Literature Review Reveals a Global Access Inequity to Urban Green Spaces

Differences in the accessibility to urban resources between different racial and socioeconomic groups have exerted pressure on effective planning and management for sustainable city development. However, few studies have examined the multiple factors that may influence the mitigation of urban green spaces (UGS) inequity. This study reports the results of a systematic mapping of access inequity research through correspondence analysis (CA) to reveal critical trends, knowledge gaps, and clusters based on a sample of 49 empirical studies screened from 563 selected papers. Our findings suggest that although the scale of cities with UGS access inequity varies between countries, large cities (more than 1,000,000 population), especially in low- and middle-income countries (LMICs), are particularly affected. Moreover, the number of cities in which high socioeconomic status (high-SES) groups (e.g., young, rich, or employed) are at an advantage concerning access to UGS is substantially higher than the number of cities showing better accessibility for low-SES groups. Across the reviewed papers, analyses on mitigating interventions are sparse, and among the few studies that touch upon this, we found different central issues in local mitigating strategies between high-income countries (HICs) and LMICs. An explanatory framework is offered, explaining the interaction between UGS access inequity and local mitigating measures

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Though deep reinforcement learning (DRL) has obtained substantial success, it may encounter catastrophic failures due to the intrinsic uncertainty of both transition and observation. Most of the existing methods for safe reinforcement learning can only handle transition disturbance or observation disturbance since these two kinds of disturbance affect different parts of the agent; besides, the popular worst-case return may lead to overly pessimistic policies. To address these issues, we first theoretically prove that the performance degradation under transition disturbance and observation disturbance depends on a novel metric of Value Function Range (VFR), which corresponds to the gap in the value function between the best state and the worst state. Based on the analysis, we adopt conditional value-at-risk (CVaR) as an assessment of risk and propose a novel reinforcement learning algorithm of CVaR-Proximal-Policy-Optimization (CPPO) which formalizes the risk-sensitive constrained optimization problem by keeping its CVaR under a given threshold. Experimental results show that CPPO achieves a higher cumulative reward and is more robust against both observation and transition disturbances on a series of continuous control tasks in MuJoCo

Task Aware Dreamer for Task Generalization in Reinforcement Learning

A long-standing goal of reinforcement learning is to acquire agents that can learn on training tasks and generalize well on unseen tasks that may share a similar dynamic but with different reward functions. A general challenge is to quantitatively measure the similarities between these different tasks, which is vital for analyzing the task distribution and further designing algorithms with stronger generalization. To address this, we present a novel metric named Task Distribution Relevance (TDR) via optimal Q functions of different tasks to capture the relevance of the task distribution quantitatively. In the case of tasks with a high TDR, i.e., the tasks differ significantly, we show that the Markovian policies cannot differentiate them, leading to poor performance. Based on this insight, we encode all historical information into policies for distinguishing different tasks and propose Task Aware Dreamer (TAD), which extends world models into our reward-informed world models to capture invariant latent features over different tasks. In TAD, we calculate the corresponding variational lower bound of the data log-likelihood, including a novel term to distinguish different tasks via states, to optimize reward-informed world models. Extensive experiments in both image-based control tasks and state-based control tasks demonstrate that TAD can significantly improve the performance of handling different tasks simultaneously, especially for those with high TDR, and demonstrate a strong generalization ability to unseen tasks

Curcumin-Loaded Mixed Micelles: Preparation, Characterization, and In Vitro

The objective of this study was to prepare curcumin-loaded mixed Soluplus/TPGS micelles (Cur-TPGS-PMs) for oral administration. The Cur-TPGS-PMs showed a mean size of 65.54 ± 2.57 nm, drug encapsulation efficiency over 85%, and drug loading of 8.17%. The Cur-TPGS-PMs were found to be stable in various pH media (pH 1.2 for 2 h, pH 6.8 for 2 h, and pH 7.4 for 6 h). The X-ray diffraction (XRD) patterns illustrated that curcumin was in the amorphous or molecular state within PMs. The In vitro release test indicated that Cur-TPGS-PMs possessed a significant sustained-release property. The cell viability in MCF-7 cells was found to be relatively lower in Cur-TPGS-PM-treated cells as compared to free Cur-treated cells. CLSM imaging revealed that mixed micelles were efficiently absorbed into the cytoplasm region of MCF-7 cells. Therefore, Cur-TPGS-PMs could have the significant value for the chronic breast cancer therapy

Effects of Urbanization on the Dynamics and Equity of Access to Urban Parks from 2000 to 2015 in Beijing, China

Urban parks provide multiple ecosystem services as an important element of the urban space and improve human health and wellbeing. This study used the Gaussian-based 2SFCA method to evaluate the spatiotemporal distribution of and changes in park accessibility within the Sixth Ring Road in Beijing over 15 years. The study also used bivariate correlation analysis to analyze the relationship between urbanization factors and park access. The results showed that the overall park accessibility in both quantity and proximity had increased from 2000 to 2015, but there were still certain areas (percentage) that had limited access to parks. The inequity of distribution in park accessibility had been detected accompanying the rapid increase in park quantity in 2015. Furthermore, the development of urban parks mismatched that of urbanization in terms of urban land increase. The correlation between accessibility changes and population urbanization is not significant. Proper urban green space planning based on the distribution of population density and urban land use is indispensable in avoiding the aggravation of inequity in the process of urban expansion. This study contributes to the assessment of the current park allocation efficiency and helps urban planners and policymakers make prompt adjustments in the rapidly urbanizing process