Volume 13 | Issue 1 |

 Abstract

One of the most well-established ways for improving athletic performance, specifically with respect to endurance sports, is through altitude training. Systematic review is synthesized to provide findings from multiple studies that examine the impact of different altitude training models including 'live high, train low' (LHTL) and 'live high, train high' (LHTH) in endurance athletes. However, within and between studies, the outcomes were highly variable and were influenced by both individual variability and genetics, and there was a high degree of consistency across studies in terms of key physiological changes such as improved oxygen transport and ventilatory acclimatization. Most research confirms that altitude training improves endurance performance, but the exact time of exposure and duration, as well as athlete specific responses, are key factors in maximizing its benefit. Altitude training protocols still need further research to refine them and maximize performance outcome in a wide range of endurance sports.

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 Keywords

Altitude, Endurance, Athletes, Physiological Adaptations, Performance

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Leveraging Computer Simulations for Ethical and Efficient Drug Testing The reliance on animal experimentation in drug testing faces increasing scrutiny due to ethical, scientific, and economic challenges. Computer simulations, powered by advancements in artificial intelligence (AI), provide a transformative alternative to traditional methods by offering precision and innovation in drug development. This project explores the development of predictive models that leverage comprehensive datasets--spanning chemical compositions, biological activities, and human reactions--to forecast drug efficacy and safety with accuracy. Beyond predictive modeling, computer simulation in drug testing delivers a comprehensive and critical examination of current and emerging research on designing and developing advanced drug delivery systems. These systems focus on physicochemical principles which are engineered to address specific therapeutic needs in both experimental and clinical settings. By illustrating the pivotal role of a multidisciplinary approach, this project underscores the integration of biology, chemistry, and physics in optimizing drug delivery systems. By minimizing animal testing, accelerating drug development timelines, and enhancing safety profiles, this project provides a more ethical and efficient framework for drug testing. The combination of cutting-edge simulations and multidisciplinary expertise ensures the delivery of safer and more effective therapeutic solutions, revolutionizing the future of drug development.

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 Keywords

Artificial intelligence (AI), Drug testing, Ethical alternatives , Predictive modeling, Animal testing alternatives

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The essence of guidance is to help a person understand himself and understand his abilities and limitations . With the help of guidance, a person is able to work at his level. With the help of guidance, a person can solve his problems and prepare for the problems that lie ahead.

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Mean Consept process importance of Direction

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Abstract In Indian culture morality is inextricably related with dharma and take the form of dharmaniti. Dharma is that which upholds the man, the society and above all the universe. On the other hand, morality is not just a bundle of few rules or principles designed for living a life with material or sensual pleasure, rather a behavioural pattern or style for healthy, disciplined and righteous life mingled with a feeling of empathy and compassion. The prime aim of dharmaniti is to serve the most and absolute well-being of each and every member of this universe and any violation of this dharmaniti, provoked by evil inclinations, leads to unwanted harmful adverse effects. Basically, In Indian context dharma designated as right conduct, following which morality is fully revealed within a man. In this article, I am trying to deal with certain aspects of the very concept of this dharma as it has been referred in Indian philosophical tradition.

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Keywords -Dharma, morality, sad?c?ra, ?ta, peace, co-existence.

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Transforming India's banking landscape is underway. The Reserve Bank of India (RBI) envisions payment banks as a solution to serve low income households and small businesses by offering low-cost savings accounts and remittance services. The goal is to help individuals reliant on cash transactions transition to formal banking. While opening branches in every village might be expensive for traditional banks, the widespread availability of mobile phones offers a cost-effective way to deliver basic Banking services to rural areas. This initiation is also accelerate India's move towards a cashless economy. The domestic remittance market estimated at around Rs. 800-900 billion, is growing and mobile based money transfers could capture a significant portion, particularly for migrant workers. Payment banks will also support the Government's direct benefit transfer program by channeling subsidies for healthcare, education and gas directly into beneficiaries' accounts. Notably, this marks the first time private business groups have received RBI approval for banking services since nationalization. This paper explores the objectives of payment banks, the opportunities they present, and the challenges facing India's evolving banking system.

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Banking services, Cashless economy, Nationalization, Traditional banks

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Drones, otherwise known as unmanned aerial vehicles, are revolutionizing the field of agriculture, logistics, disaster management, and environmental monitoring. Such systems come with advanced AI-driven technologies for real-time data analysis and precision operations alongside autonomous navigation capabilities unseen before while offering unprecedented efficiency and reliability. Recent trends in developing obstacle avoidance systems, edge computing, hybrid drones, and swarming capabilities have highly enhanced the functionality of drones. With these advancements, drones can now be used for crop health monitoring and precision spraying, medical supply delivery, or search-and-rescue operations. Yet, most of these problems remain with drones: limited battery life, regulatory obstacles, and security issues. Lighter materials, alternative sources of energy, and secure communication protocols are on the horizon and could help solve most of these issues. This paper explores the current progress, implementations, and difficulties related to the advancement of drone technology. It looks at its revolutionary role in serving the demands of the present and opening new paths for growth and integration.

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Applications of Drones, AI-Guided Drone Navigation, Drone Environmental Stability, Multimodal Systems.

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This paper explores the growing landscape of caste, class, and social justice in West Bengal, focusing on the period under Mamata Banerjee's leadership. The state has long been a site of complex sociopolitical dynamics, with entrenched caste hierarchies and socioeconomic disparities shaping its political discourse. This study delves into the state's reservation policies and examines their role in addressing the needs of marginalized communities, including Scheduled Castes (SCs), Scheduled Tribes (STs), and Other Backward Classes (OBCs). Since 2011, West Bengal's approach to social justice has developed from class-based policies under the CPI (M) to a more caste-conscious framework under the Trinamool Congress (TMC). Mamata Banerjee's government has expanded reservation benefits for OBCs, especially Muslim communities, because of her political benefits in the election as there are no constitutional provisions for religious based reservation in India. A total of 97 Muslim castes were included in the list of OBCs in Categories A and B. The paper also highlights the legal complexities surrounding these policies, including the 2024 Calcutta High Court ruling that invalidated the OBC status of Muslim communities, which sparked intense political debate. West Bengal's reservation system fosters inclusion; however, a new study reveals its limitations and contradictions, particularly the conflict between economic equality and caste-based justice. West Bengal's complex interplay of caste, political power, and social justice is further examined through key legal and political milestones. The evolving trajectory of social justice in West Bengal, a product of political and legal influences, highlights valuable lessons on the intricate relationships between caste, class, and policy-making in modern India.

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Marginalized Castes, Other Backward Classes (OBCs), Social Justice, Reservation Policy, Politics, Muslims, Calcutta High Court, Supreme Court of India, Mandal Commission. Trinamool Congress (TMC), Bhartiya Janta Party (BJP), CPI(M), Indian National Congress (Indira).

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Viral diseases pose a significant threat to global health, with a vast array of viruses infecting humans and animals, causing widespread morbidity and mortality. This review aims to provide a comprehensive overview of the laboratory investigation of viral diseases, highlighting the importance of understanding the biology and pathogenesis of viruses. Viruses, consisting of genetic material encased in a proteinaceous capsid, rely on host cells for replication and spread of disease. This review will delve into the diverse range of viral diseases, including arboviruses, bunyaviruses, cytomegalovirus, papillomavirus, and many others, which affect various organ systems and manifest in different clinical presentations. The laboratory investigation of viral diseases is crucial for diagnosis, surveillance, and prevention of outbreaks. This review will summarize the current laboratory methods and techniques used in the detection, identification, and characterization of viruses, as well as discuss the challenges and limitations faced in the laboratory investigation of viral diseases. The review will also highlight the significance of laboratory investigation in informing public health policy and guiding the development of effective vaccines and treatments.

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Genetic material, Detection, Identification, Public health policy

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The Purpose of this study was to compare the achievement level in science subject among the students of Government Prishadiya Upper Primary Schools and students of Aided Junior High School. The sample size group is 300 students for Government Parishadiya Upper Primary Schools and 300 students of Aided Junior High School. A test of 20 marks is applied on each student . Stratified random sampling method used for collection of data.Then after calculating the answer and analysing the result by statistical tools and t-test ,the result of the study shows that there is no significant difference in the achievement level in science subject among the students of Parishadiya Upper Primary Schools and students of Aided Junior High School. It is Possible that the teachers of Government Parishadiya Upper Primary Schools and Aided Junior High School have similar interest in teaching or the learning level of the students of Government Parishadiya Upper Primary Schools and students of Aided Junior High School is same.

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Comparative study of achievement level in science subjects among the students of Government Parishadiya Upper Primary Schools and students of Aided Junior High Schools of district Pilibhit.

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Facial expression recognition (FER) is an important component in improving human computer interaction through the ability of machines to recognize human emotions. The new improved FER systems have been using deep learning techniques, especially Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Real time emotion recognition is something that CNNs excel at as their spatial feature extraction powers them to be very good at extracting spatial features from static images. On the other hand, RNNs are aptly suited for temporal sequences, that is, for capturing of emotion progression with time that is crucial for video based FER. In this paper, we offer a comparison of CNNs and RNNs, with respect to their strengths, limitations, and where we think they are best applied. It also examines hybrid models that combine both structures, and thus presents a complete approach to exploiting the combined capabilities of both architectures. Our findings suggest that CNNs are well suited for fast, static image recognition, while RNNs are better suited for dynamic, sequence based tasks. The next step in future research should extend to making models more robust and integrating multimodal data to make more adaptive and accurate FER systems.

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 Keywords

Facial Expression Recognition, Convolutional Neural Networks, Recurrent Neural Networks, Deep Learning, Emotion Recognition

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