Movement is an important animal behavior contributing to reproduction and survival.Animal movement is often examined in arenas or enclosures under laboratory conditions.We used the red flour beetle(Tribolium castaneum...Movement is an important animal behavior contributing to reproduction and survival.Animal movement is often examined in arenas or enclosures under laboratory conditions.We used the red flour beetle(Tribolium castaneum)to examine here the effect of the arena size,shape,number of barriers,access to the arena's center,and illumination on six movement properties.We demonstrate great differences among arenas.For example,the beetles moved over longer distances in clear arenas than in obstructed ones.Movement along the arena's perimeter was greater in smaller arenas than in larger ones.Movement was more directional in round arenas than in rectangular ones.In general,the beetles stopped moving closer to the perimeter and closer to corners(in the square and rectangular arenas)than expected by chance.In some cases,the arena properties interacted with the beetle sex to affect several movement properties.All these suggest that arena properties might also interact with experimental manipulations to affect the outcome of studies and lead to results specific to the arena used.In other words,instead of examining animal movement,we in fact examine the animal interaction with the arena structure.Caution is therefore advised in interpreting the results of studies on movement in arenas under laboratory conditions and we recommend paying attention also to barriers or obstacles in field experiments.For instance,movement along the arena's perimeter is often interpreted as centrophobism or thigmotaxis but the results here show that such movement is arena dependent.展开更多
Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest...Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.展开更多
We studied the foraging processes of wildebeest using an advection-diffusion equation. We equipped the model with data collected between 1999 and 2007 from the Serengeti ecosystem from 18 GPS-collared wildebeest. Resu...We studied the foraging processes of wildebeest using an advection-diffusion equation. We equipped the model with data collected between 1999 and 2007 from the Serengeti ecosystem from 18 GPS-collared wildebeest. Results analysis show that wildebeest foraging behavior can be explained by advective and diffusive parameters in a heterogeneous habitat like the Serengeti ecosystem.展开更多
A new mathematical system applicable to whatever Brownian problems where the Fickian diffusion equation (F-equation) is applicable was established. The F-equation, which is a parabolic type partial differential equati...A new mathematical system applicable to whatever Brownian problems where the Fickian diffusion equation (F-equation) is applicable was established. The F-equation, which is a parabolic type partial differential equation in the evolution equation, has ever been used for linear diffusion problems in the time-space (t, x, y, z). In the parabolic space (xt–0.5, yt–0.5, zt–0.5), the present study reveals that the F-equation becomes an ellipse type Poisson equation and furthermore the elegant analytical solutions are possible. Applying the new system to one-dimension nonlinear interdiffusion problems, the solutions were previously obtained as the analytical expressions. The obtained solutions were also elegant in accordance with the experimental results. In the present study, nonlinear diffusion problems are discussed in the two and three dimensional cases. The Brownian problem is widely relevant not only to material science but also to other various science fields. Hereafter, the new mathematical system will be thus extremely useful for the analysis of the Brownian problem in various science fields.展开更多
Multi-level multi-scale resource selection models using machine learning were compared and contrasted for generating predictive maps of jaguar habitat (Panthera onca) in the Brazilian Pantanal. Multiple spatial scales...Multi-level multi-scale resource selection models using machine learning were compared and contrasted for generating predictive maps of jaguar habitat (Panthera onca) in the Brazilian Pantanal. Multiple spatial scales and temporal movement levels were run within several analytical modeling frameworks for comparison. Included in the analysis were multi-scale raster grains (30 m, 90 m, 180 m, 360 m, 720 m, 1440 m) and GPS collaring temporal movement levels (point, path, and step). Various analytical methods were used for comparison of models that could accommodate data structural levels (group, individual, case-control). Models compared included conditional logistic regression, generalized additive modeling (GAM), and classification regression trees, such as random forests (RF) and gradient boosted regression tree (GBM). The goals of the study were to discuss the potential and limitations for machine learning methods using GPS collaring data to produce predictive habitat suitability mapping using the various scales and levels available. Results indicated that choosing the appropriate temporal level and raster scale improved model outputs. Overall, larger level analytical modeling frameworks and those that used multi-scale raster grains showed the best model evaluation with the inherent condition that they predict a broader scale and subset of data. The identification of the appropriate spatial scale, temporal scale and statistical model need careful consideration in predictive mapping efforts.展开更多
Understanding the movement of animals is fundamental to population and community ecology. Historically, it has been difficult to quantify movement patterns of most fishes, but technological advances in acoustic teleme...Understanding the movement of animals is fundamental to population and community ecology. Historically, it has been difficult to quantify movement patterns of most fishes, but technological advances in acoustic telemetry have increased our abilities to monitor their movement. In this study, we combined small-scale active acoustic tracking with large-scale passive acoustic monitoring to develop an empirical movement model for sixgill sharks in Puget Sound, WA, USA. We began by testing whether a correlated random walk model described the daily movement of sixgills; however, the model failed to capture home-ranging behavior. We added this behavior and used the resultant model （a biased random walk model） to determine whether daily movement patterns are able to explain large-scale seasonal movement. The daily model did not explain the larger-scale pat- terns of movement observed in the passive monitoring data. In order to create the large-scale patterns, sixgills must have per- formed behaviors （large, fast directed movements） that were unobserved during small-scale active tracking. In addition, seasonal shifts in location were not captured by the dally model. We added these ＇unobserved＇ behaviors to the model and were able to capture large-scale seasonal movement of sixgill sharks over 150 days. The development of empirical models of movement al- lows researchers to develop hypotheses and test mechanisms responsible for a species movement behavior and spatial distribution. This knowledge will increase our ability to successfully manage species of concern [Current Zoology 58 （1）： 103-115, 2012].展开更多
基于单树随机树搜索算法(Single directional rapidly-exploring random tree,single-RRT)和双树随机树搜索算法(Bi-directional rapidly-exploring random tree,bi-RRT),对7R机械臂的避障达点运动规划展开系统研究。基于single-RRT算...基于单树随机树搜索算法(Single directional rapidly-exploring random tree,single-RRT)和双树随机树搜索算法(Bi-directional rapidly-exploring random tree,bi-RRT),对7R机械臂的避障达点运动规划展开系统研究。基于single-RRT算法进行避障达点运动的数值仿真和实物样机试验。提出一种新的bi-RRT算法,结合末端姿态调整和关节自运动来生成目标树。并利用7R机械臂的解析逆解,生成目标位形。传统的bi-RRT算法只给定了一个目标位形,而新算法中目标点树根是由一群目标位形组成。在给定的障碍物环境中,机器人自动选择某一合适的位形作为目标节点来引导搜索树最有效地生长。通过数值仿真,验证该方法的优越性。利用Matlab和C++的混合编程和OpenGL开发了7R机械臂避障达点运动规划仿真软件。利用该软件,对基于bi-RRT的7R机械臂避障达点运动规划进行虚拟样机的试验研究。展开更多
文摘Movement is an important animal behavior contributing to reproduction and survival.Animal movement is often examined in arenas or enclosures under laboratory conditions.We used the red flour beetle(Tribolium castaneum)to examine here the effect of the arena size,shape,number of barriers,access to the arena's center,and illumination on six movement properties.We demonstrate great differences among arenas.For example,the beetles moved over longer distances in clear arenas than in obstructed ones.Movement along the arena's perimeter was greater in smaller arenas than in larger ones.Movement was more directional in round arenas than in rectangular ones.In general,the beetles stopped moving closer to the perimeter and closer to corners(in the square and rectangular arenas)than expected by chance.In some cases,the arena properties interacted with the beetle sex to affect several movement properties.All these suggest that arena properties might also interact with experimental manipulations to affect the outcome of studies and lead to results specific to the arena used.In other words,instead of examining animal movement,we in fact examine the animal interaction with the arena structure.Caution is therefore advised in interpreting the results of studies on movement in arenas under laboratory conditions and we recommend paying attention also to barriers or obstacles in field experiments.For instance,movement along the arena's perimeter is often interpreted as centrophobism or thigmotaxis but the results here show that such movement is arena dependent.
基金supported by Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2021]General 442)Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2023]General 179)Guizhou Provincial Department of Science and Technology(Guizhou Science and Technology Cooperation Support[2023]General 096).
文摘Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.
文摘We studied the foraging processes of wildebeest using an advection-diffusion equation. We equipped the model with data collected between 1999 and 2007 from the Serengeti ecosystem from 18 GPS-collared wildebeest. Results analysis show that wildebeest foraging behavior can be explained by advective and diffusive parameters in a heterogeneous habitat like the Serengeti ecosystem.
文摘A new mathematical system applicable to whatever Brownian problems where the Fickian diffusion equation (F-equation) is applicable was established. The F-equation, which is a parabolic type partial differential equation in the evolution equation, has ever been used for linear diffusion problems in the time-space (t, x, y, z). In the parabolic space (xt–0.5, yt–0.5, zt–0.5), the present study reveals that the F-equation becomes an ellipse type Poisson equation and furthermore the elegant analytical solutions are possible. Applying the new system to one-dimension nonlinear interdiffusion problems, the solutions were previously obtained as the analytical expressions. The obtained solutions were also elegant in accordance with the experimental results. In the present study, nonlinear diffusion problems are discussed in the two and three dimensional cases. The Brownian problem is widely relevant not only to material science but also to other various science fields. Hereafter, the new mathematical system will be thus extremely useful for the analysis of the Brownian problem in various science fields.
文摘Multi-level multi-scale resource selection models using machine learning were compared and contrasted for generating predictive maps of jaguar habitat (Panthera onca) in the Brazilian Pantanal. Multiple spatial scales and temporal movement levels were run within several analytical modeling frameworks for comparison. Included in the analysis were multi-scale raster grains (30 m, 90 m, 180 m, 360 m, 720 m, 1440 m) and GPS collaring temporal movement levels (point, path, and step). Various analytical methods were used for comparison of models that could accommodate data structural levels (group, individual, case-control). Models compared included conditional logistic regression, generalized additive modeling (GAM), and classification regression trees, such as random forests (RF) and gradient boosted regression tree (GBM). The goals of the study were to discuss the potential and limitations for machine learning methods using GPS collaring data to produce predictive habitat suitability mapping using the various scales and levels available. Results indicated that choosing the appropriate temporal level and raster scale improved model outputs. Overall, larger level analytical modeling frameworks and those that used multi-scale raster grains showed the best model evaluation with the inherent condition that they predict a broader scale and subset of data. The identification of the appropriate spatial scale, temporal scale and statistical model need careful consideration in predictive mapping efforts.
文摘Understanding the movement of animals is fundamental to population and community ecology. Historically, it has been difficult to quantify movement patterns of most fishes, but technological advances in acoustic telemetry have increased our abilities to monitor their movement. In this study, we combined small-scale active acoustic tracking with large-scale passive acoustic monitoring to develop an empirical movement model for sixgill sharks in Puget Sound, WA, USA. We began by testing whether a correlated random walk model described the daily movement of sixgills; however, the model failed to capture home-ranging behavior. We added this behavior and used the resultant model （a biased random walk model） to determine whether daily movement patterns are able to explain large-scale seasonal movement. The daily model did not explain the larger-scale pat- terns of movement observed in the passive monitoring data. In order to create the large-scale patterns, sixgills must have per- formed behaviors （large, fast directed movements） that were unobserved during small-scale active tracking. In addition, seasonal shifts in location were not captured by the dally model. We added these ＇unobserved＇ behaviors to the model and were able to capture large-scale seasonal movement of sixgill sharks over 150 days. The development of empirical models of movement al- lows researchers to develop hypotheses and test mechanisms responsible for a species movement behavior and spatial distribution. This knowledge will increase our ability to successfully manage species of concern [Current Zoology 58 （1）： 103-115, 2012].
文摘基于单树随机树搜索算法(Single directional rapidly-exploring random tree,single-RRT)和双树随机树搜索算法(Bi-directional rapidly-exploring random tree,bi-RRT),对7R机械臂的避障达点运动规划展开系统研究。基于single-RRT算法进行避障达点运动的数值仿真和实物样机试验。提出一种新的bi-RRT算法,结合末端姿态调整和关节自运动来生成目标树。并利用7R机械臂的解析逆解,生成目标位形。传统的bi-RRT算法只给定了一个目标位形,而新算法中目标点树根是由一群目标位形组成。在给定的障碍物环境中,机器人自动选择某一合适的位形作为目标节点来引导搜索树最有效地生长。通过数值仿真,验证该方法的优越性。利用Matlab和C++的混合编程和OpenGL开发了7R机械臂避障达点运动规划仿真软件。利用该软件,对基于bi-RRT的7R机械臂避障达点运动规划进行虚拟样机的试验研究。
