PM2.5-Related Health Economic Benefits Evaluation Based on Air Improvement Action Plan in Wuhan City, Middle China

On the basis of PM2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided premature deaths in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors

LassoNet:Deep Lasso-Selection of 3D Point Clouds

Selection is a fundamental task in exploratory analysis and visualization of 3D point clouds. Prior researches on selection methods were developed mainly based on heuristics such as local point density, thus limiting their applicability in general data. Specific challenges root in the great variabilities implied by point clouds (e.g., dense vs. sparse), viewpoint (e.g., occluded vs. non-occluded), and lasso (e.g., small vs. large). In this work, we introduce LassoNet, a new deep neural network for lasso selection of 3D point clouds, attempting to learn a latent mapping from viewpoint and lasso to point cloud regions. To achieve this, we couple user-target points with viewpoint and lasso information through 3D coordinate transform and naive selection, and improve the method scalability via an intention filtering and farthest point sampling. A hierarchical network is trained using a dataset with over 30K lasso-selection records on two different point cloud data. We conduct a formal user study to compare LassoNet with two state-of-the-art lasso-selection methods. The evaluations confirm that our approach improves the selection effectiveness and efficiency across different combinations of 3D point clouds, viewpoints, and lasso selections. Project Website: https://lassonet.github.ioComment: 10 page

AmbiguityVis: Visualization of Ambiguity in Graph Layouts

Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graphlayout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteriasimultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attentionto these potentially problematic areas present in the drawing, this paper presents a technique that highlights common types of visualambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguityin edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge lengths, visual overlap in communitystructures and node/edge aggregation, are proposed to quantify areas of ambiguity in the drawing. These metrics and others arethen displayed using a heatmap-based visualization that provides visual feedback to developers of graph drawing and visualizationapproaches, allowing them to quickly identify misleading areas. The novel metrics and the heatmap-based visualization allow a userto explore ambiguities in graph layouts from multiple perspectives in order to make reasonable graph layout choices. The effectivenessof the technique is demonstrated through case studies and expert reviews

Microwave-assisted rapid and regioselective synthesis of N-(alkoxycarbonylmethyl) nucleobases in water

A facile and eco-friendly approach has been developed for the preparation of N-(ethyoxycarbonylmethyl) nucleobases and N-(iso-propoxycarbonylmethyl) nucleobases, which are important building blocks for Peptide Nucleic Acids (PNA). All the nucleobases are regioselectively alkylated and the desired products are obtained in moderate to high yields under microwave irradiation for 8 min in water as the solvent and in the presence of Et3N as the base

3D-Printed Artificial Microfish

Hydrogel microfish featuring biomimetic structures, locomotive capabilities, and functionalized nanoparticles are engineered using a rapid 3D printing platform: microscale continuous ­optical printing (μCOP). The 3D-printed ­microfish exhibit chemically powered and magnetically guided propulsion, as well as highly efficient detoxification capabilities that highlight the technical versatility of this platform for engineering advanced functional microswimmers for diverse biomedical applications

3D-Printed Artificial Microfish

Hydrogel microfish featuring biomimetic structures, locomotive capabilities, and functionalized nanoparticles are engineered using a rapid 3D printing platform: microscale continuous ­optical printing (μCOP). The 3D-printed ­microfish exhibit chemically powered and magnetically guided propulsion, as well as highly efficient detoxification capabilities that highlight the technical versatility of this platform for engineering advanced functional microswimmers for diverse biomedical applications

Recent Advances in Mechanisms and Treatments of Airway Remodeling in Asthma: A Message from the Bench Side to the Clinic

Airway remodeling in asthma is a result of persistent inflammation and epithelial damage in response to repetitive injury. Recent studies have identified several important mediators associated with airway remodeling in asthma, including transforming growth factor-β, interleukin (IL)-5, basic fibroblast growth factor, vascular endothelial growth factor, LIGHT, tumor necrosis factor (TNF)-α, thymic stromal lymphopoietin, IL-33, and IL-25. In addition, the epithelium mesenchymal transformation (EMT) induced by environmental factors may play an important role in initiating this process. Diagnostic methods using sputum and blood biomarkers as well as radiological interventions have been developed to distinguish between asthma sub-phenotypes. Human clinical trials have been conducted to evaluate biological therapies that target individual inflammatory cells or mediators including anti IgE, anti IL-5, and anti TNF-α. Furthermore, new drugs such as c-kit/platelet-derived growth factor receptor kinase inhibitors, endothelin-1 receptor antagonists, calcium channel inhibitors, and HMG-CoA reductase inhibitors have been developed to treat asthma-related symptoms. In addition to targeting specific inflammatory cells or mediators, preventing the initiation of EMT may be important for targeted treatment. Interestingly, bronchial thermoplasty reduces smooth muscle mass in patients with severe asthma and improves asthma-specific quality of life, particularly by reducing severe exacerbation and healthcare use. A wide range of different therapeutic approaches has been developed to address the immunological processes of asthma and to treat this complex chronic illness. An important future direction may be to investigate the role of mediators involved in the development of airway remodeling to enhance asthma therapy

Application Research on Anti-Occlusion Target Tracking Strategy Based on IMU and Video Image Information Synthesis in Airborne Electro-Optical Reconnaissance and Aiming System

Target tracking is a core working mode of airborne photoelectric reconnaissance and aiming system, and its performance directly determines the mission efficiency of the airborne system. Aiming at the outstanding problems and technical difficulties in the application of target tracking, according to the multi-sensor configuration and application characteristics of the system, an intelligent target tracking strategy based on inertial measurement and video image information fusion is proposed, which integrates multi-dimensional information such as inertial navigation, motion mea-surement, servo control, geography and image coordinates. Simulation analysis and flight test show that the strategy can effectively improve the anti-jamming performance of target tracking, realize the robust and persistent target tracking in full dynamic complex scenes, and improve the combat ability of reconnaissance and surveillance, target positioning, weapon guidance of the airborne system