关于动力学理論中的扰动方法

本文讨论了动力学理论中求解Vlasov-Maxwell方程的扰动方法,证明了第一次线性化后的高阶分布函数对研究电磁波与带电粒子之间的互作用没有影响,并给出了第二次线性化后的Vlasov-Maxwell方程的一般求解方法.     

脊波导回旋管的大信号分析

本文在建立脊波导大回旋半径回旋管模型的基础上,对此回旋管做了非线性理论计算和分析,给出了脊波导场和QP_W公式的表达式。对于脊波导TE_(101)、TE_(301)模式电子回旋基波和回旋三次谐波工作的三种回旋管情形做了详细的计算。结果指出,TE_(301)回旋三次谐波工作的回旋管有51％的高效率。     

成电8010分布式計算机之特点

成电8010是基于单板机开发成功的分布式微机过程控制系统。该系统的性能特点是任务的动态调度、机间合作、优美降级和资源分享等。这些特点使其应用非常成功。本文就是对这些性能特点作相应的分析和介绍。     

黄化型大麦的系列研究 Ⅲ南黄大麦生长发育的调查

本文系统地报道了南黄大麦与原品种早熟3号在生育期、植株高度、叶片长宽、分蘖数以及穗部性状等方面的比较.指出南黄大麦除出土时间,倒二叶的长宽与早熟3号基本一致,剑叶长宽略大于早熟3号外,其余性状差异显著.植株矮小,生长发育缓慢,这与黄化型大麦叶色浅,叶绿体的片层结构不发达,光合机能弱,光合产物少有关.     

Convective Filmwise Condensation of R-11 inside a Vertical Tube

Partial condensation of refrigerant R-11 was experimentally and theoretically studied. The test apparatus consisted of two concentric tubes, with the vapor flowing downward in the inner tube and the cooling water in the annular space in countercurrent direction. By using the available dimensionless correlation, the mean heat transfer coefficient of the cooling water was determined, and then the mean condensationheat transfer coefficient was calculated from the overall heat transfer coefficient.The model of a homogeneous two-phase mixture of liquid and vapor, and Prandtl's principle of analogy between the momentum and heat transfer were used to establish the type of the correlation. Adopting the methods of the gradually linear regression and F-level evidence testing, the present paper proposed the dimensionless correlation to predict the relationship among the mean Nusselt number, Prandtl number, Kutateladze number and the dimensionless tube length.     

多源场的高斯定理及其应用

现行的电磁学对线电荷的能量公式、静电平衡条件都没有直接推导过.本文先提出多源场的高斯定理公式,然后进行推导,以供参考.     

Sparse additive models

Summary.  We present a new class of methods for high dimensional non-parametric regression and classification called sparse additive models. Our methods combine ideas from sparse linear modelling and additive non-parametric regression. We derive an algorithm for fitting the models that is practical and effective even when the number of covariates is larger than the sample size. Sparse additive models are essentially a functional version of the grouped lasso of Yuan and Lin. They are also closely related to the COSSO model of Lin and Zhang but decouple smoothing and sparsity, enabling the use of arbitrary non-parametric smoothers. We give an analysis of the theoretical properties of sparse additive models and present empirical results on synthetic and real data, showing that they can be effective in fitting sparse non-parametric models in high dimensional data.     

Parametric non-mixture cure models for schedule finding of therapeutic agents

We propose a phase I clinical trial design that seeks to determine the cumulative safety of a series of administrations of a fixed dose of an investigational agent. In contrast with traditional phase I trials that are designed solely to find the maximum tolerated dose of the agent, our design instead identifies a maximum tolerated schedule that includes a maximum tolerated dose as well as a vector of recommended administration times. Our model is based on a non-mixture cure model that constrains the probability of dose limiting toxicity for all patients to increase monotonically with both dose and the number of administrations received. We assume a specific parametric hazard function for each administration and compute the total hazard of dose limiting toxicity for a schedule as a sum of individual administration hazards. Throughout a variety of settings motivated by an actual study in allogeneic bone marrow transplant recipients, we demonstrate that our approach has excellent operating characteristics and performs as well as the only other currently published design for schedule finding studies. We also present arguments for the preference of our non-mixture cure model over the existing model.     

On equality of ordinary least squares estimator,best linear unbiased estimator and best linear unbiased predictor in the general linear model

The equality of ordinary least squares estimator (OLSE), best linear unbiased estimator (BLUE) and best linear unbiased predictor (BLUP) in the general linear model with new observations is investigated through matrix rank method, some new necessary and sufficient conditions are given.