Volume 13 | Issue 6

 Abstract

The increasing frequency and intensity of floods due to climate change pose a major threat to life, property, and infrastructure. "Flood Sentinel: A Smart System for Flood Forecasting and Monitoring Using Remote Sensing" is designed to address these challenges through the integration of real-time data analytics, IoT-based environmental monitoring, and remote sensing technologies. The system leverages historical flood data, meteorological patterns, precipitation levels, river discharge rates, and soil moisture to generate accurate and early flood predictions. It employs advanced predictive models along with IoT sensors and weather stations to continuously monitor environmental conditions. A robust, multi-channel alert mechanism ensures timely dissemination of flood warnings through SMS, email, and social media, enabling communities and disaster management authorities to take proactive measures. The system's intuitive interface promotes accessibility, awareness, and faster decision-making during emergencies. With its adaptability to evolving technologies and environmental datasets, Flood Sentinel serves as a scalable and sustainable model for modern flood risk management and disaster resilience planning.

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Flood Forecasting, Remote Sensing, IoT Sensors, Disaster Management, Real-Time Monitoring, Early Warning System

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Historically the word handicrafts meant products made mostly by hand and the market for such goods was limited to small, often underdeveloped, local areas. With new technologies and machines, however, that same market expanded and began to draw global attention. In India the revival of handicrafts soon became obvious; plentiful raw materials and low-cost labour underpinned much of the success. Rajasthan, famed for its culture and heritage, stood out by offering a wider range of items than most other states. Support from both central and state governments has also played a key role in nurturing this growth.

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Handicrafts, Machines, Geographical Areas, Expensive Labour, Natural Stone.

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This study explores a sound-based surveillance system designed to detect critical audio events like gunshots, glass breaking, sirens, screams, and door slams. Using real-world sound recordings from a selected dataset, the system processes and classifies these events for timely threat identification. By focusing on practical audio signal processing methods and a streamlined classification pipeline, this research offers a reliable tool for enhancing safety in urban environments through efficient sound monitoring.

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 Keywords

Sound Event Detection, Audio-based Surveillance, VGGish Embeddings, Transfer Learning, Deep Neural Network (DNN), Acoustic Scene Analysis, Environmental Sound Classification, Urban Security, High-risk Sound Events, ESC-50 Dataset, Audio Signal Processing, Public Safety Monitoring, Semantic Audio Features, Real-time Threat Detection, Intelligent Mon itoring Systems.

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 Abstract

Heat shock proteins (HSPs) are a conserved family of molecular chaperones that maintain protein homeostasis under physiological and stress conditions. In the oral environment, HSPs such as HSP27, HSP60, HSP70, and HSP90 are constitutively expressed in mucosa, salivary glands, and dental pulp, and their expression is upregulated by thermal, oxidative, or microbial stress. Beyond their canonical roles in protein folding and degradation, HSPs act as danger-associated molecular patterns (DAMPs) to modulate innate and adaptive immunity, participate in wound healing, and preserve tissue integrity. In oral pathology, aberrant HSP expression has been implicated in infections (e.g., Candida, Streptococcus), inflammatory conditions (periodontitis, peri-implantitis, pulpitis), and odontogenic lesions (keratocysts, ameloblastomas). In potentially malignant disorders such as leukoplakia and lichen planus, elevated HSP27 and HSP70 levels correlate with dysplastic severity, while in oral squamous cell carcinoma (OSCC), overexpression of HSP27, HSP70, and HSP90 promotes tumor cell survival, invasion, and chemoresistance. These findings underscore the diagnostic and prognostic potential of HSPs as biomarkers. Moreover, pharmacologic modulation of HSP activity--via HSP90 inhibitors (e.g., geldanamycin analogs), HSP70 ATPase blockers, or HSF-1 antagonists--offers novel therapeutic avenues. However, monotherapy may induce compensatory chaperone upregulation; thus, combination strategies targeting multiple HSPs or integrating conventional therapies may be required. Continued investigation into HSP localization, post-translational regulation, and interplay with oral microenvironmental cues will advance our understanding and enable translation into clinical practice.

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: Heat Shock Proteins, Oral Pathology,HSP70,HSP90 Inhibitors, Oral Squamous Cell Carcinoma, Protein Homeostasis,Molecular,Chaperones,Diagnostic Biomarkers

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 Abstract

Swami Vivekananda's life mission was to empower individuals through "Man-making education", which to him meant nurturing the complete development of a person - mind, body, and spirit. He believed education should go beyond just learning facts and passing exams, and instead help bring out the hidden potential within each learner. For Vivekananda, intellectual growth and spiritual wisdom were intertwined, and he advocated for a balance between the two. At the core of his philosophy was the beautiful synthesis of science and spirituality, which he saw as complementary, not contradictory, allowing individuals to live a more holistic, fulfilling, and purposeful life. This paper delves into the very aspect of Vivekananda's idea or the vision of Education posing an integrated rather than contradictory approach between Rationality and Spirituality. It explores how his philosophy of education seamlessly blends the coexistence of science and spirituality by addressing four fundamental questions: 'Who, Why, Where, and When.' Through an analysis of his teachings based on these principles, we will uncover how science and spirituality are not opposing forces but rather complementary elements that, together, shape individuals capable of meaningfully contributing to both society and their own personal growth.

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Man-making education, Rationality, Swami Vivekananda, Modern Education, spirituality.

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Abstract--In response to the exponential growth of digital data and increasing cyber threats, this paper proposes a comprehen- sive framework for cybersecurity and intellectual property (IP) protection in data privacy systems. The framework integrates advanced encryption techniques, blockchain-based IP verifica- tion, and machine learning-driven threat detection to safeguard sensitive data and protect IP rights. It employs a multi-layered security architecture combining homomorphic encryption, zero- knowledge proofs, and distributed ledger technology to ensure data confidentiality and IP authenticity. The framework offers scalable solutions for enterprises to handle sensitive data while complying with global privacy regulations.

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cybersecurity, intellectual property protection, data privacy, blockchain, homomorphic encryption, machine learning, threat detection

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The anatomical and functional importance of Guda (anus) has been emphasized in Ayurvedic literature, particularly in the context of Pranayatana and Sadhyapranahara Marma. This study aims to resolve the prevailing controversies surrounding the concept of Gudavalis by correlating classical Ayurvedic descriptions with modern anatomical interpretations. A multidimensional methodology was employed, including literary review, cadaveric dissection, and a clinical trial involving Mula Bandha practices. The study's findings contribute toward an integrative understanding of Ayurveda and contemporary science, particularly in anorectal disorders.

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Guda, Gudavali, Mula Bandha, Cadaveric Study, Applied Anatomy, Ayurveda Introduction

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This paper introduces various generalized closed sets in Fermatean Picture Fuzzy Topological Spaces (FPFTS), including generalized closed, generalized pre-closed, generalized semi-closed and generalized ?-closed sets. The fundamental properties, theorems and proofs are presented with numerical examples.

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Fermatean Picture Fuzzy generalized closed, Fermatean Picture Fuzzy generalized pre-closed, Fermatean Picture Fuzzy generalized semi-closed and Fermatean Picture Fuzzy generalized ?-closed sets

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Rajasthan, renowned for its vibrant traditions, majestic architecture, and timeless folk arts, has successfully leveraged its cultural heritage as a cornerstone for economic development. This paper explores how Rajasthani culture actively contributes to various sectors of the economy, including tourism, handicrafts, hospitality, rural development, and creative industries. The state's cultural richness attracts millions of tourists annually, supports thousands of artisans through handicraft exports, promotes rural livelihoods via heritage tourism, and stimulates job creation across urban and rural landscapes. Additionally, Rajasthan's festivals, folk performances, and royal hospitality traditions have positioned it as a global cultural destination. With its growing involvement in film production, luxury tourism, and international branding, Rajasthani culture has not only preserved its historical essence but also evolved into a powerful economic driver. This comprehensive analysis highlights the symbiotic relationship between cultural preservation and economic progress in Rajasthan, demonstrating how tradition, when integrated with modern enterprise, can create inclusive and sustainable growth.

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RAJASTHANI CULTURE

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This study explores the embracing and implementation of Human Resource (HR) analytics tools in the Fast-Moving Consumer Goods (FMCG) industry in Hyderabad, focusing on their impact on workforce management and organizational planning. The research examines the challenges faced by FMCG companies in integrating HR analytics into their operations and evaluates its role in enhancing employee performance, retention, and organizational efficiency. A section size of 200 respondents from diverse FMCG organizations was surveyed to assess the perceptions and experiences of HR professionals and managers. The study employs descriptive statistics, correlation, regression, and ANOVA analysis to explore the relationships between HR analytics and organizational outcomes. The findings indicate a positive influence of HR analytics on tactical decision-making processes, but also highlight several confronts in its adoption, such as confrontation to change as well as the lack of adequate infrastructure. The study concludes by providing recommendations for enhancing the effectiveness of HR analytics in FMCG companies and contributes to the mounting body of knowledge on the strategic part of HR analytics in improving organizational performance.

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Keywords: HR analytics, FMCG industry, workforce management, organizational planning, employee performance

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This paper is an attempt to evaluate progress made by the Rashtriya Madhyamik Shiksha Abhiyan, which aims to improve the quality of secondary education in India. It intends to access the progress made toward achieving the overall goals of this programme in Uttar Pradesh, the largest child populous state of the nation, namely, providing access to secondary education, declining drop-out rate, repetition rate and increasing internal efficiency rate. It also accesses the extent to which gender disparities and differences between social groups such as scheduled castes and tribes and others have been reduced in respect of the outcome. Also, interventions to facilities, access to schooling, to ensure social equity, quality of education and more importantly allocation of plan expenditure in the state appear to have had an impact.

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Secondary Education, Gender, Quality, Equity, Fund Allocation.

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The aim of this research is to automate and enhance the inspection process of educational institutions using Artificial Intelligence. Traditional inspections often suffer from inefficiencies and lack of transparency. To address this, an AI-driven inspection system was developed, integrating image processing, document analysis, and geolocation verification. The system utilizes OpenCV and PyTesseract for detecting facility conditions such as cleanliness, damage, and fire safety compliance from images. Furthermore, document uploads are analyzed using NLP to extract key details like faculty qualifications and institutional compliance. A GPS-based authenticity check ensures the submitted data is genuine and captured on-site. MongoDB is used for structured data storage and retrieval, while Streamlit serves as the user interface for inspection and reporting. The results include real-time inspection summaries, visual analytics, and automated compliance scoring, significantly improving efficiency and accuracy in the inspection process. The project demonstrates the practical application of AI in institutional quality assurance and serves as a scalable solution for governing bodies and educational boards.

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AI Inspection, Image Analysis, Document Parsing, GPS Authentication, Institutional Compliance, Educational Evaluation.

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In industrialized nations, migration has added to the richness of racial, ethnic, and cultural diversity. People who migrate face a variety of stressors that can affect their mental health, such as adjusting to a new society, changing their identity and self-concept, and losing social support networks, religious traditions, and cultural norms. It is true that certain immigrant groups have higher incidence of mental illness. To effectively meet the needs of this growing and vulnerable population, mental health professionals must be sensitive to the particular pressures and cultural elements that impact immigrants and refugees. Reviewing the ideas of migration, cultural loss, and cultural identity, this essay will investigate how these three facets of a migrant's experience and cultural congruity are related to one another. The elevated incidence of mental illness in impacted migrant groups are thought to be mostly caused by the intricate interactions between biological, psychological, and social factors, as well as the migration process, cultural grief, cultural identity, and cultural congruity.

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Keywords: Migration, mental illness, impact, cultural identity, cultural congruity, interaction.

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Duchenne Muscular Dystrophy (DMD) is a rare and severe genetic disorder that primarily affects young boys, leading to progressive muscle weakness and disability. This article provides a comprehensive overview of DMD, including its etiology, clinical manifestations, diagnostic methods, treatment options, ongoing research efforts, and potential future therapies. By exploring the underlying genetic mutation, pathophysiology, and impact on affected individuals and their families, this article aims to shed light on the challenges faced by patients with DMD and the strides made in understanding and managing this debilitating condition. Duchenne Muscular Dystrophy (DMD) is a rare and debilitating genetic disorder that primarily affects young boys, causing progressive muscle weakness and loss of mobility. This paper provides an in-depth examination of the pathophysiology, genetic basis, clinical manifestations, diagnostic methods, and current therapeutic strategies for DMD. The disorder arises from mutations in the dystrophin gene, leading to the absence of this essential protein in muscle cells. As a result, muscle fibers are susceptible to damage and degeneration, ultimately leading to severe muscle wasting. Early diagnosis through genetic testing and clinical evaluation is crucial for timely intervention, as the natural course of the disease is characterized by loss of ambulation and life-threatening complications. Various therapeutic approaches, such as corticosteroids, physical therapy, and emerging gene-based therapies, are discussed in detail. This review aims to provide a comprehensive understanding of DMD and highlight the ongoing research efforts to improve the quality of life for affected individuals.

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Duchenne Muscular Dystrophy (DMD), Genetic disorder, Dystrophin gene Muscle weakness, Clinical manifestations, Physical therapy.

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Large amounts of e-waste produced by electrical and electronic gadgets are found all over the world nowadays and have turned into a global ecological concern. Because certain components of various electronic devices include compounds that are hazardous due to their density and conditions, e-waste is considered harmful. These materials' hazardous content poses a risk to both the environment and human health. Its deadly compounds combined with soil, water, and air have a dangerous direct or indirect influence on all biodiversity. The study's foundation is a survey of the literature on the effects of electronic waste on the environment and human health. It was determined that there was a massive production of e-waste and that there were insufficient and inappropriate measures in place to handle it. Additionally, it was shown that e-waste had a significant negative influence on both the environment and human health.

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E-waste, electrical and electronic equipment, EEE, environment, human health.

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The Tibetan Crisis, rooted in China's 1950 annexation of Tibet and the subsequent 1959 uprising, has significantly shaped Sino-Indian relations, with the Dalai Lama, Tenzin Gyatso, playing a pivotal role as both a spiritual and political figure. Fleeing to India in 1959 after the failed Lhasa uprising, the Dalai Lama established the Central Tibetan Administration (CTA) in Dharamsala, creating a government-in-exile that has been a persistent irritant in Sino-Indian diplomacy. This abstract explores the Dalai Lama's evolving role, from leading Tibet's resistance to advocating the Middle Way Approach for autonomy within China, and its implications for Sino-Indian relations. Initially, India's hosting of the Dalai Lama and Tibetan refugees strained ties with China, contributing to tensions culminating in the 1962 Sino-Indian War. China's suspicion of Indian support for Tibetan activities, despite India's official stance limiting the Dalai Lama to religious and cultural roles, continues to fuel mistrust. The Dalai Lama's international advocacy, including his 1987 Five-Point Peace Plan and global travels, has amplified Tibet's cause, aligning it with Western support and complicating India's balancing act between supporting Tibetan exiles and managing relations with China. This research offers a structured historical and theoretical analysis of India-China relations, focusing on the Tibet issue and the Dalai Lama's influence from 1947 to the present. It employs international relations theories to contextualize the conflict and proposes pathways for peaceful resolution. The findings aim to contribute to understanding the geopolitical complexities of the Tibetan crisis and its impact on Sino-Indian relations, offering insights for future diplomatic strategies.

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Tibetan Crisis, Sino-Indian War, Dalai Lama, Five Point Peace Plan

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Agriculture is a rapidly growing sector worldwide due to the increasing population. One of the main challenges in agriculture is improving farming efficiency and quality without constant physical monitoring to meet the rising food demand. Additionally, climate conditions pose significant challenges to the agricultural industry. The aim of this research paper is to propose a smart farming model based on the Internet of Things (IoT) using clustering techniques to address adverse conditions. In this model, various sensors such as soil moisture, temperature, rain detection, and humidity, water level sensors are utilized for different purposes. The collected data will be stored in the cloud and processed automatically. Smart agriculture can be adopted through crop control, data collection, and automated analysis. The purpose of this paper is to demonstrate how IoT can be implemented in monitoring humidity, soil conditions, temperature, water supply levels, and climate conditions. The proposed IoT-based Smart Farming System integrates different sensors and a Wi-Fi module to produce live data feeds that can be accessed online. Agriculture is very important for the growth of any country. However, even in today's technology-driven world, most farmers still use old-fashioned, manual methods of farming. To reduce the need for too much physical work and constant checking, this study introduces an automatic farming system using the Internet of Things (IoT).This system uses sensors and a small computer (like a Raspberry Pi) to monitor and control basic farming tasks such as: Watering plants, Turning lights on or off in greenhouses, Alerting farmers about important issues. The system also sends important information--like water levels, temperature, and humidity--to a central server and directly to farmers. This helps farmers keep track of their farms more easily and can also be useful for further research in agriculture. If many farms use this system, the collected data can help improve farming methods for everyone.

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IoT, Sensors, Cloud, Smart farming.

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North East India is affected by a deficit in animal origin protein. The region represents the highest per capita consumption however farmers are unable to meet the demand. The consumers rely on meat, fish and eggs imported from rest of India leading to high per unit price of protein. While ICMR nutritional estimates indicate a 25 Kg annual protein demand for adults, studies peg protein uptake in India at 5-6 Kgs annually. The Animal Husbandry department of Assam estimates a state wide shortfall of 316 thousand tonnes of meat. National Statistics data indicates that North Eastern states spend the highest share of household food budget on meat within India. Our study focussed on stakeholders, entrepreneurs and farmers from across Assam to identifying the animal protein with acceptable economic, social and environmental indicators for policy level support. The study focussed on Assam as the hub of production and North East India as the market. Environment, Social and Governance (ESG) parameters were evaluated in conjunction with Triple Bottom Line (TBL) Considerations and the results were analysed using CRISILS ESG scoring methodology. Keywords: Protein deficit, Green House Gases (GHG) emission, Triple Bottom line (TBL), Environment, Social and Governance (ESG) New Enterprises, Agri Business Incubators, Women first commodity. JEL Codes - J16, M21, M41, Q1, Q11, Q13, Q51

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Triple Bottom Line (TBL), ESG as a factor in policy making for small businesses, Women in agri business, Incubation services,

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This paper addresses this critical need by proposing an AI-driven multimodal cyberbullying detection system that integrates Natural Language Processing, Computer Vision, and Deep Learning techniques. By leveraging large-scale, diverse datasets and advanced feature fusion methods, the system aims to significantly improve detection accuracy and reduce false alarms. The proposed approach supports safer digital environments, empowering platforms to proactively identify and mitigate cyberbullying across multiple media formats, thus protecting vulnerable users more effectively than existing unimodal solutions.

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Cyberbullying, Multimodal Machine Learning, Natural Language Processing, Computer Vision, Deep Learning, Social Media Analytics

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The vague reliability of the system is studied usually by using classical set theory. Nevertheless, analyzing the system's actual state cannot be done using classical set theory. Given that today's current techniques are the outcome of continuous advancements in science and engineering technology, fuzzy set theory is one of the best theories to account for subjectivity and vagueness in information. This article aims to analyze mechanical systems vague reliability, specifically as it relates to the compressor house unit (CHU). Four subsystems make up the compressor house unit. The compressor house unit's vague reliability is being assessed using the parallel series network method, which is determined by combining Sugano's fuzzy failure rate methodologies with trapezoidal vague numbers (TrapVan). In this article, the authors also applied the suggested method for estimating fuzzy reliability by Sugeno's fuzzy method with the help of parallel-series and series-parallel system methods for TrapVaN. The approach using a mathematical illustration and a graphical representation has been performed in this article.

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Vague Sets (VaS), Compressor House Unit (CHU), Fuzzy Failure Rate (FFR), Trapezoidal Vague Numbers (TrapVaN)

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