EMPIRICAL ANALYSIS OF THE ROLE OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCES RECRUITMENT AND SELECTION

This study provides an empirical evaluation of AI's function in the field of human resources (HR) hiring and selection. Human resources departments may save time and effort by using sophisticated algorithms and machine learning to efficiently sort through piles of applicants and make well-informed decisions. The potential for AI to lessen the prevalence of unconscious bias in the recruiting process is an especially particular advantage. Furthermore, the incorporation of AI into the recruiting process has improved the candidate experience via the use of real-time interaction technologies such as chatbots. Despite its benefits, integrating AI into HR is not without its share of difficulties, most notably protecting employee data and avoiding becoming too dependent on digital tools. The research highlights the need of a unified strategy, which strikes a balance between the efficacy of AI and that of human judgment

Depression and its Association with Housing conditions and Family among Pregnant Women of Rural Varanasi

Background: Depressive disorders were the second leading cause of years lost due to disability in 2010 after low back pain and leading cause of disability adjusted life years (WHO 2010). Gestational depression may lead to low birth weight, premature births etc. Housing and family are important aspects of one daily life which if are unsatisfactory can increase stress level of its members. Aims & Objectives: The aim of this study is to see the relationship of housing and family with depression among pregnant women. Material & Methods: This is a community based cross sectional study of 220 pregnant women in 10 randomly selected villages of Chiraigaon, Varanasi, Uttar Pradesh during one year period; using predesigned, pretested and semi structured interview schedule for assessing housing and family conditions. Results: Depression was found to be more in women living in kutcha house, nuclear family and illiterate husband, husband as head of family and belonging to lower socio-economic status. Increasing number of female child also increases depression. Conclusion: Housing structure, education of husband, socio-economic status and number of daughters should be assessed in every pregnant woman as these affect depressive state of pregnant women which can adversely affect the outcome of pregnancy

ENTREPRENEURIAL MINDSET IN MODERN APPAREL: THE ROLE OF MACHINE LEARNING IN DRIVING SUSTAINABLE INNOVATION

The apparel industry is on the cusp of a significant transformation, driven by an entrepreneurial spirit that embraces innovative approaches and sustainable practices. This study investigates the incorporation of ML in the contemporary apparel industry, highlighting its potential to promote transformative sustainable practices. Focusing on garment firms, the study demonstrates how ML is being used to be Source eco-friendly materials, reduce waste ,improve energy efficiency, increase supply chain transparency. The study also draws on qualitative insights from industry experts to identify the possibilities and challenges of integrating ML within the apparel industry. Overall, the study highlights the paradigm shift underway in the apparel industry, driven by an entrepreneurial mindset and facilitated by ML technology. This study functions as a guiding light, directing policymakers, industry leaders, and academics towards the advancement of a balanced integration of ML and sustainable entrepreneurship in modern apparel practices

Nutrition Information Post COVID-19: A twitter content analysis

Realizing social media's importance, many doctors, nutritionists, health coaches and general users have registered on social media and actively share health information. Users may easily access and exchange health information. It benefits both users and practitioners. Qualitative data analysis is employed to study Twitter communication content to understand better the relationship between users’ interest in healthy eating. The research examined Twitter nutrition health information using hashtags. The frequency of hashtags was ranked. The content analysis quantifies social media healthy diet hashtags. Theme modification and word and phrase recurrence analysis to identify two primary themes and significant sentiments relating to Covid-19 and nutrition. Python and NLP are used to analyze and interpret the data to help acquire in-depth information

16S rRNA Long-Read Sequencing of the Granulation Tissue from Nonsmokers and Smokers-Severe Chronic Periodontitis Patients

Smoking has been associated with increased risk of periodontitis. The aim of the present study was to compare the periodontal disease severity among smokers and nonsmokers which may help in better understanding of predisposition to this chronic inflammation mediated diseases. We selected deep-seated infected granulation tissue removed during periodontal flap surgery procedures for identification and differential abundance of residential bacterial species among smokers and nonsmokers through long-read sequencing technology targeting full-length 16S rRNA gene. A total of 8 phyla were identified among which Firmicutes and Bacteroidetes were most dominating. Differential abundance analysis of OTUs through PICRUST showed significant (p>0.05) abundance of Phyla-Fusobacteria (Streptobacillus moniliformis); Phyla-Firmicutes (Streptococcus equi), and Phyla Proteobacteria (Enhydrobacter aerosaccus) in nonsmokers compared to smokers. The differential abundance of oral metagenomes in smokers showed significant enrichment of host genes modulating pathways involving primary immunodeficiency, citrate cycle, streptomycin biosynthesis, vitamin B6 metabolism, butanoate metabolism, glycine, serine, and threonine metabolism pathways. While thiamine metabolism, amino acid metabolism, homologous recombination, epithelial cell signaling, aminoacyl-tRNA biosynthesis, phosphonate/phosphinate metabolism, polycyclic aromatic hydrocarbon degradation, synthesis and degradation of ketone bodies, translation factors, Ascorbate and aldarate metabolism, and DNA replication pathways were significantly enriched in nonsmokers, modulation of these pathways in oral cavities due to differential enrichment of metagenomes in smokers may lead to an increased susceptibility to infections and/or higher formation of DNA adducts, which may increase the risk of carcinogenesis

Abstracts of National Conference on Biological, Biochemical, Biomedical, Bioenergy, and Environmental Biotechnology

This book contains the abstracts of the papers presented at the National Conference on Biological, Biochemical, Biomedical, Bioenergy, and Environmental Biotechnology (NCB4EBT-2021) Organized by the Department of Biotechnology, National Institute of Technology Warangal, India held on 29–30 January 2021. This conference is the first of its kind organized by NIT-W which covered an array of interesting topics in biotechnology. This makes it a bit special as it brings together researchers from different disciplines of biotechnology, which in turn will also open new research and cooperation fields for them. Conference Title: National Conference on Biological, Biochemical, Biomedical, Bioenergy, and Environmental BiotechnologyConference Acronym: NCB4EBT-2021Conference Date: 29–30 January 2021Conference Location: Online (Virtual Mode)Conference Organizer: Department of Biotechnology, National Institute of Technology Warangal, Indi