Volume 12 | Issue 5 |

 Abstract

The current investigation aims to explore the English learning challenges faced by rural Cuddalore District high school pupils.152 samples were drawn utilizing the random sampling technique from a variety of rural Cuddalore District schools. The normative survey method was used in this investigation. Evaluating the degree of English learning difficulties among high school students is one of the study's key goals.The English Learning Difficulties Scale (2017), developed and standardized by Dr. D. Ponmozhi and A. Thenmozhi was used by the investigator for this purpose. Linguistic challenges, remedial challenges, teaching challenges, parenting challenges, and psychological challenges are the five components of this 28-item assessment. There is a 5-point rating system for every component.The English Learning Difficulties scale's internal validity was determined to be 0.94 and its reliability to be 0.88 using Cronbach's Alpha. Descriptive, deferential, correlational, and regression analyses were carried out using SPSSIBM23. The rural high school students English Learning Difficulties are High (85-112).The School type, Age, Fathers qualification and parental income have significant relationship with English Learning Difficulties of rural high school students. The prediction model two of the ten predictors and was reached in two steps with 8 variables removed. The model was statistically significant, F(2, 149)= 7.497,p < .001, and accounted for approximately 9% of the variance of English Learning Difficulties (R2=0.091 Adjusted R2= 0.079). Inspection of the structure coefficient suggests that, the School type and Fathers Qualification were relatively strong indicators of English Learning Difficulties of rural high school children. The Teaching Challenges and Psychological Challenges were relatively strong factors of English Learning Difficulties of rural high school children.

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Key words: English Learning Difficulties, rural high school children

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The 21st century is often look upon as the Era of Artificial Intelligence and Technology. Today Artificial Intelligence (AI), Computer science along with its applications, Machine learning and Technology are transforming society and industries at large by automating tasks across the knowledge economy. From medicine development to writing and editing, AI is upsetting and transforming various traditional professions. The influence of AI in the Ed-tech market is thriving. Artificial intelligence is a field of study and the resulting innovations and developments that have culminated in computers, machines, and other artifacts having human-like intelligence characterized by cognitive abilities, learning, adaptability, and decision-making capabilities. AI initially took the form of computer and computer related technologies, transitioning to web-based and online intelligent education systems, and ultimately with the use of embedded computer systems, together with other technologies, the use of humanoid robots and web-based chatbots to perform instructor's duties and functions independently or with instructors. The purpose of the study is to explore the role of Artificial intelligence and technology in the field of education in India. The study reveals that Artificial Intelligence (AI) and technology are reshaping the knowledge economy and propelling us into a future where the possibilities seem limitless.

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Role, Artificial Intelligence (AI), Computer Science, Machine Learning, Technology, Field of Education.

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Garcinol, a polyisoprenylated benzophenone derived from the Garcinia indica fruit, has garnered significant interest for its multifaceted therapeutic properties. This review synthesizes research done on garcinol's effects on various diseases, including diabetes, cancer, ulcerative conditions, and neurodegenerative disorders. In diabetes, garcinol exhibits antidiabetic potential by modulating glucose metabolism and enhancing insulin sensitivity. Its anticancer properties are profound, characterized by the inhibition of cell proliferation, induction of apoptosis, and suppression of metastasis across various cancer types. Garcinol also demonstrates potent antiulcer activity, providing gastric mucosal protection through antioxidant and anti-inflammatory mechanisms. Additionally, garcinol shows promise in neuroprotection, mitigating oxidative stress, and neuroinflammation, which are pivotal in the pathogenesis of neurodegenerative diseases such as Alzheimer's and Parkinson's. Despite these promising findings, clinical studies are necessary to confirm these effects and understand the underlying molecular mechanisms comprehensively. This review underscores garcinol's potential as a therapeutic agent and highlights the need for further research to explore its full medicinal capabilities.

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Garcinol, diabetes, cancer, antiulcer, neurodegenerative diseases, therapeutic potential, antioxidant, anti-inflammatory, neuroprotection, molecular mechanisms.

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In today's era, electricity is a fundamental necessity, yet traditional metering methods pose various challenges. Typically, an authorized meter reader from the Electricity Department visits homes to record energy consumption and calculate charges, a process prone to human error, time inefficiencies, and labor costs. This paper presents an innovative approach to automating the billing system by integrating a microcontroller with energy meters. The system utilizes a centralized server to store data, accessible to both officials and users via an Android application or website, ensuring secure data transmission. In cases of non-compliance with electricity board regulations, the system can automatically disconnect the power supply.Additionally, this solution addresses the prevalent issue of electricity theft. The proposed method includes advanced mechanisms for detecting tampering and unauthorized interference, promptly sending alerts to both the server and the user. The system is equipped with sensors to monitor for unusual patterns and anomalies, indicating possible theft or tampering. Upon detection, immediate notifications are dispatched, enabling swift action to mitigate losses. This approach not only streamlines energy management but also enhances the detection and prevention of power theft, contributing to a more efficient and reliable electricity distribution system. By leveraging IoT technology, the solution offers a comprehensive, automated method to manage and secure electrical energy usage, ultimately promoting sustainability and operational efficiency in the energy sector.

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IoT, power theft detection, energy management, automated billing system, microcontroller, smart meters, data security, electricity consumption monitoring, tampering detection, remote disconnection, energy efficiency, electricity distribution system, Android application, server database, real-time monitoring.

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Metformin is a widely used type-2 Antidiabetic drug that also helps in reducing the occurrence and risk of various Metabolic Disorders. Pectin is a Plant-based soluble dietary fiber. Both Pectin and Metformin have a role in glycemic control and their potential as an adjunct therapy in Diabetes management. This review includes the existing literature on combined use of Metformin and pectin, their synergetic effects and therapeutic implications, Potential benefits and challenges, Using Metformin and Pectin for Moms-to-Be, Impact of High-Temperature Exposure on Metformin-Pectin Interaction, Anti-Diabetic Flavors with Pectin, Future direction and Conclusion.

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Metformin, Pectin, Heat, Flavor

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This research paper introduces a novel application for predicting plant diseases and curing the disease by using Convolutional Neural Networks (CNNs). Separate CNN models were trained on labeled datasets like cotton and potato leaves, each associated with their respective diseases. The primary goal is to employ of two standard CNN systems to detect various diseases in cotton and potato plants. Given India's heavy reliance on agriculture, this innovation is crucial to address challenges faced by the sector, including technological limitations, limited access to credit and markets, and the impact of climate change. this research paper are susceptible to various diseases that can impede their growth and result in substantial yield losses. The conventional disease detection methods involve manual inspection and disease prognosis, which are time consuming and less accurate. The research show- cases the effectiveness of the automated plant disease detection and curing system, with two best models achieving impressive accuracies of 97.10% and 96.94% . These results offer promising insights for potential applications in crop management, benefiting the agricultural sector and contributing to increased productivity and profitability.

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: Convolutional Neural Networks (CNNs), Deep learning, ResNet50, VGG16, Fusion of , Image classification, Transfer learning.

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This research article presents an experimental analysis of how lubricant viscosity impacts the vibration behavior of rolling element bearings. Using an FFT analyzer, the study investigates the vibrational responses under varying conditions, utilizing three lubricant grades: NLGI 1, NLGI 2, and NLGI 3. The bearings were tested under three different loads (3 kg, 6 kg, and 9 kg) and three rotational speeds (300 rpm, 600 rpm, and 900 rpm). The analysis revealed that lubricant viscosity significantly influences the vibration characteristics of the bearings. Among the tested lubricants, NLGI 2 demonstrated superior performance and stability across all test conditions. This grade effectively minimized vibration amplitudes, providing better-damping properties compared to NLGI 1 and NLGI 3. The findings suggest that selecting the appropriate lubricant viscosity is crucial for optimizing the operational performance and longevity of rolling element bearings, particularly in varying load and speed conditions. This research contributes valuable insights for industries aiming to enhance machinery reliability through informed lubrication strategies.

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Lubricant Viscosity, Vibration Analysis, Rolling Element Bearings, FFT Analyzer, Bearing Performance

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Background: Non-traumatic shoulder pain is the third most common cause of consultations for musculoskeletal pain in primary health care. Despite being one of the most common reasons for consultation, there is no established protocol for treatment due to the complexity of its etiology. However, it has been shown that the presence of myofascial trigger points on the shoulder muscles is a common condition associated with patients suffering from shoulder pain. This protocol has been created which describes the design of a randomized controlled trial to evaluate the effectiveness of the inclusion of dry needling(DN)within a protocol of manual physiotherapy and therapeutic exercise in the treatment of Chronic Shoulder Pain Of Unspecific origin. Methods: Thirty-six participants aged 18-65 years will be recruited having mechanical chronic shoulder pain on unspecific origin and meeting the inclusion criteria. These will be randomized to one of two interventions, (i) DN, manual physiotherapy and therapeutic exercise or (ii) sham DN, manual physiotherapy and therapeutic exercise. The protocol will cover 6 weeks of treatment, with a 6-month follow-up. Our main outcome measure will be the Visual Analogue Scale For pain. Discussion: This is the first study to combine the use of DN, manual physiotherapy and an exercise program with a 6-monthfollow-up,thus becoming a new contribution to the treatment of chronic shoulder pain, while new lines of research may be established to help determine the effects of D Non chronic shoulder pain and the frequency and proper dosage.

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Trigger Point Dryneedling, Non-Traumatic Shoulder pain, Physiotherapy, Therapeutic exercise, Myofascial trigger point

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This paper presents an in-depth investigation into the correlation between infrastructure quality and educational achievement in primary schools across Begusarai District. The study aims to elucidate how the condition of school facilities influences student learning outcomes. Using a mixed-methods approach, data was collected through surveys, interviews, and academic performance records. The findings reveal significant associations between infrastructure deficiencies and educational achievement disparities. Recommendations are provided to address infrastructure gaps and improve the overall quality of primary education in Begusarai District.

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infrastructure quality, educational achievement, primary schools of Begusarai District.

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Today's organ donation and transplantation systems encounter a multitude of requirements and challenges. These challenges span various stages, including the registration of donors, matching donors with recipients, the removal and delivery of organs, and the transplantation procedures. Each stage must comply with a complex web of legal, clinical, ethical, and technical constraints. To address these multifaceted needs and ensure a process that is both fair and efficient, thereby enhancing patient experience and building trust, an integrated end-to-end organ donation and transplantation system is essential. To achieve this, we propose a solution based on a private Ethereum blockchain. This technology is designed to manage the entire organ donation and transplantation process in a manner that is secure, traceable, auditable, private, and trustworthy. By leveraging blockchain technology, we can ensure that every step of the process is recorded immutably and transparently, which is crucial for maintaining the integrity of the system. Our approach includes the development of smart contracts that automate the recording of events, thereby ensuring the provenance and integrity of data throughout the process. These smart contracts facilitate the secure and transparent execution of various tasks, from donor registration to organ matching and transplantation. In summary, our proposed private Ethereum blockchain solution aims to revolutionize the organ donation and transplantation system by making it more secure, transparent, and reliable, ultimately improving patient outcomes and trust in the system.

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Blockchain, Ethereum, Organ Donation, Transplantation, Smart Contracts

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