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CEPC Technical Design Report

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Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai wujun Cai Yijian Cai Yizhou Cai Yuchen Cai Haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen Xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho Ming-Chung Chu Xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH university of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui university HefeiAnhui Applied Physics department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu university Institute of ScienceVaranasi Bandirma Onyedi Eylul university Bandirma Beihang university Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal university Beijing Brown university ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad university Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo university Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal university WuhanHubei Central South university ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang university HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China university of Geosciences Beijing China university of Geosciences WuhanHubei China university of Mining and Technology XuzhouJiangsu China West Normal university NanchongSichuan Chongqing university Department of PhysicsChongqing Chulalongkorn university Bangkok City university of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell university IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu university DalianLiaoning Dalian university of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China university Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

Energy storage materials derived from Prussian blue analogues

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Science Bulletin 2017年第5期62卷 358-368页

作者： Feng Ma Qing Li Tanyuan Wang Hanguang zhang Gang wu State Key Laboratory of Material Processing and Die & Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China department of Chemical and Biological Engineering University at Buffalo The State University of New York Buffalo NY 14260 USA

Prussian blue analogues(PBAs) with open frameworks have drawn much attention in energy storage fields due to their tridimensional ionic diffusion path, easy preparation, and low cost. This review summarizes the recent progress of using PBAs and their derivatives as energy storage materials in alkali ions,multi-valent ions, and metal-air batteries. The key factors to improve the electrochemical performance of PBAs as cathode materials in rechargeable batteries were firstly discussed. Several approaches for performance enhancement such as controlling the amounts of vacancies and coordinated water, optimizing morphologies, and depositing carbon coating are described in details. Then, we highlighted the significance of their diverse architectures and morphologies in anode materials for lithium/sodium ion batteries. Finally, the applications of Prussian blue derivatives as catalysts in metal-air batteries are also reviewed, providing insights into the origin of favorable morphologies and structures of catalyst for the optimal performance.

关键词： Prussian blue analogues Energy storage Rechargeable battery Open frameworks Cathode materials Anode materials Catalysts

Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi_(2)N_(4)

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npj Computational Materials 2022年第1期8卷 1216-1222页

作者： Yabei wu Zhao Tang Weiyi Xia Weiwei Gao Fanhao Jia Yubo zhang Wenguang Zhu Wenqing zhang Peihong zhang department of Materials Science and Engineering and Shenzhen Institute for Quantum Science&engineering Southern University of Science and TechnologyShenzhenGuangdong518055China Guangdong Provincial Key Lab for Computational Science and Materials Design and Shenzhen Municipal Key Lab for Advanced Quantum Materials and DevicesSouthern University of Science and TechnologyShenzhenGuangdong518055China ICQD Hefei National Laboratory for Physical Science at the MicroscaleKey Laboratory of Strongly-Coupled Quantum Matter PhysicsChinese Academy of SciencesDepartment of Physicsand Synergetic Innovation Center of Quantum Information and Quantum PhysicsUniversity of Science and Technology of ChinaHefeiAnhui230026China department of Physics University at BuffaloState University of New YorkBuffaloNY14260USA department of Physics Dalian University of TechnologyDalianLiaoning116024China International Centre for Quantum and Molecular Structures Materials Genome InstituteDepartment of PhysicsShanghai University99 Shangda RoadShanghai200444China

The electronic structure of two-dimensional(2D)materials are inherently prone to environmental perturbations,which may pose significant challenges to their applications in electronic or optoelectronic devices.A 2D material couples with its environment through two mechanisms:local chemical coupling and nonlocal dielectric screening *** local chemical coupling is often difficult to predict or control *** dielectric screening,on the other hand,can be tuned by choosing the substrates or layer thickness in a controllable ***,a compelling 2D electronic material should offer band edge states that are robust against local chemical coupling *** it is demonstrated that the recently synthesized MoSi_(2)N_(4)is an ideal 2D semiconductor with robust band edge states protected from capricious environmental chemical coupling *** many-body perturbation theory calculations are carried out to illustrate how the band edge states of MoSi_(2)N_(4)are shielded from the direct chemical coupling effects,but its quasiparticle and excitonic properties can be modulated through the nonlocal dielectric screening *** unique property,together with the moderate band gap and the thermodynamic and mechanical stability of this material,paves the way for a range of applications of MoSi_(2)N_(4)in areas including energy,2D electronics,and optoelectronics.

关键词： dielectric protected quasi

Machine learning-based prognostic and metastasis models of kidney cancer

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Cancer Innovation 2022年第2期1卷 124-134页

作者： Yuxiang zhang Na Hong Sida Huang Jie wu Jianwei Gao Zheng Xu Fubo zhang Shaohui Ma Ye Liu Peiyuan Sun Yanping Tang Chun Liu Jianzhong shou Meng Chen National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina Digital Health China Technologies Co.Ltd.BeijingChina department of public policy Cornell UniversityIthacaNew YorkUSA The Key Laboratory of Geriatrics Beijing Institute of GeriatricsInstitute of Geriatric MedicineChinese Academy of Medical SciencesBeijing Hospital/National Center of Gerontology of National Health CommissionBeijingChina

Background:Kidney cancer originates from the urinary tubule epithelial system of the renal parenchyma,accounting for 20% of all urinary system *** 70% of cases are localized at diagnosis,and 30%are *** localized kidney cancers can be cured by surgery,but most metastatic patients relapse after surgery and eventually die of kidney ***,accurately predicting patient survival and identifying high-risk metastatic patients will effectively guide interventions and improve ***:This study used the data of 12,394 kidney cancer patients from the surveillance,epidemiology,and end results database to construct a research cohort related to kidney cancer survival and *** machine learning models(including support vector machines,logistic regression,decision tree,random forest,XGBoost,AdaBoost,K-nearest neighbors,and multilayer perceptron)were developed to predict the survival and metastasis of kidney cancer and six evaluation indicators(accuracy,precision,sensitivity,specificity,F1 score,and area under the receiver operating characteristic[AUROC])were used to verify,evaluate,and optimize the ***:Among the eight machine learning models,Logistic Regression has the highest AUROC in both prediction *** 3-year survival prediction,the Logistic Regression model had an accuracy of 0.684,a sensitivity of 0.702,a specificity of 0.670,a precision of 0.686,an F1 score of 0.683,and an AUROC of *** tumor metastasis prediction,the Logistic Regression model had an accuracy of 0.800,a sensitivity of 0.540,a specificity of 0.830,a precision of 0.769,an F1 score of 0.772,and an AUROC of ***:In this study,we selected appropriate variables from both statistical and clinical significance and developed and compared eight machine learning models for predicting 3-year survival and metastasis of kidney *** prediction results and evaluation results demonstrated that our model could provide decis

关键词： machine learning kidney cancer survival metastasis prognostic model

Dual-sized hollow particle incorporated fibroin thermal insulating coatings on catheter for cerebral therapeutic hypothermia

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Bioactive Materials 2023年第8期26卷 116-127页

作者： Ming Li Yuan Gao Miaowen Jiang Hongkang zhang Yang zhang Yan wu Wenhao Zhou Di wu Chuanjie wu Longfei wu Luzi Bao Xiaoxiao Ge Zhengfei Qi Ming Wei Ang Li Yuchuan Ding Jicheng zhang Guangzhen Pan Yu wu Yan Cheng Yufeng Zheng Xunming Ji China-America Institute of Neuroscience and Beijing Institute of Geriatrics Xuanwu HospitalCapital Medical UniversityBeijing100053China School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing100191China Beijing Institute for Brain Disorders Capital Medical UniversityBeijing100069China School of Materials Science and Engineering Peking UniversityBeijing100871China Shaanxi Key Laboratory of Biomedical Metallic Materials Northwest Institute for Nonferrous Metal ResearchXi’an710016China department of Biomedical Engineering Columbia UniversityNew York CityNY10027USA department of Neurosurgery Wayne State University School of MedicineDetroitMI48201USA Gong Yi Van-research Innovation Composite Material Co.Ltd Zheng Zhou451299China department of Neurosurgery Xuanwu HospitalCapital Medical UniversityBeijing100053China

Selective endovascular hypothermia has been used to provide cooling-induced cerebral neuroprotection,but current catheters do not support thermally-insulated transfer of cold infusate,which results in an increased exit temperature,causes hemodilution,and limits its cooling ***,air-sprayed fibroin/silica-based coatings combined with chemical vapor deposited parylene-C capping film was prepared on *** coating features in dual-sized-hollow-microparticle incorporated structures with low thermal *** infusate exit temperature is tunable by adjusting the coating thickness and infusion *** peeling or cracking was observed on the coatings under bending and rotational scenarios in the vascular *** efficiency was verified in a swine model,and the outlet temperature of coated catheter(75μm thickness)was 1.8-2.0◦C lower than that of the uncoated *** pioneering work on catheter thermal insulation coatings may facilitate the clinical translation of selective endovascular hypothermia for neuroprotection in patients with acute ischemic stroke.

关键词： Silk fibroin Thermal insulation coating Catheter Stroke Hypothermia

Combined subsampling and analytical integration for efficient large-scale GW calculations for 2D systems

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npj Computational Materials 2020年第1期6卷 660-668页

作者： Weiyi Xia Weiwei Gao Gabriel Lopez-Candales Yabei wu Wei Ren Wenqing zhang Peihong zhang department of Physics University at BuffaloState University of New YorkBuffaloNY 14260USA Center for Computational Materials Oden Institute for Computational Engineering and SciencesThe University of Texas at AustinAustinTX 78712USA department of Physics and Shenzhen Institute for Quantum Science&Engineering Southern University of Science and TechnologyShenzhen 518055 GuangdongChina Guangdong Provincial Key Lab for Computational Science and Materials Design Southern University of Science and TechnologyShenzhen 518055 GuangdongChina Shenzhen Municipal Key Lab for Advanced Quantum Materials and Devices Southern University of Science and TechnologyShenzhen 518055 GuangdongChina International Centre for Quantum and Molecular Structures Shanghai UniversityShanghai 200444China department of Physics Shanghai UniversityShanghai 200444China

Accurate and efficient predictions of the quasiparticle properties of complex materials remain a major challenge due to the convergence issue and the unfavorable scaling of the computational cost with respect to the system *** GW calculations for two-dimensional(2D)materials are especially *** unusual analytical behaviors of the dielectric screening and the electron self-energy of 2D materials make the conventional Brillouin zone(BZ)integration approach rather inefficient and require an extremely dense k-grid to properly converge the calculated quasiparticle *** this work,we present a combined nonuniform subsampling and analytical integration method that can drastically improve the efficiency of the BZ integration in 2D GW calculations.

关键词： analytical integration subsampling

Three paralogous clusters of the miR-17-92 family of microRNAs restrain IL-12-mediated immune defense

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Cellular & Molecular Immunology 2021年第7期18卷 1751-1760页

作者： Xiang zhang Sinead MSmith Xi Wang Baohong Zhao Li wu Xiaoyu Hu Institute for Immunology and School of Medicine Tsinghua UniversityBeijing100084China Tsinghua-Peking Center for Life Sciences Beijing10084China Beijing Key Laboratory for Immunological Research on Chronic Diseases Beijing100084China department of Clinical Medicine School of MedicineTrinity College DublinDublinIreland department of Immunology Beijing Key Laboratory for Cancer Invasion and MetastasisAdvanced Innovation Center for Human Brain ProtectionSchool of Basic Medical SciencesCapital Medical UniversityBeijing100069China Arthritis and Tissue Degeneration Program and the David Z.Rosensweig Genomics Research Center Hospital for Special SurgeryNew YorkNY10021USA department of Medicine Weill Cornell Medical CollegeNew YorkNY10021USA

MicroRNAs(miRNAs)have been widely implicated in immune regulation,but evidence for the coordinated function of paralogous miRNA clusters remains ***,by using genetically modified mice with individual or combined cluster deficiencies,we found that three paralogous clusters of the miR-17-92 family of miRNAs collectively suppressed IL-12 production in ***,miR-17-92 family miRNAs deficiencies resulted in heightened production of IL-12 and thus enhanced the host defense against intracellular pathogen Listeria monocytogenes in ***,different members of the miR-17-92 family of miRNAs acted on a common target,PTEN,to inhibit IL-12 expression by modulating the PI3K-Akt-GSK3 *** addition,the expression of miR-17-92 family miRNAs was collectively inhibited by the transcription factor RBP-J,and RBP-J-associated macrophage functional defects were genetically rescued by deleting three clusters of miR-17-92 family miRNAs on a RBP-J null ***,our results illustrated key roles of three clusters of miR-17-92 family miRNAs in cooperatively controlling IL-12-mediated immune responses and identified miR-17-92 family miRNAs as functional targets of RBP-J in macrophages.

关键词： miR-17-92 family miRNAs microRNA IL-12 RBP-J Macrophages

Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning

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World Journal of Pediatrics 2023年第11期19卷 1094-1103页

作者： Wen‑Yuan zhang Zhong‑Hua Chen Xiao‑Xia An Hui Li Hua‑Lin zhang Shui‑Jing wu Yu‑Qian Guo Kai zhang Cong‑Li Zeng Xiang‑Ming Fang department of Anesthesiology and Intensive Care School of MedicineThe First Affiliated HospitalZhejiang UniversityQingChun Road 79Hangzhou 310003China department of Anesthesiology Shaoxing People’s Hospital(Shaoxing HospitalZhejiang University School of Medicine)Shaoxing 312000China department of Anesthesiology Vagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNYUSA

Background Pediatric sepsis is a complicated condition characterized by life-threatening organ failure resulting from a dysregulated host response to infection in *** is associated with high rates of morbidity and mortality,and rapid detection and administration of antimicrobials have been *** objective of this study was to evaluate the diagnostic biomarkers of pediatric sepsis and the function of immune cell infiltration in the development of this *** Three gene expression datasets were available from the Gene Expression Omnibus ***,the differentially expressed genes(DEGs)were found with the use of the R program,and then gene set enrichment analysis was carried ***,the DEGs were combined with the major module genes chosen using the weighted gene co-expression *** hub genes were identified by the use of three machine-learning algorithms:random forest,support vector machine-recursive feature elimination,and least absolute shrinkage and selection *** receiver operating characteristic curve and nomogram model were used to verify the discrimination and efficacy of the hub *** addition,the inflammatory and immune status of pediatric sepsis was assessed using cell-type identification by estimating relative subsets of RNA transcripts(CIBERSORT).The relationship between the diagnostic markers and infiltrating immune cells was further *** Overall,after overlapping key module genes and DEGs,we detected 402 overlapping *** pediatric sepsis diagnostic indicators,CYSTM1(AUC=0.988),MMP8(AUC=0.973),and CD177(AUC=0.986)were investigated and demonstrated statistically significant differences(P<0.05)and diagnostic efficacy in the validation *** indicated by the immune cell infiltration analysis,multiple immune cells may be involved in the development of pediatric ***,all diagnostic characteristics may correlate with immune cells to varying *** The candida

关键词： Paediatric sepsis Bioinformatics Machine-Learning Biomarkers Immune cell infiltration

Revealing the dynamics of the alloying and segregation of Pt-Co nanoparticles via in-situ environmental transmission electron microscopy

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Nano Research 2023年第2期16卷 3055-3062页

作者： Xing Li Shaobo Cheng Yanghua He Lixiang Qian Dmitri Zakharov Gang wu Chongxin Shan Liang zhang Dong Su Henan Key Laboratory of Diamond Optoelectronic Materials and Devices Key Laboratory of Material PhysicsSchool of Physics and MicroelectronicsZhengzhou UniversityZhengzhou 450052China Center for Functional Nanomaterials Brookhaven National LaboratoryUptonNY 11973USA department of Chemical and Biological Engineering University at BuffaloThe State University of New YorkBuffaloNY 14260USA Center for Combustion Energy School of Vehicle and MobilityTsinghua UniversityBeijing 100084China Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China

Thermal treatment is a general and efficient way to synthesize intermetallic catalysts and may involve complicated physical *** far,the mechanisms leading to the size and composition heterogeneity,as well as the phase segregation behavior in Pt-Co nanoparticles(NPs)are still not well *** in-situ environmental transmission electron microscopy,the formation dynamics and segregation behaviors of Pt-Co alloyed NPs during the thermal treatment were *** is found that Pt-Co NPs on zeolitic imidazolate frameworks-67-derived nanocarbon(NC)are formed consecutively through both particle migration coalescence and the Ostwald ripening *** existence of Pt NPs is found to affect the movement of Co NPs during their *** the help of theoretical calculations,the correlations between the composition and migration of the Pt and Co during the ripening process were *** complex alloying processes are revealed as key factors leading to the heterogeneity of the synthesized Pt-Co alloyed *** oxidation environment,the Pt-Co NPs become surface faceted gradually,which can be attributed to the oxygen facilitated relatively higher segregation rate of Co from the(111)*** work advances the fundamental understanding of design,synthesis,and durability of the Pt-based nanocatalysts.

关键词： intermetallic catalyst alloying ripening segregation dynamics environmental transmission electron microscopy(ETEM)