Volume 13 | Issue 5 |

 Abstract

Abstract: Introduction: To offer insights that help enhance practitioner well-being and patient care, this study investigates the difficulties mental health practitioners encounter in their day-to-day contact with patients, looking at the psychological, mental, and professional demands of working in this field. Methodology: The lived experiences of mental health professionals dealing with patients in various settings are explored in this qualitative study using a phenomenological method. The study aims to understand how these professionals view and handle daily professional, emotional, and mental challenges when interacting with patients. Results: The three major themes, Psychological Progression, Therapeutic Evolution, and Supportive Formation, emphasize the significant aspects of the experiences of mental health professionals, such as mental and emotional growth, techniques for coping with emotional stress, and approaches to improving patient involvement and social engagement. Discussion: Psychological progression fosters growth through resilience, self-care, and professional development. Therapeutic evolution enhances mental health care through improved strategies, resilience, and continuous professional growth. Supportive development in mental health counseling fosters resilience, ethical care, and professional balance to enhance client outcomes and practitioner well-being. Conclusion: This study explores the many challenges that mental health professionals face. It explored the challenges of mental health professionals with their mental health, as well as their coping and emotional regulation techniques. It discussed mental health professionals' self-care and how they follow specific standards to maintain their personal and professional ethics.

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 Keywords

Index Terms - Mental health, professionals, well-being, therapy, phenomenology.

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Creative Commons Attribution 4.0 and The Open Definition

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A hybrid power generation system combining solar energy and wind energy offers a sustainable, off-grid solution for charging mobile phones and laptops. This system utilizes solar panels and wind turbines to harness renewable energy from both sunlight and wind, which is then stored in a battery bank for later use. The system integrates a hybrid charge controller that optimizes the use of both energy sources, ensuring efficient storage and energy distribution. A DC-to-USB converter or inverter is used to provide power to mobile phones and laptops. This paper discusses the system's components, functionality, and potential benefits for remote or off-grid locations, aiming to reduce reliance on traditional grid electricity. The system makes use of a battery to store the energy generated by both the power generators. This battery supply is now connected through the inverter for usage. The system provides 2 types of outputs. 1 USB outputs for 1 x 5V DC mobile charging ports and 1 x 230V AC port with current limitation for charging laptops only. The system is fitted with 4 wheels for ease of movement making it very portable. It can easily be used near bus stops, garden, historical monuments, zoo, college campus, corporate parks, footpaths, open parking and more.

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 Keywords

SOLAR ,WIND,BATTERY,CIRCUIT BOARD, INTRODUCTION TO HYBRID SYSTEM,TYPES OF HYBRID SYSTEM,

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Creative Commons Attribution 4.0 and The Open Definition

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Modern surveillance, security, and airspace mon- itoring systems rely heavily on flying object detection. The challengeisintheexactdetectionoffast-movingairborneobjects including drones, birds, planes, and balloons especially under varying lighting, altitude, and background clutter conditions. This paper presents HawkEye, a deep learning-based ensemble system combining YOLO (You Only Look Once) and DETR (DEtection TRansformer) models, to provide improved accuracy and robustness in flying object identification. The model is trained on the Flying Objects OB 100 dataset, which coversmany aerial scenarios. The paper offers two key approaches:The paper proposes two primary techniques: (1) DOLO, ahybrid architecture combining YOLO's real-time efficiency with DETR's; and (2) an ensemble learning approach combining several YOLO versions with DETR

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 Keywords

FlyingObjectDetection,YOLO,DETR,Ensem- ble Learning, Deep Learning, Computer Vision.

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This study investigates the pivotal role of strategic partnerships in fostering technological innovation within the contemporary business landscape. By analyzing the benefits, challenges, and critical success factors of such collaborations, the research elucidates how organizations leverage complementary expertise, shared resources, and market synergies to achieve competitive advantages. The study explores various partnership models--horizontal alliances, vertical partnerships, joint ventures, and research consortia--through real-world case studies, including Airbnb's collaboration with payment giants and the unsuccessful Uber-Toyota-Volvo autonomous driving alliance. A novel ADeCuMaS framework is proposed to guide organizations in crafting and sustaining effective partnerships. The findings underscore the importance of aligned goals, robust governance, collaborative culture, and continuous adaptation for unlocking the transformative potential of strategic alliances.

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Strategic Partnerships, Technological Innovation, ADeCuMaS Framework, Synergistic Innovation, Market Expansion, Risk Mitigation, Collaborative Culture

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Signature Verification Is An Important Aspect Of Contemporary Security Systems, As It Verifies The Authenticity Of A Person Through His Or Her Own Handwritten Signature. As More And More Systems Rely On Digital Systems, There Is A Greater Demand For Automated, Precise, And Effective Signature Verification Systems. Conventional Signature Verification Techniques Include Manual Verification Or Simple Automated Methods, Which Are Time-Consuming And Susceptible To Errors. This Paper Introduces A Novel Signature Verification Method With Convolutional Neural Networks (Cnns) That Utilize Deep Learning Methods To Examine And Validate Signatures. Through The Combination Of A CNN-Based Model With An Easy-To-Use Streamlit Frontend, This System Provides An End-User-Friendly Experience For Real-Time Verification Of Handwritten Signatures. The New Approach Is To Preprocess The Input Signature Images Through Normalization Of Their Sizes, Conversion Into Grayscale, And Improvement Of Their Quality For Uniformity. The Preprocessed Signature Images Are Then Input Into A CNN Model That Extracts The Hierarchical Features, Including Edges, Textures, And Shapes, Automatically, Through A Sequence Of Convolutional And Pooling Layers. This Allows The Model To Extract Efficiently The Subtle Differences Between Authentic And Fake Signatures. The CNN Model Is Trained On A Labeled Dataset Of Authentic And Forged Signatures Using Backpropagation To Adjust The Weights And Enhance The Accuracy Of The Model. The CNN Model Architecture Involves Several Convolutional Layers Followed By Fully Connected Layers, Which Forms A Strong Foundation For Classification. The Model Is Then Deployed Into A Streamlit-Based Frontend Where Users Can Upload Signature Images To Be Verified. Streamlit Offers An Interactive And Light-Weight Environment, Allowing Users To See The Outcome Of The Signature Verification In Real-Time. The System Provides A Yes Or No Output On Whether The Uploaded Signature Is Genuine Or Fake Depending On The Predictions Of The CNN Model. The Streamlit Interface Also Offers A Friendly Presentation Of The Process, Displaying The Uploaded Signature, The Analysis Of The CNN, And The Final Verification Outcome. This Method Has Great Benefits Compared To The Conventional Methods, Such As Higher Accuracy, Scalability, And Capability To Process Large Datasets. The Application Of CNNs In Signature Verification Guarantees High-Level Feature Extraction And Reduces Human Error. Furthermore, The Application Of Streamlit Makes The System Easier To Use And More Accessible, Making It Applicable In Various Fields, Ranging From Banking To Legal Systems. The Integration Of CNN-Based Signature Authentication And Streamlit Frontend Is An Advanced Solution To This Important Security Problem.

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 Keywords

Convolutional neural network (CNN); Signature verification; Pre-processing, Pre-trained Model, Fine-tuning, Classification.

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 Abstract

Delivery drones are revolutionizing the logistics industry by incorporating state-of-the-art technology to streamline the delivery process. Utilizing advanced navigation systems such as GPS and autonomous flight controls, these drones are capable of reaching precise delivery points in both urban and remote locations. With enhanced imaging and sensor technology, they can detect obstacles and ensure safe, accurate landings. Real-time communication through cellular and satellite networks provides continuous tracking and oversight, allowing for optimized logistics management. Intelligent flight path algorithms minimize delivery time and maximize efficiency, while modern power solutions, including LiPo batteries and advanced energy management systems, ensure prolonged flight and dependable service. These drones are designed to handle a wide variety of payloads, including sensitive goods, enhancing the efficiency, scalability, and safety of last-mile delivery operations in diverse conditions

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Autonomous navigation, Last-mile logistics, Mission Planner, Real-time monitoring, Wireless communication

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The increasing need for automation and resource optimization in agriculture has emphasized the importance of intelligent irrigation systems. This paper presents the design and implementation of a cost-effective and scalable Pump Control Unit for smart farming applications. The system employs an Arduino Uno microcontroller integrated with a GSM module to enable remote control and monitoring of a three-phase induction motor used for irrigation. Critical protection features such as overcurrent, overvoltage, dry-run detection, and thermal shutdown are incorporated to enhance equipment safety and reliability. The GSM-based communication interface allows farmers to operate and supervise motor functions via SMS, ensuring operability even in remote areas with limited internet access. Comprehensive testing demonstrates that the proposed system significantly reduces manual intervention, improves motor longevity, and supports efficient water management practices. The results affirm the system's potential to contribute to sustainable agricultural practices and serve as a foundational platform for future smart farming enhancements.

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Smart Farming, Arduino Uno, GSM Communication, Pump Automation, Motor Protection, Dry Run Detection, Remote Monitoring, Irrigation System, Agricultural IoT, Embedded Systems

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Ayurveda is one of the oldest traditional heritages of our country, offering deep insights into health and longevity. It acts as a treasure trove of life's healthful wisdom, steering individuals towards the core goals of Ayurveda. The acharyas, or sages, through their careful observations, explore the depths of Ayurveda, sharing invaluable knowledge through their texts. In modern times, the idea of circadian rhythm, or biological clock, has garnered considerable interest, defined as the 24-hour cyclical changes that occur within our bodies and their clinical significance. Notably, this concept is also discussed in our ancient scriptures, which have not been given the acknowledgment they merit. These scriptures describe the cyclical nature of doshas, which vary over time and present different symptoms in the body. The acharyas have prescribed daily, nightly, and seasonal routines based on these doshas, which are vital for sustaining overall health throughout life, with each routine possessing its own clinical relevance. Establishing a daily regimen is essential for health, enabling necessary adjustments in body, mind, and spirit. A well-organized routine supports the balance of Tridoshas. Biological rhythms, including circadian, ultradian, and infradian rhythms, regulate bodily functions in a rhythmic fashion, governed by an internal clock. Each Dosha exhibits daily fluctuations influenced by digestion phases and age. Factors such as a person's age, circadian rhythm, and eating habits play a significant role in human physiology. Disruptions in the circadian rhythm, caused by environmental influences and bodily changes, can lead to various health problems known as circadian rhythm disorders. Agni, which signifies digestion and metabolism, can either foster health when properly managed or become harmful if ignored. Grasping the concept of Agni is crucial for maintaining optimal digestive and metabolic health. Both the physiological and pathological aspects of Agni are explored and highlighted. The importance of jataragni must be recognized, as it is responsible for the initial breakdown of complex food into simpler forms for the body to absorb. A disruption in this Agni can lead to the creation of ama, srotodushtilakshana, and various health complications. A thorough understanding of Agni's fundamental principles is essential for accurate diagnosis and effective treatment selection. Classical Ayurvedic texts detail a recommended daily routine, known as Dinacharya and Ritucharya, which outlines daily and seasonal practices for individuals to achieve optimal health and a balanced lifestyle. The principles of Ayurveda help us identify the most advantageous times for daily activities while keeping Doshic rhythms in an ideal state. To maintain health and prevent disorders related to modern lifestyles, it is crucial to understand the circadian rhythm in Ayurveda, the factors that disrupt it, its pathogenesis, and the suggested strategies for resetting it.

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Ayurveda, circadian rhythm, Agni, Tridosh, biological clock.

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Enhancing education and job training in Adivasi regions requires a holistic approach that prioritizes inclusivity, skill development, and economic empowerment. Schools tailored to tribal communities should integrate traditional knowledge with modern subjects, ensuring culturally relevant learning experiences. Training programs focused on agriculture, eco-tourism, handicrafts, and digital literacy can open new employment avenues while preserving indigenous practices. Collaborations with industries and NGOs can provide mentorship, financial support, and career pathways suited to local contexts. Government policies that promote scholarships, vocational centers, and entrepreneurship programs further strengthen opportunities for sustainable livelihoods. By fostering an environment of education, skill-building, and employment-focused training, Adivasi communities can achieve self-sufficiency while retaining their rich heritage and traditions, expanding access to quality education and job training in Adivasi regions is essential for fostering sustainable development and economic empowerment. A comprehensive approach begins with culturally inclusive education that integrates traditional knowledge alongside modern subjects, allowing students to retain their heritage while preparing for contemporary careers. Strengthening digital learning opportunities through mobile technology and internet access can bridge gaps in formal education, especially in remote areas.

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skill development,

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We present initial results from investigations into thin films of a novel material, a double half-Heusler Mn?FeCoGe? thin film deposited onto silicon (100) and glass substrates using thermal evaporation. The specimens were examined for their morphology and crystallographic structure using scanning electron microscopy and diffraction techniques. The composition was analyzed using X-ray spectroscopy. Our investigation further underscores the critical role of stoichiometry in achieving the desired properties of the material.

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Mn2CoFeGe2, Double Half-Heusler, Thin films

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Creative Commons Attribution 4.0 and The Open Definition