Background Despite the recent progress in 3D point cloud processing using deep convolutional neural networks,the inability to extract local features remains a challenging problem.In addition,existing methods consider ...Background Despite the recent progress in 3D point cloud processing using deep convolutional neural networks,the inability to extract local features remains a challenging problem.In addition,existing methods consider only the spatial domain in the feature extraction process.Methods In this paper,we propose a spectral and spatial aggregation convolutional network(S^(2)ANet),which combines spectral and spatial features for point cloud processing.First,we calculate the local frequency of the point cloud in the spectral domain.Then,we use the local frequency to group points and provide a spectral aggregation convolution module to extract the features of the points grouped by the local frequency.We simultaneously extract the local features in the spatial domain to supplement the final features.Results S^(2)ANet was applied in several point cloud analysis tasks;it achieved stateof-the-art classification accuracies of 93.8%,88.0%,and 83.1%on the ModelNet40,ShapeNetCore,and ScanObjectNN datasets,respectively.For indoor scene segmentation,training and testing were performed on the S3DIS dataset,and the mean intersection over union was 62.4%.Conclusions The proposed S^(2)ANet can effectively capture the local geometric information of point clouds,thereby improving accuracy on various tasks.展开更多
Jihei buffer zone of the Second Songhua River in lower reaches of Songyuan City of the Songhua River was taken as the research object,and the current water quality,point source and non-point source pollution,and regio...Jihei buffer zone of the Second Songhua River in lower reaches of Songyuan City of the Songhua River was taken as the research object,and the current water quality,point source and non-point source pollution,and regional social and economic conditions of the buffer zone and its upstream water functional area were investigated.According to pollution sources and pollutant carrying capacity of water functional areas,analysis on main pollution factors in buffer zone was completed.展开更多
The China Basic Medical Insurance Program was created in 1999 with three objectives:equal accessibility,affordability,and quality.Today,it has become the biggest medical insurance program in the world,covering 95%of C...The China Basic Medical Insurance Program was created in 1999 with three objectives:equal accessibility,affordability,and quality.Today,it has become the biggest medical insurance program in the world,covering 95%of China's population.Since 2015,China's healthcare ecosystem has been reshaped by increasing innovation,which has in turn been driven by regulatory reform,enhancement of research and development capability,and capital market development.There has also been improved regulatory efficiency to reduce lags in launching drugs.In 2022,nearly 20%of novel active substances launched globally were from China.China has also risen to become the second biggest contributor to innovation in terms of pipelines.Using a“fast-follow”strategy,many locally developed innovative drugs can compete with products from multinational companies in their quality and pricing.However,China's pharmaceutical and biotechnology industry will continue to face challenges in pricing and reimbursement,as well as a shortened product lifecycle with rapid price erosion.The government has already accelerated the timeline for updating the drug reimbursement list and is willing to create a high-quality medical insurance program.However,some obstacles are hard to overcome,including reimbursement for advanced therapies,limited funding and an increasing burden of disease due to an aging population.This article reviews the trajectory of medical innovation in China,including the challenges.Looking forward,balancing affordability and innovation will be critical for China to continue the trajectory of growth.The article also offers some suggestions for future policy reform,including optimizing reimbursement efficiency with a focus on highquality solutions,enhancing the value assessment framework,payer repositioning from“value buyer”to“strategic buyer”,and developing alternative market access pathways for innovative drugs.展开更多
文摘Background Despite the recent progress in 3D point cloud processing using deep convolutional neural networks,the inability to extract local features remains a challenging problem.In addition,existing methods consider only the spatial domain in the feature extraction process.Methods In this paper,we propose a spectral and spatial aggregation convolutional network(S^(2)ANet),which combines spectral and spatial features for point cloud processing.First,we calculate the local frequency of the point cloud in the spectral domain.Then,we use the local frequency to group points and provide a spectral aggregation convolution module to extract the features of the points grouped by the local frequency.We simultaneously extract the local features in the spatial domain to supplement the final features.Results S^(2)ANet was applied in several point cloud analysis tasks;it achieved stateof-the-art classification accuracies of 93.8%,88.0%,and 83.1%on the ModelNet40,ShapeNetCore,and ScanObjectNN datasets,respectively.For indoor scene segmentation,training and testing were performed on the S3DIS dataset,and the mean intersection over union was 62.4%.Conclusions The proposed S^(2)ANet can effectively capture the local geometric information of point clouds,thereby improving accuracy on various tasks.
文摘Jihei buffer zone of the Second Songhua River in lower reaches of Songyuan City of the Songhua River was taken as the research object,and the current water quality,point source and non-point source pollution,and regional social and economic conditions of the buffer zone and its upstream water functional area were investigated.According to pollution sources and pollutant carrying capacity of water functional areas,analysis on main pollution factors in buffer zone was completed.
文摘The China Basic Medical Insurance Program was created in 1999 with three objectives:equal accessibility,affordability,and quality.Today,it has become the biggest medical insurance program in the world,covering 95%of China's population.Since 2015,China's healthcare ecosystem has been reshaped by increasing innovation,which has in turn been driven by regulatory reform,enhancement of research and development capability,and capital market development.There has also been improved regulatory efficiency to reduce lags in launching drugs.In 2022,nearly 20%of novel active substances launched globally were from China.China has also risen to become the second biggest contributor to innovation in terms of pipelines.Using a“fast-follow”strategy,many locally developed innovative drugs can compete with products from multinational companies in their quality and pricing.However,China's pharmaceutical and biotechnology industry will continue to face challenges in pricing and reimbursement,as well as a shortened product lifecycle with rapid price erosion.The government has already accelerated the timeline for updating the drug reimbursement list and is willing to create a high-quality medical insurance program.However,some obstacles are hard to overcome,including reimbursement for advanced therapies,limited funding and an increasing burden of disease due to an aging population.This article reviews the trajectory of medical innovation in China,including the challenges.Looking forward,balancing affordability and innovation will be critical for China to continue the trajectory of growth.The article also offers some suggestions for future policy reform,including optimizing reimbursement efficiency with a focus on highquality solutions,enhancing the value assessment framework,payer repositioning from“value buyer”to“strategic buyer”,and developing alternative market access pathways for innovative drugs.
