Volume 14 | Issue 5 |

 Abstract

In this paper, we introduce fractional integrals and differentials of the extended Mittag-Leffler functions E_(?,?)^(?,? ;c,d) (z;p,q). In this continuation of the study of fractional calculus.

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Fractional Intergral, Mittag-Leffler Function, Extended Mittag-Leffler Functions

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Fixed point theory in metric spaces using interpolative contractive mapping has greatly developed in recent times. In this article we prove fixed point results satisfying interpolative type integral contractive condition in metric spaces.

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Metric space, integral type contractive condition, integral type interpolative contraction conditions, fixed point.

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This paper examines the issues, expenses, and administrative strains encountered by businesses in the process of meeting the India Goods and Services Tax (GST). It dwells upon the problems of the layered tax system, the constant shifts in taxation, and the inconsistencies in regulations implemented in different states, which also impacts SMEs with few resources, specifically. The administrative burden, such as a large amount of paperwork, several returns filing, and the adherence to the regional differences are examined. The paper also looks at the efforts by the government to make the life of GST easier, including easy filing of returns, GST help desks and online training programs. It also puts focus on technology, such as ERP software and artificial intelligence-based applications that are capable of automating compliance. Suggestions on how to lessen the compliance burden are given as well as policy recommendations on how to simplify the processes. Lastly, the research directions in the future are also defined with the emphasis on industry-specific issues and geographic differences in the GST implementation processes that will help improve compliance and assist businesses.

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GST compliance, administrative burden, SMEs, GSTN portal, digital transformation, tax filing simplification, government initiatives.

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Artificial Intelligence (AI) has emerged as a powerful technology in transforming space exploration and satellite imagery analysis by enabling efficient processing of large and complex geospatial data. With the rapid growth of high-resolution satellite imagery, traditional data analysis methods are no longer sufficient to provide accurate and timely insights. AI techniques such as machine learning and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly improved image classification, object detection, and segmentation tasks. Advanced approaches, including transformer-based models and multimodal AI systems, further enhance data interpretation by integrating satellite imagery with environmental and sensor data. Recent innovations such as edge AI enable real-time onboard satellite processing, reducing latency and improving efficiency, while reinforcement learning supports autonomous spacecraft navigation and mission optimization. Generative AI techniques are also utilized for image enhancement and data reconstruction. These advancements have expanded applications in climate monitoring, disaster management, precision agriculture, urban planning, and deep space exploration. However, challenges such as data quality issues, high computational requirements, limited labelled datasets, and hardware constraints in space environments remain significant. Future research directions, including federated learning, swarm intelligence, and AI-driven interplanetary exploration, aim to address these limitations. Overall, the integration of AI technologies is transforming satellite imagery analysis and space systems into more intelligent, autonomous, and efficient frameworks, paving the way for next-generation innovations in Earth observation and beyond.

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Artificial Intelligence, Satellite Imagery, Space Exploration, Machine Learning, Deep Learning, Convolutional Neural Networks (CNN), Transformers, Edge AI, Reinforcement Learning, Generative AI, Remote Sensing, Geo AI, Earth Observation, Autonomous Systems, Multimodal AI

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In recent decades, growing awareness about nutrition, fitness, and disease prevention has led to an increased emphasis on healthy eating practices. Social media platforms, wellness movements, and health-focused lifestyle trends have significantly influenced individuals' attitudes toward food and dietary habits. While adopting a balanced and nutritious diet is generally associated with improved physical and psychological well-being, an excessive and rigid preoccupation with consuming only foods perceived as healthy may lead to problematic eating patterns. One such emerging phenomenon in the field of eating behavior research is orthorexia nervosa, a term introduced by Steven Bratman to describe an unhealthy obsession with eating foods considered pure, natural, or healthy. Orthorexia nervosa is characterized by an intense fixation on the quality and purity of food rather than its quantity. Individuals displaying orthorexic tendencies often develop strict dietary rules, eliminate entire food groups perceived as unhealthy, and experience significant anxiety or guilt when these self-imposed dietary standards are violated. Over time, this rigid adherence to dietary ideals may lead to nutritional deficiencies, psychological distress, and social impairment, particularly when eating behaviors interfere with daily functioning or social interactions. Contemporary psychological perspectives suggest that orthorexic tendencies may be closely linked with dietary obsessions and rigid beliefs about health and nutrition. Individuals may develop strong cognitive beliefs that consuming only certain types of foods leads to moral superiority, improved self-control, or optimal health outcomes. These beliefs may gradually reinforce restrictive eating behaviors and contribute to obsessive patterns of food selection, meal preparation, and dietary monitoring. Furthermore, increasing exposure to health-related information through digital media and wellness culture may contribute to the internalization of unrealistic standards regarding "clean eating" and dietary purity. While healthy eating behaviors are widely encouraged, excessive preoccupation with food quality and health beliefs may paradoxically result in maladaptive patterns resembling eating disorder symptomatology. Despite growing research interest in orthorexia nervosa, the psychological mechanisms underlying orthorexic tendencies remain insufficiently explored. In particular, limited research has examined how dietary obsessions and beliefs about healthy eating contribute to the development and maintenance of orthorexic behaviors. Understanding these underlying cognitive and behavioral patterns is important for identifying individuals at risk and for informing prevention and intervention strategies. Therefore, the present study aims to examine orthorexic tendencies among individuals and explore their relationship with dietary obsessions and healthy eating beliefs, contributing to the expanding body of literature on emerging eating-related psychopathology.

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orthorexia nervosa, perfectionism, obessions, dietary habits

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This study focuses on analyzing the business development strategies and tools used for client acquisition with reference to Kirtane and Pandit LLP, Chartered Accountants. Client acquisition plays a significant role in the growth of professional service firms by improving market reach, competitiveness, and client relationships. The study covers key business development approaches such as referrals, networking, digital marketing, and relationship management, which strongly influence client acquisition in chartered accountancy firms. It examines how these strategies impact client growth, service delivery, and overall firm performance. Various analytical tools such as questionnaire surveys, percentage analysis, and chart representation are used to evaluate the effectiveness of client acquisition practices. The study also highlights the role of business development activities in strengthening client trust and long-term relationships. It identifies both opportunities and challenges associated with acquiring new clients. The findings provide insights into improving business development practices for sustainable growth. Overall, the study emphasizes the importance of effective strategies and tools in enhancing competitiveness and supporting long-term success.

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study emphasizes the importance of effective strategies and tools in enhancing competitiveness and suppor

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ABSTRACT: Background: Medial Tibial Stress Syndrome (TSS), commonly known as shin splints, is a frequent overuse injury affecting the lower extremities, particularly among athletes and individuals engaged in repetitive weight bearing activities. Bowling, though perceived as a low-impact sport, involves repetitive biomechanical stresses that may predispose recreational bowlers to tibial stress injury. Because of all these factors can cause TSS in future, So Prevent future impairments Proper diagnosis is important. The Shin Palpation Test (SPT) is a simple and reliable clinical tool for identifying TSS. Methodology: This observational study includes 58 recreational bowlers aged 18-30 years, selected through convenience sampling. Participants with a minimum of 2 years of playing experience will be screened according to inclusion and exclusion criteria. After obtaining informed consent, demographic data will be recorded, and the Shin Palpation Test will be administered bilaterally. Any report of pain during palpation will be noted as a positive finding. Result: Data will be analysed to calculate the prevalence of TSS among recreational bowlers. The findings will be presented in terms of prevalence rate and distribution according to demographic and pain intensity. Conclusion: The study is expected to provide evidence regarding the prevalence of Tibial Stress Syndrome in recreational bowlers. The study concluded that 88% shows the prevalence of Tibial Stress Syndrome in recreational bowlers. Findings may help increase awareness of injury risks in non-professional sports participants and guide preventive and management strategies.

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Tibial Stress Syndrome, Shin Splints, Recreational Bowlers, Shin Palpation Test

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This extensive research document is an extensive review of current literature concerning the field of Earthquake Monitoring and Alert systems, both of which are part of traditional Earthquake Monitoring using seismological methods, and the newest technological innovations. Based on our work, major trends are precisely analyzed using seismic monitoring technologies, machine learning applications, artificial intelligence integration, early warning systems, Internet of Things (IoT) based monitoring networks, and preventive methodologies that are deployed and implemented all over the globe. Through a rigorous study of the current research by 2020-2025, this paper reveals prominent developments in real- time seismic instruments, deep learning approaches in earthquake detection, transformer-based models in heterogeneous environments, and community-based earthquake early warning systems. Key findings include breakthroughs in the development of real-time monitoring capabilities with detection accuracies of more than 95%, predictive modeling capabilities that employ advanced neural networks with more than 700,000 labeled training examples, and community-based, early warning systems with practical implementation in sixteen countries worldwide. The study highlights ongoing issues with the ability to accurately predict earthquakes long enough ahead, system interoperability with different types of monitoring networks in heterogeneous networks, false alarm handling in real-time warning systems, and fair coverage across the globe, especially in the developing world. The paper further focuses on the global growth of earthquake early warning (EEW) systems using diverse communication technologies, the science and societal impact of aftershocks, emerging technologies for aftershock monitoring and loss reduction, and the important relationship between earthquakes and tsunamis with the integrated multi- hazard warning approaches. Issues and challenges related to these advancements are systematically addressed.

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Earthquake Early Warning, Seismic Monitoring, Machine Learning, IoT Sensor Networks, Aftershock Forecasting, Tsunami Warning, Deep Learning, Edge Computing, Real-time Detection, Hazard Mitigation

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Background: Benign paroxysmal positional vertigo (BPPV) is one of the most common vestibular disorders, characterized by brief episodes of vertigo triggered by changes in head position. Canalith repositioning and habituation exercises are commonly used conservative treatment approaches. Among these, Epley's Manoeuvre and Brandt-Daroff exercises are widely practiced, yet their comparative effectiveness requires further evaluation. Objective: To compare the effectiveness of Epley's Manoeuvre and Brandt Daroff exercises in reducing symptoms of vertigo and improving functional outcomes in patients with benign paroxysmal positional vertigo. Methodology: A comparative experimental study was conducted on patients clinically diagnosed with posterior canal BPPV. Participants were randomly divided into two groups. Group A received Epley's Manoeuvre, while Group B was treated with Brandt-Daroff exercises. Outcome measures included vertigo severity, frequency of dizziness episodes, and balance performance, assessed at baseline and after the intervention period. Results: Both treatment groups demonstrated significant improvement in vertigo symptoms and functional balance. However, patients treated with Epley's Manoeuvre showed faster and greater reduction in vertigo severity and symptom resolution compared to those performing Brandt-Daroff exercises. Conclusion: Both Epley's Manoeuvre and Brandt-Daroff exercises are effective in the management of BPPV. However, Epley's Manoeuvre is more effective in achieving rapid symptom relief, making it the preferred first-line treatment, while Brandt-Daroff exercises serve as a useful adjunct or home-based management option.

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Benign paroxysmal positional vertigo, Epley's Manoeuvre, Brandt Daroff exercises, vestibular rehabilitation, dizziness.

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The advent of technologies and advancement of artificial intelligence (AI) has raised significant concerns leading to a phenomenon termed AI anxiety. As Artificial Intelligence (AI) has become increasingly integrated into teaching and learning, teaching professionals particularly teachers and trainees need to understand students' attitudes toward artificial intelligence and AI learning anxiety to ensure its appropriate implementation. In this research, attitudes toward artificial intelligence and AI learning anxiety among 195 B.Ed. Trainees [90 Males (Urban 45 & Rural 45); 105 Females (Urban 50 & Rural 55)] is selected from teachers' training institutions namely, Aligarh Teacher's Training College, Aligarh and Jamia Urdu College of Education- JUCE (Aligarh) located in different locations of Aligarh (U.P.). The data was collected using standardized tools; Schepman and Rodway's General Attitudes towards Artificial Intelligence Scale: GAAIS (2020) and Wang & Wang's Artificial Intelligence Anxiety Scale: AIAS (2022). The findings reveal that (i) there is significant relationship between Attitudes toward Artificial Intelligence and AI Learning Anxiety among B.Ed. trainees (ii) there is significant difference between B.Ed. trainees regarding their attitude towards artificial intelligence and AI learning anxiety across gender and locale. Findings highlight the pivotal role of attitudes toward artificial intelligence and associated AI learning anxiety in shaping teacher aspirants' acceptance of AI. Understanding the root causes of AI learning anxiety and implementing strategic interventions are critical steps for mitigating its rise as society enters the era of pervasive AI. Therefore, stakeholders and educators should cultivate students' AI learning attitudes among B.Ed. trainees through comprehensive AI education and guiding them to form correct emotions through scientific and psychological interventions so that they encounter least AI learning anxiety.

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 Keywords

Artificial Intelligence, AI Attitude, AI learning Anxiety, B.Ed. trainees, Integration.

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