Applied Science and Biotechnology Journal for Advanced Research https://abjar.vandanapublications.com/index.php/ojs <p>Applied Science and Biotechnology Journal for Advanced Research is a Peer-Reviewed &amp; Refereed open access bimonthly international journal publishing original research papers / articles from all the fields of applied science and biotechnology subjects. Authors are encouraged to submit complete unpublished and original works, which are not under review in any other journals. </p> <p><strong>JOURNAL PARTICULARS</strong></p> <p><strong>Title:</strong> Applied Science and Biotechnology Journal for Advanced Research<br /><strong>Frequency:</strong> Bimonthly (6 issue per year)<br /><strong>ISSN (Online):</strong> <a href="https://portal.issn.org/resource/ISSN/2583-553X" target="_blank" rel="noopener">2583-553X</a><br /><strong>Publisher:</strong> <a href="https://www.vandanapublications.com/" target="_blank" rel="noopener">Vandana Publications</a>, Lucknow, India (Registered under the Ministry of MSME, Government of India with the registration number “UDYAM-UP-50-0046532”)<br /><strong>Chief Editor:</strong> Prof. (Dr.) Sanjay Kumar Singh<br /><strong>Copyright:</strong> Author<br /><strong>License:</strong> Creative Commons Attribution 4.0 International License<br /><strong>Starting Year:</strong> 2022<br /><strong>Subject:</strong> Applied Science and Biotechnology<br /><strong>Language:</strong> English<br /><strong>Publication Format:</strong> Online<br /><strong>Contact Number:</strong> +91-9696045327<br /><strong>Email Id:</strong> abjar@vandanapublications.com<br /><strong>Website:</strong> <a href="https://abjar.vandanapublications.com">https://abjar.vandanapublications.com</a><br /><strong>Registered Address:</strong> 78/77, New Ganesh Ganj, Lucknow-226018, Uttar Pradesh, India.</p> Vandana Publications en-US Applied Science and Biotechnology Journal for Advanced Research 2583-553X A Review Study on Insecure Food Habits and its Impact on Health & Healthcare https://abjar.vandanapublications.com/index.php/ojs/article/view/65 <p>Health is primary matter for every individual, to large extent it has to be a primary matter. Healthcare is immensely required elements for human being. It has the potential of scaling up towards business avenues. Health is such an issue that gets attention of States and Central government primarily to the extent that the local authorities are also involved. Healthcare Entrepreneurship has always been the massive support to the Economic growth. Healthcare Entrepreneurship wasn’t potentially the preferred choice however the advent of the Pharmacy Courses and the avenue of online operations in Pharmacy sector gave a good boost to the Healthcare sector. Food habits eventually have an impact on the health and insecure food habit destroys the physical &amp; mental health of human being. Insecure food habits is characterized by limited access to nutritious and safe food, have emerged as a pressing public health concern worldwide.</p> <p>This review study comprehensively examines the intricate relationship between insecure food habits and their profound impact on health and healthcare systems. Drawing upon secondary data investigations, this study explores the multifaceted repercussions of food insecurity on various dimensions of health, encompassing nutritional deficiencies, chronic diseases, mental health disorders, and overall well-being. Through a systematic analysis of existing literature, this review underscores the urgent need for targeted interventions and policy measures to alleviate food insecurity and mitigate its adverse health outcomes. This study provides valuable insights to inform evidence-based strategies aimed at promoting health equity and enhancing the resilience of healthcare systems in the face of food insecurity challenges.</p> Pooja Patel Dr. Rajesh Kumar Pandey Copyright (c) 2024 Pooja Patel, Dr. Rajesh Kumar Pandey https://creativecommons.org/licenses/by/4.0 2024-05-15 2024-05-15 3 3 1 7 10.5281/zenodo.11195957 A Study on Deep Learning Architectures and Dimensionality Reduction Techniques on Gene Expression Data https://abjar.vandanapublications.com/index.php/ojs/article/view/64 <p>Genomics, driven by the evolution of high-throughput sequencing and microarray technologies, has become one of the key inventions of cracking the secrets of complex biological systems. The deep learning architecture not only provides with a powerful tool to derive the hidden insights from the huge amount of genomic data, but also enables to mine meaningful information. In this study, we will examine the application of deep learning methods in the analysis of genomics data, specifically on dimensionality reduction and predictive modeling for binary phenotypes. We focus on the problems with the existing strategies, spot the avenues for the further research, and provide you with a glimpse of the dramatic influence of deep learning on genomics. In this study, we delve into the application of deep learning methods in the analysis of genomic data, with a specific focus on two crucial aspects: dimensionality reduction and predictive modeling for binary phenotypes. Dimensionality reduction techniques are essential for tackling the high-dimensional nature of genomic data, where thousands or even millions of features (e.g., gene expressions, genetic variants) are measured for each sample. Deep learning models can effectively capture the complex relationships and patterns within this high-dimensional space, enabling the extraction of lower-dimensional representations that preserve the most salient information. Throughout this study, we critically examine the existing strategies and approaches in the field of genomics, identifying their limitations and highlighting the avenues for further research. We explore how deep learning can address these challenges and provide a glimpse into the dramatic influence this technology is poised to have on the field of genomics.</p> Remyamol K M Philip Samuel Copyright (c) 2024 Remyamol K M https://creativecommons.org/licenses/by/4.0 2024-05-17 2024-05-17 3 3 8 13 10.5281/zenodo.11211521 Development and Characterization of Pili (Canarium ovatum Engl.) Wine https://abjar.vandanapublications.com/index.php/ojs/article/view/59 <p>This study aimed to estimate the potential of pili (<em>Canarium</em> <em>ovatum</em> L.) pomace as substrate for the production of fruit wine. The pili fruit wine was characterized in terms of physico-chemical characteristics (pH, TSS and alcohol content) and consumer acceptability level (appearance, taste, aroma, mouthfeel and overall acceptability). It was produced using 5%, 10% and 15% pili pomace as Treatment 1, 2 and 3, respectively. Results showed increase in alcohol content and TSS with increase in concentration of pili pomace while there is decrease in pH as concentration of pili pomace is increased. It was also observed that there is a gradual decrease in total soluble solids and pH and a gradual increase in alcohol content as fermentation time proceeded. Thirty (30) sensory panelists rated pili fruit wine as highly acceptable as commercial wine. Results of the consumer acceptability survey of the pili wine obtained an average rating of 7.71 in overall acceptability which can be interpreted as high liking for the product. Except for appearance, consumer acceptability results of pili fruit wine did not show any significant differences (at 0.05 significance level) in terms of taste, aroma, mouthfeel and overall acceptability when compared to commercial wine.</p> Robelle M. Tapado Copyright (c) 2024 Robelle M. Tapado https://creativecommons.org/licenses/by/4.0 2024-05-21 2024-05-21 3 3 14 19 10.5281/zenodo.11229377