Moderate lameness leads to marked behavioral changes in dairy cows

Lameness is one of the most prevalent diseases affecting the welfare of cows in modern dairy production. Lameness leads to behavioral changes in severely lame cows, which have been investigated in much detail. For early detection of lameness, knowledge of the effects of moderate lameness on cow behavior is crucial. Therefore, the behavior of nonlame and moderately lame cows was compared on 17 Swiss dairy farms. On each farm, 5 to 11 nonlame (locomotion score 1 of 5) and 2 to 7 moderately lame (locomotion score 3 of 5) cows were selected for data collection in two 48-h periods (A, B) separated by an interval of 6 to 10 wk. Based on visual locomotion scoring, 142 nonlame and 66 moderately lame cows were examined in period A and 128 nonlame and 53 moderately lame cows in period B. Between these 2 periods, the cows underwent corrective hoof trimming. Lying behavior, locomotor activity, and neck activity were recorded by accelerometers (MSR145 data logger, MSR Electronics GmbH, Seuzach, Switzerland), and feeding and rumination behaviors by noseband sensors (RumiWatch halter, ITIN + HOCH GmbH, Liestal, Switzerland). Furthermore, visits to the brush and the concentrate feeder, and the milking order position were recorded. In comparison with nonlame cows, moderately lame cows had a longer lying duration, a longer average lying bout duration, and a greater lateral asymmetry in lying duration. Average locomotor activity, locomotor activity during 1 h after feed delivery or push-ups, and average neck activity were lower in moderately lame cows. Eating time and the number of eating chews (jaw movements) were reduced in moderately lame compared with nonlame cows, whereas no effect of moderate lameness was evident for ruminating time, number of ruminating chews and boluses, and average number of ruminating chews per bolus. Moderately lame cows visited the concentrate feeder and the brush less frequently, and they were further back in the milking order compared with nonlame cows. In conclusion, nonlame and moderately lame cows differed in a biologically relevant way in many of the behavioral variables investigated in this study. Therefore, the use of these behavioral changes seems to be promising to develop a tool for early lameness detection.     

利拉鲁肽对急性心肌梗死PCI术后心肌的保护作用

目的: 探讨利拉鲁肽对急性心肌梗死（AMI）经皮冠状动脉介入术（PCI）术后心肌的保护作用。 方法: 将110例于我院就诊的初发AMI并发应激性高血糖的患者分为两组，各55例；在常规标准治疗的基础上，观察组患者给予利拉鲁肽治疗，对照组患者采用胰岛素治疗；分别于PCI术前以及术后测定血液肌酸磷酸激酶（CK）、血肌酸激酶同工酶（CKMB）、肌钙蛋白T（cTnT）、B型利钠肽前体（NT-pro-BNP）及超敏C反应蛋白（hs-CRP）比较心肌损伤情况；测定术后7 d及30 d的心肌灌注缺损积分、左心室射血分数（LVEF）、左心室舒张末期内径（LVEDD）比较心功能恢复情况。结果: 两组患者术后CK、CKMB、cTnT、hs-CRP均明显升高（P<0.05），NT-pro-BNP明显降低（P<0.05），观察组48 h峰值明显低于对照组（t=5.188、7.081、2.180、5.091、4.748, P<0.05）；心肌灌注缺损积分两组术后30 d指标较7 d时降低，对照组下降明显（t=7.963,P<0.05），术后7 d观察组明显低于对照组（t=6.235,P<0.05）。LVEF、LVEDD术后30 d指标较7 d时升高，观察组LVEF差异显著（t=2.016,P<0.05）；同期组间比较，术后30 d LVEF差异显著（t=2.032,P<0.05），其余差异不明显（P>0.05）。结论:利拉鲁肽可在AMI患者PCI术后对心肌发挥一定的保护作用。     

建筑工程地基检测技术要点分析及优化对策

针对建筑工程的地基检测技术进行重点分析,并且相应的提出了检测技术的优化对策,以此来促进建筑工程得以顺利发展。     

基于局部放电法的矿用高压电缆信号去噪算法研究

干扰噪声直接影响局部放电法有效检测矿用高压电缆故障。基于局部放电法，综合采用理论计算、仿真实验、现场试验的方法，对比分析了短时傅里叶变换和傅里叶分析去噪法的原理和优缺点，提出了一种矿用高压电缆的局部放电去噪算法——小波阈值去噪法，同时，选择了合理的阈值函数和去噪流程。基于此，采用白噪声和连续周期信号作为高压电缆的干扰噪声，进行了模拟仿真实验。结果表明，小波阈值去噪法可有效抑制白噪声，其中，Db2小波性能和去噪效果最好；同时，现场试验结果显示，去噪后信噪比得到了显著增加，验证了小波阈值去噪法的合理性和可靠性。     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.     

A Combined Ordered Macro‐Mesoporous Architecture Design and Surface Engineering Strategy for High‐Performance Sulfur Immobilizer in Lithium–Sulfur Batteries

The practical application of lithium–sulfur (Li–S) batteries is hindered by the “shuttle” of lithium polysulfides (LiPS) and sluggish Li–S kinetics issues. Herein, a synergistic strategy combining mesoporous architecture design and defect engineering is proposed to synthesize multifunctional defective 3D ordered mesoporous cobalt sulfide (3DOM N‐Co₉S_8?x) to address the shuttling and sluggish reaction kinetics of polysulfide in Li–S batteries. The unique 3DOM design provides abundant voids for sulfur storage and enlarged active interfaces that reduce electron/ion diffusion pathways. Meanwhile, X‐ray absorption spectroscopy shows that the surface defect engineering tunes the CoS₄ tetrahedra to CoS₆ octahedra on Co₉S₈, endowing abundance of S vacancies on the Co₉S₈ octahedral sites. The ever‐increasing S vacancies over the course of electrochemical process further promotes the chemical trapping of LiPS and its conversion kinetics, rendering fast and durable Li–S chemistry. Benefiting from these features, the as‐developed 3DOM N‐Co₉S_8?x/S cathode delivers high areal capacity, superb rate capability, and excellent cyclic stability with ultralow capacity fading rate under raised sulfur loading and low electrolyte content. This design strategy promotes the development of practically viable Li–S batteries and sheds lights on the material engineering in related energy storage application.     

基于机器视觉的手机电池表面缺陷检测

针对手机电池表面质量人工检测情况,开发了电池表面缺陷无损检测系统软件。首先电池表面经过倾斜矫正、感兴趣区域提取和字符灰度值修改等预处理操作,通过基于灰度密度分布和灰度差的自适应阈值亮度法对感兴趣区域进行子图像遍历,融合有重合区域的缺陷子图像并滤除没有明显缺陷的区域;然后采用支持向量机多种类分类法,提取二值图像像素分布规律作为训练特征,识别电池表面缺陷种类;最后设计了人机交互界面,确定最佳的可变参数,实验测试缺陷识别率达95%以上。     

Occurrence and diversity of Listeria spp. in seafood processing plant environments

Listeria contamination in processing plant environments is a major issue for the seafood industry worldwide; faster and more reliable results are therefore desired for early detection and monitoring of environmental Listeria spp. This study aimed to gain a better understanding of the prevalence and diversity of Listeria spp., and to evaluate a rapid detection method, the 3M Molecular Detection Assay (MDA) Listeria, for its ability to detect Listeria spp. in environmental samples from seafood processing plants. Duplicate environmental sponge samples (n = 444) were collected from 152 different sites within three seafood processing plants, and analyzed for Listeria spp. by the MDA method (after 26 and 48 h of enrichment) and the U.S. Food and Drug Administration Bacteriological Analytical Manual method. Overall, detection of Listeria spp. by the two methods did not differ significantly (p > 0.05); 11 (4.9%) and 13 (5.9%) samples were positive for Listeria spp. by the MDA and FDA-BAM method, respectively. The sensitivity of the MDS was 87.0% (95% CI: 77.4–96.6%), specificity was 97.6% (95% CI: 95.5–99.7%), accuracy was 95.3%, and the positive predictive value was 89.4% (95% CI: 80.5–98.2%). Classification of 19 Listeria isolates by partial SigB sequencing analysis identified three allelic types. Twelve of these isolates were ATs 58 and 60 which were classified as Listeria monocytogenes lineage I and serotypes 1/2b, 3b, 4b, 4d, 4e, by multiplex-PCR serotyping. Six Listeria isolates were classified as Listeria innocua (AT31). Our data show that the 3M Molecular Detection Assay Listeria provides rapid and reliable results for detection and monitoring of Listeria spp., which are important for seafood processing plants. Effective Listeria monitoring programs will allow for improved development of Listeria control measures in order to minimize cross-contamination in finished products.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.