Survey of 1012 moldy dwellings by culture fungal analysis: Threshold proposal for asthmatic patient management

Different countries have tried to define guidelines to quantify what levels of fungi are considered as inappropriate for housing. This retrospective study analyzes indoor fungi by cultures of airborne samples from 1012 dwellings. Altogether, 908 patients suffering from rhinitis, conjunctivitis, and asthma were compared to 104 controls free of allergies. Portuguese decree law no 118/2013 (PDL118), ANSES (a French environmental and health agency) recommendations, and health regulations of Besançon University Hospital were applied to determine the rates of non‐conforming dwellings, which were respectively 55.2%, 5.2%, and 19%. Environmental microbiological results and medical data were compared. The whole number of colonies per cubic meter of air was correlated with asthma (P < 0.001) and rhinitis (P = 0.002). Sixty‐seven genera and species were detected in bedrooms. Asthma was correlated to Aspergillus versicolor (P = 0.004) and Cladosporium spp. (P = 0.02). Thresholds of 300 cfu/m³ for A. versicolor or 495 cfu/m³ for Cladosporium spp. are able to discriminate 90% of the asthmatic dwellings. We propose a new protocol to obtain an optimal cost for indoor fungi surveys, excluding surface analyses, and a new guideline to interpret the results based on >1000 cfu/m³ of whole colonies and/or above threshold levels for A. versicolor or Cladosporium spp.     

磁环表面缺陷图像分割算法的研究及实时实现

为实现小型磁环表面细微缺陷图像无监督分割,并提高分割精度与计算效率,本文提出了一种基于改进2D Gabor滤波器组的自适应阈值分割方法。首先,利用多尺度、多方向的Gabor滤波器组对缺陷图像进行滤波降噪处理,抑制目标区域与背景区域内部的噪声污染,同时增强区域间的差异性；然后,通过对处理后图像的灰度统计特性分析,根据缺陷图像的灰度均值及方差构造了灰度阈值计算公式,实现了小型磁环表面细微缺陷图像的自适应分割。实验结果表明,本文算法可快速、准确地分割缺陷并抑制噪声干扰,在分割精度、计算效率等方面也优于传统的选择迭代法、OTSU、最大熵等方法,并能够在先进的SEED-DVS8168平台上实时实现,验证了此算法的可行性与实时性。     

基于三角形循环二分算法的图像去雾研究

为了提高图像去雾效果,采用三角形循环二分算法处理图像。首先分析基本暗通道算法图像去雾;接着基于三角形循环二分算法对大气光值精确计算,将图像沿对角线分成4个三角形区域,只对雾浓度最较高的区域进行二分图形划分,选取三角形最长边的中点,连接到对应三角形最长边的顶点,循环执行直到满足预先设定的面积阈值;然后自适应调节透射率,避免色彩失真;最后给出了算法流程。实验仿真显示,本文算法去雾后的图像在视觉上更加清晰,可见边集合数目比、平均梯度比值、直方图相似度系数、综合评价指标相比其他算法较好,能够满足图像去雾对清晰度、信息量的要求。     

自然光照条件下植被几何光学四分量的提取算法

目的 几何光学四分量是指在太阳光照条件下传感器所能观测的4个光学分量，即光照植被、光照土壤、阴影植被和阴影土壤。四分量是构成遥感几何光学模型的重要内容。在近地表遥感应用中，相机俯视拍照是提取四分量的一个途径。准确快速地从图像数据中提取四分量对植被冠层结构参数反演和植被长势监测具有重要意义。方法 植被与土壤二分量的识别是四分量提取的基础。目前大多数二分类算法在自然光照条件复杂时分类误差较大。本文基于卷积神经网络（CNN）和阈值法实现了多种二分类和四分量提取算法。阈值法中，使用SHAR-LABFVC （shadow-resistant algorithm：LABFVC）实现植被与土壤的二分类，并在此基础上应用二次阈值分割获取四分量，称为二次阈值法；基于CNN的方法中，采用U-Net架构，并使用RGB和RGBV数据进行训练得到U-Net和U-Net-V模型，前者完成二分类和四分量任务，后者只完成四分量提取实验。最后，对一种结合U-Net与阈值法的混合算法进行四分量提取实验。结果 本文在18幅图像（1 800个子图）数据上进行了实验，结果表明，与目视解译得到的四分量真值相比较，U-Net-V和混合法精度最高，具有相近的均方根误差（RMSE）（0.06和0.07）和相关系数（0.95和0.94）；二次阈值法与U-Net模型精度略低于上述两种算法，RMSE分别是0.08和0.09，相关系数均为0.88。在二分类实验中，U-Net的分类正确率是91%，SHAR-LABFVC为85%。结论 通过对比实验表明，在二分类问题中，U-Net可以更好地应对复杂自然光照条件下的数字图像。在四分量提取实验中，混合法和U-Net-V的结果优于U-Net与二次阈值法，可以用于提取四分量。     

Improved fatigue crack growth resistance by retrogression and re‐aging heat treatment in 7010 aluminum alloy

Aircraft grade 7010 aluminum alloy was heat treated to two different conditions: (1) standard peak aging (T6) and (2) retrogression and re‐aging (RRA). The microstructures of these alloys were characterized by using transmission electron microscope. Fatigue crack growth rate (FCGR) tests were conducted using standard compact tension specimens, following ASTM standards. Tests were conducted at various stress ratios, R ranging from 0.1 to 0.7. The RRA‐treated alloy was observed to contain coarsened η′ (MgZn₂) precipitates with higher inter‐particle spacing when compared with T6‐treated alloy. The grain boundary precipitates (GBPs) were also coarsened and discontinuous in RRA‐treated alloy as compared with continuous GBPs in T6 condition. The FCGR was lower and ΔK_th was higher in RRA‐treated alloy compared with T6‐treated alloy at all the stress ratios investigated. Improved fatigue crack growth resistance in RRA‐treated alloy was correlated to the modified microstructure and enhanced crack closure levels.     

Genetic parameters for hoof health traits estimated with linear and threshold models using alternative cohorts

A national genetic evaluation program for hoof health could be achieved by using hoof lesion data collected directly by hoof trimmers. However, not all cows in the herds during the trimming period are always presented to the hoof trimmer. This preselection process may not be completely random, leading to erroneous estimations of the prevalence of hoof lesions in the herd and inaccuracies in the genetic evaluation. The main objective of this study was to estimate genetic parameters for individual hoof lesions in Canadian Holsteins by using an alternative cohort to consider all cows in the herd during the period of the hoof trimming sessions, including those that were not examined by the trimmer over the entire lactation. A second objective was to compare the estimated heritabilities and breeding values for resistance to hoof lesions obtained with threshold and linear models. Data were recorded by 23 hoof trimmers serving 521 herds located in Alberta, British Columbia, and Ontario. A total of 73,559 hoof-trimming records from 53,654 cows were collected between 2009 and 2012. Hoof lesions included in the analysis were digital dermatitis, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, and white line disease. All variables were analyzed as binary traits, as the presence or the absence of the lesions, using a threshold and a linear animal model. Two different cohorts were created: Cohort 1, which included only cows presented to hoof trimmers, and Cohort 2, which included all cows present in the herd at the time of hoof trimmer visit. Using a threshold model, heritabilities on the observed scale ranged from 0.01 to 0.08 for Cohort 1 and from 0.01 to 0.06 for Cohort 2. Heritabilities estimated with the linear model ranged from 0.01 to 0.07 for Cohort 1 and from 0.01 to 0.05 for Cohort 2. Despite a low heritability, the distribution of the sire breeding values showed large and exploitable variation among sires. Higher breeding values for hoof lesion resistance corresponded to sires with a higher prevalence of healthy daughters. The rank correlations between estimated breeding values ranged from 0.96 to 0.99 when predicted using either one of the 2 cohorts and from 0.94 to 0.99 when predicted using either a threshold or a linear model.     

自适应连续多级分区与初始阈值估计的快速模板匹配方法

归一化互相关测度在光照改变时比采用绝对差之和测度（SAD）要稳定，但是归一化互相关测度的缺陷在于它的计算量非常大。为此，提出了一种结合自适应连续多级分区和初始阈值估计的基于归一化互相关（NCC）的快速模板匹配算法。根据模板图像中不同模块的梯度值，将模板图像进行逐级分区，通过分区顺序将互相关之和分为不同的层，得到各层互相关的上界，运用柯西-施不等式得到上界间的关系，形成自适应连续多级分区淘汰方法。同时，为了加快匹配速度，利用初始阈值估计产生一个较大的边界阈值，以淘汰初始搜索时的大量非匹配点，减少搜索点数目。实验结果表明:所提出的算法具有较好的鲁棒性，且算法的执行速度优于传统算法。