Volume 13 | Issue 5 |

 Abstract

Calisthenics, a form of bodyweight training rooted in ancient traditions, has witnessed a global resurgence due to its accessibility, versatility, and effectiveness in promoting functional fitness. This review explores the historical evolution of calisthenics, its core principles, and its physiological and psychological benefits. It compares calisthenics with traditional resistance training, highlights its unique emphasis on skill development, and evaluates the scientific literature supporting its effectiveness for strength, hypertrophy, cardiovascular fitness, and mental well-being. Common movements, progression strategies, and injury prevention measures are outlined alongside insights into popular training programs and nutritional considerations. The influence of social media in fostering a global calisthenics community is also discussed. While calisthenics presents certain limitations, especially in lower-body hypertrophy and structured progression, it remains a sustainable and empowering training modality for diverse populations. This review underscores calisthenics as a holistic, evolving discipline with growing relevance in fitness, rehabilitation, and preventive healthcare.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Calisthenics, Bodyweight Training, Functional Fitness, Muscle Hypertrophy, Strength Training, Mobility, Flexibility, Skill Development, Street Workout, Physical Conditioning.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Domestic Violence, Psychological Distress, Mental Health, Composite Abuse Scale-Revised (CASR-SF), Clinical Outcomes in Routine Evaluation (CORE-OM), Trauma, Resilience, Social Support

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Maintaining a healthy codebase over time is an ongoing hurdle for software teams. This study examines how different restructuring strategies perform when applied at key milestones--early development, major releases, and maintenance periods. We compare three approaches (manual refactoring, rule-based transformations, and AI-assisted restructuring) using four popular tools (RefactorX, Rearchitect, CodeRenew, SmartRefactor) under static, dynamic, and combined (hybrid) analysis. Across eight real-world projects and 2,592 experimental runs, we measured changes in code complexity, coupling, and code-smell counts, along with tool runtime and developer feedback. Our findings reveal that AI-powered methods deliver the largest complexity reductions (?25 %) with modest time investment, whereas rule-based tools strike a favorable balance between speed and effectiveness. Downtime around major releases offers the strongest opportunity for broad improvements, and hybrid analysis emerges as the most efficient way to catch both static and runtime issues. We close with clear, context-sensitive recommendations to aid teams in choosing the right restructuring strategy.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Software Restructuring; Refactoring; Lifecycle Stages; Technical Debt; Analysis Mechanisms.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sentiment analysis, especially within the realm of English-language movie reviews, has seen substantial progress thanks to the availability of diverse and expressive data. This research presents a novel Stacked Ensemble-Based Architecture (SEBA) for binary sentiment classification of movie reviews. We curated and annotated a dataset of 5,000 English movie reviews, supplemented with widely-used public datasets from platforms like Kaggle, Hugging Face, IMDB. Our methodology employs sophisticated text preprocessing techniques and represents data using Term Frequency-Inverse Sentence Frequency (TF-ISF) with word-level N-grams. The research establishes Logistic Regression as a baseline model before integrating more advanced algorithms including BERT and LSTM within our ensemble framework. To optimize classification performance, we applied extensive hyperparameter tuning and ensemble learning strategies. Additionally, we implemented a filter to mask explicit language, ensuring that such content doesn't unfairly skew sentiment judgment. Experimental results demonstrate that SEBA achieved 80.8% across accuracy, precision, and recall metrics, with an F1-score of 80.7%, significantly outperforming individual classifiers. These findings indicate SEBA's considerable potential for deployment in real-world binary sentiment analysis applications, particularly for entertainment content evaluation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sentiment Analysis, Binary Classification

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT Neck pain is a prevalent musculoskeletal condition globally affecting individuals across all age groups, especially adults with sedentary lifestyles, poor posture, and work-related strain. Exercise therapy is a cornerstone in the conservative management of non-specific and mechanical neck pain. This narrative review discusses the role of various types of exercise--stretching, strengthening, endurance training, posture correction, and motor control retraining--in alleviating neck pain and improving functional outcomes. The review draws on evidence from randomized controlled trials and systematic reviews sourced from PubMed and Google Scholar to present the physiological rationale, clinical outcomes, and efficacy of exercise interventions. The article concludes by emphasizing that exercise, when properly prescribed and individualized, can significantly reduce pain intensity, improve range of motion, and enhance the quality of life in patients with neck pain.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Neck pain, exercise therapy, posture, muscle strengthening, physiotherapy, rehabilitation, cervical spine.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Magical realism is a literary genre that weaves elements of the extraordinary and supernatural into a realistic narrative, giving a sense of wonder and elevating the reader's experience. Latin American authors are known for their expertise in this genre, blending the mystical with everyday life. One of the most celebrated authors of magical realism is Isabel Allende, whose novel, The House of the Spirits, showcases this genre's depth and power. Through her use of magical realism, Allende conveys profound themes of memory, family legacy, and interconnectedness. This paper examines the role of magical realism in The House of the Spirits by analyzing how these elements enhance the narrative, deepen character development, and shape the reader's experience.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

magical realism, character, family legacy, culture, politics, and gender

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A study and configuration of a new transformerless buck-boost converter is proposed in this work. The normal buck-boost converter has simple configuration and high efficiency. The disadvantage of the normal converter is restricted voltage gain, negative output voltage, floating power switch, discontinuous output and input currents. For eliminating the disadvantages of the normal converter, a new transformer less buck-boost converter is proposed. The proposed new transformer less buck-boost converter consists of two switches, two capacitors, two inductors and one resistor load in the circuit. The two power switches of the proposed converter operate simultaneously. The proposed buck-boost converter gives the voltage gain is squared or quadratic times of normal converter which makes it suitable for solar energy applications. In continuous conduction mode, a voltage gain, operating principles, small-signal model and voltage stress are described for the proposed converter. To improve the stability of a system, a PI controller is used in the proposed converter. The structure of the proposed buck-boost converter circuit is simulated in MATLAB/ SIMULINK

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

High voltage gain, transformerless buck-boost converter, small signal model, voltage stress.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The following dissertation performs a critical analysis of AI and CSR integration in CSR decision-making while exploring ethical and legal complications that occur from AI-based approaches. The investigation evaluates the role of AI in CSR ethical decision-making processes within corporate governance frameworks but explores the critical risks that occur from diminished transparency along with decreased accountability and biased data usage. This investigation introduces an historical and legal exploration of CSR which tracks its development from charitable origins into institutionalized obligatory practices within India as per the Companies Act, 2013. The research examines the AI-based transformation of CSR delivery by exploring predictive analytics systems and stakeholder sentiment tools which enable real-time monitoring capabilities. The research methodology utilizes a comparative case study examination of four international organizations namely IBM and Microsoft and the Tata Group and Infosys which presents how artificial intelligence boosts CSR projects from education to healthcare and sustainability to digital inclusion. The research finds that AI improves CSR effectiveness because of its scalable operations along with efficiency while presenting legal and moral problems because of hidden computing systems that lack proper rules and could diminish human evaluation capabilities. The dissertation proposes a model merger of AI capabilities with human supervision for responsible innovation and supports it with comprehensive ethical-legal guidelines. The research adds new insights toward discussions about digital ethics and responsible business conduct and policy development for AI governance in CSR.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI Ethics, Corporate Social Responsibility, Legal Framework, Accountability, Stakeholder Engagement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Neuropathic (peripheral neuropathy) refers to a condition or disorder that affects the nervous system, particularly the peripheral nerves which is the network of nerves outside the brain and spinal cord that transmit information to and from the rest of the body. It involves damage or dysfunction of the nerves, leading to various symptoms like numbness, tingling, pain, and weakness in the hands and feet, often arising from underlying conditions like Diabetes, vitamin deficiencies, exposure to toxins, or autoimmune disorder. Treatment and management depend on the underlying cause and may include medication, physical therapy, lifestyle changes, and in some cases, surgery. In some instance, peripheral neuropathy can be temporary and resolve with appropriate treatment, while in others, it may be a chronic condition requiring ongoing management.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Affected system, Prevalence and Impact, Intractability, Multidisciplinary Approach, Treatment Options, Focus on Quality of Life, Ongoing Research, Underlying Causes, Importance of Early Diagnosis and Intervention, Lifestyle Modification.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The automotive air conditioning (AC) system plays a vital role in ensuring cabin comfort and vehicle endurance, and its design has received increasing attention. The air duct, which connects the AC compressor to the cockpit instrument panel outlets, significantly influences the system's cooling efficiency through its structural and flow characteristics. Its air delivery performance directly affects the uniformity of temperature and velocity fields within the cabin, thereby impacting occupant comfort. Due to spatial constraints, air duct design is among the most challenging aspects of vehicle HVAC system development. Consequently, optimizing the duct to balance spatial integration with energy efficiency is a key research focus. This study presents a CFD-based approach to the simulation and optimization of an automotive air duct. The model is initially developed using Ansa, meshed with Meshing software, and analyzed in Fluent to assess internal flow behavior. By applying defined inlet conditions, airflow distribution across outlets is evaluated. Based on a baseline vehicle duct model, issues such as turbulence and uneven outlet flow are addressed through design modifications--maintaining original spatial dimensions--and the improvements are validated through simulation results.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AC duct, Automotive, CFD, Simulation, Model optimization and improvement

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Creative Commons Attribution 4.0 and The Open Definition