上海市亚微米颗粒物中水溶性含氮组分的分布特征

细颗粒态无机和有机含氮组分的形成、转化、传输和沉降在大气氮循环中发挥重要作用. 为了解上海亚微米颗粒物(PM$_{1}$)中含氮物质的质量浓度、组成及季节变化特征, 使用大流量采样器采集了 2017—2018 年 66 个 PM$_{1}$ 样品, 并应用离子色谱仪和紫外/可见光光度计分析了水溶性无机离子和水溶性有机氮(water-soluble organic nitrogen, WSON)的质量浓度. 结果表明: 上海 PM$_{1}$中NH$_{4}^{+}$-N、NO$_{3}^{-}$-N、WSON 的年平均质量浓度分别为 1.79、0.97、0.41 μg/m³; NH$_{4}^{+}$-N 对水溶性总氮(water-soluble total nitrogen, WSTN)的贡献最高(56%), NO$_{3}^{-}$-N 次之(31%), WSON 为 13%. 上海PM$_{1}$中含氮组分的质量浓度存在冬季最高、夏季最低的季节变化趋势, 但NH$_{4}^{+}$-N、NO$_{3}^{-}$-N 和 WSON 对 WSTN 贡献的季节变化存在明显的不同, NH$_{4}^{+}$-N 在不同季节变化较小, NO$_{3}^{-}$-N 表现出显著的冬高(38%)、夏低(18%)的特点, 而 WSON 夏季最高(22%)、冬季最低(8%). 正矩阵因子分解(positive matrix factorisation, PMF)法的源解析结果表明: 二次反应和生物质燃烧贡献了上海 PM$_{1}$ 中 WSON 的 48%, 燃煤贡献了 11%, 植物源挥发性有机化合物二次转化贡献了 20%, 餐饮和机动车贡献了 21%. WSON 的来源有显著的季节变化.     

Does a lot help a lot? Forecasting stock returns with pooling strategies in a data‐rich environment

A variety of recent studies provide a skeptical view on the predictability of stock returns. Empirical evidence shows that most prediction models suffer from a loss of information, model uncertainty, and structural instability by relying on low‐dimensional information sets. In this study, we evaluate the predictive ability of various lately refined forecasting strategies, which handle these issues by incorporating information from many potential predictor variables simultaneously. We investigate whether forecasting strategies that (i) combine information and (ii) combine individual forecasts are useful to predict US stock returns, that is, the market excess return, size, value, and the momentum premium. Our results show that methods combining information have remarkable in‐sample predictive ability. However, the out‐of‐sample performance suffers from highly volatile forecast errors. Forecast combinations face a better bias–efficiency trade‐off, yielding a consistently superior forecast performance for the market excess return and the size premium even after the 1970s.     

条件故障下3-元n-立方体的容错分析

研究了条件边故障下3-元n-立方体中较大连通分支点的数目，进而证明了3-元n-立方体是(4n－6)-条件边故障强Menger边连通的。最后通过一个反例说明该结果是最优的。     

基于多目标的民用航空发动机典型部件维修间隔确定

发动机部件维修间隔制定得合理与否对民机运行的安全性与维修成本有着至关重要的影响，而MSG-3逻辑思想对维修间隔确定的方法没有提及。为此，本文通过建立数学模型，之后采用遗传算法对模型进行求解来确定发动机上典型部件的维修间隔，从而得到部件的维修间隔理论值。文章选取反推同步锁进行案例分析，将求得的维修间隔值和737NG维修计划文件（MPD）中的维修间隔值对比，发现误差为6.9%，表明了模型和算法的可行性。因此本文方法可以为国内发动机制造商确定部件维修间隔提供参考。     

Constructing and evaluating core inflation measures from component‐level inflation data

This paper undertakes a comprehensive examination of 10 measures of core inflation and evaluates which measure produces the best forecast of headline inflation out‐of‐sample. We use the Personal Consumption Expenditure Price Index as our measure of inflation. We use two sets of components (17 and 50) of the Personal Consumption Expenditure Price Index to construct these core inflation measures and evaluate these measures at the three time horizons (6, 12 and 24 months) most relevant for monetary policy decisions. The best measure of core inflation for both sets of components and over all time horizons uses weights based on the first principal component of the disaggregated (component‐level) prices. Interestingly, the results vary by the number of components used; when more components are used the weights based on the persistence of each component is statistically equivalent to the weights generated by the first principal component. However, those forecasts using the persistence of 50 components are statistically worse than those generated using the first principal component of 17 components. The statistical superiority of the principal component method is due to the fact that it extracts (in the first principal component) the common source of variation in the component level prices that accurately describes trend inflation over the next 6–24 months.     

基于积分分离式PID控制的耕深调节系统研究

耕作过程中保持耕深稳定是提高耕作质量的重要措施之一.以小型耕耘机的后悬挂旋耕部件为研究对象,提出了一种基于积分分离式PID控制的耕深自动测量和调节的系统,采用双倾角传感器检测耕深,消除了田块自身与绝对水平面倾角的误差影响,通过在误差信号的处理中使用积分分离式PID控制算法,利用Simulink中的SimHydraulic模块对耕深控制系统进行动态仿真研究,与未加入PID控制算法时的仿真结果进行比较,发现几乎消除了系统的耕深超调现象.同时,将响应时间由4.0s左右缩短到1.4s左右,使耕深控制系统的动态响应达到较好的效果.田间试验结果表明,当耕深设定为10cm和16cm时,实测耕深稳定性变异系数分别为6.05%和3.54%,均低于10%,达到了农业机械作业标准所规定的旋耕作业农艺要求.     

药用植物白芨块茎挥发油组分的GC-MS分析及成分鉴定

通过分析道地药材白芨块茎中挥发油的化学成分,为进一步揭示其药理作用提供科学依据。采用二氯甲烷为萃取剂提取白芨块茎中的挥发油,利用气相色谱-质谱联用技术(GC-MS)鉴定分析白芨块茎中挥发油的化学成分。结果显示从白芨块茎中共鉴定到 34种主要化学成分,相对含量较高的组分有3-甲基丁醛、乙酸、3-甲基-1-丁醇、4-氨基-3-甲基苯酚和乙偶姻等。该研究将为后续进一步开发利用白芨的食疗保健功效提供了理论参考。     

求解对流扩散方程的紧致二级四阶Runge-Kutta差分格式

将指数变换u(x,t)=p(x,t)exp(k2εx)应用于一维对流扩散方程,对空间变量x应用紧致差分格式,时间变量t采用二级四阶Runge-Kutta方法,提出了精度为o(τ4+h4)的绝对稳定的差分格式,讨论了稳定性.最后通过数值算例说明该格式的有效性.     

一类二维Landau-Lifshitz方程的差分格式

研究了一类unj的模等于1保持不变的Landau-Lifshitz方程的差分格式(简称LL).运用迭代格式t/2h2,通过模拟几个初始条件得到数值解,并在一定条件下给出了数值算例和解的误差比较.     

中距协同空战决策过程二次聚类重构与评估

未来空战将以中距空战为主，找出导致中距空战结果的原因是开展贴近实际的中距空战智能决策需解决的重要问题。针对空战训练过程中记录数据分布的复杂特点，建立了中距协同空战训练评估模型，提出了基于高阶导数聚类和相对模糊熵聚类的二次聚类方法，计算编队协同决策集，实现编队中距协同空战决策过程重构。以编队协同搜索和协同机动决策的角度，寻找编队协同决策与中距空战结果的相关性，并通过实例评估验证了聚类算法的合理性。