bluuebunny/crossref_metadata_2025 huggingface dataset:
Marketing and Sales Promotion
Authors:   School of Business Studies  Kalinga University, Naya Raipur-492101, Balarabe Yahaya
Published: May 2024

Marketing and sales promotion plans should begin with an overview of the campaign's background, goals, and methodology. It establishes the framework for the other parts of the marketing strategy and is thus crucial to them. Potentially addressed in the introduction are the following significant points: Good or Service Provide a high-level summary of the advertised item or service to kick things off. The marketing strategies discussed later in the article are supported by this background knowledge. Be very explicit about what you want to achieve with the sales and marketing campaign. Whether the objective is to introduce a new product, increase sales, or enhance brand awareness among consumers, it must be clearly articulated. For any advertising effort to be effective, you need to identify your target audience. This section may contain demographic information such as age, gender, location, socioeconomic status, etc. Knowing one's target audience inside and out is critical for crafting effective marketing messages. Goals for Marketing: Outline the specific outcomes you desire from your marketing and sales initiatives. Goals should be SMART (specific, measurable, attainable, relevant, and time-bound) and align with the overall objectives of the organisation. Outline the marketing objectives and the strategies that will be implemented to achieve them. This includes things like sales, influencer partnerships, social media promotions, advertising, etc. Financial Resources: Provide a brief overview of the financial resources that will be utilised for the marketing and sales promotion drives. So now we're all on the same page, and we have all the tools we need to put the plan into action. The desired result is a discussion of the expected outcomes of the sales promotion and advertising campaign. Revenue projections, increases in brand awareness, targets for new client acquisition, etc. are all instances of such measures. Appropriately acknowledge and appreciate those who have contributed to developing the plan for marketing and sales promotion. Taking everything into account, the introduction does a fantastic job of setting the stage for the sales promotion and marketing materials and providing readers with an idea of what to expect in terms of tone and substance. Being both brief and informative, it should stimulate interest in the next marketing activities.
Surveying Emerging Trends in DDoS Defense
Authors:   Jain(Deemed-to-be University), Pandey Sumith
Published: May 2024

This The DDoS attack threat is evolving, and because of this, organizations are discovering and using new modern technologies to lay the ground for more effective defensive strategies. This paper is devoted to the investigation of the most efficient methods fighting DDoS – downtime of the network, and ensuring cybersecurity on different domains. First of all, the integration of Convolutional Neural Networks (CNNs) into cybersecurity is a very promising move with respect to fighting exactly the phishing and application-layer DDoS attacks in greater details than the machine learning approaches like the LSTMs and SAEs. Another aspect of building the effective opposition against the dummy data attacks on the critical infrastructures, for example on the power systems, is creating the multi-dimensional mitigation models composed of various timely detection techniques and robust network architecture. In addition, the usage of Physically Unclonable Functions (PUFs) in network architectures provides a means of authentication as well as access control that can improve the resilience of a network against DDoS attacks. PUFs enables the blockade of unwanted packets of high volume traffic, allowing granular traffic filtration and isolation. By using hardware solutions such as Distributed-Denial-of-Service (DDoS) attack prevention, SDN-biased security frame with deep learning algorithms can improve network resilience with significant detection and response to slow-rate DDoS attacks. At last EWMA, KNN, and CUSUM as statistical methods integrated with FOG computing architectures ensure real time and effective solution for the detection and mitigation of DDoS attacks in the IoT networks, making them immune to the current as well as the continuously emerging cyber threats. Through the integration of these cutting edge methods, organizations will be able to hold their ground against cyberattacks catalyzed by DDoS menace and stay ahead of dynamic threats whenever they arise. Keywords— Cloud computing, Data threats, Data Protection, Cloud security.
Design & Development of Smart Fire Safety System For e-Vehicles Using IOT
Authors:   Wainganga College Of Engineering & Management, Nagpur Near Gumgaon Railway  Station, Wardha  Road Nagpur,, Patorkar Sandip
Published: May 2024

The project concept of An autonomous fire safety mechanism for EVs is an inventive way of considering a less cost-effective design and a more convenient application for e-vehicle safety. Day by day, the number of fatalities in electric vehicles increases. In this project, our main aim is to reduce the number of accidents with electric vehicles by making a smart fire safety system for electric vehicles. With the rapid adoption of electric vehicles (EVs), ensuring their safety, particularly concerning fire hazards, has become paramount. This abstract presents a conceptual framework for a sophisticated fire safety system tailored specifically for EVs. The proposed system integrates advanced technologies such as battery monitoring systems (BMS), temperature and smoke sensors, machine learning algorithms, active fire suppression mechanisms, emergency shutdown features, remote monitoring capabilities, user alerts, and compliance with safety standards. By combining these elements into a cohesive system, EV manufacturers can significantly mitigate the risks associated with fires in electric vehicles, enhancing overall safety for drivers, passengers, and emergency responders. With this technique, the fire extinguisher automatically puts out the fire when it detects flames or smoke coming from the vehicle's fire zones. Numerous factors can cause an electric vehicle to catch fire. The lithium-ion battery is the primary cause of flames in electric vehicles used within them. Installing an autonomous fire extinguishing system with Internet of Things (IoT) technology can reduce potential financial loss from a fire while also raising vehicle and human safety standards. Additionally, as soon as an accident is discovered, the nearby authorities or emergency services are notified, allowing them to get to you sooner. KEYWORDS:- Accident prevention, emergency alert, controller, fire incident, IOT technology, etc.
IMPACT OF ENDOWMENT EFFECT ON CUSTOMER PURCHASING BEHAVIOUR
Authors:   Assistant Professor, MBA Dept.,St.Pious X Degree and P.G. College for women, Nacharam., P Gayathri
Published: May 2024

An instance known as the endowment effect occurs when someone values an item they currently possess more highly than they would if they did not own it. Things that are emotionally or symbolically significant to an individual can be a good example of the endowment effect. "Ownership" and "loss aversion" have been found to be the two primary psychological factors driving the endowment effect. Companies frequently attempt to capitalize on this cognitive bias in marketing, which is closely related to the endowment effect. If investors have a well-defined investment strategy that includes a timetable for selling particular investments, they can mitigate the endowment effect. This article focuses on exploring the facts, and importance of the endowment effect on purchases and sales as well. Keywords: endowment effect, cognitive bias, marketing, investment, strategy, psychological factors
Track Maven
Authors:   Computer Science & Engineering Acropolis Institute of Technology  & Research Indore, India, Trivedi Adarsh
Published: May 2024

Track Maven is a web application designed to streamline task management processes within organizations. Track Maven aims to provide a centralized platform for managing tasks, enabling efficient task assignment, monitoring, and tracking. The dashboard offers a user-friendly interface for creating, updating, and deleting tasks, as well as assigning tasks to specific teams or individuals. It also includes features for monitoring task completion status and generating reports to track team performance. The project utilizes React for the frontend interface, Node.js and Express.js for the backend server, and MongoDB as the database. The application is secured using JWT authentication, ensuring that only authorized users can access and modify task-related information. Additionally, the dashboard includes data visualization features to provide managers with insights into team productivity and task completion rates. Keywords— Task Management, Dashboard, Task Tracking, Data Visualization, JWT Authentication.
Soil Analysis and Crop Prediction System
Authors:   JAYAWANT COLLEGE OF ENGINEERING AND POLYTECHNIC , KILLEMACHINDRAGAD,SANGLI, Patil, Vijaya
Published: May 2024

In the vast tapestry of the earth's bounty, where agriculture reigned supreme, a quest unfolded – a pursuit of sustainable practices and optimal crop selection, crucial threads in the fabric of food security and economic prosperity. For in those regions where the farmer's toil was the heartbeat of livelihood, an intricate dance between soil, environment, and crop suitability posed a formidable challenge, one that traditional knowledge and experience alone could not fully unravel. Thus, a clarion call echoed through the fertile fields, beckoning a new era of innovation – a comprehensive soil analysis and crop prediction system that would harness the power of machine learning, weaving data into a tapestry of enlightened cultivation. Like a grand symphony, this system harmonized a multifaceted approach, blending the rigorous physicochemical analysis of soil samples with the rhythmic cadence of climatic data and the echoes of historical crop yield. From the soil's pH to its nutrient composition, texture, and moisture content, each parameter was meticulously evaluated, a prelude to the orchestration that would follow.This earthly aria was then enriched by the melodious whispers of meteorological data – temperature, rainfall patterns, and humidity levels, each note tailored to the region's unique symphony.But it was the machine learning ensemble, a grand chorus of supervised and unsupervised algorithms, that truly breathed life into this composition. Trained on a comprehensive dataset of soil analysis, climatic conditions, and historical crop yield records, these algorithms learned to decipher the intricate patterns and harmonies that bind input variables to crop performance, their synthetic synapses firing in perfect synchronicity.and from this symphony emerged the system's crowning aria – a resonant recommendation of crops tailored to the specific soil and environmental conditions of each location, a harmonious blend of predicted yield potential and optimal growing conditions.
A STUDY ON ADOPTION OF GREEN PRACTICES AMONG THE STAFF MEMBERS OF HEI'S OF THE NORTH MAHARASHTRA REGION
Authors:   G H Raisoni University, Amravati, Pande Mr. Amol P.
Published: May 2024

Today, not only the business organization and industries concern about the environment but also the Educational especially Higher Educational Institutes also worry to save the environment. By implementing Green Practices in the HEI’s institutes and colleges will help to achieve the Environmental Sustainability which is the major concern of the today’s world. The study focuses on the awareness of the staff members of the HEI’s of the North Maharashtra Region about Green Practices. The study also concentrates on staff members of the HEI’s of the North Maharashtra Region are how much concern with adoption of Green Practices in the Campus. The study also focuses on a relationship between awareness about Green Practices and the Gender of the staff members of the HEI’s of North Maharashtra Region. The study also enhance the existing form of the knowledge on a relationship between adoption of Green Practices and the Gender of the staff members of the HEI’s of North Maharashtra Region. Keywords: Green Practices, Green Employee, Environment Sustainability.
SOLAR WIRELESS ELECTRIC VEHICLE CHARGING SYSTEM
Authors:   Department of Electronics and Telecommunication, Rajiv Gandhi Institute of Technology,, Kamble, Amar
Published: May 2024

This research paper introduces a groundbreaking Solar-powered wireless charging solution for electric vehicles, responding to the global shift toward sustainable transportation. The project employs solar panels to efficiently capture and store energy, utilizing wireless energy transfer technology for eco-friendly EV charging. Key objectives include harnessing solar energy, wireless power transmission, DC charging, and lowering our dependency on traditional grid electricity. The project's weight stems from its potential to advance sustainable transportation, reduce emissions, and drive innovation in wireless power transfer and solar technology. It serves as a proof-of-concept, demonstrating feasibility, inspiring investment, and promoting awareness of renewable energy's role in EV charging for a greener future. Keywords : Future mobility trends, Innovation in charging technology, Sustainable transportation, Wireless energy transfer
Data Structure Profiler Using MERN Technology
Authors:   Assitant Professor, Department of Computer Science and Engineering, Raj Kumar Goel Institute of Technology, Ghaziabad, India, Sharma Rahul
Published: May 2024

Profiler introduces a cutting-edge approach to efficiently manage and track Data Structures and Algorithms (DSA) in software development projects. In the realm of modern software engineering, where complexity is ubiquitous and scalability is critical, effective management of DSAs is essential for ensuring the robustness, maintainability, and performance of software systems. DSA Profiler seamlessly integrates into the development lifecycle, offering developers a centralized platform to meticulously document, organize, and monitor the implementation of various data structures and algorithms within their codebase. Its intuitive interfaces and powerful functionalities facilitate the process of incorporating, modifying, and optimizing DSAs. By providing detailed insights and analytics, DSA Profiler empowers developers to make informed decisions about the most appropriate data structures and algorithms for their specific needs, ultimately streamlining the development process and significantly enhancing code quality. One of the standout features of DSA Profiler is its ability to benchmark data structures and algorithms, allowing developers to evaluate their performance under different conditions. This benchmarking capability ensures that developers can identify and address performance bottlenecks early in the development cycle. Furthermore, This collaborative environment helps maintain consistency and adherence to standards across projects, which is particularly beneficial in large-scale and distributed development environments. Keywords - data structure benchmarking, data structure optimization, algorithm performance tracking, software scalability, development lifecycle integration, codebase management, performance analytics, collaborative development tools, real-time optimization recommendations.
Stock Price Prediction Using Machine Learning
Authors:   Department of Computer Science and Engineering, GUPTA, ANUJ KUMAR
Published: May 2024

This project’s Researchers have been studying different methods to effectively predict the stock market price. Useful prediction systems allow traders to get better insights about data such as: future trends. Also, investors have a major benefit since the analysis give future conditions of the market. One such method is to use machine learning algorithms for forecasting. A number of researchers have come up with various ways to solve this problem, mainly there are traditional methods so far, such as artificial neural network is a way to get hidden patterns and classify the data which is used in predicting stock market. This project proposes a different method for prognosing stock market prices. It does not fit the data to a specific model; rather we are identifying the latent dynamics existing in the data using machine learning architectures. In this work we use Machine learning architectures Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN) and Hybrid approach of LSTM + CNN for the price forecasting of NSE listed companies and differentiating their performance. On a long term basis, sling window approach has been applied and the performance was assessed by using root mean square error.
YOLOv4 BASED POTHOLE DETECTION SYSTEM
Authors:   Department of Computer Science and Engineering, Jawaharlal Nehru New College of Engineering, Shimoga, M Nandish
Published: May 2024

Potholes are very commonly found these days and they found everywhere. This leads to major disturbances to our society in the form of vehicle damages, accidents and it also effects the economy of that countries where potholes are present. To solve the problem, the solution is created using YOLO (You Only Look Once) algorithm for pothole detection. It is a pretrained model which detects the pothole using YOLO v4 algorithm. In last decade many different techniques are proposed but YOLO gave better results and the speed and accuracy is also high. In the object detection system, the input is given in the form of images or videos and the respective output is to detect the object. Key Words: YOLO v4 algorithm, Pothole.
DEEPFAKE DETECTION USING LSTM & RESNEXT-50 1
Authors:   Department of Information Technology,  Mahatma Gandhi Institution of Technology, Gandipet, Hyderabad., SM MS VARALAKSHMI,
Published: May 2024

As computing power increases, "deep fakes," or films that seem like they were created by a real person, are becoming feasible thanks to deep learning algorithms. Political instability, terrorism, revenge porn, or extortion can be the motivation for these lifelike face swapped deep fakes. This research presents a novel deep learning system that can recognize the difference between real and AI-generated films.We have developed a method that can identify deep fake replacements and reenactments automatically. We're using AI to combat AI. Our system's Res-Next Convolution neural network retrieves properties at the frame level. A recurrent neural network (RNN) trained using long short-term memory (LSTM) characteristics can distinguish between deep films and regular movies. On big, balanced, and mixed datasets, our technique is tested by Face-Forensic++ [1], Deepfake Detection Challenge [2], and Celeb-DF [3]. The quality of real-time data is enhanced by this. We prove that our technology consistently outperforms the competitors. Computer vision, Res-Next Convolution neural network, RNN, and LSTM are some of the index phrases.
Epilots : A System to Predict Hard Landing During the Approach Phase of Commercial Flights
Authors:   Siddhartha Institute of Technology and Sciences, M .Mamatha,
Published: May 2024

This project aims to develop a system called E-Pilots that uses machine learning algorithms to predict hard landings during the approach phase of commercial flights.The system will analyze flight data to precede hard landings.The goal is to provide pilots with real-time warnings and guidance to prevent accidents and improve safety.The research methodology includes the collection and analysis of flight data, the development and testing of machine learning algorithms, and the integration of the E-Pilots system with existing flight systems.The findings of this project are expected to contribute to the improvement of aviation safety and reduce the occurrence of hard landings. The implications of this research may also extend to other areas of aviation safety and flight automation.
AI YOUTUBE VIDEO SUMMARY USING NLP
Authors:   Dept. of Computer Science and Engineering  Siddhartha Institute of Technology & Sciences  Telangana, India, Kumar, R.Dinesh
Published: May 2024

The "AI YouTube Video Summary using NLP" project introduces an innovative solution to the burgeoning challenge of digesting vast amounts of video content on platforms like YouTube. With the exponential growth of online video, users often face time constraints and information overload, hindering their ability to extract valuable insights efficiently. Our project addresses this issue by harnessing the capabilities of Artificial Intelligence (AI) and Natural Language Processing (NLP) to automatically generate concise summaries of YouTube videos. Through a seamless integration with the MERN stack, our system enables users to input video URLs and receive summaries in three distinct forms: short, long, and key insights. By automating the process of transcript extraction, linguistic analysis, and summarization, our system streamlines content consumption, offering users a time-saving and effective method for accessing essential information. By leveraging machine learning algorithms and linguistic analysis techniques, our system accurately identifies and distills key themes, concepts, and insights embedded within the video content. This empowers users to gain comprehensive understanding without the need for exhaustive viewing, thereby enhancing their browsing experience and knowledge acquisition. In essence, the "AI YouTube Video Summary using NLP" project represents a significant advancement in content consumption methodologies, offering a practical solution to the challenges posed by the proliferation of video content online. Through our innovative approach, we aim to revolutionize the way users engage with YouTube videos, facilitating efficient information extraction and empowering them to make the most of their online viewing experience. Keywords: Artificial Intelligence (AI), Natural Language Processing (NLP), Text Summarization, Multimedia Content Analysis, Automatic Summarization.
Desktop Assistant Based on NLP
Authors:   Department of Computer Science and Engineering ,  IIMT College of Engineering , Greater Noida , U.P, Singh Ankit Kumar
Published: May 2024

Natural Language Processing (NLP) has emerged as a critical component of artificial intelligence, enabling machines to comprehend and interact with human language. This research paper explores the current state of the art in NLP, highlighting recent innovations, trends, and ongoing challenges. It delves into various applications of NLP, discusses the datasets and models that drive advancements, and examines the evaluation metrics used to assess NLP systems. Key innovations such as transformers, pre-trained language models, and transfer learning have revolutionized the field, leading to significant improvements in performance across a variety of tasks. Additionally, the paper addresses the growing emphasis on ethical AI and bias mitigation, as well as the integration of NLP with other AI technologies to create multimodal systems. Applications of NLP in text classification, sentiment analysis, machine translation, conversational agents, and information retrieval are thoroughly examined. The discussion extends to the critical role of benchmark datasets and pre-trained models in driving progress. Furthermore, the paper evaluates the effectiveness of various metrics used to measure the performance of NLP systems. Finally, the future prospects and potential research directions are considered, highlighting the ongoing efforts to push the boundaries of what NLP can achieve in an increasingly interconnected and data-driven world. Keywords Natural language processing . Natural language understanding . Natural language generation
Sleep Disorder Detection Using EEG Signals
Authors:   Department of Electronics and Communication, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, Indiia, S G Shashank
Published: May 2024

Sleep disorders are prevalent health concerns affecting millions of individuals worldwide, with adverse impacts on overall well-being and cognitive function. Detecting and diagnosing these disorders accurately is crucial for effective treatment planning and management. This project focuses on utilizing Electroencephalogram (EEG) signals, a non-invasive method for monitoring brain activity, to detect sleeping disorders. By leveraging advanced signal processing techniques and machine learning algorithms, this research aims to develop a robust and accurate system capable of identifying various types of sleep disorders, such as insomnia, sleep apnea, and narcolepsy, based on EEG data. The proposed approach holds the potential to enhance early detection, personalized treatment strategies, and ultimately improve the quality of life for individuals affected by sleep disorders. Keywords-Ambulatory EEG, automatic scoring, deep learning, electroencephalography, sleep staging.
SMART PLANT HEALTH CARE SYSTEM: Image Based Disease Detection and Pesticide Remediation
Authors:   Department of ECE ,Dayananda Sagar academy of technology and management , Banglore , Karnataka, Savadakar Rohan S
Published: May 2024

Plant and tree populations must be preserved and supported in order to mitigate the growing issues brought about by food and water scarcity brought on by population increase and climate change. The occurrence of plant diseases is a major issue in agriculture as it severely reduces agricultural output. In order to overcome this difficulty, scientists are investigating novel approaches that make use of sensors and imaging to collect data on plant health in order to detect diseases early on. The goal of this project is to create a "Smart Plant Health Care System" that combines embedded technologies such as Arduino, Raspberry Pi, and Jetson Nano for pesticide remediation controlled by Arduino and image-based illness diagnosis. More specifically, convolutional neural networks (CNNs) are implemented for real-time illness diagnosis using the processing capacity and adaptability of the Raspberry Pi. Keywords: Smart Agriculture, Plant Health Monitoring, Disease Detection,
The Influence Of Sports Facility Management And Teacher Services On The Effectiveness Of Physical Education
Authors: Donny Setiawan  , Antonius Tri Wibowo
Published: May 2024

This study aimed to assess the level of management of sports facilities and teacher services in relation to the effectiveness of physical education in high schools. In this study, the researchers employed a descriptive survey research method. The participants of this study consisted of physical education instructors and eleventh-grade students from public high schools in Banyuwangi Regency, comprising a total of 3500 students. A random sampling procedure was employed, resulting in a sample size of 95 pupils. Two commonly used methods for collecting data are questionnaires and documentation. The author conducted data analysis using various statistical tests, including the correlation coefficient test, the coefficient of determination, the t test, and the F test. Based on the findings of the study, it has been determined that: 1) The school's facility management is deemed adequate; 2) The services rendered by teachers are deemed satisfactory. There is sufficient quality in both facility management and instructor services.
Physical Fitness Management Of Madrasah Ibtidaiyah Students
Authors: Wening Nugraheni  , Syahra Andriyany  , Ahmad Alwi Nurudin
Published: May 2024

This study was conducted with the aim of assessing the level of physical fitness of MI Muhammadiyah Cipetir students. The type of research used is descriptive quantitative, and the method applied is survey. The population that became the focus of the research was all MI Muhammadiyah Cipetir students. The research sample consisted of 267 students, selected through the total sampling method. Data collection techniques were carried out through TKJI tests and measurements, including sit-ups, vertical jump, pull-ups, 40 meter sprints, and 600 meter runs. Data analysis used a percentage-based quantitative descriptive statistical approach. The results showed that students' physical fitness level could be categorized as "Excellent" in 2 students (0.75%), "Good" in 68 students (25.47%), "Moderate" in 117 students (43.82%), "Less" in 70 students (26.22%), and "Very Poor" in 10 students (3.75%). Thus, it can be concluded that the level of physical fitness of MI Muhammadiyah Cipetir students in general is in the "Moderate" category.
The Paradox of Thermodynamic Instability
Authors: Jensen William B. , Kugel Roger W. , Pinhas Allan R.
Published: May 2024

The constraints on the Gibbs free energy equation required to intercompare the stabilities of chemical species are reviewed, and the concept of thermodynamically unstable but kinetically stable compounds is defined. A method for synthesizing these compounds is then discussed based on a rule first stated by the French chemist, Pierre Macquer, in 1749, and its modern application illustrated using several concrete examples. A simple graphical method for visualizing trends in thermodynamically stable versus thermodynamically unstable compounds is then introduced and illustrated with example plots. The paper concludes with a brief note on terminology.
Suicide attempts by poisoning and other means: distinguishing characteristics
Authors: Blay Córdoba Ainara , Pallàs Oriol , Fonseca Francina , Cirera Isabel , Torrens Marta , Supervía August
Published: May 2024

OBJETIVOS. Identificar posibles diferencias en los intentos de suicidio en función del uso de tóxicos u otros métodos, describir posibles factores predictivos de utilización de un método toxicológico y determinar los tóxicos más utilizados. MATERIAL Y MÉTODO. Estudio observacional descriptivo retrospectivo de los pacientes que consultaron por intento de suicidio entre enero de 2018 y julio de 2021 en los servicios de urgencias médicas y psiquiátricas de un Hospital Universitario de tercer nivel. Se analizaron las diferencias según hubieran utilizado un método toxicológico o no toxicológico. Se recogieron datos demográficos, antecedentes psiquiátricos y de consumo de sustancias, intentos previos de suicidio, redacción de carta de despedida y presencia de clínica. RESULTADOS. Se registraron 653 pacientes por tentativa de suicidio. La mayoría empleó un método toxicológico (87,6%). Existieron diferencias en el sexo (70,6% de mujeres en el método toxicológico y 55,6% de varones en el no toxicológico; p < 0,001). En ambos grupos había mayoría de españoles (71,2% vs 58%; p = 0,021) y antecedentes de enfermedad psiquiátrica (84,6% vs 80,2%). Los factores que predicen el uso de un método toxicológico son el sexo femenino y los antecedentes de trastorno adictivo. En cambio, los antecedentes de trastorno psicótico se asocian negativamente con el uso de tóxicos. CONCLUSIONES. Existen diferencias en los intentos de suicidio entre grupos según el método empleado, fundamentalmente el sexo predominante, la nacionalidad y determinados antecedentes psiquiátricos.
Risk of thromboembolic events after recovery from SARS-CoV-2 infection
Authors: González-Revuelta Enrique , Lago-Gancedo Héctor , Camacho-Montes Borja , Leiva-Bisbicuth Sonia Paola , Iglesias-Vela Marta , Seco-Calvo Jesús
Published: May 2024

INTRODUCCIÓN. La infección por SARS-CoV-2 ha presentado una alta frecuencia de episodios tromboembólicos como complicación. Sin embargo, los efectos ya superada la fase aguda continúan siendo un interrogante, desconociéndose si el efecto protrombótico persiste. MATERIAL Y MÉTODO. Estudio de casos y controles que definió como casos los tromboembolismos atendidos en urgencias hospitalarias entre el 1 noviembre de 2020 y el 31 de marzo de 2021. Se comparó con una serie de controles seleccionados entre las consultas a urgencias en el mismo periodo con el fin de conocer, atendiendo al antecedente de COVID-19, el riesgo protrombótico de la misma. Finalmente, se realizó un modelo predictivo sobre estos episodios mediante regresión logística binaria. RESULTADOS. Se seleccionaron 179 casos y 390 controles. La mayoría de los casos se debieron a accidente cerebrovascular y síndrome coronario agudo (30,2 y 21,2%, respectivamente) y 17 (9,5%) presentó antecedente de COVID-19 superada recientemente. De los 390 controles, 35 (8,9%) había padecido la infección. Estos datos arrojaron una OR de 1,064 (IC 95% de 0,58-1,96), así como un modelo de escaso poder predictivo (R2 = 0,028). El tamaño del efecto fue pequeño en todas las variables del modelo, si bien en la gravedad con la que se padeció la COVID-19, el tamaño del efecto fue medio (0,2). CONCLUSIONES. El riesgo protrombótico en pacientes que ya han superado la enfermedad por COVID-19 no es significativamente mayor. Su manejo clínico no exigiría de anticoagulación profiláctica durante periodos prolongados.
Results of HDV RNA detection in male seminal fluid and female cervical swab samples using RT-PCR
Authors: Enkhjargal Saruul , Lkhagva-Ochir Oyungerel , Enkhbat Anir , Dashdorj Naranjargal , `Vangan Nyamtsengel , Oidovsambuu Odgerel
Published: May 2024

Mongolia has an extremely high prevalence of hepatitis D virus (HDV), which leads to increased morbidity and mortality from hepatocellular carcinoma (HCC). HDV is the most severe form of chronic viral hepatitis (CVH). A recent study estimated that the prevalence of anti-HDV was 67.5% among hepatitis B surface antigen-positive cases in Mongolia. HDV infection is particularly prevalent in sexually active young people. The virus may be transmitted through sexual intercourse, and it is crucial to confirm this by detecting HDV RNA in semen and cervical swabs of patients with chronic hepatitis delta. This pilot study was conducted with 16 participants, including eight males and eight females. Viral RNA was isolated from the blood, male seminal fluid, and female cervical swab samples of all participants in the study. HDV RNA was quantified using RT-PCR in samples from blood, seminal fluid, and cervical swabs. This study found that the detection rate of HDV RNA differed between male and female samples, with 62.5% of seminal fluid samples in the male cohort being positive compared with 87.5% in the female cohort. The data shows a statistically significant difference between genders for the presence of HDVRNA in seminal fluid and cervical swabs (OR 0.238, 95% CI= 0.02-3.01). A significant correlation was found between blood HDV RNA quantity and HDV RNA presence status in seminal fluid and cervical swab samples, indicating a potential risk of sexual HDV transmission. The R2 values for semen and cervical swab samples were 0.1095 and 0.9755, respectively.
Result of the research on Sainfoin (Onobrychis sativa L) varieties in the Great Lake region of Mongolia
Authors: Batkhishig Zogsokh , Batmunkh Lamjav
Published: May 2024

This study aimed to determine a sainfoin variety best suited to the soil and weather conditions of the Great Lake Basin region inUlaangom soum of Uvs aimag (province). We carried out studies into five varieties of sainfoin, including Peschany 1251, Tashyl 3, Novosibirsky 1284, Shortandisky 83, and Mikhailovsky-5, which were compared with each other without irrigation trial. Sainfoin has a  high resistance to cold winter conditions, high temperatures and and dry drought conditions. Sainfoin varieties growing in Mongolia are highly palatable perennial leguminous plants.  According to the result of our research, sainfoin is well acclimatized to Uvs province’s soil and weather conditions. The variety with the highest performance showing is Taskhyl 3, which was generated atthe Plant Research Center of Khakassia, a republic of Russia located in southern Siberia.
Faktor dan Dampak dari Peningkatan Urbanisasi di DKI Jakarta pada Tahun 2023
Authors: Zaera Mohammad Rayhan Putra
Published: May 2024

Adanya perpindahan atau pergeseran populasi penduduk perdesaan menuju perkotaan dengan jumlah besar atau yang biasa disebut dengan urbanisasi merupakan suatu fenomena sosial. Fenemona sosial ini juga apabila tidak mendapatkan pengelolaan yang baik akan menciptakan masalah sosial baru. Adanya urbanisasi tentu didorong oleh beberapa faktor salah satunya tidak adanya keseimbangan antara pertumbuhan ekonomi di desa dan perkotaan. Makalah ini ditulis menggunakan metode kualitatif
Peranan Manajemen Laba Sebagai Variabel Intervening terhadap Profitabilitas dan Likuiditas terhadap Nilai Perusahaan Perusahaan Asuransi Umum yang terdaftar di Bursa Efek Indonesia (2018 – 2022)
Authors: Bakar Abu
Published: May 2024

Penelitian ini memiliki tujuan untuk menganalisis pengaruh profitabilitas dan likuiditas terhadap nilai perusahaan dengan manajemen laba sebagai variabel intervening. Populasi dari penelitian ini adalah laporan keuangan perusahaan asuransi umum yang terdaftar di Bursa Efek Indonesia periode tahun 2018 – 2022. Sampel dipilih menggunakan purposive sampling yaitu perusahaan asuransi umum yang menerbitkan laporan keuangan di BEI selama periode 2018-2022 dan memiliki nilai buku positif. Data dianalisis menggunakan metode regresi dan analisa jalur (Path Analysis) dengan aplikasi SPSS. Hasil penelitian ini menunjukan bahwa profitabilitas berpengaruh terhadap manajemen laba sedangkan likuiditas tidak berpengaruh terhadap manajemen laba. Profitabilitas berpengaruh terhadap nilai perusahaan sedangkan likuiditas dan manajemen laba tidak berpengaruh terhadap nilai perusahaan. Manajemen laba sebagai variabel intervening dapat memediasi likuiditas terhadap nilai perusahaan.
Atratividade e palatabilidade de ração encapsulada de isolado pro-teico de soja, maltodextrina e goma arábica para alevinos de tilápia do Nilo (Oreochromis niloticus)
Authors: Fernandes Vanessa Lopes , Negrini Celma , Ogava Luci Emi , Piovesan Márcia Regina , Hattori Jahina Fagundes de Assis , Boscolo Wilson Rogério
Published: May 2024

O objetivo do trabalho foi avaliar a atratividade e palatabilidade de encapsulados para alevinos de tilápia do Nilo (Oreochromis niloticus). Arraçoados com quatro dietas experimentais contendo encapsulado de proteína isolada de soja, encapsulado de goma arábica, encapsulado de maltodextrina e ração controle. Doze alevinos distribuídos em 12 aquários com capacidade para 22 litros foram alimentados quatro vezes ao dia com dietas aleatórias previamente sorteadas, todos os peixes comeram todas as dietas. Foram oferecidos 30 pellets por alimentação e a filmagem com três minutos de gravação foi avaliada quanto aos seguintes parâmetros: tempo para capturar o primeiro pellet, número de rejeições, número de aproximação sem captura de pellets e número de pellets consumidos. Posteriormente, os vídeos foram avaliados e calculado o índice de atratividade e palatabilidade. Nesta pesquisa, as dietas avaliadas não apresentaram diferença estatística em relação ao índice de atratividade e palatabilidade entre os tratamentos para a espécie de tilápia do Nilo (Oreochromis niloticus). Indicando que os encapsulantes testados podem ser utilizados sem o comprometimento da aceitabilidade por parte do animal.
Análise da passagem do glóbulo vermelho humano por dois poros cilíndricos longos
Authors: Rossetto José João , Abatti Paulo José , Hu Liangzhong
Published: May 2024

Este trabalho descreve uma análise da passagem do glóbulo vermelho humano por dois poros cilíndricos longos. São deduzidas expressões relacionando a área da superfície da membrana e o volume da célula vermelha do sangue com os elementos que definem o perfil geométrico dos poros, no caso raios e comprimentos dos cilindros, no qual o glóbulo é capaz de transpor os poros. As aplicações práticas do modelo são ilustradas e apresentadas. Modelos geométricos e gráficos são elaborados indicando as condições da passagem da célula pelos poros. Deduz-se que o modelo aponta para a construção de um filtro mecânico artificial para seletividade de glóbulos vermelhos funcionando como uma micropipeta de sucção. Discutem-se também as implicações biológicas do modelo, a respeito do fenômeno de filtração dos glóbulos vermelhos na polpa vermelha do baço humano, em especial na passagem dos glóbulos pelos cordões de Billroth.
Trilhas interpretativas no parque estadual do turvo: conhecendo os elementos da natureza
Authors: Marcuzzo Suzane Bevilacqua , Jaskulski Letícia Pawoski , Zimmerman Pâmela
Published: May 2024

A interpretação ambiental é um instrumento que promove a reaproximação do ser humano com a natureza, e em Parques Naturais atua enriquecendo a experiência do visitante para que se torne memorável e incentive ações de conservação. Assim, este estudo propõe um roteiro interpretativo para a Trilha das Lagoas do Parque Estadual do Turvo, no noroeste do Rio Grande do Sul. Os pontos interpretativos foram definidos pela presença de espécies botânicas ameaçadas, de relevante interesse por sua função, ou de beleza cênica única. Assim, foi escolhido o tema “Senhoras da Floresta: sabedoria que transcende o tempo”, e determinados sete pontos interpretativos que foram interpretados de maneira lúdica, possibilitando o despertar de emoções nos visitantes.
Estratégias de comunicação alternativa e aumentativa para crianças autistas
Authors: Santos Silvana Maria Aparecida Viana , Boechat Gisela Paula Faitanin , Carmo Jonathan Porto Galdino do
Published: May 2024

Esta revisão bibliográfica abordou o desafio de melhorar a comunicação de crianças com Transtorno do Espectro Autista (TEA) através da Comunicação Alternativa e Aumentativa (CAA). O objetivo geral foi analisar a eficácia das estratégias de CAA para crianças com TEA, identificando práticas eficientes e desafios na sua implementação. Utilizou-se uma metodologia de revisão da literatura, examinando estudos de caso e pesquisas recentes para coletar dados sobre o uso da CAA em contextos educacionais e domésticos. Os resultados indicaram que a CAA oferece melhorias significativas na capacidade de comunicação das crianças com TEA, promovendo maior interação social e inclusão. No entanto, a implementação eficaz da CAA enfrenta desafios como a falta de formação específica de profissionais e resistências à adoção dessas ferramentas. As considerações finais destacaram a necessidade de treinamento profissional, personalização das ferramentas de CAA e a importância dos avanços tecnológicos para futuras intervenções.
Acoustic emission measurement during the proof loading of the new bridge over Odra river in Wrocław
Authors: Kliński Maksymilian , Panek Maciej
Published: May 2024

The acoustic emission method is applied for damage monitoring through the analysis of internal events within the material. Sensors were placed at the cantilever joint during the proof loading. Signal analysis revealed potential damages. Signal values were compared against criteria for assessing the condition of reinforced concrete structures. Regular measurements detect potential damages, and combining this technique with other methods enhances its efficiency
Calculation of prestressing force losses in precast elements interconnected with concrete topping
Authors: Krzywoń Rafał
Published: May 2024

The article presents the basics of the analysis of prestressing force losses due to common shrinkage and creep deformations of precast concrete, concrete topping and steel relaxation in a pre-tensioned concrete composite structure. The presented considerations apply to beams or slabs where the pre-tensioned unit is joined with the cast-in-place concrete topping. Due to the change in geometry, as well as various properties and rheological phenomena of the joined concretes, the formulas used to calculate time-dependent prestressing force losses must be modified. Of particular importance is the shrinkage of the concrete topping, which causes deflection and most often introduces additional tensile stresses in the area of the prestressing tendons. The proposed prediction method is an extension of the theoretical assumptions that are the basis for the principles of determining prestressing force losses presented in Eurocode 2. They allow to take into account the influence of load history on the increase in creep strains
COVID-19: LETALIDADE E FATORES ASSOCIADOS AOS ÓBITOS
Authors: Gemelli Ivanice Fernandes Barcellos , Corrêa Marcelo Tiago Balthazar , Moreira Kátia Fernanda Alves , Farias Edson dos Santos
Published: May 2024

Objetivo: Caracterizar o coeficiente de letalidade e analisar os óbitos e fatores associados durante a pandemia de COVID-19. Métodos: Estudo transversal, pacientes cadastrados na base e-SUS-VE. Foi calculado o coeficiente de letalidade e análise dos fatores associados aos óbitos por regressão logística. Resultados: Picos de óbitos ocorreram em maio/2020 e janeiro/2021, com 263 e 719, respectivamente. O coeficiente de letalidade foi maior no sexo masculino (14,19‰). Os fatores associados aos óbitos foram sexo masculino, ≥60 anos, morbidades respiratórias, renais, cromossômicas, diabetes, imunossupressão, cardiovascular, sintomas de febre, tosse, dor de garganta, dispneia e profissionais da saúde (p<0,01). Conclusão: A letalidade e o número de óbitos foram elevados. Maior chance de óbito para o sexo masculino, idade maior ou igual a 60 anos, morbidades respiratórias e cardiovasculares, além de doenças renais, cromossômicas, diabetes, imunossupressão, sintomas dor de garganta e dispneia, ainda tosse e febre e ser profissional da saúde.
Explorando la influencia de la inteligencia emocional en la educación: perspectivas y desafíos
Authors: Mora Ynedy , Oquendo Elizabeth , León Olivia , Arteaga Johana , Ortiz Lozada Elizabet
Published: May 2024

La investigación tiene por propósito: Describir la exploración de la influencia de la inteligencia emocional en la educación: perspectivas y desafíos. Los Materiales y Métodos se emplearon   un estudio de carácter cualitativo con diseño retrospectivo y de naturaleza fenomenológica.  La población estuvo conformada por treinta y cinco (35) alumnos  objeto de estudio de la  Escuela fiscomisional El Profeta Jeremías, dichos estudiantes son de  6to grado De estos, treinta y cinco (35) diecinueve (19) son hombres (54,28%) y 16 son mujeres (45,71%).  La selección de los participantes fue realizada a través de un muestreo probabilístico no intencional por conveniencia y accesibilidad al investigador hasta que se llegó a la saturación de la información. Seleccionando las respuestas de los tres (03) hembras y tres (03) varones como sujetos claves; se realizó una entrevista a informantes de sexto grado con edades comprendidas entre 12 y 14 años y de contextos socioeconómicos bajo-medio perteneciente a un centro educativo de zona urbana. Se puede concluir: Las respuestas de los sujetos (estudiantes) seleccionados de sexto (6to) grado, la inteligencia emocional es especialmente importante porque es un momento crítico en el desarrollo de las habilidades sociales y emocionales. Durante este período, los estudiantes comienzan a interactuar más intensamente con sus compañeros y a desarrollar sus propias identidades, lo que puede ser un desafío para su capacidad para gestionar las emociones y las relaciones interpersonales.