Measurement and Identification of the Parameters of SPICE-Models of a Bipolar Transistor

A method of measuring and identifying the static parameters of a bipolar transistor is considered. The characteristic of the transistor, from which the parameters of the model are determined, is chosen depending on what group the calculated parameters belong to. The characteristics are measured in such a way that the equations of the model describing them can be reduced to the simplest form.     

基于模式理论光栅椭偏参数反演的数值模拟

将一种广泛用于求解系统优化问题的方法——正单纯形法，求解光栅的椭偏方程。首先，利用求解光栅的傅立叶模式理论对TE和TM波的复反射系数进行求解。然后计算出其相应的椭偏参数(△，Ψ)，并在该值的基础上加入不同偏差的随机高斯噪声，将加入噪声后的值(△m，Ψm)作为模拟测量值。最后使用优化算法进行反演。通过对几种常用面形光栅椭偏参数的数值模拟，一方面表明傅立叶模式理论计算光栅的椭偏参数不仅精度高。而且速度快；另一方面表明利用正单纯形法得到的光栅参数值很接近于正演时假设的参数值，从而从理论上证明了利用椭偏法测量光栅各种光学参数的可行性。     

钻井参数仪的模块化设计方法研究

文章以模块化设计原理为基础，讨论了钻井参数仪的模块划分，模块化设计准则和主要设计内容。采用模块化设计方法、现场设备网络的开放网络和现场总线解决方案设计的钻井参数仪，具有传输信号稳定、可靠性高、抑制噪声能力强、组建现场网络成本低等特点。     

A stochastic model for localized disturbances and its applications

A stochastic model for local disturbances, particularly for a temporal harmonic with random modulations in amplitude and/or phase, is proposed in this paper. Results for the second moment responses of a linear single-degree-of-freedom system to this type of stochastic loading demonstrate a significant change in response characteristics due to a small uncertainty. A local phenomenon may last much longer and resonance may be smeared to a broad range. Integrated with wavelet transform, the proposed approach may be used to model a random process with non-stationary frequency content. Especially, it can be effectively used for Monte Carlo simulation to generate large size of samples that have similar characteristics in time and frequency domains as a pre-selected mother sample has. The technique has a great potential for the case where uncertainty study is warranted but the available samples are limited.     

带参数的一阶脉冲微分方程边值问题

利用上下解和单调迭代法。讨论了带参数的一阶脉冲微分方程。获得了单边Lipschitz条件下这类方程边值问题的解的存在性。     

Texture Changes During the Ripening of Port Salut Argentino Cheese in 2 Sampling Zones

ABSTRACT: Texture changes during ripening of Port Salut Argentino cheese for different sampling zones were studied. Compression relaxation tests were performed and results were analyzed using both Maxwellian and Peleg's models. Elastic equilibrium modulus obtained from the Maxwellian model decreased from 1.22 to 0.11 10⁴Pa during ripening. The constants derived from Peleg's model, k₁ and k₂, diminished with ripening time from 1.18 to 0.71 min and from 1.27 to 1.12, respectively. Asymptotic equilibrium modulus from Peleg's model decreased from 0.95 to 0.07 10⁴Pa during ripening. Rate parameters derived from a 1st order kinetics applied to both equilibrium moduli showed that the decrease was faster in the external zone (0.0846 d⁻¹) than in the central zone (0.0368 d⁻¹). The correlation between equilibrium moduli, salt concentration, moisture content, and maturation indexes was obtained with a determination coefficient of 0.76.     

Addition of pectolytic enzymes: an enological practice which improves the chromaticity and stability of red wines

Summary The effect of the addition of four commercial pectolytic preparations on the visual characteristics (colour and turbidity) of red wines has been evaluated. The effect of both clarifying and colour extracting enzymes and the effect of different doses used, were evaluated and compared. All the red wines treated enzymatically, independent of the type of enzyme and dose, present chromatic characteristics which can be considered better than those of the control wines. Also, those wines treated with enzymes had greater stability during 2 years storage in bottles, in particular the turbidity was better than untreated wines.     

真空制盐蒸发结晶器的设计与实践

真空蒸发制盐外热式强制逆循环轴向出料蒸发结晶器，经多个厂家生产应用实践证明是成功的，具有生命力的。这种新型结构，作为一项新技术新设备应加强研究，总结提高，推广应用。不断完善。文章从流体力学、结晶机理角度要求，到具体工程设计参数和材质选用。论述了该罐的特点。     

A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm

The estimation of the differences among groups in observational studies is frequently inaccurate owing to a bias caused by differences in the distributions of covariates. In order to estimate the average treatment effects when the treatment variable is binary, Rosenbaum and Rubin [1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55] proposed an adjustment method for pre-treatment variables using propensity scores. Imbens [2000. The role of the propensity score in estimating dose-response functions. Biometrika 87, 706-710] extended the propensity score methodology for estimation of average treatment effects with multivalued treatments.However, these studies focused only on estimating the marginal mean structure. In many substantive sciences such as the biological and social sciences, a general estimation method is required to deal with more complex analyses other than regression, such as testing group differences on latent variables. For latent variable models, the EM algorithm or the traditional Monte Carlo methods are necessary. However, in propensity score adjustment, these methods cannot be used because the full distribution is not specified.In this paper, we propose a quasi-Bayesian estimation method for general parametric models that integrate out the distributions of covariates using propensity scores. Although the proposed Bayes estimates are shown to be consistent, they can be calculated by existing Markov chain Monte Carlo methods such as Gibbs sampler. The proposed method is useful to estimate parameters in latent variable models, while the previous methods were unable to provide valid estimates for complex models such as latent variable models.We also illustrated the procedure using the data obtained from the US National Longitudinal Survey of Children and Youth (NLSY1979-2002) for estimating the effect of maternal smoking during pregnancy on the development of the child's cognitive functioning.     

Sandia National Laboratories Validation Workshop: Structural dynamics application

This article specifies a virtual structural dynamic subsystem and some systems, as well as mathematical models that approximately simulate them. The purpose is to define a setting for model validations conceived by participants in the Sandia National Laboratories Validation Workshop. Some broad guidelines for the model validations are set, as well as a regulatory requirement to be satisfied by the target system. Participants are directed to present techniques for subsystem model validation, to analytically predict whether or not the regulatory requirement will be met, and to estimate the likelihood of accuracy of the prediction.