Study of the synergistic effect of boron nitride and carbon nanotubes in the improvement of thermal conductivity of epoxy composites

The enhancement of the thermal conductivity, keeping the electrical insulation, of epoxy thermosets through the addition of pristine and oxidized carbon nanotubes (CNTs) and microplatelets of boron nitride (BN) was studied. Two different epoxy resins were selected: a cycloaliphatic (ECC) epoxy resin and a glycidylic (DGEBA) epoxy resin. The characteristics of the composites prepared were evaluated and compared in terms of thermal, thermomechanical, rheological and electrical properties. Two different dispersion methods were used in the addition of pristine and oxidized CNTs depending on the type of epoxy resin used. Slight changes in the kinetics of the curing reaction were observed in the presence of the fillers. The addition of pristine CNTs led to a greater enhancement of the mechanical properties of the ECC composite whereas the oxidized CNTs presented a greater effect in the DGEBA matrix. The addition of CNTs alone led to a marked decrease of the electrical resistivity of the composites. Nevertheless, in the presence of BN, which is an electrically insulating material, it was possible to increase the proportion of pristine CNTs to 0.25 wt% in the formulation without deterioration of the electrical resistivity. A small but significant synergic effect was determined when both fillers were added together. Improvements of about 750% and 400% in thermal conductivity were obtained in comparison to the neat epoxy matrix for the ECC and DGEBA composites, respectively. © 2019 Society of Chemical Industry     

某铁矿隔水护顶矿柱厚度计算及安全影响预测

科学合理地确定矿山隔水护顶矿柱安全厚度是矿山安全生产的前提条件，为保障某铁矿地表民房、道路等建（构）筑物安全，防止矿山开采过程中产生的导水裂隙带贯通第四系含水层，采用荷载传递交汇线法、K.B.鲁别涅依他估算法和冒落带、导水裂隙带高度估算法3种理论分析方法对隔水护顶矿柱厚度进行计算，并利用数值模拟手段对留设隔水护顶矿柱后的开采过程安全影响进行了分析，对理论计算结果进行了验证。3种理论计算方法得出的隔水护顶矿柱厚度分别为14.3～17.3 m、17.5～31.4 m和41.8～57.4 m，推荐隔水护顶矿柱留设厚度为60 m。通过数值模拟分析得出，在留设60 m厚的隔水护顶矿柱的基础上，开采区域和隔水护顶矿柱位置产生的最大拉应力约0.47 MPa，矿山开采不会对隔水护顶矿柱造成破坏；地表产生的最大水平位移约5.8 cm，最大垂直位移约26.5 cm，最大倾斜为1.70 mm/m，最大曲率为0.20 mm/m2，最大水平变形值为0.70 mm/m，满足相关规范要求，预测矿山开采不会造成地表建（构）筑物破坏。     

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.     

陈四楼煤矿“123456双重预防体系”的建设与应用

针对煤矿“双重预防体系”如何落地生根问题，结合陈四楼煤矿在风险分级管控和隐患排查治理方面的实用方法和“双重预防体系”的建设经验，深入研究了“双重预防体系”的相关标准、风险隐患事故之间的关系及其各自的产生和发展机理、安全风险的有关辨识评估方法、事故隐患的排查和治理方法，分析了传统安全管理模式与“双重预防体系”的新型安全管理模式的差别，总结出了“123456双重预防体系”这个囊括了事前安全风险辨识、事中隐患排查治理、事后安全现状评估的创新成果，实现了“事前、事中、事后”的全过程控制，对夯实煤矿安全管理根基、促进矿井平稳有序发展发挥着越来越重要的作用，为煤炭行业“双重预防体系”的落地生根提供了借鉴和参考。     

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。     

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。     

A gradient boosting decision tree approach for insider trading identification: An empirical model evaluation of China stock market

Insider trading is a kind of criminal behavior in stock market by using nonpublic information. In recent years, it has become the major illegal activity in China’s stock market. In this study, a combination approach of GBDT (Gradient Boosting Decision Tree) and DE (Differential Evolution) is proposed to identify insider trading activities by using data of relevant indicators. First, insider trading samples occurred from year 2007 to 2017 and corresponding non-insider trading samples are collected. Next, the proposed method is trained by the GBDT, and initial parameters of the GBDT are optimized by the DE. Finally, out-of-samples are classified by the trained GBDT–DE model and its performances are evaluated. The experiment results show that our proposed method performed the best for insider trading identification under time window length of ninety days, indicating the relevant indicators under 90-days time window length are relatively more useful. Additionally, under all three time window lengths, relative importance result shows that several indicators are consistently crucial for insider trading identification. Furthermore, the proposed approach significantly outperforms other benchmark methods, demonstrating that it could be applied as an intelligent system to improve identification accuracy and efficiency for insider trading regulation in China stock market.