Volume 12 | Issue 12 |

 Abstract

One could argue that clove is the most potent antioxidant currently known. The U.S. Department of Agriculture created the Oxygen Radical Absorption Capacity (ORAC) test as a way to compare antioxidant activity. Clove's ORAC value is higherthan10million. A drop of clove oil contains 400 times the antioxidant power of wolf berries or blueberries. People have been aware of cloves' health advantages for thousands of years. It is an effective natural remedy for many ailments. In addition to its culinary uses, clove buds have many medicinal and recreational uses. Home kitchens account for the majority of clove spice consumption worldwide. Nonetheless, the clove is used commercially to make clove oil, which contains active ingredients with anti-inflammatory, anti-thrombotic, anti-fungal, anti-viral, anti-microbial, anti-diabetic, anaesthetic, pain-relieving, and insect-repellent qualities. The primary ingredient in clove buds that gives them their therapeutic qualities is eugenol. Given the foregoing, we felt it was worthwhile to put together a current review paper on cloves that covers their chemical components, synonyms, phytopharmacology, and therapeutic applications.

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 Keywords

Introduction, common name, Synonyms, Chemical constituents, Medicinal used

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Human Activity Recognition (HAR) plays a crucial role in health monitoring, smart environments, and human-computer interaction. This study investigates four machine learning models Logistic Regression, Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) for activity identification using mobile sensor data. The dataset comprises gyroscope and accelerometer readings from smartphones. Preprocessing techniques such as feature extraction, noise reduction, and normalization are applied to enhance model performance. The results indicate that while Logistic Regression provides a reliable baseline, ANN, LSTM, and GRU models outperform it, particularly in capturing temporal dependencies. Among the evaluated models, The GRU model delivers the best performance, achieving an accuracy of 97.2% and a loss of 0.28%.

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 Keywords

Human Activity Recognition, HAR, Mobile Sensors, Logistic Regression, Artificial Neural Networks, Long Short-Term Memory, GRU, Deep Learning.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Kidney stones associated with pain and suffering. Kidney stone disease (KSD) (also called nephrolithiasis/or urolithiasis )is a global health issue that progresses affecting people in almost all developed and developing countries. This spread-out disease around the world carries an incidence of 5-15%. Its prevalence is considerably on the higher side with recurrence mostly after treatment. While many methods are available to treat Kidney stone disease, their prevention should be adopted to decrease the suffering and economic burden of Kidney stone disease. The pathogenesis and risk factors leading to stone formation must be known before the control measures for the formation of stones can be instituted. Less urine output and dehydration remain common risks for every type of stone, while hypercalciuria, hyperoxaluria, and hypocitraturia remain major risks for calcium stones. Thus, in this article will be find up-to-date knowledge-based strategies mainly on prevention and Kidney stone disease. Fluid intake particularly is very important (water-2.5-3.0 L/d). Diuresis has also been encouraged. With dietary restrictions, we can minimize the incidence and recurrence of kidney stones. The present review focuses on the pathophysiology and available treatment options for the kidney stones.

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 Keywords

Bioactive compound, citrate, diuresis, natural compound, nephrolithiasis, probiotics, protection, urolithiasis, Renal stones, Colic, Calcium stones, Calculi, Dietary , Lifestyle, western world , disease management , Korean and European company .

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Access to justice is a fundamental right, yet millions lack adequate legal resources. AI chatbots are proposed as transformative tools to bridge this gap by democratizing legal information access. This paper synthesizes insights from case studies, user-centric research, and technical evaluations to explore their potential. It highlights key barriers, including ethical concerns, technical limitations, and user trust issues. Emerging findings underscore the role of tailored implementations like LEGALBOT and JuridiQC's AI-based search tools in addressing these challenges. The study concludes with recommendations for optimizing chatbot efficacy in legal contexts.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Access to Justice, AI Chatbots, Legal Information, User Trust, Natural Language Processing, Ethical Challenges.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Flavonoids, a class of naturally occurring polyphenolic compounds, have shown significant potential in cancer prevention and treatment, particularly for lung cancer. Widely present in fruits, vegetables, and plant-derived foods, flavonoids exhibit a range of biological properties, including antioxidant, anti-inflammatory, and anticancer effects. Studies suggest that dietary flavonoids can serve as effective agents to mitigate lung cancer risk by targeting various carcinogenic pathways. The anticancer mechanisms of flavonoids involve multiple molecular pathways. They exhibit antioxidative effects by scavenging free radicals and preventing DNA damage, which can lead to mutations and tumor initiation. Furthermore, flavonoids modulate key signaling pathways such as PI3K/Akt and MAPK, inhibit cell cycle progression, and induce apoptosis in cancer cells. Notably, flavonoids target receptor tyrosine kinases (RTKs), such as EGFR and VEGFR, which play critical roles in lung cancer development. By inhibiting these receptors, flavonoids disrupt signaling cascades that promote tumor proliferation and survival. In conclusion, flavonoids offer a natural, safe, and cost-effective approach to lung cancer prevention and treatment.

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 Keywords

Flavonoids, Receptor tyrosine kinase, Lung cancer.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Technological developments have impacted almost every aspect of life over the past few decades and are still growing. One such technological development that is being utilized in numerous industries and has the potential to drastically alter the world is artificial intelligence (AI). Artificial Intelligence (AI) is software that has the ability to think effectively, much like a human. There are four types of artificial intelligence (AI), according to some research: systems that behave like people, think like people, and act like people. Bersin (2018) claims that AI is currently integrated into many commercial activities and found in most software applications. A particular company function is human resources (HR), whereby AI integration is occurring more rapidly with respect to various HR functions such as recruitment, orientation, and training, to mention a few. AI integration in HR will allow HR professionals to focus more on strategic duties and less on lower-value, repetitive chores, but it does not mean that AI will completely replace HR managers. As a result, the image of how AI might help streamline and reorganize HR operations for greater agility and efficiency is undoubtedly more complicated. This article, which focuses on qualitative research, aims to explain how AI has been integrated into various HR tasks and its effects on firms, employees, and HRs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI, HRM, Talent Acquisition, web based HRM, Learning and Development, HR practices

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The deployment of a powered by sunlight wireless charging system is examined in this research in order to meet the increasing demand for effective battery charging for electric cars (EVs). Since EVs are becoming a viable way to cut pollution, upgrading the infrastructure for charging them is essential to increasing customer convenience and dependability. Over the past 30 years,wireless power transfer (WPT) and solar energy harvesting have advanced significantly, especially in terms of power levels that can be used for charging. The capacity to forecast when solar energy will be most available determines how effective such a system will be reducing dependency on the grid and optimizing the usage of clean, renewable energy. By surpassing the constraints of battery technology, this study seeks to stimulate additional advancements in solar-based

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Wireless Power Transfer_(WPT), Solar energy, Electric vehicles (EVs), Wireless charging, Renewable energy, Solar-powered WPT, Battery charging, Sustainable transportation, Dynamic charging, Stationary charging, Green energy solutions

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

With the ever-growing awareness pertaining to dental esthetics, there is greater emphasis by parents on obtaining satisfactory solutions to unsightly dental problems in their children. From the perspective of the health of permanent teeth, proper intake of diet, phonetics, space maintenance and esthetic appreciation, the significance of primary teeth cannot be ignored. It is, however, challenging to restore extensively destroyed anterior teeth with restorations that are durable, retentive, as well as esthetic owing to several factors. A strip crown is essentially a crown form filled with a composite that is bonded onto the tooth. Since these composite crowns provide superior esthetics than other forms of anterior coronal coverage restorative options and are easy to repair in case of subsequent chip or fracture, they are extremely popular for restoring primary anterior teeth. Despite the technique being used for over two decades, longitudinal clinical data on the longevity of these crowns are limited and there is a definite paucity of literature concerning the clinical success based on the extent of surface area used for adhesion and therefore in this current case report, retention was increased by giving retentive points on the buccal and palatal aspect thereby increasing the macro mechanical retention along with micro mechanical retention.

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 Keywords

strip crown, aesthetics, retention, early childhood caries, resin composite.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Heart disease remains one of the leading causes of mortality worldwide, necessitating the development of accurate and efficient prediction systems to enable timely diagnosis. This study evaluates the performance of four machine learning models--Logistic Regression, Decision Tree, Support Vector Machine (SVM), and Convolutional Neural Network (CNN)--for heart disease detection. The models were trained and tested on a structured dataset, and their performance was compared using metrics such as accuracy, precision, recall, and F1-score. CNN demonstrated the highest performance with an accuracy of 89%, outperforming traditional models due to its ability to capture complex data patterns. Logistic Regression and SVM achieved comparable results with an accuracy of 88%, highlighting their effectiveness in structured data environments. The Decision Tree model showed relatively lower performance with an accuracy of 85%, limited by its overfitting tendencies. This comparative study highlights the strengths and limitations of each model, providing valuable insights into their suitability for heart disease prediction. The findings emphasize the potential of CNN in delivering reliable predictions and pave the way for future enhancements through model optimization, ensemble techniques, and real-world deployment in medical applications

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Heart Disease, Machine Learning, Deep Learning, Logistic Regression, Decision Tree, Support Vector Machine, Convolutional Neural Network

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Children's Hobbies Prediction, Forecasting, Django Framework

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Creative Commons Attribution 4.0 and The Open Definition