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
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
Background:Cold temperatures cause blood vessels to constrict,shallow breathing,and slight thickening of the blood.Working in extremely cold environments can have negative effects on health,yet there are currently no ...Background:Cold temperatures cause blood vessels to constrict,shallow breathing,and slight thickening of the blood.Working in extremely cold environments can have negative effects on health,yet there are currently no effective biomarkers to monitor these health conditions.Proteins are important intermediate phenotypes that can provide a theoretical basis for understanding disease pathophysiology.Proteins in the circulatory system reflect the physiological status of individuals,and plasma proteins have significant potential as biomarkers for various health conditions.Methods:In this study,we employed the Mendelian randomization(MR)method to analyze the effects of freezing temperatures on over 2900 plasma proteins.Subsequently,the selected plasma proteins were subjected to causal analysis in relation to 55 diseases,including respiratory disorders,cardiovascular diseases,various cancers,and oral diseases.The aim was to identify proteins that could serve as biomarkers for health status.Results:Our results indicate that cold environments may affect the concentrations of 78 plasma proteins.Further MR analysis revealed that nine of these plasma proteins are associated with the risk of respiratory disorders,cardiovascular diseases,various cancers,and oral diseases.Conclusion:These proteins show promise as biomarkers for monitoring the hazards and risks faced by individuals working in cold environments.These findings provide valuable insights into the biological mechanisms underlying occupational hazards.展开更多
This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities.A comparable filter is used to improve the visual quality of the...This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities.A comparable filter is used to improve the visual quality of the photographs by reducing truncations in the existing images.Furthermore,the collected images undergo processing using histogram gradients and a flexible threshold value that may be adjusted in specific situations.Thus,it is possible to reduce the occurrence of overlapping circumstances in collective picture characteristics by substituting grey-scale photos with colorized factors.The proposed method offers additional robust feature representations by imposing a limiting factor to reduce overall scattering values.This is achieved by visualizing a graphical function.Moreover,to derive valuable insights from a series of photos,both the separation and in-version processes are conducted.This involves analyzing comparison results across four different scenarios.The results of the comparative analysis show that the proposed method effectively reduces the difficulties associated with time and space to 1 s and 3%,respectively.In contrast,the existing strategy exhibits higher complexities of 3 s and 9.1%,respectively.展开更多
Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threat...Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threaten flight safety and mission success.Traditional path planning methods typically depend solely on the distribution of static obstacles to generate collision-free paths,without accounting for constraints imposed by enemy detection and strike capabilities.Such a simplified approach can yield safety-compromising routes in highly complex urban airspace.To address these limitations,this study proposes a multi-parameter path planning method based on reachable airspace visibility graphs,which integrates UAV performance constraints,environmental limitations,and exposure risks.An innovative heuristic algorithm is developed to balance operational safety and efficiency by both exposure risks and path length.In the case study set in a typical mixed-use urban area,analysis of airspace visibility graphs reveals significant variations in exposure risk at different regions and altitudes due to building encroachments.Path optimization results indicate that the method can effectively generate covert and efficient flight paths by dynamically adjusting the exposure index,which represents the likelihood of enemy detection,and the path length,which corresponds to mission execution time.展开更多
Essentially clearing the structure-activity relationship between iron carbide catalysts involving multiple active centers to understand the reaction mechanism of CO hydrogenation conversion process is still a great ch...Essentially clearing the structure-activity relationship between iron carbide catalysts involving multiple active centers to understand the reaction mechanism of CO hydrogenation conversion process is still a great challenge.Here,two main micro-environment factors,namely electronic properties and geometrical effects were found to have an integrated effect on the mechanism of CO hydrogenation conversion,involving active sites on multiple crystal phases.The Bader charge of the surface Fe atoms on the active sites had a guiding effect on the CO activation pathway,while the spatial configuration of the active sites greatly affected the energy barriers of CO activation.Although the defective surfaces were more conducive to CO activation,the defective sites were not the only sites to dissociate CO,as CO always tended to dissociate in a wider area.This synergistic effect of the micro-environment also occurred during the CO conversion process.Surface C atoms on relatively flat configurations were more likely to form methane,while the electronic properties of the active sites could effectively describe the C-C coupling process,as well as distinguish the coupling mechanisms.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
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
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
Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across vari...Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.展开更多
This study addresses the issue of spray icing on the air intake grilles of ship power systems in cold maritime environments.Through numerical simulation methods,the influence of environmental parameters on icing chara...This study addresses the issue of spray icing on the air intake grilles of ship power systems in cold maritime environments.Through numerical simulation methods,the influence of environmental parameters on icing characteristics is revealed,and an energy-efficient zoned electric heating anti-icing strategy is proposed.A threedimensional grille model is constructed to systematically analyze the effects of environmental temperature(from−20℃to−4℃),droplet diameter(from 50μm to 500μm),and liquid water content(from 0.5 g/m³to 8 g/m³)on icing rates and blockage of the flow channel.The results indicate that low temperature and high liquid water content significantly exacerbate icing.Under the condition of an environmental temperature of−20℃,droplet diameter of 500μm,and liquid water content of 8 g/m³,the flow channel blockage ratio reaches 30.95%within 10 min.Additionally,as droplet diameter increases,the droplet impingement and icing regions become more concentrated toward the leading edge of blades.To mitigate grille icing in cold environments,an electric heating film configuration is employed for thermal protection.Optimization of the heating strategy reveals that the zoned heating approach,compared to the initial uniform heating scheme,effectively homogenizes surface temperature distribution while reducing total power consumption by 37.47%.This study validates the engineering applicability of the zoned electric heating anti/de-icing strategy,providing theoretical and technical support for the design of anti-icing systems in ship power systems operating in cold maritime regions.展开更多
This paper aims to address the problem of multi-UAV cooperative search for multiple targets in a mountainous environment,considering the constraints of UAV dynamics and prior environmental information.Firstly,using th...This paper aims to address the problem of multi-UAV cooperative search for multiple targets in a mountainous environment,considering the constraints of UAV dynamics and prior environmental information.Firstly,using the target probability distribution map,two strategies of information fusion and information diffusion are employed to solve the problem of environmental information inconsistency caused by different UAVs searching different areas,thereby improving the coordination of UAV groups.Secondly,the task region is decomposed into several high-value sub-regions by using data clustering method.Based on this,a hierarchical search strategy is proposed,which allows precise or rough search in different probability areas by adjusting the altitude of the aircraft,thereby improving the search efficiency.Third,the Elite Dung Beetle Optimization Algorithm(EDBOA)is proposed based on bionics by accurately simulating the social behavior of dung beetles to plan paths that satisfy the UAV dynamics constraints and adapt to the mountainous terrain,where the mountain is considered as an obstacle to be avoided.Finally,the objective function for path optimization is formulated by considering factors such as coverage within the task region,smoothness of the search path,and path length.The effectiveness and superiority of the proposed schemes are verified by the simulation.展开更多
This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy ...This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.展开更多
The haematopoietic stem cell transplantation(HSCT)ward serves as a temporary residence for patients following their surgical procedures,necessitating adherence to rigorous aseptic standards.However,the current atmosph...The haematopoietic stem cell transplantation(HSCT)ward serves as a temporary residence for patients following their surgical procedures,necessitating adherence to rigorous aseptic standards.However,the current atmosphere within these wards frequently contributes to feelings of depression among patients.Research indicates that a restorative environment has the potential to alleviate negative emotional states in individuals.This study utilized the HSCT ward of Peking University First Hospital as a case study to examine the decorative preferences.This investigation was conducted through a questionnaire that was informed by the patients’inherent preferences and insights derived from research on restorative environments.The results indicated that the incorporation of floral decorations,particularly those resembling sunflowers,in ward corridors,communal activity areas,and walls can significantly enhance patients’sense of hope.Additionally,it is essential to improve the environmental visual experience in the nurses’lounge and demonstration rooms for medical staff.展开更多
BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons comb...BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.展开更多
Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strate...Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strategy is to use virtual agents as substitutes for physical entities,balancing interaction efficiency with environmental immersion.However,the impact of virtual agent size and form on interaction performance remains unclear.Methods Two experiments were conducted to explore how virtual agent size and form affect interaction performance,immersion,and preference in MR environments.The first experiment assessed five virtual agent sizes(25%,50%,75%,100%,and 125%of physical size).The second experiment tested four types of frames(no frame,consistent frame,half frame,and surrounding frame)across all agent sizes.Participants,utilizing a head mounted display,performed tasks involving moving cups,typing words,and using a mouse.They completed questionnaires assessing aspects such as the virtual environment effects,interaction effects,collision concerns,and preferences.Results Results from the first experiment revealed that agents matching physical object size produced the best overall performance.The second experiment demonstrated that consistent framing notably enhances interaction accuracy and speed but reduces immersion.To balance efficiency and immersion,frameless agents matching physical object sizes were deemed optimal.Conclusions Virtual agents matching physical entity sizes enhance user experience and interaction performance.Conversely,familiar frames from 2D interfaces detrimentally affect interaction and immersion in virtual spaces.This study provides valuable insights for the future development of MR systems.展开更多
The concept of Traditional Chinese Medicine(TCM)emphasizes the intrinsic connection between human beings and nature,positing that the human body undergoes distinct physiological changes in response to various natural ...The concept of Traditional Chinese Medicine(TCM)emphasizes the intrinsic connection between human beings and nature,positing that the human body undergoes distinct physiological changes in response to various natural environments.Cold,as a primary external factor in cold areas,necessitates the body's autonomous adaptation to uphold optimal living conditions.The repercussions of cold on the body are both far-reaching and profound,with metabolic equilibrium adjustments playing a pivotal role.This article,rooted in the TCM principle of Yin-Yang balance,delves into the metabolic intricacies and adaptive responses to the human body in cold environments.The effects manifest in heat-producing tissues,systemic substance consumption,the blood substance concentrations,liver function,and metabolic rhythms.The article subsequently presents TCM recommendations for maintaining health in cold climates.It concludes by advocating the exploration of metabolic homeostasis changes as a key avenue for investigating the metabolic traits s of populations in cold regions.We posit that such insights will enhance comprehension of the metabolic shifts in cold region populations and advance the evolution of regional medicine.展开更多
Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerabl...Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet.Traditional signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging attacks.Therefore,there is the need for an IDS which can learn from data and detect new threats.Ensemble Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking technique.In this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta learner.The proposed DSNN model was trained and evaluated with the next-generation dataset,TON_IoT.Several pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE technique.Accuracy,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble model.Our experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML models.In addition,the model proposed for IDS has been compared with similar models.The proposed DSNN achieved better performance metrics than the other models.The proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.展开更多
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.
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funded by the Health Commission of Heilongjiang Province(Project Number:20230808010517).
文摘Background:Cold temperatures cause blood vessels to constrict,shallow breathing,and slight thickening of the blood.Working in extremely cold environments can have negative effects on health,yet there are currently no effective biomarkers to monitor these health conditions.Proteins are important intermediate phenotypes that can provide a theoretical basis for understanding disease pathophysiology.Proteins in the circulatory system reflect the physiological status of individuals,and plasma proteins have significant potential as biomarkers for various health conditions.Methods:In this study,we employed the Mendelian randomization(MR)method to analyze the effects of freezing temperatures on over 2900 plasma proteins.Subsequently,the selected plasma proteins were subjected to causal analysis in relation to 55 diseases,including respiratory disorders,cardiovascular diseases,various cancers,and oral diseases.The aim was to identify proteins that could serve as biomarkers for health status.Results:Our results indicate that cold environments may affect the concentrations of 78 plasma proteins.Further MR analysis revealed that nine of these plasma proteins are associated with the risk of respiratory disorders,cardiovascular diseases,various cancers,and oral diseases.Conclusion:These proteins show promise as biomarkers for monitoring the hazards and risks faced by individuals working in cold environments.These findings provide valuable insights into the biological mechanisms underlying occupational hazards.
基金financially supported by Ongoing Research Funding Program(ORF-2025-846),King Saud University,Riyadh,Saudi Arabia.
文摘This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities.A comparable filter is used to improve the visual quality of the photographs by reducing truncations in the existing images.Furthermore,the collected images undergo processing using histogram gradients and a flexible threshold value that may be adjusted in specific situations.Thus,it is possible to reduce the occurrence of overlapping circumstances in collective picture characteristics by substituting grey-scale photos with colorized factors.The proposed method offers additional robust feature representations by imposing a limiting factor to reduce overall scattering values.This is achieved by visualizing a graphical function.Moreover,to derive valuable insights from a series of photos,both the separation and in-version processes are conducted.This involves analyzing comparison results across four different scenarios.The results of the comparative analysis show that the proposed method effectively reduces the difficulties associated with time and space to 1 s and 3%,respectively.In contrast,the existing strategy exhibits higher complexities of 3 s and 9.1%,respectively.
基金supported by the Ministry of Industry and Information Technology(No.23100002022102001)。
文摘Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threaten flight safety and mission success.Traditional path planning methods typically depend solely on the distribution of static obstacles to generate collision-free paths,without accounting for constraints imposed by enemy detection and strike capabilities.Such a simplified approach can yield safety-compromising routes in highly complex urban airspace.To address these limitations,this study proposes a multi-parameter path planning method based on reachable airspace visibility graphs,which integrates UAV performance constraints,environmental limitations,and exposure risks.An innovative heuristic algorithm is developed to balance operational safety and efficiency by both exposure risks and path length.In the case study set in a typical mixed-use urban area,analysis of airspace visibility graphs reveals significant variations in exposure risk at different regions and altitudes due to building encroachments.Path optimization results indicate that the method can effectively generate covert and efficient flight paths by dynamically adjusting the exposure index,which represents the likelihood of enemy detection,and the path length,which corresponds to mission execution time.
基金supported by the Research Fund for National Key Research and Development Program of China(2022YFA1503804,2021YFA1501403)the Natural Science Foundation of China(22208094,21922803,92034301,22008066 and 21776077)+2 种基金the China Postdoctoral Science Foundation(BX20190116)the Innovation Program of Shanghai Municipal Education Commission(17ZR1407300)the Program of Shanghai Academic/Technology Research Leader(21XD1421000).
文摘Essentially clearing the structure-activity relationship between iron carbide catalysts involving multiple active centers to understand the reaction mechanism of CO hydrogenation conversion process is still a great challenge.Here,two main micro-environment factors,namely electronic properties and geometrical effects were found to have an integrated effect on the mechanism of CO hydrogenation conversion,involving active sites on multiple crystal phases.The Bader charge of the surface Fe atoms on the active sites had a guiding effect on the CO activation pathway,while the spatial configuration of the active sites greatly affected the energy barriers of CO activation.Although the defective surfaces were more conducive to CO activation,the defective sites were not the only sites to dissociate CO,as CO always tended to dissociate in a wider area.This synergistic effect of the micro-environment also occurred during the CO conversion process.Surface C atoms on relatively flat configurations were more likely to form methane,while the electronic properties of the active sites could effectively describe the C-C coupling process,as well as distinguish the coupling mechanisms.
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.
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.
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.
文摘Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.
基金supported in part by the Ship Preliminary Research Project (No.3020401020102)。
文摘This study addresses the issue of spray icing on the air intake grilles of ship power systems in cold maritime environments.Through numerical simulation methods,the influence of environmental parameters on icing characteristics is revealed,and an energy-efficient zoned electric heating anti-icing strategy is proposed.A threedimensional grille model is constructed to systematically analyze the effects of environmental temperature(from−20℃to−4℃),droplet diameter(from 50μm to 500μm),and liquid water content(from 0.5 g/m³to 8 g/m³)on icing rates and blockage of the flow channel.The results indicate that low temperature and high liquid water content significantly exacerbate icing.Under the condition of an environmental temperature of−20℃,droplet diameter of 500μm,and liquid water content of 8 g/m³,the flow channel blockage ratio reaches 30.95%within 10 min.Additionally,as droplet diameter increases,the droplet impingement and icing regions become more concentrated toward the leading edge of blades.To mitigate grille icing in cold environments,an electric heating film configuration is employed for thermal protection.Optimization of the heating strategy reveals that the zoned heating approach,compared to the initial uniform heating scheme,effectively homogenizes surface temperature distribution while reducing total power consumption by 37.47%.This study validates the engineering applicability of the zoned electric heating anti/de-icing strategy,providing theoretical and technical support for the design of anti-icing systems in ship power systems operating in cold maritime regions.
基金supported by the Natural Science Foundation of China(62273068)the Fundamental Research Funds for the Central Universities(3132023512)Dalian Science and Technology Innovation Fund(2019J12GX040).
文摘This paper aims to address the problem of multi-UAV cooperative search for multiple targets in a mountainous environment,considering the constraints of UAV dynamics and prior environmental information.Firstly,using the target probability distribution map,two strategies of information fusion and information diffusion are employed to solve the problem of environmental information inconsistency caused by different UAVs searching different areas,thereby improving the coordination of UAV groups.Secondly,the task region is decomposed into several high-value sub-regions by using data clustering method.Based on this,a hierarchical search strategy is proposed,which allows precise or rough search in different probability areas by adjusting the altitude of the aircraft,thereby improving the search efficiency.Third,the Elite Dung Beetle Optimization Algorithm(EDBOA)is proposed based on bionics by accurately simulating the social behavior of dung beetles to plan paths that satisfy the UAV dynamics constraints and adapt to the mountainous terrain,where the mountain is considered as an obstacle to be avoided.Finally,the objective function for path optimization is formulated by considering factors such as coverage within the task region,smoothness of the search path,and path length.The effectiveness and superiority of the proposed schemes are verified by the simulation.
基金The National Natural Science Foundation of China (32371993)The Natural Science Research Key Project of Anhui Provincial University(2022AH040125&2023AH040135)The Key Research and Development Plan of Anhui Province (202204c06020022&2023n06020057)。
文摘This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.
基金Sponsored by National Natural Science Foundation of China(52278045).
文摘The haematopoietic stem cell transplantation(HSCT)ward serves as a temporary residence for patients following their surgical procedures,necessitating adherence to rigorous aseptic standards.However,the current atmosphere within these wards frequently contributes to feelings of depression among patients.Research indicates that a restorative environment has the potential to alleviate negative emotional states in individuals.This study utilized the HSCT ward of Peking University First Hospital as a case study to examine the decorative preferences.This investigation was conducted through a questionnaire that was informed by the patients’inherent preferences and insights derived from research on restorative environments.The results indicated that the incorporation of floral decorations,particularly those resembling sunflowers,in ward corridors,communal activity areas,and walls can significantly enhance patients’sense of hope.Additionally,it is essential to improve the environmental visual experience in the nurses’lounge and demonstration rooms for medical staff.
基金Supported by Hangzhou Medical and Health Technology Project,No.OO20191141。
文摘BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.
基金the Strategic research and consulting project of Chinese Academy of Engineering(2023-HY-14).
文摘Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strategy is to use virtual agents as substitutes for physical entities,balancing interaction efficiency with environmental immersion.However,the impact of virtual agent size and form on interaction performance remains unclear.Methods Two experiments were conducted to explore how virtual agent size and form affect interaction performance,immersion,and preference in MR environments.The first experiment assessed five virtual agent sizes(25%,50%,75%,100%,and 125%of physical size).The second experiment tested four types of frames(no frame,consistent frame,half frame,and surrounding frame)across all agent sizes.Participants,utilizing a head mounted display,performed tasks involving moving cups,typing words,and using a mouse.They completed questionnaires assessing aspects such as the virtual environment effects,interaction effects,collision concerns,and preferences.Results Results from the first experiment revealed that agents matching physical object size produced the best overall performance.The second experiment demonstrated that consistent framing notably enhances interaction accuracy and speed but reduces immersion.To balance efficiency and immersion,frameless agents matching physical object sizes were deemed optimal.Conclusions Virtual agents matching physical entity sizes enhance user experience and interaction performance.Conversely,familiar frames from 2D interfaces detrimentally affect interaction and immersion in virtual spaces.This study provides valuable insights for the future development of MR systems.
基金This work was funded by the National Centre for the Development of TCM Education(TC2023002).
文摘The concept of Traditional Chinese Medicine(TCM)emphasizes the intrinsic connection between human beings and nature,positing that the human body undergoes distinct physiological changes in response to various natural environments.Cold,as a primary external factor in cold areas,necessitates the body's autonomous adaptation to uphold optimal living conditions.The repercussions of cold on the body are both far-reaching and profound,with metabolic equilibrium adjustments playing a pivotal role.This article,rooted in the TCM principle of Yin-Yang balance,delves into the metabolic intricacies and adaptive responses to the human body in cold environments.The effects manifest in heat-producing tissues,systemic substance consumption,the blood substance concentrations,liver function,and metabolic rhythms.The article subsequently presents TCM recommendations for maintaining health in cold climates.It concludes by advocating the exploration of metabolic homeostasis changes as a key avenue for investigating the metabolic traits s of populations in cold regions.We posit that such insights will enhance comprehension of the metabolic shifts in cold region populations and advance the evolution of regional medicine.
文摘Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet.Traditional signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging attacks.Therefore,there is the need for an IDS which can learn from data and detect new threats.Ensemble Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking technique.In this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta learner.The proposed DSNN model was trained and evaluated with the next-generation dataset,TON_IoT.Several pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE technique.Accuracy,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble model.Our experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML models.In addition,the model proposed for IDS has been compared with similar models.The proposed DSNN achieved better performance metrics than the other models.The proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.
