In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although ...In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although intelligent rescue robots can enter hazardous environments in place of humans,smoke poses major challenges for human detection algorithms.These challenges include the attenuation of visible and infrared signals,complex thermal fields,and interference frombackground objects,all ofwhichmake it difficult to accurately identify trapped individuals.To address this problem,we propose VIF-YOLO,a visible–infrared fusion model for real-time human detection in dense smoke environments.The framework introduces a lightweight multimodal fusion(LMF)module based on learnable low-rank representation blocks to end-to-end integrate visible and infrared images,preserving fine details while enhancing salient features.In addition,an efficient multiscale attention(EMA)mechanism is incorporated into the YOLOv10n backbone to improve feature representation under low-light conditions.Extensive experiments on our newly constructedmultimodal smoke human detection(MSHD)dataset demonstrate thatVIF-YOLOachievesmAP50 of 99.5%,precision of 99.2%,and recall of 99.3%,outperforming YOLOv10n by a clear margin.Furthermore,when deployed on the NVIDIA Jetson Xavier NX,VIF-YOLO attains 40.6 FPS with an average inference latency of 24.6 ms,validating its real-time capability on edge-computing platforms.These results confirm that VIF-YOLO provides accurate,robust,and fast detection across complex backgrounds and diverse smoke conditions,ensuring reliable and rapid localization of individuals in need of rescue.展开更多
Antibiotic resistance genes(ARGs) are recognized as a primary threat to the sustainability of environment and human health in the 21^(st) century.Nanomaterials(NMs) have attracted substantial attention due to their un...Antibiotic resistance genes(ARGs) are recognized as a primary threat to the sustainability of environment and human health in the 21^(st) century.Nanomaterials(NMs) have attracted substantial attention due to their unique dimensions and structures.Unfortunately,emerging evidence suggests that NMs may facilitate the transmission of ARGs.It is crucial to elucidate how NMs affect the evolution and dissemination of ARGs.The current review comprehensively examines the role of NMs in the widespread transmission of ARGs in aquatic environments and the underlying mechanisms involved in the process.It aims to clarify the effects and mechanisms of NMs on the horizontal gene transfer processes that are associated with ARGs,including the enhancement of cell membrane permeability,the formation of nanopores on membranes,promotion of mutagenesis,and the generation of reactive oxygen species(ROSs).Furthermore,the trade-off between the removal of ARGs and horizontal transfer has been elucidated.The review aspires to guide future research directions,advance knowledge on the implications of NMs in the field of ARGs' transmission,and provide a theoretical foundation for the development of safer and more effective applications of NMs.展开更多
Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular...Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular devices,affect the distribution and uploading processes of model parameters.In FL-assisted Internet of Vehicles(IoV)scenarios,challenges such as data heterogeneity,limited device resources,and unstable communication environments become increasingly prominent.These issues necessitate intelligent vehicle selection schemes to enhance training efficiency.Given this context,we propose a new scenario involving FL-assisted IoV systems under dynamic and uncertain communication conditions,and develop a dynamic interval multi-objective optimization algorithm to jointly optimize various factors including training experiments,system energy consumption,and bandwidth utilization to meet multi-criteria resource optimization requirements.For the problem at hand,we design a dynamic interval multi-objective optimization algorithm based on interval overlap detection.Simulation results demonstrate that our method outperforms other solutions in terms of accuracy,training cost,and server utilization.It effectively enhances training efficiency under wireless channel environments while rationally utilizing bandwidth resources,thus possessing significant scientific value and application potential in the field of IoV.展开更多
To assess the effectiveness of vaccination in contaminated environments,this study introduces a modeling framework that encompasses two transmission routes,namely direct human-to-human contact and indirect human-to-en...To assess the effectiveness of vaccination in contaminated environments,this study introduces a modeling framework that encompasses two transmission routes,namely direct human-to-human contact and indirect human-to-environment contact,as well as the implementation of new M72/AS01_(E)vaccine.Motivated by this,a coupled age-structured tuberculosis(TB)model is proposed.Its well-posedness requirement is verified using the integrated semigroup theory.Furthermore,this study presents a comprehensive analysis of threshold dynamics associated with the proposed model.Specifically,the global stability of the disease-free and positive steady states is demonstrated by employing Lyapunov functionals.Lastly,the effects of the vaccination with M72/AS01_(E)and contaminated environments on TB control are numerically simulated.Experimental results indicate that high concentrations of Mycobacterium tuberculosis in contaminated environments may somewhat impede TB control efforts,but that large-scale deployment of new vaccine could significantly reduce the prevalence of TB.展开更多
In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often fa...In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.展开更多
With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comp...With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.展开更多
As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies r...As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.展开更多
The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-...The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-treated samples demonstrate protective ability index values exceeding 2,indicating robust protective properties of the developed rust layers.The corrosion rates of ACS-and EPS-treated samples are similar.During the initial corrosion stage,γ-FeOOH emerges as the dominant corrosion product.With the prolonged atmospheric exposure,γ-FeOOH content progressively decreases through phase transformation into thermodynamically stableα-FeOOH and densely structured Fe_(3)O_(4),which markedly suppresses the corrosion of the steel.Notably,the corrosion rate of the coated EPS sample is obviously lower than that of the coated ACS counterpart,which is ascribed to the distinctive micro-roughness of EPS-treated surfaces that promote mechanical interlocking with protective coatings.展开更多
To meet the requirements of electromagnetic(EM)theory and applied physics,this study presents an overview of the state-of-the-art research on obtaining the EM properties of media and points out potential solutions tha...To meet the requirements of electromagnetic(EM)theory and applied physics,this study presents an overview of the state-of-the-art research on obtaining the EM properties of media and points out potential solutions that can break through the bottlenecks of current methods.Firstly,based on the survey of three mainstream approaches for acquiring EM properties of media,we identify the difficulties when implementing them in realistic environments.With a focus on addressing these problems and challenges,we propose a novel paradigm for obtaining the EM properties of multi-type media in realistic environments.Particularly,within this paradigm,we describe the implementation approach of the key technology,namely“multipath extraction using heterogeneous wave propagation data in multi-spectrum cases”.Finally,the latest measurement and simulation results show that the EM properties of multi-type media in realistic environments can be precisely and efficiently acquired by the methodology proposed in this study.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
To the editor:Adverse home environments(AHE),characterised by family conflict,parental separation or dysfunctional parenting,are linked to negative mental health outcomes in children and adults.12 AHE disproportionate...To the editor:Adverse home environments(AHE),characterised by family conflict,parental separation or dysfunctional parenting,are linked to negative mental health outcomes in children and adults.12 AHE disproportionately affect children with neurodevelopmental disorders such as attention-deficit/hyperactivity disorder(ADHD),which is characterised by inattention,hyperactivity/impulsivity and functional impairments.3 Apart from core symptoms,including inattention and hyperactivity,disruptive behaviour disorders(DBD),such as oppositional defiant disorder(ODD)and conduct disorder(CD),may be associated with AHE.Conduct problems are risk factors for ODD.And CD has become a main concern for childhood mental health.展开更多
Background Over the last few years,the rapid advancement of technology has led to the development of many approaches to digitalization.In this respect,metaverse provides 3D persistent virtual environments that can be ...Background Over the last few years,the rapid advancement of technology has led to the development of many approaches to digitalization.In this respect,metaverse provides 3D persistent virtual environments that can be used to access digital content,meet virtually,and perform several professional and leisure tasks.Among the numerous technologies supporting the metaverse,immersive Virtual Reality(VR)plays a primary role and offers highly interactive social experiences.Despite growing interest in this area,there are no clear design guidelines for creating environments tailored to the metaverse.Methods This study seeks to advance research in this area by moving from state-of-the-art studies on the design of immersive virtual environments in the context of metaverse and proposing how to integrate cutting-edge technologies within this context.Specifically,the best practices were identified by i)analyzing literature studies focused on human behavior in immersive virtual environments,ii)extracting common features of existing social VR platforms,and iii)conducting interviews with experts in a specific application domain.Specifically,this study considered the creation of a new virtual environment for MetaLibrary,a VR-based social platform aimed at integrating public libraries into metaverse.Several implementation challenges and additional requirements have been identified for the development of virtual environments(VEs).These elements were considered in the selection of specific cutting-edge technologies and their integration into the development process.A user study was also conducted to investigate some design aspects(namely lighting conditions and richness of the scene layout)for which deriving clear indications from the above analysis was not possible because different alternative configurations could be chosen.Results The work reported in this paper seeks to bridge the gap between existing VR platforms and related literature in the field,on the one hand,and requirements regarding immersive virtual environments for the metaverse,on the other hand,by reporting a set of best practices which were used to build a social virtual environment that meets users'expectations and needs.Conclusions Results suggest that carefully designed virtual environments can positively affect user experience and interaction within metaverse.The insights gained from this study offer valuable cues for developing immersive virtual environments for the metaverse to deliver more effective and engaging experiences.展开更多
In the fields of optoelectronics and semiconductors, reliable fixation and handling of brittle materials (glass, wafer, etc.) in high-temperature, vacuum, and vibration environments face particular technical challenge...In the fields of optoelectronics and semiconductors, reliable fixation and handling of brittle materials (glass, wafer, etc.) in high-temperature, vacuum, and vibration environments face particular technical challenges. These challenges include the inability of suction cups in a vacuum, the residue of chemical adhesives, and the easy damage of mechanical clamping. In this paper, fluorine-based bionic adhesive pads (FBAPs) obtained using molding technology to imitate gecko micropillar arrays are presented. FBAPs inhibit the substantial decay of adhesive properties at high temperatures and provide stable and reliable performance in vacuum and vibration environments. The results demonstrated that the decayed force values of the normal and tangential strength of the FBAP were only 9.01% and 5.82% of the planar samples when warmed up to 300℃ from 25℃, respectively. In a vacuum, all FBAPs exhibit less than 20% adhesion attenuation, and in a vibrational environment, they can withstand accelerations of at least 4.27 g. The design of the microstructure arrays enables the realization of efficient and non-destructive separation through mechanical rotation or blowing. It provides a bionic material basis for the fixation of brittle materials on smooth surfaces under complex environments and for transportation automation.展开更多
Earth is moving through a period of extreme uncertainty as global climates change,natural disasters become more frequent and severe,and governments grapple with the difficulty these issues pose for managing natural re...Earth is moving through a period of extreme uncertainty as global climates change,natural disasters become more frequent and severe,and governments grapple with the difficulty these issues pose for managing natural resources and people.Nowhere are these challenges more pressing than across the world's drylands,where a combination of hotter drier climates challenge food security,sustainable food production and often fuel unrest and political instability.It is against this backdrop that Fu and Stafford Smith,two global leaders in dryland science draw on>80 years of collective wisdom on drylands to describe how humans and natural processes intersect in an era of global change(Fu and Stafford Smith,2024).展开更多
The authors regret that the scientific names of some species mentioned in the paper were incorrectly presented.The incorrect sci-entific names,their locations in the paper,correct spellings and refer-ences,are listed ...The authors regret that the scientific names of some species mentioned in the paper were incorrectly presented.The incorrect sci-entific names,their locations in the paper,correct spellings and refer-ences,are listed below.展开更多
With the increasing demand for water in hydroponic systems and agricultural irrigation,viral diseases have seriously affected the yield and quality of crops.By removing plant viruses in water environments,virus transm...With the increasing demand for water in hydroponic systems and agricultural irrigation,viral diseases have seriously affected the yield and quality of crops.By removing plant viruses in water environments,virus transmission can be prevented and agricultural production and ecosystems can be protected.But so far,there have been few reports on the removal of plant viruses in water environments.Herein,in this study,easily recyclable biomass-based carbon nanotubes catalysts were synthesized with varying metal activities to activate peroxymonosulfate(PMS).Among them,the magnetic 0.125Fe@NCNTs-1/PMS system showed the best overall removal performance against pepper mild mottle virus,with a 5.9 log_(10)removal within 1 min.Notably,the key reactive species in the 0.125Fe@NCNTs-1/PMS system is^(1)O_(2),which can maintain good removal effect in real water matrices(river water and tap water).Through RNA fragment analyses and label free analysis,it was found that this system could effectively cleave virus particles,destroy viral proteins and expose their genome.The capsid protein of pepper mild mottle virus was effectively decomposed where serine may be the main attacking sites by^(1)O_(2).Long viral RNA fragments(3349 and 1642 nt)were cut into smaller fragments(∼160 nt)and caused their degradation.In summary,this study contributes to controlling the spread of plant viruses in real water environment,which will potentially help protect agricultural production and food safety,and improve the health and sustainability of ecosystems.展开更多
With the rapid development of drone technology,drones are increasingly used in urban environments,but they also bring many security risks,such as illegal reconnaissance,smuggling,and terrorist attacks.Therefore,it is ...With the rapid development of drone technology,drones are increasingly used in urban environments,but they also bring many security risks,such as illegal reconnaissance,smuggling,and terrorist attacks.Therefore,it is of great significance to study the anti-UAV technology in the urban environment.This paper analyzes the advantages and disadvantages of existing technologies and their applicability in the urban environment from the aspects of UAV detection,identification,and countermeasures,and discusses the future development trend of anti-UAV technology,aiming to provide a reference for urban safety protection.展开更多
Human interaction with natural environments is gaining increasing attention in environmental sciences as research consistently shows that access to green spaces,clean air,and biodiversity plays a crucial role in enhan...Human interaction with natural environments is gaining increasing attention in environmental sciences as research consistently shows that access to green spaces,clean air,and biodiversity plays a crucial role in enhancing physical health,reducing stress,and improving overall well-being.This study conducts a bibliometric and visualization-based analysis of forest therapy research,emphasizing its physiological and psychological benefits.Using the Web of Science database,we identified and analyzed 414 studies from 1998 to 2023.Through CiteSpace and VOSviewer,we mapped these documents to examine research trends,publication networks,leading scholars and institutions,key journals,and thematic evolution.Findings indicate that forest therapy research is predominantly concentrated in East Asia,North America,Australia,and Europe,with strong collaborative networks among authors and institutions.The concentration of publications,research evolution,and keyword trends reflect the development of forest therapy research.The analysis further identifies sixteen research clusters and discusses two research themes:physiological and psychological effects.By analyzing how the natural environment contributes to human well-being,we provide a comprehensive and visually structured understanding of forest therapy as an intersection of environmental science,public health and well-being,and ecosystem conservation.Our findings offer a new perspective for future interdisciplinary research,emphasizing the need for well-designed clinical trials to substantiate forest therapy’s diverse health effects and its role in promoting sustainable interactions between human societies and natural environments.展开更多
Tensegrity structures,embodying the principles of continuous tensioning and discrete compression,have emerged as fundamental frameworks in locomotive soft robotics for navigating uneven and unpredictable environments,...Tensegrity structures,embodying the principles of continuous tensioning and discrete compression,have emerged as fundamental frameworks in locomotive soft robotics for navigating uneven and unpredictable environments,owing to their flexible and resilient traits.By means of a straightforward and cost-effective method to achieve structure-driven,vibration-driven tensegrity shows great potential,particularly in tasks demanding random exploration.However,the design guidance for vibration-driven tensegrity and their performance evaluation in unstructured terrain remain unrevealed due to the complex dynamics of the structure.This paper presents a small six-bar tensegrity robot,driven by wireless vibration motors,designed for deployment in disaster rescue and search scenarios.Finite element simulation is used to investigate how structural characteristics,excitation parameters,and the arrangement of motors affect the kinematic performance of this tensegrity system.A prototype of the six-bar tensegrity robot with three motors located on the lower ends of the three lower struts is designed and manufactured after the numerical simulations.A simple control policy which adjusts the motion of the tensegrity robot by turning on or off the motors on different locations is proposed.The prototype with and without the control policy is tested in man-made environments of various complexity.It shows that the ability and efficiency of the tensegrity robot in exploring unstructured environments is significantly enhanced by the proposed control policy.It is believed that the potential of the vibration-driven tensegrity robot could be further exploited by integrating multi-source sensors and more intelligent control policies.展开更多
Extreme environments are unstructured and change rapidly,making human exploration in unfamiliar areas difficult.Construction robotics can help reduce risks to human safety and property in these environments by integra...Extreme environments are unstructured and change rapidly,making human exploration in unfamiliar areas difficult.Construction robotics can help reduce risks to human safety and property in these environments by integrating digital technology and artificial intelligence.This technology has the potential to significantly improve the quality and efficiency of construction,making it a key area for future research.Extreme environments include hazardous work sites,polluted areas,and harsh natural conditions.Our review of construction robotics in these settings highlights several knowledge gaps.We focused on four main areas:mechanism design,perception,planning,and control.Our analysis reveals challenges in practical applications,such as creating adaptable mechanisms,accurately perceiving changing environments,planning for unstructured sites,and optimizing control models.Future research should explore:biomimetic designs inspired by nature,multimodal data fusion for perception,adaptive planning strategies,and hybrid control models that combine data-driven and mechanism-based approaches.展开更多
基金funded by the National Natural Science Foundation of China under Grant 62306128the Leading Innovation Project of Changzhou Science and Technology Bureau underGrant CQ20230072+2 种基金the Basic Science Research Project of Jiangsu Provincial Department of Education under Grant 23KJD520003the Science and Technology Development Plan Project of Jilin Provinceunder Grant 20240101382JCthe National KeyR esearch and Development Program of China under Grant 2023YFF1105102.
文摘In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although intelligent rescue robots can enter hazardous environments in place of humans,smoke poses major challenges for human detection algorithms.These challenges include the attenuation of visible and infrared signals,complex thermal fields,and interference frombackground objects,all ofwhichmake it difficult to accurately identify trapped individuals.To address this problem,we propose VIF-YOLO,a visible–infrared fusion model for real-time human detection in dense smoke environments.The framework introduces a lightweight multimodal fusion(LMF)module based on learnable low-rank representation blocks to end-to-end integrate visible and infrared images,preserving fine details while enhancing salient features.In addition,an efficient multiscale attention(EMA)mechanism is incorporated into the YOLOv10n backbone to improve feature representation under low-light conditions.Extensive experiments on our newly constructedmultimodal smoke human detection(MSHD)dataset demonstrate thatVIF-YOLOachievesmAP50 of 99.5%,precision of 99.2%,and recall of 99.3%,outperforming YOLOv10n by a clear margin.Furthermore,when deployed on the NVIDIA Jetson Xavier NX,VIF-YOLO attains 40.6 FPS with an average inference latency of 24.6 ms,validating its real-time capability on edge-computing platforms.These results confirm that VIF-YOLO provides accurate,robust,and fast detection across complex backgrounds and diverse smoke conditions,ensuring reliable and rapid localization of individuals in need of rescue.
基金supported by the State Key Laboratory of Urban Water Resource and Environment (Harbin Institute of Technology) (No.2022TS13)the key projects of National Natural Science Foundation of China (No.2019YFC0408503)the Key Research Program of Wuhan (No.2022022202015015)。
文摘Antibiotic resistance genes(ARGs) are recognized as a primary threat to the sustainability of environment and human health in the 21^(st) century.Nanomaterials(NMs) have attracted substantial attention due to their unique dimensions and structures.Unfortunately,emerging evidence suggests that NMs may facilitate the transmission of ARGs.It is crucial to elucidate how NMs affect the evolution and dissemination of ARGs.The current review comprehensively examines the role of NMs in the widespread transmission of ARGs in aquatic environments and the underlying mechanisms involved in the process.It aims to clarify the effects and mechanisms of NMs on the horizontal gene transfer processes that are associated with ARGs,including the enhancement of cell membrane permeability,the formation of nanopores on membranes,promotion of mutagenesis,and the generation of reactive oxygen species(ROSs).Furthermore,the trade-off between the removal of ARGs and horizontal transfer has been elucidated.The review aspires to guide future research directions,advance knowledge on the implications of NMs in the field of ARGs' transmission,and provide a theoretical foundation for the development of safer and more effective applications of NMs.
基金supported in part by the Central Guidance for Local Science and Technology Development Funds under Grant No.YDZJSX2025D049Shanxi Provincial Graduate Innovation Research Program under Grant No.2024KY652.
文摘Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular devices,affect the distribution and uploading processes of model parameters.In FL-assisted Internet of Vehicles(IoV)scenarios,challenges such as data heterogeneity,limited device resources,and unstable communication environments become increasingly prominent.These issues necessitate intelligent vehicle selection schemes to enhance training efficiency.Given this context,we propose a new scenario involving FL-assisted IoV systems under dynamic and uncertain communication conditions,and develop a dynamic interval multi-objective optimization algorithm to jointly optimize various factors including training experiments,system energy consumption,and bandwidth utilization to meet multi-criteria resource optimization requirements.For the problem at hand,we design a dynamic interval multi-objective optimization algorithm based on interval overlap detection.Simulation results demonstrate that our method outperforms other solutions in terms of accuracy,training cost,and server utilization.It effectively enhances training efficiency under wireless channel environments while rationally utilizing bandwidth resources,thus possessing significant scientific value and application potential in the field of IoV.
文摘To assess the effectiveness of vaccination in contaminated environments,this study introduces a modeling framework that encompasses two transmission routes,namely direct human-to-human contact and indirect human-to-environment contact,as well as the implementation of new M72/AS01_(E)vaccine.Motivated by this,a coupled age-structured tuberculosis(TB)model is proposed.Its well-posedness requirement is verified using the integrated semigroup theory.Furthermore,this study presents a comprehensive analysis of threshold dynamics associated with the proposed model.Specifically,the global stability of the disease-free and positive steady states is demonstrated by employing Lyapunov functionals.Lastly,the effects of the vaccination with M72/AS01_(E)and contaminated environments on TB control are numerically simulated.Experimental results indicate that high concentrations of Mycobacterium tuberculosis in contaminated environments may somewhat impede TB control efforts,but that large-scale deployment of new vaccine could significantly reduce the prevalence of TB.
文摘In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2023-00235509Development of security monitoring technology based network behavior against encrypted cyber threats in ICT convergence environment).
文摘With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.
基金supported by Kyonggi University Research Grant 2025.
文摘As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.
基金support by National Natural Science Foundation of China(Grant No.52401103)Key Scientific Research Project in Shanxi Province(Grant No.202302050201015)+3 种基金Central Guiding Science and Technology Development of Local Fund(Grant No.YDZJSK20231A046)the Special Fund for Science and Technology Innovation Teams of Shanxi Province(202204051001004)Science and Technology Cooperation and Exchange Special Project of Shanxi Province(202404041101038)Postgraduate Education Innovation Project of Shanxi Province(Grant No.2024SJ304).
文摘The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-treated samples demonstrate protective ability index values exceeding 2,indicating robust protective properties of the developed rust layers.The corrosion rates of ACS-and EPS-treated samples are similar.During the initial corrosion stage,γ-FeOOH emerges as the dominant corrosion product.With the prolonged atmospheric exposure,γ-FeOOH content progressively decreases through phase transformation into thermodynamically stableα-FeOOH and densely structured Fe_(3)O_(4),which markedly suppresses the corrosion of the steel.Notably,the corrosion rate of the coated EPS sample is obviously lower than that of the coated ACS counterpart,which is ascribed to the distinctive micro-roughness of EPS-treated surfaces that promote mechanical interlocking with protective coatings.
基金supported by the Beijing Natural Science Foundation(No.L212029)the National Natural Science Foundation of China(No.62271043).
文摘To meet the requirements of electromagnetic(EM)theory and applied physics,this study presents an overview of the state-of-the-art research on obtaining the EM properties of media and points out potential solutions that can break through the bottlenecks of current methods.Firstly,based on the survey of three mainstream approaches for acquiring EM properties of media,we identify the difficulties when implementing them in realistic environments.With a focus on addressing these problems and challenges,we propose a novel paradigm for obtaining the EM properties of multi-type media in realistic environments.Particularly,within this paradigm,we describe the implementation approach of the key technology,namely“multipath extraction using heterogeneous wave propagation data in multi-spectrum cases”.Finally,the latest measurement and simulation results show that the EM properties of multi-type media in realistic environments can be precisely and efficiently acquired by the methodology proposed in this study.
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 National Natural Science Foundation Youth Project (81901386)the Fundamental Research Funds for the Central Universities (YG2025ZD07)+5 种基金the National Science and Technology Innovation 2030 Major Project of China (2021ZD0203900)National Natural Science Foundation of China (NSFC) grant (82422029)the Science and Technology Commission of Shanghai Municipality (24Y22800200, 22QA1407900)NSFC grant (82271530)Innovation teams of high-level universities in Shanghaithe Scientific Research and Innovation Team of Liaoning Normal University (24TD004).
文摘To the editor:Adverse home environments(AHE),characterised by family conflict,parental separation or dysfunctional parenting,are linked to negative mental health outcomes in children and adults.12 AHE disproportionately affect children with neurodevelopmental disorders such as attention-deficit/hyperactivity disorder(ADHD),which is characterised by inattention,hyperactivity/impulsivity and functional impairments.3 Apart from core symptoms,including inattention and hyperactivity,disruptive behaviour disorders(DBD),such as oppositional defiant disorder(ODD)and conduct disorder(CD),may be associated with AHE.Conduct problems are risk factors for ODD.And CD has become a main concern for childhood mental health.
基金Supported by Fondazione TIM in the context of the “Facciamola Facile” initiativeby Programma Operativo Nazionale (PON)“Ricerca e Innovazione” 2014-2020-DM 1062/2021 funds
文摘Background Over the last few years,the rapid advancement of technology has led to the development of many approaches to digitalization.In this respect,metaverse provides 3D persistent virtual environments that can be used to access digital content,meet virtually,and perform several professional and leisure tasks.Among the numerous technologies supporting the metaverse,immersive Virtual Reality(VR)plays a primary role and offers highly interactive social experiences.Despite growing interest in this area,there are no clear design guidelines for creating environments tailored to the metaverse.Methods This study seeks to advance research in this area by moving from state-of-the-art studies on the design of immersive virtual environments in the context of metaverse and proposing how to integrate cutting-edge technologies within this context.Specifically,the best practices were identified by i)analyzing literature studies focused on human behavior in immersive virtual environments,ii)extracting common features of existing social VR platforms,and iii)conducting interviews with experts in a specific application domain.Specifically,this study considered the creation of a new virtual environment for MetaLibrary,a VR-based social platform aimed at integrating public libraries into metaverse.Several implementation challenges and additional requirements have been identified for the development of virtual environments(VEs).These elements were considered in the selection of specific cutting-edge technologies and their integration into the development process.A user study was also conducted to investigate some design aspects(namely lighting conditions and richness of the scene layout)for which deriving clear indications from the above analysis was not possible because different alternative configurations could be chosen.Results The work reported in this paper seeks to bridge the gap between existing VR platforms and related literature in the field,on the one hand,and requirements regarding immersive virtual environments for the metaverse,on the other hand,by reporting a set of best practices which were used to build a social virtual environment that meets users'expectations and needs.Conclusions Results suggest that carefully designed virtual environments can positively affect user experience and interaction within metaverse.The insights gained from this study offer valuable cues for developing immersive virtual environments for the metaverse to deliver more effective and engaging experiences.
基金supported by the National Natural Science Foundation of China(No.52075249)the Tianyuan Laboratory Fund(No.24-JSKY-ZZKT-14).
文摘In the fields of optoelectronics and semiconductors, reliable fixation and handling of brittle materials (glass, wafer, etc.) in high-temperature, vacuum, and vibration environments face particular technical challenges. These challenges include the inability of suction cups in a vacuum, the residue of chemical adhesives, and the easy damage of mechanical clamping. In this paper, fluorine-based bionic adhesive pads (FBAPs) obtained using molding technology to imitate gecko micropillar arrays are presented. FBAPs inhibit the substantial decay of adhesive properties at high temperatures and provide stable and reliable performance in vacuum and vibration environments. The results demonstrated that the decayed force values of the normal and tangential strength of the FBAP were only 9.01% and 5.82% of the planar samples when warmed up to 300℃ from 25℃, respectively. In a vacuum, all FBAPs exhibit less than 20% adhesion attenuation, and in a vibrational environment, they can withstand accelerations of at least 4.27 g. The design of the microstructure arrays enables the realization of efficient and non-destructive separation through mechanical rotation or blowing. It provides a bionic material basis for the fixation of brittle materials on smooth surfaces under complex environments and for transportation automation.
文摘Earth is moving through a period of extreme uncertainty as global climates change,natural disasters become more frequent and severe,and governments grapple with the difficulty these issues pose for managing natural resources and people.Nowhere are these challenges more pressing than across the world's drylands,where a combination of hotter drier climates challenge food security,sustainable food production and often fuel unrest and political instability.It is against this backdrop that Fu and Stafford Smith,two global leaders in dryland science draw on>80 years of collective wisdom on drylands to describe how humans and natural processes intersect in an era of global change(Fu and Stafford Smith,2024).
文摘The authors regret that the scientific names of some species mentioned in the paper were incorrectly presented.The incorrect sci-entific names,their locations in the paper,correct spellings and refer-ences,are listed below.
基金supported by the National Natural Science Foundation of China(No.52170060)the Major Science and Technology Project from the Ministry of Water Resources(No.SKS-2022069)the Science and Technology Program of Inner Mongolia Autonomous Region(No.2021GG0089).
文摘With the increasing demand for water in hydroponic systems and agricultural irrigation,viral diseases have seriously affected the yield and quality of crops.By removing plant viruses in water environments,virus transmission can be prevented and agricultural production and ecosystems can be protected.But so far,there have been few reports on the removal of plant viruses in water environments.Herein,in this study,easily recyclable biomass-based carbon nanotubes catalysts were synthesized with varying metal activities to activate peroxymonosulfate(PMS).Among them,the magnetic 0.125Fe@NCNTs-1/PMS system showed the best overall removal performance against pepper mild mottle virus,with a 5.9 log_(10)removal within 1 min.Notably,the key reactive species in the 0.125Fe@NCNTs-1/PMS system is^(1)O_(2),which can maintain good removal effect in real water matrices(river water and tap water).Through RNA fragment analyses and label free analysis,it was found that this system could effectively cleave virus particles,destroy viral proteins and expose their genome.The capsid protein of pepper mild mottle virus was effectively decomposed where serine may be the main attacking sites by^(1)O_(2).Long viral RNA fragments(3349 and 1642 nt)were cut into smaller fragments(∼160 nt)and caused their degradation.In summary,this study contributes to controlling the spread of plant viruses in real water environment,which will potentially help protect agricultural production and food safety,and improve the health and sustainability of ecosystems.
文摘With the rapid development of drone technology,drones are increasingly used in urban environments,but they also bring many security risks,such as illegal reconnaissance,smuggling,and terrorist attacks.Therefore,it is of great significance to study the anti-UAV technology in the urban environment.This paper analyzes the advantages and disadvantages of existing technologies and their applicability in the urban environment from the aspects of UAV detection,identification,and countermeasures,and discusses the future development trend of anti-UAV technology,aiming to provide a reference for urban safety protection.
文摘Human interaction with natural environments is gaining increasing attention in environmental sciences as research consistently shows that access to green spaces,clean air,and biodiversity plays a crucial role in enhancing physical health,reducing stress,and improving overall well-being.This study conducts a bibliometric and visualization-based analysis of forest therapy research,emphasizing its physiological and psychological benefits.Using the Web of Science database,we identified and analyzed 414 studies from 1998 to 2023.Through CiteSpace and VOSviewer,we mapped these documents to examine research trends,publication networks,leading scholars and institutions,key journals,and thematic evolution.Findings indicate that forest therapy research is predominantly concentrated in East Asia,North America,Australia,and Europe,with strong collaborative networks among authors and institutions.The concentration of publications,research evolution,and keyword trends reflect the development of forest therapy research.The analysis further identifies sixteen research clusters and discusses two research themes:physiological and psychological effects.By analyzing how the natural environment contributes to human well-being,we provide a comprehensive and visually structured understanding of forest therapy as an intersection of environmental science,public health and well-being,and ecosystem conservation.Our findings offer a new perspective for future interdisciplinary research,emphasizing the need for well-designed clinical trials to substantiate forest therapy’s diverse health effects and its role in promoting sustainable interactions between human societies and natural environments.
基金supported by the National Natural Science Foundation of China(Grant Nos.52178175 and 52108182)the National Natural Science Foundation of Zhejiang Province(Grant No.LZ23E080003).
文摘Tensegrity structures,embodying the principles of continuous tensioning and discrete compression,have emerged as fundamental frameworks in locomotive soft robotics for navigating uneven and unpredictable environments,owing to their flexible and resilient traits.By means of a straightforward and cost-effective method to achieve structure-driven,vibration-driven tensegrity shows great potential,particularly in tasks demanding random exploration.However,the design guidance for vibration-driven tensegrity and their performance evaluation in unstructured terrain remain unrevealed due to the complex dynamics of the structure.This paper presents a small six-bar tensegrity robot,driven by wireless vibration motors,designed for deployment in disaster rescue and search scenarios.Finite element simulation is used to investigate how structural characteristics,excitation parameters,and the arrangement of motors affect the kinematic performance of this tensegrity system.A prototype of the six-bar tensegrity robot with three motors located on the lower ends of the three lower struts is designed and manufactured after the numerical simulations.A simple control policy which adjusts the motion of the tensegrity robot by turning on or off the motors on different locations is proposed.The prototype with and without the control policy is tested in man-made environments of various complexity.It shows that the ability and efficiency of the tensegrity robot in exploring unstructured environments is significantly enhanced by the proposed control policy.It is believed that the potential of the vibration-driven tensegrity robot could be further exploited by integrating multi-source sensors and more intelligent control policies.
基金supported in the Strategic Research and Consulting Project of the Chinese Academy of Engineering(2023-XZ-90 and 2023-JB-09-10)the National Key Research and Development Program of China(2021YFF0500301 and 2023YFB3711300)+1 种基金the National Natural Science Foundation of China(72171092 and 71821001)the Natural Science Fund for Distinguished Young Scholars of Hubei Province(2021CFA091).
文摘Extreme environments are unstructured and change rapidly,making human exploration in unfamiliar areas difficult.Construction robotics can help reduce risks to human safety and property in these environments by integrating digital technology and artificial intelligence.This technology has the potential to significantly improve the quality and efficiency of construction,making it a key area for future research.Extreme environments include hazardous work sites,polluted areas,and harsh natural conditions.Our review of construction robotics in these settings highlights several knowledge gaps.We focused on four main areas:mechanism design,perception,planning,and control.Our analysis reveals challenges in practical applications,such as creating adaptable mechanisms,accurately perceiving changing environments,planning for unstructured sites,and optimizing control models.Future research should explore:biomimetic designs inspired by nature,multimodal data fusion for perception,adaptive planning strategies,and hybrid control models that combine data-driven and mechanism-based approaches.
