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A large-scale transcriptional study reveals inhibition of COVID-19 related cytokine storm by traditional Chinese medicines

引用

Science Bulletin 2021年第9期66卷 884-888,M0003页

作者： Yifei Dai Weijie Qiang Yu Gui Xue Tan Tianli Pei Kequan Lin Siwei Cai Liang Sun Guochen Ning Jianxun Wang Hongyan Guo Yimin Sun Jing Cheng Lan Xie Xun Lan Dong Wang State Key Laboratory of Southwestern Chinese Medicine Resources School of Basic Medical SciencesChengdu University of Traditional Chinese MedicineChengdu 611137China Department of Basic Medical Sciences School of MedicineTsinghua UniversityBeijing 100084China Institute of Medicinal Plant Development Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100193China School of Pharmacy Chengdu University of Traditional Chinese MedicineChengdu 611137China High Performance Computing Department National Supercomputing Center in ShenzhenShenzhen 518055China Department of Electronic and Computer Engineering College of EngineeringDrexel UniversityPhiladelphia 19104USA Dongli District Jinqiao Street Community Health Service Center Tianjin 300300China Department of Biomedical Engineering School of MedicineTsinghua UniversityBeijing 100084China School of Life Sciences Beijing University of Chinese MedicineBeijing 100029China National Engineering Research Center for Beijing Biochip Technology Beijing 102206China State Key Laboratory of Membrane Biology School of MedicineTsinghua UniversityBeijing 100084China Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases Hangzhou 310003China Medical Systems Biology Research Center School of MedicineTsinghua UniversityBeijing 100084China

The application of traditional Chinese medicine(TCM)has made great contributions to the fight against the epidemic of coronavirus disease-2019(COVID-19).Despite the remarkable therapeutic effects of TCM,the molecular mechanisms of TCM formulae inhibiting COVID-19 are still not fully ***,we cφm-bined the automated high throughput sequencing-based high throughput screening(HTS^(2))assay with bioinformatics and computer-aided drug design(CADD)to investigate the molecular mechanisms of TCM-mediated therapeutic effects on COVID-19-related cytokine storm(Fig.1a).

关键词：细胞因子风暴六君子汤理中汤诊疗方案黄连解毒汤中药提取物肺炎分子机制

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Composite behavioral modeling for identity theft detection in online social networks

arXiv

引用

arXiv 2018年

作者： Wang, Cheng Yang, Bo Department of Computer Science and Technology Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education China

In this work, we aim at building a bridge from poor behavioral data to an effective, quick-response, and robust behavior model for online identity theft detection. We concentrate on this issue in online social networks (OSNs) where users usually have composite behavioral records, consisting of multi-dimensional low-quality data, e.g., offline check-ins and online user generated content (UGC). As an insightful result, we find that there is a complementary effect among different dimensions of records for modeling users' behavioral patterns. To deeply exploit such a complementary effect, we propose a joint model to capture both online and offline features of a user's composite behavior. We evaluate the proposed joint model by comparing with some typical models on two real-world datasets: Foursquare and Yelp. In the widely-used setting of theft simulation (simulating thefts via behavioral replacement), the experimental results show that our model outperforms the existing ones, with the AUC values 0:956 in Foursquare and 0:947 in Yelp, respectively. Particularly, the recall (True Positive Rate) can reach up to 65:3% in Foursquare and 72:2% in Yelp with the corresponding disturbance rate (False Positive Rate) below 1%. It is worth mentioning that these performances can be achieved by examining only one composite behavior (visiting a place and posting a tip online simultaneously) per authentication, which guarantees the low response latency of our method. This study would give the cybersecurity community new insights into whether and how a real-time online identity authentication can be improved via modeling users' composite behavioral patterns. Copyright © 2018, The Authors. All rights reserved.

关键词： Behavioral research

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Vision-based Semantic Mapping and Localization for Autonomous Indoor Parking

Vision-based Semantic Mapping and Localization for Autonomou...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Huang, Yewei Zhao, Junqiao He, Xudong Zhang, Shaoming Feng, Tiantian Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China School of Surveying and Geo-Informatics Tongji University Shanghai China

ISBN: (纸本)9781538644522

In this paper, we proposed a novel and practical solution for the real-time indoor localization of autonomous driving in parking lots. High-level landmarks, the parking slots, are extracted and enriched with labels to avoid the aliasing of low-level visual features. We then proposed a robust method for detecting incorrect data associations between parking slots and further extended the optimization framework by dynamically eliminating suboptimal data associations. Visual fiducial markers are introduced to improve the overall precision. As a result, a semantic map of the parking lot can be established fully automatically and robustly. We experimented the performance of real-time localization based on the map using our autonomous driving platform TiEV, and the average accuracy of 0.3m track tracing can be achieved at a speed of 10kph. © 2018 IEEE.

关键词： Autonomous vehicles

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The dominant role of East Asia warming in increasing tropical western North Pacific tropical cyclone intensity

Research Square

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Research Square 2021年

作者： Xu, Jing Zhao, Ping Chan, Johnny C.L. Shi, Mingyuan Yang, Chi Xing, Rui Zhao, Siyu State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing China Guy Carpenter Asia-Pacific Climate Impact Centre School of Energy and Environment City University of Hong Kong Hong Kong National Meteorological Information Center Beijing China College of Global Change and Earth System Science Beijing Normal University Beijing China Meteorological Service in Binhai New Area Tianjin China University of California at Los Angeles CA United States

The increase in intense tropical cyclone (TC) activity over the western North Pacific (WNP) has often been linked to a warming ocean1-8. Here we show, however, that the TC intensity increasing trend in the tropical WNP during the past three decades are mainly related to the warming of the East Asian continent, especially a warming Tibetan Plateau (TP). The regional weak increasing trend of local sea surface temperature unlikely supplies the necessary energy for this increase in TC intensity. Instead, a weakened vertical wind shear (VWS) appears to be the main contributing factor. Through numerical simulations, we demonstrate that the warming TP strengthens the South Asian high-pressure system, which triggers a wave train toward the tropical WNP, subsequently modifying the upper- and lower-tropospheric zonal winds to reduce the VWS. Applying the high correlation between TC intensity and the local VWS to climate model projection results supports that TCs will likely become stronger, with a significantly increasing rate of 1.0 m s-1/10 years during 2021–2050, due to a further warming of the East Asian continent. Thus, the rims of East Asia and Southeast Asia could face an increasing risk of intense typhoons. © 2021, CC BY.

关键词： Tropical cyclone

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EEG Based Depression Recognition by Combining Functional Brain Network and Traditional Biomarkers

EEG Based Depression Recognition by Combining Functional Bra...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Shuting Sun Huayu Chen Xuexiao Shao Liangliang Liu Xiaowei Li Bin Hu Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Lanzhou China CAS Center for Excellence in BrainScience and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors Beijing China Ministry of Education Engineering Research Center of Open Source Software and Real-Time System (Lanzhou University) Lanzhou China

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

This Electroencephalography (EEG)-based research is to explore the effective biomarkers for depression recognition. Resting-state EEG data were collected from 24 major depressive patients (MDD) and 29 normal controls using 128-electrode geodesic sensor net. To better identify depression, we extracted multi-type of EEG features including linear features (L), nonlinear features (NL), functional connectivity features phase lagging index (PLI) and network measures (NM) to comprehensively characterize the EEG signals in patients with MDD. And machine learning algorithms and statistical analysis were used to evaluate the EEG features. Combined multi-types features (All: L+ NL + PLI + NM) outperformed single-type features for classifying depression. Analyzing the optimal features set we found that compared to other type features, PLI occupied the largest proportion of which functional connections in intra-hemisphere were much more than that of in inter-hemisphere. In addition, when using PLI features and All features, high frequency bands (alpha, beta) could achieve obviously higher classification accuracy than low frequency bands (delta, theta). Parietal-occipital lobe in the high frequency bands had great effect in depression identification. In conclusion, combined multi-types EEG features along with a robust classifier can better distinguish depressive patients from normal controls. And intra-hemispheric functional connections might be an effective biomarker to detect depression. Hence, this paper may provide objective and potential electrophysiological characteristics in depression recognition.

关键词： Electroencephalography Depression Feature extraction Electrodes Biomarkers Support vector machines Entropy

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Multi-criteria collaborative filtering based on matrix filling 4

Multi-criteria collaborative filtering based on matrix filli...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Ye, Li Wu, Chunming Qiang, Baohua Xie, Wu College of Computer Information Science Southwest University Chongqing China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic Technology Guilin China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex System Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9781538683392

In multi-criteria collaborative filtering, the data sparsity is a critical factor affecting the effectiveness of the algorithm. Existing solutions generally remove low-efficiency data through dimensionality reduction, decomposition, etc. While at lower data dimension, they also lose original data information, which impacts the accuracy of predicted ratings. This paper adopts a new processing strategy and proposes to use the matrix filling method to handle the missing data. Firstly, an improved similarity algorithm combined with the Jaccard Similarity Coefficient is used to calculate the predicted rating. Secondly, the Reliable Factor is introduced to prevent the error of filling data. Finally, multiple linear regression is employed for aggregating the ratings of the criteria to eventually yield preferred predicted ratings. A series of experiments show that the proposed method can precisely reflect the user's similarity and achieve better results in predicted ratings, in contrast to traditional methods. © 2018 IEEE.

关键词： Collaborative filtering

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Evolution model for word-of-mouth communication based on improved cellular automata 2019

Evolution model for word-of-mouth communication based on imp...

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2019 International Conference on Management Science and Industrial Engineering, MSIE 2019

作者： Su, Jiafu Yu, Xin Hu, Sensen National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University No. 19 Xuefu Avenue Nan'an District Chongqing China International College National Institute of Development Administration 118 Moo3 Serithai Road Klong-Chan Bangkapi Bangkok Thailand Chongqing Key Laboratory of Electronic Commerce and Supply Chain System Chongqing Technology and Business University No. 19 Xuefu Avenue Nan'an District Chongqing China

ISBN: (纸本)9781450362641

From the view of the micro-interaction between customers, this paper aims to investigate the evolution process and mechanism for Word-of-Mouth (WOM) communication. First, consulting the SIS model, this work depicts the process of WOM communication employing the thought of epidemic spread. Then, this paper improves the traditional cellular automata model to better reflect the WOM communication in reality. On its basis, the WOM communication evolution model is proposed. Through simulation of the proposed model, this paper studies the evolution process of WOM communication, and the influence of the WOM introduction strategy and the accessibility of WOM between communities on WOM communication performance. The results give us a comprehensive understanding of the evolution process and mechanism of WOM communication, and reveal valuable management enlightenments about how to improve the WOM communication performance, which are helpful to the managers and decision makers to effectively carry out WOM management. © 2019 ACM.

关键词： Cellular automata

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Codebook-Based Beam Tracking for Conformal Array-Enabled UAV MmWave Networks

arXiv

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arXiv 2020年

作者： Zhang, Jinglin Xu, Wenjun Gao, Hui Pan, Miao Han, Zhu Zhang, Ping Key Lab of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing100876 China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering University of Houston HoustonTX77204 United States University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China

Millimeter wave (mmWave) communications can potentially meet the high data-rate requirements of unmanned aerial vehicle (UAV) networks. However, as the prerequisite of mmWave communications, the narrow directional beam tracking is very challenging because of the three-dimensional (3D) mobility and attitude variation of UAVs. Aiming to address the beam tracking difficulties, we propose to integrate the conformal array (CA) with the surface of each UAV, which enables the full spatial coverage and the agile beam tracking in highly dynamic UAV mmWave networks. More specifically, the key contributions of our work are three-fold. 1) A new mmWave beam tracking framework is established for the CA-enabled UAV mmWave network. 2) A specialized hierarchical codebook is constructed to drive the directional radiating element (DRE)-covered cylindrical conformal array (CCA), which contains both the angular beam pattern and the subarray pattern to fully utilize the potential of the CA. 3) A codebook-based multiuser beam tracking scheme is proposed, where the Gaussian process machine learning enabled UAV position/attitude predication is developed to improve the beam tracking efficiency in conjunction with the tracking-error aware adaptive beamwidth control. Simulation results validate the effectiveness of the proposed codebook-based beam tracking scheme in the CA-enabled UAV mmWave network, and demonstrate the advantages of CA over the conventional planner array in terms of spectrum efficiency and outage probability in the highly dynamic scenarios. Copyright © 2020, The Authors. All rights reserved.

关键词： Millimeter waves

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CoxRF: Employee Turnover Prediction Based on Survival Analysis

CoxRF: Employee Turnover Prediction Based on Survival Analys...

引用

Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Qianwen Zhu Jiaxing Shang Xinjun Cai Linli Jiang Feiyi Liu Baohua Qiang College of Computer Science Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University Chongqing China College of Computer Science Chongqing University Chongqing China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China

ISBN: (数字)9781728140346

ISBN: (纸本)9781728140353

In human resource management, employee turnover prediction is very important for company operation since the leave of key employees can bring great loss to companies. However, most existing researches focused on employee-centered turnover prediction, while ignored the historical events of turnover behaviors as well as the longitudinal data of each work. Therefore, in this paper we propose a turnover prediction algorithm named CoxRF from an event-centered perspective, which combines the statistical results of survival analysis with ensemble learning and therefore simplifies the problem to a traditional supervised binary classification problem. In addition, we come up with the concepts of "event-person" and "time-event" to help construct survival data with censored data. We compare CoxRF with several baseline methods on a real dataset crawled from the biggest professional social platform of China. The results demonstrate its effectiveness for predicting turnovers. Besides, we have the following findings: i) gender plays a key role in employee turnover behavior and female employees have a higher turnover rate than male employees; ii) the external environmental factor such as GDP growth also contributes greatly to employee turnovers, which is hardly considered in previous data-driven studies; iii) The employee turnover behavior varies across different industries, where the IT group has significantly higher turnover rate than the government group; iv) Employees with good education backgrounds have a higher turnover rate than those with ordinary backgrounds after working for 3 to 5 years.

关键词： Hazards Companies Prediction algorithms Computer science Predictive models Data models Industries

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Object measurement system based on Surveillance video-images 1

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6th International Conference on Frontier computing, FC 2017

作者： Duan, Hui-Xian Wang, Jun Song, Lei Liu, Na Cyber Physical System R&D Center The Third Research Institute of Ministry of Public Security Shanghai201204 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China Shanghai International Technology and Trade United Co. Ltd Shanghai200031 China

ISBN: (数字)9789811073984

ISBN: (纸本)9789811073977

Object measurement based on surveillance video-images is a critical task in the field of intelligent video surveillance. In this paper, we proposed an object measurement system based on surveillance video-images. Firstly, considering the scene of the urban video surveillance, a novel calibration tool is designed for such scene, which is portable, collapsible and operational. Next, based on the portable calibration tool, the intrinsic and extrinsic parameters of the surveillance camera can be estimated. Then, an object measurement system based on surveillance video-images is developed, which include the acquisition module of calibration data, the computation module of camera parameters, the selection module of measurement endpoint and the computation module of object. Finally, in the traffic checkpoint, experiments are carried out to verify the effectiveness of the object measurement system. The results show that as long as the surveillance camera is one-time calibrated based on the portable calibration tool, this system can measure the object on the surveillance video-images captured by the calibrated camera. What’s more, experimental results have shown that the object measurement system can be used to estimate the vehicle speed and measure the body height within the acceptable error range, and then have demonstrated the effectiveness of the object measurement system. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Calibration

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