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1.
《Journal of dairy science》2022,105(6):5471-5492
The detection of reproductive tract disease (RTD) 3 wk postpartum is important because of its effect on subsequent reproductive outcomes. Numerous methods for the diagnosis of RTD are described, some of which are more practical and instantaneous in terms of diagnosis. Two of these methods involve identification of purulent vaginal discharge (PVD) and evidence of ultrasonographic uterine changes indicative of endometritis (UE). The objectives of our retrospective observational study were (1) to assess the association of PVD or UE score at the prebreeding examination (PBE) with the hazard of pregnancy within the subsequent breeding season; (2) to determine the test sensitivity (Se) and specificity (Sp) at the point of sampling of both tests using a Bayesian latent class model; and (3) to determine the effect of varying positivity thresholds on test accuracy. To achieve these objectives, we analyzed an initial data set of 5,049 PBE from 2,460 spring-calved cows in 8 herds between 2014 and 2018. Each PBE was conducted once between 25 and 86 d in milk. At each PBE, vaginal discharge was obtained with a Metricheck device (Simcro) whereas uterine contents were assessed using transrectal ultrasonography. Purulent vaginal discharge was scored on a scale of 0 to 3 depending on discharge character, and UE was scored on a scale of 0 to 4 depending on the presence and consistency of intraluminal fluid. Cows with scores of ≥2 in either test had received treatment. Fertility data were available from 4,756 PBE after data exclusion. The association between PVD or UE score at the PBE and subsequent hazard of pregnancy was analyzed using a Cox proportional hazards model. Cows with a PVD score of 2 or 3 were less likely to conceive than cows with a PVD score 0 [score 2 hazard ratio (HR) = 0.74; 95% confidence interval (CI): 0.59–0.94; score 3 HR = 0.65; 95% CI: 0.51–0.84]. Cows with a UE score of 1, 2, 3, or 4 were less likely to conceive than cows with a UE score of 0 (score 1 HR = 0.82; 95% CI: 0.73–0.93; score 2 HR = 0.79; 95% CI: 0.62–1.00; score 3 HR = 0.43; 95% CI: 0.43–0.90; score 4 HR = 0.39; 95% CI: 0.26–0.58). To determine the Se and Sp of PVD or UE score for diagnosis of RTD at the time of PBE, a Bayesian latent class model was fitted on 2,460 individual cow PBE. Flat priors were used for the Se and Sp of UE, whereas informative priors were used for PVD Se (mode = 65%, 5th percentile = 45%) and Sp (mode = 90%, 5th percentile = 80%) and RTD prevalence (mode = 20%, 5th percentile = 10%). Posterior estimates (median and 95% Bayesian probability intervals; BPI) were obtained using ‘rjags' (R Studio). The optimal test thresholds (PVD and UE score ≥1) were selected by assessing the effect of different thresholds on test estimates and using a misclassification cost analysis. Based on these, median (95% BPI) Se for PVD and UE score ≥1 were 44% (29–60%) and 67% (33–100%), respectively. Median Sp for PVD and UE score ≥1 were 90% (86–93%) and 91% (86–93%), respectively. Higher scores in both tests were associated with impaired fertility, and UE scoring with a threshold of ≥1 had the highest test Se and Sp estimates although test Se was conditional on days in milk when the PBE occurred.  相似文献   
2.
A pattern net assisted mapping artificial neural network (PAMANN) model for estimation of parameters in problem with large data (1300 × 121 matrix size) is reported. A pattern net-based multilayer perceptron neural network (MLPNN) model for clustering the data, followed by mapping MLPNN model for mapping the target with the input, is developed as PAMANN model. A heat transfer problem with combined mode conduction and radiation in porous medium is solved numerically, and is called direct model. In the inverse model, a PAMANN model is developed by using data generated through the direct model. The PAMANN model is able to estimate two parameters (extinction coefficient β and convective coupling P2) after taking temperature profile as input. The model is tested for different number of neurons in hidden layer, and different levels of noise in input data. Twelve different algorithms are explored in training of mapping MLPNN, and compared for performance. Levenberg–Marquardt algorithm is found to estimate the parameters with high accuracy, but took high CPU time. Bayesian regularization is found to consume very high CPU time with moderate accuracy in estimation of parameters. Variations in hidden layer neuron number and noise in input data, were done to analyze the performance of mapping MLPNN with different training algorithms. Algorithms O-Step Secant, conjugate gradient with Polak-Ribiére updates, and conjugate gradient with Fletcher-Reeves updates are able to handle all variations of noise and number of neurons in hidden layer, with good accuracy of estimation and low CPU time consumption. Under high computational resource LM algorithm can be used for all cases. Up to 0.99132 value of regression coefficient is obtained in mapping MLPNN model with 15 hidden neurons, indicating the high accuracy of the model. With the help of PAMANN model, highly accurate (absolute error 1.78%) estimation of parameters is obtained. The model can handle upto 1% noise in input data, while giving accurate results.  相似文献   
3.
针对现有频谱分离方法进行声学场景分类研究时其分类准确率不高的问题,提出了一种基于梅尔频谱分离和长距离自校正卷积神经网络(long-distance self-calibration convolutional neural network, LSCNet)的声学场景分类方法。首先,介绍了频谱的谐波打击源分离原理,提出了一种梅尔频谱分离算法,将梅尔频谱分离出谐波分量、打击源分量和残差分量;然后,结合自校正神经网络和残差增强机制,提出了一种长距离自校正卷积神经网络;该模型采用频域自校正算法以及长距离增强机制来保留特征图原始信息,通过残差增强机制和通道注意力增强机制加强了深层特征与浅层特征间的关联度,且结合多尺度特征融合模块,以进一步提取模型训练中输出层的有效信息,从而提高模型的分类准确率;最后,基于Urbansound8K和ESC-50数据集开展了声学场景分类实验。实验结果表明:梅尔频谱的残差分量能够针对性地减少背景噪音的影响,从而具有更好的分类性能,且LSCNet实现了对特征图中频域信息的关注,其最佳分类准确率分别达到90.1%和88%,验证了该方法的有效性。  相似文献   
4.
目前许多多标签文本分类方法主要关注文档表示,而丢失了大量标签相关的语义信息,导致分类效果不理想。针对以上问题,提出一种基于标签推理和注意力融合的分类方法,挖掘文档中与标签相关的特征以及相似标签之间的相关性,学习标签信息进行标签推理,同时采用注意力机制自学习地融合文档表示和标签表示,最终完成多标签分类任务。在AAPD和RCV1-V2数据集上进行实例验证,该方法的F1值分别达到了0.732和0.887,与其他最新方法相比其准确度均有提升,实验结果证明了标签推理和注意力融合策略的有效性。  相似文献   
5.
田珂 《弹道学报》2022,34(3):49-57
利用连续波雷达测试弹丸径向速度时,会遇到弹丸、火炮、雷达及外界因素异常,测试的径向速度会出现缺失,导致递推出的炮口初速不准确。为此,选择建立合理的模型预测出缺失的径向速度对数据进行重构。雷达测试的径向速度属于一维数据,大口径弹丸的径向速度主要包含线性特征,小口径弹丸的径向速度既包含线性特征又包含非线性特征,都可以建立ARIMA模型、GM(1,1)灰色模型和回归模型进行预测。但是这些传统模型有时预测能力比较局限,预测精度不理想。为了充分整合所有模型的预测优势,提高预测精度,选择建立组合模型进行预测。针对大口径弹丸,建立由ARIMA、GM(1,1)和一阶线性回归方程构建的组合模型进行预测,针对小口径弹丸,建立由ARIMA、GM(1,1)和二次多项式回归方程构建的组合模型进行预测,为了保证预测精度,按照迭代的方式进行预测。实验结果表明,无论是大口径弹丸还是小口径弹丸,组合模型的预测精度始终高于单项模型,平均相对误差小于1‰,更加适合作为弹丸径向速度的预测模型。  相似文献   
6.
本文针对钽铌选厂不同入选原矿的选矿结果差异开展了对入选原矿分类的研究。在物料平衡分析的基础上,以最小化物料平衡误差为目标,建立了面向求解生产所有环节物料变化系数的数学模型,并运用差分进化算法进行运算求解;根据求解出的不同入选原矿的物料变化系数,运用聚类的方法进行入选原矿的分类,确定不同类别入选原矿的物料变化系数。  相似文献   
7.
《Journal of dairy science》2022,105(3):2439-2452
Bias in dairy genetic evaluations, when it exists, has to be understood and properly addressed. The origin of biases is not always clear. We analyzed 40 yr of records from the Lacaune dairy sheep breeding program to evaluate the extent of bias, assess possible corrections, and emit hypotheses on its origin. The data set included 7 traits (milk yield, fat and protein contents, somatic cell score, teat angle, udder cleft, and udder depth) with records from 600,000 to 5 million depending on the trait, ~1,900,000 animals, and ~5,900 genotyped elite artificial insemination rams. For the ~8% animals with missing sire, we fit 25 unknown parent groups. We used the linear regression method to compare “partial” and “whole” predictions of young rams before and after progeny testing, with 7 cut-off points, and we obtained estimates of their bias, (over)dispersion, and accuracy in early proofs. We tried (1) several scenarios as follows: multiple or single trait, the “official” (routine) evaluation, which is a mixture of both single and multiple trait, and “deletion” of data before 1990; and (2) several models as follows: BLUP and single-step genomic (SSG)BLUP with fixed unknown parent groups or metafounders, where, for metafounders, their relationship matrix gamma was estimated using either a model for inbreeding trend, or base allele frequencies estimated by peeling. The estimate of gamma obtained by modeling the inbreeding trend resulted in an estimated increase of inbreeding, based on markers, faster than the pedigree-based one. The estimated genetic trends were similar for most models and scenarios across all traits, but were shrunken when gamma was estimated by peeling. This was due to shrinking of the estimates of metafounders in the latter case. Across scenarios, all traits showed bias, generally as an overestimate of genetic trend for milk yield and an underestimate for the other traits. As for the slope, it showed overdispersion of estimated breeding values for all traits. Using multiple-trait models slightly reduced the overestimate of genetic trend and the overdispersion, as did including genomic information (i.e., SSGBLUP) when the gamma matrix was estimated by the model for inbreeding trend. However, only deletion of historical data before 1990 resulted in elimination of both kind of biases. The SSGBLUP resulted in more accurate early proofs than BLUP for all traits. We considered that a snowball effect of small errors in each genetic evaluation, combined with selection, may have resulted in biased evaluations. Improving statistical methods reduced some bias but not all, and a simple solution for this data set was to remove historical records.  相似文献   
8.
借鉴国内外相关甲烷排放核算研究成果和实践经验,结合中国城镇燃气典型输配系统的工艺特点,进行甲烷排放源识别及分类研究。研究表明,城镇燃气典型输配系统从门站进站管道到用户燃气表之间的所有设施、设备、组件及连接处都存在甲烷排放的可能,按照排放类型分为逃逸排放和放散排放;按照设施类型分为埋地燃气管道排放、燃气厂站排放和终端用户排放。根据国内外文献调研,不同设施类型中的材料材质、设备类型是影响甲烷排放量的重要因素,因此将排放源细分为6个一级排放源,21个二级排放源,72个三级排放源,为城镇燃气典型输配系统排放清单编制奠定基础。  相似文献   
9.
10.
借鉴国内外相关甲烷排放核算研究成果和实践经验,结合中国城镇燃气典型输配系统的工艺特点,进行甲烷排放源识别及分类研究。研究表明,城镇燃气典型输配系统从门站进站管道到用户燃气表之间的所有设施、设备、组件及连接处都存在甲烷排放的可能,按照排放类型分为逃逸排放和放散排放;按照设施类型分为埋地燃气管道排放、燃气厂站排放和终端用户排放。根据国内外文献调研,不同设施类型中的材料材质、设备类型是影响甲烷排放量的重要因素,因此将排放源细分为6个一级排放源,21个二级排放源,72个三级排放源,为城镇燃气典型输配系统排放清单编制奠定基础。  相似文献   
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