Volume 13 | Issue 4 |

 Abstract

Diabetic retinopathy (DR) is a leading cause of preventable blindness, necessitating accurate and early diagnosis. This paper presents EfficientViT, a novel deep learning framework that combines EfficientNetV2's local feature extraction with a Vision Transformer (ViT) for global context modeling to improve DR grading on the APTOS 2019 dataset. Our hybrid architecture leverages cross-attention fusion to integrate CNN and transformer features, while contrastive pretraining enhances performance with limited labeled data. The model achieves 97.9% accuracy (with test-time augmentation) and a 0.990 AUC, outperforming ResNet50 (94.5%) and DenseNet121 (95.8%). To ensure clinical interpretability, we introduce attention-guided Grad-CAM++, generating heatmaps with a 63% IoU overlap against clinician annotations--a 12% improvement over standard Grad-CAM. Comprehensive evaluations reveal robust performance across all DR severity grades, with 96% sensitivity for proliferative DR (Grade 4). This research introduces several key innovations to enhance diabetic retinopathy (DR) screening, including a hybrid CNN-Transformer architecture that combines EfficientNetV2 and Vision Transformer (ViT) with attention fusion for optimized feature learning, achieving state-of-the-art 97.9% accuracy on the APTOS 2019 dataset. The framework incorporates self-supervised contrastive pretraining to reduce labeled data requirements by 40%, addressing annotation bottlenecks in medical imaging. Notably, the system generates explainable AI outputs through lesion-localizing heatmaps that align with clinician markings, bridging the critical gap between algorithmic performance and clinical trust. Together, these advances--spanning novel model design, data-efficient training, and interpretable outputs--deliver a clinically viable solution that balances high diagnostic accuracy with real-world deployability for DR screening programs.

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 Keywords

Diabetic Retinopathy, Deep Learning, EfficientNetV2, Vision Transformer, Explainable AI, Medical Imaging.

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The formation of Jharkhand in 2000, carved out from Bihar, marked a significant milestone rooted in decades of socio-political aspirations for autonomy, development, and recognition of indigenous identity. This study, titled "From Aspirations to Realities: Tracing the Journey of Jharkhand's Political Landscape and Governance Challenges," aims to critically examine the trajectory of the state's political evolution and governance dynamics since its inception. It explores how the early aspirations for socio-economic development, cultural preservation, and effective governance have been addressed or undermined by the interplay of political leadership, administrative policies, and grassroots mobilization. By analysing the shifts in political paradigms, governance frameworks, and the resultant socio-economic outcomes, this research seeks to highlight persistent challenges and achievements within Jharkhand's political fabric. Furthermore, it delves into issues of corruption, regional disparities, tribal rights, and policy implementation that have continuously shaped the state's governance landscape. Through a comprehensive review of policy documents, electoral trends, and qualitative interviews, the study provides nuanced insights into how Jharkhand's journey from aspirations to realities reflects broader struggles for effective governance and inclusive development.

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 Keywords

Tribal, Land, Development, Governance, Political, Rights

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The management of biomedical waste (BMW) has grown to be a major concern for healthcare practitioners due to the increased risk of infection and harm. Handling medical waste improperly can have detrimental effects on one's health. The hospital personnel in every healthcare setting urgently need to be made more aware of BMWM. It is not only legally required but also socially responsible to handle biological waste effectively. Assessing staff nurses' knowledge of biomedical waste management and determining the relationship between chosen demographic characteristics and staff nurses' degree of knowledge about BMW management were the goals. The nursing staff members who interact with BMW were the participants in a descriptive cross-sectional study. A semi-structured survey was used to gather the data. Findings reveal that 20% of staff nurses had inadequate knowledge, whereas 50% had high knowledge. Knowledge of qualified biomedical waste management and the length of their clinical practice were shown to be significantly correlated (p<0.05). Results show that twenty percent of staff nurses lacked expertise, whereas fifty percent had strong knowledge. Knowledge of qualified biomedical waste management and the duration of their clinical practice were shown to be significantly correlated (p < 0.05). Conclusions: Because staff nurses handle biomedical waste directly, they should receive regular training and supervision are essential for better healthcare waste management and implementation.

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Biomedical waste, Hospital, Knowledge, Staff nurses

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The paper explores the historical evolution of Bhutan as a buffer state between India and China, tracing its transformation from the colonial era to contemporary geopolitical dynamics. The analysis begins with British colonial interventions in the Eastern Himalayan region, particularly focusing on the 1772 skirmish, the Treaty of Sinchula (1865), and the Treaty of Punakha (1910), which established Bhutan's early dependence on and alignment with British India. These colonial-era policies and treaties not only redefined Bhutan's territorial and diplomatic orientation but also initiated its role as a strategic buffer zone. The post-colonial phase, including the 1949 Indo-Bhutan Treaty and the rise of Communist China, further entrenched Bhutan's buffer status. Events such as the 1959 Tibetan Uprising and the 1962 Sino-Indian War intensified India's strategic interest in Bhutan. More recently, the 2007 Indo-Bhutan treaty revision and the 2017 Doklam standoff have reinforced Bhutan's geopolitical relevance. The hypothesis guiding this study is: Colonial-era interventions laid the foundation for Bhutan's evolution as a buffer state between India and China. Using a qualitative, descriptive approach rooted in postcolonial theory, the paper uses manual content analysis to highlight how colonial legacies continue to influence Bhutan's foreign policy and regional positioning.

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 Keywords

British Colonialism, Postcolonial theory, Bhutan, Buffer state, Colonial legacy

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The main aspect is to introduced and study some new class of function called Nano generalized semi Continuous function (briefly gscf) and Nano generalized semi Irresolute function(briefly gsif) Also, introduce and study about Nanosemi-interior , Nanosemi-closure and Nano generalized semi Continuous and Irresolute. And also to investigate some properties of these sets and to study some properties, remarks related to these sets.

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Ngeneralized semi closed sets, Ngeneralized semi Continuous function, Ngeneralized semi Irresolute function.

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Morphometry is a statistical and mathematical study of the Earth's surface that examines the dimension, form, and composition of landscapes. For this investigation, the Venna River basin has been chosen. This river has 60 km length with 125 sq. Km. Catchment area. It's provide the water for near about 30 villages. For the present study, 30-meter resolution SRTM remote sensing data were obtained from the USGS website and processed using ERDAS Imagine and ArcGIS software. The generated DEM, map of slope, and drainage map were applied for the morphometric study of the river Venna Watershed.

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 Keywords

Catchment, Morphometric SRTM, USGS.

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This study examines the social well-being among college students. The aim of the study was (i) To find the level of social well-being and its dimensions, such as social acceptance, social responsibility, social coherence and social support among college students and (ii) To find out the significant difference between college students in their social well-being and its dimension with respect to gender, type of family, social group member, type of family, locality, subject and mobile usage. A survey method was used for the study. A simple random sampling technique was used for selecting 107 college students from Thoothukudi, Tamilnadu. Descriptive and inferential statistical techniques were used for analyzing data. The level of social acceptance among college students was found to be moderate. The level of social responsibility, social coherence, social support and social well-being among college students is low, and there is no significant difference between college students in their social well-being and its dimensions with respect to gender, degree, type of family, locality of residence, social group member, subject and mobile usage per day.

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 Keywords

Social well-being, college students, social acceptance, social responsibility, social coherence and social support

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract For the purpose of designing cities that are able to effectively respond to climate change and rapid urbanization, urban-scale environmental performance evaluations are necessary. High-resolution, multi-scale, and temporal assessments of multiple interrelated environmental criteria are made possible by RS technologies. Despite its growing adoption in urban sustainability, a comprehensive review of RS's role in multi-criteria decision-making is still lacking. This review analyzes 124 research articles to explore RS applications in spatio-temporal analysis, impact evaluation, mitigation strategy assessment, and predictive modeling across five interconnected environmental criteria: urban air quality, urban heat, outdoor thermal comfort, building energy consumption, and solar potential. RS facilitates the integration of morphological, thermal, and meteorological data, enabling the evaluation of urban interdependence, such as the influence of urban form on air pollution dispersion, heat retention, and energy demand. Machine learning and AI-enhanced models improve air quality predictions, urban heat mitigation strategies, energy forecasting, and solar potential assessments. Real-time urban climate monitoring at finer spatial scales is further enhanced by UAVs, LiDAR, and nanosatellite technologies, facilitating dynamic planning interventions. Advances in AI-driven downscaling, digital twins, and nano satellite networks continue to expand RS capabilities despite difficulties with data resolution, temporal coverage, and real-time monitoring. RS gives urban planners and policymakers the tools they need to create climate-adaptive, energy-efficient, and resilient cities by making it easier to make decisions based on multiple factors.

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Keywords :Remote sensing ,Environment ,Air quality ,Urban heat ,Outdoor thermal comfort ,Building energy ,Solar photovoltaic

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Abstract: The global community is currently grappling with the challenges of environmental degradation and pollution, primarily driven by the excessive exploitation of natural resources by humanity in pursuit of unplanned development through rapid scientific and industrial advancements. It is imperative that we now implement measures for environmental restoration alongside conservation efforts, facilitated by effective environmental education to ensure a sustainable future for society. India possesses significant potential to offer the essential environmental educational framework required globally, owing to its rich natural resources. The Indian education system is undergoing transformation through the introduction of the new National Education Policy, which aims to tackle prevalent environmental issues and their solutions from early childhood education through to postgraduate and research levels. This paper reviews the current status of environmental education, highlighting its key components and challenges, while also evaluating its alignment with the newly adopted education policy.

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Key words: New Education Policy, Environmental Science, Environmental Education, Future challenges.

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This prospective analysis investigates the impact of such work schedules on the stress levels and overall work-life quality of Tamil Nadu State Transport Corporation (TNSTC) employees, focusing on the Kumbakonam region. The transport plays a vital role in the development of our country. Its main objective is to connect the urban and rural areas. Most of the students and office goers are using the buses. India's passenger transport for small and medium distances is bus oriented and many other transport industries the safety of travelers and other road users is of prime importance. The main objective of this paper is identified and analysis the factors influencing job stress among the transport employees. A multiple linear regression model demonstrates that irregular work schedules significantly decrease the quality of work life among TNSTC employees. These findings emphasize the need for organizational strategies and support systems tailored to mitigate the stressors associated with different shifts, enhance employee well-being, and improve public transportation services in the Kumbakonam region.

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 Keywords

Shift work, irregular schedules, stress, work-life quality, employee well-being, public service, occupational health.

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Creative Commons Attribution 4.0 and The Open Definition