A detail-enhanced sampling strategy in Hadamard single-pixel imaging

Hadamard single-pixel imaging is an appealing imaging technique due to its features of low hardware complexity and industrial cost.To improve imaging efficiency,many studies have focused on sorting Hadamard patterns to obtain reliable reconstructed images with very few samples.In this study,we propose an efficient Hadamard basis sampling strategy that employs an exponential probability function to sample Hadamard patterns in a direction with high energy concentration of the Hadamard spectrum.We used the compressed-sensing algorithm for image reconstruction.The simulation and experimental results show that this sampling strategy can reconstruct object reliably and preserves the edge and details of images.

先进的前道CMP设备及整合解决方法

概述了未来IC器件可采用的前道CMP设备及整合解决方法的巨大进展。为提高设备的可用性和生产线的运作效率,在一台设备上采用多用途的整合解决方法。而且,对这些方法与下一代无磨料网膜抛光设备的能力进行了比较。未来数代器件要求的CMP工艺技术包括先进的抛光头、先进的现场终点系统、多平台、多抛光头结构。与下一代消耗品(单独硬抛光垫、高平面性磨料、无磨料抛光等)结合,能使直接抛光浅沟槽隔离(STI)工艺方法满足0.18μm乃至更小特征尺寸的器件要求。采用新型多步工艺进行了多晶硅CMP。先进的多晶硅金属介质(PMD)抛光工艺展示了更长寿命的抛光垫和更高的金刚石盘片生产效率和更强的设备可用性。这些工艺技术已全部成功地使用在生产线,并正在生产中进行测试。

Prediction of urban human mobility using large-scale taxi traces and its applications

This paper investigates human mobility patterns in an urban taxi transportation system. This work focuses on predicting human mobility from discovering patterns of in the number of passenger pick-ups quantity （PUQ） from urban hotspots. This paper proposes an improved ARIMA based prediction method to forecast the spatial-temporal variation of passengers in a hotspot. Evaluation with a large-scale real- world data set of 4 000 taxis＇ GPS traces over one year shows a prediction error of only 5.8%. We also explore the applica- tion of the pl^di^fioti approach to help drivers find their next passetlgerS, The sinatllation results using historical real-world data demonstrate that, with our guidance, drivers can reduce the time taken and distance travelled, to find their next pas- senger＋ by 37.1% and 6.4% respectively,

A Monte Carlo Neural Fictitious Self-Play approach to approximate Nash Equilibrium in imperfect-information dynamic games

Solving the optimization problem to approach a Nash Equilibrium point plays an important role in imperfect information games,e.g.,StarCraft and poker.Neural Fictitious Self-Play(NFSP)is an effective algorithm that learns approximate Nash Equilibrium of imperfect-information games from purely self-play without prior domain knowledge.However,it needs to train a neural network in an off-policy manner to approximate the action values.For games with large search spaces,the training may suffer from unnecessary exploration and sometimes fails to converge.In this paper,we propose a new Neural Fictitious Self-Play algorithm that combines Monte Carlo tree search with NFSP,called MC-NFSP,to improve the performance in real-time zero-sum imperfect-information games.With experiments and empirical analysis,we demonstrate that the proposed MC-NFSP algorithm can approximate Nash Equilibrium in games with large-scale search depth while the NFSP can not.Furthermore,we develop an Asynchronous Neural Fictitious Self-Play framework(ANFSP).It uses asynchronous and parallel architecture to collect game experience and improve both the training efficiency and policy quality.The experiments with th e games with hidden state information(Texas Hold^m),and the FPS(firstperson shooter)games demonstrate effectiveness of our algorithms.

Management and operation of extra-large Fangcang hospitals:experience and lessons from containing the highly contagious SARS-CoV-2 Omicron in Shanghai,China

Introduction Omicron is more contagious and stealthier than the previous strains.The basic reproduction number of Omicron is around 8–12,whereas that of the previous mainstream strain Delta is only 5–8[1].Omicron’s symptoms are relatively mild[2]compared with Delta’s symptoms;however,Omicron’s transmission ability is very strong,and its risk to children and the elderly remains high[3].In addition,the vaccine’s preventive effect on Omicron has weakened.Therefore,Omicron can easily cause a rapid outbreak in a city.The population density of megacities and the limited public health resources further exacerbate the difficulty of Omicron prevention and control.

Pyramid-VAE-GAN:Transferring hierarchical latent variables for image inpainting

Significant progress has been made in image inpainting methods in recent years.However,they are incapable of producing inpainting results with reasonable structures,rich detail,and sharpness at the same time.In this paper,we propose the Pyramid-VAE-GAN network for image inpainting to address this limitation.Our network is built on a variational autoencoder(VAE)backbone that encodes high-level latent variables to represent complicated high-dimensional prior distributions of images.The prior assists in reconstructing reasonable structures when inpainting.We also adopt a pyramid structure in our model to maintain rich detail in low-level latent variables.To avoid the usual incompatibility of requiring both reasonable structures and rich detail,we propose a novel cross-layer latent variable transfer module.This transfers information about long-range structures contained in high-level latent variables to low-level latent variables representing more detailed information.We further use adversarial training to select the most reasonable results and to improve the sharpness of the images.Extensive experimental results on multiple datasets demonstrate the superiority of our method.Our code is available at https://github.com/thy960112/Pyramid-VAE-GAN.

Protecting healthcare personnel from 2019-nCoV infection risks:lessons and suggestions

The outbreak of a novel coronavirus disease(COVID-19,caused by the 2019-nCoV infection)in December 2019 is one of the most severe public health emergencies since the founding of People’s Republic of China in 1949.Healthcare personnel(HCP)nationwide are facing heavy workloads and high risk of infection,especially those who care for patients in Hubei Province.Sadly,as of February 20,2020,over two thousand COVID-19 cases are confirmed among HCP from 476 hospitals nationwide,with nearly 90%of them from Hubei Province.Based on literature search and interviews with some HCP working at Wuhan,capital city of Hubei,we have summarized some of the effective measures taken to reduce infection among HCP,and also made suggestions for improving occupational safety during an infectious disease outbreak.The experience and lessons learned should be a valuable asset for international health community to contain the ongoing COVID-19 epidemic around the world.

Dynamic road crime risk prediction with urban open data

Crime risk prediction is helpful for urban safety and citizens’life quality.However,existing crime studies focused on coarse-grained prediction,and usually failed to capture the dynamics of urban crimes.The key challenge is data sparsity,since that 1)not all crimes have been recorded,and 2)crimes usually occur with low frequency.In this paper,we propose an effective framework to predict fine-grained and dynamic crime risks in each road using heterogeneous urban data.First,to address the issue of unreported crimes,we propose a cross-aggregation soft-impute(CASI)method to deal with possible unreported crimes.Then,we use a novel crime risk measurement to capture the crime dynamics from the perspective of influence propagation,taking into consideration of both time-varying and location-varying risk propagation.Based on the dynamically calculated crime risks,we design contextual features(i.e.,POI distributions,taxi mobility,demographic features)from various urban data sources,and propose a zero-inflated negative binomial regression(ZINBR)model to predict future crime risks in roads.The experiments using the real-world data from New York City show that our framework can accurately predict road crime risks,and outperform other baseline methods.

Taizhou’s COVID-19 prevention and control experience with telemedicine features

The outbreak of coronavirus disease 2019(COVID-19)has spread rapidly around the world.As of May 30,2020,a total of 84568 confirmed COVID-19 cases have been recorded in China,with a mortality rate of approximately 5.5%.Taizhou is a prefecture-level city in Zhejiang Province.A total of 146 cases were diagnosed in this epidemic,with a fatality rate of 0%.This condition is due to the establishment of an“Internet+”diagnosis and treatment model based on online medical application(APP),telemedicine,WeChat service,and consultation hotline in Taizhou.Taizhou led in opening the“COVID-19 Prevention and Treatment Special Line”in China,which is conducive to pre-hospital screening,suppressing social panic,and clinical support.Hospitals also carried out related online lectures and popularization of science.We summarize Taizhou’s COVID-19 prevention and control experience with telemedicine features,with a view to providing reference for the control of the epidemic at home and abroad.

Comprehensive narrative review of real-world COVID-19 vaccines:viewpoints and opportunities

Currently,people all over the world have been affected by coronavirus disease 2019(COVID-19).Fighting against COVID-19 is the top priority for all the countries and nations.The development of a safe and effective COVID-19 vaccine is considered the optimal way of ending the pandemic.Three hundred and 44 vaccines were in development,with 149 undergoing clinical research and 35 authorized for emergency use as to March 15 of 2022.Many studies have shown the effective role of COVID-19 vaccines in preventing SARS-CoV-2 infections as well as serious and fatal COVID-19 cases.However,tough challenges have arisen regarding COVID-19 vaccines,including long-term immunity,emerging COVID-19 variants,and vaccine inequalities.A systematic review was performed of recent COVID-19 vaccine studies,with a focus on vaccine type,efficacy and effectiveness,and protection against SARS-CoV-2 variants,breakthrough infections,safety,deployment and vaccine strategies used in the real-world.Ultimately,there is a need to establish a unified evaluation standard of vaccine effectiveness,monitor vaccine safety and effectiveness,along with the virological characteristics of SARS-CoV-2 variants;and determine the most useful booster schedule.These aspects must be coordinated to ensure timely responses to beneficial or detrimental situations.In the future,global efforts should be directed toward effective and immediate vaccine allocations,improving vaccine coverage,SARS-CoV-2 new variants tracking,and vaccine booster development.