Auxiliary Tools Research Articles

ANÁLISE DA RESPONSABILIDADE CIVIL ACERCA DE COBRANÇAS INDEVIDAS NAS RELAÇÕES DE CONSUMO

The article has social and academic relevance, as it proposes a perspective of discussion about Law, as a normative science, which seeks and generates effectiveness in social pacification. The attainment of social peace depends primarily on the disincentive provided to individuals who do not exercise self-protection in exchange for those who can potentially cause them harm. In this sense, the research aims to analyze the civil liability regarding undue charges in daily consumer relations, in addition to demonstrating how the jurisprudence, in attention to the State of Amazonas, has positioned itself in relation to the theme, seeking to identify the main causes that may give rise to the charges, as well as to demonstrate the methods and auxiliary tools so that solutions can be found in order to inhibit and reduce the damage caused Consumers. The stage of development of scientific knowledge on the subject is under the aspect of seeking the identification of the best response of the State to the analysis of civil liability arising from accidents in consumer relations. In this case, the main line applied will be to analyze the role of jurisprudence and pondering its limitations and ensuring efficiency in the solutions. Therefore, the research method used will be through the study of legislation, bibliography and doctrine for a better range of results.

The effect of special exercises using some auxiliary tools to develop some bio-kinetic abilities and the accuracy of the crushing and snatch forehand strikes among badminton players

The best means and ways to develop an athlete's physical and skill capabilities, and among these means is the use of training aids that help develop some bio-kinetic abilities, and prepared exercises have had an important role in improving athletic performance in badminton, where the player must possess physical fitness, explosive power, and strength. Characterized by speed as well as accuracy, awareness, and focus while playing on the court, the badminton player must be physically fit through a continuous movement of small and large muscles to achieve good performance, which requires special physical abilities and skills, and the most important of these bio-kinetic abilities are agility, coordination, and measuring the coordination between the eye and the arm. These abilities are needed by the badminton player while playing on the court. The study aimed to prepare special exercises using some auxiliary tools to develop some bio-kinetic abilities and the accuracy of the crushing and lightning forehand strikes among badminton players, in addition to identifying the effect of special exercises using some auxiliary tools on For badminton players, the researcher adopted the experimental method, and the sample number was (10) players from the badminton training center in the Armenian club, aged (17-19). They were distributed into two experimental and control groups, and they were chosen randomly because the research objectives require the use of athletes proficient in the game's technical performance. The researcher applied her main experiment using special exercises with some auxiliary tools, with (4) training units per week for (8) weeks. The results of the study showed that there was a positive effect on the results of bio-kinetic abilities between the two groups and in favor of the experimental group. It was shown in the kinetic response speed test for the first experimental group 7.423, agility 3.012, and compatibility 3.123, and for the second experimental group in the kinetic response speed test 3.208, agility 6.861, and compatibility 6.907. As for the skill tests for the first experimental group, The front smash hit was 7,234 and the diagonal front snap shot was 28.00. It was shown in the skill tests for the second experimental group that the front smash hit was 3,372 and the diagonal front snap shot was 3,400, which included exercises. The researcher recommends adopting the results of this study and disseminating them, and emphasizing equipping the stadiums with modern training methods, due to the results they achieve. Positive physical development serves one of the goals of sustainable development: good health and good education.

Successful strategies for preventing and controlling violence against people with intellectual disabilities: a scoping review

BackgroundViolence against people with intellectual disabilities is unfortunately a reality all over the world, as they are one of the populations most vulnerable to various forms of aggression. Assertive prevention and control measures are crucial to tackle and reduce this problem. The aim of this study was to map and summarize the main measures for preventing and controlling domestic violence against people with intellectual disabilities. MethodsThis was a scoping review conducted in accordance with the JBI guidelines. The databases consulted were: National Library of Medicine (PubMed); Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science; Excerpta Medica DataBASE (EMBASE); Latin American and Caribbean Health Sciences Literature (LILACS) and SCOPUS. Studies included in this review reported on strategies to address domestic violence against people with intellectual disabilities, published in the last ten years, in Portuguese, Spanish or English.ResultsA total of 11 studies were included in this review. Six studies had high methodological quality and five had moderate. Cognitive-behavioral intervention programs, educational technologies and/or auxiliary tools, along with the full participation of people with intellectual disabilities in domestic violence prevention measures are appropriate strategies for dealing with this issue.ConclusionDomestic violence against people with intellectual disabilities is relatively unexplored in the health-field scientific literature. Prevention and control measures should be developed with the active involvement of people with intellectual disabilities, generating engagement and knowledge. Preventive measures should be adapted to the personal context and conditions of individuals with special needs, such as those with persistent or chronic mental disorders.

Application of Participatory Ergonomic Method to Reduce Musculoskeletal Disorders With Rapid Whole Body Assessment (REBA) at PT. Adyawinsa Stamping Industries

PT. Adyawinsa Stamping Industry is one of the automotive companies in Karawang, West Java. In the production process, most of the work has poor posture, which can cause VascularDisorders (MSDs). In the process of eliminating and reducing the risk of MSDs in the workplace, the level of MSD risk experienced by workers is calculated using the REBA method. The results of the REBA calculation obtained several activities with values above 9 (meaning that an improvement is needed). To improve the work system using the Participatory ergonomic (PE) method involving the operator, management and ergonomics. The results of the application of PE in helping to reduce the risk level of MSDs are engineering (making auxiliary tools and also management engineering) that can improve the work posture used, namely using the REBA method. Based on the results of the REBA calculation after the improvement, the risk generated is a risk level smaller than the previous posture, namely medium and low. Real improvements are hoped to create a safe, comfortable, and productive workplace.

РАЗРАБОТКА ВИРТУАЛЬНОЙ ЛАБОРАТОРИИ «ОСНОВЫ АЛГОРИТМИЗАЦИИ И ПРОГРАММИРОВАНИЯ»

The article discusses the experience of developing a virtual laboratory for algorithmization and programming based on the resources of a higher educational institution. This interactive platform provides convenient interaction between students and teachers, helps to improve the programming skills of its users and allows teachers to effectively manage the learning process within the framework of the courses they have created. The relevance of this work is due to the need to use auxiliary tools in the educational process in full-time or distance learning. The main stages of the program development are described, in particular, a comparative analysis of existing solutions is performed, the roles of users and their tasks are considered, and the main functional characteristics of the developed application are listed. The general algorithm of the application functioning is described.

Routine blood parameters as auxiliary diagnostic tools for Mycoplasma pneumoniae infection in children.

Introduction. Recently, the incidence of Mycoplasma pneumoniae (M. pneumoniae) infection in children has been increasing annually. Early differential diagnosis of M. pneumoniae infection can not only avoid the abuse of antibiotics, but also is essential for early treatment and reduction of transmission.Gap statement. The change of routine blood parameters may have important clinical significance for the diagnosis of M. pneumoniae infection, but it has not been reported so far.Aim. This study aims to establish a predictive model for M. pneumoniae infection and explore the changes and clinical value of routine blood parameters in children with M. pneumoniae infection, serving as auxiliary indicators for the diagnosis and differentiation of clinical M. pneumoniae infection.Methodology. A total of 770 paediatric patients with respiratory tract infections were enrolled in this study, including 360 in the M. pneumoniae group, 40 in the SARS-CoV-2 group, 200 in the influenza A virus group, and 170 in the control group. The differences of routine blood parameters among all groups were compared, and risk factors were analysed using multivariate logistics analysis, and the diagnostic efficacy of differential indicators using ROC curves.Results. This study revealed that Mono% (OR: 3.411; 95% CI: 1.638-7.102; P=0.001) was independent risk factor associated with M. pneumoniae infection, and Mono% (AUC=0.786, the optimal cutoff at 7.8%) had a good discriminative ability between patients with M. pneumoniae infection and healthy individuals. Additionally, Mono% (OR: 0.424; 95% CI: 0.231-0.781; P=0.006) and Lymp% (OR: 0.430; 95% CI: 0.246-0.753; P=0.003) were independent risk factors for distinguishing M. pneumoniae infection from influenza A virus infection, and the Lymp% (AUC=0.786, the optimal cutoff at 22.1%) and Net% (AUC=0.761, the optimal cutoff at 65.2%) had good discriminative abilities between M. pneumoniae infection and influenza A infection. Furthermore, platelet distribution width (OR: 0.680; 95% CI: 0.538-0.858; P=0.001) was independent risk factor for distinguishing M. pneumoniae infection from SARS-CoV-2 infection. Meanwhile, the ROC curve demonstrated that PDW (AUC=0.786, the optimal cutoff at 15%) has a good ability to differentiate between M. pneumoniae infection and SARS-CoV-2 infection.Conclusion. This study demonstrates that routine blood parameters can be used as auxiliary diagnostic indicators for M. pneumoniae infection and provide reference for the diagnosis and differentiation of clinical M. pneumoniae infection.

Analyzing parametric influences driving age-associated changes in absorption using a PBPK-GSA approach

The advanced age population may be susceptible to an increased risk of adverse effects due to increased drug exposure after oral dosing. Factors such as high-interindividual variability and lack of data has led to poor characterization of absorption's role in pharmacokinetic changes in this population. Physiologically based pharmacokinetic (PBPK) models are increasingly being used during the drug development process, as their unique qualities are advantageous in atypical scenarios such as drug-drug interactions or special populations such as older people. Along with relying on various sources of data, auxiliary tools including parameter estimation and sensitivity analysis techniques are employed to support model development and other applications. However, sensitivity analyses have mostly been limited to localized techniques in the majority of reported PBPK models using them. This is disadvantageous, since local sensitivity analyses are unsuitable for risk analysis, which require assessment of parametric interactions and proper coverage of the input space to better estimate and subsequently mitigate the effects of the phenomenon of interest. For this reason, this study seeks to integrate a global sensitivity analysis screening method with PBPK models based in PK-Sim® to characterize the consequences of potential changes in absorption that are often associated with advanced age. The Elementary Effects (Morris) method and visualization of the results are implemented in R and three model drugs representing Biopharmaceutical Classification System classes I-III that are expected to exhibit some sensitivity to three age-associated hypotheses were successfully tested.

Tumor markers determination in malignant pleural effusion: pearls and pitfalls.

Serum and pleural fluid tumor markers are well-recognized auxiliary diagnostic tools for malignant pleural effusion (MPE). Here, we discuss some pearls andpitfalls regarding the role of tumor markers in MPE management. The following issues are discussed in this article: What is the appropriate clinical scenario for evaluating pleural tumor markers? Which tumor markers should be advocated for diagnosing MPE? Can extremely high levels of tumor markers be employed to establish a diagnosis of MPE? Does the serum-to-pleural fluid ratio of a tumor marker have the same diagnostic efficacy as the measurement of that marker alone in the pleural fluid? Can tumor markers be usedto estimate the risk of specific cancers? What should beconsidered when interpreting the diagnostic accuracy of tumor markers? How should tumor marker studies be performed? We addressed these issues with published works, particularly systematic reviews and meta-analyses.

Problems and Solutions in Vertical Addition of Adults Mental Disorders

This study discusses the problems of adult students (30-40 years old) with mental disabilities in vertical addition learning and proposes several tailored solutions. Through the specific analysis of three students that participated in the study, the difficulties in the process of their mathematical operation ability acquisition are found, such as being influenced by others, and forgetting to carry numbers. In response to these problems, concrete measures have been taken, such as improving students’ self-confidence, using auxiliary tools, and concretizing mathematical concepts. Through the implementation of these measures, a noticeable difference in mathematical ability was achieved. The research summarized some teaching experiences, including the rational use of tools, and attention to students’ psychology and behavior norms.

Construction of a Fine Extraction Process for Seismic Methane Anomalies Based on Remote Sensing: The Case of the 6 February 2023, Türkiye–Syria Earthquake

Identifying seismic CH4 anomalies via remote sensing has been verified as a legitimate method. However, there are still some problems, such as unknown reliability due to the complex characteristics of seismic anomalies. In this study, a multi-dimensional and multi-scale methane seismic anomaly extraction process for remote sensing was constructed with the Robust Satellite Technique (RST) based on the Atmospheric Infrared Sounder (AIRS) CH4 data and then applied to the 2023 Türkiye–Syria earthquake. This study obtained the two-dimensional temporal–spatial distribution of methane anomalies and temporal variation in the anomaly index. Based on this, the three-dimensional profile structure of the 8-day methane anomaly was extracted to determine the reliability of the anomaly. Finally, based on the daily methane anomaly, combined with atmospheric circulation and backward trajectory analysis as auxiliary tools, the influence of air mass migration was excluded to enhance the accuracy of CH4 anomaly determination. The results show that the three-dimensional anomalous structure is consistent with the geological characteristics of tectonic activities, and it appears as a “pyramid” or “inverted pyramid” type in a three-dimensional space. The anomalies caused by air mass migration can be eliminated by combining them with synoptic-scale circulation motion. The time series calculated at the epicenter or a certain point in a region may not accurately reflect the influence of regional or specific tectonic activity in the atmosphere. Thus, the optimal determination of the range and magnitude of atmospheric anomalies caused by tectonic activities is a difficult task for future research.

Prediction of Super-enhancers Based on Mean-shift Undersampling

Background: Super-enhancers are clusters of enhancers defined based on the binding occupancy of master transcription factors, chromatin regulators, or chromatin marks. It has been reported that super-enhancers are transcriptionally more active and cell-type-specific than regular enhancers. Therefore, it is necessary to identify super-enhancers from regular enhancers. A variety of computational methods have been proposed to identify super-enhancers as auxiliary tools. However, most methods use ChIP-seq data, and the lack of this part of the data will make the predictor unable to execute or fail to achieve satisfactory performance. Objective: The aim of this study is to propose a stacking computational model based on the fusion of multiple features to identify super-enhancers in both human and mouse species. Methods: This work adopted mean-shift to cluster majority class samples and selected four sets of balanced datasets for mouse and three sets of balanced datasets for human to train the stacking model. Five types of sequence information are used as input to the XGBoost classifier, and the average value of the probability outputs from each classifier is designed as the final classification result. Results: The results of 10-fold cross-validation and cross-cell-line validation prove that our method has superior performance compared to other existing methods. The source code and datasets are available at https://github.com/Cheng-Han-max/SE_voting. Conclusion: The analysis of feature importance indicates that Mismatch accounts for the highest proportion among the top 20 important features.

Three-dimensional replica of the temporal bone in the teaching of human anatomy.

The current study proposes the comparison of the visualization and identification of anatomical details between natural human temporal bone, its respective copy from three-dimensional printing, and the virtual model obtained from CBCT. The sample consisted of undergraduate students in Dentistry (Group UE, n = 22), Postgraduate students in Radiology and Imaging (Group P-RI, n = 20), and Postgraduate students in Forensic Odontology (Group P-FO, n = 24). All participants attended a theoretical class on specialized anatomy of the temporal bone and subsequently performed the markings of 10 determined structures. The number of correct identifications was similar in natural bone and printed three-dimensional models in all groups (p > 0.05). The virtual model showed a significantly lower number of correct structures (p < 0.05) in the 3 groups. In general, there were significantly higher percentages of accurate answers among postgraduate students compared to undergraduate students. Most graduate students believed that the printed three-dimensional model could be used to teach anatomy in place of natural bone, while undergraduate students disagreed or were unsure (p < 0.05). Regarding the virtual tomographic image, in all groups, students disagreed or were not sure that its use would be beneficial in replacing natural bone. Three-dimensional and virtual models can be used as auxiliary tools in teaching anatomy, complementing practical learning with natural bones.

Research on the Application of Artificial Intelligence in The Teaching Reform of Ideological and Political Courses in Universities

The rapid development of artificial intelligence (AI) technology has brought new opportunities and challenges to the field of education. As an important link to cultivate students' comprehensive quality and socialist core values, it is necessary to carry out continuous teaching reform and innovation. Based on the idea of AI-enabled ideological and political course teaching reform, this study aims to explore how to use artificial intelligence technology to improve the teaching effect and learning experience of ideological and political course. This study first analyzes the application status of artificial intelligence technology in education, and then discusses the application potential of artificial intelligence in ideological and political courses. Then, it puts forward the teaching reform strategy of ideological and political course based on artificial intelligence, including the use of virtual reality technology, the application of intelligent auxiliary teaching tools to enhance personalized teaching, and the construction of intelligent learning management system. Finally, through case analysis, this paper discusses the effect of ideological and political teaching reform in colleges and universities. The results show that the application of artificial intelligence technology can effectively improve the teaching effect and learning experience of ideological and political courses, and provide new ideas and methods for the teaching reform of ideological and political courses in colleges and universities.

Network Pharmacology-Based Virtual Screening of Chemical Constituents from Vitexnegundo Linn's Discovered Novel Molecular Targets for Breast Cancer Treatment.

The Chinese chaste tree Vitexnegundo (VN) is a popular herb in South and Southeast Asia that has several health benefits, including the ability to inhibit tumor growth and induce apoptosis in multiple tumors. Literature revealed scanty research on breast cancer, with little focus on the molecular mechanism of the disease and an emphasis on targets, biological networks, and active components. Exploring natural compounds as possible therapeutic options is an old but still promising approach for drug discovery and development. This study used a thorough computational and statistical method to screen potential drug candidates. The active ingredients and targets of VN were identified using SwissADME, SwissTargetPrediction, STITCH, IMPPAT database, KNapSAcK database, and literature. The OMIM and GeneCards databases were searched for possible targets related to breast cancer. The PASS online server was used to check the probability of active metabolite (Pa) against breast cancer. To build protein-protein interactions (PPI) networking, the intersection of disease and drug targets was uploaded to the STITCH database. Cytoscape software was used to analyze the topology parameters of networking to identify hub targets. Gene Ontology (GO) was analyzed using Metascape and ShinyGO, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed using the David database and SR plot, and the site of expression and protein domain were studied using FunRich. We employed AutoDockvina, Discovery Studio, and UCSF ChimeraX software and auxiliary tools for molecular docking and analysis. Zincpharmer was used for pharmacophore mapping. ADMET analysis was conducted using ADMETsar, Swiss ADME, ADMETLab servers, and mypresto using GROMACS for molecular dynamics simulation (MDS). A total of 65 targets and 21 active ingredients were identified. Further investigation was conducted on 20 hub targets selected through PPI networking construction. The enrichment analysis results indicated that the key factors were P, amyloid-beta response, cellular response to amyloid- beta, Pos. reg. of G2/M transition of the mitotic cell cycle, and response to a toxic substance. The molecular docking, pharmacophore mapping, and MD simulation results indicated that apigenin, kaempferol, and luteolin positively interacted with CDK1 and CDK6 proteins. This study is the first to use network pharmacology, molecular docking, pharmacophore mapping, and MD simulation to identify the active ingredients, molecular targets, and critical biological pathways responsible for VN anti-breast cancer. The study provides a theoretical basis for further research in this area.

Large Language Models Diagnose Facial Deformity.

This study examines the application of Large Language Models (LLMs) in diagnosing jaw deformities, aiming to overcome the limitations of various diagnostic methods by harnessing the advanced capabilities of LLMs for enhanced data interpretation. The goal is to provide tools that simplify complex data analysis and make diagnostic processes more accessible and intuitive for clinical practitioners. An experiment involving patients with jaw deformities was conducted, where cephalometric measurements (SNB Angle, Facial Angle, Mandibular Unit Length) were converted into text for LLM analysis. Multiple LLMs, including LLAMA-2 variants, GPT models, and the Gemini-Pro model, were evaluated against various methods (Threshold-based, Machine Learning Models) using balanced accuracy and F1-score. Our research demonstrates that larger LLMs efficiently adapt to diagnostic tasks, showing rapid performance saturation with minimal training examples and reducing ambiguous classification, which highlights their robust in-context learning abilities. The conversion of complex cephalometric measurements into intuitive text formats not only broadens the accessibility of the information but also enhances the interpretability, providing clinicians with clear and actionable insights. Integrating LLMs into the diagnosis of jaw deformities marks a significant advancement in making diagnostic processes more accessible and reducing reliance on specialized training. These models serve as valuable auxiliary tools, offering clear, understandable outputs that facilitate easier decision-making for clinicians, particularly those with less experience or in settings with limited access to specialized expertise. Future refinements and adaptations to include more comprehensive and medically specific datasets are expected to enhance the precision and utility of LLMs, potentially transforming the landscape of medical diagnostics.

Savižudiškų minčių intensyvumo skalė (SIDAS) ir Savižudiško elgesio klausimynas – patikslintas (SBQ-R): lietuviškų versijų psichometriniai rodikliai

The Suicidal Ideation Attributes Scale (SIDAS) and the Suicidal Behaviors Questionnaire-Revised (SBQ-R) are widely used psychological instruments for assessing people‘s suicidal ideation and suicidal behavior. The aim of this study was to examine the psychometric characteristics of the Lithuanian versions of the SIDAS and SBQ-R. We analysed data collected from four samples: a Lithuanian general population quota sample based on age, gender and place of residence (N = 697, 52.9% women, aged 18–79 years); a sample of students (N = 2013, 72 % women, aged 18–29 years); a clinical sample of suicidal patients (N = 35, 77.1% women, aged 18–59 years); and a test-retest sample of students who completed the instruments twice within a two-week period (N = 54, 70.4% women, aged 18–47 years). The participants answered questions on gender, and age and completed the SIDAS and SBQ-R. The data analysis revealed that the Lithuanian versions of the SIDAS and SBQ-R have good internal consistency, temporal stability, construct, convergent, and criterion validity. The Lithuanian versions of the SIDAS and SBQ-R can be used to measure suicidality in research settings, as well as in clinical work as auxiliary tools.

The teaching of the Art and Science of Medicine

Teaching of medicine hails back to the age of Hippocrates; in the “Oath” he considers his teachers equal to his parents. Teaching, clinical practice and research constitute the three pillars of medicine, and they are interconnected. The methods of teaching medicine are very important. Auditorium lectures are being replaced by teaching in small groups and problem-oriented teaching. Still the enthusiasm of the teacher who can also become a mentor is a critical ingredient. The teacher should not just transmit but also create knowledge. The advent of artificial intelligence provides new auxiliary tools but also poses new challenges. We must not forget that we are shaping the future of tomorrow.

Combined ultrasound endoscopy-guided fine-needle aspiration with DNA methylation of SHOX2 and RASSF1A genes to enhance the auxiliary diagnostic precision of pancreatic cancer

The purpose of this study was to assess the influence and the clinical effectiveness of the short stature homeobox 2 (SHOX2) and ras association domain family 1A (RASSF1A) genes by tissue sampling through ultrasound endoscopy-guided fine-needle aspiration (EUS-FNA) as auxiliary diagnostic tools for pancreatic cancer (PC). Methylation markers were detected in 96 patients using real-time fluorescence quantitative PCR (qPCR), and the performance of this diagnostic assay was compared with CA19-9, CEA, and puncture fluid-based exfoliative cytology using receiver operating characteristic curve (ROC) analysis. The PC group exhibited higher methylation rates for SHOX2, RASSF1A, and the combined assay of both genes compared to the control group (95.7 % vs. 54.0 %, 78.3 % vs. 36.0 %, and 73.9 % vs. 16.0 %, P < 0.05). The areas under the ROC curve (AUC) for CA19-9, CEA, liquid-based exfoliative cytology, SHOX2, RASSF1A, the combination of SHOX2 and RASSF1A, the combination assay with CEA, CA19-9, and liquid-based exfoliative cytology were 0.827, 0.692, 0.767, 0.770, 0.732, 0.870, 0.870, 0.933, and 0.900, respectively. Therefore, the methylation assay based on the combined SHOX2 and RASSF1A genes in EUS-FNA puncture fluid is more effective than using a single gene, liquid-based exfoliative cytology, or intravenous tumor markers for diagnosing PC. Combining the conventional marker CA19-9 enhances the diagnostic value, making it a promising approach to complement histology and cytology.

New method for taxonomic descriptions with coded notation, producing dynamic and interchangeable output.

A proposal for taxonomic species description notation is presented to replace the traditional descriptive texts for a coded matrix, avoiding redundant adjectives and subjective descriptions. This is an attempt to enhance the species description rate and to make the descriptions output available to other scientific disciplines, machine learning, interactive and computer-assisted identification keys, metadata analysis and its applications. The method consists of presenting the description of the overall morphology in a coded matrix, following a character list with detailed observed conditions for each character. The method is dynamic and open to amendments and new data addition as they become available. We test the new method describing five new species of Collembola Symphypleona of the genus Pararrhopalites as a generalized model and made the coded output available. We conclude that a coded taxonomic description is an advance to the traditional taxonomic text, with potential to enhance the global descriptions rate. The generated descriptions are dynamic, expandable and can be easily used in other fields of science, allowing non-experts to access the data for phylogenetic, biogeographic, ecological studies and metadata analysis. Even though an experienced taxonomist will always be necessary to make a detailed taxonomic description, it is a step forward to a general template to semi-automated taxon recognition and to future development of auxiliary tools for species description using machine learning and templates to speed up the time-consuming phase of schematic figures preparation, after the expert interpretations are done.

Classification and Analysis of the Application of Knowledge Graphs in Education

A classification of the use of knowledge graphs in the educational field is presented and analyzes the methods used is carried out. The lack of systematization of the use of knowledge graphs in education, adapted to the individual needs and interests of various stakeholders, has necessitated the analysis and classification of the use of knowledge graphs in education, taking into account the key participants in the educational process. The purpose of the article is to classify the use of knowledge graphs by key participants in the educational field and analyze the methods used to construct and manipulate knowledge graphs. The research methodology is based on review, analysis, classification of scientific articles and projects. As a result of the analysis, several conclusions were obtained. The most common application of knowledge graphs is their use as an educational environment for students, serving as a tool for learning specific subject areas. Teachers perceive knowledge graphs as a means of organizing and structuring educational materials, and education managers consider them valuable for constructing individual learning trajectories and as auxiliary tools for decision making. Various authors have proposed a variety of approaches to working with knowledge graphs, using a variety of techniques such as machine learning, natural language processing algorithms, ontology creation, expert assistance, and the use of a wide range of models. The general trend is that methods for working with knowledge graphs often combine different approaches and technologies to achieve maximum efficiency in solving specific problems. The possibility of further application of the results is to identify the least covered group of stakeholders and develop for them a model of a recommendation system based on knowledge graphs, using modern and relevant methods for processing them.