齐次核的Hilbert型多重级数不等式取最佳常数因子的等价条件及应用

利用实分析技巧和权函数方法, 讨论具有齐次核的多重级数Hilbert型不等式, 得到了其取最佳常数因子的充分必要条件, 并给出其应用.     

宇宙临界减速因子

本文证明了如果中微子具有质量,那么膨胀宇宙的临界减速因子q_c就不是通常所说的1/2而是等于1。     

浅谈智能模糊控制恒压供水系统

文章介绍在变频恒压供水系统的基础上采用智能模糊控制等特性来完成恒压供水。     

Alcohol dehydrogenase 2 is a major hepatic enzyme for human retinol metabolism

The metabolism of all-trans- and 9-cis-retinol/ retinaldehyde has been investigated with focus on the activities of human, mouse and rat alcohol dehydrogenase 2 (ADH2), an intriguing enzyme with apparently different functions in human and rodents. Kinetic constants were determined with an HPLC method and a structural approach was implemented by in silico substrate dockings. For human ADH2, the determined K_m values ranged from 0.05 to 0.3 μM and k_cat values from 2.3 to 17.6 min⁻¹, while the catalytic efficiency for 9-cis-retinol showed the highest value for any substrate. In contrast, poor activities were detected for the rodent enzymes. A mouse ADH2 mutant (ADH2Pro47His) was studied that resembles the human ADH2 setup. This mutation increased the retinoid activity up to 100-fold. The K_m values of human ADH2 are the lowest among all known human retinol dehydrogenases, which clearly support a role in hepatic retinol oxidation at physiological concentrations. Received 12 October 2006; received after revision 6 December 2006; accepted 8 January 2007     

奇异积分算子对p幂可积函数的逼近常数的上界估计

本文探讨由正偶核确定的奇异积分算子对连续函数的逼近常数与对p幂可积函数的逼近常数之间的关系,并由此得到Fejér算子、Jackson算子和Vallee-Poussin算子对p幂可积函数逼近常数的上界。     

三球式和转台式角动量守恒演示器的研制与应用

本文详细介绍了笔者研制的三球式和转台式两种新型角动量守恒演示器的结构、特点和使用方法。     

哈里·柯林斯思想对SSK的贡献研究

在诸多科学知识社会学的文献中,柯林斯文章的引证率位居同类研究者榜首,文章分析了哈里·柯林斯在其研究范围内做出的贡献。     

首达渗流中关于时间常数μ的上界估计

对2维首达渗流的时间常数μ给出了一个上界估计．     

谈英语阅读中捷效寻读教学及能力的培养

根据对一些学生的日常阅读情况的观察和阅读理论最新的研究成果 ,以及心理学的相关理论的分析 ,提出应该加强捷效寻读技能的教学 ,从理论和实践上提出了相应的方法。     

Exponential smoothing: Behavior of the ex-post sum of squares near 0 and 1

When using simple exponential smoothing on a given time series the nature of the relationship between the optimal smoothing constant and the autocorrelation structure of the series remains an unresolved question. Although numerical search routines can easily be used to find optimal values of the smoothing constant, they offer little insight into the nature of the relationship between the estimated smoothing constant and the structure of the underlying time series. We suggest that renewed investigations of the ex-post sum of squares function may prove helpful in this pursuit. Results are presented that illustrate how the optimal smoothing constant depends upon the value used to initialize the smoothing and upon the sample autocorrelation coefficients of the observed series. These results are based on a new formula for the derivative of the ex-post sum of squares function. In particular, the derivative is examined near 0 and 1, where great simplifications occur in its form, thereby facilitating investigations near these points. A necessary and sufficient condition is stated for when the ex-post sum of squares must have a positive derivative at 0 and the autocorrelation coefficients of the differenced series are shown to affect the sign of the derivative near 1. Based on these results, a general algorithm is presented as an alternative to grid search routines for minimizing the ex-post sum of squares.