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.     

政府生产性基础设施投资对农业经济增长的影响——基于西安市的实证研究

根据西安市1988—2006年间的数据建立柯布一道格拉斯生产函数,在自回归分布滞后模型（ADL）下用最小二乘法（OLS）进行估计。实证分析结果显示：政府基础设施投资对西安市农业经济增长贡献显著,并且其作用远大于非基础设施投资的贡献,表明政府的生产性基础设施投资是西安市农业经济快速增长的关键因素。在此基础上,对西安市政府近期进行基础设施投资的重点方向提出了相关的政策建议。