Plant Copper Amine Oxidases: Key Players in Hormone Signaling Leading to Stress-Induced Phenotypic Plasticity

Polyamines are ubiquitous, low-molecular-weight aliphatic compounds, present in living organisms and essential for cell growth and differentiation. Copper amine oxidases (CuAOs) oxidize polyamines to aminoaldehydes releasing ammonium and hydrogen peroxide, which participates in the complex network of reactive oxygen species acting as signaling molecules involved in responses to biotic and abiotic stresses. CuAOs have been identified and characterized in different plant species, but the most extensive study on a CuAO gene family has been carried out in Arabidopsis thaliana. Growing attention has been devoted in the last years to the investigation of the CuAO expression pattern during development and in response to an array of stress and stress-related hormones, events in which recent studies have highlighted CuAOs to play a key role by modulation of a multilevel phenotypic plasticity expression. In this review, the attention will be focused on the involvement of different AtCuAOs in the IAA/JA/ABA signal transduction pathways which mediate stress-induced phenotypic plasticity events.     

Display illumination with modulated directional backlight

Illumination is essential for modern life as colorful world is perceived by human visionary system. Display technology has been developing rapidly in recent decades, and the basic principle is related to the way that the image is illuminated and light is emanated. Traditional illumination is provided by different types of light sources, and the display image is visible in large viewing space until the emanating light decays to zero. This work proposes and demonstrates a novel illumination scheme for a display in which the displaying images are visible only in specific spatial regions. The directional backlight ensures the image propagating to specific direction while imaging visibility can be controlled to terminate abruptly at certain distance from the display screen while exerting no influence to nearby regions. The working principle for such an illumination scheme is the use of the modulated coherent directional backlight through an axicon lens. It is shown that the illumination scheme can robustly deliver carried image information to the designated viewing region. This new illumination scheme has many advantages over conventional illumination, including its usage for personal display, very lower energy consumption, as well as minimizing light hazard pollution.     

On optical flow techniques applied to breaking surges

Surface wave breaking is a challenging two-phase flow process which plays an important role in numerous physical processes. A highly-turbulent unsteady breaking surge was investigated experimentally in a large facility, and substantial aeration occurred in the roller. The application of three optical flow techniques (Lucas-Kanade, Horn-Schunck and Farnback) to the air-water region was tested. The results indicated that the Farnback technique provided most accurate results, although some misleading results could be obtained near the air-water boundaries of the roller. The bore generation by a rapid gate closure showed a highly-unsteady complicated velocity field, with substantial free-surface deformations, wave breaking and formation of large coherent structures before the surge detached from the gate. Further upstream, the surge propagated as a hydraulic jump in translation and the data showed a marked shear region with a recirculation zone above, showing air-water flow features comparable to stationary hydraulic jumps. The upper and lower bounds of air-water flow region yielded data implying an air-to-water velocity ratio about 4–5 for a Froude number Fr₁ = 2.1.     

多先验融合的图像显著性目标检测算法

为了更加准确地检测出图像中的显著性目标，提出了多先验融合的显著性目标检测算法。针对传统中心先验对偏离图像中心的显著性目标会出现检测失效的情况，提出在多颜色空间下求显著性目标的最小凸包交集来确定目标的大致位置，以凸包区域中心计算中心先验。同时通过融合策略将凸包区域中心先验、颜色对比先验和背景先验融合并集成到特征矩阵中。最后通过低秩矩阵恢复模型生成结果显著图。在公开数据集MSRA1000和ESSCD上的仿真实验结果表明，MPLRR能够得到清晰高亮的显著性目标视觉效果图，同时F，AUC，MAE等评价指标也比现有的许多方法有明显提升。     

THE effect of Srandom DOPANT fluctuation on threshold voltage and drain current variation in junctionless nanotransistors

We investigate the effect of dopant random fluctuation on threshold voltage and drain current variation in a two-gate nanoscale transistor. We used a quantum-corrected technology computer aided design simulation to run the simulation (10000 randomizations). With this simulation, we could study the effects of varying the dimensions (length and width), and thicknesses of oxide and dopant factors of a transistor on the threshold voltage and drain current in subthreshold region (off) and overthreshold (on). It was found that in the subthreshold region the variability of the drain current and threshold voltage is relatively fixed while in the overthreshold region the variability of the threshold voltage and drain current decreases remarkably, despite the slight reduction of gate voltage diffusion (compared with that of the subthreshold). These results have been interpreted by using previously reported models for threshold current variability, load displacement, and simple analytical calculations. Scaling analysis shows that the variability of the characteristics of this semiconductor increases as the effects of the short channel increases. Therefore, with a slight increase of length and a reduction of width, oxide thickness, and dopant factor, we could correct the effect of the short channel.     

Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time series

This article proposes new bootstrap procedures for detecting multiple persistence shifts in a time series driven by non-stationary volatility. The assumed volatility process can accommodate discrete breaks, smooth transition variation as well as trending volatility. We develop wild bootstrap sup-Wald tests of the null hypothesis that the process is either stationary [I(0)] or has a unit root [I(1)] throughout the sample. We also propose a sequential procedure to estimate the number of persistence breaks based on ordering the regime-specific bootstrap p-values. The asymptotic validity of the advocated procedures is established both under the null of stability and a variety of persistence change alternatives. A comparison with existing tests that assume homoskedasticity illustrates the finite sample improvements offered by our methods. An application to OECD inflation rates highlights the empirical relevance of the proposed approach and weakens the case for persistence change relative to existing procedures.     

面部运动单元检测研究综述

面部运动单元检测旨在让计算机从给定的人脸图像或视频中自动检测需要关注的运动单元目标。经过二十多年的研究，尤其是近年来越来越多的面部运动单元数据库的建立和深度学习的兴起，面部运动单元检测技术发展迅速。首先，阐述了面部运动单元的基本概念，介绍了已有的常用面部运动单元检测数据库，概括了包括预处理、特征提取、分类器学习等步骤在内的传统检测方法；然后针对区域学习、面部运动单元关联学习、弱监督学习等几个关键研究方向进行了系统性的回顾梳理与分析；最后讨论了目前面部运动单元检测研究存在的不足以及未来潜在的发展方向。     

菌型叶根动叶片叶根叶冠内径向的加工

菌型叶根动叶片是一种新型的动叶片,采用数控铣加工叶根内径向面时留0.1~0.2mm余量,然后在进行叶根内径向磨削,叶冠直接加工到位,没有后序磨削加工,由于叶根叶冠在加工过程中不是一次装夹完成的,根冠存在一定的落差,在后续的装配中容易产生配合间隙,无法达到要求。文中介绍了一种新的加工工艺,解决了这一问题。     

改进HSR-FCN的服装图像识别分类算法研究

目前网络上的服装图像数量增长迅猛，对于大量服装图像实现智能分类的需求日益增加。将基于区域的全卷积网络（Region-Based Fully Convolutional Networks，R-FCN）引入到服装图像识别中，针对服装图像分类中网络训练时间长、形变服装图像识别率低的问题，提出一种新颖的改进框架HSR-FCN。新框架将R-FCN中的区域建议网络和HyperNet网络相融合，改变图片特征学习方式，使得HSR-FCN可以在更短的训练时间内达到更高的准确率。在模型中引入了空间转换网络，对输入服装图像和特征图进行了空间变换及对齐，加强了对多角度服装和形变服装的特征学习。实验结果表明，改进后的HSR-FCN模型有效地加强了对形变服装图像的学习，且在训练时间更短的情况下，比原来的网络模型R-FCN平均准确率提高了大约3个百分点，达到96.69%。