Folding of a nascent polypeptide chain in vitro: cooperative formation of structure in a protein module.

We have prepared a family of peptide fragments of the 64-residue chymotrypsin inhibitor 2, corresponding to its progressive elongation from the N terminus. The growing polypeptide chain has little tendency to form stable structure until it is largely synthesized, and what structures are formed are nonnative and lack, in particular, the native secondary structural elements of alpha-helix and beta-sheet. These elements then develop as sufficient tertiary interactions are made in the nearly full-length chain. The growth of structure in the small module is highly cooperative and does not result from the hierarchical accretion of substructures.

DESIGN OF A MINIATURIZED SOP INTEGRATED GNSS RF FRONT-END MODULE

Navigation devices used to be bulky and expensive and were not widely commercialized for personal use. Nowadays, all useful electronic devices are turning into being handheld so that they can be conveniently used anytime and anywhere. One can claim that almost any mobile phone, used today, has quite strong navigational capabilities that can efficiently work anywhere in the globe. No matter where you are, you can easily know your exact location and make your way smoothly to wherever you would like to go. This couldn’t have been made possible without the existence of efficient and small microwave circuits responsible for the transmission and reception of high quality navigation signals. This thesis is mainly concerned with the design of novel highly miniaturized and efficient filtering components working in the Global Navigational Satellite Systems (GNSS) frequency band to be integrated within an efficient Radio Frequency (RF) front-end module (FEM). A System-on-Package (SoP) integration technique is adopted for the design of all the components in this thesis. Two novel miniaturized filters are designed, where one of them is a wideband filter targeting the complete GNSS band with a fractional bandwidth of almost 50% at a center frequency of 1.385 GHz. This filter utilizes a direct inductive coupling topology to achieve the required wide band performance. It also has very good out-of-band rejection and low IL. Whereas the other dual band filter will only cover the lower and upper GNSS bands with a rejection notch in between the two bands. It has very good inter band rejection. The well-known “divide and conquer” design methodology was applied for the design of this filter to help save valuable design and optimization time. Moreover, the performance of two commercially available ultra-Low Noise Amplifiers (LNAs) is studied. The complete RF FEM showed promising preliminary performance in terms of noise figure, gain and bandwidth, where it out performed other commercial front-ends in these three aspects. All the designed circuits are fabricated and tested. The measured results are found to be in good agreements with the simulations.

TEXDOC: Stata module to create a LaTeX document including Stata output

texdoc provides tools to create a LaTeX document from within Stata in a weaving fashion. This is especially useful if you want to produce a LaTeX document that contains Stata output, such as, e.g., a Stata Journal article or solutions to statistics homework assignments.

TABLETUTORIAL: Stata module to provide tutorial on automated table generation and reporting

-tabletutorial- illustrates how Stata can be used to export statistical results and generate customized reports. Part 1 explains how results from Stata routines can be accessed and how they can be exported using the -file- comand or a wrapper such as, e.g., -mat2txt-. Part 2 shows how model estimation results can be archived using -estwrite- and how models can be tabulated and exported to LaTeX, MS Excel, or MS Word using -estout-. Part 3 illustrates how to set up automatic reports in LaTeX or MS Word. The tutorial is based on a talk given at CEPS/INSTEAD in Luxembourg in October 2008. After install, type -help tabletutorial- to start the tutorial (in Stata 8, type -whelp tabletutorial-). The -mat2txt-, -estwrite-, and -estout- packages, also available from SSC, are required to run the examples.

PSPLINE: Stata module providing a penalized spline scatterplot smoother based on linear mixed model technology

Pspline uses xtmixed to fit a penalized spline regression and plots the smoothed function. Additional covariates can be specified to adjust the smooth and plot partial residuals.

NLCHECK: Stata module to check linearity assumption after model estimation

nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model

LOGITCPRPLOT: Stata module to graph component-plus-residual plot for logistic regression

logitcprplot can be used after logistic regression for graphing a component-plus-residual plot (a.k.a. partial residual plot) for a given predictor, including a lowess, local polynomial, restricted cubic spline, fractional polynomial, penalized spline, regression spline, running line, or adaptive variable span running line smooth

RRREG: Stata module to estimate linear probability model for randomized response data

rrreg fits a linear probability model for randomized response data

OAXACA: Stata module to compute the Blinder-Oaxaca decomposition

-oaxaca- computes the so-called Blinder-Oaxaca decomposition, which is often used to analyze wage gaps by sex or race. Older versions of this routine are available as -oaxaca9- and -oaxaca8-.

DIGDIS: Stata module to analyze the distribution of digits

digdis tabulates the distribution of digits of the specified variables, performs goodness-of-fit tests against a reference distribution and, optionally, graphs the distributions. The default is to tabulate the first (nonzero) digit and to test against Benford's law. The moremata package and the mgof package, also available from SSC, are required.

MGOF: Stata module to perform goodness-of-fit tests for multinomial data

mgof computes goodness-of-fit tests for the distribution of a discrete (categorical, multinomial) variable. The default is to perform classical large sample chi-squared approximation tests based on Pearson's X2 statistic and the log likelihood ratio (G2) statistic or a statistic from the Cressie-Read family. Alternatively, mgof computes exact tests using Monte Carlo methods or exhaustive enumeration. A Kolmogorov-Smirnov test for discrete data is also provided. The moremata package, also available from SSC, is required.

ADOLIST: Stata module to manage lists of ado packages

-adolist- creates, installs and uninstalls lists of user ado packages.

ANOGI: Stata module to generate Analysis of Gini

anogi computes the "Analysis of Gini" for population sub-groups proposed by Frick et al. (2006; Sociological Methods and Research 34/4).

GSAMPLE: Stata module to draw a random sample

gsample draws a random sample from the data in memory. Simple random sampling (SRS) is supported, as well as unequal probability sampling (UPS), of which sampling with probabilities proportional to size (PPS) is a special case. Both methods, SRS and UPS/PPS, provide sampling with replacement and sampling without replacement. Furthermore, stratified sampling and cluster sampling is supported.