Volume 11 | Issue 12 |

 Abstract

Psychosomatic disease which are also called as psychological Factors that affect Physical condition by DSM-V. These are the condition by where psychological factors (stress, anxiety) triggered or exacerbated physical illnesses. Stress has a strong influence on mind and emotions thereby affect the functioning of mind and physical body. The article shows how Homoeopathic approach is best for psychosomatic diseases, how the principle of homoeopathy helps in understanding the psychosomatic diseases because when homoeopathy cures a normal individual, the deeper side of his being i.e., emotions, the will and the understanding or the rational mind comes into equilibrium i.e., health.

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 Keywords

Psychosomatic, Psychophysiological, Homoeopathy, Holistic treatment

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This review article provides an overview of the role of herbal medicine in the management of chronic diseases. Chronic diseases, such as diabetes, cardiovascular disease, and arthritis, present significant challenges to healthcare globally. The growing interest in herbal medicine as an alternative and complementary therapy has prompted investigations into its potential benefits, mechanisms of action, and limitations. Herbal medicine offers a wide range of potential benefits in chronic disease management. These include symptom relief, antioxidant activity, immune system modulation, metabolic regulation, and reduced side effects compared to some conventional medications. Phytochemical constituents, modulation of gene expression, enzyme activity, and interactions with the gut microbiota contribute to the mechanisms of action of herbal medicine.Despite the potential benefits, herbal medicine faces certain limitations and considerations. Standardization and quality control are essential to ensure product consistency and reliability. Drug interactions, the lack of regulatory oversight, and the need for more robust scientific evidence are factors that require attention. In conclusion, herbal medicine presents a promising adjunct or alternative approach in the management of chronic diseases. Its potential benefits, mechanisms of action, and limitations need to be carefully considered in clinical practice and research. Further scientific exploration and collaboration between traditional and modern medicine are crucial for evidence-based decision-making and improved patient outcomes.

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Keywords: herbal medicine, chronic diseases, management, alternative therapy, complementary therapy, benefits, mechanisms of action, limitations.

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ABSTRACT Purpose: First-ever mandatory regulations on corporate social responsibility in India were enacted by the Companies Act of 2013. All companies who have been covered under Section 135 of the Act are obligated to invest a specified percentage of their earnings towards socially conscious initiatives. The key objective of the present study is to examine the sample company's spending patterns of corporate social responsibility activities through the SWOT analysis framework. Design/Methodology/Approach: The present research is a case study of TCS Limited. The study used secondary data from the annual reports of the sample company, the Companies Act of 2013, and research articles on corporate social responsibility. Findings/Results: There is a higher level of compliance of corporate social responsibility provisions by the sample company. The CSR expenditure of the company on CSR activities show the rising trend during the study period. The company contributes major part of the mandatory amount to be spend on CSR related activities to the TCS Foundation. The company have been undertaking multi-year CSR project and progammes. Promotion of Health, Education and Skill enhancement in the local community are the prominent and prioritized CSR areas of the company. The study also identified good financial performance, duly compliance with CSR-related law, effective human capital, employee participation in CSR activities, and rich history of philanthropic engagement of the company as well as its parent company, and strategic CSR policies are the main factors that strengthen the CSR practices. Practical Implication: The findings of the current research study will facilitate understanding the effort of the sample company to address the social issues through its CSR activities. Originality/Value: This research will contribute to the corporate world in complying with CSR rules, designing the CSR policy of the company, and spending on needed activities on a priority basis. Paper Type: Company Analysis

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 Keywords

Corporate Social Responsibility, CSR, Legal framework, Spending pattern, SWOC/SWOT Analysis, Compliance

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The aim of this study is to review on poly herbal face pack for glowing skin by using natural herbal ingredients Papaya, Turmeric, Aloe vera, Orange peel, etc., Everyone wants beautiful, alluring skin today. Acne, pimples and postules are common among those who suffer from them. According to Ayurveda, skin problems are usually due to contamination of blood. Herbal face packs help to stimulate blood circulation, rejuvenate muscles, keep skin supple, and remove dirt from skin pores. The advantages of herbal cosmetics are their non-toxicity, reduced anti-disease reactions. Now a day, human skin has become more sentient for faster aging, atopic dermatitis, acne and many more skin related problems, which mainly arise due to increased pollution, microbe's etc. The present study shows the preparation, evaluation technique and different ingredients details used in formulation of polyherbal facepack also it shall be used for commercial purpose.

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Herbal face pack, Antibacterial, Natural, Saffron, Aloe vera.

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The pandemic caused by the COVID-19 epidemic has affected most sectors in the world. This includes academics, a world of millions of enrolled students and active teachers with a history of regular courses in institutions and was stuck at home due to the pandemic. An online class to continue the educational process was introduced in most countries including India. Both teaching and learning take place in this space with electronic devices relatively new to the entire teaching and learning community. It was the first time in India that online classes were conducted on this massive scale. During the start of online courses, various challenges for both teaching and learning communities there, but one thing is good that Internet is a major technological advance that shapes society, institutions as well as universities all around the world. Now, there are numerous virtual platforms are developed which are student friendly and learners centric. Here we will try to enumerate various online teaching-learning platforms and tools which play key roles for the learners (school and college students considering all regular/correspondence courses) in this era.

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Keywords - virtual platforms, learners, tools, online class, pandemic etc.

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Sentiment analysis, often a common topic of study in the nexus of NLP and ML is opinion mining. Computing techniques are used to analyse text for a sense of the author's emotional state. The capacity of machine learning methods to identify patterns and extract relevant characteristics from textual input has made them promising for use in sentiment analysis jobs. This paper offers a detailed comparison of the relative performance among the several machine learning methods that have been used for sentiment analysis jobs. We describe the metrics that measure how well different strategies perform across different domains and datasets, weigh their benefits and drawbacks, and provide insights into how well they perform overall. The goal of this research is to assist academics and professionals in selecting the top machine learning techniques for sentiment analysis tasks based on their particular requirements.

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sentiment analysis, public opinion, domains, and datasets etc.

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Amino acids are traditionally categorized based on their biochemical attributes. In this study, the focus shifts to reorganizing amino acids solely according to structural statistics, thereby mitigating existing chemical biases. The proposed machine learning model is to propose classification of the novel amino acid based on their structural insights. Main aim is to study the protein sequences of the candidates,that have been crystallized and their X-ray structures are well known and deposited in Protein Data Bank (PDB). Growth in available amino acids eventually slows down the speed of identifying the protein constituted by the number of amino acids. Hence, there is a requirement for an effective model to predict the secondary protein structure swiftly and accurately. This model has been designed to anticipate the protein's secondary structure through specific predefined tasks. Our Aim is to study the protein sequences of the candidates who have been crystallized and their X-ray structures are known and deposited in Research Collaboratory for Structural Bioinformatics (RCSB) PDB. The sequences of all the known crystal structures are to be downloaded from PDB and then a table is to be prepared based on occurrence of each amino acid on independent positions in the range of secondary structure. Once the data is ready, the noise must be removed accordingly, and the inferences will be made by polishing the data above a reasonable threshold. This focuses on forecasting the required parameters by analyzing the arrangement of amino acids and their neighboring context.

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Keywords--Amino acid classification, Random Forest Classifier, Machine Learning Model, Bioinformatics, Protein structure, Feature extraction, Feature selection, Sequence analysis, Structural insights, FASTA Sequence, RCSB, Protein Data Bank, Decision Tree, Cross-validation, Protein sequence analysis, Predictive modeling.

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In this paper, the Clinical Decision Support System employs a state-of-the-art of ML models, including Random Forest, Decision Tree, SVM, and Naive Bayes integrated into a user-friendly application developed with Streamlit. By leveraging the capabilities of OpenCV for voice processing, the system enhances diagnostic accuracy and expedites disease prediction. This innovative solution amalgamates advanced algorithms with intuitive voice recognition, creating a seamless and efficient platform for healthcare professionals. With its robust predictive capabilities and user-centric design, the system represents a significant advancement in medical decision support, demonstrating the synergy between artificial intelligence, user interface development with Streamlit, and image processing through OpenCV for a comprehensive healthcare solution.

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Clinical Decision Support System,Patient Case Similarity, Random Forest,SVM,Naive Bayes, Decision Tree,cdss,OpenAI,Symptoms, Disease Prediction, Open CV, AI , ML

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In Era of globalization where the sustainable technological developments are happening like a wild fire it is very important to manage stress as stress being an inevitable trauma in the present generation affect peoples' capacity and ability to perform especially in Women Employees. Women Employees cannot eradicate suffering, but can be influence healing process. Stress management practices must therefore get a new focus on facilitating the healing of emotional stress faced by Women Employees . The article is aimed at analyzing the causes of stress and testing the relationship between demographic factors and quality of work in women employees working from home in selected MNC's in Mysuru city. The study also aimed at showing the role of voluntary adoption of strategical practices to cope up with stress to enhance quality of work among women employees. An Experimental Study was conducted through structured questionnaire using statistical tools like One-way Anova and independent sample t testing, and it was revealed that there is a significant difference between demography and quality of work among women employees working from home and majority of the respondents agreed that there are certain factors which causes stress during working from home.

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Quality of work, Stress management, Work from Home (WFH)

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In light of the global discussion surrounding Industry 4.0 (I 4.0), this study looks into how manufacturing is changing in India and the problems that are making it hard to use advanced digital technologies in a smooth way. The study was made because I 4.0 has become more important because of its possible effects on society, the economy, and manufacturing. These effects have been made even more important by the COVID-19 pandemic, which has slowed down global businesses and supply lines. The main goal is to find out how ready Indian manufacturing companies are to work with Industry 4.0 plans. The study creates a strong tool called the "I 4.0 Maturity Model," which has seven categories and 34 maturity items. Exploratory case studies in auto-component, food processing, and electronics product manufacturing firms, along with a complete survey of 174 organizations in India's many manufacturing sectors, show that the model works in the real world. Investigating India's manufacturing landscape amidst the global Industry 4.0 discourse, this study addresses challenges hindering the integration of advanced digital technologies. Motivated by the pandemic's impact, the research focuses on assessing the readiness of Indian manufacturing for Industry 4.0. Introducing the 'I 4.0 Maturity Model,' validated through case studies and a survey involving 174 organizations, the study reveals a low maturity level, with sectors operating at 'Digital Novice' and 'Outsider' levels. Larger companies show higher readiness. Sectorial analyses highlight varied technology adoption, emphasizing barriers like capital investments and skills gaps. A three-phase roadmap offers insights, contributing a valuable self-assessment 'I 4.0 Maturity Model.' Recommendations aim to guide policy for successful adoption, not only in India but also for similar economies globally.

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 Keywords

Industry 4.0, Covid-19 Pandemic, Digital Novice, Recommendations, Manufacturing Sector

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