Analysis of pressure and heat distribution in a dilating or contracting filter chamber with two outlets using multivariate spectral quasilinearization method

The development of efficient filters is an essential part of industrial machinery design, specifically to increase the lifespan of a machine. In the filter chamber design considered in this study, the magnetic material is placed along the horizontal surface of the filter chamber. The inside of the filter chamber is layered with a porous material to restrict the outflow of unwanted particles. This study aims to investigate the flow, pressure, and heat distribution in a dilating or contracting filter chamber with two outlets driven by injection through a permeable surface. The proposed model of the fluid dynamics within the filter chamber follows the conservation equations in the form of partial differential equations. The model equations are further reduced to a steady case through Lie's symmetry group of transformation. They are then solved using a multivariate spectral-based quasilinearization method on the Chebyshev–Gauss–Lobatto nodes. Insights and analyses of the thermophysical parameters that drive optimal outflow during the filtration process are provided through the graphs of the numerical solutions of the differential equations. We find, among other results, that expansion of the filter chamber leads to an overall decrease in internal pressure and an increase in heat distribution inside the filter chamber. The results also show that shrinking the filter chamber increases the internal momentum inside the filter, which leads to more outflow of filtrates.     

基于改进灰狼优化算法的服务功能链映射算法

随着工业互联网、车联网、元宇宙等新型互联网应用的兴起，网络的低时延、可靠性、安全性、确定性等方面的需求正面临严峻挑战。采用网络功能虚拟化技术在虚拟网络部署过程中，存在服务功能链映射效率低与部署资源开销大等问题，联合考虑节点激活成本、实例化开销，以最小化平均部署网络成本为优化目标建立了整数线性规划模型，提出基于改进灰狼优化算法的服务功能链映射（improved grey wolf optimization based service function chain mapping，IMGWO-SFCM）算法。该算法在标准灰狼优化算法基础上添加了基于无环K最短路径（K shortest path，KSP）问题算法的映射方案搜索、映射方案编码以及基于反向学习与非线性收敛改进三大策略，较好地平衡了其全局搜索及局部搜索能力，实现服务功能链映射方案的快速确定。仿真结果显示，该算法在保证更高的服务功能链请求接受率下，相较于对比算法降低了11.86%的平均部署网络成本。     

Frequency response data-based peak filter design applied to MIMO large-scale high-precision scan stage

A large-scale high-precision scan stage is important equipment in the industrial productions of micro-fabrication such as flat panel display (FPD) lithography systems. Designing controllers for multi-input multi-output (MIMO) systems is time-consuming and needs experience because of the interaction between each axis and many controller tuning parameters. The aim of this study is to develop a peak filter design method based on frequency response data to reduce repetitive disturbance. This data-based approach does not use the model and only uses the frequency response data of the controlled system and the disturbance spectrum calculated from the scanning error data (Contribution 1). The peak filter is designed by convex optimization and satisfies robust stability conditions for six-degree-of-freedom systems (Contribution 2). The control performance of the designed peak filter is experimentally demonstrated with an industrial MIMO large-scale high-precision scan stage in reducing the scanning error of the main stroke of the translation along the $x$-axis (Contribution 3).     

Cornus officinalis vinegar reduces body weight and attenuates hepatic steatosis in mouse model of nonalcoholic fatty liver disease

This study aimed to determine the main bioactive components of Cornus officinalis vinegar (COV) and assess the effects of COV on the body weight (BW) and hepatic steatosis in a nonalcoholic fatty liver disease (NAFLD) mouse model. Seven-week-old KM female mice were divided into five treatment groups: (1) Normal control (NC) group, (2) high fat diet (HFD) group, (3) low concentration treatment group (3.5% COV), (4) medium concentration treatment group (5.0% COV), and (5) high concentration treatment group (6.5% COV). Mice in the NC group were fed with a normal chow diet, and those in the other four groups were fed with a HFD known for causing obesity for 10 weeks. Then, mice in the three COV treatment groups were orally administered with COV once a day for 6 weeks. Results showed that the contents of loganin and morroniside in COV reached 16.82 and 51.17 µg/ml, respectively, and COV also contained multiple organic acids. COV significantly reduced BW, abdominal fat weight, liver weight, and the levels of glucose, triglyceride, and low-density lipoprotein cholesterol of serum and increased the levels of high-density lipoprotein cholesterol of serum (p < 0.05). COV also improved the liver function and anti-oxidant activity of liver (p < 0.05). COV treatments increased the interleukin-10 expression and reduced the tumor necrosis factor-α expression in the liver tissue of NAFLD mice (p < 0.05). Histopathological observation revealed that COV suppressed hepatic lipid accumulation and steatosis. The results suggest that COV may contribute to the alleviation of NAFLD and obesity.     

Memory-based dynamic event-triggered control for networked interval type-2 fuzzy systems subject to DoS attacks

In this article, the memory-based dynamic event-triggered controller design issue is investigated for networked interval type-2 (IT2) fuzzy systems under non-periodic denial-of-service (DoS) attacks. For saving limited network bandwidth, a novel memory-based dynamic event-triggered mechanism (DETM) is proposed to schedule data communication. Unlike existing event-triggered generators, the developed memory-based DETM can utilize a series of newly released signals and further save network resources by introducing interval dynamic variables. Moreover, to improve design flexibility, an IT2 fuzzy controller with freely selectable fuzzy rule number and premise membership functions (MFs) is synthesized. Then, a new switched time-delay system with imperfectly matched MFs is established under the consideration of memory-based DETM and DoS attacks simultaneously. Besides, based on the property of MFs, the boundary information of membership grades and slack matrices are introduced in the stability analysis. Furthermore, by using a piecewise Lyapunov–Krasovskii method, membership-functions-dependent criteria are deduced to ensure the asymptotic stability of built fuzzy switched systems. Finally, the effectiveness of proposed control strategies is demonstrated by simulation examples.     

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.     

Efficiency evaluation of healthcare services in China based on stochastic multicriteria acceptability analysis and directional distance function

Evaluating the efficiency of healthcare services accurately can help in analyzing the rationality of inputs and outputs in such services. Considering the consistency and equity of assessment criteria, this study conducts the stochastic multicriteria acceptability analysis (SMAA-2) with a directional distance function to evaluate the efficiency of healthcare services in 31 provincial administrative regions of mainland China, as observed in 2018. We use SMAA-DDF to explore all the projection directions to the efficient frontier instead of a certain projection direction. We measure the maximum and average efficiencies for each of the 31 provincial healthcare services. Our empirical findings show that only seven provinces achieve optimal healthcare service efficiency; the eastern area performed the best, followed by the central, western, and northeast areas. Furthermore, the path along the projection directions is provided to help inefficient provinces improve their efficiency and obtain the best possible positions.     

GO/PI复合纳米纤维的制备及其过滤性能研究

为制备高过滤效率、低过滤阻力的空气过滤材料,将氧化石墨烯纳米颗粒(GO)掺杂到聚酰亚胺(PI)纺丝溶液中,制备氧化石墨烯/聚酰亚胺(GO/PI)复合纳米纤维过滤材料。通过观察其形貌、过滤性能来确定最优纺丝工艺参数。结果表明:当PI质量分数为30%,GO质量分数为1%,纺丝电压为25 kV,接收距离为20 cm时,复合纳米薄膜的纤维形貌较好,过滤性能优良。与PI纯组分纳米纤维过滤材料相比,GO/PI复合纳米纤维过滤材料的过滤性能更好,制得GO/PI复合纳米纤维膜的平均孔径为1.8μm,过滤效率为99.68%,过滤阻力仅为85.35 Pa。     

采煤机惯性导航定位动态零速修正技术

基于捷联惯性导航与轴编码器组合的采煤机惯性导航定位是综采工作面可行的采煤机定位技术。惯性导航提供姿态角参数，轴编码器提供速度参数，采煤机惯性导航定位利用航位推算算法解算出东北天坐标系下的位置坐标。为了进一步提高定位精度，在消除确定性偏差的基础上，根据惯性导航姿态误差方程，以东、北、天3个方向的平台失准角为状态量构建状态方程，根据动态零速修正技术的非完整约束条件，以采煤机坐标系横向和垂直方向速度值为观测量构建量测方程，建立卡尔曼滤波模型，并进行移动平台模拟采煤机运行试验验证。在试验条件下，第3刀导航东、北方向最大误差分别由0.639 7，0.856 7 m减小为0.456 4，0.594 2 m。第4刀导航东、北方向最大误差分别由0.644 4，0.910 6 m减小为0.466 5，0.603 0 m。东、北方向定位精度提升了30%。     

基于深度学习的番茄叶部病害识别模型

番茄叶病种类多、成因复杂,其预防和识别难度较大。传统基于机器学习的方法多靠人工识别,需要一定的专家经验,且具有主观性强、识别准确率不高等缺点。为实现番茄叶病特征的自动提取,并提高识别准确率,提出一种基于深度学习的番茄叶病识别模型。该模型基于卷积神经网络对番茄叶部病害特征进行自动提取,获得高维特征后,采用PCA降维算法去除冗余特征;从增大类间距离并减小类内距离的角度改进了softmax分类器,提高了识别准确率。将该模型在CrowdAI提供的数据集上进行了仿真验证,结果表明,该模型能够对番茄叶部常见10种病害进行自动提取特征和识别,综合识别准确率达到95%以上。