Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
Forest ecosystems are important for biodiversity conservation and human societies,but are under pressure due to climate change and human interventions.This applies to natural forests as well as tree plantations.The la...Forest ecosystems are important for biodiversity conservation and human societies,but are under pressure due to climate change and human interventions.This applies to natural forests as well as tree plantations.The latter are globally widespread and therefore gaining increasing importance for biodiversity conservation.However,even after dieback due to increasing disturbance frequencies,such plantations are primarily managed for economic returns,leading to growing conflicts among stakeholders.In particular,the impact of forest management on biodiversity is being discussed.This study investigates the effects of five management approaches in a landscape severely affected by spruce(Picea abies L.)dieback on beetle diversity,conservation,and community composition.We considered direct effects of management and indirect effects of environmental parameters separately in ground-dwelling and flight-active beetles.Beetle diversity was strongly affected by forest management,with nonintervention deadwood stands being most beneficial for beetles.In addition,we show indirect effects of environmental factors.In general,parameters related to salvage logging(e.g.open canopies,tree stumps)influenced beetle diversity and conservation negatively,while positive effects were found for soil nutrient availability and plant species richness.Community composition differed strongly among management categories and indicated a lack of landscape connectivity for open habitat species,as we found only low proportions of such species even on salvage-logged sites.We propose a mixture of management approaches after bark beetle outbreaks,including a substantial proportion of non-intervention deadwood stands,to increase landscape heterogeneity and connectivity.This may increase overall biodiversity while addressing the concerns of both forestry and species conservation.展开更多
This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated ...This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments.Initially,a collaborative planning cost function for the multi-UAV system is formulated,thereby converting the trajectory planning challenge into an optimization problem.Building on the foundational dung beetle optimization(DBO)algorithm,BFDBO incorporates three significant innovations:a boundary reflection mechanism,an adaptive mixed exploration strategy,and a dynamic multi-scale mutation strategy.These enhancements are intended to optimize the equilibrium between local exploration and global exploitation,facilitating the discovery of globally optimal trajectories thatminimize the cost function.Numerical simulations utilizing the CEC2022 benchmark function indicate that all three enhancements of BFDBOpositively influence its performance,resulting in accelerated convergence and improved optimization accuracy relative to leading optimization algorithms.In two battlefield scenarios of varying complexities,BFDBO achieved a minimum of a 39% reduction in total trajectory planning costs when compared to DBO and three other highperformance variants,while also demonstrating superior average runtime.This evidence underscores the effectiveness and applicability of BFDBO in practical,real-world contexts.展开更多
Nature-inspired designs have increasingly influenced biomedical engineering by providing superior biomechanical performance and structural stability.In this study,the diabolical ironclad beetle elytra structure was ap...Nature-inspired designs have increasingly influenced biomedical engineering by providing superior biomechanical performance and structural stability.In this study,the diabolical ironclad beetle elytra structure was applied to stent strut designs and thoroughly evaluated through various computational simulations to assess their potential to enhance the mechanical performance of WE43 magnesium alloy stents.Connected elliptical structures with a vertical-to-horizontal length ratio of 1:1.8 were incorporated in varying numbers and then compared to conventional laser-cut stents using 3-point bending,crush,crimping,and expansion tests,internal carotid artery insertion simulations,and computational fluid dynamics analyses.The results demonstrated that the biomimetic stents exhibited significantly improved stress distribution and reduced applied stress while maintaining hemodynamic stability.Computational fluid dynamics simulations further confirmed that the biomimetic could reduce wall shear stress and improve blood flow,thereby potentially minimizing the risk of restenosis and thrombosis.These findings suggest that diabolical ironclad beetle-inspired stent structures may offer enhanced biomechanical performance and clinical safety in magnesium-based endovascular interventions.展开更多
Any malfunctions of the actuators of the robots have the potential to destroy the robot’s normal motion,and most of the current actuator fault diagnosis methods are difficult to meet the requirements of simplifying t...Any malfunctions of the actuators of the robots have the potential to destroy the robot’s normal motion,and most of the current actuator fault diagnosis methods are difficult to meet the requirements of simplifying the actuator modeling and solving the difficulty of fault data collection.To solve the problem of real-time diagnosis of actuator faults in the 3-PR(P)S parallel robot,the model of 3-PR(P)S parallel robot and data-driven-based method for the fault diagnosis are presented.Firstly,only the input-output relationship of the actuator is considered for modeling actuator faults,reducing the complexity of fault modeling and reducing the time consumption of parameter identification,thereby meeting the requirements of real-time diagnosis.A Simulink model of the electromechanical actuator(EMA)was constructed to analyze actuator faults.Then the short-term analysis method was employed for collecting the sample data of the slider position on the test platform of the EMA system and feature extraction.Training samples for neural networks are obtained.Furthermore,we optimized the Back Propagation(BP)neural network using the Dung Beetle Optimization Algorithm(DBO),which effectively resolved the weights and thresholds of the BP neural network.Compared to BP and Particle Swarm Optimization(PSO)-BP,the DBO-BP has better convergence,convergence rate,and the best-classifying quality.So,the classification for the different actuator faults is obviously improved.Finally,a fault diagnosis system was designed for the actuator of the 3-PR(P)S parallel robot,and the experimental results demonstrate that this system can detect actuator faults within 0.1 seconds.This work also provides the technical support for the fault-tolerant control of the 3-PR(P)S Parallel robot.展开更多
Tenebrionid beetles represent a crucial arthropod taxon in the Gobi desert ecosystems owing to their species richness and high biomass,both of which are essential for maintaining ecosystem health and stability.However...Tenebrionid beetles represent a crucial arthropod taxon in the Gobi desert ecosystems owing to their species richness and high biomass,both of which are essential for maintaining ecosystem health and stability.However,the spatiotemporal variations of tenebrionid beetle assemblages in the Gobi desert remain poorly understood.In this study,the monthly dynamics of tenebrionid beetles in the central part of the Hexi Corridor,Northwest China,a representative area of the Gobi desert ecosystems,were monitored using pitfall trapping during 2015-2020.The following results were showed:(1)monthly activity of tenebrionid beetles was observed from March to October,with monthly activity peaking in spring and summer,and monthly activity periods and peak of tenebrionid beetle species exhibited interspecific differences that varied from year to year;(2)spatial distribution of tenebrionid beetle community was influenced by structural factors.Specifically,at a spatial scale of 24.00 m,tenebrionid beetle community was strongly and positively correlated with the dominant species,with distinct spatial distribution patterns observed for Blaps gobiensis and Microdera kraatzi alashanica;(3)abundance of tenebrionid beetles was positively correlated with monthly mean precipitation and monthly mean temperature,whereas monthly abundance of B.gobiensis and M.kraatzi alashanica was positively correlated with monthly mean precipitation;and(4)the cover of Reaumuria soongarica(Pall.)Maxim.and Nitraria sphaerocarpa Maxim.had a positive influence on the number of tenebrionid beetles captured.In conclusion,monthly variation in precipitation significantly influences the community dynamic of tenebrionid beetles,with precipitation and shrub cover jointly determining the spatial distribution pattern of these beetles in the Gobi desert ecosystems.展开更多
Biodiversity loss is a significant problem at a global scale and may be amplified by climate change.In recent years,coniferous forests have had substantial die-back across Europe due to drought and subsequent bark-bee...Biodiversity loss is a significant problem at a global scale and may be amplified by climate change.In recent years,coniferous forests have had substantial die-back across Europe due to drought and subsequent bark-beetle outbreaks.As many studies on the consequences of disturbance and subsequent management have focused on natural stands,management implications for managed spruce stands are not well understood,even though such stands are widespread throughout Europe.In this study,beetle taxonomy,conservation value,and community com-position are compared among spruce plantations and four post-disturbance management approaches:standing dead-wood,lying deadwood,clear cuts,and long-term succession.Diversity and community composition differed significantly among management categories,while different beetle fami-lies responded similarly.Intact spruce stands harbored the lowest beetle diversity while the highest taxonomic diver-sity and conservation value was on clear cuts and stands with lying or standing deadwood.The proportion of forest specialists was highest in successional forests.In summary,different forest management categories harbored distinct beetle communities at the family-,species-,and ecological guild levels.Therefore,post-disturbance management should consider the landscape scale and include different management types.This enhances landscape heterogeneity and thus overall biodiversity but could also mitigate negative impacts of natural disturbances on ecosystem services.展开更多
Network traffic identification is critical for maintaining network security and further meeting various demands of network applications.However,network traffic data typically possesses high dimensionality and complexi...Network traffic identification is critical for maintaining network security and further meeting various demands of network applications.However,network traffic data typically possesses high dimensionality and complexity,leading to practical problems in traffic identification data analytics.Since the original Dung Beetle Optimizer(DBO)algorithm,Grey Wolf Optimization(GWO)algorithm,Whale Optimization Algorithm(WOA),and Particle Swarm Optimization(PSO)algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution,an Improved Dung Beetle Optimizer(IDBO)algorithm is proposed for network traffic identification.Firstly,the Sobol sequence is utilized to initialize the dung beetle population,laying the foundation for finding the global optimal solution.Next,an integration of levy flight and golden sine strategy is suggested to give dung beetles a greater probability of exploring unvisited areas,escaping from the local optimal solution,and converging more effectively towards a global optimal solution.Finally,an adaptive weight factor is utilized to enhance the search capabilities of the original DBO algorithm and accelerate convergence.With the improvements above,the proposed IDBO algorithm is then applied to traffic identification data analytics and feature selection,as so to find the optimal subset for K-Nearest Neighbor(KNN)classification.The simulation experiments use the CICIDS2017 dataset to verify the effectiveness of the proposed IDBO algorithm and compare it with the original DBO,GWO,WOA,and PSO algorithms.The experimental results show that,compared with other algorithms,the accuracy and recall are improved by 1.53%and 0.88%in binary classification,and the Distributed Denial of Service(DDoS)class identification is the most effective in multi-classification,with an improvement of 5.80%and 0.33%for accuracy and recall,respectively.Therefore,the proposed IDBO algorithm is effective in increasing the efficiency of traffic identification and solving the problem of the original DBO algorithm that converges slowly and falls into the local optimal solution when dealing with high-dimensional data analytics and feature selection for network traffic identification.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
Decaying wood is an essential element of forest ecosystems and it affects its other components.The aim of our research was to determine the decomposition rate of deadwood in various humidity and thermal conditions in ...Decaying wood is an essential element of forest ecosystems and it affects its other components.The aim of our research was to determine the decomposition rate of deadwood in various humidity and thermal conditions in the gaps formed in the montane forest stands.The research was carried out in the Babiog orski National Park.The research plots were marked out in the gaps of the stands,which were formed as a result of bark beetle gradation.Control plots were located in undisturbed stands.The research covered wood of two species–spruce and beech in the form of cubes with dimensions of 50 mm×50 mm×22 mm.Wood samples were placed directly on the soil surface and subjected to laboratory analysis after 36 months.A significant influence of the wood species and the study plot type on the physicochemical properties of the tested wood samples was found.Wood characteristics strongly correlated with soil moisture.A significantly higher mass decline of wood samples was recorded on the reference study plots,which were characterized by more stable moisture conditions.Poorer decomposition of wood in the gaps regardless of the species is related to lower moisture.The wood species covered by the study differed in the decomposition rate.Spruce wood samples were characterized by a significantly higher decomposition rate compared to beech wood samples.Our research has confirmed that disturbances that lead to the formation of gaps have a direct impact on the decomposition process of deadwood.展开更多
Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In...Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In recent years,meta-heuristic algorithms have been widely used in FS problems,so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization(HBCSSDBO)algorithm is proposed in this paper to improve the effect of FS.In this hybrid algorithm,the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem.By combining the K nearest neighbor(KNN)classifier,the comparative experiments for FS are carried out between the proposed method and four advanced meta-heuristic algorithms on 16 UCI(University of California,Irvine)datasets.Seven evaluation metrics such as average adaptation,average prediction accuracy,and average running time are chosen to judge and compare the algorithms.The selected dataset is also discussed by categorizing it into three dimensions:high,medium,and low dimensions.Experimental results show that the HBCSSDBO feature selection method has the ability to obtain a good subset of features while maintaining high classification accuracy,shows better optimization performance.In addition,the results of statistical tests confirm the significant validity of the method.展开更多
Natural disturbances have significantly intensified across European forests,with bark beetle outbreaks being the most rapidly escalating disturbance type.Since 2018,the Czech Republic(Central Europe)has become a Europ...Natural disturbances have significantly intensified across European forests,with bark beetle outbreaks being the most rapidly escalating disturbance type.Since 2018,the Czech Republic(Central Europe)has become a Europe's disturbance epicentre due to the unprecedented outbreak of spruce bark beetle Ips typographus in the forests dominated by Norway spruce Picea abies.Here we provide novel insights into the impacts and dynamics of this disturbance from 2016 to 2022.The investigation is based on annual forest change maps developed by the classification of optical and Synthetic Aperture Radar satellite imagery.We identified seven major outbreak foci across the country,where the outbreaks culminated between 2018 and 2021.Most of the outbreak waves exhibited a symmetric shape,characterized by a three-year build-up phase,a single culmination year,and the subsequent decline.The substantial proportion of spruce remaining in the outbreak areas after the culmination point implies that resource depletion is an improbable cause for the outbreak's retreat.In the year of retreat,the proportion of spruce in the forest ranged between 26%and 36%in most of the outbreak areas.The disturbance dynamics manifested a transition from the emergence of new tree mortality spots in the early outbreak phase to their short-range expansion,suggesting density-dependent changes in bark beetle dispersal during the studied period.The core disturbance zone,pinpointed in 2022,covered an area of 9,000 km^(2) and experienced a 38%loss in forest cover.Within this area,forest fragmentation increased significantly,leading to a greater forest patch complexity and reduced connectivity among the patches.The presented findings can serve as a glimpse into the future for other European regions,revealing the potential impacts of natural disturbances amplified by climate change.展开更多
Corn stalks are a kind of common organic fertilizer and feed material in agriculture in China,as well as an important source of modern biomass energy and new materials.Hemicellulose is an important component in corn s...Corn stalks are a kind of common organic fertilizer and feed material in agriculture in China,as well as an important source of modern biomass energy and new materials.Hemicellulose is an important component in corn stalks,and it is very important to determine its content in corn stalks.In this paper,the feasibility of near-infrared spectroscopy(NIRS)combined with chemometrics for rapid detection of hemicellulose content in corn stalks was studied.In order to improve the accuracy of NIRS detection,a new intelligent optimization algorithm,dung beetle optimizer(DBO),was applied to select characteristic wavelengths of NIRS.Its modeling performance was compared with that based on characteristic wavelength selection using genetic algorithm(GA)and binary particle swarm optimization(BPSO),and it was found that the characteristic wavelength selection performance of DBO was excellent,and the regression accuracy of hemicellulose quantitative detection model established by its preferred characteristic wavelengths was better than the above two intelligent optimization algorithms.展开更多
The natural composition of forests has undergone significant changes over recent centuries.A closer-to-natural tree species composition has long been perceived as key to a high biodiversity.We investigated the impact ...The natural composition of forests has undergone significant changes over recent centuries.A closer-to-natural tree species composition has long been perceived as key to a high biodiversity.We investigated the impact on communities of click beetles(Elateridae)caused by changes in the tree species composition of spruce monocultures compared to reference sites of recently unmanaged natural beech forests.To collect data,passive interception traps were distributed within managed spruce stands of different age classes and natural beech forests of various developmental stages.The beetle species richness was slightly but not significantly higher in the beech forests.The saproxylic species group was significantly more common in the spruce stands,whereas the group of nonsaproxylic species was significantly more abundant in the beech stands.In the commercial stands,the significantly highest species richness was in the clearings(0–10-year-old stands),and at this forest age class,the vast majority of the beetle species occurred in the spruce stands.In the developmental stages of the natural forest,a slightly higher beetle richness was found at the disintegration stage.The study results suggested that different tree species compositions and stand structures affect the communities of click beetles and substantially change their species composition and thus their response to external influences.Therefore,management of stands using diverse silvicultural systems is recommended for creating diverse ecological niches in forests.展开更多
To improve the flexural properties of Beetle Elytron Plates(BEPs)and clarify the effect of the transition arcs(chamfers)between the skins and the trabeculae,the chamfers were set in BEPs,and then the influence of the ...To improve the flexural properties of Beetle Elytron Plates(BEPs)and clarify the effect of the transition arcs(chamfers)between the skins and the trabeculae,the chamfers were set in BEPs,and then the influence of the chamfer on BEPs'mechanical properties was investigated via experimentation and the Finite Elemnent Method simulation(FEM).The results indicate that the influence of the chamfer on the flexural properties and ductility was most obvious in the Trabecular Beetle Elytron Plates(TBEPs),less obvious in the Honeycomb Plates(HPs)and basically no efiect was observed on End-trabecular Beetle Elytron Plates(EBEPs).The chamfer can improve the mechanical stability of EBEPSs.As the chamfer diameter increased in the BEPs,the length of the residual trabecular root on the skin increased when failure occurred in the TBEPs.The crack position in the honeycomb wallsof the HPs gradually shifted from the skin to the center.The EBEPs continued to exhibit oblique cracks.From the perspective of the force characteristics of these BEPs.combined with numerical simulation,the influence mechanism of the chamfer on their flcxural propertics was investigated.展开更多
This study investigates the dung beetle fauna in northern Pakistan, including Khyber Pakhtunkhwa province, Gilgit-Baltistan（formerly known as the Northern Areas of Pakistan）, and Federally Administered Tribal Areas,...This study investigates the dung beetle fauna in northern Pakistan, including Khyber Pakhtunkhwa province, Gilgit-Baltistan（formerly known as the Northern Areas of Pakistan）, and Federally Administered Tribal Areas, based on collections and determined specimens. The area is diverse and contains a variety of flora and fauna pertaining to different habitats. We conducted surveys in the Alpine Zone, Montane Temperate Forest and Tropical Deciduous Forest. Three genera and five species, Digitonthophagus gazelle,Digitonthophagus bonasus, Heliocopris midas, Heliocopris bucephalus and Gymnopleurus flagellates were collected. Identification keys and distribution notes are provided. Heliocopris bucephalus was found to be a new country record to Pakistan.展开更多
A scanning electron microscope was used to observe the structures of the setae on the surface of a dung beetle Copris ochus, Motschulsky. There are lots of setae on the body surface, especially on the ventral part sur...A scanning electron microscope was used to observe the structures of the setae on the surface of a dung beetle Copris ochus, Motschulsky. There are lots of setae on the body surface, especially on the ventral part surface and lateral to the legs which are different in size, arrangement and shape. These setae have different lengths and many thorns on the whole seta. The top ends of these setae stand up without furcations which direct uprightly towards the surface of the touched soil. By the method of removing these setae, getting the insect weight before and after digging into the dung we affirm farther that the setae on the beetle body surface form the anti-stick and non-adherent gentle interface. The soil machines and components made by imitating the gentle body surface of beetles have favorable non-adherent results.展开更多
Efficient collection of water from fog provides a potential solution to solve the global freshwater shortage problem, particularly in the desert or arid regions. In this work, a flexible and highly efficient fog colle...Efficient collection of water from fog provides a potential solution to solve the global freshwater shortage problem, particularly in the desert or arid regions. In this work, a flexible and highly efficient fog collector was prepared by mimicking the back exoskeleton structure of the Namib desert beetle. The improved fog collector was constructed by a superhydrophobic-superhydrophilic patterned fabric via a simple weaving method, followed by in-situ deposition of copper particles. Compared with the conventional fog collector with a plane structure, the fabric has shown a higher water-harvesting rate at 1432.7 mg/h/cm2,owing to the biomimetic three-dimensional structure, its enhanced condensation performance enabled by the copper coating and the rational distribution of wetting units. The device construction makes use of the widely available textile materials through mature manufacturing technology, which makes it highly suitable for large-scale industrial production.展开更多
In order to found new carriers of pine wood nematode(PWN),Bursaphelenchus xylophilus,beetles were collected from pine wilt disease-affected areas in six provinces in China.A total of 8830 beetles of 29 species was col...In order to found new carriers of pine wood nematode(PWN),Bursaphelenchus xylophilus,beetles were collected from pine wilt disease-affected areas in six provinces in China.A total of 8830 beetles of 29 species was collected and examined to determine whether they were PWN carriers.Eight species were identified as carriers.Results included the first worldwide report of Monochamus uigromaculatus,Semanotus siuoauster,and Uraecha angusta being carriers of PWN,and the first report from China of A rhopalus rusticus carrying PWN.Monochamus alternatus was commonly collected in all six provinces and was the dominant species in four inland affected areas and A.rusticus was dominant in two coastal affected areas.The species varied between different neighboring regions in the same province.The distribution of the same species varied considerably over different regions.展开更多
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
基金supported by Forschungsanstalt für Waldo kologie und Forstwirtschaft(FAWF)of Landesforsten Rheinland-Pfalz(FF 5.3-01-2021)。
文摘Forest ecosystems are important for biodiversity conservation and human societies,but are under pressure due to climate change and human interventions.This applies to natural forests as well as tree plantations.The latter are globally widespread and therefore gaining increasing importance for biodiversity conservation.However,even after dieback due to increasing disturbance frequencies,such plantations are primarily managed for economic returns,leading to growing conflicts among stakeholders.In particular,the impact of forest management on biodiversity is being discussed.This study investigates the effects of five management approaches in a landscape severely affected by spruce(Picea abies L.)dieback on beetle diversity,conservation,and community composition.We considered direct effects of management and indirect effects of environmental parameters separately in ground-dwelling and flight-active beetles.Beetle diversity was strongly affected by forest management,with nonintervention deadwood stands being most beneficial for beetles.In addition,we show indirect effects of environmental factors.In general,parameters related to salvage logging(e.g.open canopies,tree stumps)influenced beetle diversity and conservation negatively,while positive effects were found for soil nutrient availability and plant species richness.Community composition differed strongly among management categories and indicated a lack of landscape connectivity for open habitat species,as we found only low proportions of such species even on salvage-logged sites.We propose a mixture of management approaches after bark beetle outbreaks,including a substantial proportion of non-intervention deadwood stands,to increase landscape heterogeneity and connectivity.This may increase overall biodiversity while addressing the concerns of both forestry and species conservation.
基金funded by the National Defense Science and Technology Innovation project,grant number ZZKY20223103the Basic Frontier InnovationProject at the Engineering University of PAP,grant number WJY202429+2 种基金the Basic Frontier lnnovation Project at the Engineering University of PAP,grant number WJY202408the Graduate Student Funding Priority Project,grant number JYWJ2024B006Key project of National Social Science Foundation,grant number 2023-SKJJ-A-116.
文摘This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments.Initially,a collaborative planning cost function for the multi-UAV system is formulated,thereby converting the trajectory planning challenge into an optimization problem.Building on the foundational dung beetle optimization(DBO)algorithm,BFDBO incorporates three significant innovations:a boundary reflection mechanism,an adaptive mixed exploration strategy,and a dynamic multi-scale mutation strategy.These enhancements are intended to optimize the equilibrium between local exploration and global exploitation,facilitating the discovery of globally optimal trajectories thatminimize the cost function.Numerical simulations utilizing the CEC2022 benchmark function indicate that all three enhancements of BFDBOpositively influence its performance,resulting in accelerated convergence and improved optimization accuracy relative to leading optimization algorithms.In two battlefield scenarios of varying complexities,BFDBO achieved a minimum of a 39% reduction in total trajectory planning costs when compared to DBO and three other highperformance variants,while also demonstrating superior average runtime.This evidence underscores the effectiveness and applicability of BFDBO in practical,real-world contexts.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2024-00449812,2022R1I1A3064173)the Korea government(MSIT)(No.RS-2024-00335915).
文摘Nature-inspired designs have increasingly influenced biomedical engineering by providing superior biomechanical performance and structural stability.In this study,the diabolical ironclad beetle elytra structure was applied to stent strut designs and thoroughly evaluated through various computational simulations to assess their potential to enhance the mechanical performance of WE43 magnesium alloy stents.Connected elliptical structures with a vertical-to-horizontal length ratio of 1:1.8 were incorporated in varying numbers and then compared to conventional laser-cut stents using 3-point bending,crush,crimping,and expansion tests,internal carotid artery insertion simulations,and computational fluid dynamics analyses.The results demonstrated that the biomimetic stents exhibited significantly improved stress distribution and reduced applied stress while maintaining hemodynamic stability.Computational fluid dynamics simulations further confirmed that the biomimetic could reduce wall shear stress and improve blood flow,thereby potentially minimizing the risk of restenosis and thrombosis.These findings suggest that diabolical ironclad beetle-inspired stent structures may offer enhanced biomechanical performance and clinical safety in magnesium-based endovascular interventions.
文摘Any malfunctions of the actuators of the robots have the potential to destroy the robot’s normal motion,and most of the current actuator fault diagnosis methods are difficult to meet the requirements of simplifying the actuator modeling and solving the difficulty of fault data collection.To solve the problem of real-time diagnosis of actuator faults in the 3-PR(P)S parallel robot,the model of 3-PR(P)S parallel robot and data-driven-based method for the fault diagnosis are presented.Firstly,only the input-output relationship of the actuator is considered for modeling actuator faults,reducing the complexity of fault modeling and reducing the time consumption of parameter identification,thereby meeting the requirements of real-time diagnosis.A Simulink model of the electromechanical actuator(EMA)was constructed to analyze actuator faults.Then the short-term analysis method was employed for collecting the sample data of the slider position on the test platform of the EMA system and feature extraction.Training samples for neural networks are obtained.Furthermore,we optimized the Back Propagation(BP)neural network using the Dung Beetle Optimization Algorithm(DBO),which effectively resolved the weights and thresholds of the BP neural network.Compared to BP and Particle Swarm Optimization(PSO)-BP,the DBO-BP has better convergence,convergence rate,and the best-classifying quality.So,the classification for the different actuator faults is obviously improved.Finally,a fault diagnosis system was designed for the actuator of the 3-PR(P)S parallel robot,and the experimental results demonstrate that this system can detect actuator faults within 0.1 seconds.This work also provides the technical support for the fault-tolerant control of the 3-PR(P)S Parallel robot.
基金funded by the National Natural Science Foundation of China(U23A2063)the Gansu Province Top-notch Leading Talents Project(E339040101)the National Natural Science Foundation of China(41771290,42377043,41773086).
文摘Tenebrionid beetles represent a crucial arthropod taxon in the Gobi desert ecosystems owing to their species richness and high biomass,both of which are essential for maintaining ecosystem health and stability.However,the spatiotemporal variations of tenebrionid beetle assemblages in the Gobi desert remain poorly understood.In this study,the monthly dynamics of tenebrionid beetles in the central part of the Hexi Corridor,Northwest China,a representative area of the Gobi desert ecosystems,were monitored using pitfall trapping during 2015-2020.The following results were showed:(1)monthly activity of tenebrionid beetles was observed from March to October,with monthly activity peaking in spring and summer,and monthly activity periods and peak of tenebrionid beetle species exhibited interspecific differences that varied from year to year;(2)spatial distribution of tenebrionid beetle community was influenced by structural factors.Specifically,at a spatial scale of 24.00 m,tenebrionid beetle community was strongly and positively correlated with the dominant species,with distinct spatial distribution patterns observed for Blaps gobiensis and Microdera kraatzi alashanica;(3)abundance of tenebrionid beetles was positively correlated with monthly mean precipitation and monthly mean temperature,whereas monthly abundance of B.gobiensis and M.kraatzi alashanica was positively correlated with monthly mean precipitation;and(4)the cover of Reaumuria soongarica(Pall.)Maxim.and Nitraria sphaerocarpa Maxim.had a positive influence on the number of tenebrionid beetles captured.In conclusion,monthly variation in precipitation significantly influences the community dynamic of tenebrionid beetles,with precipitation and shrub cover jointly determining the spatial distribution pattern of these beetles in the Gobi desert ecosystems.
基金supported by Forschungsanstalt fur Waldokologie und Forstwirtschaft (FAWF)of Landesforsten Rheinland-Pfalz (FF5.3-01-2021).
文摘Biodiversity loss is a significant problem at a global scale and may be amplified by climate change.In recent years,coniferous forests have had substantial die-back across Europe due to drought and subsequent bark-beetle outbreaks.As many studies on the consequences of disturbance and subsequent management have focused on natural stands,management implications for managed spruce stands are not well understood,even though such stands are widespread throughout Europe.In this study,beetle taxonomy,conservation value,and community com-position are compared among spruce plantations and four post-disturbance management approaches:standing dead-wood,lying deadwood,clear cuts,and long-term succession.Diversity and community composition differed significantly among management categories,while different beetle fami-lies responded similarly.Intact spruce stands harbored the lowest beetle diversity while the highest taxonomic diver-sity and conservation value was on clear cuts and stands with lying or standing deadwood.The proportion of forest specialists was highest in successional forests.In summary,different forest management categories harbored distinct beetle communities at the family-,species-,and ecological guild levels.Therefore,post-disturbance management should consider the landscape scale and include different management types.This enhances landscape heterogeneity and thus overall biodiversity but could also mitigate negative impacts of natural disturbances on ecosystem services.
基金supported by the National Natural Science Foundation of China under Grant 61602162the Hubei Provincial Science and Technology Plan Project under Grant 2023BCB041.
文摘Network traffic identification is critical for maintaining network security and further meeting various demands of network applications.However,network traffic data typically possesses high dimensionality and complexity,leading to practical problems in traffic identification data analytics.Since the original Dung Beetle Optimizer(DBO)algorithm,Grey Wolf Optimization(GWO)algorithm,Whale Optimization Algorithm(WOA),and Particle Swarm Optimization(PSO)algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution,an Improved Dung Beetle Optimizer(IDBO)algorithm is proposed for network traffic identification.Firstly,the Sobol sequence is utilized to initialize the dung beetle population,laying the foundation for finding the global optimal solution.Next,an integration of levy flight and golden sine strategy is suggested to give dung beetles a greater probability of exploring unvisited areas,escaping from the local optimal solution,and converging more effectively towards a global optimal solution.Finally,an adaptive weight factor is utilized to enhance the search capabilities of the original DBO algorithm and accelerate convergence.With the improvements above,the proposed IDBO algorithm is then applied to traffic identification data analytics and feature selection,as so to find the optimal subset for K-Nearest Neighbor(KNN)classification.The simulation experiments use the CICIDS2017 dataset to verify the effectiveness of the proposed IDBO algorithm and compare it with the original DBO,GWO,WOA,and PSO algorithms.The experimental results show that,compared with other algorithms,the accuracy and recall are improved by 1.53%and 0.88%in binary classification,and the Distributed Denial of Service(DDoS)class identification is the most effective in multi-classification,with an improvement of 5.80%and 0.33%for accuracy and recall,respectively.Therefore,the proposed IDBO algorithm is effective in increasing the efficiency of traffic identification and solving the problem of the original DBO algorithm that converges slowly and falls into the local optimal solution when dealing with high-dimensional data analytics and feature selection for network traffic identification.
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financed by the National Science Centre,Poland:decision no.DEC 2020/39/B/NZ9/00372 and decision no.DEC-2021/43/O/NZ9/00066。
文摘Decaying wood is an essential element of forest ecosystems and it affects its other components.The aim of our research was to determine the decomposition rate of deadwood in various humidity and thermal conditions in the gaps formed in the montane forest stands.The research was carried out in the Babiog orski National Park.The research plots were marked out in the gaps of the stands,which were formed as a result of bark beetle gradation.Control plots were located in undisturbed stands.The research covered wood of two species–spruce and beech in the form of cubes with dimensions of 50 mm×50 mm×22 mm.Wood samples were placed directly on the soil surface and subjected to laboratory analysis after 36 months.A significant influence of the wood species and the study plot type on the physicochemical properties of the tested wood samples was found.Wood characteristics strongly correlated with soil moisture.A significantly higher mass decline of wood samples was recorded on the reference study plots,which were characterized by more stable moisture conditions.Poorer decomposition of wood in the gaps regardless of the species is related to lower moisture.The wood species covered by the study differed in the decomposition rate.Spruce wood samples were characterized by a significantly higher decomposition rate compared to beech wood samples.Our research has confirmed that disturbances that lead to the formation of gaps have a direct impact on the decomposition process of deadwood.
基金This research was funded by the Short-Term Electrical Load Forecasting Based on Feature Selection and optimized LSTM with DBO which is the Fundamental Scientific Research Project of Liaoning Provincial Department of Education(JYTMS20230189)the Application of Hybrid Grey Wolf Algorithm in Job Shop Scheduling Problem of the Research Support Plan for Introducing High-Level Talents to Shenyang Ligong University(No.1010147001131).
文摘Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In recent years,meta-heuristic algorithms have been widely used in FS problems,so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization(HBCSSDBO)algorithm is proposed in this paper to improve the effect of FS.In this hybrid algorithm,the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem.By combining the K nearest neighbor(KNN)classifier,the comparative experiments for FS are carried out between the proposed method and four advanced meta-heuristic algorithms on 16 UCI(University of California,Irvine)datasets.Seven evaluation metrics such as average adaptation,average prediction accuracy,and average running time are chosen to judge and compare the algorithms.The selected dataset is also discussed by categorizing it into three dimensions:high,medium,and low dimensions.Experimental results show that the HBCSSDBO feature selection method has the ability to obtain a good subset of features while maintaining high classification accuracy,shows better optimization performance.In addition,the results of statistical tests confirm the significant validity of the method.
基金supported by the project“EVA4.0”,No.CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE of the Czech Republicthe project of the National Agency for Agriculture Research of the Czech Republic No.QK23020039lthe Technology Agency of the Czech Republic under grant No.SS02030018.
文摘Natural disturbances have significantly intensified across European forests,with bark beetle outbreaks being the most rapidly escalating disturbance type.Since 2018,the Czech Republic(Central Europe)has become a Europe's disturbance epicentre due to the unprecedented outbreak of spruce bark beetle Ips typographus in the forests dominated by Norway spruce Picea abies.Here we provide novel insights into the impacts and dynamics of this disturbance from 2016 to 2022.The investigation is based on annual forest change maps developed by the classification of optical and Synthetic Aperture Radar satellite imagery.We identified seven major outbreak foci across the country,where the outbreaks culminated between 2018 and 2021.Most of the outbreak waves exhibited a symmetric shape,characterized by a three-year build-up phase,a single culmination year,and the subsequent decline.The substantial proportion of spruce remaining in the outbreak areas after the culmination point implies that resource depletion is an improbable cause for the outbreak's retreat.In the year of retreat,the proportion of spruce in the forest ranged between 26%and 36%in most of the outbreak areas.The disturbance dynamics manifested a transition from the emergence of new tree mortality spots in the early outbreak phase to their short-range expansion,suggesting density-dependent changes in bark beetle dispersal during the studied period.The core disturbance zone,pinpointed in 2022,covered an area of 9,000 km^(2) and experienced a 38%loss in forest cover.Within this area,forest fragmentation increased significantly,leading to a greater forest patch complexity and reduced connectivity among the patches.The presented findings can serve as a glimpse into the future for other European regions,revealing the potential impacts of natural disturbances amplified by climate change.
基金Supported by San Heng San Zong Project of Heilongjiang Bayi Agricultural University(ZRCPY202314).
文摘Corn stalks are a kind of common organic fertilizer and feed material in agriculture in China,as well as an important source of modern biomass energy and new materials.Hemicellulose is an important component in corn stalks,and it is very important to determine its content in corn stalks.In this paper,the feasibility of near-infrared spectroscopy(NIRS)combined with chemometrics for rapid detection of hemicellulose content in corn stalks was studied.In order to improve the accuracy of NIRS detection,a new intelligent optimization algorithm,dung beetle optimizer(DBO),was applied to select characteristic wavelengths of NIRS.Its modeling performance was compared with that based on characteristic wavelength selection using genetic algorithm(GA)and binary particle swarm optimization(BPSO),and it was found that the characteristic wavelength selection performance of DBO was excellent,and the regression accuracy of hemicellulose quantitative detection model established by its preferred characteristic wavelengths was better than the above two intelligent optimization algorithms.
基金funded by the Internal Grant Agency of the Faculty of Forestry and Wood Science,No.43120/1312/3106the support of the Ministry of Agriculture of the Czech Republic,NAZV No.QK21020371.
文摘The natural composition of forests has undergone significant changes over recent centuries.A closer-to-natural tree species composition has long been perceived as key to a high biodiversity.We investigated the impact on communities of click beetles(Elateridae)caused by changes in the tree species composition of spruce monocultures compared to reference sites of recently unmanaged natural beech forests.To collect data,passive interception traps were distributed within managed spruce stands of different age classes and natural beech forests of various developmental stages.The beetle species richness was slightly but not significantly higher in the beech forests.The saproxylic species group was significantly more common in the spruce stands,whereas the group of nonsaproxylic species was significantly more abundant in the beech stands.In the commercial stands,the significantly highest species richness was in the clearings(0–10-year-old stands),and at this forest age class,the vast majority of the beetle species occurred in the spruce stands.In the developmental stages of the natural forest,a slightly higher beetle richness was found at the disintegration stage.The study results suggested that different tree species compositions and stand structures affect the communities of click beetles and substantially change their species composition and thus their response to external influences.Therefore,management of stands using diverse silvicultural systems is recommended for creating diverse ecological niches in forests.
基金funded by the National Key R&D Program of China(Grant No.2017YFC0703700).
文摘To improve the flexural properties of Beetle Elytron Plates(BEPs)and clarify the effect of the transition arcs(chamfers)between the skins and the trabeculae,the chamfers were set in BEPs,and then the influence of the chamfer on BEPs'mechanical properties was investigated via experimentation and the Finite Elemnent Method simulation(FEM).The results indicate that the influence of the chamfer on the flexural properties and ductility was most obvious in the Trabecular Beetle Elytron Plates(TBEPs),less obvious in the Honeycomb Plates(HPs)and basically no efiect was observed on End-trabecular Beetle Elytron Plates(EBEPs).The chamfer can improve the mechanical stability of EBEPSs.As the chamfer diameter increased in the BEPs,the length of the residual trabecular root on the skin increased when failure occurred in the TBEPs.The crack position in the honeycomb wallsof the HPs gradually shifted from the skin to the center.The EBEPs continued to exhibit oblique cracks.From the perspective of the force characteristics of these BEPs.combined with numerical simulation,the influence mechanism of the chamfer on their flcxural propertics was investigated.
基金supported by the National Basic Research Program of China (973 Program) (2011CB302102)by a Humboldt Fellowship (M.B.) from the Alexander von Humboldt Foundation
文摘This study investigates the dung beetle fauna in northern Pakistan, including Khyber Pakhtunkhwa province, Gilgit-Baltistan（formerly known as the Northern Areas of Pakistan）, and Federally Administered Tribal Areas, based on collections and determined specimens. The area is diverse and contains a variety of flora and fauna pertaining to different habitats. We conducted surveys in the Alpine Zone, Montane Temperate Forest and Tropical Deciduous Forest. Three genera and five species, Digitonthophagus gazelle,Digitonthophagus bonasus, Heliocopris midas, Heliocopris bucephalus and Gymnopleurus flagellates were collected. Identification keys and distribution notes are provided. Heliocopris bucephalus was found to be a new country record to Pakistan.
文摘A scanning electron microscope was used to observe the structures of the setae on the surface of a dung beetle Copris ochus, Motschulsky. There are lots of setae on the body surface, especially on the ventral part surface and lateral to the legs which are different in size, arrangement and shape. These setae have different lengths and many thorns on the whole seta. The top ends of these setae stand up without furcations which direct uprightly towards the surface of the touched soil. By the method of removing these setae, getting the insect weight before and after digging into the dung we affirm farther that the setae on the beetle body surface form the anti-stick and non-adherent gentle interface. The soil machines and components made by imitating the gentle body surface of beetles have favorable non-adherent results.
基金National Natural Science Foundation of China(5197206321501127+3 种基金51502185)Natural Science Foundation of Fujian Province(2019J01256)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX191916)the funds from China postdoctoral science foundation grant(2019TQ0061)。
文摘Efficient collection of water from fog provides a potential solution to solve the global freshwater shortage problem, particularly in the desert or arid regions. In this work, a flexible and highly efficient fog collector was prepared by mimicking the back exoskeleton structure of the Namib desert beetle. The improved fog collector was constructed by a superhydrophobic-superhydrophilic patterned fabric via a simple weaving method, followed by in-situ deposition of copper particles. Compared with the conventional fog collector with a plane structure, the fabric has shown a higher water-harvesting rate at 1432.7 mg/h/cm2,owing to the biomimetic three-dimensional structure, its enhanced condensation performance enabled by the copper coating and the rational distribution of wetting units. The device construction makes use of the widely available textile materials through mature manufacturing technology, which makes it highly suitable for large-scale industrial production.
基金supported by the National Key Research and Development Program of China(Grant Number:2017YFD0600104)the Shenyang Science and Technology Planning Project(Grant Number:18-400-3-03)。
文摘In order to found new carriers of pine wood nematode(PWN),Bursaphelenchus xylophilus,beetles were collected from pine wilt disease-affected areas in six provinces in China.A total of 8830 beetles of 29 species was collected and examined to determine whether they were PWN carriers.Eight species were identified as carriers.Results included the first worldwide report of Monochamus uigromaculatus,Semanotus siuoauster,and Uraecha angusta being carriers of PWN,and the first report from China of A rhopalus rusticus carrying PWN.Monochamus alternatus was commonly collected in all six provinces and was the dominant species in four inland affected areas and A.rusticus was dominant in two coastal affected areas.The species varied between different neighboring regions in the same province.The distribution of the same species varied considerably over different regions.
