BackgroundEighty per cent of adolescents globally do insufficient physical activity. Parks are a popular place for adolescents to be active. However, little is known about which park features are associated with higher levels of park use by adolescents.ObjectivesThis study aimed to examine which environmental park features, and combination of features, were correlated with higher levels of park use for physical activity among adolescents. By examining park features in parks used by adolescents for physical activity, this study also aimed to create a park ‘attractiveness’ score predictive of adolescent park use, and to identify factors that might predict use of their closest park.MethodsAdolescents (n = 1304) living in Geraldton, a large rural centre of Western Australia, completed a survey that measured physical activity behaviour, perceptions of park availability and the main park used for physical activity. All parks in the study area (n = 58) were digitized using a Geographic Information System (GIS) and features audited using the Public Open Space Desktop Auditing Tool (POSDAT).ResultsOnly 27% of participants reported using their closest park for physical activity. Park use was associated with seven features: presence of a skate park, walking paths, barbeques, picnic table, public access toilets, lighting around courts and equipment and number of trees >25. When combined to create an overall attractiveness score, every additional ‘attractive’ feature present, resulted in a park being nearly three times more likely to be in the high use category.ConclusionsTo increase park use for physical activity, urban planners and designers should incorporate park features attractive to adolescents.

No abstract

No abstract

Strategies should be put in place to encourage use of proximate supportive environments. Planning neighborhoods to reduce barriers to access and interventions to overcome seasonal variations in behavior may improve participation levels among adolescents.

No abstract

No abstract

SUMMARYThis paper presents an optimal feedback controller capable of driving a non-linear control system from an arbitrary initial state to a fixed final state in minimum time. The controller is based on a feedforward multilayer neural network trained repeatedly using open-loop optimal control data which densely span the field of extremals of the non-linear system. The effectiveness of the controller is clearly demonstrated by a simulation on a two-link robot manipulator. The effect of sensorlactuator noise and parameter variation is also included to confirm the robustness of the controller.

By the end of 2020, the COVID-19 pandemic had exceeded 83 million cases worldwide. Given the shared origins of planning and public health, new living and social conditions have prompted an interest in how urban planning could respond to the pandemic's associated implications. In 2020, a national online survey Plan My Australia was conducted among planning experts (n = 161), in part, to identify new challenges facing urban planning and design due to the pandemic. The findings reported here revealed that many experts identified better planning for future pandemics in Australia could require some reconsideration of city size, urban density, self-sufficiency, public transport use, open space provision and housing design.