bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychological and pedagogical conditions for teaching residents of foreign language professional communication based on an integrated approach
Authors: Belyaev A. A. 
Published: July 2024

Importance. Proficiency in a professional foreign language at the present stage is one of the key requirements determining competitiveness in the labor market. The formation of professional foreign-language communicative competence of medical specialists gives them access to specialized research and journals, since most of them are published exclusively in English. However, in practice, when receiving medical education in residency, the main attention is paid to the study of natural sciences, while learning a foreign language is of secondary importance. Using an integrated approach to learning, it becomes possible to organize a more effective educational process through a comprehensive study of a subject discipline and a foreign language in a single educational space. The purpose of this work is to identify the psychological and pedagogical conditions of training residents of foreign language professional communication based on an integrated approach.Research Methods. The study was conducted using theoretical and empirical methods that allow to study and analyze scientific and methodological literature on the organization of foreign language teaching based on an integrated subject-language approach. The analysis of the literature revealed certain patterns that actualize the need to comply with a number of psychological and pedagogical conditions when teaching residents of foreign language professional communication based on an integrated approach. Based on the available research, the external and internal factors underlying the psychological and pedagogical conditions aimed at optimizing the educational process were summarized.Results and Discussion. In the course of the conducted research, the following psychological and pedagogical conditions for teaching residents of foreign language professional communication based on an integrated approach were identified: 1) motivation of residents to study professional English; 2) possession of professional foreign language competence by residents at the Advanced Mid level on the ACTFL scale; 3) formation of an integrated course of professional foreign language communicative competence and competence in the field of professional communication by the teacher; 4) the methodological dominant in the educational process are professionally oriented cases.Conclusion. The process of teaching residents of foreign language professional communication is not an axiomatic phenomenon, therefore it is directly dependent on a number of psychological and pedagogical conditions. The identified psychological and pedagogical conditions are of a recommendatory nature and act as a starting point for teaching residents of foreign language professional communication based on an integrated approach. The results of the study can be used in the methodology of teaching foreign languages to medical students and residents.
Communicative skills of a teacher-choreographer as a means of students forming emotional and aesthetic experience
Authors: Klimenko A. V. 
Published: July 2024

Importance. Changes in society entail the presentation of new requirements for the teacher as a specialist and personality. Today, teaching Internet-dependent students who require little communication is a specialized skill that demands emotionally intense communicative skills from teachers aimed at engaging them in a productive educational process. The communicative skills of the choreographer-teacher should contribute to the emotional and aesthetic experience formation of students. This experience is formed in the interaction process between a teacher and a student, subject to correction of age-related, individual socially conditioned deformations of the students’ personality. The purpose of the study is to establish the need for developing the communicative skills of a choreographer teacher as an effective way to enhance the emotional and aesthetic development of students.Research Methods. The following methods are used: analysis of psychological and pedagogical literature, systematization and comparison, generalization of the author’s experience, observation, which enabled the substantiation of the emotionally and aesthetically saturated communicative component of the teacher’s activity as a leader in the process of forming the emotional and aesthetic experience of students and a dance group. On the basis of the main provisions of the systemic, cultural, activity-centered, personality-focused approaches, the development of interrelated blocks of personality qualities and properties in the emotionally saturated communicative learning process is shown: cognitive, psychological-dynamic and morally significant.Results and Discussion. It is proved that the teacher’s communicative skill are the key to achieving high educational and outcomes through the varied methods’ use of interaction with students. These skills are essential for effectively addressing their socio-psychological and personal issues. The direct correlation between the learning process results and the teacher's competence level in emotional and aesthetic communication with students has been established. A specialized course has been designed for choreographers to enhance their emotional and aesthetic component of communicative skills, which encompasses psychological, dynamic, and moral aspects of personality development.Conclusion. Based on the results of theoretical and empirical research, the structure of an emotionally saturated, aesthetic communicative aspect of the pedagogical skill of a choreographer teacher has been developed. Success in the formation of the modern students’ emotional and aesthetic experience is achievable provided that there is a high level of communicative skills of the teacher, the formation of which is facilitated by the developed special course “Enhancing the communicative skills of a choreographer teacher”.
Erratological approach to teaching complex sentences to a foreign audience
Authors: Tskhovrebov A. S. 
Published: July 2024

Importance. Teaching foreign students of engineering and technical profile to complex specific text-forming structures of scientific style of speech is a laborious process. The identification of the causes and mechanisms of the occurrence of the errors noted in the structure of a complex sentence, their analysis (identification, elimination, correction) facilitates the process of studying these important grammatical units. The purpose of the research is to develop a new approach (erratological) to the study of a complex sentence based on error analysis. Its structural and meaningful description is proposed. Materials and methods. The study is conducted on the basis of the Military Institute (Engineering and Technical) Military Academy of Logistics named after Army General A.V. Khrulev. The research material is a corpus of “negative material” obtained as a result of an experimental study of the speech of engineering students. The corpus of violations in a complex sentence formed the basis of the approach we developed, called the “erratological approach”. This study is also based on the analysis and generalization of scientific works on erratology.Results and Discussion. An erratological approach to the study of complex structures of the scientific style of speech has been developed, including six main interrelated stages – the selection of grammatical material, the organization of grammatical material (its logical arrangement), the introduction of grammatical material (presentation in classes in the language of the specialty), training, practice, control, which allow you to form not only Russian-speaking professional competencies, but also skills for all types of speech activity.Conclusion. The use of an erratological approach, namely complex work with one’s own mistakes in the classroom, will ensure the student’s undoubted interest in learning a new language, will contribute to the intensification of the educational process, enrich it with new technologies, teaching methods, a new system of tasks, will form both linguistic and professional competence.
Table tennis as part of an elective course in physical education
Authors: Mukina E. Yu. , Ivinsky D. V. 
Published: July 2024

Importance. One of the methods to improve the level of physical education teaching is the introduction of elective disciplines. Elective disciplines allow the student to satisfy his professional interests and personal inclinations, and give the teacher the opportunity to organize the educational process most effectively.Materials and Methods. One of the issues of teaching is carrying out constant monitoring and recording of progress, the correct distribution of points for completing assignments. Continuous monitoring allows the teacher to identify shortcomings and issues that arise when teaching elective disciplines and timely adjust the educational process.Results and Discussion. Using the pedagogical principles of sports-oriented physical development, we are developed a system of criteria that allows us to effectively assess the preparation of students in the process of studying the elective discipline “Table Tennis”. The assessment system is focused on the content of educational material in the module and took into account the main areas of training such as special technical training, theoretical and methodological foundations of tennis, general physical training. The assessment of the level of students’ training in special technical training is carried out by testing the skills of performing certain technical techniques. The quality and speed of performing these techniques are translated into points. During the learning process, the set of technical techniques becomes more complex or the requirements for the speed and quality of its implementation increase.Conclusion. The presented assessment system made it possible to effectively assess the level of students’ preparation when studying the elective discipline “Table Tennis”.
MODERNIZATION OF THE ELECTRIC DRIVE OF PUMPING UNITS OF THE DISTRICT HEATING NETWORK IN THE CONTEXT OF INCREASING THEIR ENERGY EFFICIENCY
Authors: Fedirko Mykhailo , Brukhanskyi Ruslan , Brych Vasyl , Olishynska Ruslana 
Published: July 2024

Quantitative and qualitative indicators of the modernization of the electric drive of a pumping unit of a network with throttle control of the coolant supply of a centralized heat supply system are determined. The possibility of modernizing the electric drive by replacing outdated electric motors of energy efficiency class IE1, which are still used in electric drives of pumping units, with electric motors of energy efficiency classes IE2 and IE3 from different manufacturers, has been substantiated. The energy consumption was calculated based on the technical data of the pump and electric motors provided by the manufacturers and includes the calculation of the energy consumption of pumping units in a typical operating cycle typical for district heating networks, which involves operation at reduced load for a long time. Comparative calculated data on the daily and annual energy consumption of the considered electric motors in a typical operating cycle of a pumping unit, with respect to the least energy-efficient electric motor among those considered, were obtained. The practical significance of the results obtained is to understand that the selection of an electric motor by efficiency at variable load, i.e., actually on the basis of the IE energy efficiency class assigned in accordance with the IEC 60034-30-1 standard, is incorrect, It is substantiated that the choice should be made using the efficiency interpolated by the method of polynomial interpolation of the motor loss curve, while taking into account the economic feasibility of choosing an electric motor between energy efficiency classes, in this case IE2 and IE3, and different manufacturers.
Patient-Specific Functional Liver Segments based on Centerline Classification of the Hepatic and Portal Veins
Authors: d'Albenzio Gabriella , Meng Ruoyan , Aghayan Davit , Pelanis Egidijus , Sakinis Tomas , Solberg Ole Vegard , Tangen Geir Arne , Kumar Rahul P. , Elle Ole Jakob , Edwin Bjørn , Palomar Rafael 
Published: July 2024

Abstract

Couinaud’s liver segment classification has been the standard for liver surgeryplanning for nearly seven decades. However, its reliance on fixedplanar boundaries does notalways align with individual anatomical variations. This study aims to propose a new methodfor classifying liver functional segments that incorporates patient-specific liver morphology,3D vascular systems, and user-defined landmarks.
Methods. We developed an adaptable clas-sification approach that integrates individual anatomical variations. This approach involves:(1) defining landmarks on 3D models of hepatic and portal veins to compute centerlines,and (2) calculating liver segments by assigning voxel labels based on the proximity to thesecenterlines. We compared our method with conventional plane-based and portal vein-based classifications.
Results. Our method demonstrated greater adaptability by incorporatinghepatic and portal veins, including peripheral branches, and deviating from the classicalCouinaud classification. The findings show that our approach not only overcomes the limi-tations of traditional methods but also provides a more precise and surgery-ready definitionof liver segments, especially in complex cases involving segments 5 and 8.
Conclusion. Our method offers significant improvements in liver segment classification, enhancing visualiza-tion in complex cases and better assessing vascular perfusionterritories. Feedback from liversurgery specialists underscores its potential benefits for surgical planning and outcomes.
A Deep Learning Body Compositions Assessment Application with L3 CT Images: Multiple Validations
Authors: Zhang Liang , Li Jiao , Yang zhi , Yan Jun , Zhang Lin , Gong Long-bo 
Published: July 2024

Abstract

Objectives: Body composition assessment is very useful for evaluating a patient’s status in the clinic, but recognizing, labeling, and calculating the body compositions would be burdensome.This study aims to develop a web-based service that could automate calculating the areas of skeleton muscle (SM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) according to L3 computed tomography (CT) images.
Materials & Methods: 1200 L3 CT images were gathered from Xuzhou Central Hospital. Of these, 70% were used as the training dataset, while the remaining 30% were used as the validating dataset. The UNet framework was combined with attention gate, Squeeze and Excitation block (SEblock), and Atrous Spatial Pyramid Pooling (ASSP) modules to construct the segmentation deep learning model. The model's efficacy was externally validated using two other test datasets with multiple metrics, the consistency test and manual result checking. A graphic user interface was also created and deployed using the Streamlit Python package.
Results： The custom deep learning model named L3 Body Composition Segmentation Model (L3BCSM) was constructed. The model's Mean Dice is 0.932(SATA)，0.915(VATA), and 0.956(SMA), which is equal to classic models including UNETR and AHNet. L3BCSM also achieved satisfactory metrics in two external test datasets, consistent with the qualified label and resistant to the poor label. An internet-based application was developed using L3BCSM, which has four functional modules: population analysis, time series analysis, consistency analysis, and manual result checking.
Conclusion: The body composition assessment application was well developed, which would benefit the clinical practice and related research.
An AI Powered Emotion Recognition System
Authors: Hasan Faraz , Arora Lakshay , Tickoo Anshul 
Published: July 2024

Abstract

Imagine a digital world where your computer understands how you feel. This project is all about making that a reality by bringing together the magic of technology and human emotions. We're creating a special place online, a web-based platform, where your computer can see your emotions in real-time through your webcam. You can just be yourself, expressing your feelings naturally, or have a chat with our friendly interactive bot that can understand how you're feeling, whether you're actively talking or just going about your day. We're using smart computer programs, along with deep learning concepts, to look at your facial expressions and figure out if you're happy, sad, surprised, or anything in between. The project doesn't just stop there – we're taking it a step further. We want the platform to adapt to you, offering things that match your mood, be it interesting content, helpful resources, or just a comforting chat. And it's not only about your face – we're working on making the chatbot understand the emotions in your words too. We care a lot about your privacy, ensuring that you're in control and comfortable every step of the way. Your feedback is like the secret ingredient, helping us make this digital space more accurate and supportive. This project isn't just about tech; it's about making your online experience more human, touching areas like education, mental health, and customer service in a whole new way.
Efficiency-Based Housing Allocation: Leveraging DEA with CCR Model for Enhanced Decision-Making in Real Estate
Authors: GUPTA ISHIKA , . Himanshi 
Published: July 2024

Abstract

In an innovative approach to traditional house searches, this study leverages Data Envelopment Analysis (DEA) with the Charnes, Cooper and Rhodes (CCR) model. Live Housing data from a diverse pool of houses is analyzed, clustering them based on price ranges. By constructing an efficiency frontier graph, the study identifies optimal housing allocations within each cluster. This method not only refines the house search process but also quantifies the efficiency of houses, enabling a nuanced comparison. The application of DEA provides a robust framework for evaluating housing options, offering a data-driven solution to enhance decision-making in the real estate market.
Predicting Cardiovascular Disease with Machine Learning: A Comparative Analysis of Classification Models
Authors: Malhotra Diya , Saini Aarushi 
Published: July 2024

Abstract

Cardiovascular disease is a very serious health issue. So, in order to prevent its spread, we need to understand the reason behind it’s increase. Different factors like our lifestyle, our genes, the surroundings that we live in and so on all contribute to the risk of getting CVD. So, it is important to make positive changes in our day-to-day life which in the end will make us healthier. This research paper delves into understanding the importance behind such factors. We have used various classification models such as Logistic Regression, Decision Tree Algorithm, Random Forest, KNN, Support vector machine and Naïve Bayes to make predictions regarding cardiovascular disease patients. We have used data from UCI Repository that includes the features (predicator variables) such as age, BMI, gender, cholesterol, alcohol intake and so on to determine the presence of cardiovascular disease patients (response variable). Different models have been used to find out which model works best and we have done this by estimating various metrics that are essential for the assessment of model performance such as accuracy, precision, recall, etc. The Support Vector Machine model had the highest accuracy, Roc-Auc. So, this shows that the Support Vector Machine (SVM) so far is the best model for making predictions regarding CVD.
Discovery of intestinal microorganisms that affect the improvement of muscle strength
Authors: Chung Hea-Jong , Ahn Ji-Seon , Kim Hae-Mi , Han Eui-Jeong , Hong Seong-Tshool 
Published: July 2024

Abstract

This study explores a new method to investigate how gut bacteria influence the host, specifically focusing on muscle strength, independent of the host's genetic background. Fecal transplants from humans (FMT) into mice revealed a dramatic impact of gut bacteria on muscle strength, with some mice experiencing increases, no change, or decreases. Analysis of the gut bacterial communities showed distinct compositions between mice with different muscle strength outcomes. Further investigation identified two bacterial species, Lactobacillus johnsonii (L. johnsonii) and Limosilactobacillus reuteri (L. reuteri), whose abundance correlated with improved muscle strength. Supplementation with these bacteria in healthy mice confirmed their ability to enhance muscle strength. Interestingly, the bacteria appear to work by increasing the production of follistatin (FST) and insulin-like growth factor-1 (IGF1), proteins crucial for muscle growth. This study provides the first evidence that specific gut bacteria can directly improve muscle strength and introduces a novel approach to studying the gut microbiome's influence on complex traits.
Transfer learning with BERT and ClinicalBERT models for multiclass classification of radiology imaging reports
Authors: Mithun Sneha , Sherkhane Umesh B. , Jha Ashish Kumar , Shah Sneha , Purandare Nilendu C , Rangarajan V. , Dekker A. , Bermejo Inigo , Wee L. 
Published: July 2024

Abstract

This study assessed the use of pre-trained language models for classifying cancer types as lung (class1), esophageal (class2), and other cancer (class0) in radiology reports. We compared BERT, a general-purpose model, with ClinicalBERT, a clinical domain-specific model. The models were trained on radiology reports from our hospital and validated on a hold-out set from the same hospital and a public dataset (MIMIC-III). We used 4064 hospital radiology reports: 3902 for training (which were further divided into a 70:30 random train–test split) and 162 as a hold-out set. 542 reports from MIMIC-III were used for independent external validation. The ground-truth labels were generated by two expert radiologists independently. The F1 score for the classes 0, 1, and 2 on internal validation were 0.62, 0.87, and 0.90 for BERT, and 0.93, 0.97, and 0.97 for ClinicalBERT respectively. External validation F1 score for the classes 0, 1, and 2 were 0.66, 0.37, and 0.46 and for BERT, and 0.68, 0.50, and 0.64 for ClinicalBERT respectively. ClinicalBERT outperformed BERT demonstrating the benefit of domain-specific pre-training for this task. The higher accuracy for lung cancer might be due to imbalanced data with more lung cancer reports.