Deep learning-based air pollution analysis on carbon monoxide in Taiwan

Ecological Informatics, Journal Year: 2024, Volume and Issue: 80, P. 102477 - 102477

Published: Jan. 17, 2024

Global air pollution poses a threat to humanity. Specifically, CO directly affects cardiovascular and other organ tissues leads numerous chronic diseases major public health problems. The effective implementation of deep learning model for predicting variations in levels would enable the early formulation policies controlling pollution. In this study, seasonal gated recurrent unit (SGRU) model, which is time-series prediction was developed predict Taiwan. Atmospheric measurements from 2005 2021 were collected Environmental Protection Administration Taiwan preprocessed using Kalman filter achieve accurate forecasting. performance proposed SGRU compared with that autoregressive integrated moving average (ARIMA), ARIMA, exponential smoothing (ETS), Holt–Winters ETS, support vector regression, long short-term memory models terms mean absolute percentage error (MAPE) root square error. achieved lowest MAPE value 0.94, demonstrated its superior performance. construction an can assist government entities formulating social care strategies planning future control measures.

Language: Английский

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Predicting academic achievement from the collaborative influences of executive function, physical fitness, and demographic factors among primary school students in China: ensemble learning methods

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Jan. 23, 2024

Abstract Background Elevated levels of executive function and physical fitness play a pivotal role in shaping future quality life. However, few studies have examined the collaborative influences mental health on academic achievement. This study aims to investigate key factors that collaboratively influence primary school students' achievement from function, fitness, demographic factors. Additionally, ensemble learning methods are employed predict achievement, their predictive performance is compared with individual learners. Methods A cluster sampling method was utilized select 353 students Huai'an, China, who underwent assessments for The recursive feature elimination cross-validation identify Ensemble models, utilizing eXtreme Gradient Boosting Random Forest algorithms, were constructed based Bagging methods. Individual learners developed using Support Vector Machine, Decision Tree, Logistic Regression, Linear Discriminant Analysis followed by establishment Stacking model. Results Our findings revealed sex, body mass index, muscle strength, cardiorespiratory inhibition, working memory, shifting influencing students. Moreover, models demonstrated superior predicting among Conclusions results suggest recognizing sex differences emphasizing simultaneous development cognition well-being can positively impact warrant further attention, as they enable an accurate early warning system

Language: Английский

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Alterations of triple network dynamic connectivity and repetitive behaviors after mini-basketball training program in children with autism spectrum disorder

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 21, 2025

Physical exercise has been demonstrated to effectively mitigate repetitive behaviors in children with autism spectrum disorder (ASD), but the underlying dynamic brain network mechanisms are poorly understood. The triple model consists of three networks that jointly regulate cognitive and emotional processes is considered be core aberrant manifestations ASD. This study investigated whether a mini-basketball training program (MBTP) could alter connectivity network. 28 male ASD were scanned twice resting-state functional MRI assessed for using behavior scale (RBS-R). 15 group participated 12-week MBTP, while 13 control maintained their regular routines. feature Dynamic independent component analysis (dyn-ICA) its ability capture rate change between regions. In this study, it was specifically employed examine both groups. Compared group, exhibited distinct patterns two networks: Network 1 involved cross-network changes within network, 2 pertained alterations default mode Furthermore, reduction RBS-R Total score observed reflecting improvements self-injurious restricted behavior. Correlation revealed amelioration associated enhanced parts These findings suggest MBTP can improve linked connectivity.

Language: Английский

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Classical materials for sensors

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 23 - 39

Published: Jan. 1, 2025

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Effects of mini-basketball training program on social communication impairments and regional homogeneity of brain functions in preschool children with autism spectrum disorder

BMC Sports Science Medicine and Rehabilitation, Journal Year: 2024, Volume and Issue: 16(1)

Published: April 24, 2024

Abstract Background Social communication impairments (SCI) is a core symptom of autism spectrum disorder (ASD) and marked by challenges in social interaction. Although physical exercise has been shown to improve SCI, this finding not supported comprehensive scientific evidence. Existing research established strong link between the SCI children with ASD abnormalities regional homogeneity (ReHo). Therefore, investigating effects on Reho patients may help elucidate neurological mechanisms involved. Methods The present study included 30 preschool diagnosed ASD, 15 participants each group (experimental control). experimental underwent 12-week mini-basketball training program (MBTP) based routine behavioral rehabilitation, while control only received rehabilitation. Responsiveness Scale-Second Edition (SRS-2) was employed assess both groups. Resting-state functional magnetic resonance imaging technology used evaluate ReHo Results After MBTP, significant × time interactions were observed groups total SRS-2 scores ( F = 14.514, p < 0.001, η 2 0.341), as well domains cognition 15.620, 0.358), 12.460, 0.01, 0.308), autistic mannerisms 9.970, 0.263). No statistical difference found for awareness subscale motivation interaction (all > 0.05). exhibited increased right Cerebellum_Crus1 parahippocampal gyrus, coupled decreased left middle frontal gyrus (orbital part), superior (dorsolateral), postcentral parietal gyrus. Furthermore, decrease positively correlated changes behaviors Conclusions Our underscores effectiveness MBTP ameliorating among ASD. Trial registration trial retrospectively registered Chinese Clinical Registry (ChiCTR1900024973; August 5, 2019).

Language: Английский

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Using interpretable machine learning methods to identify the relative importance of lifestyle factors for overweight and obesity in adults: pooled evidence from CHNS and NHANES

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Nov. 1, 2024

Overweight and obesity pose a huge burden on individuals society. While the relationship between lifestyle factors overweight is well-established, relative contribution of specific remains unclear. To address this gap in literature, study utilizes interpretable machine learning methods to identify importance as predictors adults.

Language: Английский

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Diagnosing autism severity associated with physical fitness and gray matter volume in children with autism spectrum disorder: Explainable machine learning method

Complementary Therapies in Clinical Practice, Journal Year: 2023, Volume and Issue: 54, P. 101825 - 101825

Published: Dec. 30, 2023

Language: Английский

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Aspectos del Trastorno Espectro Autista Relevantes para la Psicopedagogía: Una Revisión Sistemática

Ciencia Latina Revista Científica Multidisciplinar, Journal Year: 2024, Volume and Issue: 7(6), P. 5821 - 5834

Published: Jan. 10, 2024

El trastorno del espectro autista es un conjunto de características que modifican el comportamiento una persona a nivel social y comunicativo, con patrones atípicos funcionamiento comportamiento. Se desarrolla revisión sistemática enfocada en destacar los aspectos relevantes conocer psicopedagogía, responde rango temporalidad para las publicaciones últimos cinco años. Para la recolección información se utilizó base datos SCOPUS, través Science Direct, donde luego depuración resultados proyectan doce análisis, cuales, abordan tres claves; clínicas, repercusión contexto, avances modelos intervención aprendizaje. concluye tiene repercusiones desarrollo formación aprendizaje, sin embargo, detección oportuna, terapias rehabilitación, incorporación trabajo distintos niveles académicos apoyo tecnológicos facilitan su inserción contextos sociales.

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Effects of mini-basketball training program on social communication impairments and salience network in preschool children with autism spectrum disorder

International Journal of Developmental Disabilities, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 14

Published: Aug. 24, 2024

Objectives This study aims to explore the impact of a 12-week mini-basketball training program (MBTP) on social communication impairments and salience network in preschool children with autism spectrum disorder (ASD), reveal potential neural mechanisms by which MBTP improves ASD children.

Language: Английский

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Predictive Analysis of Autism Spectrum Disorder using Machine Learning Techniques^*

Published: June 21, 2024

Language: Английский

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