In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for conso...In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this paper.XG-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for nodes.The XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping model.Among them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus results.In order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT communication.Finally,we evaluate the performance of XG-PBFT.The experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of nodes.The results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.展开更多
A stochastic epidemic model with two age groups is established in this study,in which the susceptible(S),the exposed(E),the infected(I),the hospitalized(H)and the recovered(R)are involved within the total population,t...A stochastic epidemic model with two age groups is established in this study,in which the susceptible(S),the exposed(E),the infected(I),the hospitalized(H)and the recovered(R)are involved within the total population,the aging rates between two age groups are set to be constant.The existence-and-uniqueness of global positive solution is firstly showed.Then,by constructing several appropriate Lyapunov functions and using the high-dimensional Itô’s formula,the sufficient conditions for the stochastic extinction and stochastic persistence of the exposed individuals and the infected individuals are obtained.The stochastic extinction indicator and the stochastic persistence indicator are less-valued expressions compared with the basic reproduction number.Meanwhile,the main results of this study are modified into multi-age groups.Furthermore,by using the surveillance data for Fujian Provincial Center for Disease Control and Prevention,Fuzhou COVID-19 epidemic is chosen to carry out the numerical simulations,which show that the age group of the population plays the vital role when studying infectious diseases.展开更多
BACKGROUND Diabetic intracerebral hemorrhage(ICH)is a serious complication of diabetes.The role and mechanism of bone marrow mesenchymal stem cell(BMSC)-derived exosomes(BMSC-exo)in neuroinflammation post-ICH in patie...BACKGROUND Diabetic intracerebral hemorrhage(ICH)is a serious complication of diabetes.The role and mechanism of bone marrow mesenchymal stem cell(BMSC)-derived exosomes(BMSC-exo)in neuroinflammation post-ICH in patients with diabetes are unknown.In this study,we investigated the regulation of BMSC-exo on hyperglycemia-induced neuroinflammation.AIM To study the mechanism of BMSC-exo on nerve function damage after diabetes complicated with cerebral hemorrhage.METHODS BMSC-exo were isolated from mouse BMSC media.This was followed by transfection with microRNA-129-5p(miR-129-5p).BMSC-exo or miR-129-5poverexpressing BMSC-exo were intravitreally injected into a diabetes mouse model with ICH for in vivo analyses and were cocultured with high glucoseaffected BV2 cells for in vitro analyses.The dual luciferase test and RNA immunoprecipitation test verified the targeted binding relationship between miR-129-5p and high-mobility group box 1(HMGB1).Quantitative polymerase chain reaction,western blotting,and enzyme-linked immunosorbent assay were conducted to assess the levels of some inflammation factors,such as HMGB1,interleukin 6,interleukin 1β,toll-like receptor 4,and tumor necrosis factorα.Brain water content,neural function deficit score,and Evans blue were used to measure the neural function of mice.RESULTS Our findings indicated that BMSC-exo can promote neuroinflammation and functional recovery.MicroRNA chip analysis of BMSC-exo identified miR-129-5p as the specific microRNA with a protective role in neuroinflammation.Overexpression of miR-129-5p in BMSC-exo reduced the inflammatory response and neurological impairment in comorbid diabetes and ICH cases.Furthermore,we found that miR-129-5p had a targeted binding relationship with HMGB1 mRNA.CONCLUSION We demonstrated that BMSC-exo can reduce the inflammatory response after ICH with diabetes,thereby improving the neurological function of the brain.展开更多
On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness...On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material properties.This work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material parameters.The use of echo groups allows the use of lower frequencies,and hence more accommodative to structural complexity.To train the ANNs,a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure.The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model.This results in a set of dataset for training the ANN model.Once the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN.Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method.The results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic constants.Moreover,the reliability and accuracy of inverse prediction is significantly improved.Thus,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other available methods or equipment.展开更多
In the context of economic globalization,while multinational enterprises from developed countries occupy a high-end position in the global value chain,enterprises from developing countries are often marginalized in th...In the context of economic globalization,while multinational enterprises from developed countries occupy a high-end position in the global value chain,enterprises from developing countries are often marginalized in the world market.In China,resource-based state-owned enterprises(SOEs)are tasked with the mission of safeguarding resource security,and their internationalization development ideas and strategic deployment are significantly and fundamentally different from those of other non-state-owned enterprises and large multinational corporations.This study provides ideas for the globalization policies of enterprises in developing countries.We consider J Group in western China as a case and discuss its productive investment and global production network development from 2010 to 2019.We found that J Group was‘Partly'globalized,and there are multiple core nodes with the characteristics of centralized and decentralized coexistence in the production network;in addition,the overall layout centre shifted to Southeast Asia and China;however,its global production was restricted by the enterprise's investment security considerations,support and restrictions of the home country,political security risk of the host country,and sanctions from the West.These findings provide insights for future research:under the wave of anti-globalization and'internal circulation as the main body',resource SOEs should consider the potential risk of investment,especially keeping the middle and downstream industrial chain in China as much as possible.展开更多
文摘In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this paper.XG-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for nodes.The XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping model.Among them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus results.In order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT communication.Finally,we evaluate the performance of XG-PBFT.The experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of nodes.The results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.
基金Supported by National Natural Science Foundation of China(61911530398,12231012)Consultancy Project by the Chinese Academy of Engineering(2022-JB-06,2023-JB-12)+3 种基金the Natural Science Foundation of Fujian Province of China(2021J01621)Special Projects of the Central Government Guiding Local Science and Technology Development(2021L3018)Royal Society of Edinburgh(RSE1832)Engineering and Physical Sciences Research Council(EP/W522521/1).
文摘A stochastic epidemic model with two age groups is established in this study,in which the susceptible(S),the exposed(E),the infected(I),the hospitalized(H)and the recovered(R)are involved within the total population,the aging rates between two age groups are set to be constant.The existence-and-uniqueness of global positive solution is firstly showed.Then,by constructing several appropriate Lyapunov functions and using the high-dimensional Itô’s formula,the sufficient conditions for the stochastic extinction and stochastic persistence of the exposed individuals and the infected individuals are obtained.The stochastic extinction indicator and the stochastic persistence indicator are less-valued expressions compared with the basic reproduction number.Meanwhile,the main results of this study are modified into multi-age groups.Furthermore,by using the surveillance data for Fujian Provincial Center for Disease Control and Prevention,Fuzhou COVID-19 epidemic is chosen to carry out the numerical simulations,which show that the age group of the population plays the vital role when studying infectious diseases.
基金Supported by the National Natural Science Foundation of China,No.81900743Heilongjiang Province Outstanding Young Medical Talents Training Grant Project,China,No.HYD2020YQ0007.
文摘BACKGROUND Diabetic intracerebral hemorrhage(ICH)is a serious complication of diabetes.The role and mechanism of bone marrow mesenchymal stem cell(BMSC)-derived exosomes(BMSC-exo)in neuroinflammation post-ICH in patients with diabetes are unknown.In this study,we investigated the regulation of BMSC-exo on hyperglycemia-induced neuroinflammation.AIM To study the mechanism of BMSC-exo on nerve function damage after diabetes complicated with cerebral hemorrhage.METHODS BMSC-exo were isolated from mouse BMSC media.This was followed by transfection with microRNA-129-5p(miR-129-5p).BMSC-exo or miR-129-5poverexpressing BMSC-exo were intravitreally injected into a diabetes mouse model with ICH for in vivo analyses and were cocultured with high glucoseaffected BV2 cells for in vitro analyses.The dual luciferase test and RNA immunoprecipitation test verified the targeted binding relationship between miR-129-5p and high-mobility group box 1(HMGB1).Quantitative polymerase chain reaction,western blotting,and enzyme-linked immunosorbent assay were conducted to assess the levels of some inflammation factors,such as HMGB1,interleukin 6,interleukin 1β,toll-like receptor 4,and tumor necrosis factorα.Brain water content,neural function deficit score,and Evans blue were used to measure the neural function of mice.RESULTS Our findings indicated that BMSC-exo can promote neuroinflammation and functional recovery.MicroRNA chip analysis of BMSC-exo identified miR-129-5p as the specific microRNA with a protective role in neuroinflammation.Overexpression of miR-129-5p in BMSC-exo reduced the inflammatory response and neurological impairment in comorbid diabetes and ICH cases.Furthermore,we found that miR-129-5p had a targeted binding relationship with HMGB1 mRNA.CONCLUSION We demonstrated that BMSC-exo can reduce the inflammatory response after ICH with diabetes,thereby improving the neurological function of the brain.
基金Supported by National Natural Science Foundation of China(Grant No.51805141)Funds for Creative Research Groups of Hebei Province of China(Grant No.E2020202142)+2 种基金Tianjin Municipal Science and Technology Plan Project of China(Grant No.19ZXZNGX00100)Key R&D Program of Hebei Province of China(Grant No.19227208D)National Key Research and development Program of China(Grant No.2020YFB2009400).
文摘On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material properties.This work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material parameters.The use of echo groups allows the use of lower frequencies,and hence more accommodative to structural complexity.To train the ANNs,a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure.The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model.This results in a set of dataset for training the ANN model.Once the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN.Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method.The results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic constants.Moreover,the reliability and accuracy of inverse prediction is significantly improved.Thus,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other available methods or equipment.
基金supported by National Natural Science Foundation of China(Grants No.41971198 and 42371198)Fundamental Research Funds for the Central Universities(Grant No.lzujbky-2023-it24).
文摘In the context of economic globalization,while multinational enterprises from developed countries occupy a high-end position in the global value chain,enterprises from developing countries are often marginalized in the world market.In China,resource-based state-owned enterprises(SOEs)are tasked with the mission of safeguarding resource security,and their internationalization development ideas and strategic deployment are significantly and fundamentally different from those of other non-state-owned enterprises and large multinational corporations.This study provides ideas for the globalization policies of enterprises in developing countries.We consider J Group in western China as a case and discuss its productive investment and global production network development from 2010 to 2019.We found that J Group was‘Partly'globalized,and there are multiple core nodes with the characteristics of centralized and decentralized coexistence in the production network;in addition,the overall layout centre shifted to Southeast Asia and China;however,its global production was restricted by the enterprise's investment security considerations,support and restrictions of the home country,political security risk of the host country,and sanctions from the West.These findings provide insights for future research:under the wave of anti-globalization and'internal circulation as the main body',resource SOEs should consider the potential risk of investment,especially keeping the middle and downstream industrial chain in China as much as possible.
