Volume 13 | Issue 9

 Abstract

Migration is more than the physical act of moving from one place to another; it often represents a profound transformation of identity, selfhood, and belonging. For women, this experience is deeply gendered--shaped by patriarchal expectations, socio-cultural constraints, and the psychological toll of uprooting. Across time and geography, female migrants have had to navigate the double bind of displacement and gender oppression, where the promise of freedom or survival often comes at the cost of emotional and bodily autonomy. In literature, the female migrant's story is frequently a narrative of rupture, resilience, and reinvention. This is particularly evident in Amrita Pritam's Pinjar, Bharati Mukherjee's Jasmine, and Angie Cruz's Dominicana--three novels that portray women at the intersection of migration, violence, and identity. These protagonists do not simply move across borders; they are shaped, broken, and remade by them. Their journeys highlight how migration can be both a trauma and a site of potential empowerment, revealing the complex interplay between personal agency and historical force.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Contextualize Migration and its Impact on Female Protagonists - A Legal Perspective

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The success of pharmaceutical distribution channels in South India is investigated in this study in relation to distributor efficacy, cultural alignment, and trust. The study finds important relationship drivers that lead to better distributor performance using primary data from 103 respondents and statistical methods including multiple linear regression and exploratory factor analysis. According to the research, distributor effectiveness is greatly increased by trust and cultural fit, which has a favorable impact on outcomes like customer happiness, sales growth, and strategic fit. These observations highlight the necessity for pharmaceutical companies to give relational and cultural compatibility equal weight with pricing and logistics plans.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pharmaceutical supply chain, distributor effectiveness, trust, cultural alignment, supply chain performance, factor analysis, South India

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Recruitment is often considered the foundation of organizational success, as the quality of employees directly influences productivity, innovation, and long-term sustainability. However, the process of identifying, attracting, and retaining the right candidates has historically been challenging for organizations across sectors. Common problems such as extended hiring timelines, high recruitment costs, limited visibility into candidate quality, and difficulty in predicting long-term retention have created inefficiencies. In recent years, the rapid growth of digital tools and data-driven decision-making has introduced new opportunities to reimagine recruitment. Among these, Human Resource (HR) analytics has emerged as a powerful approach that combines data, technology, and predictive modeling to enhance every stage of the hiring cycle. The present study investigates the role of HR analytics in recruitment by combining primary survey data and secondary case study evidence. A survey was conducted with 45 HR professionals from diverse organizations, focusing on recruitment methods, adoption of analytics, challenges encountered, and perceived benefits. The data was analyzed and visualized using Power BI, enabling a clear interpretation of trends and patterns. In parallel, secondary case studies from global leaders such as Unilever, Google, and IBM were examined to understand practical applications of HR analytics in recruitment and talent management. Findings suggest that while job portals and traditional methods remain important, HR analytics tools are increasingly being used for resume screening, candidate assessments, and predictive retention analysis. The majority of organizations reported improvements in hiring quality, efficiency, and fairness, though limitations such as high costs, lack of skilled analysts, and data privacy concerns remain barriers. This study concludes that HR analytics is not merely a supporting tool but a strategic enabler of modern recruitment. By integrating analytics with human judgment, organizations can build recruitment processes that are faster, more objective, and better aligned with long-term organizational goals.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

HR Analytics, Recruitment, Predictive Hiring, Talent Acquisition, Data-Driven HR

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract Background: Rheumatoid arthritis (RA) is a long-lasting inflammatory condition that profoundly affects the health-related quality of life (HRQoL) for those who suffer from it. Given the disease's impact on physical, emotional, and social aspects of well-being, understanding the factors influencing HRQoL and the global diversity in these factors is essential for enhancing patient care (1, 4, 6, 10, 14). Objective: The goal of this systematic review is to assess the existing literature regarding HRQoL in individuals with RA, focusing on associated factors and regional disparities to develop more effective, patient-focused strategies (1, 5, 7, 13, 19). Methods: A thorough examination of 13 studies conducted in various countries--including Morocco, Egypt, Nepal, China, India, Poland, Indonesia, among others--was carried out (1-8, 10, 13, 14, 19). These studies employed cross-sectional, observational, and preliminary designs to evaluate HRQoL using validated instruments (e.g., SF-36, WHOQOL-BREF, HAQ-DI) and explored connections with disease activity, functional status, sociodemographic factors, and treatment approaches (4, 6, 7, 14, 15). Results: Most studies indicated a notable decline in HRQoL among RA patients (1, 4, 5, 6, 10). Influential factors included disease duration and activity (4, 6, 11), gender (13), employment status (2, 3), healthcare access (5, 8, 18), and mental health (12). Women, patients with elevated disease activity, and those in settings with limited resources experienced a more pronounced impact (5, 6, 7, 13). Investigations into interventions demonstrated favorable effects of targeted treatments and support for daily living on HRQoL outcomes (7, 8, 12). Conclusion: HRQoL for patients with RA is consistently observed to be lower, with significant evidence underlining the role of both clinical and social determinants (1, 4, 6, 13, 14). It is vital to address these factors through integrated and culturally aware interventions to enhance patient outcomes (10, 12, 18, 20). There is a need for more longitudinal and intervention-oriented studies to inform global best practices (14, 16).

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Rheumatoid arthritis; Health-related quality of life (HRQoL); Disease activity; Work ability; Functional status; Patient-centered care; Chronic disease; Global health disparities; Psychosocial impact; Rheumatology

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents an extensive review of seminal contributions at the intersection of ancient Indian philosophy and artificial intelligence (AI), with a particular emphasis on cognitive science, natural language processing and mental health. Anchored in both classical epistemological systems and emerging AI frameworks. The reviewed literature spans from metaphysical interpretations of Sanskrit grammar and Vedic knowledge systems to advanced computational methods like large language models and deep learning. The paper documents the evolution from philosophical abstraction to technological implementation, highlighting the integration of symbolic knowledge systems, ethical AI, and computational linguistics rooted in Indian tradition. The review concludes by emphasizing the enduring relevance of ancient wisdom in addressing contemporary challenges in AI, ethics, and cognitive modelling.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sanskrit, Artificial Intelligence, Cognitive Science, Bhagavad Gita, NLP, Vedanta, Knowledge Representation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the role of the Deen Dayal Upadhyaya Grameen Kaushalya Yojana (DDU-GKY) in generating employment through placement-oriented skill training. Focusing on three core objectives -- (1) identifying the placement-based courses offered under DDU-GKY, (2) assessing trainees' satisfaction with those courses, and (3) evaluating the overall effectiveness of the Central Government's skill-training interventions -- the research uses primary data collected from trainees enrolled in DDU-GKY programmes. A structured questionnaire was administered to capture information on course choice, placement outcomes, perceived training quality, and satisfaction levels. Data are analysed using descriptive statistics and inferential tests (e.g., chi-square tests and ANOVA) to test the stated hypotheses about the relationship between course selection, satisfaction, and programme effectiveness. The study aims to highlight which courses deliver the best placement outcomes, identify gaps between trainee expectations and programme delivery, and offer evidence-based recommendations to improve DDU-GKY implementation and placement linkages. The findings are intended to inform policymakers, training partners, and stakeholders involved in rural skill development and employment generation.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

DDU-GKY; skill development; placement-based courses; trainee satisfaction; employment generation; programme effectiveness; rural livelihood; vocational training

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Basanti priyamvada : yatharthk avlokan

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Basanti priyamvada : yatharthk avlokan

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT: Background: Epilepsy is a chronic neurological condition that profoundly affects patient's quality of life (QOL) due to recurrent seizures, cognitive deficits, psychosocial stigma, and adverse effects of antiepileptic medications. Pharmacists, as accessible healthcare providers, are increasingly involved in patient education, medication management, and adherence support, which may positively influence QOL outcomes. Objective: This systematic review aims to examine the effectiveness of pharmacist interventions in improving the quality of life of individuals living with epilepsy. Methods: A thorough literature search was conducted in PubMed, Scopus, Google Scholar, PsycINFO, MEDLINE, and Web of Science for studies published between July 2015 and July 2025. Eligible studies assessed pharmacist interventions such as patient counselling, educational programs, adherence monitoring, and pharmaceutical care and their impact on QOL in epilepsy patients. Data were extracted on study characteristics, intervention strategies, outcome measures, and key results. Results: Evidence from multiple studies demonstrates that pharmacist interventions enhance medication adherence, reduce treatment-related adverse effects, and improve health-related quality of life (HRQOL) in epilepsy patients. Structured counselling, educational support, and adherence-focused programs were consistently associated with better QOL outcomes across diverse populations and clinical settings. Conclusion: Pharmacist interventions are effective in improving the quality of life of patients with epilepsy. Incorporating pharmacists into multidisciplinary care teams is recommended to optimize clinical outcomes and patient wellbeing.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key-words: Pharmacist interventions, Epilepsy, Quality of life, Anti-epilepsy medications and Health-related quality of life

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present study was carried out to assess the larvicidal potential of the indigenous plant Mentha longifolia against the larvae of the Aedes aegypti (vector of Dengue, Chikungunya, and Zika), Anopheles stephensi (vector of urban malaria), and Culex quinquefasciatus (vector of Lymphatic filariasis). The acetone extract of plant leaves was used at 25, 50, 100, 200, 300, and 500 ppm dilutions in bioassays against different larval instars of the three mosquito species. Twenty larvae were exposed to the leaf extract at each concentration in a final volume of 100 ml formulation taken in a 250 ml glass beaker. The mortality data were analysed by the log-probit method, and lethal concentration (LC) values were calculated. The LC50 - LC90 values of Mentha longifolia extract against third instar larvae were calculated as 73.56 - 160.45, 72.49 & 146.57, and 81.23 - 84.69, while fourth instar larvae were calculated as 78.16 - 172.64, 81.17 - 173.47, and 144.24 - 149.26 for Aedes aegypti, Anopheles stephensi, and Culex quinquefasciatus, respectively.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

mosquito larvae, Mentha longifolia, Aedes aegypti, Anopheles stephensi, Culex quinquefasciatus, Plant extract, LC50, LC90

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: Respiratory tract infections (RTIs) continue to be a primary cause of illness and death globally, especially in low- and middle-income nations. They account for a substantial proportion of outpatient visits and hospital admissions in pulmonology departments. Due to overlapping clinical features of viral and bacterial infections, empirical antibiotic therapy is frequently initiated without microbiological confirmation. This practice significantly contributes to antimicrobial resistance (AMR), posing substantial challenges to public health. Objectives: To systematically review literature on antibiotic prescribing trends and drug utilization patterns in pulmonology departments of tertiary care hospitals, focusing on irrational prescribing, stewardship implementation, and guideline adherence. Methods: A comprehensive search of PubMed, Scopus, and Google Scholar (2015-2024) was conducted using predefined keywords. Four peer-reviewed studies that met eligibility criteria were selected. A narrative synthesis was used. Results: The review found high empirical use of broad-spectrum antibiotics--especially third-generation cephalosporins, macrolides, and fluoroquinolones. Adherence to guidelines was poor, and microbiological testing was infrequent. Studies implementing Antimicrobial Stewardship Programs (ASPs) reported improvements in prescribing behavior. Conclusion: Empirical antibiotic use is prevalent in pulmonology settings. Implementation of ASPs, improved diagnostics, and training are essential for optimizing antibiotic use and preventing AMR.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Antibiotics, Prescribing Patterns, Pulmonology, Antimicrobial Resistance, Drug Utilization, Tertiary Care Hospitals.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Digital marketing has revolutionized the way businesses interact with consumers, particularly among younger, tech-savvy demographics such as college students. This study aims to investigate the impact of digital marketing on the consumer buying behaviour of college students in Kerala. The specific objectives include examining the influence of social media platforms on purchase decisions, assessing the role of online advertisements in shaping brand preference, analyzing the relationship between digital marketing strategies and customer loyalty, and evaluating consumer trust and satisfaction in online purchases. Using a structured questionnaire, primary data will be collected from students across various colleges in Kerala. The data will be analyzed using statistical tools such as correlation and regression analysis to test the hypotheses, including the null hypothesis (H?) that there is no significant relationship between digital marketing strategies and consumer buying behaviour, and the alternative hypothesis (H?) that social media marketing has a significant positive impact on purchase decisions. The findings are expected to provide valuable insights for marketers and educational institutions on leveraging digital channels effectively to engage with student consumers, enhance brand loyalty, and drive informed purchasing behaviour.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Marketing, Consumer Behaviour, Social Media, Online Advertising, Brand Loyalty, College Students, Kerala.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Chattisgarh rajya ke pramukh parytan evam dharmik sthal

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chattisgarh rajya ke pramukh parytan evam dharmik sthal

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Continuous monitoring of vital parameters is essen- tial in modern healthcare, particularly for patients with chronic illnesses and elderly populations. Conventional wearable devices typically operate at fixed sampling rates, resulting in unnecessary energy consumption and reduced device lifetime. This paper presents a Python-based simulation framework for dynamic mode switching in health monitoring embedded systems. The proposed approach employs a Finite State Machine (FSM) to adaptively transition between Normal, Alert, and Critical states based on variations in heart rate (HR) and blood oxygen saturation (SpO2). The framework was implemented using open- source Python libraries (NumPy, SciPy, and Matplotlib) for signal generation, threshold detection, and real-time visualization. Simulation results demonstrate that the system conserves energy during stable conditions while ensuring responsiveness during abnormal events. Unlike prior studies that rely heavily on MATLAB/Simulink, this work highlights Python as a cost- effective and flexible platform for rapid prototyping of embedded healthcare solutions, with strong scalability toward IoT integra- tion and predictive analytics.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Health Monitoring, Embedded Systems, Dy- namic Mode Switching, Python Simulation, Finite State Machine, SpO2, Heart Rate, Energy-efficient Healthcare.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The integration of Artificial Intelligence (AI) in education presents transformative opportunities and significant challenges. AI technologies, such as adaptive learning systems, intelligent tutoring, and automated grading, offer personalized learning experiences, enhanced engagement, and improved efficiency in educational settings. These innovations enable educators to tailor instruction to individual student needs, facilitate real-time feedback, and reduce administrative burdens, thereby fostering a more effective and inclusive learning environment. However, the adoption of AI in education also raises critical challenges, including data privacy concerns, ethical considerations, and the potential for exacerbating educational inequalities. Additionally, there is a need for substantial teacher training and infrastructural support to effectively implement AI-driven tools. This paper explores the dual aspects of AI integration in education by examining its potential to revolutionize teaching and learning while addressing the ethical, practical, and technological hurdles that must be overcome to realize its full potential.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Intelligent Tutoring Systems, Personalized Learning Educational Technology, Virtual Classrooms, Data Privacy, Ethical Considerations, Educational Inequality.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The persistent challenge of non-performing assets (NPAs) has had a profound impact on the financial stability and profitability of the Indian banking sector. This study undertakes a comparative analysis of NPAs and key performance indicators--net profit margin (NPM) and net interest margin (NIM) between selected public sector banks (SBI, UBI, Canara Bank) and private sector banks (ICICI, HDFC, Axis Bank) over the five-year period from FY 2021 to FY 2025. The results reveal that private sector banks consistently outperform public sector banks in terms of NPM and NIM, with significant statistical differences across most years. While public sector banks have shown improvement in managing NPAs, the gap in asset quality remains significant in the later years of the study. Furthermore, regression findings confirm a strong negative relationship between NPAs and both NPM and NIM, underscoring the critical role of asset quality in financial performance.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Non-Performing Assets (NPAs), Public Sector Banks, Private Sector Banks, Net Profit Margin, Net Interest Margin, Financial Performance

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Economic inequality continues to shape the trajectory of national and global development. The Kuznets Curve hypothesis, introduced by Simon Kuznets in 1955, suggests an inverted-U relationship between inequality and economic growth. In early stages, inequality tends to rise as industrialisation favours capital-intensive sectors. However, beyond a certain income threshold, improved education, democratic redistribution, and labour participation contribute to an eventual decline. While this model remains influential, it often overlooks micro-level interventions that may influence the inflection and trajectory of inequality--especially among socially marginalised populations.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Inequality in education

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Among the important and essential principles of Green Chemistry Catalysis is the most valuable one. Green chemistry is the application of a set of principles that eradicates or minimizes the use or formation of hazardous materials in the formulation, execution and utilization of chemical products and emphasizes vulnerability minimization as the desired quality while developing new synthetic protocols. In recent years, nanotechnology, specifically nanocatalysis has become an emerging field of science due to its higher activity, selectivity and productivity as compared to conventional catalysts. Due to the exclusive structural and electronic characteristics of the nano materials and the exceptionally large surface area to volume ratio impart unique catalytic properties to nano particles. In this article we will be discussing the latest advances in the field of nano-catalysis and surfactant mediated generation of Nano Pockets which have opened new ways to explore synthetic methodologies for generation of novel functional materials.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Green Chemistry, Atom Economy, Nano Catalysis, Aqueous Solution Organic Synthesis, Surfactant Combined Catalyst

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Accurate classification of petrological samples is fundamental to geological investigations and resource exploration. Traditional methods relying on manual lithographic analysis are time-consuming and subject to expert bias. This study presents a novel deep learning framework for automated classification of Lithographical thin-section images. Utilizing convolutional neural networks (CNNs), the model was trained on a curated dataset encompassing diverse rock types, including igneous, sedimentary, and metamorphic classes. Data augmentation and transfer learning techniques enhanced model generalizability and performance. The proposed system achieved an overall classification accuracy exceeding 90%, outperforming conventional machine learning baselines. The results highlight the potential of deep learning to streamline petrological workflows, reduce human error, and enable large-scale geological mapping. Future work aims to integrate geochemical data and expand the model's applicability to field-acquired samples

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Accuracy, Convolution, Deep Learning, Image, Lithography, Neural Network.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Beti Bachao, Beti Padhao (BBBP) scheme, initiated by the Government of India in January 2015, is a flagship national program designed to address two critical issues: the Declining child sex ratio (CSR) and the promotion of education and empowerment of the Girl child. The scheme adopts a convergent approach, integrating the efforts of the Ministry Of Women and Child Development, Ministry of Health and Family Welfare, and Ministry Of Education. Despite extensive publicity through mass media campaigns, community Meetings, and school programs, studies across India reveal that awareness levels and Accurate understanding of the scheme's objectives vary considerably, particularly in rural And socio-economically disadvantaged regions. In the context of Bihar, where sociocultural norms, literacy rates, and economic constraints influence women's empowerment And gender equality, it becomes imperative to assess the community's knowledge Regarding BBBP and identify the socio-demographic factors that influence it.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Beti Bachao Beti Padhao, knowledge assessment, rural community, sociodemographic factors, awareness programs, Bihar, gender equality, girl child education.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This Liver cancer remains one of the most significant causes of cancer-related mortality globally, necessitating fast and accurate diagnosis. Traditional diagnostic approaches, such as biopsies and imaging, are often invasive and time-consuming. Deep learning has emerged as a promising solution in the medical imaging domain due to its ability to automate feature extraction and deliver high accuracy. This study focuses on using Convolutional Neural Networks (CNNs) and other deep learning models to detect liver cancer from CT and MRI scans. The proposed framework incorporates feature extraction, classification, and segmentation to enhance diagnostic precision. Experimental results show that the deep learning models outperform traditional machine learning techniques in metrics such as accuracy, recall, and F1-score. The findings support the integration of AI-based systems to assist radiologists in early detection and improve patient outcomes.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

CNNs, Liver Cancer, Deep Learning, CT and MRI Segmentation.

  License

Creative Commons Attribution 4.0 and The Open Definition