锥阀稳态液动力及阀芯表面压力分布数值模拟

基于Fluent流场仿真软件,对锥阀外流和内流情况下阀芯所受稳态液动力及阀芯表面压力分布进行了数值模拟和分析。结果表明,稳态液动力随着阀口压差的增大而增加;当阀口压差大于2.5MPa时,阀芯表面出现负压,阀口处发生气蚀;当阀口开度为1mm时,稳态液动力最大;在其他条件相同的情况下,锥阀内流时的液动力小于锥阀外流时的液动力。     

多分支水平井技术提高煤层透气性机理分析及数值模拟

本文研究了煤层瓦斯解吸-扩散-渗流的运移规律;分析了多分支水平井技术的增透机理：增大瓦斯解吸影响面积,沟通煤层裂隙并促进裂隙发育,降低瓦斯流动阻力。以山西晋城煤层气田为例,通过分支井产量模型研究分析得出分支数目和分支段长对产能的影响关系：分支井数目越大,抽采效果越好;分支井长度越长,抽采效果越好。     

基于磁性微泡对比剂的超声和磁共振影像融合算法

文中提出了一种新的基于磁性微泡对比剂的超声影像和磁共振影像之间的融合算法．首先利用磁性微泡对比剂对体模进行超声和磁共振显影,并对显影进行边缘分割．运用非采样contourlet变换（nonsubsampled contourlet transform．NSCT）对源图像进行分解,然后对低频子带系数采用自适应动态加权非负矩阵分解（dynamic weighted non-negative matrix factorization．DWNMF）结合分割图像进行融合．然后对各带通方向子带系数采用空间频率激励的脉冲耦合神经网络进行融合,最后利用NSCT逆变换得到融合图像．研究结果表明,利用磁性微泡对比剂并结合上述算法对超声影像和磁共振影像进行融合,可以获得预期的融合效果．     

有机/无机杂化材料与多功能纤维研究进展

有机/无机杂化材料能够实现有机高分子材料与无机材料在纳米或分子水平上的复合,在发挥各自组分特性的同时,体现出特有的协同效应,如新性能、多功能.该原理同样适用于有机/有机杂化体系.随着产业用纤维材料的不断发展,其应用领域也随之拓展,开发新型高分子材料,实现纤维的多功能化成为研究热点.根据纤维多功能化的发展需求,结合有机/无机杂化机理,在分子水平上设计构筑杂化功能材料,采用结构设计、界面构筑的方法建立杂化功能材料与成纤高聚物杂化体系.以成纤高分子的结构设计及凝聚态控制、纳米纤维和低维纳米材料的结构可控制备及其功能化复合为例,简要介绍了有机/无机杂化原理在纤维多功能化方面的研究进展,最后提出了多功能化有机/无机杂化纤维的展望.     

A mixed-model approach for genome-wide association studies of correlated traits in structured populations

Genome-wide association studies (GWAS) are a standard approach for studying the genetics of natural variation. A major concern in GWAS is the need to account for the complicated dependence structure of the data, both between loci as well as between individuals. Mixed models have emerged as a general and flexible approach for correcting for population structure in GWAS. Here, we extend this linear mixed-model approach to carry out GWAS of correlated phenotypes, deriving a fully parameterized multi-trait mixed model (MTMM) that considers both the within-trait and between-trait variance components simultaneously for multiple traits. We apply this to data from a human cohort for correlated blood lipid traits from the Northern Finland Birth Cohort 1966 and show greatly increased power to detect pleiotropic loci that affect more than one blood lipid trait. We also apply this approach to an Arabidopsis thaliana data set for flowering measurements in two different locations, identifying loci whose effect depends on the environment.     

An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations

Population structure causes genome-wide linkage disequilibrium between unlinked loci, leading to statistical confounding in genome-wide association studies. Mixed models have been shown to handle the confounding effects of a diffuse background of large numbers of loci of small effect well, but they do not always account for loci of larger effect. Here we propose a multi-locus mixed model as a general method for mapping complex traits in structured populations. Simulations suggest that our method outperforms existing methods in terms of power as well as false discovery rate. We apply our method to human and Arabidopsis thaliana data, identifying new associations and evidence for allelic heterogeneity. We also show how a priori knowledge from an A. thaliana linkage mapping study can be integrated into our method using a Bayesian approach. Our implementation is computationally efficient, making the analysis of large data sets (n > 10,000) practicable.     

基于耳蜗图多示例分析的音频场景分类模型

音频场景分类(Acoustic Scene Classification, ASC)是计算听觉场景领域最具挑战的任务之一。传统的ASC模型大多采用基于线性频率分析的手工特征加基于深度学习的分类模型方法。然而,一方面,由于基于线性频率分析的特征提取方法无法模拟人耳基底膜的非线性频率选择特性,从而造成特征分辨率低下的问题;另一方面,现有的分类模型无法解决由于音源复杂且音频事件高度重叠所造成的分类准确率低下的问题。为了解决以上问题,提出了基于耳蜗图多示例分析的音频场景分类模型,一方面采用中心频率按照等效带宽均匀分布的余弦滤波器组对信号频谱进行滤波以模拟人耳听觉感知特性;另一方面,通过引入多示例学习刻画整个数据结构的特点以提高分类准确率。此外,为了抵抗音频事件的频移影响,在多示例学习分类模型的分类预测整合器中采用平均池化方法。在DCASE 2018和DCASE 2019竞赛所提供的Task1a数据集上的实验结果表明,本文提出的模型比DCASE 2018竞赛所提供的基线系统以及传统的基于Log Mel特征提取和多示例学习的模型实现了更高的分类准确率,同时也验证了平均池化要优于最大池化。