Wavelet Features for Recognition of First Episode of Schizophrenia from MRI Brain Images

Machine learning methods are increasingly used in various fields of medicine, contributing to early diagnosis and better quality of care. These outputs are particularly desirable in case of neuropsychiatric disorders, such as schizophrenia, due to the inherent potential for creating a new gold standard in the diagnosis and differentiation of particular disorders. This paper presents a scheme for automated classification from magnetic resonance images based on multiresolution representation in the wavelet domain. Implementation of the proposed algorithm, utilizing support vector machines classifier, is introduced and tested on a dataset containing 104 patients with first episode schizophrenia and healthy volunteers. Optimal parameters of different phases of the algorithm are sought and the quality of classification is estimated by robust cross validation techniques. Values of accuracy, sensitivity and specificity over 71% are achieved

Targeting of cytochrome b2 into the mitochondrial intermembrane space

Cytochrome b2 contains 2-fold targeting information: an amino-terminal signal for targeting to the mitochondrial matrix, followed by a second cleavable sorting signal that functions in directing the precursor into the mitochondrial intermembrane space. The role of the second sorting sequence was analyzed by replacing one, two or all of the three positively charged amino acid residues which are present at the amino-terminal side of the hydrophobic core by uncharged residues or an acidic residue. With a number of these mutant precursor proteins, processing to the mature form was reduced or completely abolished and at the same time targeting to the matrix space occurred. The accumulation in the matrix depended on a high level of intramitochondrial ATP. At low levels of matrix ATP, the mutant proteins were sorted into the intermembrane space like the wild-type precursors. The results: (i) suggest the existence of one or more matrix components that specifically recognize the second sorting signal and thereby trigger the translocation into the intermembrane space; (ii) indicate that the mutant signals have reduced ability to interact with the recognition component(s) and then embark on the default pathway into the matrix by interacting with mitochondrial hsp70 in conjunction with matrix ATP; (iii) strongly argue against a mechanism by which the hydrophobic segment of the sorting sequence stops translocation in the hydrophobic phase of the inner membrane

Stochastic dynamics of adhesion clusters under shared constant force and with rebinding

Single receptor-ligand bonds have finite lifetimes, so that biological systems can dynamically react to changes in their environment. In cell adhesion, adhesion bonds usually act cooperatively in adhesion clusters. Outside the cellular context, adhesion clusters can be probed quantitatively by attaching receptors and ligands to opposing surfaces. Here we present a detailed theoretical analysis of the stochastic dynamics of a cluster of parallel bonds under shared constant loading and with rebinding. Analytical solutions for the appropriate one-step master equation are presented for special cases, while the general case is treated with exact stochastic simulations. If the completely dissociated state is modeled as an absorbing boundary, mean cluster lifetime is finite and can be calculated exactly. We also present a detailed analysis of fluctuation effects and discuss various approximations to the full stochastic description.Comment: Revtex, 29 pages, 23 postscript figures included (some with reduced image quality

Polarization singularities from unfolding an optical vortex through a birefringent crystal

Optical vortices (nodal lines and phase singularities) are the generic singularities of scalar optics but are unstable in vector optics. We investigate experimentally and theoretically the unfolding of a uniformly polarized optical vortex beam on propagation through a birefringent crystal and characterize the output field in terms of polarization singularities (C lines and points of circular polarization; L surfaces and lines of linear polarization). The field is described both in the 2-dimensional transverse plane, and in three dimensions, where the third is abstract, representing an optical path length propagated through the crystal. Many phenomena of singular optics, such as topological charge conservation and singularity reconnections, occur naturally in the description

Electronic Structure and Magnetic Properties of β\beta-Ti6_{6}Sn5_{5}

The electronic structure of $\beta$-Ti$_{6}$Sn$_{5}$ has been studied based on the density functional theory within the local-density approximation. The calculation indicates that $\beta$-Ti$_{6}$Sn$_{5}$ is very close to ferromagnetic instability and shows ferromagnetic ordering after rare earth element doping. Large enhancement of the static susceptibility over its non-interacting value is found due to a peak in the density of states at the Fermi level

Polarization singularities from unfolding an optical vortex through a birefringent crystal

Optical vortices (nodal lines and phase singularities) are the generic singularities of scalar optics but are unstable in vector optics. We investigate experimentally and theoretically the unfolding of a uniformly polarized optical vortex beam on propagation through a birefringent crystal and characterize the output field in terms of polarization singularities (C lines and points of circular polarization; L surfaces and lines of linear polarization). The field is described both in the 2-dimensional transverse plane, and in three dimensions, where the third is abstract, representing an optical path length propagated through the crystal. Many phenomena of singular optics, such as topological charge conservation and singularity reconnections, occur naturally in the description

Superconducting phase transition in the Nambu - Jona-Lasinio model

The Nambu - Bogoliubov - de Gennes method is applied to the problem of superconducting QCD. The effective quark-quark interaction is described within the framework of the Nambu - Jona-Lasinio model. The details of the phase diagram are given as a function of the strength of the quark-quark coupling constant $G^{\prime}$. It is find that there is no superconducting phase transition when one uses the relation between the coupling constants $G^{\prime}$ and $G$ of the Nambu - Jona-Lasinio model which follows from the Fierz transformation. However, for other values of $G^{\prime}$ one can find a rich phase structure containing both the chiral and the superconducting phase transitions.Comment: 7 pages, 3 figure

The Loss Rank Principle for Model Selection

We introduce a new principle for model selection in regression and classification. Many regression models are controlled by some smoothness or flexibility or complexity parameter c, e.g. the number of neighbors to be averaged over in k nearest neighbor (kNN) regression or the polynomial degree in regression with polynomials. Let f_D^c be the (best) regressor of complexity c on data D. A more flexible regressor can fit more data D' well than a more rigid one. If something (here small loss) is easy to achieve it's typically worth less. We define the loss rank of f_D^c as the number of other (fictitious) data D' that are fitted better by f_D'^c than D is fitted by f_D^c. We suggest selecting the model complexity c that has minimal loss rank (LoRP). Unlike most penalized maximum likelihood variants (AIC,BIC,MDL), LoRP only depends on the regression function and loss function. It works without a stochastic noise model, and is directly applicable to any non-parametric regressor, like kNN. In this paper we formalize, discuss, and motivate LoRP, study it for specific regression problems, in particular linear ones, and compare it to other model selection schemes.Comment: 16 page