An fMRI study of magnitude comparison and exact addition in children

By contrast to the adult literature, in which a consistent parietofrontal network for number processing has been identified, the data from studies of number processing in children have been less consistent, probably due to differences in study design and control conditions. Number processing was examined using functional magnetic resonance imaging in 18 right-handed children (8–12 years) from the Cape Coloured community in Cape Town, South Africa, using Proximity Judgment and Exact Addition (EA) tasks. The findings were consistent with the hypothesis that, as in adults, the anterior horizontal intraparietal sulcus (HIPS) plays a major role in the representation and manipulation of quantity in children. The posterior medial frontal cortex, believed to be involved in performance monitoring in more complex arithmetic manipulations in adults, was extensively activated even for relatively simple symbolic number processing in the children. Other areas activated to a greater degree in the children included the left precentral sulcus, which may mediate number knowledge and, for EA, the head of the caudate nucleus, which is part of a fronto-subcortical circuit involved in the behavioral execution of sequences. Two regions that have been linked to number processing in adults — the angular gyrus and posterior superior parietal lobule — were not activated in the children. The data are consistent with the inference that although the functional specialization of the anterior HIPS may increase as symbolic number processing becomes increasingly automatic, this region and other elements of the parietofrontal network identified in adults are already reliably and robustly activated by middle childhood.     

A new domain decomposition method with overlapping patches for ultrascale simulations: Application to biological flows

We address the failure in scalability of large-scale parallel simulations that are based on (semi-)implicit time-stepping and hence on the solution of linear systems on thousands of processors. We develop a general algorithmic framework based on domain decomposition that removes the scalability limitations and leads to optimal allocation of available computational resources. It is a non-intrusive approach as it does not require modification of existing codes. Specifically, we present here a two-stage domain decomposition method for the Navier–Stokes equations that combines features of discontinuous and continuous Galerkin formulations. At the first stage the domain is subdivided into overlapping patches and within each patch a C⁰ spectral element discretization (second stage) is employed. Solution within each patch is obtained separately by applying an efficient parallel solver. Proper inter-patch boundary conditions are developed to provide solution continuity, while a Multilevel Communicating Interface (MCI) is developed to provide efficient communication between the non-overlapping groups of processors of each patch. The overall strong scaling of the method depends on the number of patches and on the scalability of the standard solver within each patch. This dual path to scalability provides great flexibility in balancing accuracy with parallel efficiency. The accuracy of the method has been evaluated in solutions of steady and unsteady 3D flow problems including blood flow in the human intracranial arterial tree. Benchmarks on BlueGene/P, CRAY XT5 and Sun Constellation Linux Cluster have demonstrated good performance on up to 96,000 cores, solving up to 8.21B degrees of freedom in unsteady flow problem. The proposed method is general and can be potentially used with other discretization methods or in other applications.     

Directed transport and complex dynamics of vortices in a Josephson junction network driven by modulated currents

Directed transport of vortices in a Josephson junction network (JJN) with structural disorder is studied using a numerical simulation. Using spatiotemporal modulation of driving currents, the directed transport of vortices occurs even in the presence of disorder under certain conditions. From the analyses of the current–voltage and local voltage characteristics, it is found that the collective motion of vortices has an importance for the occurrence of directed transport.     

视觉模式识别网络及光电实现

在形态学网络及改进的Ｈａｍｍｉｎｇ网络基础上，提出视觉模式识别网络及训练算法，形态学网络作为特征提取网络，具有相对图像平移和尺度不变的特性，改进的Ｈａｍｍｉｎｇ网络加速完成特征矢量的分类操作。经过学习的视觉模式识别网络，可完成图像特征的提取，实现相对于图像平移和尺度不变的模式识别，在此基础上，建立了光电视觉模式识别体系，从而实现实时模式识别。     

在BES实验中用神经元网络法鉴别e,μ,π

研究了两种不同的神经元网络法,BP网络和LVQ网络,对北京谱仪(BES)实验中e,μ,π粒子的鉴别,取得了较常规方法要好的结果.用于训练和检验的μ子样本来自宇宙线事例,e和π粒子则是由真实实验数据精选的,虽然样本本身具有非均匀的动量谱,但BP网络的检验结果给出的粒子选择效率在整个动量区间却仍然具有相当均匀的分布,LVQ网络稍逊之.至少是在我们研究的这一课题中证明了BP网络的模式识别功能要优于LVQ网络.     

基于匹配网络若干问题的推论

深入分析了匹配网络中存在的基本问题，并归纳出６个推论。     

人工神经网络法校正ICP┐AES中重叠光谱干扰

本文将反向传播人工神经网络（ＢＰ－ＡＮＮ）用于ＩＣＰ－ＡＥＳ中重叠光谱干扰的校正。利用模拟的Ｃｅ４１３．３８０ｎｍ和Ｐｒ４１３．３６１ｎｍ光谱对神经网络的训练方式、输入值范围、噪声影响等作了较详细的讨论。     

Pattern recognition system for the discrimination of multiple sclerosis from cerebral microangiopathy lesions based on texture analysis of magnetic resonance images

In this study, a pattern recognition system has been developed for the discrimination of multiple sclerosis (MS) from cerebral microangiopathy (CM) lesions based on computer-assisted texture analysis of magnetic resonance images. Twenty-three textural features were calculated from MS and CM regions of interest, delineated by experienced radiologists on fluid attenuated inversion recovery images and obtained from 11 patients diagnosed with clinically definite MS and from 18 patients diagnosed with clinically definite CM. The probabilistic neural network classifier was used to construct the proposed pattern recognition system and the generalization of the system to unseen data was evaluated using an external cross validation process. According to the findings of the present study, statistically significant differences exist in the values of the textural features between CM and MS: MS regions were darker, of higher contrast, less homogeneous and rougher as compared to CM.     

调度自动化机房网络配线管理软件设计与实现

针对公司调度自动化机房网络配线无图纸管理和标签标识不规范的情况,自主研发了一套机房网络配线管理软件。首先,分析了配线可视化管理软件应对网络配线绘图和标签信息自动生成的功能需求,并运用MVC模式理论进行软件架构设计;其次,重点阐述了基于QT图形库的关键功能实现,包括核心图元类的构建、元件库组件可配置生成、图形序列化反序列操作、拓扑查找、设备图元属性管理及标签信息自动生成功能等;最后,通过举例说明该软件在实际机房管理中的使用方法和应用成效。应用结果表明,通过绘制整个机房的网络连接图并录入相关设备属性信息,有助于提高机房网络故障的诊断效率和降低机房系统的运维风险。     

Photonic band structures of quadrangular multiconnected networks

By means of the network equation and generalized dimensionless Floquet-Bloch theorem,this paper investigates the properties of the band number and width for quadrangular multiconnected networks (QMNs) with a different number of connected waveguide segments (NCWSs) and various matching ratio of waveguide length (MRWL).It is found that all photonic bands are wide bands when the MRWL is integer.If the integer attribute of MRWL is broken,narrow bands will be created from the wide band near the centre of band structure.For two-segment-connected networks and three-segment-connected networks,it obtains a series of formulae of the band number and width.On the other hand,it proposes a so-called concept of two-segment-connected quantum subsystem and uses it to discuss the complexity of the band structures of QMNs.Based on these formulae,one can dominate the number,width and position of photonic bands within designed frequencies by adjusting the NCWS and MRWL.There would be potential applications for designing optical switches,optical narrow-band filters,dense wavelength-division-multiplexing devices and other correlative waveguide network devices.