Volume 14 | Issue 6

 Abstract

India's urban transformation is occurring alongside rapid economic growth, expanding infrastructure, and increasing climate-related risks. As the country advances towards the vision of Viksit Bharat @2047, ensuring access to affordable, inclusive, and climate-resilient housing has become central to sustainable urban development. This paper examines the evolving concept of housing affordability in urban India, arguing that affordability extends beyond housing cost to encompass accessibility to livelihoods, public transport, social infrastructure, housing finance, and climate-resilient urban services. It highlights the importance of preserving existing community resilience mechanisms through in-situ upgrading, tenure security, and participatory planning rather than displacement-led redevelopment. The paper further explores the growing interaction between climate vulnerability and housing insecurity, particularly among low-income households residing in environmentally fragile locations. It emphasizes the need for climate-sensitive planning, resilient housing design, risk-informed land-use policies, and green infrastructure to reduce exposure to environmental hazards. The study reviews policy instruments for expanding affordable housing supply, including Transit-Oriented Development, land value capture, public-private partnerships, viability gap funding, rental housing reforms, and blended finance mechanisms. It also discusses the role of digital technologies in improving rental market transparency and housing governance. Additionally, the paper advocates for gender-responsive and universally accessible housing, integration of vernacular building knowledge with modern standards, passive cooling strategies, circular construction practices, and adoption of sustainable building frameworks. The analysis concludes that the future of affordable housing in India lies in the integration of accessibility, inclusion, resilience, sustainability, and economic opportunity. By aligning housing policy with climate adaptation and inclusive urbanization goals, India can create resilient communities that support social equity, environmental sustainability, and the aspirations of a developed nation by 2047.

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 Keywords

Climate Resilient Housing, Viksit Bharat, Rental Housing, Housing Finance

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The rapid advancement of Generative Artificial Intelligence (GenAI) has significantly transformed English Language Teaching (ELT), particularly in the area of writing instruction. AI-powered tools such as ChatGPT, Google Gemini, Microsoft Copilot, and Grammarly have introduced new opportunities for supporting learners throughout various stages of the writing process, including idea generation, grammar correction, revision, and academic writing assistance. Despite these pedagogical benefits, concerns regarding academic integrity, ethical use, overreliance on AI, critical thinking, teacher readiness, data privacy, and equitable access continue to influence the adoption of these technologies in educational settings. This narrative review synthesizes recent literature published between 2020 and 2026 to examine the applications, opportunities, and challenges of Generative AI in writing instruction within English Language Teaching. The review is guided by the Technological Pedagogical Content Knowledge (TPACK) framework, which provides a theoretical lens for understanding the effective integration of AI technologies into writing pedagogy. The findings indicate that Generative AI can enhance writing quality, learner autonomy, personalized learning, and formative feedback when implemented within sound pedagogical practices. However, responsible integration requires comprehensive AI literacy, institutional policies, ethical governance, curriculum redesign, and continuous professional development for educators. The review further identifies several research gaps, including the need for longitudinal studies, comparative evaluations of emerging AI platforms, and investigations across diverse educational and cultural contexts. Overall, this review contributes to the growing body of literature by providing a comprehensive synthesis of current evidence and offering practical implications for educators, researchers, curriculum developers, and policymakers seeking to integrate Generative AI responsibly into ELT writing instruction.

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Generative Artificial Intelligence, English Language Teaching, Writing Instruction, ChatGPT, TPACK, Artificial Intelligence, Academic Writing, AI Literacy, Educational Technology, Writing Pedagogy.

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The rapid advancement of digital technologies has transformed the educational landscape across the globe. Among emerging technologies, Virtual Reality (VR) and Augmented Reality (AR) have gained significant attention in higher education due to their ability to create immersive and interactive learning experiences. Traditional teaching methods often fail to maintain student engagement and practical understanding, especially in technology-driven academic environments. This research paper explores how the integration of VR and AR combined learning systems can improve student satisfaction in higher education institutions. The study examines the impact of immersive technologies on learner engagement, academic performance, motivation, and experiential learning. It also discusses the challenges faced during implementation, including infrastructure limitations, faculty training, and accessibility issues. The paper adopts a qualitative and analytical approach by reviewing recent studies, technological developments, and educational practices related to VR and AR systems. Findings indicate that combined VR and AR learning environments significantly enhance student satisfaction by promoting active participation, real-time visualization, collaborative learning, and personalized educational experiences. Furthermore, immersive learning technologies support practical skill development and bridge the gap between theoretical and applied knowledge. The study concludes that VR and AR integrated learning systems have the potential to revolutionize higher education by creating learner-centered educational environments that improve both academic effectiveness and student satisfaction

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Virtual Reality, Augmented Reality, Higher Education, Student Satisfaction, Immersive Learning, Educational Technology, Interactive Learning

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Artificial Intelligence (AI) is revolutionizing the financial services industry by enhancing customer experience, improving operational efficiency, and enabling personalized financial solutions. Despite the growing adoption of AI-powered financial services, consumer acceptance remains influenced by various technological and behavioural factors. This study investigates the factors influencing the adoption of AI-based financial services among Indian consumers. The research examines the impact of trust, perceived usefulness, perceived ease of use, security, privacy concerns, financial literacy, and social influence on consumers' adoption intention. A quantitative research design was employed, and primary data were collected from 400 respondents using a structured questionnaire based on a five-point Likert scale. The collected data were analysed using descriptive statistics, multiple regression analysis, and one-way ANOVA through SPSS. The findings revealed that trust emerged as the most influential predictor of adoption intention, followed by perceived usefulness, security, financial literacy, perceived ease of use, and social influence. Privacy concerns were found to negatively affect consumers' willingness to adopt AI-based financial services. Furthermore, significant differences in adoption intention were observed across age groups. The study contributes to the growing literature on AI adoption in financial services and provides valuable insights for financial institutions, fintech firms, and policymakers seeking to enhance consumer acceptance of AI-enabled financial technologies.

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Artificial Intelligence, AI-Based Financial Services, Adoption Intention, Trust, Financial Literacy, Privacy Concerns, FinTech, Consumer Behaviour.

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Cancer is the major killer among the major causes of death in the world. this dreadful condition has attracted the minds of physicians & surgeons from the very early times. it will be fascinating to note that sushruta (father of surgery) had mentioned about the cancer (arbuda). Ayurvedic texts mentioned about arbuda, which is considered as an equivalent of cancer. Acharya charaka described arbuda in the chapter on shopha i.e. Inflammatory & non-inflammatory swellings (cha.su.18.; cha.chi.12.). Acharya sushruta provided more information on arbuda, granthi, apachi, gandamala etc. Which is cancer related conditions. cancer is often compared to arbuda of ayurvedic classics, many other conditions are found to fall under different tumours. It is very important to do nidanpanchakatmaka study on ayurvedic approach of cancer.

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Cancer, Arbuda, Tumour, Nidan, Rupa, management, preventive measures

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Zooplanktons are good indicator of the changes in water quality so their diversity is one of the most important ecological parameters in water quality assessment. Aquatic ecosystems consist of physico-chemical and biotic components. The present study was undertaken to explore the diversity and ecology of Zooplanktons in kotdam. The present observations were made for a period of 18 months from Aug. 2022 to Jan 2024.They were identified by following standard taxonomic keys and illustrations. The zooplanktons were identified in the kotdam water which was belonged to three groups: Rotifera, Crustacea and Protozoa. Crustacean was the dominant group followed by Protozoa and Rotifera. Zooplankton ostacoda showed the dominance like stenocypris, throughout the investigation. Therefore, they can be significantly applied as indicators of organic pollution. It can be concluded that rushing flood or rainy water with fertilizers and insecticides going in to kotdam to polluted and rapidly turning towards eutrophication in future. So our findings highlighted the deterioration of water quality of the kotdam due to urbanization and human activities. The study recommended avoiding as far as possible the discharge of untreated sewage and other pollutants into the water.

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Zooplankton, kotdam, jhunjhunu, fertilizers, Eutrophication.

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Women's Rights: A Key Element of Fairness, Justice, and Human Progress

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Women's Rights: A Key Element of Fairness, Justice, and Human Progress

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This paper presents a physics-based 3D humanoid locomotion system trained entirely via reinforcement learning using Proximal Policy Optimization (PPO) within the Unity ML-Agents framework. A multi-joint humanoid agent learns stable, goal-directed bipedal walking using proprioceptive observations including joint angles, angular velocities, body orientation, and binary foot-ground contact signals, without any hand-crafted controllers or motion capture data. The continuous action space drives 35 joint torques through PD control with joint limit constraints. A multi-term reward function promotes forward progress, upright posture, and contact discipline while penalizing falls and degenerate behaviors. Training employed 25 parallel agents over 2.8 million timesteps, completing in 1.23 hours. The final policy (ragdoll_smooth_v2) achieved a cumulative reward of +845.38, compared to approximately -12,000 at initialization, demonstrating significant policy improvement. The trained policy is exported as an ONNX model enabling real-time inference deployment. TensorBoard metrics including cumulative reward, episode length, policy loss, value loss, and curiosity loss confirm stable convergence and consistent gait emergence throughout training.

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 Keywords

Reinforcement Learning; Proximal Policy Optimization; Humanoid Locomotion; Unity ML-Agents.

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The Career Guidance and Skill Mapping Platform is a web-based application designed to help students and job seekers identify suitable career paths based on their skills, interests, and qualifications. The system analyzes user profiles, maps existing skills with industry requirements, and provides personalized career recommendations. It also suggests courses and learning resources to bridge skill gaps. The platform aims to simplify career planning and improve employability by offering data-driven guidance and skill assessment tools.

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Career Guidance, Skill Mapping, Career Recommendation System, Skill Gap Analysis, Employability Enhancement, MERN Stack, Student Career Planning, Learning Resources, Professional Development, Web-Based Platform, Skill Assessment, Career Counseling, Personalized Recommendations, Course Suggestions, Industry Requirements.

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Abstract Western Rajasthan is a globally significant repository of petrified wood, offering crucial paleontological and geological insights into the Earth's deep past. The region contains ancient fossilized forests - predominantly found in the Jaisalmer and Barmer basins - that document the climatic transitions and shifting depositional environments of the Indian subcontinent over millions of years. The petrified wood of western Rajasthan is deeply tied to the geological history of the Thar Desert and surrounding sedimentary basins. The petrified wood of western Rajasthan is deeply tied to the geological history of the Thar Desert and surrounding sedimentary basins. The fossils are preserved within the Mesozoic strata (specifically the Lathi and Jaisalmer formations) and the Cenozoic Barmer Hill Formation. The ancient trees were swept into deltaic or marine environments, rapidly buried under thick sediments, and subjected to groundwater rich in silica. Over millions of years, organic plant matter was replaced with silicate minerals like quartz via permineralization, cell by cell. Akal Wood Fossil Park (Jaisalmer): Designated as a National Geological Monument, this 21- hectare park is the most famous site for petrified wood. It houses 25 petrified tree trunks (including extinct gymnosperms) dating back to the Early Jurassic period (~180 million years ago).

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Key Words : petrified wood, Jurassic period, Palaeocene, wood-boring trace fossils, Sedimentary basins.

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OLAP is an integral part of Business Intelligence, which assists in the process of converting raw data into meaningful information by using multidimensional analysis. On the other hand, OLTP systems are designed in a normalized manner to process real-time transactions. This paper theoretically presents a technique for the conversion of OLTP data to OLAP data by using ETL processes. ER modeling is used in OLTP, whereas dimensional modeling is used in OLAP.

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Comparative Analysis and Transformation Techniques between OLTP and OLAP

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The rapid growth of artificial intelligence (AI) is having a major impact on various creative fields, including music. This study focuses on the role of artificial intelligence in music and examines in detail how it functions as a threat or an opportunity, particularly in the fields of creativity, music production and education. The research primarily follows the development of technology in the field of music, with a focus on the digitisation of traditional practices. Later, he explores the use of artificial intelligence in music composition, in production processes and in the enhancement of voice, and he focuses on how these technologies are changing the role of musicians and producers. Especially focused on AI-based tools to help you compose, mix, master and personalize learning in music education. The study also identifies possible challenges associated with artificial intelligence, including concerns about originality, ethical implications and the potential replacement of human musicians. It also highlights the opportunities that AI creates, such as increased accessibility, efficiency and innovation in music creation and teaching. Through a balanced analysis, this research seeks to understand the evolving relationship between human creativity and machine intelligence. The findings suggest that, while artificial intelligence introduces some risks, it is largely acting as a supporting tool to enhance human potential rather than replacing it. The study concludes by emphassising the importance of adapting to technological progress while preserving the essence of human creativity in music through ethical instruments and practices in music, production and education.

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Artificial intelligence, Machine learning, data Analysis, Music technology, Music production

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Railway tracks form the backbone of modern transportation systems, enabling safe and efficient movement of passengers and goods across long distances. However, track cracks, structural defects, and unexpected obstacles such as animals can lead to serious accidents, derailments, and operational disruptions. This paper presents an Embedded IoT Framework for Real-Time Railway Track Integrity Assessment and Obstacle Detection using Arduino Nano. The proposed system integrates an IR sensor for crack detection, an ultrasonic sensor for obstacle identification, a NEO-6M GPS module for location tracking, and an ESP8266 Wi-Fi module for real-time data transmission. The system is mounted on a movable platform driven by BO motors and controlled through an L293D motor driver to perform continuous inspection of railway tracks. Upon detection of a crack or obstacle, an alert is generated through a buzzer, while location details are transmitted to the Blynk application for remote monitoring. The developed framework reduces dependency on manual inspection, improves detection accuracy, enhances operational efficiency, and contributes to safer railway transportation through continuous automated track surveillance and timely fault reporting.

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Railway Track Monitoring, Crack Detection, Obstacle Detection, Arduino Nano, IoT, ESP8266, GPS Tracking, Ultrasonic Sensor, IR Sensor, Blynk Application, Railway Safety, Embedded Systems.

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The 21st century's technological boom has paradoxically fueled lifestyle disorders like dyslipidemia--a major cardiovascular risk factor characterized by abnormal blood lipid levels. Ayurveda, India's ancient health science, views health as complete well-being beyond mere absence of disease. Classical texts describe Shonita Abhishyanda--excess Kapha and Medodhatu in Rasa-Rakta--as a Santarpanajanya Vyadhi matching dyslipidemia's clinical profile. Arising from Virudhahara and over-nourishment, Shonita Abhishyanda causes Srotorodha and progresses to Sthaulya, Hridshula, and Margavarana complications, paralleling hyperlipidemia's atherosclerotic sequelae. This review correlates their etiology, pathophysiology, and clinical features, offering an integrative Ayurvedic framework for early detection and holistic lipid disorder management.

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Dyslipidemia, Shonita Abhishyanda, Lipid, Virudhaahara, Santarpanjanya vyadhi.

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The automotive B-pillar is one of the most critical structural members in a vehicle body, playing a significant role in occupant protection during side-impact collisions. The present work focuses on the crashworthiness analysis and optimization of an automotive B-pillar using finite element analysis techniques. A detailed B-pillar model was developed and meshed using HyperMesh, while impact simulations were performed using LS-DYNA under dynamic loading conditions. Initially, a baseline B-pillar model was analyzed to evaluate its structural response in terms of displacement, stress, strain, and energy absorption. To improve crash performance and reduce structural weight, a systematic optimization approach was adopted. The study involved material substitution using steel DP1000 steel, aluminium alloy, and carbon fiber reinforced polymer (CFRP), followed by thickness reduction and slot introduction in low-stress regions. Further design modifications were implemented to enhance stiffness and control deformation. The study highlights the effectiveness of finite element analysis as a cost-effective tool for evaluating and optimizing automotive safety components. The findings provide valuable insights for the development of lightweight and high-performance B-pillar structures capable of meeting modern vehicle safety requirements.

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B-Pillar , side impact, CAE, FEA , Vehicle

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Abstract The study explicates the financial security of rural women by providing guaranteed wage employment and promoting economic independence. The study focusing on the role of the MGNREGA on the financial security of the rural women, focusing on income generation, household expenditure, savings and decision-making power. The findings highlight the participation helps them to increased income stability, improvement in their basic necessities and strengthened women's economic empowerment by increasing their involvement in household financial decision.

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Keywords: MGNREGA, financial stability, savings, decision-making, bargaining power.

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International labor migration has become a defining feature of Nepal's development trajectory, generating substantial remittance inflows that contribute significantly to household livelihoods and the national economy. However, the extent to which remittance-led development translates into sustainable improvements in household well-being remains contested. This study examines the socioeconomic impacts of labor migration on migrant families left behind in Nepal, with particular attention to household vulnerability and institutional responses. Using a convergent parallel mixed-methods design, the research combines quantitative survey data from 400 migrant households with qualitative evidence from six Focus Group Discussions and 18 Key Informant Interviews conducted across Rupandehi, Palpa, and Myagdi districts. The findings demonstrate that while remittances enhance household income, improve access to education and healthcare, and support daily consumption, their developmental potential is constrained by persistent debt burdens, limited productive investment, and continued dependence on overseas employment. The study further reveals that left-behind women experience increased responsibilities in household management, agriculture, and caregiving, often without corresponding gains in decision-making authority. Children and elderly family members face varying degrees of emotional, educational, and care-related challenges associated with prolonged family separation. At the institutional level, local governments possess important mandates to support migrant households, yet their responses remain limited due to resource constraints, competing development priorities, and weak integration of migration concerns into local planning processes. The study argues that remittance-led development alone cannot address the multidimensional vulnerabilities experienced by migrant families. Strengthening institutional capacity, expanding local social protection mechanisms, and promoting productive use of remittances are essential for transforming migration into a more inclusive and sustainable development pathway in Nepal.

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 Keywords

Labor migration; Remittances; Household vulnerability; Institutional capacity; Migration governance; Social reproduction; Gender inequality; Left-behind families; Nepal; Transnational migration; Reintegration; Debt-induced migration

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The interactive linguistic approach is an educational methodology that emphasizes learner-centered, communicative, and interactive language learning. It focuses on authentic communication, collaboration, and learner engagement to develop linguistic skills. Major objective of the study is to find out the effectiveness Interactive Linguistic Approach based instructional package in English on reading comprehension of upper primary school students. Experimental method was adopted for the study. Two group pretest post-test nonequivalent experimental design is used. This study was executed on a sample of 80 upper primary school students. Simple random sampling technique is used for the study. 40 students were selected as experimental group and 40 students were selected as control group. The experimental group was exposed to Interactive Linguistic Approach based instruction while the control group was exposed to activity-oriented instruction. This study concluded that the interactive linguistic approach based instruction is better than activity-oriented instruction for enhancing reading comprehension of students at upper primary level.

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Interactive Linguistic Approach, Reading Comprehension

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Human activity understanding has become a critical area of research due to its wide-ranging applications in healthcare, human-computer interaction, surveillance, and affective computing. This paper presents a comprehensive review of recent advancements in human movement analysis, gesture recognition, and emotion detection, focusing on both vision-based and sensor-based methodologies. Various data acquisition techniques--such as RGB-D cameras, inertial sensors, electromyography (EMG), and electroencephalography (EEG)--are examined in relation to their role in capturing motion and emotional states. Additionally, we explore classical machine learning and deep learning frameworks employed for feature extraction and classification in each domain. The paper provides a comparative analysis of current approaches, identifies key challenges such as inter-subject variability, real-time processing, and multi-modal data fusion, and outlines future research directions aimed at developing robust and adaptive systems.

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Gesture Recognition, Emotion Detection, Machine Learning, Deep Learning

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Farmers often rely on intermediaries to sell their produce, which reduces their profits and limits their access to larger markets. A web-based digital marketplace enables direct interaction between farmers and buyers, ensuring fair pricing, greater market reach, and transparent transactions. The platform streamlines agricultural trade, reduces supply chain inefficiencies, and helps farmers increase their income while providing buyers with fresh produce at competitive prices. The Farm Management System is a web-based platform designed to digitize and streamline the process of managing farmer information and agricultural products. The system allows users to register, log in securely, and perform key operations such as adding, viewing, editing, and deleting farmer records. Additionally, users can manage agro products by uploading details such as product name, description, and price. The application ensures secure access through an authentication module and maintains transparency with a trigger logging system that records significant actions within the platform. The backend is powered by a MySQL database, integrated through SQLAlchemy ORM in Flask, which handles data storage for users, farmers, farming types, products, and system logs. The use of Flask as the web framework ensures a lightweight, modular, and scalable architecture. The system provides a responsive web interface for ease of use and supports administrative tasks with functionality to manage different farming types and monitor user activity. This system is particularly beneficial in agricultural sectors for maintaining organized and accessible digital records, promoting efficiency, and reducing manual workload. It serves as a foundational tool for smart farming practices and can be expanded in the future with analytics, mobile access, and AI-based crop recommendations.

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MySQL, SQLAlchemy ORM, Farm Management System, AI-based crop recommendations

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