ESTIMATE ON THE BLOCH CONSTANT FOR CERTAIN HARMONIC MAPPINGS UNDER A DIFFERENTIAL OPERATOR

In this paper,we first obtain the precise values of the univalent radius and the Bloch constant for harmonic mappings of the formL(f)=zfz-zfz,where f represents normalized harmonic mappings with bounded dilation.Then,using these results,we present better estimations for the Bloch constants of certain harmonic mappings L(f),where f is a K-quasiregular harmonic or open harmonic.Finally,we establish three versions of BlochLandau type theorem for biharmonic mappings of the form L(f).These results are sharp in some given cases and improve the related results of earlier authors.

THE FEKETE-SZEG?INEQUALITY AND SUCCESSIVE COEFFICIENTS DIFFERENCE FOR A SUBCLASS OF CLOSE-TO-STARLIKE MAPPINGS IN COMPLEX BANACH SPACES

Let C be the familiar class of normalized close-to-convex functions in the unit disk.In[17],Koepf demonstrated that,as to a function■in the class C,■By applying this inequality,it can be proven that‖a3|-|a2‖≤1 for close-to-convex functions.Now we generalized the above conclusions to a subclass of close-to-starlike mappings defined on the unit ball of a complex Banach space.

MRI 3D-Vibe联合T2 mapping成像对腕关节三角纤维软骨复合体损伤的评价及定量分析

目的探讨3.0TMRI三维容积插入式屏气检查(three dimension volumetric interpolated breath-hold examination,3D-Vibe)和T2 mapping成像对腕关节三角纤维软骨复合体(triangular fibrocartilage complex,TFCC)损伤的评价及软骨定量分析。材料与方法对TFCC损伤组35例及健康对照组30例行双侧腕关节常规、3D-Vibe和T2 mapping序列扫描。在T2 mapping图像中分别测量桡侧软骨、三角纤维软骨盘(triangular fibrocartilage disc,TFC)、纤维血管组织、类半月板、尺侧附着处的T2值。结果类半月板的损伤组与健康组T2值差异无统计学意义(P>0.05),余各区域损伤组与健康组T2值总体均数差异均有统计学意义(P<0.01);损伤组各区域T2值两两比较差异均有统计学意义(P<0.05)。不同年龄段的T2值总体均数差异具有统计学意义(P<0.05)。分型及病程对TFCC损伤患者的T2值有显著影响(P<0.01);年龄、性别对TFCC损伤患者的T2值影响不显著(P>0.05)。结论3.0 T MRI 3D-Vibe及T2 mapping成像技术有助于对TFCC损伤进行评价及软骨定量分析,其T2值能够反映软骨损伤的分子生物学变化,易受损伤分型及病程的影响,但不受年龄及性别的影响。

Mapping epistasis and environment × QTX interaction based on four-omics genotypes for the detected QTX loci controlling complex traits in tobacco

Using newly developed methods and software, association mapping was conducted for chromium content and total sugar in tobacco leaf, based on four-omics datasets. Our objective was to collect data on genotype and phenotype for 60 leaf samples at four developmental stages, from three plant architectural positions and for three cultivars that were grown in two locations. Association mapping was conducted to detect genetic variants at quantitative trait SNP(QTS) loci, quantitative trait transcript(QTT) differences,quantitative trait protein(QTP) variability, and quantitative trait metabolite(QTM) changes,which can be summarized as QTX locus variation. The total heritabilities of the four-omics loci for both traits tested were 23.60% for epistasis and 15.26% for treatment interaction.Epistasis and environment × treatment interaction had important impacts on complex traits at all-omics levels. For decreasing chromium content and increasing total sugar in tobacco leaf, six methylated loci can be directly used for marker-assisted selection, and expression of ten QTTs, seven QTPs and six QTMs can be modified by selection or cultivation.

An Alternative Way to Mapping Cone: The Algebraic Topology of the Pinched Tensor

In this research, we explore the properties and applications of the mapping cone and its variant, the pinched mapping cone. The mapping cone is a construction that arises naturally in algebraic topology and is used to study the homotopy type of spaces. It has several key properties, including its homotopy equivalence to the cofiber of a continuous map, and its ability to compute homotopy groups using the long exact sequence associated with the cofiber. We also provide an overview of the properties and applications of the mapping cone and the pinched mapping cone in algebraic topology. This work highlights the importance of these constructions in the study of homotopy theory and the calculation of homotopy groups. The study also points to the potential for further research in this area which includes the study of higher homotopy groups and the applications of these constructions to other areas of mathematics.

Influence of outliers on QTL mapping for complex traits

A method was proposed for the detection of outliers and influential observations in the framework of a mixed linear model, prior to the quantitative trait locus (QTL) mapping analysis. We investigated the impact of outliers on QTL mapping for complex traits in a mouse BXD population, and observed that the dropping of outliers could provide the evidence of additional QTL and epistatic loci affecting the 1stBrain-OB and the 2ndBrain-OB in a cross of the abovementioned population. The results could also reveal a remarkable increase in estimating heritabilities of QTL in the absence of outliers. In addition, simulations were conducted to investigate the detection powers and false discovery rates (FDRs) of QTLs in the presence and absence of outliers. The results suggested that the presence of a small proportion of outliers could increase the FDR and hence decrease the detection power of QTLs. A drastic increase could be obtained in the estimates of standard errors for position, additive and additive× environment interaction effects of QTLs in the presence of outliers.

A Preliminary Study of Mapping Genes Underlying Complex Traits Based on Chromosome Segment Substitution Lines

Complex traits are the features whose properties are determined by multiple factors, which can be genetic or environmental. Most of economically important characteristics of plants and animals belong to this special catego-

Points of Coincidence and Common Fixed Points for Ⅱ-Expansive Mappings on Complex Valued Metric Spaces

Abstract. We use the two mappings satisfying II-expansive conditions on complex valued metric spaces to construct the convergent sequences and prove that the unique limit of the sequences is the point of coincidence or common fixed point of the two mappings. Also, we discuss the uniqueness of points of coincidence or common fixed points and give the existence theorems of unique fixed points. The obtained results generalize and improve the corresponding conclusions in references.

Logistic Mapping-Based Complex Network Modeling

In this paper, a new topological approach for studying an integer sequence constructed from Logistic mapping is proposed. By evenly segmenting [0,1]?into N non-overlapping subintervals which is marked as , representing the nodes identities, a network is constructed for analysis. Wherein the undirected edges symbolize their relation of adjacency in an integer sequence obtained from the Logistic mapping and the top integral function. By observation, we find that nodes’ degree changes with different values of??instead of the initial value—X0, and the degree distribution presents the characteristics of scale free network, presenting power law distribution. The results presented in this paper provide some insight into degree distribution of the network constructed from integer sequence that may help better understanding of the nature of Logistic mapping.

An improved Gmapping algorithm based map construction method for indoor mobile robot

With the rapid development in the service,medical,logistics and other industries,and the increasing demand for unmanned mobile devices,mobile robots with the ability of independent mapping,localization and navigation capabilities have become one of the research hotspots.An accurate map construction is a prerequisite for a mobile robot to achieve autonomous localization and navigation.However,the problems of blurring and missing the borders of obstacles and map boundaries are often faced in the Gmapping algorithm when constructing maps in complex indoor environments.In this pursuit,the present work proposes the development of an improved Gmapping algorithm based on the sparse pose adjustment(SPA)optimizations.The improved Gmapping algorithm is then applied to construct the map of a mobile robot based on single-line Lidar.Experiments show that the improved algorithm could build a more accurate and complete map,reduce the number of particles required for Gmapping,and lower the hardware requirements of the platform,thereby saving and minimizing the computing resources.

CONSTRUCTION OF PLURIHARMONIC MAPS INTO COMPLEX GRASSMANN MANIFOLDS

In this paper, some construction theorems of pluriharmonic maps into complex Grassmann manifolds axe obtained. By these, there exists a characterization of strongly isotropic pluriharmonic maps.

Virtual network mapping algorithm for large-scale network environment

A major challenge of network virtualization is the virtual network resource allocation problem that deals with efficient mapping of virtual nodes and virtual links onto the substrate network resources. However, the existing algorithms are almost concentrated on the randomly small-scale network topology, which is not suitable for practical large-scale network environments, because more time is spent on traversing SN and VN, resulting in VN requests congestion. To address this problem, virtual network mapping algorithm is proposed for large-scale network based on small-world characteristic of complex network and network coordinate system. Compared our algorithm with algorithm D-ViNE, experimental results show that our algorithm improves the overall performance.

A numerical study of coupled maps representing energy exchange processes between two environmental interfaces regarded as biophysical complex systems

The field of environmental sciences is abundant with various interfaces and is the right place for the application of new fundamental approaches leading towards a better understanding of environmental phenomena. Following the definition of environmental interface by Mihailovic and Bala? [1], such interface can be, for example, placed between: human or animal bodies and surrounding air, aquatic species and water and air around them, and natural or artificially built surfaces (vegetation, ice, snow, barren soil, water, urban communities) and the atmosphere, cells and surrounding environment, etc. Complex environmental interface systems are (i) open and hierarchically organised (ii) interactions between their constituent parts are nonlinear, and (iii) their interaction with the surrounding environment is noisy. These systems are therefore very sensitive to initial conditions, deterministic external perturbations and random fluctuations always present in nature. The study of noisy non-equilibrium processes is fundamental for modelling the dynamics of environmental interface regarded as biophysical complex system and for understanding the mechanisms of spatio-temporal pattern formation in contemporary environmental sciences. In this paper we will investigate an aspect of dynamics of energy flow based on the energy balance equation. The energy exchange between interacting environmen- tal interfaces regarded as biophysical complex systems can be represented by coupled maps. Therefore, we will numerically investigate coupled maps representing that exchange. In ana- lysis of behaviour of these maps we applied Lyapunov exponent and cross sample entropy.

Coupled maps serving the exchange processes on the environmental interfaces regarded as complex systems

We have defined the environmental interface through the exchange processes between media forming this interface. Considering the environmental interface as a complex system we elaborated the advanced mathematical tools for its modelling. We have suggested two coupled maps serving the exchange processes on the environmental interfaces spatially ranged from cellular to planetary level, i.e. 1) the map with diffusive coupling for energy exchange simulation and 2) the map with affinity, which is suitable for matter exchange processes at the cellular level. We have performed the dynamical analysis of the coupled maps using the Lyapunov exponent, cross sample as well as the permutation entropy in dependence on different map parameters. Finally, we discussed the map with affinity, which shows some features making it a promising toll in simulation of exchange processes on the environmental interface at the cellular level.

A novel image fusion algorithm based on 2D scale-mixing complex wavelet transform and Bayesian MAP estimation for multimodal medical images

In this paper,we propose a new image fusion algorithm based on two-dimensional Scale-Mixing Complex Wavelet Transform(2D-SMCWT).The fusion of the detail 2D-SMCWT cofficients is performed via a Bayesian Maximum a Posteriori(MAP)approach by considering a trivariate statistical model for the local neighboring of 2D-SMCWT coefficients.For the approx imation coefficients,a new fusion rule based on the Principal Component Analysis(PCA)is applied.We conduct several experiments using three different groups of multimodal medical images to evaluate the performance of the proposed method.The obt ained results prove the superiority of the proposed method over the state of the art fusion methods in terms of visual quality and several commonly used metrics.Robustness of the proposed method is further tested against different types of noise.The plots of fusion met rics establish the accuracy of the proposed fusion method.

Peak-to-average power ratio reduction using selective mapping with unequal power distribution

A new approach for peak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM) systems was proposed.This approach is based on assigning powers to the different subcarriers of OFDM using an unequal power distribution strategy.In addition,a reduced complexity selective mapping (RC-SLM) scheme was proposed.The proposed scheme is based on partitioning the frequency domain symbol sequence into several sub-blocks,and then each sub-block is multiplied by different phase sequences whose length is shorter than that used in the conventional SLM scheme.Then,a kind of low complexity conversions is used to replace the IFFT blocks.The performance of the proposed RC-SLM scheme along with the new approach was studied with computer simulation.The obtained results show that the proposed RC-SLM scheme is able to achieve the lowest computational complexity when compared with other low complexity schemes proposed in the literature while at the same time improves the PAPR reduction performance by about 0.3 dB.

复谱映射下融合高效Transformer的语音增强方法

针对卷积神经网络(Convolutional Neural Network,CNN)过去在语音增强中表现优异但对全局特征捕获不足,以及Transformer近年展现出长序列间依赖优势但又存在局部细节特征丢失、参数量大等问题,该文为了充分利用CNN与Transformer的优势并弥补各自不足,提出了一种在复频谱映射下的新型卷积模块与高效Transformer融合的单通道语音增强网络。该网络由编码层、传输层与双分支解码层组成:在编解码部分设计了一种协作学习模块(Collaborative Learning Block,CLB)来监督交互信息,在减少参数量的同时提高主干网络对复特征的获取能力;传输层中则提出一种时频空间注意Transformer模块分别对语音子频带和全频带信息建模,充分利用声学特性来模拟局部频谱模式并捕获谐波间依赖关系。将该模块进一步与通道注意分支相结合,设计了一种可学习的双分支注意融合(Dual-branch Attention Fusion,DAF)机制,从空间-通道角度提取上下文特征以加强信息的多维度传输;最后,在此基础上搭建一种高斯加权渐进网络作为中间传输层,通过堆叠DAF模块进行加权求和后输出以充分利用深层特征,使得解码过程更具鲁棒性。分别在英文VoiceBank-DEMAND数据集、中文THCHS30语料库与115种环境噪声下进行消融以及综合对比实验,结果表明,该文方法仅以最小0.68×10^(6)的参数量,相比于大部分最新相关网络模型取得了更优的主、客观指标,具有较为突出的增强性能与泛化能力。

复杂环境下基于自适应极线约束的AGV视觉SLAM算法

针对传统视觉同步定位与地图构建(SLAM)算法不能有效处理复杂环境中的动态及潜在动态目标而影响定位与建图性能的问题,提出一种基于Mask R-CNN神经网络以及ORB-SLAM3算法改进的视觉SLAM方法。针对动态目标,提出一种基于语义信息的运动一致性检验算法,使用自适应阈值的极线约束方法实现图像中动态特征点的精确剔除;针对潜在动态目标,提出一种改进的长期数据关联方法,通过增大关键帧选取密度及优化关键帧中的潜在动态目标信息,对算法的回环优化和地图融合过程进行改进,提高回环优化效果与地图复用性。在TUM数据集和真实场景中进行验证,实验结果表明与ORB-SLAM3算法相比,采用TUM数据集在低动态场景和高动态场景中的绝对轨迹均方根误差分别减小8.5%和65.6%;在真实场景下测试,所提算法的定位精度提高了62.5%。

非圆形隧洞衬砌支护下应力与位移的新解法

以往在利用平面弹性复变函数方法进行衬砌支护作用下非圆形隧洞的力学分析时,一般将洞室外域保角映射到象平面的单位圆外域,并认为可以利用同一个映射函数将衬砌截面映射到象平面的圆环域内。当衬砌厚度很薄时,这种方法是可行的,而当衬砌相对较厚时,利用同一映射函数所得到的衬砌截面形状发生严重失真。为解决此问题,本文引入两套映射函数,分别将洞室外域映射到象平面的单位圆的圆外域,衬砌截面映射到圆环域。这种方法可以适应于不同的衬砌厚度,利用这种方式获得的衬砌截面,在衬砌较厚时仍能保证衬砌厚度相对均匀。在求解解析函数过程中不再采用传统的幂级数解法,而是使用边界配点法,将两套映射函数结合,获得了该问题的应力解和位移解。本文以马蹄形隧洞为例,求解结果与ANSYS软件所得数值解吻合很好,分析了衬砌厚度对隧洞应力和位移的影响。根据本文解答可以方便、快捷地进行相近条件下隧道的初步设计。

照护图在医疗复杂性儿童家庭中的应用进展

照护图是医疗保健提供者帮助家庭确定护理协调需求的工具,其积极意义在于促进医疗复杂性儿童家庭中心共享护理、提升其出院准备度和育儿胜任感水平、衡量家庭的经济成本效益。本文介绍了照护图的起源与发展、与其他护理工具的区别、评估工具,阐述照护图的实施过程及在医疗复杂性儿童家庭中的应用效果,以期为相关研究及临床实践提供参考。