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关键词： 肝硬化   凝血酶原时间   血小板   价值  

摘要： 目的分析凝血酶原时间与血小板检验方式诊断肝硬化疾病的价值。方法挑选2018年3月-2019年3月来我院治疗的40例肝硬化患者作为观察组,选择同期来我院体检的40例健康者作为对照组,所有研究对象全部接受凝血酶原时间与血小板检验,分析相关指标水平。结果观察组的PT、PDW、MPV水平都高于对照组,且PLT、PCT水平都低于对照组(P<0.05)。观察组出血患者PT、MPV、PDW水平都高于未出血患者,而PLT、PCT水平低于未出血患者(P<0.05)。结论诊断肝硬化疾病时,实施凝血酶原时间及血小板检验,可以较好体现肝功能受损状况与出血状况,为诊治提供有利参考。

关键词： 检验实验室   质量体系   生活必需品   生产监控   食品质量   标准规范   合格率   食品检验检测  

摘要： 随着现代社会的高速发展与经济水平的不断提高,食品作为人们入口的生活必需品,其安全性受到了国家和人民的高度重视。尤其是在重大食品卫生事件发生的情况下,人们更关注自己每天所吃食品的安全性。同时,国家也出台了一系列规定以加大食品生产监控和食品检验检测力度,希望以此提高食品的合格率,保证食品质量。可以说,质量体系作为检测标准规范在食品检验实验室管理中起到了非常重要的作用。

关键词： 持续质量改进护理干预   血常规检验   采血标本   质量控制  

摘要： 目的:探讨持续质量改进护理干预对血常规检验前采血标本质量控制的作用研究。方法:选取2017年8月~2019年1月我院收治的需要进行血常规检验患者86例,根据护理干预方法的不同分为两组,对照组使用常规管理模式,研究组使用持续质量改进护理干预。比较两组血常规结果、标本不合格率、一次采血成功率、不良情况发生率。结果:研究组PLT、HGB、RBC、HCT均低于对照组(P<0.05),MCHC、WBC高于对照组(P<0.08);研究组标本不合格率低于对照组(P<0.05);研究组一次采血成功率高于对照组(P<0.05),不良情况发生率低于对照组(P<0.05)。结论:在血常规检验前实施持续质量改进护理干预,可以保障采血标本质量控制,减少不良反应的发生,应当进一步推广应用。

关键词： 动物检疫   食品安全   作用  

摘要： 饲料食品添加剂和动物性药品的滥用是造成动物疫情、动物性食品安全问题的主要原因,对人类健康和动物饲料生产、出口造成严重影响,必须高度重视动物的检测和检疫,以确保食品安全。本文结合我国实际情况,分析总结动物食物安全的现状和影响动物食物安全的其他重要因素,论述动物食品检验和检疫对动物性食品安全的作用和重要性。

关键词： Land cover classification   Sentinel   Google Earth Engine   Big data   Remote sensing   Iran  

摘要： Accurate information about the location, extent, and type of Land Cover (LC) is essential for various applications. The only recent available country-wide LC map of Iran was generated in 2016 by the Iranian Space Agency (ISA) using Moderate Resolution Imaging Spectroradiometer (MODIS) images with a considerably low accuracy. Therefore, the production of an up-to-date and accurate Iran-wide LC map using the most recent remote sensing, machine learning, and big data processing algorithms is required. Moreover, it is important to develop an efficient method for automatic LC generation for various time periods without the need to collect additional ground truth data from this immense country. Therefore, this study was conducted to fulfill two objectives. First, an improved Iranian LC map with 13 LC classes and a spatial resolution of 10 m was produced using multi-temporal synergy of Sentinel-1 and Sentinel-2 satellite datasets applied to an object-based Random forest (RF) algorithm. For this purpose, 2,869 Sentinel-1 and 11,994 Sentinel-2 scenes acquired in 2017 were processed and classified within the Google Earth Engine (GEE) cloud computing platform allowing big geospatial data analysis. The Overall Accuracy (OA) and Kappa Coefficient (KC) of the final Iran-wide LC map for 2017 was 95.6% and 0.95, respectively, indicating the considerable potential of the proposed big data processing method. Second, an efficient automatic method was developed based on Sentinel-2 images to migrate ground truth samples from a reference year to automatically generate an LC map for any target year. The OA and KC for the LC map produced for the target year 2019 were 91.35% and 0.91, respectively, demonstrating the efficiency of the proposed method for automatic LC mapping. Based on the obtained accuracies, this method can potentially be applied to other regions of interest for LC mapping without the need for ground truth data from the target year.

关键词： fluorescent fingerprinting   fluorophores   honey   discrimination   chemometrics   principal component analysis   tris(2,2 '-bipyridyl)dichlororuthenium(II)  

摘要： In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used 36 honey samples from different sources to which various fluorophores were added (tris-(2,2 '-bipyridyl) dichlororuthenium(II) (Ru(bpy)(3)(2+)), zinc(II) 8-hydroxyquinoline-5-sulfonate (8-Ox-Zn), and thiazole orange in the presence of two types of deoxyribonucleic acid). The fluorescence spectra were obtained within 400-600 nm and treated by principal component analysis (PCA). No fluorophore allowed for the discrimination of all samples. To evaluate the discrimination performance of fluorophores, we introduced crossing number (CrN) calculated as the number of mutual intersections of confidence ellipses in the PCA scores plots, and relative position (RP) characterized by the pairwise mutual location of group centers and their most distant points. CrN and RP parameters correlated with each other, with total sensitivity (TS) calculated by Mahalanobis distances, and with the overall rating based on all metrics, with coefficients of correlation over 0.7. Most of the considered parameters gave the first place in the discrimination performance to Ru(bpy)(3)(2+) fluorophore.

关键词： Generalized zero shot classification   Generative adversarial network   Class consistency   Semantic consistency  

摘要： Generalized zero shot classification aims to recognize both seen and unseen samples in test sets, which has gained great attention. Recently, many works consider using generative adversarial network to generate unseen samples for solving generalized zero shot classification problem. In this paper, we study how to generate discriminative and meaningful samples. We propose a method to learn discriminative and meaningful samples for generalized zero shot classification tasks (LDMS) by generative adversarial network with the regularization of class consistency and semantic consistency. In order to make the generated samples discriminative, class consistency is used, such that the generated samples of the same classes are near and of different classes are far away. In order to make the generated samples meaningful, semantic consistency is used, such that the semantic representations of the generated samples are close to their class prototypes. It encodes the discriminative information and semantic information to the generator. In order to alleviate the bias problem, we select some confident unseen samples. We use the seen samples, the generated unseen samples and the selected confident unseen samples to train the final classifier. Extensive experiments on all datasets demonstrate that the proposed method can outperform state-of-the-art models on generalized zero shot classification tasks.

关键词： galaxies   active galactic nuclei   radio galaxies   spectral classification  

摘要： This is a detailed spectral classification of 96 active galaxies from the Veron-Cetty and Veron catalog (2010, Version 13, VCV-13) of active galaxies and quasars. These objects were identified as radio sources using standard radio catalogs. Those galaxies which had radio sources in at least 6 different radio bands and had been identified spectrally in the SDSS catalog were selected. The types of activity of these were determined using their SDSS spectra. Three diagnostic diagrams and a direct study of the spectra were used for more certain classification. As a result, the classifications of 85% of the objects were changed. The radio sources in different radio bands make it possible to construct the spectral distribution of the energy in the radio range and to compare it with the optical activity types.

关键词： Human hair   Label-free   Proteomics   Geometric   Racial   Biomarkers  

摘要： Differences in the physiological proteome of men of different racial origin is poorly researched, albeit hair is mostly composed of keratins and keratin-associated proteins. Hence, we have carried out label-free, shotgun proteomics analysis on hair samples collected from black African, Caucasian, Asian, and Mixed-Ancestry donors within a heterogeneous population of the Western Cape of South Africa. Further, the same hair was also classified using geometrical measurements. Using both qualitative and quantitative proteomics bioinformatics pipelines, we identified over 450 protein groups (FDR = 0.01). Identified protein classes included keratins, keratin-associated proteins, histone proteins and desmosomes, inter alia. No protein by quantitative proteomic analyses significantly differentiated racial or geometric groups in our cohort. Functional pathway analysis of top-ranking proteins showed enrichment for skin, epidermal and tissue development, as well as intermediate-filament organization. Racial classification is a social construct, and attributing differences in a biologic endpoint to it is both imprecise and valueless in the era of precision medicine. Nonetheless, clarity on the physiological hair proteome could serve as a foundation for using hair proteomics for disease biomarker and targeted therapy identification for precision medicine. For the first time, we established the physiological hair proteome of individuals in a culturally diverse cohort from Africa. Significance: For the first time we have been able to characterize the physiological human hair proteome in a culturally diverse South African cohort. We have also identified that proteomics differences were not observed in individual hair samples using our quantitative proteomics bioinformatics pipeline. This outcome supports a widely known notion that DNA sequence comparison often shows that people on each continent are not more genetically similar to one another than to people who come from other conti