On creative machines and the physical origins of freedom.
Ontology highlight
ABSTRACT:
SUBMITTER: Briegel HJ
PROVIDER: S-EPMC3400932 | biostudies-other | 2012
REPOSITORIES: biostudies-other
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Project description:Using a cross-sectional study design, we tested a structural equation model of hypothesized relationships among a group of variables: motivational climate in physical education (PE), students' social competence in PE, out of-school physical activity (PA) motivation, PA intention and their moderate-to-vigorous PA (MVPA). Based on the self-reports of 363 fourth to sixth grade elementary school students (172 girls, 191 boys), the model revealed that the task-involving motivational climate in PE was linked to higher MVPA via cooperation in PE, and also via extrinsic motivation and PA intention. Ego-involving motivational climate was related to higher extrinsic motivation and amotivation, further to higher PA intention and, finally, to higher MVPA. Task-involving motivational climate was positively linked to students' social competence markers of cooperation and empathy, and negatively to disruptiveness. Ego-involving motivational climate was positively related to disruptiveness and impulsivity, the markers of low social competence. The study showed that the motivational climate and co-operational aspect of social competence both played significant roles in students' PA motivation, PA intention and MVPA. A pedagogical model that brings the learning of social competence relevant skills to the fore is creative physical education (CPE). Analysis of CPE is provided which highlights teaching behaviors which contribute to the students' MVPA through motivational climates, co-operation, PA motivation and PA intention.
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Project description:BackgroundPhysical activity is a health-relevant lifestyle factor associated with various benefits on physical and mental health. Several meta-analyses indicated effects of acute and chronic physical activities on elementary cognitive functions such as executive control processes, memory, and attention. Meta-analytic evidence on the effects of physical activity on creative idea generation, which involves a conglomerate of these elementary cognitive functions, is largely missing.ObjectiveA twofold approach was used to evaluate (1) if there is an association between habitual physical activity and creative ideation and (2) if physical activity interventions (acute and chronic) enhance creative ideation performance.MethodsMultilevel meta-analytic methods were applied to (1) evaluate the cross-sectional association between creative ideation performance and measures of habitual physical activity and (2) the effect of physical activity on creative ideation performance. Indicators of creative ideation (fluency, flexibility, originality, elaboration, or composite score), creativity domain (verbal, figural), population (adults, children), gender, study quality, and publication year served as moderator variables for both meta-analyses. Analyses of intervention studies additionally examined the moderator variables study design (between, within), time of measurement (during, after), and implementation of intervention (acute, chronic).ResultsThe applied meta-analytic multilevel analysis indicated a medium effect for cross-sectional studies (r = 0.22, SE = 0.06, p = 0.002, 95% CI [0.10-0.34]) based on 17 effects sizes from seven studies. The pooled effects of 28 intervention studies, providing 115 effect sizes, indicated a medium effect size of Hedges' g = 0.47 (SE = 0.09, p < 0.001, 95% CI [0.30-0.65]). Furthermore, a stronger effect was observed for chronic interventions of several days or weeks in comparison with acute interventions of one single bout.ConclusionThis study adds important new meta-analytic evidence on the beneficial role of physical activity beyond mental and physical health outcomes: Physical activity has a positive impact on creative ideation, which expands the literature on the role of physical activity in more elementary cognitive functions such as executive control, memory, and attention. Moderator analyses suggested that chronic interventions showed stronger effects than single bouts of physical activity. Rigorously conducted randomized controlled intervention studies and more cross-sectional studies are needed to broaden the evidence in this nascent field of research.
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Project description:The coronavirus disease 2019 (COVID-19) pandemic is influencing our lives in an enormous and unprecedented way. Here, we explore COVID-19-lockdown's consequences for creative activity. To this end, we relied on two extensive diary studies. The first, held on March 2019 (pre-pandemic), involved 78 students who reported their emotions and creativity over 2 weeks (927 observations). The second, conducted on March 2020 (during the pandemic and lockdown), involved 235 students who reported on their emotions, creativity, and the intensity of thinking and talking about COVID-19 over a month (5,904 observations). We found that compared with 2019, during the lockdown, students engaged slightly yet statistically significantly more in creative activities. An analysis of diaries collected during the pandemic also showed that the days when students spent more time discussing or searching for information about COVID-19 were characterized by a higher creative activity yet also mixed emotions. We discuss potential explanations of these unexpected results along with future study directions.
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Project description:BackgroundMost machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem.ObjectivesThe aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities.MethodsTwo random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians.ResultsSimulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software.ConclusionsRandom forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications.
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Project description:BackgroundA construction method has emerged in which a camera is installed around a construction machine, and the operator remotely controls the machine while synchronizing the vibration of the machine with the images seen from the operator's seat using virtual reality (VR) technology. Indices related to changes in heart rate (HR) and physical vibration, such as heart rate variability (HRV) and multiscale entropy (MSE), can then be measured among the operators. As these indices are quantitative measures of autonomic regulation in the cardiovascular system, they can provide a useful means of assessing operational stress.ObjectiveIn this study, we aimed to evaluate changes in HR and body vibration of machine operators and investigate appropriate methods of machine operation while considering the psychological load.MethodsWe enrolled 9 remote operators (18-50 years old) in the experiment, which involved 42 measurements. A construction machine was driven on a test course simulating a construction site, and three patterns of operation-riding operation, remote operation using monitor images, and VR operation combining monitor images and machine vibration-were compared. The heartbeat, body vibration, and driving time of the participants were measured using sensing wear made of a woven film-like conductive material and a three-axis acceleration measurement device (WHS-2). We used HRV analysis in the time and frequency domains, MSE analysis as a measure of the complexity of heart rate changes, and the ISO (International Standards Organization) 2631 vibration index. Multiple regression analysis was conducted to model the relationship among the low frequency (LF)/high frequency (HF) HRV, MSE, vibration index, and driving time of construction equipment. Efficiency in driving time was investigated with a focus on stress reduction.ResultsMultiple comparisons conducted via the Bonferroni test and Kruskal-Wallis test showed statistically significant differences (P=.05) in HRV-LF/HF, the vibration index, weighted acceleration, motion sickness dose value (MSDVz), and the driving time among the three operation patterns. The riding operation was found to reduce the driving time of the machine, but the operation stress was the highest in this case; operation based on the monitor image was found to have the lowest operation stress but the longest operation time. Multiple regression analysis showed that the explanatory variables (LH/HF), RR interval, and vibration index (MSDVz by vertical oscillation at 0.5-5 Hz) had a negative effect on the driving time (adjusted coefficient of determination R2=0.449).ConclusionsA new method was developed to calculate the appropriate operating time by considering operational stress and suppressing the physical vibration within an acceptable range. By focusing on the relationship between psychological load and physical vibration, which has not been explored in previous studies, the relationship of these variables with the driving time of construction machines was clarified.
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2024-05-06 | GSE266263 | GEO