A fully three-dimensional atomistic quantum mechanical study on random dopant-induced effects in 25-nm MOSFETs

A fully 3-D atomistic quantum mechanical simulation is presented to study the random dopant-induced effects in nanometer metal-oxide-semiconductor field-effect transistors. The empirical pseudopotential is used to represent the single particle Hamiltonian, and the linear combination of bulk band method is used to solve the million atom Schrodinger equation. The gate threshold fluctuation and lowering due to the discrete dopant configurations are studied. It is found that quantum mechanical effects increase the threshold fluctuation while decreasing the threshold lowering. The increase of threshold fluctuation is in agreement with the researchers' early study based on an approximated density gradient approach. However, the decrease in threshold lowering is in contrast with the density gradient calculations.

CSSI-PRO: a method for secondary structure type editing, assignment and estimation in proteins using linear combination of backbone chemical shifts

Estimation of secondary structure in polypeptides is important for studying their structure, folding and dynamics. In NMR spectroscopy, such information is generally obtained after sequence specific resonance assignments are completed. We present here a new methodology for assignment of secondary structure type to spin systems in proteins directly from NMR spectra, without prior knowledge of resonance assignments. The methodology, named Combination of Shifts for Secondary Structure Identification in Proteins (CSSI-PRO), involves detection of specific linear combination of backbone H-1(alpha) and C-13' chemical shifts in a two-dimensional (2D) NMR experiment based on G-matrix Fourier transform (GFT) NMR spectroscopy. Such linear combinations of shifts facilitate editing of residues belonging to alpha-helical/beta-strand regions into distinct spectral regions nearly independent of the amino acid type, thereby allowing the estimation of overall secondary structure content of the protein. Comparison of the predicted secondary structure content with those estimated based on their respective 3D structures and/or the method of Chemical Shift Index for 237 proteins gives a correlation of more than 90% and an overall rmsd of 7.0%, which is comparable to other biophysical techniques used for structural characterization of proteins. Taken together, this methodology has a wide range of applications in NMR spectroscopy such as rapid protein structure determination, monitoring conformational changes in protein-folding/ligand-binding studies and automated resonance assignment.

Two-dimensional NMR spectroscopy of connected transitions by linear combination of flip angle dependent cosy: An alternative scheme for E.COSY

An alternative pulse scheme which simplifies and improves the recently proposed P.E.COSY experiment is suggested for the retention of connected or unconnected transitions in a coupled spin system. An important feature of the proposed pulse scheme is the improved phase characteristics of the diagonal peaks. A comparison of various experiments designed for this purpose, namely COSY-45, E.COSY, P.E.COSY and the present scheme (A.E.COSY), is also presented. The suppression of unconnected transitions and the measurement of scalar coupling constants and their relative signs are illustrated from A.E.COSY spectra of 2,3-dibromopropionic acid and 2-(2-thienyl)pyridine.

Adaptive linear combination of heuristic orderings in constructing examination timetables

In this paper, we investigate adaptive linear combinations of graph coloring heuristics with a heuristic modifier to address the examination timetabling problem. We invoke a normalisation strategy for each parameter in order to generalise the specific problem data. Two graph coloring heuristics were used in this study (largest degree and saturation degree). A score for the difficulty of assigning each examination was obtained from an adaptive linear combination of these two heuristics and examinations in the list were ordered based on this value. The examinations with the score value representing the higher difficulty were chosen for scheduling based on two strategies. We tested for single and multiple heuristics with and without a heuristic modifier with different combinations of weight values for each parameter on the Toronto and ITC2007 benchmark data sets. We observed that the combination of multiple heuristics with a heuristic modifier offers an effective way to obtain good solution quality. Experimental results demonstrate that our approach delivers promising results. We conclude that this adaptive linear combination of heuristics is a highly effective method and simple to implement.

Quantitative 1H-magnetic resonance spectroscopy of human brain: Influence of composition and parameterization of the basis set in linear combination model-fitting

Localized short-echo-time (1)H-MR spectra of human brain contain contributions of many low-molecular-weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information.

The Boltzmann collision integrals for a combination of Maxwellians

The gain and loss integrals in the Boltzmann equation for a rigid sphere gas are evaluated in closed form for a distribution which can be expressed as a linear combination of Maxwellians. Application to the Mott-Smith bimodal distribution shows that the gain is also bimodal, but the two modes in the gain are less pronounced than in the distribution. Implications of these results for simple collision models in non-equilibrium flow are discussed.

Distributed Function Computation over Fields and Rings via Linear Compression of Sources

The setting considered in this paper is one of distributed function computation. More specifically, there is a collection of N sources possessing correlated information and a destination that would like to acquire a specific linear combination of the N sources. We address both the case when the common alphabet of the sources is a finite field and the case when it is a finite, commutative principal ideal ring with identity. The goal is to minimize the total amount of information needed to be transmitted by the N sources while enabling reliable recovery at the destination of the linear combination sought. One means of achieving this goal is for each of the sources to compress all the information it possesses and transmit this to the receiver. The Slepian-Wolf theorem of information theory governs the minimum rate at which each source must transmit while enabling all data to be reliably recovered at the receiver. However, recovering all the data at the destination is often wasteful of resources since the destination is only interested in computing a specific linear combination. An alternative explored here is one in which each source is compressed using a common linear mapping and then transmitted to the destination which then proceeds to use linearity to directly recover the needed linear combination. The article is part review and presents in part, new results. The portion of the paper that deals with finite fields is previously known material, while that dealing with rings is mostly new.Attempting to find the best linear map that will enable function computation forces us to consider the linear compression of source. While in the finite field case, it is known that a source can be linearly compressed down to its entropy, it turns out that the same does not hold in the case of rings. An explanation for this curious interplay between algebra and information theory is also provided in this paper.

Recognition by Linear Combinations of Models

Visual object recognition requires the matching of an image with a set of models stored in memory. In this paper we propose an approach to recognition in which a 3-D object is represented by the linear combination of 2-D images of the object. If M = {M1,...Mk} is the set of pictures representing a given object, and P is the 2-D image of an object to be recognized, then P is considered an instance of M if P = Eki=aiMi for some constants ai. We show that this approach handles correctly rigid 3-D transformations of objects with sharp as well as smooth boundaries, and can also handle non-rigid transformations. The paper is divided into two parts. In the first part we show that the variety of views depicting the same object under different transformations can often be expressed as the linear combinations of a small number of views. In the second part we suggest how this linear combinatino property may be used in the recognition process.

Model-Based Matching by Linear Combinations of Prototypes

We describe a method for modeling object classes (such as faces) using 2D example images and an algorithm for matching a model to a novel image. The object class models are "learned'' from example images that we call prototypes. In addition to the images, the pixelwise correspondences between a reference prototype and each of the other prototypes must also be provided. Thus a model consists of a linear combination of prototypical shapes and textures. A stochastic gradient descent algorithm is used to match a model to a novel image by minimizing the error between the model and the novel image. Example models are shown as well as example matches to novel images. The robustness of the matching algorithm is also evaluated. The technique can be used for a number of applications including the computation of correspondence between novel images of a certain known class, object recognition, image synthesis and image compression.

On linear combinations of L-orthogonal polynomials associated with distributions belonging to symmetric classes

This paper deals with the classes S-3(omega, beta, b) of strong distribution functions defined on the interval [beta(2)/b, b], 0 < beta < b <= infinity, where 2 omega epsilon Z. The classification is such that the distribution function psi epsilon S-3(omega, beta, b) has a (reciprocal) symmetry, depending on omega, about the point beta. We consider properties of the L-orthogonal polynomials associated with psi epsilon S-3(omega, beta, b). Through linear combination of these polynomials we relate them to the L-orthogonal polynomials associated with some omega epsilon S-3(1/2, beta, b). (c) 2004 Elsevier B.V. All rights reserved.

Modified linear prediction method for directions of arrival estimation of narrow-band plane waves

A modified linear prediction (MLP) method is proposed in which the reference sensor is optimally located on the extended line of the array. The criterion of optimality is the minimization of the prediction error power, where the prediction error is defined as the difference between the reference sensor and the weighted array outputs. It is shown that the L2-norm of the least-squares array weights attains a minimum value for the optimum spacing of the reference sensor, subject to some soft constraint on signal-to-noise ratio (SNR). How this minimum norm property can be used for finding the optimum spacing of the reference sensor is described. The performance of the MLP method is studied and compared with that of the linear prediction (LP) method using resolution, detection bias, and variance as the performance measures. The study reveals that the MLP method performs much better than the LP technique.

Novel Design of Honeycombs Using a Seamless Combination of Auxetic and Conventional Cores Toward Phononic Band Gap Engineering

A novel design for the geometric configuration of honeycombs using a seamless combination of auxetic and conventional cores- elements with negative and positive Possion ratios respectively, has been presented. The proposed design has been shown to generate a superior band gap property while retaining all major advantages of a purely conventional or purely auxetic honeycomb structure. Seamless combination ensures that joint cardinality is also retained. Several configurations involving different degree of auxeticity and different proportions auxetic and conventional elements have been analyzed. It has been shown that the preferred configurations open up wide and clean band gap at a significantly lower frequency ranges compared to their pure counterparts. In view of existence of band gaps being desired feature for the phononic applications, reported results might be appealing. Use of such design may enable superior vibration control as well. Proposed configurations can be made isovolumic and iso-weight giving designers a fairer ground of applying such configurations without significantly changing size and weight criteria.

Effect of In0.2Ga0.8As and In0.2Al0.8As combination layer on band offsets of InAs quantum dots

We demonstrate the self-organized InAs quantum dots capped with thin and In0.2Al0.8As and In0.2Ga0.8As combination layers with a large ground and first excited energy separation emission at 1.35 mum at room temperature. Deep level transient spectroscopy is used to obtain quantitative information on emission activation energies and capture barriers for electrons and holes. For this system, the emission activation energies are larger than those for InAs/GaAs quantum dots. With the properties of wide energy separation and deep emission activation energies, self-organized InAs quantum dots capped with In0.2Al0.8As and In0.2Ga0.8As combination layers are one of the promising epitaxial structures of 1.3 mum quantum dot devices. (C) 2004 American Institute of Physics.

Characterization of linear epitope of the beta(2)-microglobulin via combination of MALDI-TOF-MS with immunoaffinity

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry(MALDI-TOF-MS), in combination with immunoaffinity provided a powerful tool for determining epitope (antigenic determinant) in protein. The linear epitope of the beta(2)-microglobulin was characterized in the paper. The method as follows: at first beta(2)-microglobulin was digested by a proteolytic enzyme to produce an appropriate set of peptide fragments, then peptide fragments containing the linear epitope were selected and separated from the pool of peptide fragments by immunoprecipitation with the monoclonal antibody. The agarose beads were collected carefully after the reaction. Unbound peptides would be washed away, while the peptides containing the epitope would remain bound to the immobilized antibody after. the beads were washed several times with appropriate buffer. At last the masses of the bound peptides were identified directly by MALDI-TOF MS. Using Endoproteinase Glu-C Endoproteinase Lys-C and Trypsin in the experiment, the linear epitope of beta(2)-microglobulin was located within peptide fragment 59-69, that is, DWSFYLLYYTE.