bluuebunny/crossref_metadata_2025 huggingface dataset:
Newcastle Disease Virus strain XIV.2 Infection in Geese and Guinea fowls: A Comparative Pathological Study
Authors: Abari John , Oladele Sunday , du Lawal , du Lawal , Orakpoghenor Ochuko , Enam Samson , Elijah John , Bilbonga Garleya , Elijah Mary , Ogala Ojonigo , Ogala Ojonigo , Sanka Jibrin
Published: April 2024

Aim: The study evaluates the pathogenic potential of strain XIV.2 NDV in geese and guinea fowls experimentally.
Methods: Forty birds, comprising 20 geese and 20 guinea fowls, aged seven weeks were randomly divided into four groups (A–D), kept in separate pens as follows: 10 Control geese, 10 Infected geese, 10 Control guinea fowls and 10 Infected guinea fowls. The birds in group B and D were inoculated with 0.2 mL of strain XIV.2 NDV inoculum (titre of 108.2/0.1 mL ELD50) intra-nasally, while those in group A and C were inoculated with phosphate buffered solution (PBS) intra-nasally respectively. Gross and histopathological procedures were performed using standard methods.
Results: Revealed transient clinical signs without mortality in infected geese whereas moderate clinical signs with mortality were observed in infected guinea fowls. Gross lesions were mild in infected geese from 6 to 28 days post-inoculation, (dpi) and in infected guinea fowls at 3, 21 and 28 dpi, with moderate lesions observed from 6, 11, 12 and 14 dpi. Histopathological lesions in infected geese were moderate from 3 to 21 dpi, but mild at 28 dpi, whereas mild lesions were observed from 3 to 6 dpi, followed by moderate lesions from 9 to 28 dpi in infected guinea fowls.
Conclusion: Morbidity and mortality due to strain XIV.2 NDV infection were moderate in guinea fowls, but inapparent and transient in geese. Therefore, free-ranging system commonly practice in the region should either be discouraged or vaccination of these species of birds should be encouraged.
Evaluation of fresh frozen plasma usage at Tezpur Medical College and Hospital: A two-year study
Authors: Talukdar Partha , Sarmah Amrit , Bhuyan Akash , Jain Priyanka
Published: April 2024

Background: Rational usage of blood components is important to ensure their availability to needy patients and to avoid unnecessary risk. Despite available guidelines, improvement in quality control, and standardization about the use of fresh frozen plasma (FFP), many studies around the world show a high frequency of its inappropriate use.

Aims and Objectives: (i) To evaluate the pattern of FFP usage in our hospital and to categorize usage as appropriate or inappropriate based on FFP transfusion guidelines. (ii) To evaluate the effectiveness of FFP transfusion based on pre- and post-transfusion international normalized ratio (INR) values by calculating P-value using a paired t-test.

Materials and Methods: This retrospective observational study was done by retrieving requisition forms of all the patients who received FFP transfusion in Tezpur Medical College, Tezpur, Assam, during the period of 2 years (November 01, 2020–October 31, 2022). Patients who received other blood products along with FFP were excluded from this study.

Results: 1420 units of FFP were supplied to 850 patients during the study period of which 64% went to males. The most common age group receiving FFP was 30–39 years (28%). The most common indication for FFP was liver disease (33%). Appropriate usage was found in 74% of episodes and inappropriate usage in 26% of episodes. Statistically significant improvement was seen in post-transfusion INR when usage was appropriate (P < 0.001).

Conclusion: The study highlighted the pattern of FFP usage in various clinical settings. Regular screening of requisition forms for proper guidelines-based indications, administrative interventions, and meetings of the hospital blood transfusion committee for education and sensitization of medical staff will go a long way in ensuring appropriate usage and good transfusion practice.
A comparative evaluation of 0.75% ropivacaine with fentanyl versus 0.75% ropivacaine with dexmedetomidine in intrathecal anesthesia for lower limb surgeries
Authors: Rajan Aneesh , Tarsis Sheen , S Mohideen , I Abunaya
Published: April 2024

Background: Anesthesia for lower limb surgeries can be administered locally, regionally (spinal or epidural), or generally. The primary option is still spinal anesthesia because of its quick onset, excellent blockage, low infection risk, low failure rate, and affordability. The most widely utilized method is bupivacaine spinal anesthesia. By extending and strengthening the sensory blockade, an adjuvant not only boosts the effectiveness of a local anesthetic but also lowers the dosage of local anesthetic drugs.

Aims and Objectives: The aims and objectives of the study are to assess the synergistic effect and safety of adding dexmedetomidine to ropivacaine 0.75% in the subarachnoid block for lower limb surgeries compared to fentanyl to ropivacaine 0.75%.

Materials and Methods: The present study was a prospective randomized control study, carried out at the Department of Anesthesiology and Critical Care, Kempegowda Institute of Medical Sciences, Bangalore, for a period of 2 years. Two groups of 30 subjects each were selected for the study by simple random sampling. Patients with physical status ASA 1 or 2 who underwent elective lower limb surgeries were included. Patients in Group F (n = 30) received 3 mL of isobaric 0.75% ropivacaine and 25 μg fentanyl (0.5 mL) and in Group D (n = 30) received 3 mL of isobaric 0.75% ropivacaine with 10 μg dexmedetomidine (0.5 mL). Sensory testing was assessed by loss of pinprick sensation. The motor block in the lower limb was graded according to the modified Bromage scale. Duration of analgesia was noted. Hemodynamic parameters were recorded every 5 min for 1st 30 min and thereafter every 30 min till the patient complained of pain. Results were analyzed using the SPSS 20.0 version and the association was tested using Student t-test and Chi-square test.

Results: The average time for sensory block onset was 2.93 ± 0.25 min in Group D and 2.43 ± 1.14 min in Group F. In both Group D and Group F, the length of the sensory block was 281.33 ± 25.15 and 144.67 ± 19.43, respectively, and was extremely significant both statistically and clinically. When compared to Group F, which had analgesia for 144.67 ± 19.43 min, Group D experienced analgesia for a significantly longer duration, 360.67 ± 16.17 min. There was a statistically significant difference (<0.001). In Group D, the average motor block duration was 339.67 ± 19.21 min, whereas in Group F, it was 92.33 ± 16.95 min.

Conclusion: When compared to fentanyl as an adjuvant to ropivacaine, intrathecal dexmedetomidine causes a faster onset of sensory and motor blockade and a longer duration of motor and sensory block, as well as hemodynamic stability, higher sedation, and a longer duration of post-operative analgesia.
A Gut Feeling: Biomedical Knowledge Graphs for Interrelating the Gut Microbiome and Mental Health
Authors:   , Liu Ting
Published: April 2024

The thesis delves into an investigation of the association between gut microbiota and mental health by constructing biomedical knowledge graphs sourced from scientific literature, including text and depicted molecular pathway graphs, and public databases, where the information is retrieved using a combination of automated and manual techniques. We provide an extensive introductory overview of the general architecture of knowledge graph construction and a ten-rule guide for applying Semantic Web technologies effectively when constructing knowledge graphs. The thesis introduces three relevant biomedical knowledge graphs: Microbiota Knowledge Graph (MiKG), Pre-/Probiotics Knowledge Graph (PPKG) and Ketamine Pathway (KetPath) Knowledge Graph. These graphs are built upon the tripartite relationship between gut microbiota, neurotransmitters, and mental disorders. Querying the integrated knowledge graphs revealed novel insights into the intricate interplay among these elements, ranging from the general level, such as potential new overall strategies for using probiotics in treating mental disorders, to the specific level, such as particular expression patterns of the bdnf gene in certain health conditions.
Instruction-Giving in EFL Classrooms: A Case of a University in Viet Nam
Authors: Dang Thi Minh Tam , Tong Thi Mai Huong
Published: April 2024

Organizing effective instruction is a characteristic of classroom management, which minimizes time wasting and keeps students moving at a good pace. The primary purpose of this study is to explore the current practice of instruction-giving strategies being utilized in EFL classrooms in a Vietnamese public university. To achieve this goal, both qualitative and quantitative methods were utilized to explore the critical characteristics of instruction-giving. Classroom observations were the primary data collection method. During 19  observations, 25 instructions were noted for analysis. The findings of this study present certain characteristics of instruction-giving, namely attention-grabbing skills, repetition, the use of mother tongue and language, demonstration, and checking understanding to support instruction delivery. Also, the study’s findings propose weaknesses that EFL teachers can take into consideration for better instruction-giving.
Malayalam Handwritten Words Recognition: A Review
Authors:   Student, Department of computer science and engineering, Universal Engineering College, Kerala, India., N S Aswin
Published: April 2024

This review examines character segmentation and offers an elegant method for identifying and transforming handwritten Malayalam words from picture documents into text. Character touchings, different writing styles, and noisy, damaged scanned photos make it difficult to recognise handwritten text. Taking use of today's world of rich data and algorithmic developments, the system uses deep convolutional neural networks (CNNs) to address these challenges. The three steps of Malayalam handwritten word recognition are segmentation, recognition, and pre-processing. Making Malayalam character datasets is the first stage, and then pre-processing to improve image quality comes next. Then, in order to maximise the system's capacity to precisely forecast Malayalam characters, a CNN model is built to extract relevant information. The last phase of the recognition process involves the system classifying the characters. This project is significant since it uses CNN filters to enhance feature recognition, which enhances the accuracy of Malayalam character prediction. Key Words: Deep Learning, Deep Convolution Neural Network (DCNN), Character recognition, Character segmentation,
Experimental Research on Concrete Strength Parameters: Glass Powder with Different Dosages Replacing Cement in M25 & M30 Concrete
Authors:   Department of Civil Engineering & Dr.K.V.Subba Reddy Institute of Technology, Kumar Ediga Anil
Published: April 2024

Waste products, agricultural waste, and other natural elements are currently the focus of scientific attention as they seek to create technologies that may be used as building raw materials. On the other hand, recycling helps build a cleaner, safer environment while also boosting the economy. The purpose of this research is to find out how much stronger concrete becomes when various glass particles are used in place of cement in M25 and M30 concrete mixes. Glass bottles and other bottles that end up in landfills are a byproduct of people's daily water use and other unsanitary practices. Land filling broken glass is an environmentally harmful and unsustainable practice since the material does not biodegrade. Glass is mostly composed of silica. The primary objective of this research is to examine the potential effects of using glass powder as a partial cement substitute in two distinct concrete grades, M25 and M30, at varying percentages (5%, 10%, 15%, 20% & 25% of the cement weight). On days 7, 14, and 28, we compared the findings to those of normal concrete by testing the strength and split tensile strength. Key Words: Cement, glass powder, natural sand, coarse aggregate, compressive strength, cracking tensile strength.
MEDI ASSIST PORTAL
Authors:   Dept of MCA-Trinity Academy of Engineering, Pune, India, Dake Divya
Published: April 2024

Service institutions are considered one of the most important institutions in our time, and they have become a great place in our lives The health institutions are considered the most important, because they provide many types of required health services and related to the safety of the health of individuals, and through cooperation between the academic study and the health sector. This research paper presented a proposal Medical assist portal system project is primarily focused on managing medical-related records within a hospital. More precisely, this system helps track medical reports. The system also shows all available employees and patients. more ever, the system can total inventory and pharmacy records, this system containing of two major sections: database structure, and GUI frames (created in PHP, HTML, and CSS). The database constructed with MYSQL and the GUI frame make it easier for novitiate users to utilize the suggested system. at the latest this paper describes a hospital system that can be used to manage and analyses hospital information related to patients, treatments, and appointments. The practical implications of this system are: It can help hospitals to manage their operations more easily by providing a centralized system for managing patient info, treat records, The system can be of assistance hospital administrators to make data-driven decisions by providing them with real-time information about hospital operations, and improve patient care by providing doctors with easy and user friendly access to patient information and treatment records, The system can be beneficial to reduce errors and improve accuracy by automating many of the manual processes involved in managing hospital information. Overall, the MH described in this paper has the ability to increase efficiency, accuracy, and quality of hospital operations, which can ultimately lead to better patient outcomes. Keywords: hospital system, pharmacy, health, patient
Mart Billing System
Authors:   J.J. Magdum College of Engineering, Jaysingpur., D. A. Nikam, Sangram
Published: April 2024

The Mart Billing System for Mega Project is a comprehensive software solution designed to streamline and automate the billing process for large-scale mart operations. In the contemporary retail landscape, efficient billing systems are indispensable for managing transactions, inventory, and customer interactions seamlessly. This project addresses the complexities of managing billing operations in mega marts by integrating advanced features and technologies. Key features of the Mart Billing System include a user-friendly interface for both cashiers and customers, robust inventory management capabilities, real-time transaction processing, and secure payment options. The system is designed to handle high volumes of transactions efficiently, ensuring minimal wait times for customers during peak hours. Moreover, the Mart Billing System incorporates advanced reporting and analytics tools, enabling mart managers to gain valuable insights into sales trends, inventory turnover rates, and customer preferences. These insights empower decision-makers to optimize pricing strategies, stock levels, and promotional campaigns for enhanced profitability and customer satisfaction.
A Comparative Study of the Experimental Investigation of different types of fibres used in Concrete
Authors:   Assistant Professor in Department of Civil Engineering  Global Group of Institutes, Amritsar, Singh Jaspinder
Published: April 2024

Different types of fibres used in concrete have received much attention in civil engineering in recent years, mainly because they improve the low tensile strength and shrinkage cracks of concrete. However, there are still many problems in the research results on different types of Fibers. For example, there is still debate about the performance-enhancing or detrimental effects of different types of fibres in concrete. There is also a dispute about the influence of the size, strength, elastic modulus and other characteristic parameters of each fibre on the properties of the substrate. Research on fibre mixing rules of hybrid fibre reinforced concrete (HFRC) is incomplete. There is controversy regarding the choice of fibres for hybrid yarns as well as the characterization of the hybrid effect. In summary, it is necessary to review, synthesize and compare current research on FRC. Based on the major research achievements on FRC in recent years, this article synthesizes and evaluates existing research in experimental research and theoretical research on different types of fibre materials, aiming to create Reference conditions for researchers in the same field. Finally, combined with research experience in related fields, new perspectives and proposals on FRC's research are proposed for research and application. This research paper is mainly focus on the different fibres (glass, cotton, steel). KEYWORDS:- GLASS FIBRE, COTTON FIBRE, STEEL FIBRE, TENSILE STRENGTH, COMPRESSIVE STRENGTH,
RF based Automatic Traffic Route Clearance System for Emergency Vehicle
Authors:   UG Students, Department of Electronics & Communication Engineering, Sai Rajeswari Institute of Technology, Proddatur, Andhra Pradhesh – 516360, L Mrs. Gayathri,
Published: April 2024

Traditional time-based traffic management systems are often inadequate for addressing the complexities of modern urban traffic, resulting in delays for emergency service vehicles such as ambulances and fire services. This project proposes a wireless communication-based approach to alleviate ambulance congestion in urban areas, presenting an innovative traffic clearance system that is easily deployable and cost-effective. Keywords— Arduino, ESP 32 Microcontroller, Solar panel ,GPS,RFID Sensor.
Design of Three Elements Lotus Leaf Shape Wideband Antenna for Wireless Communication Applications
Authors:   Assistant Professor, Dept of ECE, Krishna University College of Engg & Tech, Machilipatnam, AP, India, K Rojamani
Published: April 2024

The work presents a three-elements lotus leaf-shaped wideband antenna (BIMS) designed for wireless communication applications. The antenna's size is reduced without compromising performance. The BIMS uses bio-inspired shapes like leaves, trees, animals, or insects as preference. The antenna is simulated using fiberglass laminate (FR4) as a substrate, offering maximum gain and occupying less area compared to conventional patch antennas. The work demonstrates the potential of BIMS in reducing antenna size without compromising performance. Key Words: BIMS (Bio-inspired Micro Strip), Antenna, Size, Shape, Work
Arduino Based Pickup and Drop Robot
Authors:   Final Year, Department of Electronics and Telecommunication,  Priyadarshini  College Of Engineering, Nagpur., O.G. Prof.Hastak,
Published: April 2024

A robotic arm is designed using Arduino to pick and place the objects via user commands. It will pick and place an object from source to destination safely. The soft catching gripper used in the arm will not apply any extra pressure on the objects. The robot is controlled using android based smartphones through Bluetooth. Based on the commands given by the user the robot moves accordingly. At the receiver end there are four motors interfaced with the micro controller. Two for the vehicle movement and the remaining two are for arm and gripper movement. Blue control application is used for the controlling of robot Keywords: Six Axis, Bluetooth Module, Micro-controller, Stepper Motor.
Object Detection and Recognition Using Image Processing
Authors:   Dept. Of MCA, Trinity Academy of Engineering, Pune, India, Kalshetti Mallinath
Published: April 2024

Object detection and recognition are critical problems in computer vision, with numerous applications in areas such as surveillance, autonomous systems, and medical imaging. This study provides a comprehensive overview of object detection and recognition utilizing image processing methods. Object detection is the process of finding and locating objects inside picture or video frames. Traditional approaches were based on handcrafted features and classifiers, but recent advancements in deep learning, particularly Convolutional Neural Networks (CNNs), have changed the discipline. Architectures such as You Only Look Once (YOLO), Single Shot MultiBox Detector (SSD), and Region-based CNNs (R-CNNs) have transformed real-time object identification by processing images rapidly while maintaining high accuracy. These models use anchor boxes and pyramid networks to recognize objects at various scales and aspect ratios.
Real-Time Multimodal Emotion Recognition
Authors: Bhargavi, Mrs.S.
Published: April 2024

Safeguarding the well-being of women and children presents a challenging research endeavor. Multimodal emotion recognition poses a formidable task within this domain. The field of Human-Computer Interaction (HCI) heavily relies on multimodal data, encompassing audio, video, text, facial expressions, body motions, bio-signals, and physiological data, to predict the safety of women and children. Substantial research efforts have been dedicated to this cause. To develop an optimal multimodal model for emotion recognition, which integrates visual, textual, auditory, and video modalities, a novel deep learning framework is proposed. This framework involves a comprehensive analysis of data, feature extraction, and model-level fusion. Innovative feature extractor networks are tailored specifically for processing visual, textual, auditory, and video data. At the model level, an effective multimodal emotion recognition model is devised, synthesizing information from images, text, voice, and video. The proposed models exhibit impressive performance on three benchmark multimodal datasets, namely IEMOCAP, Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), and Surrey Audio-Visual Expressed Emotion (SAVEE), achieving high predicted accuracies of 96%, 97%, and 97%, respectively. Comparative analysis with existing emotion recognition models further validates the efficacy and optimality of the proposed approach. The application of multimodal enhanced emotion recognition holds promise in predicting women and children's safety. Index Terms: Facial Expression Recognition, Deep Learning, Multimodal, Women's Safety, Audio-Visual Media, Fusion.
Sentiment analysis of the awareness of environmental sustainability
Authors: Kularbphettong Kunyanuth , Roonrakwit Pattarapan , Boonseng Chongrag
Published: April 2024

This study examines the sentiment analysis of awareness of environmental sustainability. Environmental sustainability is the responsible management and utilization of Earth's natural resources to meet the needs of the present generation and ensure that future generations will access those resources. The awareness of environmental sustainability has been growing globally as people, businesses, and governments recognize the importance of preserving the planet for current and future generations. Sentiment analysis of environmental sustainability involves evaluating opinions, attitudes, and emotions expressed in texts related to environmental sustainability, and analyzing sentiment can provide insights into public perception, awareness, and engagement with environmental issues. This exploratory study's primary goal is to conduct social media opinion mining in the context of Thai people's environmental sustainability. The paper presented how to build a model of sentiment analysis with linguistic analysis, including data preprocessing steps, feature extraction, and model constructions. The techniques used in this research include Logistic Regression, Random Forests, Support Vector Machine, Word Segmentation and Bag of Words. The result shows that the model is able to categorize sentiment analysis opinions in the sustainability context primarily in positive terms. The positive sentiments suggest a sustained, long-term shift in awareness, or they might be influenced by specific events or trends. However, positive sentiment analysis results are expressed towards environmental sustainability initiatives, such as renewable energy projects, waste reduction efforts, or conservation programs. Moreover, public awareness plays a crucial role in influencing individual behavior, corporate practices, and government policies towards a more sustainable and environmentally conscious future.
Bridging knowledge divides: Examining the dynamic landscape of ICT integration in Pakistan’s education sector
Authors: Sain Zohaib Hassan , Lama Alma Vorfi
Published: April 2024

This study delves into information technology's (ICT) effects on educational curriculum development, specifically focusing on the Pakistani context. The effects of information and communication technology (ICT) on various nations’ educational curricula are global. Integrating ICT into the academic sector is crucial to advancing educational planning in today's technology-driven era. The research aims to scrutinize the utilization and influence of ICT in Pakistan's educational landscape. A straightforward sampling procedure systematically gathered data from 385 Lahore city respondents spanning five public universities. The outcomes elucidate a substantial positive correlation between the availability and utilization of ICT and the enhancement of students' knowledge and learning skills. The study accentuates the pivotal role of ICT in amplifying educational efficiency and underscores its significance in shaping policies within the education sector. The ramifications of the research extend to educators, policymakers, and stakeholders, emphasizing the imperative need to integrate ICT into educational practices to achieve optimal outcomes effectively. By acknowledging the affirmative impact of ICT on academic development, this study contributes valuable insights that can guide strategies for elevating educational quality and planning in the digital age, ensuring a more robust and technology-enabled educational system. This suggests that integrating ICT positively impacts educational effectiveness and is essential for informing policies within the education sector.
Online teaching of radiation protection to health professionals: Lessons learned
Authors: Alcaraz-Banos Miguel , Cobo-Najar Manuel , Achel Daniel Gyingiri , Garcia-Gamuz Jose Antonio , Olivares-Rueda Amparo
Published: April 2024

The study examines the online teaching of radiation protection to health professionals. Training in Radiological Protection is considered a basic requirement for radiology professionals and students in Health Sciences. Over the past 22 years, various educational materials, including videos and teaching resources, have been produced following the Guidelines on education and training in radiological protection for medical exposures of the European Commission. These materials have been utilized in various online learning modalities. The objective of this work is to assess the impact of this study on student training. To achieve this, different data collection processes have been carried out, according to the period, and have been analyzed. The results of this training have been analyzed through diverse methods, demonstrating adequate acquisition of basic theoretical contents and a positive acceptance of this methodology by the 6,518 students examined. However, the need to create original specialized materials and resources, the increase in the teacher's workload, and the lack of institutional recognition of the teacher's effort limit its development. On the other hand, it can also be concluded that the acquisition of practical skills by the student is a weakness of the online learning system that requires the incorporation of the teacher in a face-to-face or traditional manner in the delivery of these specialized practical contents. This study allows for a better utilization of the available tools in the training of students in this subject.
Assessment of Employee Well-Being on Organisational Effectiveness & Productivity: A Literature Review
Authors: Murphy Kendra A.
Published: April 2024

This paper examines the various and complex aspects of employee well-being, including global and individual perspectives. The study examines the pivotal role of leadership, organizational culture, job satisfaction, job quality, age and gender dynamics, and family-friendly practices in shaping employee well-being. Through a synthesis of existing research, key findings emerge, highlighting the significance of engaged leadership in promoting employee performance and well-being. Additionally, the impact of organizational justice and supportive work environments on employee perceptions of fairness and well-being is discussed. Furthermore, the relationship between job satisfaction, job quality, and employee well-being is explored, emphasizing the importance of addressing diverse employee needs. The study also delves into age and gender differences in well-being, as well as the influence of family-friendly practices on reducing work-life conflict. Overall, this literature review provides valuable insights for organizations seeking to prioritize employee well-being as a strategic imperative in today's dynamic business landscape, ultimately contributing to enhanced organizational performance and success.
Implementation of FPGA-based Accelerator for Convolutional Neural Networks
Authors: Siddiqui Abdullah Farhan , Naik Prof. B. Rajendra
Published: April 2024

This research paper presents a novel FPGA-based accelerator tailored for Convolutional Neural Networks (CNNs), specifically implemented on the Virtex-7 evaluation kit. By harnessing the inherent parallel processing capabilities of FPGAs, the architecture of the accelerator is meticulously crafted using Verilog. The FPGA implementation demonstrates a resource-efficient design, making use of 588 Look-Up Tables (LUTs) and 353 Flip Flops. Notably, the efficient utilization of these resources signifies a careful balance between computational efficiency and the available FPGA resources. This research significantly contributes to the field of hardware acceleration for CNNs by offering an optimized solution for high-performance deep learning applications. The presented architecture serves as a promising foundation for future advancements in FPGA-based accelerators, providing valuable insights for researchers and engineers working in the domain of hardware optimization for Convolutional Neural Networks.
Enhancing Medical Data Analysis with Federated Learning in the Internet of Medical Things
Authors: Kjwan Alyaa Ali Hameed , Mohammad Omar Hasan
Published: April 2024

The Internet of Things refers to physical items, which are equipped with software, sensors, computing power, and other technologies, and that communicate with other electronic devices and systems over communication networks or the Internet. A collection of medical devices and software programmes known as the Internet of Medical Things (IoMT) link to healthcare networks via internet computing. Machine-to-machine communication, which is the foundation of IoMT, is made feasible by medical equipment that includes Wi-Fi. IoMT devices have the ability to analyse and store collected data by connecting to cloud services. IoMT is a different moniker for IoT in healthcare. Since data is transferred via the internet and the IoMT creates a lot of data, privacy concerns are important. The vast volume of data produced by IoMT devices calls for big data processing, and federated learning tackles privacy issues as a way to overcome these difficulties. The big data health care framework for IoMT is discussed in this article. It is built on federated learning.
Symptom-Based Disease Prediction: A Machine Learning Approach
Authors: Sirigineedi Manikanta , Kumar Matta Eswar Surya Manikanta , Prakash Rali Surya , Reddy Velagala Pavan Kumar , Tirunagari Poojitha
Published: April 2024

The advent of machine learning techniques has revolutionized various sectors, including healthcare. This project concentrates on leveraging machine learning algorithms for disease prediction based on symptoms. With a dataset comprising 132 symptoms and 41 diseases, the aim is to develop a robust predictive model capable of accurately diagnosing diseases given a set of symptoms. The process involves several key steps. Initially, the dataset is preprocessed to handle missing values, encode categorical variables, and normalize the data. To determine which symptoms are most pertinent to the prognosis of a disease, feature selection techniques are utilized. Various machine learning algorithms, including decision trees, support vector machines, random forests, and XGBoost, were explored to determine the most effective prediction model. XGBoost, in particular, emerges as one of the topperforming models because of its capacity to manage complicated relationships within the data and its effectiveness in handling imbalanced datasets. To evaluate the models' performance, evaluation criteria like accuracy, precision, recall, and F1-score are used. Moreover, to enhance model performance and avoid overfitting, techniques like crossvalidation and hyperparameter tuning are utilized. The proposed system holds significant potential in aiding healthcare professionals in diagnosing diseases promptly and accurately, thereby improving patient outcomes and reducing healthcare costs. It is important to note that the model needs further validation on diverse datasets and regular updates to remain relevant in clinical settings.
Tik Tok Ban in Nepal: Reactions of the public
Authors: Lamichhane Sonika
Published: April 2024

TikTok was the most popular social media app in Nepal and a major source of income for content creators, artists, influencers, and users. The government of Nepal made the decision to ban TikTok on November 13, 2023, stating it was disrupting social harmony in the country, which brought anger to the TikTok users. This research critically considers how the TikTok ban has been met with reactions from the public. This qualitative content analysis approach will look for a deep exploration of the emotional, professional, and creative dimensions of public experiences. Hence, the study’s main finding is to shed light on how the TikTok ban has affected the public and to know their opinions on it. In conclusion, the findings of this study shed light on the consequences of the TikTok ban in Nepal and people’s reactions to it, emphasizing the need to find a solution and to make strict rules and regulations for social media.
Identifying the technical and tactical characteristics of Olympic medallists in karate
Authors: Seyedi Reza , Tabben Montassar , Augustovicova Dusana , Laird Peter , Zhang Dacho , Feng Ren Xiao
Published: April 2024

This study primarily aimed to conduct an observational analysis of Olympic finalists’ performance to determine the patterns and characteristics of karate at the highest level of competition. Due to the need for a complete analytical system, we can use this study to create useful information about the planning process based on winning strategies. The research is based on an analysis of athletes who go to the final of the Tokyo Olympic Games. Thirty fights in the male competition were analysed. Prevalence, percentage frequency, and nonparametric tests were used (Fisher’s exact test, the likelihood ratio test, and Pearson’s chi-square test) for data analysis. Quantity indicators showed that male karate athletes tend to use upper limb karate techniques (53.70%) more than lower limb (35.65%) and a combination (upper and lower or lower and upper limb 10.65%). The difference in scoring by two tactical models of attack and counterattack was significant, and 69.2% of the points were scored by attacking. Moreover, the results suggest a predominant scoring technique using the Kisami-Tsuki model has the highest number of attacks. Considering these characteristics can provide important indicators for technical and tactical coaches and physical trainers to design special training conditions for their athletes.
Aspectos gerais e principais agentes biológicos envolvidos em surtos de doenças veiculadas por alimentos (DVA´s): uma revisão
Authors: Silva Juliana Bernardo da , Silva Anna Giselle Cavalcanti Vaz Mendes , Oliveira Neto José Atanásio de , Barbosa Iago Carvalho , Imazaki Pedro Henrique , Soares Anísio Francisco , Medeiros Elizabeth Sampaio de
Published: April 2024

Este estudo consistiu numa revisão breve para caracterizar o panorama epidemiológico dos surtos de doenças veiculadas por alimentos no Brasil, entre 2019 e 2024. Dos 52 artigos científicos examinados, apenas três foram considerados relevantes, com dois reportando dados de períodos anteriores ao foco da investigação. Os resultados destacam o norovírus e Toxoplasma gondii como principais agentes etiológicos recorrentes em surtos de doenças de transmissão hídrica e alimentar (DTHA), associados principalmente ao consumo de picolés, hortaliças, queijos artesanais e água. Esses achados sublinham a necessidade de aprimorar as práticas de manipulação de alimentos e vigilância sanitária. As políticas públicas, incluindo a Instrução Normativa do Ministério da Agricultura, Pecuária e Abastecimento e as Resoluções da Diretoria Colegiada da ANVISA, são essenciais para prevenção e controle de DTHA, juntamente com a fiscalização efetiva e a adoção de boas práticas de fabricação. Este estudo ressalta a importância do comprometimento de todos os atores da cadeia produtiva para garantir a segurança dos alimentos.
Sistemas de produção compatíveis com projetos de desenvolvimento sustentável: ideias e reflexões a partir do PDS Porto Seguro, Marabá, PA
Authors: Barros Ariel Medrado , Rosal Louise Fereira
Published: April 2024

Este trabalho buscou compreender, a partir de um estudo de caso no Projeto de Desenvolvimento Sustentável Porto Seguro, em Marabá, PA, sistemas de produção possíveis para essa modalidade de assentamento. Para isto, foram utilizadas as seguintes metodologias: caminhada transversal, construção de mapa falado e entrevista com formulário semiestruturado. A descrição dos dados aborda os processos produtivos existentes no PDS, como extrativismo, quintais florestais, cultivos de ciclo curto e criação de animais de pequeno porte, e possíveis sistemas produtivos que podem ser mais explorados no território, como meliponicultora, olericultura e piscicultura. Concluiu-se que a modalidade de assentamento rural do INCRA, denominada PDS, é uma alternativa para a implantação de novos assentamentos sob uma lógica mais sustentável na região, apesar das contradições e dificuldades na execução do projeto, pois ainda persiste no território algum grau de degradação e supressão vegetal, apresentado no trabalho a partir de mapas temporais de uso e ocupação do solo. Entretanto, o caráter experimental da modalidade na região, uma vez que nenhum dos moradores tinha experiência prévia de viver, produzir e conviver em um PDS, deve ser considerado, pois tem sido um aprendizado coletivo contínuo, que precisa ser cada vez mais estimulado por meio de rodas de conversa e trocas de experiências entre os membros do território.
''Socialismo do século XXI'' na américa latina países: principais desafios e perspectivas
Authors: Costa Otávio Barduzzi Rodrigues da
Published: April 2024

Nos últimos anos, afetado pelo sistema político, ambiente político, política, economia e a condição ambiental externa, o “Socialismo do século XXI" na América Latina enfrenta uma série de desafios severos, as mudanças drásticas da situação mundial pressionaram a América Latina regiões, as forças políticas e sociais na América Latina mudaram significativamente. A pressão dominante do partido governante de esquerda aumenta, a prática do "socialismo do século 21" na Venezuela e outros países enfrentam muitas dificuldades, seu futuro é incerto. Este artigo pretende analisar, através da análise bibliográfica a situação do socialismo latino americano.
A concepção de sujeito em Bakhtin e Vygotsky: a linguagem como mediadora do processo de constituição dos sujeitos
Authors: Schwartz Cleonara Maria , Jesus Miriani Azevedo de
Published: April 2024

O presente artigo tem como proposição, abordar a concepção de sujeito em Bakhtin e Vygotsky, destacando a linguagem como mediadora do processo de constituição dos sujeitos.  Apresenta aspectos de proximidade e convergência no pensamento desses estudiosos, centrando-se em nosso objeto de estudo. A partir de pesquisa bibliográfica, desenvolve os estudos propostos tecendo elos na corrente discursiva e dialogando com os aportes teóricos, dentre os quais destacam-se: Bakhtin (2011), Vygotsky (2000, 2009), Volóchinov (2018), Faraco (2009), Fiorin (2020), dentre outros.
Boardroom integrity and the crusade against fraud: Navigating corporate governance in Indonesia
Authors: Juhandi Nendi
Published: April 2024

This study delves into the intricate landscape of corporate governance within Indonesian corporations, scrutinizing its efficacy in deterring financial statement fraud. By amalgamating insights from a systematic literature review, quantitative analyses of secondary data, and logistic regression methods, the research elucidates the multifaceted interplay between various governance mechanisms and the persistence of fraudulent activities. Central to our findings is the pivotal role of board size in enhancing corporate oversight and mitigating fraud, juxtaposed against the ambiguous impacts of other governance elements such as audit committee effectiveness and board experience. This complexity underscores the paramount importance of ethical leadership and the "tone at the top" in fostering a corporate culture steeped in integrity, which is instrumental in fraud prevention. The paper posits that the dual focus on strengthening structural governance frameworks and nurturing ethical corporate leadership is essential for safeguarding Indonesia's economic integrity and promoting sustainable development. Through this lens, the study not only contributes to the academic discourse on corporate governance but also offers actionable insights for policymakers, corporate leaders, and regulatory bodies striving to combat corporate fraud in Indonesia.
The impact of digital currencies on traditional banking systems: An analysis
Authors: Ahmad Syarif
Published: April 2024

In the wake of the digital revolution, the financial landscape has seen the emergence of digital currencies as potent tools that promise to redefine traditional banking systems. This paper delves into the myriad ways through which digital currencies influence the operational, regulatory, and competitive arenas of traditional banks. By integrating empirical data analysis with an exhaustive review of current scholarly and industry literature, we uncover the nuanced dynamics between digital currencies and traditional banking institutions. Our investigation reveals that while digital currencies offer unparalleled efficiencies and opportunities for financial innovation, they simultaneously challenge the existing regulatory frameworks and pose risks to the stability and security of traditional financial systems. The outcomes of this research not only shed light on the immediate effects of digital currencies but also pave the way for future inquiries into their long-term implications on the global financial ecosystem.
The effect of preanalytical phase on the stability of the osmotic fragility and morphological changes in erythrocytes in cattle (Bos taurus)
Authors: Antos Piotr , Machura Marta
Published: April 2024

Hereditary spherocytosis in cattle is a disorder that results from a nonsense mutation in SLC4A1 gene that encodes band 3 membrane protein. This membranopathy leads to a production of spherically-shaped RBCs with reduced deformability and shorter lifespan in circulation. The laboratory diagnosis of hereditary spherocytosis commonly rely on erytrocyte osmotic fragility test (OFT), which is time and work consuming and can be influenced by the preanalytical factors. The aim of the study was to determine the effect of the preanalytical phase on the stability of the osmotic fragility and morphological changes of bovine erythrocytes. The blood was collected from the tail vein from Holstein-Friesian cows (n = 20) into tubes with EDTA or lithium heparin. The erythrocyte resistance to hemolysis was measured by osmotic fragility test immediately after blood collection and 24, 48 and 72 hours after storage at 4oC or room temperature. The thin blood smears were also prepared, stained and examined for cell morphology.The results showed that bovine erythrocyte osmotic fragility remains stable during 24 hours storage at 4oC regardless of the anticoagulant used. It suggests the possibility of performing OFT the day after blood collection when storing blood at 4oC. It was also found that bovine erythrocytes stored at room temperature have reduced osmotic resistance. However, heparin better preserves osmotic resistance of bovine erythrocytes at room temperature. Erythrocytes that are stored undergo changes during the storage period. The microscopic examination of cell morphology revealed the transformation of bovine discocytes into different stages of echinocytes, which rapidly occurs during the first three days of storage.
Evasão escolar no contexto de uma pandemia - Um estudo de caso no Ensino Médio
Authors: Naves Laura Helena , Ferreira Maria Divina da Cunha , Santos José Leonardo Diniz de Melo , Vieira Maurício Aires , Oliveira Ericka Anulina Cunha de , Reis Geancarla Sousa , Silva Camila Vieira da
Published: April 2024

O presente capítulo reflete sobre o impacto da pandemia de Covid-19 na evasão escolar lançando luz sobre uma questão de extrema relevância para a educação e a sociedade como um todo. A educação, como processo formativo e emancipatório, enfrenta desafios diversos, especialmente em tempos de crise como a que vivenciamos. Durante a pandemia, a escola se viu obrigada a se reinventar, buscando alternativas para garantir a continuidade do processo educacional e evitar o abandono dos estudantes. A evasão escolar representa um entrave significativo para o pleno desenvolvimento dos indivíduos e para a construção de uma sociedade mais justa e igualitária. Por isso, compreender os fatores que influenciam esse fenômeno é fundamental para implementar políticas educacionais mais eficazes e inclusivas. No contexto do estudo realizado no Colégio Estadual Dona Iayá, foi possível constatar que, mesmo diante dos desafios impostos pela pandemia, os esforços conjuntos dos gestores, professores e alunos resultaram em índices reduzidos de evasão escolar. A implementação de projetos pedagógicos adaptados à realidade remota, com aulas gravadas e em tempo real, demonstrou-se uma estratégia eficaz para manter o interesse dos alunos e garantir sua permanência nos estudos. Além disso, a análise dos dados revelou que o suporte oferecido pela escola, como o fornecimento de kits alimentares e o acompanhamento pedagógico constante, desempenhou um papel crucial na mitigação dos efeitos da pandemia sobre a evasão escolar. Esse resultado evidencia a importância de uma abordagem holística e integrada para enfrentar os desafios educacionais em tempos de crise. Portanto, os resultados obtidos neste estudo não apenas fornecem insights valiosos para a compreensão do fenômeno da evasão escolar, mas também apontam para a necessidade de investimentos contínuos em políticas e práticas educacionais que promovam a equidade, a inclusão e o pleno desenvolvimento dos estudantes, mesmo em contextos adversos como o da pandemia de Covid-19.