Latin American convergence and divergence towards the mortality profiles of developed countries

It is uncertain whether Latin America and Caribbean (LAC) countries are approaching a single mortality regime. Over the last three decades, LAC has experienced major public health interventions and the highest number of homicides in the world. However, these interventions and homicide rates are not evenly shared across countries. This study documents trends in life expectancy and lifespan variability for 20 LAC countries, 2000–14. By extending a previous method, we decompose differences in lifespan variability between LAC and a developed world benchmark into cause-specific effects. For both sexes, dispersion of amenable diseases through the age span makes the largest contribution to the gap between LAC and the benchmark. Additionally, for males, the concentration of homicides, accidents, and suicides in mid-life further impedes mortality convergence. Great disparity exists in the region: while some countries are rapidly approaching the developed regime, others remain far behind and suffer a clear disadvantage in population health.     

半脆弱印刷数字有意义水印算法研究

数字水印技术是在数字作品中嵌入不明显的记号。该文分析了印刷品制作中包含数模-模数转换过程的特性,与数字水印技术相结合,将纯数字域的防伪手段应用到模拟领域中的印刷品上。将印刷品扫描打印过程作为失真信道进行建模分析,并在算法中加入预失真;比较了数字水印各算法,结合印刷品的特性采用并改进特征值分解的方法,嵌入和检测有意义水印,通过该水印对二次扫描打印印刷品脆弱不可检测,来达到防伪的要求。该算法相对于空域算法和其他变换域算法有复杂度低、检测准确度高的优势。     

高速SDRAM控制器设计的FPGA实现

同步动态存储器(SDRAM)控制器通常用有限状态机实现,对于一般的设计方法,由于状态数量多,状态转换通常伴随大的组合逻辑而影响运行速度,因此,SDRAM控制器的速度限制了SDRAM存储器的访问速度。该文从结构优化入手来优化方法,利用状态机分解的思想将大型SDRAM控制状态机用若干小的子状态机实现,达到简化逻辑的目的,不仅提高了速度还节省了资源,对该类大型SDRAM控制器的实现有一定参考意义。     

中国货币政策和财政政策相对有效性的实证研究

在我国由计划经济向市场经济的体制转轨过程中,货币政策和财政政策已成为我国宏观经济调节的主要手段,在我国的经济发展中发挥了重要作用。但货币政策和财政政策是各自独立的政策体系,由于作用的方式和条件有较大区别,其效果也有较大不同,文章试图应用脉冲响应函数和方差分解方法,对改革开放以来我国货币政策和财政政策的效果进行实证比较研究,并得出有关结论,为我国的宏观调控政策提供理论分析和实证检验的依据。     

Model diagnostics for smoothing spline ANOVA models

The author proposes some simple diagnostics for assessing the necessity of selected terms in smoothing spline ANOVA models. The elimination of practically insignificant terms generally enhances the interpretability of the estimates and sometimes may also have inferential implications. The diagnostics are derived from Kullback‐Leibler geometry and are illustrated in the settings of regression, probability density estimation, and hazard rate estimation.     

L~1空间上的Fourier乘子判定定理

本文利用Torchinsky分解和一种全新的二进制分解得到一个极为有用的L1空间上的Fourier乘子的判定定理.该定理较之经典的判定定理适用于更为广泛的一类乘子.     

基于二阶段随机规划的城市医疗废弃物回收网络设计

城市医疗废弃物日益增加,且回收需求量受诸多因素的影响,难以准确预测,假定回收需求为确定值的医疗废弃物网络优化设计不能与实际需求相匹配。本文考虑了离散随机参数环境下,医疗回收网络设计中选址规划、分配计划及运输规划的协同优化问题,建立了以选址成本、运输成本最小为目标,设施与车辆能力限制为约束的二阶段随机规划模型。根据模型特点,设计了基于Benders decomposition的求解算法,同时,设计了一系列加速技术用于提高算法的求解效率。最后,以国内某城市医疗回收网络为背景设计算例,检验本文模型和求解策略的可行性和有效性。结果表明：相比确定性规划,随机规划的解能够节约总成本,结合一系列加速技术的Benders decomposition方法比CPLEX与纯的Benders decomposition更有优势。     

一种新的高分辨定位去噪方法

高分辨定位技术在近几年得到人们的广泛注意,在这方面的研究工作相当活跃。本文提出一种新的多目标阵列接收信号协方差矩阵的去噪方法,并对结果进行了计算机模拟。     

Multiscale Combined Forecast of Carbon PriceBased on Mixed Structure Data

Accurate forecast of the carbon trading price is of great significance in promoting the scientific and rational development of carbon trading market. Therefore, this paper proposes a multi-scale combined forecasting method for carbon price based on mixed structure data. First, the Google Index is used to extract the unstructured data related to the carbon price.The dimensions of unstructured data are reduced based on principal component analysis. Then, EMD is employedto the structured data,unstructured data and the carbon trading price to obtain different IMFs, which are reconstructed by the Fine-to-Coarse technique to get low, high frequency sequence and trend sequence. Furthermore, the three items are predicted respectively by using ARIMA, PLS and neural networks according to the features of each scale in time series. Finally, the forecasting results are summed to get the carbon price forecast sequence. The proposed method is used to forecast carbon price in EU. The empirical results show that the prediction accuracy of the model is higher than that of the single prediction method and the prediction method that time series aren’t decomposed by EMD, which is of great applicability.