Investigation of iodine as a donor in MBE grown Hg1−xCdxTe

N-type Hg_1−xCd_xTe layers with x values of 0.3 and 0.7 have been grown by molecular beam epitaxy using iodine in the form of CdI₂ as a dopant. Carrier concentrations up to 1.1 × 10¹⁸ cm⁻³ have been achieved for x = 0.7 and up to 7.6 × 10¹⁷ cm⁻³ for x=0.3. The best low temperature mobilities are 460 cm²/(Vs) and 1.2 × 10⁵ cm²/(Vs) for x=0.7 and x=0.3, respectively. Using CdI₂ as the dopant modulation doped HgTe quantum well structures have been grown. These structures display very pronounced Shubnikov-de Haas oscillations and quantum Hall plateaus. Electron densities in the 2D electron gas in the HgTe quantum well could be varied from 1.9 × 10¹¹ cm⁻² up to 1.4 × 10¹² cm⁻² by adjusting the thicknesses of the spacer and doped layer. Typical mobilities of the 2D electron gas are of the order of 5.0 × 10⁴ cm²/(Vs) with the highest value being 7.8 × 10⁴ cm²/(Vs).     

Biosynthetic studies on the macrolide antibiotic turimycin using 14C-labeled precursors

Using a strain of Streptomyces hygroscopicus JA 6599 several 14C-compounds were investigates as potential precursors of the macrolide antibiotic turimycin followed by partial degradation to localize the radioactivity. L-Methionine-14C-methyl and n-butyrate-1-14C were incorporated exclusively and in a specific manner. The incorporation ratios were dependent on the addition time of the precursors. Studies of the incorporation of acylmycaroses and demycarosyl turimycin into the antibiotic are also reported.     

混合自回归动平均时间序列的自回归参数估计

在二阶平稳时间序列的混合自回归动平均(ARMA)的表达式中,现在的观测可表示为它自己的过去历史的有限线性组合(自回归部分)加上不能预测的部分,后者是由不相关随机变量的有限线性组合(移动平均部分)构成的。本文讨论只利用输出数据时对已知阶数的混合ARMA时间序列的自回归(AR)参数的估计问题。     

Design considerations for thin film coated semiconductor thermal neutron detectors—I: basics regarding alpha particle emitting neutron reactive films

Semiconductor-based thermal neutron detectors provide a compact technology for neutron detection and imaging. Such devices can be produced by externally coating semiconductor-charged-particle detectors with neutron reactive films that convert free neutrons into charged-particle reaction products. Commonly used films for such devices utilize the ¹⁰B(n,)⁷Li reaction or the ⁶Li(n,)³H reaction, which are attractive due to the relatively high energies imparted to the reaction products. Unfortunately, thin film or “foil” type thermal neutron detectors suffer from self-absorption effects that ultimately limit neutron detection efficiency. Design considerations that maximize the efficiency and performance of such devices are discussed. Theoretical and experimental results from front coated, back coated, and “sandwich” designs are presented.     

A smoothness priors long AR model method for spectral estimation

A new smoothness priors long AR model method approach is taken to the short data span spectral estimation problem. An autoregressive (AR) model that is relatively long compared to the data length is considered. The smoothness priors are in the form of the integrated squared derivatives of the AR model whitening filter. A smoothness tradeoff parameter or Bayesian hyperparameter balances the tradeoff between the infidelity of the AR model to the data and the infidelity of the model to the smoothness constraint. The critical computation of the likelihood of the hyperparameters of the Bayesian model is realized by a constrained least squares computation. Numerical examples are shown. The results of simulation studies using entropy comparison evaluations of the Bayesian and minimum AIC-AR methods of spectral estimation are also shown.     

Computation of the mean-square response of a stationary time-discrete system

A machine computational procedure for evaluating the mean-square response of an uncorrelated sequence excited stationary time-discrete system is presented.     

Estimation of the autoregressive parameters of a mixed autoregressive moving-average time series

The problem of estimating the autoregressive parameters of a mixed autoregressive moving-average (ARMA) time series (of known order) using the output data alone is treated. This problem is equivalent to the estimation of the denominator terms of the scalar transfer function of a stationary, linear discrete time system excited by an unobserved unenrrelated sequence input by employing only the observations of the scalar output. The solution of this problem solves the problem of the identification of the dynamics of a white-noise excited continuous-time linear stationary system using sampled data. The latter problem was suggested by Bartlett in 1946. The problem treated here has appeared before in the engineering literature. The earlier treatment yielded biased parameter estimates. An asymptotically unbiased estimator of the autoregressive parameters is obtained as the solution of a modified set of Yule-Walker equations. The asymptotic estimator covariance matrix behaves like a least-squares parameter estimate of an observation set with unknown error covariances. The estimators are also shown to be unbiased in the presence of additive independent observation noise of arbitrary finite correlation time. An example illustrates the performance of the estimating procedures.