Volume 12 | Issue 9 |

 Abstract

This study investigates the role of corporate governance in shaping the financial reporting quality and overall financial performance of Aditya Birla Grasim Industries, a leading Indian conglomerate. By analysing the board composition, audit committee effectiveness, and executive compensation, the research examines how these governance practices influence key financial indicators such as Return on Equity (ROE), Return on Assets (ROA), and Earnings per Share (EPS). Utilizing a quantitative research approach, the study employs regression analysis to evaluate the relationships between governance variables and financial outcomes. The findings reveal that strong corporate governance, characterized by a balanced board and effective audit practices, positively impacts financial reporting quality and enhances company performance. These insights underscore the importance of continuous improvements in governance practices to sustain financial stability and investor confidence

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Corporate governance Financial reporting quality Financial performance Aditya Birla Grasim Industries Board composition Audit committee effectiveness Executive compensation Return on Equity (ROE) Return on Assets (ROA) Earnings per Share (EPS) Quantitative research Regression analysis Governance variables Financial outcomes Balanced board Audit practices Financial stability Investor confidence

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Chlor-alkali industry, Solid waste, SWE, Toxicity, Behavioural study, Enzyme, ions

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 Abstract

The ozone hole found over the Earth's poles, for example in Antarctica, has no connection with the actual stratospheric ozone layer but is closely related to other atmospheric components (Aerosols, Gases, water vapour, SO2, NO2, OH, NH3, CH4, N2O, SO3, H2O, CO2, HOCl, etc.). Because they are primarily affected by temperature, as a result, the level of solar radiation increases for some time because these atmospheric components mainly absorb or interfere with ultraviolet radiation after oxygen and ozone layer. When the temperature becomes extremely low, the states of these atmospheric components changes and they reduce or stop affecting the radiation. And as soon as the polar vortex ends and the temperature there gradually increases, they again return to the gaseous states and start affecting the radiation. As a result, the amount of solar radiation reaching the surface decreases. Therefore, it is clear that atmospheric components are affected due to extremely low temperature, which increases the level of solar radiation, but this increased radiation has no direct connection with the ozone layer.

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Ozone Hole, Ozone Layer, Atmospheric Components, Polar Stratospheric Cloud.

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Organization of Petroleum Exporting Countries (OPEC) and its allies agreed to historic production cuts to stabilize prices, For several decades, the OPEC has been the major player and its move has been watched closely by various nations, leading upstream companies, ONGC (Oil and Natural Gas Corporation) is a domestic Indian oil company involves in upstream industry doing E&P activities such as producing crude oil, natural gas and other value added petroleum products. The company's revenue depends upon the changes in international crude oil prices therefore, it watches closely the crude oil market.ONGC's Crude oil sales dependent upon world benchmark Crude Oil Prices viz. Dated Brent price , WTI (West Texas Intermediate) Cushing Mo01 price, Bonny Light FOB Nigeria London price in terms of USD per barrel. This study shows the relationship of changes in world benchmark prices have an impact on ONGC's domestic crude oil sales in terms of crore.

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 Keywords

Crude Oil (petroleum), Dated Brent price , US $ per barrel, WTI (West Texas Intermediate) Cushing Mo01 price, Bonny Light FOB Nigeria London, Oil Market and Benchmark.

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Pollination transfers pollen grains from a blossom's male anther to its female stigma the process of pollination incorporates all events from maturation to zygote division. Honeybees are primary pollinators for the majority of the world's angiosperms, pollinating about 66% of the world's 1500 crop species accounting for 15-30% of food production, (ollerton etal., 2012) honeybees have proved to be effective pollinators of a variety of crops including horticultural crops, oilseeds, forage crops, fibre crops and cereal crops (Rahman, 2006). Bees are the champion pollinators in fruit crop production. However, honeybees are still more important to farmers because of their pollination service, which increase the crop yield, (Sharma et al., 2015). Honeybee pollinators directly (or) indirectly provide 30 percent of the world's food supply.

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Honeybee, Pollination activity, Crop yield, Enhancement of Honeybees.

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 Abstract

DHERADUN JANPAD KE MADHYAMIK STAR PR ADHYANRAT VIDHYARTHIYO KI SAIKSHIK UPLABDHI KA TULNATMAK ADHYAYAN

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DHERADUN JANPAD KE MADHYAMIK STAR PR ADHYANRAT VIDHYARTHIYO KI SAIKSHIK UPLABDHI KA TULNATMAK ADHYAYAN

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Fuzzy systems are mathematical frameworks for dealing with uncertainty and imprecision, which are common in real-world applications. Matrix-based approaches provide a powerful toolset for the analysis and implementation of fuzzy systems. This paper explores the theory behind matrix- based approaches to fuzzy systems, their computational advantages, and a range of applications in various fields such as control systems, decision-making, and pattern recognition.

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Matrix, Fuzzy

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Artificial Intelligence (AI) is increasingly becoming a transformative force in the healthcare sector, driving innovations in diagnostics, treatment personalization, and operational efficiencies. This paper examines the significant impact of AI technologies, such as machine learning, deep learning, and natural language processing, on healthcare delivery. AI enhances diagnostic accuracy, facilitates personalized treatment plans, and accelerates drug discovery processes, potentially leading to improved patient outcomes and reduced healthcare costs. However, the integration of AI in healthcare also presents challenges, including concerns over data privacy, algorithmic biases, and the need for robust ethical guidelines. This research synthesizes current literature and analyses real-world data to assess AI's benefits and limitations in healthcare settings. The findings underscore AI's potential while highlighting key areas that require careful consideration for its effective implementation in medical practice.

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Artificial Intelligence, Healthcare Technology, Diagnostic Accuracy, Personalized Medicine, Machine Learning, Drug Discovery, Data Privacy, Algorithmic Bias, Ethical AI

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The rise of AI-powered automation is reshaping job markets worldwide, presenting both opportunities and challenges. AI has the capability to streamline repetitive tasks, improving operational efficiency and reducing the necessity for human involvement in specific positions. This article delves into the dual impact of AI on employment markets, with a focus on its potential to replace certain jobs while creating demand for new skills and roles. Sectors like manufacturing, retail, finance, and healthcare are undergoing significant transformations as AI drives changes in the nature of work. While AI has the potential to boost productivity and innovation, it also poses challenges for low-skilled workers who may face displacement. Conversely, AI is stimulating the growth of high-skilled roles, particularly in areas related to AI development, programming, and system maintenance. This research aims to provide a comprehensive examination of the influence of AI-driven automation on employment patterns. It will analyse both the short-term and long-term impacts on various sectors, concentrating on the skills gap, patterns of employment, and economic consequences. The study also underscores the importance of initiatives to retrain and enhance the skills of workers to prepare for a technology-driven future. Through factual data and analysis, this article underscores significant trends in job displacement, the emergence of new roles, and the socio-economic impact of AI integration. The findings indicate that a balanced approach, combined with effective retraining programs and policy measures, can help mitigate the risks associated with job displacement while maximizing the benefits of AI-driven automation.

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AI-powered automation, job markets, employment trends, job displacement, skills gap, retraining, workforce transformation, AI integration.

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This research proposes a cutting-edge hybrid framework integrating difference equations and neural networks for efficient signal analysis, with applications in moment theory. The study addresses the limitations of traditional signal processing methods by leveraging the strengths of mathematical modeling and machine learning. A novel difference equation-based approach is developed to extract salient features from signals, which are then utilized to train a neural network for improved pattern recognition and classification. Theoretical foundations in moment theory are established to ensure robustness and accuracy.

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Creative Commons Attribution 4.0 and The Open Definition

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Signal Analysis, Difference Equations, Neural Networks, Moment Theory, Hybrid Framework, Feature Extraction, Anomaly Detection

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