Volume 13 | Issue 4 |

 Abstract

Androsace globifera contains significant phytochemicals such as saponins and is utilized for treating liver and kidney diseases, amenorrhea, skin allergies, leucorrhoea, and as an abortifacient. Morphological studies reveal that the leaves are diverse in shape, ranging from speculating to elliptical. Organoleptic analysis indicates an astringent taste, aromatic odor, and brittle fracture, with the stem being straight and colored brownish-green. The flowers are pink with 12-15 blooms, five petals, seven sepals, a 1.5 mm style, and a 3 mm capsule. The powdered leaves and roots are greenish and brown, respectively, with an astringent and aromatic odor, and a bitter and acrid taste. Microscopic and physicochemical studies identify vascular bundles and upper and lower epidermal cells. The moisture content of roots and leaves is 2.5% and 3%, respectively. The total ash content of roots and leaves is 25% and 22.5%, acid-insoluble ash is 12.5% and 9%, and water-soluble ash is 10% and 8.9%. The extractive values for roots and leaves are as follows: water (0.8% and 1%), ethanol (4% and 2.25%), chloroform (8% and 8.5%), ethyl acetate (9% and 7%), and methanol (11% and 13%). Leaf constants include a stomatal number of 5, a stomatal index of 2.5-7, a vein islet number of 11-17, a vein termination number of 9-12, and a palisade ratio of 2:6. Fluorescent studies show the leaves and roots as light brown and dark brown, respectively. Histochemical analysis reveals the presence of lignified cellulose and cuticular cell walls, aleurone grains, calcium oxalate, fatty acids, resins, inulin, mucilage, tannins, and hydroxyl anthraquinones.

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 Keywords

Androsace globifera, Characteristics, Evaluation, Microscopy, Screening

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 Abstract

This paper presents the design and implementation of a versatile floor cleaning robot, controlled through an Android application. The robot integrates multiple cleaning functionalities--vacuuming, mopping, spraying, and drying--while ensuring effective navigation and obstacle avoidance. It is equipped with a modular cleaning platform, adjustable cleaning pads, and real-time resource and battery monitoring, all controlled through a user-friendly mobile interface. Building on previous research in smart home systems, intelligent path planning, and sensor fusion, the proposed system maximizes cleaning efficiency and adaptability, while significantly reducing user effort. The robot's ability to adapt to various floor types, optimize cleaning routes, and enable remote operation via mobile scheduling and monitoring is demonstrated through experimental tests. This work advances the development of energy-efficient cleaning devices and smart home automation.

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 Keywords

Autonomous cleaning robot, Smart home, Obstacle detection, Android control, Vacuuming, mopping, Adaptive navigation

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 Abstract

This report investigates the existing work on optimizing house price estimation with machine learning and deep learning techniques. Focusing on its base data types structured and then multi-modal (price, geospatial etc.) it runs through essential algorithms such as Linear Regression, XGBoost and Neural Network and compares their capabilities pros and cons. From the results, it emphasizes the ability of these methods to enhance predictive accuracy based on heterogeneous data sources, whilst challenges such as interpretability of models and integration of data persist. Promising future directions to move the field forward, such as hybrid models and multi-modal approaches, are discussed.

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 Keywords

Deep learning, machine learning, house price prediction, multi-modal data, neural networks, regression analysis, feature engineering, hybrid models

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 Abstract

For domestic, agricultural, and industrial purposes, groundwater is an essential supply of fresh water in India, particularly in regions with inadequate surface water infrastructure. Groundwater quality in Coimbatore, Tamil Nadu, a fast-growing metropolis renowned for its textile industries, is being weakened by pollution from sewage, automobile emissions, industrial discharges, and agricultural runoff. The physicochemical properties of borewell water from western Coimbatore's non-traffic and traffic-congested areas are compared in this study. To evaluate water quality and comprehend the impact of human activity, parameters including pH, TDS, hardness, chloride, and microbiological content were examined. The study emphasises the influence of urbanisation and traffic-related pollution on groundwater, pointing out notable variations in water quality between the two zones.

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 Keywords

Groundwater quality, Borewell water, Physicochemical analysis, Urban pollution, Traffic areas, Coimbatore, Water contamination, Sustainable water management, Industrial effluents, Microbial content.

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The rapid advancement of Artificial Intelligence (AI) has introduced new complexities into the traditional framework of Intellectual Property Rights (IPRs). This research explores the legal challenges posed by AI-generated works in the Indian context, focusing on three primary domains of IP law--copyright, patents, and trademarks. It critically analyzes whether the existing legal structure, which assumes human authorship and inventorship, is equipped to handle autonomous or semi-autonomous outputs generated by AI systems. Drawing upon doctrinal research, comparative analysis with jurisdictions such as the United States, the European Union, and the United Kingdom, and policy reports by international organizations like WIPO, this paper reveals significant doctrinal and enforcement gaps in Indian IP law. It argues for the introduction of sui generis rights for AI-generated creations and recommends legislative amendments to accommodate AI's growing role in innovation and branding. By proposing a reform-oriented legal framework rooted in accountability, transparency, and global compatibility, the paper advocates for India to lead a proactive IP law transformation suitable for the AI era.

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 Keywords

Artificial Intelligence, Intellectual Property Rights, Copyright, Patents, Trademarks, India, Legal Reform, Sui Generis Rights, AI-Generated Works, Innovation Law Acknowledgement

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Agriculture forms the foundation of numerous nations, including India, sustaining millions by overcoming challenges like climate shifts and outbreaks of plant ailments. Innovative research has led to the creation of a web-based platform offering real-time guidance on optimal crop choices, considering points such as soil health, temperature, humidity, ph levels.This platform brings together advanced machine learning and deep learning techniques to address critical areas of precision agriculture. It comprises five key modules: Crop Recommendation, Yield Prediction, Plant Disease Detection, Smart Farming Guidance, and Weather Forecasting .The Crop Recommendation module suggests the most suitable crops for cultivation based on parameters such as soil type, pH, nutrient content, and regional agro-climatic conditions. This promotes sustainable crop planning and resource optimization. The Yield Prediction engine uses historical yield data, meteorological records, and agricultural inputs to forecast potential productivity, aiding in economic planning and supply chain management. Through the Plant Disease Detection module, farmers can identify diseases early by uploading images of affected crops, which are analyzed using convolutional neural networks to suggest accurate diagnoses and treatments. The Smart Farming Guidance system delivers dynamic recommendations for irrigation scheduling, nutrient management, and pest control tailored to current crop conditions. Additionally, the Weather Forecasting component offers hyper-local predictions, enabling timely interventions to mitigate climate-related risks. Collectively, AgriSense stands as a holistic advisory platform that empowers farmers, enhances crop productivity, and contributes to the advancement of smart and sustainable agriculture globally.

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crop recommendation, machine learning, plant disease identification, random forest, weather-forecast ,fertilizer recommendation.

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This paper proposes a Smart Industrial Real-Time Water Quality Monitoring and Prediction System that integrates the Internet of Things (IoT) and machine learning to improve industrial water management and environmental safety. The system monitors key water parameters -Total Dissolved Solids (TDS), ammonia concentration, pH, turbidity, and temperature via dedicated sensors connected to an Arduino microcontroller, with data transmitted to the Thing-Speak cloud platform using an ESP8266 Wi-Fi module. Real-time alerts are facilitated through an on-site buzzer and a Telegram bot to notify users of abnormal conditions. For predictive analytics, the system employs machine learning algorithms such as Random Forest, Naive Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), XG-Boost, Logistic Regression, and Decision Tree to classify water quality status based on historical data. This unified framework provides a scalable and cost-effective solution for continuous monitoring, early warning, and data-driven decision-making across industries such as manufacturing, agriculture, and wastewater treatment.

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 Keywords

Water Quality Monitoring, Internet of Things (IoT), Machine Learning, Real-Time Prediction, Industrial Water Management, Environmental Safety.

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 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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Creative Commons Attribution 4.0 and The Open Definition

 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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Education, Learning, Informal education, formal education

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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 Keywords

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

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