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.     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

基于Massive MIMO及频谱叠加的5G SA网络上行优化方法

大规模多输入多输出(Multiple-Input Multiple-Output, MIMO)可以有效提升5G SA网络的上行链路数据传输速率以及可靠性。针对5G SA网络上行链路速率和覆盖不均衡的情况,提出了基于大规模MIMO的分组算法,将发送信号矢量进行分组,组内采用最大似然检测,组外采用基于正交三角分解(QR分解)的干扰消除检测,并且结合5G频谱的叠加策略,在降低算法复杂度的同时,有效提升网络覆盖和速率。通过5G SA现网实测,通过MIMO降低分组数量能够提升分组检测性能,结合上行低频段频谱叠加策略能够有效提升5G SA网络上行覆盖30%,提升5G SA网络上行平均速率40%~80%,特别是弱覆盖边缘的网络速率,最高可达600%。     

浅谈拆除爆破工程中存在的问题和对策

拆除爆破工程的广泛应用为社会主义经济建设提供了有益的帮助,充分体现了科学技术是第一生产力。但是在拆除爆破领域也存在不少问题,如设计、施工、安全防护、爆破器材管理、爆破理论研究等方面还有许多不足,这需要我们认真正视,并采取切实有效的对策加以解决。文中针对存在的问题提出了一些对策,可以为拆除爆破界的同行们借鉴。     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Analytical approach on magnetohydrodynamic Casson fluid flow past a stretching sheet via Adomian decomposition method

Flow phenomena of three-dimensional conducting Casson fluid through a stretching sheet are proposed in the present investigation with the impact of the magnetic parameter in a permeable medium. The adaptation of particular transformations is useful to modify the governing equations into their nondimensional as well as the ordinary form. However, these transformed equations are nonlinear and approximate analytical methods for the solution of the complex form of governing equations. In particular, the Adomian decomposition method is proposed for the solution. The behavior of several variables, such as the magnetic and porous matrix, on the flow profile as well as the rate of shear stress, are discussed via graphs and tables. The conformity of the current result with the earlier study shows a road map for further investigation. The major concluding remarks are; the retardation in the velocity distribution is rendered due to an increase in the Casson parameter moreover, the Casson parameter favors in reducing the rate of shear stress coefficient in magnitude.     

Coal char gasification for co-production of fuel gas and methane decomposition catalysts

Partial gasification of coal char was conducted with addition of metal oxides for co-production of fuel gas and methane decomposition catalysts. Effect of the metal composition (Ni, Co and Fe based mono- or bi-metals) was investigated on the fuel gas production and the resultant catalyst surface and textural properties, morphology and performance in catalytic methane decomposition (CMD). Besides H₂-rich fuel gas production (the combustion energy up to 11.03–23.42 MJ/kg_char) from the gasification, the gasification residue can directly serve as the effective and efficient catalyst for CMD. The Fe and Fe–Co composite oxides were found to be better among the mono- and bi-metallic oxides for the fuel gas production during the gasification, respectively. The Ni-based mono-/bi-metallic catalysts could display high and stable methane conversion (up to 80%) during the 600-min CMD test at 850 °C. Promotional role of the second metal in CMD was discussed on the carbon diffusion, metal mobility and reducibility, formation and growth of the deposited carbons. The formed carbon morphology after CMD was analyzed based on the Kirkendall effect and Tammann temperature and further correlated to the potential catalyst deactivation.     

The Tumor Proteolytic Landscape: A Challenging Frontier in Cancer Diagnosis and Therapy

In recent decades, dysregulation of proteases and atypical proteolysis have become increasingly recognized as important hallmarks of cancer, driving community-wide efforts to explore the proteolytic landscape of oncologic disease. With more than 100 proteases currently associated with different aspects of cancer development and progression, there is a clear impetus to harness their potential in the context of oncology. Advances in the protease field have yielded technologies enabling sensitive protease detection in various settings, paving the way towards diagnostic profiling of disease-related protease activity patterns. Methods including activity-based probes and substrates, antibodies, and various nanosystems that generate reporter signals, i.e., for PET or MRI, after interaction with the target protease have shown potential for clinical translation. Nevertheless, these technologies are costly, not easily multiplexed, and require advanced imaging technologies. While the current clinical applications of protease-responsive technologies in oncologic settings are still limited, emerging technologies and protease sensors are poised to enable comprehensive exploration of the tumor proteolytic landscape as a diagnostic and therapeutic frontier. This review aims to give an overview of the most relevant classes of proteases as indicators for tumor diagnosis, current approaches to detect and monitor their activity in vivo, and associated therapeutic applications.     

Optical design of the Lyman alpha based beam emission spectroscopy(LAB)diagnostic on the HL-2A tokamak

In this article, we present the optical design of a novel diagnostic on the HL-2 A tokamak, i.e. the20-channel edge Lyman-alpha beam emission spectroscopy, which is a promising solution for edge density turbulence research on tokamaks, as it offers the possibility of density fluctuation measurement with a 3.3 mm spatial resolution while maintains a high temporal resolution of1 μs. The optical path, including the reflective collection optics, the high-dispersion spectrometer, and the linear detector array, is carefully optimized to obtain a good image quality and a high throughput. The maximum root mean square radius of the collection optics is 64 μm.The detected photon flux is estimated to be about 10~(11) photons/s/channel.     

A customized low-rank prior model for structured cartoon–texture image decomposition

The mathematical characterization of the texture component plays an instrumental role in image decomposition. In this paper, we are concerned with a low-rank texture prior based cartoon–texture image decomposition model, which utilizes a total variation norm and a global nuclear norm to characterize the cartoon and texture components, respectively. It is promising that our decomposition model is not only extremely simple, but also works perfectly for globally well-patterned images in the sense that the model can recover cleaner texture (or details) than the other novel models. Moreover, such a model can be easily reformulated as a separable convex optimization problem, thereby enjoying a splitting nature so that we can employ a partially parallel splitting method (PPSM) to solve it efficiently. A series of numerical experiments on image restoration demonstrate that PPSM can recover slightly higher quality images than some existing algorithms in terms of taking less iterations or computing time in many cases.