Nature Of Categories Research Articles

Examining barriers and reasons for sport retirement in women's soccer: A qualitative study

The present research aimed to 1) examine the barriers that interfere with the progression of women's soccer and 2) analyze adult women's reasons for abandoning the practice of federated soccer. For this purpose, a qualitative methodology, with 14 semi-structured interviews of female national category soccer players, was used. The results of the inductive content analysis suggested that the players' main reasons for quitting sports were incompatibility or lack of time, lack of group cohesion within the sports context, and individual demotivation. Knowledge of these results may be of great interest to the sport environment. Thus, the people in charge could promote different strategies to improve sports and personal situations.

Clustering uncertain overlapping symptoms of multiple diseases in clinical diagnosis

In various fields, including medical science, datasets characterized by uncertainty are generated. Conventional clustering algorithms, designed for deterministic data, often prove inadequate when applied to uncertain data, posing significant challenges. Recent advancements have introduced clustering algorithms based on a possible world model, specifically designed to handle uncertainty, showing promising outcomes. However, these algorithms face two primary issues. First, they treat all possible worlds equally, neglecting the relative importance of each world. Second, they employ time-consuming and inefficient post-processing techniques for world selection. This research aims to create clusters of observed symptoms in patients, enabling the exploration of intricate relationships between symptoms. However, the symptoms dataset presents unique challenges, as it entails uncertainty and exhibits overlapping symptoms across multiple diseases, rendering the formation of mutually exclusive clusters impractical. Conventional similarity measures, assuming mutually exclusive clusters, fail to address these challenges effectively. Furthermore, the categorical nature of the symptoms dataset further complicates the analysis, as most similarity measures are optimized for numerical datasets. To overcome these scientific obstacles, this research proposes an innovative clustering algorithm that considers the precise weight of each symptom in every disease, facilitating the generation of overlapping clusters that accurately depict the associations between symptoms in the context of various diseases.

Exploring the categorical nature of colour perception: Insights from artificial networks

The electromagnetic spectrum of light from a rainbow is a continuous signal, yet we perceive it vividly in several distinct colour categories. The origins and underlying mechanisms of this phenomenon remain partly unexplained. We investigate categorical colour perception in artificial neural networks (ANNs) using the odd-one-out paradigm. In the first experiment, we compared unimodal vision networks (e.g., ImageNet object recognition) to multimodal vision-language models (e.g., CLIP text-image matching). Our results show that vision networks predict a significant portion of human data (approximately 80%), while vision-language models account for the remaining unexplained data, even in non-linguistic experiments. These findings suggest that categorical colour perception is a language-independent representation, though it is partly shaped by linguistic colour terms during its development. In the second experiment, we explored how the visual task influences the colour categories of an ANN by examining twenty-four Taskonomy networks. Our results indicate that human-like colour categories are task-dependent, predominantly emerging in semantic and 3D tasks, with a notable absence in low-level tasks. To explain this difference, we analysed kernel responses before the winner-takes-all stage, observing that networks with mismatching colour categories may still align in underlying continuous representations. Our findings quantify the dual influence of visual signals and linguistic factors in categorical colour perception and demonstrate the task-dependent nature of this phenomenon, suggesting that categorical colour perception emerges to facilitate certain visual tasks.

The Impact of Computational Power on Environmental Sustainability – A Comparative Study Involving Two Categories of National- Level Computing Infrastructure

The Impact of Computational Power on Environmental Sustainability – A Comparative Study Involving Two Categories of National- Level Computing Infrastructure

Os Descaminhos da Dialética Hegeliana entre Lógica e Natureza

The aim of this study is to investigate the relationship between Logic and Nature within the Hegelian system. Our focus lies on the status of the categories of nature: are they merely a redoubling of the equivalent logical categories or is there a substantial difference between them? First, we analyze the secondary literature on the subject and conclude that it falls short of the complexity of the problem. Secondly, we make a detailed comparison between the Philosophy of Nature and the Science of Logic and hypothesize that the natural categories presuppose logic as a standard, that is, a kind of ruler that determines what the ideal development would be; however, as nature fails to faithfully reproduce this standard, its categories deviate considerably from the logical categories.

Green Synthesis of Clay/rGO Composite for Sensitive Detection of Para Nitrophenol in the Environment

AbstractNitrophenols (e. g., para nitrophenol), although they have beneficial properties, their residuals are injurious to the environment owing to their high lethal potential for many categories of nature (e. g. animals, humans, plants, etc.), which require their monitoring. In this paper, a new Clay/green reduced graphene oxide composite (Clay/rGO) was efficaciously synthesized and utilized as an excellent modifier for carbon paste electrode (CPE) for the electro‐analytical determination of paranitrophenol (PNØ). The electrochemical futures and reduction of PNØ at the surface of the as‐prepared Clay/rGO˧CPE have been executed using DPV differential pulse voltammetry (DPV), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The use of the EIS provided that the Clay/rGO˧CPE facilitate the electron exchange process. By using the DPV technique in phosphate buffer (PB) under biological pH (7) (PB_7) the prepared monitor exhibited an excellent linearity relationship in the concentration ranges from 1.0 to 1000.0 μM with a detection limit (DL=3×σ/P) of 0.16 μM and a quantification limit of (QL=10×σ/P) of 0.54 μM. The Clay/rGO˧CPE offered high selectivity and a satisfactory concert in the electroanalytical sensing of PNØ in wastewater sample.

Unveiling the health implications of working hours in the Indonesian workforce

This research aims to evaluate and compare the impact of working hours on the physical and psychological well-being of workers before and during the COVID-19 pandemic, where people were forced to work from home. While existing studies primarily concentrate on the physical and mental health of office workers, there is a notable gap in understanding how changes in work hours affect individuals in various professional sectors. This study seeks to address this gap by conducting a comprehensive investigation across a diverse range of employment, encompassing white collar, gray collar, and blue collar occupations. Using datasets from Indonesia's National Labor Survey (Sakernas) in 2019 and 2020, the study focuses on the working-age population engaged in various occupations, including employees, casual agricultural workers, and casual non-agricultural workers. Further categorization involves classifying individuals into white collar, gray collar, and blue collar segments. The total number of individuals analyzed was 215,607 in 2019 and 201,077 in 2020. Employing an ordered logistic regression method due to the categorical nature of the dependent variable, the study reveals consistent findings regarding the impact of working hours on health across the years 2019 and 2020. Extended work hours correlate with improved health outcomes, indicating better health for those working longer, while individuals with fewer hours exhibit lower chances of achieving good health. In 2019, occupational status significantly influences worker health, with gray and blue collar workers having lower probabilities of better health compared to white collar workers. However, this occupational effect on health is absent in 2020.

Exemplar-based ingroup projection: The superordinate national category is associated more strongly with ingroup than outgroup political leaders

We studied mental representations of social categories in the context of political groups nested within national identities. Extending previous works derived from the Ingroup Projection Model, which had investigated category representations based on prototypical attributes, we examined category representations based on prototypical exemplars, focusing on group leaders. We hypothesized that the mental representation of the superordinate, national, category is more strongly associated with the mental representation of ingroup political leaders than outgroup political leaders. We tested our hypothesis in three preregistered experiments, looking at two different national-political contexts and using diverse methods. In Studies 1 (N = 145) and 2 (N = 103), both conducted in Israel, we found that participants explicitly associated the national category with leaders of their own political camp more than with leaders of the rival political camp. In Study 2, we further found that participants were more likely to falsely remember that ingroup relative to outgroup political leaders were paired with the national category (versus their political wing). In Study 3 (N = 381), conducted in the USA, we found using an implicit measure of association (ST-IAT) that Democrats and Republicans sorted stimuli, representing political leaders, faster when the national category (represented by American symbols) was paired with the ingroup rather than the outgroup category. Implications for theoretical accounts of ingroup projection, as well as for the understanding of political polarization and intergroup leadership, are discussed.

Factors influencing vowel adaptation in English loanwords in Korean

Abstract This study explores the extent to which perceptual and other factors (i.e., orthography and standardization) affect vowel adaptation in English loanwords in Korean. It also examines whether perceptual variability gives rise to adaptation variability, and it further addresses whether the degree of perceptual influence in vowel adaptation is different from that in consonant adaptation. Data on Korean listeners’ perceptual mapping patterns for English vowels were collected in an English-to-Korean vowel category mapping experiment and compared to the patterns in a loanword database. The results indicate that perceptual factors have a great impact on the adaptation of English vowels into Korean, in line with de Jong and Cho’s (de Jong, Kenneth & Mi-Hui Cho. 2012. Loanword phonology and perceptual mapping: Comparing two corpora of Korean contact with English. Language 88. 341–368) findings for the adaptation of English consonants into Korean. Consequently, factors such as orthography and standardization are viewed as deviations from these perceptual influences. The impact of perceptual adaptation is, however, rather limited because the correlation between perceptual mappings and loanword mappings is less robust for English vowel adaptation than for English consonant adaptation possibly due to the less categorical nature of vowels relative to consonants. Additionally, the results show that increased strength of modal perceptual mappings is related to less loanword variability in vowel adaptation.

Re-Orientations: Spain and Jerusalem in the Longue Durée

ABSTRACT This article provides a brief overview of Spain’s historical ties to Jerusalem, arguing that a Mediterranean approach to Spanish Jerusalem encourages us to resituate the Holy City in both space and time as a key location in the articulation of Spanish imperial and national identity. By recovering the fundamental Mediterraneanness of Spanish entanglements with Jerusalem, scholars are also obliged to recognize at once the complex, interdependent, porous borders through which the categories of empire and nation are regularly negotiated, and the profoundly transtemporal resonance of those configurations, which continue to matter today.

Identifying Medicine Shortages With the Twitter Social Network: Retrospective Observational Study.

Early identification is critical for mitigating the impact of medicine shortages on patients. The internet, specifically social media, is an emerging source of health data. This study aimed to explore whether a routine analysis of data from the Twitter social network can detect signals of a medicine shortage and serve as an early warning system and, if so, for which medicines or patient groups. Medicine shortages between January 31 and December 1, 2019, were collected from the Dutch pharmacists' society's national catalog Royal Dutch Pharmacists Association (KNMP) Farmanco. Posts on these shortages were collected by searching for the name, the active pharmaceutical ingredient, or the first word of the brand name of the medicines in shortage. Posts were then selected based on relevant keywords that potentially indicated a shortage and the percentage of shortages with at least 1 post was calculated. The first posts per shortage were analyzed for their timing (median number of days, including the IQR) versus the national catalog, also stratified by disease and medicine characteristics. The content of the first post per shortage was analyzed descriptively for its reporting stakeholder and the nature of the post. Of the 341 medicine shortages, 102 (29.9%) were mentioned on Twitter. Of these 102 shortages, 18 (5.3% of the total) were mentioned prior to or simultaneous to publication by KNMP Farmanco. Only 4 (1.2%) of these were mentioned on Twitter more than 14 days before. On average, posts were published with a median delay of 37 (IQR 7-81) days to publication by KNMP Farmanco. Shortages mentioned on Twitter affected a greater number of patients and lasted longer than those that were not mentioned. We could not conclusively relate either the presence or absence on Twitter to a disease area or route of administration of the medicine in shortage. The first posts on the 102 shortages were mainly published by patients (n=51, 50.0%) and health care professionals (n=46, 45.1%). We identified 8 categories of nature of content. Sharing personal experience (n=44, 43.1%) was the most common category. The Twitter social network is not a suitable early warning system for medicine shortages. Twitter primarily echoes already-known information rather than spreads new information. However, Twitter or potentially any other social media platform provides the opportunity for future qualitative research in the increasingly important field of medicine shortages that investigates how a larger population of patients is affected by shortages.

Planetary justice: a systematic analysis of an emerging discourse

ABSTRACT Justice concerns have been central to contemporary social and ecological debates for decades but have only recently made inroads into the Earth system centric discourses on the Anthropocene and planetary boundaries. Our focus here is the emerging discourse on planetary justice which has aimed to be a corrective to this lacuna. Our goals in this paper are to delineate the general parameters and novel contributions of planetary justice while also recognizing the emergent variability within this discourse. In order to accomplish these goals we analyze the discourse through three interrelated analytical themes: First, how approaches to planetary justice envision scope across different human practices and categories of humanity and nature. Second, how they envision scale across space and time. Third, how they envision the ecosocial purpose of planetary justice.

Ideological Hatred and the New Social Cleavages

The war in Ukraine pushed a large part of the planet to reformulate its narratives, its arguments and rationalities to accommodate an impossible reality: a real, hot war in the European mainland where everybody had already embraced the mantra of a for-ever post-war-scenario. With the politicians re-using old and highly symbolical expressions, all of us were driven in the middle of a semantic turmoil. One year after, we may easily distinguish the opposite camps all around the world and the line between them drawn by the new, post-communist source of dissonances: the bare ideology covered in fluid, transparent inter-textual coats, as if the war itself were just a synthesis of history, geopolitics, religion, modernization and international relations altogether. However, beyond all these, there comes a well-known theory to seek its own updates: Julien Benda labeled three types of hatred, namely of race, class and nation. My claim is that this war in Ukraine added a full-fledged new category of ideological hatred, cutting across the above mentioned ones as if annulling their existence and subordinating all to the present commands of politics. I intend to explore these divisions, tracing a line to connect all four types while searching for the anatomy of the new (old) ghost: the ideological hatred, how it works with the sociological categories of race, class and nation encapsulating them to create new political subjects. The latter are the combating parts in this war and we may say that the war renovated the sociological division of roles through reconfiguring the players in the game.

Nonsyndromic Craniosynostosis Correlation Between Ethnicity, Race, and Pattern of Affected Suture Type: Meta-Analysis.

Previous studies have sought to analyze risk factors associated with craniosynostosis and while syndromic craniosynostosis is often linked to genetic mutations, the factors impacting nonsyndromic cases are less investigated. The aim of current meta-analysis is to evaluate the relationship between ethnicity and suture type in nonsyndromic craniosynostosis patients. The search term "craniosynostosis [Title/Abstract] AND (race [Title/Abstract] OR ethnicity [Title/Abstract])) NOT (syndrome [Title/Abstract])" was used to search the PubMed, Cochrane, and MEDLINE databases. Analyses were conducted separately for each racial and ethnic group for each suture type cohort. Odds ratios were conducted for each suture cohort and confounders were adjusted using linear mixed-effect models. Because of the homogeneity of the populations and categorical nature of the classification, binary logistic regression was run on aggregate data. The literature search yielded 165 articles. After reviewing titles, abstracts, and manuscript contents of these articles, 5 studies were ultimately included in a meta-analysis. Studies with missing data for a particular cohort or variable were excluded from the respective analysis. Hispanic children had higher odds of sagittal suture involvement (OR: 1.53, P <0.001), whereas Asian had coronal suture (OR: 2.47, P <0.001). Both Asian and African American children had significantly lower odds of sagittal suture involvement (OR: 0.50, P <0.001 and OR: 0.7, P =0.04, respectively). The relationship between ethnicity and craniosynostosis has been suggested as a risk factor, but without definitive conclusion. Present meta-analysis findings demonstrated association between ethnicity and suture type, however further research with larger scale and geographically varied data is warranted.

Prospects for Multicultural Encounters and Identification Processes - Insights from Case Studies among Migrants in Brazil

This paper analyses how multicultural encounters have shaped groupism processes and notions of identities among migrants in contemporary Brazil. To do that, the paper contextualises the particular sense of hybridity built in the Brazilian multiculturalism approach, and how it enabled certain encounters and senses of belonging beyond nationhood-oriented groupism and sometimes beyond ethnicity-oriented groupism. The paper brings insights from a fieldwork study held among a hundred migrants living in the two main charity shelters in Sao Paulo-Brazil, demonstrating how these individuals operate different senses of belonging through encounters according to different aims. It explains how they operate their belonging to migrant categories (and the vulnerabilities associated with it) for claiming for dignity, rights and access to basic services in Brazil. The paper also explains how these migrants operate other belongings beyond such migrant status and nationality categories (such as belongings related to gender, age, language, profession, religion, etc.) in other encounters with different aims and dynamics. Overall, the paper also aims to contribute to scrutinising the reified concept of 'group' which dominates mainstream literature, indicating how the perspective of encounters might allow us to identify more fluid and spontaneous categories which seem to better comprehend contemporary multicultural relations.

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data

BackgroundMachine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios.MethodsWe compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning.ResultsDepending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively.ConclusionsBy illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

Analyzing Macroeconomic Indicators that May Affect Economic Growth in Sub-Saharan African Countries: A Panel Data Analysis in the Context of Income Level Classification (1990-2019)

The purpose of the study was to ascertain whether the export-import coverage ratio (EXIM), the income of natural resources (NATR), labour force participation rate (LFPR), and foreign direct investment (FDI) had a positive or negative impact on economic growth for 34 Sub-Saharan African countries using data from 1990 to 2019. The change in Gross Domestic Product Per Capita (%) is used in the study as a proxy for the economic growth variable, and Sub-Saharan African nations were categorized based on the United Nations' income classification system to create more homogeneous groups and consequently more accurate analysis results. To do this, 34 Sub-Saharan African nations were divided into three income categories: lower-middle-income, upper-middle-income, and low-income. The income categories established by the UN were considered while drawing this distinction. This divide led to the analysis of 18 low-income nations, 12 lower-middle-income countries, and 4 upper-middle-income countries. One of the dynamic panel data analysis techniques, the two-step system GMM panel data analysis, was used as the econometric analysis approach. According to the estimations, FDI in lower-middle-income sub-Saharan African countries was statistically significant and inversely related to economic growth; it was observed that the coverage ratio of exports to imports has a statistically significant and linear relationship. None of these independent variables were found to influence economic growth in low-income sub-Saharan African countries. There is a statistically significant correlation between the LFPR and NATR and economic development in the upper-middle income category of nations analyzed. As a result, the influence of factors varied and fluctuated on economic growth based on the income levels of different groups.

Effects of a Physical Training Program on Cognitive and Physical Performance and Health-Related Variables in Professional esports Players: A Pilot Study

The present study focused on the effects of a physical training program on physical- and psychological-related variables in professional esports players. Five professional League of Legends (LOL) players belonging to the highest national category participated in this study. Data were obtained before and after a 5 h virtual training session (acute), as well as before and after an 8-week intervention period, focused on decreasing the impact of fatigue on players’ health and performance. The results showed that a complete virtual training session influences their performance, decreasing jump height and joint mobility (p &lt; 0.01), as well as increasing perceived physical and cognitive exertion by 76.9% (p &lt; 0.01) and 166.67% on the “Rating of Fatigue” scale (p = 0.002). Moreover, the intervention was able to reduce the impact of fatigue (30.8% and 43.3% reduction in cognitive and overall fatigue, respectively, p &lt; 0.05), improving, at the same time, the amount of muscle mass by 2%, jumping ability by 9.8% to 21%, and strength levels in various exercises by 63% to 173% (p &lt; 0.01). The implementation of a physical training program is capable of reducing the players’ fatigue perception, improving their physical conditioning and health status, and decreasing the injury risk.

Spatiotemporal Distribution Characteristics and Inventory Analysis of Near-Road Traffic Pollution in Urban Areas

Vehicle emissions belong to the category of near-surface sources, occur close to human activity areas, and pose a greater threat to human health than other anthropogenic pollution sources. Furthermore, the study of the spatiotemporal characteristics of near-road traffic pollution is of great significance to urban and regional ambient air quality management, and is also an important basis for vehicle emission inventories, as well as the assessment of ambient air impact. Most previous studies have analyzed the spatiotemporal characteristics of hydrocarbons (HCs), carbon monoxide (CO), nitrogen oxides (NOx), and carbon dioxide (CO2) in urban vehicle emissions over a certain time, without considering the synergistic effect of mobile source particulate matter, NOx, and volatile organic compounds (VOCs). In this study, we analyze the composition of vehicles with different emission standards from road mobile sources in Anqing City, China. National category III and IV vehicles are the main contribution sources of various pollutants, accounting for more than 60% of emissions. Although national category I and II vehicles accounted for less than 1% of the total number of vehicles, their contribution to emissions cannot be ignored, especially for CO and HCs, the contribution of which from such vehicles can reach about 7%. This is mainly due to the low level of pollution control arising from the larger emission factor and greater age of these vehicles. Furthermore, eliminating old cars and increasing the proportion of national category VI vehicles can effectively reduce vehicle pollutant emissions. In terms of the spatiotemporal distribution characteristics, highways around urban areas are also the main sources of heavy vehicles, and the emission intensity of these pollutants is also higher on national roads and highways surrounding urban areas. In addition, the presence of m/p-xylene and toluene solvent-using species is detected, which indicates that petrol vehicle emissions, LPG and petrol volatilization, and solvent-using sources contribute significantly to ozone formation in the ozone pollution process. Comparing weekdays and non-weekdays, the PM2.5 peaks on non-weekdays are significantly higher than those on weekdays, and there is no “weekend effect”, which indicates that traffic emissions have little influence on PM2.5 emissions, and may be related to energy use and industrial pollution. Overall, this study strengthens the understanding of the relationship between emissions, traffic volumes, and vehicle types on spatial and temporal scales, and emphasizes the need for further investigation and comprehensive measures to mitigate pollution from these emissions.

The Subterranean Unsettling of Science, Race, and Religion: Obeah, Petroleum Geology, and Risk in Trinidad

Abstract When scholars have compared “African traditional religion” and “Western science,” they have often treated the terms of this comparison as racialized unitary entities, which are either radically different or somewhat similar (even as Western categories of rationality or nature remain the basis for these comparisons). This essay unsettles these assumptions by focusing on practices that are called “science” in the fields of both petroleum geology and Afro-Caribbean religion. Based on long-term ethnographic research in Trinidad, arguably the world’s oldest site of commercial oil extraction, I show how internal differences between those involved in “petroleum science” and “African religion” reveal a spectrum of meanings for the word “science” centered on relations to risk. At one end of this spectrum, science conveyed ideals of stable tradition that de-risked claims to knowledge for energy sector specialists intent on securing foreign investment or for “Yorubacentric” lineages of African religion centering initiation-based authority. At this spectrum’s other end, “science” foregrounded the risks of accessing hard-to-perceive forces in petroleum exploration or “spiritual work.” By focusing on heterogeneous practices rather than cultural essences or ideals of rationality, I show how the ethical implications of “science” depend on differing experiences of the risks of working with subterranean powers. While petroleum surveys at my field site in Trinidad required embodied risks by laborers, geologists backgrounded these contexts of power, representing the risks of their work as a problem of scientific accuracy. Afro-Trinidadian spiritual workers, in contrast, foregrounded the embodied risks of science as the ground of ethical practice.