Volume 13 | Issue 8 |

 Abstract

This paper investigates the role of traditional practitioners in Kalahandi district, Odisha, as custodians of indigenous healing systems embedded in cultural and ecological knowledge. Drawing on historical records, ethnographic insights, and primary field data, the study examines how healers--locally known as Disaris, Baidyas, and Gunias--have served as frontline healthcare providers for tribal communities across generations. It analyzes their diagnostic techniques, plant-based therapies, spiritual rituals, and the socio-cultural frameworks that confer legitimacy upon their practices. Despite disruptions from colonial interventions, restrictive forest policies, and the expansion of biomedical systems, these practitioners have exhibited remarkable resilience and adaptability. The paper also addresses contemporary threats posed by modernization and underscores the urgency of policy frameworks that recognize and integrate indigenous healthcare into mainstream health strategies. Findings reveal that traditional healers not only sustain community health but also contribute significantly to biodiversity conservation, cultural continuity, and the advancement of sustainable healthcare models.

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 Keywords

Ethnomedicine, traditional healers, indigenous knowledge, Kalahandi, biodiversity conservation, cultural resilience, medical pluralism

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Pantheism has been a powerful element in religion and literature and its practitioners identify God with everything. The two poets--William Wordsworth from 19th century England and Raghunath Choudhary from 20th Century India displayed deep pantheistic inclinations in their poetical works. Wordsworth's pantheism was the outcome of his familiarity with Plato and Spinoza. Choudhary's pantheism , on the other hand , was based solely on Indian philosophical traditions. Although Wordsworth discarded pantheism later in his life, Choudhary never modified or discarded his pantheistic outlook.

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Pantheism, Wordsworth, Raghunath Choudhary

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Worldwide, cervical cancer is a leading cause of cancer-related death for women. Increased survival rates and effective treatment outcomes depend on timely and accurate detection. This review offers a thorough analysis of current methods for detecting cervical cancer, with an emphasis on new developments in machine learning and imaging technology. It examines the foundations of important imaging techniques, including colposcopy, and assesses how machine learning algorithms can improve diagnostic precision. The study also summarizes current research results, identifies new trends, and suggests future paths to improve the efficiency and accessibility of cervical cancer diagnosis.

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Cervical Cancer, Early Detection, Screening Methods, Pap Smear, Colposcopy, Biopsy, Digital Colposcopy, Optical Coherence Tomography (OCT), Spectroscopy, Machine Learning, Deep Learning

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Creative Commons Attribution 4.0 and The Open Definition

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operating profit, regression diagnostics, multicollinearity, model selection, financial indicators, predictive modeling

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Introduction: Lymphadenopathy especially cervical lymphadenopathy is commonly presented complaint in pediatric age group. In majority of pediatric cases, enlarged lymph nodes are due to reactive causes and are self-limiting. Hence excision biopsy is not required in all cases. FNAC is safe, accurate, minimally invasive procedure where resources are limited, and access to surgical biopsy is limited. Material and methods: This retrospective study was carried out with the data collected for period of 2 years from January 2022 to December 2023, from department of pathology, GMERS medical College and hospital, Sola, Ahmedabad. All pediatric cases (<=18 years) with superficial lymphadenopathy where FNAC was performed during the study period was included. Aspirated material was stained with H&E, PaP stain, Giemsa stain and Z&N stain (whenever required). Lymphadenopathy was classified, based on cytomorphological findings into Benign (Nonspecific reactive, Acute suppurative, Granulomatous) and Neoplastic. Results: Total 126 lymph nodes were aspirated during study period in pediatric age group. The results were categorized into 2 broad categories: Benign and Malignant. Among Benign lesion- 49 cases (38.89%) were of Nonspecific reactive lymphadenitis, 53 cases (42.06%) were of Granulomatous and 22 cases (17.46%) were of acute suppurative lymphadenitis. Among malignant - 2 cases were identified, 1 of Hodgkin Lymphoma (0.8%) and 1 of Non-Hodgkin Lymphoma (0.8%). In this study maximum number of the patients were in the age group of 11-18 years (61.90%) followed by 6-10 years (23%), in <=5years (15.08%). Male to Female ratio is 1: 0.96. Conclusion: FNAC is safe, rapid and accurate method of investigation in pediatric superficial lymphadenopathy and help in next appropriate steps of management. Nonspecific reactive and Granulomatous (tuberculous) lymphadenopathy are most common cytomorphological findings seen in pediatric superficial lymphadenopathy examination.

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cervical lymphadenopathy, FNAC, pediatric age group

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This paper presents a comparative study of advanced machine learning algorithms for prime number classification across diverse numerical ranges. Seven models Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), XGBoost (XGB), and LightGBM (LGBM) are systematically evaluated in terms of both predictive accuracy and computational efficiency across eight distinct prime number intervals. The assessment incorporates key performance metrics such as Accuracy, Precision, Recall, F1-Score, ROC-AUC, average training time per epoch, and the average number of epochs required for convergence. Findings from the analysis emphasize the inherent trade-offs between accuracy and efficiency, providing practical guidance for selecting optimal models in large-scale classification scenarios. The results reveal noticeable variations in model performance based on both the prime number range and the chosen algorithm. Ensemble models like XGBoost and LightGBM consistently achieved higher accuracy in larger ranges, whereas Logistic Regression and Decision Trees showed limited scalability. k-Nearest Neighbors performed well in smaller ranges but lost efficiency as the dataset size increased. Overall, the study underscores the balance between accuracy and computational cost, providing useful guidance for selecting suitable machine learning models in prime number classification and broader computational number theory tasks.

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Prime Number Classification, Machine Learning, Accuracy, Computational Efficiency, Convergence Rate, Analysis, Number Theory.

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ABSTRACT: Introduction: This article explains that financial institutions in any country are the lifeblood of the economy. Banks are important in today's society. International experience proves that countries that promote free trade develop rapidly and steadily. To be effective, employees are "resources" that can only be used for training. This means that employees can combine new skills with their previous experiences and develop new ideas. Literature review: According to Soteriou, Andreas and Zenios, A. Stavros. (1997) stated that customer satisfaction is an important factor in bank sales which has a long-term financial impact on the banking sector. Objective of this study: The main objective of this research paper is to examine the relationship between Bagalkot District Commercial Bank and financial performance and to analyze the performance of Bagalkot District Commercial Bank in terms of customer satisfaction and employees. Methodology of study: This section discusses the research methods used in this study, including: Statistical methods used for quantitative and qualitative analysis. Secondary and primary data used in this research. The sample size is 150. Based on data analysis and interviews with experts in relevant fields, Study A has 10 questions and Study B has 15 questions. 4 means satisfied, 5 means satisfied but not very comfortable. Research Hypotheses: The hypotheses tested in this article are as follows: H0: There is no difference in customer satisfaction in banking sector in different parts of Bagalkot district. 2. H0: There is no difference in customer satisfaction among bank employees in different parts of Bagalkot district. Data Analysis and Interpretation: The second picture is determined by analyzing the data and activities of the companies it works with and there are five variables: Productivity, Income, Availability of Money, Production, Quality and Capacity. Collect valuable information from bank employees and bank customers to measure customer satisfaction and employee satisfaction. Finding: Research shows that there are differences in customer satisfaction among different groups. Jobs and incomes change every year. However, customer satisfaction does not differ significantly by gender and education level. The analysis shows that there are differences in the happiness of employees of different ages and professions, but there is no difference in employee satisfaction due to gender difference. Conclusion: The analysis shows that people are more important than money in finance. Banks that fulfill their human responsibilities such as social participation, customer satisfaction, and employee satisfaction are successful. Keyword: Commercial Banks, Productivity and Social Relations, Employee Performance and Satisfaction

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Keyword: Commercial Banks, Productivity and Social Relations, Employee Performance and Satisfaction

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This study investigates the ethnomedicinal practices of indigenous communities in the Kalahandi district of Odisha, India, where access to modern healthcare remains limited. Conducted between July 2023 and January 2024, the research draws on both primary and secondary sources to document traditional plant-based remedies used for the prevention and treatment of various ailments. Fieldwork was carried out across ten villages, involving interviews with 48 informants, including both traditional healers (Kavirajs) and knowledgeable non-healers. Data were collected using structured and semi-structured questionnaires, supplemented by direct observation and guided field visits. A total of 61 plant species--comprising 30 trees, 14 shrubs, and 17 herbs--were recorded for their medicinal applications. The study details preparation methods, routes of administration, and the use of additional ingredients such as milk, sugar, and water. Plant identification was verified using standard botanical literature, and photographic documentation supported the authenticity of the findings. Both qualitative and quantitative analyses were employed to interpret the data. This research contributes to the preservation of indigenous knowledge systems and highlights the continued relevance of ethnomedicine in rural health care.

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Ethnomedicine, Indigenous knowledge, Tribal healthcare, Medicinal plants, Kalahandi district, Traditional healing systems, Biodiversity conservation

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Humans are truly unique beings, distinguished by our intelligence, social nature, capacity for love and compassion, imagination, and self-reflection. These qualities set us apart from other species and have enabled us to accomplish incredible things and have a lasting impact on the world. Research shows that spirituality can benefit both the mind and the body. Whether someone is coping with cancer or clinical depression, spiritual exercises help them increase acceptance, decrease negative emotions, find meaning, and deepen their relationships with others. Spiritual well-being and physical health have a much deeper connection than most people would ever know. Spiritual well-being clears the path to better physical health. It removes the blockages that are working as impediments to your overall well-being. It acts as a guide to enhancing your mental and physical health. The Proposed study has revealed significant relationships between spirituality, health-related behaviors, and physical and psychological well-being in terms of the type of acquired education, Family background, Age, Gender etc. The results included both spirituality and health-related behaviors that are associated with psychological well-being. The relationship between spirituality and psychological well-being was stronger in the human mind and spirit group of participants.

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Spirituality, Mental health, physical Health, family person

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Use of Artificial Intelligence (AI) in Education: Prospects and Challenges

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Use of Artificial Intelligence (AI) in Education: Prospects and Challenges

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