AIM:To evaluate the choroidopathy in patients with systemic lupus erythematosus(SLE)using enhanced depth imaging spectral domain optical coherence tomography(EDI SD-OCT)and optical coherence tomography angiography(OCT...AIM:To evaluate the choroidopathy in patients with systemic lupus erythematosus(SLE)using enhanced depth imaging spectral domain optical coherence tomography(EDI SD-OCT)and optical coherence tomography angiography(OCTA).METHODS:A total of 74 patients with SLE and 40 healthy volunteers were included in this cross-sectional study.SLE patients were further divided into three subgroups based on clinical and blood biochemistry findings.Ocular parameters obtained on ophthalmologic examination and optical imaging(EDI SD-OCT and OCTA)included the best corrected distance visual acuity(logMAR CDVA),subfoveal choroidal thickness(SCT),choroidal vascularity index(CVI)and vessel density(VD)of superficial capillary plexus(SCP)and deep capillary plexus(DCP).RESULTS:SLE patients had significantly lower values for CVI and VD of DCP(DVD)than control subjects.Amongst SLE patients,gender and chloroquine dose were found to be independent determinants of CVI while age predicted SCT.Steroid dose was a significant predictor for foveal VD of SCP(SVD),chloroquine dose for parafoveal SVD,gender for total DVD,and gender and steroid dose for perifoveal DVD.No correlation of logMAR CDVA and SCT was noted between SLE patients and control subjects.No correlation of SCT was noted with disease duration,Systemic Lupus Erythematosus Disease Activity Index(SLEDAI)score,hydroxychloroquine(HCQ)dose or steroid dose.No correlation of CVI was noted with patient age,disease duration,SLEDAI score,HCQ dose or steroid dose.No significant difference was noted between SLE subgroups in terms of any of the ocular parameters studied.CONCLUSION:The findings reveal the presence of ocular findings suggestive of early onset choroidopathy on EDI SD-OCT and OCTA in SLE patients,in the absence of ocular manifestations or active disease.展开更多
Precise and robust three-dimensional object detection(3DOD)presents a promising opportunity in the field of mobile robot(MR)navigation.Monocular 3DOD techniques typically involve extending existing twodimensional obje...Precise and robust three-dimensional object detection(3DOD)presents a promising opportunity in the field of mobile robot(MR)navigation.Monocular 3DOD techniques typically involve extending existing twodimensional object detection(2DOD)frameworks to predict the three-dimensional bounding box(3DBB)of objects captured in 2D RGB images.However,these methods often require multiple images,making them less feasible for various real-time scenarios.To address these challenges,the emergence of agile convolutional neural networks(CNNs)capable of inferring depth froma single image opens a new avenue for investigation.The paper proposes a novel ELDENet network designed to produce cost-effective 3DBounding Box Estimation(3D-BBE)froma single image.This novel framework comprises the PP-LCNet as the encoder and a fast convolutional decoder.Additionally,this integration includes a Squeeze-Exploit(SE)module utilizing the Math Kernel Library for Deep Neural Networks(MKLDNN)optimizer to enhance convolutional efficiency and streamline model size during effective training.Meanwhile,the proposed multi-scale sub-pixel decoder generates high-quality depth maps while maintaining a compact structure.Furthermore,the generated depthmaps provide a clear perspective with distance details of objects in the environment.These depth insights are combined with 2DOD for precise evaluation of 3D Bounding Boxes(3DBB),facilitating scene understanding and optimal route planning for mobile robots.Based on the estimated object center of the 3DBB,the Deep Reinforcement Learning(DRL)-based obstacle avoidance strategy for MRs is developed.Experimental results demonstrate that our model achieves state-of-the-art performance across three datasets:NYU-V2,KITTI,and Cityscapes.Overall,this framework shows significant potential for adaptation in intelligent mechatronic systems,particularly in developing knowledge-driven systems for mobile robot navigation.展开更多
A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay ...A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay arrivals of surface-bottom reflection and bottom-surface reflection intersect at the source depth. Two hydrophones deployed vertically with a certain interval are required at least. If the receiver depths are known, the pair of time delays can be used to estimate the source depth. With the proposed method the source depth can be estimated successfully in a moderate range in the deep ocean without complicated matched-field calculations in the simulations and experiments.展开更多
AIM:To evaluate the postoperative refractive prediction error(PE)and determine the factors that af fect the refractive outcomes of combined pars plana vitrectomy(PPV)or silicone oil removal(SOR)with cataract surgery.M...AIM:To evaluate the postoperative refractive prediction error(PE)and determine the factors that af fect the refractive outcomes of combined pars plana vitrectomy(PPV)or silicone oil removal(SOR)with cataract surgery.METHODS:The study is a retrospective,case-series study.Totally 301 eyes of 301 patients undergoing combined PPV/SOR with cataract surgery were enrolled.Eligible individuals were separated into four groups according to their preoperative diagnoses:silicone oil-filled eyes after PPV(group 1),epiretinal membrane(group 2),macular hole(group 3),and primary retinal detachment(RD;group 4).The variables af fecting postoperative refractive outcomes were analyzed,including age,gender,preoperative best-corrected visual acuity(BCVA),axial length(AL),keratometry average,anterior chamber depth(ACD),intraocular tamponade,and vitreoretinal pathology.The outcome measurements include the mean refractive PE and the proportions of eyes with a PE within±0.50 diopter(D)and±1.00 D.RESULTS:For all patients,the mean PE was-0.04±1.17 D,and 50.17%of patients(eyes)had a PE within±0.50 D.There was a significant difference in refractive outcomes among the four groups(P=0.028),with RD(group 4)showing the least favorable refractive outcome.In multivariate regression analysis,only AL,vitreoretinal pathology,and ACD were strongly associated with PE(all P<0.01).Univariate analysis revealed that longer eyes(AL>26 mm)and a deeper ACD were correlated with hyperopic PE,and shorter eyes(AL<26 mm)and a shallower ACD were correlated with myopic PE.CONCLUSION:RD patients have the least favorable refractive outcome.AL,vitreoretinal pathology,and ACD are strongly associated with PE in the combined surgery.These three factors affect refractive outcomes and thus can be used to predict a better postoperative refractive outcome in clinical practice.展开更多
This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapi...This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.展开更多
Discussions on Chinese modernization are offering African countries both conceptual inspiration and practical references as they explore their own sustainable development paths.
Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees l...Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.展开更多
This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later step...This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.展开更多
A sudden increase in the radial depth(SIRD)is a distinctive phenomenon in plunge milling.It is typically characterized by a sharp increase in cutting force at the end of the axial feed of the tool,accompanied by harsh...A sudden increase in the radial depth(SIRD)is a distinctive phenomenon in plunge milling.It is typically characterized by a sharp increase in cutting force at the end of the axial feed of the tool,accompanied by harsh machine vibration sounds,which can negatively impact the reliability of plunge milling.This paper proposes an optimization method to eliminate SIRD in five-axis plunge milling.Initially,a five-axis plunge milling experiment and an analysis of the spatial position relationship between the plunge tools and the workpiece revealed that the cause of SIRD is unreasonable tool path planning.Subsequently,using the cutter position and cutter axis vector as variables,an SIRD discrimination model was developed for adjacent cutter positions and extended to multiple cutter positions.Optimizing the plunge milling tool path is considered a multivariate optimization problem that involves determining the cutter point and cutter axis vector.The SIRD discrimination model was used as a constraint function to aid in solving for the variables.The simulation and experimental results indicate that with the remaining volume of material as the optimization target,the optimized plunge milling tool path results in a residual material volume that is less than 60%of the gradually decreasing plunge depth.This optimization decreases the subsequent semi-finishing time of the workpiece and enhances machining efficiency.Additionally,it does not rely on operator experience and facilitates efficient automated optimization of the tool path to exclude SIRD.展开更多
Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a signi...Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a significant challenge faced in the field of computer vision.However,existing monocular video depth estimation models tend to produce blurred or inaccurate depth information in regions with object edges and low texture.To address this issue,we propose a monocular depth estimation model architecture guided by semantic segmentation masks,which introduces semantic information into the model to correct the ambiguous depth regions.We have evaluated the proposed method,and experimental results show that our method improves the accuracy of edge depth,demonstrating the effectiveness of our approach.展开更多
A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path...A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.展开更多
An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengt...An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.展开更多
Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned pa...Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned paths in complex environments is challenging.This paper proposes a feasible path planning algorithm named Closed-loop Radial Ray A^(*)(CL-RaA^(*)).The core components of the CL-RaA^(*)include an adaptive variable-step-size path search and a just-in-time expansion primitive.The former enables fast path search in complex environments,while the latter ensures the feasibility of the generated paths.By integrating these two components and conducting safety checks on the trajectories to be expanded,the CL-RaA^(*)can rapidly generate safe and feasible paths that satisfy the differential constraints that comprehensively consider the dynamics and control characteristics of six-degree-of-freedom fixed-wing UAVs.The final performance tests and simulation validations demonstrate that the CL-RaA^(*)can generate safe and feasible paths in various environments.Compared to feasible path planning algorithms that use the rapidlyexploring random trees,the CL-RaA^(*)not only ensures deterministic planning results in the same scenarios but also generates smoother feasible paths for fixed-wing UAVs more efficiently.In environments with dense grid obstacles,the feasible paths generated by the CL-RaA^(*)are more conducive to UAV tracking compared to those planned using Dubins curves.展开更多
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
This paper focuses on optimally determining the existence of connected paths between some given nodes in random ring-based graphs.Serving as a fundamental underlying structure in network modeling,ring topology appears...This paper focuses on optimally determining the existence of connected paths between some given nodes in random ring-based graphs.Serving as a fundamental underlying structure in network modeling,ring topology appears as commonplace in many realistic scenarios.Regarding this,we consider graphs composed of rings,with some possible connected paths between them.Without prior knowledge of the exact node permutations on rings,the existence of each edge can be unraveled through edge testing at a unit cost in one step.The problem examined is that of determining whether the given nodes are connected by a path or separated by a cut,with the minimum expected costs involved.Dividing the problem into different cases based on different topologies of the ring-based networks,we propose the corresponding policies that aim to quickly seek the paths between nodes.A common feature shared by all those policies is that we stick to going in the same direction during edge searching,with edge testing in each step only involving the test between the source and the node that has been tested most.The simple searching rule,interestingly,can be interpreted as a delightful property stemming from the neat structure of ring-based networks,which makes the searching process not rely on any sophisticated behaviors.We prove the optimality of the proposed policies by calculating the expected cost incurred and making a comparison with the other class of strategies.The effectiveness of the proposed policies is also verified through extensive simulations,from which we even disclose three extra intriguing findings:i)in a onering network,the cost will grow drastically with the number of designated nodes when the number is small and will grow slightly when that number is large;ii)in ring-based network,Depth First is optimal in detecting the connectivity between designated nodes;iii)the problem of multi-ring networks shares large similarity with that of two-ring networks,and a larger number of ties between rings will not influence the expected cost.展开更多
In this paper, we provide a bijection between the set of underdiagonal lattice paths of length n and the set of(2, 2)-Motzkin paths of length n. Besides, we generalize the bijection of Shapiro and Wang(Shapiro L W, Wa...In this paper, we provide a bijection between the set of underdiagonal lattice paths of length n and the set of(2, 2)-Motzkin paths of length n. Besides, we generalize the bijection of Shapiro and Wang(Shapiro L W, Wang C J. A bijection between 3-Motzkin paths and Schr¨oder paths with no peak at odd height. J. Integer Seq., 2009, 12: Article 09.3.2.) to a bijection between k-Motzkin paths and(k-2)-Schr¨oder paths with no horizontal step at even height. It is interesting that the second bijection is a generalization of the well-known bijection between Dyck paths and 2-Motzkin paths.展开更多
Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level st...Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level stemming from the doped rare earth ion or intrinsic defects to the electronic structure of the host,and therefore thermoluminescence measurement becomes a radical technology in studying trap depth,which is one of the significant parameters that determine the properties of persistent luminescence and photostimulated luminescence.However,the results of trap depth obtained by different thermoluminescence methods are quite different so that they are not comparable.Herein,we analyzed different thermoluminescence methods,selected and improved the traditional peak position method of T_(m)/500 to be E=(-0.94Inβ+30.09)kT_(m).Only the experimental heating rate(β)is needed additionally,but the accuracy is improved greatly in most cases.This convenient and accurate method will accelerate the discovery of novel rare earth-doped materials.展开更多
Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lowe...Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.展开更多
The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving...The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.展开更多
With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths ha...With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.展开更多
文摘AIM:To evaluate the choroidopathy in patients with systemic lupus erythematosus(SLE)using enhanced depth imaging spectral domain optical coherence tomography(EDI SD-OCT)and optical coherence tomography angiography(OCTA).METHODS:A total of 74 patients with SLE and 40 healthy volunteers were included in this cross-sectional study.SLE patients were further divided into three subgroups based on clinical and blood biochemistry findings.Ocular parameters obtained on ophthalmologic examination and optical imaging(EDI SD-OCT and OCTA)included the best corrected distance visual acuity(logMAR CDVA),subfoveal choroidal thickness(SCT),choroidal vascularity index(CVI)and vessel density(VD)of superficial capillary plexus(SCP)and deep capillary plexus(DCP).RESULTS:SLE patients had significantly lower values for CVI and VD of DCP(DVD)than control subjects.Amongst SLE patients,gender and chloroquine dose were found to be independent determinants of CVI while age predicted SCT.Steroid dose was a significant predictor for foveal VD of SCP(SVD),chloroquine dose for parafoveal SVD,gender for total DVD,and gender and steroid dose for perifoveal DVD.No correlation of logMAR CDVA and SCT was noted between SLE patients and control subjects.No correlation of SCT was noted with disease duration,Systemic Lupus Erythematosus Disease Activity Index(SLEDAI)score,hydroxychloroquine(HCQ)dose or steroid dose.No correlation of CVI was noted with patient age,disease duration,SLEDAI score,HCQ dose or steroid dose.No significant difference was noted between SLE subgroups in terms of any of the ocular parameters studied.CONCLUSION:The findings reveal the presence of ocular findings suggestive of early onset choroidopathy on EDI SD-OCT and OCTA in SLE patients,in the absence of ocular manifestations or active disease.
文摘Precise and robust three-dimensional object detection(3DOD)presents a promising opportunity in the field of mobile robot(MR)navigation.Monocular 3DOD techniques typically involve extending existing twodimensional object detection(2DOD)frameworks to predict the three-dimensional bounding box(3DBB)of objects captured in 2D RGB images.However,these methods often require multiple images,making them less feasible for various real-time scenarios.To address these challenges,the emergence of agile convolutional neural networks(CNNs)capable of inferring depth froma single image opens a new avenue for investigation.The paper proposes a novel ELDENet network designed to produce cost-effective 3DBounding Box Estimation(3D-BBE)froma single image.This novel framework comprises the PP-LCNet as the encoder and a fast convolutional decoder.Additionally,this integration includes a Squeeze-Exploit(SE)module utilizing the Math Kernel Library for Deep Neural Networks(MKLDNN)optimizer to enhance convolutional efficiency and streamline model size during effective training.Meanwhile,the proposed multi-scale sub-pixel decoder generates high-quality depth maps while maintaining a compact structure.Furthermore,the generated depthmaps provide a clear perspective with distance details of objects in the environment.These depth insights are combined with 2DOD for precise evaluation of 3D Bounding Boxes(3DBB),facilitating scene understanding and optimal route planning for mobile robots.Based on the estimated object center of the 3DBB,the Deep Reinforcement Learning(DRL)-based obstacle avoidance strategy for MRs is developed.Experimental results demonstrate that our model achieves state-of-the-art performance across three datasets:NYU-V2,KITTI,and Cityscapes.Overall,this framework shows significant potential for adaptation in intelligent mechatronic systems,particularly in developing knowledge-driven systems for mobile robot navigation.
基金Supported by the National Natural Science Foundation of China under Grant No 11174235
文摘A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay arrivals of surface-bottom reflection and bottom-surface reflection intersect at the source depth. Two hydrophones deployed vertically with a certain interval are required at least. If the receiver depths are known, the pair of time delays can be used to estimate the source depth. With the proposed method the source depth can be estimated successfully in a moderate range in the deep ocean without complicated matched-field calculations in the simulations and experiments.
基金Supported by the National Natural Science Foundation of China (No.81770972,No.81970843)。
文摘AIM:To evaluate the postoperative refractive prediction error(PE)and determine the factors that af fect the refractive outcomes of combined pars plana vitrectomy(PPV)or silicone oil removal(SOR)with cataract surgery.METHODS:The study is a retrospective,case-series study.Totally 301 eyes of 301 patients undergoing combined PPV/SOR with cataract surgery were enrolled.Eligible individuals were separated into four groups according to their preoperative diagnoses:silicone oil-filled eyes after PPV(group 1),epiretinal membrane(group 2),macular hole(group 3),and primary retinal detachment(RD;group 4).The variables af fecting postoperative refractive outcomes were analyzed,including age,gender,preoperative best-corrected visual acuity(BCVA),axial length(AL),keratometry average,anterior chamber depth(ACD),intraocular tamponade,and vitreoretinal pathology.The outcome measurements include the mean refractive PE and the proportions of eyes with a PE within±0.50 diopter(D)and±1.00 D.RESULTS:For all patients,the mean PE was-0.04±1.17 D,and 50.17%of patients(eyes)had a PE within±0.50 D.There was a significant difference in refractive outcomes among the four groups(P=0.028),with RD(group 4)showing the least favorable refractive outcome.In multivariate regression analysis,only AL,vitreoretinal pathology,and ACD were strongly associated with PE(all P<0.01).Univariate analysis revealed that longer eyes(AL>26 mm)and a deeper ACD were correlated with hyperopic PE,and shorter eyes(AL<26 mm)and a shallower ACD were correlated with myopic PE.CONCLUSION:RD patients have the least favorable refractive outcome.AL,vitreoretinal pathology,and ACD are strongly associated with PE in the combined surgery.These three factors affect refractive outcomes and thus can be used to predict a better postoperative refractive outcome in clinical practice.
基金the National Natural Science Foundation of China(Grant No.42274119)the Liaoning Revitalization Talents Program(Grant No.XLYC2002082)+1 种基金National Key Research and Development Plan Key Special Projects of Science and Technology Military Civil Integration(Grant No.2022YFF1400500)the Key Project of Science and Technology Commission of the Central Military Commission.
文摘This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.
文摘Discussions on Chinese modernization are offering African countries both conceptual inspiration and practical references as they explore their own sustainable development paths.
基金supported in part by 14th Five Year National Key R&D Program Project(Project Number:2023YFB3211001)the National Natural Science Foundation of China(62273339,U24A201397).
文摘Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.
文摘This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.
基金Supported by National Natural Science Foundation of China(Grant Nos.52075076,U1908231)National Key R&D Program of China(Grant No.2019YFA0705304)。
文摘A sudden increase in the radial depth(SIRD)is a distinctive phenomenon in plunge milling.It is typically characterized by a sharp increase in cutting force at the end of the axial feed of the tool,accompanied by harsh machine vibration sounds,which can negatively impact the reliability of plunge milling.This paper proposes an optimization method to eliminate SIRD in five-axis plunge milling.Initially,a five-axis plunge milling experiment and an analysis of the spatial position relationship between the plunge tools and the workpiece revealed that the cause of SIRD is unreasonable tool path planning.Subsequently,using the cutter position and cutter axis vector as variables,an SIRD discrimination model was developed for adjacent cutter positions and extended to multiple cutter positions.Optimizing the plunge milling tool path is considered a multivariate optimization problem that involves determining the cutter point and cutter axis vector.The SIRD discrimination model was used as a constraint function to aid in solving for the variables.The simulation and experimental results indicate that with the remaining volume of material as the optimization target,the optimized plunge milling tool path results in a residual material volume that is less than 60%of the gradually decreasing plunge depth.This optimization decreases the subsequent semi-finishing time of the workpiece and enhances machining efficiency.Additionally,it does not rely on operator experience and facilitates efficient automated optimization of the tool path to exclude SIRD.
文摘Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a significant challenge faced in the field of computer vision.However,existing monocular video depth estimation models tend to produce blurred or inaccurate depth information in regions with object edges and low texture.To address this issue,we propose a monocular depth estimation model architecture guided by semantic segmentation masks,which introduces semantic information into the model to correct the ambiguous depth regions.We have evaluated the proposed method,and experimental results show that our method improves the accuracy of edge depth,demonstrating the effectiveness of our approach.
基金supported by the National Science Fund for Distinguished Young Scholars(52425211)BIT Research Fund Program for Young Scholars(XSQD-202201005).
文摘A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.
基金Supported by the funding from RMIT Internal Research Grant R1.
文摘An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.
基金supported by the National Natural Science Foundation of China(No.52272382)the Fundamental Research Funds for the Central Universities,China。
文摘Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned paths in complex environments is challenging.This paper proposes a feasible path planning algorithm named Closed-loop Radial Ray A^(*)(CL-RaA^(*)).The core components of the CL-RaA^(*)include an adaptive variable-step-size path search and a just-in-time expansion primitive.The former enables fast path search in complex environments,while the latter ensures the feasibility of the generated paths.By integrating these two components and conducting safety checks on the trajectories to be expanded,the CL-RaA^(*)can rapidly generate safe and feasible paths that satisfy the differential constraints that comprehensively consider the dynamics and control characteristics of six-degree-of-freedom fixed-wing UAVs.The final performance tests and simulation validations demonstrate that the CL-RaA^(*)can generate safe and feasible paths in various environments.Compared to feasible path planning algorithms that use the rapidlyexploring random trees,the CL-RaA^(*)not only ensures deterministic planning results in the same scenarios but also generates smoother feasible paths for fixed-wing UAVs more efficiently.In environments with dense grid obstacles,the feasible paths generated by the CL-RaA^(*)are more conducive to UAV tracking compared to those planned using Dubins curves.
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 NSF China(No.61960206002,62020106005,42050105,62061146002)Shanghai Pilot Program for Basic Research-Shanghai Jiao Tong University。
文摘This paper focuses on optimally determining the existence of connected paths between some given nodes in random ring-based graphs.Serving as a fundamental underlying structure in network modeling,ring topology appears as commonplace in many realistic scenarios.Regarding this,we consider graphs composed of rings,with some possible connected paths between them.Without prior knowledge of the exact node permutations on rings,the existence of each edge can be unraveled through edge testing at a unit cost in one step.The problem examined is that of determining whether the given nodes are connected by a path or separated by a cut,with the minimum expected costs involved.Dividing the problem into different cases based on different topologies of the ring-based networks,we propose the corresponding policies that aim to quickly seek the paths between nodes.A common feature shared by all those policies is that we stick to going in the same direction during edge searching,with edge testing in each step only involving the test between the source and the node that has been tested most.The simple searching rule,interestingly,can be interpreted as a delightful property stemming from the neat structure of ring-based networks,which makes the searching process not rely on any sophisticated behaviors.We prove the optimality of the proposed policies by calculating the expected cost incurred and making a comparison with the other class of strategies.The effectiveness of the proposed policies is also verified through extensive simulations,from which we even disclose three extra intriguing findings:i)in a onering network,the cost will grow drastically with the number of designated nodes when the number is small and will grow slightly when that number is large;ii)in ring-based network,Depth First is optimal in detecting the connectivity between designated nodes;iii)the problem of multi-ring networks shares large similarity with that of two-ring networks,and a larger number of ties between rings will not influence the expected cost.
基金The NSF(11601020,11501014)of ChinaOrganization Department of Beijing Municipal Committee(2013D005003000012)Science and Technology Innovation Platform-Business Project 2017(PXM2017_014213_000022)
文摘In this paper, we provide a bijection between the set of underdiagonal lattice paths of length n and the set of(2, 2)-Motzkin paths of length n. Besides, we generalize the bijection of Shapiro and Wang(Shapiro L W, Wang C J. A bijection between 3-Motzkin paths and Schr¨oder paths with no peak at odd height. J. Integer Seq., 2009, 12: Article 09.3.2.) to a bijection between k-Motzkin paths and(k-2)-Schr¨oder paths with no horizontal step at even height. It is interesting that the second bijection is a generalization of the well-known bijection between Dyck paths and 2-Motzkin paths.
基金Project supported by the National Natural Science Foundation of China(52372134,12274023)the Fundamental Re search Funds for the Central Universities(FRF-EYIT-23-04)。
文摘Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level stemming from the doped rare earth ion or intrinsic defects to the electronic structure of the host,and therefore thermoluminescence measurement becomes a radical technology in studying trap depth,which is one of the significant parameters that determine the properties of persistent luminescence and photostimulated luminescence.However,the results of trap depth obtained by different thermoluminescence methods are quite different so that they are not comparable.Herein,we analyzed different thermoluminescence methods,selected and improved the traditional peak position method of T_(m)/500 to be E=(-0.94Inβ+30.09)kT_(m).Only the experimental heating rate(β)is needed additionally,but the accuracy is improved greatly in most cases.This convenient and accurate method will accelerate the discovery of novel rare earth-doped materials.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20202 and 52275477).
文摘Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.
基金supported in part by the National Natural Science Foundation of China(Nos.52205532 and 624B2077)the National Key Research and Development Program of China(No.2023YFB4302003).
文摘The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.
基金The 2024 Guangdong University of Science and Technology Teaching,Science and Innovation Project(GKJXXZ2024028)。
文摘With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.
