Chemical durability and surface alteration of lanthanide zirconates (A2Zr2O7: A = La-Yb)

Chemical durability of lanthanide zirconates (A₂Zr₂O₇) (A = La-Yb) under near-field environments is important for evaluating their application as potential nuclear waste forms. In this work, A₂Zr₂O₇ (A = La-Yb) are synthesized by spark plasma sintering with controlled microstructure and their chemical durability are evaluated in a nitric acid solution (pH = 1). Scanning transmission electron microscopy analysis reveals an amorphous passivation film either enriched with Zr or lanthanide. The complex chemistry of the passivation films can be correlated with a transition in corrosion mechanisms from a preferential release of lanthanide in La₂Zr₂O₇ to a preferential release of Zr in Er₂Zr₂O₇ and Yb₂Zr₂O₇. These results suggest a dominant mechanism of incongruent dissolution and surface reorganization for the formation of passivation films. Strong correlations are identified between the leaching rates and cation ionic size, ionic potential, electronegativity differences between A-site cation and Zr, and bonding valence sum of oxygen, suggesting important impacts of structural and bonding characteristics in controlling chemical durability of lanthanide zirconates.     

Influence of temperature on acoustic emission source location accuracy in underground structure

An acoustic emission (AE) experiment was carried out to explore the AE location accuracy influenced by temperature. A hollow hemispherical specimen was used to simulate common underground structures. In the process of heating with the flame, the pulse signal of constant frequency was stimulated as an AE source. Then AE signals received by each sensor were collected and used for comparing localization accuracy at different temperatures. Results show that location errors of AE keep the same phenomenon in the early and middle heating stages. In the later stage of heating, location errors of AE increase sharply due to the appearance of cracks. This provides some beneficial suggestions on decreasing location errors of structural cracks caused by temperature and improves the ability of underground structure disaster prevention and control.     

从蚕的生命到艺术：中国古代生命观的哲学表达

中国考古出土的蚕业实物及蚕的艺术形象比较丰富,蚕的艺术形象如蚕纹、陶蚕蛹、牙雕蚕、玉石蚕、铜蚕、金蚕等,可统称为"蚕的模拟形态"。对蚕的模拟形态的功用,已有的诸多解释都有待完善。研究表明,蚕的模拟形态或艺术形象表达的功用或为饰品,或为装饰图案,或有待进一步考究。但无论哪种功用,用"蚕"这一形象都蕴含了特有的用意。通过对中国古代生命观的考察,文章认为蚕的艺术形象折射出相应的中国古代哲学生命观,即中国古人追求的死而复生、生生不息、羽化成仙、长乐无极等观念。     

Reproductive tract disease in Irish grazing dairy cows: Retrospective observational study examining its association with reproductive performance and accuracy of 2 diagnostic tests

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.     

Removing data and using metafounders alleviates biases for all traits in Lacaune dairy sheep predictions

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.     

基于形态审美的产品基因网络造型研究

目的 利用产品形态审美基因网络，对台灯外轮廓曲线的相关性进行综合分析，析出产品优化与创新设计的关键要素。方法 以三次贝塞尔曲线对台灯的外轮廓曲线进行基因编码，规律性调整控制点的坐标生成新曲线形态，进行曲线视觉力感知识别，挖掘曲线间的相关性;以曲线基因为节点，相关性为边构建产品形态审美基因网络，并对网络进行拓扑分析，析出关键设计节点辅助设计者进行产品设计。结果 运用产品形态基因网络的理论找到原型设计的关键性节点，并进行设计优化，使产品造型设计更符合消费者的审美习惯和偏好。结论 通过对台灯外轮廓线的案例实践，证实了产品形态基因网络在产品细节优化和造型创新设计方面具有实用性和可靠性，能够辅助设计者找到关键设计节点并协调设计的基因集团。     

Graduate Student Literature Review: Considerations for nutritional grouping in dairy farms

Each cow in a group has different nutritional requirements even if the group is formed by cows of similar age, number of lactations, and lactation stage. Common dairy farm management setup does not support formulating a diet that accurately matches individual nutritional requirements for each cow; therefore, a proportion of cows in the group will be overfed and another proportion underfed. Overfeeding and underfeeding cows increases the risk of metabolic diseases, decreases milk production, and increases nutrient waste. Consequently, profitability of dairy farms and the environment are negatively affected. Nutritional grouping is a management strategy that aims to allocate lactating cows homogeneously according to their nutritional requirements. Groups of cows with more uniform nutritional requirements facilitates the formulation of more accurate diets for the group. Current availability of large data streams on dairy farms facilitates the design of algorithms to implement nutritional grouping. Our review summarizes important factors to consider when grouping cows, describes nutritional grouping approaches, and summarizes benefits of implementing nutritional grouping in dairy farms.     

Digital twin-based analysis of volumetric error mapping procedures

The evaluation of the volumetric accuracy of a machine tool is an open challenge in the industry, and a wide variety of technical solutions are available in the market and at research level. All solutions have advantages and disadvantages concerning which errors can be measured, the achievable uncertainty, the ease of implementation, possibility of machine integration and automation, the equipment cost and the machine occupation time, and it is not always straightforward which option to choose for each application. The need to ensure accuracy during the whole lifetime of the machine and the availability of monitoring systems developed following the Industry 4.0 trend are pushing the development of measurement systems that can be integrated in the machine to perform semi-automatic verification procedures that can be performed frequently by the machine user to monitor the condition of the machine. Calibrated artefact based calibration and verification solutions have an advantage in this field over laser based solutions in terms of cost and feasibility of machine integration, but they need to be optimized for each machine and customer requirements to achieve the required calibration uncertainty and minimize machine occupation time.This paper introduces a digital twin-based methodology to simulate all relevant effects in an artefact-based machine tool calibration procedure, from the machine itself with its expected error ranges, to the artefact geometry and uncertainty, artefact positions in the workspace, probe uncertainty, compensation model, etc. By parameterizing all relevant variables in the design of the calibration procedure, this simulation methodology can be used to analyse the effect of each design variable on the error mapping uncertainty, which is of great help in adapting the procedure to each specific machine and user requirements. The simulation methodology and the analysis possibilities are illustrated by applying it on a 3-axis milling machine tool.     

原油含水在线检测影响因素的研究

微波法作为原油开采过程中最常用的含水率检测方式,其检测效果极易受到实际开采环境中多因素影响从而产生检测误测。试验分析了矿化度以及温度两种实际开采环境下存在的因素对于微波实时检测含水率精度的影响。通过对试验数据的处理,运用二次拟合有效得出含水检测值伴随矿化度(矿化度组分:CaCl_2)的变化规律。利用试验所得规律,可有效将微波含水传感器精度提高,为提高微波含水检测精度的研究提供了校正参数和理论依据。