Volume 13 | Issue 9 |

 Abstract

ABSTRACT Urban and semi-urban academic campuses serve as crucial green refuges for avian populations, especially in arid regions like the Thar Desert. This study presents the first systematic assessment of the avian diversity at the G.H.S. Government College campus in Sujangarh, Rajasthan. Conducted over a period from September 2024 to April 2025, the research aimed to document the species composition, their seasonal variation, and conservation status. Using the line transect method and systematic observation points, a total of 49 bird species across 30 families were recorded. The assemblage was dominated by resident species along with few summer and winter visitors also reported, reflecting the campus resource availability. The presence of species like Cattle egret (Ardea coromanda) and the Indian Peafowl (Pavo cristatus) underscores the campus ecological value. However, species of conservation concern, such as the Egyptian Vulture (Neophron percnopterus; Endangered), were also observed utilizing the area as a flyover zone. This study concludes that the college campus, with its mosaic of gardens, scattered trees, and built-up areas, functions as a vital micro-habitat for local avifauna. The findings highlight the importance of urban biodiversity conservation and recommend specific green management practices to enhance the campus's value for wildlife.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Avian diversity, Urban ecology, College campus, Sujangarh, Thar Desert, Micro-habitat, Conservation, Green refuge, Resident birds, Line transect.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Folk deities serve as the custodians of indigenous faith, embodying the spiritual consciousness of rural communities and weaving together the intricate tapestry of cultural heritage. Among such revered deities, Sri Sri Maa Shitala occupies a place of profound significance in Bengal's religious landscape, venerated as the divine protectress against epidemics and a harbinger of health and well-being. This paper delves into the rich cultural and historical dimensions of the Sri Sri Maa Shitala Puja in Rangamatia village, nestled in the Bamangola block of Malda district, West Bengal. Established in 1965 by the esteemed Biswas family, this sacred tradition has transcended its humble origins, evolving into a grand spectacle of collective devotion, drawing thousands of fervent worshippers each year. Rooted in oral tradition and mythological reverence, the puja is an embodiment of the interplay between faith and traditional medical beliefs. Maa Shitala, often depicted seated on a donkey and carrying a broom, neem leaves, and a pot of cooling water, symbolizes both disease and its cure, reinforcing the age-old understanding of balance and purification. The rituals associated with her worship, including the practice of Arandhan (a day of complete abstinence from cooking), the offering of Sinni prasad, and the communal observances, reflect the deep-seated folk wisdom that intertwines spirituality with public health practices. Beyond its religious essence, this annual observance has undergone a profound sociological transformation, shifting from a localized village ritual to an expansive congregation of faith that parallels major Hindu festivals. The research explores how this enduring tradition continues to thrive, fostering intergenerational participation, reinforcing social unity, and preserving Bengal's rich folk heritage amidst the tides of modernization. Through an interdisciplinary lens, this study seeks to illuminate the enduring legacy, ritualistic nuances, and societal impact of this 65-year-old sacred tradition, underscoring its pivotal role in shaping communal identity and spiritual resilience.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Shitala Puja, Folk Deity, Traditional Medical Beliefs, Arandhan Ritual, Sinni Prasad, Socio-Religious Transformation, Mass Participation.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Eco-epidemiological models are critical for understanding the intricate interplay between ecological and epidemiological processes in ecosystems. This study focuses on a prey-predator model that includes a prey species and the susceptible-exposed-infected-recovered (SEIR) epidemiological framework. Integrating these processes provides insight into how disease transmission affects population stability and predator-prey communications. We use mathematical and computational tools to analyze the model and find important thresholds and conditions that result in diverse environmental and epidemiological effects. Our findings emphasize the relevance of disease control and ecological conservation techniques in preserving ecosystem equilibrium

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Eco-epidemiological model, predator-prey dynamics, SEIR (Susceptible-Exposed-Infected-Recovered) model, disease spreading, population stability, mathematical modeling. Epidemiologic thresholds, Environmental protection, Lyapunov function

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Climate Resilient Agriculture

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT: In the modern world e-commerce is emerging as a biggest player and is contributing towards growth and development of the economy. The rapid expansion of e-commerce has significantly transformed the global retail landscape, leading to a notable decline in traditional brick-and-mortar retail formats. This study aims to explore how the rise of e-commerce has significantly influenced traditional retail by analysing consumer trends and traditional retailers' experiences. It also examines the challenges faced by traditional retailers in adapting to digital disruption and the strategies some have adopted to remain competitive. It will provide insights into the future of retail, emphasizing the growing importance of hybrid business models, digital transformation, and customer-centric approaches. This study contributes to a deeper understanding of the ongoing shift in the retail sector and its implications for businesses, consumers, and policymakers.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: E-commerce, Physical stores, Retail and Digital Age.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

LoRa (Long Range) technology has emerged as a highly efficient low-power wireless communication standard capable of supporting long-distance data transmission, making it suitable for defense and critical monitoring applications. In modern military operations, continuous health monitoring and accurate geolocation of soldiers are essential to ensure safety and enhance mission outcomes. This study presents a low-power LoRa-based soldier safety mechanism that integrates biomedical sensors with GPS tracking for real-time data acquisition and transmission. The system utilizes sensors to measure vital health parameters such as heart rate, pulse rate, and body temperature, while GPS provides precise geolocation data. All collected information is processed by a microcontroller and transmitted through a LoRa transceiver to a base station for continuous monitoring. In emergency situations, anomalies in health readings or the activation of a panic button generate immediate alerts, enabling faster medical response and tactical decision-making. The proposed design demonstrates a reliable, cost-effective solution to safeguard soldier lives and optimize battlefield strategies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

LoRa, IoT, Soldier Safety, GPS Tracking, Health Monitoring, Wireless Communication, Panic Button, Low-Power System.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Construction worker safety relies critically on proper Personal Protective Equipment (PPE) usage, yet current automated detection systems exhibit significant limitations including environmental sensitivity, computational complexity, and restricted detection scope. This research presents an innovative framework enhancing the established Faster-PPENet through six core technological innovations: advanced attention mechanisms, vision-language contextual reasoning, adaptive multi-sensor fusion, edge optimization techniques, few-shot learning capabilities, and synthetic data augmentation approaches. proposed system systematically addresses fundamental challenges in existing PPE detection systems by implementing coordinate attention mechanisms for improved feature discrimination, integrating large language models for intelligent safety compliance interpretation, developing adaptive sensor fusion enabling all-weather operation, optimizing architectures for edge deployment, facilitating rapid adaptation through meta-learning, and enhancing training robustness through synthetic data generation. Experimental validation demonstrates substantial improvements over baseline systems: 10.7% increase in mean Average Precision (mAP) on the CHV dataset (from 0.8655 to 0.9570), 68% reduction in computational overhead enabling real-time edge deployment, expansion from 4 to 17 detectable PPE categories, 93.1% accuracy maintained across diverse construction environments, and 74% cost reduction compared to manual monitoring approaches.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Construction safety, PPE detection, attention mechanisms, vision-language models, edge computing, multi-modal fusion, synthetic data augmentation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Jeevika initiatives, implemented under the Bihar Rural Livelihoods Promotion Society, has emerged as a transformative model for rural development by leveraging the collective strength of Self-Help Groups (SHGs). These women-led SHGs function as grassroots institutions that drive socio-economic change through financial inclusion, livelihood diversification and social empowerment. This paper explores the pivotal role played by SHGs under Jeevika in enhancing households income ,promoting entrepreneurship and fostering socio-economic resilience among marginalized communities. Based on the Jeevika Annual report 2017-22, this study conducts a comparative analysis of three key livelihood interventions i.e. farm intervention, livestock intervention and non-farm intervention through SHGs under the Jeevika initiative in Bihar livelihood promotion. The study finds that while all three interventions have unique strengths, livestock and non-farm intervention offer quicker income turnaround, where farm-based intervention ensure long term food and income stability. Integrating all three through community institutions like SHGs leads to a more resilient, inclusive, and sustainable rural livelihood ecosystem.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Jeevika, (SHGs), Livelihood Interventions, Sustainable Rural Livelihoods

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The integration of artificial intelligence (AI) into medical imaging has opened new frontiers for accurate, efficient, and scalable brain tumor diagnostics. This study evaluates and compares the performance of Logistic Regression (LR), Random Forest (RF), and Artificial Neural Networks (ANN) in differentiating glioblastoma multiforme (GBM), lymphoma, and metastases using radiomics features derived exclusively from contrast-enhanced T1-weighted MRI scans. A retrospective cohort of 85 patients (62 GBM, 23 lymphoma) was analyzed, with radiomic features extracted via the IBSI-compliant PyRadiomics framework following manual segmentation. To address natural class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied, creating balanced datasets for robust evaluation. Models were trained and validated using stratified 10-fold cross-validation, with performance measured by accuracy, sensitivity, specificity, and area under the ROC curve (AUC). Results demonstrated that ANN consistently outperformed classical methods, achieving 79% accuracy (AUC 0.83) on the original dataset and 87% accuracy (AUC 0.90) on the balanced dataset, compared with RF (74% and 84.5%) and LR (42% and 63%). In multiclass classification, ANN achieved an overall accuracy of 79.4% with a macro-AUC of 0.887, effectively distinguishing GBM, lymphoma, and metastases. These findings confirm the superiority of deep learning in handling complex, high-dimensional imaging data, particularly when supported by preprocessing and data balancing strategies. By demonstrating the strengths and limitations of different approaches, this study highlights the potential of AI-driven radiomics to enhance diagnostic reliability, reduce variability, and improve patient triage in neuro-oncology.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence (AI), Brain Tumor Classification, Radiomics, Magnetic, Resonance Imaging (MRI) and Deep Learning

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Meitei Pangal Community is one of the major ethnic groups while Meitei being the largest community inhabiting in the Manipur valley. They comprise of 8.40 percent of the total population of the state and majority Meitei community representing about 53 percent. They have been playing major roles in the socio-economic development of Manipuri society thereby earning a unique position for them. Meitei Pangal began to settle in 1606 A.D in Manipur during the time of King Khagemba (1597- 1652) as recorded in Cheitharol Kumbaba, the Royal Chronicles of Manipur. They assimilated into Meitei society by marrying Meitei women. Meiteilon (Meitei Language) is adopted as their mother tongue. They practice the Meitei way of living and culture though they profess Islam religion and strictly following the Islamic code of conduct and the Islamic Sariyat (Law). The main objective is to study on the customary rituals and practices of birth amongst Meitei Pangal. Descriptive and explorative research methods will be employed. The present study is based on field work, open ended interviews of Moulavis and other Islamic Scholars. Royal Chronicles (Cheitharol Kumpaba and Ningthourol Lampuba), Puyas (archaic manuscripts), foreigners accounts, books, newspapers, magazines are taken as literary sources.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ritual Practices, Customs, Birth Ceremony, Meitei Pangal

  License

Creative Commons Attribution 4.0 and The Open Definition