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1. Enabling smart curb management with spatiotemporal deep learning

   https://doi.org/10.1016/j.compenvurbsys.2022.101914  

   Hao, Haiyan; Wang, Yan; Du, Lili; Chen, Shigang (January 2023, Computers, Environment and Urban Systems)
2. Social media algorithms can curb misinformation, but do they?

   Bagchi, C; Menczer, F; Lundquist, J; Tarafdar, M; Paik, A; Grabowicz, P A (September 2024, Science)

   A recent article in Science by Guess et al. estimated the effect of Facebook's news feed algorithm on exposure to misinformation and political information among Facebook users. However, its reporting and conclusions did not account for a series of temporary emergency changes to Facebook's news feed algorithm in the wake of the 2020 U.S. presidential election that were designed to diminish the spread of voter-fraud misinformation. Here, we demonstrate that these emergency measures systematically reduced the amount of misinformation in the control group of the study, which was using the news feed algorithm. This issue may have led readers to misinterpret the results of the study and to conclude that the Facebook news feed algorithm used outside of the study period mitigates political misinformation as compared to reverse chronological feed. 

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3. Improving Ecological Restoration to Curb Biotic Invasion—A Practical Guide

   https://doi.org/10.1017/inp.2018.29  

   Guo, Qinfeng; Brockway, Dale G.; Larson, Diane L.; Wang, Deli; Ren, Hai (December 2018, Invasive Plant Science and Management)

   Abstract Common practices for invasive species control and management include physical, chemical, and biological approaches. The first two approaches have clear limitations and may lead to unintended (negative) consequences, unless carefully planned and implemented. For example, physical removal rarely completely eradicates the targeted invasive species and can cause disturbances that facilitate new invasions by nonnative species from nearby habitats. Chemical treatments can harm native, and especially rare, species through unanticipated side effects. Biological methods may be classified as biocontrol and the ecological approach. Similar to physical and chemical methods, biocontrol also has limitations and sometimes leads to unintended consequences. Therefore, a relatively safer and more practical choice may be the ecological approach, which has two major components: (1) restoration of native species and (2) biomass manipulation of the restored community, such as selective grazing or prescribed burning (to achieve and maintain viable population sizes). Restoration requires well-planned and implemented planting designs that consider alpha-, beta-, and gamma-diversity and the abundance of native and invasive component species at local, landscape, and regional levels. Given the extensive destruction or degradation of natural habitats around the world, restoration could be most effective for enhancing ecosystem resilience and resistance to biotic invasions. At the same time, ecosystems in human-dominated landscapes, especially those newly restored, require close monitoring and careful intervention (e.g., through biomass manipulation), especially when successional trajectories are not moving as intended. Biomass management frequently uses prescribed burning, grazing, harvesting, and thinning to maintain overall ecosystem health and sustainability. Thus, the resulting optimal, balanced, and relatively stable ecological conditions could more effectively limit the spread and establishment of invasive species. Here we review the literature (especially within the last decade) on ecological approaches that involve biodiversity, biomass, and productivity, three key community/ecosystem variables that reciprocally influence one another. We focus on the common and most feasible ecological practices that can aid in resisting new invasions and/or suppressing the dominance of existing invasive species. We contend that, because of the strong influences from neighboring areas (i.e., as exotic species pools), local restoration and management efforts in the future need to consider the regional context and projected climate changes. 

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4. Nitrogen-hungry bacteria added to farm soil curb greenhouse-gas emissions

   https://doi.org/10.1038/d41586-024-01363-3  

   He, Guang; Löffler, Frank E (June 2024, Nature)

   Innovative solutions are needed to decrease greenhouse-gas emissions. Field trials show that supplementing farm soil with a bacterium that consumes the greenhouse gas nitrous oxide can substantially lower harmful emissions. 

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5. Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks

   https://doi.org/10.1145/3394486.3403127  

   Zhang, Yingxue; Li, Yanhua; Zhou, Xun; Kong, Xiangnan; Luo, Jun (August 2020, Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining)

   Given an urban development plan and the historical traffic observations over the road network, the Conditional Urban Traffic Estimation problem aims to estimate the resulting traffic status prior to the deployment of the plan. This problem is of great importance to urban development and transportation management, yet is very challenging because the plan would change the local travel demands drastically and the new travel demand pattern might be unprecedented in the historical data. To tackle these challenges, we propose a novel Conditional Urban Traffic Generative Adversarial Network (Curb-GAN), which provides traffic estimations in consecutive time slots based on different (unprecedented) travel demands, thus enables urban planners to accurately evaluate urban plans before deploying them. The proposed Curb-GAN adopts and advances the conditional GAN structure through a few novel ideas: (1) dealing with various travel demands as the "conditions" and generating corresponding traffic estimations, (2) integrating dynamic convolutional layers to capture the local spatial auto-correlations along the underlying road networks, (3) employing self-attention mechanism to capture the temporal dependencies of the traffic across different time slots. Extensive experiments on two real-world spatio-temporal datasets demonstrate that our Curb-GAN outperforms major baseline methods in estimation accuracy under various conditions and can produce more meaningful estimations. 

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