Volume 13 | Issue 4 |

 Abstract

Psidium guajava also known as common guava belonging to the Myrtaceae family. Their leaves accelerate follicular activities, diminish dandruff formation, strengthen hair also acts as mild cleansers. Guava leaves are fortified with bioactive composition such as flavonoids, tannins and essential oils. Guava leaves is a potential natural ingredient due to their sustainable content of favorable compounds using Psidium guajava extract in formulation of hair mask can shield hair follicles from damage, can strengthen hair follicles, reduce hair breakage. Also can assist to softer, shinier and healthy hair. Guava leaves if incorporated to hair mask stimulate hair follicles and boost hair growth. The antioxidants present in guava leaves minimize oxidative stress which can damage hair follicle and result to hairfall. Guava leaves are also sustainable because of being abundant in nature also the extraction process is environmental friendly.

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guava leaves extract, hair follicle, hair mask, antioxidant, sustainable, environmental friendly

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 Abstract

In today's constantly shifting global context, informal education is an essential complement to conventional educational systems. Unlike structured classroom education, which has predefined curricula and evaluations, informal education comes naturally from daily experiences, social interactions, media engagement, travel, observation, and self-directed discovery. It is a lifelong, adaptable, and self-motivated process that is highly responsive to individual interests, cultural contexts, and real-world situations. Informal education fosters adaptability, creativity, teamwork, emotional intelligence, empathy, and critical problem-solving abilities--all of which are required for success in today's complicated world. It frequently fills gaps left by formal education, strengthening underprivileged populations while encouraging lifelong learning and inclusive progress. However, the lack of established frameworks and certification creates difficulties in analysis, validation, and integration. This study investigates these issues and presents a paradigm for bridging informal and formal educational approaches, emphasizing informal learning's transformative significance in developing well-rounded, resilient, and innovative individuals. As the world grows more linked and complex, the importance of informal education must be recognized, promoted, and strategically integrated to ensure a future-ready society.

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 Keywords

Education, Learning, Informal education, formal education

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The Syrian Civil War, which began in 2011, is rooted in decades of authoritarian rule, economic mismanagement, and social inequality under President Bashar al-Assad's regime. Widespread unrest emerged from political repression, economic hardships, and sectarian favoritism, particularly against marginalized Sunni Muslims. As the conflict escalated, extremist factions like ISIS gained prominence, complicating the opposition landscape and prompting significant foreign interventions. This multifaceted crisis has not only created a severe humanitarian disaster but has also profoundly altered the balance of power in the Middle East. The war has notably affected Kurdish aspirations for autonomy, as historically marginalized groups sought self-governance amidst the ethnic and sectarian divides exacerbated by the conflict. The Assad regime's dual strategy of repression and tactical alliances with Kurdish forces against ISIS further complicated the dynamics, leading to shifting alliances that reshaped the region's political landscape. Sectarian divides have been a critical factor in transforming the Middle East's balance of power. The Assad regime's brutal repression of Sunni protests and its framing of the conflict in sectarian terms rallied Alawite support while alienating Sunnis. Foreign interventions have further polarized the conflict, with Iran backing Assad and Sunni-majority states supporting opposition groups. This sectarian strife has intensified regional rivalries, complicating peace efforts and contributing to broader geopolitical instability. The emergence of ISIS, exploiting the chaos to enforce its radical Sunni ideology through severe human rights violations, has further deepened sectarian divides and complicated prospects for lasting peace in the region. This report examines the governance strategies of the Assad regime during the Syrian Civil War and their impact on the balance of power in the Middle East. It highlights the regime's brutal repression of dissent, reliance on external alliances with Russia and Iran, and the resulting human rights abuses that fragmented authority amid rising opposition and extremist factions like ISIS. Iran's military and logistical support has reinforced Assad's position while deepening sectarian tensions, as it seeks to bolster Shia influence against Sunni adversaries. Russia's military intervention since 2015 has further solidified Assad's regime, enhancing its geopolitical interests and complicating U.S.-Russia relations. Meanwhile, Saudi Arabia's support for opposition groups reflects its efforts to counter Iranian influence, though challenges such as fragmentation among rebel factions and evolving U.S. policies have complicated its objectives. Overall, the interplay of these dynamics underscores a shifting balance of power in the region, characterized by increased foreign intervention, sectarian strife, and a humanitarian crisis that complicates prospects for peace and stability. The fall of President Bashar al-Assad's regime in Syria signifies a crucial shift in the Middle East's balance of power, following over a decade of civil war. The regime's weakened military, compounded by diminished support from key allies Russia and Iran, has led to significant territorial losses, including the recent rebel offensive that captured Damascus. This collapse has created a precarious state in Syria, characterized by escalating violence and a dire humanitarian crisis affecting over 17 million people. UN officials stress the urgent need for a credible political transition and the preservation of state institutions amidst widespread instability. Iran's influence is notably waning as Hezbollah reallocates resources to confront Israel, complicating its regional strategy and weakening its military posture. The emergence of Islamist rebel leadership poses new security challenges for Israel and risks further destabilizing Iran's proxy networks. As regional and global powers vie to fill the power vacuum, the implications for foreign policy and stability in the Middle East remain profound and complex, necessitating increased international support and funding to address the humanitarian crisis and facilitate aid delivery across conflict lines.

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syrian civil war,ISIS, Middle East, Russia, USA, Humanitarian crisis, UN.

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Retinopathy of Prematurity (ROP) is a significant cause of visual impairment among preterm infants, but its impact extends beyond vision to broader neurodevelopmental outcomes.(1) This narrative review explores findings from an observational study conducted in Belagavi City, assessing the cognitive, language, motor, social-emotional, and adaptive behavior development of children with ROP at three years of age using the Bayley Scales of Infant and Toddler Development IV (BSID-IV). Results indicate that while social-emotional domains are relatively preserved, significant delays are evident in cognitive, language, and motor domains. Risk factors such as severe ROP, low birth weight, consanguinity, and maternal factors like preeclampsia were associated with poorer developmental outcomes. Early neurodevelopmental screening and targeted interventions are recommended to improve the developmental trajectories of these children.

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Keywords: Retinopathy of Prematurity, Neurodevelopment, BSID-IV, Cognitive Delay, Motor Delay, Belagavi

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The rise of autonomous and semi-autonomous machinery in industrial settings necessitates advanced safety mechanisms to ensure smooth operation while preventing collisions and protecting nearby workers. This project proposes an AI-based Extreme-Edge Collision-Avoidance System utilizing a Temporal Convolutional Network (TCN) deployed on an STM32 microcontroller. The system integrates multiple sensing technologies, including LIDAR, Camera Modules, Ultrasonic Sensors, and Infrared Sensors, to comprehensively monitor the machine's surroundings. At the system's core, the STM32 microcontroller processes real-time data from the sensors via a driver circuit, ensuring ultra-low-latency response. AI-based monitoring runs on a Raspberry Pi, analyzing time-series sensor data using the TCN model to detect potential hazards in real-time. The AI algorithm predicts collision risks and enhances situational awareness, ensuring timely interventions critical for industrial safety. Upon detecting an obstacle, the STM32 microcontroller triggers immediate corrective actions, controlling machinery operations while engaging an alarm and alert system to notify nearby workers. The integration of Raspberry Pi extends computational flexibility, supporting data logging, visualization, and remote monitoring, while enabling machine learning model updates. The system ensures robust performance in noisy and dynamic industrial environments by leveraging sensor fusion and AI. Extreme-edge processing minimizes latency, optimizes energy consumption, and maintains a compact memory footprint. Designed for seamless integration into industrial applications, this real-time collision avoidance system significantly enhances workplace safety, reduces accidents, and improves operational efficiency.

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Collision avoidance, Industrial safety, Edge computing, Ultrasound sensors, Temporal Convolutional Network (TCN), Machine learning, Low-power MCU, Raspberry Pi, Real-time processing, Sensor fusion, Acoustic noise robustness, Embedded systems, Proximity sensing, Smart manufacturing, Industrial automation.

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Automatic License Plate Recognition (ALPR) is an advanced computer vision technology that extracts vehicle registration numbers from images and videos for various applications, including security, traffic management, and automated parking systems. This research focuses on developing an efficient and accurate ALPR system leveraging Optical Character Recognition (OCR) and Fuzzy Searching techniques to enhance accuracy, even with noisy or unclear images. The system follows a structured approach where license plate images are first captured through a camera, processed using OCR to extract alphanumeric characters, and further refined with fuzzy searching algorithms to handle variations caused by lighting, font differences, and image distortions. The extracted license number is then matched against a database to identify the vehicle owner and generate real-time reports for security personnel, administrators, or authorities. A key contribution of this research is the integration of real-time analytics and a user-friendly dashboard for monitoring visitor logs, security access, and traffic trends. The proposed model is tested on a dataset of license plate images under varying environmental conditions to evaluate performance in terms of accuracy, processing time, and robustness. Experimental results demonstrate that our approach significantly improves recognition accuracy compared to traditional OCR-based models, particularly in challenging scenarios. This work has broad applications in smart parking systems, automated toll collection, vehicle entry management in organizations, and traffic surveillance. The future scope includes integrating deep learning-based recognition methods, expanding the dataset to accommodate multiple regional plate formats, and enhancing security features with blockchain-based data integrity.

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 Keywords

License Plate Recognition, OCR, Fuzzy Searching, Image Processing, ALPR, Smart Security, Automated Vehicle Identification.

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Creative Commons Attribution 4.0 and The Open Definition

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Federalism, as a system of governance, distributes power between a central authority and constituent political units, such as states or provinces. This research paper provides a detailed analysis of federalism, evaluating its pros and cons in contemporary governance. Drawing on scholarly literature and theoretical frameworks, the paper investigates how federalism promotes democracy, diversity, and accountability, while also exploring its challenges in coherence, efficiency, and governance. Additionally, the paper discusses relevant topics such as fiscal federalism, intergovernmental relations, and the role of federalism in managing crises and fostering innovation.

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Federalism, Authority, Governance, power, state, intergovernmental

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In today's digital world, typing efficiency and accuracy are crucial for seamless communication. Users often struggle with slow typing speeds and frequent errors, especially in text-based interfaces. Next Word Prediction is a critical application of Natural Language Processing (NLP) that enhances user experience in text input systems by suggesting the next probable word based on the context. It focuses on implementing a Next Word Predictor using Long Short-Term Memory (LSTM) networks, a type of Recurrent Neural Network (RNN) designed to handle sequential data efficiently. LSTMs are well-suited for capturing long-term dependencies in text, enabling context-aware and accurate predictions. The model is trained on a large text collection, allowing it to learn linguistic patterns, grammatical structures, and semantic relationships between words. Preprocessing steps include tokenization, embedding, and sequence generation, which prepare the data for training. The system is evaluated using perplexity and accuracy metrics to ensure performance, improving both typing speed and accuracy. LSTM-based Next Word Prediction models can be integrated into various applications, including virtual keyboards, chatbots, and assistive writing tools, enhancing user interaction.

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 Keywords

Natural Language Processing (NLP), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), Linguistic Patterns, Grammatical Structures.

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ABSTRACT:- Brand loyalty plays a massive role by acting as a critical determinant of consumer behaviour thereby influencing purchase patterns and long-term brand attachment. Specially in an environment which is increasingly shaped by rapid dissemination of information and negative word-of-mouth (NWOM). Understanding the protective function of brand loyalty has become crucial in a world where negative word-of-mouth (NWOM) and the quick spread of information are shaping society more and more. The goal of this study, "Shielded by Loyalty: Analyzing Consumer Resistance to Negative Word-of-Mouth," is to investigate how consumer resistance to NWOM and brand loyalty are related. The study's goals are to determine how loyal consumers are to a brand, how much they are exposed to unfavorable word-of-mouth, and how loyalty levels relate to resistance behaviors. To determine whether loyalty serves as a protective barrier against adverse influences, special consideration is given to extremely devoted customers. A structured questionnaire that can be accessed by a wide range of people, including common and semi-literate consumers, is used to gather primary data. To analyze the data, statistical tools are used, with an emphasis on finding trends, correlations, and differences among various loyalty segments. It is anticipated that the results will show a positive correlation between resistance to NWOM and brand loyalty, emphasizing loyalty as a moderating factor in consumer decision-making. The study adds to the body of knowledge on consumer behavior and offers useful advice for brand strategists who want to improve customer retention and brand resilience against reputational risks.

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Key words:- Consumer Behaviour, Brand Loyalty, Negative Word-of-Mouth, Consumer retention.

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 Abstract

Mergers and acquisitions (M&A) have repeatedly emerged as a favored strategy for organizations seeking to expand beyond their organic capacities. In contrast to internal growth, which can be slow and limited by resource availability, mergers and acquisitions provide companies with a more rapid and significant means of expansion. Through these strategic agreements, corporations might penetrate new markets, expand their product offerings, gain technological competencies, or remove competition. M&A serves as a potent instrument for corporate restructuring, enabling firms to reorganize activities, optimize processes, and enhance overall efficiency. The incentives for mergers and acquisitions are primarily economic, typically based on the desire for enhanced profitability, expanded market share, and enduring sustainability. Companies may opt to merge with or purchase others in reaction to evolving industry dynamics, new consumer needs, or macroeconomic concerns. Every transaction is distinct, shaped by a confluence of strategic foresight, fiscal preparedness, and regulatory structures. This research seeks to examine the financial ramifications of M&A activities, specifically analyzing the impact on the financial performance of acquiring corporations before and after the merger or acquisition. The paper examines a series of chosen M&A deals in India throughout two notable periods to accomplish this objective. The research employs a series of essential financial ratios--namely profitability, liquidity, leverage, and efficiency ratios--to assess the performance of acquiring firms during these intervals. These financial indicators provide a thorough overview of the companies' operational and financial well-being. Additionally, the paired t-test at a 5% significance level is utilized to evaluate the statistical significance of the variations in financial performance pre- and post-merger. This meticulous methodology guarantees that the results are both sound and dependable, enhancing the comprehension of the actual financial implications of M&A selections inside the Indian business environment.

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 Keywords

Mergers and Acquisitions (M&A), Inorganic Growth, Financial Performance, Strategic Restructuring, Acquirer Company, Pre-Merger Analysis, Post-Merger Analysis, Financial Ratios, Statistical Analysis, Indian Corporate Sector, Profitability, Liquidity, Leverage

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