Volume 12 | Issue 3

 Abstract

This review addresses the global impact of urinary tract infections (UTIs), affecting millions annually and exacerbated by antimicrobial resistance. The dominant pathogen, Uropathogenic Escherichia coli (UPEC), underscores the urgency for alternative solutions. Despite varied management approaches, recurrent UTIs persist as a socio-economic burden.Herbal remedies like cranberry, cinnamon, clove, garlic, and coconut water are explored for their antibacterial properties as potential alternatives to conventional treatments. The complexity of UTIs, classified by factors like symptoms and site, necessitates tailored treatments, particularly for complicated cases linked to underlying conditions.Various factors contribute to UTI prevalence, especially in females. Symptoms range from mild to severe, requiring prompt treatment to prevent complications and combat antimicrobial resistance. The situation in India, with E. coli resistance to key antibiotics, emphasizes the need for innovative strategies, including the integration of herbal medicine alongside antibiotics.Future prospects involve the development of new drugs, vaccines targeting uropathogens, and exploration of novel antibiotics. The review emphasizes revisiting traditional practices in alignment with the World Health Organization's strategy. In essence, the review contributes insights into alternative UTI treatments, urging attention to this pressing global health concern.

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 Keywords

Urinary tract infections , Herbal medicine , Uropathogenic Escherichia coli , Herbal remedies

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This article examines the evolving landscape of the European Union's (EU's) trade policy. It explores the core objectives that have driven the EU's trade strategy, recent adaptations to address new challenges, and key factors shaping its future direction. The EU champions free trade, promoting economic growth and international cooperation through its trade agreements. However, the current global order presents challenges and opportunities. The EU is adapting its approach to address issues like rising protectionism, the US-China rivalry, and the need for climate action. The article also explores the impact of trade agreements, using the EU-Canada Comprehensive Economic and Trade Agreement (CETA) as a case study. It concludes by emphasizing the need for the EU to balance economic interests with environmental sustainability and social considerations in its trade policy.

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 Keywords

1. EU trade policy 2. Free trade 3. Geopolitical tensions 4. Protectionism 5. Climate change 6. Digitalization 7. Open markets 8. Fair competition 9. Sustainability 10. Global trade rules 11. Strategic autonomy 12. Enforcement 13. Reciprocity 14. Digital trade 15. Data protection 16. Intellectual property rights 17. Rise of protectionism 18. US-China rivalry 19. WTO reforms 20. Carbon border adjustments 21. COVID-19 impact 22. Social dimension 23. Trade agreements 24. EU-Canada Comprehensive Eco

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The Khasi tribe in Meghalaya has a unique matrilineal system where women enjoy full security and the youngest daughter, known as Ka Khadduh, inherits ancestral property. She plays a crucial role in caring for her parents and ensuring the welfare and education of her siblings. Khasi women's are enjoying more rights and respect as compared to other parts of the country.Childrens use to take mother's surname and khasi males move into his in laws house after marriage.Some Khasi men's were protesting against this tradition. According to some of the khasi males ,they are having a secondary status in the society.This paper will delve into the Customary inheritance system of the Khasi community and how it has evolved with modernization, focusing on the roles of the youngest daughter, other daughters, and sons in the inheritance of ancestral property.

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Customary,inheritance,ka Khadduh, Khasi

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This study explores the use of machine learning algorithms for crime prediction using historical data of public property crime in a large coastal city in southeast China. The comparative analysis focuses on the predictive power of several machine learning models. The findings indicate that the LSTM model outperformed other methods such as KNN, random forest, support vector machine, naive Bayes, and convolutional neural networks when solely using historical crime data. Furthermore, incorporating built environment data such as points of interest (POIs) and urban road network density into the LSTM model as covariates improved the prediction effect. These results have implications for the formulation of policing strategies and the implementation of crime prevention and control.

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Crime Detection, Crime Analysis, Machine Learning

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The survey titled "Dental Telecare Insights: Exploring Viability and Patient Contentment in Virtual Consultations and Follow-ups" offers a meticulous examination of teledentistry, a revolutionary fusion of telecommunications and dentistry. With a primary focus on evaluating teledentistry's viability and patient satisfaction, the survey elucidates its roots, evolution, and diverse applications. Methodologically robust, the survey employs a cross-sectional study design among BDS college students and dental graduates in Pune, Maharashtra. Results highlight varied objectives, patient satisfaction nuances, and the impact on rural populations. Discussions encompass environmental concerns, cost implications, and the delicate balance between crisis management and preventive measures. The study underscores the paramount significance of maintaining patient confidentiality, ensuring secure data transmission, and reinforcing trust in telehealth platforms, echoing the imperative for standardized practices in the burgeoning field of dental telecare.

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Teledentistry,Patient satisfaction,Virtual consultations,Telehealth,Preventive dentistry,Cost-effectiveness,Environmental concerns,Patient confidentiality,Hybrid approach,Dental education.

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The "Underwater Tank Cleaning System" concept presents an innovative solution for effectively cleaning debris from the surface of underwater tank. The system utilizes a PMDC motor as its driving force, a diaphragms water pump and filtration bag is used to efficiently remove contaminants. A suction pipe is employed to facilitate the intake of debris into the system. Additionally, to ensure operational safety and longevity, a thermistor is integrated to monitor and regulate motor temperature underwater. To enhance user interaction and control, the system is equipped with a Cam Development Board (ESP32). This allows users to monitor and manage the cleaning process via wired connection, providing real- time feedback and control capabilities.

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PMDC Motor, Flow Meter, filtration Bag, SMPS, brush

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What if one day u wake up and your application starts getting a lot of unexpected traffic? This is amazing, isn't it? But is your application ready for it? Can it handle so much traffic? In this project we propose a Elastic load balancer. ELB (Elastic Load Balancer) is a service provided by AWS (Amazon Web Services) which is used to balance the incoming load (traffic) on multiple EC2 instances which can be in multiple availability zones. Load balancing distributes the network traffic in such a manner that increases speed and the performance of web applications. Modern ELB uses "Round robin algorithm". The real time applications of ELB are high traffic websites, E- commerce applications, Media streaming, Gaming applications, Mobile applications. ELB improves scalability, availability and fault tolerance of web applications and services.

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Elastic Load Balancer, Amazon Web Services, Elastic Compute Cloud, Round Robin, Scalability.

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To analyse the variation of cost between LGSF building and RCC building and time reduction in construction

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Light gauge steel frame,cost control, time reduction

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A build-up of senile plaques (SPs) and neurofibrillary tangles (NFTs) in the brain is the pathological hallmark of Alzheimer's disease (AD), the primary cerebrovascular illness that causes dementia. Diabetes mellitus is a condition marked by improper carbohydrate metabolism and increased blood glucose levels. It is caused by a malfunction in the body's capacity to create or respond to the hormone insulin. There is growing recognition that cognitive impairment is a significant comorbidity of diabetes mellitus. There are many stages of diabetes-related cognitive impairment, each with unique cognitive characteristics, affected age groups and prognoses, and most likely distinct underlying processes. Additionally, mounting data points to a number of linkages between the neuropathology underlying DM and AD, and evidence even points to the possibility that experimental production of DM might result in cognitive failure, even in rodent animal models. Deficits in spatial learning are correlated with unique modifications in hippocampus synaptic plasticity in animal models of diabetes. Although the complex pathophysiology of diabetic encephalopathy is not fully known, it is evident that it has characteristics with the pathophysiology of diabetic neuropathy and brain aging. Chronic hyperglycemia-related alterations in metabolism and blood vessels are present, and there may also be abnormalities in the brain's ability to use insulin. Thus, insulin treatment may have a direct impact on the brain in addition to addressing hyperglycemia. Therefore, insulin therapy may have a direct impact on the brain in addition to treating hyperglycemia. It is not yet known why AD typically occurs in older people, despite genetic research demonstrating that the primary component of SPs, ?-amyloid peptide (A?), is the critical element causing AD pathogenesis.

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Senile plaques, Neurofibrillary tangles, Alzheimer's disease, Diabetes mellitus, Dementia, Synaptic plasticity, ?-amyloid peptide.

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Horticulture stays significant in driving financial change, practical jobs, and advancement in emerging nations. This paper gives a far reaching examination and conversation of environmental change influences on water and horticulture areas and suggestions for the fulfillment of formative results like food security, destitution decrease, and practical improvement in Southern Africa. The audit gives strategy messages for adapting, adjusting, and fabricating flexibility of water and agrarian creation frameworks despite extended changes in environment and changeability. The point is to direct the district towards the accomplishment of the Supportable Improvement Objectives. Future projections for Southern Africa demonstrate decreased precipitation, expanded temperatures, and high inconstancy for most of the district with extreme decreases on the drier and minimal western parts. These effects have significant ramifications for farming execution and commitment to public and provincial formative objectives. The district is projected to encounter decreases of somewhere in the range of 15% and half in rural efficiency, a situation that would worsen food uncertainty in the locale. The test is to increment efficiency on ebb and flow arable land through productive and reasonable administration of accessible water and energy, and simultaneously decreasing tension on the climate. Reasonableness and availability of creative variation estimates on water assets stay basic and these systems ought to be important for more extensive manageable advancement endeavors. By and large, endeavors to improve agrarian efficiency need to underline interests in maintainable administration and utilization of water and energy assets in agribusiness to accomplish practical monetary development and jobs.

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Key Words: Environmental Change; Transformation; Flexibility; Water assets; Food Security; Manageability

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The escalating prevalence of diabetes globally has positioned it as a significant contributor to mortality rates. Elevated blood glucose levels and insulin resistance are implicated in a spectrum of health complications, encompassing cardiovascular diseases, renal dysfunction, neuropathies, and diabetic retinopathy--a debilitating condition marked by vision impairment. Early detection serves as a pivotal determinant in mitigating the progression of diabetic retinopathy and averting irreversible visual impairment. Consequently, the imperative for a robust screening methodology becomes apparent. To this end, a comprehensive investigation into deep learning strategies has been undertaken. Leveraging publicly available datasets, our research ends have focused on the acquisition and reprocessing of data pertaining to diabetic individuals. Furthermore, the development of sophisticated machine learning algorithms, including deep neural networks such as Convolutional Neural Networks (CNNs), has been instrumental in refining our screening approach. The culmination of these efforts has yielded promising outcomes, as evidenced by the system's proficiency in accurately discerning normal retinal images from those indicative of aberrant pathology with a remarkable degree of certainty. In conclusion, the integration of advanced technologies, such as deep learning and machine learning, holds considerable promise in revolutionizing diabetic retinopathy screening protocols. By harnessing the power of these methodologies, we can enhance early detection, facilitate timely intervention, and ultimately ameliorate the burden of diabetic retinopathy on global visual health outcomes

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Diabetic Retinopathy, Deep Learning, KNN, CNN

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In today's globalized world, effective cross-cultural communication is essential for success in various personal, academic, and professional endeavors. English language proficiency plays a significant role in facilitating communication across cultural boundaries. This paper explores the impact of English language proficiency on cross-cultural communication success, examining its influence on interpersonal interactions, academic achievements, and professional opportunities. By analyzing research findings and real-world examples, this paper highlights the importance of English language proficiency as a key determinant of success in cross-cultural communication.

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English language proficiency, cross-cultural communication, globalization, interpersonal interactions, academic achievements, professional opportunities.

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Image manipulation and forgery present significant challenges across various domains, including forensics, security, and media authentication. This is a novel approach that integrates Error Level Analysis (ELA) with Convolutional Neural Networks (CNNs) to differentiate between authentic and tampered images. Using the Cassia v2 dataset containing both real and fake instances, diverse data augmentation techniques, such as flattening, resizing, and converting images to ELA format, are applied to enhance model robustness. The dataset is partitioned into 80% training and 20% validation sets to facilitate comprehensive model training and evaluation. Utilizing Keras, a Sequential model is developed, incorporating Conv2D, MaxPooling2D, Dropout, Flatten, and Dense layers for effective feature extraction and classification. Training utilizes the Adam optimizer for parameter optimization. Evaluation metrics, including loss, accuracy, and a confusion matrix, are employed to assess model performance. Results demonstrate promising accuracy, with the model achieving 98.8% training and 92.8% validation accuracy, showcasing the efficacy of the proposed methodology in accurately distinguishing between real and fake images. This approach holds potential for applications in image forensics, security, and authentication domains.

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Fake images, ELA, CNN, Sequential model, Adam optimizer

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Social media nowadays is the 'best possibilities available' to an item to get in touch with potential customers directly. Community social networking sites are the method which is widely used to interact socially. In most cases, these new media won the belief and trust of customers by linking with them at a deeper level. Social media marketing is the new mantra for many manufacturers, wholesalers and retailers since early a season ago. Promoters are considering many various social media possibilities and arising with new social projects at a better frequency than ever before. Social media marketing and the companies that utilize it have become more intensified. The boom of social media trend is as amazing as that and the speed at which it is improving is incredible. International companies have identified social media marketing as a potential promotion system and began to use them with enhancements to power their marketing with social media promotion. This paper discusses about the awareness level of e-consumers in social media sites and the impact of social media advertisements on e-consumers. It also presents an outline on social media marketing in Coimbatore.

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Online shopping cart

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This paper provides a discourse on the crucial role played by folk songs in the transmission and preservation of cultural history and identity within the context of Nagaland. It is rooted in the pressing need and significance of safeguarding the extensive and meaningful folk songs that serve not only as musical compositions but also as potent agents of history and identity. These folk songs serve as invaluable repositories of cultural narratives, offering profound insights into the cultural heritage and way of life of the Naga people. The renowned Angami folk song "AvuNei Hu" is selected as the focal point of analysis in this paper to shed light on the intricate interplay between tradition, identity, and storytelling through music. This paper aims to highlight the enduring significance of folk music as a vital component of cultural heritage, emphasizing its role as a conduit for preserving and transmitting the rich cultural history and identity of Nagaland for generations to come.

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Oral Tradition, Folk Songs, Cultural Narratives

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Tuberculosis (TB) remains a pressing global health concern, demanding accurate diagnostic tools for timely intervention. This study introduces a ground breaking machine learning framework for TB detection, leveraging the K-Nearest Neighbors (KNN) algorithm. Utilizing a comprehensive dataset sourced from Kaggle, encompassing diverse demographic and clinical attributes of individuals suspected of TB, our research focuses on refining the KNN model to precisely classify TB-positive and TB-negative cases. Notably, our approach achieves an impressive accuracy of 95.12%, highlighting the robustness and efficacy of the proposed methodology. Through meticulous experimentation and rigorous evaluation, including cross-validation and independent test set analysis, we ascertain the reliability and generalizability of our model. Furthermore, our investigation delves into the impact of varying KNN parameters on performance, offering invaluable insights into parameter tuning strategies for improved TB detection. This study signifies a significant leap forward in TB diagnostics, demonstrating the potential of machine learning techniques to complement existing methodologies and enhance patient outcomes. The study's findings reveal the algorithm's potential as a significant advancement in medical imaging analysis, offering a promising tool for healthcare professionals in the early detection of TB. The integration of KNN into TB detection workflows could revolutionize the diagnostic process, leading to improved patient outcomes and a reduction in the global TB burden.

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Detection of Tuberculosis, Machine Learning (ML), K-Nearest Neighbors (KNN) algorithm, Image Classification.

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Water scarcity is a serious challenge for agriculture, which heavily relies on insufficient monsoon rains. To address this issue, an Internet of Things (IoT) and Machine Learning (ML) based smart irrigation system is proposed. This system predicts irrigation requirements using environmental parameters and weather forecasting, optimized by an ensemble ML method. The system reduces water, labour, and plant nutrient usage with a low-cost prototype achieving above 90% accuracy. A flexible IoT platform is designed to enable developers to easily integrate IoT and ML components for customized analytical methods in precision irrigation. This platform benefits both IoT specialists and farmers by reducing water waste, lowering costs, and ensuring safer crop yields. An intelligent irrigation system is implemented using an IoT-enabled ML-trained system for optimal water consumption. IoT sensors capture real-time ground and environmental data, which is analyzed by ML to provide irrigation minimizing human intervention.

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IOT, Smart Irrigation, Machine learning, Ensembling, Agriculture.

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Crime fiction has fascinated readers through the ages. This paper explores the changing portrayal of female characters in crime fiction. Early works often relegated women to stereotypical roles: the victim, the femme fatale, or the sidekick. Characters like Miss Marple and Miss Loveday Brooke offered glimpses of more complex heroines, but it was not until the mid-20th century that authors like Dorothy L. Sayers and Patricia Highsmith challenged gender norms with characters like Harriet Vane and Tom Ripley. The Silent Patient by Alex Michaelides serves as a case study. While Alicia Berenson, the accused murderer, displays psychological complexity, she remains somewhat limited. Kathy Faber, Theo Faber's wife, embodies a different stereotype - the cheating spouse. In contrast, Clarice Starling from Thomas Harris' The Silence of the Lambs exemplifies a more modern heroine. Intelligent, resourceful, and haunted by her past, Clarice navigates a male-dominated world with both strength and vulnerability. By analysing both characters through Eysenck's PEN model, the paper highlights the enduring influence of past portrayals while celebrating the emergence of multifaceted female characters who challenge expectations and drive the genre forward.

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Crime fiction, The Silent Patient, The Silence of the Lambs, Eysenck's PEN model

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In Gudiyatham Taluk, out of total population, 180,971 were engaged in work activities. 83.5% of workers describe their work as Main Work (Employment or Earning more than 6 Months) while 16.5% were involved in Marginal activity providing livelihood for less than 6 months. Of 180,971 workers engaged in Main Work, 10,209 were cultivators (owner or co-owner) while 27,078 were Agricultural labourers.

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Atthi, Rural Clinic

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In recent years, there has been a growing recognition of, open jails or open correctional institutions, as a potential solution to these challenges. This research paper aims to examine the necessity and viability of open prisons in India, by exploring their potential benefits, legal frameworks, and socio-economic implications. This research paper attempts to provide a comprehensive analysis of the need for open prisons in India, as They have the potential to address the issue of overcrowding, promote rehabilitation and reduce recidivism rates. However, their implementation needs to be accompanied by a strong regulatory framework and supportive policies to overcome the associated challenges. As the country moves towards a more progressive criminal justice system, open prisons can play a crucial role in making rehabilitation and reintegration a reality for inmates. Further research in this area can help refine and improve the efficacy of open prison systems in India.

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Open prisons, Prison reform , Rights of accused

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Creative Commons Attribution 4.0 and The Open Definition