack needs servicing. This paper describes NEOVOLT, a small college-level prototype that reads battery voltage and current with an ESP32 microcontroller and sets out a method for estimating State of Health (SOH) as a percentage. The ESP32 samples a voltage-sensor module, converts the raw ADC count into an estimated terminal voltage, and prints the result on a serial monitor. A current sensor is included so that charge can be integrated over time once a suitable load and a calibrated sensor are available. So far the system has been tried only on a small 9 V battery, not an EV traction pack, and three preliminary voltage comparisons against a multimeter are reported. In those readings the ESP32 value was 0.06 to 0.07 V below the multimeter reference. The work therefore presents a measurement workflow and a proposed capacity-based SOH calculation; it does not claim validated SOH prediction for EV batteries.

The process of urbanisation results in a transformation of the natural landscape into an urbanised one, which in turn increases surface runoff and reduces the recharge of groundwater, thereby causing serious instances of urban flooding. To address this issue, the concept of Integrated Blue-Green Infrastructure (BGI) offers a means of managing stormwater in a sustainable manner by combining a number of connected blue infrastructure elements, for example green roofs, rain gardens, wetlands, and urban forests, etc., these contributing to infiltration, the reduction of runoff, and improved water quality. In this study, a methodology based on geospatial technology is applied in order to produce a BGI suitability map by identifying the most appropriate locations for implementation. This methodology, which makes use of remote sensing and geographic information system techniques, examines a variety of factors such as slope, drainage density, land use/cover, and proximity to roads. Core patches are chosen to act as ecological nodes, the corridors are mapped by means of the least-cost path approach, and the networks are then refined using the gravity model.

The rapid development of Artificial Intelligence (AI) and Large Language Models (LLMs) has introduced new possibilities for providing personalized support to students in higher education. Conventional educational chatbots generally focus on answering questions and providing learning resources, but they may not sufficiently consider the emotional state of a learner during an interaction. A student who is confused, frustrated, anxious, motivated, or confident may require different forms of instructional support even when asking questions about the same academic topic. This paper proposes an emotion-aware adaptive learning chatbot that combines emotion detection, learning-context analysis, and Large Language Model-based response generation to provide personalized student support.
The proposed framework first receives a student&#39;s natural-language query and identifies the probable emotional state expressed in the conversation. The system then analyzes the academic context of the query, determines the student&#39;s apparent learning requirement, and constructs an adaptive prompt for the Large Language Model. Based on the detected emotion and learning context, the chatbot generates a response with an appropriate level of explanation, tone, examples, hints, and learning recommendations. The framework can support common learning-centered states such as confusion, frustration, anxiety, engagement, satisfaction, and neutral interaction. The proposed architecture is designed to remain simple enough for practical implementation in higher education while allowing systematic evaluation of emotion classification, response quality, personalization, and student satisfaction.
The research is motivated by recent literature showing growing use of LLMs and chatbots in education while also identifying limitations related to personalization, emotional responsiveness, privacy, over-reliance, and real-world evaluation. Recent reviews also indicate that affective computing research in online higher education frequently studies confusion, frustration, engagement, and sentiment, but many systems are not validated in actual educational settings. The proposed work therefore connects emotion recognition with adaptive LLM-based educational interaction. The paper presents the conceptual framework, system modules, processing workflow, implementation approach, evaluation methodology, limitations, and future research directions.

The study investigated the association between educational factors, socioeconomic characteristics, and students’ academic performance, based on the SPD24 Student Performance Dataset. A quantitative, observational design was utilized to analyze 98,000 student records across 41 variables . The analysis comprised descriptive statistics, Spearman rank correlations, chi-square tests of independence, Cramér’s V effect-size estimation, ordinal logistic regression, and further comparisons of multinomial logistic regression and XGBoost. The dataset did not contain any missing values, duplicate records, or duplicate student IDs. Academic performance was classified into three categories; Low (24.68%), Medium (37.66%) and High (37.66%). Spearman correlation (ρ = 0.9371, p < 0.001) identified a very strong association between prior academic performance and the outcome, so this variable was left out of the primary regression model to avoid potential target leakage or outcome-construction overlap. Categorical association tests showed a statistically significant association between parental education level and academic performance, but the effect size was negligible (Cramér’s V = 0.0100). Socioeconomic status was the only predictor that was statistically significant at the 0.05 level in the ordinal logistic regression model (β = −0.0290, p = 0.0446). However, the additional classification results showed limited predictive discrimination, with accuracy of 38.08%, balanced accuracy of 33.70%, macro-F1 score of 0.290, and multiclass ROC-AUC of 0.501. In general, the findings indicate that the associations found were mostly weak, and the observational design does not permit causal conclusions.

Out-of-hospital delivery remains a significant contributor to maternal and neonatal morbidity and mortality in Nigeria despite improvements in antenatal care utilization. This study explored nurse-related factors contributing to out-of-hospital delivery among women attending antenatal and postnatal clinics in selected health facilities in Bayelsa State, Nigeria. A qualitative descriptive research design was adopted. Participants were purposively selected from women attending antenatal and postnatal clinics who had experienced out-of-hospital delivery within the preceding two years. Data were collected through three Focus Group Discussions (FGDs) using a semi-structured discussion guide developed from relevant literature. The discussions were audio-recorded, transcribed verbatim, and analysed using thematic content analysis following the six-step approach of Braun and Clarke (2006). The findings revealed six major themes influencing women’s decisions to deliver outside health facilities: nursing workforce availability, negative nurse-related experiences and disrespectful maternity care, fear and distrust of nurses’ clinical recommendations, nurse–patient communication gaps, trust in traditional birth attendants, and nursing service readiness. Participants reported that disrespectful attitudes, inadequate emotional support, poor communication, prolonged waiting time, shortage of nurses, inadequate explanations regarding clinical decisions, and deficiencies in emergency preparedness discouraged them from utilizing health facilities for childbirth. Conversely, traditional birth attendants were perceived as more patient, compassionate, accessible, and emotionally supportive during labour.The study concludes that nurse-related factors substantially influence women’s choice of place of delivery in Bayelsa State. Improving respectful maternity nursing care, strengthening nurse–patient communication, increasing the nursing workforce, enhancing continuous professional development, and improving nursing service readiness are critical strategies for increasing health facility deliveries and reducing preventable maternal and neonatal morbidity and mortality. The findings provide evidence to guide nursing practice, maternal health policy, and interventions aimed at improving the quality and utilization of skilled maternity services.

The growing presence of Chinese construction firms in Uganda has increased the deployment of expatriate workers to culturally diverse environments, highlighting the need to understand factors that enhance expatriate effectiveness. Drawing on Cultural Intelligence Theory, this study examined the mediating role of cultural intelligence in the relationship between pre-deployment training and job performance among Chinese expatriate construction workers in Uganda. A quantitative cross-sectional survey design was employed, involving 212 Chinese expatriates working across fourteen major infrastructure projects. Pre-deployment training was measured using a 12-item scale, cultural intelligence was assessed using the 20-item Cultural Intelligence Scale, and job performance was evaluated using a 9-item supervisor-rated scale. Data were analyzed using Structural Equation Modeling (SEM) in AMOS. The findings revealed that pre-deployment training significantly enhanced all four dimensions of cultural intelligence, namely metacognitive, cognitive, motivational, and behavioral cultural intelligence. Behavioral cultural intelligence exhibited the strongest relationship with training (β = .72, p < .001), followed by metacognitive cultural intelligence (β = .68, p < .001). Furthermore, all dimensions of cultural intelligence positively influenced job performance, with behavioral cultural intelligence (β = .42, p < .001) and metacognitive cultural intelligence (β = .34, p < .001) emerging as the strongest predictors. The results further demonstrated that cultural intelligence fully mediated the relationship between pre-deployment training and job performance, indicating that training enhances performance through the development of intercultural capabilities. The study concludes that cultural intelligence is a critical determinant of expatriate effectiveness in Uganda's construction sector and recommends that multinational construction firms strengthen pre-deployment training programs by emphasizing cultural awareness, intercultural communication, and behavioral adaptability. The study contributes to the literature by extending Cultural Intelligence Theory to the African construction context and demonstrating the central role of cultural intelligence in translating training investments into improved expatriate performance.

Chemical enterprises need a practical way to translate human-factors diagnoses into improvements that survive everyday production pressures. This article develops an action research framework for that purpose through a focused narrative review and conceptual synthesis of 18 scholarly and institutional sources, including a methodological correction. Sources cover action research, chemical-accident analysis, safety behaviour, process-safety governance, and intervention evaluation. The synthesis connects the four levels of the Human Factors Analysis and Classification System with a five-stage cycle of diagnosis, joint planning, action, observation, and reflection. Its analytical outputs are a mapping of human-factor problems to management actions, a two-cycle implementation design, and an indicator architecture separating critical-control performance, reporting activity, occupational injury, and process-safety events. The proposed first cycle examines procedure usability, task practice, and supervisory feedback; the second adapts the intervention in response to documented implementation barriers and observed control performance. Worker participation is specified as a decision process with recorded responses to proposals. Evaluation combines repeated observations, exposure-adjusted outcomes, qualitative explanations, and an explicit record of intervention changes. These are methodological results rather than evidence of an achieved reduction in accidents. The framework offers chemical enterprises a traceable route from diagnosis to organisational learning while preserving engineering controls, formal change management, and independent evaluation. Its effectiveness requires prospective validation in operating facilities.

Herbal hair serums are leave-on cosmetic preparations intended to improve hair feel, manageability, shine, lubrication and resistance to everyday grooming friction through a suitable vehicle combined with selected botanical materials. Interest in plant-derived ingredients has encouraged the use of aloe vera, amla, bhringraj, hibiscus, neem, rosemary and fenugreek in hair-care products. However, a plant's traditional use or activity in a laboratory model does not establish that a finished serum improves hair growth or treats a scalp disorder. Product performance depends on botanical identity, extraction method, phytochemical variability, ingredient compatibility, vehicle composition, deposition on the hair shaft or scalp, preservation, packaging and storage. This narrative review discusses the scientific basis of herbal hair serums, hair structure and cosmetic damage, commonly used botanical ingredients, formulation components, development workflow, evaluation methods, stability and quality control, comparative formulation considerations, safety and Indian regulatory context. Physical and physicochemical tests such as appearance, homogeneity, pH where applicable, viscosity, rheology and spreadability are considered alongside botanical marker analysis, microbiological quality, preservative effectiveness, packaging compatibility and direct assessment of cosmetic performance. Evidence is appraised according to study type, distinguishing hair-fibre testing, in vitro and animal findings, small human studies, traditional use and product-specific clinical evidence. Existing evidence supports rational design and quality testing, but direct comparative studies of standardized finished herbal serums remain limited. Future progress requires authenticated raw materials, reproducible extraction, transparent ingredient specifications, product-specific stability protocols and well-designed human-use studies that assess relevant outcomes without overstating medical claims. Herbal origin should not be treated as a guarantee of safety, stability or superiority. A scientifically developed serum should therefore be judged as a complete formulation whose quality, tolerability, claimed cosmetic performance and reproducibility are demonstrated for its intended use.

Ashwagandha (Withania somnifera (L.) Dunal) is an important medicinal plant in Ayurvedic practice and an increasingly investigated ingredient in contemporary herbal products. Its chemical profile includes steroidal lactones known as withanolides, withanosides, alkaloids and other constituents whose relative abundance varies by plant part, source and extraction process. Experimental studies report antioxidant, anti-inflammatory, neurobiological, endocrine and stress-response effects, while human research has most consistently examined perceived stress, anxiety-related symptoms and sleep. Randomized trials and evidence syntheses suggest potential benefits for selected stress and sleep outcomes, but findings are constrained by small samples, heterogeneous preparations, differences in outcome measures and generally short treatment periods. Evidence for cognition, physical performance, reproductive outcomes and metabolic health is promising in some studies but remains insufficient to support broad therapeutic claims. Much of the evidence for anticancer, neuroprotective and disease-modifying activity is preclinical and cannot be directly translated into clinical recommendations. Safety assessment is essential because gastrointestinal symptoms and drowsiness are reported, rare cases of clinically apparent liver injury have been described, and potential interactions with thyroid, sedative, immunosuppressive, antihypertensive and glucose-lowering medicines warrant attention. Pregnancy and breastfeeding are important precautionary contexts, and long-term safety remains uncertain. This narrative review summarizes botanical identity, phytochemistry, proposed mechanisms, therapeutic evidence, formulation and standardization considerations, safety issues and research priorities. Overall, Ashwagandha is a scientifically interesting botanical with a limited but developing clinical evidence base; reproducible product characterization and adequately powered, independently replicated trials are needed before its uses can be defined more confidently.

Assessment of land suitability and pre-construction risks has been done through laborious, manual site surveys that cannot easily incorporate real-time geospatial and environmental information. In order to address these drawbacks, this paper proposes a Smart Land Analysis Platform, an automated, web-based decision support tool designed for engineers, urban planners and real estate developers. The system architecture consists of a responsive frontend developed using the React/Vite framework together with a fast backend based on FastAPI that runs asynchronously on top of five external spatial APIs: Nominatim for geocoding, ISRIC SoilGrids for soil structure analysis, ESA WorldCover 10 m for satellite land cover classification, OpenStreetMap (Overpass) for mapping of infrastructure and road accessibility, and Open-Meteo Flood for flood risk analysis. The core of this platform is the Multi-Factor Weighted Scoring Algorithm, which aggregates different types of parameters (flood risk, soil load-bearing capacity, environmental constraints and road accessibility) and produces a land suitability percentage and an associated risk category. The platform is intended as a preliminary screening aid and does not replace site surveys, laboratory soil testing or statutory approval.

E-commerce companies collect large amounts of order data, but using it to make sound decisions on sales planning, discounts and returns remains difficult. This study analyses 34,500 orders placed between September 2023 and September 2025 across seven product categories and five regions, using data analysis and machine learning. Total net sales were 5.87 million after discounts of 308,518 (5.0% of sales). Electronics contributed 56.6% of sales, while Grocery lost money on average, with 95.5% of its orders unprofitable. The top third of customers generated 70.7% of revenue. Discounts were associated with lower profit per order but not with more returns. A LightGBM model predicted order-level net sales with R² = 0.987 and MAE = 4.76, but this is largely because net sales are calculated directly from price, quantity and discount, so the model mainly reproduced a known formula. A second LightGBM model, using lagged sales features, forecast monthly net sales between 233,000 and 262,000 for September 2025 to February 2026. Random Forest and Extra Trees models predicting whether an order would be returned reached only about 0.60 ROC-AUC, indicating that the available attributes carry little information about returns. The study also discusses its limitations and presents a Streamlit application and a Power BI dashboard for sharing the results.

Background: Antenatal, delivery and postnatal services provide opportunities to prevent, identify and manage maternal and newborn health risks. Local evidence can help services respond to barriers affecting families. Objective: To examine the association between maternal healthcare utilization and reported child health outcomes among women attending selected government hospitals in Delta North Senatorial District, Delta State, Nigeria.
Methods: The source thesis describes a cross-sectional questionnaire study conducted at Federal Medical Centre, Asaba; General Hospital, Ogwashi-Ukwu; and General Hospital, Ibusa. Its abstract reports 330 respondents. Descriptive statistics and Pearson product–moment correlation were reported. The methods chapter, however, gives a planned sample of 355; the final analytic sample and all statistical outputs must be reconciled with the original dataset before submission.
Results: The thesis reports generally favourable agreement-scale responses for child immunization, lower frequency of illness, normal growth and development, absence of birth complications, exclusive breastfeeding, fewer hospitalizations and good general health (reported grand mean 3.32; n=330). It reports a positive correlation between maternal healthcare utilization and child health outcomes (r=0.906, described as significant at the 0.01 level), and between antenatal clinic visitation and child outcomes (r=0.948, described as significant at the 0.01 level). The available manuscript extract does not show exact p-values, confidence intervals or complete correlation tables; these coefficients are therefore provisional.
Conclusion: The thesis reports strong positive associations between maternal-care utilization indicators and self-reported child health indicators. Because the design is cross-sectional and measures are self-reported, the findings cannot establish causation. The manuscript should not be submitted until the sample discrepancy, correlation tables and coding of composite measures have been checked against the source data.

The study examined Perception and Utilization of National Health Insurance Authority among Healthcare Professional at Federal Medical Centre Asaba with particular attention to Maternal and Child Health Care Services. Three research questions and three hypothesis guided the study. A descriptive–cross sectional design was adopted. The population of the study comprised 1,291 healthcare professional including nurses, doctors, pharmacists, laboratory scientists and physiotherapists. Using the Krejcie and Morgan (1970) sampling technique 330 respondents were selected. A researcher structured instrument titled ‘Perception and Utilization of National Health Insurance Authority - Healthcare Professional Questionnaire (UPHNIA-HPQ) was used for data collection. The instrument was validated by experts and subjected to a reliability testing, a coefficient of 0.89 was obtained by cronbach Alpha to determine internal consistency. Out of the 330 questionnaire distributed 295 were returned valid for analysis representing 89.4%. Data was analysed using frequency, percentages, mean and standard deviation,One-Way Analysis of Variance (ANOVA) and Independent t-test at 0.05 significance. The results showed an overall favorable perception of NHIA services. The level of utilization was also relatively high, with a grand mean of 3.06. Nurses recorded the highest perception mean (3.24), while laboratory scientists recorded the lowest (3.08); however, the difference was not statistically significant (F = 1.681, p = .154). Similarly, nurses recorded the highest utilization mean (3.12), while physiotherapists recorded the lowest (2.88), but the difference was not statistically significant (F = 1.910, p = .109). Gender differences in perception were also not significant (t = -1.19, p = .235), while the gender difference in utilization was not statistically significant (t = -1.72, p = .086). The study concludes that healthcare professionals at Federal Medical Centre, Asaba generally perceived NHIA services favorably and utilized them at a relatively high level, with no statistically significant differences based on professional category or gender. It is recommended that NHIA and hospital management sustain positive aspects of the scheme while improving information, accessibility, administrative efficiency and the overall service experience.

Biologic medicines have transformed the management of cancer, autoimmune disorders, infectious diseases, endocrine disorders, and rare diseases, but their manufacture commonly depends on centralized facilities, specialized cell culture infrastructure, extensive purification, controlled storage, and distribution networks. These requirements can constrain rapid deployment and access, particularly when demand is geographically dispersed or changes suddenly. Cell-free biologics production uses isolated transcription and translation machinery to synthesize proteins outside intact living cells, creating an open and programmable production environment. This review examines the scientific foundations, workflow, expression platforms, applications, enabling technologies, advantages, limitations, and regulatory considerations of cell-free biologics production, with particular emphasis on point-of-care and decentralized medicine. Cell-free systems can reduce the biological constraints associated with host-cell growth, enable rapid genetic reprogramming, support high-throughput experimentation, and facilitate freeze-dried formats that can be stored and activated when needed. Demonstrated applications include recombinant therapeutic proteins, cytokines, enzymes, antibodies and antibody-related products, glycoproteins, vaccines, antimicrobial proteins, and difficult-to-express proteins. Integration with synthetic biology, artificial intelligence, automation, microfluidics, portable reaction hardware, and lyophilization may further support compact manufacturing platforms. However, cell-free production is not yet a universal replacement for conventional biomanufacturing. Important barriers include reaction cost, productivity and stability, folding, post-translational modification, purification, analytical control, sterility, reproducibility, scale-up, validation, and regulatory oversight. The future role of the technology is therefore likely to be complementary: centralized manufacturing will remain important for high-volume products, while validated cell-free platforms may expand rapid, distributed and personalized production for selected biologics and emergency settings.

Background: Older adults living in institutional settings may experience depressive symptoms alongside social disconnection and chronic physical illness. Describing the symptom pattern in this group can help inform assessment and supportive care. Objective: To describe the sociodemographic profile, reported mental and physical symptoms, and recorded physical comorbidities among older residents assessed for separation-related depression in an institutional setting in Jaipur, India. Methods: This descriptive secondary analysis uses aggregate data reported in an existing postgraduate research manuscript. The source manuscript describes 70 residents aged over 50 years who met its stated criteria for depression and were assessed using the 15-item Geriatric Depression Scale (GDS-15). Frequencies and percentages were summarized from the reported tables; no individual-level data were available for re-analysis. Results: Persistent sadness was recorded in all 70 participants (100%), followed by loneliness in 54 (77.1%), feelings of worthlessness or being a burden in 49 (70.0%), irritability or mood swings in 41 (58.6%), and social withdrawal or reduced interest in activities in 37 (52.9%). Sleep disturbance was recorded in 61 (87.1%), loss of appetite in 57 (81.4% based on n=57/70), gastrointestinal discomfort in 52 (74.3%), weight loss in 48 (68.6%), and fatigue or low energy in 44 (62.9%). Osteoarthritis (48/70; 68.6%), hypertension (42/70; 60.0%), and type 2 diabetes (29/70; 41.4%) were the most frequently recorded comorbidities. Conclusion: The records indicate a substantial overlap of emotional symptoms, somatic complaints, and chronic physical conditions in this selected institutional sample. These descriptive findings do not establish causation or population prevalence and support the importance of comprehensive, person-centred assessment in older residents.

Rapid advances in Artificial Intelligence (AI) are reshaping the employment landscape, making some positions redundant while creating new opportunities. Higher education institutions in India must adapt to this evolving environment by incorporating Artificial Intelligence (AI) literacy into their educational programmes. This paper examines the impact of Artificial Intelligence (AI) on job performance and highlights the importance of promoting Artificial Intelligence (AI) literacy within higher education in India. It examines the current status of Artificial Intelligence (AI) implementation in Indian regions, the competencies required for the future workforce, and the barriers facing higher education institutions in delivering Artificial Intelligence (AI) literacy. The paper concludes with recommendations for policy makers, academics, and industry stakeholders to ensure that Indian graduates have the necessary skills to succeed in an Artificial Intelligence (AI)-driven economy.
Currently, a significant amount of data is being managed by most universities in India. This data is used to monitor student admissions, examination processes, academic records, degree verification, and official documents. AI (Artificial Intelligence) has emerged as an important element within the framework of higher education in recent years. According to the 2024 Times Higher Education Survey, nearly 60% of university faculty members are now incorporating AI (Artificial Intelligence) tools into their professional activities. UNESCO (United Nations Educational, Scientific and Cultural Organization) recently stated that AI (artificial intelligence) is changing the way educators teach faster than any educational reform seen in decades. This prompts us to consider:- Will Indian universities simply observe these changes, or will they actively participate in shaping the future of Artificial Intelligence (AI)-powered education across India? The National Education Policy (NEP) 2020 aims to broaden access, enhance research capacity, promote internationalization, and establish world-class institutions. Nevertheless, this objective can only be realized if our universities and colleges are ready for Artificial Intelligence (AI)-integrated educational efforts. Those who embrace this change will prosper. On the contrary, those who resist will be left behind.

This study undertakes a comparative empirical evaluation of the Black–Scholes Model (BSM) and the Binomial Hedging Model in valuing options and hedge positions of five companies listed on the National Stock Exchange (NSE) of India — HDFC Asset Management Company Ltd., Bharti Airtel Ltd., Larsen & Toubro Ltd., Adani Power Ltd., and MRF Ltd. — across sixteen monthly observations spanning April 2024 to July 2025. Using monthly opening and closing prices as proxies for spot and near-term reference prices, the study computes the BSM parameters (S/X, d1, d2, N(d1), N(d2)), the resultant call and put premiums, and a Binomial Hedge Model that scales the spot price across nine hedge-ratio scenarios (0.05 to 0.80), from which variance and standard deviation of the hedged position are derived. Descriptive and comparative statistical analysis reveals those instances where the BSM produced negative and hence economically implausible put premiums for two of the five companies, and a degenerate, boundary-value outcome for Adani Power arising from an extreme standardised moneyness input. In contrast, the Binomial Hedge Model produced internally consistent, monotonically scaling risk measures across all companies, with variance shown to scale with the square of the hedge ratio. The study concludes that the two models are complementary rather than substitutable: the BSM offers an efficient closed-form estimate when volatility and moneyness inputs are correctly calibrated, whereas the Binomial framework offers a more transparent, tractable and numerically robust device for scenario-based hedge-ratio risk management, particularly when the underlying's price behaviour departs from the log-normal, constant-volatility assumptions of the BSM.

Artificial Intelligence (AI) is transforming electronic commerce through personalised product recommendations, intelligent chatbots, predictive analytics, and automated customer support. These applications may influence how consumers search for products, evaluate alternatives, develop trust, and form purchase intentions. This study proposes an empirical investigation of AI-enabled shopping features among online shoppers in Hyderabad, Telangana, India. It focuses on perceived relevance of AI-powered recommendations, AI-driven personalisation, chatbot effectiveness, consumer trust, and perceived privacy risk in relation to purchase intention. The proposed framework draws on the Technology Acceptance Model and established research on trust in online shopping. Primary data are to be collected through a structured questionnaire using a five-point Likert scale. A target of 200–300 eligible respondents is proposed, subject to access and an appropriate sample-size justification. Descriptive statistics, reliability analysis, correlation, and multiple regression are proposed for analysis. As the survey has not yet been conducted, this manuscript does not report empirical findings. The study is designed to provide context-specific evidence on consumer perceptions of AI-enabled e-commerce in Hyderabad and to inform platform decisions concerning personalisation, customer service, privacy, and responsible AI adoption.

Most early-stage founders piece together their startup journey with tools never meant for the job—LinkedIn for finding a co-founder, a WhatsApp group for hearing about events, and whoever they happen to know for mentorship. None of this is coordinated, and a lot of it comes down to luck. This paper describes An Integrated Startup Collaboration Platform, a web application that puts idea validation, co-founder matching, mentor booking, and event discovery behind one login instead of five. The system has five modules: authentication, idea submission and validation, a matching engine, mentor and event booking, and an admin/notification layer. JWT handles authentication, with role-based access so a Founder, Mentor, Organizer, or Admin only sees what is relevant to them. The matching module is the core contribution — it encodes a founder's skills, industry interest, and commitment level, then uses a K-Nearest Neighbors approach to rank other founders by compatibility rather than leaving the search to keyword matching. The stack is React.js on the frontend, Node.js and Express on the backend, and PostgreSQL for storage, chosen mainly because the data involved — founders, ideas, matches, sessions — is relational by nature. The goal is modest but practical: cut down the time a founder spends jumping between disconnected tools and make the co-founder suggestions they get actually worth looking at.
The proposed platform would contribute to achieving Sustainable Development Goal (SDG) 4: Quality Education by promoting mentorship, knowledge exchange, and entrepreneurial education. The initiative will also support SDG 9: Industry, Innovation and Infrastructure since it will provide an avenue for idea development and cooperation among start-up companies in a digital environment. It will also facilitate attaining SDG 17: Partnerships for the Goals by creating a meeting point for founders, mentors, and event managers to share expertise and partnership opportunities to achieve specific goals.

Road accident victims often do not receive timely help because the occupants may be injured or unconscious and unable to tell anyone where the accident happened. This paper presents the Accident Messaging System (AMS), a low-cost Internet of Things (IoT) prototype that detects a possible vehicle accident, warns the occupants, gives a short chance to cancel a false alert, and sends the vehicle location to a predefined contact. An ESP32 microcontroller coordinates an MPU6050 accelerometer, an SW-420 vibration sensor, a NEO-6M Global Positioning System (GPS) receiver, a SIM800L Global System for Mobile communications (GSM) module, a buzzer, a push button and a regulated power-supply stage. A possible accident is flagged when the total acceleration exceeds a threshold of 1.90 g or the vibration sensor is triggered. The buzzer then sounds and a five-second window allows the user to cancel the alert. If it is not cancelled, the system obtains the GPS coordinates, builds a Google Maps link and sends it as a Short Message Service (SMS) message through the SIM800L, which is powered from a dedicated regulated supply. The paper describes the architecture, wiring, power design, detection algorithm, calibration steps and test plan of the prototype, and discusses its limitations, such as the 100 ms polling interval, the GPS start-up delay and the dependence on 2G network coverage. The design is modular and can be extended with higher sampling rates, machine-learning-based severity classification and cloud connectivity.

Safe storage of medicines is an essential aspect of healthcare that ensures the quality, safety, stability, and therapeutic effectiveness of pharmaceutical products. Improper storage conditions, such as exposure to excessive heat, moisture, direct sunlight, and inappropriate temperatures, may lead to medicine degradation, reduced efficacy and potential health risks. The present study aims to create awareness among the general public regarding the importance of proper medicine storage practices and to assess their knowledge about safe handling, storage conditions, expiry dates, and disposal of unused medicines.
The study focuses on educating individuals about maintaining medicines in their original packaging, storing them in a cool and dry place according to manufacturers' instructions, keeping medicines out of the reach of children, and following specific refrigeration requirements wherever necessary. Special emphasis is placed on preventing accidental poisoning, medication errors, and the use of expired or improperly stored medicines. Public awareness can be promoted through questionnaires, educational campaigns, counselling sessions, posters, and community-based activities.
The study highlights the important role of pharmacists and healthcare professionals in providing appropriate guidance regarding medicine storage and disposal. Improving public knowledge and encouraging responsible storage practices can contribute to better medication safety, preservation of medicine quality, and overall public health.

Shampoos contain functional ingredients, including surfactants, fragrances, conditioning agents, colorants, and preservatives. Preservatives prevent microbial growth, maintain product quality, and reduce contamination during storage and use. However, methyliso thiazolinone and methylchloro isothiazolinone have been linked to allergic contact dermatitis in sensitized individuals. Consumers may also have concerns about parabens, despite difficulty distinguishing ingredient hazards, exposure-related risks, and marketing claims.A survey and shampoo-label reading exercise were conducted to assess consumer awareness of preservatives and other cosmetic additives. The study examined participants’ ability to identify common preservatives, interpret ingredient labels, and understand the role of preservatives in product safety and stability. Consumer beliefs regarding preservative benefits and risks were also evaluated in relation to age, education, cosmetic-use frequency, prior skin reactions, and experience reading ingredient labels. The findings identified gaps in consumer knowledge and misunderstandings regarding preservative functions, safety information, and the relationship between chemical exposure and individual risk.

Access to safe and chemically and microbiologically acceptable drinking water is fundamental to public health. However, variations in source characteristics, geochemical conditions, anthropogenic activities, treatment efficiency, storage practices, and distribution systems can influence the quality of water available for domestic consumption. Consequently, systematic monitoring of drinking-water quality is essential for evaluating its suitability and identifying potential quality-related concerns.
The present study, entitled “Water Quality Testing of Local Drinking Water Sources,” focuses on the systematic evaluation and comparative assessment of water samples collected from selected local drinking-water sources. The study incorporates a multidisciplinary analytical approach involving the determination of physical, physicochemical, chemical parameters. The investigated parameters include colour, pH, electrical conductivity, total hardness, calcium hardness.
Water samples will be collected using appropriately labelled sampling containers and handled according to suitable sampling and preservation procedures. Laboratory analyses will be performed using appropriate standardized analytical techniques, including instrumental measurements, complexometric titration, argentometric titration, acid–base titration, spectrophotometric/colorimetric methods, depending on the parameter under investigation.
The analytical data will be systematically compiled and subjected to appropriate statistical treatment to determine central tendency, variability, and differences among sampling locations. The obtained values will subsequently be compared with applicable drinking-water quality standards to assess the conformity of the investigated samples with recommended requirements. The study will also examine variations among different sources and identify parameters showing comparatively elevated or reduced values.
The findings of this investigation are expected to provide a scientific overview of the quality characteristics of selected local drinking-water sources and contribute to greater awareness regarding water-quality monitoring, public health, environmental management, and sustainable access to safe drinking water. The study may also provide a baseline for further investigation involving seasonal monitoring, expanded geographical coverage, and correlation among physicochemical and microbiological parameters.

Adult literacy programmes are a primary route to inclusion for out-of-school adults, yet their delivery in conflict-affected settings depends on sound planning and administration. This study examined how five challenges (planning, funding, facilitator and staffing capacity, monitoring and supervision, and insecurity with sociocultural barriers) relate to administrative effectiveness and programme outcomes of adult literacy programmes in Bama Local Government Area (LGA), Borno State. A cross-sectional survey design was used with 312 stakeholders (facilitators, centre administrators, agency officials and community representatives). Data were analysed with partial least squares structural equation modelling (PLS-SEM) using 2,000 bootstrap resamples. The measurement model showed satisfactory reliability and validity (composite reliability .88 to .91; AVE .65 to .72; maximum HTMT = .69). The model explained 42.2% of the variance in administrative effectiveness and 38.9% in programme outcomes. All five challenges significantly reduced administrative effectiveness, with weak monitoring and supervision (β = −.28) and inadequate funding (β = −.25) strongest. Administrative effectiveness strongly predicted programme outcomes (β = .47) and partially mediated the effect of every challenge. The paper recommends predictable funding, a costed local literacy plan, facilitator professionalisation and routine supervision.

Artificial Intelligence (AI) has emerged as a transformative technology with significant potential to improve educational management and enhance personalized learning in higher education. This study examined the influence of AI applications and AI-supported personalized learning on educational management in Nigerian public universities from a Systems Thinking perspective. Specifically, the study investigated the influence of AI applications on educational management and determined how AI-supported personalized learning contributes to institutional effectiveness. A descriptive survey research design was adopted for the study. The population comprised academic staff, administrative staff, and undergraduate students from selected Nigerian public universities, while a sample of 300 respondents was selected through purposive, stratified, and simple random sampling techniques. Data were collected using the researcher-developed Artificial Intelligence Applications, Personalized Learning and Educational Management Questionnaire (AIAPLEMQ), which yielded an overall Cronbach's Alpha reliability coefficient of 0.86. Mean and standard deviation were used to answer the research questions, while Chi-square statistics tested the hypotheses at the 0.05 level of significance. The findings revealed that AI applications positively influence educational management by enhancing administrative decision-making, reducing delays in routine administrative processes, and improving institutional effectiveness. Similarly, AI-supported personalized learning positively influenced educational management by promoting learner engagement, individualized learning experiences, monitoring students' progress, and improving academic performance. The study concludes that integrating AI into university administration and instructional processes can significantly enhance educational management in Nigerian public universities. It recommends increased investment in AI infrastructure, staff capacity building, and AI-enabled personalized learning systems to improve institutional performance and educational quality.

This study explores how university teachers’ engagement in academic activities contributes to advancing the tertiary education industry, with a particular focus on the Bangladeshi higher education context. Using a qualitative research design, in-depth semi-structured interviews were conducted with faculty members from diverse disciplines to understand their experiences, motivations, and perceived institutional challenges. Thematic analysis revealed four dominant patterns: intrinsic commitment to teaching and learning, strong yet under-supported motivation for research, institutional and administrative barriers that limit academic productivity, and the critical role of recognition and professional development in sustaining long-term engagement. Collectively, the findings highlight that while teachers demonstrate genuine passion for academic work, effective institutional structures, supportive leadership, and resource provision are essential for enabling them to contribute meaningfully to sector-wide advancement. The study offers insights that can guide universities and policymakers in strengthening academic ecosystems and fostering sustained faculty engagement.

Milk is one of the most important food items consumed daily by people of all age groups because of its high nutritional value. It is a rich source of essential nutrients, including proteins, fats, carbohydrates, vitamins, and minerals, which are necessary for the growth, development, and maintenance of the human body. However, milk adulteration has become a significant concern regarding food quality and consumer safety. Adulteration involves the addition of unwanted or unauthorised substances to milk, which may affect its nutritional composition, purity, and suitability for consumption.
The project entitled Detection of Food Adulterants in Daily Food Items (Milk) focuses on the study of milk quality and the identification of possible adulterants using basic chemical and analytical techniques. Common milk adulterants include water, starch, detergents, and urea. These substances may be added to increase the volume, alter the consistency, or change the apparent composition of milk. Their presence can affect milk quality and may pose potential health risks to consumers.
The main objective of this project is to understand the importance of detecting milk adulteration and to develop practical knowledge of simple laboratory testing methods. The study involves the examination of three milk samples using pH paper, iodine solution, a foam formation test, and titration with sodium hydroxide to determine titratable acidity. These methods help in studying selected characteristics of milk and screening for certain possible adulterants. A survey of 30 respondents is also included to understand public awareness, purchasing habits, and opinions regarding milk adulteration.

Proteins are essential nutrients that play an important role in growth, tissue repair, muscle development, and maintaining overall health. The present Community Engagement Project focuses on nutritional chemistry awareness, with special emphasis on protein awareness among gym members and the general public. The project aims to study the importance of proteins, identify common dietary sources, and understand public knowledge regarding protein requirements and supplements.
It includes a review of existing scientific literature, a questionnaire-based survey, and laboratory-based study of selected nutritional samples using biochemical testing methods. The project seeks to connect theoretical knowledge with practical applications and promote awareness about the importance of balanced nutrition and informed dietary choices in everyday life.

This study examined the school health services, manpower and health appraisal as correlates of health promotion in primary schools in Delta State, Nigeria. Three research questions and three hypotheses guided the study. The study employed a correlational research design. The study targeted 10,676 teachers in primary schools in Delta State. The sample size for the study is 370 primary school teachers. The sampling techniques that were used to select the teachers are proportionate stratified and simple random sampling techniques. The main data collection tool for the study will be a questionnaire. Both face and content validity of the instrument were estimated. The reliability index of the instrument was estimated using Cronbach Alpha reliability coefficient. Descriptive statistics of mean and standard deviation were used to answer the research questions. Pearson’s product-moment correlation coefficient was used to test the null hypotheses. The significance level for hypothesis testing was set at 0.05. The findings of the study revealed that school health services, available manpower and health appraisal significantly correlates with health promotion in primary schools in Delta State. The finding concluded that the presence, adequacy and effective implementation of these health variables play a critical role in fostering pupils’ well-being, preventive health behaviours and engagement in health-promoting activities. The study recommended amongst others that schools should strengthen and institutionalize comprehensive health service programmes by ensuring regular health appraisal, first aid provision and structured referral systems, to support ongoing health promotion activities among pupils.

This study examined relationship between unresolved grief and marital adjustment of married staff in tertiary institutions in Delta State. Three research questions and one null hypothesis guided the study. The research adopted a correlational research design. The population of the study comprised 3,257 married staff of tertiary institutions in Delta State. The sample size was 787 married Staff of tertiary institutions in Delta State. A multi-stage sampling method was used to select the sample. The instrument for the study was a questionnaire. The validity of the instrument was obtained through experts’ judgement and factor analysis. The reliability was determined using measures of internal consistency. The data were analysed using mean, standard deviation, Pearson Product Moment Correlation Coefficient of determination and regression statistics. All the hypotheses were tested at a 0.05 level of significance. The findings of this study revealed that the level of unresolved grief and marital adjustment among married staff in tertiary institutions in Delta State is high; and that there is a significant negative relationship between unresolved grief and marital adjustment. Arising from the findings of this study, the study recommended amongst others that professional marital counselling interventions should be integrated into staff welfare programmes to address emotional distress, reduce marital stress, and equip couples with adaptive coping strategies that enhance marital adjustment.

This study examined the influence of classroom environment on academic performance of secondary school students in Delta North Senatorial District of Delta State. One research question and one null hypothesis guided the study. The study utilized the correlational research design. The population of the study consist of 9,385 SS 2 students in public secondary schools in Delta North Senatorial District in the 2024/2025 academic session. The sample size comprised of 357 students. The multistage sampling procedure was used to select the sample. The data for the study were collected using questionnaire. The instrument was validated through experts’ judgement and factor analysis. Cronbach alpha reliability coefficient was used to check for the reliability of the items. The data obtained were analysed using Pearson’s correlation and coefficient of determination for the research question and linear regression for the hypothesis. The hypotheses were tested at 0.05 level of significance. The findings of the study revealed that there is a significant relationship between classroom environment and academic performance among secondary school students in Delta North Senatorial District of Delta State. In view of these findings, the study recommended amongst others, that government and principals should prioritise the improvement of physical and psychosocial classroom conditions.

This study investigated the relationship between perceived discrimination and mental health help-seeking behaviour among undergraduates in Delta State. One research question was answered, and one corresponding hypothesis was tested at the 0.05 level of significance. The study adopted a correlational research design. The population comprised 28,597 undergraduates in public universities in Delta State. A sample of 1,023 undergraduate students was selected using a multistage sampling procedure. Data were collected using questionnaires. The instruments were subjected to face, content and construct validation by experts and factor analysis, while their reliability was established using Cronbach's alpha method. Data collected were analysed using descriptive statistics, Pearson Product Moment Correlation and coefficient of determination was used to answer the research question while regression statistics was used to test the null hypothesis at 0.05 level of significance. The findings revealed that perceived discrimination showed a significant relationship with mental health help-seeking behaviour. The study concluded that mental health help-seeking behaviour among undergraduates is influenced by perceived discrimination. It was therefore recommended, among others, that university management should strengthen campus mental health services, implement culturally and religiously sensitive mental health awareness programmes, provide financial support initiatives for students experiencing economic hardship, promote adaptive coping skills through counselling interventions, and develop gender-responsive and level-specific mental health programmes to enhance professional help-seeking among undergraduates.

This study examined the relationship that exists between family structure and the psychological well-being of adolescents in secondary schools in Edo State, Nigeria. Two research questions and one null hypothesis guided the study. The population of the study comprised 27,704 SSS 3 students. The sample size comprised 1,023 students. The sampling method that was used is the multistage sampling method. Questionnaire was the instrument that was used to collect data. The validities of the instrument were carried out through experts’ judgement and factor analysis. Cronbach alpha was used to estimate the reliability of the instrument. Mean, standard deviation and Pearson’s coefficient of determination were used to answer the research questions while Linear Regression statistics was used to test the hypothesis at 0.05 level of significance. The findings of the study revealed that the level of psychological well-being among adolescents in secondary schools across Edo State is high. The finding also found that there is no significant relationship between family structure and the psychological well-being of adolescents in secondary schools across Edo State. It is recommended amongst others, that schools should sustain existing support systems, such as counselling services and positive school climate initiatives, to maintain and further enhance students’ well-being.

Landslides are recurrent natural hazards that cause major economic losses and human casualties worldwide, particularly in mountainous regions experiencing intensive rainfall and anthropogenic slope modification. This study presents a comprehensive cloud-computing framework for continuous, regional-scale monitoring of landslide-prone slopes using Google Earth Engine (GEE). Multi-source satellite data, including Sentinel-1 C-band Synthetic Aperture Radar (SAR), Sentinel-2 Multispectral Instrument (MSI) imagery, Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), and Shuttle Radar Topography Mission (SRTM) digital elevation model, were integrated over a five-year observation period from January 2020 to December 2024. Normalised Difference Vegetation Index (NDVI), Normalised Difference Moisture Index (NDMI), dual-polarisation radar backscatter coefficients (VV and VH), and rainfall anomaly z-scores were calculated at monthly intervals. A novel combined multi-sensor Anomaly Index (AI) was developed by integrating standardised anomalies across all monitoring variables. Pixels exhibiting AI < -1.0 for two or more consecutive months were classified as anomalous and considered potentially unstable. Furthermore, a Random Forest machine learning classifier was trained using ten geoenvironmental predictors to generate a high-resolution landslide susceptibility map. The model achieved an Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.84 with 95% confidence interval [0.80, 0.88], accuracy of 78%, precision of 76%, recall of 72%, and F1-score of 74%. The proposed framework demonstrates that GEE enables low-cost, near-real-time, multi-temporal monitoring of unstable slopes at regional scale, providing a practical early warning tool for disaster risk reduction agencies. The framework is particularly valuable for remote and inaccessible terrain where ground instrumentation is logistically challenging.

Digital technologies are increasingly being incorporated into pharmaceutical formulation and manufacturing to improve process understanding, flexibility, and patient-centred product design. This narrative review examines the scientific basis, pharmaceutical applications, quality considerations, and regulatory landscape of artificial intelligence (AI)/machine learning (ML), three-dimensional (3D) printing, and smart or continuous manufacturing. Literature was identified from PubMed, ScienceDirect, SpringerLink, MDPI journals, and official FDA and ICH sources, with emphasis on publications from 2018 to 2026 and inclusion of earlier landmark studies. Evidence was organized narratively by technology, formulation and process-development considerations, pharmaceutical applications, quality assurance, regulation, and translational barriers. The reviewed literature shows that AI/ML can support formulation optimization, predictive modelling, and process monitoring, but model performance remains dependent on representative data, external validation, and appropriate human oversight. 3D printing enables individualized dose strengths, complex release profiles, and multidrug dosage forms; however, excipient limitations, reproducibility, throughput, stability, and regulatory validation remain important barriers. Smart and continuous manufacturing can integrate process analytical technology (PAT), automation, and data analytics to strengthen process control and facilitate real-time quality assessment, with continuous manufacturing supported by ICH Q13. Regulatory development for AI remains comparatively less mature: FDA materials include discussion papers, 2025 draft guidance, and 2026 non-binding guiding principles. Overall, the technologies are complementary rather than interchangeable, and their wider clinical and industrial adoption will depend on robust validation, scalable manufacturing platforms, workforce capability, data governance, and regulatory clarity.

The Indian automotive landscape is undergoing a structural paradigm shift, with the electric two-wheeler (E2W) scooter segment spearheading the country's sustainable mobility revolution. Amid rising internal combustion engine (ICE) running costs, governmental subsidy adjustments, and rapid advancements in battery technology, Indian consumers are actively evaluating electric scooters as viable everyday alternatives. This study empirically examines the determinants of consumer perception—specifically Total Cost of Ownership (TCO) advantage, Range Anxiety & Charging Infrastructure Deficit, Perceived Technological Reliability & Safety, and Environmental Consciousness—and their structural impact on Electric Scooter Purchase Intent. Utilizing a cross-sectional empirical survey design, primary data was collected from 435 active two-wheeler commuters across Tier-1 and Tier-2 Indian urban ecosystems (Bengaluru, Pune, Delhi-NCR, Hyderabad, and Ahmedabad). Construct validity, reliability, bivariate correlations, and multiple linear regression analyses were conducted. The empirical results demonstrate that Economic Advantage / TCO (β = 0.362, p < 0.001) and Perceived Technological Reliability & Battery Safety (β = 0.288, p < 0.001) serve as the strongest positive determinants of purchase intent, while Environmental Consciousness (β = 0.174, p < 0.01) offers modest positive reinforcement. Conversely, Range Anxiety & Infrastructure Deficit (β = -0.215, p < 0.001) persists as a significant cognitive barrier inhibiting adoption. The findings provide critical strategic and product-level implications for original equipment manufacturers (OEMs), infrastructure developers, and policymakers aiming to foster mass EV adoption across emerging automotive markets.

Although this is guaranteed by the Constitution, protected by many statutes and even shaken by judicial interventions and an ever-growing public programme, gender discrimination is still a perennial issue with human-rights dimensions in Indian society. It is manifested in unequal access to education, paid employment, property, political decision-making, health care and justice, gender-based violence, child marriage, dowry and other traditional gender-based practices, sexual harassment, unpaid care work responsibilities, and the exclusion of transgender and gender diverse people. This is a paper which critically addresses gender discrimination from a human-rights and social-work approach in the context of India. It uses a secondary, narrative-review and conceptual approach relying on the provisions of the Constitution, Indian laws, judgments by the Supreme Court, data from national surveys, and reports from public institutions and international organisations. There are significant gaps that remain as evidenced by the available indicators: the World Bank Gender Data Portal, based on ILO modelled estimates, indicates a gender gap in labour force participation in India of 77.6 per cent men to 32.4 per cent women in 2025. There is also a disparity in paid employment and caregiving in the unpaid sphere, as captured in the 2024 Time Use Survey. According to the NCRB data for 2023, there were around 4.48 lakh registered cases of crimes against women and according to analysis of NFHS-5 data, child marriage is a serious concern, even though it has dropped. Care needs to be taken that these indicators reflect administrative cases which are a result of reporting and registration rather than incidence. The authors contend that legal prohibition of gender discrimination is not enough: implementation, remedial options, economic autonomy, social norm change and intersectional responses are all crucial. It explores the connection between equality, dignity, autonomy and substantive justice, examines the disconnect between rights-based claims and actual occurrences, and concludes that there is a need for concerted action from government, education, employment, community groups and social support services. The main finding is that human rights are meaningful when women and gender diverse people are able to enjoy them safely, equally and without social or institutional discrimination.

The urgent need to reduce climate change and move toward low-carbon economies has increased the demand for accurate carbon accounting and clear financial reporting. Artificial Intelligence (AI) has become an important tool that can improve the accuracy, speed, and reliability of measuring, reporting, and verifying carbon emissions. This study explains how AI technologies can strengthen carbon accounting systems and improve transparency in sustainability reports. By using tools such as machine learning, natural language processing, big data analytics, and blockchain systems, organizations can provide better environmental, social, and governance (ESG) information and reduce problems like greenwashing and lack of clear information.The paper uses a qualitative research method based on a review of recent academic studies, regulations, and industry reports. The findings show that AI helps estimate emissions more accurately, automates compliance reporting, and increases stakeholder trust through transparent data systems. However, challenges such as poor data quality, ethical issues, regulatory differences, and lack of common technology standards still exist. The study adds to research on sustainable finance by proposing a framework for AI-based carbon accounting and discussing its importance for policymakers, financial institutions, and corporate managers.

This study examined the effect of motivation on employee performance at the Ministry of Agriculture and Irrigation (MAI) in Hirshabelle State, Somalia. The study focused on key motivational factors such as recognition, training, financial incentives, promotion opportunities, and leadership support, and their influence on employee performance in terms of productivity, efficiency, and quality of work. A quantitative, descriptive, and correlational research design was employed. Data were collected using a structured 5-point Likert-scale questionnaire administered to all 39 employees of the ministry, and all responses were analyzed.
The findings revealed that recognition and training were the most common motivational practices, while financial incentives and promotion opportunities were perceived as inconsistent. The results further showed a positive relationship between employee motivation and performance, with highly motivated employees demonstrating better efficiency and quality of work. Motivational challenges, particularly irregular salary payments and weak leadership, were found to negatively affect employee performance. The study concludes that both intrinsic and extrinsic motivational factors are essential for improving employee performance in public sector institutions.

Purpose: This study examines the relationship between the reality of using interactive artificial intelligence (AI) applications and the development of Islamic social values among students with learning disabilities, from the perspective of special education teachers in Irbid, Jordan, and it identifies the challenges that limit the use of these applications. Design/methodology/approach: A cross-sectional survey was applied through a 24-item questionnaire with three axes (reality of use, role in developing Islamic social values, and challenges), measured on a five-point agreement scale, and it was answered by 283 special education teachers working in government schools, private schools, and special education centres. The data were analysed through descriptive statistics, multiple linear regression with a bootstrap robustness test, and Welch tests for demographic differences. Findings: The teachers reported a high level of use (M = 4.12), a high perceived role of the applications in developing the values (M = 4.03), and a high level of challenges (M = 3.79), mainly the concern of the parents, the little Arabic Islamic content, and the cost. The reality of use was positively associated with the perceived development of values after controlling for the demographic variables (β1 = 0.46, p < .001, f² = 0.25), and the bootstrap 95% confidence interval [0.35, 0.56] confirmed the result. The teachers who received training in AI reported a higher reality of use than the others (d = 0.70), while no significant differences appeared by gender, qualification, experience, or type of institution. Originality: To the best of our knowledge, this is the first quantitative study that links AI applications with Islamic social values for students with learning disabilities in the Jordanian context. Practical implications: The findings support including the use of AI applications for teaching values in the training programmes of special education teachers, producing Arabic Islamic content suitable for students with learning disabilities, and addressing the cost, the infrastructure, and the concerns of the parents.

Spam detection remains an important problem in cybersecurity, where effective classifiers must balance detection quality with computational efficiency. This paper presents a lightweight spam classifier built around a four-layer BERT-mini encoder and a custom classification head. The system combines a pretrained transformer backbone with progressive feature transformation, mixed-precision training, sequence truncation, and an interactive graphical user interface. Experiments were conducted on the SMS Spam Collection dataset. On the reported evaluation split, the model achieves an F1-score of 0.9329, with 47 ms reported inference latency per message. The results indicate that compact transformer-based architecture can provide competitive spam-classification performance while reducing computational requirements relative to larger transformer models.

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Modern Omni channel marketing strategy operates in an increasingly complex, high-dimensional, and non-stationary environment. Traditional marketing attribution and budget allocation frameworks—such as heuristics, single-touch attribution (First-Touch, Last-Touch), and static econometric modeling—fail to capture sequential consumer decision interactions, cross-channel synergy decay, and delayed conversion feedback loops. In this paper, we propose a novel algorithmic marketing framework integrating Deep Reinforcement Learning (DRL) with an Attention-Based Multi-Touch Attribution (Attn-MTA) mechanism to optimize dynamic content personalization and real-time media spend allocation. We model the consumer decision journey as a high-dimensional Continuous State-Space Markov Decision Process (MDP), wherein an agent leverages Proximal Policy Optimization (PPO) paired with a Soft Actor-Critic (SAC) module to adaptively reallocate promotional touchpoints across digital, social, search, and programmatic media. Furthermore, our attention mechanism explicitly decouples path-dependent multi-touch contribution weights from conversion outcomes, eliminating systemic biases in credit assignment. Extensive empirical evaluations conducted on multi-million clickstream transaction datasets demonstrate that our proposed DRL-MTA framework achieves a 42.6% uplift in Return on Ad Spend (ROAS), a 31.4% reduction in Customer Acquisition Cost (CAC), and superior convergence stability compared to state-of-the-art heuristic and predictive baselines. Finally, we provide an enterprise deployment architecture and discuss strategic implications for marketing leaders navigating privacy-first data environments.

Background
The establishment of the National Commission for Homoeopathy (NCH) has significantly modernised the governance, ethical standards, and educational regulations of homoeopathic practice in India. While homoeopathic practitioners are increasingly integrated into mainstream healthcare systems, they operate within a complex legal grid. There remains a critical gap in understanding their exact responsibilities, boundaries, and liabilities under Indian jurisprudence.
Objectives
This study aims to provide a critical analysis of the medico-legal responsibilities of homoeopathic practitioners under the current NCH framework. It evaluates the legal expectations regarding emergency handling, medical negligence, informed consent, and documentation, while identifying potential areas of vulnerability for the clinician.
Methodology
A qualitative and analytical legal review was conducted. It involved a comprehensive cross-examination of the National Commission for Homoeopathy Act, 2020, relevant NCH regulations, and landmark judgments by the Supreme Court of India concerning medical negligence (Section 106 of the Bharatiya Nyaya Sanhita, 2023) and the Consumer Protection Act, 2019.
Results
The analysis reveals that while the NCH framework strengthens professional ethics, ambiguity persists regarding the legal boundaries of homoeopathic physicians in handling acute socio-legal emergencies and cross-practice. Furthermore, many practitioners lack formal training in the exact protocols of issuing valid medical certificates, managing dying declarations, and navigating the witness box. This gap elevates their vulnerability to allegations of professional misconduct or negligence.
Conclusion
The NCH framework successfully elevates professional accountability but must be supported by continuous medico-legal education. To safeguard practitioners and ensure patient safety, there is an urgent need to introduce mandatory, practice-oriented training modules in Forensic Medicine and Medical Jurisprudence for registered practitioners.

Now a days the importance of Green Finance (GF) is getting immense popularity not only at global scenario but also in our nation too. Green Finance is finance-related matters or items such as loans, investments and financial instruments movement towards environment friendly or benefits by businesses or persons or companies or any other organisations for the sake of sustainable development and economy in the form of green buildings, renewable energy, climate adoption and water management. The present research paper is going to study the impact and role of financial instruments or mechanisms in the improvement of sustainable development in Hyderabad city, the city is also known as a main technological and economic centre in our nation. The research is planning on key initiatives in green buildings and ESG (Environmental, Social and Governance) aligned financial instruments in Hyderabad city of Telangana state. The study is going to identify the critical mechanisms which are facilitating GF (Green Finance) allocation to desirable ESG goals. The study is going to apply the analytical method of research in relation to the green building certification and ESG aligned financial instruments in the fast-growing city (Hyderabad) towards green finance in India. The study contributes to the understanding of how Hyderabad develops city’s economy and can mobilize green finance to accomplish pollution reduction, promotion in sustainable economic growth, urban climate action and improve healthy environment to all the stakeholders of the city. The paper concludes that a synergistic relationship between robust certification standards and accessible financial mechanisms is crucial for driving urban sustainability.

This study examines the growth in assets under management (AUM), net asset value (NAV) and returns of ten actively managed equity mutual fund schemes in India, five in the large-cap category and five in the flexi-cap category, using 60 monthly observations from January 2021 to December 2025. Combined AUM of the ten schemes rose from ₹1,32,292 crore to ₹4,31,957 crore (3.27 times), and the flexi-cap schemes increased their share of this pool from 46% to 64%. 8 of the 10 schemes delivered a NAV compound annual growth rate (CAGR) above that of the Nifty 50 (14.14%), with HDFC Flexi Cap (24.03%) highest and Axis Bluechip (11.39%) lowest. A one-way analysis of variance (ANOVA) on 590 monthly returns found no statistically significant difference in mean monthly returns across the ten schemes, F(9, 580) = 0.30, p = .975, η² = 0.005; the null hypothesis was therefore not rejected, and the result was robust to non-parametric and heteroscedasticity-robust tests. In contrast, a supplementary ANOVA showed that monthly AUM growth differed significantly across schemes, F(9, 580) = 9.70, p < .001, η² = 0.131, driven chiefly by Parag Parikh Flexi Cap and Canara Robeco Bluechip. The results suggest that investor money has been far more unevenly distributed across schemes than the returns earned would justify, which has implications for fund selection, distribution and investor education.

The prevalence of gastrointestinal diseases such as irritable bowel syndrome, functional dyspepsia, constipation, inflammatory bowel diseases, and gastroesophageal reflux disease is increasing globally and are now being associated with the dysbiosis of gut microbiota, dysfunction of the epithelial barrier, immunological imbalance, and alterations in the gut-brain axis. While conventional pharmacotherapies may offer temporary relief but can be problematic due to side effects and lack the ability to reverse microbial dysbiosis. This review aims at critically examining the therapeutic application of probiotics and Foeniculum vulgare (fennel) as a phytobiotic approach for managing the gut microbiome and gastrointestinal disorders. Literature searches were performed in PubMed, Scopus, Web of Science, and Google Scholar databases up to 2025 with the use of key terms such as gut microbiome, probiotics, Foeniculum vulgare, phytobiotics, synbiotics, and gastrointestinal disorders. Peer-reviewed scientific publications on the topic have been chosen and studied concerning their mechanisms, efficiency, and synergy. The use of probiotics, like Lactobacillus and Bifidobacterium, promotes a healthier digestive tract through maintaining the microbial balance, formation of short-chain fatty acids, increase in epithelial cell integrity, and regulation of immune reactions. Foeniculum vulgare is endowed with trans-anethole, fenchone, flavonoids, and phenolic acids and features the ability to perform as an antispasmodic agent, have antimicrobial effects, act as an antioxidant, reduce inflammation, and serve as a prebiotic. It may be expected that their synergy can result in better efficacy owing to inflammation reduction, better mucus protection, and proper bacterial metabolic processes. Using advanced drug delivery methods, such as microencapsulation, can promote better results as well. Nevertheless, clinical trials and standardization are necessary for developing this new treatment method.

With increased adoption of choice architecture in online environments through defaults, scarcity and social proof cues, personalised recommendations, and interface level nudges to guide consumer choice, a key concern has been this balance between positive nudging that supports the decision-making process, and manipulative nudges that can diminish the consumer's perceived autonomy – and this literature continues to be largely dispersed across the fields of behavioural economics, consumer psychology, information systems and ethics. Accordingly, this paper proposes a conceptual paper that will build theory on the digital nudging phenomenon – understanding how digital nudges influence consumer perceptions, decision making and perceived autonomy – by developing a conceptual synthesis based on a literature review integrating perspectives from nudging, dual-process, self-determination, reactance theory and dark patterns, in response to existing calls for theoretical exploration and conceptual development, that will not only construct an integrative framework for digital nudge effects but also generate testable propositions that bridge the "for good" nudge and "dark" nudge perspectives, inform decision making in practice, stimulate future research on this important research area, and provide managerial and regulatory implications.

Digital banking has transformed the traditional banking system by providing convenient, fast, and technology-driven financial services to customers. The present study examines the impact of digital banking services on customer satisfaction with special reference to Karnataka. The study is based on primary data collected from 50 respondents using a structured questionnaire and simple random sampling technique. Various aspects such as the usage of digital banking services, frequency of use, purpose of use, security perception, and satisfaction level were analyzed. The results indicate that a majority of respondents frequently use digital banking services such as UPI payments, mobile banking, and internet banking. Most respondents reported that digital banking reduces bank visits and provides greater convenience in performing financial transactions. The study also found that a large proportion of respondents are satisfied with digital banking services, although certain issues such as network problems and security concerns still exist. Overall, digital banking services have a positive impact on customer satisfaction, improving the efficiency and accessibility of banking services. The study suggests that banks should enhance security measures, improve technological infrastructure, and increase digital awareness programs to further strengthen customer satisfaction with digital banking services.

Cancer treatment has progressed from nonspecific cytotoxic chemotherapy toward molecularly guided approaches that seek to improve tumor selectivity while preserving therapeutic potency. Antibody–drug conjugates (ADCs) represent an important evolution of this strategy by combining a tumor-recognizing monoclonal antibody with a highly potent cytotoxic payload through a chemically designed linker. The antibody component contributes selective antigen binding and, in many products, promotes internalization; the linker controls stability during systemic circulation and intracellular drug release; and the payload produces the principal antitumor effect. Advances in antibody engineering, linker chemistry, conjugation control and payload selection have contributed to the clinical success of ADCs in both hematological malignancies and solid tumors. Contemporary products such as trastuzumab deruxtecan, sacituzumab govitecan, mirvetuximab soravtansine, enfortumab vedotin and datopotamab deruxtecan illustrate how ADC design can extend activity across different tumor types and antigen-expression levels. Nevertheless, ADC therapy does not eliminate systemic toxicity and is affected by antigen heterogeneity, limited tumor penetration, altered trafficking, payload resistance and other mechanisms of treatment failure. Toxicities may arise from target expression in normal tissues, premature payload release or exposure to active metabolites. This review summarizes the historical development, structural components, mechanisms of action, target selection, linker and payload technologies, drug-to-antibody ratio, conjugation methods, pharmacokinetics, clinically approved ADCs, clinical applications, safety considerations, resistance mechanisms, combination strategies and next-generation approaches. Emphasis is placed on critical comparison of ADC technologies and on the emerging role of biomarker-guided and site-specific designs in precision oncology.

Mackerel (Rastrelliger kanagurta) is one of the capture fisheries commodities with high economic value and is widely marketed at TPI Tambak Lorok. The marketing process for Indian mackerel involves several marketing agencies that can influence the marketing margin and the price share received by fishers. This study aims to analyze the condition of capture fisheries, marketing channels, marketing margins, fisherman’s share, and marketing efficiency of Indian mackerel at TPI Tambak Lorok, Semarang. The study was conducted in February 2026 using a descriptive method with a survey approach. Sampling of traders was carried out using purposive sampling. Data collection was conducted through interviews, observation, documentation, and literature study, then analyzed descriptively and quantitatively using marketing distribution analysis, marketing margin, fisherman’s share, and marketing efficiency. The results showed that the production of Indian mackerel at Tambak Lorok Fish Auction Place area from 2020–2024 experienced an increase, with the 2024 production amounting to 11,276 kg and a production value of IDR 169,140,000. The marketing system for Indian mackerel consists of two marketing channels, namely marketing channel I (fishers–consumers) and marketing channel II (fishers–retailers–consumers). Marketing channel I has a marketing margin of IDR 0/kg and a fisherman’s share of 100%, while marketing channel II has a marketing margin of IDR 5,000/kg and a fisherman’s share of 83.33%. The study concludes that Marketing Channel I is the most efficient because it has a shorter distribution chain, lower marketing margin, and a higher share received by fishers.

Electronic payment systems (EPS) such as debit cards, credit cards, internet banking, tele-banking and mobile banking offer faster and more convenient transactions than cash and cheques. Although Sri Lanka’s payment infrastructure has expanded markedly, including the national LANKAQR standard introduced in 2018, consumer uptake has not matched the technological supply. This study identifies the critical factors affecting consumer perception of EPS and determines the key antecedents among them. A conceptual framework drawing on the Technology Acceptance Model (TAM), UTAUT and Diffusion of Innovations theory proposes seven antecedents (perceived usefulness, perceived ease of use, perceived security, trust, perceived cost, social influence and facilitating conditions) and seven hypotheses (H1–H7). Primary data will be collected through a five-point Likert-scale online questionnaire from 200 employed or self-employed EPS users in the Gampaha district. Analysis comprises descriptive statistics and mean ranking, Cronbach’s alpha reliability testing, correlation, and multiple regression. Using an illustrative simulated dataset (n = 200), all constructs showed good reliability (Cronbach’s α = 0.80–0.86) and the regression model explained 62% of the variance in consumer perception. Perceived security (β = 0.323), perceived ease of use (β = 0.249), perceived usefulness (β = 0.241), trust (β = 0.167) and facilitating conditions (β = 0.150) were significant positive predictors, whereas perceived cost and social influence were not significant.

This paper examines the contested processes of rehabilitation of the Meo community in the Matsya Union (formed by the merger of the princely states of Alwar, Bharatpur, Dholpur and Karauli) and the adjoining Gurgaon district between 1948 and 1949. In the aftermath of Partition violence, tens of thousands of Meos- a liminal agrarian community straddling Hindu and Muslim cultural practices- were displaced from their lands in Alwar and Bharatpur, seeking refuge primarily in Gurgaon. While many ultimately migrated to Pakistan, a substantial number remained in or returned to India, asserting claims to their ancestral holdings amid the competing demands of Hindu and Sikh refugees from West Punjab. Drawing on archival correspondence, cabinet committee records, fact-finding committee reports and ministerial notes, the study analyses the bureaucratic contestations that shaped Meo resettlement. Central to these conflicts were jurisdictional and ideological differences between the Ministry of States (under Vallabhbhai Patel) and the Ministry of Relief and Rehabilitation, as well as broader divergences between Nehru and Patel. Nehru consistently pressed for the return and temporary-to-permanent allotment of land to Meos who had remained in or returned to the Indian Union, viewing their rehabilitation as essential to secular nation-building and agricultural continuity. Patel and officials aligned with the States Ministry, by contrast, prioritised the settlement of non-Muslim refugees on vacated Meo lands and favoured more restrictive criteria for Meo claims, reflecting security concerns and local political pressures in the newly integrated princely territories.

The increasing use of Artificial Intelligence (AI) in auditing is changing the way financial information is examined and potential fraudulent activities are identified. AI-based techniques can process extensive financial datasets and assist auditors in recognizing unusual transactions, recurring patterns, and potential indicators of fraud. Despite these advantages, the limited interpretability of many AI models creates challenges for auditors who are responsible for evaluating and supporting their professional decisions.
This study focuses on Explainable Artificial Intelligence (XAI) as a means of improving the transparency of AI-assisted fraud detection. Although previous research has largely concentrated on the predictive capability and adoption of AI-based auditing tools, comparatively less attention has been given to the behavioural and professional factors associated with explainability. In particular, the relationships among explainability, perceived transparency, auditor trust, professional scepticism, and fraud-detection effectiveness require further consideration.
The study uses a qualitative secondary-data approach based on academic publications, professional auditing standards, industry reports, and relevant regulatory documents. The literature is reviewed and synthesized to identify major themes, relationships, limitations, and opportunities for future research.
Based on the reviewed literature, the study proposes a conceptual framework in which XAI improves the interpretability of AI-generated fraud alerts, thereby increasing perceived transparency and supporting appropriate auditor trust. Professional scepticism is positioned as an important safeguard that encourages auditors to critically evaluate AI recommendations rather than accept them automatically. The framework therefore emphasizes collaboration between AI systems and human auditors, with AI supporting analytical tasks while final professional responsibility remains with the auditor.

Generative artificial intelligence (GenAI) is moving rapidly from experimentation into teachers’ everyday planning, assessment, resource creation and instructional decision-making, yet adoption remains uneven and ethically contested in K–12 schools. Existing research has concentrated primarily on teacher-level acceptance, preparedness and AI literacy, leaving limited multilevel evidence on how school leaders’ own AI competence and ethical leadership shape teachers’ classroom use of GenAI and the translation of that use into instructional innovation. This study develops a multilevel model that positions principal AI literacy and ethical leadership as school-level antecedents, teacher GenAI adoption as a teacher-level mediating mechanism, and instructional innovation as the downstream pedagogical outcome. The study is grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) and Social Learning Theory. A matched principal–teacher quantitative design is proposed for licensed Montessori and Montessori-oriented private schools in Greater Accra, Ghana. The target design is at least 60 school clusters, one principal per school and approximately eight to ten teachers per school. Principal AI literacy will be measured from principal reports, ethical leadership from aggregated teacher ratings, and GenAI adoption and instructional innovation from teacher responses collected in two waves. Multilevel structural equation modelling will be used to evaluate measurement quality, between-school variance, direct cross-level effects and indirect effects through teacher GenAI adoption. The study is designed to contribute to educational leadership and AI-in-education research by showing whether technologically literate and ethically credible principals create school conditions in which teachers not only adopt GenAI but convert it into responsible instructional innovation.

Numeracy skills and self-efficacy are important for elementary students’ success in mathematics, yet improvement may vary according to the learning approach. This study examined normalized gain in numeracy skills and self-efficacy among elementary students following a Problem-Based Learning intervention, emphasizing improvement magnitude rather than posttest differences. A quantitative quasi-experimental study used a nonequivalent pretest-posttest control group design involving 36 fifth-grade students, with 18 in the Problem-Based Learning group and 18 in the conventional-learning group. Data were collected through a numeracy skills test on angle measurement and a self-efficacy questionnaire. Normalized gain was calculated from pretest and posttest scores and compared using an independent-samples t-test. The Problem-Based Learning group increased in numeracy from 41.16 to 77.16, yielding a normalized gain of 0.6264, categorized as moderate, compared with 0.1436, categorized as low, in the conventional-learning group. Self-efficacy increased from 59.00 to 78.61, with a normalized gain of 0.4762, while the conventional-learning group showed −0.0053. Differences in normalized gain were significant for numeracy skills (t = 10.838, p < 0.001) and self-efficacy (t = 13.933, p < 0.001). These findings indicate greater normalized improvement under Problem-Based Learning and contribute evidence on improvement magnitude. Further research should examine longer interventions and broader school contexts.

A school calendar is generally understood as an administrative document designed to provide information about academic schedules, holidays, institutional events, and important dates. However, a school calendar can also function as a significant visual and cultural document through which an educational institution communicates its philosophy, institutional identity, values, student experiences, and relationship with the wider social and cultural environment. The present qualitative study examines the school calendar of Deep Darshan Vidhya Sankul as a multimodal institutional document. The study adopts a qualitative visual-documentary approach to understand how educational activities, student participation, institutional events, cultural representations, and visual elements contribute to the construction of the institution's identity.
The analysis considers the calendar not merely as a chronological arrangement of dates but as a form of institutional communication containing textual and visual modes of meaning-making. Particular attention is given to the representation of students, school activities, celebrations, natural imagery, institutional presentation, and the relationship between visual design and educational communication. The findings indicate that a school calendar can operate beyond its administrative function and may serve as a medium for communicating educational values, participation, community engagement, cultural consciousness, and institutional identity. The study further argues that such calendars can be examined as components of the hidden curriculum because they communicate values and expectations through visual and textual representations that may not necessarily appear in the formal curriculum.

समावेशी शिक्षा आधुनिक शिक्षा व्यवस्था की एक महत्वपूर्ण अवधारणा है, जिसका उद्देश्य विभिन्न क्षमताओं, सामाजिक एवं आर्थिक पृष्ठभूमियों तथा सीखने की विविध आवश्यकताओं वाले सभी विद्यार्थियों को एक समान शैक्षिक वातावरण उपलब्ध कराना है। समावेशी कक्षा में विद्यार्थियों के शैक्षणिक विकास के साथ-साथ उनके सामाजिक, भावनात्मक एवं मनोवैज्ञानिक समायोजन पर भी विशेष ध्यान दिया जाता है। इस संदर्भ में सहपाठी सहयोग एक प्रभावशाली शैक्षिक एवं सामाजिक प्रक्रिया के रूप में उभरता है। सहपाठी सहयोग के माध्यम से विद्यार्थी एक-दूसरे की सहायता करते हैं, विचारों का आदान-प्रदान करते हैं, सामूहिक गतिविधियों में भाग लेते हैं तथा सामाजिक संबंधों का निर्माण करते हैं।
प्रस्तुत शोध-पत्र का मुख्य उद्देश्य समावेशी कक्षा में सहपाठी सहयोग और विद्यार्थियों के समायोजन के मध्य संबंध का विश्लेषण करना है। अध्ययन में समायोजन को मुख्यतः सामाजिक, भावनात्मक, शैक्षिक एवं विद्यालयीय समायोजन के आयामों के संदर्भ में समझा गया है। उपलब्ध साहित्य के विश्लेषण से स्पष्ट होता है कि सकारात्मक सहपाठी संबंध विद्यार्थियों में अपनत्व, आत्मविश्वास, सहयोग की भावना तथा विद्यालय के प्रति सकारात्मक दृष्टिकोण विकसित करने में सहायक हो सकते हैं। विशेष रूप से विशेष शैक्षिक आवश्यकताओं वाले विद्यार्थियों के लिए सहपाठी सहयोग सामाजिक सहभागिता और कक्षा में स्वीकार्यता को बढ़ाने में महत्वपूर्ण भूमिका निभा सकता है। साथ ही, प्रभावी सहपाठी सहयोग के लिए शिक्षक की भूमिका, कक्षा का वातावरण, सहयोगात्मक गतिविधियों की प्रकृति तथा विद्यार्थियों के बीच सकारात्मक दृष्टिकोण आवश्यक हैं।

Nail polish removers are cosmetic preparations used to remove nail polish from the nail plate by dissolving or redissolving the film-forming components of nail polish. Acetone is one of the most commonly used nail-polish-removing solvents; however, frequent use may contribute to nail dryness and irritation. Acetone-free removers containing solvents such as ethyl acetate have therefore gained attention as alternative formulations. Ethyl acetate is an effective organic solvent used in nail polish and nail-polish-remover preparations. Aloe vera is a natural cosmetic ingredient associated with moisturizing and skin-conditioning properties. Vitamin E is a lipid-soluble antioxidant widely used in cosmetic formulations. Orange oil provides a pleasant citrus aroma and contains volatile terpenes, particularly limonene. Caprylic/capric triglycerides are lightweight emollient ingredients used in cosmetics for skin conditioning and emolliency. The proposed nail-polish-removing wipe combines ethyl acetate as the principal solvent with aloe vera, vitamin E, orange oil and caprylic/capric triglycerides as conditioning and sensory ingredients. The formulation is intended to provide convenient nail-polish removal while reducing the dry feel associated with solvent exposure. However, because aloe vera gel is generally water-containing while ethyl acetate and the lipid ingredients belong predominantly to organic/oil phases, compatibility, phase stability, solvent evaporation, preservative requirements and wipe saturation must be evaluated carefully. Therefore, the proposed formulation represents a suitable basis for laboratory development and evaluation of acetone-free nail-polish-removing wipes.

Rising youth unemployment and rapid digitalisation have pushed policymakers and educators to ask whether entrepreneurship education that is delivered and applied through digital tools can translate into real economic gains for young people. This study examined the relationship between digital entrepreneurship education (DEE) and youth economic empowerment (YEE) among Nigerian tertiary students, and tested whether digital skills (DSK) and entrepreneurial self-efficacy (ESE) transmit this relationship. A cross-sectional survey design was applied to an illustrative sample of 320 students drawn from computer science/ICT, business/economics, and education programmes in North-East Nigeria. Reliability was acceptable for all scales (Cronbach's α = .79–.86). DEE was positively associated with YEE (β = .46, p < .001), and a serial mediation model with bias-corrected bootstrapping showed that 43% of this total effect operated indirectly, primarily through ESE and through the sequential path DSK → ESE. Students with high DEE exposure reported markedly higher empowerment than those with low exposure, F(2, 317) = 33.08, p < .001, η² = .17. The findings suggest that digital entrepreneurship curricula should deliberately build confidence and applied digital competence rather than transmit business knowledge alone. Policy and curriculum recommendations are provided.

Mathematical concepts are often communicated through symbols, equations, graphs, and formal procedures, which can make abstract relationships difficult to connect with familiar experience. Embodied cognition emphasizes the role of perception, action, gesture, and bodily interaction in cognition, while conceptual metaphor explains how structure from a familiar experiential domain can support understanding of an abstract mathematical domain. This study presents an integrated Metaphor-Embodied Simulation Approach that connects these perspectives. A conceptual literature-synthesis and framework-development methodology was used to examine work on embodied cognition, mathematical cognition, conceptual metaphor, embodied simulation, enactive metaphorising, action and language, gesture, and technology-supported embodied learning. The synthesis produced a framework linking embodied experience, conceptual metaphor, metaphorical mapping, embodied simulation, mathematical representation, and conceptual understanding. It also produced structured algorithms for designing metaphor-embodied mathematical activities and assessing explanation, formal representation, transfer, metaphor-related misconceptions, and independent reasoning. The results indicate that embodied experience can serve as a meaningful starting point for mathematical thought when it is explicitly connected to mathematical language, representation, reflection, and gradual abstraction. The framework is a conceptual synthesis rather than evidence of a single experimentally established cognitive mechanism. It provides a reproducible basis for future empirical testing and for the design and assessment of embodied mathematical learning activities.

This study examined the moderating role of national culture on the relationships among leadership perception, employee commitment, and customer satisfaction in multinational companies (MNCs) operating in Ghana. Using a quantitative cross-sectional design, data were collected from 360 frontline employees and 1,080 customers across eight MNCs in the banking, telecommunications, and hospitality sectors. Leadership perception was measured using culturally adapted leadership scales, employee commitment was assessed using Meyer and Allen's three-component commitment scale, customer satisfaction was measured using SERVQUAL-derived scales, and national culture was operationalized through Hofstede's cultural dimensions. Descriptive statistics, Pearson's correlation, and hierarchical regression with moderation analyses were conducted. Results revealed that leadership perception significantly predicted affective commitment (β = 0.44, p < .001) and customer satisfaction (β = 0.38, p < .001). National culture significantly moderated the leadership-commitment relationship (β = -0.19, p < .001) and the commitment-customer satisfaction relationship (β = -0.16, p < .01), with stronger effects observed in high collectivism and high-power distance contexts. Employee commitment significantly mediated the leadership-customer satisfaction relationship, with the indirect effect stronger in high collectivism cultures. The findings highlight that culturally congruent leadership practices enhance employee commitment and customer satisfaction. Implications for cross-cultural leadership development, employee engagement, and service quality management in Ghanaian MNCs are discussed.

This study examined the effect of perceived inclusive leadership on employee commitment and customer-facing outcomes in service organizations in Ghana. Using a quantitative cross-sectional design, data were collected from 360 frontline employees and 1,080 customers across six organizations in the banking, telecommunications, and hospitality sectors. Perceived inclusive leadership was measured using an adapted Inclusive Leadership Scale, employee commitment was measured using Meyer and Allen's three-component commitment scale, and customer-facing outcomes were assessed through service quality and customer satisfaction measures. Descriptive statistics, Pearson's correlation, and hierarchical regression analyses were conducted to examine relationships and mediating effects. Results revealed significant positive correlations between perceived inclusive leadership and employee commitment (r = 0.53, p < .001), and between perceived inclusive leadership and customer-facing outcomes (r = 0.48, p < .001). Hierarchical regression demonstrated that perceived inclusive leadership significantly predicted employee commitment (β = 0.45, p < .001), accounting for 30% of the variance. Employee commitment significantly mediated the relationship between perceived inclusive leadership and customer-facing outcomes (indirect effect = 0.23, 95% CI: 0.16 to 0.30). The findings highlight that inclusive leadership fosters employee commitment, which translates into superior service delivery and customer satisfaction. Implications for leadership development, employee engagement, and service quality management in Ghanaian service organizations are discussed.

This study examined the influence of leadership perception on employee commitment and customer satisfaction within multinational corporations (MNCs) operating in Ghana, testing the applicability of the service-profit chain framework in a developing economy context. Using a quantitative cross-sectional design, data were collected from 420 employees and 210 customers across six MNCs in the financial services and telecommunications sectors. Leadership perception was measured using the Multifactor Leadership Questionnaire (MLQ), employee commitment was assessed using the Three-Component Model (Affective, Continuance, and Normative Commitment), and customer satisfaction was measured using the American Customer Satisfaction Index (ACSI). Descriptive statistics, Pearson's correlation, and hierarchical regression analyses were conducted to examine the relationships among the variables. Results revealed significant positive correlations between leadership perception and employee commitment (r = 0.54, p < .001), employee commitment and customer satisfaction (r = 0.49, p < .001), and leadership perception and customer satisfaction (r = 0.41, p < .001). Hierarchical regression analyses demonstrated that leadership perception significantly predicted employee commitment (β = 0.52, p < .001) and customer satisfaction (β = 0.38, p < .001), while employee commitment mediated the relationship between leadership perception and customer satisfaction. The findings confirm the service-profit chain's applicability in the Ghanaian MNC context, highlighting that effective leadership enhances employee commitment, which in turn drives customer satisfaction. Implications for leadership development, human resource management, and service quality enhancement in MNCs are discussed.

This study examines the moderating effect of financial literacy on the relationship between Point-of-Sale (POS) transactions and economic growth in Nigeria, using time-series data from 2012 to 2025. Employing the Autoregressive Distributed Lag (ARDL) bounds testing approach, the study investigates both short-run and long-run dynamics among the variables. The empirical findings reveal that POS transactions exert a positive and significant influence on economic growth in both the short run and the long run. More importantly, the interaction between POS transactions and financial literacy is found to be highly significant (β = 5.25, p = 0.001), indicating that the growth-enhancing benefits of POS systems are amplified when users possess adequate financial knowledge. Diagnostic and stability tests confirmed the robustness, reliability, and stability of the estimated model. The study recommends intensified financial literacy programmes, targeted financial education campaigns for traders and small businesses, and investment in digital payment infrastructure to enhance the effectiveness of POS systems in promoting economic growth in Nigeria.

This study examines the association between sustainable finance and corporate value among ten large Indian listed companies. Sustainable finance is represented by published CRISIL ESG scores for FY2024–25, while corporate value is proxied by market capitalisation reported in April 2025. The sample comprises Reliance Industries, HDFC Bank, Tata Consultancy Services, Bharti Airtel, ICICI Bank, State Bank of India, Infosys, Bajaj Finance, Hindustan Unilever and ITC. Descriptive analysis, Pearson correlation and an exploratory ordinary least squares regression using log market capitalisation are applied. The mean ESG score is 66.0, with scores ranging from 55 to 76. The correlation between ESG score and log market capitalisation is -0.128 (p=0.725), and the regression R² is 0.016. The small cross-sectional sample does not provide statistically significant evidence of a direct association between the two variables. The result highlights the importance of controlling for firm size, industry, profitability, leverage and other determinants when assessing value effects of sustainable finance.

This study examines the relationship between FinTech adoption and bank performance in India using FY 2024–25 evidence from six selected scheduled commercial banks: HDFC Bank, Axis Bank, Punjab National Bank, South Indian Bank, Karur Vysya Bank and Ujjivan Small Finance Bank. FinTech adoption is proxied by the share of financial transactions conducted through digital channels, while bank performance is measured primarily through Return on Assets (ROA), with Return on Equity (ROE) and Net Non-Performing Asset (NPA) ratio used as supplementary indicators. The evidence shows that digital transaction penetration was already very high across the sample, ranging from 92.4% to 98%. A simple cross-sectional regression produces a small positive coefficient between digital-transaction share and ROA, but the relationship is statistically insignificant. The Pearson correlation is approximately 0.103 (p=0.846), and the model explains only about 1.1% of the variation in ROA. The findings indicate that high digital adoption by itself does not guarantee higher profitability. Bank size, business model, asset quality, capital structure, pricing, operating efficiency and the ability to convert technology investment into revenue and productivity may be more important determinants of performance. The study contributes by separating the measurement of digital adoption from financial outcomes and by highlighting the need for multidimensional FinTech-performance models in Indian banking research.

Digital payments have become a central component of India's financial transformation. This study examines whether higher adoption of digital payments is associated with broader financial inclusion across Indian states. The empirical analysis uses FY 2024–25 state-level data for 14 major states/territories for which comparable public UPI-intensity observations were available, combined with Reserve Bank of India banking indicators. Digital-payment adoption is measured by UPI transactions per capita. Financial inclusion is represented by an equal-weighted composite index based on bank branches per 100,000 population, scheduled commercial bank deposits per capita, scheduled commercial bank credit per capita, and the credit-deposit ratio. Descriptive statistics, correlation analysis and an OLS regression with heteroskedasticity-robust standard errors are employed. The analysis identifies a positive cross-sectional association between UPI intensity and the composite financial-inclusion measure. Because the design is cross-sectional and the sample is limited by the availability of comparable state-wise UPI intensity data, the results should be interpreted as evidence of association rather than causation. The paper highlights the importance of combining digital-payment expansion with banking access, affordability, digital capability and responsible financial-service delivery.

As the incidence of shopping cart abandonment in online retail continues to damage profits on a global scale with recent reports of the issue having reached as high as 70.19% of transactions during 2025 (Statista, in Das Sarma et al. 2025), with checkout phase hesitation consistently identified as the closest psychological stimulus to non-purchase in the stimuli-organism-response model (Wang et al. 2022), a situation that is only further exacerbated by proof that decision procrastination mediate the relations between consumers' mood and the likelihood of abandoning items in the cart (Silva et al. 2025), this theoretical paper seeks to close that persistent theoretical gulf that exists in relation to why this reasoned, rather than mere reflexive or unintended, restraint should lead to lasting constraint and cart abandonment. It is proposed that a conceptual model in which purchase hesitation is a prime determinant of abandoned cart behavior be developed, with self-regulatory efficacy (as interpreted by consumers to reflect their perceived capacity to deliberately restrain, delay, or ignore an initial preference for a product) as the fundamental mediator of transition between hesitation and explicit abandon of shopping cart content; this proposal derives mainly from an elaboration of Bandura's theory of Self-Efficacy and Social Cognitive Theory in explaining a "regulatory confidence" facet and from application of Regulatory Focus Theory in addressing the promotional and precautionary motivations that drive behavior associated with e-cart purchase processes (Kukar-Kinney et al. 2022). We also attempt to address friction at the time of decision/checkout choice as well as complexities in products for comparison that had individually been shown to strengthen the possibility of abandoned shopping carts (Sharma and Srivastava, in Das Sarma et al. 2025). Within this conceptual framework, purchase hesitation's impacts are mediated, both directly and indirectly through self-regulatory efficacy as behavioral intent/outcome of high regulatory efficiency under circumstances that entail product examination/choice and subsequent hesitation; the research is aimed to expand a scarce body of literature, which connect deliberate self-regulation to non-purchase activities online, and beyond purely habitual causes like spontaneity and inconvenience, giving e-commerce sites and digital marketers empirical bases for the development of checkout strategies that align with rather than counteract the purchase decisions being supported, and providing research hypothesis structures tested through structural equation modelling, for Indian as well as other emerging online markets.

This study assessed retirement plan strategies for job performance of academic staff in public universities in Rivers State, Nigeria. The study was guided by three objectives and corresponding research questions and hypotheses, focusing on healthcare savings plans, avoidance of new long-term liabilities, and regular Voluntary Additional Contribution (VAC) to pension accounts and their influence on the job performance of academic staff. A descriptive survey research design was adopted. The population comprised 3,165 academic staff in the three public universities in Rivers State, namely the University of Port Harcourt, Rivers State University, and Ignatius Ajuru University of Education. A proportionate stratified random sample of 316 academic staff, comprising 204 males and 112 females, was selected. Data were collected using a self-structured 21-item instrument titled: Assessment of Retirement Plan Strategies for Job Performance of Academic Staff in Public Universities Scale (ARPSJPASPUS). The instrument was validated through expert review and supervisor vetting, while Cronbach's Alpha yielded an overall reliability coefficient of 0.85. Of the 316 copies administered, 293 (93%) were retrieved, while 287 (91%) were usable for analysis. Mean and standard deviation were used to answer the research questions, while z-test statistics were used to test the three null hypotheses at the 0.05 level of significance. The findings showed that healthcare savings plans, avoidance of new long-term liabilities, and regular VAC to pension accounts each influence the job performance of academic staff to a high extent. Significant differences were found in healthcare savings plans based on age and avoidance of new long-term liabilities based on university ownership, whereas no significant difference existed for regular VAC based on university ownership. The study concluded that retirement plan strategies are important for supporting academic staff job performance and recommended improved access to healthcare savings plans, regular financial counselling on long-term liabilities, and increased voluntary pension contributions.

This study investigated personality traits as predictors of imposter syndrome among secondary school students in Rivers State. The study was guided by five research questions and their corresponding null hypotheses. The design for the study was correlational research design. The population of the study comprises all the 197,428 senior secondary school students enrolled in the 367 public senior secondary schools in Rivers State. A sample of 398 respondents as determined by Taro Yamane Formula. In the distribution of the sample size multi-stage sampling procedure was used to draw the sample size. Two instruments were used for the study. They are personality Traits Scale (PTS) and Imposter Syndrome Scale (ISS). Research instruments were validated by three experts in the field of Measurement and Evaluation. The construct validity was also done using factor analysis. To ensure the reliability of the instruments, Cronbach alpha technique was used for all the instruments. The alpha coefficients of 0.78 and 0.87 for personality traits and imposter syndrome respectively. Research questions were answered using simple regression while hypotheses were tested using t-test associated with simple regression. Results revealed that personality traits (extraversion, neuroticism, openness to experience, agreeableness and conscientiousness) significantly predict imposter syndrome among secondary school students in Rivers State. It was recommended among others that School counsellors should develop and implement personality-awareness and self-development programmes for secondary school students to help them understand their individual personality characteristics, develop healthy self-perceptions, and manage personality-related tendencies that may contribute to feelings of inadequacy, self-doubt and imposter syndrome.

This study examines teacher competencies and the development of STEM education in lower secondary schools within the context of digital transformation and the application of artificial intelligence (AI). Teacher competence is evaluated based not only on the ability to use technology but also on the capacity to effectively integrate technology into pedagogical practice. Data were collected from teachers via questionnaires focusing on the utilization of digital resources, technology- and AI-supported STEM lesson design, digital assessment, and student monitoring and support. The results indicate a high level of engagement with digital resources; however, the integration of technology and AI into lesson design, assessment, and student support remains inconsistent. The study suggests a need to enhance teachers' digital pedagogical competencies by aligning technology and AI with STEM teaching practices.

Hoppers in cement factories are subjected to continuous abrasive wear from limestone and clinker, and the metallic and conventional polymeric liners currently used are costly to replace and environmentally burdensome. This study characterizes three waste-derived materials, rice husk ash (RHA), waste soda-lime glass (WG), and recycled high-density polyethylene (HDPE), to establish their suitability as constituents of a sustainable composite hopper liner. RHA and WG were sourced locally, processed by washing, drying, controlled combustion (RHA) or milling (WG), and analysed by X-ray fluorescence (XRF) to determine chemical composition. Recycled HDPE was sorted, washed, shredded and cryogenically ground, then examined by Fourier-transform infrared spectroscopy (FTIR) to confirm polymer identity and detect degradation. Scanning electron microscopy (SEM) was used to examine the microstructure of RHA and WG, while density, specific gravity, and bulk density were determined for all three materials. XRF results showed RHA contained 93.90% SiO2 (84.62% amorphous) with low loss-on-ignition (4.6%), confirming a highly reactive, thermally stable pozzolanic filler, while WG was dominated by SiO2 (72.5%), Na2O (14%) and CaO (10%), consistent with typical soda-lime glass chemistry. FTIR spectra of the recycled HDPE displayed the characteristic C–H stretching and bending bands (2913, 2847, 1465 and 721 cm⁻¹) expected of a polyethylene backbone, with a weak carbonyl-region absorption near 1742 cm⁻¹ indicating minor oxidative degradation from prior service life. SEM micrographs revealed irregular, angular RHA particles with a porous cellular structure and irregular, sharp-edged WG particles favourable for mechanical interlocking in a polymer matrix. Physical property testing showed RHA and WG densities of 2.182 and 2.495 g/cm³ respectively, both markedly higher than recycled HDPE (0.952 g/cm³), while RHA displayed the lowest bulk density (0.40 g/cm³), indicating high porosity. Taken together, the results indicate that RHA offers hardness- and wear-enhancing silica reinforcement, WG offers a hard, mechanically interlocking filler with pozzolanic secondary chemistry, and recycled HDPE offers a light, ductile, chemically stable matrix; the three waste streams are therefore chemically and physically complementary and are recommended as viable raw materials for a sustainable, low-cost composite hopper liner. Composite fabrication, blend optimization and comparative mechanical performance against conventional liner materials are reported in a companion study.

Sustainability is a core part of the institutional development, especially in academic institutions, where universities are increasingly responsible for reducing environmental footprint, fostering knowledge production and advancing social responsibility. Academic Libraries as an important functional unit of universities use a lot of resources in the fields of energy consumption, keeping the library infrastructure, provision of information management and technology-based services. The concept of green library has appeared as a strategy that combines the environmental issue with library functions such as energy saving, optimizing the use of resources, digitalization, minimizing waste and adopting environmental management strategies. The results indicate that strategic planning, institutional commitment, financial resources, and awareness of the library professionals and users are important issues in the process of making a green library. The study suggests that there is a need to enhance sustainable infrastructure, encourage sustainable energy usage, establish green policies and embed the concept of sustainable responsibility in library management systems. Green libraries have the potential to make a huge contribution to sustainable higher education by lowering the environmental footprint and enhancing the user experience and operational efficiency.

Silicosis is a progressive, irreversible, and incurable occupational lung disease caused by the inhalation of respirable crystalline silica dust (RCS), leading to chronic inflammation and pulmonary fibrosis. Despite being preventable, it remains a significant global health burden, with diagnosis often occurring only after irreversible damage has ensued. The ancient Ayurvedic medical system describes a sophisticated model of disease progression known as Kriya Kala, the six sequential stages of pathogenesis which provides a structured timeline from initial imbalance to complication. This paper systematically correlates the modern pathophysiology of silicosis, from particle deposition to end-stage fibrosis and complications, with these six stages of Kriya Kala (Sanchaya, Prakopa, Prasara, Sthana Samsraya, Vyakti, and Bheda). By establishing this conceptual bridge, we propose a novel, integrative framework that enhances the understanding of the disease continuum. This model underscores the critical importance of early identification and offers a strategic paradigm for stage-specific interventions, combining the preventive and holistic principles of Ayurveda with modern diagnostic and therapeutic tools to mitigate the progression of this devastating disease.

Due to ever-increasing world desire for renewable, sustainable energy source(s) and inherent environmental & economic challenges with fossil fuel consumption and the first-generation biodiesel feedstocks composed of edible oils; considerable academic/industrial focus has been given for identification of suitable alternative non-edible oil-bearing plant species like ornamental tree 'Cordia sebestena' that is less explored in terms of its seed oil potential, as suitable feed stocks for biodiesel production via transesterification as well as the limitations associated with the conventionally used homogeneous alkaline catalysts are well documented and can be briefly outlined as: their tendencies for saponification in the presence of the trace amount of free fatty acids and/or moisture present in oils, difficulties encountered in separating/purifying them from the resultant mixture, production of several volumes of environmentally undesirable wastewater during neutralization and washing phases, and lack of recovery and reuse in subsequent cycles. All these aspects negatively impact on economic feasibility and environmental sustainability of the large scale biodiesel production and necessitate a conceptual paradigm shift towards designing and developing systematic optimization of alternative heterogeneous catalysts, based on metal oxides, mixed oxide systems, calcium-rich wastes, biochar, or engineered nanostructured supports, having superior catalytic stability, enhanced surface basicity/acidity, more porosity and surface area, greater reusability, etc. Thus, in this conceptual paper, the establishment of a comprehensive theoretical framework, integrating heterogeneous catalysis surface-reaction theory and green chemistry, for studying and determining the relationships between varying physicochemical properties of candidate catalysts-such as crystalline nature, pore size and structure, density of active sites etc.- and optimize them using statistical approach of Response Surface Methodology, and/or other statistical design of experiments, in an effort to achieve the maximum yield and conversion to FAMEs from Cordia sebestena oil and simultaneously bridging the current knowledge gap on empirical and/or theoretical linkages between under-explored feedstocks like Cordia sebestena oil and development of heterogeneous catalysts for biodiesel production, eventually to be evolved to a conceptual model where catalyst synthesis & characterization is integrated with optimization of reaction parameters and catalysts reusability.

Through testamentary succession a person can put an end to the rules of intestacy and ensure that his property is distributed according to his wishes. In India, this freedom to distribute one's property after his/her demise is governed by a complex, layered system of laws, which include, the Indian Succession Act 1925, the Hindu Succession Act 1956, uncodified Muslim personal law, law of evidence, and the Registration Act 1908. This paper, taking a doctrinal approach, discusses what is valid will, restrictions placed on testamentary freedom under different personal-law systems, and the legal standards of proof to be established before a court. Analysing statutes and leading Supreme Court decisions including H. Venkatachala Iyengar v B.N. Thimmajamma, Jaswant Kaur v Amrit Kaur, Derek A.C. Lobo v Ulric M.A. Lobo and John Vallamattom v Union of India. The courts frequently differentiate between the validity of a will and its truth, mandating that the propounded disprove any necessary circumstance; registration and attestation do not inherently dispel doubt. Testamentary freedom is unqualified for Christians, Hindus and Parsis, but is restricted to one-third in the case of Muslims. The report concludes that will law is fundamentally settled but actually contestable. It proposes that they will be more precisely distinguished and that safe deposit and registration be enlarged and that old testators be protected.

Quick commerce (Q-commerce) represents a new phase of digital retail in which frequently purchased products are delivered to consumers within a very short time, generally through geographically distributed micro-fulfilment facilities and hyperlocal delivery networks. In India, the rapid expansion of Q-commerce has been supported by smartphone adoption, digital payments, urban concentration of demand, platform-based logistics and changing expectations of convenience. This paper examines the principal drivers, consumer implications, operating model, opportunities and challenges associated with Q-commerce in India. The study uses a qualitative exploratory design based on secondary evidence from peer-reviewed research, industry reports, policy documents and authoritative institutional sources. The analysis shows that Q-commerce creates value through proximity, assortment optimization, real-time information, data-driven demand forecasting and last-mile coordination, but its growth also creates questions concerning profitability, labour conditions, data governance, urban traffic and environmental externalities. The paper develops an integrated discussion linking consumer value, operational capability, technology, institutional governance and sustainability. It argues that the long-term development of Q-commerce depends not simply on shorter delivery times, but on improving unit economics, worker protections, responsible data practices, resilient fulfilment networks and environmentally efficient last-mile systems. The paper concludes with implications for platforms, policymakers and researchers and identifies directions for future empirical research.

This descriptive study assessed selected anthropometric, body-composition, and physiological indicators among 11 female students aged 18–22 years. The recorded variables included height, body weight, total body fat, visceral fat, body mass index (BMI), body age, blood pressure, and heart rate. All participants had senior-secondary education as their reported educational qualification. Ten participants were from Haryana and one was from Bihar. Five participants belonged to joint families and six to nuclear families; nine were from rural areas and two from urban areas. Ten participants were vegetarian and one was non-vegetarian. The mean height was 157.36 ± 4.26 cm, mean weight was 49.43 ± 5.54 kg, mean BMI was 19.77 ± 2.28 kg/m², mean total body fat was 27.79 ± 4.55%, mean visceral fat was 1.75 ± 1.16, mean systolic blood pressure was 110.36 ± 9.58 mmHg, mean diastolic blood pressure was 75.00 ± 11.82 mmHg, and mean heart rate was 82.64 ± 11.89 beats per minute. The findings provide a preliminary descriptive profile of the participants and may be useful for planning health, nutrition, physical-activity, and ergonomic-awareness programs. Because the sample was small and non-random, the results should not be generalized to all female students.

Psoriasis is a chronic, immune-mediated, inflammatory dermatological disorder that presents unique psychosocial, hormonal, and quality-of-life challenges for female patients. While individualized homoeopathy is commonly utilized for chronic dermatosis, there is a lack of focused clinical data regarding the specific therapeutic outcomes of primary constitutional remedies within female cohorts.
Objective: To evaluate the clinical efficacy of four major individualized homoeopathic medicines—Sulphur, Pulsatilla, Sepia, and Graphites—in the management of psoriasis in female patients.
Methods: A prospective, observational clinical study was conducted over a period of 12 months. A sample size of 60 female participants diagnosed with chronic plaque psoriasis were enrolled based on predefined selection criteria. Individualized prescriptions of Sulphur, Pulsatilla, Sepia, or Graphites were selected using classic homoeopathic principles, accounting for the patients' physical, mental, and miasmatic totals. Therapeutic outcomes were evaluated periodically using the Psoriasis Area and Severity Index (PASI) and the Dermatology Life Quality Index (DLQI) scores at baseline and subsequent follow-ups. Data were statistically analyzed using a paired t-test.
Results: Out of the 60 participants enrolled, a statistically significant reduction in the mean baseline PASI and DLQI scores was observed at the conclusion of the 12-month treatment period (p < 0.05). Significant objective improvements were documented in plaque scaling, erythema, and infiltration. Among the evaluated remedies, Sepia and Pulsatilla were frequently indicated in cases showing marked hormonal correlations, while Sulphur and Graphites demonstrated high efficacy in patients presenting severe metabolic skin alterations and intense pruritus. No severe medicinal aggravations or adverse toxicological events were reported.

The dimension of our study includes east Godavari district for REE mineralization where secondary geochemical dispersion, geophysical and geological signatures acts as catalyst in the creation of mineral potential map at the scale of one toposheet. to understand the regional and local variation in the data integration this attempt was made. on the regional scale agnigundla basemetal belt and surrounding area was considered for mineral potential mapping to understand the extension of mineral belt.
The study area for copper mineralization forms a part of the Agnigundala Mineral Belt located in the northern most corner of Nallamalai Fold Belt. The Agnigundala Mineralised Belt is known for its base metal potentiality. Bandlamottu Pb-mines is a fine example of base metal mineralization.
The area for REE mineralization is occupied by the rocks of Khondalite, Charnockite and Migmatites Groups of Eastern Ghats Supergroup in the north, overlain by Tirupathi Formation of East Coast / Gondwana of Gondwana Supergroup, Deccan-Trap, Rajahmundry Sandstone towards southern part and Krishna-Godavari Formation towards southwest The Khondalite Group is represented by khondalite, which occupies the northern part of the area. Khondalite is observed around Mellisala, Gopalpuram and Tirumalayyapalem. It is chiefly of garnet-sillimanite + graphite gneiss and contains a few thin impersistent bands of quartzite at places. Intermediate charnockite and hypersthene granite/acid charnockite comprising the charnockite Group occur as minor bodies. The Migmatite Group is made up of garnetiferous quartzo feldspathic gneiss and manganiferous quartzo-feldspathic rocks which are derived from the former due influx of quartzo feldspathic injections and observed near Rajavaram, korukonda and Srirangapatam.

In 21st-century globalization, data and technology have transformed into new geopolitical instruments. This research paper analyses how India is shaping a novel and powerful paradigm of digital diplomacy by leveraging its Digital Public Infrastructure (DPI), particularly the Unified Payments Interface (UPI). While Western nations treat technology as a tool for monopoly and profit (Digital Neo-colonialism), and China utilizes it for debt traps and surveillance, India has presented a secure, affordable, and transparent "third alternative" for the Global South. Grounded in Joseph Nye’s theory of "Soft Power" and Alexander Wendt’s "Social Constructivism," this study establishes that by treating technology as a "Global Public Good," India is imparting a new direction to South-South Cooperation. The international expansion of UPI not only shields developing nations from the "weaponization of finance" and grants them strategic autonomy, but it also lays the foundation for an equitable and multipolar digital world order.

This study evaluates the financial stability, operational efficiency, and earning performance of commercial banks using the supervisory CAMEL (Capital Adequacy, Asset Quality, Management Efficiency, Earnings Quality, and Liquidity) framework. Utilizing balanced panel data across ten leading public and private sector commercial banks over a ten-year observation period (2014–2024, N = 100 bank-year observations), the study identifies the primary balance-sheet determinants of bank profitability. Employing Pooled Ordinary Least Squares (OLS), Fixed Effects (FE) panel estimation, and robustness checks via Random Effects (RE), the empirical findings indicate that asset quality (measured by Net Non-Performing Assets) and management efficiency (measured by the Cost-to-Income Ratio) exert statistically significant negative effects on Return on Assets (ROA) and Return on Equity (ROE). In contrast, well-capitalized institutions operating with optimized credit-to-deposit ratios sustain superior net interest margins. The paper provides actionable managerial insights regarding forward-looking credit underwriting, dynamic loan provisioning, and risk-weighted capital allocation.

This Research paper explores the contentious outcomes of decolonization in Nigeria, highlighting the detrimental effects of technological advancement on natural landscapes. Author emphasizes the relentless deforestation driven by Western companies and brings to light Nigeria&#39;s struggle to restore ecological balance. This research paper highlights the deep connections between the forest and Yoruba folklore and imagination. The forest represents the persistent deterioration of natural resources and spiritual life in postcolonial Nigeria. The central spatial elements that define fictional universe include the ghetto, the forest, and Madame Koto’s bar. The ghetto and the forest are the main destinations for the abiku&#39;s movements, with the bar functioning as a luminal space between these realms. The ghetto is characterized by dirt and violence, results from colonial and neocolonial forces that have driven chaotic urbanization. Conversely, the forest symbolizes resistance, a realm where the forces of nature challenge human violence. This tension is mirrored in the environmental degradation caused by deforestation and the construction boom that follows the destruction of the trees. Authour presents a unique view of the natural world, integrating motifs from Nigerian traditions. Against the backdrop of globalization and neo-colonial exploitation, and with an acute awareness of environmental vulnerability, and illustrates a compassionate understanding of how human activities endanger natural processes.

The rapid growth of digital technologies is changing the way, work to be analyse and the skills required for employment across the world. Technologies such as artificial intelligence, automation, data analytics, and digital platforms are reshaping job roles and increasing the need for workers who are digitally skilled, flexible, and willing to keep learning throughout their careers. In this changing environment, digital literacy has become a basic and essential skill. It is not limited to using digital tools but also includes critical thinking, problem-solving, ethical use of technology, and effective communication in digital spaces. Higher education institutions play an important role in preparing students for this future workforce because they connect academic learning with employment opportunities. However, many graduates still face challenges related to skill gaps and employability, showing that current curricula often do not keep pace with technological change. This situation calls for a clearer understanding of how digital literacy and skills development should be designed and taught in higher education.
This paper uses a conceptual and analytical approach to examine how higher education institutions can support digital literacy for long-term employability. Based on digital skills frameworks and employability studies, the paper presents an integrated framework that links digital literacy, teaching practices, institutional strategies, and labor market needs. The analysis shows that effective digital skills development cannot be achieved through isolated technology courses alone. Instead, digital competencies should be included across subjects, teaching methods, assessments, and faculty training. When digital literacy is embedded in the overall learning environment, students become more adaptable, innovative, and better prepared for changing career paths. The paper also emphasizes the need for cooperation between higher education institutions, industries, and policymakers to ensure that academic programs match workforce requirements. By focusing on inclusive learning, continuous skill development, and responsible use of digital technologies, the study highlights the growing responsibility of higher education in preparing students for the future of work. The paper concludes by offering practical suggestions for educators and policymakers and identifying areas for future research in different educational and national contexts.

Correct botanical identification is fundamental to pharmacognosy, herbal drug authentication, conservation, and reproducible medicinal-plant research. Species of Bauhinia are particularly suitable for comparative morphological study because several taxa share conspicuously bilobed leaves, similar tree or shrub habits, and broadly comparable floral architecture. The present comparative review examines seven taxa: Bauhinia purpurea L., B. variegata L., B. tomentosa L.,
B. racemosa Lam., B. malabarica Roxb., B. vahlii Wight & Arn., and B. acuminata L. Comparative morphological characters were evaluated and checked against authoritative floristic and nomenclatural sources. Habit, leaf size and architecture, lobe depth, venation, indumentum, inflorescence, flower colour and markings, calyx, corolla, androecium, pod and seed characters, and flowering period were assessed for their diagnostic value. Most observations were consistent with published descriptions. However, two reproductive characters required important correction: B. vahlii is described in authoritative floristic sources with three fertile stamens rather than ten, while
B. malabarica is not appropriately characterized as having five fertile and five sterile stamens; male flowers are described with ten fertile stamens and female flowers with reduced staminodes.
Current nomenclatural databases place B. malabarica and B. vahlii under Piliostigma malabaricum and Phanera vahlii, respectively; the traditional names are retained as the principal names in this review, with current names supplied parenthetically for taxonomic clarity. The review demonstrates that reliable identification should not depend on a single character. Instead, a hierarchical combination of habit, leaf architecture, floral characters, reproductive morphology, and pod features provides a more robust field-authentication strategy. The resulting comparative framework can support pharmacognostical standardization, herbarium authentication, teaching, and preliminary field identification of morphologically similar Bauhinia and allied taxa.

This article critically re-examines the Administration of Juvenile Justice in Nigeria, tracing it’s evolution from the Colonial era Children and Young Persons Ordinance 1943 and up to the contemporary Child Rights Act (CRA) 2003.Drawing on the legal transplantation theory, there is argument that the Nigeria's Juvenile Justice system is a clear example of "fragmented legal transplantation", and this fragmentation undermines the effective realization of children’s right guaranteed under International treaties, for example Convention on the Rights of the Child and the African Charter on the Rights and Welfare of the Child. The central contention that the CRA’s domestication requirement is not merely administrative but a constitutional mechanism that sustains the colonial-era fragmentation, rendering the Act a symbolic commitment that denies millions of Nigerian children the protections that international law and national legislation purport to guarantee.
This Article relies on doctrinal analysis, supported by a comparative analysis from India and South Africa. This article highlights three structural impediment to a uniform child rights protection: (i)the constitutional allocation of criminal procedure and welfare matters to the state list; (ii)there is no federal enforcement mechanism to enforce the states domestication; and (iii)the side by side operation of conflicting customary and religious legal orders. This article argues that these impediments do not happen per chance as they are but a structural issue, and that they render the Child Rights Act a mere paper work, a legislative aspiration:rehabilitative in theory while it is retributive in fact.

The article concludes by proposing dual reform: first, a constitutional amendment fo inclusion of Juvenile Justice on the Exclusive Legislative List, and second, a federal fiscal system initiative adopting a conditional access to certain federal allocations on state adoption and enforcement of the CRA, with non-complaints state losing eligibility. Absent such reforms, the administration of Juvenile Justice in Nigeria will remain a constitutional failure, leaving millions of children amongst the nation’s most vulnerable

Ayurveda, the ancient Indian system of medicine, is founded on the Panchamahabhuta Siddhanta—the doctrine of five great elements (Prithvi, Ap, Tejas, Vayu, Akasha). This elemental framework explains the constitution of the human body, diet, and environment. Nutrigenomics, a modern discipline, investigates how nutrients interact with genes to influence health outcomes. This article explores the conceptual parallels between Panchamahabhuta and nutrigenomics, highlighting their relevance in personalized nutrition, preventive medicine, and integrative healthcare. By correlating elemental theory with molecular nutrition, the paper proposes a holistic model for future interdisciplinary research.

Security Operations Centers (SOCs) act as the primary defense for protecting businesses against the constant barrage of cyber threats we see today. However, the traditional way of running a SOC is essentially drowning under too many alerts, slow manual checks, and a serious lack of expert analysts to do the heavy lifting. Artificial Intelligence (AI) has stepped in as a real game-changer here, providing a way to automate workflows, spot threats with much better accuracy, and jump on incidents way faster than before. This paper breaks down a framework for an AI-driven SOC that brings together machine learning, behavioral tracking, threat data, and SOAR technology to modernize cybersecurity for the long haul.

Cloud computing is technology developing demand architecture, which was really useful for IT enterprises. Using cloud computing that offers cost effective & customer flexible service. This cloud computing is useful for big organization like Google, Facebook, Dropbox etc. And also this may increase the competence of the organization without giving new training for the fresher. Various countries data centers adopting cloud computing because of its database and application but the highest priority is for the securing of data. Cloud computing is Mainly used for its performance, accessibility and its affordable price. The main purpose of using cloud computing is for the protection of data. When we aware the word data security means the first thing is qualities (confidentiality, integrity and availability). In this data security is also having major issues, which means the data stored that was automatically stored over the cloud. When we used to see the development of computing technology in the cloud environment for the future advancement is fully based on the data privacy and data security protection. It may helps to use mainly for the organization & government sector.In this paper discussed about cloud computing security challenges and issue, while transferring the data into the cloud and also get reliable solution to overcome from the data security while using the cloud environment. That the comparative research from the existing cloud security approach about data privacy and data security by utilizing cloud computing. It will be useful to strengthen the security of data storage in a cloud environment.

Hair fall (Intithār al-Sha‘r) is a complex condition influenced by multiple factors, affecting millions worldwide. Unani medicine attributes hair loss to imbalances in Ghidhā (nutrition) and disturbances in Bukhārāt- i -Dukhāniyya (essential vaporous substances), often due to chronic illnesses, poor diet, or temperamental imbalances. In contrast, modern medicine links hair fall especially Telogen Effluvium (TE) to oxidative stress, nutritional deficiencies. This article aims to bridge the gap between Unani concepts and modern biomedical science. Jawarish Jalinoos, a traditional Unani formulation with 17 herbal ingredients known for their antioxidant, anti-inflammatory, and hair-regenerating effects. Key compounds such as β-sitosterol, jatamansic acid, piperine, quercetin, and asarone function through mechanisms like VEGF up regulation, 5α-reductase inhibition, and free radical scavenging. this paper highlights how Jawarish Jalinoos combats oxidative stress, enhances scalp circulation, modulates growth factors, and aligns with the known causes of hair fall in both Unani and modern medicine. It offers a holistic, integrative approach to managing hair loss.

Quantity surveying (QS) firms in Nigeria operate in a competitive and economically volatile environment in which firm-level factors such as organisational culture, innovative practice, learning leadership, and financing method have each been separately linked to firm performance and survival. Machine learning (ML) is increasingly proposed as a technology capable of enhancing QS firm performance directly, yet firm-performance research in Nigeria has not yet tested whether ML adoption instead acts as a mediating mechanism through which existing firm-level antecedents translate into improved performance. This paper reviews the empirical literature on QS firm performance in Nigeria, on the decades-long history of IT and innovation adoption within Nigerian QS practice, and on AI/ML-mediated or AI/ML-moderated firm and employee performance more broadly, with the aim of proposing a conceptual mediation framework. Drawing on twenty sources published between 2005 and 2026, the review finds consistent evidence that organisational culture, innovative practice, learning environment and leadership, and financing method each significantly predict QS firm performance or survival in Nigeria; that QS-specific technology adoption in Nigeria has progressed from basic computer usage in the mid-2000s, through moderate software and ICT adoption in the 2010s, to today's still-early engagement with AI and ML tools; and, in adjacent Nigerian sectors and in a recent Nigeria-focused systematic review of AI for construction cost and schedule prediction, that AI/ML measurably improves firm-level outcomes and has been shown to mediate the relationship between an underlying organisational capability and perceived organisational performance. Within the QS-specific literature itself, however, no reviewed study has yet tested machine learning as a mediator of the relationship between firm-level antecedents and QS firm performance. The paper proposes a conceptual framework in which ML adoption mediates the relationship between four firm-level antecedents and four performance outcomes, illustrated with the only directly comparable direct-versus-indirect effect pattern identified in the reviewed Nigerian QS-firm literature, and concludes with directions for the framework's future empirical testing.

Background: Psychological stress is associated with cardiovascular risk through autonomic, neuroendocrine, inflammatory, vascular, myocardial, and behavioral pathways. Ayurveda describes Atichinta (excessive worry or mental preoccupation) among the factors associated with Rasavaha Srotas Dushti and identifies Hridaya as a principal root of Rasavaha Srotas.
Objective: To critically synthesize classical Ayurvedic descriptions of Atichinta, Rasavaha Srotas, and Hridaya and examine their possible conceptual relationships with contemporary mechanisms of stress-related cardiovascular disease, while clearly distinguishing textual evidence from modern mechanistic inference.
Methods: A narrative review was undertaken using classical Ayurvedic sources, including Charaka Samhita, Sushruta Samhita, and Sharangadhara Samhita, together with selected biomedical literature identified through PubMed and major cardiovascular literature. The modern evidence synthesis focused on psychological stress, autonomic and hypothalamic–pituitary–adrenal responses, endothelial dysfunction, inflammation, coronary microvascular dysfunction, mental stress-induced myocardial ischemia, and Takotsubo syndrome. The literature was updated through September 2026. No formal systematic-review risk-of-bias assessment or quantitative meta-analysis was undertaken.
Discussion: Classical Ayurveda places Atichinta within the etiological framework of Rasavaha Srotas Dushti and assigns Hridaya an important role in Rasa, circulation, and Manas-related concepts. Contemporary evidence supports plausible associations between psychological stress and cardiovascular dysfunction through sympathetic and hypothalamic–pituitary–adrenal activation, altered vascular function, inflammation, and stress-related myocardial effects. These parallels may support hypothesis generation, but Sanga, Rasa Dushti, and Vyana Vayu should not be presented as direct anatomical or molecular equivalents of microvascular obstruction, inflammation, or autonomic physiology.
Conclusion: The proposed Manas–Hridaya Axis should be regarded as a hypothesis-generating integrative framework rather than an established pathophysiological model. Future research should operationalize Ayurvedic constructs independently and prospectively test their relationships with validated psychological, autonomic, vascular, and cardiovascular outcomes.

Soil testing and soil awareness are essential for understanding soil quality, fertility, and its suitability for agricultural and environmental purposes. Soil properties, including organic matter and moisture content, play an important role in plant growth, nutrient availability, and soil health. To create awareness about soil quality and the importance of soil testing, soil samples from Rajasthan and Bhayandar were analysed and compared. The aim of the study was to determine the organic matter and moisture content of the collected soil samples using standard laboratory methods. Organic matter was estimated by the Walkley– Black method, which involves the oxidation of organic carbon using potassium dichromate in the presence of concentrated sulphuric acid, followed by titration with ferrous ammonium sulphate. Moisture content was determined gravimetrically by drying the soil samples in an oven at 105°C until a constant weight was obtained.The experimental results showed that the Rajasthan soil sample contained 0.38% moisture and 0.50% organic matter, whereas the Bhayandar soil sample showed 12.52% moisture and 0.465% organic matter. These results indicate differences in the moisture and organic matter content of the two soil samples. Such variations may be associated with differences in environmental conditions, soil composition, and water-retention properties.In conclusion, the study highlights the importance of soil testing in assessing soil quality and promoting soil awareness. Comparing soil samples from different regions helps develop an understanding of soil characteristics and their influence on plant growth and environmental sustainability. Regular soil testing can support informed decisions regarding soil management, agricultural practices, and the conservation of soil resources.

The principle of “no significant harm” is a foundational obligation of contemporary international water law, requiring watercourse states to exercise due diligence in preventing substantial injury to co-riparian states. India occupies a uniquely contradictory position in South Asian hydrophilics: simultaneously an upstream state relative to Pakistan and Bangladesh, and a downstream state relative to China. This paper examines India’s transboundary water practices through the lens of the no-harm principle, analysing treaty engagements, dispute resolution participation, and diplomatic postures across the Indus, Ganges, and Brahmaputra systems. The analysis reveals that India’s relationship with the no-harm principle is characterised by selective acceptance and strategic ambiguity. India has consistently refused to ratify the 1997 UN Watercourses Convention, citing the undefined nature of “significant harm” as a primary objection. Yet India has formally incorporated no-harm language into bilateral treaties such as the 1960 Indus Waters Treaty and the 1996 Ganges Treaty, while resisting operationalisation of substantive obligations through third-party mechanisms. The 2025 decision to place the Indus Waters Treaty in “abeyance” represents a critical juncture, with the Permanent Court of Arbitration affirming that unilateral suspension is legally impermissible and that fundamental principles of international water law remain binding irrespective of treaty status. The paper argues that India’s approach reflects a broader structural tension between upstream strategic interests and the normative constraints of international law, and that this tension is likely to intensify as China’s upstream activities on the Brahmaputra reshape the regional hydropolitical landscape.

India’s Labour Codes are one of the most ambitious projects of statutory integration in recent decades. The Industrial Relations Code, 2020, which is fully implemented in November 2025, integrates a total of twenty-nine different labour laws into a cohesive system of union recognition, dispute resolution, layoffs, and termination thresholds. In this paper, we will explore the effects of rationalization in terms of code integration by contrasting India’s developing termination system with a long-recognized American doctrine of employment-at-will. In contrast to India’s system of employment security based on procedural safeguards, standing orders, and 'last in, first out' retrenchment practices, employment-at-will in America values managerial flexibility where employers are free to terminate employees without 'just cause' provided certain statutory and public policy-violating requirements are maintained. These seemingly different models rest on a broader set of values: mass protection and institutionalized bargaining in India, versus individualized contractual autonomy in America.
India’s approach, while ensuring industrial relation stability, may result in a deterioration in hiring incentives, especially in small firms. Conversely, American flexibility allows quick adjustment to an altered workforce at a cost of high exposure to wrongful termination suits and undermined employment security. By finding best practices across jurisdictions, such as a mediation system for the U.S. and an adaptive waiver of notices for India, this study points out the ways in which flexibility and fairness can be brought together in the global labour market that is changing due to the rise in the gig economy.

Corporate tax planning is an important component of financial management because taxation directly affects corporate cash flows, investment capacity and after-tax profitability. This study examines the conceptual and empirical relationship between corporate tax planning and firm performance in the Indian corporate sector. The proposed study focuses on ten selected Indian listed companies and covers FY2020–21 to FY2024–25. Corporate tax planning is measured using Effective Tax Rate (ETR), Cash Effective Tax Rate (Cash ETR) and Book-Tax Difference (BTD), while firm performance is measured through Return on Assets (ROA), Return on Equity (ROE) and, where appropriate, Tobin's Q. Firm size, leverage, sales growth, capital intensity and firm age are included as control variables. The study integrates agency theory, stakeholder theory and tax-planning perspectives and proposes a panel regression framework. Existing Indian evidence indicates that effective tax rates vary with profitability, firm size, growth, leverage, asset tangibility and non-debt tax shields, while recent research finds that the performance consequences of tax avoidance depend on governance and ownership structures. The study therefore treats tax planning as a conditional financial strategy rather than assuming that a lower tax burden automatically improves performance.

Rauwolfia serpentina (L.) Benth. ex Kurz., commonly known as Sarpagandha, is an important medicinal plant of the family Apocynaceae, widely used in traditional systems of medicine, particularly Ayurveda, for the management of neurological, cardiovascular, and mental disorders. Classical Ayurvedic texts describe Sarpagandha as being indicated in Vata-vyadhi, Unmada, Apasmara, Anidra, and Visa, owing to its Tikta rasa, Rukṣa guna, Usna virya, and Katu vipaka. Ethnomedicinally, the plant has been used for the treatment of snake bites, insomnia, insanity, hypertension, and various systemic disorders.
Phytochemical investigations reveal the presence of more than eighty indole alkaloids, including reserpine, ajmaline, yohimbine, and serpentine, which are responsible for its wide spectrum of pharmacological activities. Modern experimental and in silico studies have demonstrated antihypertensive, sedative, antipsychotic, cardioprotective, hypolipidaemic, antidiabetic, antimicrobial, antioxidant, anti-inflammatory, antidiarrhoeal, and neuroprotective properties of Rauwolfia serpentina. Notably, reserpine established the plant as the world’s first plant-derived antihypertensive drug, marking a milestone in cardiovascular therapeutics.This review comprehensively highlights the ethnomedicinal importance, Ayurvedic perspective, phytochemistry, and pharmacological potential of Rauwolfia serpentina, supporting its relevance in evidence-based integrative medicine and future phytopharmaceutical development.

Nardostachys jatamansi, commonly referred to as Spikenard, is a rare, perennial herbaceous species indigenous to the high-altitude alpine regions of the Himalayas. Historically significant in diverse traditional medicinal frameworks—including Ayurveda, Homeopathy, and the Indian System of Medicine (ISM)—this rhizomatous plant is increasingly recognized for its multifaceted pharmacological potential in contemporary medicine. This article reviews the botanical classification, complex chemical composition, and therapeutic activities of N. jatamansi. The plant is rich in bioactive sesquiterpenes, such as jatamansone, nardal, and patchouli alcohol, alongside various phenols and flavonoids. Extensive experimental studies demonstrate that N. jatamansi extracts possess significant antioxidant, anti-stress, and anticonvulsant properties. Notably, the plant exhibits neuroprotective effects, enhancing memory function in neurodegenerative models and reducing ischemic damage in cerebral palsy simulations. Furthermore, its antiproliferative effects in breast cancer cells and its clinical efficacy in managing Stage 1 hypertension underscore its potential as a versatile therapeutic agent.

Buthūr-i-Labaniyya, commonly identified with acne vulgaris, is a chronic inflammatory disorder of the pilosebaceous unit characterized by comedones, papules, pustules and, in more severe cases, nodules and scarring. In the Unani System of Medicine, Buthūr-i-Labaniyya has traditionally been discussed under the broader concepts of Mizāj, Akhlāṭ, Mādda, digestion and the movement and elimination of abnormal matter. Classical Unani physicians described the condition as a cutaneous manifestation associated with altered bodily matter and localized accumulation within the skin. This narrative review examines the classical Unani understanding of Buthūr-i-Labaniyya alongside contemporary knowledge of acne pathogenesis and critically evaluates the available evidence on Unani management. Classical texts, including Al-Qānūn fī al-Ṭibb, Al-Ḥāwī fī al-Ṭibb, Kitāb al-Fākhir and later Unani pharmacological and dermatological works, were considered together with published clinical studies and experimental investigations. Particular attention was given to the concepts of Balgham, Mādda, Saddah, Tajfīf, Tahlīl and Jālī, as well as individual medicinal plants and compound formulations used traditionally for acne. Available clinical studies of preparations such as Tila-i-Muhāsā, Zimād-i-Muhāsā, Itrifal Shāhtra, Sharbat-i-Unnāb and Laṭūkh suggest potential therapeutic benefit, but the evidence remains limited by small sample sizes, short treatment periods, heterogeneous formulations and variable methodological quality. The traditional concepts may provide useful hypotheses for further investigation, but they should not be regarded as direct equivalents of established modern pathological mechanisms. Future research should focus on standardized formulations, adequately powered randomized clinical trials, validated outcome measures, mechanistic investigations and long-term safety assessment.

Education in India has often been characterized as having a breadth of access, a range in opportunities, distinction in scholarship and an engagement in social and public issues. Yet there are large segments of population who remain excluded from the benefit of education. This is especially true for scheduled castes, scheduled tribes, minorities, women and other deprived communities. At present the country is facing several challenges in education such as problem of illiteracy, educational inequality, imbalances in the growth of educational institutions, etc. In the present research paper discussed emerging challenges and new initiatives in the Indian Education System.

AQI crisis in India is one of the most challenging issues among the nation in the current scenario, which badly affects social harmony and public health as well in many dimensions. Across the nation air pollution has turned into a severe and protracted problem has a profound impact on people's social life along with physical and mental health degradation. This paper concludes the social and mental fallout of India's air pollution crisis with policy recommendations. Poor air quality affects every day social behavior, social harmony along with the psychological states such as anxiety, depression and cognitive decline. In this research work sociological theories, health surveys and recent events are used. India's air pollution problem related suggestions are also provided here to deal with social and psychological challenges.

Psidium guajava (L.), commonly known as guava, is a tropical fruit plant belonging to the family Myrtaceae and is widely cultivated in countries such as India, Indonesia, Pakistan, Bangladesh, and South America. Guava leaves contain a wide range of biologically active phytochemicals, including flavonoids, phenolic compounds, and tannins. Major constituents reported in the leaves include quercetin, avicularin, apigenin, guaijaverin, kaempferol, hyperin, myricetin, gallic acid, catechin, epicatechin, chlorogenic acid, epigallocatechin gallate, and caffeic acid.
Various studies have demonstrated that guava leaf extracts possess several pharmacological activities, including antioxidant, antimicrobial, antidiabetic, antidiarrheal, anticancer, hepatoprotective, and lipid-lowering effects. These beneficial properties are mainly attributed to the presence of diverse phytoconstituents present in the leaves. Therefore, guava leaves have considerable potential for use in pharmaceutical and functional food preparations. However, further experimental and clinical studies are required to establish their therapeutic efficacy and safety.

Oryza sativa L. (Jeerakashala rice), a traditional aromatic rice variety widely cultivated in Kerala, is a natural source of carbohydrates, proteins, vitamins, minerals, and bioactive compounds with potential cosmetic benefits. The present study focuses on the preparation and evaluation of Jeerakashala rice powder as a natural exfoliating agent for lip scrub formulation. The rice grains were processed, dried, and finely powdered to obtain a suitable exfoliating material. The prepared rice powder was incorporated into a lip scrub formulation along with natural moisturizing and nourishing ingredients. The formulation was evaluated for appearance, colour, odour, texture, homogeneity, pH, spreadability, washability, exfoliating ability, and stability. The fine particles of rice powder are expected to assist in the gentle removal of dead and dry skin cells while the other natural ingredients help maintain lip softness and moisture. The study highlights the potential of Jeerakashala rice powder as a simple, economical, and naturally derived exfoliating ingredient for cosmetic lip-care applications.

Beta vulgaris L. (Beetroot) is a natural source of betalains, antioxidants, vitamins, minerals, and other bioactive compounds with potential cosmetic benefits. The present study focuses on the preparation and evaluation of beetroot powder as a natural colourant in lip scrub formulation. Fresh beetroot was processed, dried, and finely powdered to obtain a suitable natural colouring material. The prepared beetroot powder was incorporated into a lip scrub formulation along with natural exfoliating, moisturizing, and nourishing ingredients. The formulation was evaluated for appearance, colour, odour, texture, homogeneity, pH, spreadability, washability, exfoliating ability, and stability. The betalain pigments present in beetroot powder are expected to impart a natural reddish-pink colour to the formulation, while its antioxidant constituents may provide additional cosmetic benefits. The study highlights the potential of beetroot powder as a simple, economical, and naturally derived colouring ingredient for cosmetic lip-care applications.

The scientific significance of the data presented in this article lies in the fact that they form the basis for the development of a technology for producing activated carbon adsorbents by modifying walnut and almond shells and using the resulting adsorbent for the purification of metals and wastewater from metallurgical plants. The practical significance of these results lies in the development of an industrial technology for producing activated carbon adsorbents from local agricultural waste and their use in industrial wastewater treatment.

Averrhoa bilimbi Linn. is a tropical medicinal plant widely cultivated in many tropical and subtropical regions due to its therapeutic potential. Traditionally, different parts of the plant have been used in the management of diabetes mellitus, hypertension, microbial infections, and several other health conditions. The present review aims to provide a comprehensive overview of the ethnomedicinal uses, phytochemical constituents, and pharmacological properties of A. bilimbi by correlating traditional knowledge with available scientific evidence. Information was compiled from peer-reviewed publications indexed in scientific databases such as PubMed, Medline, EMBASE, and ScienceDirect, with emphasis on studies published between 1995 and 2015. Experimental investigations have demonstrated that A. bilimbi possesses a broad spectrum of biological activities, including antidiabetic, antihypertensive, antimicrobial, antioxidant, hepatoprotective, hypolipidemic, and thrombolytic effects. These findings support its traditional use and highlight its significance as a promising source of bioactive phytochemicals for complementary and alternative medicine. Despite extensive pharmacological research, the specific compounds responsible for many of these therapeutic effects have not yet been fully isolated or characterized. Further studies employing advanced phytochemical and molecular techniques are therefore warranted to identify the active constituents, elucidate their mechanisms of action, and establish their clinical efficacy and safety. This study highlights the promise of A. bilimbi for future drug discovery and development while consolidating the present understanding of the organism.

Values form the very essence of Indian society. While modern man is making rapid strides of progress in every field, he often experiences a sense of deficiency, stress, frustration, or dissatisfaction in life. This stems from the fact that he has gradually lost sight of his values. Values serve as a pathway leading humans toward an elevated life; a society and culture grounded in such values establish a unique identity on the global stage. The National Education Policy (NEP) 2020 highlights three key categories of values: human and ethical values, constitutional values, and social-global values. Instilling these values in children from an early age paves the way for the creation of exemplary citizens. Teachers play a foundational role in this process of value formation, as they are often the first role models a child encounters in school. The NEP 2020 places significant emphasis on value-based education and the role of teacher training. To this end, a four-year integrated B.Ed. degree is set to become the minimum qualification for school teachers by 2030. In the modern era, teacher training is essential for acquiring new knowledge and diverse skills. Value-based education enables the new generation to integrate social values with technological advancement, making teacher training indispensable. The NEP 2020 places special emphasis on the holistic development of students and 360-degree assessment through innovative teaching methods. Only when teachers are personally grounded in values can they shape the character of children for the nation's bright future. Thus, a teacher acts as a guide, a mentor and a role model of life's ideals, leading the child toward success through education.

Artificial Intelligence (AI) is emerging as one of the most important technologies transforming the financial sector. The rapid growth of machine learning, deep learning, natural language processing, predictive analytics, computer vision, robotic process automation and generative artificial intelligence has changed the way financial institutions collect information, assess risk, serve customers and make financial decisions. Banks, insurance companies, investment firms, fintech companies and regulatory institutions are increasingly using AI for credit assessment, fraud detection, anti-money laundering, customer service, investment analysis, algorithmic trading, risk management and regulatory compliance.
This research article examines the major opportunities, challenges and future directions associated with the application of AI in finance. The study follows a conceptual and descriptive research design and is based primarily on secondary data collected from academic research papers, books, reports of international financial institutions, regulatory publications and government sources. Recent literature and institutional reports published mainly during 2020–2026 are reviewed to identify major developments and emerging research themes. The analysis indicates that AI can improve operational efficiency, reduce processing costs, strengthen fraud detection, support more accurate credit assessment, personalise financial services, improve investment decisions and strengthen regulatory compliance. At the same time, AI creates significant concerns relating to data quality, privacy, cybersecurity, algorithmic bias, lack of explainability, model risk, hallucinations in generative AI, third-party technology dependence and potential systemic financial risks.
The study concludes that the future of AI in finance depends not only on technological innovation but also on responsible governance, human oversight, high-quality data, explainable models, cybersecurity and appropriate regulation. The future direction is likely to involve greater integration of generative AI, AI agents, real-time analytics and intelligent automation. Financial institutions should therefore adopt a balanced approach that combines technological innovation with accountability, transparency, consumer protection and financial stability.

Paul Michel Foucault was born in Poitiers, France, on October 15, 1926. He passed away in Paris on June 25, 1984, at the age of 57. Foucault stands as one of the most influential intellectual figures of the twentieth century. A philosopher, historian of ideas, social theorist, and literary critic, he held the Chair of the History of Systems of Thought at the prestigious Collège de France, where he taught from 1970 until his death. His oeuvre rigorously interrogates the relationship between power and knowledge, demonstrating how these forces intertwine and operate as instruments of social control through institutional practices. Although frequently associated with post-structuralism and postmodernism, Foucault himself rejected such categorizations, preferring to describe his intellectual project as a critical history of modernity. The reach of his ideas extended far beyond academic circles, shaping not only philosophical and social scientific discourse but also inspiring political movements and activist initiatives, which drew upon his analyses to challenge mechanisms of domination and articulate strategies of resistance. This article offers a concise overview of Foucault’s work in commemoration of the centenary of his birth.

This survey examined prospects and challenges of entrepreneurship education in public universities in Rivers State, Nigeria. The aim was to ascertain the challenges and prospects of entrepreneurship education in public universities domiciled in Rivers State drawing insights from an empirical review of extant literature. The empirical review of existing literature identified key challenges of entrepreneurship education as inadequate funding, poor infrastructural facilities, shortage of qualified instructors, a disconnect between theory and practical knowledge, poor integration of digital and innovation-based skills and weak collaboration between industry stakeholders and tertiary institutions. Despite these challenges, this study, revealed venture creation and employment generation as prospects of entrepreneurship education. Consequent on this, this study concludes that entrepreneurship education promises a self-reliant future, it holds strong developmental prospects in public universities in Rivers State and serves as a viable scheme for addressing unemployment in Rivers State, Nigeria. Therefore, this study recommended that a more robust curriculum development on entrepreneurship, stronger university-industry collaboration/partnership, adequate funding, adoption of practical and experiential learning methods, integration of technology into work and strengthened entrepreneurial policies and frameworks.

In India, it is common perception that doing domestic work is below dignity. Although performance of household chores also require skill but they fall under unorganised sector. Domestic workers do not have any protection under the current labour legislations as domestic workers belong to unorganised sector. The domestic work is performed in “private households” which is not covered by professional definition of industry to which labour laws could apply. Similarly, a special statute has been enacted to target entire unorganised sector workers known as “the Unorganised Workers Social Security Act, 2008”. This Act has included domestic workers under the unorganised sector. But this Act has not defined domestic workers specifically. This, Act provides benefit to workers by some schemes mentioned in Schedule-I. One such scheme is the Rashtriya Swasth Bima Yojana (RSBY). Several attempts have been made so far to enact a comprehensive law for domestic workers but all attempts have failed. It started from the earliest attempt in the form of the Domestic Worker (Conditions of Service) Bill, 1959. The latest attempt in this this direction was the Domestic Workers (Regulation of Work and Social Security) Bill, 2017. Also, recently, the government has formulated four Labour Codes i.e., the Code on Wages, 2019, the Code on Industrial Relations, 2020, the Code on Social Security, 2020, the Occupational Safety, Health and Working Conditions Code 2020. These codes aim at securing protection to workers including unorganised workers. Further, the All-India Survey on Domestic Workers is being conducted by the Labour Bureau, Chandigarh under the directions of the Ministry of Labour and Employment. Only after the enactment of special legislation for domestic workers will get proper safeguard and recognition of rights.

Background: Psychogenic nonepileptic seizures (PNES), also termed functional seizures, are episodes resembling epileptic seizures without the characteristic epileptic ictal discharges activity. Some patients with functional neurological disorder (FND) also present with abnormal involuntary limb movements, including dystonic posturing.
Case presentation: A patient with a previously established diagnosis of PNES presented with recurrent uncontrolled flexion of the left elbow, interfering with upper-limb movement and functional activities. The clinical assessment focused on the frequency and characteristics of the abnormal movement, elbow range of motion (ROM), functional limitations, and associated neurological findings.
Intervention: A physiotherapy programme was planned using patient education, movement retraining, attention-redirection strategies, graded functional reaching, relaxation, and a home exercise programme, in coordination with the treating neurologist and mental health professional. These interventions are based on rehabilitation principles for functional motor symptoms.
Outcome: Changes in elbow ROM, frequency and duration of abnormal movements, and upper-limb functional ability should be documented using objective pre- and post-treatment measurements.
Conclusion: Individualized physiotherapy may contribute to functional recovery in patients with functional motor symptoms associated with PNES. However, uncontrolled elbow flexion requires appropriate neurological assessment and should not automatically be attributed to PNES.

Indian juvenile justice law does not treat a child who has come into conflict with law as an adult offender in miniature. The Juvenile Justice (Care and Protection of Children) Act, 2015 requires the State to respond to the act committed, but in a manner that keeps the child’s development, dignity and capacity for reform in view. Observation homes, special homes and places of safety are the institutional instruments of that response. Custody within such an institution, however, is not rehabilitation in itself. Rehabilitation is achieved only when the period of placement is used for education, counselling, health care, employable skills, work with the family and structured after-care. This article examines the statutory framework, tests institutional practice against it, identifies the recurring gaps between law and delivery, and proposes measures to make institutional care serve its declared purpose: the safe and lasting return of the child to society.

The abstract will introduce Dr. B.R. Ambedkar as a social reformer, intellectual, political leader, and the central figure in the anti-caste movement in twentieth-century India. The paper will examine how Ambedkar transformed the struggle against caste oppression from a social reform issue into a movement based on rights, dignity, representation, and equality. The study will analyse major movements, political interventions, writings, and the historical transition from colonial caste structures to constitutional guarantees of social justice. The period 1920–1956 covers Ambedkar’s emergence as a leader of the Depressed Classes, major movements such as Mahad Satyagraha, political negotiations such as the Poona Pact, and his conversion to Buddhism. The Poona Pact of 1932 was a major turning point in debates over political representation of the Depressed Classes. The Mahad Satyagraha of 1927 represented Ambedkar’s attempt to challenge caste-based exclusion from public resources and assert human dignity.