Are you curious about the impact of urbanization on our access to green spaces? Well, "Improved Human Greenspace Exposure Equality during 21st Century Urbanization" has got you covered! This study uses satellite data and population-weighted metrics to analyse changes in human exposure to greenspaces in over 1000 cities worldwide. Excitingly, it reveals that urbanization has led to an increase in greenspace coverage and a reduction in inequality in greenspace exposure over the past two decades.

"Deep Trip Generation with Graph Neural Networks for Bike Sharing System Expansion" takes us on a journey into the world of bike-sharing planning and expansion. Using cutting-edge graph neural networks and urban data, this study predicts station-level demand, outperforming traditional methods and offering valuable insights for selecting station locations and planning capacities.

Shhh... Do you hear that? It's the sound of traffic noise and its impact on our well-being. "Automated Simulation for Household Road Traffic Noise Exposure: Application and Field Evaluation in a High-Density City" presents an innovative simulation-based method to assess household noise exposure in densely populated areas. By considering the intricate interplay between roads, buildings, and topography, this study sheds light on the significant burden of road traffic noise on urban households and offers insights for noise mitigation and public health strategies.

"Associations of Urban Built Environment with Cardiovascular Risks and Mortality: A Systematic Review" examines how the built environment in cities impacts cardiovascular disease risks and outcomes. With a focus on factors like greenness and walkability, the study uncovers promising associations between urban features and lower cardiovascular risks.

Check out our paper "Compressing Network Populations with Modal Networks Reveal Structural Diversity" published in Communications Physics. The authors present efficient methods that automatically construct representative network representations, making it easier to explore and preprocess large sets of network samples. It's a fascinating read for anyone interested in understanding the intricate connections within data networks.

Drawing on over a decade's investigation in Enninglu, a neighbourhood district in Guangzhou that underwent several rounds of political struggles related to redevelopment and conservation, our paper "Police and Politics in Aesthetics-Based Urban Governance: Redevelopment and Grassroots Struggles in Enninglu, Guangzhou, China" reveals how local residents negotiated aesthetic norms enacted by the state. Particular attention is paid to the interactions between the aesthetic regime imposed by the state and grassroots people reclaiming their own aesthetic sensibilities, culminating in a contingent, inconclusive, and “impure” space of politics.