The Experts below are selected from a list of 20919 Experts worldwide ranked by ideXlab platform
Jianhong Fang - One of the best experts on this subject based on the ideXlab platform.
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heavy metals in coastal wetland sediments of the pearl river estuary china
Environmental Pollution, 2007Co-Authors: Qusheng Li, Zhifeng Wu, Na Zhang, Jianhong FangAbstract:Abstract Sediment quality in coastal wetlands of the Pearl River Estuary was concerned since the wetlands were used for land reclamation, aquaculture and Wildlife Protection, and meanwhile served as one of the main ultimate sinks for large amount of heavy metals discharged from the rapidly developing Pearl River Delta. Total concentrations of heavy metal, such as Zn, Ni, Cr, Cu, Pb, and Cd, and their chemical speciation were investigated. Results showed that the sediments were significantly contaminated by Cd, Zn and Ni with concentration ranges of 2.79–4.65, 239.4–345.7 and 24.8–122.1 mg/kg, respectively. A major portion (34.6–46.8%) of Pb, Cd, and Zn was strongly associated with exchangeable fractions, while Cu, Ni and Cr were predominantly associated with organic fractions, residual, and Fe–Mn oxide. Cd and Zn would be the main potential risk and the sediment quality is no longer meeting the demand of the current wetland utilization strategies.
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heavy metals in coastal wetland sediments of the pearl river estuary china
Environmental Pollution, 2007Co-Authors: Bei Chu, Na Zhang, Shasha Cai, Jianhong FangAbstract:Abstract Sediment quality in coastal wetlands of the Pearl River Estuary was concerned since the wetlands were used for land reclamation, aquaculture and Wildlife Protection, and meanwhile served as one of the main ultimate sinks for large amount of heavy metals discharged from the rapidly developing Pearl River Delta. Total concentrations of heavy metal, such as Zn, Ni, Cr, Cu, Pb, and Cd, and their chemical speciation were investigated. Results showed that the sediments were significantly contaminated by Cd, Zn and Ni with concentration ranges of 2.79–4.65, 239.4–345.7 and 24.8–122.1 mg/kg, respectively. A major portion (34.6–46.8%) of Pb, Cd, and Zn was strongly associated with exchangeable fractions, while Cu, Ni and Cr were predominantly associated with organic fractions, residual, and Fe–Mn oxide. Cd and Zn would be the main potential risk and the sediment quality is no longer meeting the demand of the current wetland utilization strategies.
Sheng Zhong - One of the best experts on this subject based on the ideXlab platform.
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On repeated stackelberg security game with the cooperative human behavior model for Wildlife Protection
Applied Intelligence, 2019Co-Authors: Binru Wang, Zhi-hua Zhou, Yuan Zhang, Sheng ZhongAbstract:Inspired by successful deployments of Stackelberg Security Game in real life, researchers are working hard to optimize the game models to make them more practical. Recent security game work on Wildlife Protection makes a step forward by taking the possible cooperation among attackers into consideration. However, it models attackers to have complete rationality, which is not always possible in practice given they are human beings. We aim to tackle attackers’ bounded rationality in the complicated, cooperation-enabled and multi-round security game for Wildlife Protection. Specifically, we construct a repeated Stackelberg game, and propose a novel adaptive human behavior model for attackers based on it. Despite generating defender’s optimal strategy requires to solve a non-linear and non-convex optimization problem, we are able to propose an efficient algorithm that approximately solve this problem. We perform extensive real-life experiments, and results from over 25,000 game plays show our solution effectively helps the defender to deal with attackers who might cooperate.
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on repeated stackelberg security game with the cooperative human behavior modelfor Wildlife Protection
Adaptive Agents and Multi-Agents Systems, 2017Co-Authors: Binru Wang, Yuan Zhang, Sheng ZhongAbstract:Inspired by successful deployments of Stackelberg Security Game in real life, researchers are working hard to optimize the game models to make them more practical. Recent security game work on Wildlife Protection makes a step forward by taking the possible cooperation among attackers into consideration. However, it models attackers to have complete rationality, which is not always possible in practice given they are human beings. We aim to tackle attackers' bounded rationality in the complicated, cooperation-enabled and multi-round security game for Wildlife Protection. Specifically, we construct a repeated Stackelberg game, and propose a novel adaptive human behavior model for attackers based on it. Despite generating defender's optimal strategy requires to solve a non-linear and non-convex optimization problem, we are able to propose an efficient algorithm that approximately solve this problem. We perform extensive real-life experiments, and results show our solution effectively helps the defender to deal with attackers who might cooperate.
Yang Zhang - One of the best experts on this subject based on the ideXlab platform.
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identifying the zoonotic origin of sars cov 2 by modeling the binding affinity between the spike receptor binding domain and host ace2
Journal of Proteome Research, 2020Co-Authors: Xiaoqiang Huang, Chengxin Zhang, Robin Pearce, Gilbert S Omenn, Yang ZhangAbstract:Despite considerable research progress on SARS-CoV-2, the direct zoonotic origin (intermediate host) of the virus remains ambiguous. The most definitive approach to identify the intermediate host would be the detection of SARS-CoV-2-like coronaviruses in wild animals. However, due to the high number of animal species, it is not feasible to screen all the species in the laboratory. Given that binding to ACE2 proteins is the first step for the coronaviruses to invade host cells, we propose a computational pipeline to identify potential intermediate hosts of SARS-CoV-2 by modeling the binding affinity between the Spike receptor-binding domain (RBD) and host ACE2. Using this pipeline, we systematically examined 285 ACE2 variants from mammals, birds, fish, reptiles, and amphibians, and found that the binding energies calculated for the modeled Spike-RBD/ACE2 complex structures correlated closely with the effectiveness of animal infection as determined by multiple experimental data sets. Built on the optimized binding affinity cutoff, we suggest a set of 96 mammals, including 48 experimentally investigated ones, which are permissive to SARS-CoV-2, with candidates from primates, rodents, and carnivores at the highest risk of infection. Overall, this work not only suggests a limited range of potential intermediate SARS-CoV-2 hosts for further experimental investigation, but also, more importantly, it proposes a new structure-based approach to general zoonotic origin and susceptibility analyses that are critical for human infectious disease control and Wildlife Protection.
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identifying zoonotic origin of sars cov 2 by modeling the binding affinity between spike receptor binding domain and host ace2
bioRxiv, 2020Co-Authors: Xiaoqiang Huang, Chengxin Zhang, Robin Pearce, Gilbert S Omenn, Yang ZhangAbstract:Despite considerable research progress on SARS-CoV-2, the direct zoonotic origin (intermediate host) of the virus remains ambiguous. The most definitive approach to identify the intermediate host would be the detection of SARS-CoV-2-like coronaviruses in wild animals. However, due to the high number of animal species, it is not feasible to screen all the species in the laboratory. Given that the recognition of the binding ACE2 proteins is the first step for the coronaviruses to invade host cells, we proposed a computational pipeline to identify potential intermediate hosts of SARS-CoV-2 by modeling the binding affinity between the Spike receptor-binding domain (RBD) and host ACE2. Using this pipeline, we systematically examined 285 ACE2 variants from mammals, birds, fish, reptiles, and amphibians, and found that the binding energies calculated on the modeled Spike-RBD/ACE2 complex structures correlate closely with the effectiveness of animal infections as determined by multiple experimental datasets. Built on the optimized binding affinity cutoff, we suggested a set of 96 mammals, including 48 experimentally investigated ones, which are permissive to SARS-CoV-2, with candidates from primates, rodents, and carnivores at the highest risk of infection. Overall, this work not only suggested a limited range of potential intermediate SARS-CoV-2 hosts for further experimental investigation; but more importantly, it proposed a new structure-based approach to general zoonotic origin and susceptibility analyses that are critical for human infectious disease control and Wildlife Protection.
Binru Wang - One of the best experts on this subject based on the ideXlab platform.
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On repeated stackelberg security game with the cooperative human behavior model for Wildlife Protection
Applied Intelligence, 2019Co-Authors: Binru Wang, Zhi-hua Zhou, Yuan Zhang, Sheng ZhongAbstract:Inspired by successful deployments of Stackelberg Security Game in real life, researchers are working hard to optimize the game models to make them more practical. Recent security game work on Wildlife Protection makes a step forward by taking the possible cooperation among attackers into consideration. However, it models attackers to have complete rationality, which is not always possible in practice given they are human beings. We aim to tackle attackers’ bounded rationality in the complicated, cooperation-enabled and multi-round security game for Wildlife Protection. Specifically, we construct a repeated Stackelberg game, and propose a novel adaptive human behavior model for attackers based on it. Despite generating defender’s optimal strategy requires to solve a non-linear and non-convex optimization problem, we are able to propose an efficient algorithm that approximately solve this problem. We perform extensive real-life experiments, and results from over 25,000 game plays show our solution effectively helps the defender to deal with attackers who might cooperate.
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on repeated stackelberg security game with the cooperative human behavior modelfor Wildlife Protection
Adaptive Agents and Multi-Agents Systems, 2017Co-Authors: Binru Wang, Yuan Zhang, Sheng ZhongAbstract:Inspired by successful deployments of Stackelberg Security Game in real life, researchers are working hard to optimize the game models to make them more practical. Recent security game work on Wildlife Protection makes a step forward by taking the possible cooperation among attackers into consideration. However, it models attackers to have complete rationality, which is not always possible in practice given they are human beings. We aim to tackle attackers' bounded rationality in the complicated, cooperation-enabled and multi-round security game for Wildlife Protection. Specifically, we construct a repeated Stackelberg game, and propose a novel adaptive human behavior model for attackers based on it. Despite generating defender's optimal strategy requires to solve a non-linear and non-convex optimization problem, we are able to propose an efficient algorithm that approximately solve this problem. We perform extensive real-life experiments, and results show our solution effectively helps the defender to deal with attackers who might cooperate.
Xiaoqiang Huang - One of the best experts on this subject based on the ideXlab platform.
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identifying the zoonotic origin of sars cov 2 by modeling the binding affinity between the spike receptor binding domain and host ace2
Journal of Proteome Research, 2020Co-Authors: Xiaoqiang Huang, Chengxin Zhang, Robin Pearce, Gilbert S Omenn, Yang ZhangAbstract:Despite considerable research progress on SARS-CoV-2, the direct zoonotic origin (intermediate host) of the virus remains ambiguous. The most definitive approach to identify the intermediate host would be the detection of SARS-CoV-2-like coronaviruses in wild animals. However, due to the high number of animal species, it is not feasible to screen all the species in the laboratory. Given that binding to ACE2 proteins is the first step for the coronaviruses to invade host cells, we propose a computational pipeline to identify potential intermediate hosts of SARS-CoV-2 by modeling the binding affinity between the Spike receptor-binding domain (RBD) and host ACE2. Using this pipeline, we systematically examined 285 ACE2 variants from mammals, birds, fish, reptiles, and amphibians, and found that the binding energies calculated for the modeled Spike-RBD/ACE2 complex structures correlated closely with the effectiveness of animal infection as determined by multiple experimental data sets. Built on the optimized binding affinity cutoff, we suggest a set of 96 mammals, including 48 experimentally investigated ones, which are permissive to SARS-CoV-2, with candidates from primates, rodents, and carnivores at the highest risk of infection. Overall, this work not only suggests a limited range of potential intermediate SARS-CoV-2 hosts for further experimental investigation, but also, more importantly, it proposes a new structure-based approach to general zoonotic origin and susceptibility analyses that are critical for human infectious disease control and Wildlife Protection.
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identifying zoonotic origin of sars cov 2 by modeling the binding affinity between spike receptor binding domain and host ace2
bioRxiv, 2020Co-Authors: Xiaoqiang Huang, Chengxin Zhang, Robin Pearce, Gilbert S Omenn, Yang ZhangAbstract:Despite considerable research progress on SARS-CoV-2, the direct zoonotic origin (intermediate host) of the virus remains ambiguous. The most definitive approach to identify the intermediate host would be the detection of SARS-CoV-2-like coronaviruses in wild animals. However, due to the high number of animal species, it is not feasible to screen all the species in the laboratory. Given that the recognition of the binding ACE2 proteins is the first step for the coronaviruses to invade host cells, we proposed a computational pipeline to identify potential intermediate hosts of SARS-CoV-2 by modeling the binding affinity between the Spike receptor-binding domain (RBD) and host ACE2. Using this pipeline, we systematically examined 285 ACE2 variants from mammals, birds, fish, reptiles, and amphibians, and found that the binding energies calculated on the modeled Spike-RBD/ACE2 complex structures correlate closely with the effectiveness of animal infections as determined by multiple experimental datasets. Built on the optimized binding affinity cutoff, we suggested a set of 96 mammals, including 48 experimentally investigated ones, which are permissive to SARS-CoV-2, with candidates from primates, rodents, and carnivores at the highest risk of infection. Overall, this work not only suggested a limited range of potential intermediate SARS-CoV-2 hosts for further experimental investigation; but more importantly, it proposed a new structure-based approach to general zoonotic origin and susceptibility analyses that are critical for human infectious disease control and Wildlife Protection.
