Feeding behavior parameters and temporal patterns in mid-lactation Holstein cows across a range of residual feed intake values

Residual feed intake (RFI) is a measurement of the difference between actual and predicted feed intake when adjusted for energy sinks; more efficient cows eat less than predicted (low RFI) and inefficient cows eat more than predicted (high RFI). Data evaluating the relationship between RFI and feeding behaviors (FB) are limited in dairy cattle; therefore, the objective of this study was to determine daily and temporal FB in mid-lactation Holstein cows across a range of RFI values. Mid-lactation Holstein cows (n = 592 multiparous; 304 primiparous) were enrolled in 17 cohorts at 97 ± 26 d in milk (± standard deviation), and all cows within a cohort were fed a common diet using automated feeding bins. Cow RFI was calculated as the difference between predicted and observed dry matter intake (DMI) after accounting for parity, days in milk, milk energy, metabolic body weight and change, and experiment. The associations between RFI and FB at the level of meals and daily totals were evaluated using mixed models with the fixed effect of RFI and the random effects of cow and cohort. Daily temporal FB analyses were conducted using 2-h blocks and analyzed using mixed models with the fixed effects of RFI, time, RFI × time, and cohort, and the random effect of cow (cohort). There was a positive linear association between RFI and DMI in multiparous cows and a positive quadratic relationship in primiparous cows, where the rate of increase in DMI was less at higher RFI. Eating rate, DMI per meal, and size of the largest daily meal were positively associated with RFI. Daily temporal analysis of FB revealed an interaction between RFI and time for eating rate in multiparous and primiparous cows. The eating rate increased with greater RFI at 11 of 12 time points throughout the day, and eating rate differed across RFI between multiple time points. There tended to be an interaction between RFI and time for eating time and bin visits in multiparous cows but not primiparous cows. Overall, there was a time effect for all FB variables, where DMI, eating time and rate, and bin visits were greatest after the initial daily feeding at 1200 h, increased slightly after each milking, and reached a nadir at 0600 h (6 h before feeding). Considering the relationship between RFI and eating rate, additional efforts to determine cost-effective methods of quantifying eating rate in group-housed dairy cows is warranted. Further investigation is also warranted to determine if management strategies to alter FB, especially eating rate, can be effective in increasing feed efficiency in lactating dairy cattle.     

C105管桩混凝土设计参数取值的探讨

通过试验得出了C105混凝土100 mm×100 mm×100 mm立方体非标准试件抗压强度换算系数以及C105混凝土的标准方差和强度变异系数。采用理论计算,得到了棱柱体抗压强度与立方体抗压强度的比值α_c1,并与试验实测平均值进行了比较,验证了理论计算方法的可行性。此外,通过对比分析,探讨了直接外延法和引用公式法两种C105混凝土设计参数计算方法的正确性,研究结果可为C105管桩混凝土的设计和应用提供参考。     

混凝土结构的压电声波检测分析

本文介绍了混凝土结构的压电体波和表面波检测的主要进展,对两种压电声波检测的优缺点进行了总结。体波检测设备一般埋入混凝土内部,需要选择合理的检测部位,检测结果较为精确;声表面波检测无需选择特定的部位,但是检测深度有限。在实际检测工作过程中,可以联合两种方法相互验证。     

用于电弧检测的电力专用SoC设计

针对传统的电弧电路故障检测结果不准确的问题,设计用于电弧检测的SoC系统,并且在55nm工艺下进行流片验证。采用包含两种结构的模数转换器的片上电压源,设计了锁相环以及复位电路,精度最高可达8.67 bit。验证结果表明,本设计可提高电弧检测的准确性。     

A novel 4D resolution imaging method for low and medium atomic number objects at the centimeter scale by coincidence detection technique of cosmic-ray muon and its secondary particles

The muon radiography imaging technique for high-atomic-number objects(Z) and large-volume objects via muon transmission imaging and muon multiple scattering imaging remains a popular topic in the field of radiation detection imaging. However, few imaging studies have been reported on low and medium Z objects at the centimeter scale. This paper presents an imaging system that consists of three layers of a position-sensitive detector and four plastic scintillation detectors. It acquires data by co...     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.     

缺水传感器改进设计

针对一种煤矿用本安型缺水传感器在现场安装及维护难度大,以及抽采泵供水状态下管道内有水但传感器检测显示为无水,或抽采泵停止工作时传感器检测显示有水问题,分析原产品中磁体及探头感应装置结构。改进其结构形式,并优化安装,使检测稳定可靠。实现抽采泵管道用缺水传感器的可靠性设计和轻量化设计。     

Neural Emotion Detection via Personal Attributes

There has been a recent line of work to automatically detect the emotions of posts in social media. In literature, studies treat posts independently and detect their emotions separately. Different from previous studies, we explore the dependence among relevant posts via authors' backgrounds, since the authors with similar backgrounds, e.g., "gender", "location", tend to express similar emotions. However, personal attributes are not easy to obtain in most social media websites. Accordingly, we propose two approaches to determine personal attributes and capture personal attributes between different posts for emotion detection: the Joint Model with Personal Attention Mechanism (JPA) model is used to detect emotion and personal attributes jointly, and capture the attributes-aware words to connect similar people; the Neural Personal Discrimination (NPD) model is employed to determine the personal attributes from posts and connect the relevant posts with similar attributes for emotion detection. Experimental results show the usefulness of personal attributes in emotion detection, and the effectiveness of the proposed JPA and NPD approaches in capturing personal attributes over the state-of-the-art statistic and neural models.     

Laser damage resistance of plasma-sprayed alumina and honeycomb skeleton/alumina composite ceramic coatings

Al₂O₃ and honeycomb skeleton-Al₂O₃ composite coatings on Titanium alloy (Ti–6Al–4V) were prepared by atmospheric plasma spraying. A laser ablation experiment on as-sprayed coatings was performed. In this paper, the laser damage resistance, microstructure, phase composition of Al₂O₃ coatings were examined. 3D Dimensional Confocal Microscopy, Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), and Energy Dispersive Spectrometry (EDS) characterized the laser damage morphology, microstructure, phase composition, and element analysis, respectively. The influence of the honeycomb skeleton on the laser ablation damage on as-sprayed coatings was investigated by a comparative analysis of the laser damage morphology with different laser ablation times and gas flow. The results show that the honeycomb skeleton raises thermal conductivity and thermal diffusivity. Moreover, a “tower”-like dendrite was generated during the laser irradiation of the composite coating. The honeycomb skeleton refined the structure, suppressed crack propagation, and reduced the influence of gas flow on cracks. Under the same experimental laser ablation parameters, the laser damage area of the honeycomb skeleton-Al₂O₃ composite coating was smaller than that of the Al₂O₃ coating. It was demonstrated that the laser damage resistance of the honeycomb skeleton-Al₂O₃ composite coating was superior to that of the Al₂O₃ coating.