Volume 13 | Issue 10

 Abstract

Abstract In Perumal Murugan's Trial by Silence, gender representation is explored through the emotional and psychological aftermath of societal pressures on the protagonists, Kali and Ponna. The novel critiques the rigid patriarchal expectations that define gender roles in a traditional South Indian community. Ponna, after participating in a ritual to conceive a child, faces severe societal judgment despite the act being socially sanctioned. Her character represents the double standards women endure, as they are judged for their fertility, purity, and adherence to societal norms. Ponna's journey towards reclaiming her agency reflects the tension between individual desire and societal control over women's bodies. Kali, on the other hand, is consumed by silence and isolation, struggling with the blow to his masculinity and honor. His emotional withdrawal highlights how patriarchal expectations of control, honor, and virility also affect men, driving him into a state of psychological turmoil. This novel exhibits how masculinity is tied to notions of control and ownership. Through its nuanced portrayal of both male and female suffering under patriarchy, Trial by Silence reveals the deep emotional scars gender expectations leave on individuals in traditional societies.

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Gender representation, Patriarchal expectations, Societal judgment, Masculinity and honor, Female agency

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Sensorineural hearing loss (SNHL) is the most common form of permanent auditory impairment, affecting millions worldwide and profoundly influencing communication, cognition, and quality of life. Conventional approaches, such as hearing aids and cochlear implants, provide compensation but cannot restore the physiological processes underlying natural hearing. Recent advances in molecular medicine have positioned gene therapy as a transformative strategy for hereditary and acquired forms of SNHL. This review examines current progress in gene therapy for otology, emphasizing three primary mechanisms: gene replacement, gene editing, and regenerative or neuroprotective strategies. Clinical trials targeting OTOF mutations using dual-adeno-associated viral (AAV) vectors have demonstrated measurable restoration of hearing in infants and children with auditory neuropathy, marking a milestone in translational medicine. Preclinical progress with GJB2 replacement and early trials of ATOH1-based regenerative approaches further highlight the diversity of therapeutic targets. Nonetheless, challenges remain, including vector capacity limits, immune barriers to re-dose, narrow developmental windows of efficacy, and global accessibility concerns. Future directions point toward improved vector engineering, precise genome-editing technologies for dominant mutations, integration of gene therapy with cochlear implants, and expansion of treatment to broader patient populations. Collectively, the field is moving from experimental feasibility toward clinical reality, offering hope that gene therapy may soon provide durable, biologically restorative solutions for individuals affected by hearing loss

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Sensorineural hearing loss (SNHL) represents the most prevalent form of permanent hearing

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The development of urban area is closely linked to modernization, industrialisation and the sociological process of the nation. However, urban governance and management has not been fruitful as expected. Various socio-economic, environmental and infrastructural problems act as a big hindrance to the state's overall development. Urban challenges such as urban poverty, poor infrastructure, unemployment, climate change, housing, population growth, health and sanitation etc need to be addressed in relation to urban development. The study is descriptive based on secondary data and the final analysis presents the possible steps to be undertaken in order to overcome these challenges and move forward towards development.

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Urban, Development, Challenges, Nagaland, Policies

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Automation is accomplished by the use of a variety of sensors like LDR, IR, Temperature sensor for monitoring production processes, actuators, and numerous techniques and equipment. The automation system established in this project is an automatic lamp and an automatic fan. Light Dependent Resistor (LDR) Provides variable resistance based on light intensity. Microcontroller Interfaces with the LDR, processes light level data, and controls the lamp. An Infrared (IR) sensor uses infrared radiation to detect and measure various physical properties or presence of objects by that visitor count is monitored. Fan operation is based on temperature measurements and fire detection. When smoke or fire is detected, the microcontroller activates the L293D motor driver to operate the fan, Buzzer is used for alert and water pump is used when the temperature gets more. The Wi-Fi module ESP8266 is integrated to enable wireless communication, providing seamless connectivity between the system and user interfaces, such as mobile applications and web-based platforms. In this project mobile application is used. The IoT-based control framework allows real-time monitoring and control. In this project, an Arduino Uno acts as the central controller, It has different groups of pins that allow it to connect with sensors, modules, and output devices. For displaying real-time information, a 16x2 LCD with I2C module is connected to the Arduino, showing sensor readings and system status. By integrating all these components, the Arduino Uno coordinates sensor inputs, processes the data, and activates outputs, thereby creating a fully automated and remotely monitorable auditorium system.

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Arduino UNO, ESP 8266, Sensors, IOT.

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The Government of India introduced Pradhan Mantri Mudra Yojana (PMMY) on 8th April, 2015 for providing loans upto Rs 20 lakhs to non-corporate, non-farm, small and micro enterprises (MSEs). In Nagaland's economic landscape marked by an absence of large scale industrial activity, micro and small enterprises play a crucial role in promoting self employment and entrepreneurship among youth, women and marginalized communities. By providing loans under its various categories- Shishu, Kishore, Tarun and Tarun Plus, the scheme has enabled access to formal credit for local entrepreneurs who remain outside the reach of traditional banking channels. By providing collateral free loan, the scheme has emerged as an important engine in providing the needed impetus to micro and small enterprises in providing a platform for individuals to start their own business, innovate and contribute to the state's economy. However challenges such as lack of financial literacy, infrastructural gaps and awareness has act as deterrents in realizing the scheme's full potential in the state.

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Small, Micro Enterprises, Entrepreneurship, Credit Access

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This study examines the relationship between teaching competency and professional dedication among Higher Secondary School teachers in the Puducherry regions. A sample of 300 teachers was selected using stratified random sampling to ensure representation across demographic and institutional categories. Standardized tools were used to measure teaching competency and professional dedication, and data were analyzed using descriptive statistics, t tests, and ANOVA. Results indicated high overall levels of competency (M = 78.4) and dedication (M = 82.1). Significant differences in competency were found across gender, age, and teaching experience, while dedication varied by type of school and qualification. A positive correlation emerged, highlighting their interdependence.

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Keywords: Teaching competency, professional dedication, Higher Secondary School teachers

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In today's hyper connected global marketplace, the ability of marketing strategies to remain relevant is a decisive factor for organizational success. Guerrilla Marketing Insights: Redefining Relevance in a digital era explores how the concept of "Guerrilla Marketing" can serve as a unique framework to align brand value, customer expectations, and digital transformation. The study emphasizes the growing significance of consumer-centric approaches, data-driven decision-making, and digital platforms in shaping sustainable marketing strategies. By integrating global case studies, emerging technologies, and cultural adaptability, this research highlights how Guerrilla Marketing redefines traditional marketing paradigms into more dynamic, inclusive, and innovation-driven models. The findings suggest that marketing relevance in the digital era requires not only technological adoption but also a holistic understanding of consumer behavior across borders. The paper contributes to international marketing discourse by providing actionable insights for businesses, policymakers, and academics seeking to enhance market competitiveness, brand resonance, and customer engagement in an era defined by digital disruption.

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Key Words: Guerrilla Marketing, digital transformation, marketing relevance, consumer engagement, global strategies, innovation.

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Ayurveda is the holistic system of medicine which gives equal importance to preventive and curative aspects of treatment. In Ayurveda Vandhytva (Infertility) as an inability to reproduce naturally. Infertility is a medical conditions described by the failure to achieve a clinical pregnancy after 12 month or more of regular unprotected sexual intercourse. In present modern era, female infertility is raised to the alarming extent due to diet and lifestyle modification. Form a physiological perspective infertility as a disturbance in the normal functioning of the Hormones, structural abnormalities and sperm or egg quantity to overcome this Rasayan therapy is the Ayurvedic management that focuses on rejuvenation and restoration of the body's natural functioning, mainly in the reproductive system.

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Infertility, Agni, Rasayan, Ama, Dhatu, Artava.

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ABSTRACT Attention-Deficit Hyperactivity Disorder (ADHD) is recognized as the most prevalent neurobehavioral condition in childhood. It is a multifactorial disorder of brain function marked by the triad of inattention, hyperactivity, and impulsivity. Genetic predisposition plays a major role in its causation, often influenced by environmental triggers. Although it can occur across all age groups, school-aged children are most frequently affected. In contemporary medicine, management strategies primarily include stimulant medications along with psychotherapeutic interventions. Ayurveda explains that any illness arises from the imbalance of either sharirika (physical) or manasika (psychological) doshas, or both. The characteristic symptoms of ADHD indicate involvement of vata dosha on the physical level and raja dosha on the mental plane. Shirodhara, an Ayurvedic therapeutic procedure described for mental health disorders, holds potential as a supportive intervention in behavioral conditions like ADHD. Considering its calming and stabilizing effect on the mind, Shirodhara may serve as an effective complementary approach in the management of neurobehavioral disorders.

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ADHD, Inattention, Hyperactivity, Impulsivity, Shirodhara

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Dental visits are often accompanied by psychological distress, with anxiety, stress, and depression playing significant roles in shaping treatment experiences. Although extensive research has been conducted on dental anxiety, limited attention has been given to the broader psychological dimensions, especially among women who are known to experience heightened vulnerability. This study investigates the prevalence and patterns of psychological distress among female dental patients in Bengaluru Urban, integrating both quantitative and qualitative approaches. Using the Depression, Anxiety, and Stress Scales (DASS-21), semi-structured interviews, and demographic profiling, the study highlights correlations between sociodemographic variables and distress levels. Findings reveal significant associations between younger age groups, lower educational levels, infrequent dental visits, and higher psychological distress. The study underscores the importance of integrating psychological screening into dental practice and advocates for a holistic approach that bridges dentistry and mental health in India.

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Psychological distress, dental anxiety, DASS-21, stress, depression

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Neighbourhood First Policy; India's Soft Power Diplomacy; Culture; Education; Humanitarian; and Developmental Assistance.

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The proliferation of artificial intelligence (AI) in retail has transformed customer interactions from transactional to highly personalized experiences. This study aims to investigate the direct and indirect effects of AI-powered personalization on consumer purchase intention within an omnichannel retail context. It specifically examines the mediating roles of perceived value and consumer trust. A structured questionnaire was developed and administered online to a sample of 327 Indian consumers who have experienced personalized recommendations on e-commerce platforms and in-store digital kiosks. Data analysis was conducted using SPSS for descriptive statistics and SmartPLS 4.0 for Structural Equation Modeling (SEM) to test the proposed hypotheses. The results indicate that AI-powered personalization has a significant positive direct effect on purchase intention. Furthermore, perceived value and trust were found to be significant partial mediators. Perceived value emerged as the stronger mediator, suggesting that consumers are primarily driven by the functional benefits of personalization. The study is limited by its cross-sectional design and geographic focus on urban Indian consumers. Future research could employ longitudinal designs and explore cultural differences. The findings offer practical implications for retailers to invest in AI systems that enhance perceived value (e.g., through relevant product discovery) while being transparent to build trust. This research contributes to the literature by integrating Technology Acceptance Model (TAM) and Stimulus-Organism-Response (S-O-R) framework to provide a holistic model that explains how personalization influences purchase decisions through key psychological mechanisms (perceived value and trust) in an omnichannel setting.

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Artificial Intelligence, Personalization, Omnichannel Retail, Purchase Intention, Perceived Value, Consumer Trust, Structural Equation Modeling

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A comparison of the perceptions of B.Ed. and Shiksha Shastri student teachers regarding the challenges faced in implementing the National Education Policy 2020

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A comparison of the perceptions of B.Ed. and Shiksha Shastri student teachers regarding the challenges faced in implementing the National Education Policy 2020

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In today's world, people spend a lot of time online using phones, social media, and other digital platforms. While these tools can help us connect, they can also harm mental health by causing stress, loneliness, or anxiety. Many people who need mental health support do not get it due to stigma, high costs, or lack of access to professionals. Artificial Intelligence (AI) could help by detecting emotions through online activity, messages, or speech and by offering quick support. But there are concerns about how accurate AI really is, whether it can be trusted, and how it might affect privacy. This raises an important question: Can AI be used safely and effectively to support people's emotional well-being in the digital age?

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Artificial Intelligence, Mental Health, Emotional Well-being, Digital Mental Health, AI Therapy, Mental Health Apps, Emotional AI, AI and Privacy, Online Therapy, Future of Mental Health

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Abstract: In today's digital era, networks are highly important but face growing threats such as malware, phishing, and denial-of-service attacks. Traditional intrusion detection systems, which rely on signatures, fail to detect zero-day and evolving attacks. To address this, the research proposes an intelligent IDS that uses machine learning models like SVM, Random Forest, and Logistic Regression to classify traffic as normal or malicious. The system includes real-time monitoring, automated classification, database logging, and an interactive web dashboard. Its performance is validated using metrics such as accuracy, precision, recall, and F1-score, showing strong robustness. Overall, the proposed IDS achieves higher accuracy and scalability, making it suitable for enterprises, institutions, and critical infrastructures.

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Intrusion Detection System, Machine Learning, Cybersecurity, Random Forest, Support Vector Machine, Logistic Regression

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This project introduces a real-time object detection and localization system that leverages the YOLO (You Only Look Once) pre-trained model, integrated with an intuitive user interface developed using Python's Tkinter framework. The system aims to enhance object recognition by delivering immediate visual feedback along with audio-based alerts, announcing both the identity and relative position of detected objects within the camera frame. Users interact with the system via a graphical interface that features a "Start Detection" button, initiating a live video stream. The YOLO model processes this stream in real time, identifying objects and estimating their spatial locations--such as left, right, top, bottom, or center. To support accessibility, particularly for visually impaired users or in hands-free environments, the system incorporates text-to-speech synthesis to provide verbal descriptions of the detections. By combining efficient object detection, spatial localization, and audio output, this system demonstrates practical utility in areas such as surveillance, assistive technologies, and industrial automation. The integration of YOLO ensures high-speed, accurate detection, offering a seamless and responsive user experience.

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Index Terms- YOLO (you only look once), Tkinter, OpenCV, Text to Speech Algorithm (TTS).

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The problem of predicting equity prices is fundamentally challenging, since the time series of the market are noisy and non-stationary, and influenced by nonlinear long-range processes. Standard models do not support these long-term dependencies. We use Long Short-Term Memory (LSTM) networks, which are an RNN architecture designed to operate over long horizon memories, to make price projections based on historical data. Our pipeline uses cautious feature selection, normalization, sequence windowing, and hyperparameters (units, learning rate, and dropout) are optimized by grid search. The model, trained over 100 epochs using separate training, validation, and test divisions, has a predictive accuracy of 98 percent on held-out data. These findings reaffirm the power of LSTM with regard to the ability to model complex time-structure and outperform rival methods, providing useful decision support to investors and analysts. Further developments might add real-time feeds and other financial indicators to give it even more real-world utility.

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Stock price forecasting; Long Short-Memory (LSTM); Recurrent Neural Networks (RNN); Deep learning; Time-series analysis; Nonlinear dynamics; Long-range dependencies; Feature engineering; Data normalization; Sliding-window sequences; Hyperparameter optimization; Grid search; Dropout; Learning rate; Train-validation-test split; Evaluation metrics (MAE, RMSE, MAPE); Directional accuracy; Financial markets; Volatility modeling; Real-time data integration.

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This paper presents the design and implementation of a Smart CNG Reservation System that enables users to pre-book CNG fueling slots and allows pump owners to manage station availability, subject to administrative approval. The system is developed as a Java web application using JSP and Servlets with MySQL as the backend database. It includes three modules: user, pump-owner, and administrator, each with distinct functionalities such as slot booking, pump approval, and dashboard management. Additional features such as an integrated chatbot and location-based mapping improve usability. The system reduces waiting times at CNG stations, improves pump utilization efficiency, and demonstrates scalability for urban fuel management. Future enhancements include mobile app integration and predictive slot allocation using machine learning.

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CNG reservation, slot booking, JSP/Servlets, MySQL, smart fuel management, web application

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 Abstract

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Non-Government Organisations (NGOs) play a critical role in empowering persons with disabilities and promoting their social, economic, and educational inclusion. Acting as a bridge between policy frameworks and ground-level implementation, NGOs provide a wide range of services, including education, vocational training, rehabilitation, healthcare, and advocacy. They help individuals develop skills, gain employment, and participate actively in social and civic life, while also addressing societal stigma and fostering inclusive communities. This paper examines the historical and legal context of disability rights in India and globally, highlighting the role of key legislations such as the RPwD Act, 2016, and the UNCRPD. It explores the types of NGOs, their approaches, and core functions, including awareness generation, policy advocacy, capacity building, and direct service delivery. Case studies illustrate successful interventions and best practices, while the challenges faced by NGOs--such as funding constraints, regulatory hurdles, and societal barriers--are discussed. The study emphasizes the impact of NGO initiatives on individual empowerment, community development, and systemic change. Recommendations for future directions focus on strengthening partnerships, leveraging technology, enhancing organizational capacity, and improving monitoring and evaluation. By highlighting the indispensable role of NGOs, this paper underscores their contribution to creating an inclusive society where persons with disabilities can exercise their rights fully, achieve independence, and participate meaningfully in all spheres of life.

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Non-Government Organisations (NGOs), Social Inclusion, RPWD Act, 2016, UNCRPD, Vocational Training, Rehabilitation Services.

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