Formation of low surface energy separators with undercut structures via a full-solution process and its application in inkjet printed matrix of polymer light-emitting diodes

In this paper, low surface energy separators With undercut structures were fabricated through a full solution process, These low Surface energy separators are more suitable for application in inkjet printed passive-matrix displays of polymer light-emitting diodes. A patterned PS film was formed on the P4VP/photoresist film by microtransfer printing firstly. Patterned Au-coated Ni film was formed on the uncovered P4VP/photoresist film by electroless deposition. This metal film was used as mask to pattern the photoresist layer and form undercut structures with the patterned photoresist layer. The surface energy of the metal film also decreased dramatically from 84.6 mj/m(2) to 21.1 mJ/m(2) by modification of fluorinated mercaptan self-assemble monolayer on Au surface. The low surface energy separators were used to confine the flow of inkjet printed PFO solution and improve the patterning resolution of inkjet printing successfully. Separated PFO stripes, complement with the pattern of the separators, formed through inkjet printing.

Undercut structures fabricated by microtransfer printing combined with UV exposure and their applications

In this paper. the undercut structures were fabricated by microtransfer printing of metal films on the surface of photoresist combined with UV exposure and photoresist film developing. The patterned metal films were used as mask to realize the selective UV exposure of photoresist Firstly. The undercut structures. which consist of the top metal films and the patterned bottom photoresist, formed in the subsequent developing process because of the lateral dissolving of photoresist at the edge of the unexposed regions. The method proposed in this paper has wider tolerance to the changing of the patterning parameters. but, without effect on patterning resolution since the metal film was used as the top layer. The undercut Structures were Used as separators to pattern passive-matrix display of organic light-emitting diodes (OLEDs). No visible difference of the device performance was observed Compared with the OLEDs patterned by the shadow mask.

Effects of forage composition and growing season on methane emission from sheep in the Inner Mongolia steppe of China

Understanding the effects of dietary composition on methane (CH4) production of sheep can help us to understand grassland degradation resulting in an increase of CH4 emission from ruminant livestock and its resulting significance affecting CH4 source/sink in the grazing ecosystem. The objective of this study was to investigate the effect of forage composition in the diet of sheep in July and August on CH4 production by sheep in the Inner Mongolia steppe. The four diet treatments were: (1) Leymus chinensis and Cleistogenes squarrosa (LC), (2) Leymus chinensis, Cleistogenes squarrosa and concentrate supplementation (LCC), (3) Artemisia frigida and Cleistogenes squarrosa (AC), and (4) Artemisia frigida, Cleistogenes squarrosa and concentrate supplementation (ACC). CH4 production was significantly lower in July than in August (31.4 and 36.2 g per sheep-unit per day, respectively). The daily average CH4 production per unit of digestive dry matter (DM), organic matter (OM) and neutral detergent fiber (NDF) increased by 10.9, 11.2 and 42.1% for the AC diet compared with the LC diet, respectively. Although concentrate supplementation in both the AC and LC diets increased total CH4 production per sheep per day, it improved sheep productivity and decreased CH4 production by 14.8, 12.5 and 14.8% per unit of DM, OM and NDF digested by the sheep, respectively. Our results suggested that in degraded grassland CH4 emission from sheep was increased and concentrate supplementation increased diet use efficiency. Sheep-grazing ecosystem seems to be a source of CH4 when the stocking rate is over 0.5 sheep-units ha(-1) during the growing season in the Inner Mongolia steppe.

混合模式识别系统研究

讨论基于多种分类方法的模块组合实现的混合模式识别系统，它不同于利用多分类器输出结果表决的集成系统．提出两个系统：一个面向印刷体汉字文本识别，另一个面向自由手写体数字识别．利用多种特征和多种分类方法的组合、部分识别信息控制混淆字判别策略以及提出的动态模板库匹配后处理方法，使系统的性能与传统单一分类器系统比较，获得明显改善．实验表明：多方法多策略混合是解决复杂和增强系统鲁棒性的一条途径

图象噪声的模糊聚类平滑方法

模糊C-means算法在聚类分析中已得到了成功的应用,本文提出一种利用模糊C-means算法消除噪声的新方法。一般来说,图象中的噪声点就是其灰度值与其周围象素的灰度值之差超过某个门限值的点。根据这个事实,首先利用模糊C-means算法分类,再利用标准核函数检测出噪声点,然后将噪声点去掉。由于只修改噪声点处的象素灰度值,而对于其它象素的灰度值不予改变,所以本算法能够很好地保护细节和边缘。本方法每次处理3×3个点,而以往的方法只能每次处理一个点,所以本方法能提高运算速度。文中给出了利用本方法对实际图象处理的结果,并与梯度倒数权值法进行了定量的比较。

基于Zernike正交矩的图像亚像素边缘检测算法改进

介绍了Zernike矩及基于Zernike矩的图像亚像素边缘检测原理,针对Ghosal提出的基于Zernike矩的亚像素图像边缘检测算法检测出的图像存在边缘较粗及边缘亚像素定位精度低等不足,提出了一种改进算法.推导了7×7 Zernike矩模板系数,提出一种新的边缘判断依据.改进的算法能较好检测图像边缘并实现了较高的边缘定位.最后,设计了3组不同的实验.实验结果同Canny算子及Ghosal算法相比,证明了改进算法的优越性.

表面相关多次波衰减方法与应用研究

The function of seismic data in prospecting and exploring oil and gas has exceeded ascertaining structural configuration early. In order to determine the advantageous target area more exactly, we need exactly image the subsurface media. So prestack migration imaging especially prestack depth migration has been used increasingly widely. Currently, seismic migration imaging methods are mainly based on primary energy and most of migration methods use one-way wave equation. Multiple will mask primary and sometimes will be regarded as primary and interferes with the imaging of primary, so multiple elimination is still a very important research subject. At present there are three different wavefield prediction and subtraction methods: wavefield extrapolation; feedback loop; and inverse-scattering series. I mainly do research on feedback loop method in this paper. Feedback loop method includs prediction and subtraction.Currently this method has some problems as follows. Firstly, feedback loop method requires the seismic data used to predict multiple is full wavefield data, but usually the original seismic data don’t meet this assumption, so seismic data must be regularized. Secondly, Multiple predicted through feedback loop method usually can’t match the real multiple in seismic data and they are different in amplitude, phase and arrrival time. So we need match the predicted multiple and that in seismic data through estimating filtering factors and subtract multiple from seismic data. It is the key for multiple elimination how to select a correct matching filtering method. There are many matching filtering methods and I put emphasis on Least-square adaptive matching filtering and L1-norm minimizing adaptive matching filtering methods. Least-square adaptive matching filtering method is computationally very fast, but it has two assumptions: the signal has minimum energy and is orthogonal to the noise. When seismic data don’t meet the two assumptions, this method can’t get good matching results and then can’t attenuate multiple correctly. L1-norm adaptive matching filtering methods can avoid these two assumptions and then get good matching results, but this method is computationally a little slow. The results of my research are as follows: 1. Proposed a method that interpolates seismic traces based on F-K migration and demigration. The main advantage of this method is that it can interpolate seismic traces in any offsets. It shows this method is valid through a simple model. 2. Comparing different Least-square adaptive matching filtering methods. The results show that equipose multi-channel adaptive matching filtering methods can get better results of multiple elimination than other matcing methods through three model data and two field data. 3. Proposed equipose multi-channel L1-norm adaptive matching filtering method. Because L1-norm is robust to large amplitude differences, there are no assumption on the signal has minimum energy and orthogonality, this method can get better results of multiple elimination. 4. Research on multiple elimination in inverse data space. The method is a new multiple elimination method and it is different from those methods mentioned above.The advantages of this method is that it is simple in theory and no need for the adaptive subtraction and computationally very fast. The disadvantage of this method is that it is not stabilized in its solution. The results show that equipose multi-channel and equipose pesudo-multi-channel least-square matching filtering and equipose multi-channel and equipose pesudo-multi-channel L1-norm matching filtering methods can get better results of multiple elimination than other matcing methods through three model data and many field data.

颜色在自然场景知觉中的作用

Color has an unresolved role in the rapid process of natural scene. The temporal changes of the color effect might partly account for the debates. Besides, the distinction of localized and unlocalized information has not been addressed directly in these color studies. Here we present two experiments that investigate whether color contributes to categorization in a briefly flashed natural image and also whether it is mediated by time and low-level information. By controlling the interval between target and mask stimuli, Experiment 1 tested the hypothesis that colors could facilitate in the early stage of scene perception and the effect would decay in later processing. Experiment 2 examined how the randomization of local phase information influenced the color’s advantage over gray. Together, the results suggest that color does enhance natural scene categorization at short exposure time. Furthermore, results imply that effect of color is stable between 12 and120ms, and is not accounted by showing the structures organized by localized information. Therefore，we concluded that color always make effect in the process of rapid scene categorization, and do not depend on localized information. Thus, the present study is an attempt to fill the gap in previous research; its results is an contribution to deeper understanding of the role of color in natural scene perception.