Volume 14 | Issue 2 |

 Abstract

An important factor in a nation's socioeconomic progress is its healthcare system. By lowering the burden of sickness and boosting productivity, access to high-quality healthcare services not only improves people's quality of life but also makes a substantial contribution to economic growth 1. Achieving universal health coverage (UHC) has proven to be a recurring challenge in a nation as diverse and populated as India 2.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Implementation and Utilization of Ayushman Bharat in Villages of Faridkot district

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Workforce Task Automation is a technology-driven system designed to automate repetitive tasks such as task assignment, status updates, progress tracking, and reporting. It addresses the limitations of manual workforce management, including delays, human errors, and lack of real-time visibility. By integrating intelligent scheduling, automated notifications, role-based access, and centralized data management, the system enhances productivity, accuracy, and workflow efficiency while reducing operational overhead and manual dependency.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Workforce Automation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract The global apparel industry has been growing rapidly, and consumers are purchasing and discarding garments more frequently due to low-cost "fast fashion." As a result, more used clothing is being discarded, harming the environment and creating problems for individuals and communities. Although recycling used clothing helps reduce these negative effects and make fashion more sustainable, many garments remain challenging to recycle effectively due to practical and technological barriers. Additionally, many garments are never recycled because there are enough effective procedures in place to collect, sort, and process used textile material. These systems are also very expensive to operate and lack the buildings or equipment required to manage all the waste. Many people lack basic knowledge about how to properly recycle, and government support for recycling is often weak. Improving textile recycling in various areas is made more difficult by these policy gaps. Even though recycling clothing is hard, there are a number of innovative ideas that could improve and simplify the process. The development of new devices and systems that can automatically sort and decompose used clothing into useful materials. Some technologies convert into new ones using chemical or enzymes, while others use computers and intelligent robots to separate different types of fabric faster and more accurately. Improvement of this nature raises hopes for the future recycling and repurposing of additional garment waste. Furthermore, strong economic regulation initiatives that make apparel manufacturing companies responsible for their goods can also contribute to moving fashion to a more sustainable industry. Better recycling of used clothing can be made faster by involving the cooperation and assistance of consumers, workers, the government, and brands. This review paper summarises the challenges and opportunities for recycling, providing suggestions for enhancing the recycling system and achieving long-term sustainability goals.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Garment Recycling, Textile Waste, Barriers, Opportunities, Textile Waste Components, Extended Producer Responsibilities

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Efficient water resource management is essential for sustainable urban development, particularly in rapidly growing cities where demand patterns are influenced by environmental and demographic factors. This paper presents a data-driven water demand prediction framework using Random Forest regression to forecast future water consumption. The proposed system integrates historical water usage data, environmental parameters such as rainfall and temperature, reservoir storage levels, and population growth information obtained through external APIs. The framework consists of data collection, preprocessing, feature engineering, model training, prediction, and visualization modules. Time-series features and lag-based variables are generated to capture seasonal and temporal consumption patterns. The Random Forest regression model is employed due to its ability to handle nonlinear relationships, reduce overfitting through ensemble learning, and provide feature importance insights. Experimental evaluation demonstrates improved prediction accuracy compared to traditional statistical approaches. The predicted outputs are presented through an interactive dashboard to support water distribution planning and resource allocation. The proposed system provides a scalable and adaptive solution for smart water management, enabling authorities to make data-driven decisions for efficient and sustainable water supply management.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Water Demand Forecasting, Random Forest Regression, Environmental Data Analytics, Population Growth Modeling, Data-driven Resource Allocation , Feature Engineering for Water Demand, Predictive Dashboard Visualization

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: The transition toward sustainable transportation has positioned electric vehicles (EVs) as a critical instrument for achieving environmental sustainability and reducing dependence on fossil fuels. This research article examines the role of EVs in sustainable development by analyzing opportunities, constraints, and future prospects based on primary data collected from 300 respondents across selected districts of Karnataka, including Bengaluru Urban, Mysuru, Mandya, Tumakuru, and Shivamogga. The study adopts a mixed-method approach, combining survey data with secondary sources such as government reports and policy documents. Findings reveal that environmental concern, rising fuel prices, and lower operating costs are major drivers of EV adoption, while high initial purchase cost, inadequate charging infrastructure, and range anxiety remain significant barriers. Urban districts show higher adoption levels compared to rural areas due to better infrastructure and awareness. Electric two-wheelers dominate the market owing to affordability and convenience, whereas electric cars and commercial vehicles face slower adoption. Government incentives, including tax exemptions and subsidies, have positively influenced consumer perceptions. The study concludes that EVs hold substantial potential to contribute to sustainable development by reducing greenhouse gas emissions, improving energy security, and generating green employment. However, achieving large-scale adoption requires expansion of charging infrastructure, financial incentives for rural consumers, awareness campaigns, and integration with renewable energy sources. The research offers policy recommendations for accelerating EV penetration in Karnataka and highlights future prospects for clean mobility in developing economies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Electric Vehicles, Sustainable Development, Clean Mobility, Karnataka, Environmental Sustainability, EV Adoption

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid growth of cities and the increasing demand for sustainable travel have pushed our railway networks to their limits. Traditional control systems, which rely on static timetables and manual dispatching, often struggle to adapt to real-time problems like delays or equipment failures. This leads to tracks being underused and passengers facing longer waits. This paper introduces an AI-driven framework designed to maximize track "throughput"--essentially getting more trains through a section safely and efficiently. This system uses Multi-Agent Reinforcement Learning (MARL), allowing trains to act as intelligent agents that adjust their speed, route, and priority in real-time. By using a "Curriculum Learning" strategy, that trained the AI to handle everything from normal operations to extreme weather and major disruptions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Train Traffic Control, Section Throughput, Reinforcement Learning, Multi-Agent Systems, Railway Optimization, Artificial Intelligence, Safety-Critical Systems, Deep Q-Networks.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Aurangzeb was the sixth Mughal emperor (1658-1707) and had one of the most complex and longest rules in Indian history. His administration was characterized by a strong centralized government with strict adherence to Islamic law, and military expansion/wars/conflicts. Aurangzeb sought to strengthen the imperial authority and maintain law and order over his vast empire with rich diversity. However his various policies resulted in the resistance and conflict with his people and neighbouring kingdoms. As mention previously, Aurangzeb administration was highly centralized and the emperor himself would exercise direct control over state functions, including revenue and military affairs and even judicial matters. This made him distinct from previous emperors who were not as deeply involved directly in day to day governance, personally reviewed petitions and issued orders. He emphasized efficiency, discipline, and moral accountability and thus dismissed corrupt or inefficient administrators more often than previous Mughal rulers. Aurangzeb's administration was also strongly influenced by Islamic principles and he also reinforced the use of Sharia law and also compiled a comprehensive series of Islamic jurisprudence that guided the judicial and administrative decisions during his rule called the "Fatawa-i-Alamgiri". Aurangzeb's policies however had negative effects on the empire as it became more and more divided because of the focus of Muslim laws. The re-implementation of Jizya (a tax on nonMuslims) in 1679 only added to this as this was a jump from former Mughal ruler, Akbar's policies which abolished this tax. Aurangzeb's vision of an Islamic state while legitimizing his rule alienated large sections of the non-Muslim population. Aurangzeb also retained much of the Mughal mansabdari and jagirdari system but he enforced stricter supervision. This was because he launched or wanted to launch multiple military campaigns as well as to defend and retake territory. This economic policy was effective on bringing in wealth on the short term as it strained on the populace. Many people were unhappy with the heavy taxes and Aurangzeb's military campaigns were unsuccessful on bringing on more wealth. This only highlights Aurangzeb's reign as a whole without tackling in the details as to the why and how.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Centralized administration Islamic law (Sharia) Military expansion Religious conflict Mansabdari system and Jagirdari system

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study's goal is to present an accurate and organised survey of the literature on risk tolerance. The study aims to investigate different factors which affects risk tolerance and to provide comprehensive literature review. The manuscript beings with a discussion on the risk tolerance. We explore how risk tolerance can be measured with different factors like demographic factors, Financial Literacy, Personality types and how these factors influence investors. The results showed factors like personality types, financial literacy and demographic factors is positively influence risk tolerance. The study makes a novel contribution to the strand literature of risk tolerance among investors. It highlights the substantial knowledge gaps in this field and provides a potential agenda for academicians, research organizations, and funding agencies for future research.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Risk Tolerance, Personality types, Demographic factors, Financial Literacy.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT In low- and middle-income economies, women and marginalised individuals remain excluded from formal financial services to a greater extent than their male counterparts. Digital microfinance platforms provide access to financial resources that enhance women's employment outcomes, income, and entrepreneurship opportunities. However, impacts vary across regions, sectors, and digital literacy levels. KEYWORDS Digital Microfinance, Women's Employment, Empowerment, Financial Inclusion, Policy Implications

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Microfinance, Women's Employment,Empowerment,Financial Inclusion,Policy

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Transgender individuals frequently experience social exclusion, stigma, and discrimination, which place them at elevated risk for loneliness and poor psychosocial well-being. The present study examined levels of perceived loneliness and perceived social acceptance and investigated the relationship between these constructs among transgender adults residing in Mumbai. A quantitative, cross-sectional correlational design was employed. Sixty participants (34 trans women and 26 trans men), aged 18-30 years, were recruited through community-based organizations using purposive sampling. Data were collected using the UCLA Loneliness Scale (Version 3) and the Perceived Acceptance Scale. Descriptive statistics, chi-square tests, independent samples t-tests, one-sample t-tests, and Pearson correlation analyses were performed. Results indicated high levels of perceived loneliness (M = 50.93, SD = 10.33) and moderate levels of perceived social acceptance (M = 138.97, SD = 33.15). One-sample t-tests revealed that both loneliness and social acceptance scores differed significantly from the scale midpoints (p < .001). No significant gender differences were observed in loneliness or social acceptance between trans men and trans women. A statistically significant moderate-to-strong negative correlation was found between perceived loneliness and social acceptance (r = -0.568, p < .001), indicating that higher loneliness was associated with lower social accepatance Acceptance from friends and mothers showed stronger protective associations than acceptance from fathers. The findings highlight perceived social acceptance as a crucial protective factor for the psychological well-being of transgender individuals. Interventions that strengthen family support, peer relationships, and community inclusion may play an essential role in reducing loneliness and improving mental health outcomes in this population.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Perceived loneliness, social acceptance, transgender individuals

  License

Creative Commons Attribution 4.0 and The Open Definition