螺旋槽盘形铣刀数学模型的建立

采用分析计算法详细分析并建立了螺旋槽盘形铣刀的数学模型 ,并在此基础上用 Visual Basic语言编写了螺旋槽盘形铣刀刃形参数化设计及绘图软件 ,大大提高了螺旋槽盘形铣刀的参数化计算精度和设计效率。     

Bi_2Se_3、Bi_2Te_3和Sb_2Te_3的声子和热力学性质的第一性原理研究

基于第一性原理的密度泛函理论,在未考虑和考虑自旋-轨道耦合(SOC)的情况下分别优化拓扑绝缘体Bi2Se3、Bi2Te3和Sb2Te3的结构,计算它们的声子谱及热力学性质.基于广义梯度交换相关泛函及SOC效应,计算得到三种物质的声子频率比不考虑SOC时更吻合实验数据.最后计算出三种物质的赫尔姆赫兹自由能F,内能E,等体热容CV和熵S随温度的变化趋势.     

土坯力学性能及受压本构模型研究

为获取传统土坯受压应力-应变特性,确定其数学表达式,针对湿制法和干打法制作的土坯开展了单轴抗压试验和三点抗折试验。分别从抗压、抗折强度、破坏机理以及应力-应变关系等方面分析了两类土坯的力学性能。结果表明,普通砌墙砖的抗压及抗折试验方法均适用于传统土坯,干打土坯的抗压强度为湿制土坯的3倍,抗折强度为湿制土坯的1.3倍,但湿制土坯的断裂能为干打土坯的2.5倍。受压初期,干打土坯的应力-应变曲线存在因土料压密而导致的下凹段,而湿制土坯未表现出该特性。基于两类土坯单轴受压状态下的应力-应变曲线特征,提出了土坯单轴受压本构模型,该本构模型与试验数据吻合较好,可用于土坯砌体结构的数值模拟研究。     

具有不可忽略退出的面板数据混合半参数变系数模型

由于面板数据经常出现由信息性退出而引起的缺失数据,故其统计分析比较复杂。本文假定响应变量服从部分线性半参变系数混合效应模型,其中非参数系数函数依赖于相应的退出时间。利用二步估计方法的思想求得参数与非参数部分的相合估计,减少了同时估计的参数的个数,避免了估计方程中由较多参数引起的多重共线性问题。     

全隐式E-CUSP迎风格式大攻角分离流数值模拟

采用全隐式、低耗散E-CUSP格式,通过求解雷诺平均Navier-Stokes方程耦合Spalart-Allmaras(SA)湍流模型,模拟了细长旋成体在超声速、大攻角下的流场,分析了背风面涡的发展过程.结果表明:E-CUSP格式耦合SA湍流模型能够准确地模拟背风面的流动分离和精细的二次涡,对横向分离具有较高的模拟精度;预测的物面压力系数分布和激波位置与实验数据吻合良好,力和力矩的相对误差在1.98%之内;E-CUSP格式可用于模拟复杂的分离流动,具有高的计算精度和效率.     

基于有序Logistic回归模型的北京高校男生有氧能力

为探索北京高校男生有氧能力的影响因素,通过随机抽样法抽取134名18~25岁北京高校男生,空腹抽静脉血测血液指标,用德国MetaMax 3B系统实时监测气体代谢,通过线性递增方案测得VO2max相对值。基于Spearman相关、有序Logistic回归等分析方法进行分析处理。结果表明：北京高校男生有序Logistic回归方程：Ln{P(Y≤1|x)/1-P(Y≤1|x)}=-2.757-0.067*X1-0.025*X2+0.066*X3+0.018*X4-0.009*X5;Ln{P(Y≤2|x)/1-P(Y≤2|x)}=-0.771-0.067*X1-0.025*X2+0.066*X3+0.018*X4-0.009*X5（X1=体重、X2=心率(heart rate, HR)、X3=每搏输出量(stroke volume, SVI)、X4=心室射血时间(ventricular ejection time, VET)、X5=血红蛋白(hemoglobin, HGB)）。回归方程模型系数综合检验步(step)、块(block)、模型(model)检验的P值均小于0.01;拟合优度检验的-2对数似然值(-2LL)为159.374,Cox&SnellR2为0.331,NagelkerkeR2为0.373;预测等级1准确率为45.5%,等级2准确率为100%,等级3准确率为100%,综合为81.8%,说明Logistic回归模型性能良好。Hosmer和Lemeshow检验预测值与观望值无显著性差异（P>0.05）。可见北京高校男生定量负荷心功能、血液指标与有氧能力的多元Logistic回归模型拟合度较好,且HR、SVI、VET、HGB是有氧运动能力的重要预测因素。     

Cardiovascular development: towards biomedical applicability

Advances in our understanding of cardiac development have fuelled research into cellular approaches to myocardial repair of the damaged heart. In this collection of reviews we present recent advances into the basic mechanisms of heart development and the resident and non-resident progenitor cell populations that are currently being investigated as potential mediators of cardiac repair. Together these reviews illustrate that despite our current knowledge about how the heart is constructed, caution and much more research in this exciting field is essential. The current momentum to evaluate the potential for cardiac repair will in turn accelerate research into fundamental aspects of myocardial biology.     

Forward Rates,Monetary Policy and the Economic Cycle

The short end of the yield curve incorporates essential information to forecast central banks' decisions, but in a biased manner. This article proposes a new method to forecast the Fed and the European Central Bank's decision rate by correcting the swap rates for their cyclical economic premium, using an affine term structure model. The corrected yields offer a higher out‐of‐sample forecasting power than the yields themselves. They also deliver forecasts that are either comparable or better than those obtained with a factor‐augmented vector autoregressive model, underlining the fact that yields are likely to contain at least as much information regarding monetary policy as a dataset composed of economic data series. Copyright © 2015 John Wiley & Sons, Ltd.     

状态方程计算高分子共混物的比体积

基于一个简单的非均核链流体分子热力学模型,采用不同形式的微扰项,可构筑不同形式的高分子共混物系统的状态方程。方程已被应用于关联聚苯乙烯/聚2,6-二甲基苯醚(PS/PPO)、聚苯乙烯/聚乙烯甲醚(PS/PVME)、聚苯乙烯/聚丁二烯(PS/PBD)、聚醚砜/聚氧乙烯(PESP/PEO)等高分子共混物的比体积。结果显示,用一个与温度无关的二元相互作用可调参数可满意关联所选体系的比体积,并可预测所选体系的比体积。     

Unobserved components in ARCH models: An application to seasonal adjustment

The paper deals with unobserved components in ARIMA models with GARCH errors, in the context of an actual application, namely seasonal adjustment of the monthly Spanish money supply series. The series shows clear evidence of (moderate) non-linearity, which does not disappear with simple outlier correction. The GARCH structure explains reasonably well the non-linearity, and this explanation is robust with respect to the GARCH specification. We look at the time variation of the standard error of the adjusted series estimator and show how it can be measured. Next, we look at the implications this variation has on short-term monetary control. The non-linearity seems to have a small effect in practice. It is further seen that the conditional variance of the GARCH process may, in turn, be decomposed into components. In fact, the conditional variance of the money supply series is the sum of a weak linear trend, a strong non-linear seasonal component, and a moderate non-linear irregular component. This information has policy implications: for example, there are periods in the year when policy can be more assertive because information is more precise. Finally, looking at the non-linear components of the money supply it is seen how linear combinations of non-linear series can produce series that behave linearly.