Here we propose a new concept of"molecule aging":with some special treatment,a molecule could be"aged"by losing some unknown tiny particles or pieces from atoms in the molecule,Such"aging"...Here we propose a new concept of"molecule aging":with some special treatment,a molecule could be"aged"by losing some unknown tiny particles or pieces from atoms in the molecule,Such"aging"or loss of unknown tiny particles does not change apparently its molecular structure or chemical composition,but some physicochemical properties could be changed irreversibly.We further confirm such"molecule aging"via a long-term electron attacking to age water(H_(2)O)molecules.The IR spectra show no structural difference between the fresh water and the aged one,while the NMR spectra show that the electron attacking can decrease the size of water clusters.Such facts indicate that the electron attacking indeed can"affect"the structure of water molecule slightly but without damaging to its basic molecule frame.Further exploration reveals that the hydrogen evolution reaction(HER)activity of the aged water molecule is lower than the fresh water on the same Pt/C electrocatalyst.The density functional theory calculations indicate that the shortened O-H bond in H_(2)O indeed can present lower HER activity,so the observed size decrease of water clusters from NMR probably could be attributed to the shortening of O-H bond in water molecules.Such results indicate significantly that the molecule aging can produce materials with new functions for new possible applications.展开更多
Objective: To observe the clinical effect of Rebixiao granule (热痹消颗粒剂, RBXG) in treating repeatedly attacking acute gouty arthritis and through experimental study on blood uric acid to explore RBXG's therape...Objective: To observe the clinical effect of Rebixiao granule (热痹消颗粒剂, RBXG) in treating repeatedly attacking acute gouty arthritis and through experimental study on blood uric acid to explore RBXG's therapeutic mechanism. Methods: Ninety repeatedly attacking acute gouty arthritis patients were divided into the treated group ( n =60) and control group ( n =30). The treated group was treated with RBXG, and the control group was treated with Futalin tablets (diclofenac sodium). The baseline treatment including good rest, low purine diet, sufficient water drinking and urine alkalization, etc. was then given to both groups. Hypoxanthine 600 mg/kg and niacin 100 mg/kg was applied to hyperuricemic mice by gastrogavage to establish the animal models. Results: The clinical effective rate of the treated group was 95.0% and that of the control 90.0%. Good therapeutic effects were won, insignificant difference ( P >0.05)was shown between the two groups. However, the cure rate of the treated group was 26.7% while that of the control group was 10.0%, with significant difference ( P <0.01) shown between them. The treated group had its blood uric acid lowered, which was significantly different ( P <0.05) from that of the control group. The animal experiment indicated that all the three groups treated with different dosages of RBXG, as well as the Ash bark and Smilax glabra rhizome groups had their blood uric acid content reduced in the hyperuricemic mice. Conclusion: RBXG has a quicker initiation and better treatment effects than sole anti-inflammatory and analgesic agents on the treatment of repeatedly attacking acute gouty arthritis, showing no obvious toxic or adverse reactions and therefore good for long-term administration and likely to be a safe TCM preparation to control the symptoms and reduce the onsets of repeatedly attacking of acute gouty arthritis. The animal experiment shows that both the compound preparation and part of the single ingredients in the recipe have the function of reducing blood uric acid. However, the compound recipe has better therapeutic effects, proving to be superior to single drugs.展开更多
Deep learning networks are widely used in various systems that require classification.However,deep learning networks are vulnerable to adversarial attacks.The study on adversarial attacks plays an important role in de...Deep learning networks are widely used in various systems that require classification.However,deep learning networks are vulnerable to adversarial attacks.The study on adversarial attacks plays an important role in defense.Black-box attacks require less knowledge about target models than white-box attacks do,which means black-box attacks are easier to launch and more valuable.However,the state-of-arts black-box attacks still suffer in low success rates and large visual distances between generative adversarial images and original images.This paper proposes a kind of fast black-box attack based on the cross-correlation(FBACC)method.The attack is carried out in two stages.In the first stage,an adversarial image,which would be missclassified as the target label,is generated by using gradient descending learning.By far the image may look a lot different than the original one.Then,in the second stage,visual quality keeps getting improved on the condition that the label keeps being missclassified.By using the cross-correlation method,the error of the smooth region is ignored,and the number of iterations is reduced.Compared with the proposed black-box adversarial attack methods,FBACC achieves a better fooling rate and fewer iterations.When attacking LeNet5 and AlexNet respectively,the fooling rates are 100%and 89.56%.When attacking them at the same time,the fooling rate is 69.78%.FBACC method also provides a new adversarial attack method for the study of defense against adversarial attacks.展开更多
The unconditional security of quantum key distribution(QKD) can be guaranteed by the nature of quantum physics.Compared with the traditional two-dimensional BB84 QKD protocol, high-dimensional quantum key distribution...The unconditional security of quantum key distribution(QKD) can be guaranteed by the nature of quantum physics.Compared with the traditional two-dimensional BB84 QKD protocol, high-dimensional quantum key distribution(HDQKD) can be applied to generate much more secret key.Nonetheless, practical imperfections in realistic systems can be exploited by the third party to eavesdrop the secret key.The practical beam splitter has a correlation with wavelength,where different wavelengths have different coupling ratios.Using this property, we propose a wavelength-dependent attack towards time-bin high-dimensional QKD system.What is more, we demonstrate that this attacking protocol can be applied to arbitrary d-dimensional QKD system, and higher-dimensional QKD system is more vulnerable to this attacking strategy.展开更多
Influences of polymer-based grinding aid（PGA） on the damage process of concrete exposed to sulfate attack under dry-wet cycles were investigated. The mass loss, dynamic modulus of elasticity（Erd）, and S and Ca ele...Influences of polymer-based grinding aid（PGA） on the damage process of concrete exposed to sulfate attack under dry-wet cycles were investigated. The mass loss, dynamic modulus of elasticity（Erd）, and S and Ca element contents of concrete specimens were measured. Scanning electron microscopy（SEM）, mercury intrusion porosimetry（MIP）, and X-ray diffractometry（XRD） were used to investigate the changing of microstructure of interior concrete. The results indicated that PGA was capable of reducing the mass loss and improving the sulfate attack resistance of concrete. X-ray fluorescence（XRF） analysis revealed that PGA delayed the transport process of sulfate ions and Ca ions. In addition, MIP analysis disclosed that the micropores of concrete with PGA increased in the fraction of 20-100 nm and decreased in the residues of 200 nm. Compared with the blank sample, concrete with PGA had more slender and well-organized hydration products, and no changes in hydration products ratio or type were observed.展开更多
In this paper,two new guidance laws based on differential game theory are proposed and investigated for the attacker in an attacker-defender-target scenario.The conditions for the attacker winning the game are analyze...In this paper,two new guidance laws based on differential game theory are proposed and investigated for the attacker in an attacker-defender-target scenario.The conditions for the attacker winning the game are analyzed when the target and defender using the differential game guidance law based on the linear model.The core ideas underlying the two guidance laws are the attacker evading to a critical safe boundary from the defender,and then maintaining a critical miss distance.The guidance law more appropriate for the attacker to win the game differs according to the initial parameters.Unlike other guidance laws,when using the derived guidance laws there is no need to know the target and the defender’s control efforts.The results of numerical simulations show that the attacker can evade the defender and hit the target successfully by using the proposed derived guidance laws.展开更多
Watermarking is embedding visible or invisible data within media to verify its authenticity or protect copyright.The watermark is embedded in significant spatial or frequency features of the media to make it more resi...Watermarking is embedding visible or invisible data within media to verify its authenticity or protect copyright.The watermark is embedded in significant spatial or frequency features of the media to make it more resistant to intentional or unintentional modification.Some of these features are important perceptual features according to the human visual system(HVS),which means that the embedded watermark should be imperceptible in these features.Therefore,both the designers of watermarking algorithms and potential attackers must consider these perceptual features when carrying out their actions.The two roles will be considered in this paper when designing a robust watermarking algorithm against the most harmful attacks,like volumetric scaling,histogram equalization,and non-conventional watermarking attacks like the Denoising Convolution Neural Network(DnCNN),which must be considered in watermarking algorithm design due to its rising role in the state-of-the-art attacks.The DnCNN is initialized and trained using watermarked image samples created by our proposed Covert and Severe Attacks Resistant Watermarking Algorithm(CSRWA)to prove its robustness.For this algorithm to satisfy the robustness and imperceptibility tradeoff,implementing the Dither Modulation(DM)algorithm is boosted by utilizing the Just Noticeable Distortion(JND)principle to get an improved performance in this sense.Sensitivity,luminance,inter and intra-block contrast are used to adjust the JND values.展开更多
The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charg...The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation platforms.Our approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation attacks.We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation.The xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging data.Experimental results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging points.Furthermore,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 nodes.This research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.展开更多
The paper presents experimental investigation results of crack pattern change in cement pastes caused by external sulfate attack(ESA).To visualize the formation and development of cracks in cement pastes under ESA,an ...The paper presents experimental investigation results of crack pattern change in cement pastes caused by external sulfate attack(ESA).To visualize the formation and development of cracks in cement pastes under ESA,an X-ray computed tomography(X-ray CT)was used,i e,the tomography system of Zeiss Xradia 510 versa.The results indicate that X-CT can monitor the development process and distribution characteristics of the internal cracks of cement pastes under ESA with attack time.In addition,the C3A content in the cement significantly affects the damage mode of cement paste specimens during sulfate erosion.The damage of ordinary Portland cement(OPC)pastes subjected to sulfate attack with high C3A content are severe,while the damage of sulfate resistant Portland cement(SRPC)pastes is much smaller than that of OPC pastes.Furthermore,a quadratic function describes the correlation between the crack volume fraction and development depth for two cement pastes immermed in sulfate solution.展开更多
The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of user...The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.展开更多
Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convol...Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low accuracy.Therefore,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 dataset.The hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 dataset.The evaluation accuracy of the new dataset GINKS2023 created in this paper is 0.9386.Compared to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.展开更多
Diabetic foot attack(DFA)is the most severe presentation of diabetic foot disease,with the patient commonly displaying severe sepsis,which can be limb or life threatening.DFA can be classified into two main categories...Diabetic foot attack(DFA)is the most severe presentation of diabetic foot disease,with the patient commonly displaying severe sepsis,which can be limb or life threatening.DFA can be classified into two main categories:Typical and atypical.A typical DFA is secondary to a severe infection in the foot,often initiated by minor breaches in skin integrity that allow pathogens to enter and proliferate.This form often progresses rapidly due to the underlying diabetic pathophysiology of neuropathy,microvascular disease,and hyperglycemia,which facilitate infection spread and tissue necrosis.This form of DFA can present as one of a number of severe infective pathologies including pyomyositis,necrotizing fasciitis,and myonecrosis,all of which can lead to systemic sepsis and multiorgan failure.An atypical DFA,however,is not primarily infection-driven.It can occur secondary to either ischemia or Charcot arthropathy.Management of the typical DFA involves prompt diagnosis,aggressive infection control,and a multidisciplinary approach.Treatment can be guided by the current International Working Group on the Diabetic Foot/Infectious Diseases Society of America guidelines on diabetic foot infections,and the combined British Orthopaedic Foot and Ankle Society-Vascular Society guidelines.This article highlights the importance of early recognition,comprehensive management strategies,and the need for further research to establish standardized protocols and improve clinical outcomes for patients with DFA.展开更多
Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sam...Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.展开更多
In China, Pinus pumila is mainly distributed in Daxing’anling, while those growing in the eastern Daxing’anling are primarily covered under the jurisdiction of Huzhong Forest Bureau. P. pumila is an evergreen shrub,...In China, Pinus pumila is mainly distributed in Daxing’anling, while those growing in the eastern Daxing’anling are primarily covered under the jurisdiction of Huzhong Forest Bureau. P. pumila is an evergreen shrub, 3-6 m high, and always grows vigorously. Its trunks creep along the ground, usually 10 m long or more. It is easily flammable because of the large amounts of resins and volatile oils in its body. Attacking forest fires is a dangerous work, especially in P. pumila scrubs. The fires in P. pumila scrubs are very different from those in other forest types, e.g. fierce combustion and heavy smoke. In this paper, the distribution characteristics of P. pumila scrubs were presented. Attacking techniques and safety precautions for attacking fires in P. pumila scrubs were also discussed.展开更多
Unmanned combat system is one of the important means to capture information superiority,carry out precision strike and accomplish special combat tasks in information war.Unmanned attack strategy plays a crucial role i...Unmanned combat system is one of the important means to capture information superiority,carry out precision strike and accomplish special combat tasks in information war.Unmanned attack strategy plays a crucial role in unmanned combat system,which has to ensure the attack by unmanned surface vehicles(USVs)from failure.To meet the challenge,we propose a task allocation algorithm called distributed auction mechanism task allocation with grey wolf optimization(DAGWO).The traditional grey wolf optimization(GWO)algorithm is improved with a distributed auction mechanism(DAM)to constrain the initialization of wolves,which improves the optimization process according to the actual situation.In addition,one unmanned aerial vehicle(UAV)is employed as the central control system to establish task allocation model and construct fitness function for the multiple constraints of USV attack problem.The proposed DAGWO algorithm can not only ensure the diversity of wolves,but also avoid the local optimum problem.Simulation results show that the proposed DAGWO algorithm can effectively solve the problem of attack task allocation among multiple USVs.展开更多
The prevalence of diabetes mellitus and its associated complications,particularly diabetic foot pathologies,poses significant healthcare challenges and economic burdens globally.This review synthesises current evidenc...The prevalence of diabetes mellitus and its associated complications,particularly diabetic foot pathologies,poses significant healthcare challenges and economic burdens globally.This review synthesises current evidence on the surgical management of the diabetic foot,focusing on the interplay between neuropathy,ischemia,and infection that commonly culminates in ulcers,infections,and,in severe cases,amputations.The escalating incidence of diabetes mellitus underscores the urgency for effective management strategies,as diabetic foot complications are a leading cause of hospital admissions among diabetic patients,significantly impacting morbidity and mortality rates.This review explores the pathophysiological mechanisms underlying diabetic foot complications and further examines diabetic foot ulcers,infections,and skeletal pathologies such as Charcot arthropathy,emphasising the critical role of early diagnosis,comprehensive management strategies,and interdisciplinary care in mitigating adverse outcomes.In addressing surgical interventions,this review evaluates conservative surgeries,amputations,and reconstructive procedures,highlighting the importance of tailored approaches based on individual patient profiles and the specific characteristics of foot pathologies.The integration of advanced diagnostic tools,novel surgical techniques,and postoperative care,including offloading and infection control,are discussed in the context of optimising healing and preserving limb function.展开更多
Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security vulnerabilities.This paper focuses on the distributed secure control issu...Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security vulnerabilities.This paper focuses on the distributed secure control issue of automated vehicles affected by replay attacks.A proportional-integral-observer(PIO)with predetermined forgetting parameters is first constructed to acquire the dynamical information of vehicles.Then,a time-varying parameter and two positive scalars are employed to describe the temporal behavior of replay attacks.In light of such a scheme and the common properties of Laplace matrices,the closed-loop system with PIO-based controllers is transformed into a switched and time-delayed one.Furthermore,some sufficient conditions are derived to achieve the desired platooning performance by the view of the Lyapunov stability theory.The controller gains are analytically determined by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication topologies.Finally,a simulation example is provided to illustrate the effectiveness of the proposed control strategy.展开更多
In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amount...In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amounts of local data,computing capabilities and locations of the vehicles,renewing the global model with same weight is inappropriate.The above factors will affect the local calculation time and upload time of the local model,and the vehicle may also be affected by Byzantine attacks,leading to the deterioration of the vehicle data.However,based on deep reinforcement learning(DRL),we can consider these factors comprehensively to eliminate vehicles with poor performance as much as possible and exclude vehicles that have suffered Byzantine attacks before AFL.At the same time,when aggregating AFL,we can focus on those vehicles with better performance to improve the accuracy and safety of the system.In this paper,we proposed a vehicle selection scheme based on DRL in VEC.In this scheme,vehicle’s mobility,channel conditions with temporal variations,computational resources with temporal variations,different data amount,transmission channel status of vehicles as well as Byzantine attacks were taken into account.Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.展开更多
This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control fram...This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.展开更多
Federated Learning(FL),a burgeoning technology,has received increasing attention due to its privacy protection capability.However,the base algorithm FedAvg is vulnerable when it suffers from so-called backdoor attacks...Federated Learning(FL),a burgeoning technology,has received increasing attention due to its privacy protection capability.However,the base algorithm FedAvg is vulnerable when it suffers from so-called backdoor attacks.Former researchers proposed several robust aggregation methods.Unfortunately,due to the hidden characteristic of backdoor attacks,many of these aggregation methods are unable to defend against backdoor attacks.What's more,the attackers recently have proposed some hiding methods that further improve backdoor attacks'stealthiness,making all the existing robust aggregation methods fail.To tackle the threat of backdoor attacks,we propose a new aggregation method,X-raying Models with A Matrix(XMAM),to reveal the malicious local model updates submitted by the backdoor attackers.Since we observe that the output of the Softmax layer exhibits distinguishable patterns between malicious and benign updates,unlike the existing aggregation algorithms,we focus on the Softmax layer's output in which the backdoor attackers are difficult to hide their malicious behavior.Specifically,like medical X-ray examinations,we investigate the collected local model updates by using a matrix as an input to get their Softmax layer's outputs.Then,we preclude updates whose outputs are abnormal by clustering.Without any training dataset in the server,the extensive evaluations show that our XMAM can effectively distinguish malicious local model updates from benign ones.For instance,when other methods fail to defend against the backdoor attacks at no more than 20%malicious clients,our method can tolerate 45%malicious clients in the black-box mode and about 30%in Projected Gradient Descent(PGD)mode.Besides,under adaptive attacks,the results demonstrate that XMAM can still complete the global model training task even when there are 40%malicious clients.Finally,we analyze our method's screening complexity and compare the real screening time with other methods.The results show that XMAM is about 10–10000 times faster than the existing methods.展开更多
基金funded by the Key Research and Development Program sponsored by the Ministry of Science and Technology(MOST)(2022YFA1203400)National Natural Science Foundation of China(21925205,22072145,21372155,22005294,and 22102172)。
文摘Here we propose a new concept of"molecule aging":with some special treatment,a molecule could be"aged"by losing some unknown tiny particles or pieces from atoms in the molecule,Such"aging"or loss of unknown tiny particles does not change apparently its molecular structure or chemical composition,but some physicochemical properties could be changed irreversibly.We further confirm such"molecule aging"via a long-term electron attacking to age water(H_(2)O)molecules.The IR spectra show no structural difference between the fresh water and the aged one,while the NMR spectra show that the electron attacking can decrease the size of water clusters.Such facts indicate that the electron attacking indeed can"affect"the structure of water molecule slightly but without damaging to its basic molecule frame.Further exploration reveals that the hydrogen evolution reaction(HER)activity of the aged water molecule is lower than the fresh water on the same Pt/C electrocatalyst.The density functional theory calculations indicate that the shortened O-H bond in H_(2)O indeed can present lower HER activity,so the observed size decrease of water clusters from NMR probably could be attributed to the shortening of O-H bond in water molecules.Such results indicate significantly that the molecule aging can produce materials with new functions for new possible applications.
基金Supported by Project of Science and Technology Commis sion Foundation of Jiangsu Province in 1998
文摘Objective: To observe the clinical effect of Rebixiao granule (热痹消颗粒剂, RBXG) in treating repeatedly attacking acute gouty arthritis and through experimental study on blood uric acid to explore RBXG's therapeutic mechanism. Methods: Ninety repeatedly attacking acute gouty arthritis patients were divided into the treated group ( n =60) and control group ( n =30). The treated group was treated with RBXG, and the control group was treated with Futalin tablets (diclofenac sodium). The baseline treatment including good rest, low purine diet, sufficient water drinking and urine alkalization, etc. was then given to both groups. Hypoxanthine 600 mg/kg and niacin 100 mg/kg was applied to hyperuricemic mice by gastrogavage to establish the animal models. Results: The clinical effective rate of the treated group was 95.0% and that of the control 90.0%. Good therapeutic effects were won, insignificant difference ( P >0.05)was shown between the two groups. However, the cure rate of the treated group was 26.7% while that of the control group was 10.0%, with significant difference ( P <0.01) shown between them. The treated group had its blood uric acid lowered, which was significantly different ( P <0.05) from that of the control group. The animal experiment indicated that all the three groups treated with different dosages of RBXG, as well as the Ash bark and Smilax glabra rhizome groups had their blood uric acid content reduced in the hyperuricemic mice. Conclusion: RBXG has a quicker initiation and better treatment effects than sole anti-inflammatory and analgesic agents on the treatment of repeatedly attacking acute gouty arthritis, showing no obvious toxic or adverse reactions and therefore good for long-term administration and likely to be a safe TCM preparation to control the symptoms and reduce the onsets of repeatedly attacking of acute gouty arthritis. The animal experiment shows that both the compound preparation and part of the single ingredients in the recipe have the function of reducing blood uric acid. However, the compound recipe has better therapeutic effects, proving to be superior to single drugs.
基金This work is supported by the National Key R&D Program of China(2017YFB0802703)Research on the education mode for complicate skill students in new media with cross specialty integration(22150117092)+3 种基金Major Scientific and Technological Special Project of Guizhou Province(20183001)Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ014)Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ019)Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2018BDKFJJ022).
文摘Deep learning networks are widely used in various systems that require classification.However,deep learning networks are vulnerable to adversarial attacks.The study on adversarial attacks plays an important role in defense.Black-box attacks require less knowledge about target models than white-box attacks do,which means black-box attacks are easier to launch and more valuable.However,the state-of-arts black-box attacks still suffer in low success rates and large visual distances between generative adversarial images and original images.This paper proposes a kind of fast black-box attack based on the cross-correlation(FBACC)method.The attack is carried out in two stages.In the first stage,an adversarial image,which would be missclassified as the target label,is generated by using gradient descending learning.By far the image may look a lot different than the original one.Then,in the second stage,visual quality keeps getting improved on the condition that the label keeps being missclassified.By using the cross-correlation method,the error of the smooth region is ignored,and the number of iterations is reduced.Compared with the proposed black-box adversarial attack methods,FBACC achieves a better fooling rate and fewer iterations.When attacking LeNet5 and AlexNet respectively,the fooling rates are 100%and 89.56%.When attacking them at the same time,the fooling rate is 69.78%.FBACC method also provides a new adversarial attack method for the study of defense against adversarial attacks.
基金Project supported by the National Key Research and Development Program of China(Grant No.2016YFA0302600)the National Natural Science Foundation of China(Grant No.61675235)
文摘The unconditional security of quantum key distribution(QKD) can be guaranteed by the nature of quantum physics.Compared with the traditional two-dimensional BB84 QKD protocol, high-dimensional quantum key distribution(HDQKD) can be applied to generate much more secret key.Nonetheless, practical imperfections in realistic systems can be exploited by the third party to eavesdrop the secret key.The practical beam splitter has a correlation with wavelength,where different wavelengths have different coupling ratios.Using this property, we propose a wavelength-dependent attack towards time-bin high-dimensional QKD system.What is more, we demonstrate that this attacking protocol can be applied to arbitrary d-dimensional QKD system, and higher-dimensional QKD system is more vulnerable to this attacking strategy.
基金Funded by National Natural Science Foundation of China(No.51578141)National Program on Key Basic Research Project(973 Program)(No.2015CB655102)Ministry of Science and Technology of China(No.2016YFE011820)
文摘Influences of polymer-based grinding aid（PGA） on the damage process of concrete exposed to sulfate attack under dry-wet cycles were investigated. The mass loss, dynamic modulus of elasticity（Erd）, and S and Ca element contents of concrete specimens were measured. Scanning electron microscopy（SEM）, mercury intrusion porosimetry（MIP）, and X-ray diffractometry（XRD） were used to investigate the changing of microstructure of interior concrete. The results indicated that PGA was capable of reducing the mass loss and improving the sulfate attack resistance of concrete. X-ray fluorescence（XRF） analysis revealed that PGA delayed the transport process of sulfate ions and Ca ions. In addition, MIP analysis disclosed that the micropores of concrete with PGA increased in the fraction of 20-100 nm and decreased in the residues of 200 nm. Compared with the blank sample, concrete with PGA had more slender and well-organized hydration products, and no changes in hydration products ratio or type were observed.
基金co-supported by the National Natural Science Foundation of China(No.11672093)the Shanghai Aerospace Science and Technology Innovation Foundation,China(No.SAST2016039)
文摘In this paper,two new guidance laws based on differential game theory are proposed and investigated for the attacker in an attacker-defender-target scenario.The conditions for the attacker winning the game are analyzed when the target and defender using the differential game guidance law based on the linear model.The core ideas underlying the two guidance laws are the attacker evading to a critical safe boundary from the defender,and then maintaining a critical miss distance.The guidance law more appropriate for the attacker to win the game differs according to the initial parameters.Unlike other guidance laws,when using the derived guidance laws there is no need to know the target and the defender’s control efforts.The results of numerical simulations show that the attacker can evade the defender and hit the target successfully by using the proposed derived guidance laws.
文摘Watermarking is embedding visible or invisible data within media to verify its authenticity or protect copyright.The watermark is embedded in significant spatial or frequency features of the media to make it more resistant to intentional or unintentional modification.Some of these features are important perceptual features according to the human visual system(HVS),which means that the embedded watermark should be imperceptible in these features.Therefore,both the designers of watermarking algorithms and potential attackers must consider these perceptual features when carrying out their actions.The two roles will be considered in this paper when designing a robust watermarking algorithm against the most harmful attacks,like volumetric scaling,histogram equalization,and non-conventional watermarking attacks like the Denoising Convolution Neural Network(DnCNN),which must be considered in watermarking algorithm design due to its rising role in the state-of-the-art attacks.The DnCNN is initialized and trained using watermarked image samples created by our proposed Covert and Severe Attacks Resistant Watermarking Algorithm(CSRWA)to prove its robustness.For this algorithm to satisfy the robustness and imperceptibility tradeoff,implementing the Dither Modulation(DM)algorithm is boosted by utilizing the Just Noticeable Distortion(JND)principle to get an improved performance in this sense.Sensitivity,luminance,inter and intra-block contrast are used to adjust the JND values.
基金supported by Jiangsu Provincial Science and Technology Project,grant number J2023124.Jing Guo received this grant,the URLs of sponsors’website is https://kxjst.jiangsu.gov.cn/(accessed on 06 June 2024).
文摘The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation platforms.Our approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation attacks.We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation.The xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging data.Experimental results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging points.Furthermore,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 nodes.This research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.
基金Funded by Chinese National Natural Science Foundation of China(No.U2006224)。
文摘The paper presents experimental investigation results of crack pattern change in cement pastes caused by external sulfate attack(ESA).To visualize the formation and development of cracks in cement pastes under ESA,an X-ray computed tomography(X-ray CT)was used,i e,the tomography system of Zeiss Xradia 510 versa.The results indicate that X-CT can monitor the development process and distribution characteristics of the internal cracks of cement pastes under ESA with attack time.In addition,the C3A content in the cement significantly affects the damage mode of cement paste specimens during sulfate erosion.The damage of ordinary Portland cement(OPC)pastes subjected to sulfate attack with high C3A content are severe,while the damage of sulfate resistant Portland cement(SRPC)pastes is much smaller than that of OPC pastes.Furthermore,a quadratic function describes the correlation between the crack volume fraction and development depth for two cement pastes immermed in sulfate solution.
基金funding from King Saud University through Researchers Supporting Project number(RSP2024R387),King Saud University,Riyadh,Saudi Arabia.
文摘The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.
基金supported by Science and Technology Innovation Programfor Postgraduate Students in IDP Subsidized by Fundamental Research Funds for the Central Universities(Project No.ZY20240335)support of the Research Project of the Key Technology of Malicious Code Detection Based on Data Mining in APT Attack(Project No.2022IT173)the Research Project of the Big Data Sensitive Information Supervision Technology Based on Convolutional Neural Network(Project No.2022011033).
文摘Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low accuracy.Therefore,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 dataset.The hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 dataset.The evaluation accuracy of the new dataset GINKS2023 created in this paper is 0.9386.Compared to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.
文摘Diabetic foot attack(DFA)is the most severe presentation of diabetic foot disease,with the patient commonly displaying severe sepsis,which can be limb or life threatening.DFA can be classified into two main categories:Typical and atypical.A typical DFA is secondary to a severe infection in the foot,often initiated by minor breaches in skin integrity that allow pathogens to enter and proliferate.This form often progresses rapidly due to the underlying diabetic pathophysiology of neuropathy,microvascular disease,and hyperglycemia,which facilitate infection spread and tissue necrosis.This form of DFA can present as one of a number of severe infective pathologies including pyomyositis,necrotizing fasciitis,and myonecrosis,all of which can lead to systemic sepsis and multiorgan failure.An atypical DFA,however,is not primarily infection-driven.It can occur secondary to either ischemia or Charcot arthropathy.Management of the typical DFA involves prompt diagnosis,aggressive infection control,and a multidisciplinary approach.Treatment can be guided by the current International Working Group on the Diabetic Foot/Infectious Diseases Society of America guidelines on diabetic foot infections,and the combined British Orthopaedic Foot and Ankle Society-Vascular Society guidelines.This article highlights the importance of early recognition,comprehensive management strategies,and the need for further research to establish standardized protocols and improve clinical outcomes for patients with DFA.
基金supported by Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.
基金supported by the Central Public-interest Scientific Institution Basal Research Fund Supporting Program(CAFRIFEEP200809)the State Forestry Administration Key Project (2006-84)
文摘In China, Pinus pumila is mainly distributed in Daxing’anling, while those growing in the eastern Daxing’anling are primarily covered under the jurisdiction of Huzhong Forest Bureau. P. pumila is an evergreen shrub, 3-6 m high, and always grows vigorously. Its trunks creep along the ground, usually 10 m long or more. It is easily flammable because of the large amounts of resins and volatile oils in its body. Attacking forest fires is a dangerous work, especially in P. pumila scrubs. The fires in P. pumila scrubs are very different from those in other forest types, e.g. fierce combustion and heavy smoke. In this paper, the distribution characteristics of P. pumila scrubs were presented. Attacking techniques and safety precautions for attacking fires in P. pumila scrubs were also discussed.
基金the National Natural Science Foundation of China(No.61625304)。
文摘Unmanned combat system is one of the important means to capture information superiority,carry out precision strike and accomplish special combat tasks in information war.Unmanned attack strategy plays a crucial role in unmanned combat system,which has to ensure the attack by unmanned surface vehicles(USVs)from failure.To meet the challenge,we propose a task allocation algorithm called distributed auction mechanism task allocation with grey wolf optimization(DAGWO).The traditional grey wolf optimization(GWO)algorithm is improved with a distributed auction mechanism(DAM)to constrain the initialization of wolves,which improves the optimization process according to the actual situation.In addition,one unmanned aerial vehicle(UAV)is employed as the central control system to establish task allocation model and construct fitness function for the multiple constraints of USV attack problem.The proposed DAGWO algorithm can not only ensure the diversity of wolves,but also avoid the local optimum problem.Simulation results show that the proposed DAGWO algorithm can effectively solve the problem of attack task allocation among multiple USVs.
文摘The prevalence of diabetes mellitus and its associated complications,particularly diabetic foot pathologies,poses significant healthcare challenges and economic burdens globally.This review synthesises current evidence on the surgical management of the diabetic foot,focusing on the interplay between neuropathy,ischemia,and infection that commonly culminates in ulcers,infections,and,in severe cases,amputations.The escalating incidence of diabetes mellitus underscores the urgency for effective management strategies,as diabetic foot complications are a leading cause of hospital admissions among diabetic patients,significantly impacting morbidity and mortality rates.This review explores the pathophysiological mechanisms underlying diabetic foot complications and further examines diabetic foot ulcers,infections,and skeletal pathologies such as Charcot arthropathy,emphasising the critical role of early diagnosis,comprehensive management strategies,and interdisciplinary care in mitigating adverse outcomes.In addressing surgical interventions,this review evaluates conservative surgeries,amputations,and reconstructive procedures,highlighting the importance of tailored approaches based on individual patient profiles and the specific characteristics of foot pathologies.The integration of advanced diagnostic tools,novel surgical techniques,and postoperative care,including offloading and infection control,are discussed in the context of optimising healing and preserving limb function.
基金supported in part by the National Natural Science Foundation of China (61973219,U21A2019,61873058)the Hainan Province Science and Technology Special Fund (ZDYF2022SHFZ105)。
文摘Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security vulnerabilities.This paper focuses on the distributed secure control issue of automated vehicles affected by replay attacks.A proportional-integral-observer(PIO)with predetermined forgetting parameters is first constructed to acquire the dynamical information of vehicles.Then,a time-varying parameter and two positive scalars are employed to describe the temporal behavior of replay attacks.In light of such a scheme and the common properties of Laplace matrices,the closed-loop system with PIO-based controllers is transformed into a switched and time-delayed one.Furthermore,some sufficient conditions are derived to achieve the desired platooning performance by the view of the Lyapunov stability theory.The controller gains are analytically determined by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication topologies.Finally,a simulation example is provided to illustrate the effectiveness of the proposed control strategy.
基金supported in part by the National Natural Science Foundation of China(No.61701197)in part by the National Key Research and Development Program of China(No.2021YFA1000500(4))in part by the 111 Project(No.B23008).
文摘In vehicle edge computing(VEC),asynchronous federated learning(AFL)is used,where the edge receives a local model and updates the global model,effectively reducing the global aggregation latency.Due to different amounts of local data,computing capabilities and locations of the vehicles,renewing the global model with same weight is inappropriate.The above factors will affect the local calculation time and upload time of the local model,and the vehicle may also be affected by Byzantine attacks,leading to the deterioration of the vehicle data.However,based on deep reinforcement learning(DRL),we can consider these factors comprehensively to eliminate vehicles with poor performance as much as possible and exclude vehicles that have suffered Byzantine attacks before AFL.At the same time,when aggregating AFL,we can focus on those vehicles with better performance to improve the accuracy and safety of the system.In this paper,we proposed a vehicle selection scheme based on DRL in VEC.In this scheme,vehicle’s mobility,channel conditions with temporal variations,computational resources with temporal variations,different data amount,transmission channel status of vehicles as well as Byzantine attacks were taken into account.Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.
基金the financial support from the Natural Sciences and Engineering Research Council of Canada(NSERC)。
文摘This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.
基金Supported by the Fundamental Research Funds for the Central Universities(328202204)。
文摘Federated Learning(FL),a burgeoning technology,has received increasing attention due to its privacy protection capability.However,the base algorithm FedAvg is vulnerable when it suffers from so-called backdoor attacks.Former researchers proposed several robust aggregation methods.Unfortunately,due to the hidden characteristic of backdoor attacks,many of these aggregation methods are unable to defend against backdoor attacks.What's more,the attackers recently have proposed some hiding methods that further improve backdoor attacks'stealthiness,making all the existing robust aggregation methods fail.To tackle the threat of backdoor attacks,we propose a new aggregation method,X-raying Models with A Matrix(XMAM),to reveal the malicious local model updates submitted by the backdoor attackers.Since we observe that the output of the Softmax layer exhibits distinguishable patterns between malicious and benign updates,unlike the existing aggregation algorithms,we focus on the Softmax layer's output in which the backdoor attackers are difficult to hide their malicious behavior.Specifically,like medical X-ray examinations,we investigate the collected local model updates by using a matrix as an input to get their Softmax layer's outputs.Then,we preclude updates whose outputs are abnormal by clustering.Without any training dataset in the server,the extensive evaluations show that our XMAM can effectively distinguish malicious local model updates from benign ones.For instance,when other methods fail to defend against the backdoor attacks at no more than 20%malicious clients,our method can tolerate 45%malicious clients in the black-box mode and about 30%in Projected Gradient Descent(PGD)mode.Besides,under adaptive attacks,the results demonstrate that XMAM can still complete the global model training task even when there are 40%malicious clients.Finally,we analyze our method's screening complexity and compare the real screening time with other methods.The results show that XMAM is about 10–10000 times faster than the existing methods.
