In this paper, some iterative schemes for approximating the common element of the set of zero points of maximal monotone operators and the set of fixed points of relatively nonexpansive mappings in a real uniformly sm...In this paper, some iterative schemes for approximating the common element of the set of zero points of maximal monotone operators and the set of fixed points of relatively nonexpansive mappings in a real uniformly smooth and uniformly convex Banach space are proposed. Some strong convergence theorems are obtained, to extend the previous work.展开更多
A new family of GB-majorized mappings from a topological space into a finite continuous topological spaces (in short, FC-space) involving a better admissible set-valued mapping is introduced. Some existence theorems...A new family of GB-majorized mappings from a topological space into a finite continuous topological spaces (in short, FC-space) involving a better admissible set-valued mapping is introduced. Some existence theorems of maximal elements for the family of GB-majorized mappings are proved under noncompact setting of product FCspaces. Some applications to fixed point and system of minimax inequalities are given in product FC-spaces. These theorems improve, unify and generalize many important results in recent literature.展开更多
A new family of set_valued mappings from a topological space into generalized convex spaces was introduced and studied. By using the continuous partition of unity theorem and Brouwer fixed point theorem, several exist...A new family of set_valued mappings from a topological space into generalized convex spaces was introduced and studied. By using the continuous partition of unity theorem and Brouwer fixed point theorem, several existence theorems of maximal elements for the family of set_valued mappings were proved under noncompact setting of product generalized convex spaces. These theorems improve, unify and generalize many important results in recent literature.展开更多
First, the notions of the measure of noncompactness and condensing setvalued mappings are introduced in locally FC-uniform spaces without convexity structure. A new existence theorem of maximal elements of a family of...First, the notions of the measure of noncompactness and condensing setvalued mappings are introduced in locally FC-uniform spaces without convexity structure. A new existence theorem of maximal elements of a family of set-valued mappings involving condensing mappings is proved in locally FC-uniform spaces. As applications, some new equilibrium existence theorems of generalized game involving condensing mappings are established in locally FC-uniform spaces. These results improve and generalize some known results in literature to locally FC-uniform spaces. Some further applications of our results to the systems of generalized vector quasi-equilibrium problems will be given in a follow-up paper.展开更多
A new family of set_valued mappings from a topological space into generalized convex spaces was introduced and studied. By using the continuous partition of unity theorem and Brouwer fixed point theorem, several exist...A new family of set_valued mappings from a topological space into generalized convex spaces was introduced and studied. By using the continuous partition of unity theorem and Brouwer fixed point theorem, several existence theorems of maximal elements for the family of set_valued mappings were proved under noncompact setting of product generalized convex spaces. These theorems improve, unify and generalize many important results in recent literature.展开更多
In this paper, some new iterative schemes for approximating the common element of the set of fixed points of strongly relatively nonexpansive mappings and the set of zero points of maximal monotone operators in a real...In this paper, some new iterative schemes for approximating the common element of the set of fixed points of strongly relatively nonexpansive mappings and the set of zero points of maximal monotone operators in a real uniformly smooth and uniformly convex Banach space are proposed. Some weak convergence theorems are obtained, which extend and complement some previous work.展开更多
Two existence theorems of maximal elements of condensing preference maps in locally convex Hausdorff spaces are proved which generalize the recent results of Mehta. One of them positively answers the open problem ment...Two existence theorems of maximal elements of condensing preference maps in locally convex Hausdorff spaces are proved which generalize the recent results of Mehta. One of them positively answers the open problem mentioned by Mehta.展开更多
Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance ...Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.展开更多
目的评估心肌T1/T2mapping影像组学特征在鉴别肥厚型心肌病(HCM)和扩张型心肌病(DCM)的价值,为HCM与DCM的早期精准鉴别提供临床依据。方法选取2022年1月至2025年1月我院收治的82例HCM患者与82例DCM患者作为研究对象,按7:3的比例随机分...目的评估心肌T1/T2mapping影像组学特征在鉴别肥厚型心肌病(HCM)和扩张型心肌病(DCM)的价值,为HCM与DCM的早期精准鉴别提供临床依据。方法选取2022年1月至2025年1月我院收治的82例HCM患者与82例DCM患者作为研究对象,按7:3的比例随机分为训练集(n=115)和测试集(n=49)。采用多因素Logistic回归分别构建临床模型、影像组学模型以及融合模型;通过受试者工作特征(ROC)、Hosmer-Lemeshow检验、校准曲线及决策曲线(DCA)评估三种模型的诊断效能与临床价值。结果多因素Logistic回归分析结果显示,初始T1值、强化后T1值与T2值均是心肌病类型的影响因素,以此构建临床模型:P=1.672+0.032×初始T1值+0.094×强化后T1值-0.215×T2值。经特征提取及降维筛选,最终保留9个特征参数构建影像组学模型:影像组学标签(Ra d-score)=0.120+1.253×original_shape_Sphericity-0.835×gradient_ffiifirstorder_Minimum+1.472×lbp-3D-m1_firstorder_Energy+0.927×square_firstorder_Root Mean Squared-1.156×log-sigma-2-0-mm-3D_firstorder_Median+0.784×wavelet-LHL_gldm_Dependence Variance+0.647×wavelet-HLL_glszm_Small Area Emphasis-0.513×wavelet-HLH_ngtdm_Busyness+1.088×original_g l r l m_Lo n g R u n E m p h a s i s。构建融合模型为:P=4.306+1.296×初始T1值-0.320×T2值+1.675×Rad-score。训练集与测试集的融合模型曲线下面积(AUC)分别为0.931、0.925,均高于单纯临床模型与影像组学模型,校准度与临床净收益亦表现最优。结论基于心肌T1/T2 mapping的影像组学特征能有效鉴别HCM与DCM,其与心肌T1/T2定量指标构建的融合模型具有更高的诊断效能和临床实用性,可作为临床鉴别HCM与DCM的有效工具。展开更多
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
Increasing the oil content is a key objective in peanut breeding programs.Accurate identification of quantitative trait loci(QTLs)with linked markers for oil content can facilitate marker-assisted selection for high-o...Increasing the oil content is a key objective in peanut breeding programs.Accurate identification of quantitative trait loci(QTLs)with linked markers for oil content can facilitate marker-assisted selection for high-oil breeding.In this study,a highdensity bin map was constructed by resequencing a recombinant inbred line(RIL)population(ZH16×J11)consisting of 295 lines.The bin map contained 4,212 loci and had a total length of 1,162.3 c M.Ten QTLs for oil content were identified in six linkage groups.Notably,two of these QTLs,qOCB03.1 and qOCB06.1,were consistently detected in a minimum of three environments and explained up to 13.62%of the phenotypic variation.They have not been reported in previous studies and thus are novel QTLs.The combination of favorable alleles from qOCB03.1 and qOCB06 in the RIL population could increase oil content across multiple environments from 1.50 to 2.46%.Two insertions/deletions(In Dels)markers linked to qOCB03.1 and qOCB06.1 were developed,and their association with oil content was validated in another RIL population(ZH10×ICG12625)with diverse phenotypes.In addition,the high-resolution map allowed for the precise positioning of qOCB03.1 and qOCB06.1 within a 1.77 Mb interval on chromosome B03 and a 1.51 Mb interval on chromosome B06,respectively.The annotation of genomic variants,analysis of transcriptome sequencing,and evaluation of the allelic effects in 292 peanut varieties revealed two candidate genes associated with oil content for each of the two QTLs.The candidate genes identified in this study can enable the map-based cloning of key genes controlling oil content in peanut.Furthermore,these novel and stable QTLs and their tightly linked markers are valuable for marker-assisted breeding for greater oil content in peanut.展开更多
冶金尘泥的转底炉处理工艺是目前钢铁行业采用的主要处置工艺,但在实际生产过程中经常出现还原焙烧不均匀的问题。利用微观扫描电子显微镜(scanning electron microscopy,SEM)分析结合宏观Maps统计分析,对冶金尘泥还原焙烧的不均匀性进...冶金尘泥的转底炉处理工艺是目前钢铁行业采用的主要处置工艺,但在实际生产过程中经常出现还原焙烧不均匀的问题。利用微观扫描电子显微镜(scanning electron microscopy,SEM)分析结合宏观Maps统计分析,对冶金尘泥还原焙烧的不均匀性进行详细的可视化、数据化分析。研究结果表明,冶金尘泥在焙烧温度为1250℃、焙烧时间为15 min的条件下,熟球金属化率达到89.04%、脱锌率达到81.66%、抗压强度达到3.03 kN,熟球金属化率和脱锌率会随着焙烧温度提高和焙烧时间延长而进一步提高,但熟球抗压强度在焙烧时间过长时反而逐渐降低;熟球Maps统计分析表明,提高焙烧温度更有利于提高熟球外圈和下部的还原程度,而延长焙烧时间也更有利于提高熟球下部还原程度,但对熟球内部和外圈还原程度的提升作用比较相似;同时,提高焙烧温度也更有利于提升熟球下部的致密化程度,降低熟球上、下孔隙结构的不均匀性,进而显著提高熟球整体抗压强度;但焙烧时间过长会导致熟球中小孔隙融合为大孔隙,反而降低熟球抗压强度。此外,熟球中硅酸盐(渣相)和浮氏体(FexO)更容易破裂,而金属铁(Fe)可延缓裂纹蔓延,因而,适当提高熟球金属化率、降低硅酸盐(渣相)含量也有利于提高其抗压强度。基于Maps统计分析探究了冶金尘泥还原焙烧过程中物相及孔隙的变化规律,分析结果可以为转底炉工艺处理冶金尘泥的生产实践提供指导和建议。展开更多
A topological map with the spatial relationship is an inescapable object in the research of map fusion,as it is a priori knowledge for planning path.However,there are some difficulties in topological map fusion in a d...A topological map with the spatial relationship is an inescapable object in the research of map fusion,as it is a priori knowledge for planning path.However,there are some difficulties in topological map fusion in a dynamic environment.Therefore,this paper proposes a fusion method for the hybrid topological map based on the memory sphere.A hybrid topological map is composed of occupancy grid maps and the topological structure.The hybrid map fusion can rely on rich features in occupancy grid maps.By analyzing the process of recalling scene,a memory sphere is designed to store the features and the semantic label extracted from occupancy grid maps.Then the core is the matching of the memory sphere,which is divided into two parts,fast retrieval and fine matching.We verify the effectiveness of our method in simulation and real environments,demonstrating that our method has a great performance in the dynamic environment.展开更多
Maize(Zea mays L.) is a globally significant crop that plays a crucial role in feeding the world's growing population.Among its various traits,plant height is particularly important as it affects yield,lodging res...Maize(Zea mays L.) is a globally significant crop that plays a crucial role in feeding the world's growing population.Among its various traits,plant height is particularly important as it affects yield,lodging resistance,ecological adaptability,and other important factors.Traditional methods for measuring plant height often lack cost-efficiency and accuracy.In this study,a light detection and ranging(LiDAR) sensor mounted on an unmanned aerial vehicle(UAV) was employed to collect point cloud data from 270 doubled haploid(DH) lines.This innovative application of UAV-based LiDAR technology was explored for high-throughput phenotyping in maize breeding trials.High-density genetic maps were constructed,and plant height was assessed at both single-plant and row scales across multiple developmental stages and genetic backgrounds.The findings revealed that for many varieties and small areas,single-plant-scale estimation accuracy was superior to rowscale estimation,with R2 values of 0.67 vs.0.56 and RMSE values of 0.12 m vs.0.17 m,respectively.Two high-density genetic maps were constructed based on SNP markers.In Sanya and Xinxiang,the F1DH and F2DH populations identified12 and 20 QTLs(quantitative trait loci) for plant height,respectively.This study successfully identified and validated QTLs associated with plant height,thereby revealing novel genetic loci and candidate genes.This research highlights the potential of UAV-based remote sensing to advance precision agriculture by enabling efficient,large-scale phenotyping and gene discovery in maize breeding programs.展开更多
Functional near-infrared spectroscopy quantifies cerebral hemodynamic signals by capturing oxygenation-dependent changes in hemoglobin in a noninvasive,portable,and ecologically valid manner,providing a unique insight...Functional near-infrared spectroscopy quantifies cerebral hemodynamic signals by capturing oxygenation-dependent changes in hemoglobin in a noninvasive,portable,and ecologically valid manner,providing a unique insight into neurovascular coupling.However,functional imaging biomarkers with high ecological validity for neurological disorders such as stroke,Parkinson's disease,dementia,amyotrophic lateral sclerosis,epilepsy,spinal cord injury,and traumatic brain injury are lacking,limiting the mechanistic understanding,treatment evaluations,and individualized interventions.The aim of this review is to systematically summarize evidence from the past decade on the use of functional near-infrared spectroscopy under the aforementioned conditions,synthesize its value for revealing neural mechanisms and assessing therapeutic responses,and identify current technical bottlenecks and future directions for advancement.Collectively,the findings demonstrate that functional near-infrared spectroscopy possesses substantial and far-reaching potential for uncovering the neural mechanisms underlying disease and for evaluating treatment-induced changes in brain function.Equipped with wearable probes,functional near-infrared spectroscopy can continuously and noninvasively monitor brain activity in naturalistic environments for extended periods,thereby overcoming the limitations of conventional imaging modalities that can only acquire data under restricted settings.This capability can furnish unprecedented objective neuroimaging evidence for neuroregenerative therapy research.Moreover,the portability of functional near-infrared spectroscopy allows it to be integrated into neurofeedback training systems:hemoglobin signals can be fed back to participants within milliseconds,enabling targeted,individualized,closed-loop modulation of brain function and considerably expanding the scope of hemodynamicsbased neurofeedback.When combined with other brain function assays(such as electroencephalography)and intervention techniques(such as transcranial magnetic stimulation and transcranial direct current stimulation),functional near-infrared spectroscopy also supplies high-temporal-resolution hemodynamic information,laying a critical foundation for the construction of high-precision noninvasive brain–computer interfaces,real-time cognitivestate decoding,and adaptive neuromodulation.Admittedly,almost all existing functional near-infrared spectroscopy studies are still observational and have small sample sizes,short follow-ups,and insufficient controls—shortcomings that together produce low-grade evidence.Therefore,there is still a significant gap before clinical translation can be achieved.Technically,the limited penetration depth of functional near-infrared spectroscopy restricts sampling to the superficial cortex,leaving deep nuclei largely unreachable.In addition,no consensus exists across devices regarding optode layout,light-source choice,motion-artifact correction,or analytical pipelines,creating pronounced heterogeneity that undermines reproducibility.With artificial intelligence and big data analytics advancing rapidly,functional near-infrared spectroscopy embedded within multimodal fusion frameworks is now poised to systematically map aberrant brain function signatures of neurological disorders,identify pathological regions suitable for targeted intervention,and provide real-time assessments of functional changes produced by neuroregenerative therapies.展开更多
The primary objective of this paper is to establish several sharp versions of improved Bohr inequality,refined Bohr-type inequality,and refined Bohr-Rogosinski inequality for the class of K-quasiconformal sense-preser...The primary objective of this paper is to establish several sharp versions of improved Bohr inequality,refined Bohr-type inequality,and refined Bohr-Rogosinski inequality for the class of K-quasiconformal sense-preserving harmonic mappings f=h+g in the unit disk D:={z∈C:|z|<1}.In order to achieve these objectives,we employ the non-negative quantity Sρ(h) and the concept of replacing the initial coefficients of the majorant series by the absolute values of the analytic function and its derivative,as well as other various settings.Moreover,we obtain the sharp Bohr-Rogosinski radius for harmonic mappings in the unit disk by replacing the bounding condition on the analytic function h with the half-plane condition.展开更多
Cross-modal localization,utilizing only cameras and prior light detection and ranging(LiDAR)point cloud maps,achieves high localization accuracy at a low cost.The integration of semantic information can significantly ...Cross-modal localization,utilizing only cameras and prior light detection and ranging(LiDAR)point cloud maps,achieves high localization accuracy at a low cost.The integration of semantic information can significantly enhance the accuracy at the cost of heavy computational load on optimization and huge semantic annotation on LiDAR point cloud maps.In this paper,we propose the SDA-Loc,a semantic cross-modal localization system that solely relies on visual semantic information,making our approach more streamlined compared to existing methods.We design a semantic-driven alignment algorithm that leverages visual semantic labels to perform different types of iterative closest point,allowing the system to better exploit the structural information represented by object semantics,thereby achieving accurate localization without the additional burden of point cloud annotation.Coupled with a designed dynamic error rejection mechanism,our approach effectively achieves a balance between accuracy and speed.The experiments conducted on the KITTI dataset demonstrate the competitive localization performance of our approach.Moreover,the experiment on outdoor campus dataset confirms that the proposed system can effectively mitigate the drift in visual localization under challenging lighting conditions,and proves the robustness of SDA-Loc when using poor LiDAR point cloud maps.The runtime analysis also shows that SDA-Loc strikes an excellent balance between localization accuracy and computational efficiency.展开更多
Peanut(Arachis hypogaea L.)is an important oil and edible protein crop.Its fatty acid composition not only infiuences the quality of peanut oil but also impacts fiavor,shelf life,and consumer health.Peanut oil is comp...Peanut(Arachis hypogaea L.)is an important oil and edible protein crop.Its fatty acid composition not only infiuences the quality of peanut oil but also impacts fiavor,shelf life,and consumer health.Peanut oil is comprised of approximately 80%oleic acid(C18:1)and linoleic acid(C18:2),10%palmitic acid(C16:0),and the remaining 10%includes stearic acid(C18:0),arachidic acid(C20:0),gadoleic acid(C20:1),behenic acid(C22:0),and lignoceric acid(C24:0).To unravel the genetic foundation of fatty acid content and delve into QTL localization,high-density SNP microarrays were used to genotype the RIL population of‘Sun Oleic 97R'בNC94022'.A genetic linkage map was constructed with 3,141 SNP markers,covering a total genetic distance of 3,051.81 c M.Sixty quantitative trait loci(QTLs)associated with fatty acids were distributed in 11 linkage groups,with phenotypic variance explained(PVE)ranging from 1.37 to 44.92%.Notably,the QTLs q FAT_A05.1 and q FAT_A08.1 are multiple-effect loci contributing to various fatty acid compositions.Moreover,15 haplotypes for the QTLs q FAT_A05.1 and q FAT_A08.1 were identified through genotyping 178 peanut germplasms.Haplotype analysis in a natural population confirmed the close relationship of the QTLs with the contents of oil,oleic acid,lignoceric acid,palmitic acid and behenic acid.This study serves as a valuable reference for selecting improved peanut genotypes with superior oil quality and desirable fatty acid composition.展开更多
基金the National Natural Science Foundation of China (10771050)
摘要In this paper, some iterative schemes for approximating the common element of the set of zero points of maximal monotone operators and the set of fixed points of relatively nonexpansive mappings in a real uniformly smooth and uniformly convex Banach space are proposed. Some strong convergence theorems are obtained, to extend the previous work.
基金Project supported by the Natural Science Foundation of Sichuan Education Department of China (Nos.2003A081 and SZD0406)
摘要A new family of GB-majorized mappings from a topological space into a finite continuous topological spaces (in short, FC-space) involving a better admissible set-valued mapping is introduced. Some existence theorems of maximal elements for the family of GB-majorized mappings are proved under noncompact setting of product FCspaces. Some applications to fixed point and system of minimax inequalities are given in product FC-spaces. These theorems improve, unify and generalize many important results in recent literature.
摘要A new family of set_valued mappings from a topological space into generalized convex spaces was introduced and studied. By using the continuous partition of unity theorem and Brouwer fixed point theorem, several existence theorems of maximal elements for the family of set_valued mappings were proved under noncompact setting of product generalized convex spaces. These theorems improve, unify and generalize many important results in recent literature.
基金the Natural Science Foundation of Sichuan Education Department of China (Nos.2003A081 and SZD0406)
摘要First, the notions of the measure of noncompactness and condensing setvalued mappings are introduced in locally FC-uniform spaces without convexity structure. A new existence theorem of maximal elements of a family of set-valued mappings involving condensing mappings is proved in locally FC-uniform spaces. As applications, some new equilibrium existence theorems of generalized game involving condensing mappings are established in locally FC-uniform spaces. These results improve and generalize some known results in literature to locally FC-uniform spaces. Some further applications of our results to the systems of generalized vector quasi-equilibrium problems will be given in a follow-up paper.
摘要A new family of set_valued mappings from a topological space into generalized convex spaces was introduced and studied. By using the continuous partition of unity theorem and Brouwer fixed point theorem, several existence theorems of maximal elements for the family of set_valued mappings were proved under noncompact setting of product generalized convex spaces. These theorems improve, unify and generalize many important results in recent literature.
基金Supported by the National Natural Science Foundation of China(10771050)the Natural Science Foun-dation of Hebei Province(A2010001482)
摘要In this paper, some new iterative schemes for approximating the common element of the set of fixed points of strongly relatively nonexpansive mappings and the set of zero points of maximal monotone operators in a real uniformly smooth and uniformly convex Banach space are proposed. Some weak convergence theorems are obtained, which extend and complement some previous work.
基金Project Supported by the National Natural Science Foundation of China
摘要Two existence theorems of maximal elements of condensing preference maps in locally convex Hausdorff spaces are proved which generalize the recent results of Mehta. One of them positively answers the open problem mentioned by Mehta.
基金the Deanship of Graduate Studies and Scientific Research at University of Bisha for supporting this work through the Fast-Track Research Support Programthe Deanship of Scientific Research at Northern Border University,Arar,KSA for funding this research work through the project number“NBU-FFR-2025-2903-09”.
摘要Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.
摘要目的评估心肌T1/T2mapping影像组学特征在鉴别肥厚型心肌病(HCM)和扩张型心肌病(DCM)的价值,为HCM与DCM的早期精准鉴别提供临床依据。方法选取2022年1月至2025年1月我院收治的82例HCM患者与82例DCM患者作为研究对象,按7:3的比例随机分为训练集(n=115)和测试集(n=49)。采用多因素Logistic回归分别构建临床模型、影像组学模型以及融合模型;通过受试者工作特征(ROC)、Hosmer-Lemeshow检验、校准曲线及决策曲线(DCA)评估三种模型的诊断效能与临床价值。结果多因素Logistic回归分析结果显示,初始T1值、强化后T1值与T2值均是心肌病类型的影响因素,以此构建临床模型:P=1.672+0.032×初始T1值+0.094×强化后T1值-0.215×T2值。经特征提取及降维筛选,最终保留9个特征参数构建影像组学模型:影像组学标签(Ra d-score)=0.120+1.253×original_shape_Sphericity-0.835×gradient_ffiifirstorder_Minimum+1.472×lbp-3D-m1_firstorder_Energy+0.927×square_firstorder_Root Mean Squared-1.156×log-sigma-2-0-mm-3D_firstorder_Median+0.784×wavelet-LHL_gldm_Dependence Variance+0.647×wavelet-HLL_glszm_Small Area Emphasis-0.513×wavelet-HLH_ngtdm_Busyness+1.088×original_g l r l m_Lo n g R u n E m p h a s i s。构建融合模型为:P=4.306+1.296×初始T1值-0.320×T2值+1.675×Rad-score。训练集与测试集的融合模型曲线下面积(AUC)分别为0.931、0.925,均高于单纯临床模型与影像组学模型,校准度与临床净收益亦表现最优。结论基于心肌T1/T2 mapping的影像组学特征能有效鉴别HCM与DCM,其与心肌T1/T2定量指标构建的融合模型具有更高的诊断效能和临床实用性,可作为临床鉴别HCM与DCM的有效工具。
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。
摘要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 the National Key Research and Development Program of China(2022YFD1200400)the National Natural Science Foundation of China(32161143006 and 31971903)+4 种基金the National Peanut Industry Technology System Construction,China(CARS13)the National Crop Germplasm Resources Center,China(NCGRC-2022-036)the National Program for Crop Germplasm Protection of China(19210163)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2021-OCRI)the Guangdong Provincial Key Research and Development Program-Modern Seed Industry,China(2022B0202060004)。
摘要Increasing the oil content is a key objective in peanut breeding programs.Accurate identification of quantitative trait loci(QTLs)with linked markers for oil content can facilitate marker-assisted selection for high-oil breeding.In this study,a highdensity bin map was constructed by resequencing a recombinant inbred line(RIL)population(ZH16×J11)consisting of 295 lines.The bin map contained 4,212 loci and had a total length of 1,162.3 c M.Ten QTLs for oil content were identified in six linkage groups.Notably,two of these QTLs,qOCB03.1 and qOCB06.1,were consistently detected in a minimum of three environments and explained up to 13.62%of the phenotypic variation.They have not been reported in previous studies and thus are novel QTLs.The combination of favorable alleles from qOCB03.1 and qOCB06 in the RIL population could increase oil content across multiple environments from 1.50 to 2.46%.Two insertions/deletions(In Dels)markers linked to qOCB03.1 and qOCB06.1 were developed,and their association with oil content was validated in another RIL population(ZH10×ICG12625)with diverse phenotypes.In addition,the high-resolution map allowed for the precise positioning of qOCB03.1 and qOCB06.1 within a 1.77 Mb interval on chromosome B03 and a 1.51 Mb interval on chromosome B06,respectively.The annotation of genomic variants,analysis of transcriptome sequencing,and evaluation of the allelic effects in 292 peanut varieties revealed two candidate genes associated with oil content for each of the two QTLs.The candidate genes identified in this study can enable the map-based cloning of key genes controlling oil content in peanut.Furthermore,these novel and stable QTLs and their tightly linked markers are valuable for marker-assisted breeding for greater oil content in peanut.
摘要冶金尘泥的转底炉处理工艺是目前钢铁行业采用的主要处置工艺,但在实际生产过程中经常出现还原焙烧不均匀的问题。利用微观扫描电子显微镜(scanning electron microscopy,SEM)分析结合宏观Maps统计分析,对冶金尘泥还原焙烧的不均匀性进行详细的可视化、数据化分析。研究结果表明,冶金尘泥在焙烧温度为1250℃、焙烧时间为15 min的条件下,熟球金属化率达到89.04%、脱锌率达到81.66%、抗压强度达到3.03 kN,熟球金属化率和脱锌率会随着焙烧温度提高和焙烧时间延长而进一步提高,但熟球抗压强度在焙烧时间过长时反而逐渐降低;熟球Maps统计分析表明,提高焙烧温度更有利于提高熟球外圈和下部的还原程度,而延长焙烧时间也更有利于提高熟球下部还原程度,但对熟球内部和外圈还原程度的提升作用比较相似;同时,提高焙烧温度也更有利于提升熟球下部的致密化程度,降低熟球上、下孔隙结构的不均匀性,进而显著提高熟球整体抗压强度;但焙烧时间过长会导致熟球中小孔隙融合为大孔隙,反而降低熟球抗压强度。此外,熟球中硅酸盐(渣相)和浮氏体(FexO)更容易破裂,而金属铁(Fe)可延缓裂纹蔓延,因而,适当提高熟球金属化率、降低硅酸盐(渣相)含量也有利于提高其抗压强度。基于Maps统计分析探究了冶金尘泥还原焙烧过程中物相及孔隙的变化规律,分析结果可以为转底炉工艺处理冶金尘泥的生产实践提供指导和建议。
基金the Intelligent Agricultural Machinery Innovation Research and Development Project of Hunan Province(No.202301)the National Natural Science Foundation of China(No.62373376)。
摘要A topological map with the spatial relationship is an inescapable object in the research of map fusion,as it is a priori knowledge for planning path.However,there are some difficulties in topological map fusion in a dynamic environment.Therefore,this paper proposes a fusion method for the hybrid topological map based on the memory sphere.A hybrid topological map is composed of occupancy grid maps and the topological structure.The hybrid map fusion can rely on rich features in occupancy grid maps.By analyzing the process of recalling scene,a memory sphere is designed to store the features and the semantic label extracted from occupancy grid maps.Then the core is the matching of the memory sphere,which is divided into two parts,fast retrieval and fine matching.We verify the effectiveness of our method in simulation and real environments,demonstrating that our method has a great performance in the dynamic environment.
基金supported by the National Key Research and Development Program of China (2023YFD1200500)the National Natural Science Foundation of China (32301395, 42071426, and 51922072)+3 种基金the Nanfan Special Project of the Chinese Academy of Agricultural Sciences (YBXM2305)the Central Public-Interest Scientific Institution Basal Research Fund Program, China (Y2020YJ07 and Y2022XK22)the Key Cultivation Program of the Xinjiang Academy of Agricultural Sciences, China (xjkcpy-2020003)the Open Competition Project of Heilongjiang Province, China (2021ZXJ05A03)。
摘要Maize(Zea mays L.) is a globally significant crop that plays a crucial role in feeding the world's growing population.Among its various traits,plant height is particularly important as it affects yield,lodging resistance,ecological adaptability,and other important factors.Traditional methods for measuring plant height often lack cost-efficiency and accuracy.In this study,a light detection and ranging(LiDAR) sensor mounted on an unmanned aerial vehicle(UAV) was employed to collect point cloud data from 270 doubled haploid(DH) lines.This innovative application of UAV-based LiDAR technology was explored for high-throughput phenotyping in maize breeding trials.High-density genetic maps were constructed,and plant height was assessed at both single-plant and row scales across multiple developmental stages and genetic backgrounds.The findings revealed that for many varieties and small areas,single-plant-scale estimation accuracy was superior to rowscale estimation,with R2 values of 0.67 vs.0.56 and RMSE values of 0.12 m vs.0.17 m,respectively.Two high-density genetic maps were constructed based on SNP markers.In Sanya and Xinxiang,the F1DH and F2DH populations identified12 and 20 QTLs(quantitative trait loci) for plant height,respectively.This study successfully identified and validated QTLs associated with plant height,thereby revealing novel genetic loci and candidate genes.This research highlights the potential of UAV-based remote sensing to advance precision agriculture by enabling efficient,large-scale phenotyping and gene discovery in maize breeding programs.
基金supported by the National Natural Science Foundation of China,Nos.82201474(to GL),82203835(to YF),82071330(to ZT)。
摘要Functional near-infrared spectroscopy quantifies cerebral hemodynamic signals by capturing oxygenation-dependent changes in hemoglobin in a noninvasive,portable,and ecologically valid manner,providing a unique insight into neurovascular coupling.However,functional imaging biomarkers with high ecological validity for neurological disorders such as stroke,Parkinson's disease,dementia,amyotrophic lateral sclerosis,epilepsy,spinal cord injury,and traumatic brain injury are lacking,limiting the mechanistic understanding,treatment evaluations,and individualized interventions.The aim of this review is to systematically summarize evidence from the past decade on the use of functional near-infrared spectroscopy under the aforementioned conditions,synthesize its value for revealing neural mechanisms and assessing therapeutic responses,and identify current technical bottlenecks and future directions for advancement.Collectively,the findings demonstrate that functional near-infrared spectroscopy possesses substantial and far-reaching potential for uncovering the neural mechanisms underlying disease and for evaluating treatment-induced changes in brain function.Equipped with wearable probes,functional near-infrared spectroscopy can continuously and noninvasively monitor brain activity in naturalistic environments for extended periods,thereby overcoming the limitations of conventional imaging modalities that can only acquire data under restricted settings.This capability can furnish unprecedented objective neuroimaging evidence for neuroregenerative therapy research.Moreover,the portability of functional near-infrared spectroscopy allows it to be integrated into neurofeedback training systems:hemoglobin signals can be fed back to participants within milliseconds,enabling targeted,individualized,closed-loop modulation of brain function and considerably expanding the scope of hemodynamicsbased neurofeedback.When combined with other brain function assays(such as electroencephalography)and intervention techniques(such as transcranial magnetic stimulation and transcranial direct current stimulation),functional near-infrared spectroscopy also supplies high-temporal-resolution hemodynamic information,laying a critical foundation for the construction of high-precision noninvasive brain–computer interfaces,real-time cognitivestate decoding,and adaptive neuromodulation.Admittedly,almost all existing functional near-infrared spectroscopy studies are still observational and have small sample sizes,short follow-ups,and insufficient controls—shortcomings that together produce low-grade evidence.Therefore,there is still a significant gap before clinical translation can be achieved.Technically,the limited penetration depth of functional near-infrared spectroscopy restricts sampling to the superficial cortex,leaving deep nuclei largely unreachable.In addition,no consensus exists across devices regarding optode layout,light-source choice,motion-artifact correction,or analytical pipelines,creating pronounced heterogeneity that undermines reproducibility.With artificial intelligence and big data analytics advancing rapidly,functional near-infrared spectroscopy embedded within multimodal fusion frameworks is now poised to systematically map aberrant brain function signatures of neurological disorders,identify pathological regions suitable for targeted intervention,and provide real-time assessments of functional changes produced by neuroregenerative therapies.
基金supported by University Grants Commission(IN)fellowship(F.44-1/2018(SA-III)).
摘要The primary objective of this paper is to establish several sharp versions of improved Bohr inequality,refined Bohr-type inequality,and refined Bohr-Rogosinski inequality for the class of K-quasiconformal sense-preserving harmonic mappings f=h+g in the unit disk D:={z∈C:|z|<1}.In order to achieve these objectives,we employ the non-negative quantity Sρ(h) and the concept of replacing the initial coefficients of the majorant series by the absolute values of the analytic function and its derivative,as well as other various settings.Moreover,we obtain the sharp Bohr-Rogosinski radius for harmonic mappings in the unit disk by replacing the bounding condition on the analytic function h with the half-plane condition.
基金supported by the Technology Project Managed by the State Grid Corporation of China(No.5700-202416334A-2-1-ZX).
摘要Cross-modal localization,utilizing only cameras and prior light detection and ranging(LiDAR)point cloud maps,achieves high localization accuracy at a low cost.The integration of semantic information can significantly enhance the accuracy at the cost of heavy computational load on optimization and huge semantic annotation on LiDAR point cloud maps.In this paper,we propose the SDA-Loc,a semantic cross-modal localization system that solely relies on visual semantic information,making our approach more streamlined compared to existing methods.We design a semantic-driven alignment algorithm that leverages visual semantic labels to perform different types of iterative closest point,allowing the system to better exploit the structural information represented by object semantics,thereby achieving accurate localization without the additional burden of point cloud annotation.Coupled with a designed dynamic error rejection mechanism,our approach effectively achieves a balance between accuracy and speed.The experiments conducted on the KITTI dataset demonstrate the competitive localization performance of our approach.Moreover,the experiment on outdoor campus dataset confirms that the proposed system can effectively mitigate the drift in visual localization under challenging lighting conditions,and proves the robustness of SDA-Loc when using poor LiDAR point cloud maps.The runtime analysis also shows that SDA-Loc strikes an excellent balance between localization accuracy and computational efficiency.
基金funded by the National Key Research and Development Program,China(2023YFD1202800)the Guangxi Science and Technology Major Project,China+2 种基金the Peak Project of Modern Characteristic Agriculture,China(GuikeAA23062004)the Key Research and Development Project of Shandong Province,China(2022LZGC007 and 2022LZGC022)the Taishan Scholars Program of Shandong Province,China。
摘要Peanut(Arachis hypogaea L.)is an important oil and edible protein crop.Its fatty acid composition not only infiuences the quality of peanut oil but also impacts fiavor,shelf life,and consumer health.Peanut oil is comprised of approximately 80%oleic acid(C18:1)and linoleic acid(C18:2),10%palmitic acid(C16:0),and the remaining 10%includes stearic acid(C18:0),arachidic acid(C20:0),gadoleic acid(C20:1),behenic acid(C22:0),and lignoceric acid(C24:0).To unravel the genetic foundation of fatty acid content and delve into QTL localization,high-density SNP microarrays were used to genotype the RIL population of‘Sun Oleic 97R'בNC94022'.A genetic linkage map was constructed with 3,141 SNP markers,covering a total genetic distance of 3,051.81 c M.Sixty quantitative trait loci(QTLs)associated with fatty acids were distributed in 11 linkage groups,with phenotypic variance explained(PVE)ranging from 1.37 to 44.92%.Notably,the QTLs q FAT_A05.1 and q FAT_A08.1 are multiple-effect loci contributing to various fatty acid compositions.Moreover,15 haplotypes for the QTLs q FAT_A05.1 and q FAT_A08.1 were identified through genotyping 178 peanut germplasms.Haplotype analysis in a natural population confirmed the close relationship of the QTLs with the contents of oil,oleic acid,lignoceric acid,palmitic acid and behenic acid.This study serves as a valuable reference for selecting improved peanut genotypes with superior oil quality and desirable fatty acid composition.