Volume 14 | Issue 4

 Abstract

The Nandakumar Block of Purba Medinipur district, West Bengal, has experienced a significant transformation in land use and rural livelihoods over the past three decades, primarily driven by the rapid expansion of aquaculture. This study examines the spatio-temporal dynamics of land use and land cover (LULC) change and its socio-economic implications using a combination of primary and secondary data sources. A household survey of 47 respondents, supplemented by field observations, provides insights into occupational shifts, income patterns, and livelihood transformations, while LULC data for the years 1991, 2001, 2011, and 2021 are analyzed to assess land conversion trends. The findings reveal that aquaculture expansion is a relatively recent phenomenon, intensifying particularly during the period 2011-2021, when large areas of agricultural and fallow land were converted into water bodies. This process reflects a transition from a traditionally agrarian economy to a market-oriented aquaculture system. The occupational structure analysis indicates a sharp decline in agriculture-based livelihoods alongside a substantial increase in aquaculture-dependent households, highlighting a fundamental restructuring of rural employment. Income analysis further demonstrates that aquaculture has emerged as the most economically rewarding activity, with average monthly household income increasing significantly compared to agriculture and other occupations. As a result, aquaculture has contributed to improved living standards, enhanced economic mobility, and diversification of rural livelihoods. However, the study also identifies critical challenges, including the reduction of agricultural land, growing dependence on market forces, and potential socio-economic inequalities. Overall, the study concludes that aquaculture has become a key driver of rural transformation in Nandakumar Block, offering substantial economic benefits while simultaneously raising concerns regarding environmental sustainability and long-term resilience. The findings underscore the need for integrated policy interventions to promote sustainable and inclusive aquaculture development.

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Aquaculture, Land Use Change, Socio-economic Transformation, Livelihood Shift, Nandakumar Block, West Bengal

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Bengal's Baul heritage is a singular combination of humanism, mysticism and experiential knowledge systems. Although it is frequently examined as a cultural and musical legacy, its educational value is still little known. The Baul philosophy is reinterpreted in this essay as an alternative educational system based on inclusion, experiential learning and holistic human development. The study emphasises how Baul thought which is focused on inner realisation, egalitarianism and lived experience offers insightful perspectives for modern education by utilising qualitative textual analysis of Baul traditions in Birbhum. The study makes the case that contemporary educational principles like student autonomy, value education and socioemotional learning are consistent with Baul pedagogy. The study concludes with incorporating Baul viewpoints into contemporary education which can promote inclusive, compassionate and transformative learning environments.

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Baul philosophy, experiential learning, value education, folk pedagogy

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ljdkjh ek/;fed fo|ky;] Nk=&Nk=k] O;fDrxr ruko] 'kSf{kd miyfC/k] lg&laca/kA

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Smartphones play a central role in students' academic, social, and recreational lives; however, excessive use has been increasingly associated with adverse sleep outcomes. The present study examined the relationships among smartphone addiction, bedtime procrastination, and sleep onset latency among undergraduate students in Bengaluru, India. A cross-sectional design was employed using standardized self-report measures of smartphone addiction and bedtime procrastination, along with self-reported sleep onset latency. Descriptive statistics indicated moderate levels of smartphone addiction (M = 28.80, SD = 10.38), bedtime procrastination (M = 22.04, SD = 4.87), and sleep onset latency (M = 22.31 minutes, SD = 24.42). Pearson correlation analysis revealed no significant association between smartphone addiction and bedtime procrastination (r = -.06, p = .55), while a small-to-moderate significant positive association was observed between smartphone addiction and sleep onset latency (r = .28, p = .004). The relationship between bedtime procrastination and sleep onset latency was marginally non-significant (r = .18, p = .053). These findings suggest that smartphone addiction may influence sleep onset latency through direct physiological and cognitive activation mechanisms rather than through behavioural delay. The absence of support for a mediation pathway highlights the need to reconsider commonly assumed mechanisms linking technology use and sleep. The study has implications for digital well-being interventions and sleep hygiene education and underscores the need for future research using larger samples and objective sleep measures.

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Smartphone addiction; Bedtime procrastination; Sleep onset latency; Undergraduate students; Sleep behaviour; Digital well-being

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Traditional herbal home remedies play a vital role in primary healthcare among rural and tribal communities in India. The present study aims to documents the knowledge and use of medicinal plants for the treatment of febrile illnesses among households in the Sohelwa Wildlife Sanctuary and its adjoining areas of the Tarai region of Uttar Pradesh, India. Ethnobotanical data were collected through structured interviews, household surveys, and focus group discussions using a standardized questionnaire to ensure diverse community representation. Plant specimens were collected, processed, and identified using standard floras and reference literature. The study recorded 48 ethnobotanical plant species representing 44 genera and belonging to 27 families that are traditionally used to treat various fever conditions. Fabaceae emerged as the most dominant plant family, with five species. The continued reliance on herbal remedies highlights the importance of traditional knowledge systems, particularly in regions with limited access to modern healthcare. Documentation of such ethnomedicinal practices is essential for the conservation of indigenous knowledge and may contribute to future pharmacological research.

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Ethnomedicinal plants, indigeneous commuities, febrile illnesses, Sohelwa Wildlife Sanctuary.

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Pollution of recyclable waste through food remnants, liquid spills, grease among other foreign materials makes whole recycling batches unusable, causing enormous costs incurred in the recovery of the materials. Although contamination rates in single-stream recycling systems all over the world speak of more than 25 percent, virtually all automated waste classification studies in the global sphere take the waste altogether as contaminant-free. The system discussed in this paper is a deep learning system that fills this gap. Phase 1 (v1): the interacting multi-output dual-output MobileNetV2-based multi-task model is used to categorize waste material (cardboard, glass, metal, paper, plastic), and determine contaminated condition of an image at once. It presents a series of novel synthetic contamination pipelines that programmatically use spots of dirt, liquid stains, and texture atrophy to clean images, and produces a balanced 15 000-image training corpus of three publicly available datasets. v1 model attains 66.0 per cent category classification accuracy, 87.2 per cent contamination detection accuracy (AUC: 0.932) with an inference rate of 28 images per second. Phase 2 (v2) provides system upgrades to YOLOv8s with actual multi-object localization, that is, a separate bounding box of combined category-contamination labels to each object detected in a scene. V2 is trained on 10 merged classes and attains after 47 training epochs on NVIDIA RTX 4060 mAP50 of 0.855 with mAP50-95 of 0.851. A diagnostic of stain bias indicates that the accuracy of categories decreases by 7.7 percentage points over contaminated images at v1, which causes the architectural partition at v2. Collectively, these systems offer an open-source contamination aware automated recycling system on a scale.

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Waste Classification, Contamination Detection, Deep Learning, Transfer Learning, Multi-Task Learning, YOLOv8, MobileNetV2, Synthetic Data Augmentation, Computer vision, Recycling Automation.

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The increasing demand for accessible mental well being support has led to the development of digital platforms that combine structured assessment with conversational assistance. This project presents the AI Wellness Companion, a non diagnostic web based support system that integrates the Depression Anxiety Stress Scales (DASS-21), text based emotion analysis, and a chatbot style interface within a unified application. The system uses the DASS-21, a 21-item self report instrument designed to screen for levels of depression, anxiety, and stress, alongside free text emotion evaluation through a machine learning model employing TF-IDF representations for classification. Built on the Flask framework, the application coordinates routing, data handling, and user interaction. A chatbot component further incorporates emotion predictions with a local small language model hosted on the Ollama server using the Llama 3 model to deliver empathetic and safety focused responses, with fallback templates ensuring reliability. By integrating structured self assessment with unstructured text interpretation, the approach enhances user engagement and self reflection, promoting a balanced model of digital well being support. The paper discusses the conceptual foundation, architecture, and methodological choices made during the design, stating that the tool complements professional mental health care rather than replacing it.

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mental wellness, DASS-21, TF-IDF, text classification, Flask, chatbot, Ollama, Llama 3

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Sri Aurobindo was one of the greatest philosophical thinkers in India. Not only a philosopher but also an educationist, Aurobindo realised the inadequacies of our modern education system. His integral education is not only a mere education system. It is a kind of education that talks about the human body, mind and intellect that are combined together to form a magnificent machine. The primary aim of the study is to find out how integral education emphasises the purification, regulation, and transformation of the physical nature to achieve harmonious personality development within an individual. The researcher adopted a historical research method, qualitative approach based on Sri Aurobindo's philosophical writings, educational works, as well as writings by other authors. The study finds that physical development is considered a fundamental aspect of holistic development, which is an instrument of the mind and spirit, so its proper development is essential for overall growth in present situation. In the modern era, where learners are often facing stress, lack of discipline and value conflicts, Sri Aurobindo's ideas offer practical relevance in this purpose. The study concludes that integrating physical education into contemporary curricula can help develop emotionally mature, physically fit, ethically grounded, and socially conscious individuals, thereby contributing to holistic and sustainable education, which is obviously much needed in the modern world.

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Sri Aurobindo, Integral Education, Physical Development, Learners

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The Artificial Intelligence (AI) Vehicle Recommendation System is an intelligent platform designed to assist users in selecting the most suitable vehicle based on their individual needs, preferences, and financial capacity. By integrating machine learning algorithms such as content-based filtering, collaborative filtering, and hybrid recommendation models, the system evaluates user profiles--including factors like budget, fuel type, performance, and safety features--against comprehensive vehicle datasets. The platform extracts and analyzes vehicle specifications, market trends, and consumer reviews to generate personalized recommendations that align with user requirements.The system architecture comprises user data collection, data preprocessing, feature selection, model training, and recommendation generation modules. Through continuous learning, the AI model refines its predictions and adapts to evolving market dynamics and consumer behavior. Additionally, features such as interactive user interfaces, financial planning tools, and real-time market alerts enhance user engagement and decision-making accuracy.This research highlights the role of artificial intelligence in modernizing the automotive decision process by providing efficient, data-driven, and personalized vehicle recommendations. The implementation of such systems not only optimizes consumer satisfaction but also benefits automobile dealers through improved customer targeting and inventory management.

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Artificial Intelligence, Vehicle Recommendation System, Machine Learning, Content-Based Filtering, Collaborative Filtering, Hybrid Recommendation Model, Personalized Recommendation, Data Preprocessing, Feature Selection, Predictive Analytics, Automotive Decision Support, User Preference Modeling.

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The increasing global demand for sustainable cooling solutions has driven research toward innovative building materials that minimize energy consumption while ensuring thermal comfort. This project focuses on the design and performance evaluation of a hydroceramic cooling tile incorporating hydrogel clay for passive indoor thermal regulation. Hydrogel clay, with its superior water retention and evaporative cooling properties, is integrated into ceramic tiles to enhance their thermal performance. The study aims to investigate the tile's ability to reduce indoor temperatures through evaporative cooling, improve thermal comfort, and reduce dependency on active cooling systems such as air conditioners. Experimental evaluation includes material characterization, water absorption tests, thermal conductivity analysis, and real-time monitoring of temperature variations under controlled conditions. Comparative studies with conventional ceramic tiles are conducted to quantify the cooling efficiency and durability of the developed hydroceramic tiles. The expected outcome is a cost-effective, ecofriendly, and energy-efficient building material capable of maintaining comfortable indoor conditions while contributing to sustainable construction practices. This research highlights the potential of hydroceramic cooling tiles as a scalable solution for passive cooling, promoting reduced energy demand, environmental sustainability, and improved indoor living standards.

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Hydroceramic tile, Hydrogel clay, Passive cooling, Thermal regulation, Sustainable building material, Evaporative cooling.

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The UV spectrophotometric analysis confirms that the developed method is simple, rapid, and precise for the simultaneous estimation of Paracetamol and Diclofenac Sodium in their combined marketed formulation. The Isosbestic point observed at 245 nm further validates the stoichiometric relationship and molar absorptivity consistency required for the Q-analysis and simultaneous equation approach. The results obtained are in close agreement with the label claim, indicating the minimal interference of excipients in the formulation. A percentage estimation of Paracetamol and Diclofenac Sodium in the tablet dosage form by Simultaneous Equation (Vierordt's) method was obtained at the wavelength 254 nm (For Paracetamol) and 236 nm (for Diclofenac Sodium) as 94.31% and 82.60% and the content of both drugs in mg is 306.5 mg and 41.3 mg. Total percent content of both drugs in tablet dosage form is 92.74% and a total drug concentration in mg is 347.8 mg, which shows accuracy in result. Paracetamol and Diclofenac Sodium in their combined dosage forms has been found to be simple, quick, accurate, the proposed UV spectrophotometric method for simultaneous estimation of, and cost-effective.

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Simultaneous, Stoichiometric, Absorptivity, Spectrophotometric, Concentration

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The eyes are the windows to the soul" - William Shakespeare Eye problems among school children are a significant public health concern affecting their academic performance and overall well-being. This study aimed to evaluate the effectiveness of a structured teaching programme on knowledge and practice regarding eye health among school children in selected schools of Bharanikkavu Panchayat. The objectives were to assess pre-test knowledge and practice levels, evaluate the effectiveness of the teaching programme, and determine the association between pre- test scores and selected demographic variables. A pre-experimental one-group pre-test and post- test research design was adopted. Using convenient sampling, 100 school children were selected. Data were collected through a structured questionnaire. After the pre-test, a structured teaching session using appropriate audiovisual aids was conducted, followed by a post-test after seven days.Pre-test results showed that 4% had good knowledge, 56% had average knowledge, and 40% had below-average knowledge. Regarding practice, 5% demonstrated healthy practice, 30% satisfactory practice, and 65% poor practice. Post-test findings revealed significant improvement: 72% had good knowledge, 22% average knowledge, and 6% below-average knowledge. Healthy practice increased to 83%, satisfactory practice to 10%, and poor practice reduced to 7%. The mean post-test knowledge (20.73) and practice (6.95) scores were significantly higher than pre- test scores (12.95 and 5.44 respectively). The calculated t-values for knowledge (31.002) and practice (18.53) were greater than the table value (1.96), indicating statistical significance. Chi- square analysis showed an association between pre-test scores and selected demographic variables.The study concluded that the structured teaching programme was effective in improving knowledge and practice regarding eye health among school children.

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Effectiveness, Structured Teaching Programme, Eye Health, School Children, Knowledge, Practice

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Vonoprazan, a novel potassium-competitive acid blocker (P-CAB), represents a major advancement in the management of acid-related gastrointestinal disorders by offering rapid, potent, and sustained suppression of gastric acid secretion. The drug vonoprazan operates independently from acidic activation processes and it functions outside the influence of CYP2C19 genetic polymorphisms, which allows it to maintain stable intragastric pH levels. The medication shows better results in treating erosive esophagitis and keeping mucosal healing intact while achieving successful Helicobacter pylori eradication even when clarithromycin resistance exists. The drug Vonoprazan maintains its effectiveness because it stays stable in acid environments and binds strongly to H?/K?-ATPase while maintaining stable blood levels for an extended period. The medication has proven safe for short-term use but its strong acid-blocking effects make scientists doubt how it impacts long-term elevated gastrin levels and stomach lining health. The review is based on pharmacology and clinical data and safety information of the drug vonoprazan. It examines treatment applications to demonstrate its emerging position as a PPI alternative for acid-related disease management.

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Vonoprazan; Potassium-competitive acid blocker; Proton pump inhibitors; Acid suppression; Erosive esophagitis; Gastroesophageal reflux disease; Pharmacodynamics; Peptic ulcer disease.

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The increasing demand for energy-efficient and environmentally sustainable air conditioning systems has driven the development of alternative cooling technologies. Conventional vapor compression systems are associated with high energy consumption and environmental concerns due to the use of synthetic refrigerants. In this study, an all-season eco-friendly air conditioning system integrating winter heating, direct evaporative cooling (DEC), indirect evaporative cooling (IEC), and a multi-stage hybrid cooling system is designed and experimentally evaluated. The winter heating system, powered by solar PV panels and a fan-coil unit (FCU), achieved a heating capacity of 3461 W with a maximum Energy Efficiency Ratio (EER) of 34.32 at 30 Hz. The DEC system demonstrated a high cooling capacity of approximately 12.19 kW with a maximum EER of approximately 68 at medium fan speed, although it resulted in increased outlet humidity. The IEC system provided sensible cooling without adding moisture and was evaluated under single-coil, series, and parallel configurations; the series arrangement achieved superior thermal effectiveness (0.73 vs 0.70 for parallel at 20 Hz). A hybrid system combining IEC with a vapor compression refrigeration system (VCRS) was developed, achieving an EER of approximately 3.9, which exceeds the 3.3 EER benchmark of a conventional BEE 5-star rated air conditioner. The proposed system offers a sustainable and energy-efficient alternative to conventional HVAC systems, suitable for year-round operation under varying climatic conditions.

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Evaporative Cooling, Fan-Coil Unit, Energy Efficiency Ratio, Hybrid Cooling, HVAC, Solar Heating, Indirect Evaporative Cooling, Vapor Compression Refrigeration, Eco-Friendly Air Conditioning

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This paper studies a new type of mathematical set called pr-closed sets in bitopological spaces. We examine how these sets interact with pre-regular open, pre-regular closed, and pre-regular semi-open sets. Our main results show that the union of two pr-closed sets is also pr-closed, and any set "sandwiched" between a pr-closed set and its closure is pr-closed as well. We also prove that sets sharing overlapping properties become "clopen" (both open and closed) or standard closed sets under specific conditions. Ultimately, these findings expand our understanding of bitopological structures and provide a basis for future research on continuous maps and separation axioms.

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Pr- closed sets

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The Endoscopy AI System is a deep learning-based application designed to detect gastrointestinal diseases from endoscopy images. The system uses a Convolutional Neural Network (CNN) based on the MobileNetV2 architecture to classify images into four categories: Normal, Bleeding, Ulcer, and Polyp. The model is trained on labeled medical image datasets and optimized for accurate prediction. To improve transparency and trust in the model's decisions, Explainable AI (XAI) techniques such as Grad-CAM, Layer-CAM, and LIME are integrated. These methods provide visual explanations by highlighting important regions in the image that influence the prediction. A web-based interface is developed using Django, allowing users to upload images and receive instant predictions along with confidence scores and visual explanations. The system also maintains prediction history and includes an admin dashboard for monitoring results. The proposed system aims to support early diagnosis, reduce manual effort, and assist medical professionals with reliable and interpretable AI-based predictions.

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Endoscopy, Deep Learning, MobileNetV2, Explainable AI, Image Classification, Grad-CAM, LIME, Django

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Abstract: Elections are considered a very important and integral part of politics in a democratic country. A strong democracy can only be imagined when elections are conducted in a free and fair manner without any manipulation. In a democratic system, the Election Commission cannot function properly due to various reasons, which results in the disruption of the electoral process. Such as widespread corruption in elections, rigging, fake votes, occupation of polling stations, excessive election expenditure, use of government administrative machinery for elections, political influence on the Election Commission - in view of all these, the electoral system in India has become a farce. In this context, electoral reforms play a key role in shaping the democratic framework of India, besides ensuring free, fair and transparent elections. Over the past few decades, several issues have come to light, various new trends that have hindered the electoral and democratic process. Even though legal changes have been made, they are not effective enough. Hence there is an urgent need for electoral reform and many government committees have demanded it. So, this paper critically examines the historical evolution of electoral reforms India. Also, the study focusses on issues, challenges and the steps taken by the legislature and election commission of India.

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Keywords: India, Electoral provision, Electoral Reform, Issues, Emerging Challenges.

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The impact of sustainable practices and ESG (Environmental, Social, and Governance) disclosure on investor decision-making in the Indian auto industry is examined in this study. The research aims to determine whether investors' understanding of ESG concerns effects their capital allocation decisions in light of the expanding global emphasis on responsible investment. The automotive industry, which is well-known for having a significant social and environmental impact, offers a pertinent context for this investigation. Using information gathered from 365 respondents with a range of educational backgrounds, the study uses a quantitative methodology. ANOVA, Pearson correlation, and linear regression are instances of statistical analyses. The results show that investors with more education are much more aware of sustainable practices and ESG disclosures. The influence of ESG scores on investing choices is positively correlated with knowledge levels in a statistically meaningful way. Interestingly, investment decisions are more influenced by knowledge of industry-specific sustainable practices than by broad ESG disclosure. The results highlight the increasing significance of ESG awareness in influencing investing behaviour, even if the regression model only accounts for a small percentage of the variance. In order to encourage sustainability-driven investment strategies, this study emphasizes the necessity of better ESG communication by automakers as well as the significance of investor education.

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ESG Disclosure, Sustainable Practices, Investor Decision-Making, India's Automobile Industry

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The increase in industrialization and urbanization has led to higher risks of exposure to harmful gases, which can pose serious health hazards and environmental threats. This paper presents the design and implementation of a Harmful Gas Detection and Alert System that continuously monitors the presence of toxic gases such as carbon monoxide (CO), methane (CH?), and ammonia (NH?) in the environment. The system integrates gas sensors, a microcontroller, and wireless communication modules to detect gas leakage in real-time. Upon detecting gas concentrations above predefined safety thresholds, the system triggers an audible alarm, visual indicators, and sends an instant alert via SMS or mobile application to concerned personnel. Experimental results demonstrate that the proposed system can efficiently detect harmful gas levels and provide timely warnings, thereby preventing accidents and enhancing workplace safety. This system is cost-effective, scalable, and suitable for deployment in homes, industries, and public spaces.

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Harmful gas detection, gas sensors, microcontroller, IoT alert system, safety monitoring.

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Confessional Poetry is a type of narrative and lyric verse dealing with the facts and intimate mental and physical experiences of the poet's own life. In such poetry, like a mirror, the self is a primary concern which is treated with utmost frankness, and lack of restraint, written in ordinary speech and using open forms. The readers can connect their lives with the confessional poetry as it represents different aspects of human life. A group of poets who have become known as confessional has also engendered much debate. For the female writers, confessional poetry is a medium where they can expose their psychological feelings. Kamala Das has mostly been assessed as a writer in this genre of confessional poetry. She projects her emotion as well as represents the reality of the world through portraying her own experience. She has created a permanent place for herself in the contemporary Indo - Anglican Poetry by taking the literary world in the mid-sixties. She became one of the pioneering Post-Independence Indian English Poets to have contributed immensely to the growth and development of Modern Indian English Poetry.

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Confessional, engendered, psychological, contemporary, pioneering

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