Volume 13 | Issue 4 |

 Abstract

Nowadays, people are interested in hair preparations and conditioner materials, such as shampoos, hair tonic and conditioner formulations containing herbal extracts. The Aim of present study involves preparation of herbal hair tonic by using Fenugreek leaves, Tulsi leaves, Hibiscus flower, Curry leaves and coconut oil, Almond oil, Clove oil, Eucalyptus Using the Direct Method, oil and a crude medication mixture were made into herbal hair tonic, and their antifungal and antibacterial properties were assessed. Batches F1, F2, and F3 with varying concentrations are used to construct the final preparation of these substances. F1, F2, F3 formulation is tested for antibacterial and antifungal activity. The formulation of different concentrations was characterized for analysis including Moisture content, Acid value, Saponification value, Specific gravity. The formulation exhibits favorable organoleptic qualities, no grittiness, good consistency, good spread ability, homogeneity, appearance, and pH, as well as good antifungal and antibacterial activity. Result was determined and are reported in this work.

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 Keywords

Herbal formulations, anti-fungal activity, anti- bacterial activity, hair tonic, coconut oil and almond oil

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents the design, development, and evaluation of an intelligent mock interview platform aimed at improving career readiness through real-time, AI-driven simulations. Leveraging Google's Gemini (PALM) large language model, the system dynamically generates domain-specific interview questions and evaluates user responses based on contextual relevance, fluency, and delivery. Built using JavaScript, Tailwind CSS, Firebase, and WebRTC, the platform delivers an immersive, role-based experience simulating real-world interviews. Users select a job role to receive customized sessions, during which their audio or video responses are analysed in real time. Gemini's semantic understanding enables automated feedback across articulation, content depth, confidence, and role alignment, with session data stored securely in Firebase for review and iterative learning. The architecture comprises a user interface layer, an AI services layer powered by Gemini APIs, and a data services layer. Evaluation with 75 participants from fields such as software engineering, marketing, and data science showed a 38% improvement in performance over three sessions, validated through both automated and expert assessments. User feedback emphasized the platform's realism and adaptability. This study demonstrates the effectiveness of large language models in enhancing communication skills and proposes future enhancements including emotion analysis, multilingual support, and longitudinal impact studies.

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 Keywords

Mock Interview, Gemini PALM, Real-time Feedback, Career Development, Audio-video AI, Firebase, Google Gemini PALM, AI-based Interview Training, Job Interview Practice Platform

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India's competition law framework has undergone significant reforms with the Competition (Amendment) Act, 2023, and new regulatory updates that aim to improve penalty structures, streamline merger control, and strengthen enforcement. These changes indicate a shift toward improved dispute resolution procedures, increased regulatory transparency, and stricter control of anti-competitive activities. These reforms align India's competition legislation with worldwide best practices by encouraging fair competition and protecting consumer interests, but they also raise new compliance concerns for businesses. Among the significant changes that will guarantee speedier and more comprehensive regulatory oversight are the Deal Value Threshold (DVT) for M&A transactions, a revised definition of "control," and shortened merger review timelines. The 2024 CCI regulations also introduce settlement and commitment mechanisms, revised turnover-based penalties, and formal recognition of 'hub and spoke' cartels, expanding the scope of anti-competitive conduct enforcement. This paper explores the key regulatory developments, their broader implications for market participants, and the evolving role of the Competition Commission of India in shaping a competitive and transparent economic environment.

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 Keywords

Competition Law, Antitrust Regulation, Market Competition, Merger Control, Abuse of Dominance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Listened fed people face important challenges in the urban environment, as it is an inability to detect important hearing signs such as vehicle horns, emergency sirens and other traffic -related sounds. Navigating in busy roads without awareness of going to vehicles leads to a serious security risk that limits their dynamics and freedom. To solve the problem, the project suggests an IoT-based Help Smartwatch designed to detect real-time vehicle sounds and provide intuitive alerts through light signals and vibrations.The system includes a sound detection sensor, an ESP32 microcontroller and a machine learning-based classification models, which accurately identify the sound of the vehicle when filtering the background noise. A hybrid CNN- SVM model is used to ensure accurate sound classification, and separates a variety of traffic sounds such as car horns, ambulance sirens and heavy vehicle engines. When you detect a possible danger, the smart watch activates LED indicators and vibrates with different intensity depending on the urgency of the detected sound.

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 Keywords

IoT, Assistive Technology, Hearing Impairment, Smart Wearables, Sound Detection, Vibration Alerts, Urban Safety.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The safety of railway transportation systems largely depends on the condition of the tracks. Track damages, especially cracks, can result in severe operational hazards if not detected in time. Traditional inspection techniques often fall short due to their manual nature and inefficiency in covering long distances. With the emergence of image processing and sensor-based technologies, several automated systems have been developed for crack detection. This paper presents a detailed overview of recent innovations in this field, including methods involving LED-LDR sensors, image analysis, infrared and ultrasonic sensors, and data analytics. Each method's architecture, effectiveness, and real-world feasibility are discussed to aid future implementations in railway infrastructure maintenance. Automated crack detection systems significantly reduce the need for human intervention and enable continuous monitoring. These systems offer high accuracy, reliability, and the capability to operate under varying environmental conditions. Sensor-based techniques such as ultrasonic testing and infrared thermography provide real-time data on track integrity, while image processing algorithms enable the identification of micro-cracks that are otherwise difficult to detect. Deep learning and machine learning models further enhance the precision of detection systems by learning from large datasets and identifying complex patterns. The integration of GPS and IoT modules allows for real-time tracking and remote monitoring, further optimizing maintenance schedules and resource allocation. Several experimental and commercial systems have been reviewed, highlighting their design considerations, implementation challenges, and cost-effectiveness. A comparative analysis of different detection techniques is also provided to evaluate their suitability across diverse railway environments. The paper emphasizes the need for hybrid systems that combine multiple technologies for improved accuracy and robustness. Future research directions include the development of lightweight, energy-efficient systems and the integration of AI for predictive maintenance.

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IOT

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 Abstract

The quick demand for electric vehicles (EVs) results in the development of effective, environmentally friendly, and user-friendly charging infrastructure necessary. This study investigates the design and optimization of an EV wireless rapid charging system that uses solar electricity and state-of-the-art wireless power transfer (WPT) technology. Photovoltaic (PV) panels serve as the main energy source in the suggested system, which also includes a high-frequency inductive coupling for wireless charging and an effective power management unit. To improve system performance, a multi-layered optimization technique is used, with a particular emphasis on three important areas: overall system reliability, wireless transmission efficacy, and solar energy harvesting efficiency. Energy conversion efficiency, charging time, system losses, and operating cost are examples of key performance metrics. The findings show that the suggested system can achieve high energy efficiency while lowering reliance on grid electricity with the right optimization, supporting green transportation alternatives. The system's wireless nature also improves user convenience and safety, which makes it appropriate for installation at highway charging stations and smart cities.

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 Keywords

Wireless Power Transfer , Power Management Unit , Solar Powered , Electric Vehicles

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Most of us spend a large part of our lives at work, so it plays a big role in our overall well-being. Because of this, it's very important to have a job that supports both our mental health and general health. Workplaces that support employees' mental health and help those going through tough times usually see their teams work better and get more done. Mental health refers to how someone thinks and feels about themselves and their life. It also includes a person's ability to do their best and stay connected with family, friends, coworkers, and their community (Mental Health Foundation, 2008). Today, one of the main reasons people struggle at work is because of mental health challenges caused by their job. Issues like anxiety,stress and depression are becoming more common in the workplace. In fact, depression is expected to become the second most common health issue in the world, right after heart disease (Murray & Lopez, 1996). This paper aims to explore and highlight the key factors--based on existing research--that are most likely to affect mental health at work.

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mental health, workplace, employees, anxiety, depression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Attitudes towards different hair, such as hairstyles and hair removal, vary widely across different cultures and historical periods, but it is often used to indicate a person's personal beliefs or social position, such as their age, sex, or religion. As hair is considered as barometer of beauty each one is over conscious about it and is in search for a better remedy for the maintenance and management of their crowning glory. Alopecia areata is characterized by acquired skin aliment that can affect all the hair bearing skin including scalp, beard, which is characterized by localized areas of non-scarring hair loss which can be compared with Indralupta. In Ayurveda literature Acharyas had briefly explain hair and mentioned many more modalities to treat hair loss. Nidana Parivarjana, Prachanna, Shamanoushadhi and externally use of Lepa. Prachanna Karma is a specialized form of Raktamokshana (bloodletting) in Ayurveda, primarily utilized for expelling vitiated blood and treating localized disorders. Indralupta, which according to modern goes with the name as alopecia, a condition characterized by sudden hair loss, is often associated with vitiation of Pitta and Kapha Doshas, leading to obstruction of hair follicles. This research explores the effectiveness of Prachanna Karma in the management of Indralupta, its historical references, procedural methodology, and modern clinical relevance. A thorough review of Ayurvedic texts, along with contemporary findings, is presented to establish the efficacy of this treatment.

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 Keywords

Alopecia areata, Indralupta, Ayurveda, Prachaanakarma, Lepa.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As we know, many people suffer from unhappiness in today's world, so there is a requirement for a system that recommends music based on human emotions such as anger, sadness, happiness, etc. In this paper, we propose a system named Multimodal Emotion Detection which helps people by suggesting music and movies based on their emotions. We implemented this system using the FER- 2013 dataset, which contains 35,887 images of different emotions such as sadness, happiness, neutral , surprise, disgusted, fearful, and anger. We used Python's TensorFlow framework and Haar Cascade algorithms to recommend movies and music based on human facial emotions. The main concern in existing recommendation systems is manual sorting. To avoid this, we propose this model, which automatically plays music and movies without requiring much browsing time.

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Image processing, Facial recognition, Movie Recommendation, Song Recommendation . 2 [1-2]

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Emotional stability plays a vital role in personal well-being and everyday functioning. This research explored the use of data analytics to evaluate and comprehend emotional stability, concentrating on psychological, behavioral, and environmental elements like stress. By examining survey responses, communication trends, and psychological evaluations, the study compared the reliability of the Cronbach and Omega methods. Gated Recurrent Unit (GRU) models were employed to forecast stress levels among student groups. The research developed predictive models for outcomes such as overall emotional stability, the risk of mental health problems, academic satisfaction, perceived social support, and stress levels. The analysis aimed to identify significant connections between input features and predicted outcomes, assess model performance using relevant metrics, and determine the importance of individual attributes in predicting students' well-being. It also offers valuable insights into the quantitative measurement of emotional stability and its variations in different situations.

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 Keywords

Cronbach's Alpha, Omega method, Psychometric Analysis, RNN, LSTM,GRU.

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Creative Commons Attribution 4.0 and The Open Definition