In today’s rapidly evolving digital landscape,web application security has become paramount as organizations face increasingly sophisticated cyber threats.This work presents a comprehensive methodology for implementi...In today’s rapidly evolving digital landscape,web application security has become paramount as organizations face increasingly sophisticated cyber threats.This work presents a comprehensive methodology for implementing robust security measures in modern web applications and the proof of the Methodology applied to Vue.js,Spring Boot,and MySQL architecture.The proposed approach addresses critical security challenges through a multi-layered framework that encompasses essential security dimensions including multi-factor authentication,fine-grained authorization controls,sophisticated session management,data confidentiality and integrity protection,secure logging mechanisms,comprehensive error handling,high availability strategies,advanced input validation,and security headers implementation.Significant contributions are made to the field of web application security.First,a detailed catalogue of security requirements specifically tailored to protect web applications against contemporary threats,backed by rigorous analysis and industry best practices.Second,the methodology is validated through a carefully designed proof-of-concept implementation in a controlled environment,demonstrating the practical effectiveness of the security measures.The validation process employs cutting-edge static and dynamic analysis tools for comprehensive dependency validation and vulnerability detection,ensuring robust security coverage.The validation results confirm the prevention and avoidance of security vulnerabilities of the methodology.A key innovation of this work is the seamless integration of DevSecOps practices throughout the secure Software Development Life Cycle(SSDLC),creating a security-first mindset from initial design to deployment.By combining proactive secure coding practices with defensive security approaches,a framework is established that not only strengthens application security but also fosters a culture of security awareness within development teams.This hybrid approach ensures that security considerations are woven into every aspect of the development process,rather than being treated as an afterthought.展开更多
Effect web will be an important combat means to achieve accurate,efficient,agile and reliable destruction of enemy targets.The use of Unmanned Aerial Vehicles(UAV)cluster in warfare has become a key element in the bat...Effect web will be an important combat means to achieve accurate,efficient,agile and reliable destruction of enemy targets.The use of Unmanned Aerial Vehicles(UAV)cluster in warfare has become a key element in the battle for military superiority between nations.The construction of UAV cluster effect web is a kind of combinatorial optimization in essence.By selecting the optimal combination in the limited equipment concentration,the whole network can be optimized.Firstly,in order to improve the combinatorial optimization efficiency of UAV cluster effect web,NSGA-Ⅱbased on deep Q-network(DQN-based NSGA-Ⅱ)is proposed.This algorithm is used to solve the Multi-Objective Combinatorial Optimization(MOCO)problem in the construction of effect web.Secondly,a dynamic generation method is devised to solve the problem caused by the possible destruction of enemy and our node under the fierce confrontation between the two sides.Finally,the simulation results show that the DQN-based NSGA-Ⅱis better than the genetic algorithm with single operator.The comparison experiment shows that the weight of evaluation indexes will have a corresponding influence on the optimization results.展开更多
Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility o...Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility of EMS has received considerable attention in health and transport geography studies.^([3])One of the optimal gauges for evaluating the accessibility of EMS is the response time,which is defined as the time from receiving an emergency call to the arrival of an ambulance.^([4])Beijing has already reduced the response time to approximately12 min,and the next goal is to ensure that the response time across Beijing does not exceed 12 min (the information comes from the Beijing Emergency Medical Center).展开更多
Graphene fiber supercapacitors(GFSCs)have garnered significant attention due to their exceptional features,including high power density,rapid charge/discharge rates,prolonged cycling durability,and versatile weaving c...Graphene fiber supercapacitors(GFSCs)have garnered significant attention due to their exceptional features,including high power density,rapid charge/discharge rates,prolonged cycling durability,and versatile weaving capabilities.Nevertheless,inherent challenges in graphene fibers(GFs),particularly the restricted ion-accessible specific surface area(SSA)and sluggish ion transport kinetics,hinder the achievement of optimal capacitance and rate performance.Despite existing reviews on GFSCs,a notable gap exists in thoroughly exploring the kinetics governing the energy storage process in GFSCs.This review aims to address this gap by thoroughly analyzing the energy storage mechanism,fabrication methodologies,property manipulation,and wearable applications of GFSCs.Through theoretical analysis of the energy storage process,specific parameters in advanced GF fabrication methodologies are carefully summarized,which can be used to modulate nano/micro-structures,thereby enhancing energy storage kinetics.In particular,enhanced ion storage is realized by creating more ion-accessible SSA and introducing extra-capacitive components,while accelerated ion transport is achieved by shortening the transport channel length and improving the accessibility of electrolyte ions.Building on the established structure-property relationship,several critical strategies for constructing optimal surface and structure profiles of GF electrodes are summarized.Capitalizing on the exceptional flexibility and wearability of GFSCs,the review further underscores their potential as foundational elements for constructing multifunctional e-textiles using conventional textile technologies.In conclusion,this review provides insights into current challenges and suggests potential research directions for GFSCs.展开更多
IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication,processing,and real-time monitoring across diverse applications.Due to their heterogeneous nature and constrai...IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication,processing,and real-time monitoring across diverse applications.Due to their heterogeneous nature and constrained resources,as well as the growing trend of using smart gadgets,there are privacy and security issues that are not adequately managed by conventional securitymeasures.This review offers a thorough analysis of contemporary AI solutions designed to enhance security within IoT ecosystems.The intersection of AI technologies,including ML,and blockchain,with IoT privacy and security is systematically examined,focusing on their efficacy in addressing core security issues.The methodology involves a detailed exploration of existing literature and research on AI-driven privacy-preserving security mechanisms in IoT.The reviewed solutions are categorized based on their ability to tackle specific security challenges.The review highlights key advancements,evaluates their practical applications,and identifies prevailing research gaps and challenges.The findings indicate that AI solutions,particularly those leveraging ML and blockchain,offerpromising enhancements to IoT privacy and security by improving threat detection capabilities and ensuring data integrity.This paper highlights how AI technologies might strengthen IoT privacy and security and offer suggestions for upcoming studies intended to address enduring problems and improve the robustness of IoT networks.展开更多
In the context of the rapid iteration of information technology,the Internet of Things(IoT)has established itself as a pivotal hub connecting the digital world and the physical world.Wireless Sensor Networks(WSNs),dee...In the context of the rapid iteration of information technology,the Internet of Things(IoT)has established itself as a pivotal hub connecting the digital world and the physical world.Wireless Sensor Networks(WSNs),deeply embedded in the perception layer architecture of the IoT,play a crucial role as“tactile nerve endings.”A vast number of micro sensor nodes are widely distributed in monitoring areas according to preset deployment strategies,continuously and accurately perceiving and collecting real-time data on environmental parameters such as temperature,humidity,light intensity,air pressure,and pollutant concentration.These data are transmitted to the IoT cloud platform through stable and reliable communication links,forming a massive and detailed basic data resource pool.By using cutting-edge big data processing algorithms,machine learning models,and artificial intelligence analysis tools,in-depth mining and intelligent analysis of these multi-source heterogeneous data are conducted to generate high-value-added decision-making bases.This precisely empowers multiple fields,including agriculture,medical and health care,smart home,environmental science,and industrial manufacturing,driving intelligent transformation and catalyzing society to move towards a new stage of high-quality development.This paper comprehensively analyzes the technical cores of the IoT and WSNs,systematically sorts out the advanced key technologies of WSNs and the evolution of their strategic significance in the IoT system,deeply explores the innovative application scenarios and practical effects of the two in specific vertical fields,and looks forward to the technological evolution trends.It provides a detailed and highly practical guiding reference for researchers,technical engineers,and industrial decision-makers.展开更多
In today’s digital world,the Internet of Things(IoT)plays an important role in both local and global economies due to its widespread adoption in different applications.This technology has the potential to offer sever...In today’s digital world,the Internet of Things(IoT)plays an important role in both local and global economies due to its widespread adoption in different applications.This technology has the potential to offer several advantages over conventional technologies in the near future.However,the potential growth of this technology also attracts attention from hackers,which introduces new challenges for the research community that range from hardware and software security to user privacy and authentication.Therefore,we focus on a particular security concern that is associated with malware detection.The literature presents many countermeasures,but inconsistent results on identical datasets and algorithms raise concerns about model biases,training quality,and complexity.This highlights the need for an adaptive,real-time learning framework that can effectively mitigate malware threats in IoT applications.To address these challenges,(i)we propose an intelligent framework based on Two-step Deep Reinforcement Learning(TwStDRL)that is capable of learning and adapting in real-time to counter malware threats in IoT applications.This framework uses exploration and exploitation phenomena during both the training and testing phases by storing results in a replay memory.The stored knowledge allows the model to effectively navigate the environment and maximize cumulative rewards.(ii)To demonstrate the superiority of the TwStDRL framework,we implement and evaluate several machine learning algorithms for comparative analysis that include Support Vector Machines(SVM),Multi-Layer Perceptron,Random Forests,and k-means Clustering.The selection of these algorithms is driven by the inconsistent results reported in the literature,which create doubt about their robustness and reliability in real-world IoT deployments.(iii)Finally,we provide a comprehensive evaluation to justify why the TwStDRL framework outperforms them in mitigating security threats.During analysis,we noted that our proposed TwStDRL scheme achieves an average performance of 99.45%across accuracy,precision,recall,and F1-score,which is an absolute improvement of roughly 3%over the existing malware-detection models.展开更多
With the rapid development of web3.0 applications,the volume of data sharing is increasing,the inefficiency of big data file sharing and the problem of data privacy leakage are becoming more and more prominent,and the...With the rapid development of web3.0 applications,the volume of data sharing is increasing,the inefficiency of big data file sharing and the problem of data privacy leakage are becoming more and more prominent,and the existing data sharing schemes have been difficult to meet the growing demand for data sharing,this paper aims at exploring a secure,efficient and privacy-protecting data sharing scheme under web3.0 applications.Specifically,this paper adopts interplanetary file system(IPFS)technology to realize the storage of large data files to solve the problem of blockchain storage capacity limitation,and utilizes ciphertext policy attribute-based encryption(CP-ABE)and proxy re-encryption(PRE)technology to realize secure multi-party sharing and finegrained access control of data.This paper provides the detailed algorithm design and implementation of data sharing phases and processes,and analyzes the algorithms from the perspectives of security,privacy protection,and performance.展开更多
This paper studies polygon simplification algorithms for 3D models,focuses on the optimization algorithm of quadratic error metric(QEM),explores the impacts of different methods on the simplification of different mode...This paper studies polygon simplification algorithms for 3D models,focuses on the optimization algorithm of quadratic error metric(QEM),explores the impacts of different methods on the simplification of different models,and develops a web-based visualization application.Metrics such as the Hausdorff distance are used to evaluate the balance between the degree of simplification and the retention of model details.展开更多
Inspired by nature's self-similar designs,novel honeycomb-spiderweb based self-similar hybrid cellular structures are proposed here for efficient energy absorption in impact applications.The energy absorption is e...Inspired by nature's self-similar designs,novel honeycomb-spiderweb based self-similar hybrid cellular structures are proposed here for efficient energy absorption in impact applications.The energy absorption is enhanced by optimizing the geometry and topology for a given mass.The proposed hybrid cellular structure is arrived after a thorough analysis of topologically enhanced self-similar structures.The optimized cell designs are rigorously tested considering dynamic loads involving crush and high-velocity bullet impact.Furthermore,the influence of thickness,radial connectivity,and order of patterning at the unit cell level are also investigated.The maximum crushing efficiency attained is found to be more than 95%,which is significantly higher than most existing traditional designs.Later on,the first and second-order hierarchical self-similar unit cell designs developed during crush analysis are used to prepare the cores for sandwich structures.Impact tests are performed on the developed sandwich structures using the standard 9-mm parabellum.The influence of multistaging on impact resistance is also investigated by maintaining a constant total thickness and mass of the sandwich structure.Moreover,in order to avoid layer-wise weak zones and hence,attain a uniform out-of-plane impact strength,off-setting the designs in each stage is proposed.The sandwich structures with first and second-order self-similar hybrid cores are observed to withstand impact velocities as high as 170 m/s and 270 m/s,respectively.展开更多
Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 ...Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 during concurrent outbreaks in Marburg and Frankfurt,Germany,and in Belgrade,Serbia,linked to laboratory use of African green monkeys imported from Uganda.Subsequent outbreaks and isolated cases have been reported in various African countries,including Angola,the Democratic Republic of the Congo,Equatorial Guinea,Ghana,Guinea,Kenya,Rwanda,South Africa(in an individual with recent travel to Zimbabwe),Tanzania,and Uganda.Initial human MVD infections typically occur due to prolonged exposure to mines or caves inhabited by Rousettus aegyptiacus fruit bats,the natural hosts of the virus.展开更多
文摘In today’s rapidly evolving digital landscape,web application security has become paramount as organizations face increasingly sophisticated cyber threats.This work presents a comprehensive methodology for implementing robust security measures in modern web applications and the proof of the Methodology applied to Vue.js,Spring Boot,and MySQL architecture.The proposed approach addresses critical security challenges through a multi-layered framework that encompasses essential security dimensions including multi-factor authentication,fine-grained authorization controls,sophisticated session management,data confidentiality and integrity protection,secure logging mechanisms,comprehensive error handling,high availability strategies,advanced input validation,and security headers implementation.Significant contributions are made to the field of web application security.First,a detailed catalogue of security requirements specifically tailored to protect web applications against contemporary threats,backed by rigorous analysis and industry best practices.Second,the methodology is validated through a carefully designed proof-of-concept implementation in a controlled environment,demonstrating the practical effectiveness of the security measures.The validation process employs cutting-edge static and dynamic analysis tools for comprehensive dependency validation and vulnerability detection,ensuring robust security coverage.The validation results confirm the prevention and avoidance of security vulnerabilities of the methodology.A key innovation of this work is the seamless integration of DevSecOps practices throughout the secure Software Development Life Cycle(SSDLC),creating a security-first mindset from initial design to deployment.By combining proactive secure coding practices with defensive security approaches,a framework is established that not only strengthens application security but also fosters a culture of security awareness within development teams.This hybrid approach ensures that security considerations are woven into every aspect of the development process,rather than being treated as an afterthought.
基金co-supported by the Fundamental Research Funds for the Central Universities,China。
文摘Effect web will be an important combat means to achieve accurate,efficient,agile and reliable destruction of enemy targets.The use of Unmanned Aerial Vehicles(UAV)cluster in warfare has become a key element in the battle for military superiority between nations.The construction of UAV cluster effect web is a kind of combinatorial optimization in essence.By selecting the optimal combination in the limited equipment concentration,the whole network can be optimized.Firstly,in order to improve the combinatorial optimization efficiency of UAV cluster effect web,NSGA-Ⅱbased on deep Q-network(DQN-based NSGA-Ⅱ)is proposed.This algorithm is used to solve the Multi-Objective Combinatorial Optimization(MOCO)problem in the construction of effect web.Secondly,a dynamic generation method is devised to solve the problem caused by the possible destruction of enemy and our node under the fierce confrontation between the two sides.Finally,the simulation results show that the DQN-based NSGA-Ⅱis better than the genetic algorithm with single operator.The comparison experiment shows that the weight of evaluation indexes will have a corresponding influence on the optimization results.
基金supported by National Key Research & Development Program of China (2022YFC3006201)。
文摘Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility of EMS has received considerable attention in health and transport geography studies.^([3])One of the optimal gauges for evaluating the accessibility of EMS is the response time,which is defined as the time from receiving an emergency call to the arrival of an ambulance.^([4])Beijing has already reduced the response time to approximately12 min,and the next goal is to ensure that the response time across Beijing does not exceed 12 min (the information comes from the Beijing Emergency Medical Center).
基金Shanghai Municipal Commission for Science and Technology,Grant/Award Number:23ZR1402500National Natural Science Foundation of China,Grant/Award Number:51973034+1 种基金National Scholarship CouncilNational Key Research and Development Program of China,Grant/Award Number:2023YFB3809800.
文摘Graphene fiber supercapacitors(GFSCs)have garnered significant attention due to their exceptional features,including high power density,rapid charge/discharge rates,prolonged cycling durability,and versatile weaving capabilities.Nevertheless,inherent challenges in graphene fibers(GFs),particularly the restricted ion-accessible specific surface area(SSA)and sluggish ion transport kinetics,hinder the achievement of optimal capacitance and rate performance.Despite existing reviews on GFSCs,a notable gap exists in thoroughly exploring the kinetics governing the energy storage process in GFSCs.This review aims to address this gap by thoroughly analyzing the energy storage mechanism,fabrication methodologies,property manipulation,and wearable applications of GFSCs.Through theoretical analysis of the energy storage process,specific parameters in advanced GF fabrication methodologies are carefully summarized,which can be used to modulate nano/micro-structures,thereby enhancing energy storage kinetics.In particular,enhanced ion storage is realized by creating more ion-accessible SSA and introducing extra-capacitive components,while accelerated ion transport is achieved by shortening the transport channel length and improving the accessibility of electrolyte ions.Building on the established structure-property relationship,several critical strategies for constructing optimal surface and structure profiles of GF electrodes are summarized.Capitalizing on the exceptional flexibility and wearability of GFSCs,the review further underscores their potential as foundational elements for constructing multifunctional e-textiles using conventional textile technologies.In conclusion,this review provides insights into current challenges and suggests potential research directions for GFSCs.
基金The author Dr.Arshiya Sajid Ansari extends the appreciation to the Deanship of Postgraduate Studies and Scientific Research at Majmaah University for funding this research work through the project number(R-2025-1706).
文摘IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication,processing,and real-time monitoring across diverse applications.Due to their heterogeneous nature and constrained resources,as well as the growing trend of using smart gadgets,there are privacy and security issues that are not adequately managed by conventional securitymeasures.This review offers a thorough analysis of contemporary AI solutions designed to enhance security within IoT ecosystems.The intersection of AI technologies,including ML,and blockchain,with IoT privacy and security is systematically examined,focusing on their efficacy in addressing core security issues.The methodology involves a detailed exploration of existing literature and research on AI-driven privacy-preserving security mechanisms in IoT.The reviewed solutions are categorized based on their ability to tackle specific security challenges.The review highlights key advancements,evaluates their practical applications,and identifies prevailing research gaps and challenges.The findings indicate that AI solutions,particularly those leveraging ML and blockchain,offerpromising enhancements to IoT privacy and security by improving threat detection capabilities and ensuring data integrity.This paper highlights how AI technologies might strengthen IoT privacy and security and offer suggestions for upcoming studies intended to address enduring problems and improve the robustness of IoT networks.
文摘In the context of the rapid iteration of information technology,the Internet of Things(IoT)has established itself as a pivotal hub connecting the digital world and the physical world.Wireless Sensor Networks(WSNs),deeply embedded in the perception layer architecture of the IoT,play a crucial role as“tactile nerve endings.”A vast number of micro sensor nodes are widely distributed in monitoring areas according to preset deployment strategies,continuously and accurately perceiving and collecting real-time data on environmental parameters such as temperature,humidity,light intensity,air pressure,and pollutant concentration.These data are transmitted to the IoT cloud platform through stable and reliable communication links,forming a massive and detailed basic data resource pool.By using cutting-edge big data processing algorithms,machine learning models,and artificial intelligence analysis tools,in-depth mining and intelligent analysis of these multi-source heterogeneous data are conducted to generate high-value-added decision-making bases.This precisely empowers multiple fields,including agriculture,medical and health care,smart home,environmental science,and industrial manufacturing,driving intelligent transformation and catalyzing society to move towards a new stage of high-quality development.This paper comprehensively analyzes the technical cores of the IoT and WSNs,systematically sorts out the advanced key technologies of WSNs and the evolution of their strategic significance in the IoT system,deeply explores the innovative application scenarios and practical effects of the two in specific vertical fields,and looks forward to the technological evolution trends.It provides a detailed and highly practical guiding reference for researchers,technical engineers,and industrial decision-makers.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R104)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘In today’s digital world,the Internet of Things(IoT)plays an important role in both local and global economies due to its widespread adoption in different applications.This technology has the potential to offer several advantages over conventional technologies in the near future.However,the potential growth of this technology also attracts attention from hackers,which introduces new challenges for the research community that range from hardware and software security to user privacy and authentication.Therefore,we focus on a particular security concern that is associated with malware detection.The literature presents many countermeasures,but inconsistent results on identical datasets and algorithms raise concerns about model biases,training quality,and complexity.This highlights the need for an adaptive,real-time learning framework that can effectively mitigate malware threats in IoT applications.To address these challenges,(i)we propose an intelligent framework based on Two-step Deep Reinforcement Learning(TwStDRL)that is capable of learning and adapting in real-time to counter malware threats in IoT applications.This framework uses exploration and exploitation phenomena during both the training and testing phases by storing results in a replay memory.The stored knowledge allows the model to effectively navigate the environment and maximize cumulative rewards.(ii)To demonstrate the superiority of the TwStDRL framework,we implement and evaluate several machine learning algorithms for comparative analysis that include Support Vector Machines(SVM),Multi-Layer Perceptron,Random Forests,and k-means Clustering.The selection of these algorithms is driven by the inconsistent results reported in the literature,which create doubt about their robustness and reliability in real-world IoT deployments.(iii)Finally,we provide a comprehensive evaluation to justify why the TwStDRL framework outperforms them in mitigating security threats.During analysis,we noted that our proposed TwStDRL scheme achieves an average performance of 99.45%across accuracy,precision,recall,and F1-score,which is an absolute improvement of roughly 3%over the existing malware-detection models.
基金supported by the National Natural Science Foundation of China(Grant No.U24B20146)the National Key Research and Development Plan in China(Grant No.2020YFB1005500)Beijing Natural Science Foundation Project(No.M21034).
文摘With the rapid development of web3.0 applications,the volume of data sharing is increasing,the inefficiency of big data file sharing and the problem of data privacy leakage are becoming more and more prominent,and the existing data sharing schemes have been difficult to meet the growing demand for data sharing,this paper aims at exploring a secure,efficient and privacy-protecting data sharing scheme under web3.0 applications.Specifically,this paper adopts interplanetary file system(IPFS)technology to realize the storage of large data files to solve the problem of blockchain storage capacity limitation,and utilizes ciphertext policy attribute-based encryption(CP-ABE)and proxy re-encryption(PRE)technology to realize secure multi-party sharing and finegrained access control of data.This paper provides the detailed algorithm design and implementation of data sharing phases and processes,and analyzes the algorithms from the perspectives of security,privacy protection,and performance.
文摘This paper studies polygon simplification algorithms for 3D models,focuses on the optimization algorithm of quadratic error metric(QEM),explores the impacts of different methods on the simplification of different models,and develops a web-based visualization application.Metrics such as the Hausdorff distance are used to evaluate the balance between the degree of simplification and the retention of model details.
基金the Science and Engineering Research Board(SERB),Department of Science and Technology,India,for funding this research through grant number SRG/2019/001581。
文摘Inspired by nature's self-similar designs,novel honeycomb-spiderweb based self-similar hybrid cellular structures are proposed here for efficient energy absorption in impact applications.The energy absorption is enhanced by optimizing the geometry and topology for a given mass.The proposed hybrid cellular structure is arrived after a thorough analysis of topologically enhanced self-similar structures.The optimized cell designs are rigorously tested considering dynamic loads involving crush and high-velocity bullet impact.Furthermore,the influence of thickness,radial connectivity,and order of patterning at the unit cell level are also investigated.The maximum crushing efficiency attained is found to be more than 95%,which is significantly higher than most existing traditional designs.Later on,the first and second-order hierarchical self-similar unit cell designs developed during crush analysis are used to prepare the cores for sandwich structures.Impact tests are performed on the developed sandwich structures using the standard 9-mm parabellum.The influence of multistaging on impact resistance is also investigated by maintaining a constant total thickness and mass of the sandwich structure.Moreover,in order to avoid layer-wise weak zones and hence,attain a uniform out-of-plane impact strength,off-setting the designs in each stage is proposed.The sandwich structures with first and second-order self-similar hybrid cores are observed to withstand impact velocities as high as 170 m/s and 270 m/s,respectively.
文摘Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 during concurrent outbreaks in Marburg and Frankfurt,Germany,and in Belgrade,Serbia,linked to laboratory use of African green monkeys imported from Uganda.Subsequent outbreaks and isolated cases have been reported in various African countries,including Angola,the Democratic Republic of the Congo,Equatorial Guinea,Ghana,Guinea,Kenya,Rwanda,South Africa(in an individual with recent travel to Zimbabwe),Tanzania,and Uganda.Initial human MVD infections typically occur due to prolonged exposure to mines or caves inhabited by Rousettus aegyptiacus fruit bats,the natural hosts of the virus.
