Volume 14 | Issue 4 |

 Abstract

Parkinson's disease (PD) is a progressive neurological disorder that affects motor functions and is often difficult to detect at an early stage. Traditional diagnosis mainly relies on clinical observation, which may delay timely treatment. In recent years, machine learning techniques have been widely explored to assist in the early diagnosis of Parkinson's disease by analyzing measurable physiological and behavioral signals. This paper presents a literature review of recent studies on machine learning based approaches for Parkinson's disease diagnosis using multiple data modalities. The reviewed studies utilize different types of data, including speech and voice recordings, handwriting patterns, gait signals, and sensor-based measurements collected from real world environments. A number of machine learning techniques like Support Vector Machine, Random Forest, and deep learning algorithm are examined and compared. The review highlights the strengths and limitations of existing approaches and emphasizes that multimodal systems, which combine multiple sources of data, can improve diagnostic reliability and accuracy. Results of this study provide an overview of current developments and indicate the potential of multimodal Machine learning methods to aid more effective Parkinson's disease diagnosis.

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 Keywords

Parkinson's Disease, Machine Learning, Multimodal Data, Deep Learning, Speech Analysis, Gait Analysis, Handwriting Recognition, Data Fusion, Predictive Modeling, Neurodegenerative Disorders.

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 Abstract

The study examines customer satisfaction with food delivery applications among university students. The main objective is to understand the factors influencing the level of use and satisfaction. A quantitative research design was adopted, and data was collected from 100 university students using a structured questionnaire through Google Forms. The data were analyzed using percentages and descriptive statistical methods. The results show that convenience is the main reason for using food delivery apps, with high satisfaction in delivery time and app interface, while pricing and customer support show moderate satisfaction. The study concludes that food delivery apps are widely used by students, but improvements in pricing transparency and service quality are needed.

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 Keywords

Customer Satisfaction, Food Delivery Apps, College Students, Consumer Behavior, Service Quality, Convenience, Delivery Time.

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This study examines the awareness and perception of smart health bracelets for elderly care in urban India. With the rise of wearable technology, such devices are becoming increasingly relevant in supporting elderly individuals. The study uses a survey-based approach with 60 respondents. Findings indicate moderate awareness and generally positive perception, while highlighting barriers such as cost and lack of familiarity with technology. The present study focuses on analyzing the level of awareness and perception of smart bracelets for elderly care among consumers in an urban setting. A descriptive research design was adopted, and primary data was collected through a structured questionnaire distributed via Google Forms. A total of 60 respondents participated in the study, including students, working professionals, and individuals with elderly family members. The data collected was analyzed using simple percentage methods and tabular representation to identify patterns and trends. The findings of the study indicate that while a majority of respondents are aware of smart health bracelets, detailed knowledge regarding their functions and benefits remains limited. However, the overall perception of these devices is positive, with many respondents recognising their usefulness in ensuring the safety and well-being of elderly individuals. Factors such as affordability, ease of use, and trust in technology were found to significantly influence consumer attitudes and purchase intentions. Despite the positive perception, certain barriers such as high cost, lack of technical familiarity among elderly users, and concerns about usability were identified. The study concludes that smart bracelets have strong potential in enhancing elderly care, especially in urban environments where constant supervision may not always be possible. Increasing awareness, improving user-friendly design, and making the devices more affordable can play a crucial role in encouraging wider adoption. The research also highlights the importance of understanding consumer perception as a key factor in the successful implementation of wearable healthcare technology.

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 Keywords

Smart Health Bracelets, Elderly Care, Wearable Technology, Consumer Awareness, Perception, Health Monitoring, Technology Adoption

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 Abstract

In modern financial markets, trading activities are highly dynamic and data-intensive, requiring disciplined decision-making and continuous performance evaluation. Many traders lack a structured mechanism to systematically record and analyze their trades, leading to inconsistent results and repeated mistakes. TradeJournal: Intelligent Trading Journal is designed as a comprehensive digital solution to address this challenge by providing an organized platform for tracking, analyzing, and improving trading performance. The application incorporates advanced analytical features that generate key performance indicators such as win rate, profit factor, drawdown, expectancy, and strategy-wise profitability. Interactive dashboards and graphical visualizations help users identify patterns, assess strengths and weaknesses, and recognize recurring errors. The system is implemented using Next.js for the front-end, Python Flask for the back-end, and SQLite for persistent data storage.

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 Keywords

Trading journal; performance analytics; web application; Flask; Next.js; SQLite; risk management; financial technology.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The widespread adoption of Applicant Tracking Systems (ATS) has created a critical skill gap among job seekers, particularly fresh graduates who lack access to professional resume review tools. This paper presents the AI Resume Analyzer, a full-stack web application that performs multi-dimensional, rule-based Natural Language Processing (NLP) evaluation of resumes in PDF, DOCX, and TXT formats. The system calculates five distinct performance scores--ATS Compliance, Content Completeness, Format Quality, Keywords Coverage, and Writing Impact--yielding a weighted overall score. The backend is implemented in Python using the Flask framework, with text extraction handled by PyPDF2 and python-docx. A drag-and-drop HTML5 frontend renders animated score visualizations, section detection results, ATS issue diagnostics, and prioritized improvement suggestions. All analysis is executed in server memory with no persistent storage, ensuring complete user privacy. Testing across 15 real resume samples confirmed consistent accuracy and sub-3-second response times. The system demonstrates that lightweight, rule-based NLP achieves practical and transparent resume evaluation without requiring deep learning models or external APIs.

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 Keywords

Resume analysis, ATS optimization, NLP, Flask, Python, text extraction, information retrieval, career technology, keyword extraction, job market

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 Abstract

Ombudsman for Older Persons in Finland 2025

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Ombudsman for Older Persons in Finland 2025

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The Impact of Public Relations Strategies on Print and Electronic Media: An Empirical Analysis in Visakhapatnam, Andhra Pradesh MANDRU SARATH BABU* and Dr. CHALLA RAMAKRISHNA** ABSTRACT This study delves into the public relations strategies utilized in print and electronic media across Visakhapatnam, Andhra Pradesh. By conducting an in-depth analysis, it assesses the effectiveness, challenges, and emerging trends within public relations (PR) practices in these formats. The insights generated are intended to guide practitioners and organizations in strengthening their communication approaches within the region. In the constantly changing realm of communication, the connection between media and public relations remains a fundamental pillar for organizations navigating the challenges of the digital era. This mutually dependent relationship involves a wide range of strategies and interactions that shape public opinion, engage stakeholders, and contribute to achieving organizational goals. Delving into this dynamic interplay reveals its intricacies and growing importance in today's media-dominated environment. At its essence, the bond between media and PR is both collaborative and multifaceted. PR professionals depend on media platforms to amplify messages, spread information, and connect with key audiences. In return, media outlets rely on PR practitioners to provide reliable sources, captivating narratives, and exclusive insights. This reciprocal reliance forms a constructive ecosystem where both sides work together to effectively fulfill their respective objectives. Media acts as a pivotal and strategic link connecting organizations with the public, playing a crucial role in shaping reputations, amplifying key messages, and fostering trust through earned, shared, and owned platforms. It empowers PR professionals to handle crises, secure media exposure, and engage stakeholders in real-time, thereby influencing public perception and enhancing brand credibility. As a trusted intermediary, the media is instrumental in shaping how organizations are perceived and managing their reputation. In the realm of public relations, it serves as a powerful tool for attaining third-party validation, which carries far greater credibility than paid advertising due to being conveyed by an independent entity. Public relations and advertising both rely on media channels to reach their audiences, yet they differ significantly in their methods and goals. PR emphasizes cultivating relationships, earning media coverage, and influencing public perception through storytelling and credibility. On the other hand, advertising centers on paid placements designed to directly promote products or services by driving sales and enhancing brand awareness through persuasive messaging. The connection between media and public relations plays a vital role for organizations aiming to excel in today's interconnected environment. By aligning PR strategies with media interactions, businesses can adeptly navigate the complexities of media, ensuring they remain competitive in a constantly evolving landscape. This dynamic relationship is crucial to the long-term success and resilience of organizations in the digital era. By comprehending its intricacies and effectively utilizing media channels, PR professionals have the power to amplify their communications, shape opinions, and accomplish strategic goals. Recognizing the importance of this partnership is essential for organizations seeking growth and sustainability within the ever-changing realm of media and communication trends.

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Keywords: public relations; strategies; navigating; reciprocal; ecosystem; fostering; significantly; enhancing; credibility; perception; landscape; comprehending; sustainability. *Research Scholar; **Associate Professor; Department of Journalism & Mass Communication, Andhra University, Visakhapatnam, Andhra Pradeh, India

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 Abstract

Background: Exercise-Induced Asthma (EIA), also known as Exercise-Induced Bronchoconstriction (EIB), is characterized by transient airway narrowing occurring during or after physical activity. It is commonly observed in children and adolescents and may significantly affect their participation in physical activities, overall fitness, and quality of life. Early identification is essential to prevent long-term respiratory complications and promote active lifestyles among school-going children. Methodology: A cross-sectional descriptive study was conducted among 151 school-going children aged 12-17 years in Nashik city using purposive sampling. Participants without a prior diagnosis of asthma were included. Baseline vital parameters and Peak Expiratory Flow Rate (PEFR) were recorded, followed by a 1-mile run test. Post-exercise PEFR measurements were taken at 2, 3, and 5 minutes. A reduction of more than 10% in PEFR from baseline was considered indicative of EIA. Data were analyzed using SPSS version 26, with quantitative data expressed as mean and standard deviation and qualitative data as percentages. Results: The mean pre-exercise PEFR was 263 L/min, which decreased to 205 L/min at 2 minutes post-exercise, followed by gradual recovery to 248 L/min at 5 minutes. The study revealed that 42.4% of participants exhibited clinically significant EIA. Among them, 57.6% had mild, 38.4% moderate, and 4% severe bronchoconstriction. Male participants demonstrated higher PEFR values compared to females across all time points. The mean percentage fall in PEFR was 26.8%, indicating notable variability in post-exercise airway response. Conclusion: The study demonstrates a high prevalence of exercise-induced asthma among school-going children in Nashik. The findings highlight the importance of early screening using simple tools like PEFR, along with increased awareness and implementation of preventive strategies in school health programs to ensure timely diagnosis and management.

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 Keywords

Exercise-Induced Asthma, Exercise-Induced Bronchoconstriction, Peak Expiratory Flow Rate, School Children, Prevalence, Respiratory Function, Physical Activity

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 Abstract

Heart attack is a term that is commonly used for myocardial infarction (MI). MI refers to a condition where the heart muscle experiences reduced or blocked blood flow. MI is a significant cause of death across the world, and therefore its detection is paramount. One diagnostic approach involves the use of electrocardiogram (ECG) signals. The interpretation of ECG signals, however, demands expertise and is not without inconsistencies. This paper introduces an explainable deep learning framework that leverages 12-lead ECG signals for detecting MI from the PTB-XL database. A balanced sample of 2000 was considered to eliminate any bias during the training process. We benchmark the proposed model against a traditional random forest approach and a 1D CNN model trained on raw ECG data. Our model scores 83.00accuracy and 0.9113 AUC value, which is superior to the baseline model. We use gradient-based saliency maps for visualizing important regions of the ECG signals that contribute to model predictions. Findings suggest that our explainable 1D CNN approach provides a promising solution for automatic MI detection.

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 Keywords

Deep Learning,ECG,Myocardial Infraction ,Explainable AI,1D CNN

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 Abstract

The field of neurocosmeceuticals has emerged as an innovative advancement in cosmetic science, integrating concepts from neuroscience, dermatology, and pharmacology to target the skin-brain axis. This review explores the formulation and functional mechanisms of neurocosmeceuticals designed to regulate the bidirectional communication between the central nervous system and the skin through neuroendocrine and immune pathways. The skin functions as a neuro-immuno-endocrine organ that responds to psychological stress via activation of the hypothalamic-pituitary-adrenal (HPA) axis, resulting in increased cortisol production, oxidative stress, inflammation, and impairment of the skin barrier. These changes are associated with various dermatological conditions such as acne, psoriasis, atopic dermatitis, and premature aging.Neurocosmeceuticals incorporate bioactive agents including peptides, adaptogens, antioxidants, and plant extracts to modulate neurotransmitter activity, reduce neurogenic inflammation, and restore skin homeostasis. The application of advanced drug delivery systems, such as liposomes, nanoparticles, and microemulsions, enhances the stability, penetration, and targeted delivery of active ingredients.Despite their promising potential, challenges remain, including insufficient clinical validation, lack of standardized evaluation methods, formulation instability, and regulatory uncertainties. Future developments emphasizing personalized skincare and technological advancements are expected to expand the scope of neurocosmeceuticals. Overall, these formulations represent a novel and holistic approach for managing stress-related skin disorders by addressing both physiological and psychological factors influencing skin health.

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 Keywords

Neurocosmeceuticals; Skin-brain axis; Psychodermatology; HPA axis; Neurotransmitters.

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Creative Commons Attribution 4.0 and The Open Definition