Categorization Method Research Articles

Validation of the IAC Yokohama system for reporting breast fine-needle aspiration cytology categorization of breast lesions in Vindhya region population

Background: In 2016, International academy of cytology (IAC) has established a standardized approach for reporting breast fine-needle aspiration cytology (FNAC) by categorizing the lesions in five tier system from C1 to C5 to standardize reporting, which will enhance Breast fine-needle aspiration biopsy cytology performance, interpretation, and reporting. Aims and Objectives: The aim of the study was to categorize FNAC cases according to The IAC Yokohama System and evaluate the diagnostic ability of FNAC. Materials and Methods: The current prospective analytical study was carried out in the Department of Pathology, Shyam Shah Medical College, Rewa, Madhya Pradesh, for a period of 15 months from January 2021 to March 2022 (15 months). A total of 100 cases were included in the study based on inclusion criteria. The results were analyzed based on cytological reporting and P value calculated. Results: Among the 100 cases studied highest number of cases were from the age group of 21–30 years with 29% (n=29). The most common breast laterality affected was left with 69% of affected cases. The maximum number of cases, 69% (n=69) of the total, were found to be categorized under the category C2 (benign) which was followed by Category C5 (Malignant) seen in 13% (n=13). About 9% (n=9) of the total cases were categorized as suspicious of malignancy (C4). Atypical Lesion (C3) and Unsatisfactory Lesions (C1) were categorized in 5% (n=5) and 4% (n=4) of the total cases, respectively. Conclusion: FNAC is a minimally invasive, quick, and efficient pre-operative diagnostic tool that can also be used for postoperative breast lump follow-up to prevent recurrences. FNAC using IAC Yokohama system is a rapid and effective method for the primary categorization of palpable breast lumps and provides better clarity to the clinicians in the management of the patient and can reduce unnecessary surgeries.

Portrait of Personality and its Study by Psychosemantics

The subject of the study is a portrait of a personality. Psychological massage is a detailed description of personality characteristics. The unit of personality analysis is the personal meaning. In the aggregate of other meanings, personal meaning forms a hierarchical structure that can be rebuilt in the course of life and, depending on experience, transform the content of meanings in this hierarchy. The object of research is a portrait of a personality studied by methods of psychosemantics to identify the structure, functioning of a system of values, methods of categorization describing a portrait of a personality. Psychosemantic methods are aimed at reconstructing implicit theories of personality and solve the following tasks: connecting the studied meaning of this phenomenon with other meanings, systems of meanings, highlighting and interpreting the most significant among these connections. The psychosemantic approach to the portrait of a personality is a description of a psychological (semantic) structure that contains properties-signs that can be used to characterize a personality. This structure is formed by various types of values "classifying" this construct as a "psychological portrait" The main conclusions of the study are:1) the use of psychosemantic tools for the interpretation of the "personality portrait" contributes to the disclosure of the characteristics of this phenomenon, namely, how the levels of categorization identified during the study correlate with significant topics describing the psychological portrait; 2) a portrait of a personality is a complex characteristic that reflects the inner world, the orientation of the personality and is a tool for studying a person. The novelty of the research lies in the study of implicit theories of drawing up a psychological portrait, resulting in a model of a psychological portrait.

Effect of the categorization method on the diagnostic performance of ultrasound risk stratification systems for thyroid nodules.

To evaluate whether the categorization methods of risk stratification systems (RSSs) is a decisive factor that influenced the diagnostic performances and unnecessary FNA rates in order to choose optimal RSS for the management of thyroid nodules. From July 2013 to January 2019, 2667 patients with 3944 thyroid nodules had undergone pathological diagnosis after thyroidectomy and/or US-guided FNA. US categories were assigned according to the six RSSs. The diagnostic performances and unnecessary FNA rates were calculated and compared according to the US-based final assessment categories and the unified size thresholds for biopsy proposed by ACR-TIRADS, respectively. A total of 1781 (45.2%) thyroid nodules were diagnosed as malignant after thyroidectomy or biopsy. Significantly lowest specificity and accuracy, along with the highest unnecessary FNA rates were seen in EU-TIRADS for both US categories (47.9%, 70.2%, and 39.4%, respectively, all P < 0.05) and indications for FNA (54.2%, 50.0%, and 55.4%, respectively, all P < 0.05). Diagnostic performances for US-based final assessment categories exhibited similar accuracy for AI-TIRADS, Kwak-TIRADS, C-TIRADS, and ATA guidelines (78.0%, 77.8%, 77.9%, and 76.3%, respectively, all P > 0.05), while the lowest unnecessary FNA rate was seen in C-TIRADS (30.9%) and without significant differences to that of AI-TIRADS, Kwak-TIRADS, and ATA guideline (31.5%, 31.7%, and 33.6%, respectively, all P > 0.05). Diagnostic performance for US-FNA indications showed similar accuracy for ACR-TIRADS, Kwak-TIRADS, C-TIRADS and ATA guidelines (58.0%, 59.7%, 58.7%, and 57.1%, respectively, all P > 0.05). The highest accuracy and lowest unnecessary FNA rate were seen in AI-TIRADS (61.9%, 38.6%) and without significant differences to that of Kwak-TIRADS(59.7%, 42.9%) and C-TIRADS 58.7%, 43.9%, all P > 0.05). The different US categorization methods used by each RSS were not determinant influential factors in diagnostic performance and unnecessary FNA rate. For daily clinical practice, the score-based counting RSS was an optimal choice.

A Methodological Literature Review of Acoustic Wildlife Monitoring Using Artificial Intelligence Tools and Techniques

Artificial intelligence (AI) has become a significantly growing field in the environmental sector due to its ability to solve problems, make decisions, and recognize patterns. The significance of AI in wildlife acoustic monitoring is particularly important because of the vast amounts of data that are available in this field, which can be leveraged for computer vision and interpretation. Despite the increasing use of AI in wildlife ecology, its future in acoustic wildlife monitoring remains uncertain. To assess its potential and identify future needs, a scientific literature review was conducted on 54 works published between 2015 and March 2022. The results of the review showed a significant rise in the utilization of AI techniques in wildlife acoustic monitoring over this period, with birds (N = 26) gaining the most popularity, followed by mammals (N = 12). The most commonly used AI algorithm in this field was Convolutional Neural Network, which was found to be more accurate and beneficial than previous categorization methods in acoustic wildlife monitoring. This highlights the potential for AI to play a crucial role in advancing our understanding of wildlife populations and ecosystems. However, the results also show that there are still gaps in our understanding of the use of AI in wildlife acoustic monitoring. Further examination of previously used AI algorithms in bioacoustics research can help researchers better understand patterns and identify areas for improvement in autonomous wildlife monitoring. In conclusion, the use of AI in wildlife acoustic monitoring is a rapidly growing field with a lot of potential. While significant progress has been made in recent years, there is still much to be done to fully realize the potential of AI in this field. Further research is needed to better understand the limitations and opportunities of AI in wildlife acoustic monitoring, and to develop new algorithms that can improve the accuracy and usefulness of this technology.

R-linguistics. The Principle of Linguistic Duality

Introduction. R-linguistics uses the axiomatic method in its approach to modeling the world and language [1]. Axioms define the categories of language, their properties and ways of formation. On this basis, when processing the accumulated data in the form of relations, it is possible to form systems of categories and determine the verbs connecting these categories. A reasonable question arises: if categories (to be such) must satisfy certain axioms, does this requirement apply to verbs as well? The purpose of this article is to deal with this issue.Methodology and sources. The results of the previous parts of the series are used as research tools. The axioms and methods of verb categorization formulated earlier are used to develop the necessary mathematical representations of the verb axiomatics.Results and discussion. The article introduces the axiom for the verbs of the language (the axiom of the verbal cross) and shows that this axiom is related to the categorization axiom (the correctness axiom). Although this connection is not identical, it becomes such with the additional use of the axiom of extensiveness. This relationship made it possible to formulate the fundamental principle of linguistics – the principle of duality.Conclusion. The axiomatics of verbs and categories of a language turns out to be connected, and one determines the other, so that by and large it does not matter which of them is the source of the model of the world and the appearance of language. This unity is formulated as the principle of duality in linguistics. The manifestations of the principle of duality in the language are diverse, but this article focuses on the discussion of the appearance in the language of verbs-processes and adverbs. This transition is considered, starting with obtaining the initial data about the world, to the emergence of ideas about processes and adverbs as a feature system of verbs.

Социально-философская трактовка социальности как универсальной категории

The issue of addressing the phenomenon of sociality and its research are designed to help identify the characteristics of its typological, dynamic, structural and functional properties. The problems of sociality are most acutely actualized during crises, becoming the basis for studying society. The purpose of this article was to identify and describe the categorical series of sociality based on the generalization of its characteristics. In the course of the research, the author applied the categorical systems methodology. The theoretical analysis revealed no unified interpretation of the category of sociality. Sociality is often considered to be a result of social reality, a human trait, although there are attempts to consider sociality as a general category in relation to a specific category, namely, social reality. Sociality reflects a person’s ability to exist in society, to be its full member. Using the results of the theoretical analysis, generalizations and conclusions on understanding the category of sociality, the author developed a model of the structure and elements of the categorical series of sociality based on the categorical pendulum method. This model includes the following categories: society, social life, social reality, culture, historical development, politics, citizenship, sociability, exchange, connections, dependence and interdependence. The paper revealed sociality trends in the pessimal scenario of its development. Asociality, prosociality and antisociality, in contrast to sociality, manifest themselves to varying degrees. At the same time, the information society contributes to the formation of asociality, while prosociality is a consequence of the sociocultural penetration of alien values, and antisociality is seen as a consequence of alienation, including in upbringing. Further study into the pessimal tendencies of sociality will contribute to new scientific research aimed to fulfil preventive practice-oriented tasks of counteracting the indicated antagonistic types of sociality.

Inferring the decision rules that drive co-foraging affiliations in wild mixed-species parrot groups.

Animals gathered around a specific location or resource may represent mixed-species aggregations or mixed-species groups. Patterns of individuals choosing to join these groups can provide insight into the information processing underlying these decisions. However, we still have little understanding of how much information these decisions are based upon. We used data on 12 parrot species to test what kind of information each species may use about others to make decisions about which mixed-species aggregations to participate in. We used co-presence and joining patterns with categorization and model fitting methods to test how these species could be making grouping decisions. Species generally used a simpler lower-category method to choose which other individuals to associate with, rather than basing these decisions on species-level information. We also found that the best-fit models for decision-making differed across the 12 species and included different kinds of information. We found that not only does this approach provide a framework to test hypotheses about why individuals join or leave mixed-species aggregations, it also provides insight into what features each parrot could have been using to make their decisions. While not exhaustive, this approach provides a novel examination of the potential features that species could use to make grouping decisions and could provide a link to the perceptive and cognitive abilities of the animals making these minute-by-minute decisions. This article is part of the theme issue 'Mixed-species groups and aggregations: shaping ecological and behavioural patterns and processes'.

Pressure injuries, care and prevention: the case of wheelchair users

The objective of this study was to understand the interference of pressure injuries on wheelchair users' lives and to verify the care and prevention strategies. This research is characterized as descriptive observational, with analysis and discussion of data under the qualitative paradigm. A semi-structured interview was conducted with 31 wheelchair users from the Spinal Injuries Association of Rio Grande do Sul. The qualitative analysis was performed by the data categorization and triangulation method. It was found that pressure injuries develop while users are hospitalized in hospital beds, due to the use of the wheelchair without the care of frequent seat pressure relief and the inappropriate cushions use. It was also observed that the injuries affect the health and interfere users’ quality of life, and the long treatment period for the healing of the injuries implies into the removal of social life. It’s concluded that the best solution is prevention, which should occur early through the use of products and practices that relieve pressure in certain places of the body on the wheelchair seat and in hospital beds.

A Research Survey on Real-Time Intelligent Traffic System

Nowadays, it is crucial to continuously monitor and provide real-time analysis to reduce traffic-related accidents and practices such as vehicle overloading on the roads daily. As a result, we reviewed the literature's numerous methods and techniques for vehicle detection, recognition, identification, speed estimation, and license plate recognition. In this analysis, we examined 42 articles published in the last ten years, from 2012 to 2022. Based on our research, we found that the Deep CNN is the optimum method for vehicle categorization. The motivation of this review is that none of the aforementioned models are combined into a single model, so we present a comprehensive list of all these models that may be helpful to anyone conducting the study in this area. Therefore, after reviewing the chosen research publications, we propose 20+ datasets that might be used in the field for more research. We also discovered 15+ different ML models used to detect and identify vehicles. Finally, we observed that combining machine learning and AI (Artificial Intelligence) to create intelligent traffic control systems is a promising research area.

Recursive computed ABC (cABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size

Selecting the k best features is a common task in machine learning. Typically, a few features have high importance, but many have low importance (right-skewed distribution). This report proposes a numerically precise method to address this skewed feature importance distribution in order to reduce a feature set to the informative minimum of items. Computed ABC analysis (cABC) is an item categorization method that aims to identify the most important items by partitioning a set of non-negative numerical items into subsets "A", "B", and "C" such that subset "A" contains the "few important" items based on specific properties of ABC curves defined by their relationship to Lorenz curves. In its recursive form, the cABC analysis can be applied again to subset "A". A generic image dataset and three biomedical datasets (lipidomics and two genomics datasets) with a large number of variables were used to perform the experiments. The experimental results show that the recursive cABC analysis limits the dimensions of the data projection to a minimum where the relevant information is still preserved and directs the feature selection in machine learning to the most important class-relevant information, including filtering feature sets for nonsense variables. Feature sets were reduced to 10% or less of the original variables and still provided accurate classification in data not used for feature selection. cABC analysis, in its recursive variant, provides a computationally precise means of reducing information to a minimum. The minimum is the result of a computation of the number of k most relevant items, rather than a decision to select the k best items from a list. In addition, there are precise criteria for stopping the reduction process. The reduction to the most important features can improve the human understanding of the properties of the data set. The cABC method is implemented in the Python package "cABCanalysis" available at https://pypi.org/project/cABCanalysis/.

The Classification and New Trends of Shared Control Strategies in Telerobotic Systems: A Survey.

Shared control, which permits a human operator and an autonomous controller to share the control of a telerobotic system, can reduce the operator's workload and/or improve performances during the execution of tasks. Due to the great benefits of combining the human intelligence with the higher power/precision abilities of robots, the shared control architecture occupies a wide spectrum among telerobotic systems. Although various shared control strategies have been proposed, a systematic overview to tease out the relation among different strategies is still absent. This survey, therefore, aims to provide a big picture for existing shared control strategies. To achieve this, we propose a categorization method and classify the shared control strategies into 3 categories: Semi-Autonomous control (SAC), State-Guidance Shared Control (SGSC), and State-Fusion Shared Control (SFSC), according to the different sharing ways between human operators and autonomous controllers. The typical scenarios in using each category are listed and the advantages/disadvantages and open issues of each category are discussed. Then, based on the overview of the existing strategies, new trends in shared control strategies, including the "autonomy from learning" and the "autonomy-levels adaptation," are summarized and discussed.

Consumers’ Behavior in the Field of Organic Agriculture and Food Products during the COVID-19 Pandemic in the Czech Republic: Focus on a Comparison of Hyper-, Super- and Farmers’ Markets and Direct Purchases from Producers

The aim of this paper is to assess Czech food consumers’ behavior when buying organic products during the COVID-19 pandemic, with an emphasis on the place of purchase of organic agriculture and food products—especially those purchases with the shortest logistics value chain, i.e., purchase at farmers’ markets, or directly from the producer—and a comparison with the current most common places of purchase of organic products in the Czech Republic, supermarkets and hypermarkets. Categorical data analysis methods were used to create a profile of the consumer according to the most frequent purchase locations. To create mathematical–statistical models and interpretations, the methods of logistic regression, correspondence analysis and contingency table analysis were chosen. According to the results of the survey, respondents under 25 years of age are the least likely to make purchases at farmers’ markets or directly from the producer. Consumers aged 26–35 and with a university degree are the most likely to buy organic agriculture and food products at this location, followed closely by older respondents in the categories 36–45 and 46+ and with a secondary education. It is important for manufacturers to have an overview of where, in what quantities, and for what reasons consumers buy their products, especially for reasons of production optimization and planning, ecological concerns, rural development, and the impact on local areas and the value chain.

Psychodiagnostic Research of a Dialogue in Culturally Oriented Surrounding in the Process of School Studying

the purpose of our research is to provide psychodiagnostic research of a dialogue in culturally oriented surrounding in the process of school studying.methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: the categorical method, structural and functional methods, the methods of the analysis, systematization, modeling, generalization. The experimental method was the method of organi­zing empirical research.the results of the research. We proved that the reasons of a low level of validity of opinions and judgments by pupils are: 1) unsuccessful organization of the discussion at the English language classes; 2) as a consequence of the first reason – pupils are not familiar with the discussion as a form of educational ac-tivity, they do not know how to behave at such a lesson, and most often choose a standard position of a “pupil” who listens carefully to the teacher, answers his/her questions concisely, clearly, regardless of schoolchild’s point of view; 3) 68% of pupils do not understand why they need to justify their opinions (because they always express only those opinions that are in their textbooks or that were expressed by the teacher at the previous lesson); 4) 32% of schoolchildren are afraid to substantiate their statement “incorrectly”, “ not methodically” and to get a bad mark.conclusions. We distinguish, on the one hand, a dialogue, and on the other one – a simple conversation. A dialogue is understood as a mutual communica-tion that has specific features: thematic focus or a problem solving, getting two­way information, the combination of thematic focus with two­way transmission of information that helps to solve a common problem in any way. Also we distin-guish between linguistic and psychological understanding of a dialogue, empha-sizing that in the process of psychological studying of a dialogue it is necessary to pay a great attention to both the informative exchange between partners and the features of their relationships, in particular their aspect of role interaction.

Математическая модель интеллектуальной системы поддержки принятия управленческих решений в энергосистемах

The article considers the problem of taking into account the information uncertainty for building knowledge bases in decision support systems for the operational management of the electric power system modes on the example of the Pridnestrovian Moldavian Republic power system. As part of the study, the categorical method “Universal Interaction Scheme” is used, because it allows building a conceptual model of the Pridnestrovian Moldavian Republic power systems necessary for the further development of a mathematical model. To create a mathematical model of an intelligent management decision support system in power systems, the Decision-Support System knowledge base method based on fuzzy logic is used. It is substantiated that formulating the control logic is carried out mainly at the level of qualitative representations and concepts. The latter can be formalised in terms of logical-linguistic models, which should be considered from the viewpoint of the theory of fuzzy sets and linguistic variables. The analysis of existing approaches to representing and processing fuzzy knowledge about the power system management is carried out. An approach to demonstrating the incorporation of various forms of professional ontology representation based on fuzzy logic is substantiated. The research methods involve using the apparatus of fuzzy logic, formal languages, the theory of artificial intelligence systems and decision support systems.

Conative, Personality-based, Cognitive and Competence Approaches in the Semantic Sphere of the Individual’s Creativity

the aim of our article is to show conative, personality­based, cognitive and competence approaches in the semantic sphere of the individual’s creativity, to determine their characteristics, valuable and unique qualities.methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: the categorical method, structural and functional methods, the methods of the analysis, systematization, modeling, generalization. the results of the research. We think that leading to the development of the person’s creative imagination is metaphorical imagination (personal ap-proach). The latter is able to create new images of objects, ideas, meanings and emotional­sensual experiences, appealing to the imagination of the respondent who perceives. Metaphorical imagination is manifested as a person’s ability to independent creative metaphors, creatively interpret complex metaphors, cre-atively and originally apply existing metaphorical expressions depending on the context of a certain situation. Realizing the connection between the sensual and the rational, the construction of a creative metaphorical image activates the subject’s sensory­perceptual and emotional imagination on a creative level, thereby contributing to a new and deeper understanding of their essence.conclusions. We showed that psychological researches in a great degree emphasized such creative personality traits as productive ones, creative think-ing, the implementation of creative characteristics, transformative human acti­vity, the need for self­affirmation, material well­being, the transformation of the surrounding natural and social world, the implementation of doping strategies in the context of life achievements of the individual (a conative approach); in-tellectual activity, psychological flexibility, creative motivation, multivariate vi-sion of the surrounding world, originality, divergence; personal achievements (integrative approach); mental structures, mental representations, mental ex-perience, intellectual abilities – speed, originality, sensitivity, metaphoricality, formulation and original solution of a problem, actualization of the concept of a creative act (a cognitive approach); motivation to carry out creative activities, motivation to achieve success, situational self­actualization (a motivational ap-proach); a high level of professionalism, professional and creative semantics, creative explication of the situation, professional and creative social perception, creative aspects of communication (competence approach)

Facilitative Interaction as a Multi-Level Human Activity

Тhe purpose of our research is to show facilitative interaction as a multi­level human activity, to show the significant constructive phenomena of facilita-tive interaction as a psychological status of the individual. methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: a categorical method, structural and functional methods, the methods of the analysis, systematization, modeling, generalization. Also, in our research we used empirical methods, such as statement experiment.the results of the research. It was shown, that the concept “facilitation” reflects a conscious and purposeful activity as a phenomenon characteristic, first of all, of a teacher. Thus, we singled out the attributes of facilitation: 1) cogni-tive activity; 2) the subject of the activity; 3) the functions of the subject; 4) the object of the activity; 5) the motives of the activity; 6) the purpose of the activity; 7) functions of the activity; 8) the ways of performing activities; 9) methods of activity implementation (and means relevant for the implementation of these activities); 11) the result of the activity.conclusions. We showed the characteristics of facilitative interaction. We proved, that the Activity was the basis, means and positive condition for the development of the Personality. The Activity is the expedient transformation of the surrounding reality of people. We call activity “a unit of life”, mediated by the process of mental reflection. Also, outside activity there are neither means of the activity, nor signs, nor objects of art; there are no people outside the activity.Therefore, the activity is a purposeful, multi­level human activity. “Pur-poseful” is because “the subject” appears as its goal. “Multi­level” is because it includes into its structure of actions, secondary motivation, determined by the purpose and the tasks of the activity. And this, in turn, ensures the actualization of the main goal­motive of the activity by the individual. And, finally, the opera-tion of the activity differs from the action in that it is not marked by a goal, but by the conditions of the activity in which this goal is explained. It is very necessary to distinguish the actions from the activities and from operations.

The Problem of the Influence of Social Intelligence of Teachers on the Organization of Problem-Based Learning at Secondary Schools

The purpose of our article is to study the level of the development of tea­chers’ social intelligence of teenagers and senior pupils who teach the natural sciences and humanities; to receive and to analyze the results according to Sub-test 3 “Verbal Expressions” (Гилфорд &amp; О’Салливен, 2021), which determine the ability to understand the significance of such verbal reactions of people de-pending on the context of the situation; to study the problem of the influence of Social Intelligence of teachers on the organization of problem­based learning at secondary schools.methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: the categorical method, structural and functional methods, the methods of the analysis, systematization, modeling and generalization. In our research we used empirical methods, such as statement study and molding experiment. With the aim to diagnose the level of the development of social intelligence of teachers we used the test of J. Gilford and M.O’Sullivan “Research of Social Intelligence”, adapted by O.S. Mykhailova (Гилфорд &amp; О’Салливен, 2021).the results of the research. We diagnose the level of the development of the ability to predict the development of a social situation depending on exter-nal circumstances. There is a slight tendency towards higher indicators of social intelligence of women, but there aren’t significant differences in the indicators of social intelligence of men and women at high, medium and low levels, which have been established. We can note that the subjects who performed the tasks of this test equally well, had indicators of a high level of development of so-cial intelligence. We proved, that because respondents with a high level of the development of social intelligence according to this subtest are able to extract the maximum amount of information about people’s behavior, they are able to understand the language of non­verbal communication, express quick and accu-rate judgments about other people, successfully predict their reactions in given conditions, show farsightedness in the relationships with others, which contri­butes to their successful social adaptation.conclusions. So, teachers with a high level of social intelligence are usually successful communicators. They are characterized by contact, openness, tact, benevolence and cordiality. A high level of social intelligence is associated with a great interest in solving social problems, by the need to influence others and it is often combined with a high level of organizational pupils’ skills development. All the listed personal qualities characterize teachers of humanitarian professions.

Psycholinguistic Paradigm of Transformational Model of English-Ukrainian Translation

the purpose of our research is: 1) to show the main psychological cha­racteristics of oral translation activity; 2) to organize the ascertainment study and to analyze the results of it according to the selected criteria, such as: a) the level of students’ communicative and speaking activity; b) the level of personal and situational anxiety; c) the language hearing level; 3) to propose Transfor-mational Model of English­Ukrainian Translation, using English phraseological units, and to describe it.methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: the categorical method, structural and functional methods, the methods of the analysis, systematization, modeling, generalization. The empirical method is ascertaining research.the results of the research. We think that the data of psycholinguistic ob-servations are the means of modifying existing models of implementation of translation activities. We propose a universal Transformational Model of Eng-lish­Ukrainian Translation as the most possible translation model. We believe that this model includes three stages: 1) the analysis, during which the surface structure in language A is reduced to a set of grammatical transformations (the analysis taking into account grammatical relations and meanings of linguistic units); 2) transferring the analyzed material from language A to language B; 3) the reconstruction or final adaptation of the final message taking into account the norms of the language having been used to translate the text.conclusions. We proved that grammatical transformations were one of the methods of semantic analysis of the original text and one of the ways of con-structing the final statement. However, reducing the translation to only gram-matical transformations somewhat simplifies the real process of translation, since it uses both lexical­syntactic paraphrasing and semantic modifications due to situational­pragmatic factors, etc. As a result, the translation itself is con-sidered by us as a combination of three components: on the one hand, it is a product, on the other one, it is a certain number of technologies, and on the third hand, it is a process of combining (for the translator) a certain set of signs (the original text) and taking into account the effectiveness of semantic perception by the recipient of a set of signs offered to him/her by the translator.

Immunogenic cell death-associated biomarkers classification predicts prognosis and immunotherapy efficacy in pancreatic ductal adenocarcinoma.

Immunogenic cell death (ICD) is a sort of regulated cell death (RCD) sufficient to trigger an adaptive immunological response. According to the current findings, ICD has the capacity to alter the tumor immune microenvironment by generating danger signals or damage-associated molecular patterns (DAMPs), which may contribute in immunotherapy. It would be beneficial to develop ICD-related biomarkers that classify individuals depending on how well they respond to ICD immunotherapy. We used consensus clustering to identify two ICD-related groupings. The ICD-high subtype was associated with favorable clinical outcomes, significant immune cell infiltration, and powerful immune response signaling activity. In addition, we developed and validated an ICD-related prognostic model for PDAC survival based on the tumor immune microenvironment. We also collected clinical and pathological data from 48 patients with PDAC, and patients with high EIF2A expression had a poor prognosis. Finally, based on ICD signatures, we developed a novel PDAC categorization method. This categorization had significant clinical implications for determining prognosis and immunotherapy. Our work emphasizes the connections between ICD subtype variations and alterations in the immune tumor microenvironment in PDAC. These findings may help the immune therapy-based therapies for patients with PDAC. We also created and validated an ICD-related prognostic signature, which had a substantial impact on estimating patients' overall survival times (OS).

Sensorial analysis of categorized data of special coffee to identify similar crop seasons pairs using Kappa

This paper presents the proposal of a statistical method to analyse dependent agreement data with categorical ordinal responses for a longitudinal study in sensorial analysis of special coffee. The assessment of sensory attributes of special coffees were carried out by certified raters using a continuous scale of grades. The approach aimed to applying data categorization methods commonly used in machine learning which generated not only a concise summary of continuous attributes to describe the data but also allowed to maximize the agreement grades in a longitudinal study. A previous analysis was carried out to identify the similarity of grades in all sample unities. The categorization allowed the construction of marginal models for all distinct pairs time observed in the longitudinal study for modeling the concordance correlationskappa. It also enabled to conclude that samples of harvests related to yellow grain fruits have similar sensorial characteristics. Higher altitudes are significantly favorable to obtain samples with similar sensorial characteristics identifying the set of covariates which contributed either in positive or negative way while estimating kappa.