超高温高压液动截止阀阀座红套结构

介绍了一种名为红套阀座组的新型阀座结构，该结构适用于运行在超高温、高压以及特殊工况截止阀的研发与制造。根据阀座红套结构的研发背景，阐述了红套阀座组的特点、红套装配过盈量与加热温度的确定方法，最后通过有限元分析与压力试验对红套阀座组的设计效果进行验证。     

一抹热情的“中国红”

中国红是三原色中的大红，又名“绛色”。中国红是中国人的魂，尚红习俗的演变，记载着中国人的心路历程。经过世代承启、沉淀、深化和扬弃，传统精髓逐渐嬗变为中国文化的底色。中国红，象征着热忱、奋进、团结的民族品格。因此，西方也把这种红称为“China Red”。     

黄继雄：另类CIO

条纹T恤、牛仔裤，双肩包。如果不是工作人员介绍，记者还以为眼前这个阳光大男孩走错了门。他就是红蜻蜒集团的CIO黄继雄，这位貌似“80后”的年轻人已经在红蜻蜒集团奋斗了十年，把红蜻蜒集团信息化部门从最早他一个人孤军奋战带领至今已经发展为46人的IT大团队。     

猪附红细胞体病的防治

阐述了猪附红细胞体病这种由猪附红细胞体引起的人畜共患的传染病的主要特征是贫血、黄疸、高热、皮肤发红等。根据过去山西部分县发病流行情况调查和防治实践经验，提出对猪附红细胞体病的预防和治疗措施。     

RGB颜色格雷码结构光三维测量技术研究

提出一种基于RGB颜色格雷码的结构光编码方法。该方法是将红、蓝条纹按二进制格雷码编码方式进行编排，并在红、蓝条纹之间用一个像素的绿条纹作为分界。由于投射光强相同，基于CCD的摄像机拍得的条纹图像中绿条纹向红、蓝区域扩散程度等同，提取绿条纹的中心即可获得条纹的准确定位，再依据三角法原理实现三维物体测量。文中具体介绍了该方法的编码、解码原理，分析了基于HSI空间的彩色图像分割方法，给出了基于3dsMAX和MATLAB环境下的重构仿真实验结果。     

超超临界机组高压筒形缸结构高温蠕变研究

对东方汽轮机超超临界135 MW等级一次再热机组高压筒形缸的高温蠕变特性进行了研究，利用ABAQUS软件建立了三维有限元模型，进行了稳态温度场、应力场和20万h蠕变等效应力、应变计算，分析了汽缸、红套环的蠕变强度，以及紧固件蠕变松弛对结构密封性的影响。结果表明：稳态工况下，红套环样式的筒形缸整体应力水平低于材料工作温度下的屈服强度；20万h缸体关键位置的蠕变强度合格；高温蠕变引起红套环紧力下降，10万h内汽缸中分面密封性满足设计要求。     

望远镜红膜物镜色度设计与检验初探

在红膜的设计与镀制过程中，由于影响薄膜的因素较多，因而实际镀制的红膜其反射颜色是不一致的，造成了红膜标准的多样性。为此本文将从色度计量方面给出设计的具体要求，即从光谱特性曲线计算红膜物镜的透射色度和反射色度；ＸＹＺ表色系统的色度座标值（Ｘ、Ｙ、Ｚ）及其取值范围，色饱和度的大小，检验时的光路、光源等。     

我国百万千瓦级核岛主设备制造完全实现国产化

由中国第一重型机械集闭公司承制的我同首台完全自主开发的红沿河核电站1号机组核反应堆压力容器，12月18日完工并发往辽宁红沿河。经检测，设备的各项技术指标全部满足要求，标志着我国百万干瓦级核岛主设备的制造完全实观同产化，具备了为我国核电建设标准化、批量化、规模化发展提供成套装备的能力。     

连铸坯的红送

重点介绍了太钢连铸坯红送实施过程中的重要工艺环节、技术及装备，并通过实施后的效果来说明连铸坯红送是一项重要的节能降耗、增产增效工程。     

山坡地红芪的栽培方法研究

首先简要阐明了红芪的种植条件,然后说明了山坡地红芪栽培的现状,目前红芪的栽培方法没有得到具体落实,使得红芪的质量逐渐下降,不利于其有效生长,最后围绕着选择合理的种植区域、完善作床及搭棚工序、加强红芪种子的处理、选择适宜的播种时机、提高红芪的田间管理、加大病虫害防治力度六个层面,探讨了山坡地红芪栽培的具体方法,以供参考。     

防止和减缓镀银层变色的探讨

分析了影响镀银件产生变色的因素，并通过实践和研究提出了防止与延缓镀银件变色的方法。     

神经网络MIMO非线性滤波器及其在颜色测量中的应用研究

本文设计了一种神经网络MIMO(多输入多输出)非线性滤波器。该方法成功地用软件技术解决了测色中非晶硅集成色敏传感器光谱三刺激值信号难以处理的问题,大大简化了测色系统光学结构,并对传统方法难以处理的MIMO非线性滤波问题具有普遍的指导意义。     

真彩色铁谱图像的色彩压缩存储

本文针对铁谱图象的特点,采用色彩压缩与数据编码相结合的复合压缩方法,使铁谱图象数据得到了有效的压缩,实现了一种简单,实用,压缩率较高的彩用图象的压缩算法。     

HisTOOLogy: an open‐source tool for quantitative analysis of histological sections

HisTOOLogy is an open‐source software for the quantification of digital colour images of histological sections. The simple graphical user interface enables both expert and non‐expert users to rapidly extract useful information from stained tissue sections. The software's main feature is a generalizable colour separation algorithm based on k‐means clustering which accurately and reproducibly returns the amount of colour per unit area for any stain, thus allowing the quantification of tissue components. Here we describe HisTOOLogy's algorithms and graphical user interface structure, showing how it can be used to separate different dye colours in several classical stains. In addition, to demonstrate how the tool can be employed to obtain quantitative information on biological tissues, the effect of different hepatic tissue decellularization protocols on cell removal and matrix preservation was assessed through image analysis using HisTOOLogy and compared with conventional DNA and total protein content assays. HisTOOLogy's performance was also compared with ImageJ's colour deconvolution plug‐in, demonstrating its advantages in terms of ease of use and speed of colour separation.     

Detection of partial occlusions of assembled components to simplify the disassembly tasks

An automatic disassembly cell requires of a computer vision system for recognition and localization of the products and each of theirs components. The detection of occlusions adds more information to the knowledge base to identify components and products, and generate a trustworthy and precise relational model (generic graph of hierarchic relations among the different components that make up the product). In this paper, a method to detect partial occlusions in assembled components is presented. This method is based on the fusion of regions and edges information, and it offers a certain degree of simplification for the recognition and modelled of the disassembly tasks, of the set of components which compose the product. The proposed approach to detect regions is a hybrid approach between RGB and HSV spaces. The bi-dimensional histogram V/S is employed for the selection of the appropriate thresholds which serve as an aid to diminish the influence of the highlights and shadows in images. The goal of this paper is to present an approach for the detection of occlusions in assembled components from a combination of HSV and RGB spaces, a bi-dimensional histogram and an edge detector.     

Predicting Visible Image Degradation by Colour Image Difference Formulae

It carried out a CRT monitor based psychophysical experiment to investigate the quality of three colour image difference metrics, the CIEAE ab equation, the iCAM and the S-CIELAB metrics. Six original images were reproduced through six gamut mapping algorithms for the observer experiment. The result indicates that the colour image difference calculated by each metric does not directly relate to perceived image difference.     

The recycling of wool clothes: an artificial neural network colour classification tool

Recycling of clothes is a straightforward approach for the supply of a coloured raw material which does not involve the cost of the colouring process. A real time and completely automated colour classification tool for woollen clothes to be recycled is proposed. The tool uses the combination of a statistical method, called matrix approach, of a self-organizing feature map (SOFM) and a feed-forward backpropagation artificial neural network (FFBP ANN)-based approach, to correctly classify the clothes by respecting the selection criteria provided by human know-how. The developed tool, which uses an appositely developed workbench with a spectrophotometer, is aware of the way the different coloured clothes to be recycled combine each other to create a new one. The tool has been validated using a set of 5,000 differently coloured clothes to be recycled and the classification error in classifying the clothes is within 5%, i.e., lower than the one resulting from the use of an expert human operator.     

Colour thresholding and objective quantification in bioimaging

Computer imaging is rapidly becoming an indispensable tool for the quantification of variables in research and medicine. Whilst its use in medicine has largely been limited to qualitative observations, imaging in applied basic sciences, medical research and biotechnology demands objective quantification of the variables in question. In black and white densitometry (0–256 levels of intensity) the separation of subtle differences between closely related hues from stains is sometimes very difficult. True-colour and real-time video microscopy analysis offer choices not previously available with monochrome systems. In this paper we demonstrate the usefulness of colour thresholding, which has so far proven indispensable for proper objective quantification of the products of histochemical reactions and/or subtle differences in tissue and cells. In addition, we provide interested, but untrained readers with basic information that may assist decisions regarding the most suitable set-up for a project under consideration. Data from projects in progress at Tulane are shown to illustrate the advantage of colour thresholding over monochrome densitometry and for objective quantification of subtle colour differences between experimental and control samples.     

Segmentation of epithelium in H&E stained odontogenic cysts

An algorithm for the automated segmentation of epithelial tissue in digital images of histologic tissue sections of odontogenic cysts (cysts originating from residual odontogenic epithelium) is presented. The algorithm features an image standardization process that greatly reduces variation in luminance and chrominance between images due to variations in sample preparation. Segmentation of the epithelial regions of images uses an algorithm based on binary graph cuts where graph weights depend on probabilities obtained from colour histogram models of epithelium and stroma image regions. Algorithm training used a data set of 38 images of four types of odontogenic cyst and was tested using a separate data set of 35 images of the same four cyst types. The best parameters for the segmentation algorithm were determined using a response-surface optimizer. The best parameter set resulted in an overall mean (± std. dev.) sensitivity of 91.5 ± 17% and overall mean specificity of 85.1 ± 18.6% on the training set. Particularly good results were obtained for dentigerous and odontogenic keratocysts for which the mean sensitivities/specificities were 91.9 ± 6.15%/97.4 ± 2.15% and 96.1 ± 1.98%/98.7 ± 3.16%, respectively. Our method is potentially applicable to many pathological conditions in similar tissues, such as skin and mucous membranes where there is a clear microscopic distinction between epithelium and connective tissues.     

Digital stain separation for histological images

It is often desirable to perform digital image analyses on sections prepared for human interpretation, e.g. nuclear chromatin texture analysis or three-dimensional reconstructions using sections requiring human delineation of structures of interest. Unfortunately such analyses are often more effective using stains with less complex contrast. Here an automated selective 'de-staining' method for digital images is presented. The method separates an image into its red, green and blue and hue, saturation and intensity components. A mask of stained tissue is prepared by automatic percentile thresholding. A single weighted inverted colour channel is then added to each of the three primary colour channels separately by an iterative algorithm that adjusts the weights to give minimum variance within the mask. The modified red, green and blue channels are then recombined. This method is automatic requiring no pre-definition of stain colours or special hardware. The method is demonstrated to 'de-stain' nuclei in haematoxylin and eosin (H&E) sections (and a separate haematoxylin image can be derived from this). An image of isolated brown reaction product is produced with immunoperoxidase preparations counterstained with haematoxylin. Furthermore trichrome (haematoxylin van Gieson, picrosirius red) and other common stains may be separated into their components with modifications of the same algorithm. Although other methods for colour separation do exist (e.g. spectral pathology and colour deconvolution) these require special apparatus or precise calibration and foreknowledge of pure dye colour spectra. The present method of digital stain separation is fully automatic with no such prerequisites.