嵌入式实时操作系统内核混合代码的自动化验证框架

"如何构造高可信的软件系统"已成为学术界和工业界的研究热点.操作系统内核作为软件系统的基础组件，它的安全可靠是构造高可信软件系统的重要环节.为了确保操作系统内核的安全可靠，将形式化方法引入到操作系统内核验证中，提出了一个自动化验证操作系统内核的框架.该验证框架包括：（1）分别对C语言程序和混合语言程序（C语言和汇编语言）进行验证；（2）在混合语言程序验证中，为汇编程序建立抽象模型，并将C语言程序和抽象模型粘合形成基于C语言验证工具可接收的验证模型；（3）从规范中提取性质，基于该自动验证工具，对性质完成自动验证；（4）该框架不限于特定的硬件架构.成功地运用该验证框架对两种不同硬件平台的嵌入式实时操作系统内核μC/OS-II进行了验证.结果显示：利用该框架在对两个不同的硬件平台上内核验证时，框架的可重复利用率很高，高达到88%，虽然其抽象模型需要根据不同的硬件平台进行重构.在对基于这两种平台的操作系统内核验证中，分别发现了10~12处缺陷.其中，在ARM平台上两处与硬件相关的问题被发现.实验表明，该方法对不同硬件平台的同一个操作系统分析验证具有一定的通用性.     

Broad-Spectral-Range Sustainability and Controllable Excitation of Hyperbolic Phonon Polaritons in α-MoO3

Hyperbolic phonon polaritons (HPhPs) in orthorhombic-phase molybdenum trioxide (α-MoO₃) show in-plane hyperbolicity, great wavelength compression, and ultralong lifetime, therefore holding great potential in nanophotonic applications. However, its polaritonic response in the far-infrared (FIR) range remains unexplored due to challenges in experimental characterization. Here, monochromated electron energy loss spectroscopy (EELS) in a scanning transmission electron microscope (STEM) is used to probe HPhPs in α-MoO₃ in both mid-infrared (MIR) and FIR frequencies and correlate their behaviors with microstructures and orientations. It is found that low structural symmetry leads to various phonon modes and multiple Reststrahlen bands (RBs) over a broad spectral range (over 70 meV) and in different directions (55–63 meV and 119–125 meV along the b-axis, 68–106 meV along the c-axis, and 101–121 meV along the a-axis). These HPhPs can be selectively excited by controlling the direction of swift electrons. These findings provide new opportunities in nanophotonic and optoelectronic applications, such as directed light propagation, hyperlenses, and heat transfer.     

Calorimetric study and thermodynamic description of Ga-Ge-Li liquid alloys

This publication contains the thermodynamic results received by the drop calorimetry method. The experiments were conducted for four different cross sections, at the temperature of 1080 K. The investigated alloys were as follows: (Ga_0.75Li_0.25)_1-xGe_x, (Ge_0.50Li_0.50)_1-xGa_x, (Ga_0.50Li_0.50)_1-xGe_x, (Ga_0.25Li_0.75)_1-xGe_x. The mixing enthalpy changes measured for all four cross sections of the Ga-Ge-Li system are characterized by negative deviations from the ideal solutions. The Muggianu model with the ternary interaction parameters was applied to elaborate the experimental data of the mixing enthalpy change with the use of the optimized thermodynamic parameters of the binary systems available in the literature.     

A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.     

Optimal resilient power grid operation during the course of a progressing wildfire

We study a two-stage stochastic and nonlinear optimization model for operating a power grid exposed to a natural disaster. Although this approach can be generalized to any natural hazard of continuous (and not instantaneous) nature, our focus is on wildfires. We assume that an approaching wildfire impacts the power grid by reducing the transmission capacity of its overhead lines. At the time when proactive decisions have to be taken, the severity of the wildfire is not known. This introduces uncertainty. In this paper, we extend previous work by more realistically capturing this uncertainty and by strengthening the mathematical programming formulation through standard reformulation techniques. With these reformulation techniques, the resulting two-stage, convex mixed-integer quadratically constrained programming formulation can be efficiently solved using commercial quadratic programming solvers as demonstrated on a case study on a modified version of the IEEE 123-bus test system with 100 scenarios. We also quantify the uncertainties through a second case study using the following three standard metrics of two-stage stochastic optimization: the expected value of perfect information, the expected result of using the expected value solution and the value of the stochastic solution.     

基于二元水循环的水量-水质-水效联合调控模型开发与应用

为将我国最严格水资源管理制度的实践与二元水循环理论相结合，提高“三条红线”控制指标的科学性与合理性，本文以SWAT模型为基础，通过改进子流域划分方法、添加经济社会模块和人工用水模块，对其人工侧支循环模拟进行了系统的完善，开发了基于SWAT的水量-水质-水效联合调控模型SWAT_WAQER。以广西南流江流域为例，从国民经济用水量、河道径流与水质等方面对模型进行校验，并在此基础上划分了2030年“三条红线”控制指标。结果表明：该模型性能良好，能够用于不同节水情景下的国民经济用水量、污染物排放量、水功能区水质达标结果分析，可以作为科学制定“三条红线”控制指标的有力支撑工具。     

无失效数据机载多余度EWIS可靠性研究

针对高可靠度机载多余度EWIS各组成部分寿命服从指数分布但参数未知的情况，提出采用无失效数据可靠度分析方法评估EWIS的可靠度水平。通过Monte-Carlo仿真方法对连接形式为“先并联、后串联”EWIS各组成部分寿命进行抽样，利用“最小最大值”方法获得系统寿命的抽样值，用概率纸检验法初步判断EWIS寿命是否服从威布尔分布，再用Pearson拟合优度检验法判断EWIS寿命是否服从威布尔分布。结合无故障飞行时间的样本值与EWIS寿命服从威布尔分布的假设，采用无失效数据分析方法评估EWIS的可靠度水平。研究方法对机载多余度EWIS无失效数据可靠度分析有一定的贡献。     

Capsiate Intake with Exercise Training Additively Reduces Fat Deposition in Mice on a High-Fat Diet,but Not without Exercise Training

While exercise training (ET) is an efficient strategy to manage obesity, it is recommended with a dietary plan to maximize the antiobesity functions owing to a compensational increase in energy intake. Capsiate is a notable bioactive compound for managing obesity owing to its capacity to increase energy expenditure. We aimed to examine whether the antiobesity effects of ET can be further enhanced by capsiate intake (CI) and determine its effects on resting energy expenditure and metabolic molecules. Mice were randomly divided into four groups (n = 8 per group) and fed high-fat diet. Mild-intensity treadmill ET was conducted five times/week; capsiate (10 mg/kg) was orally administered daily. After 8 weeks, resting metabolic rate and metabolic molecules were analyzed. ET with CI additively reduced the abdominal fat rate by 18% and solely upregulated beta-3-adrenoceptors in adipose tissue (p = 0.013) but did not affect the metabolic molecules in skeletal muscles. Surprisingly, CI without ET significantly increased the abdominal fat rate (p = 0.001) and reduced energy expenditure by 9%. Therefore, capsiate could be a candidate compound for maximizing the antiobesity effects of ET by upregulating beta-3-adrenoceptors in adipose tissue, but CI without ET may not be beneficial in managing obesity.     

马尔可夫跳变线性系统最优控制的研究现状与进展

马尔可夫跳变线性系统（MJLS）是一种具有多个模态的随机系统，系统在各个模态之间的跳变转移由一组马尔可夫链来决定。MJLS模型因其在表示过程中可以产生突变而更能精确的描述实际工程应用中的系统。近年来，MJLS的最优控制问题成为了研究的热点，动态规划、极大值原理以及线性矩阵不等式等成为了解决此类问题的主流方法。本文对MJLS最优控制领域的研究现状进行了综述。分别对一般情况下、带有噪声的情况下、带有时滞的情况下以及某些特定情况下的MLJS最优控制问题的国内外研究现状进行论述。最后进行了总结并提出MJLS最优控制领域未来值得关注的研究方向。