Numerical study of microscopic particle arrangement of suspension flow in a narrow channel for the estimation of macroscopic rheological properties

In a narrow channel, the apparent relative viscosity of a suspension with finite-size particles is strongly dependent on its microscopic particle arrangement. Relative viscosity increases when suspended particles flow near the channel wall; thus, a suspension in a narrow channel does not always exhibit the same rheological properties even if the concentration is the same. In this study, we focus on the inertia and concentration of particles in a narrow channel and consider their effects on the microscopic particle arrangement and macroscopic suspension rheology. Two-dimensional pressure-driven suspension flow simulations were performed using a two-way coupling scheme, and normalized particle density distribution (PDD) were implemented to consider their particle arrangements. The results demonstrated that the velocity profiles for the particle suspension were changed by the Reynolds number and particle concentration because of the interactions between particles according to the power-law index. These changes affected the particle equilibrium positions in the channel, and the subsequent changes in solvent layer thickness caused changes in the macroscopic apparent viscosity. The behavior of microscopic particles played important roles in determining macroscopic rheology. Thus, we have confirmed that a normalized PDD can be used to estimate and assess the macroscopic rheology of a suspension.     

A NEW OIL SEEPAGE IN THE OMAN MOUNTAINS AND ITS GEOLOGICAL,GEOCHEMICAL AND PETROLEUM SYSTEMS CONTEXT

A minor natural oil seepage is described from an unlikely setting in the Oman Mountains. The host rocks are fractured pelagic limestones of the lower member of the Triassic – Lower Jurassic Matbat Formation of the Hamrat Duru Group in the lower part of the allochthonous Hawasina Complex. This paper summarises Oman's established oil families and documents previously recorded oil seepages as context for describing the new seepage, its geochemistry, and possible source rock. The seep oil is different to those known from Oman's oil fields and probably derived from a poor quality, Mesozoic clastic source rock containing a mix of terrigenous and marine organic matter. The most likely source appears to be the Toarcian turbiditic upper member of the Matbat Formation, equivalent to the clastic Mafraq Formation of the Arabian Platform. The occurrence of source rocks in the allochthonous sediments of the NeoTethyan Hawasina Basin has been suspected previously, though their commercial significance remains to be established.     

A blockchain-based audit approach for encrypted data in federated learning

The development of data-driven artificial intelligence technology has given birth to a variety of big data applications. Data has become an essential factor to improve these applications. Federated learning, a privacy-preserving machine learning method, is proposed to leverage data from different data owners. It is typically used in conjunction with cryptographic methods, in which data owners train the global model by sharing encrypted model updates. However, data encryption makes it difficult to identify the quality of these model updates. Malicious data owners may launch attacks such as data poisoning and free-riding. To defend against such attacks, it is necessary to find an approach to audit encrypted model updates. In this paper, we propose a blockchain-based audit approach for encrypted gradients. It uses a behavior chain to record the encrypted gradients from data owners, and an audit chain to evaluate the gradients’ quality. Specifically, we propose a privacy-preserving homomorphic noise mechanism in which the noise of each gradient sums to zero after aggregation, ensuring the availability of aggregated gradient. In addition, we design a joint audit algorithm that can locate malicious data owners without decrypting individual gradients. Through security analysis and experimental evaluation, we demonstrate that our approach can defend against malicious gradient attacks in federated learning.     

有砟轨道路基翻浆冒泥模型试验系统的研发与应用

为研究既有线有砟轨道路基的翻浆冒泥机理，自主研发了一套能够模拟循环荷载–湿化耦合作用的模型试验系统。模型试样直径500 mm，由厚度分别为350 mm的路基土和200 mm的道砟组成，整个试样在高强度透明有机玻璃模型筒中制备完成。模型试验系统配备有监测荷载、位移、体积含水率和孔隙水压力的4种传感器，并通过高清相机对颗粒迁移过程进行图像捕捉。基于所研发的试验系统，针对辛泰铁路典型翻浆冒泥病害路段土样，开展翻浆冒泥模型试验。试验结果表明：动孔隙水压力是导致翻浆冒泥病害产生的关键因素。随着体积含水率的增加，动孔隙水压力引起的颗粒迁移量逐渐增加；在饱和状态下，会引起大量颗粒迁移，翻浆冒泥现象显著。试验结束时，道砟污染指数达到25%，在实际工程中已严重影响铁路的正常运营，有必要对污染道砟进行换填。     

Can regional policies shape migration flows?

Our empirical analysis focuses on the effect of regional policies on migration attraction factors in Europe. We employ a regression discontinuity design to assess the causal relationship between the reception of large amounts of public funds and migration flows in the EU-15 regions. In highly-subsidised regions, we find a large increase in the share of foreign citizens from less-developed countries when compared to low-subsidised regions with similar pre-treatment characteristics. The analysis shows that such an increase is due to the positive impact of the European regional policy on job market opportunities as well as the improvement of public goods supply.     

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.     

异种铁素体耐热钢接头界面组织及其影响

综述了铁素体与铁素体异种金属焊缝（dissimilar metal welds，DMWs）接头界面组织及其影响。结果表明，在焊后热处理或运行温度下的铁素体钢DMWs接头的不均匀界面组织中，通常会形成脱碳层和增碳层。在铁素体钢DMWs焊接接头界面组织影响因素中，焊缝金属的化学成分有重要影响；焊后热处理规范（温度和时间）、工作温度下运行时间的影响较为突出；焊接工艺参数的影响亦不可忽略。异种钢接头界面处近缝区裂纹的产生，以及接头的蠕变强度随Larson Miller 参数增大而下降等不利影响，均为异种钢界面碳迁移行为所导致。焊缝成分控制法是接头界面组织控制或改善的必要条件，而脱碳层部位转移法能有效防止裂纹发生，亦是接头安全运行的重要工艺措施之一。     

超高效液相色谱⁃四极杆⁃飞行时间质谱对含PET食品接触材料中可迁移非挥发性物质的筛查研究

采用超高效液相色谱⁃四极杆⁃飞行时间高分辨质谱（UPLC⁃Q⁃TOF）对4类不同类型的含聚对苯二甲酸乙二醇酯（PET）材质的食品接触材料在4 %乙酸和50 %乙醇模拟物中的迁移出的非挥发性未知物进行筛查解析。结果表明，产品在4 %乙酸模拟物的迁移风险远小于50 %乙醇模拟物，主要迁移物质为聚合单体形成的寡聚物，抗氧剂、润滑剂、胶黏剂等加工助剂以及生产加工、迁移过程中形成的非有意添加物（NIAS）物质；纯PET材质的产品迁移物质较少，多层复合材料迁移物质较多。复合材质的产品中，PET材质可能在生产时添加了己二酸、癸二酸、新戊二醇等物质，进行了改性处理；此外，部分迁移物质会与模拟物中的乙醇发生反应，生成新的NIAS物质。     

ROS-Mediated Anti-Tumor Effect of Coptidis Rhizoma against Human Hepatocellular Carcinoma Hep3B Cells and Xenografts

Coptidis Rhizoma is the dried rhizome from the Coptis chinensis Franch. that has been shown to have a number of beneficial pharmacological properties including antioxidant, anti-inflammatory, and anti-cancer effects. However, the anti-cancer effects of Coptidis Rhizoma on hepatocellular carcinoma (HCC) remain unclear. In this study, we investigated the anti-cancer properties of Coptidis Rhizoma ethanol extract (CR) in HCC Hep3B cells and in a xenograft mouse model. Our results showed that the CR significantly inhibited cell growth and induced apoptosis in Hep3B cells through increased expression of Bcl-2 associated x-protein (Bax) and cleavage of poly-ADP ribose polymerase (PARP), reduced expression of Bcl-2, and activated caspases. CR also increased the generation of intracellular reactive oxygen species (ROS), which caused a loss of mitochondrial membrane potential (MMP, ΔΨm) and activation of the mitochondria-mediated intrinsic apoptosis pathway. Moreover, N-acetylcysteine (NAC), a ROS inhibitor, markedly blocked the effects of CR on apoptotic pathways. CR also induced the expression of light chain 3 (LC3)-I/II, a key autophagy regulator, whereas CR-mediated autophagy was significantly suppressed by NAC. In addition, pre-treatment with NAC perfectly attenuated the inhibition of cell invasion and migration of CR-stimulated Hep3B cells. Furthermore, oral administration of CR suppressed Hep3B tumor growth in xenograft mice without toxicity, alterations to body weight, or changes in hematological and biochemical profiles. Taken together, our findings suggest that CR has anti-tumor effects that result from ROS generation, and may be a potential pharmacological intervention for HCC.     

安卓平台上的医用图像信息采集系统的开发设计

为了探讨在安卓平台上构建医用图像采集系统的开发个案,分析通过以智能手机、平板电脑为核心安卓设备通过拍照获得化验单数据后进行文本识别并提交智慧医疗系统的解决方案。本文首先通过二值化算法形成低阈值图像数据,使用卷积神经元网络算法对文本进行逐一识别,使用K-means算法对识别后的单字文本进行字段记录值的整合并形成元数据库服务于其他智慧医疗系统模块。在使用9000组数据对神经元网络进行前期训练的前提下,该系统的识别准确率达到了99.5%以上。本系统具有一定的可行性,对未来智慧医疗的系统开发有实践意义。