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Methods and Practices for Institutional Benchmarking based on Research Impact and Competitiveness: A Case Study of ShanghaiTech University

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Journal of data and Information Science 2019年第3期4卷 55-72页

作者： Jiang Chang Jianhua Liu Library and information services ShanghaiTech University Shanghai 201210 China Beijing Wanfang Data Ltd. Beijing 100038 China

Purpose: To develop and test a mission-oriented and multi-dimensional benchmarking method for a small scale university aiming for internationally first-class basic research.Design/methodology/approach: An individualized evidence-based assessment scheme was employed to benchmark ShanghaiTech University against selected top research institutions,focusing on research impact and competitiveness at the institutional and disciplinary levels.Topic maps opposing ShanghaiTech and corresponding top institutions were produced for the main research disciplines of ShanghaiTech. This provides opportunities for further exploration of strengths and weakness. Findings: This study establishes a preliminary framework for assessing the mission of the university. It further provides assessment principles, assessment questions, and indicators.Analytical methods and data sources were tested and proved to be applicable and efficient.Research limitations: To better fit the selective research focuses of this university, its schema of research disciplines needs to be re-organized and benchmarking targets should include disciplinary top institutions and not necessarily those universities leading overall rankings.Current reliance on research articles and certain databases may neglect important research output types.Practical implications: This study provides a working framework and practical methods for mission-oriented, individual, and multi-dimensional benchmarking that ShanghaiTech decided to use for periodical assessments. It also offers a working reference for other institutions to adapt. Further needs are identified so that ShanghaiTech can tackle them for future benchmarking.Originality/value: This is an effort to develop a mission-oriented, individually designed,systematically structured, and multi-dimensional assessment methodology which differs from often used composite indices.

关键词： Differentiating evaluation Mission-driven assessment Evidence-based assessment Benchmarking Research performance

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BGB-A445,a novel non-ligand-blocking agonistic anti-OX40 antibody,exhibits superior immune activation and antitumor effects in preclinical models

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Frontiers of Medicine 2023年第6期17卷 1170-1185页

作者： Beibei Jiang Tong Zhang Minjuan Deng Wei Jin Yuan Hong Xiaotong Chen Xin Chen Jing Wang Hongjia Hou Yajuan Gao Wenfeng Gong Xing Wang Haiying Li Xiaosui Zhou Yingcai Feng Bo Zhang Bin Jiang Xueping Lu Lijie Zhang Yang Li Weiwei Song Hanzi Sun Zuobai Wang Xiaomin Song Zhirong Shen Xuesong Liu Kang Li Lai Wang Ye Liu Department of Biology BeiGene(Beijing)Co.Ltd.Beijing 102206China Department of Discovery Biomarkers BeiGene(Beijing)Co.Ltd.Beijing 102206China Department of Clinic Development BeiGene(Beijing)Co.Ltd.Beijing 102206China Department of Biologics BeiGene(Beijing)Co.Ltd.Beijing 102206China

t OX40 is a costimulatory receptor that is expressed primarily on activated CD4+,CD8+,and regulatory T cells.The ligation of OX40 to its sole ligand OX40L potentiates T cell expansion,differentiation,and activation and also promotes dendritic cells to mature to enhance their cytokine production.Therefore,the use of agonistic anti-Ox40 antibodies for cancer immunotherapy has gained great interest.However,most of the agonistic anti-OX40 antibodies in the clinic are OX40L-competitive and show limited efficacy.Here,we discovered that BGB-A445,a non-ligand-competitive agonistic anti-OX40 antibody currently under clinical investigation,induced optimal T cell activation without impairing dendritic cell function.In addition,BGB-A445 dose-dependently and significantly depleted regulatory T cells in vitro and in vivo via antibody-dependent cellular cytotoxicity.In the MC38 syngeneic model established in humanized OX40 knock-in mice,BGB-A445 demonstrated robust and dose-dependent antitumor efficacy,whereas the ligand-competitive anti-Ox40 antibody showed antitumor efficacy characterized by a hook effect.Furthermore,BGB-A445 demonstrated a strong combination antitumor effect with an anti-PD-1 antibody.Taken together,our findings show that BGB-A445,which does not block OX40-OX40L interaction in contrast to clinical-stage anti-OX40 antibodies,shows superior immune-stimulating effects and antitumor efficacy and thus warrants further clinical investigation.

关键词： BGB-A445 OX40 agonistic antibody OX40L noncompetitive

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Online Scheduling on Two Parallel Identical Machines Under a Grade of Service Provision

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Journal of the Operations Research Society of China 2022年第4期10卷 689-702页

作者： Shuang Cai Ke Liu data Department Beijing Kingsoft Cloud Network Technology Co.Ltd.Beijing100086China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing100190China University of Chinese Academy of Sciences Beijing100190China

In this paper,we investigate online scheduling problems on two parallel identical machines under a grade of service provision with makespan as the objective function.The jobs arrive over time and each job can be scheduled only when it has already been arrived.We consider three different versions:(i)the two machines cannot be idle at the same time until all arrived jobs have been processed;(ii)further to the first problem,jobs are processed on a first-come,first-serviced basis;(iii)each job must be assigned to one of the two machines as soon as it arrives.Respectively for three online scheduling problems,optimal online algorithms are proposed with competitive ratio(√5+1)/2,(√5+1)/2 and 5/3.

关键词： Online scheduling Parallel machines A grade of service provision GoS

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CDCAT: A Multi-Language Cross-Document Entity and Event Coreference Annotation Tool

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Tsinghua Science and Technology 2022年第3期27卷 589-598页

作者： Yang Xu Boming Xia Yueliang Wan Fan Zhang Jiabo Xu Huansheng Ning School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China beijing Engineering Research Center for Cyberspace data Analysis and Applications Beijing 100083China Research Institute with Run Technologies Company Ltd.Beijing 100192China School of Information Engineering Xinjiang Institute of EngineeringUrumqi 830091China

A tool for the manual annotation of cross-document entity and event coreferences that helps annotators to label mention coreference relations in text is essential for the annotation of coreference corpora. To the best of our knowledge, CROss-document Main Events and entities Recognition(CROMER) is the only open-source manual annotation tool available for cross-document entity and event coreferences. However, CROMER lacks multi-language support and extensibility. Moreover, to label cross-document mention coreference relations, CROMER requires the support of another intra-document coreference annotation tool known as Content Annotation Tool, which is now unavailable. To address these problems, we introduce Cross-Document Coreference Annotation Tool(CDCAT), a new multi-language open-source manual annotation tool for cross-document entity and event coreference, which can handle different input/output formats, preprocessing functions, languages, and annotation systems. Using this new tool, annotators can label a reference relation with only two mouse clicks. Best practice analyses reveal that annotators can reach an annotation speed of 0.025 coreference relations per second on a corpus with a coreference density of 0.076 coreference relations per word. As the first multi-language open-source cross-document entity and event coreference annotation tool, CDCAT can theoretically achieve higher annotation efficiency than CROMER.

关键词： event coreference entity coreference manual annotation tool natural language processing

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A subspace based method for modelling building’s thermal dynamic in district heating system and parameter extrapolation verification

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Building Simulation 2023年第11期16卷 2145-2158页

作者： Junfeng Zhang Lanbin Liu Yameng Liu University of Science and Technology beijing 30 Xueyuan RoadBeijing100083China beijing Nuanliu Technology Co. Ltd.Beijing100083China

The district heating system(DHS)consumes a lot of energy in winter,and its control accuracy needs to be improved urgently.To apply advanced process control(APC)in DHS,the thermal dynamic model of the existing buildings is essential.This paper uses the subspace method which is a data-driven approach for modelling the thermal dynamics of the building.The model’s performance is analyzed using the collected data,and the differences compared to the classical methods are also analyzed.The method reduces the RMSE by about 20%compared with the ARX model for the same complexity.Subsequently,the analysis of the training residuals indicates that the estimate of periodic intra-building disturbance can be obtained by minimizing the training residuals.By introducing the estimated disturbance function,the RMSE on the test set is further reduced by 26%.At the end of the article,a simple parameter extrapolation experiment is conducted,and the result shows that the parameters can be extrapolated to other buildings without large errors.

关键词： modelling district heating system state-space ARX thermal dynamics

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A data-Oriented Method to Optimize Hydraulic Fracturing Parameters of Tight Sandstone Reservoirs

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Energy Engineering 2024年第6期121卷 1657-1669页

作者： Zhengrong Chen Mao Jiang Chuanzhi Ai Jianshu Wu Xin Xie CNOOC Research Institute Co. Ltd.Beijing100028China

Based on the actual data collected from the tight sandstone development zone, correlation analysis using theSpearman method was conducted to determine the main factors influencing the gas production rate of tightsandstone fracturing. An integrated model combining geological engineering and numerical simulation of fracturepropagation and production was completed. Based on data analysis, the hydraulic fracture parameters wereoptimized to develop a differentiated fracturing treatment adjustment plan. The results indicate that the influenceof geological and engineering factors in the X1 and X2 development zones in the study area differs significantly.Therefore, it is challenging to adopt a uniform development strategy to achieve rapid production increase. Thedata analysis reveals that the variation in gas production rate is primarily affected by the reservoir thickness andpermeability parameters as geological factors. On the other hand, the amount of treatment fluid and proppantaddition significantly impact the gas production rate as engineering factors. Among these factors, the influence ofgeological factors is more pronounced in block X1. Therefore, the main focus should be on further optimizing thefracturing interval and adjusting the geological development well location. Given the existing well location, thereis limited potential for further optimizing fracture parameters to increase production. For block X2, the fracturingparameters should be optimized. data screening was conducted to identify outliers in the entire dataset, and adata-driven fracturing parameter optimization method was employed to determine the basic adjustment directionfor reservoir stimulation in the target block. This approach provides insights into the influence of geological,stimulation, and completion parameters on gas production rate. Consequently, the subsequent fracturing parameteroptimization design can significantly reduce the modeling and simulation workload and guide field operations toimprove and optimize hydraulic fracturing effic

关键词： data mechanism driven fracturing parameters gas production correlation tight sandstone gas

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Sludge composition and characteristics shaped microbial community and further determined process performance: A study on full-scale thermal hydrolysis-anaerobic digestion processes

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Journal of Environmental Sciences 2024年第3期137卷 96-107页

作者： Wei Liu Chenxiang Sun Wei Li Tianle Li Zhan Chen Jiawei Wang Zhengran Ren Xianghua Wen School of Environment Tsinghua UniversityBeijing 100084China Jinneng Holding Group DatongShanxi 037000China Research and Development Center Beijing Drainage Group Co.Ltd.Beijing 100124China beijing Dabeinong Science and Technology Group Co. Ltd.Beijing 100080China

Anaerobic digestion (AD) with thermal hydrolysis (TH) pretreatment is a promising process for excess sludge treatment,while there lacks of the knowledge from full-scale process about the impact of sludge composition and characteristics on microbial community and performance.The sludge physiochemical indices,microbial community and performance data of four full-scale TH-AD plants were characterized,and their relationships was elucidated.The four plants were operated under almost similar total organic loading rate (OLR)but their methanogenesis performance differentiate into two groups,namely superior group(SupG) and the inferior group (Inf G).In both groups,TH effectively solubilized particulate organic compounds,meanwhile raised the ammonia nitrogen (NH_(4)^(+)-N) and volatile fatty acid (VFA) concentration.Compared with the Sup G,thermal hydrolyzed sludge of Inf G had higher level of VFAs,NH_(4)^(+)-N and total chemical oxygen demand (t COD),which showed higher inhibition effect on microbes,leading to a community with lower diversity,lower abundance of carbohydrate degrading functional guild,higher protein degrading one,and methanogens that adapted to limited substrates,and further declined the methane production rate.Thus,it was recommended that OLR alone was not sufficient for controlling the system in design and operation,the concentration of VFAs,NH_(4)^(+)-N and t COD should be equally considered.Their higher concentration,together with the higher abundance of Defluviitoga and Proteiniphilum were recommended as indicators for inferior running condition.Our results proposed that microbial communities played a role of bridge between environmental factors and performance,provided implications for engineering ecology and operational regulation for full-scale sludge TH-AD process.

关键词： Thermal hydrolysis Anaerobic digestion Microbial community Full-scale

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Hyperspectral Image Classification Based on Capsule Network

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Chinese Journal of Electronics 2022年第1期31卷 146-154页

作者： MA Qiaoyu ZHANG Xin ZHANG Chunlei ZHOU Heng School of Science China University of Geosciences (Beijing) School of Statistics Beijing Normal University beijing Zhongdi Runde Petroleum Technology Co. Ltd.

The conventional convolutional neural network performs not well enough in the ground objects classification because of its insufficient ability in maintaining sensitive spectral information and characterizing the covariance of spatial structure, resulting from the narrow sensitive frequency band and complex spatial structure with diversity of hyperspectral remote sensing data which caused more serious phenomena of "same material, different spectra" and "different material, same spectra".Therefore, an improved capsule network is proposed and introduced into hyperspectral image target recognition. A convolution structure combining shallow features and multi-scale depth features is put forward to reduce the phenomena of "different material, same spectra" firstly,and then the diversity of the spatial structure is expressed by the capsule vector and sub-capsule division in channel wise, so that the averaging effect of the convolution process is weakened in the spectral domain and the spatial domain to reduce the phenomena of "same material, different spectra". By comparing the experimental results on the hyperspectral data sets such as Indian Pines,Salinas, Tea Tree and Xiongan, the capsule network shows strong spatial structure expression ability, flexible deep and shallow feature fusion ability in multi-scale, and its accuracy in target recognition is better than that of conventional convolutional neural networks, so it is suitable for the recognition of complex targets in hyperspectral images.

关键词： Capsule network Space-spectrum fusion Hyperspectral Classification Deep learning

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Bearing Fault Diagnosis Method of Wind Turbine Based on Improved Anti-Noise Residual Shrinkage Network

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Energy Engineering 2022年第2期119卷 665-680页

作者： Xiaolei Li beijing Goldwind Science&Goldwind Huineng Technology Co. Ltd.Beijing100176China

Aiming at the difficulty of rolling bearing fault diagnosis of wind turbine under noise environment,a new bearing fault identification method based on the Improved Anti-noise Residual Shrinkage Network(IADRSN)is proposed.Firstly,the vibration signals of wind turbine rolling bearings were preprocessed to obtain data samples divided into training and test sets.Then,a bearing fault diagnosis model based on the improved anti-noise residual shrinkage network was established.To improve the ability of fault feature extraction of the model,the convolution layer in the deep residual shrinkage network was replaced with a Dense-Net layer.To further improve the anti-noise ability of the model,the first layer of the model was set as the Drop-block layer.Finally,the labeled data samples were used for training model and the trained model was applied to the test set to output the fault diagnosis results.The results showed that the proposed method could achieve the fault diagnosis of wind turbine bearing more accurately in the high noise environment through comparison and verification.

关键词： Bearing fault diagnosis improved residual shrinkage network noise immunity

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Application of big data and artificial intelligence in epidemic surveillance and containment

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Intelligent Medicine 2023年第1期3卷 36-43页

作者： Zengtao Jiao Hanran Ji Jun Yan Xiaopeng Qi AI lab Yidu Cloud(Beijing)Technology Co.Ltd.Beijing 100083China Center for Global Public Health Chinese Center for Disease Control and PreventionBeijing 102206China

Faced with the current time-sensitive COVID-19 pandemic,the overburdened healthcare systems have resulted in a strong demand to develop newer methods to control the spread of the pandemic.Big data and artificial intelligence(AI)have been leveraged amid the COVID-19 pandemic;however,little is known about their use for supporting public health efforts.In epidemic surveillance and containment,efforts are needed to treat critical patients,track and manage the health status of residents,isolate suspected cases,and develop vaccines and antiviral drugs.The applications of emerging practices of artificial intelligence and big data have become powerful"weapons"to fight against the pandemic and provide strong support in pandemic prevention and control,such as early warning,analysis and judgment,interruption and intervention of epidemic,to achieve goals of early detection,early report,early diagnosis,early isolation and early treatment.These are the decisive factors to control the spread of the epidemic and reduce the mortality.This paper systematically summarized the application of big data and AI in epidemic,and describes practical cases and challenges with emphasis on epidemic prevention and control.The included studies showed that big data and AI have the potential strength to fight against COVID-19.However,many of the proposed methods are not yet widely accepted.Thus,the most rewarding research would be on methods that promise value beyond COVID-19.More efforts are needed for developing standardized reporting protocols or guidelines for practice.

关键词： Epidemic prevention and control Epidemiological investigation Artificial intelligence Big data Early

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