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Copyright of Diametros: An Online Journal of Philosophy is the property of Diametros: An Online Journal of Philosophy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We submitted this paper to the special issue, "Four Decades of Rough Set Theory: Achievements and Future." We have researched a theory and an execution tool for rule generation from a Deterministic Information System (DIS) and a Non-deterministic Information System (NIS). We developed the NIS-Apriori algorithm, which combines the rough sets-based concept and the Apriori algorithm, for rule generation from NIS. We term this research series as a Rough set Non-deterministic Information Analysis (RNIA). In the first half of this paper, we describe the framework of RNIA and its execution environment, as well as the results we achieved. Then, later in this paper, we enumerate various applications of RNIA, such as detection of data dependencies, decision support, estimation and completion of missing values, the problem of learning DIS from NIS, and generation of rules from non-tabular and multiple heterogeneous data sets. They are our current and prospective subjects. RNIA's capabilities can lead to several developments. • Our past research on RNIA is reviewed with its execution videos. • Attribute dependency (or feature selection) analysis using the obtained rules is studied. • Solutions to Missing value imputation and Machine Learning by Rule Generation (MLRG) are presented with their execution videos. • A Descriptor-based Information System (DbIS) for rule generation from non-tabular data sets is studied. [ABSTRACT FROM AUTHOR]

[Display omitted] • New technique on recurrent neural network models to predict the conditions in hybrid-digital model of cardiovascular system. • Novel approach to combination of data from a laboratory model and neural network models to correlate the parameters of the cardiovascular system. • Presentation of possible application of the unique hybrid-digital model of cardiovascular system. End-systolic elastance of the left ventricle along with the waveforms of pressure and volumetric blood flow in particular sectors of the circulatory system are of importance in diagnosing various problems like dilated cardiomyopathy, left-ventricular hypertrophy, pulmonary hypertension, or ischemic heart disease. The objective of the paper is to broaden the spectrum of available methods to estimate those parameters since currently accessible techniques are often costly or troublesome. Six models have been developed − three of them estimate end-systolic elastance, two perform regression of volumetric blood flow, and one predicts blood pressure. Training datasets have been collected applying the unique hybrid-digital model. The input of the designed models consists of two or three different waveforms representing pressure and volumetric blood flow in particular areas, including heart ventricles, atria, and pulmonary vessels, in addition to the heart rate value. The basis of each model comprises bidirectional Long Short-Term Memory layers along with the dropout and feed-forward layers. Models that estimate end-systolic elastance achieved various accuracy. One of them performed exceptionally well since the absolute error did not exceed 0.169 m m H g c m 3 which is a negligibly small value. The root-mean-square error (RMSE) of the model predicting pressure waveform reached 0.165 m m H g in the worst case. Regression of the volumetric blood flow resulted in 6.062 c m 3 s worst-case RMSE for the model focusing on the pulmonary valve and 15.979 c m 3 s for pulmonary veins model. Computed results, especially those of the models estimating end-systolic elastance, indicate that it is possible to utilize neural networks to estimate those parameters with sufficient accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Socjologii Jakościowej is the property of Redakcja Przegladu Socjologii Jakosciowej and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Zircon U-Pb SIMS dating combined with in-context (in thin section) monazite and xenotime U + Th-total Pb dating was used to clarify the Palaeozoic evolution of the 'cold' Chopok granite (Nízke Tatry Mountains, Slovakia). Four distinct zircon, monazite and xenotime age domains testify to a prolonged evolution from igneous formation to multi-stage metasomatism and hydrothermal overprinting. The geological interpretation of age patterns from 'cold' granites, expected to have low zircon saturation temperatures (<800 °C) and relatively high amounts of zircon inheritance, requires special care, especially for what concerns proper attribution of zircon inheritance and igneous growth ages. These issues can be resolved using zircon saturation temperatures (T Zrn) as proxy for the amount of zircon inheritance in combination with the temperature differences between T Zrn and the granite solidus. In this respect, the Chopok granite is an atypical 'cold' granite. Due to T Zrn being substantially lower (ca. 80 °C ± 50 °C) than the granite solidus temperature, practically no zircon inheritance was found. The zircon age data indicates that the Chopok granite is a product of an Early Ordovician (475.8 ± 3.3 Ma) magmatic event, corresponding with the widespread Early Palaeozoic magmatism recorded throughout the European Variscan belt. This is further corroborated by phosphate mineral ages. The post-magmatic activity recorded in the U-Pb systematics of zircon and phosphates overgrowths can be related to the different phases of the evolution of the Variscan orogen: Early Carboniferous (ca. 352 Ma) metasomatism documents the main Variscan orogenic event, whereas the Permo-Triassic age (ca. 255 Ma) reflects thermo-tectonic activity associated with large-scale crustal extension, contemporaneous with the initial continental leading to the break-up of Pangea. Unlabelled Image • 'Cold' - 'hot' granite classification is not ubiquitously valid. • The Chopok granite is an atypical 'cold' granite in showing little inheritance. • The Chopok granite formation is Early Ordovician not Carboniferous. [ABSTRACT FROM AUTHOR]

In the Polish literature on the subject, prostitution is analyzed from various theoretical perspectives, but, first of all, from the perspective of social pathology. This approach makes the researchers focus mainly on the social maladjustment of women providing sex services and the reasons for their violation of the normative order. In my ethnographic research conducted in escort agencies in Poland, I was willing to go beyond this narrow outlook. I have adapted an interactionist perspective to analyze the escort agencies as organizations where intense interactions between employees, as well as employees and clients, take place, the sex work process is organized, and the meanings of prostitution are negotiated. I conducted the analysis according to the procedures of the grounded theory methodology. It allowed me to see and describe such processes as: (re)defining the situation of providing sex services from vice to work, sex work as a collective action, performing sex work, secondary socialization for sex work. The adaption of an interactionist perspective opens some new directions for analysis, which could help to understand the phenomenon of women getting involved in and continuing to provide sex services for a long time. [ABSTRACT FROM AUTHOR]

Copyright of Studia Socjologiczne is the property of Studia Socjologiczne and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Machine learning methods for the identification of child sexual abuse materials (CSAM) have been previously studied, however, they have serious limitations. Firstly, the training sets used to train the appropriate machine learning algorithms were not previously annotated by a forensic expert in anthropology. Secondly, previously presented solutions have rarely used models trained using real pornographic content involving children. Thirdly, previous studies have not presented a detailed justification for the classification decisions made, which is important due to the recent guidelines of the European Commission (Artificial Intelligence Act). The aim of the study was to train convolution neural networks (CNNs) using expert-labelled CSAM images and thereby identify the elements of the body and/or the environment that are critical for classifications by the neural network. To train and evaluate machine learning models, we used 60,000 images equally divided into four classes (CSAM images, images displaying sexual activity involving adults, images of people without sexual activity, and images not containing people). We used four neural network architectures: MobileNet, ResNet152, xResNet152 and its modification ResNet-s, designed for the purpose of research. The trained models provided high accuracy of classifying CSAM images: xResNet152 (F1 = 0.93, 92,8%), xResNet-s (F1 = 0.93, 93,1%), ResNet152 (F1 = 0.90, 91,39%), MobileNet (F1 ranged from 0.85 to 0.87, accuracy ranged from 86% to 87%). The results of the conducted research suggest that using expert knowledge (in sexology and anthropology) significantly improved the accuracy of the models. In regard to further anthropological analysis, the results indicate that the breasts, face and torso are crucial areas for the classification of pornographic content with children's participation. Results suggests that the ResNet-s neural network may be a reliable tool for clinical work and to support the work of experts witnesses in the field of anthropology. The study design received a positive opinion of the Ethics Committee of the Faculty of Mathematics, Informatics and Mechanics of the University of Warsaw. The clinical material was used for research purposes with the consent of the relevant prosecutor's offices. Authors provided free version of Windows application to classify CSAM for forensic experts, policemen and prosecutors at the OSF repository (DOI: 10.17605/OSF.IO/RU7JX). • Machine learning is believed to be the best solution for CSAM identification. • The machine learning models cannot replace human, but it can assist their work. • Neural networks are not fully explainable. • Using expert knowledge improves the explainability of the machine learning models. [ABSTRACT FROM AUTHOR]

Making women's bodies accessible to men in the commercial context is related to specific ways of experiencing it. The purpose of the article is to discuss the category of a non-present, selectively present, and present body, which refers to ways in which female sex workers experience their bodies during commercial sex acts. There will also be conditions listed that correspond to the occurrence of each of these categories. The article is based on qualitative data (mainly unstructured interviews), which were analyzed in accordance with the procedures of grounded theory methodology. [ABSTRACT FROM AUTHOR]

Copyright of Pediatric Endocrinology, Diabetes & Metabolism is the property of Termedia Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Socjologii Jakościowej is the property of Redakcja Przegladu Socjologii Jakosciowej and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)