Volume 12 | Issue 2 |

 Abstract

Introduction: Adverse drug reactions (ADRs) represent a significant concern for patient safety and necessitate robust monitoring and reporting mechanisms. This systematic literature review delves into the landscape of ADR reporting, with a specific focus on leveraging the electronic health record (EHR) as a surveillance tool. Despite existing guidelines, variability in reporting standards persists among healthcare facilities worldwide. Methods: A comprehensive search encompassing PubMed and the Cochrane Database of Systematic Reviews was conducted, targeting original articles and reports from reputable organizations. The review explores challenges encountered in ADR reporting, including under-reporting rates and interinstitutional variability. Potential strategies for improvement, such as direct reporting by consumers and enhanced healthcare provider education, are examined. Results: Despite concerted efforts to promote ADR reporting, persistent barriers remain, including inadequate knowledge among healthcare professionals and logistical challenges in establishing robust reporting systems. Direct consumer reporting initiatives have shown promise in certain countries but warrant further investigation. Additionally, while the EHR presents promising opportunities for ADR monitoring, issues such as lack of standardization and alert fatigue hinder its effectiveness in practice. Discussion: Addressing barriers to ADR reporting is imperative to strengthen pharmacovigilance systems and uphold patient safety standards. The review underscores the importance of standardized reporting practices, technological advancements, and targeted educational interventions to optimize ADR monitoring and reporting efficacy. Conclusion: By embracing targeted interventions and capitalizing on technological innovations, healthcare systems can bolster their capacity to detect, report, and mitigate ADRs effectively. This proactive approach not only enhances patient safety but also optimizes pharmacotherapy outcomes, ultimately advancing public health objectives.

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Keywords: Adverse drug reactions (ADRs), Pharmacovigilance, Electronic health record (EHR), Under-reporting, Healthcare provider education, Patient safety

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Automatic text summarization plays a crucial role in information retrieval and natural language processing tasks. This research project focuses on developing a web-based application for multilanguage text summarization. The application utilizes the Flask framework and leverages the capabilities of the SpaCy library for language processing. The application allows users to input text in multiple languages, including English, Hindi, Kan- nada, and Malayalam, and generates a concise summary of the provided text. The summarization process involves tokenizing the input text, removing stop words and punctuation, and identifying key sentences for the summary. The system employs different SpaCy language models based on the selected language for accurate language-specific processing. The application supports an intuitive user interface that enables users to interact with the system easily. Users can input their text, select the desired language, and obtain a summary of the input text. The system provides valuable assistance in quickly extracting important information from documents and texts, saving time and effort for users who need to process large volumes of information. The evaluation of the application demonstrates its effectiveness in generating informative summaries across multiple languages. The performance of the system is evaluated based on various metrics such as summary length, similarity to the source text, and overall coherence. The results indicate that the application produces concise and meaningful summaries, making it a valuable tool for information extraction in diverse linguistic contexts. Overall, this research project showcases the development of a web-based multi-language text summarization application that effectively summarizes text in English, Hindi, Kannada, and Malayalam languages. The application provides a user-friendly interface and demonstrates promising performance in generating accurate and concise summaries. Future enhancements may involve expanding language support, refining the summarization algorithms, and incorporating advanced natural language processing techniques to improve the overall summarization quality and user Page 1 experience

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 Keywords

Multilingual NLP ,Text Summarization, Spacy, Flask ,Natural Language Processing, Web Application ,ROUGE Evaluation, Language Processing, Machine Learning, Python ,Web Development

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT Introduction: Pregnancy is the term used to describe the period in which a fetus develops inside a woman's womb or uterus.The third stage of labor has traditionally been defined as the time between the birth ofthe baby and the delivery of the placenta and membranes. It is the third stage that is the most perilous for the woman because of the risk of postpartum hemorrhage (PPH). Methods: A Quasi Experimental was carried out on 100 b.sc nursing 3rd year students to assess the effectiveness of self instructional module. Assessment of knowledge among students regardingactive management of third stage of labor was conducted through questionnaire before Intervention, then self instructional module was administered for 15days. Post test was conducted on 16th day.Result: study result revealed that self instructional module was effective to increase the knowledge of students. Conclusion:As per findings of the present study, self-instructional module was valuable in increasing knowledge regarding active management of 3rd stage of labor among B.Sc. 3rd year nursing students. Key words: knowledge, self instructional module, active management of third stage of labour.

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Key words: knowledge, self instructional module, active management of third stage of labour.

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Plant-derived herbal remedies provide an effective means for treating diseases difficult to treat by other systems of medicines; hepatic disease is one such disease. Exploring and establishing the scientific basis for the therapeutic action of herbal plant medicines is essential. In this research work, the stembark of Bombax ceiba Linn. was evaluated for hepatoprotective activity. The selection of the plant was based on its previously reported literature of antioxidant potentials due to flavonoid contains. Dried stem bark was extracted by various solvents in a soxhlet apparatus and evaluated for pharmacognostic profile. To estimate hepatoprotective potential, stem bark extract of Bombax ceiba carbon tetra chloride induced liver narcosis rat model was selected, and the acetone extract of B. ceiba was administered orally. Radical scavenging potential, total bilirubin count, serum enzyme levels, and histopathological study of the liver were selected as evaluating parameters. Results showed a significant reversal of (p<0.05) hepatotoxicity compared to diseased animals. However, no significant difference was observed in animals treated with the standard Sylimarin . Study concludes the hepatoprotective potential of acetone extract of B. ceiba stembark.

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Keywords: B.ceiba, shalmali, hepatoprotective, flavonoids, antioxidant

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Creative Commons Attribution 4.0 and The Open Definition

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Over the passage of time, there has been an enormous growth in the rise of E-Commerce platforms in India as it has brought numerous benefits, such as better consumer access to a wide range of goods and services with the convenience of online shopping. Hence, it has become imperative for businesses to protect their brand in the digital world through trademark protection. As the buying and selling of goods and services takes place via electronic means thus, it is being termed as e-commerce. It creates a direct link between the manufacturers/sellers and consumers, making it convenient for distribution and ensuring free and continuous transfers. However, the prevalence of counterfeit products, parallel importation of goods, sale of defective products, etc., has led to trademark infringements in these direct transactions which has in turn hindered the growth of e-commerce in India and is gravely affecting the digital economy as well as the overall integrity of the online marketplace. Counterfeited goods refer to the act of producing emulated goods that provide a much degraded quality and are manufactured and sold under another company's trademark without any prior consent or approval. This is done to deceive consumers into believing that they are purchasing genuine products. When such goods are sold on e-commerce portals, they bear unauthorized reproductions of the registered trademarks. This plays with the distinctiveness of the original brands and puts the consumers in a dilemma leading to trademark infringements. The anonymity of these online transactions makes it a challenge to identify the parties and hold them accountable for their actions. E-commerce portals provide a vast range of access and ease for such producers to set up online shops, which not only reduces the verification process but targeting audiences also get easy by way of e-commerce platforms which in turn, amplifies the impact of their illicit acts. While the 2009 amendment to Information Technology Act, 2000 clarified intellectual property rights issues in the cyber law, the unresolved issue of secondary liability for a third-party trademark infringement poses a significant challenge. Hence, by way of a non- doctrinal research the researcher aims to delve into the concept of secondary liability of e-commerce platforms in India, the US and the UK by doing a comparative analysis of the judicial pronouncements given in this matter, to identify the responsibilities and liabilities of these e-commerce portals when it comes to selling and offering of counterfeited products. Collaboration between the e-commerce portals, rights holders and government agencies can prove to be very effective in curbing counterfeiting. With the help of growing AI, bots can detect and prevent the listing of such counterfeit goods. By way of these technologies, seller behaviors and product specifications can be studied and analyzed, thereby decreasing the chances of trademark infringement. The research explains the twisted challenges of counterfeiting, shedding light on the complexities of protecting trademark rights in the online marketplace. Through this study, proposed amendments to existing legislation will be examined to curb trademark infringement on e-commerce portals. The result underscores the need for a solidly built enforcement mechanism, associated efforts between the stakeholders, law enforcement agencies, intellectual property rights holders, etc., and the enhanced consumer awareness campaigns to control this rapidly growing menace.

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Trademark Infringement, Counterfeited goods, E-commerce, Secondary Liability, Intellectual Property Rights Holders.

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This study assessed the degree of environmental safeguarding on the practices, obstacles, and scope of implementation in combating the dumping and illegal trafficking of electronic trash. The study employed a descriptive survey method to examine the practices, challenges, and level of implementation regarding e-waste management (specifically dumping and illicit trade). The research involved 45 participants who were employed in the City Environmental and Natural Resources Office (CENRO), Environmental Management Bureau (EMB), and Metro Manila Development Authority (MMDA). The study revealed that efforts to combat the disposal of electronic trash were frequently successful, whereas the illegal trade of electronic garbage was occasionally successful. Assessing the composite of difficulties related to e-waste dumping and illicit trade yielded positive results. Furthermore, on the level of enforcement against the dumping and illegal trafficking of e-waste, both received consistent verbal affirmation. In summary, the behavior of individuals in building new social norms for e-waste trade, use, and dumping can be influenced by personal qualities and the perceived effectiveness of the outcomes. The researcher suggests the establishment of e-waste facilities and environmental systems and aligning extension activities with research findings utilizing qualitative or mixed design.

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Creative Commons Attribution 4.0 and The Open Definition

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Environmental Protection, Dumping and Illicit Trade of Electronic Waste, Practices, Implementation, Challenges

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Marketing of Handloom fabrics in Manipur is done by weavers themselves, master weavers, middlemen, co-operative societies and also by marketing organizations, Handloom houses of Apex, All India Handlooms Fabric Marketing Co-operative Societies and sales and showrooms of Handicrafts and Handloom Export Corporation etc., The handloom sector plays an important role in the economic development and livelihood of the rural poor in the state. It contributes significantly by generating more employment opportunities and providing bread to the rural poor. Mostly in the state handloom market is done in the local markets. The market is an unorganized one with no control over buying, selling and pricing of the product. There is almost no promotion activity for the handloom products, which is also one of the reasons why the market is not expanding to a wider scale. The article is taken up in order to study about some of the commonly produced handloom fabrics and the present marketing system adopted by the weavers in the local markets of the State.

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handloom, marketing, Manipur, weavers, product

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Creative Commons Attribution 4.0 and The Open Definition

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In the domain of distributed relational databases, efficient query optimization stands as a cornerstone for achieving peak performance. As data spans across multiple nodes, the intricacy of query handling escalates, emphasizing the pivotal role of optimization methods in curtailing execution time and resource consumption. This paper presents a thorough examination of query optimization strategies within distributed relational databases, encompassing both centralized and distributed approaches. We explore a spectrum of techniques, such as cost-based optimization, parallel query processing, and adaptive query processing, elucidating their advantages, constraints, and suitability across diverse distributed database frameworks. Moreover, we address emerging trends and hurdles in query optimization within distributed systems, offering insights into potential paths for future research and advancement.

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Query Optimization, Relational Databases, Partitioning, Challenges

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This analysis delves into the myriad qualities exhibited by Moringa oleifera, commonly recognized by its colloquial name, the drumstick tree. The plant, rich in essential phytochemicals, is native to Africa and Asia, thriving in tropical and sub-tropical regions. Renowned for its nutritional richness, Moringa is abundant in vitamins, minerals, and antioxidants, demonstrating its efficacy in various beneficial roles, including anti-inflammatory, antidiabetic, antimicrobial, and antihypertensive activities. The chemical constituents of Moringa oleifera include Vitamins, Carotenoids, Tannins, Saponin, Phenolic acid, and Minerals, contributing to its health-promoting properties. Examining pharmacological aspects, Moringa oleifera demonstrates potential in Anti-inflammatory, Antidiabetic, Antimicrobial, Antihypertensive, Analgesic, Anticancer and Antispasmodic activities. These findings suggest a broad spectrum of health benefits, though further research is crucial for real-world applications. Understanding the plant's versatility offers insights into its potential contributions to various industries and health domains.

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Moringa oleifera, Chemical consituent, Antioxidant, Anti-inflammatory, Health

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Creative Commons Attribution 4.0 and The Open Definition

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This review paper explores the comprehensive integration of advanced artificial intelligence (AI) techniques into online marketplaces, with a primary focus on addressing challenges encountered by businesses, particularly small enterprises. Motivated by the imperative need for a tool that enables small businesses to scale effectively through the incorporation of the latest technological advancements, the project seeks to democratize access to AI. Employing a multifaceted approach, it strategically tackles the long-tail problem pervasive in online commerce. Techniques such as Product Sentiment Analysis, Opinion Mining, Sales Prediction, Dynamic Pricing, Product Recommendation, and Customer Segmentation collectively contribute to mitigating challenges associated with diverse product catalogs, enhancing overall efficiency, and improving the user experience of online marketplaces. Customer Segmentation employs K-means Clustering to group customers based on similar characteristics, enabling tailored marketing strategies, and enhancing personalization. Dynamic pricing, addressed through Linear Regression, models relationships influencing pricing dynamics, facilitating optimal dynamic pricing based on relevant input variables. Opinion Mining for Products leverages RoBERTa, a state-of-the-art natural language processing model, to extract nuanced opinions and sentiments from product reviews. Product Recommendation utilizes K-nearest neighbors with Means to provide a personalized and user-centric recommendation system, contributing to an enhanced customer experience. Sales Prediction employs Time Series analysis to analyze historical sales data, identify patterns, and make informed predictions about future sales trends, ultimately improving decision- making processes and optimizing inventory management. The integration of these diverse AI modules into a cohesive backend infrastructure ensures seamless communication and interoperability. The creation of an admin panel for real-time statistics serves as a centralized hub for stakeholders to visualize key metrics and make data-driven decisions, facilitating efficient oversight and management of AI-driven functionalities within the online marketplace. In conclusion, this transformative project represents a novel approach to empower small businesses through the strategic integration of AI techniques, effectively addressing critical challenges and leveraging advanced methodologies to revolutionize online commerce and make AI-driven optimization accessible and impactful for businesses navigating the complexities of the digital landscape.

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 Keywords

Deep Learning, Machine Learning, E-Commerce, Artificial Intelligence, Sentiment Analysis, Opinion Mining, Product Recommendation, Dynamic Pricing, Sales Prediction, Market Segmentation, Customer Segmentation, Prescriptive AI, Business Intelligence, Neural Networks, Support Vector Machines, Transformers, K-Means Clustering, Time-Series Forecasting, Time-Series Analysis, Linear Regression.

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Creative Commons Attribution 4.0 and The Open Definition