<abstract><title style='display:none'>Abstract</title> The precedent studies on the validity of Modus ponens and Modus tollens have been carried out with most regard to a major type of conditionals in which the conditional clause is a sufficient condition for the main clause. But we sometimes, in natural language arguments, find other types of conditionals in which the conditional clause is a necessary or necessary and sufficient condition for the main clause. In this paper I reappraise, on the basis of new definitions of Modus ponens and Modus tollens, their validity/invalidity in natural language arguments in consideration of all types of conditionals.</abstract>

MODUS PONENS AND MODUS TOLLENS: THEIR VALIDITY/INVALIDITY IN NATURAL LANGUAGE ARGUMENTS

<abstract><title style='display:none'>Abstract</title>Poincaré plot is a return map which can help perform graphical analysis of data. We can also fit an ellipse to the plot shape by determining descriptors SD1, SD2 and SD1/SD2 ratio to study the data quantitatively. In this paper we show examples of application of Poincaré plots in analysis of various kinds of biomedical signals: RR intervals, EMG, gait data and EHG.</abstract>

Poincaré Plots in Analysis of Selected Biomedical Signals

<abstract><title style='display:none'>Abstract</title>English for specific purposes (ESP) has been conceptualized by its leading scholars, like Hutchinson and Waters (1987) or Dudley-Evans and St. John (1998), as a multi-stage process, where the ESP practitioner fulfils a variety of roles, including that of learner needs researcher, course designer, language instructor, learning assessor, and course evaluator. The performance of these roles requires considerable knowledge of a linguistic, socio-cultural and pedagogical nature, necessary to inform the teacher’s cognitive processes, par- ticularly those involved in course decision making. The necessary professional knowledge of the ESP teacher, which is gained through professional school- ing, teacher training, and teaching experience, comprises both relevant theo- retical concepts (knowing what) and performance skills (knowing how). It di- rectly impacts on all stages of the ESP process, namely the planning, design, teaching, assessment and evaluation of a course, largely determining its quality. The present paper focuses on ESP teacher cognition, especially those cognitions (i.e. knowledge and beliefs) that are involved in course design, informing the teacher’s choices of course parameters and instructional practices. Elaborating on the concepts developed by language cognition scholars, like Shulman (1987), Andrews (e.g. 2007), and Borg (e.g. 2006), the author tries to outline the in- ternal structure of ESP teacher cognition and describe the function of each subordinate knowledge base. The paper also presents the preliminary results of a small-scale exploratory study into the professional cognition of 13 teachers of Legal and Business English employed at the University of Warsaw.</abstract>

THE ROLE OF TEACHER KNOWLEDGE IN ESP COURSE DESIGN

<abstract><title style='display:none'>Abstract</title>The aim of this study was to evaluate the possibility of incorrect assessment of mortality risk factors in a group of patients affected by acute coronary syndrome, due to the lack of hazard proportionality in the Cox regression model. One hundred and fifty consecutive patients with acute coronary syndrome (ACS) and no age limit were enrolled. Univariable and multivariable Cox proportional hazard analyses were performed. The proportional hazard assumptions were verified using Schoenfeld residuals, χ2 test and rank correlation coefficient t between residuals and time. In the total group of 150 patients, 33 (22.0%) deaths from any cause were registered in the follow-up time period of 64 months. The non-survivors were significantly older and had increased prevalence of diabetes and erythrocyturia, longer history of coronary artery disease, higher concentrations of serum creatinine, cystatin C, uric acid, glucose, C-reactive protein (CRP), homocysteine and B-type natriuretic peptide (NT-proBNP), and lower concentrations of serum sodium. No significant differences in echocardiography parameters were observed between groups. The following factors were risk of death factors and fulfilled the proportional hazard assumption in the univariable model: smoking, occurrence of diabetes and anaemia, duration of coronary artery disease, and abnormal serum concentrations of uric acid, sodium, homocysteine, cystatin C and NT-proBNP, while in the multivariable model, the risk of death factors were: smoking and elevated concentrations of homocysteine and NT-proBNP. The study has demonstrated that violation of the proportional hazard assumption in the Cox regression model may lead to creating a false model that does not include only time-independent predictive factors.</abstract>

Hjärtsektionen, Medicinkliniken, Länsjukhuset i Kalmar, Sweden

Department of Pathophysiology, Medical Faculty in Katowice, Medical University of Silesia, Poland

Department of Statistics, Faculty of Pharmacy with the Division of Laboratory Medicine in Sosnowiec, Medical University of Silesia, Poland

Limitations of Cox Proportional Hazards Analysis in Mortality Prediction of Patients with Acute Coronary Syndrome

<abstract><title style='display:none'>Abstract</title>The development of genre-awareness is a key issue in legal translator training, as, according to research, semantic text comprehension depends largely on the recognition of genres/text types. Legal translators must be familiar with the rhetorical and textual conventions of legal genres both in the source- and the target language – the two code systems – to realise the communicative aim of the translation, and to be able to produce texts that are acceptable by the professional community.Consequently, in legal translator training the development of intercultural competence has double implications: it refers not only to the ability to transfer between legal systems, but also between legal genres. The biggest challenge of translator training is to improve skills and competences effectively through a selection of texts that realistically meet the changing needs of the translation market, but, at the same time, can be successfully adjusted to the level of proficiency attained by students at different levels of the training.Drawing on both practical experience and empirical research, the paper attempts to present a methodological scheme for the selection and grading of legal genres and text types in legal translator training, taking into account some of the functional typologies, and several other relevant aspects. With a practical approach, the selected genres are introduced in the context of exercises aimed at improving genre-transfer competence and some other skills vital for legal translators. Although the presented scheme/case study has been designed for an actual 3-semester legal translator training where students have legal degrees, it is supplemented with further methodological guidelines so that it can be adapted to other legal translator trainings of any level.</abstract>

The Role of Genres and Text Selection in Legal Translator Training

<abstract><title style='display:none'>Abstract</title>Biomedical signals are frequently noisy and incomplete. They produce complex and high-dimensional data sets. In these mentioned cases, the results of traditional methods of signal processing can be skewed by noise or interference present in the signal. Information entropy, as a measure of disorder or uncertainty in the data, was introduced by Shannon. To date, many different types of entropy methods have appeared with many different application areas. The purpose of this paper is to present a short overview of some methods of entropy analysis and to discuss their suitability for use in the analysis of biomedical signals.</abstract>

Entropy-Based Algorithms in the Analysis of Biomedical Signals

<abstract>
<title style='display:none'>Abstract</title>
Fulfilling the needs of securing the food market was a key problem for the economy of the People’s Republic of Poland. According to the assumptions of the socialist system, all basic means of production were owned by the state and society as a whole, and production: its structure and volume depended on central assumptions. Farmers not only had to face the issue of reconstruction of farms in the post-war period, they were also obliged to make compulsory deliveries, and had the main responsibility for feeding the country. Production capacity in the face of the growing needs of society was insufficient, which forced rationing and the use of substitutes in the diet. There were periodic declines in the consumption of selected commodities, especially meat. The purpose of this article is to analyze the situation of the food market in the period 1945–1989, taking into account the burden of the countryside, the level of consumption and the import and export of basic food products.
</abstract>

Food Crises in Post-War Poland (1945–1989)

<abstract>
<title style='display:none'>Abstract</title>
Different approaches analyze the strength of a natural language argument in different ways. This paper contrasts the <italic>dialectical</italic>, <italic>structural</italic>, <italic>probabilistic</italic> (or Bayesian), <italic>computational</italic>, and <italic>empirical</italic> approaches by exemplarily applying them to a single argumentative text (<italic>Epicureans on Squandering Life</italic>; Aikin &amp; Talisse, 2019). Rather than pitching these approaches against one another, our main goal is to show the room for fruitful interaction. Our focus is on a dialectical analysis of the <italic>squandering argument</italic> as an argumentative response that voids an interlocutor’s right to assertion. This analysis addresses the pragmatic dimensions of arguing and implies an argument structure that is consistent with empirical evidence of perceived argument strength. Results show that the squandering argument can be evaluated as a (non-fallacious) <italic>ad hominem</italic> argument, which however is not necessarily stronger than possible arguments attacking it.
</abstract>

Thou Shalt Not Squander Life – Comparing Five Approaches to Argument Strength

<abstract>
<title style='display:none'>Abstract</title>
There is a growing sense among translational hermeneuticists that their assumptions pertaining to the act of translation as seen from the hermeneutical perspective should align them more with a cognitive field. Taking the above view into account, the aim of this paper is to introduce the idea of translational (neuro)hermeneutics into the field of translation studies. The first part of the paper is dedicated to the concept of (neuro)hermeneutics as based on Gambino and Pulvirenti (2019) approach to literary studies, which is then followed by the theoretical and methodological issues associated with philosophy of landscape taken from the perspective of new cultural geography and of embodiment. The second part of this paper presents the theoretical and methodological considerations as regards translations of landscape descriptions and their analysis, with emphasis on the concept of the (neuro)hermeneutic circle. The paper concludes with suggestions as to further advancement within the field of translational (neuro)hermeneutics.
</abstract>

Towards Translational (Neuro)Hermeneutics of Landscape: Theoretical and Methodologial Considerations on Translational Analysis

<abstract>
<title style='display:none'>Abstract</title>
This paper explores the integration of machine learning into economics and social sciences, assessing its potential impact and limitations. It introduces fundamental machine learning concepts and principles, highlighting the differences between the two disciplines, particularly the focus on causal inference in economics and prediction in machine learning. The paper discusses diverse applications of machine learning, from extracting insights from unstructured data to creating novel indicators and improving predictive accuracy, while also addressing challenges related to data quality, computational efficiency, and data ownership. It emphasizes the importance of standardization, transparency, and ethical considerations in prediction tasks, recognizing that machine learning is a powerful tool but cannot replace economic theory. Ultimately, researchers remain optimistic about the transformative potential of machine learning in re-shaping research methodologies and generating new insights in economics and social sciences.
</abstract>

Evaluating the Role of Machine Learning in Economics: A Cutting-Edge Addition or Rhetorical Device?

<abstract>
<title style='display:none'>Abstract</title>
The purpose of the article is to examine the post-pandemic business cycle in Poland and in the United States in the light of the Austrian business cycle theory. The study shows that this theory satisfactorily explains the post-pandemic business cycle. Moreover, it seems that the Austrian business cycle theory explains some important facts better than competing theories of business cycle. The analysis also indicates that the post-pandemic business cycle differs significantly in many respects from previous business cycles – and that these differences could be explained within the framework of the Austrian business cycle theory.
</abstract>

Post-Pandemic Business Cycle in Poland and in the United States in the Light of the Austrian Business Cycle Theory

<abstract>
<title style='display:none'>Abstract</title>
Crises come and go, but it is good if, from the perspective of the past, we can point to some positives of the crisis that has just passed. Indeed, in the article we first find a snapshot of the export activity of the Polish economy in recent years, a picture which is positive, despite the very serious crises in the global economy. This picture may not be complete due to the scope of the study, but it shows what is most important in author opinion – our place in the international division of labor over the last 15 years. This place has steadily improved, with particularly spectacular increases in importance observed during the years of the Covid-19 pandemic crisis and after the outbreak of war in Ukraine.
The second section of the article presents an analysis of agri-food exports in a broader time frame, dating back to the 2000s. It aims to highlight the rise of agri-food exports as a proportion of GDP and total exports. Equally fascinating is the geographical and commodity structure and the mportance of Polish agri-food imports in the total of those made by selected countries. As a result, an interesting picture of Polish agri-food exports appears to have emerged, allowing positive assessments to be formulated. Quite optimistic prognoses for the future are also noticeable.
</abstract>

Export of the Agri-Food Sector in the Conditions of Recent Crises

<abstract><title style='display:none'>Abstract</title>Decisions are taken by humans very often during professional as well as leisure activities. It is particularly evident during surfing the Internet: selecting web sites to explore, choosing needed information in search engine results or deciding which product to buy in an on-line store. Recommender systems are electronic applications, the aim of which is to support humans in this decision making process. They are widely used in many applications: adaptive WWW servers, e-learning, music and video preferences, internet stores etc. In on-line solutions, such as e-shops or libraries, the aim of recommendations is to show customers the products which they are probably interested in. As input data the following are taken: shopping basket archives, ratings of the products or servers log files.The article presents a solution of recommender system which helps users to select an interesting product. The system analyses data from other customers' ratings of the products. It uses clustering methods to find similarities among the users and proposed techniques to identify users' profiles. The system was implemented in Apache Mahout environment and tested on a movie database. Selected similarity measures are based on: Euclidean distance, cosine as well as correlation coefficient and loglikehood function.</abstract>

Clustering Algorithms in Hybrid Recommender System on MovieLens Data

<abstract><title style='display:none'>Abstract</title> Despite the fact that the notion of internal representation has - at least according to some - a fundamental role to play in the sciences of the mind, not only has its explanatory utility been under attack for a while now, but it also remains unclear what criteria should an explanation of a given cognitive phenomenon meet to count as a (truly, genuinely, nontrivially, etc.) representational explanation in the first place. The aim of this article is to propose a solution to this latter problem. I will assume that representational explanations should be construed as a form of mechanistic explanations and proceed by proposing a general sketch of a functional architecture of a representational cognitive mechanism. According to the view on offer here, representational mechanisms are mechanisms that meet four conditions: the structural resemblance condition, the action-guidance condition, the decouplability condition, and the error-detection condition.</abstract>

Explaining Cognitive Phenomena with Internal Representations: A Mechanistic Perspective

<abstract><title style='display:none'>Abstract</title>In this work, a system for the classification of liver dynamic contest- enhanced CT images is presented. The system simultaneously analyzes the images with the same slice location, corresponding to three typical acquisition moments (without contrast, arterial- and portal phase of contrast propagation). At first, the texture features are extracted separately for each acquisition mo- ment. Afterwards, they are united in one “multiphase” vector, characterizing a triplet of textures. The work focuses on finding the most appropriate features that characterize a multi-image texture. At the beginning, the features which are unstable and dependent on ROI size are eliminated. Then, a small subset of remaining features is selected in order to guarantee the best possible classification accuracy. In total, 9 extraction methods were used, and 61 features were calculated for each of three acquisition moments. 1511 texture triplets, corresponding to 4 hepatic tissue classes were recognized (hepatocellular carcinoma, cholangiocarcinoma, cirrhotic, and normal). As a classifier, an adaptive boosting algorithm with a C4.5 tree was used. Experiments show that a small set of 12 features is able to ensure classification accuracy exceeding 90%, while all of the 183 features provide an accuracy rate of 88.94%.</abstract>

Faculty of Computer Science, Bialystok University of Technology, Poland

Signal and Image Processing Laboratory (LTSI), University of Rennes 1, France

National Institute of Health and Medical Research (INSERM), University of Rennes 1, France

Computer-Aided Diagnosis of Liver Tumors Based on Multi-Image Texture Analysis of Contrast-Enhanced CT. Selection of the Most Appropriate Texture Features

<abstract><title style='display:none'>Abstract</title>Infertility is recognized as a major problem of modern society. Assisted Reproductive Technology (ART) is the one of many available treatment options to cure infertility. However, the efficiency of the ART treatment is still inadequate. Therefore, the procedure’s quality is constantly improving and there is a need to determine statistical predictors as well as contributing factors to the successful treatment. There is a concern over the application of adequate statistical analysis to clinical data: should classic statistical methods be used or would it be more appropriate to apply advanced data mining technologies? By comparing two statistical models, Multivariable Logistic Regression analysis and Artificial Neural Network it has been demonstrated that Multivariable Logistic Regression analysis is more suitable for theoretical interest but the Artificial Neural Network method is more useful in clinical prediction.</abstract>

Department of Statistics and Medical Informatics, Medical University of Bialystok, Poland

Department of Gamete and Embryo Biology, Institute of Animal Reproduction and Food Research of Polish Academy of Sciences, Olsztyn, Poland

Shore Institute for Reproductive Medicine, Lakewood, NJ, USA

Comparison of Artificial Neural Networks and Logistic Regression Analysis in Pregnancy Prediction Using the In Vitro Fertilization Treatment

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Studies in Logic, Grammar and Rhetoric

The Journal of University of Bialystok

 The journal Studies in Logic, Grammar and Rhetoric is published under the auspices of the Polish Society for Logic and Philosophy of Science, and along with Logic and...

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 The journal Studies in Logic, Grammar and Rhetoric is published under the auspices of the Polish Society for Logic and Philosophy...