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.     

考虑特高压和复杂接线的直流偏磁风险治理

准东—皖南特高压直流工程是世界上首个±1 100kV特高压输电工程,避免其可能造成的直流偏磁风险意义重大。为此,结合安徽电网规划情况,对接地极附近165km范围内的大地构造调研和现场实测反演得到等效的土壤模型,依据场路耦合理论建立安徽电网交流系统直流电流分布计算模型,计算各个变电站主变中性点电流,分析了直流偏磁对安徽省交流电网影响范围、影响程度及主要的影响因素,并探讨了换流站和特高压站变压器受直流偏磁的影响,针对各电压等级变电站提出直流偏磁抑制措施,制定治理原则,进一步探究综合治理方案,从而使治理效果、治理经济性达到较好的平衡。     

Ferroelectric and electromechanical performance of diverse engineered states of Mn-doped 0.75Pb(Mg1/3Nb2/3)O3-0.25PbTiO3 ceramics

The materials processing history has a great influence on their properties and finally determines their application effect. In this paper, the ferroelectric, polarization-switching current, and strain properties of Mn-doped 0.75Pb(Mg_1/3Nb_2/3)O₃-0.25PbTiO₃ ceramics were studied in fresh state, aged state, and poled state, respectively. Compared with the symmetric polarization-electric-field (P-E) hysteresis loops, current-density-electric-field (J-E) curves, and bipolar electric-field-induced strain (S-E) curves in fresh state samples, asymmetric P-E loops, J-E curves, and bipolar S-E curves were obtained in poled state samples. Well-aged-state samples exhibit double hysteresis P-E loop, four peaks J-E curves, and symmetric S-E curves without negative strain. The symmetry-conforming short-range order (SC-SRO) principle of point defects and internal electric field E_i is employed to clarify the different phenomenon of three states. Results indicated that randomly oriented defect polarization P_D in aged samples can reverse the spontaneous polarization P_S back and result in the double hysteresis P-E loop and four peaks J-E curves. The oriented P_D and resulting E_i in poled-state samples will lead to the asymmetric loops and strain memory effect.     

Optimal asymmetrical back plane biasing for energy efficient digital circuits in 28 nm UTBB FD-SOI

In this work we propose an optimal back plane biasing (OBB) scheme to be used in a UTBB FD SOI technology that minimizes the energy per operation consumption of sub threshold digital CMOS circuits. By using this OBB scheme, simulations show that more than 30% energy savings can be obtained with low threshold voltage (LVT) devices in comparison with classic symmetric back plane biasing (SBB) schemes. Additionally, this OBB scheme allows to adjust the performance of the circuit with very small energy penalties. A very simple and intuitive model, for sub threshold digital CMOS circuits, was developed to justify the benefits obtained by OBB. The results predicted by the model are confirmed with extensive simulation results. We show that the OBB approach can be applied easily to a given circuit just based on the information provided by a logic simulation of the circuit (or even an analysis of its structure) and simple electrical simulations of the pMOS and nMOS transistors. Finally, we show that the variability in the energy consumption is improved by using OBB and suggests that new sizing methodologies must be studied to fully benefit from the wide back plane voltage range available in UTBB FD SOI technology for the design of robust energy efficient digital circuits.     

Ferroelectric Exchange Bias Affects Interfacial Electronic States

In polar oxide interfaces phenomena such as superconductivity, magnetism, 1D conductivity, and quantum Hall states can emerge at the polar discontinuity. Combining controllable ferroelectricity at such interfaces can affect the superconducting properties and sheds light on the mutual effects between the polar oxide and the ferroelectric oxide. Here, the interface between the polar oxide LaAlO₃ and the ferroelectric Ca-doped SrTiO₃ is studied by means of electrical transport combined with local imaging of the current flow with the use of scanning a superconducting quantum interference device (SQUID). Anomalous behavior of the interface resistivity is observed at low temperatures. The scanning SQUID maps of the current flow suggest that this behavior originates from an intrinsic bias induced by the polar LaAlO₃ layer. Such intrinsic bias combined with ferroelectricity can constrain the possible structural domain tiling near the interface. The use of this intrinsic bias is recommended as a method of controlling and tuning the initial state of ferroelectric materials by the design of the polar structure. The hysteretic dependence of the normal and the superconducting state properties on gate voltage can be utilized in multifaceted controllable memory devices.     

基于深度学习的安全缺陷报告预测方法实证研究

软件安全问题的发生在大多数情况下会造成非常严重的后果，及早发现安全问题，是预防安全事故的关键手段之一.安全缺陷报告预测可以辅助开发人员及早发现被测软件中潜藏的安全缺陷，从而尽早得以修复.然而，由于安全缺陷在实际项目中的数量较少，而且特征复杂（即安全缺陷类型繁多，不同类型安全缺陷特征差异性较大），这使得手工提取特征相对困难，并随后造成传统机器学习分类算法在安全缺陷报告预测性能方面存在一定的瓶颈.针对该问题，提出基于深度学习的安全缺陷报告预测方法，采用深度文本挖掘模型TextCNN和TextRNN构建安全缺陷报告预测模型；针对安全缺陷报告文本特征，使用skip-grams方式构建词嵌入矩阵，并借助注意力机制对TextRNN模型进行优化.所构建的模型在5个不同规模的安全缺陷报告数据集上展开了大规模实证研究，实证结果表明：深度学习模型在80%的实验案例中都要优于传统机器学习分类算法，性能指标F1-score平均可提升0.258，在最好的情况下甚至可以提升0.535.除此之外，针对安全缺陷报告数据集存在的类不均衡问题，对不同采样方法进行了实证研究，并对结果进行了分析.     

Dependence of mechanical and tribological performance on the microstructure of (CrAlTiNbV)Nx high-entropy nitride coatings in aviation lubricant

The (CrAlTiNbV)N_x coatings are fabricated by controlling the substrate bias via magnetron sputtering method. Under low substrate bias, the coating tends to form a loose columnar crystal structure with (200) preferred orientation. However, when the substrate bias increases, the coating transforms into a dense nanocrystalline structure, and the (111) orientation is enhanced. As the substrate bias increases, the residual stress and hardness of the coating gradually increase, while the adhesion strength decreases slightly. Friction tests show that the coating possesses the lowest average friction coefficient (about 0.06) and wear rate (8.7 × 10^-9 mm³/N·m) in 4050# aviation lubricant, which is achieved under the substrate bias of -96 V and -126 V, respectively.     

Potential effects of hormonal synchronized breeding on genetic evaluations of fertility traits in dairy cattle: A simulation study

About 30% of producers use hormone protocols to synchronize ovulation and perform timed artificial insemination (AI) in Canada. Days from calving to first service (CTFS) and first service to conception (FSTC) become masked phenotypes leading to biased genetic evaluations of cows for these fertility traits. The objectives of this study were to (1) demonstrate and quantify the potential amount of bias in genetic evaluations, and (2) find a procedure that could remove the bias. Simulation was used for both objectives. The proposed solution was to identify cows that have been treated by hormone protocols, make their CTFS and FSTC missing, and perform a multiple trait analysis including traits that have high genetic correlations with CTFS and FSTC, and which are not affected by the hormone protocols themselves. A total of 12 scenarios (S1–S12) were tested, changing the percentage of herds and cows that were randomly selected to be under timed AI. Cows that were given hormone protocols had CTFS of 86 d and FSTC of 0, which were used in genetic evaluation. Four criteria were used to indirectly measure the presence of bias: (1) the correlation between true (TBV) and estimated (EBV) breeding values (accuracy); (2) the differences in the mean EBV of top 25, 50, and 75 sires; (3) changes in correlation between TBV and EBV rankings; and (4) the changes in mean EBV over the simulated generations. All criteria changed unfavorably and proportionally to the increased use of timed AI. The accuracy within each class of animals (cows, dams, or sires) decreased proportionally with increased use of timed AI, varying from 0.32 (S12) to 0.52 (S1) for bull EBV for CTFS. The average EBV of the top sires (best 25, 50, 75, or 100 sires) approached population average EBV values when increasing the number of treated animals. The sire rank correlation between EBV and TBV within simulated scenarios was smaller for scenarios with more synchronized animals, going from 0.38 (S12) to 0.67 (S1). The long-term use of hormonal synchronized cows clearly decreased the mean EBV over generations in the population for CTFS and FSTC. The inclusion of genetically correlated traits in a multiple trait model was effective in removing the bias due to the presence of hormonal synchronized cows. However, given the constraints within the simulation, it is important that further investigation with real data is conducted to determine the true effect of including timed AI records within genetic evaluations of fertility traits in dairy cattle.     

Model Misspecification of Generalized Gamma Distribution for Accelerated Lifetime-Censored Data

Abstract

The performance of reliability inference strongly depends on the modeling of the product’s lifetime distribution. Many products have complex lifetime distributions whose optimal settings are not easily found. Practitioners prefer to use simpler lifetime distribution to facilitate the data modeling process while knowing the true distribution. Therefore, the effects of model mis-specification on the product’s lifetime prediction is an interesting research area. This article presents some results on the behavior of the relative bias (RB) and relative variability (RV) of pth quantile of the accelerated lifetime (ALT) experiment when the generalized Gamma (GG₃) distribution is incorrectly specified as Lognormal or Weibull distribution. Both complete and censored ALT models are analyzed. At first, the analytical expressions for the expected log-likelihood function of the misspecified model with respect to the true model is derived. Consequently, the best parameter for the incorrect model is obtained directly via a numerical optimization to achieve a higher accuracy model than the wrong one for the end-goal task. The results demonstrate that the tail quantiles are significantly overestimated (underestimated) when data are wrongly fitted by Lognormal (Weibull) distribution. Moreover, the variability of the tail quantiles is significantly enlarged when the model is incorrectly specified as Lognormal or Weibull distribution. Precisely, the effect on the tail quantiles is more significant when the sample size and censoring ratio are not large enough. Supplementary materials for this article are available online.     

Confirmation of odd sample bias in triadic design preference tests with a no-preference option,using confusable stimuli,and a solution

Two preference test methods utilizing triadic designs (i.e., presenting two identical products and a different product in a test) have been proposed to improve the validity of the paired preference test using a no-preference response option, by considering responses generated from preference bias (i.e., consumers’ responses are tilted toward a preference response rather than a no-preference response, resulting in the overestimation of preference responses). One of the test methods was the replicated duo-trio difference-preference (DT-Preference) test method, which had a balanced-reference design, while the other was the triadic preference test method. These two methods were designed to provide more conservative preference results in different ways. For the DT-Preference test method, it was assumed that the preference responses that were simply generated from the preference bias would also be prone to an odd sample bias (i.e., consumers tilted the preference against the stimulus that was most different from the other two) in the triadic design. For the triadic preference test method, the responses were screened out if the subjects reported a preference between the identical stimuli, assuming no bias in the triadic design. In the present study, the odd sample bias assumed in the triadic design was tested by the triadic preference test method and the DT-Preference test method by using two pairs of confusable orange juice stimuli assumed to have negligible preference by 256 consumers. For the DT-Preference test method, two variants of the duo-trio test designs were used. The odd sample bias was confirmed for all test methods using triadic designs, invalidating the application of the triadic preference test method without replication.