Volume 13 | Issue 4 |

 Abstract

Pain and anxiety from injections are a common problem, especially in children and patients with needle phobia. In this article, the Cool-Tune-Vibe is a compact, non-invasive device that reduces injection-related pain by integrating heat distraction, thermal stimulation, and vibrational feedback. The device works according to the principles of pain theory of Gate Control Theory, using a combination of localized cooling, soothing music, and gentle vibrations, to distract sensory nerves at the site of injection. This multi modal approach can effectively reduce pain sensation, improve patient comfort, and is particularly applicable in clinical, pediatric, and vaccination settings. Experimental studies have shown a significant reduction in perceived pain levels, which demonstrates the potential to improve the patient experience of everyday injections.

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 Keywords

Bluetooth, Arduino Nano, Injection, Needle Anxiety

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The growth in smart home technologies has raised the stakes on energy efficiency research. Most existing smart home energy monitoring systems have been focusing on general energy tracking, machine learning-based energy consumption prediction, and cloud-based monitoring solutions. There is a lack of automated energy-saving mechanisms for specific high-power-consuming appliances such as TVs and ovens that continue to consume electricity when left unattended. This paper introduces an innovative IoT-based smart home energy monitoring system with integration of motion sensors for the functionality of auto-off for TVs and an automated power cut-off mechanism for ovens. The proposed system detects user presence near the TV and automatically turns it off when no movement is detected for a predefined time to prevent unnecessary consumption of power. Besides, the oven power cut-off system ensures that the flow of electricity is stopped as soon as the heating process is over, which saves energy consumption. Both systems are connected to a mobile application for real-time monitoring and manual control. The realization of this system can greatly improve household energy efficiency while maintaining user convenience. Experimental tests and simulations suggest a huge electricity saving as compared to conventional energy monitoring systems 15.

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 Keywords

Smart home automation, energy monitoring, motion sensors, TV auto-off, oven power cut-off, electricity reduction, IoT, mobile app integration.

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 Abstract

The surge in the tourism industry has massively attracted tourists to India on a large scale to the places of dark tourism. Dark tourism is a niche within the tourism industry nowadays that concentrates on visiting places connected to sorrow, tragedy, or death. The darkest eras of human history, effects of war or disaster, impacted communities, dark incidents of infamous crimes, the popularity of social media, and stories of human history behind tragedies have all contributed to the rise in popularity of this type of tourism in recent years. The surge is not only because of the external and mysterious stories and reasons associated with the site it also involves certain internal human factors associated with human behavior and psyche. The paper aimed to study those internal factors like behavioral intention, motivation, and triggers that instill the urge among tourists to visit a destination of dark tourism. Research has tried to focus on the experiences of the tourists and the transition they observe in their feelings and emotions before, after, and during the tour. For serving this purpose narrative inquiry will be performed based on the interviews of those tourists that have visited a site of dark tourism. The results have justified that the tour is initiated as a result of curiosity, past human experiences, some emotional triggers, or a feeling of thrill. Findings have also stated that the emotions and feelings of the tourists can change a lot from curiosity to acceptance towards the negative energies, from thrill to the satisfaction of completing the tour, and much more.

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 Keywords

Dark tourism, Behavior intention, Motivation, Triggers, Emotions and Feelings

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research paper investigates how Brain Breaks video-based classroom physical activity intervention programs affect the physical fitness, psychological health, and well-being of pre-adolescent children aged 9 to 12 years in India. 110 students were divided into experimental (n = 60) and control (n = 50) groups in a quasi-experimental design. For twelve weeks, the experimental group watched Brain Breaks films, which included two to five minutes of physical activity six days a week during classroom sessions. Assessments were conducted between the two groups using the EUROFIT Physical Fitness Test, the World Health Organisation (WHO) Well-Being Scale, and the Physical Activity Enjoyment Scale (PAES) before and after the intervention. ANCOVA was used to assess within-group and between-group differences in the data. Descriptive statistics (mean and standard deviation) were calculated for each variable. In each variable, the control group showed negligible changes. According to these results, schoolchildren's resilience, mental health, and enjoyment of physical exercise could all be greatly improved by short, planned physical activity interventions like Brain Breaks. The research highlights how these activities could be used in classrooms to encourage holistic development and discourage sedentary behaviour

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 Keywords

Physical activity; EUROFIT; Children; Technology-based video intervention; Psychological scale.

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 Abstract

Tax provisions are always important to government and taxpayers. Out of many tax provisions, provisions related to Capital Gains significantly affect investments in the country. It has a direct relation with investment choices of investors which may increase investments in economy and vice versa. Amendments in tax provisions may make taxpayers feel happy or sad, depending on how it is satisfying or affecting them. Government every year makes amendments in tax provisions to balance the needs of own as well as taxpayers both. Recently, in Union Budget 2024 government has made significant changes in tax provisions related to capital gains such as withdrawal of indexation in case of long-term capital gains, changes in capital gains tax rates, making buyback of shares taxable, increasing exemption limit for long term capital gains in respect of equity-oriented investments. Since taxation always have direct relations with taxpayers, knowing how these amendments related to capital gains tax provisions has affected investors are very important. The current study focuses on the satisfaction level of investors with respect capital gains tax amendments made in Union Budget 2024 and their perception towards it.

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BUDGET, CAPITAL GAINS, INVESTOR, SATISFACTION, TAX AMENDMENTS

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This paper presents the design, development, and implementation of a bionic arm controlled using servo motors and an Arduino microcontroller. The proposed system aims to replicate human hand movements with a focus on precision, efficiency, and affordability. A tendon-driven mechanism is integrated with servo actuators to ensure smooth articulation of fingers and wrist motion. The system incorporates forward and inverse kinematics for accurate positioning, along with real-time embedded control algorithms. Performance validation through experimental testing highlights the effectiveness of the bionic arm in replicating grasping and manipulation tasks. The research contributes to the field of prosthetics and assistive robotics by offering an open-source, low-cost alternative to commercial bionic limbs.

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 Keywords

Bionic arm, servo motors, Arduino, kinematics, embedded control, prosthetics.

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Creative Commons Attribution 4.0 and The Open Definition

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An experimental evaluation of the solar photovoltaic (PV) system's depletion under the weather.investigating how blurring affects the PV system with different solar radiation levels four PV solar module panels (20W, Manf: Usha Solar) subject to parallel (SP) weather are used in this investigation--cross-sectional rate-arrested (TCT) and forecast. To evaluate the PV system's performance under artificial lighting fixtures, the test set includes electrical performance rating devices with a variable load. Furthermore, performance comparisons between PV modules programmed into the SP and TCT modified PV modules were conducted under the shading I-II test case.A thorough examination is aided by the anomalous behaviour of the current-voltage (V-V) and power-voltage (P-V) curves when numerous power points, such as local maximum power points (LMPP) and ground mass points (GMPPT), are present. Furthermore, performance indicator measures such as GMPP power, low power loss, and fill factor (FF) were evaluated under both PV power assumptions in distinct shadow scenarios.

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 Keywords

Solar energy, series-parallel connection. Total-cross-tied connection, power losses, power, fill factor

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 Abstract

The advancement of intelligent systems has significantly impacted the healthcare industry, enabling the development of automated diagnostic tools for early disease detection and monitoring. Respiratory diseases, particularly in children, are among the most common health concerns, requiring timely and accurate diagnosis. Traditional methods rely on clinical evaluations and laboratory tests, which can be time-consuming and resource-intensive. In this study, we introduce RESPITECH, a deep learning-based framework for automated cough sound classification. By leveraging audio signal processing techniques and machine learning, RESPITECH aims to differentiate between healthy and pathological coughs in individuals, with a focus on respiratory conditions such as asthma, upper respiratory tract infection (URTI), and lower respiratory tract infection (LRTI), COPD, Pneumonia, Bronchitis and also Healthy lungs. Our approach employs a Convolutional Neural Network model (CNN) trained on Mel-Frequency Cepstral Coefficients (MFCCs) extracted from a carefully curated dataset of cough sounds labeled by clinicians. The CNN model is designed to capture temporal dependencies in cough sounds, enhancing classification performance. When trained to distinguish between healthy and pathological coughs, the model achieves an accuracy exceeding 84%, aligning closely with physician diagnoses. To improve classification performance for specific respiratory pathologies, multiple cough epochs per subject are aggregated, resulting in an overall accuracy surpassing 91% for detecting asthma, URTI, and LRTI. However, classification performance declines when distinguishing between four separate cough categories, as certain pathological coughs share overlapping acoustic characteristics, leading to misclassification. A detailed analysis of the MFCC feature space through a longitudinal study indicates that pathological coughs, regardless of the underlying condition, exhibit similar acoustic patterns, making it challenging to differentiate between specific respiratory diseases using MFCCs alone. This suggests that while MFCCs provide valuable spectral information, additional features or multimodal data integration may be necessary for finer disease discrimination. Despite these challenges, RESPITECH demonstrates strong potential as an automated, non-invasive screening tool for respiratory disease monitoring. Future work will explore advanced feature extraction techniques, multimodal learning approaches, and real-world deployment strategies to enhance diagnostic accuracy and clinical applicability.

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 Keywords

Deep Learning,Neural Networks,Convolutional Neural Networks (CNNs),Long Short-Term Memory (LSTM),Feature Extraction,Data Representation,Audio Classification.

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Creative Commons Attribution 4.0 and The Open Definition

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Consumer buying behavior plays a pivotal role in shaping marketing strategies within the health and wellness industry, particularly in the growing market of protein powder supplements. This study investigates the key factors that influence the purchasing decisions of youngsters in Vadodara regarding protein powder supplements. The research focuses on elements such as product taste, nutritional content, pricing, availability, brand reputation, peer influence, and promotional activities. It also explores consumer perceptions of health benefits and the role of social media in shaping preferences. Data was collected from 200 young residents of Vadodara through a structured questionnaire, ensuring a diverse representation across gender, age groups (18-30), and fitness backgrounds. Descriptive statistical tools, including bar graphs and pie charts, were used to identify trends and analyze correlations. The findings reveal that most youngsters prioritize nutritional value and visible fitness results, followed by taste and price. Social media influencers and gym trainers play a significant role in influencing buying behaviour, while brands with transparent labeling and trusted quality enjoy higher loyalty. These insights indicate a shift towards informed and health-conscious decision-making among young consumers. To remain competitive in this evolving market, brands should focus on developing clean-label, result-oriented products, adopt digital marketing strategies, and engage fitness communities through credible endorsements. Such strategies are vital for enhancing brand engagement and increasing the adoption of protein powder supplements among health-aware youth in Vadodara.

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 Keywords

Consumer behavior, protein powder supplements, Vadodara, youth, buying patterns, health perception, fitness influence, promotional strategies, brand loyalty

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cervical cancer is a significant worldwide health concern. With the intention of advising medical professionals and researchers on current advancements and potential future paths in this area, this comprehensive analysis provides an overview of the available and developing cervical cancer therapy options. Surgical techniques, radiation therapy, and chemotherapy are the current treatment options for cervical cancer; they are often used in combination, depending on the disease's stage and severity. However, in situations that are advanced or recurrent, these traditional therapies may not be effective and are often associated with serious adverse effects. As a result, the need for creative treatment approaches is rising. Recent developments in cervical cancer treatment include a variety of cutting-edge strategies including gene-based therapy, immunotherapy, and targeted therapy. Clinical trials have shown promising outcomes for targeted medicines, such as those that inhibit Vascular Endothelial Growth Factor (VEGF) and Epidermal Growth Factor Receptor (EGFR), particularly when paired with conventional medications. Immunotherapy has revolutionized cancer treatment and has great potential for people with cervical cancer, especially when it comes to immune checkpoint inhibitors. Furthermore, gene therapy approaches that involve gene editing and oncolytic viruses provide novel ways to eradicate cancer cells while protecting healthy tissue. Patient outcomes for cervical cancer might be significantly improved in the next years by incorporating these novel medicines into routine medical care. To address medication resistance concerns, find predictive biomarkers for patient selection, and enhance treatment regimens, further study is required. In order to get these new treatments from lab research to clinical practice and eventually lessen the global effect of cervical cancer, partnerships between medical professionals, academics, and the pharmaceutical industry will be essential.

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 Keywords

HPV, Chemotherapy, Immunotherapy, Targeted therapy.

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Creative Commons Attribution 4.0 and The Open Definition