As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilienc...As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS.First,a unified resilience-driven coopera-tive reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement.Subsequently,a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence,combining the cooperative pair resilience contribution index(CPRCI)and coop-erative pair importance index(CPII).At last,the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include differ-ent attack modes and intensities.The analysis results can pro-vide a reference for decision-makers to manage UWSoS.展开更多
Objective:Healthcare workers,as a high-stress professional group,face long-term high intensity workloads and complex medical environments,resulting in increasingly prominent mental health issues.In particular,the wide...Objective:Healthcare workers,as a high-stress professional group,face long-term high intensity workloads and complex medical environments,resulting in increasingly prominent mental health issues.In particular,the widespread presence of anxiety symptoms and somatic pain has become a major factor affecting both the quality of care and the career development of healthcare workers.This study aims to investigate the mediating and moderating roles of psychological resilience and sleep in the relationship between somatic pain and anxiety among healthcare workers.Methods:A cross-sectional questionnaire survey was conducted among 1661 healthcare workers.The instruments used included the Generalized Anxiety Disorder-7(GAD-7),item 3 from the Patient Health Questionnaire-9(PHQ-9),the 10-item Connor-Davidson Resilience Scale(CD-RISC-10)for psychological resilience,and the Visual Analogue Scale(VAS)for assessing anxiety,sleep disturbance,psychological resilience,and somatic pain.Results:The detection rate of anxiety symptoms among healthcare workers was 38.95%.Psychological resilience was significantly negatively correlated with anxiety symptoms(r=−0.451,P<0.01),sleep disturbance(r=−0.313,P<0.01),and somatic pain(r=−0.214,P<0.01).Moreover,psychological resilience partially mediated the relationship between somatic pain and anxiety(β=−0.103,P<0.01),and sleep quality moderated the latter part of the mediation model(“somatic pain-psychological resilience-anxiety”).Conclusion:Under high-intensity workloads,healthcare workers generally experience severe anxiety symptoms.Psychological resilience plays an important protective mediating role in their mental health,and sleep quality serves as a moderator in this relationship.Enhancing healthcare workers’psychological resilience and improving their sleep may promote both their physical and mental well-being.展开更多
In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance o...In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance of the SoS,and a resilience-based importance measure analysis is conducted to provide suggestions in the design and optimization of the structure of the SoS.In this paper,the components of the SoS are simplified as four kinds of network nodes:sensor,decision point,influencer,and target.In this networked SoS,the number of operation loops is used as the performance indicator,and an approximate algorithm,which is based on eigenvalue of the adjacency matrix,is proposed to calculate the number of operation loops.In order to understand the performance change of the SoS during the attack and defense process in the operations,an integral resilience model is proposed to depict the resilience of the SoS.From different perspectives of enhancing the resilience,different measures,parameters and the corresponding algorithms for the resilience importance of components are proposed.Finally,a case study on an SoS is conducted to verify the validity of the network modelling and the resiliencebased importance analysis method.展开更多
Prior research on the resilience of critical infrastructure usually utilizes the network model to characterize the structure of the components so that a quantitative representation of resilience can be obtained. Parti...Prior research on the resilience of critical infrastructure usually utilizes the network model to characterize the structure of the components so that a quantitative representation of resilience can be obtained. Particularly, network component importance is addressed to express its significance in shaping the resilience performance of the whole system. Due to the intrinsic complexity of the problem, some idealized assumptions are exerted on the resilience-optimization problem to find partial solutions. This paper seeks to exploit the dynamic aspect of system resilience, i.e., the scheduling problem of link recovery in the post-disruption phase.The aim is to analyze the recovery strategy of the system with more practical assumptions, especially inhomogeneous time cost among links. In view of this, the presented work translates the resilience-maximization recovery plan into the dynamic decisionmaking of runtime recovery option. A heuristic scheme is devised to treat the core problem of link selection in an ongoing style.Through Monte Carlo simulation, the link recovery order rendered by the proposed scheme demonstrates excellent resilience performance as well as accommodation with uncertainty caused by epistemic knowledge.展开更多
OBJECTIVE Exposure to stressful events can be differently perceived by individuals depending on the level of stress resilience or vulnerability.The neural processes that underlie such clinical y and social y important...OBJECTIVE Exposure to stressful events can be differently perceived by individuals depending on the level of stress resilience or vulnerability.The neural processes that underlie such clinical y and social y important differences are largely unknown.As insula cortex is important in emotional processing,we have examined whether the changes in synaptic plasticity in the insula cortex involved in stress resilience or vulnerability.METHODS Mice were divided into two groups:control and stress group.Stress group was treated by foot electric shock twice daily(0.8 mA,2 s,ten times in 1 min) in continuous two weeks.Then we used fear conditioning test to detect re-experiencing of traumatic experience,open field test to detect avoidance,pre-pulse inhibition experiment to detect hyper arousal.The changes of synaptic plasticity in the insular cortex were recorded by the multiple channels electrophysiology and whole cell patch.RESULTS According to the behavioral scores,it was divided into resilient and vulnerable group.In the fear conditioning test,the vulnerable group showed the significant freezing time decreased than that of the resilient group(P<0.01).In the open field test,the time that enter the center zone of vulnerable group is increased than that resilient group(P<0.01);In the pre-pulse inhibition experiment,there are not significant difference of PPI value in both groups(P=0.4239).And then electrophysiological experiments are performed to detect the synaptic plasticity of the insular cortex.Compared with the resilient group,the LTP level was decreased(P<0.05) and the mEPSC was increased(P<0.01) in vulnerable group.CONCLUSION The impairment of synaptic plasticity in the insular cortex may be one of the neural mechanisms for the vulnerability to chronic stress.展开更多
Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rat...Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rate-distortion based error resilience method is proposed. Firstly, the intra/inter mode decision is implemented using macro-block(MB) refresh, and then redundant picture and reference frame selection are utilized together to realize the redundant coding. The estimated error propagation distortion and bit consumption of refresh MB are used for the mode and reference frame decision of refresh MB. Secondly, by analyzing the statistical property in the successive frames, the error propagation distortion and bit consumption are formulated as a function of temporal distance. Encoding parameters of the current frame is determined by the estimated error propagation distortion and bit consumption. Thirdly, by comparing the rate-distortion cost of different combinations, proper selection of error resilience method is performed before the encoding process of the current frame. Finally, the MB mode and bit distribution of the primary picture are analyzed for the derivation of the texture information. The motion information is subsequently incorporated for the calculation of video content complexity to implement the content based redundant coding. Experimental results demonstrate that the proposed algorithm achieves significant performance gains over the LA-RDO and HRP method when video is transmitted over error-prone channel.展开更多
When the protective and protected systems are detached,the former can be allowed to absorb the kinetic energy of the impacting projectile through large deformation without considering the back face signature of the la...When the protective and protected systems are detached,the former can be allowed to absorb the kinetic energy of the impacting projectile through large deformation without considering the back face signature of the latter.This paper presents a novel double-face knitted fabric(DFKF)designed for this very impacting scenario.Shooting tests equipped with high-speed camera were used to characterize the ballistic performance with the impact velocities ranging from 100 m/s to 450 m/s.The results showed that the ballistic limits(V_(bl))of DFKF are approximately triple and double that of its counterpart UD and plain fabrics,respectively.For mass-normalized metrics,the specific energy absorption(SEA)is 250%and 350%greater than the UD and plain fabrics at their corresponding V_(bl)s.The quasi-static tests showed that the DFKF displayed greater resilience,crease recovery properties,and flexibility,which also made it an especially better candidate than UD and plain weaves for the design of umbrella surface cloth.It was also found that DFKF is dependent on yarn count and the incorporation of spandex.A prototype anti-ballistic umbrella is manufactured using DFKF made of 200D multi-filament yarn.The ballistic performance is also sensitive to the impact site when the umbrella is subjected to impact.展开更多
Complex systems widely exist in nature and human society.There are complex interactions between system elements in a complex system,and systems show complex features at the macro level,such as emergence,self-organizat...Complex systems widely exist in nature and human society.There are complex interactions between system elements in a complex system,and systems show complex features at the macro level,such as emergence,self-organization,uncertainty,and dynamics.These complex features make it difficult to understand the internal operation mechanism of complex systems.Networked modeling of complex systems is a favorable means of understanding complex systems.It not only represents complex interactions but also reflects essential attributes of complex systems.This paper summarizes the research progress of complex systems modeling and analysis from the perspective of network science,including networked modeling,vital node analysis,network invulnerability analysis,network disintegration analysis,resilience analysis,complex network link prediction,and the attacker-defender game in complex networks.In addition,this paper presents some points of view on the trend and focus of future research on network analysis of complex systems.展开更多
Orthogonal netted radar systems （ONRS） can fundamentally improve the radar performance by using a group of specially designed orthogonal polyphase code signals which require a very low aperiodic autocorrelation peak...Orthogonal netted radar systems （ONRS） can fundamentally improve the radar performance by using a group of specially designed orthogonal polyphase code signals which require a very low aperiodic autocorrelation peak sidelobe level, low aperiodic cross-correlation, and a good resilience to small Doppler shifts. However, the existing numerical solutions degrade severely in the presence of small Doppler shifts. A new set of polyphase sequences is presented with good correlation properties as well as resilience to Doppler shifts. These sequences are built by using numerical optimization based on correlation properties as well as the Doppler effects on matched filter outputs, which maintains the Doppler tolerance. The statistical simulated annealing algorithm and the greedy code search method are used to optimize the sequences. Correlation and Doppler results are compared with the best-known sequences and show to be superior.展开更多
In this paper, we focus on the failure analysis of unmanned autonomous swarm(UAS) considering cascading effects. A framework of failure analysis for UAS is proposed.Guided by the framework, the failure analysis of UAS...In this paper, we focus on the failure analysis of unmanned autonomous swarm(UAS) considering cascading effects. A framework of failure analysis for UAS is proposed.Guided by the framework, the failure analysis of UAS with crash fault agents is performed. Resilience is used to analyze the processes of cascading failure and self-repair of UAS. Through simulation studies, we reveal the pivotal relationship between resilience, the swarm size, and the percentage of failed agents.The simulation results show that the swarm size does not affect the cascading failure process but has much influence on the process of self-repair and the final performance of the swarm.The results also reveal a tipping point exists in the swarm. Meanwhile, we get a counter-intuitive result that larger-scale UAS loses more resilience in the case of a small percentage of failed individuals, suggesting that the increasing swarm size does not necessarily lead to high resilience. It is also found that the temporal degree failure strategy performs much more harmfully to the resilience of swarm systems than the random failure. Our work can provide new insights into the mechanisms of swarm collapse, help build more robust UAS, and develop more efficient failure or protection strategies.展开更多
The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parall...The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.展开更多
The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soil...The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.展开更多
Although the dynamic properties of subgrade soils in seasonally frozen areas have already been studied, few researchers have considered the influence of shallow groundwater during the freeze–thaw(F–T) cycles. So a m...Although the dynamic properties of subgrade soils in seasonally frozen areas have already been studied, few researchers have considered the influence of shallow groundwater during the freeze–thaw(F–T) cycles. So a multifunctional F–T cycle system was developed to imitate the groundwater recharge in the subgrade during the freezing process and a large number of dynamic triaxial experiments were conducted after the F–T cycles. Some significant factors including the F–T cycle number, compaction degree, confining pressure, cyclic deviator stress, loading frequency, and water content were investigated for the resilient modulus of soils. The experimental results indicated that the dynamic resilient modulus of the subgrade was negatively correlated with the cyclic deviator stress, F–T cycle number, and initial water content, whereas the degree of compaction, confining pressure, and loading frequency could enhance the resilient modulus. Furthermore, a modified model considering the F–T cycle number and stress state was established to predict the dynamic resilient modulus. The calculated results of this modified model were very close to the experimental results. Consequently, calculation of the resilient modulus for F–T cycles considering the dynamic load was appropriate. This study provides reference for research focusing on F–T cycles with groundwater supply and the dynamic resilient moduli of subgrade soils in seasonally frozen areas.展开更多
The fatigue behavior, indirect tensile strength （ITS） and resilient modulus test results for warm mix asphalt （WMA） as well as hot mix asphalt （HMA） at different ageing levels were evaluated. Laboratory-prepared...The fatigue behavior, indirect tensile strength （ITS） and resilient modulus test results for warm mix asphalt （WMA） as well as hot mix asphalt （HMA） at different ageing levels were evaluated. Laboratory-prepared samples were aged artificially in the oven to simulate short-term and long term ageing in accordance with AASHTO R30 and then compared with unaged specimens. Beam fatigue testing was performed using beam specimens at 25 ℃ based on AASHTO T321 standard. Fatigue life, bending stiffness and dissipated energy for both unaged and aged mixtures were calculated using four-point beam fatigue test results. Three-point bending tests were performed using semi-circular bend （SCB） specimens at -10 ℃ and the critical mode I stress intensity factor K1 was then calculated using the peak load obtained from the load-displacement curve. It is observed that Sasobit and Rheofalt warm mix asphalt additives have a significant effect on indirect tensile strength, resilient modulus, fatigue behavior and stress intensity factor of aged and unaged mixtures.展开更多
The current study aims to evaluate the dynamic response of stabilized cohesive soil using an enzymatic preparation in terms of resilient modulus.We ran a series of resilient modulus testing according to AASHTO T307 on...The current study aims to evaluate the dynamic response of stabilized cohesive soil using an enzymatic preparation in terms of resilient modulus.We ran a series of resilient modulus testing according to AASHTO T307 on three types of cohesive soil treated with an enzymatic preparation to investigate its potential on roads construction.The results show significant improvement in the resilient modulus values,estimated at 1.4 to 4.4 times that observed for the untreated soil.Because of the complexity in conducting the resilient modulus measurement,we did a regression analysis to produce reliable correlation formula to predict the resilient modulus for untreated and stabilised soil samples involving stress state.The resilient modulus values for the subgrade materials at the anticipated field stresses were determined using a universal model.The enzymatic preparation was applied in pavement of a sample road and evaluated using the plate load test.SEM analysis for soil samples shows improvement in the soil compaction via reduction of voids between soil particles.XRD analysis shows no major structural changes in the treated soils.The enzymatic preparation contains 43 mg/mL of proteins.We used the SDS-PAGE(sodium dodecyl sulphate polyacrylamide gel electrophoresis)technique to identify the main protein components;however,the presence of interfering materials(surfactants)hinders the separation.展开更多
Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are eas...Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are easy to be blocked or reflected by obstacles such as walls and furniture.A resilient tightly-coupled inertial navigation system(INS)/UWB integration is proposed and implemented for indoor UAV navigation in this paper.A factor graph optimization(FGO)method enhanced by resilient stochastic model is established to cope with the indoor challenging scenarios.To deal with the impact of UWB non-line-of-sight(NLOS)signals and noise uncertainty,the conventional neural net-works(CNNs)are introduced into the stochastic modelling to improve the resilience and reliability of the integration.Based on the status that the UWB features are limited,a‘two-phase'CNNs structure was designed and implemented:one for signal classification and the other one for measurement noise prediction.The proposed resilient FGO method is tested on flighting UAV platform under actual indoor challenging scenario.Compared to classical FGO method,the overall positioning errors can be decreased from about 0.60 m to centimeter-level under signal block and reflection scenarios.The superiority of resilient FGO which effectively verified in constrained environment is pretty important for positioning accuracy and integrity for indoor navigation task.展开更多
基金This work was supported by Ph.D.Intelligent Innovation Foundation Project(201-CXCY-A01-08-19-01)Science and Technology on Information System Engineering Laboratory(05202007).
文摘As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS.First,a unified resilience-driven coopera-tive reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement.Subsequently,a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence,combining the cooperative pair resilience contribution index(CPRCI)and coop-erative pair importance index(CPII).At last,the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include differ-ent attack modes and intensities.The analysis results can pro-vide a reference for decision-makers to manage UWSoS.
基金supported by the Natural Science Foundation of Hunan Province,China(2023JJ60076)。
文摘Objective:Healthcare workers,as a high-stress professional group,face long-term high intensity workloads and complex medical environments,resulting in increasingly prominent mental health issues.In particular,the widespread presence of anxiety symptoms and somatic pain has become a major factor affecting both the quality of care and the career development of healthcare workers.This study aims to investigate the mediating and moderating roles of psychological resilience and sleep in the relationship between somatic pain and anxiety among healthcare workers.Methods:A cross-sectional questionnaire survey was conducted among 1661 healthcare workers.The instruments used included the Generalized Anxiety Disorder-7(GAD-7),item 3 from the Patient Health Questionnaire-9(PHQ-9),the 10-item Connor-Davidson Resilience Scale(CD-RISC-10)for psychological resilience,and the Visual Analogue Scale(VAS)for assessing anxiety,sleep disturbance,psychological resilience,and somatic pain.Results:The detection rate of anxiety symptoms among healthcare workers was 38.95%.Psychological resilience was significantly negatively correlated with anxiety symptoms(r=−0.451,P<0.01),sleep disturbance(r=−0.313,P<0.01),and somatic pain(r=−0.214,P<0.01).Moreover,psychological resilience partially mediated the relationship between somatic pain and anxiety(β=−0.103,P<0.01),and sleep quality moderated the latter part of the mediation model(“somatic pain-psychological resilience-anxiety”).Conclusion:Under high-intensity workloads,healthcare workers generally experience severe anxiety symptoms.Psychological resilience plays an important protective mediating role in their mental health,and sleep quality serves as a moderator in this relationship.Enhancing healthcare workers’psychological resilience and improving their sleep may promote both their physical and mental well-being.
基金supported by the National Natural Science Foundation of China(71571004)
文摘In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance of the SoS,and a resilience-based importance measure analysis is conducted to provide suggestions in the design and optimization of the structure of the SoS.In this paper,the components of the SoS are simplified as four kinds of network nodes:sensor,decision point,influencer,and target.In this networked SoS,the number of operation loops is used as the performance indicator,and an approximate algorithm,which is based on eigenvalue of the adjacency matrix,is proposed to calculate the number of operation loops.In order to understand the performance change of the SoS during the attack and defense process in the operations,an integral resilience model is proposed to depict the resilience of the SoS.From different perspectives of enhancing the resilience,different measures,parameters and the corresponding algorithms for the resilience importance of components are proposed.Finally,a case study on an SoS is conducted to verify the validity of the network modelling and the resiliencebased importance analysis method.
基金supported by the National Natural Science Foundation of China(51479158)the Fundamental Research Funds for the Central Universities(WUT:2018III061GX)
文摘Prior research on the resilience of critical infrastructure usually utilizes the network model to characterize the structure of the components so that a quantitative representation of resilience can be obtained. Particularly, network component importance is addressed to express its significance in shaping the resilience performance of the whole system. Due to the intrinsic complexity of the problem, some idealized assumptions are exerted on the resilience-optimization problem to find partial solutions. This paper seeks to exploit the dynamic aspect of system resilience, i.e., the scheduling problem of link recovery in the post-disruption phase.The aim is to analyze the recovery strategy of the system with more practical assumptions, especially inhomogeneous time cost among links. In view of this, the presented work translates the resilience-maximization recovery plan into the dynamic decisionmaking of runtime recovery option. A heuristic scheme is devised to treat the core problem of link selection in an ongoing style.Through Monte Carlo simulation, the link recovery order rendered by the proposed scheme demonstrates excellent resilience performance as well as accommodation with uncertainty caused by epistemic knowledge.
基金National Natural Science Foundation of China(81402912).
文摘OBJECTIVE Exposure to stressful events can be differently perceived by individuals depending on the level of stress resilience or vulnerability.The neural processes that underlie such clinical y and social y important differences are largely unknown.As insula cortex is important in emotional processing,we have examined whether the changes in synaptic plasticity in the insula cortex involved in stress resilience or vulnerability.METHODS Mice were divided into two groups:control and stress group.Stress group was treated by foot electric shock twice daily(0.8 mA,2 s,ten times in 1 min) in continuous two weeks.Then we used fear conditioning test to detect re-experiencing of traumatic experience,open field test to detect avoidance,pre-pulse inhibition experiment to detect hyper arousal.The changes of synaptic plasticity in the insular cortex were recorded by the multiple channels electrophysiology and whole cell patch.RESULTS According to the behavioral scores,it was divided into resilient and vulnerable group.In the fear conditioning test,the vulnerable group showed the significant freezing time decreased than that of the resilient group(P<0.01).In the open field test,the time that enter the center zone of vulnerable group is increased than that resilient group(P<0.01);In the pre-pulse inhibition experiment,there are not significant difference of PPI value in both groups(P=0.4239).And then electrophysiological experiments are performed to detect the synaptic plasticity of the insular cortex.Compared with the resilient group,the LTP level was decreased(P<0.05) and the mEPSC was increased(P<0.01) in vulnerable group.CONCLUSION The impairment of synaptic plasticity in the insular cortex may be one of the neural mechanisms for the vulnerability to chronic stress.
基金Project(40927001)supported by the National Natural Science Foundation of ChinaProject(2011R09021-06)supported by the Program of Key Scientific and Technological Innovation Team of Zhejiang Province,ChinaProject supported by the Fundamental Research Funds for the Central Universities of China
文摘Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rate-distortion based error resilience method is proposed. Firstly, the intra/inter mode decision is implemented using macro-block(MB) refresh, and then redundant picture and reference frame selection are utilized together to realize the redundant coding. The estimated error propagation distortion and bit consumption of refresh MB are used for the mode and reference frame decision of refresh MB. Secondly, by analyzing the statistical property in the successive frames, the error propagation distortion and bit consumption are formulated as a function of temporal distance. Encoding parameters of the current frame is determined by the estimated error propagation distortion and bit consumption. Thirdly, by comparing the rate-distortion cost of different combinations, proper selection of error resilience method is performed before the encoding process of the current frame. Finally, the MB mode and bit distribution of the primary picture are analyzed for the derivation of the texture information. The motion information is subsequently incorporated for the calculation of video content complexity to implement the content based redundant coding. Experimental results demonstrate that the proposed algorithm achieves significant performance gains over the LA-RDO and HRP method when video is transmitted over error-prone channel.
基金support from the following for aspects of the research,authorship,and/or publication of this article:National Natural Science Foundation of China(Grant No.12302187)Innovation Program of Wuhan-Shuguang Project(Grant No.202201080102).
文摘When the protective and protected systems are detached,the former can be allowed to absorb the kinetic energy of the impacting projectile through large deformation without considering the back face signature of the latter.This paper presents a novel double-face knitted fabric(DFKF)designed for this very impacting scenario.Shooting tests equipped with high-speed camera were used to characterize the ballistic performance with the impact velocities ranging from 100 m/s to 450 m/s.The results showed that the ballistic limits(V_(bl))of DFKF are approximately triple and double that of its counterpart UD and plain fabrics,respectively.For mass-normalized metrics,the specific energy absorption(SEA)is 250%and 350%greater than the UD and plain fabrics at their corresponding V_(bl)s.The quasi-static tests showed that the DFKF displayed greater resilience,crease recovery properties,and flexibility,which also made it an especially better candidate than UD and plain weaves for the design of umbrella surface cloth.It was also found that DFKF is dependent on yarn count and the incorporation of spandex.A prototype anti-ballistic umbrella is manufactured using DFKF made of 200D multi-filament yarn.The ballistic performance is also sensitive to the impact site when the umbrella is subjected to impact.
基金supported by the State Key Program of National Natural Science Foundation of China(72231011)the National Natural Science Foundation of China(72071206,72001209,71971213)the Science Foundation for Outstanding Youth Scholars of Hunan Province(2022JJ20047).
文摘Complex systems widely exist in nature and human society.There are complex interactions between system elements in a complex system,and systems show complex features at the macro level,such as emergence,self-organization,uncertainty,and dynamics.These complex features make it difficult to understand the internal operation mechanism of complex systems.Networked modeling of complex systems is a favorable means of understanding complex systems.It not only represents complex interactions but also reflects essential attributes of complex systems.This paper summarizes the research progress of complex systems modeling and analysis from the perspective of network science,including networked modeling,vital node analysis,network invulnerability analysis,network disintegration analysis,resilience analysis,complex network link prediction,and the attacker-defender game in complex networks.In addition,this paper presents some points of view on the trend and focus of future research on network analysis of complex systems.
文摘Orthogonal netted radar systems （ONRS） can fundamentally improve the radar performance by using a group of specially designed orthogonal polyphase code signals which require a very low aperiodic autocorrelation peak sidelobe level, low aperiodic cross-correlation, and a good resilience to small Doppler shifts. However, the existing numerical solutions degrade severely in the presence of small Doppler shifts. A new set of polyphase sequences is presented with good correlation properties as well as resilience to Doppler shifts. These sequences are built by using numerical optimization based on correlation properties as well as the Doppler effects on matched filter outputs, which maintains the Doppler tolerance. The statistical simulated annealing algorithm and the greedy code search method are used to optimize the sequences. Correlation and Doppler results are compared with the best-known sequences and show to be superior.
基金This work was supported by the Science and Technology on Reliability&Environmental Engineering Laboratory(6142004004-2)the Science Technology Commission of the CMC(2019-JCJQ-JJ-180,ZZKY-YX-10-3).
文摘In this paper, we focus on the failure analysis of unmanned autonomous swarm(UAS) considering cascading effects. A framework of failure analysis for UAS is proposed.Guided by the framework, the failure analysis of UAS with crash fault agents is performed. Resilience is used to analyze the processes of cascading failure and self-repair of UAS. Through simulation studies, we reveal the pivotal relationship between resilience, the swarm size, and the percentage of failed agents.The simulation results show that the swarm size does not affect the cascading failure process but has much influence on the process of self-repair and the final performance of the swarm.The results also reveal a tipping point exists in the swarm. Meanwhile, we get a counter-intuitive result that larger-scale UAS loses more resilience in the case of a small percentage of failed individuals, suggesting that the increasing swarm size does not necessarily lead to high resilience. It is also found that the temporal degree failure strategy performs much more harmfully to the resilience of swarm systems than the random failure. Our work can provide new insights into the mechanisms of swarm collapse, help build more robust UAS, and develop more efficient failure or protection strategies.
基金Project(KC18071)supported by the Application Foundation Research Program of Xuzhou,ChinaProjects(2017YFC0804401,2017YFC0804409)supported by the National Key R&D Program of China
文摘The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.
基金Project(51878078)supported by the National Natural Science Foundation of ChinaProject(2018-025)supported by the Training Program for High-level Technical Personnel in Transportation Industry,ChinaProject(CTKY-PTRC-2018-003)supported by the Design Theory,Method and Demonstration of Durability Asphalt Pavement Based on Heavy-duty Traffic Conditions in Shanghai Area,China。
文摘The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.
基金Projects(41672312, 41972294) supported by the National Natural Science Foundation of ChinaProject(2017CFA056) supported by the Outstanding Youth Foundation of Hubei Province, ChinaProject(KFJ170104) supported by the Changsha University of Science & Technology via Open Fund of National Engineering Laboratory of Highway Maintenance Technology, China。
文摘Although the dynamic properties of subgrade soils in seasonally frozen areas have already been studied, few researchers have considered the influence of shallow groundwater during the freeze–thaw(F–T) cycles. So a multifunctional F–T cycle system was developed to imitate the groundwater recharge in the subgrade during the freezing process and a large number of dynamic triaxial experiments were conducted after the F–T cycles. Some significant factors including the F–T cycle number, compaction degree, confining pressure, cyclic deviator stress, loading frequency, and water content were investigated for the resilient modulus of soils. The experimental results indicated that the dynamic resilient modulus of the subgrade was negatively correlated with the cyclic deviator stress, F–T cycle number, and initial water content, whereas the degree of compaction, confining pressure, and loading frequency could enhance the resilient modulus. Furthermore, a modified model considering the F–T cycle number and stress state was established to predict the dynamic resilient modulus. The calculated results of this modified model were very close to the experimental results. Consequently, calculation of the resilient modulus for F–T cycles considering the dynamic load was appropriate. This study provides reference for research focusing on F–T cycles with groundwater supply and the dynamic resilient moduli of subgrade soils in seasonally frozen areas.
文摘The fatigue behavior, indirect tensile strength （ITS） and resilient modulus test results for warm mix asphalt （WMA） as well as hot mix asphalt （HMA） at different ageing levels were evaluated. Laboratory-prepared samples were aged artificially in the oven to simulate short-term and long term ageing in accordance with AASHTO R30 and then compared with unaged specimens. Beam fatigue testing was performed using beam specimens at 25 ℃ based on AASHTO T321 standard. Fatigue life, bending stiffness and dissipated energy for both unaged and aged mixtures were calculated using four-point beam fatigue test results. Three-point bending tests were performed using semi-circular bend （SCB） specimens at -10 ℃ and the critical mode I stress intensity factor K1 was then calculated using the peak load obtained from the load-displacement curve. It is observed that Sasobit and Rheofalt warm mix asphalt additives have a significant effect on indirect tensile strength, resilient modulus, fatigue behavior and stress intensity factor of aged and unaged mixtures.
基金Project supported by the Academy of Scientific Research and Technology,ASRT,Cairo,Egypt
文摘The current study aims to evaluate the dynamic response of stabilized cohesive soil using an enzymatic preparation in terms of resilient modulus.We ran a series of resilient modulus testing according to AASHTO T307 on three types of cohesive soil treated with an enzymatic preparation to investigate its potential on roads construction.The results show significant improvement in the resilient modulus values,estimated at 1.4 to 4.4 times that observed for the untreated soil.Because of the complexity in conducting the resilient modulus measurement,we did a regression analysis to produce reliable correlation formula to predict the resilient modulus for untreated and stabilised soil samples involving stress state.The resilient modulus values for the subgrade materials at the anticipated field stresses were determined using a universal model.The enzymatic preparation was applied in pavement of a sample road and evaluated using the plate load test.SEM analysis for soil samples shows improvement in the soil compaction via reduction of voids between soil particles.XRD analysis shows no major structural changes in the treated soils.The enzymatic preparation contains 43 mg/mL of proteins.We used the SDS-PAGE(sodium dodecyl sulphate polyacrylamide gel electrophoresis)technique to identify the main protein components;however,the presence of interfering materials(surfactants)hinders the separation.
基金National Natural Science Foundation of China(Grant No.62203111)the Open Research Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University(Grant No.21P01)the Foundation of Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology,Ministry of Education,China(Grant No.SEU-MIAN-202101)to provide fund for conducting experiments。
文摘Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are easy to be blocked or reflected by obstacles such as walls and furniture.A resilient tightly-coupled inertial navigation system(INS)/UWB integration is proposed and implemented for indoor UAV navigation in this paper.A factor graph optimization(FGO)method enhanced by resilient stochastic model is established to cope with the indoor challenging scenarios.To deal with the impact of UWB non-line-of-sight(NLOS)signals and noise uncertainty,the conventional neural net-works(CNNs)are introduced into the stochastic modelling to improve the resilience and reliability of the integration.Based on the status that the UWB features are limited,a‘two-phase'CNNs structure was designed and implemented:one for signal classification and the other one for measurement noise prediction.The proposed resilient FGO method is tested on flighting UAV platform under actual indoor challenging scenario.Compared to classical FGO method,the overall positioning errors can be decreased from about 0.60 m to centimeter-level under signal block and reflection scenarios.The superiority of resilient FGO which effectively verified in constrained environment is pretty important for positioning accuracy and integrity for indoor navigation task.
