Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods...Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.展开更多
As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies r...As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.展开更多
With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments rem...With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments remains a critical challenge.To address this problem,this paper proposes an improved path planning algorithm—Random Geometric Graph(RGG)-guided Rapidly-exploring Random Tree(R-RRT)—based on the classical Rapidly-exploring Random Tree(RRT)framework.First,a refined 3D occupancy grid map is constructed from Light Detection and Ranging point cloud data through ground filtering,noise removal,coordinate transformation,and obstacle inflation using spherical structuring elements.During the planning stage,a dynamic goal-biasing strategy is introduced to adaptively adjust the sampling direction,the sampling distribution is optimized using a pre-generated RGG,and collision detection is accelerated via a K-Dimensional Tree structure.After initial trajectory generation,redundant nodes are eliminated via greedy pruning,and a curvature-minimizing gradient-based optimizationmethod is applied to smooth the trajectory.Experimental results conducted in a simulated substation environment demonstrate that,compared with mainstream path planning algorithms,the proposed R-RRT achieves superior performance in terms of path length,planning time,and trajectory smoothness.Comprehensive analysis shows that the proposed method significantly enhances trajectory quality,planning efficiency,and operational safety,validating its applicability and advantages for high-precision 3D path planning in complex substation inspection scenarios.展开更多
目的利用CRISPR/Cas9基因编辑技术构建斑马鱼map3k15敲除纯合品系,为进一步研究map3k15在肾脏疾病方面的作用提供动物模型。方法1)分析map3k15在斑马鱼中的表达模式;2)利用CRISPR/Cas9基因编辑技术构建斑马鱼map3k15敲除纯合品系;3)观察...目的利用CRISPR/Cas9基因编辑技术构建斑马鱼map3k15敲除纯合品系,为进一步研究map3k15在肾脏疾病方面的作用提供动物模型。方法1)分析map3k15在斑马鱼中的表达模式;2)利用CRISPR/Cas9基因编辑技术构建斑马鱼map3k15敲除纯合品系;3)观察map3k15缺失对斑马鱼表型的影响。结果1)map3k15在斑马鱼前肾中表达,且MAP3K15/Map3k15蛋白在多物种间具有高度保守性;2)成功构建了斑马鱼map3k15-/-突变体,并保留+2 bp及+1 bp 2种突变品系;3)map3k15突变斑马鱼在胚胎发育过程中出现卵黄囊、心包及头部的水肿,且随发育时间延长,症状逐渐加重。结论成功构建了map3k15敲除的纯合斑马鱼品系,为未来研究map3k15在肾脏发育及疾病中的作用提供了重要的模型。展开更多
Wheat grain morphology,particularly grain length(GL)and width(GW),is a key determinant of yield.To improve the suboptimal grain dimensions of the local anthocyanin-rich variety Guizi 1(GZ1),we crossed it with Zhongyan...Wheat grain morphology,particularly grain length(GL)and width(GW),is a key determinant of yield.To improve the suboptimal grain dimensions of the local anthocyanin-rich variety Guizi 1(GZ1),we crossed it with Zhongyan 96-3(ZY96-3),an elite germplasm known for faster grain filling and superior grain size.A genotyping-by-sequencing(GBS)approach was applied to an F_(2)population of 110 individuals derived from GZ1×ZY96-3,resulting in the identification of 23,134 high-quality SNPs.Most of the SNPs associated with GL and GW were clustered on chromosomes 2B,3A,and 3B.QTL mapping for GL revealed two major loci,GL1 on chromosome 2B and GL2 on chromosome 3B,and eight candidate genes were identified within their corresponding intervals(2B:63.6–70.4 Mb;3B:631.5–633.3 Mb).These genes encode proteins potentially involved in grain size regulation,including a TOR2 regulation-associated protein,erect spike 2(EP2),fibroblast growth factor 6(FGF6),cellulose synthase-like(CSLD),RelA/pot homologue three family protein,and three GDSL esterase/lipase(GLIP)proteins.Additionally,we detected a QTL associated with GW on chromosome 3A and identified two candidate genes,TOR2 regulation and starch synthase within the 61.4–68.5 Mb interval.Overall,this study provides a strong theoretical and technical basis for wheat genetic improvement and offers valuable resources for precise QTL mapping and candidate gene discovery.展开更多
基金National Key Scientific Instrument and Equipment Development Project under Grant No.61827801the open research fund of State Key Laboratory of Integrated Services Networks,No.ISN22-11+1 种基金Natural Science Foundation of Jiangsu Province,No.BK20211182open research fund of National Mobile Communications Research Laboratory,Southeast University,No.2022D04。
文摘Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.
基金supported by Kyonggi University Research Grant 2025.
文摘As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.
基金Funding for this research was provided by the Program for Scientific Research Innovation Team in Colleges and Universities of Anhui Province(No.2022AH010095)the Hefei Key Technology R&D“Champion-Based Selection”Project(No.2023SGJ011).
文摘With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments remains a critical challenge.To address this problem,this paper proposes an improved path planning algorithm—Random Geometric Graph(RGG)-guided Rapidly-exploring Random Tree(R-RRT)—based on the classical Rapidly-exploring Random Tree(RRT)framework.First,a refined 3D occupancy grid map is constructed from Light Detection and Ranging point cloud data through ground filtering,noise removal,coordinate transformation,and obstacle inflation using spherical structuring elements.During the planning stage,a dynamic goal-biasing strategy is introduced to adaptively adjust the sampling direction,the sampling distribution is optimized using a pre-generated RGG,and collision detection is accelerated via a K-Dimensional Tree structure.After initial trajectory generation,redundant nodes are eliminated via greedy pruning,and a curvature-minimizing gradient-based optimizationmethod is applied to smooth the trajectory.Experimental results conducted in a simulated substation environment demonstrate that,compared with mainstream path planning algorithms,the proposed R-RRT achieves superior performance in terms of path length,planning time,and trajectory smoothness.Comprehensive analysis shows that the proposed method significantly enhances trajectory quality,planning efficiency,and operational safety,validating its applicability and advantages for high-precision 3D path planning in complex substation inspection scenarios.
文摘目的利用CRISPR/Cas9基因编辑技术构建斑马鱼map3k15敲除纯合品系,为进一步研究map3k15在肾脏疾病方面的作用提供动物模型。方法1)分析map3k15在斑马鱼中的表达模式;2)利用CRISPR/Cas9基因编辑技术构建斑马鱼map3k15敲除纯合品系;3)观察map3k15缺失对斑马鱼表型的影响。结果1)map3k15在斑马鱼前肾中表达,且MAP3K15/Map3k15蛋白在多物种间具有高度保守性;2)成功构建了斑马鱼map3k15-/-突变体,并保留+2 bp及+1 bp 2种突变品系;3)map3k15突变斑马鱼在胚胎发育过程中出现卵黄囊、心包及头部的水肿,且随发育时间延长,症状逐渐加重。结论成功构建了map3k15敲除的纯合斑马鱼品系,为未来研究map3k15在肾脏发育及疾病中的作用提供了重要的模型。
基金Funding for this project was provided by the National Natural Science Foundation of China(Grants No.32160456,32360474,32360486,32260496)the Key Laboratory of Functional Agriculture of Guizhou Provincial Higher Education Institutions(Grant No.Qianjiaoji(2023)007).
文摘Wheat grain morphology,particularly grain length(GL)and width(GW),is a key determinant of yield.To improve the suboptimal grain dimensions of the local anthocyanin-rich variety Guizi 1(GZ1),we crossed it with Zhongyan 96-3(ZY96-3),an elite germplasm known for faster grain filling and superior grain size.A genotyping-by-sequencing(GBS)approach was applied to an F_(2)population of 110 individuals derived from GZ1×ZY96-3,resulting in the identification of 23,134 high-quality SNPs.Most of the SNPs associated with GL and GW were clustered on chromosomes 2B,3A,and 3B.QTL mapping for GL revealed two major loci,GL1 on chromosome 2B and GL2 on chromosome 3B,and eight candidate genes were identified within their corresponding intervals(2B:63.6–70.4 Mb;3B:631.5–633.3 Mb).These genes encode proteins potentially involved in grain size regulation,including a TOR2 regulation-associated protein,erect spike 2(EP2),fibroblast growth factor 6(FGF6),cellulose synthase-like(CSLD),RelA/pot homologue three family protein,and three GDSL esterase/lipase(GLIP)proteins.Additionally,we detected a QTL associated with GW on chromosome 3A and identified two candidate genes,TOR2 regulation and starch synthase within the 61.4–68.5 Mb interval.Overall,this study provides a strong theoretical and technical basis for wheat genetic improvement and offers valuable resources for precise QTL mapping and candidate gene discovery.
