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A route for the study on mass transfer enhancement by adding particles in liquid phase

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Chinese Journal of Chemical Engineering 2022年第8期35卷 158-165页

作者： Xing su Ning Qiao Bao-chang sun College of Chemical and Material Engineering Quzhou UniversityQuzhou 324000China State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical TechnologyBeijing 100029China Research Center of the Ministry of Education for High Gravity Engineering and Technology Beijing University of Chemical TechnologyBeijing 100029China

This work presents a route for the study on the absorption performance of gas into liquid under the condition of adding particles in a stirred constant temperature reactor.Two evaluated systems,hydrogen–water and hydrogen–methanol,with the addition of activated carbon particles(ACP)were carried out,respectively.The results showed that the addition of ACP into the water can enhance the mass transfer between hydrogen and water,the enhancement factor increases rapidly with the increase of the ACP content,and then tends to be unchanged.However,for the hydrogen–methanol system,ACP has little effect on the mass transfer performance.In addition,a gas–liquid mass transfer model considering the effect of solid particle enhancement was established based on the shuttle effect and two-film model.Results indicated that the predicted value agreed well with the experimental value in both hydrogen–methanol–ACP and hydrogen–water–ACP systems.

关键词： Mass transfer Hydrogen Water Methanol Activated carbon

Artificial intelligence for COVID-19: battling the pandemic with computational intelligence

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Intelligent Medicine 2022年第1期2卷 13-29页

作者： Zhenxing Xu chang su Yunyu Xiao Fei Wang Department of Population Health Sciences Weill Cornell MedicineCornell UniversityNew York 10065United States Department of Health Service Administration and Policy Temple UniversityPhiladelphia 19122United States

The new coronavirus disease 2019(COVID-19)has become a global pandemic leading to over 180 million confirmed cases and nearly 4 million deaths until June 2021,according to the World Health Organization.Since the initial report in December 2019,COVID-19 has demonstrated a high transmission rate(with an R_(0)>2),a diverse set of clinical characteristics(e.g.,high rate of hospital and intensive care unit admission rates,multi-organ dysfunction for critically ill patients due to hyperinflammation,thrombosis,etc.),and a tremendous burden on health care systems around the world.To understand the serious and complex diseases and develop effective control,treatment,and prevention strategies,researchers from different disciplines have been making significant efforts from different aspects including epidemiology and public health,biology and genomic medicine,as well as clinical care and patient management.In recent years,artificial intelligence(AI)has been introduced into the healthcare field to aid clinical decision-making for disease diagnosis and treatment such as detecting cancer based on medical images,and has achieved superior performance in multiple data-rich application scenarios.In the COVID-19 pandemic,AI techniques have also been used as a powerful tool to overcome the complex diseases.In this context,the goal of this study is to review existing studies on applications of AI techniques in combating the COVID-19 pandemic.Specifically,these efforts can be grouped into the fields of epidemiology,therapeutics,clinical research,social and behavioral studies and are summarized.Potential challenges,directions,and open questions are discussed accordingly,which may provide new insights into addressing the COVID-19 pandemic and would be helpful for researchers to explore more related topics in the post-pandemic era.

关键词： COVID-19 pandemic Artificial intelligence Electronic health record Machine learning

Numerical Simulation of Dust Removal in the Cyclone Collector of a Straw Crusher Based on a Discrete Phase Model

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Fluid Dynamics & Materials Processing 2023年第5期19卷 1143-1157页

作者： Zhuang Wu chang su Hua Xu Liu Wang State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mine Anhui University of Science and TechnologyHuainan232001China School of Mechanical Engineering Anhui University of Science and TechnologyHuainan232001China

The cyclone dust collector is an important subsystem of straw crushers used in agriculture.In the present study,a new type of dust collector with involute morphology is proposed to obtain better dust removal efficiency with respect to that of classical tangential and spiral dust collectors.A discrete phase model(DPM)method is used in synergy with a turbulence model,and the SIMPLE algorithm to simulate the flow field inside the dust collector and the related particle dynamics.It is shown that the internal flow field features a primary swirl,a secondary swirl and blockage effects.Moreover,for the involute dust collector,the tangential velocity in the initial stage and the pressure in the high-pressure area are larger than those obtained for the classical types.The dust removal efficiency is 37.11%,25.3%,and 16.37%for the involute type dust collector,the tangential type and the spiral type,respectively.

关键词： Cyclone dust collector the involute type efficiency of dust removal numerical simulation

Achieving Excellent Electromagnetic Interference Shielding Effectiveness in High Rare Earth Mg-12Gd-3Y alloy via Nd Addition Combined with Hot Rolling and Aging

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Acta Metallurgica Sinica(English Letters) 2023年第10期36卷 1665-1679页

作者： Wenlong Xu chang su Yuan Yuan Jingying Bai Xianhua Chen College of Materials Science&Engineering Chongqing UniversityChongqing400045China National Engineering Research Center for Mg Alloys Chongqing UniversityChongqing400045China Beijing Spacecrafts China Academy of Space TechnologyBeijing100194China

Achieving excellent electromagnetic interference(EMI)shielding effectiveness(SE)in high rare earth(RE)-content Mg alloys is currently a significant technical challenge.This work systematically investigated the effects of different Nd elements on the electrical conductivity and EMI SE of Mg-12Gd-3Y-xNd alloy by adding Nd elements to the high RE content Mg-12Gd-3Y alloy,followed by a combined process of hot rolling and aging(R-A).The results indicate that the addition of Nd elements leads to reduced solid solubility of Gd and Y,resulting in a large amount of precipitation.The Mg-12Gd-3Y-2.0Nd alloy has the optimum EMI SE after 63%R-A treatment,reaching 88-118 dB at 30-1500 MHz.The Mg-12Gd-3Y-xNd alloy has acicular and granular forms of the Mg5(Gd,Y,Nd)(abbreviated as Mg5RE)phase after R-A treatment.The granular Mg5RE phase gradually breaks up and refines into more minor scales with increasing rolling reduction and is diffusely distributed in the matrix.The acicular Mg5RE phase is densely arranged,with cross-distribution in some areas.The cross-distributed acicular Mg5RE phase,the delicate granular Mg5RE phase,and the denseβ′phase provide more interfaces for reflecting electromagnetic waves and increase the multiple reflection loss of incident electromagnetic waves.In addition,the Mg-12Gd-3Y-xNd alloy deflects most of the c-axis of the grains parallel to the normal direction(ND)as the rolling reduction increases,making the impedance difference between the plate surface and air larger.The increased impedance makes the material reflect more loss to incident electromagnetic waves.The combined use of these two leads to an excellent EMI SE of Mg-12Gd-3Y-xNd with high RE content after R-A treatment.

关键词： Mg-Gd-Y-Nd alloy Acicular phase Granular phase Electrical conductivity Electromagnetic interference shielding effectiveness

Fossil pharyngeal teeth of grass carp group and their implications for evolution, temporal and spatial distribution pattern, and paleoenvironment

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Science China Earth Sciences 2021年第11期64卷 1844-1859页

作者： Ruifeng su Mee-Mann chang Gengjiao CHEN Key Laboratory of Vertebrate Evolution and Human Origins Institute of Vertebrate of Paleontology and PaleoanthropologyChinese Academy of SciencesBeijing 100044China Beijing Institutes of Life Science Chinese Academy of SciencesBeijing 100101China Chinese Academy of Sciences Center for Excellence in Life and Paleoenvironment Beijing 100044China University of Chinese Academy of Sciences Bejing 100049China Natural History Museum of Guangxi Zhuang Autonomous Region Nanning 530012China

Grass carp(Ctenopharyngodon idella)is a cyprinid species,widely living in the freshwater on the plain area of East Asia.The fish has characteristic comb-like pharyngeal teeth,an adaptation to their typical vegetarian feeding habit.This paper deals with fossil pharyngeal teeth that related to grass carp,found from about 20 localities,ranging from the lower Oligocene to Holocene.Based on the morphology of the teeth,we established two new genera and species related to the genus Ctenopharyngodon(Dezaoia saintjaquensis,Eoctenopharyngodon liui)and two new species of Ctenopharyngodon(C.xiejiaensis and C.orientalis).The first recognized C.idella pharyngeal teeth were from the lower Pliocene of Yushe,Shanxi,and many others from 11 Pleistocene to Holocene localities.Judged from the materials and their occurrences,the grass carp may have originated from the western part of China during the early Oligocene.Throughout the Miocene,the grass-carp-like pharyngeal teeth were discovered from a vast area in China,indicating an appropriate atmosphere for the grass carp to develop,although the climate in the western part of China was possibly drier than that in the eastern part.From the beginning of the Pliocene,as the consequence of a considerable uplift of the Tibetan Plateau,the large rivers in East Asia finally formed,created favorable conditions for the Recent grass carp to thrive.Most teeth were collected in association with fossil mammals.Therefore,we are using the associated fossil mammals as the checking reference against which to test our interpretation of the surrounding environment of the water system in which the grass carp lived.

关键词： Comb-like pharyngeal teeth Grass carp and grass-carp-like fish Evolution Development of environment

Competition on robust deep learning

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National Science Review 2023年第6期10卷 13-15页

作者： Yinpeng Dong chang Liu Wenzhao Xiang Hang su Jun Zhu Department of Computer Science and Technology Institute for AI Tsinghua-Bosch Joint ML Center THBI Lab BNRist Center Tsinghua University Institute of Image Communication and Networks Engineering in the Department of Electronic Engineering (EE) Shanghai Jiao Tong University Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Peng Cheng Laboratory Pazhou Laboratory (Huangpu)

PROBLEM In recent years,the rapid development of artificial intelligence (AI) technology,especially machine learning and deep learning, is profoundly changing human production and lifestyle.In various fields,such as robotics,face recognition,autonomous driving and healthcare,AI is playing an important role.However,although AI is promoting the technological revolution and industrial progress,its security risks are often overlooked.Previous studies have found that the wellperforming deep learning models are extremely vulnerable to adversarial examples [1-3].The adversarial examples are crafted by applying small,humanimperceptible perturbations to natural examples,but can mislead deep learning models to make wrong predictions.The vulnerability of deep learning models to adversarial examples can raise security and safety threats to various realworld applications.

关键词： robustness adversarial example adversarial training deep learning

Genome-wide analysis of differential DNA methylation in Silver-Russell syndrome

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Science China(Life Sciences) 2017年第7期60卷 692-699页

作者： Di Wu Chunxiu Gong chang su Department of Endocrinology Genetics and Metabolism Beijing Children's Hospital Capital Medical University National Center for Children's Health MOE Key Laboratory of Major Diseases in Children Beijing 100045 China

Silver-Russell Syndrome(SRS) is clinically heterogeneous disorder characterized by low birth weight, postnatal growth restriction, and variable dysmorphic features. Current evidence strongly implicates imprinted genes as an important etiology of SRS. Although almost half of the patients showed DNA hypomethylation at the H19/IGF2 imprinted domain, and approximately7%–10% of SRS patients have maternal uniparental disomy of chromosome 7(UPD(7) mat); the rest of the SRS patients shows unknown etiology. In this study, we investigate whether there are further DNA methylation defects in SRS patients. We measured DNA methylation in seven SRS patients and five controls at more than 485,000 CpG sites using DNA methylation microarrays. We analyzed methylation changes genome-wide and identified the differentially methylated regions(DMRs) using bisulfite sequencing and digital PCR. Our analysis identifies epimutations at the previously characterized domains of H19/IGF2,providing proof of principle that our methodology can detect the changes in DNA methylation at imprinted loci. In addition,our results showed a novel SRS associated imprinted gene OSBPL5 located on chromosome 11p14 with the probe cg25963939,which is hypomethylated in 4/7 patients(P=0.023, β=.0.243). We also report DMRs in other genes including TGFβ3, HSF1,GAP43, NOTCH4 and MYH14. These DMRs were found to be associated with SRS using GO pathway analysis. In this study,we identified the probe cg25963939, located at the 5′UTR of imprinted gene OSBPL5, as a novel DMR that is associated with SRS. This finding provides new insights into the mechanism of SRS etiology and aid the further stratification of SRS patients by molecular phenotypes.

关键词： DNA甲基化基因组分析综合征罗素印迹基因 SRS 银低出生体重

Data-based real-time petrochemical gas diffusion simulation approach on virtual reality

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Virtual Reality & Intelligent Hardware 2023年第3期5卷 266-278页

作者： Min YANG Yong HAN chang su Xue LI Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China

Background Petrochemical products possess a high risk of flammability,explosivity,and toxicity,making petrochemical accidents exceedingly destructive.Therefore,disaster analysis,prediction,and real-time simulations have become important means of controlling and reducing accident hazards.Methods This study proposes a complete real-time simulation solution of gas diffusion with coordinate and concentration data,which was mainly aimed at simulating the types of harmful gas leakage and diffusion accidents in the petrochemical industry.The rendering effect was more continuous and accurate through grid homogenization and trilinear interpolation.This study presents a data processing and rendering parallelization process to enhance simulation efficiency.Gas concentration and fragment transparency were combined to synthesize transparent pixels in a scene.To ensure the approximate accuracy of the rendering effect,improve the efficiency of real-time rendering,and meet the requirement of intuitive perception using concentration data,a weighted blended order-independent transparency(OIT)with enhanced alpha weight is presented,which can provide a more intuitive perception of the hierarchical information of concentration data while preserving depth information.This study compares and analyzes three OIT algorithms-depth peeling,weighted blended OIT,and weighted blended OIT with enhanced alpha weight-in terms of rendering image quality,rendering time,required memory,and hierarchical information.Results Using weighted blended OIT with an enhanced alpha weight technique,the rendering time was shortened by 53.2%compared with that of the depth peeling algorithm,and the texture memory required was significantly smaller than that of the depth peeling algorithm.The rendering results of weighted blended OIT with an enhanced alpha weight were approximately accurate compared with those of the depth peeling algorithm as the ground truth,and there was no popping when surfaces passed through one another.Simultaneously,compared with weighted b

关键词： Real-time gas diffusion simulation Trilinear interpolation Order-independent transparency rendering parallelization

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis:A Review

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 814-835页

作者： Matthew Brendel chang su Zilong Bai Hao Zhang Olivier Elemento Fei Wang Department of Population Health Sciences Weill Cornell MedicineCornell UniversityNew YorkNY 10065USA Institute for Computational Biomedicine Caryl and Israel Englander Institute for Precision MedicineDepartment of Physiology and BiophysicsWeill Cornell MedicineCornell UniversityNew YorkNY 10065USA Department of Health Service Administration and Policy Temple UniversityPhiladelphiaPA 19122USA

Single-cell RNA sequencing(scRNA-seq)has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously.Analysis of scRNA-seq data plays an important role in the study of cell states and phenotypes,and has helped elucidate biological processes,such as those occurring during the development of complex organisms,and improved our understanding of disease states,such as cancer,diabetes,and coronavirus disease 2019(COVID-19).Deep learning,a recent advance of artificial intelligence that has been used to address many problems involving large datasets,has also emerged as a promising tool for scRNA-seq data analysis,as it has a capacity to extract informative and compact features from noisy,heterogeneous,and high-dimensional scRNA-seq data to improve downstream analysis.The present review aims at surveying recently developed deep learning techniques in scRNA-seq data analysis,identifying key steps within the scRNA-seq data analysis pipeline that have been advanced by deep learning,and explaining the benefits of deep learning over more conventional analytic tools.Finally,we summarize the challenges in current deep learning approaches faced within scRNA-seq data and discuss potential directions for improvements in deep learning algorithms for scRNA-seq data analysis.

关键词： Single-cell RNA sequencing Single-cell sequencing Deep learning Deep neural network Artificial intelligence