Background:Children spend substantial time in childcare,and the reasons parents choose a particular childcare type may differ by family.However,little is known about how childcare type influences habitual(full day)act...Background:Children spend substantial time in childcare,and the reasons parents choose a particular childcare type may differ by family.However,little is known about how childcare type influences habitual(full day)activity levels among children.Therefore,exploring patterns between childcare type and habitual physical activity(PA)(i.e.,light,moderate-to-vigorous PA(MVPA),and total PA)and sedentary time(ST)in young Canadian children is needed.Methods:A nationally representative sample of preschoolers from Cycles 3 and 4 of the Canadian Health Measures Survey was used in this cross-sectional study.Childcare type(e.g.,center-based childcare,home-based childcare,home with parent,kindergarten)was reported by parents.Preschoolers wore an Actical accelerometer for 7 days.Device and population-spcific cut-points were applied to delineate PA intensities and ST.Population means and sample totals were calculated to examine average daily and hourly rates of activity.Results:Preschoolers’rates of MVPA and total PA from the 4 childcare arrangements ranged from 65.99 min/day to 74.62 min/day(5.48-6.18 min/h)and 274.20 min/day to 281.66 min/day (22.69-23.21 min/h),respectively,while ST ranged from 443.13 min/day to 460.57 min/day(36.80-37.31 min/h).No significant differences were observed in daily or hourly rates of activity.Conclusion:This study provides a snapshot of the levels of PA and ST among preschoolers in various childcare settings at a national level,with no differences observed in habitual activity levels based on childcare enrollment.Additional research is needed to clarify the relationship between young children’s PA and childcare type,with consideration given to the quality of the childcare settings.展开更多
A novel approach to optimizing any given mathematical function, called the MOdified REinforcement Learning Algorithm (MORELA), is proposed. Although Reinforcement Learning (RL) is primarily developed for solving Marko...A novel approach to optimizing any given mathematical function, called the MOdified REinforcement Learning Algorithm (MORELA), is proposed. Although Reinforcement Learning (RL) is primarily developed for solving Markov decision problems, it can be used with some improvements to optimize mathematical functions. At the core of MORELA, a sub-environment is generated around the best solution found in the feasible solution space and compared with the original environment. Thus, MORELA makes it possible to discover global optimum for a mathematical function because it is sought around the best solution achieved in the previous learning episode using the sub-environment. The performance of MORELA has been tested with the results obtained from other optimization methods described in the literature. Results exposed that MORELA improved the performance of RL and performed better than many of the optimization methods to which it was compared in terms of the robustness measures adopted.展开更多
基金Patricia Tucker is supported by an Early Researcher Award from the Ontario Ministry of Research and Innovation.
文摘Background:Children spend substantial time in childcare,and the reasons parents choose a particular childcare type may differ by family.However,little is known about how childcare type influences habitual(full day)activity levels among children.Therefore,exploring patterns between childcare type and habitual physical activity(PA)(i.e.,light,moderate-to-vigorous PA(MVPA),and total PA)and sedentary time(ST)in young Canadian children is needed.Methods:A nationally representative sample of preschoolers from Cycles 3 and 4 of the Canadian Health Measures Survey was used in this cross-sectional study.Childcare type(e.g.,center-based childcare,home-based childcare,home with parent,kindergarten)was reported by parents.Preschoolers wore an Actical accelerometer for 7 days.Device and population-spcific cut-points were applied to delineate PA intensities and ST.Population means and sample totals were calculated to examine average daily and hourly rates of activity.Results:Preschoolers’rates of MVPA and total PA from the 4 childcare arrangements ranged from 65.99 min/day to 74.62 min/day(5.48-6.18 min/h)and 274.20 min/day to 281.66 min/day (22.69-23.21 min/h),respectively,while ST ranged from 443.13 min/day to 460.57 min/day(36.80-37.31 min/h).No significant differences were observed in daily or hourly rates of activity.Conclusion:This study provides a snapshot of the levels of PA and ST among preschoolers in various childcare settings at a national level,with no differences observed in habitual activity levels based on childcare enrollment.Additional research is needed to clarify the relationship between young children’s PA and childcare type,with consideration given to the quality of the childcare settings.
文摘A novel approach to optimizing any given mathematical function, called the MOdified REinforcement Learning Algorithm (MORELA), is proposed. Although Reinforcement Learning (RL) is primarily developed for solving Markov decision problems, it can be used with some improvements to optimize mathematical functions. At the core of MORELA, a sub-environment is generated around the best solution found in the feasible solution space and compared with the original environment. Thus, MORELA makes it possible to discover global optimum for a mathematical function because it is sought around the best solution achieved in the previous learning episode using the sub-environment. The performance of MORELA has been tested with the results obtained from other optimization methods described in the literature. Results exposed that MORELA improved the performance of RL and performed better than many of the optimization methods to which it was compared in terms of the robustness measures adopted.
