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Modeling viral evolution:A novel SIRSVIDE framework with application to SARS-CoV-2 dynamics

hLife 2024年第5期2卷 227-245页

作者： Kaichun Jin Xiaolu Tang Zhaohui Qian Zhiqiang Wu Zifeng Yang Tao Qian Chitin Hon Jian Lu State Key Laboratory of Protein and Plant Gene Research Center for BioinformaticsSchool of Life SciencesPeking UniversityBeijingChina NHC Key Laboratory of Systems Biology of Pathogens Institute of Pathogen BiologyChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory HealthThe First Affiliated Hospital of Guangzhou Medical UniversityGuangdongChina Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications Department of Engineering ScienceFaculty of Innovation EngineeringMacao University of Science and TechnologyMacaoChina Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases KingMed School of Laboratory MedicineGuangzhou Medical UniversityGuangdongChina Macao Center for Mathematical Sciences Macao University of Science and TechnologyMacaoChina Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacaoChina

Understanding evolutionary trends in emerging viruses,such as severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),is crucial for effective public health management and ***,extensive debates have arisen concerning viral evolutionary trends,particularly the interplay between transmissibility,pathogenicity,and immune *** this context,we have developed a novel computational model named SIRSVIDE(Susceptible-Infected-Recovered-Susceptible-Variation-Immune Decay-Immune Escape)to simulate the transmission and evolutionary dynamics of viral *** simulation results indicate that under conditions of high mutation rates,elevated transmission rates,and larger susceptible host populations,viral populations exhibit prolonged increases in transmissibility and immune escape,accompanied by reductions in pathogenicity and noticeable short-term fluctua***,when the total susceptible population size and mutation rate decrease,substantial uncertainty in the evolutionary trends of viral populations becomes *** summary,the SIRSVIDE model establishes a comprehensive framework for generating both short-and long-term viral epidemiological and evolutionary *** simulation outcomes align with existing evidence indicating that SARS-CoV-2 is undergoing selection for heightened transmissibility,decreased pathogenicity,and enhanced immune ***,the model sheds light on the possible evolutionary dynamics of other viruses.

关键词： viral evolution severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) transmissibility-pathogenicity trade-off immune escape

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Accuracy Raising Technique for Multivariate Spline Quasi-Interpolants over Type-2 Triangulations

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Journal of Mathematical Research with Applications 2022年第3期42卷 318-330页

作者： Shenggang ZHANG Chungang ZHU Qinjiao GAO School of Science Zhejiang University of Science and Technology School of Mathematical Sciences Dalian University of Technology School of Statistics and Mathematics Zhejiang Gongshang University Collaborative Innovation Center of Statistical Data Engineering Technology & ApplicationZhejiang Gongshang University

Given a multivariate quasi-interpolation operator with the partition of unity property,we propose a method to raise the accuracy with simple knots. The resulting operators possess higher accuracy while not requiring any derivative information of the underlying function. On that basis, we improve the multivariate spline quasi-interpolants with higher accuracy over type-2triangulations. Moreover, we apply the improved quasi-interpolants to simulate time developing partial differential equations(PDEs). The numerical experiments verify the efficiency of the proposed methods.

关键词： quasi-interpolation polynomial reproduction multivariate spline numerical solution

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Quantitative Applications of Weather Satellite data for Nowcasting:Progress and Challenges

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Journal of Meteorological Research 2024年第3期38卷 399-413页

作者： Jun LI Jing ZHENG Bo LI Min MIN Yanan LIU Chian-Yi LIU Zhenglong LI WPaul MENZEL Timothy J.SCHMIT John L.CINTINEO Scott LINDSTROM Scott BACHMEIER Yunheng XUE Yayu MA Di DI Han LIN Innovation Centre for Fengyun Meteorological Satellite(FYSIC) National Satellite Meteorological CentreChina Meteorological AdministrationBeijing100081China School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University and Southern Laboratory of Ocean Science and EngineeringZhuhai519082China Key Laboratory of Geographic Information Science(Ministry of Education) East China Normal UniversityShanghai200241China Research Center for Environmental Changes Academia SinicaTaipei11529China Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-MadisonMadisonWI53706USA Sensors and Calibration Branch STAR/NESDISMadisonWI53706USA Wuxi University Wuxi214105China School of Computer Science Chengdu University of Information TechnologyChengdu610225China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing210044China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National and Local Joint Engineering Research Center of Satellite Geospatial Information TechnologyFuzhou UniversityFuzhou350108China

Monitoring and predicting highly localized weather events over a very short-term period,typically ranging from minutes to a few hours,are very important for decision makers and public *** these events usually relies on radar observations through monitoring and *** advanced high-resolution imaging and sounding observations from weather satellites,nowcasting can be enhanced by combining radar,satellite,and other data,while quantitative applications of those data for nowcasting are advanced through using machine learning *** applications include monitoring the location,impact area,intensity,water vapor,atmospheric instability,precipitation,physical properties,and optical properties of the severe storm at different stages(pre-convection,initiation,development,and decaying),identification of storm types(wind,snow,hail,etc.),and predicting the occurrence and evolution of the *** observations can provide information on the environmental characteristics in the preconvection stage and are very useful for situational awareness and storm *** paper provides an overview of recent progress on quantitative applications of satellite data in nowcasting and its challenges,and future perspectives are also addressed and discussed.

关键词： weather satellite quantitative applications nowcasting pre-convection

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具有双功能酶活性的Au/Cu多级组装颗粒的构建

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science China Materials 2023年第4期66卷 1471-1483页

作者：李清张嘉兴王跃飞闵继伟申雨禾刘伟刘雪峰苏荣欣齐崴 State Key Laboratory of Chemical Engineering School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300072China Collaborative Innovation Center of Chemical Science and Engineering(Tianjin) Tianjin 300072China Tianjin Key Laboratory of Membrane Science and Desalination Technology Tianjin UniversityTianjin 300072China Automotive Data of China Co. Ltd.Tianjin 300300China

纳米酶被定义为具有独特纳米结构和催化活性的模拟酶.受天然酶的启发,我们报道了一种具有仿多酚氧化酶和过氧化物酶活性的双功能Au/Cu多级组装颗粒(Hops).它不但能够快速氧化难降解的有毒酚类污染物,还可以用于灵敏检测生物供能物质.Au/... 详细信息

纳米酶被定义为具有独特纳米结构和催化活性的模拟酶.受天然酶的启发,我们报道了一种具有仿多酚氧化酶和过氧化物酶活性的双功能Au/Cu多级组装颗粒(Hops).它不但能够快速氧化难降解的有毒酚类污染物,还可以用于灵敏检测生物供能物质.Au/Cu Hops纳米酶表现出优异的催化活性和可回收性,并且可在极端条件下保持稳定.值得注意的是,与天然漆酶相比,在相同质量浓度下,Au/Cu Hops纳米酶催化对苯二酚氧化反应具有更高的底物亲和力和6.37倍的Vmax.此外,基于Au/Cu Hops的仿过氧化物酶活性,我们构建了级联反应系统用于检测葡萄糖浓度,检测限低至5μmol L^(-1).最后,通过分子动力学模拟,我们证明了Cu-S簇在Au/Cu Hops表面形成双催化活性位点,并通过密度泛函理论计算揭示了纳米酶的催化途径.该工作对双功能纳米酶的构建和应用具有重要意义.

关键词：密度泛函理论计算灵敏检测纳米酶可回收性极端条件分子动力学模拟模拟酶葡萄糖浓度

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Multimedia Classification via Tensor Linear Discriminant Analysis

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IEEE Transactions on Broadcasting 2024年第4期70卷 1139-1152页

作者： Chang, Shih-Yu Wu, Hsiao-Chun Yan, Kun Chih-Hao Huang, Scott Wu, Yiyan San Jose State University Department Of Applied Data Science San JoseCA95192 United States Louisiana State University School Of Electrical Engineering And Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center For Ai Applications Taoyuan32003 Taiwan Guilin University Of Electronic Technology Guangxi Key Laboratory Of Wireless Wideband Communication And Signal Processing Department Of Information And Telecommunication Guilin541004 China National Tsing Hua University Department Of Electrical Engineering Hsinchu300 Taiwan Western University Department Of Electrical And Computer Engineering LondonONN6A 3K7 Canada

Linear discriminant analysis (LDA) is a well-known feature-extraction technique for data analytic and pattern classification. As the dimensionality of multimedia data has increased in this big era, it is often to characterize data by tensors. Over the past two decades, researchers have thus explored to extend LDA to the general tensor space, especially in two common ways: LDA of tensors using tensor decomposition methods (by conversion of tensors to matrices) and LDA of tensors built upon the T-product. However, both of the aforementioned approaches have restrictions thereby. A critical problem about how to carry out LDA of arbitrary scatter tensors based on the Einstein product still remains unsolved by the existing methods. Therefore, we propose a novel tensor LDA (a.k.a. TLDA) approach, which can carry out the LDA of arbitrary-dimensional scatter-tensors without any need of tensor decomposition. Besides, for reducing the computation time, we also design a parallel paradigm to execute our proposed TLDA in this work. Numerical experiments conducted over real multimedia data demonstrate the efficacy of our proposed new TLDA in terms of classification accuracy. Moreover, the comparison of the classification accuracies, computational-complexities, and memory-complexities of our proposed novel TLDA scheme and other existing tensor-based LDA methods is made. By leveraging TLDA for high-dimensional feature extraction, segmentation, and user-item interaction data processing, future multimedia recommendation systems can facilitate more accurate, engaging, and satisfactory user experience over the Internet. © 1963-12012 IEEE.

关键词： Tensors

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Progress in research on ultrasound radiomics for predicting the prognosis of breast cancer

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Cancer innovation 2023年第4期2卷 283-289页

作者： Xuantong Gong Xuefeng Liu Xiaozheng Xie Yong Wang Department of Ultrasound National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBejjing Advanced Innovation Center for Big Data and Brain Computing(BDBC)Beihang UniversityBeijingChina School of Computer and Communication Engi neering.University of Science and Technology Beijing BeijingChina

Breast cancer is the most common malignant tumor and the leading cause of cancer-related deaths in women *** means of predicting the prognosis of breast cancer are very helpful in guiding treatment and improving patients'*** extracted by radiomics reflect the genetic and molecular characteristics of a tumor and are related to its biological behavior and the patient's ***,radiomics provides a new approach to noninvasive assessment of breast cancer *** is one of the commonest clinical means of examining breast *** recent years,some results of research into ultrasound radiomics for diagnosing breast cancer,predicting lymph node status,treatment response,recurrence and survival times,and other aspects,have been *** this article,we review the current research status and technical challenges of ultrasound radiomics for predicting breast cancer *** aim to provide a reference for radiomics researchers,promote the development of ultrasound radiomics,and advance its clinical application.

关键词： breast cancer deeplearning prognosisprediction radiomics ultrasound

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V2I Based Environment Perception for Autonomous Vehicles at Intersections

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China Communications 2021年第7期18卷 1-12页

作者： Xuting Duan Hang Jiang Daxin Tian Tianyuan Zou Jianshan Zhou Yue Cao Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&Safety ControlSchool of Transportation Science and EngineeringBeihang UniversityBeijing 100191China School of Cyber Science and Engineering Wuhan UniversityWuhan 430072China

In recent years,autonomous driving technology has made good progress,but the noncooperative intelligence of vehicle for autonomous driving still has many technical bottlenecks when facing urban road autonomous driving challenges.V2I(Vehicle-to-Infrastructure)communication is a potential solution to enable cooperative intelligence of vehicles and *** this paper,the RGB-PVRCNN,an environment perception framework,is proposed to improve the environmental awareness of autonomous vehicles at intersections by leveraging V2I communication *** framework integrates vision feature based on *** normal distributions transform(NDT)point cloud registration algorithm is deployed both on onboard and roadside to obtain the position of the autonomous vehicles and to build the local map objects detected by roadside multi-sensor system are sent back to autonomous vehicles to enhance the perception ability of autonomous vehicles for benefiting path planning and traffic efficiency at the *** field-testing results show that our method can effectively extend the environmental perception ability and range of autonomous vehicles at the intersection and outperform the PointPillar algorithm and the VoxelRCNN algorithm in detection accuracy.

关键词： V2I environmental perception autonomous vehicles 3D objects detection

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Photothermal and pH dual-responsive self-healing coating for smart corrosion protection

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Journal of Materials science & Technology 2022年第12期107卷 34-42页

作者： Yao Huang Panjun Wang Weimin Tan Wenkui Hao Lingwei Ma Jinke Wang Tong Liu Fan Zhang Chenhao Ren Wei Liu Dawei Zhang Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China National Materials Corrosion and Protection Data Center University of Science and Technology BeijingBeijing 100083China National Engineering Research Center for Coatings CNOOC Changzhou Paint and Coatings Industry Research InstituteChangzhou 213016China State Key Laboratory of Advanced Power Transmission Technology(Global Energy Interconnection Research Institute Co.Ltd. )Beijing 100083China BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Graduate School of University of Science and Technology BeijingFoshan 528300China

A novel self-healing coating with photothermal and pH dual-responsive properties has been designed to protect carbon steel against corrosion by loading the stimuli-responsive microcapsules into a shape memory epoxy coating. The sandwich-like microcapsules were based on reduced graphene oxide/mesoporous silica(r GO@MS) assembled with a p H-responsive poly(N,N-dimethylaminoethyl methacrylate)(PDMAEMA) layer, and were loaded with benzotriazole(BTA) inhibitors(abbreviated as rGO@MS-P-BTA). Under near-infrared(NIR) light irradiation, the prominent photothermal effect of rGO could not only elevate the coating temperature to activate the shape memory effect and close the coating scratch, but also facilitate the release of corrosion inhibitors to suppress the corrosion activity. Moreover,the PDMAEMA as a p H-driven “gatekeeper” realized the controlled release of BTA from microcapsules at acid conditions. The surface morphology analysis, electrochemical impedance spectroscopy(EIS), and scanning electrochemical microscopy(SECM) were performed to evaluate the self-healing performance of the composite coatings. The results showed that the combination of NIR light and p H-responsive selfhealing effects endowed the coating with short healing time and prominent healing efficiency.

关键词： Self-healing coatings Corrosion inhibitors Photothermal effects pH-responsive Shape memory polymers

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Multi-Object Segmentation of Coronary Artery OCT Images Based on Multi-Scale Deeping Learning Method 42

Multi-Object Segmentation of Coronary Artery OCT Images Base...

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42nd Chinese Control Conference, CCC 2023

作者： Cheng, Hanchang Ren, Shangjie Zhang, Wei Hebei University of Technology Tianjin300401 China Tianjin University Tianjin300100 China Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Tianjin300401 China School of Artificial Intelligent and Data Science Hebei University of Technology Tianjin300130 China

ISBN: (纸本)9789887581543

Optical Coherence Tomography (OCT) is one of the most promising new laminar imaging techniques that has been developed rapidly in recent years. To achieve multi-objective segmentation of coronary arteries, a multi-scale and multi-object segmentation method based on the Deeplabv3+ model is proposed. The difficulty of this task is the small size of the targets as well as the size differences and shape similarities between the targets. This paper adds a multi-scale analysis module to the original deeplabv3+ base structure. In the model training, we obtain the pre-training model by training a small number of guidewires with obvious features, and later use the prior knowledge in it to train a larger number of objects with irregularly shaped stent. After experiments, it is shown that the model can achieve better segmentation in coronary OCT images with different object sizes. The accuracy of the model can reach 83.52% and the dice coefficient can reach 0.82. The method in this paper has obvious segmentation advantages for stents and guidewires in coronary arteries with multiple sizes, small objects, and blurred boundaries. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Optical tomography

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Find truth in the hands of the few:acquiring specific knowledge with crowdsourcing

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Frontiers of Computer science 2021年第4期15卷 5-16页

作者： Tao HAN Hailong SUN Yangqiu SONG Yili FANG Xudong LIU SKLSDE Lab School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100191China Department of Computer Science and Engineering Hong Kong University of Science and TechnologyClearwater BayHong Kong 999077China School of Computer and Information Engineering Zhejiang Gongshang UniversityHangzhou 310018China

Crowdsourcing has been a helpful mechanism to leverage human intelligence to acquire useful ***,when we aggregate the crowd knowledge based on the currently developed voting algorithms,it often results in common knowledge that may not be *** this paper,we consider the problem of collecting specific knowledge via *** the help of using external knowledge base such as WordNet,we incorporate the semantic relations between the alternative answers into a probabilisticmodel to determine which answer is more *** formulate the probabilistic model considering both worker’s ability and task’s difficulty from the basic assumption,and solve it by the expectation-maximization(EM)*** increase algorithm compatibility,we also refine our method into semi-supervised *** results show that our approach is robust with hyper-parameters and achieves better improvement thanmajority voting and other algorithms when more specific answers are expected,especially for sparse data.

关键词： crowdsourcing knowledge acquisition EM algorithm label aggregation

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