Volume 12 | Issue 3 |

 Abstract

Artificial Intelligence (AI) is a branch of computer science dedicated to creating systems that can perform tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, language understanding, and decision-making. AI algorithms are designed to analyze large amounts of data, recognize patterns, and make predictions or decisions based on that analysis. The goal of AI is to develop machines that can mimic human cognitive abilities and perform tasks more efficiently and accurately than humans. AI has applications across various industries, including healthcare, finance, transportation, education, and entertainment, and it continues to advance rapidly, driving innovation and reshaping the way we live and work.

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"ARTIFICIAL INTELLIGENCE AND ITS ASPECTICAL ANALYSIS"

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By ensuring product quality, safety, and efficacy, formulation development plays a crucial role in pharmaceutical research and is necessary for both therapeutic and commercial success. Up until and including market approval, the many components of formulation development interact with other phases in product development, such as discovery research. Every medication item requires a custom formulation because of the complexity of many routes that could impact product stability, the unique properties of the medicinal molecule, unique patient requirements, and even marketing concerns. Formulation development can be approached in a number of ways, relying on scientific theories and a logical design that applies these insights to thousands of components. This article reviews formulation development and explains pre-formulation and sop handling so that readers can understand the significance of these processes and recognize, respect.

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Formulation Development, Preformulation, SOP, Tablet, Evaluation.

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ABSTRACT Background: Physical Therapy plays an important role in the management of Knee Osteoarthritis (OA). Egoscue exercise is a form of corrective exercise, it is the most convenient method for treating recurrent musculoskeletal pain caused by ageing, accidents, sports injuries, and other disorders. Effectiveness of Egoscue exercise showed that there was marked reduction in knee pain, improvement in body-function and balance in individuals with knee osteoarthritis. Study Purpose: To evaluate the effectiveness of Egoscue exercise on Pain, Body-function and Balance in individuals with Knee Osteoarthritis. Basic Methods: Eighteen (n=18) individuals with grade 2 and grade 3 knee OA were recruited for this study. The individuals were taken according to inclusion criteria and received set of Egoscue exercise for 5days/week for about 3 weeks. The outcome measures were numeric pain rating scale(NPRS), knee injury and osteoarthritis outcome score(KOOS), lower quarter Y balance test(YBT-LQ) assessed at pre and post intervention. Main Results: The study showed statistically significant difference between pre and post treatment within subjects with knee OA after 3 weeks of intervention in pain, body-function and balance in terms of NPRS(p value<0.001), KOOS(p value<0.001), YBT-LQ (p value<0.001) which is highly significant. Principal Conclusion: Egoscue corrective exercises considerably decreased pain in participants with OA knees while also enhancing bodily function and balance. However no discernible changes in the YBT-LQ test for balance in the posteromedial direction of the right leg was noted.

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Keywords: Balance; Body-function; Egoscue Exercises; Knee Osteoarthritis; Knee Pain

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The "Generative Neural Networks Novel Image Generation" project aims to expand the creative and generative capabilities of neural networks beyond traditional discriminative models. In previous contexts, mostly neural networks been utilized for tasks involving input-to-output mappings, such as image classification and text generation. However, this project delves into the realm of generative models, where the focus shifts from making decisions to creating entirely new and unique creative content. At its core, the project equips neural networks that have the power to craft images that encapsulate the style and essence of existing training data. This synthesis of new, yet familiar, visual content introduces diversity and creativity. Beyond artistic value, the project holds practical value in data augmentation, offering a solution to data scarcity by generating synthetic content that can enhance machine learning model performance. The impact of this project extends across industries. In healthcare, it assists medical image analysis by generating realistic data for algorithm training. In fashion, it aids design by creating new patterns and styles. Moreover, the project also addresses data privacy concerns, enabling information sharing without compromising sensitive details. By forging a bridge between technology and creativity, the "Generative Neural Networks to create Innovative Images Generation" project innovation enriches data science. Furthermore, the project underscores the significance of synthetic data in addressing data scarcity and privacy concerns. Synthetic data has the potential to supplement real datasets in scenarios where access to authentic data is limited or protected

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Generative Neural Networks, Novel Image Generation, Creative, Data Augmentation, Synthetic Content, Data Security, Healthcare, Fashion.

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The present study sought to analyze the Indian Research Information Network System (IRINS) instances with particular reference to universities in Tamil Nadu. The study explores the resource impact from scholarly resources, the contributions of top of individual Tamilnadu universities, the h-index, the top faculty of respective state universities, and the h-index. The study finding shows that Annamalai University holds the highest faculties, 1095 (30.25%). Tamil Nadu Agriculture University has the highest 12736 scholarly publications among the state universities of Tamil Nadu state, with Scopus citation 27944 and Crossref citation 22057. Anna University has the highest h-index 942 among the state universities in Tamil Nadu state. Prof. Madhukar Hemamalini (Mother Teresa Women's University) has the highest 527 scholarly resources and Prof. Muthusamy Lakshmanan from Barathidasan University has the highest 9801 Scopus citations and 8988 crossref citations with 50 h-index among the state university faculty members in Tamilnadu

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IRINS, State Universities, INFLIBNET, Tamil Nadu

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The study employs a quantitative approach to estimate the factors affecting the performance of Exchange-Traded Funds (ETFs) concerning Equity Mutual Funds. This study provides both quantitative and qualitative results The study utilizes secondary data, specifically net asset value (NAV) of equity mutual funds and Jakarta Composite Index, obtained from the official websites of Financial Service Authority and Indonesia Stock Exchange. Additionally, data related to ETFs and equity mutual funds, specifically NAV, is collected from various sources like the Association of Mutual Fund in India (AMFI) and financial websites such as Money Control, Growth, and ET Money. The risk taken by the investor return earned through the investment. To evaluation of the performance of equity mutual fund and ETF, after consideration of the return earned for risk incurred by the investor, various risk adjusted performance parameters such as Sharpe Ratio, Jensen's Alpha, Beta, Treynor ratio and Sortino ratio. The findings suggest that the performance drivers differ between Mutual Funds and ETFs. For Mutual Funds, risk plays a crucial role, while for ETFs, both volatility and fund selection skill are significant factors. This information can be valuable for investors seeking to optimize their portfolio based on the specific characteristics of these investment vehicles.

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Mutual Fund, Exchange Trade Fund, Affecting Performance, Factor Analysis, Risk adjusted performance, Qualitative Study

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Abstract:The Dimethoate is one of the pesticide most widely used in agriculture sector in Maharashtra to control the varieties of pests and ectoparasites. The acute toxicity bioassay tests were conducted at various concentrations ranging from 5.0 and 13.0 mg/l freshwater fish, Rasbora daniconius for 24, 48, 72 and 96 h. The acute toxicity values were determined as 11.58, 10.25, 10.63 and 9.13 ppm respectively under laboratory conditions respectively. These LC50 values showed that the chemical is highly toxic to the fish. Then the fish were exposed to sub lethal concentrations 96 h LC50 9.13 ppm and studied the significant changes in glycogen, Protein and lipid levels of the fresh wet tissues. In the present investigation glycogen content of muscle, gill, liver and kidney as 12.78, 9.01, 42.30 and 11.12 mg/gm/wet.wt of tissues respectively. In Protein content of muscle, gill, liver and kidney as 18.04, 10.39, 15.85 and 10.02 mg/gm/wet.wt of tissues respectively and lipid content of muscle, gill, liver and kidney as 59.01, 49.23, 68.01 and 55.25 mg/gm/wet.wt of tissues respectively. In glycogen, protein and lipid content decreases in all tissues when compared with the control group.

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Keywords: Glycogen, Protein, Lipid, Rasbora Daniconius, Dimethoate.

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In recent years of research, it has been discovered that noble metal nanoparticles, due to their exceptional optical properties, have unique applications in nanoscience. Scientists believe that plasmonic nanoparticles can be utilized as nano heaters, opening new avenues of research at the nanoscale. Plasmonic nanoparticles act as nano heaters that can be controlled remotely by light, resulting in the emergence of an evolving field known as Thermoplasmonic. The goal of all Thermoplasmonic applications is to significantly improve the photothermal conversion of plasmonic nanoparticles, but different sizes of nanoparticles present challenges. The present paper describes the photothermal effect induced by plasmonic nanoparticles of different nano geometry that act as nano sources of heat. Further, basic understanding and some simulation techniques for measuring the heat unleashed by plasmonic nanoparticles at the nanoscale order, as well as recent advances summarized for the application of Thermoplasmonic, specifically to biomedical applications using the photothermal effect, particularly for photothermal cancer therapy, drug and gene delivery, photothermal imaging, and nano-surgery

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Nanoparticles, Plasmonic, Thermoplasmonic, Heat generation

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Creative Commons Attribution 4.0 and The Open Definition

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Digital technology has become an indispensable component of modern education, revolutionizing the learning process in profound ways. This research paper provides an in-depth examination of the multifaceted role of digital technology in shaping contemporary learning environments. Through an extensive review of existing literature, this paper explores the impact of digital technology on student engagement, pedagogical practices, educational outcomes, and the overall learning experience. Additionally, it addresses the challenges and opportunities associated with the integration of digital technology in education, including issues such as access, equity, privacy, and security. By synthesizing current research findings and best practices, this paper aims to provide valuable insights into how digital technology can be effectively leveraged to enhance teaching and learning in the digital age.

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Digital technology, learning process, education, student engagement, pedagogy, challenges, opportunities

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Creative Commons Attribution 4.0 and The Open Definition

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This project conducts a comprehensive financial performance analysis of Happiest Minds Technologies Limited, a leading IT company specializing in digital transformation services. The study employs various analytical tools, including ratio analysis, trend analysis, correlation, regression, and standard deviation, to evaluate the company's profitability, operational efficiency, solvency, and liquidity. Key findings indicate that Happiest Minds has exhibited strong profitability, as evidenced by consistent and robust net profit margins and an increasing trend in earnings per share (EPS). However, challenges exist in asset utilization efficiency, as indicated by a declining trend in return on assets (ROA). Additionally, fluctuations in solvency ratios highlight the need for a balanced capital structure to mitigate financial risks effectively. The study concludes with recommendations for Happiest Minds to enhance asset utilization, strengthen short-term liquidity, optimize capital structure, manage variability in financial metrics, and base strategic decisions on thorough financial analysis. Overall, while the company has demonstrated resilience and profitability, continuous monitoring and strategic financial management are essential to sustain long-term growth and profitability in a dynamic market environment.

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Happiest Minds Technologies Limited, Financial performance analysis, Profitability, Operational efficiency, Solvency, Liquidity, Ratio analysis, Trend analysis, Asset utilization efficiency Strategic decisions.

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