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Preschool age is a golden period for the emergence of executive functions (EFs) that, in turn, predict learning and adaptive behavior throughout all life. The study was aimed to identify which EFs measures significantly explained the learning prerequisites and the mediation role of self-regulatory and executive behavior recorded in structured or free settings. One hundred and twenty-seven preschoolers were remotely assessed by standardized tests of response inhibition, working memory, control of interference, and cognitive flexibility. Teachers provided a global measure of learning prerequisites by an observational questionnaire. Self-regulatory behavior during the assessment was evaluated by a rating scale filled by the examiners. Executive function behavior in daily life was measured by a questionnaire filled by parents. Accuracy in tasks of response inhibition and working memory explained about 48% of the variability in learning prerequisites while response speed and accuracy in the control of interference and in cognitive flexibility were not significant. EFs also had indirect effects, mediated by the child's self-regulatory behavior evaluated during the assessment but not in daily life. The results are interpreted with respect to the contribution of the main EF components to school readiness and the mediation of the child behavior as measured in structure contexts.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8617927 | PMC |
http://dx.doi.org/10.3390/children8110964 | DOI Listing |
Driven by eutrophication and global warming, the occurrence and frequency of harmful cyanobacteria blooms (CyanoHABs) are increasing worldwide, posing a serious threat to human health and biodiversity. Early warning enables precautional control measures of CyanoHABs within water bodies and in water works, and it becomes operational with high frequency in situ data (HFISD) of water quality and forecasting models by machine learning (ML). However, the acceptance of early warning systems by end-users relies significantly on the interpretability and generalizability of underlying models, and their operability.
View Article and Find Full Text PDFJ Chem Phys
September 2025
National Synchrotron Radiation Laboratory, State Key Laboratory of Advanced Glass Materials, Anhui Provincial Engineering Research Center for Advanced Functional Polymer Films, University of Science and Technology of China, Hefei, Anhui 230029, China.
Polymer density is a critical factor influencing material performance and industrial applications, and it can be tailored by modifying the chemical structure of repeating units. Traditional polymer density characterization methods rely heavily on domain expertise; however, the vast chemical space comprising over one million potential polymer structures makes conventional experimental screening inefficient and costly. In this study, we proposed a machine learning framework for polymer density prediction, rigorously evaluating four models: neural networks (NNs), random forest (RF), XGBoost, and graph convolutional neural networks (GCNNs).
View Article and Find Full Text PDFJ Exp Anal Behav
September 2025
Oslo Metropolitan University, Norway.
Go/no-go successive matching (GNG-matching) tasks are one of several procedures used to establish conditional discriminations. This study presents a systematic review aimed at comparing procedures and outcomes of empirical studies using GNG-matching tasks for the emergence of symmetry, transitive, and global equivalence relations in humans and non-humans. A total of 22 articles were analyzed-nine with nonhumans and thirteen with humans.
View Article and Find Full Text PDFChem Biol Interact
September 2025
School of Public Health, Ningxia Medical University, Yinchuan City, Ningxia Hui Autonomous Region, China; Key Laboratory of Environmental Factors and Chronic Disease Control, No.1160, The Street of Shengli, Xingqing District, Yinchuan, Ningxia Hui Autonomous Region, China. Electronic address: hmin81
Paraquat (PQ) is characterized by neurotoxicity. In daily life, PQ exposure mainly occurs through chronic and trace pathways, which induce progressive neuronal damage or neuronal synaptic loss. Previously, mitochondrial dysfunction was a critical underlying mechanism.
View Article and Find Full Text PDFEur Radiol Exp
September 2025
Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
In radiomics, features are often linked to biomarkers and are generally expected to be reproducible, as reproducibility is considered a prerequisite for developing predictive models in clinical applications. However, this perspective overlooks feature interactions and may underestimate the potential value of nonreproducible features. Through experiments simulating a test-retest scenario, we demonstrate that even non-reproducible features can contribute significantly to predictive performance.
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