Novel viewpoints have led to an understanding that good soccer performers are capable of continuous decision-making and performing excellent motor skills in a well-conditioned mental state. Our aims in this review were to (a) summarize the effects of different conditions and constraints on a soccer player's response and (b) identify potential training designs for varied soccer tasks from a multivariate perspective, emphasizing tactical training. We performed a systematic literature review according to PRISMA guidelines and identified multiple different player constraints, including model strategies for play, drills designed for varied conditions, and training regimens for the dimensions of the physical demands soccer players will face. The use of match-sized training spaces may improve physical fitness and collective tactical behavior, while smaller spaces may contribute to improving tactical behavior from micro-structures (e.g., 1 vs. 1). Pre-session exercises that accelerate the appearance of fatigue during training may help delay the onset of match fatigue and boost players' creativity. Pitch modifications (dimensions or boundary modifications), modification of game principles (defending strategies or team formations), and altering the number of players involved or coach instructions may contribute to different player improvements. Differential learning, as a non-linear pedagogy, may induce improvements in all dimensions, but especially in creative thinking.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1177/00315125211073404 | DOI Listing |
Int J Mol Sci
December 2024
Laboratory Adhesion and Inflammation (LAI), Inserm UMR 1067, Cnrs Umr 7333, Aix-Marseille Université UM 61, 13009 Marseille, France.
During the last decade, artificial intelligence (AI) was applied to nearly all domains of human activity, including scientific research. It is thus warranted to ask whether AI thinking should be durably involved in biomedical research. This problem was addressed by examining three complementary questions (i) What are the major barriers currently met by biomedical investigators? It is suggested that during the last 2 decades there was a shift towards a growing need to elucidate complex systems, and that this was not sufficiently fulfilled by previously successful methods such as theoretical modeling or computer simulation (ii) What is the potential of AI to meet the aforementioned need? it is suggested that recent AI methods are well-suited to perform classification and prediction tasks on multivariate systems, and possibly help in data interpretation, provided their efficiency is properly validated.
View Article and Find Full Text PDFEntropy (Basel)
November 2024
Sony Computer Science Laboratories, Tokyo 141-0022, Japan.
The symmetric Kullback-Leibler centroid, also called the Jeffreys centroid, of a set of mutually absolutely continuous probability distributions on a measure space provides a notion of centrality which has proven useful in many tasks, including information retrieval, information fusion, and clustering. However, the Jeffreys centroid is not available in closed form for sets of categorical or multivariate normal distributions, two widely used statistical models, and thus needs to be approximated numerically in practice. In this paper, we first propose the new Jeffreys-Fisher-Rao center defined as the Fisher-Rao midpoint of the sided Kullback-Leibler centroids as a plug-in replacement of the Jeffreys centroid.
View Article and Find Full Text PDFZdr Varst
March 2025
Angela Boškin Faculty of Health Care, Spodnji Plavž 3, 4270 Jesenice, Slovenia.
Aim: The aim of the study was to explore the experiences of patients with delivered healthcare in selected Slovenian hospitals.
Methods: A cross-sectional study was employed. A total of 1,748 patients participated.
Biostatistics
December 2024
Center for Applied Statistics, School of Statistics, Renmin University of China, No. 59 Zhongguancun Street, Beijing, 100872, P.R. China.
Previous studies have identified attenuated pre-speech activity and speech sound suppression in individuals with Schizophrenia, with similar patterns observed in basic tasks entailing button-pressing to perceive a tone. However, it remains unclear whether these patterns are uniform across individuals or vary from person to person. Motivated by electroencephalographic (EEG) data from a Schizophrenia study, we develop a generalized functional linear mixed model (GFLMM) for repeated measurements by incorporating subject-specific functional random effects associated with multiple functional predictors.
View Article and Find Full Text PDFBMC Public Health
January 2025
Society and Ageing Research Lab (SARLab), Vrije Universiteit Brussel, Brussels, Belgium.
Background: Due to a globally ageing population, the demand for informal caregivers is increasing. This study investigates the socio-demographic profile of informal caregivers in Belgium and assesses the relationship between informal care (intensity and care recipients) and mental health, considering potential moderators like education, age, and gender.
Methods: Using population-based data from the 2013 and 2018 waves of the Belgian Health Interview Survey (N = 14,661), we conducted multivariate (multinomial/ordinal) logistic and linear regression analyses to examine the socio-demographic profile of informal caregivers and their psychological distress, measured through the General Health Questionnaire (GHQ-12).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!