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 Authors are encouraged to submit complete unpublished and original works, which are not under review in any other journals.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> en-US abjar@vandanapublications.com (Prof. (Dr.) Sanjay Kumar Singh) abhishek@vandanapublications.com (Abhishek Shukla) Wed, 31 Jan 2024 00:00:00 +0000 OJS 3.3.0.7 http://blogs.law.harvard.edu/tech/rss 60 Study of Biodiversity Areas for Conservation in India https://abjar.vandanapublications.com/index.php/ojs/article/view/54 <p>Three broadly accepted claims in conservation biology are that the world's developing tropical countries will see the largest declines in biodiversity in the near future, that these regions are among the least studied globally, and that local community support is particularly important for protection in these regions. In assessing India's protected areas, we evaluate these generalizations. Most ecoregions in India are covered by the 5% of the country that is officially protected, and protected areas have played a significant role in the country's lack of reported species extinctions over the last 70 years. Future chances are improved by India's robust conservation-friendly laws, government investment in its 50 Tiger Reserves, and compensation programs that boost local support. However, connectivity and species utilization in buffer zones are important since many protected areas are too small to support a complete complement of species. The success and difficulties of conservation differ across regions based on their level of development. Protected areas with the greatest biodiversity are found in less developed regions, most notably the biodiverse northeast Himalaya, and are the product of localized efforts by committed individuals. We show that there is much potential for ecotourism to boost local income all around India. Our analysis validates the relevance of local support, growing dangers, and a deficiency of data. Particularly needed are studies on biodiversity in buffer zones, long-term monitoring plans, and an evaluation of the financial and environmental benefits of tourism. The creation of monitoring plans for "eco-sensitive zones" surrounding protected areas and a strong focus on maintaining already-established protected areas should be the two key objectives for policymakers.</p> Dr. Gargi Copyright (c) 2024 Dr Gargi https://creativecommons.org/licenses/by/4.0 https://abjar.vandanapublications.com/index.php/ojs/article/view/54 Mon, 29 Jan 2024 00:00:00 +0000 Public Key Encryption and Keyword Search Mapping https://abjar.vandanapublications.com/index.php/ojs/article/view/55 <p>This work addresses a difficult method for searching for crucial keywords for mixed cloud statistics (MRSE), which is a first step towards enabling secure cloud data processing. Among the different meanings of multiple terms, we choose the relevant concept of "relational coherence". Businesses can now more easily and affordably outsource a greater variety of products and services to community clouds thanks to cloud computing. To guarantee that sensitive personal data is kept enclosed before being supplied for their work. Given the enormous number of users of data and records in a search engine, it must be able to search for a specific phrase using numerous keyword searches and show a connection between them measure in order to successfully satisfy the demand of obtaining data. First, we suggest using the simple-to-use MRSE technique to protect a computer that contains internal objects. Real-world dataset experiments demonstrate that the suggested approaches do not significantly reduce the associated computing and communication expenses. One of the ways we effectively represent user information needs through optimization is by mapping feedback sessions to pseudo (fake) documents. Average precision (CAP) is a new metric used to assess the quality of the reconstructed online search results. Experiments with real data demonstrate that the suggested strategies have very little effect on transmission and computation. We extend these two methods to include more search semantics in order to enhance the search experience provided by the data search service.</p> Manoj Sharma, Akshay Gupta Copyright (c) 2024 Manoj Sharma, Akshay Gupta https://creativecommons.org/licenses/by/4.0 https://abjar.vandanapublications.com/index.php/ojs/article/view/55 Tue, 30 Jan 2024 00:00:00 +0000 Trajectory Data to Improve Unsupervised Learning and Intrinsic https://abjar.vandanapublications.com/index.php/ojs/article/view/56 <p>The three primary components of machine learning (ML) are reinforcement learning, unstructured learning, and structured learning. The last level, reinforcement learning, will be the main topic of this study. We'll cover a few of the more well-liked reinforcement learning techniques, though there are many more. Reinforcement agents are software agents that make use of reinforcement learning to optimize their rewards within a specific context. The two primary categories of rewards are extrinsic and intrinsic. It's a certain result we obtain after abiding by a set of guidelines and achieving a particular objective. An even better illustration of an intrinsic reward than money is the agent's enthusiasm to learn new skills that could come in handy later on.</p> Laxmi Gautam, Rajneesh Kumar Copyright (c) 2024 Laxmi Gautam, Rajneesh Kumar https://creativecommons.org/licenses/by/4.0 https://abjar.vandanapublications.com/index.php/ojs/article/view/56 Tue, 30 Jan 2024 00:00:00 +0000 A Setting Technique for Comparative Protein Modelling for Web based SMART Tool https://abjar.vandanapublications.com/index.php/ojs/article/view/57 <p>When the "hairless protein" linked to the hairless gene, which is necessary for hair growth, stops working, the result will be total hairlessness. This gene is located on chromosome 8 at locations 22027873-22045326. The hairless gene, which similarly aids in histone demethylation, is a member of the JmjC domain superfamily. With 1189 residues in the hairless protein, the domain sequence spans positions 946 to 1157 and is 212 amino acids long. JmjC domains have been identified in over 100 bacterial and eukaryotic sequences due to significant sequence similarity. Among them the human hairless gene, which is mutated in alopecia universalis sufferers. We have attempted to use the bioinformatics method to homology model the JmjC domain in the hairless protein. The tools and programmes used in this work are NCBI-BLASTP, EBIClustalW, SMART, 3D-PSSM, DeepView/Switzerland-PDB Viewer, PyMOL, and WhatCheck. The structure of the JmjC domain is predicted using the template crystal structure of the probable antibiotic biosynthesis protein from Thermus thermophilus HB8. The minimised energy value of the modelled domain structure was -3394.570 KJ/mol. The WHAT IF-Proteins Model Check tool was used to verify the simulated domain structure.</p> Mohd. Azyumardi Azra Copyright (c) 2024 Mohd. Azyumardi Azra https://creativecommons.org/licenses/by/4.0 https://abjar.vandanapublications.com/index.php/ojs/article/view/57 Wed, 31 Jan 2024 00:00:00 +0000