bluuebunny/crossref_metadata_2025 huggingface dataset:
Case Report on the Outcome of the Scheduled Exercise and Manual Physiotherapy on A Male Patient with Failed Neck Surgery Syndrome
Authors:   Sports Physiotherapist Intern at Dux International Academy, Spain, Samad Shaikh Abdus , Antony Nahum , Ali Zeeshan
Published: May 2024

Pain and discomfort after spinal surgery are known as "Failed Back Surgery Syndrome (FBSS)" and "Failed Neck Surgery Syndrome (FNSS)," respectively. Understanding what triggers FBSS/FNSS is essential for treating it. Outcomes can be affected by preoperative symptoms, patient expectations, and previous surgeries. Imaging techniques including X-rays, CT scans, and MRIs help doctors diagnose physical problems. After surgical attempts have failed, conservative treatment is often suggested. A 34-year-old Indian man after cervical surgery had neuropathic neck discomfort. Scheduled exercise and manual physiotherapy completed the treatment. Manual therapy addressed scar tissue adhesions and nerve mobility, while exercise improved neck strength, flexibility, and stability. Twelve weeks of three-times-a-week treatment. Manual physiotherapy uses soft tissue mobilisation, myofascial release, joint mobilisation, and nerve gliding to alleviate neck pain and restore function. The patient's neck pain, mobility, and neuropathic symptoms improved over twelve weeks after the intervention. The intervention also improved the group's flexibility, mobility, and pain management, as seen by a greater range of motion, decreased discomfort, and higher pressure pain threshold. Balance increased as well. NDI scores showed little improvement after the intervention. Moreover, the intervention improved physical performance, pain management, and balance, however further research could address neck impairment elements not addressed by the intervention (Table 1). A 34-year-old Indian guy with a history of cervical surgery was cured of chronic neuropathic neck pain after 12 weeks of exercise and manual physiotherapy. Manual treatment targeted scar tissue and nerve movement, while exercise relieved neck pain and mobility. Keywords: Failed Back Surgery Syndrome (FBSS)”, Cervical Surgery, Neuropathic Symptoms, Neck Pain
ONE-TIME ENDOVIDEOSURGICAL INTERVENTIONS IN THE TREATMENT OF UROLOGICAL DISEASES
Authors: Попов С.В. , Гусейнов Р.Г. , Скрябин О.Н. , Помешкин Е.В. , Давыдов А.В. , Мирзабеков М.М. , Перепелица В.В. , Зайцев А.С.
Published: May 2024

Единовременные эндовидеохирургические вмешательства при лечении урологических заболеваний, в случае достаточной отработки методики, являются эффективным методом лечения. При этом они выполняются только у 2,0 – 6,4% пациентов, нуждающихся в таких вмешательствах. Цель настоящего исследования: анализ периоперационных результатов симультанных вмешательств и соответствующих изолированных операций при урологических заболеваниях. Материал и методы проведен ретроспективный анализ периоперационных результатов хирургического лечения 5748 пациентов, прооперированных в период с 01.09.2018 по 30.12.2019. При этом анализировали следующие периоперационные показатели: продолжительность вмешательства, объем интраоперационной кровопотери, время дренирования мочевого пузыря уретральным катетером, частота встречаемости инфекционно-воспалительных осложнений со стороны органов мочеполовой системы в ближайшем послеоперационном периоде, количество койко-дней в стационаре в послеоперационном периоде, продолжительность анестезии. Результаты: выявлены преимущества единовременных эндовидеохирургических вмешательств перед двух- и более этапными вмешательствами урологического профиля по продолжительности, объему интраоперационной кровопотери, частоте развития инфекционно-воспалительных осложнений со стороны урологических органов в раннем послеоперационном периоде и другим изучаемым показателям. Заключение: результаты проведенного исследования полностью подтверждают целесообразность и необходимость более широкого использования единовременных эндовидеохирургических вмешательств при плановом хирургическом лечении сочетанных заболеваний урологического профиля.
САЛЫШТЫРМАЛУУ АСПЕКТТЕ СКЛЕРОТРОФИЯЛЫК ЛИХЕН МЕНЕН ШАРТТАЛГАН УРЕТРАЛДЫК СТРИКТУРА МЕНЕН ООРУГАН БЕЙТАПТАРДЫ ДАРЫЛООНУН НАТЫЙЖАЛАРЫ
Authors: Акылбек С. , Курбаналиев Р.М.
Published: May 2024

Склероатрофический лихен является идиопатическим хроническим воспалительным заболеванием кожи, с тенденцией развития осложненной формы в виде стриктурной болезни уретры у пациентов обоих полов. Современная реконструктивно-восстановительная хирургия в лечении стриктур уретры у мужчин непрерывно пополняет свою базу данных различными современными методами, однако, стриктура уретры, обусловленная лихеном, требует унификации показаний к выбору способов буккальной уретропластики, так как по данным литературы, является в настоящее время наиболее высоко эффективной и требует изучения результатов эффективности и в более отдаленные сроки.

Склератрофикалык лихен идиопатиялык өнөкөт сезгенүү тери оорусу болуп саналат, эки жыныстагы бейтаптарда уретралдык стриктуралык оору түрүндө татаал форманы өнүктүрүү тенденциясы бар. Эркектердин уретра стриктурасын дарылоодо Заманбап реконструктивдик-калыбына келтирүүчү хирургия өзүнүн маалымат базасын ар кандай заманбап ыкмалар менен толуктап турат, бирок лихен менен шартталган уретра стриктурасы буккал уретропластикасынын ыкмаларын тандоодо көрсөтмөлөрдү бириктирүүнү талап кылат, анткени адабияттын маалыматы боюнча азыркы учурда эң эффективдүү жана натыйжалуулуктун натыйжаларын жана узак мөөнөттө изилдөөнү талап кылат.

Scleroatrophic lichen is an idiopathic chronic inflammatory skin disease with a tendency to develop a complicated form in the form of stricture disease of the urethra in patients of both sexes. Modern reconstructive and reconstructive surgery in the treatment of urethral strictures in men continuously replenishes its database with various modern methods, however, urethral stricture caused by lichen requires unification of indications for the choice of methods of buccal urethroplasty, since according to the literature, it is currently the most highly effective and requires studying the results of effectiveness and in the longer term.
YAPAY ZEKÂ VARLIKLARININ HUKUKİ STATÜSÜ ÜZERİNE DİSİPLİNLER ARASI BİR MUHAKEME
Authors: Küçük Emin Seyyid
Published: May 2024

Yapay zekâ sistemlerinin yaygınlaşmasıyla birlikte toplum üzerindeki etkisi gün geçtikçe artmakta ve son yıllarda yaşanan çığır açıcı gelişmelerle birlikte yapay zekâ teknolojisine olan ilgi artmaktadır. Şöyle ki; yapay zekâ hâlihazırda savunmadan sanayiye, eğitimden bilişime birçok farklı alanda kullanılmaktayken, piyasaya sürülen büyük dil modelleriyle birlikte insanların yapay zekâya ulaşımı kolaylaşmış ve bu sayede bireysel ölçekte kullanım da artmış, yapay zekâ sistemleri hayatımıza entegre olmuştur. Yapay zekâ sistemleri, bir insanın saatler içinde yapabileceği işlemleri saniyeler içinde yapabilmektedir. Yapay zekâ teknolojisini asıl ilgi odağı haline getiren noktaysa; bu teknolojinin kapasitesinin insanın hayal gücüyle eşdeğer olmasıdır. Şöyle ki; gelişen yapay zekâ teknolojisiyle Einstein’la izafiyet teorisi üzerine sohbet edilebilmekte, istenilen sanatçıya musiki eserler icra ettirilebilmektedir. Yapay zekâ teknolojisinin bu denli hızlı gelişimi, çözümlenmesi gereken pek çok hukuki soru ve sorunu beraberinde getirmektedir. Sorumluluk ve tazminat hukuku, fikri ve sınai haklar, kişilik hakları bu bağlamda ilk akla gelen ve çözümlenmesi gereken hukuki konulardır. Esasen bu sorunların temelinde yatan ana sorunsal ise yapay zekânın hukuki statüsüdür. Bu hukuki statünün açığa kavuşturulmasıyla beraber yapay zekâ sisteminin kullanımından doğabilecek ihtilaflara uygulanacak hukuk kuralları da belirlenebilecektir. Bu bağlamda doktrinde yapay zekânın hukuki kişiliği haiz olmadığını ve mevcut hukuki düzenlemelere yapılacak çeşitli düzenlemelerle bu sorunun üstesinden gelinebileceğini savunan görüşler bulunduğu gibi yapay zekânın kişiliği haiz olması gerektiğini savunan farklı görüşler de mevcuttur. Bu bağlamda Avrupa Parlamentosu’nun önerdiği elektronik kişilik modeli başta olmak üzere Amerikan hukuku dâhil yapay zekâ sistemleri için çeşitli kişilik modelleri önerilmektedir. Bu makale, bir görüşü kayıtsız şartsız savunmak yerine hâlihazırda doktrinde tartışılan görüşleri eleştirel yönleriyle değerlendirmekte ve bu değerlendirmede de karşılaştırmalı hukuk ve normatif metodolojilerinden yararlanmaktadır. Bu makalenin ayrıca, klasik bir hukuki metinden farklılaşarak, yapay zekânın yapısını, öğrenme biçimini ve çalışma prensiplerini inceleyen ve bu incelemeyi hukuki kişi ve kişilik kavramları ile sentezleyen disiplinler arası bir çalışma özelliği bulunmaktadır. Bu çalışma, ileride kendini temsil edebileceği ve bir şeyi neden yapmak isteyeceğini bilebilecek seviyede olacağı öngörülen bir varlığın, hukuki kişiliği haiz olmamasının modern hukuk anlayışıyla bağdaşmadığını, yapay zekânın sui generis yapısına uygun bir kişilik modelinin geliştirilmesinin gerekli olduğunu, bu sayede gelecekte oluşabilecek muhtemel uyuşmazlıkların önüne geçilebileceğini veya doğru bir hukuki düzlemde çözüme kavuşturulabileceğini tartışmaktadır.
DRIVER DROWSINESS DETECTION SYSTEM
Authors:   Information Technology, Medi-Caps University, Indore, India, Vyas Vansh
Published: May 2024

The proposed system utilizes facial landmark detection and eye aspect ratio calculation to detect drowsiness in real-time from a webcam feed. It employs the dlib library for face detection and facial landmark prediction. The eye aspect ratio (EAR) is computed from the distances between specific points on the eyes. When the EAR falls below a predefined threshold for a certain number of consecutive frames, it triggers an alert indicating potential drowsiness. The alert includes visual cues on the video feed, an auditory alert using the playsound library, and even sends an instant WhatsApp message using pywhatkit to notify a designated contact about the drowsiness. This system serves as a useful tool for monitoring driver fatigue or alertness in various contexts, promoting safety and awareness. Its capacity to swiftly identify and alert users to the onset of drowsiness represents a significant leap forward in safety technology. By mitigating the risk of accidents stemming from fatigue-induced impairments, this project underscores the pivotal role of computer vision in real-time human behavior monitoring, offering a versatile and invaluable tool for fostering safety and awareness across various domains. Keywords: Drowsiness Detection; Python; Whatsapp messaging; Webcam feed; Computer Vision; Alert System; Real-time monitoring; Eye-Aspect Ratio; Frame Processing; Facial Recognition.
Determinants Affecting Life Insurance Purchase Decision at Jhapa District
Authors:   Lumbini Banijya Campus, Rajbansh Prabin Kumar RajbanshPrabin Kumar
Published: May 2024

This paper aims to investigate the effect of determining factors like Customer Attitude, Insurance Awareness, Financial Literacy and Social Factor on purchase decision of life insurance policy in Jhapa district of Nepal. Primary data have been collected through structured questionnaire using online method i.e. Google Forms out of 384 life insurance policy holders resident of Jhapa district of Nepal. A descriptive Research and causal comparative design was used and sample was selected by purposive sampling method. Smart PLS 4 is used as a data analysis tool and various tests like descriptive analysis, Measurement Model Assessment, Convergent Validity and Discriminant Validity, Model Fit Assessment, Structural Model Assessment and Importance-Performance Map Analysis (IMPA) tests were conducted as analysis tool to assess the quantitative raw data. The study concludes that Customer Attitude, Financial Literacy, and Insurance Awareness has significant effect with the purchase decision of life insurance policy whereas Social Factor has no significant effect with the purchase decision of life insurance policy. Financial Literacy has the highest influence over purchase decision of life insurance. Thus, the marketers, policymakers and insurance companies must pay more attention in bringing more effective and fruitful programs to enhance the life insurance demand.
Predictive Modelling of Traffic Flow with Deep Learning Techniques
Authors:   Department of Artificial Intelligence & Machine Learning  Malla Reddy University, Hyderabad., Kumar, M. Srujan
Published: May 2024

This project delves into predictive modeling for traffic flow using deep learning techniques, focusing on the Metro Interstate dataset. Traffic Flow Prediction (TFP) is crucial for Intelligent Transport Systems (ITS), optimizing vehicle movement, reducing congestion, and improving route efficiency. Leveraging advancements in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Big Data, our study explores various techniques and models for TFP. We highlight DL models' advantages over traditional ML methods, propelled by the wealth of real-time traffic data fostered by smart cities, presenting opportunities to craft robust predictive models. The core of our project revolves around developing a multi-step Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM) architecture. Our model forecasts traffic volume between Minneapolis and St. Paul, Minnesota, predicting volume two hours into the future based on a six-hour historical window. We explore DL algorithms' efficacy, including LSTM and Gated Recurrent Unit (GRU), in mitigating challenges like the vanishing gradient problem common in RNNs. Our analysis compares various NN models, emphasizing the importance of data availability for training and fine-tuning ML/DL models, with the Metro Interstate dataset serving as a crucial asset for comprehensive traffic flow analysis and model development.
Comprehensive Study of Road Safety Issues in Sangli City with Improvement Measures
Authors:   DR. A. D. SHINDE COLLEGE OF ENGINEERING. Bhadgaon, Gadhinglaj. Dist: Kolhapur Pin: 416502  Department of Civil Engineering, Shiragavi Prof. Mrs. Pooja
Published: May 2024

A Road Safety Audit (RSA) is a comprehensive, independent team's official examination of the safety performance of an existing or planned road or intersection. It qualitatively assesses and reports on potential road safety issues and finds solutions that improve overall road users' safety better. This study aims to understand the different factors which show severity of accidents. A review of the actual scene conditions reveals that incorrect signage and a misleading road layout also played an important role. The goal of this research is to highlight significant safety problems that were detected when conducting an RSA on a road. Finally, according to the findings collected, countermeasures were recommended.
Nexikon Society (Society Management System)
Authors:   LovelyProfessionalUniversity Jalandhar,Punjab, Kumari, Rani
Published: May 2024

The “The Nexikon Society” is an offers an integrated platform aimed at facilitating effective communication, information sharing, and issue resolution within residential communities. This platform serves as a centralized hub where society members can access real-time updates, notices, and event announcements, fostering a stronger sense of community engagement and collaboration. Through the Nexikon website, residents have easy access to various community-related information, including updates on ongoing projects, upcoming events, and important notices. Additionally, the platform allows members to view profiles of their neighbour’s, facilitating networking and social interactions within the community. A significant feature of Nexikon is its complaint management system, which enables members to report issues or concerns pertaining to the society. This feature ensures that grievances are addressed promptly and promotes transparency and accountability among society administrators. Moreover, the website restricts database modification privileges to the administrator, ensuring the integrity and security of the data. The administrator is tasked with managing member information, overseeing platform operations, and performing essential tasks to ensure its smooth functioning. Keywords— Society Management System, Residential Communities, Communication, Information Dissemination, Issue Resolution, Administrator, Database Management.
A Systematic Literature Review of Working Capital Management in Business Organizations
Authors:   Master of Business Administration (MBA)  Faculty of Management Studies, CMS Business School  Bengaluru, Karnataka 560009, NAIDU MONISHA.Y.
Published: May 2024

Working capital management is a crucial aspect of financial management that focuses on the effective management of a company's current assets and liabilities to ensure the smooth operation of day-to-day activities. A literature review on working capital management reveals a plethora of research studies highlighting the significance of optimizing working capital to enhance a firm's profitability, liquidity, and overall financial performance. Several studies have emphasized the importance of maintaining an optimal level of working capital to strike a balance between liquidity and profitability. By efficiently managing components such as cash, inventory, accounts receivable, and accounts payable, companies can minimize the risk of financial distress and improve their operational efficiency. Researchers have proposed various models and techniques to assess and improve working capital management practices, such as the cash conversion cycle, the operating cycle, the current ratio, and the quick ratio. Moreover, studies have also explored the impact of working capital management on firm value and performance. It has been widely documented that effective working capital management positively influences a company's profitability and shareholder value. By reducing the cash conversion cycle and operating cycle, firms can release trapped capital and reinvest it in value-creating activities. Conversely, inadequate working capital management can lead to financial constraints, increased costs, and reduced profitability. Furthermore, researchers have investigated the determinants and challenges of working capital management across different industries and regions. Factors such as industry characteristics, firm size, profitability, growth rate, and macroeconomic conditions have been identified as key determinants of working capital management practices. Cultural, regulatory, and technological factors also play a significant role in shaping companies' approaches to working capital management. In conclusion, the literature review on working capital management underscores the importance of adopting efficient strategies to manage current assets and liabilities effectively. By optimizing working capital levels, companies can improve their financial performance, enhance liquidity, and create long-term value for stakeholders.
POLICY HOLDERS ATTITUDE TOWARDS MEDI CLAIM INSURANCE IN DINDIGUL CITY WITH REFERENCE TO STAR HEALTH AND ALLIED INSURANCE LTD
Authors:   Associate Professor of Commerce, Parvathy’s Arts and Science College, Dindigul, S Dr. Sukumar
Published: May 2024

The present study analyzes the attitudes towards Mediclaim insurance with special reference to Dindigul city, the data were collected and analyzed as per the requirement of the study. The primary data were collected from the respondents through interview schedule in Jan 2024 to Feb 2024. The study has adopted proportionate stratified random sampling method for selecting 100 respondents. The results revealed the fact that the factors, age, education, marital status, family size, number of earning members, income and awareness have influenced the level of attitude of the policyholders. Whereas the factors like sex, occupation and patronage mentality did not influence the level of attitude. Health insurances are the best way to help people reduce their financial burden. Hence it is very important to educate the community regarding the best health insurance available so that they can take the maximum benefits from it. Keywords: Health insurance, Schemes, Attitude, Patronage, Mentality of Policyholders,
Advance Emergency and Traffic Management System
Authors:   Department of Computer Science Jyothy Institute of Technology, D Basavesh
Published: May 2024

Urban Alert is an innovative Android application that addresses urban emergencies, traffic management, and safety concerns. The system has a strong accident or emergency feature that allows users to quickly capture and upload incident details with location information. The traffic management component uses advanced algorithms such as YOLO and CNN to monitor and analyze real- time traffic conditions through IoT-enabled cameras. The application optimizes ambulance routes for zero traffic, minimizing response times during emergencies. Furthermore, safety options allow users to send alerts to relevant departments based on their specific needs. This paper examines the technical implementation, results, and evaluation of each feature, demonstrating how they can impact urban safety and response efficiency. Urban Alert is a comprehensive solution that enhances emergency response, traffic management, and public safety in urban areas. Keywords – Emergency Response, Traffic Management, IoT and AI Integration, Ambulance Routing, Safety Options, Real-time Incident Monitoring.
Valuable Content Marketing: Strategies for B2B Success
Authors:   Department of Commerce and Management  Kalinga University Naya Raipur, Chhattisgarh, Patel, Jay
Published: May 2024

Conventional promoting strategies, known for their interruptive nature, are losing adequacy in the present computerized scene. Organizations are battling to catch B2B client consideration with meddling techniques like cold pitches and mass publicizing. This examination investigates a strong new methodology: Marketing digital content to businesses. B2B Content Advertising: A Solution to Traditional Marketing Problems B2B digital content marketing is positioned in this study as an inbound marketing strategy. Dissimilar to nosy strategies, inbound showcasing draws in clients by furnishing them with significant and applicable substance. This substance, circulated decisively through website pages, online entertainment, and different channels, encourages trust and lays out the brand as a dependable wellspring of data. Here are a few key focal points: Esteem Added Quality written substance makes all the difference: Making great substance that tends to the particular necessities and difficulties looked by B2B crowds is vital. This content ought to be seen as enlightening, important, drawing in, and convenient. From Offering to Making a difference: A shift in mindset: B2B content promoting requires a huge social shift inside showcasing groups. It requires progressing from a "offering" mindset to a "making a difference" one. This requires an adjustment of promoting goals, strategies, measurements, and ranges of abilities. The Distributer Outlook: Fruitful B2B content promoting requests a "distributing" approach. Brands should foster a profound comprehension of their interest group's data needs and purchasing venture.
Exploring Digital Health Tool Adoption and the Impact of HR Analytics on Decision-making in Jalandhar’s Healthcare Organizations
Authors:   Lovely professional University, Rawat, Vandana
Published: May 2024

This study assesses the virtual tool adoption panorama within healthcare organizations. The healthcare enterprise is undergoing a length of huge transformation, pushed by way of the ever-developing need for advanced performance, patient care, and value control. Digital fitness equipment, encompassing a wide variety of technologies from affected person portals and telemedicine platforms to wearable health trackers and digital fitness records (EHRs), are hastily reworking how healthcare is introduced. This study delves into now not most effective the extent of virtual tool adoption however additionally the influence of HR analytics on choice-making within these businesses. HR analytics, the software of statistics analysis techniques to human resource management practices, offers precious insights into personnel traits, recruitment strategies, and employee performance. By examining how healthcare organizations leverage HR statistics to shape their group of workers strategies, the have a look at explores the ability blended effect of those developments on decision-making inside the healthcare panorama. This research seeks to offer insights into the changing landscape of healthcare pushed via technology and its considerable impact on HR decision making. Understanding the elements that power virtual tool adoption within healthcare corporations is critical for optimizing using these technologies. This observe will explore the perceived benefits and demanding situations related to digital health equipment, in conjunction with the position of leadership and organizational tradition in facilitating a success implementation. Additionally, the studies will study how HR analytics are being utilized to tell staffing decisions, training programs, and overall performance control inside healthcare groups.
PERCEPTION OF INVESTORS TOWARDS INITIAL PUBLIC OFFERING
Authors:   Lumbini Banijya Campus, Gautam Dilina
Published: May 2024

The aim of this research is to empirically investigate the perception of investors towards IPO. The research is based on primary data which was collected from 92 investors who were from Rupandehi district .Correlation and regression analysis were used to analyze the relationship between independent variables (Company Goodwill, Company performance, Company sector and Market information) and dependent variable (investment decision). The study revealed that Company performance is the highly considerable factors before making investment decision in IPO. Keywords: Initial Public Offering, Perceptions, Financial Market Investor, Company performance.
COSMETIC SUGGESTION BASED ON SKIN CONDITION
Authors:   Professor, Department of ISE JNN College of Engineering,, H C Suchethana
Published: May 2024

These days, beauty and cosmetology are exceptionally basic to a person's look. People get to a collection of things through online shopping and e-commerce websites. It is very challenging to choose the right cosmetic for human skin. Given that each person contains a specific type of skin, choosing right cosmetics that suit the person may be annoying. The composition depends on skin type, which can be dry, oily, or normal. Due to the significant crash that makeup have on a person's looks, the client must to choose the finest cosmetics for themselves based on person components . Identification of product that does not include any harms or allergies for the clients is very important. Thus the point of this application is to highlight the current applications of AI and machine learning in beautification and cosmetology by thorough examination of skin condition and prescribe personalized cosmetics based on the type of skin and buy secure things for the skin utilizing the Convolutional Neural Network (CNN). The objective is to achieve tall precision and recognize the skin type precisely. Keywords: Cosmetic, Skin type, Machine learning, Convolutional Neural Network.
Enhancing the Sense of Place in Indian Religious Streets: A Comparative Study
Authors:   MURP Faculty of Architecture and Planning, Dr. APJ AKTU, Lucknow, UP, Srivastava Ayushi
Published: May 2024

Indian religious cities are renowned for their spiritual significance and cultural vibrancy, with streets serving as vital arteries that connect devotees to sacred sites and cultural landmarks. This research paper investigates the intricate dynamics of public open spaces within Indian religious cities, focusing on two iconic streets: Vishram Bazaar Street in Mathura and Bhakti Vedanta Marg in Vrindavan. Through a comprehensive analysis of physical, perceptual, socio-cultural, and functional aspects, the study aims to understand the nuances shaping the sense of place in these revered urban settings. Findings reveal a juxtaposition of moderately negative and positive perceptions, indicating the need for targeted interventions to enhance the overall quality of these streetscapes and preserve their cultural and spiritual significance. Recommendations for physical improvements, cultural preservation initiatives, and functional enhancements are proposed to enrich the urban experience and promote sustainable development in Indian religious cities. Key Words: Indian religious cities, Streetscape dynamics, Sense of place analysis, Vishram Bazaar Street, Bhakti Vedanta Marg, Cultural vibrancy, Sacred sites, Infrastructure challenges, Community perceptions, Socio-cultural analysis, Street quality, Cultural preservation, Place-making, Collaborative planning
DROWSINESS PREVENTION SYSTEM FOR DRIVERS
Authors:   Assistant professor, Department of Biomedical Engineering, Sri Shakthi Institute of Engineering and Technology, Tamilnadu ,India., S Ms..Pavithra
Published: May 2024

The Anti-Fatigue Alert System is a vital invention meant to tackle the dangerous problem of driver sleepiness, which is a major cause of traffic accidents globally. This device uses a variety of behavioural and physiological markers to identify when a driver starts to become sleepy, giving early alerts to help avoid potential collisions. The alert system keeps track of the alertness levels of drivers using sophisticated sensor technologies and algorithms. When fatigue signals are recognised, it intervenes with an aural, visual, or vibrating signal. The creation, operation, and efficacy of anti-fatigue alert system in reducing the dangers of driver drowsiness are examined in this abstract, which highlights the essential role these devices play in improving traffic safety and preventing fatalities. Keywords: Fatigue, Alert system, Safety management.
Detection of Drowsy Drivers in Video Sequences via LSTM with CNN Features
Authors:   Department of Computer Science  and Engineering  Lovely Professional University Phagwara, Punjab, Kaur, Navjot
Published: May 2024

Fatigued driving is one of the main causes of traffic accidents. This paper developed a method for sleep drive detection that makes use of the convolutional neural network (CNN), recurrent neural network (RNN), short-term neural network (LSTM), cascade, and cam switching algorithms. Using CNN, the algorithm initially extracts the driver's face traits. The RNN that predicts the driver's degree of tiredness is then fed these features. The technology tracks the driver's eyes and eyelids using algorithms called Cascades and Cam shifts. The accuracy of the sleepiness prediction is increased further with the usage of this data. Using datasets of video recordings of attentive and somnolent drivers, the system was assessed. The outcomes demonstrated how well the algorithm could identify sleepy drivers. This system may be able to stop sleepy driving-related accidents. Ten thousand videos of awake and sleepy drivers were used to train the algorithm. Drivers can be observed in real time by the system. If the system detects that the driver is sleepy, it has the ability to sound an alarm. The technology can be used to stop driving when sleepy from causing accidents. Keywords: Convolution neural network, Recurrent neural networks, long short-term memory, eye tracking, face detection, drowsy driver detection, deep learning, computer vision, machine learning, and deep learning.
Correlation between hyperemesis gravidarum risk factors and body weight of first-trimester pregnant women
Authors: Handayani Handayani , Salsabila Afifah , Hijriyati Yoanita , Wulandari Shenda Maulina
Published: May 2024

Background: Nausea and vomiting early in pregnancy are experienced by around 70-80% of pregnant women. If nausea and vomiting occur too often, it will become a pathological condition called hyperemesis gravidarum. Many factors trigger hyperemesis gravidarum, necessitating more in-depth research regarding the risk factors for hyperemesis gravidarum and their impact on the weight of pregnant women in the first trimester.
Purpose: This study aimed to analyze the correlation between hyperemesis gravidarum risk factors and the body weight of first-trimester pregnant women in East Jakarta. 
Methods: A quantitative study employing descriptive analysis and a cross-sectional case-control method was conducted, including 84 first-trimester respondents selected using targeted sampling techniques. Data collection was performed using questionnaires, and data analysis was conducted using Chi-square.
Results: There is a significant relationship between the risk factor variables for severe morning sickness, namely age, occupation, history of vomiting, anemia, and the outcome, which is the measurement of pregnant women’s weight.
Conclusions: There is a relationship between age, occupation, pregnancy, history of vomiting, anemia, and mild stress with the results of weight measurement of pregnant women in the first 3 months of pregnancy.
The future of renewable energy in Iran's energy policy
Authors:   International Relations, East Tehran Branch, Islamic Azad University, Tehran, Iran, Hajimineh Rahmat , Rezaei Rad Ebrahim ,   International Relations, Science and Research Branch, Islamic Azad University, Tehran, Iran
Published: May 2024

Renewable energy has become a very important issue in the world. Access problems, high prices, and environmental issues of fossil fuels have caused the world to turn to renewable energy. Using the quantitative-qualitative combined methodology and the theoretical framework of energy security, this research has tried to answer the question of what the future of renewable energy in Iran is. The hypothesis of this research is that despite the adoption of programs and policies for the productivity and development of renewable energy in Iran, sanctions and investment problems make the development of renewable energy in Iran a structural problem. The findings of the research indicate that in the long term, solving structural challenges such as sanctions and investment and encouraging investment in renewable energy can provide a transition path by diversifying energy sources. So, the article tries to analyze the situation of renewable energy in terms of opportunities and challenges and show a vision of the future of this energy in Iran.
Predicting power and solar energy using neural networks and PCA with meteorological parameters from Diass and Taïba Ndiaye
Authors:   Electrical Engineering Department of Polytechnic School of Dakar (ESP), Water, Energy, Environment, Industrial Process Laboratory (LE3PI), Dakar, Senegal, Diop Sambalaye , Silly Traore Papa , Lamine Ndiaye Mamadou , Sambou Vincent ,   Departmemt of Physics of the Joseph KI-ZERBO UNIVERSITY), Laboratory of Renewable Thermal Energies(LETRE), Ouagadougou, Burkina Faso
Published: May 2024

The excessive reliance on conventional fossil fuel-based resources poses a significant threat to our environment. To mitigate this impact, it has become increasingly crucial to increase the integration of intermittent and non-polluting energy sources into our electrical grids. However, while this higher penetration rate brings benefits such as improved producer satisfaction and reduced fossil fuel consumption, it also presents challenges for traditional non-smart electrical networks. To promote intermittent energy sources effectively and maintain a balance between consumption and production, accurate forecasting of these energy outputs plays a vital role. This research paper focuses on studying the application of artificial neural networks for predicting the power and energy output of the Diass solar power plant in the short and medium term. The proposed approach utilizes not only the meteorological data from the city where the power plant is located but also data from a nearby city with a data acquisition station. Principal component analysis (PCA) is employed to select the relevant variables for the prediction model. Furthermore, the results obtained from our approach are compared to existing literature that solely uses meteorological data from the power plant's location. The comparison shows that our method achieves more satisfactory results, with mean absolute errors and root mean square errors of 0.0223 KWh and 0.003 KWh, respectively, and a prediction accuracy of 94.57% in terms of energy and power. It is worth noting that the computational resource requirements for our approach are higher, with simulation times ranging between 1788 seconds and 2201 seconds. By utilizing a broader range of data sources and employing advanced techniques like artificial neural networks, this research contributes to improving the accuracy of solar power generation forecasts. The findings highlight the potential of incorporating additional data inputs and advanced modeling techniques to enhance the performance of renewable energy systems, paving the way for a more sustainable and efficient energy future.
Waste heat recovery technologies in modern internal combustion engines
Authors:   Machine and Vehicle Design (MVD), Materials and Mechanical Engineering, University of Oulu, P.O. Box 4200, FI90014 Oulu, Finland, Moradi Jamshid , Mahmoudzadeh Andwari Amin , Könnö Juho , Gharehghani Ayat ,   School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran, Pesyridis Apostolos ,   Metapower Limited, Exeter EX2 4AY, UK
Published: May 2024

Waste heat recovery (WHR) technologies in internal combustion engines (ICEs) outline various methods to harness wasted energy for improved efficiency and reduced emissions. The discussion covers heat exchangers, turbo-compounding, bottoming cycles, thermoelectric generators (TEGs), thermochemical recuperation (TCR), thermoacoustic conversion, and absorption refrigeration. Each technology's principles, applications, benefits, and challenges are explored, highlighting advancements and innovations from industry leaders. The abstract underscores the ongoing efforts to maximize energy efficiency and minimize environmental impact in ICEs across diverse vehicle types and applications.
Desempenho cognitivo de pessoas idosas residentes em áreas rurais: revisão sistemática
Authors: Santos Paola Pereira dos , Lima Eduardo dos Santos de , Scortegagna Silvana Alba
Published: May 2024

O processo de envelhecimento pode ser acompanhado por um declínio em várias funções cognitivas, como memória, atenção, raciocínio, linguagem e funções executivas. Os Transtornos Neurocognitivos, considerados uma fase de transição entre a cognição saudável e a patologia, podem ser frequentes com o avanço da idade. Entretanto, o processo de envelhecimento é multideterminado e pode ser significativamente diferente para os indivíduos, alguns adultos mais velhos experimentam declínio cognitivo, enquanto outros mantêm um alto nível de desempenho cognitivo até o fim da vida. Esta Revisão Sistemática (RS) pretende compreender os fatores sociodemográficos implicados no desempenho cognitivo da população idosa residente em áreas rurais. Para atingir esse objetivo, pretende-se responder a três questões: a) Quais são os aspectos cognitivos da população de idosos residentes em áreas rurais quando comparados aos residentes urbanos?; b) Quais os fatores de risco relacionados às alterações dos aspectos cognitivos?; c) Quais os instrumentos utilizados nas avaliações dos aspectos cognitivos de pessoas idosas? A RS seguiu as orientações das diretrizes do Preferred Reporting Items for Systematic Reviews and Meta-Analyses, contemplou artigos publicados nas bases de dados Pubmed, LiLacs, Pepsic, e Science Direct, entre os anos de 2018 e 2023. Foram encontrados 6.689 estudos relacionados à temática sendo que 9 estudos preencheram os critérios de inclusão. Houve predominância de deficiências cognitivas em adultos idosos que residem em áreas rurais quando comparados aos que vivem em áreas urbanas, tendo como principais fatores de risco as condições sociodemográficas, o contexto sócio-histórico que influencia de forma direta na promoção de educação, o acesso à saúde primária e as condições econômicas. Entre os instrumentos de avaliação utilizados nas pesquisas, destacam-se o Mini Exame do Estado Mental (n=6) e a Escala Revisada de Demência de Hasegawa (n=2). Os diferentes instrumentos utilizados na avaliação da cognição, seus pontos de corte, as múltiplas traduções e adaptações que dependem das características geográficas, podem ter influenciado nos resultados das pesquisas. A identificação de sintomas de transtornos neurocognitivos pode auxiliar nos diagnósticos, evitar seu desenvolvimento e contribuir na preservação da qualidade de vida da população idosa, fomentando a construção de um sistema de saúde equitativo para todos.
Espiritualidade e poder: uma análise semiótica da trilogia O Senhor dos Anéis
Authors: Medeiros Alexsandro Melo , Medeiros Luana Pantoja
Published: May 2024

Este artigo tem por objetivo analisar o aspecto semiótico audiovisual, ou seja, a partir da transmutação do texto verbal (literário) em um não verbal (cinematográfico) da trilogia O Senhor dos Anéis. Os dados apresentados foram coletados seguindo uma metodologia de pesquisa bibliográfica analisando aspectos teóricos referentes à semiótica. Discute-se como a trilogia retrata a relação simbólica entre o claro e o escuro, o belo e o feio, luz e trevas, a partir do confronto entre as forças do bem e as forças do mal cuja construção simbólica se dá em torno do poder do Um Anel. Pretende-se realizar uma hermenêutica da simbologia presente na trilogia e como essa simbologia é carregada de espiritualidade e disputa pelo poder a partir do confronto entre as forças do bem e do mal. Na luta contra o poder do Um Anel surge A Sociedade do Anel: nove companheiros que serão guiados através dessa longa jornada pelo mago Gandalf. Ao retratar o confronto entre as forças do bem e as forças do mal, a trilogia ressalta uma relação simbólica entre o claro e o escuro, luz e trevas, o belo e o feio.
Transformação da saúde: o impacto da Inteligência Artificial na medicina moderna
Authors: Leite Kassio Romulo Veras , Pasquali Marco Antonio Batisti , Silva Thales André Strabelli Neves da , Rodrigues Lucas Von-Rondon Venâncio , Melo Guilherme Dantas Ximenes , Pacheco Ana Paula Queiroz Dias Fernandes , Lourenço Filho Maurício Caetano , Lopes José Roberto Ribeiro , Bezerra Samuel de Souza , Scaravonatti Maria Eduarda Fideles , Sousa Maria Clara Dias de , Torres Francisco Brenon de Oliveira , Guimarães Priscila Anne Monteiro , Santos Jordano Bruno Cardoso Pinto dos
Published: May 2024

A incorporação da inteligência artificial (IA) na medicina moderna tem promovido uma revolução significativa na forma como os cuidados de saúde são prestados e na maneira como as doenças são compreendidas e tratadas. Este artigo investiga o impacto diversificado da IA em múltiplos aspectos da medicina, abrangendo diagnóstico, tratamento, gestão de saúde e pesquisa médica. Com base em uma revisão abrangente da literatura e estudos de caso selecionados, demonstra-se como esta tecnologia tem aprimorado a acurácia diagnóstica em condições médicas variadas. Essas melhorias são observadas em diversas especialidades, incluindo neurologia, radiologia e patologia, entre outras. Além disso, foi examinado o papel da IA na personalização de tratamentos, enfatizando sua capacidade de analisar grandes volumes de dados para fornecer recomendações terapêuticas personalizadas. Foi considerado os desafios éticos, regulatórios e práticos que surgem com a adoção da IA na saúde, incluindo questões de privacidade de dados, viés algorítmico e a necessidade de um quadro regulatório robusto. Prospecta-se, ainda, o futuro da IA na medicina, postulando que a sua incorporação contínua poderá não apenas incrementar a eficiência dos cuidados de saúde, mas também democratizar o acesso a terapias médicas de alta qualidade em escala global. O estudo ressalta a necessidade de uma abordagem colaborativa e interdisciplinar para superar as barreiras à adoção da IA, assegurando que seu potencial seja completamente explorado na reinvenção do cenário da saúde.
Definição dos parâmetros de corte para usinagem de aço inoxidável
Authors: Rizo Samuel
Published: May 2024

O processo de fabricação por usinagem demanda uma cuidadosa análise dos parâmetros de corte e dos fenômenos envolvidos, como a formação de cavaco, os esforços de corte, o avanço adequado das ferramentas, as rugosidades do material usinado, as vibrações e os mecanismos de desgaste das ferramentas. Nesse contexto, o objetivo primordial deste estudo é realizar uma análise detalhada e estabelecer parâmetros apropriados para iniciar a fabricação. Por meio dos resultados obtidos, será possível ajustar esses parâmetros, buscando alcançar eficiência e qualidade na produção. É importante ressaltar que a seleção dos parâmetros de fabricação já apresenta desafios, especialmente devido às características dos materiais, como o encruamento, que aumenta a resistência do material e torna o processo de fabricação mais complexo. Portanto, é crucial obter parâmetros precisos ou próximos dos ideais para minimizar perdas de tempo e materiais, o que pode ser especialmente oneroso em períodos de crise. Além disso, é essencial precificar os serviços de forma competitiva, visando manter a preferência dos clientes. A pré-configuração desses parâmetros durante a programação pode significativamente acelerar o processo de fabricação de peças na usinagem.
Direito, código processo civil: chamamento ao processo
Authors: Gomes Emmannuell Fernandes Cardoso
Published: May 2024

Esta pesquisa analisa a aplicabilidade do chamamento ao processo na esfera do Direito Processual Civil brasileiro, destinado a aumentar a eficiência e equidade judiciais, permitindo que o réu requisite, para o processo, terceiros na mesma obrigação legal envolvidos. De natureza exploratória e qualitativa, a pesquisa sublinhou a análise de decisões judiciais, e o constante na literatura acadêmica, e na legislação pertinente, relativamente às discrepâncias entre Prático-teóricas como e aplicabilidade do chamamento ao processo.  Teoricamente projetado para promover justiça e economia processual, na prática, resultados indicam que, o chamamento ao processo enfrenta, frequentemente, o comprometimento de seus objetivos por limitações devidas, principalmente, à extensão dos litígios e complexidade que possam surgir. Conclui-se que revisão das normativas legais e práticas se faz urgente no afã garantir que sejam atendidos efetivamente os seus propósitos Primordiais que aludem ao chamamento ao processo, sugerindo-se a inclusão de métodos quantitativos em pesquisas futuras para a exata avaliação dos impactos. Para reformas legislativas e melhorias procedimentais no sistema judiciário brasileiro é primordial a análise das implicações práticas e teóricas desse dispositivo legal.
Saúde mental e qualidade de vida de paciente com Doença Obstrutiva Crônica Pulmonar
Authors: Lucena Thayná Rakel Quirino , Barros Michelly Alves , Linhares Rebeca Ferreira , Arruda Neto Matheus Dias de , Santos Vitória Nicoly Andrade dos , Silva Luana Idalino da , Sousa Milena Nunes Alves de
Published: May 2024

A doença pulmonar obstrutiva crônica é uma síndrome clínica que compreende a bronquite crônica e o enfisema pulmonar. Um desafio a ser enfrentado, tanto para sustentar um equilíbrio físico quanto emocional. Entender a relação entre qualidade de vida e saúde mental dos pacientes com Doença Pulmonar Obstrutiva Crônica (DPOC). Foi realizada uma revisão integrativa da literatura, buscando responder a seguinte questão: quais as relações entre qualidade de vida e saúde mental nos pacientes com DPOC? Foram realizadas buscas nas revistas digitais como ScienceDirect, National Library of Medicine, Scientific Eletronic Library Online e Biblioteca Virtual em Saúde. Posteriormente, foram aplicados os critérios de elegibilidade e de exclusão, seguido da leitura dos artigos selecionados, somando um total de 17. Os achados indicaram que aspectos como interrupção de tratamento, comorbidades associadas, depressão e ansiedade são fatores que diminuem a qualidade de vida e saúde mental dos pacientes, por conseguinte, um acompanhamento continuado e prolongado, exercícios mente e corpo são resultados promissores que elevam qualidade de vida e saúde mental em pacientes com DPOC. Assim, terapias de cuidado continuado, terapia mente-corpo e práticas regulares de exercícios físicos geram melhor resposta no quadro clínico e na qualidade de vida do paciente.