Particle Characteristics’ Influence on FLASH Sintering of Potassium Sodium Niobate: A Relationship with Conduction Mechanisms

The considerable decrease in temperature and time makes FLASH sintering a more sustainable alternative for materials processing. FLASH also becomes relevant if volatile elements are part of the material to be processed, as in alkali-based piezoelectrics like the promising lead-free K_0.5Na_0.5NbO₃ (KNN). Due to the volatile nature of K and Na, KNN is difficult to process by conventional sintering. Although some studies have been undertaken, much remains to be understood to properly engineer the FLASH sintering process of KNN. In this work, the effect of FLASH temperature, T_F, is studied as a function of the particle size and impurity content of KNN powders. Differences are demonstrated: while the particle size and impurity degree markedly influence T_F, they do not significantly affect the densification and grain growth processes. The conductivity of KNN FLASH-sintered ceramics and KNN single crystals (SCs) is compared to elucidate the role of particles’ surface conduction. When particles’ surfaces are not present, as in the case of SCs, the FLASH process requires higher temperatures and conductivity values. These results have implications in understanding FLASH sintering towards a more sustainable processing of lead-free piezoelectrics.     

Segmentation of retinal blood vessels using a novel clustering algorithm (RACAL) with a partial supervision strategy

In this paper, segmentation of blood vessels from colour retinal images using a novel clustering algorithm with a partial supervision strategy is proposed. The proposed clustering algorithm, which is a RAdius based Clustering ALgorithm (RACAL), uses a distance based principle to map the distributions of the data by utilising the premise that clusters are determined by a distance parameter, without having to specify the number of clusters. Additionally, the proposed clustering algorithm is enhanced with a partial supervision strategy and it is demonstrated that it is able to segment blood vessels of small diameters and low contrasts. Results are compared with those from the KNN classifier and show that the proposed RACAL performs better than the KNN in case of abnormal images as it succeeds in segmenting small and low contrast blood vessels, while it achieves comparable results for normal images. For automation process, RACAL can be used as a classifier and results show that it performs better than the KNN classifier in both normal and abnormal images.     

Implementation of High-Dimensional Feature Map for Segmentation of MR Images

A method that considerably reduces the computational and memory complexities associated with the generation of high-dimensional (≥3) feature maps for image segmentation is described. The method is based on the K-nearest neighbor (KNN) classification and consists of two parts: preprocessing of feature space and fast KNN. This technique is implemented on a PC and applied for generating 3D and 4D feature maps for segmenting MR brain images of multiple sclerosis patients.     

Hepatic gene expression discriminates responders and nonresponders in treatment of chronic hepatitis C viral infection

BACKGROUND & AIMS: Pegylated interferon (IFN)-alpha plus ribavirin is the most effective treatment of chronic hepatitis C but has unpleasant side effects and high costs. A large proportion of patients do not respond to therapy for reasons that are unclear. We used gene expression profiling to investigate the molecular basis for treatment failure. METHODS: Expression profiling was performed on percutaneous needle liver biopsy specimens taken before therapy. Gene expression levels were compared among 15 nonresponder, 16 responder, and 20 normal liver biopsy specimens. Differential gene expression was confirmed using real-time polymerase chain reaction. RESULTS: We identified 18 genes whose expression differed significantly between all responders and all nonresponders (P < .005). Many of these 18 genes are IFN sensitive and 2 (ISG15/USP18) are linked in a novel IFN-regulatory pathway, suggesting a possible rationale for treatment resistance. Using a number of independent classifier analyses, an 8-gene subset accurately predicted treatment response for 30 of 31 patients. The classifier analyses were applicable to patients with genotype 1 infection and were not correlated with viral load, disease activity, or fibrosis. CONCLUSIONS: Hepatic gene expression profiling identified consistent differences in patients who subsequently fail treatment with pegylated IFN-alpha plus ribavirin: up-regulation of a specific set of IFN-responsive genes predicts nonresponse to exogenous therapy. These data may be of use in predicting clinical responses to treatment.     

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories.This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.     

基于表面肌电信号的手腕动作模式识别

基于表面肌电信号的肢体动作模式识别是假手仿生控制的基础.为提高动作模式识别率,从肌电信号的产生机理出发,选取分别表征肌电信号形态特征——细节复杂度和整体自似性的近似熵指标和分维数指标,作为模式识别的特征向量;同时提出一种具有增量学习能力的K最近邻(KNN)模型增量学习算法作为模式识别的分类器.在对10位受试者手腕的4个精细动作(腕伸、腕屈、腕内旋、腕外旋)的识别实验中,取得了92.5％以上的正确识别率.同时对增量学习能力对分类器动作模式识别率的影响做对比实验,当假肢使用者生理变化时,以KNN模型增量学习算法作为分类器比采用不具增量学习能力的KNN模型算法的识别率高4.5％.实验表明,该肌电信号动作模式的识别方法方案合理,具有应用价值.     

Analysis of the procedures used to evaluate suicide crime scenes in Brazil: A statistical approach to interpret reports

This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences.     

Features of the Structure and Electrophysical Properties of Solid Solutions of the System (1-x-y) NaNbO3-xKNbO3-yCd0.5NbO3

Ferroelectric ceramic materials based on the (1-x-y) NaNbO₃-xKNbO₃-yCd_0.5NbO₃ system (x = 0.05–0.65, y = 0.025–0.30, Δx = 0.05) were obtained by a two-stage solid-phase synthesis followed by sintering using conventional ceramic technology. It was found that the region of pure solid solutions extends to x = 0.70 at y = 0.05 and, with increasing y, it narrows down to x ≤ 0.10 at y = 0.25. Going out beyond the specified concentrations leads to the formation of a heterogeneous region. It is shown that the grain landscape of all studied ceramics is formed during recrystallization sintering in the presence of a liquid phase, the source of which is unreacted components (Na₂CO₃ with T_melt. = 1126 K, K₂CO₃ with T_melt. = 1164 K, KOH with T_melt. = 677 K) and low-melting eutectics in niobate mixtures (NaNbO₃, T_melt. = 1260 K, KNbO₃, T_melt. = 1118 K). A study of the electrophysical properties at room temperature showed the nonmonotonic behavior of all dependences with extrema near symmetry transitions, which corresponds to the logic of changes in the electrophysical parameters in systems with morphotropic phase boundaries. An analysis of the evolution of dielectric spectra made it possible to distinguish three groups of solid solutions: classical ferroelectrics (y = 0.05–0.10), ferroelectrics with a diffuse phase transition (y = 0.30), and ferroelectrics relaxors (y = 0.15–0.25). A conclusion about the expediency of using the obtained data in the development of materials and devices based on such materials has been made.     

基于智能视觉技术的白及饮片真伪快速辨识方法研究

目的 利用电子眼和色差仪分别对白及Bletillastriata及其伪品进行辨识,旨在建立白及真伪的快速辨识方法。方法 首先基于《中国药典》、地方标准和HPLC指纹图谱对多采集来源的134批白及及其伪品样品进行综合鉴别,以确定标杆辨识信息（Y）。然后基于电子眼和色差仪分别获取上述样品的智能视觉信息（X）。最后利用Matlab建立Y=F(X)模型,即分别建立白及真伪二分类（白及、非白及）和四分类（白及、天麻Gastrodiaelata、玉竹Polygonatumodoratum、黄花白及Bletilla ochracea）的主成分分析-判别分析（principal component analysis-discriminant analysis,PCA-DA）、偏最小二乘-判别分析（partial least squares-discriminant analysis,PLS-DA）、最小二乘-支持向量机（least squares-support vector machine,LS-SVM）和K最近邻（K nearest neighbor,KNN）辨识模型并验证。结果 经留一法交互验证...