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关键词： Classical logic   Classification   Computational intelligence   Fuzzy Logic   Meat   Pattern recognition   WATER-HOLDING CAPACITY   MEAT QUALITY   PH   MUSCULATURE   SLAUGHTER   MUSCLE   TIME  

摘要： Meat classification methods are commonly based on quality parameters standardized by numeric ranges. However, some animal samples from different production chains do not match the current grades proposed. These unclassifiable samples are not capable to fit into a standard created by crisp range of values due to being infeasible toward its definition. An alternative to handle this kind of sample classification is the fuzzy logic, which could deal with uncertainty and ambiguity degree like human reasoning. In this work, we compare the traditional classification method and fuzzy approaches with the objective to handle the infeasible samples. This was compared to traditional pork standards using eleven real-life datasets with a total of 1798 samples described by pH, water holding capacity and/or L* value. The results demonstrated that traditional classification could not predict the unclassifiable samples. On the other hand, the fuzzy approaches improve significantly the number of classified samples. Performance of the fuzzy approaches were compared with several machine learning algorithms, but no significant statistical difference was observed. Finally, a real-life study case was explored, highlighting some advantages and further achievements of the fuzzy modeling.

关键词： Elemental content   Wine samples   Geographical origin   South America   Feature selection   GEOGRAPHICAL ORIGIN   CLASSIFICATION   AUTHENTICITY   SPECTROSCOPY   VARIETIES   MACHINE   QUALITY  

摘要： This paper proposes an approach for feature selection aimed at classifying wines samples according to place of origin. The method relies on Kruskal-Wallis non-parametric test to remove non significant features, and Linear Discriminant Analysis to derive a feature importance index. The ranked features according that index are iteratively added and classification performance is assessed after each insertion. The number of selected features is chosen according the maximum accuracy in a repeated 10-fold cross-validation. Aiming at improving cate-gorization accuracy, different classification techniques are tested. When applied to a wine dataset comprised of 53 samples from four South America countries (Argentina, Brazil, Chile, and Uruguay) and 45 chemical elements concentrations determined by ICP-OES and ICP-MS, the proposed framework yielded average 99.9% accurate classifications in the testing set, and retained average 6.73 of the 45 original elements. Retained chemical ele-ments were then qualitatively assessed.

关键词： DEEP-WATER RENEWAL   AUTOTROPHIC PICOPLANKTON   PHOTOSYNTHETIC PIGMENTS   AULACOSEIRA-BAICALENSIS   MICROCYSTIS-AERUGINOSA   ELEMENTAL COMPOSITION   SPRING PHYTOPLANKTON   CHLOROPHYLL MAXIMA   CLIMATE-CHANGE   ALPINE LAKES  

摘要： Recent research has highlighted how Lake Baikal, Siberia, has responded to the direct and indirect effects of climate change (e.g., ice-cover duration), nutrient loading, and pollution, manifesting as changes in phytoplankton/zooplankton populations, community structure, and seasonal succession. Here, we combine and compare analyses of chlorophyll a (an estimate of total algal biomass), carotenoid pigments (biomarkers of algal groups), and lake water silicon isotope geochemistry (delta Si-30(DSi)) to differentiate spatial patterns in dissolved silicon (DSi) uptake at Lake Baikal. A total of 15 sites across the three basins (south, central, and north) of Lake Baikal were sampled in August 2013 along a depth gradient of 0-180 m. Strong, significant correlations were found between vertical profiles of photic zone DSi concentrations and delta Si-30(DSi) compositions (r = -0.81, p < 0.001), although these are strongest in the central basin aphotic zone (r = -0.98, p < 0.001). Data refute the hypothesis of DSi uptake by picocyanobacteria. Algal biomass profiles and high surface delta Si-30(DSi) compositions suggest greater productivity in the south basin and more oligotrophic conditions in the north basin. delta Si-30(DSi) signatures are highest at depth (20 m) in central basin sites, indicating greater (10-40%) DSi utilization at deep chlorophyll maxima. DSi limitation occurs in the pelagic central basin, probably reflecting a high diatom biomass bloom event (Aulacoseira baicalensis). Meanwhile in the more hydrologically restricted, shallow Maloe More region (central basin), both high delta Si-30(DSi) compositions and picocyanobacteria (zeaxanthin) concentrations, respectively point to the legacy of an "Aulacoseira bloom year" and continuous nutrient supply in summer months (e.g., localized eutrophication).

关键词： Mapping   particle filtering   spectral feature fitting   spectral hourglass wizard   DARK-FIELD MICROSCOPY   RAMAN-SPECTROSCOPY   ANALYTICAL TOOL   SPECTRA   QUALITY   CEO2  

摘要： Hyperspectral imaging (HSI) and classification are established methods that are being applied in new ways to the analysis of nanoscale materials in a variety of matrices. Typically, enhanced darkfield microscopy (EDFM)-based HSI data (also known as image datacubes) are collected in the wavelength range of 400-1000 nm for each pixel in a datacube. Utilising different spectral library (SL) creation methods, spectra from pixels in the datacube corresponding to known materials can be collected into reference spectral libraries (RSLs), which can be used to classify materials in datacubes of experimental samples using existing classification algorithms. In this study, EDFM-HSI was used to visualise and analyse industrial cerium oxide (CeO2; ceria) nanoparticles (NPs) in rat lung tissues and in aqueous suspension. Rats were exposed to ceria NPs via inhalation, mimicking potential real-world occupational exposures. The lung tissues were histologically prepared: some tissues were stained with hematoxylin and eosin (H&E) and some were left unstained. The goal of this study was to determine how HSI and classification results for ceria NPs were influenced by (1) the use of different RSL creation and classification methods and (2) the application of those methods to samples in different matrices (stained tissue, unstained tissue, or aqueous solution). Three different RSL creation methods - particle filtering (PF), manual selection, and spectral hourglass wizard (SHW) - were utilised to create the RSLs of known materials in unstained and stained tissue, and aqueous suspensions, which were then used to classify the NPs in the different matrices. Two classification algorithms - spectral angle mapper (SAM) and spectral feature fitting (SFF) - were utilised to determine the presence or absence of ceria NPs in each sample. The results from the classification algorithms were compared to determine how each influenced the classification results for samples in different matrices. The resu

关键词： On-chip biosensor   Time-of-Flight Secondary Ion Mass   Spectrometry   Multi-component layers   Biofunctionalization   Indirect immunoassay   Binding stoichiometry   ION MASS-SPECTROMETRY   INTEGRATED OPTOELECTRONIC BIOSENSOR   BIOTIN-STREPTAVIDIN SYSTEM   SURFACE-ANALYSIS   FILMS   IMMUNOSENSORS   SPECTROSCOPY   IMMUNOASSAY   PERFORMANCE   ALBUMIN  

摘要： Time-of-flight secondary ion mass spectrometry has been employed to examine, with biomolecular discrimination, sensing arm areas (20 mu m x 600 mu m) of integrated onto silicon chips Mach-Zehnder interferometers aiming to optimize their biofunctionalization with regard to indirect immunochemical (competitive) detection of ochratoxin A. Sensing areas are examined after: modification with (3-amino propyl) triethoxysilane, spotting of OTA-ovalbumin conjugate (probe) from solutions with different concentration, blocking with bovine serum albumin, reaction with OTA-specific mouse monoclonal antibody followed by goat anti-mouse IgG secondary antibody. Component mass loadings of all proteins involved in immunodetection are determined from TOF-SIMS micro-analysis combined with ellipsometry of planar surfaces. These data show that partial desorption of surface-bound probe and blocking protein takes place upon primary immunoreaction to a degree that depends on probe concentration in spotting solution. Taking into account this desorption, apparent binding stoichiometry of both antibodies in immune complexes formed onto chip surface is determined more accurately than the respective evaluation based on real-time sensor response. In addition, mass loadings for probe and secondary antibody is observed to saturate for optimum probe concentrations. Also, principal component analysis of TOF-SIMS data could resolve both immunoreactions and biofunctionalization and discriminate surfaces prepared with optimum probe concentrations from those prepared using suboptimum ones. (C) 2018 Elsevier B.V. All rights reserved.

关键词： 食品检验   质量体系   实验室管理   检测实验室   社会环境   整改工作   食品产业   标准化  

摘要： 在现阶段食品领域监管经营展现标准化、实效化的社会环境中,食品产业运行链条关键流程中食品检测实验室体系统筹监管的升级整改工作便变得非常重要。质量体系是食品检测实验室体系统筹监管的规范性要领原则,始终体现着协助调节的特殊作用。

关键词： 劳动关系氛围   情绪劳动   创新行为  

摘要： 本文基于对服务行业350名员工的调查数据,探讨劳动关系氛围对员工创新行为的作用机理,并验证其是否通过情绪劳动的中介作用对创新行为产生影响。研究结果表明,劳资双赢氛围和员工参与氛围与表层行为和深层行为都有着显著的正相关关系,劳资对立氛围与员工的深层行为有着显著的负相关关系,与员工的表层行为并未发现有着显著的相关关系;劳资双赢氛围与员工参与氛围对创新行为都有着显著的正相关关系,劳资对立氛围与创新行为有显著的负相关关系;通过中介效应检验,深层行为在劳动关系氛围与创新行为之间起部分中介作用,表层行为在劳动关系氛围与创新行为的关系中不起中介作用。

关键词： 激光诱导击穿光谱   特征谱线   自组织特征映射   相关分析   分类识别  

摘要： 激光诱导击穿光谱技术具有微损、原位、快速分析的特点,在样品分类识别、成分分析等领域有广阔的应用前景。为探索该技术在天然地质样品识别应用的可行性,提出了一种自组织特征映射神经网络结合相关判别对天然地质样品LIBS光谱分类识别的方法。为减小全谱中背景噪声等不相关数据干扰、降低计算量,在元素谱线归属的基础上进行了特征谱线提取,实现了高维光谱数据的降维。以特征谱数据为输入建立网络训练模型,得到具有输入样本特征的权向量,通过权向量与待测样本进行相关分析可以实现样品分类。对16种天然地质样品的分类算法实验证明,在全谱、主成分降维和特征谱段三种数据处理方法中,特征谱的降维和提取LIBS数据主特征效果最优。改进的SOM网络结合相关判别算法比支持向量机方法和直接应用SOM网络方法的分类准确度更高,初步证实了该方法的有效性。