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Research Paper

Tribal Health in India: Status, Challenges, and Strategies for Strengthening Healthcare Delivery

Tribal health remains one of the most neglected domains within the Indian public health system despite constitutional safeguards and multiple targeted programmes. Scheduled Tribes (STs), constituting approximately 8.6% of India’s population, continue to experience disproportionately high morbidity and mortality due to a complex interaction of socio-economic deprivation, geographical isolation, cultural barriers, and systemic inadequacies in healthcare delivery. Historical marginalisation, poverty, low literacy levels, and poor living conditions have collectively contributed to persistent health inequities among tribal communities. Conventional healthcare models, which largely follow a uniform national approach, have failed to adequately address the unique cultural, social, and environmental contexts of tribal populations, resulting in limited utilisation of health services and delayed care-seeking behaviour. This paper presents a detailed narrative analysis of the health status of tribal populations in India, drawing upon secondary data from national surveys, census reports, and published literature. The study examines key indicators related to maternal and child health, nutritional status, communicable and non-communicable diseases, and healthcare utilisation patterns among tribal communities. It further explores systemic barriers such as inadequate infrastructure, workforce shortages, accessibility issues, financial constraints, and discrimination within healthcare settings. By reviewing existing policy frameworks and community-based models, the paper proposes context-specific and culturally sensitive strategies to strengthen primary healthcare delivery in tribal areas. The findings emphasise the need for integrated, participatory, and rights-based approaches to reduce health disparities and improve overall health outcomes among tribal populations.

Published by: Aadya Gaur

Author: Aadya Gaur

Paper ID: V12I1-1159

Paper Status: published

Published: February 13, 2026

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Review Paper

A Survey on Modern Computational Methods for Drug Repurposing

Drug repurposing, the process of identifying new therapeutic uses for existing drugs, offers a promising strategy to accelerate drug development by significantly reducing costs, time, and risks compared to de novo drug discovery. The increasing availability of large-scale biomedical data has catalysed the development of computational approaches to systematically identify and prioritise repurposing candidates. This survey reviews the state-of-the-art computational methodologies, with a particular focus on network medicine and machine learning-based techniques. We discuss key approaches such as pathway-based analysis, network proximity, matrix factorisation, and the growing application of deep learning, particularly Graph Neural Networks (GNNs), which leverage complex biomedical networks. The paper explores how these methodsutilisee heterogeneous data—including drug-target interactions, gene-disease associations, and molecular structures—to generate repurposing hypotheses. Furthermore, we outline the primary challenges in the field, including data integration, model generalizability, and the need for explainability, and discuss future directions, such as the integration of multi-modal data and the development of more sophisticated, interpretable AI models.

Published by: Aditi Dipak Thorat, Shlok Shivaji Kaule, Paras Vijay Tak, Anuj Prakash Gagare, Vijayendra S. Gaikwad

Author: Aditi Dipak Thorat

Paper ID: V12I1-1157

Paper Status: published

Published: February 13, 2026

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Research Paper

Predicting Adolescent Psychological Outcomes of Therapeutic Chatbot Use by Integrating Neuroscience, Chatbot, and User Behaviour

As we find our lives more and more intertwined with Artificial Intelligence, we use it for a variety of purposes. Using an AI assistant means that many tasks previously done by us can now be outsourced. This has many implications, cognitive, sociological and emotional. Earlier research in neuroscience suggests that teenagers and young adults are more vulnerable to negative psychological impacts from external influences. A study shows an increase in cognitive decline in students who use AI for essay writing. (Kosmyna). Another preprint finding shows how AI can aid medical misinformation sometimes and enhance patient care other times. (Jedrzejczak et al.). This paper discusses the effects of AI usage for companionship or mental health-focused conversations on adolescents and youth. Drawing on neuroscience literature and understanding the reward circuitry of the brain, it assesses the potential downsides of long-term usage. Deploying a basic chatbot to engage in empathetic conversations and conducting a survey (n=90) post interaction, perceived empathy, validation and other emotional factors are assessed. Another experiment is conducted to quantitatively measure chatbot validation. This paper proposes that AI is over-validating by nature and that it fosters reliance.

Published by: Kavika Singhal

Author: Kavika Singhal

Paper ID: V12I1-1151

Paper Status: published

Published: February 5, 2026

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Research Paper

Growth of Small and Medium Enterprises in Asian Countries with Special Emphasis on India

This paper examines the growth trajectory of Small and Medium Enterprises (SMEs) across Asian countries, with an emphasis on India. SMEs constitute the backbone of economic development in Asia, contributing significantly to employment generation, poverty alleviation, and export growth, yet they face persistent structural challenges like limited access to finance and inadequate infrastructure. This paper also delves into various Government interventions and policies supporting MSMEs. It also draws a comparison of India with other Asian countries such as Indonesia, Malaysia, the Philippines, and Thailand.

Published by: Daksh Singhal

Author: Daksh Singhal

Paper ID: V12I1-1148

Paper Status: published

Published: February 5, 2026

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Research Paper

The Economic Analysis of Gender Pay Gap in Sports

This research paper examines the causes of the gender pay gap in the sports industry. It looks at the many factors affecting the wages of female athletes by highlighting the role of sponsors, industries, labour markets and media. It also reflects the presentation of women in sports using sexual connotations, the limited opportunities and reduced investment they receive, which restricts their skill development and therefore the wages they earn. This research paper emphasises how earnings are not due to lack of performance or athletic abilities, but due to institutional inequalities present in sports industries consisting of women, thus they are not a true reflection of the performance of female athletes.

Published by: Advika Rao

Author: Advika Rao

Paper ID: V12I1-1147

Paper Status: published

Published: February 5, 2026

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Research Paper

Empirical Atmospheric Attenuation Models for Free Space Optical Links using Nigerian Meteorological Data

Accurate prediction of atmospheric attenuation is critical for the reliable deployment of Free Space Optical (FSO) communication systems, particularly in regions with diverse climatic conditions. This paper presents a comparative validation of three widely used empirical attenuation models—Kruse, Kim, and Al Naboulsi—using real meteorological visibility data from Nigeria. Visibility records obtained from the Nigerian Meteorological Agency (NiMet) for Lagos, Port Harcourt, Abuja, Jos, and Kano were used to compute attenuation coefficients at an operating wavelength of 1550 nm. Simulation results were compared with attenuation values derived from measured visibility data using correlation and root mean square error (RMSE) metrics. Results show that the Kim model provides the highest correlation (0.93) and lowest RMSE (2.7 dB/km), demonstrating superior suitability for tropical atmospheric conditions. The findings offer validated guidelines for selecting appropriate attenuation models for FSO-based 5G backhaul and last-mile deployments in Nigeria.

Published by: Tunde Afolabi, Dr. R. O. Okeke

Author: Tunde Afolabi

Paper ID: V12I1-1137

Paper Status: published

Published: January 23, 2026

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