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278 results on '"Cao, Zhidong"'

3. Impacts of export restrictions on the global personal protective equipment trade network during COVID-19

Author

Ye, Yang, Zhang, Qingpeng, Cao, Zhidong, Chen, Frank Youhua, Yan, Houmin, Stanley, H. Eugene, and Zeng, Daniel Dajun

Subjects
Physics - Physics and Society
Abstract

The COVID-19 pandemic has caused a dramatic surge in demand for personal protective equipment (PPE) worldwide. Many countries have imposed export restrictions on PPE to ensure the sufficient domestic supply. The surging demand and export restrictions cause shortage contagions on the global PPE trade network. Here, we develop an integrated network model, which integrates a metapopulation model and a threshold model, to investigate the shortage contagion patterns. The metapopulation model captures disease contagion across countries. The threshold model captures the shortage contagion on the global PPE trade network. Results show that, the shortage contagion patterns are mainly decided by top exporters. Export restrictions exacerbate the shortages of PPE and cause the shortage contagion to transmit even faster than the disease contagion. Besides, export restrictions lead to ineffective and inefficient allocation of PPE around the world, which has no benefits for the world to fight against the pandemic., Comment: 7 pages, 6 figures

Published
2021

4. Optimal vaccination program for two infectious diseases with cross immunity

Author

Ye, Yang, Zhang, Qingpeng, Cao, Zhidong, and Zeng, Daniel Dajun

Subjects
Quantitative Biology - Populations and Evolution, Physics - Physics and Society
Abstract

There are often multiple diseases with cross immunity competing for vaccination resources. Here we investigate the optimal vaccination program in a two-layer Susceptible-Infected-Removed (SIR) model, where two diseases with cross immunity spread in the same population, and vaccines for both diseases are available. We identify three scenarios of the optimal vaccination program, which prevents the outbreaks of both diseases at the minimum cost. We analytically derive a criterion to specify the optimal program based on the costs for different vaccines., Comment: 5 pages, 3 figures

Published
2020
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6. Effect of heterogeneous risk perception on information diffusion, behavior change, and disease transmission

Author

Ye, Yang, Zhang, Qingpeng, Ruan, Zhongyuan, Cao, Zhidong, Xuan, Qi, and Zeng, Daniel Dajun

Subjects
Physics - Physics and Society, Computer Science - Social and Information Networks
Abstract

Motivated by the importance of individual differences in risk perception and behavior change in people's responses to infectious disease outbreaks (particularly the ongoing COVID-19 pandemic), we propose a heterogeneous Disease-Behavior-Information (hDBI) transmission model, in which people's risk of getting infected is influenced by information diffusion, behavior change, and disease transmission. We use both a mean-field approximation and Monte Carlo simulations to analyze the dynamics of the model. Information diffusion influences behavior change by allowing people to be aware of the disease and adopt self-protection, and subsequently affects disease transmission by changing the actual infection rate. Results show that (a) awareness plays a central role in epidemic prevention; (b) a reasonable fraction of "over-reacting" nodes are needed in epidemic prevention; (c) R0 has different effects on epidemic outbreak for cases with and without asymptomatic infection; (d) social influence on behavior change can remarkably decrease the epidemic outbreak size. This research indicates that the media and opinion leaders should not understate the transmissibility and severity of diseases to ensure that people could become aware of the disease and adopt self-protection to protect themselves and the whole population.

Published
2020
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8. Flexible Attributed Network Embedding

Author

Shen, Enya, Cao, Zhidong, Zou, Changqing, and Wang, Jianmin

Subjects
Computer Science - Social and Information Networks, Computer Science - Machine Learning
Abstract

Network embedding aims to find a way to encode network by learning an embedding vector for each node in the network. The network often has property information which is highly informative with respect to the node's position and role in the network. Most network embedding methods fail to utilize this information during network representation learning. In this paper, we propose a novel framework, FANE, to integrate structure and property information in the network embedding process. In FANE, we design a network to unify heterogeneity of the two information sources, and define a new random walking strategy to leverage property information and make the two information compensate. FANE is conceptually simple and empirically powerful. It improves over the state-of-the-art methods on Cora dataset classification task by over 5%, more than 10% on WebKB dataset classification task. Experiments also show that the results improve more than the state-of-the-art methods as increasing training size. Moreover, qualitative visualization show that our framework is helpful in network property information exploration. In all, we present a new way for efficiently learning state-of-the-art task-independent representations in complex attributed networks. The source code and datasets of this paper can be obtained from https://github.com/GraphWorld/FANE.

Published
2018

16. Water-Energy Nexus in Power Systems: A Review

Author

Zhao, Pengfei, primary, Li, Shuangqi, additional, Shen, Yichen, additional, Gu, Chenghong, additional, Shan, Lanqing, additional, Luo, Tianyi, additional, Wang, Jiaojiao, additional, and Cao, Zhidong, additional

Published
2023
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19. COVID-19: Challenges to GIS with Big Data

Author

Zhou, Chenghu, Su, Fenzhen, Pei, Tao, Zhang, An, Du, Yunyan, Luo, Bin, Cao, Zhidong, Wang, Juanle, Yuan, Wen, Zhu, Yunqiang, Song, Ci, Chen, Jie, Xu, Jun, Li, Fujia, Ma, Ting, Jiang, Lili, Yan, Fengqin, Yi, Jiawei, Hu, Yunfeng, Liao, Yilan, and Xiao, Han

Published
2020
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21. List of contributors

Author

Alvarez, Jeffery B., primary, Bibault, Jean-Emmanuel, additional, Burgun, Anita, additional, Cai, Jinzheng, additional, Cao, Zhidong, additional, Chang, Ken, additional, Chen, Jonathan H., additional, Chen, William C., additional, Cho, Mildred, additional, Cho, Peter Jaeho, additional, Cornish, Toby C., additional, Costa, Anthony, additional, Dekker, Andre, additional, Drukker, Karen, additional, Dunn, Jessilyn, additional, Eminaga, Okyaz, additional, Erickson, Bradley J., additional, Fournier, Laure, additional, Gambhir, Sanjiv Sam, additional, Gennatas, Efstathios D., additional, Giger, Maryellen L., additional, Halilaj, Iva, additional, Harrison, Adam P., additional, He, Bryan, additional, Hong, Julian C., additional, Jin, Dakai, additional, Jin, Michael C., additional, Jochems, Arthur, additional, Kalpathy-Cramer, Jayashree, additional, Kapp, Daniel S., additional, Karimzadeh, Mehran, additional, Karnes, William, additional, Lambin, Philippe, additional, Langlotz, Curtis P., additional, Lee, Joonsang, additional, Li, Hui, additional, Liao, Joseph C., additional, Lin, Anthony L., additional, Lin, Rebecca Y., additional, Liu, Yun, additional, Lu, Le, additional, Magnus, David, additional, McIntosh, Chris, additional, Miao, Shun, additional, Min, James K., additional, Neill, Daniel B., additional, Oermann, Eric Karl, additional, Ouyang, David, additional, Peng, Lily, additional, Phene, Sonia, additional, Poirot, Maarten G., additional, Quon, Jennifer L., additional, Ranti, Daniel, additional, Rao, Arvind, additional, Raskar, Ramesh, additional, Rombaoa, Christopher, additional, Rubin, Daniel L., additional, Samarasena, Jason, additional, Seekins, Jayne, additional, Seetharam, Karthik, additional, Shearer, Emily, additional, Sibley, Adam, additional, Singh, Karnika, additional, Singh, Praveer, additional, Sordo, Margarita, additional, Suraweera, Duminda, additional, Valliani, Aly Al-Amyn, additional, van Wijk, Yvonka, additional, Vepakomma, Praneeth, additional, Wang, Bo, additional, Wang, Ge, additional, Wang, Nicholas, additional, Wang, Yirui, additional, Warner, Elisa, additional, Welch, Mattea, additional, Wong, Kimberly, additional, Wu, Zhenqin, additional, Xing, Fuyong, additional, Xing, Lei, additional, Yan, Ke, additional, Yan, Pingkun, additional, Yang, Lu, additional, Yeom, Kristen W., additional, Zachariah, Robin, additional, Zeng, Daniel, additional, Zhang, Lin, additional, Zhang, Ling, additional, Zhang, Xuhong, additional, Zhou, Li, additional, and Zou, James, additional

Published
2021
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25. Using Deep Learning to Mine the Key Factors of the Cost of AIDS Treatment

Author

Liu, Dong, Cao, Zhidong, Li, Su, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chen, Hsinchun, editor, Zeng, Daniel Dajun, editor, Karahanna, Elena, editor, and Bardhan, Indranil, editor

Published
2017
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27. Time and Economic Burden of Comorbidities Among COPD Inpatients

Author

Liu, Jiaqi, Ma, James, Wang, Jiaojiao, Zeng, Daniel, Song, Hongbin, Wang, Ligui, Cao, Zhidong, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Zheng, Xiaolong, editor, Zeng, Daniel Dajun, editor, Chen, Hsinchun, editor, and Leischow, Scott J., editor

Published
2016
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29. Optimal adaptive nonpharmaceutical interventions to mitigate the outbreak of respiratory infections following the COVID-19 pandemic: a deep reinforcement learning study in Hong Kong, China.

Author

Yao, Yao, Zhou, Hanchu, Cao, Zhidong, Zeng, Daniel Dajun, and Zhang, Qingpeng

Abstract

Background Long-lasting nonpharmaceutical interventions (NPIs) suppressed the infection of COVID-19 but came at a substantial economic cost and the elevated risk of the outbreak of respiratory infectious diseases (RIDs) following the pandemic. Policymakers need data-driven evidence to guide the relaxation with adaptive NPIs that consider the risk of both COVID-19 and other RIDs outbreaks, as well as the available healthcare resources. Methods Combining the COVID-19 data of the sixth wave in Hong Kong between May 31, 2022 and August 28, 2022, 6-year epidemic data of other RIDs (2014–2019), and the healthcare resources data, we constructed compartment models to predict the epidemic curves of RIDs after the COVID-19-targeted NPIs. A deep reinforcement learning (DRL) model was developed to learn the optimal adaptive NPIs strategies to mitigate the outbreak of RIDs after COVID-19-targeted NPIs are lifted with minimal health and economic cost. The performance was validated by simulations of 1000 days starting August 29, 2022. We also extended the model to Beijing context. Findings Without any NPIs, Hong Kong experienced a major COVID-19 resurgence far exceeding the hospital bed capacity. Simulation results showed that the proposed DRL-based adaptive NPIs successfully suppressed the outbreak of COVID-19 and other RIDs to lower than capacity. DRL carefully controlled the epidemic curve to be close to the full capacity so that herd immunity can be reached in a relatively short period with minimal cost. DRL derived more stringent adaptive NPIs in Beijing. Interpretation DRL is a feasible method to identify the optimal adaptive NPIs that lead to minimal health and economic cost by facilitating gradual herd immunity of COVID-19 and mitigating the other RIDs outbreaks without overwhelming the hospitals. The insights can be extended to other countries/regions. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Predicting Popularity of Microblogs in Emerging Disease Event

Author

Liu, Jiaqi, Cao, Zhidong, Zeng, Daniel, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chen, Yueguo, editor, Balke, Wolf-Tilo, editor, Xu, Jianliang, editor, Xu, Wei, editor, Jin, Peiquan, editor, Lin, Xin, editor, Tang, Tiffany, editor, and Hwang, Eenjun, editor

Published
2014
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35. Managing Water-Energy-Carbon Nexus for Urban Areas With Ambiguous Moment Information

Author

Zhao, Pengfei, Li, Shuangqi, Hu, Paul Jen-Hwa, Gu, Chenghong, Cao, Zhidong, and Xiang, Yue

Abstract

The rapid growth of electric load fuels urbanization but creates unsettling environmental challenges. In that regard, the energy system is a crucial part of consuming water and emitting greenhouse gases. To support reliable and economical energy system operations, with reduced water waste and carbon emissions, we design a viable co-optimization of water-energy-carbon nexus for an integrated energy system by adequately modelling essential interdependencies of power, gas, and water systems. A two-stage distributionally robust optimization method is proposed: the first-stage model minimizes the day-ahead reserve capacity scheduling for the next day, and the second-stage model enables real-time dispatch by considering the variability in renewable power generation. The carbon emissions by power generation and distribution are incorporated in both stages to ensure low-carbon operations. We use a two-stage moment-based distributionally robust approach to capture and represent the uncertainties in renewable generation. Instead of assuming a deterministic distribution, we characterize an ambiguity set with mean vectors and covariance matrices, which produces a family set of distributions. We conduct case studies using a modified IEEE 33-bus power system that includes and links a 20-node gas system and a 10-node water system. The comparative results indicate that the proposed co-optimization of water-energy-carbon nexus is superior than several benchmarks. By considering the close interdependencies of water, energy, and carbon, we create an optimal resource allocation scheme, which is capable of minimizing operation costs, lessening carbon emissions, and reducing water waste. The current research enables effective operation schemes for urban energy systems, illustrates a viable way to curb local environmental emissions, and increases water usage efficiency in the water-energy-carbon nexus.

Published
2023
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36. An Analysis of Beijing HFMD Patients Mobility Pattern during Seeking Treatment

Author

Zhu, Zhaonan, Cao, Zhidong, Zeng, Daniel Dajun, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zeng, Daniel, editor, Yang, Christopher C., editor, Tseng, Vincent S., editor, Xing, Chunxiao, editor, Chen, Hsinchun, editor, Wang, Fei-Yue, editor, and Zheng, Xiaolong, editor

Published
2013
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37. A Geospatial Analysis on the Potential Value of News Comments in Infectious Disease Surveillance

Author

Cui, Kainan, Cao, Zhidong, Zheng, Xiaolong, Zeng, Daniel, Zeng, Ke, Zheng, Min, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Chau, Michael, editor, Wang, G. Alan, editor, Zheng, Xiaolong, editor, Chen, Hsinchun, editor, Zeng, Daniel, editor, and Mao, Wenji, editor

Published
2011
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38. The Impact of Community Structure of Social Contact Network on Epidemic Outbreak and Effectiveness of Non-pharmaceutical Interventions

Author

Wang, Youzhong, Zeng, Daniel, Cao, Zhidong, Wang, Yong, Song, Hongbin, Zheng, Xiaolong, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Chau, Michael, editor, Wang, G. Alan, editor, Zheng, Xiaolong, editor, Chen, Hsinchun, editor, Zeng, Daniel, editor, and Mao, Wenji, editor

Published
2011
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39. Modeling and Simulation for the Spread of H1N1 Influenza in School Using Artificial Societies

Author

Duan, Wei, Cao, Zhidong, Ge, Yuanzheng, Qiu, Xiaogang, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Chau, Michael, editor, Wang, G. Alan, editor, Zheng, Xiaolong, editor, Chen, Hsinchun, editor, Zeng, Daniel, editor, and Mao, Wenji, editor

Published
2011
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40. Using Spatial Prediction Model to Analyze Driving Forces of the Beijing 2008 HFMD Epidemic

Author

Wang, JiaoJiao, Cao, ZhiDong, Wang, QuanYi, Wang, XiaoLi, Song, HongBin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Chau, Michael, editor, Wang, G. Alan, editor, Zheng, Xiaolong, editor, Chen, Hsinchun, editor, Zeng, Daniel, editor, and Mao, Wenji, editor

Published
2011
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41. An Online Real-Time System to Detect Risk for Infectious Diseases and Provide Early Alert

Author

Fang, Liang, Cao, Zhidong, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Chau, Michael, editor, Wang, G. Alan, editor, Zheng, Xiaolong, editor, Chen, Hsinchun, editor, Zeng, Daniel, editor, and Mao, Wenji, editor

Published
2011
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46. Human umbilical cord mesenchymal stromal cells promotes the proliferation and osteogenic differentiation of autologous bone marrow stem cells by secreting exosomes

Author

Yao Hai, Cao Zhidong, and Wu Wenyan

Subjects
Osteogenesis, Humans, Bioengineering, Bone Marrow Cells, Cell Differentiation, Mesenchymal Stem Cells, General Medicine, Exosomes, Applied Microbiology and Biotechnology, Cells, Cultured, Biotechnology, Cell Proliferation, Umbilical Cord
Abstract

Fractures are frequently encountered diseases troubling the senior population, and the research on fracture repair and the exploration of effective treatment methods are of great significance. This study aimed to clarify the effect of human umbilical cord mesenchymal stromal cell-derived extracellular vesicles (hUMSC-EVs) on the proliferation and osteogenic differentiation of autologous bone marrow stem cells (ABMSCs). The two kinds of cells were co-cultured firstly, 5-Ethynyl-2'- deoxyuridine (EDU) staining and alizarin red staining were used to detect the proliferation and osteogenic differentiation of ABMSCs. The exosomes of hUMSCs were subsequently extracted to process ABMSCs to further test the effect on the cells. The EDU positive rate of ABMSCs and Collagen II expression were elevated, whereas the TdT-mediated dUTP nick end labeling (TUNEL) positive rate and Matrix Metallopeptidase 13 (MMP13) were markedly decreased after the co-culture of hUMSCs and ABMSCs using Transwell chamber assays. The results indicated that hUMSCs could increase the proliferation of ABMSCs, reduce apoptosis, and promote matrix metabolism. The hUMSCs exosomes were separated and added to ABMSCs. As the exosomes content increased, the proliferation of ABMSCs increased simultaneously, and ABMSCs apoptosis decreased. Meanwhile, ABMSCs that migrated to the submembrane increased compared with untreated ABMSCs. Western blot, qPCR and immunofluorescence results revealed that increased exosomes contents promoted the expression of ABMSCs anabolic-related indicators gradually, while decreased the expression of catabolism-related indicators gradually. The previously described results indicated that hUMSCs promoted the proliferation and osteogenic differentiation of ABMSCs by secreting exosomes.

Published
2022

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