Visual exploration of structure–activity relationship using maximum common framework

To help tracking all molecules made in a typical medicinal chemistry project, we have developed an algorithm to generate a maximum common framework (MCF) hierarchy and an interactive tool for its visualization and analysis. By identifying all unique frameworks for a set of molecules and all molecules containing each framework, we were able to simplify the MCF hierarchy build up steps and, as a result, speed up the entire process significantly. By allowing compounds to be assigned to multiple MCFs, users can easily remove bad branching nodes and concentrate on interesting ones. MCF hierarchies provide an effective and intuitive visualization for tracking medicinal chemistry lead optimization projects. We will provide examples to illustrate its usefulness.     

Novel gel-based rapid test for non-instrumental detection of ochratoxin A in beer

A rapid easy-to-use immunoassay was optimised for the non-instrumental detection of ochratoxin A (OTA) in beer. The analytical method involves preconcentration on the immunoaffinity layer inside a column followed by direct competitive ELISA detection in the same layer. The visual cut-off value, i.e. the lowest OTA concentration resulting in no colour development, was 0.2 μg L^-1. Assay validation was performed using samples spiked with OTA. Thirty-seven naturally contaminated samples were screened with the gel-based method developed and no false-negative results were obtained. The method described offers a simple, rapid and cost-effective screening tool, thus contributing to better health protection of consumers. Figure Gel-based immunoassay of spiked beer samples.     

A fast-saliency method for real-time infrared small target detection

Infrared small target detection plays an important role in applications including military reconnaissance, early warning and terminal guidance. In this paper, we present a fast method, called fast-saliency, with very low computational complexity, for real-time small target detection in single image frame under various complex backgrounds. Different from traditional algorithms, the proposed method is inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, which is able to delineate regions of small targets in infrared images. Concisely, there are only four simple steps contained in fast-saliency. In order, they are gradient operation, square computation, Gaussian smoothing and automatic thresholding, representing the four procedures as highpass filtering, target enhancement, noise suppression and target segmentation, respectively. Especially, for the most crucial step, gradient operation, we innovatively propose a 5 × 5 facet kernel operator that holds the key for separating the small targets from backgrounds. To verify the effectiveness of our proposed method, a set of real infrared images covering typical backgrounds with sea, sky and ground clutters are tested in experiments. The results demonstrate that it outperforms the state-of-the-art methods not only in detection accuracy, but also in computation efficiency.     

Multi-window visual saliency extraction for fusion of visible and infrared images

Fusion for visible and infrared images aims to combine the source images of the same scene into a single image with more feature information and better visual performance. In this paper, the authors propose a fusion method based on multi-window visual saliency extraction for visible and infrared images. To extract feature information from infrared and visible images, we design local-window-based frequency-tuned method. With this idea, visual saliency maps are calculated for variable feature information under different local window. These maps show the weights of people’s attention upon images for each pixel and region. Enhanced fusion is done using simple weight combination way. Compared with the classical and state-of-the-art approaches, the experimental results demonstrate the proposed approach runs efficiently and performs better than other methods, especially in visual performance and details enhancement.     

Time measurement-visual analysis of nickel(II) using autocatalytic reaction with sodium sulfite/hydrogen peroxide system and its application to the length detection-flow analysis

Trace amounts of nickel(II) can function as a trigger (=reaction initiator) in an autocatalytic reaction with the sodium sulfite/hydrogen peroxide system. Based on this finding, sub-μg L⁻¹ levels of nickel(II) were determined by a time measurement using the autocatalytic reaction. The detection range using the above method was 10⁻⁹–10⁻⁵ M, the detection limit (3σ) was 8.1 × 10⁻¹⁰ M (0.047 μg L⁻¹), and the relative standard deviation was 2.66% at nickel(II) concentration of 10⁻⁷ M (n = 7). This method was applied to length detection-flow injection analysis. The detection range for the flow injection analysis was 2 × 10⁻⁹–2 × 10⁻³ M. The detection limit (3σ) was 1.4 × 10⁻⁹ M (0.082 μg L⁻¹), and the relative standard deviation was 1.86 at initial nickel(II) concentration of 10⁻⁶ M (n = 7).     

一种基于知识模型的红外目标检测方法

针对电厂冷却塔这类具有特殊建筑规范的典型目标,在分析目标红外特性与形状特性的基础上,提出了一种基于知识模型的红外目标检测方法.首先根据冷却塔目标的红外特性,提取图像的亮度、方向和局部熵特征,采用视觉注意模型提取红外图像中的显著区域,作为待检测目标的感兴趣区域;在此基础上,根据冷却塔目标的形状特性建立双曲线形状模型,在感兴趣区内进行结构特征边缘提取和形状模型拟合,构建相关判定准则检测出目标.在一组机载前视红外图像上的实验结果表明,该方法可以达到98.67％的查全率和93.97％的查准率,具有较好的目标检测效果.由于本文方法不需要基准图的参与,降低了对数据保障的要求,因此具有较大的实用性.     

开尔文电桥测电阻及用Visual Basic处理测量数据

用开尔文电桥测量金属棒的电阻率时,电阻率的不确定度是由测量金属棒直径、长度和电阻的不确定度来决定。为了又快又准确地处理实验的测量数据,设计编制了Visual Basic程序,从而方便快捷的计算出金属棒电阻率的不确定度。     

Entropy in good manufacturing system: Tool for quality assurance

It has been customary to implement Good Manufacturing Practices (GMP) in pharmaceutical organizations as a systematic and comprehensive quality approach and sometimes by regulatory enforcement. In this scenario, determination of the obvious entropy/disorder arising during the implementation has not been taken care of yet. Therefore, this paper gives the basis for applying query and visual perception of GMP system driven visualization approach, particularly the Laplace equation, to the determination of disorder and deviation pattern inside the GMP system applied in the organization. In this study, a three-dimensional mesh approached with raw and intermediate input handled under GMP parameter is considered to produce high quality products with minimum entropy (variation distribution) by adding the analogy wise different GMP parameters and process variables with Gauss Seidel iteration and thus producing visual picture of the entire system. The approximation involved in applying the equations to the GMP compliant aseptic region was analyzed. Using numerical technique and computer program, the Gauss Seidel iteration equations have been solved with appropriate GMP parameter and process variable. The result indicates that deviations vary over the GMP compliant system and that the process entropy affects the totality of disorderness. Experiments with model of GMP compliant reproductive medicine laboratory confirm that the new method provides optimal manufacturing maintaining GMP and high product quality through the visual representation of the entire system and activity to bring into notice the deviations.     

基于VB的Solid Edge变量化设计在换热器设计中的应用

在基于Solid Edge软件的基础之上,通过变量化设计建模和编写通用的Visual Basic数据驱动程序,对低温制冷空调设备中常用的各种换热器(管片式、层叠式、平行流式和管带式)进行参数化设计.以管片式换热器为例详细说明软件的三维建模过程,并为今后换热器的优化设计奠定一定的基础.     

基于广义正交迭代算法的立体视觉定位

提出了一种新的基于广义正交迭代算法的立体视觉定位.该算法通过提取CenSurE局部特征和相应的U-SURF描述符,采用SAD方法进行子像素立体匹配,并利用U-SURF描述符匹配进行前后帧图像特征跟踪.在RANSAC框架下对匹配点进行3D-3D运动估计获得了运动参量的初始值.由于3D-3D运动估计使3D点集间欧式距离误差...