单片机与接口技术项目化教学改革的实践与探索

As a comprehensive electrical and electronic course, Single Chip Microcomputer and Interface Technology is usually com- bined with automation technology, applied electronic technology, communication technology, etc., so that students can master the professional theory and application practice of single chip microcomputer. In the course teaching, teachers mainly focus on the knowledge points of single chip microcomputer system design, application programming, installation and debugging, select suitable interface circuit, application program, and organize and design the integrated circuit system and logic function of single chip micro- computer, so as to help students complete the resource allocation and function realization of different single chip microcomputer project design.     

The constrained two-dimensional guillotine cutting problem with defects: an ILP formulation,a Benders decomposition and a CP-based algorithm

This paper addresses a variant of two-dimensional cutting problems in which rectangular small pieces are obtained by cutting a rectangular object through guillotine cuts. The characteristics of this variant are (i) the object contains some defects, and the items cut must be defective-free; (ii) there is an upper bound on the number of times an item type may appear in the cutting pattern; (iii) the number of guillotine stages is not restricted. This problem commonly arises in industrial settings that deal with defective materials, e.g. either by intrinsic characteristics of the object as in the cutting of wooden boards with knotholes in the wood industry, or by the manufacturing process as in the production of flat glass in the glass industry. We propose a compact integer linear programming (ILP) model for this problem based on the discretisation of the defective object. As solution methods for the problem, we develop a Benders decomposition algorithm and a constraint-programming (CP) based algorithm. We evaluate these approaches through computational experiments, using benchmark instances from the literature. The results show that the methods are effective on different types of instances and can find optimal solutions even for instances with dimensions close to real-size.     

High-speed,two-dimensional digital image correlation algorithm using heterogeneous (CPU-GPU) framework

Two-dimensional digital image correlation (2D-DIC) is an experimental technique used to measure in-plane displacement of a test specimen. Real-time measurement of full-field displacement data is challenging due to enormous computational load of the algorithm. In order to improve the computational speed, the focus of recent research works has been on the approach of parallelization across subsets within image pairs using graphics processing unit (GPU). But alternate GPU-based parallelization approaches to improve the performance of this algorithm as per the order of data processing have not been explored. To address this research gap, our method utilizes parallelism within a subset as well as across subsets for each computation step in an iteration cycle. A heterogeneous (CPU-GPU) framework in combination with a pyramid-based initial values estimation for subsets (in parallel) is proposed in this work. The precompute steps of the proposed framework are implemented using CPU, whereas the main iterative steps are realized using GPU. It is demonstrated that the overall computational speed of the proposed heterogeneous framework improves by compared to a sequential CPU-based implementation for a pair of gray-scale images with a resolution of pixels. As an important milestone, feasibility to measure deformations in real time ( 1 s) is manifested in this study.     

基于Android平台利用表格布局制作简易计算器界面

Android程序设计中,有6大布局方法。文章重点论述了基于Android平台利用表格布局来制作一个简易的计算器界面,涉及详细的操作步骤,对计算器界面进行有效美化和优化,并做出总结。     

Maternal Malnutrition Affects Hepatic Metabolism through Decreased Hepatic Taurine Levels and Changes in HNF4A Methylation

Fetal programming implies that the maternal diet during pregnancy affects the long-term health of offspring. Although maternal diet influences metabolic disorders and non-alcoholic fatty liver disease in offspring, the hepatic mechanisms related to metabolites are still unknown. Here, we investigated the maternal diet-related alterations in metabolites and the biological pathway in male offspring at three months of age. Pregnant rats were exposed to 50% food restriction during the prenatal period or a 45% high-fat diet during the prenatal and postnatal periods. The male offspring exposed to food restriction and high-fat diets had lower birth weights than controls, but had a catch-up growth spurt at three months of age. Hepatic taurine levels decreased in both groups compared to controls. The decreased hepatic taurine levels in offspring affected excessive lipid accumulation through changes in hepatocyte nuclear factor 4 A methylation. Moreover, the alteration of gluconeogenesis in offspring exposed to food restriction was observed to a similar extent as that of offspring exposed to a high fat diet. These results indicate that maternal diet affects the dysregulation in hepatic metabolism through changes in taurine levels and HNF4A methylation, and predisposes the offspring to Type 2 diabetes and non-alcoholic fatty liver disease in later life.     

PEO对固态锂电池正极/电解质界面的改性

在固态锂电池正极/氧化物电解质界面处引入聚氧化乙烯(PEO)缓冲层以改善固体接触。首先,用热压烧结法制备了密度为5.25 g·cm-3、锂离子电导率为8.33×10-4S·cm-4的Li6.4La3Zr1.4Ta0.6O12(LLZTO)固体电解质。其次,配制了PEO-LiTFSI-LLZTO缓冲层和LiFePO4复合正极浆料,用匀胶机旋涂法将PEO缓冲层和复合正极浆料依次涂覆在电解质表面,加热加压后显著改善界面接触,测得60℃下正极界面电阻值为509Ω·cm2。测试对称电池充/放电曲线证明界面稳定性良好,电池首次循环放电容量145.8 mAh·g-1,库伦效率大于97%。     

A novel joint bidding technique for fuel cell wind turbine photovoltaic storage unit and demand response considering prediction models analysis Effect's

The stake of distributed generation resources like fuel cell in daily market is proved to be a major uncertain problem. The volatile character of market price together with the unbalanced nature of power can take hold of economic advancement of distributed generation resources which in turn can culminate in diversion retribution while the market is being struck. This study introduces a market participation model in share conditions to improve the profit for Fuel Cell/wind turbine/storage/photovoltaic and demand response. To solve the mentioned problem, an accurate prediction model is presented in this paper. This model is based on complete ensemble empirical mode decomposition, and multiple artificial neural network which is coupled with Broyden water cycle algorithm. By this algorithm, the prediction accuracy of proposed forecast engine is enhanced and could get the better results. A sure-footed stochastic optimization approach was deployed in order to take prices of markets and distributed generation resources into account. In the generation of distributed generation resources, forecasting error database in everyday, modified, and depressed market was drawn on to induce probabilistic scenario. Improbable variables were discarded by a neuro-fuzzy model. Eventually, to illustrate the joint model strategy suggested in the study, a testing system contains fuel cell/wind turbine/storage unit/photovoltaic and demand response was utilized and the attained results were calculated in two different periods.     

Minimum cost consensus model for CRP-driven preference optimization analysis in large-scale group decision making using Louvain algorithm

Large-scale group decision-making problems based on social network analysis and minimum cost consensus models (MCCMs) have recently attracted considerable attention. However, few studies have combined them to form a complete decision-making system. Accordingly, we define the satisfaction index to optimize the classical MCCM by considering the effect of the group on individuals. Similarly, we define the consistency index to optimize the consensus reaching process (CRP). Regarding the evolution of the consensus network, the Louvain algorithm is used to divide the entire group into several subgroups to ensure that each subgroup is independent but has strong cohesion. By constructing the MCCM based on the satisfaction index and the optimized consensus-reaching process, the group opinions in each subgroup are ranked to obtain the final ranking of alternatives. Finally, to verify the validity of CRP and the practical value of the proposed model, we conduct consensus network evolution and decision-making analysis in the case of a negotiation between the government and polluting companies to achieve uniform pollution emissions. Sensitivity analysis is performed to demonstrate the stability of the subgroup weights. Furthermore, a comparative analysis using existing models verifies the effectiveness of the proposed model.     

低速冲击下的界面响应和磨损行为*

为探究低速冲击下界面响应与磨损行为之间的联系，开展多周次的低速冲击磨损实验；通过分析冲击过程中的接触力峰值、接触时长、接触力冲量、动能耗散等，研究冲击速度对接触界面的力学响应的影响；通过对冲击磨痕的磨损轮廓和形貌、磨损体积的检测分析，以及对磨痕区域元素组分变化的测试，研究冲击速度对接触界面磨损损伤行为的影响。结果表明：冲击速度的增加会导致接触界面在更短的时间内受到更强烈的力学作用；能量吸收率对冲击速度的变化不敏感，但冲击速度的提高会导致单位能量造成的磨损损伤逐渐降低；冲击磨痕可分为以塑性变形和以剥层磨损为主要损伤形式的2种区域；磨损区内经历了严重的摩擦氧化，并随着冲击速度的增加发生冲击副材料转移。因此，冲击速度越高，接触界面间的摩擦越剧烈，形成的表面氧化层避免了冲击副与基底材料的直接接触，延缓了磨损损伤的进一步发展。     

MDA-TOEPGA: A novel method to identify miRNA-disease association based on two-objective evolutionary programming genetic algorithm

The association between miRNA and disease has attracted more and more attention. Until now, existing methods for identifying miRNA related disease mainly rely on top-ranked association model, which may not provide a full landscape of association between miRNA and disease. Hence there is strong need of new computational method to identify the associations from miRNA group view. In this paper, we proposed a framework, MDA-TOEPGA, to identify miRNAdisease association based on two-objective evolutionary programming genetic algorithm, which identifies latent miRNAdisease associations from the view of functional module. To understand the miRNA functional module in diseases, the case study is presented. We have been compared MDA-TOEPGA with several state-of-the-art functional module algorithm. Experimental results showed that our method cannot only outperform classical algorithms, such as K-means, IK-means, MCODE, HC-PIN, and ClusterONE, but can also achieve an ideal overall performance in terms of a composite score consisting of f1, Sensitivity, and Accuracy. Altogether, our study showed that MDA-TOEPGA is a promising method to investigate miRNA-disease association from the landscapes of functional module.