Genetic (co-)variation of methane emissions,efficiency, and production traits in Danish Holstein cattle along and across lactations

Methane emissions in ruminant livestock has become a hot topic, given the pressure to reduce greenhouse gas emissions drastically in the European Union over the next 10 to 30 yr. During the 2021 United Nations Climate Change conference, countries also made collective commitments to curb methane emissions by 2050. Genetic selection for low-methane-emitting animals, particularly dairy cows, is one possible strategy for mitigation. However, it is essential to understand how methane emissions in lactating animals vary along lactation and across lactations. This understanding is useful when making decisions for future phenotyping strategies, such as the frequency and duration of phenotyping within and across lactations. Therefore, the objectives of this study were to estimate (1) genetic parameters for 2 methane traits: methane concentration (MeC) and methane production (MeP) at 2 parity levels in Danish Holstein cows across the entire lactation using random regression models; (2) genetic correlations within and between methane traits across the entire lactation; and (3) genetic correlations between the methane traits and economically important traits throughout first lactation. Methane concentration (n = 19,639) records of 575 Danish Holstein cows from a research farm measured between 2013 and 2020 were available. Subsequently, CH₄ production in grams/day (MeP; n = 13,866) was calculated; MeP and MeC for first and second lactation (L1 and L2) were analyzed as separate traits: MeC_L1, MeP_L1, MeC_L2, and MeP_L2. Heritabilities, variance components, and genetic correlations within and between the 4 CH₄ traits were estimated using random regression models with Legendre polynomials. The additive genetic and permanent environmental effects were modeled using second-order Legendre polynomial for lactation weeks. Estimated heritabilities for MeP_L1 ranged between 0.11 and 0.49, for MeC_L1 between 0.10 and 0.28, for MeP_L2 between 0.14 and 0.36, and for MeC_L2 between 0.13 and 0.29. In general, heritability estimates of MeC traits were lower and more stable throughout lactation and were similar between lactations compared with MeP. Genetic correlations (within trait) at different lactation weeks were generally highly positive (0.7) for most of the first lactation, except for the correlation of early lactation (<10 wk) with late lactation (>40 wk) where the correlation was the lowest (<0.5). Genetic correlations between methane traits were moderate to highly correlated during early and mid lactation. Finally, MeP_L1 has stronger genetic correlations with energy-corrected milk and dry matter intake compared with MeC_L1. In conclusion, both traits are different along (and across) lactation(s) and they correlated differently with production, maintenance, and intake traits, which is important to consider when including one of them in a future breeding objective.     

Measurement of heat transfer coefficients for steam condensation on a vertical 21.5-mm-O.D. tube in the presence of air

ABSTRACT

Governing the rate of heat transport by condenser tubes in the passive containment cooling system (PCCS), the steam condensation over a vertical cylinder in the presence of air was investigated experimentally. The main objective of this study was to explore if the condensation heat transfer coefficient relies on the tube dimension, which has been a variable missed in most condensation models or has been embraced without experimental demonstration under phase change environments. The mean heat transfer coefficient was measured in the condensation test facility named JERICHO (JNU Experimental Rig for Investigation of Condensation Heat transfer On tube). The outer diameter of the condenser tube used in this study was set to 21.5 mm. The measured heat transfer coefficients were compared to those obtained from the 40-mm-O.D. tube, and a multiplier to correct the variation of the heat transfer coefficient with the tube diameter was proposed for its application to Lee correlation. The proposed correlation was further validated against another set of experimental data obtained from a separate test facility housing the 31.8-mm-O.D. tube.     

High-speed,two-dimensional digital image correlation algorithm using heterogeneous (CPU-GPU) framework

Two-dimensional digital image correlation (2D-DIC) is an experimental technique used to measure in-plane displacement of a test specimen. Real-time measurement of full-field displacement data is challenging due to enormous computational load of the algorithm. In order to improve the computational speed, the focus of recent research works has been on the approach of parallelization across subsets within image pairs using graphics processing unit (GPU). But alternate GPU-based parallelization approaches to improve the performance of this algorithm as per the order of data processing have not been explored. To address this research gap, our method utilizes parallelism within a subset as well as across subsets for each computation step in an iteration cycle. A heterogeneous (CPU-GPU) framework in combination with a pyramid-based initial values estimation for subsets (in parallel) is proposed in this work. The precompute steps of the proposed framework are implemented using CPU, whereas the main iterative steps are realized using GPU. It is demonstrated that the overall computational speed of the proposed heterogeneous framework improves by compared to a sequential CPU-based implementation for a pair of gray-scale images with a resolution of pixels. As an important milestone, feasibility to measure deformations in real time ( 1 s) is manifested in this study.     

海水源热泵抛管式换热器管外传热特性研究

为给海水源热泵抛管式换热器的优化设计提供理论依据,通过计算流体力学(CFD)数值软件对该系统中的流动和传热过程进行数值模拟。结果表明,管内对流换热努谢尔特数Nui随抛管曲率比δ、无因次节距H_o的增大而减小;管外Nu_o随δ、H_o的增大而减小,而且δ和H_o对Nu_o的影响是复杂非线性关系。在一定模拟工况下,管外表面传热系数比管内小,热阻比管内大,换热器传热性能的决定性因素在管外,基于此,该文通过数值模拟拟合出适于南海岛礁海水源热泵抛管式换热器管外传热准则关联式。     

Multi-Purpose Forensics of Image Manipulations Using Residual- Based Feature

The multi-purpose forensics is an important tool for forge image detection. In this paper, we propose a universal feature set for the multi-purpose forensics which is capable of simultaneously identifying several typical image manipulations, including spatial low-pass Gaussian blurring, median filtering, re-sampling, and JPEG compression. To eliminate the influences caused by diverse image contents on the effectiveness and robustness of the feature, a residual group which contains several highpass filtered residuals is introduced. The partial correlation coefficient is exploited from the residual group to purely measure neighborhood correlations in a linear way. Besides that, we also combine autoregressive coefficient and transition probability to form the proposed composite feature which is used to measure how manipulations change the neighborhood relationships in both linear and non-linear way. After a series of dimension reductions, the proposed feature set can accelerate the training and testing for the multipurpose forensics. The proposed feature set is then fed into a multi-classifier to train a multi-purpose detector. Experimental results show that the proposed detector can identify several typical image manipulations, and is superior to the complicated deep CNN-based methods in terms of detection accuracy and time efficiency for JPEG compressed image with low resolution.     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

基于水位和水位—流量关系的险情状态分析评估

为了正确分析评估防汛抢险中抢护后的管涌、漏洞等险情状态，根据防汛抢险实践和相关溃口失事案例，分析评估了流量与水位正、负相关时和无法观测流量时水位对险情状态的影响程度。水位的涨落及水位与堤内出险处流量的相关关系，对险情分析与状态评估具有一定的参考价值和提示作用。出险处流量随水位的上涨（下降）而增加（减少）时应注意观测围井内的含沙量和反滤料的变化情况，并排查该处险情附近区域有无新的险情，或已发生的新险情处理后有无异常迹象。     

基于消息队列的通信系统异步传送控制仿真

传统方法对通信系统异步传送控制效果不佳,存在信号干扰及传送时间间隔较长等问题。为此引入消息队列技术,提出一种新的传送控制方法来解决以上问题。对通信系统的空时信道进行空时编码设计,实现空时信道的编码增益与分集增益;利用空时编码实现通信系统中继节点的空间分集,根据空间分集结果制订异步空时传送方案;采用消息队列技术构建通信系统异步传送控制模型,实现通信系统的异步传送控制。为了验证所提方法异步传送控制效果,设计对比实验。实验结果表明,上述方法的传送时间间隔较短,抗干扰能力强,平均分集增益高,说明所提方法更适用于通信系统的异步传送控制。     

A review of topic modeling methods

Topic modeling is a popular analytical tool for evaluating data. Numerous methods of topic modeling have been developed which consider many kinds of relationships and restrictions within datasets; however, these methods are not frequently employed. Instead many researchers gravitate to Latent Dirichlet Analysis, which although flexible and adaptive, is not always suited for modeling more complex data relationships. We present different topic modeling approaches capable of dealing with correlation between topics, the changes of topics over time, as well as the ability to handle short texts such as encountered in social media or sparse text data. We also briefly review the algorithms which are used to optimize and infer parameters in topic modeling, which is essential to producing meaningful results regardless of method. We believe this review will encourage more diversity when performing topic modeling and help determine what topic modeling method best suits the user needs.     

Development and evaluation of sub-element testing of SiC/SiC ceramic matrix composites at elevated temperatures

SiC/SiC ceramic matrix composites (CMCs) are being developed for use in aero-engines to replace nickel superalloy components. Sub-element testing acts as the key stepping stone in bridging understanding derived from basic coupon testing and more complex component testing. This study presents the development of high temperature C-shape sub-element testing with the use of digital image correlation to study damage progression. The specimen is designed with a bias towards a mixed mode-stress state more similar to what a CMC component may see in service. Both monotonic and fatigue tests were completed on C specimens and compared with predicted behaviour from modelling. Test data from both test types suggested that specimens were failing once they reached a critical radial stress level. However evidence from fractography of specimens showed that in both monotonic and fatigue tests radial cracks (driven by hoop stresses) are initiating prior to circumferential cracks.