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This article describes learning activities of the HIIT PE addressing SHAPE America National Physical Education Standard #3, how student interest is obtained, and the variety of learning environments in which they can be implemented. The article also offers examples of learning activities, cognitive assessments, and a scope and sequence for teaching HIIT PE. These examples can easily be adapted for implementation across the K-12 levels. [ABSTRACT FROM AUTHOR]

In this study, we had two inter-related goals: (a) to examine sex and minority status differences on children's motivation for physical education (PE; i.e., their expectancy beliefs, subjective task values, and situational interest) and their psychomotor learning outcomes (i.e., motor competence, cardiorespiratory fitness, and in-class physical activity); and (b) to examine the relationships between children's motivation and their psychomotor learning outcomes while testing the moderation effects of sex and minority status. We recruited 195 fourth and fifth-grade students (101 boys; 94 girls; M age = 10.7, SD = 0.7 years) from three elementary schools in North Texas. Using multivariate analysis of variance, we identified a significant sex difference that favored boys in motivation and psychomotor learning outcomes, with no significant minority status difference in relation to these variables. Regression analysis revealed that children's expectancy beliefs were significantly associated with both motor competence (R 2 = 11%) and cardiorespiratory fitness (R 2 = 16%), while both situational interest and sex were associated with in-class physical activity (R 2 = 18%). Thus, improving children's expectancy beliefs may be a means of enhancing psychomotor learning outcomes in PE, especially for girls. Enhancing children's beliefs in their own ability and offering diversified PE content so as to generate greater interest may facilitate psychomotor learning. [ABSTRACT FROM AUTHOR]

Comprehensive school physical activity programs (CSPAP) offer many opportunities for children and adolescents to be physically active. CSPAP implementation is challenging, especially during the COVID-19 pandemic. In this article, we define physical activity opportunity (PAO), identify the common sources of PAOs, and conclude with a set of strategies for offering and optimizing PAOs in and beyond schools. Effective physical activity and wellness promotion takes collective initiatives by stakeholders, in and beyond schools. [ABSTRACT FROM AUTHOR]

Introduction: As the frequency of infectious diseases rises, it's more important than ever to pay attention to the competency level of front-line nurses as the primary force in front-line rescue, which has an impact on the quality of anti-epidemic response. This paper aims to construct the competency evaluation index system for front-line nurses during the outbreak of major infectious diseases. Materials and methods: This study combined literature review, critical incident technique interviews, and semi-structured in-depth interviews, as well as two rounds of Delphi expert correspondence, to construct a competence evaluation index system for front-line nurses during the outbreak of major infectious diseases. The study used purposive sampling to select 26 experts from 11 provinces and cities across China to conduct two rounds of Delphi expert consultation, and the indicators were selected based on the mean importance score > 3.5 and the coefficient of variation < 0.25, and the weights of the indicators were calculated by the Analytic Hierarchy Process. The effective recovery rates of the two rounds of correspondence questionnaires were 93.1% and 96%. Results: The effective recovery rates of the two rounds of correspondence questionnaires were 93.1% and 96%, the authority coefficients of experts were 0.96 and 0.98, the Kendall's coordination coefficients of the first, second, and third level indexes were 0.281, 0.132, and 0.285 (P < 0.001), 0.259, 0.158, and 0.415 (P < 0.001). The final index system includes 4 primary indicators (Knowledge System of Infectious Diseases, Nursing Skills for Infectious Diseases, Related Professional Abilities for Infectious Diseases, and Comprehensive Quality), 10 secondary indicators, and 64 tertiary indicators. Conclusion: The competency evaluation index system of front-line nurses during the outbreak of major infectious diseases is scientific, reasonable, and practical, which can provide a scientific basis for nursing managers to accurately understand, describe, analyze, and evaluate the competence level of nursing staff and scientifically implement the allocation of human resources in the future, as well as serve as a content framework for subsequent training programs. [ABSTRACT FROM AUTHOR]

Subway stations are typically equipped with fresh air shafts to introduce outdoor air, while the surrounding rock and air channels form a vertical earth-air heat exchanger (VEAHE). This study is the first to analyze the year-round thermal storage and exothermic characteristics of the surrounding rock. A numerical model was developed, incorporating ground surface heat transfer and axial heat transfer within the rock. The simulation results aligned well with field test data. This model was then utilized to explore the thermal storage and release properties of the surrounding rock. The findings revealed that both z-directional and r-directional annual temperature wave affect the enclosing rock. The monthly average natural energy efficiency (NEE) and storage efficiency (SE) were determined to be 10.75% and 17.47%, respectively. Notably, the shallow rock exhibited the highest NEE but the lowest SE. The energy used for fresh air pre-treatment derives not only from the rock's current annual cycle but also from previously stored energy. Lastly, λ sr and c were identified as major influencers of NEE, while λ sr , c , and the burial depth of the shaft collectively impact the air pre-treatment process in the shaft. The findings contribute to further understanding of the thermal process in VEAHE systems. • A more comprehensive and accurate numerical model was developed. • First analyzed the thermal storage and release characteristics of the enclosing rock. • Studied the efficiency of the thermal storage and release of the surrounding rock. • Investigated the factors influencing thermal storage and release of the surrounding rock. [ABSTRACT FROM AUTHOR]

• The alterations in dFC and SC networks unveil distinct characteristics associated with cLBP. • The enhanced connectivity between the FPN, SMN and thalamus signifies the most relevant changes in brain networks associated with cLBP. • The integration of different features effectively enhances the classification accuracy between cLBP patients and HC. The prolonged duration of chronic low back pain (cLBP) inevitably leads to changes in the cognitive, attentional, sensory and emotional processing brain regions. Currently, it remains unclear how these alterations are manifested in the interplay between brain functional and structural networks. This study aimed to predict the Oswestry Disability Index (ODI) in cLBP patients using multimodal brain magnetic resonance imaging (MRI) data and identified the most significant features within the multimodal networks to aid in distinguishing patients from healthy controls (HCs). We constructed dynamic functional connectivity (dFC) and structural connectivity (SC) networks for all participants (n = 112) and employed the Connectome-based Predictive Modeling (CPM) approach to predict ODI scores, utilizing various feature selection thresholds to identify the most significant network change features in dFC and SC outcomes. Subsequently, we utilized these significant features for optimal classifier selection and the integration of multimodal features. The results revealed enhanced connectivity among the frontoparietal network (FPN), somatomotor network (SMN) and thalamus in cLBP patients compared to HCs. The thalamus transmits pain-related sensations and emotions to the cortical areas through the dorsolateral prefrontal cortex (dlPFC) and primary somatosensory cortex (SI), leading to alterations in whole-brain network functionality and structure. Regarding the model selection for the classifier, we found that Support Vector Machine (SVM) best fit these significant network features. The combined model based on dFC and SC features significantly improved classification performance between cLBP patients and HCs (AUC=0.9772). Finally, the results from an external validation set support our hypotheses and provide insights into the potential applicability of the model in real-world scenarios. Our discovery of enhanced connectivity between the thalamus and both the dlPFC (FPN) and SI (SMN) provides a valuable supplement to prior research on cLBP. [ABSTRACT FROM AUTHOR]

This study aimed to examine the effects of yoga and physical fitness exercises on stress and the underlying mechanisms. Participants: Healthy undergraduates from four yoga and four fitness classes participated in Study 1 (n = 191) and Study 2 (n = 143), respectively (in 2017 Fall). Methods: Study 1 evaluated the immediate effect (a 60-minute practice) while Study 2 evaluated the durable effect (a 12-week intervention). Results: Results showed that immediate stress reduction was more salient in the yoga group than that in the fitness group in Study 1. Yoga group had a greater increase in mindfulness, which predicted stress reduction. Similar observations were made in Study 2 showing the durable effect of yoga on stress reduction through mindfulness. Conclusions: Yoga intervention is better than fitness exercises in helping undergraduates cultivate mindfulness and reduce stress. These findings may guide future interventions in stress management in college students. [ABSTRACT FROM AUTHOR]

Neuroimaging research has revealed significant changes in brain structure and function in patients with cervical spondylotic myelopathy(CSM). The thalamus plays a crucial role in this process, although its mechanisms of action remain incompletely understood. This study aimed to investigate whether spinal cord compression leads to alterations in the functional connectivity between the thalamus and the cerebral cortex, and to determine if such changes are associated with structural and functional remodeling of the brain in patients with CSM, and to identify potential neuroimaging biomarkers for classification. The study included 40 patients with CSM and 34 healthy controls(HCs) who underwent resting-state functional magnetic resonance imaging(fMRI) and structural MRI scans. Brain structural and functional metrics were quantified using functional connectivity(FC), fractional amplitude of low-frequency fluctuations(fALFF), surface-based morphometry(SBM), and independent component analysis(ICA) based on functional and structural MRI. Patients with CSM exhibited significantly reduced fALFF in the bilateral lateral lingual gyrus, bilateral calcarine fissure, left precentral gyrus and postcentral gyrus, left middle and superior occipital gyrus, left superior marginal gyrus, left inferior parietal gyrus, and right Rolandic operculum. ICA results revealed weakened functional connectivity between the sensorimotor network (SMN) and the left and right frontoparietal network(FPN), and lateral visual network (lVN), along with decreased connectivity between lVN and rFPN, and increased connectivity between lFPN and rFPN. Patients with CSM also had decreased sulcus depth in the bilateral insula, left precentral and postcentral gyrus, and right lingual gyrus and calcarine fissure. Furthermore, cervical spondylotic myelopathy patients showed decreased functional connectivity between the left ventral posterolateral nucleus (VPL) of the thalamus and the right middle occipital gyrus (MOG). Finally,multimodal neuroimaging with support vector machine(SVM) classified patients with CSM and healthy controls with 86.00% accuracy. Our study revealed that the decrease in functional connectivity between the thalamus and cortex mediated by spinal cord compression leads to structural and functional reorganization of the cortex. Features based on neuroimaging markers have the potential to become neuroimaging biomarkers for CSM. • CSM patients exhibit significant alterations in both brain structure and function. • Reduced thalamo-cortical synchronization in CSM patients mediates brain remodeling. • Neuroimaging metrics with SVM can accurately classify CSM patients and healthy controls. [ABSTRACT FROM AUTHOR]

The high-value utilization of agricultural and forestry waste holds the promise of alleviating the issues of energy crisis. Among them, the manufacturing of high-performance supercapacitor electrode materials from tobacco waste biomass is a reliable avenue. In this work, tobacco-stem-derived hierarchical porous carbon (TS-HPC) was prepared by one-pot ball milling and carbonization using calcium carbonate (CaCO 3) and potassium oxalate (K 2 C 2 O 4) as mild activating agents. Due to the synergistic activation of CaCO 3 and K 2 C 2 O 4 , the specific surface area of TS-HPC is 2749 m2/g. TS-HPC with the hierarchical porous structure greatly shows an excellent specific capacitance (402 F/g at 0.5 A/g) in the three-electrode configuration. In addition, symmetric supercapacitor based on TS-HPC exhibits 10.2 W h/kg energy density at 150.0 W/kg power density, together with outstanding cycling stability (remains 97.8% after 10,000 cycles). Moreover, we demonstrated that the gas exfoliation of CaCO 3 and K 2 C 2 O 4 could contribute to the formation of hierarchical porous structures with a synergistic activation effect. This work could provide a new perspective on the preparation of biomass-derived carbon as electrode for supercapacitors. [Display omitted] • Tobacco stem-derived carbon was prepared by one-pot ball milling and carbonization. • TS-HPC exhibits a high specific surface area of 2749 m2/g. • The synergistic gas exfoliation effect results superior pore size distribution. • TS-HPC shows high specific capacitance of 402 F/g. [ABSTRACT FROM AUTHOR]

• A comprehensive measure of model predictability signature is developed. • A list of satellite, reanalysis and ground-based precipitation products is assessed. • BATEA excels MCMC for indirect measurements of precipitation in general. • Model predictability signature has potential on merging precipitation estimates. Quantifying and reducing the errors and uncertainties in high-resolution gridded precipitation products are essential for hydrological modelling to generate realistic parameter estimates and accurate model predictions. Formal Bayesian inference provides a powerful tool to quantify rainfall uncertainty and other uncertainty factors in hydrological modelling. An efficient way to reduce rainfall uncertainty in hydrological modelling is to merge precipitation estimates from multiple sources prior to their real-world applications. However, it remains a challenging task to optimally determine the weightings of different precipitation estimates based on the predictive ability of a hydrological model, especially from a probabilistic perspective. This study addresses this issue by evaluating and merging six gridded precipitation products using formal Bayesian inference schemes, including the Markov Chain Monte Carlo (MCMC) approach and Bayesian total error analysis (BATEA). MCMC describes the total predictive uncertainty using residual error models. In contrast, BATEA utilizes the storm depth multiplier approach to separately account for rainfall uncertainty in probabilistic uncertainty quantification. A novel signature of model predictability that combines the reliability and precision of probabilistic model predictions is developed to quantify the predictive ability of a hydrological model from precipitation estimates. Using the proposed predictability signature, we examined the benefit of optimally merging multi-source precipitation estimates in improving the accuracy of hydrologic simulations by applying the method to the Danjiangkou Reservoir region (DRR) between 1998 and 2007. The analysis demonstrates that (1) BATEA, compared to MCMC, can provide more realistic estimates of model parameters and tighter predictive intervals of daily streamflow when using rain gauge observations as well as gridded precipitation products; and (2) the proposed predictability signature is efficient for optimally merging precipitation measurements as it can produce tighter uncertainty bands and better streamflow simulations than individual precipitation estimates. This study provides insights into improved quantification and reduction of uncertainty in multi-source precipitation products for hydrological modelling. [ABSTRACT FROM AUTHOR]

• A comprehensive measure of model predictability signature is developed. • A list of satellite, reanalysis and ground-based precipitation products is assessed. • BATEA excels MCMC for indirect measurements of precipitation in general. • Model predictability signature has potential on merging precipitation estimates. Quantifying and reducing the errors and uncertainties in high-resolution gridded precipitation products are essential for hydrological modelling to generate realistic parameter estimates and accurate model predictions. Formal Bayesian inference provides a powerful tool to quantify rainfall uncertainty and other uncertainty factors in hydrological modelling. An efficient way to reduce rainfall uncertainty in hydrological modelling is to merge precipitation estimates from multiple sources prior to their real-world applications. However, it remains a challenging task to optimally determine the weightings of different precipitation estimates based on the predictive ability of a hydrological model, especially from a probabilistic perspective. This study addresses this issue by evaluating and merging six gridded precipitation products using formal Bayesian inference schemes, including the Markov Chain Monte Carlo (MCMC) approach and Bayesian total error analysis (BATEA). MCMC describes the total predictive uncertainty using residual error models. In contrast, BATEA utilizes the storm depth multiplier approach to separately account for rainfall uncertainty in probabilistic uncertainty quantification. A novel signature of model predictability that combines the reliability and precision of probabilistic model predictions is developed to quantify the predictive ability of a hydrological model from precipitation estimates. Using the proposed predictability signature, we examined the benefit of optimally merging multi-source precipitation estimates in improving the accuracy of hydrologic simulations by applying the method to the Danjiangkou Reservoir region (DRR) between 1998 and 2007. The analysis demonstrates that (1) BATEA, compared to MCMC, can provide more realistic estimates of model parameters and tighter predictive intervals of daily streamflow when using rain gauge observations as well as gridded precipitation products; and (2) the proposed predictability signature is efficient for optimally merging precipitation measurements as it can produce tighter uncertainty bands and better streamflow simulations than individual precipitation estimates. This study provides insights into improved quantification and reduction of uncertainty in multi-source precipitation products for hydrological modelling. [ABSTRACT FROM AUTHOR]

A local-regional power loss analysis method based on multiphase computational fluid dynamics (CFD) simulation results is proposed in this study. This method is used to investigate the energy conversion characteristics of a three-stage electric submersible pump under high inlet gas volume fraction (IGVF) conditions. Results show that the input power and effective power increase first and then decrease along the streamline. When IGVF increases from 0% to 14.5%, the total input power and total effective power decrease by 32.4% and 56.2%, respectively. In particular, the input power and effective power in R4 drop by 62% and 67%, respectively. The high gas volume fraction (GVF) area on the blade pressure surface near the impeller inlet causes the power decrease in R4. However, the input power in R6 increases by 47.5%. This condition is due to a jet flow near the impeller outlet causes the vortex and high GVF area in R6, thereby leading to a high liquid velocity area along the radial direction near the pressure surface of the impeller blade. The kinetic energy of the fluid in the jet region increases rapidly in accordance with Bernoulli equation and is converted into pressure energy in the vortex area. The total power loss increases quickly with IGVF. The power loss near the impeller outlet area at 14.5% IGVF is ten times higher than that of 0% IGVF condition and five times higher than that of 5% IGVF condition. This condition is caused by the large air pockets accompanied by vortices in the area. This work provides a theoretical basis for the design and optimization of the multiphase pump. • Local-regional power loss analysis was used in gas-liquid pump energy conversion. • Energy conversion characteristics at pump surging condition were studied. • The value of input power, effective power and power loss in the area was obtained. • The reason for the decrease of pump work capacity in the area was pointed. • Mechanism of the influence of gas volume fraction on pump work capacity is analyzed. [ABSTRACT FROM AUTHOR]

The circulating cooling water system is widely used in various industrial production fields, and its operating cost largely depends on external factors, such as ambient temperature and working medium flow. Considering the relative elevation of the heat exchanger, this study establishes a total system operation cost analysis and optimization model based on the superstructure method. The model uses ambient dry bulb temperature, ambient wet bulb temperature, and working medium flow as random variables. Water supply temperature is adopted as the decision variable, and the minimum operating cost of the system is used as the objective function. An analysis of the effect of the three random variables on the operation cost shows that the effect of ambient dry bulb temperature on the operation cost is negligible, and the effect of ambient wet bulb temperature and working medium flow on the operation cost is significant. In addition, a control equation of water supply temperature is established to determine the "near optimal" operation, which is based on the correlation among ambient wet bulb temperature, working medium flow, and optimal water supply temperature. Then, the method is applied to a case system. The operating cost of the system is reduced by 22–31% at different times during the sampling day. [ABSTRACT FROM AUTHOR]