Throughout the lifespan,an animal can encounter predators frequently,thus the ability to avoid attacks from predators is crucial for its survival.The chances of evading danger can be greatly improved if the animal can...Throughout the lifespan,an animal can encounter predators frequently,thus the ability to avoid attacks from predators is crucial for its survival.The chances of evading danger can be greatly improved if the animal can respond immediately to the threat.Therefore,when an animal detects a threat through its visual system,it must quickly direct its gaze and attention toward the source of danger,assess the threat level,and take appropriate action.展开更多
Antimicrobial resistance is a global health crisis and carbapenem-resistant Klebsiella pneumoniae(CRKp)is listed as one of the top high-priority pathogens by the World Health Organization.Meanwhile,hypervirulent K.pne...Antimicrobial resistance is a global health crisis and carbapenem-resistant Klebsiella pneumoniae(CRKp)is listed as one of the top high-priority pathogens by the World Health Organization.Meanwhile,hypervirulent K.pneumoniae(hvKp)causes severe community-associated infections,such as liver abscesses and meningitis,in otherwise healthy individuals.Both CRKp and hvKp infections are associated with high mortality rates.The convergence of carbapenem resistance and hypervirulence within a single bacterial strain may lead to significantly more severe clinical outcomes.展开更多
The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making co...The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making collision avoidance significantly more challenging than that for space debris.Much existing research focuses on the continuous thrust model,whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally,it is important to minimize the impact on the original mission while avoiding noncooperative targets.On the other hand,the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer,posing challenges for practical engineering applications.To conquer these difficulties,this paper makes the following key contributions:(A)a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B)a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST)algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS).Numerical simulations confirm the effectiveness and efficiency of the proposed method.展开更多
Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to...Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to better implement advertising activities,this study intends to summarize the relevant research on advertising avoidance in recent years.The specific method is to use the core literature meta-analysis method to identify,filter,and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance.We review the collected articles from the following perspectives:the definition and classification,external stimulating factors,internal perception factors,and moderating factors of advertising avoidance.On this basis,the SOMR model of advertising avoidance is constructed according to the SOR model.Finally,some prospects for future related research are presented.展开更多
Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework n...Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework named the Formation Interfered Fluid Dynamical System(FIFDS) with Moderate Evasive Maneuver Strategy(MEMS) is proposed in this study.First, the UAV formation collision avoidance problem including quantifiable performance indexes is formulated. Second, inspired by the phenomenon of fluids continuously flowing while bypassing objects, the FIFDS for multiple UAVs is presented, which contains a Parallel Streamline Tracking(PST) method for formation keeping and the traditional IFDS for collision avoidance. Third, to rationally balance flight safety and collision avoidance cost, MEMS is proposed to generate moderate evasive maneuvers that match up with collision risks. Comprehensively containing the time and distance safety information, the 3-D dynamic collision regions are modeled for collision prediction. Then, the moderate evasive maneuver principle is refined, which provides criterions of the maneuver amplitude and direction. On this basis, an analytical parameter mapping mechanism is designed to online optimize IFDS parameters. Finally, the performance of the proposed method is validated by comparative simulation results and real flight experiments using fixed-wing UAVs.展开更多
1.Introduction Data inference(DInf)is a data security threat in which critical information is inferred from low-sensitivity data.Once regarded as an advanced professional threat limited to intelligence analysts,DInf h...1.Introduction Data inference(DInf)is a data security threat in which critical information is inferred from low-sensitivity data.Once regarded as an advanced professional threat limited to intelligence analysts,DInf has become a widespread risk in the artificial intelligence(AI)era.展开更多
The current global cybersecurity landscape, characterized by the increasing scale and sophistication of cyberattacks, underscores the importance of integrating Cyber Threat Intelligence (CTI) into Land Administration ...The current global cybersecurity landscape, characterized by the increasing scale and sophistication of cyberattacks, underscores the importance of integrating Cyber Threat Intelligence (CTI) into Land Administration Systems (LAS). LAS services involve requests and responses concerning public and private cadastral data, including credentials of parties, ownership, and spatial parcels. This study explores the integration of CTI in LAS to enhance cyber resilience, focusing on the unique vulnerabilities of LAS, such as sensitive data management and interconnection with other critical systems related to spatial data uses and changes. The approach employs a case study of a typical country-specific LAS to analyse structured vulnerabilities and their attributes to determine the degree of vulnerability of LAS through a quantitative inductive approach. The analysis results indicate significant improvements in identifying and mitigating potential threats through CTI integration, thus enhancing cyber resilience. These findings are crucial for policymakers and practitioners to develop robust cybersecurity strategies for LAS.展开更多
This study aims to systematically review the various factors influencing corporate tax avoidance.Tax avoidance refers to legal strategies used to minimize tax liabilities and has become a critical issue in accounting ...This study aims to systematically review the various factors influencing corporate tax avoidance.Tax avoidance refers to legal strategies used to minimize tax liabilities and has become a critical issue in accounting and corporate governance.The study examines key determinants of tax avoidance,including firm characteristics(such as size,leverage,and multinational scale),managerial attributes,executive compensation,ownership structure,corporate social responsibility(CSR)performance,as well as the impact of regulations and legal reforms.The review findings highlight that the motivations behind tax avoidance are multifaceted,driven by the interaction of economic incentives,organizational ethics,external pressures,and public policies.Moreover,strict regulatory environments and strong CSR practices can mitigate tax avoidance behaviors,although their effectiveness is often contingent upon a firm’s cultural and political context.This study offers a comprehensive mapping of the current literature and recommends future research that integrates additional variables and broader time spans to enhance the understanding of tax avoidance behavior across different national contexts.展开更多
The fast increase of online communities has brought about an increase in cyber threats inclusive of cyberbullying, hate speech, misinformation, and online harassment, making content moderation a pressing necessity. Tr...The fast increase of online communities has brought about an increase in cyber threats inclusive of cyberbullying, hate speech, misinformation, and online harassment, making content moderation a pressing necessity. Traditional single-modal AI-based detection systems, which analyze both text, photos, or movies in isolation, have established useless at taking pictures multi-modal threats, in which malicious actors spread dangerous content throughout a couple of formats. To cope with these demanding situations, we advise a multi-modal deep mastering framework that integrates Natural Language Processing (NLP), Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks to become aware of and mitigate online threats effectively. Our proposed model combines BERT for text class, ResNet50 for photograph processing, and a hybrid LSTM-3-d CNN community for video content material analysis. We constructed a large-scale dataset comprising 500,000 textual posts, 200,000 offensive images, and 50,000 annotated motion pictures from more than one platform, which includes Twitter, Reddit, YouTube, and online gaming forums. The system became carefully evaluated using trendy gadget mastering metrics which include accuracy, precision, remember, F1-score, and ROC-AUC curves. Experimental outcomes demonstrate that our multi-modal method extensively outperforms single-modal AI classifiers, achieving an accuracy of 92.3%, precision of 91.2%, do not forget of 90.1%, and an AUC rating of 0.95. The findings validate the necessity of integrating multi-modal AI for actual-time, high-accuracy online chance detection and moderation. Future paintings will have consciousness on improving hostile robustness, enhancing scalability for real-world deployment, and addressing ethical worries associated with AI-driven content moderation.展开更多
As an emerging environmental contaminant,antibiotic resistance genes(ARGs)in tap water have attracted great attention.Although studies have provided ARG profiles in tap water,research on their abundance levels,composi...As an emerging environmental contaminant,antibiotic resistance genes(ARGs)in tap water have attracted great attention.Although studies have provided ARG profiles in tap water,research on their abundance levels,composition characteristics,and potential threat is still insufficient.Here,9 household tap water samples were collected from the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)in China.Additionally,75 sets of environmental sample data(9 types)were downloaded from the public database.Metagenomics was then performed to explore the differences in the abundance and composition of ARGs.221 ARG subtypes consisting of 17 types were detected in tap water.Although the ARG abundance in tap water was not significantly different from that found in drinking water plants and reservoirs,their composition varied.In tap water samples,the three most abundant classes of resistance genes were multidrug,fosfomycin and MLS(macrolide-lincosamidestreptogramin)ARGs,and their corresponding subtypes ompR,fosX and macB were also the most abundant ARG subtypes.Regarding the potential mobility,vanS had the highest abundance on plasmids and viruses,but the absence of key genes rendered resistance to vancomycin ineffective.Generally,the majority of ARGs present in tap water were those that have not been assessed and are currently not listed as high-threat level ARG families based on the World Health Organization Guideline.Although the current potential threat to human health posed by ARGs in tap water is limited,with persistent transfer and accumulation,especially in pathogens,the potential danger to human health posed by ARGs should not be ignored.展开更多
Given the unique challenges facing the railway industry, cybersecurity is a crucial issue that must be addressed proactively. This paper aims to provide a systematic review of cybersecurity threats that could impact t...Given the unique challenges facing the railway industry, cybersecurity is a crucial issue that must be addressed proactively. This paper aims to provide a systematic review of cybersecurity threats that could impact the safety and operations of rolling stock, the privacy and security of passengers and employees, and the public in general. The systematic literature review revealed that cyber threats to the railway industry can take many forms, including attacks on operational technology systems, data breaches, theft of sensitive information, and disruptions to train services. The consequences of these threats can be severe, leading to operational disruptions, financial losses, and loss of public trust in the railway system. To address these threats, railway organizations must adopt a proactive approach to security and implement robust cybersecurity measures tailored to the industry’s specific needs and challenges. This includes regular testing of systems for vulnerabilities, incident response plans, and employee training to identify and respond to cyber threats. Ensuring the system remains available, reliable, and maintainable is fundamental given the importance of railways as critical infrastructure and the potential harm that can be caused by cyber threats.展开更多
Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localizatio...Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localization and tracking.Therefore,we propose a complete target encirclement method.Firstly,based on Hooke's law,a collision avoidance controller is designed to maintain a safe flying distance among quadrotors.Then,based on the consensus theory,a formation tracking controller is designed to meet the requirements of formation transformation and encirclement tasks,and a stability proof based on Lyapunov was provided.Besides,the target detection is designed based on YOLOv5s,and the target location model is constructed based on the principle of pinhole projection and triangle similarity.Finally,we conducted experiments on the built platform,with 3 reconnaissance quadrotors detecting and localization 3 target vehicles and 7 hunter quadrotors tracking them.The results show that the minimum average error for localization targets with reconnaissance quadrotors can reach 0.1354 m,while the minimum average error for tracking with hunter quadrotors is only 0.2960 m.No quadrotors collision occurred in the whole formation transformation and tracking experiment.In addition,compared with the advanced methods,the proposed method has better performance.展开更多
Due to the lack of human avoidance analysis,the orthosis cannot accurately apply orthopedic force during orthopedic,resulting in poor orthopedic effect.Therefore,the relationship between the human body’s active avoid...Due to the lack of human avoidance analysis,the orthosis cannot accurately apply orthopedic force during orthopedic,resulting in poor orthopedic effect.Therefore,the relationship between the human body’s active avoidance ability and force application is studied to achieve accurate loading of orthopedic force.First,a high-precision scoliosis model was established based on computed tomography data,and the relationship between orthopedic force and Cobb angle was analyzed.Then 9 subjects were selected for avoidance ability test grouped by body mass index calculation,and the avoidance function of different groups was fitted.The avoidance function corrected the application of orthopedic forces.The results show that the optimal correction force calculated by the finite element method was 60 N.The obese group had the largest avoidance ability,followed by the standard group and the lean group.When the orthopedic force was 60 N,the Cobb angle was reduced from 33.77°to 20°,the avoidance ability of the standard group at 50 N obtained from the avoidance function was 20.28%and 10.14 N was actively avoided.Therefore,when 50 N was applied,60.14 N was actually generated,which can achieve the orthopedic effect of 60 N numerical simulation analysis.The avoidance effect can take the active factors of the human body into consideration in the orthopedic process,so as to achieve a more accurate application of orthopedic force,and provide data reference for clinicians in the orthopedic process.展开更多
Advanced Persistent Threats(APTs)pose significant challenges to detect due to their“low-and-slow”attack patterns and frequent use of zero-day vulnerabilities.Within this task,the extraction of long-term features is ...Advanced Persistent Threats(APTs)pose significant challenges to detect due to their“low-and-slow”attack patterns and frequent use of zero-day vulnerabilities.Within this task,the extraction of long-term features is often crucial.In this work,we propose a novel end-to-end APT detection framework named Long-Term Feature Association Provenance Graph Detector(LT-ProveGD).Specifically,LT-ProveGD encodes contextual information of the dynamic provenance graph while preserving the topological information with space efficiency.To combat“low-and-slow”attacks,LT-ProveGD develops an autoencoder with an integrated multi-head attention mechanism to extract long-term dependencies within the encoded representations.Furthermore,to facilitate the detection of previously unknown attacks,we leverage Jenks’natural breaks methodology,enabling detection without relying on specific attack information.By conducting extensive experiments on five widely used datasets with state-of-the-art attack detection methods,we demonstrate the superior effectiveness of LT-ProveGD.展开更多
Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in ne...Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in networks and systems.Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data,learn patterns,and anticipate potential threats.Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly.Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks.This research advocates for proactive measures and adaptive technologies in defending digital environments.Improvements in detection ability by organizations will assist in safeguarding assets and integrity in operations in this increasingly digital world.This paper draws on the categorization of cyber threat detection methods using hesitant bipolar fuzzy Frank operators.Categorization is a step that is necessary for systematic comparison and assessment of detection methods so that the most suitable method for particular cybersecurity requirements is chosen.Furthermore,this research manages uncertainty and vagueness that exists in decision-making by applying hesitant bipolar fuzzy logic.The importance of the work lies in how it fortifies cybersecurity architectures with a formal method of discovering optimal detection measures and improving responsiveness,resulting in holistic protection against dynamic threats.展开更多
Objectives:Positive family functioning(FF)is critical for adolescent development,yet only a few studies have examined this developmental trajectory pathway.This study aimed to identify different types of FF developmen...Objectives:Positive family functioning(FF)is critical for adolescent development,yet only a few studies have examined this developmental trajectory pathway.This study aimed to identify different types of FF development trajectories during junior high school students,investigate their influence on social avoidance(SA),and further examine the mediating role of preference for solitude(PS)between them.Methods:A three-wave longitudinal study was used with six-month intervals.Questionnaire data were collected from 436 junior high school students in Jiangxi Province,China.Participants ranged in age from 11 to 14 years old(Mean=12.89 years,SD=1.08;50.2%male).Results:Four heterogeneous types of FF trajectories were identified:(1)a high and increasing group(14.7%);(2)a consistently high group(36.24%);(3)a consistently moderate group(45.86%);and(4)a rapid growth group(3.2%).The developmental trajectories of FF among junior high students significantly varied in their levels of SA(F(3,432)=32.03,p<0.001).Compared to the high and increasing groups,the consistently high,consistently medium,and rapid growth groups exhibited higher levels of SA.PS mediated the association between the developmental trajectory of FF and SA.Conclusion:There was a close relationship between the developmental trajectory of FF and SA.Interventions focusing on family system optimization and solitary preference management could effectively mitigate SA behaviors.These findings are important for promoting healthy socialization in adolescents.展开更多
In the realm of missile defense systems,the self-sufficient maneuver capacity of missile swarms is pivotal for their survival.Through the analysis of the missile dynamics model,a time-efficient cooperative attack stra...In the realm of missile defense systems,the self-sufficient maneuver capacity of missile swarms is pivotal for their survival.Through the analysis of the missile dynamics model,a time-efficient cooperative attack strategy for missile swarm is proposed.Based on the distribution of the attackers and defenders,the collision avoidance against the defenders is considered during the attack process.By analyzing the geometric relationship between the relative velocity vector and relative position vector of the attackers and defenders,the collision avoidance constrains of attacking swarm are redefined.The key point is on adjusting the relative velocity vectors to fall outside the collision cone.This work facilitates high-precision attack toward the target while keeping safe missing distance between other attackers during collision avoidance process.By leveraging an innovative repulsion artificial function,a time-efficient cooperative attack strategy for missile swarm is obtained.Through rigorous simulation,the effectiveness of this cooperative attack strategy is substantiated.Furthermore,by employing Monte Carlo simulation,the success rate of the cooperative attack strategy is assessesed and the optimal configuration for the missile swarm is deduced.展开更多
Beyond-visual-range(BVR)air combat threat assessment has attracted wide attention as the support of situation awareness and autonomous decision-making.However,the traditional threat assessment method is flawed in its ...Beyond-visual-range(BVR)air combat threat assessment has attracted wide attention as the support of situation awareness and autonomous decision-making.However,the traditional threat assessment method is flawed in its failure to consider the intention and event of the target,resulting in inaccurate assessment results.In view of this,an integrated threat assessment method is proposed to address the existing problems,such as overly subjective determination of index weight and imbalance of situation.The process and characteristics of BVR air combat are analyzed to establish a threat assessment model in terms of target intention,event,situation,and capability.On this basis,a distributed weight-solving algorithm is proposed to determine index and attribute weight respectively.Then,variable weight and game theory are introduced to effectively deal with the situation imbalance and achieve the combination of subjective and objective.The performance of the model and algorithm is evaluated through multiple simulation experiments.The assessment results demonstrate the accuracy of the proposed method in BVR air combat,indicating its potential practical significance in real air combat scenarios.展开更多
In this paper,a novel cooperative collision avoidance control strategy with relative velocity information for redundant robotic manipulators is derived to guarantee the behavioral safety of robots in the cooperative o...In this paper,a novel cooperative collision avoidance control strategy with relative velocity information for redundant robotic manipulators is derived to guarantee the behavioral safety of robots in the cooperative operational task.This strategy can generate the collision-free trajectory of the robotic links in real-time,which is to realize that the robot can avoid moving obstacles less conservatively and ensure tracking accuracy of terminal end-effector tasks in performing cooperative tasks.For the case where there is interference between the moving obstacle and the desired path of the robotic end-effector,the method inherits the null-space-based self-motion characteristics of the redundant manipulator,integrates the relative motion information,and uses the improved artificial potential field method to design the control items,which are used to generate the collision avoidance motion and carry out moving obstacles smoothly and less conservatively.At the same time,the strategy maintains the kinematic constraint relationship of dual-arm cooperatives,to meet the real-time collision avoidance task under collaborative tasks.Finally,the algorithm simulation indicates that the method can better ensure the tracking accuracy of the end-effector task and carry out moving obstacles smoothly.The experimental results show that the method can generate the real-time collision-free trajectory of the robot in the cooperative handling task,and the joint movement is continuous and stable.展开更多
This paper deeply explores the autonomous collision avoidance algorithm for intelligent ships,aiming to enhance the intelligence level and safety of ship collision avoidance by integrating navigation experience.An aut...This paper deeply explores the autonomous collision avoidance algorithm for intelligent ships,aiming to enhance the intelligence level and safety of ship collision avoidance by integrating navigation experience.An autonomous collision avoidance algorithm based on navigation experience is designed,a collision avoidance experience database is constructed,a quantitative model is established,and specific algorithm steps are implemented.The algorithm is verified and analyzed through simulation tests.The results show that the algorithm can effectively achieve autonomous ship collision avoidance in different scenarios,providing new ideas and methods for the development of intelligent ship collision avoidance technology.展开更多
基金supported by the National Natural Science Foundation of China(32471055 and 82171090)Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)ZJLab,Shanghai Center for Brain Science and Brain-Inspired Technology,the Lingang Laboratory(LG-QS-202203-12).
文摘Throughout the lifespan,an animal can encounter predators frequently,thus the ability to avoid attacks from predators is crucial for its survival.The chances of evading danger can be greatly improved if the animal can respond immediately to the threat.Therefore,when an animal detects a threat through its visual system,it must quickly direct its gaze and attention toward the source of danger,assess the threat level,and take appropriate action.
基金supported by the National Natural Science Foundation of China(grant numbers 81991531 to M.W.,82102440 to J.J.,and 32400149 to J.Z.).
文摘Antimicrobial resistance is a global health crisis and carbapenem-resistant Klebsiella pneumoniae(CRKp)is listed as one of the top high-priority pathogens by the World Health Organization.Meanwhile,hypervirulent K.pneumoniae(hvKp)causes severe community-associated infections,such as liver abscesses and meningitis,in otherwise healthy individuals.Both CRKp and hvKp infections are associated with high mortality rates.The convergence of carbapenem resistance and hypervirulence within a single bacterial strain may lead to significantly more severe clinical outcomes.
基金co-supported by the Foundation of Shanghai Astronautics Science and Technology Innovation,China(No.SAST2022-114)the National Natural Science Foundation of China(No.62303378),the National Natural Science Foundation of China(Nos.124B2031,12202281)the Foundation of China National Key Laboratory of Science and Technology on Test Physics&Numerical Mathematics,China(No.08-YY-2023-R11)。
文摘The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making collision avoidance significantly more challenging than that for space debris.Much existing research focuses on the continuous thrust model,whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally,it is important to minimize the impact on the original mission while avoiding noncooperative targets.On the other hand,the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer,posing challenges for practical engineering applications.To conquer these difficulties,this paper makes the following key contributions:(A)a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B)a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST)algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS).Numerical simulations confirm the effectiveness and efficiency of the proposed method.
文摘Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to better implement advertising activities,this study intends to summarize the relevant research on advertising avoidance in recent years.The specific method is to use the core literature meta-analysis method to identify,filter,and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance.We review the collected articles from the following perspectives:the definition and classification,external stimulating factors,internal perception factors,and moderating factors of advertising avoidance.On this basis,the SOMR model of advertising avoidance is constructed according to the SOR model.Finally,some prospects for future related research are presented.
基金supported in part by the National Natural Science Foundations of China(Nos.61175084,61673042 and 62203046)the China Postdoctoral Science Foundation(No.2022M713006).
文摘Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework named the Formation Interfered Fluid Dynamical System(FIFDS) with Moderate Evasive Maneuver Strategy(MEMS) is proposed in this study.First, the UAV formation collision avoidance problem including quantifiable performance indexes is formulated. Second, inspired by the phenomenon of fluids continuously flowing while bypassing objects, the FIFDS for multiple UAVs is presented, which contains a Parallel Streamline Tracking(PST) method for formation keeping and the traditional IFDS for collision avoidance. Third, to rationally balance flight safety and collision avoidance cost, MEMS is proposed to generate moderate evasive maneuvers that match up with collision risks. Comprehensively containing the time and distance safety information, the 3-D dynamic collision regions are modeled for collision prediction. Then, the moderate evasive maneuver principle is refined, which provides criterions of the maneuver amplitude and direction. On this basis, an analytical parameter mapping mechanism is designed to online optimize IFDS parameters. Finally, the performance of the proposed method is validated by comparative simulation results and real flight experiments using fixed-wing UAVs.
基金supported by the National Key Research and Development Program of China(2022YFB2703503)the National Natural Science Foundation of China(62293501,62525210,and 62293502)the China Scholarship Council(202306280318).
文摘1.Introduction Data inference(DInf)is a data security threat in which critical information is inferred from low-sensitivity data.Once regarded as an advanced professional threat limited to intelligence analysts,DInf has become a widespread risk in the artificial intelligence(AI)era.
文摘The current global cybersecurity landscape, characterized by the increasing scale and sophistication of cyberattacks, underscores the importance of integrating Cyber Threat Intelligence (CTI) into Land Administration Systems (LAS). LAS services involve requests and responses concerning public and private cadastral data, including credentials of parties, ownership, and spatial parcels. This study explores the integration of CTI in LAS to enhance cyber resilience, focusing on the unique vulnerabilities of LAS, such as sensitive data management and interconnection with other critical systems related to spatial data uses and changes. The approach employs a case study of a typical country-specific LAS to analyse structured vulnerabilities and their attributes to determine the degree of vulnerability of LAS through a quantitative inductive approach. The analysis results indicate significant improvements in identifying and mitigating potential threats through CTI integration, thus enhancing cyber resilience. These findings are crucial for policymakers and practitioners to develop robust cybersecurity strategies for LAS.
文摘This study aims to systematically review the various factors influencing corporate tax avoidance.Tax avoidance refers to legal strategies used to minimize tax liabilities and has become a critical issue in accounting and corporate governance.The study examines key determinants of tax avoidance,including firm characteristics(such as size,leverage,and multinational scale),managerial attributes,executive compensation,ownership structure,corporate social responsibility(CSR)performance,as well as the impact of regulations and legal reforms.The review findings highlight that the motivations behind tax avoidance are multifaceted,driven by the interaction of economic incentives,organizational ethics,external pressures,and public policies.Moreover,strict regulatory environments and strong CSR practices can mitigate tax avoidance behaviors,although their effectiveness is often contingent upon a firm’s cultural and political context.This study offers a comprehensive mapping of the current literature and recommends future research that integrates additional variables and broader time spans to enhance the understanding of tax avoidance behavior across different national contexts.
文摘The fast increase of online communities has brought about an increase in cyber threats inclusive of cyberbullying, hate speech, misinformation, and online harassment, making content moderation a pressing necessity. Traditional single-modal AI-based detection systems, which analyze both text, photos, or movies in isolation, have established useless at taking pictures multi-modal threats, in which malicious actors spread dangerous content throughout a couple of formats. To cope with these demanding situations, we advise a multi-modal deep mastering framework that integrates Natural Language Processing (NLP), Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks to become aware of and mitigate online threats effectively. Our proposed model combines BERT for text class, ResNet50 for photograph processing, and a hybrid LSTM-3-d CNN community for video content material analysis. We constructed a large-scale dataset comprising 500,000 textual posts, 200,000 offensive images, and 50,000 annotated motion pictures from more than one platform, which includes Twitter, Reddit, YouTube, and online gaming forums. The system became carefully evaluated using trendy gadget mastering metrics which include accuracy, precision, remember, F1-score, and ROC-AUC curves. Experimental outcomes demonstrate that our multi-modal method extensively outperforms single-modal AI classifiers, achieving an accuracy of 92.3%, precision of 91.2%, do not forget of 90.1%, and an AUC rating of 0.95. The findings validate the necessity of integrating multi-modal AI for actual-time, high-accuracy online chance detection and moderation. Future paintings will have consciousness on improving hostile robustness, enhancing scalability for real-world deployment, and addressing ethical worries associated with AI-driven content moderation.
基金supported by the National Key R&D Program of China(No.2022YFE0103200)the Hubei Provincial Natural Science Foundation of China(No.2021CFB016)the National Natural Science Foundation of China(No.52100217).
文摘As an emerging environmental contaminant,antibiotic resistance genes(ARGs)in tap water have attracted great attention.Although studies have provided ARG profiles in tap water,research on their abundance levels,composition characteristics,and potential threat is still insufficient.Here,9 household tap water samples were collected from the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)in China.Additionally,75 sets of environmental sample data(9 types)were downloaded from the public database.Metagenomics was then performed to explore the differences in the abundance and composition of ARGs.221 ARG subtypes consisting of 17 types were detected in tap water.Although the ARG abundance in tap water was not significantly different from that found in drinking water plants and reservoirs,their composition varied.In tap water samples,the three most abundant classes of resistance genes were multidrug,fosfomycin and MLS(macrolide-lincosamidestreptogramin)ARGs,and their corresponding subtypes ompR,fosX and macB were also the most abundant ARG subtypes.Regarding the potential mobility,vanS had the highest abundance on plasmids and viruses,but the absence of key genes rendered resistance to vancomycin ineffective.Generally,the majority of ARGs present in tap water were those that have not been assessed and are currently not listed as high-threat level ARG families based on the World Health Organization Guideline.Although the current potential threat to human health posed by ARGs in tap water is limited,with persistent transfer and accumulation,especially in pathogens,the potential danger to human health posed by ARGs should not be ignored.
文摘Given the unique challenges facing the railway industry, cybersecurity is a crucial issue that must be addressed proactively. This paper aims to provide a systematic review of cybersecurity threats that could impact the safety and operations of rolling stock, the privacy and security of passengers and employees, and the public in general. The systematic literature review revealed that cyber threats to the railway industry can take many forms, including attacks on operational technology systems, data breaches, theft of sensitive information, and disruptions to train services. The consequences of these threats can be severe, leading to operational disruptions, financial losses, and loss of public trust in the railway system. To address these threats, railway organizations must adopt a proactive approach to security and implement robust cybersecurity measures tailored to the industry’s specific needs and challenges. This includes regular testing of systems for vulnerabilities, incident response plans, and employee training to identify and respond to cyber threats. Ensuring the system remains available, reliable, and maintainable is fundamental given the importance of railways as critical infrastructure and the potential harm that can be caused by cyber threats.
基金the National Natural Science Foundation of China(Grant Nos.62303348 and 62173242)the Aeronautical Science Foundation of China(Grant No.2024M071048002)the National Science Fund for Distinguished Young Scholars(Grant No.62225308)to provide fund for conducting experiments.
文摘Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localization and tracking.Therefore,we propose a complete target encirclement method.Firstly,based on Hooke's law,a collision avoidance controller is designed to maintain a safe flying distance among quadrotors.Then,based on the consensus theory,a formation tracking controller is designed to meet the requirements of formation transformation and encirclement tasks,and a stability proof based on Lyapunov was provided.Besides,the target detection is designed based on YOLOv5s,and the target location model is constructed based on the principle of pinhole projection and triangle similarity.Finally,we conducted experiments on the built platform,with 3 reconnaissance quadrotors detecting and localization 3 target vehicles and 7 hunter quadrotors tracking them.The results show that the minimum average error for localization targets with reconnaissance quadrotors can reach 0.1354 m,while the minimum average error for tracking with hunter quadrotors is only 0.2960 m.No quadrotors collision occurred in the whole formation transformation and tracking experiment.In addition,compared with the advanced methods,the proposed method has better performance.
基金the Applied Basic Research Program of Educational Department of Liaoning Province(No.LJKZZ20220058)。
文摘Due to the lack of human avoidance analysis,the orthosis cannot accurately apply orthopedic force during orthopedic,resulting in poor orthopedic effect.Therefore,the relationship between the human body’s active avoidance ability and force application is studied to achieve accurate loading of orthopedic force.First,a high-precision scoliosis model was established based on computed tomography data,and the relationship between orthopedic force and Cobb angle was analyzed.Then 9 subjects were selected for avoidance ability test grouped by body mass index calculation,and the avoidance function of different groups was fitted.The avoidance function corrected the application of orthopedic forces.The results show that the optimal correction force calculated by the finite element method was 60 N.The obese group had the largest avoidance ability,followed by the standard group and the lean group.When the orthopedic force was 60 N,the Cobb angle was reduced from 33.77°to 20°,the avoidance ability of the standard group at 50 N obtained from the avoidance function was 20.28%and 10.14 N was actively avoided.Therefore,when 50 N was applied,60.14 N was actually generated,which can achieve the orthopedic effect of 60 N numerical simulation analysis.The avoidance effect can take the active factors of the human body into consideration in the orthopedic process,so as to achieve a more accurate application of orthopedic force,and provide data reference for clinicians in the orthopedic process.
基金supported in part by the Fundamental Research Funds for the Central Universities(2024JBMC031)the OpenFund of Advanced Cryptography and System Security Key Laboratory of Sichuan Province(No.SKLACSS-202312)+2 种基金the CCF-NSFOCUS Open Fund,the National Natural Science Foundation of China(Grant Nos.62202042,U20A6003,62076146,62021002,U19A2062,62127803,U1911401 and 6212780016)the Fundamental Research Funds for the Central Universities,JLU,the Industrial Technology Infrastructure Public Service Platform Project‘Public Service Platform for Urban Rail Transit Equipment Signal System Testing and Safety Evaluation’(No.2022-233-225)Ministry of Industry and Information Technology of China.
文摘Advanced Persistent Threats(APTs)pose significant challenges to detect due to their“low-and-slow”attack patterns and frequent use of zero-day vulnerabilities.Within this task,the extraction of long-term features is often crucial.In this work,we propose a novel end-to-end APT detection framework named Long-Term Feature Association Provenance Graph Detector(LT-ProveGD).Specifically,LT-ProveGD encodes contextual information of the dynamic provenance graph while preserving the topological information with space efficiency.To combat“low-and-slow”attacks,LT-ProveGD develops an autoencoder with an integrated multi-head attention mechanism to extract long-term dependencies within the encoded representations.Furthermore,to facilitate the detection of previously unknown attacks,we leverage Jenks’natural breaks methodology,enabling detection without relying on specific attack information.By conducting extensive experiments on five widely used datasets with state-of-the-art attack detection methods,we demonstrate the superior effectiveness of LT-ProveGD.
基金funded by Ongoing Research Funding program(ORF-2025-749),King Saud University,Riyadh,Saudi Arabia.
文摘Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in networks and systems.Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data,learn patterns,and anticipate potential threats.Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly.Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks.This research advocates for proactive measures and adaptive technologies in defending digital environments.Improvements in detection ability by organizations will assist in safeguarding assets and integrity in operations in this increasingly digital world.This paper draws on the categorization of cyber threat detection methods using hesitant bipolar fuzzy Frank operators.Categorization is a step that is necessary for systematic comparison and assessment of detection methods so that the most suitable method for particular cybersecurity requirements is chosen.Furthermore,this research manages uncertainty and vagueness that exists in decision-making by applying hesitant bipolar fuzzy logic.The importance of the work lies in how it fortifies cybersecurity architectures with a formal method of discovering optimal detection measures and improving responsiveness,resulting in holistic protection against dynamic threats.
基金supported by the National Natural Science Foundation of China(72164018)National Social Science Fund Project(BFA200065)Jiangxi Social Science Foundation Project(21JY13).
文摘Objectives:Positive family functioning(FF)is critical for adolescent development,yet only a few studies have examined this developmental trajectory pathway.This study aimed to identify different types of FF development trajectories during junior high school students,investigate their influence on social avoidance(SA),and further examine the mediating role of preference for solitude(PS)between them.Methods:A three-wave longitudinal study was used with six-month intervals.Questionnaire data were collected from 436 junior high school students in Jiangxi Province,China.Participants ranged in age from 11 to 14 years old(Mean=12.89 years,SD=1.08;50.2%male).Results:Four heterogeneous types of FF trajectories were identified:(1)a high and increasing group(14.7%);(2)a consistently high group(36.24%);(3)a consistently moderate group(45.86%);and(4)a rapid growth group(3.2%).The developmental trajectories of FF among junior high students significantly varied in their levels of SA(F(3,432)=32.03,p<0.001).Compared to the high and increasing groups,the consistently high,consistently medium,and rapid growth groups exhibited higher levels of SA.PS mediated the association between the developmental trajectory of FF and SA.Conclusion:There was a close relationship between the developmental trajectory of FF and SA.Interventions focusing on family system optimization and solitary preference management could effectively mitigate SA behaviors.These findings are important for promoting healthy socialization in adolescents.
基金supported by the Intelligent Aerospace System Leading Innovation Team Program of Zhejiang(2022R01003).
文摘In the realm of missile defense systems,the self-sufficient maneuver capacity of missile swarms is pivotal for their survival.Through the analysis of the missile dynamics model,a time-efficient cooperative attack strategy for missile swarm is proposed.Based on the distribution of the attackers and defenders,the collision avoidance against the defenders is considered during the attack process.By analyzing the geometric relationship between the relative velocity vector and relative position vector of the attackers and defenders,the collision avoidance constrains of attacking swarm are redefined.The key point is on adjusting the relative velocity vectors to fall outside the collision cone.This work facilitates high-precision attack toward the target while keeping safe missing distance between other attackers during collision avoidance process.By leveraging an innovative repulsion artificial function,a time-efficient cooperative attack strategy for missile swarm is obtained.Through rigorous simulation,the effectiveness of this cooperative attack strategy is substantiated.Furthermore,by employing Monte Carlo simulation,the success rate of the cooperative attack strategy is assessesed and the optimal configuration for the missile swarm is deduced.
基金National Natural Science Foundation of China(62006193,62103338)Aeronautical Science Foundation of China(2022Z023053001)+1 种基金Key Research and Development Program of Shaanxi Province(2024GX-YBXM-115)Fundamental Research Funds for the Central Universities(D5000230150)。
文摘Beyond-visual-range(BVR)air combat threat assessment has attracted wide attention as the support of situation awareness and autonomous decision-making.However,the traditional threat assessment method is flawed in its failure to consider the intention and event of the target,resulting in inaccurate assessment results.In view of this,an integrated threat assessment method is proposed to address the existing problems,such as overly subjective determination of index weight and imbalance of situation.The process and characteristics of BVR air combat are analyzed to establish a threat assessment model in terms of target intention,event,situation,and capability.On this basis,a distributed weight-solving algorithm is proposed to determine index and attribute weight respectively.Then,variable weight and game theory are introduced to effectively deal with the situation imbalance and achieve the combination of subjective and objective.The performance of the model and algorithm is evaluated through multiple simulation experiments.The assessment results demonstrate the accuracy of the proposed method in BVR air combat,indicating its potential practical significance in real air combat scenarios.
基金supported in part by the Advanced Equipment Manufacturing Technology Innovation Project of Hebei Province under Grant No.22311801D,23311807D,and 236Z1816Gin part by the National Natural Science Foundation of China under Grant No.U20A20283.
文摘In this paper,a novel cooperative collision avoidance control strategy with relative velocity information for redundant robotic manipulators is derived to guarantee the behavioral safety of robots in the cooperative operational task.This strategy can generate the collision-free trajectory of the robotic links in real-time,which is to realize that the robot can avoid moving obstacles less conservatively and ensure tracking accuracy of terminal end-effector tasks in performing cooperative tasks.For the case where there is interference between the moving obstacle and the desired path of the robotic end-effector,the method inherits the null-space-based self-motion characteristics of the redundant manipulator,integrates the relative motion information,and uses the improved artificial potential field method to design the control items,which are used to generate the collision avoidance motion and carry out moving obstacles smoothly and less conservatively.At the same time,the strategy maintains the kinematic constraint relationship of dual-arm cooperatives,to meet the real-time collision avoidance task under collaborative tasks.Finally,the algorithm simulation indicates that the method can better ensure the tracking accuracy of the end-effector task and carry out moving obstacles smoothly.The experimental results show that the method can generate the real-time collision-free trajectory of the robot in the cooperative handling task,and the joint movement is continuous and stable.
基金Research and Development of Unmanned Vessel System Based on Intelligent Ship-Shore Collaborative Technology,Hainan University of Science and Technology Science Research(HKKY2024-79)。
文摘This paper deeply explores the autonomous collision avoidance algorithm for intelligent ships,aiming to enhance the intelligence level and safety of ship collision avoidance by integrating navigation experience.An autonomous collision avoidance algorithm based on navigation experience is designed,a collision avoidance experience database is constructed,a quantitative model is established,and specific algorithm steps are implemented.The algorithm is verified and analyzed through simulation tests.The results show that the algorithm can effectively achieve autonomous ship collision avoidance in different scenarios,providing new ideas and methods for the development of intelligent ship collision avoidance technology.
