Characterizing topological and dynamical properties of complex networks without border effects

The properties of complex networks are highly Influenced by border effects frequently found as a consequence of the finite nature of real-world networks as well as network Sampling Therefore, it becomes critical to devise effective means for sound estimation of net work topological and dynamical properties will le avoiding these types of artifacts. In the current work, an algorithm for minimization of border effects is proposed and discussed, and its potential IS Illustrated with respect to two real-world networks. namely bone canals and air transportation (C) 2009 Elsevier B.V. All rights reserved.

Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

Generating segmented meshes from textured color images

This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion to extract features from the training data. The W-operator is built into the local error estimation used by Imesh to choose the mesh vertices. Furthermore, the W-operator also enables to assign a label to the triangles during the mesh construction, thus allowing to obtain a segmented mesh at the end of the process. The presented results show that the combination of W-operators with Imesh gives rise to a texture classification-based triangle mesh generation framework that outperforms pixel based methods. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.

Intrinsically Multivariate Predictive Genes

Canalizing genes possess such broad regulatory power, and their action sweeps across a such a wide swath of processes that the full set of affected genes are not highly correlated under normal conditions. When not active, the controlling gene will not be predictable to any significant degree by its subject genes, either alone or in groups, since their behavior will be highly varied relative to the inactive controlling gene. When the controlling gene is active, its behavior is not well predicted by any one of its targets, but can be very well predicted by groups of genes under its control. To investigate this question, we introduce in this paper the concept of intrinsically multivariate predictive (IMP) genes, and present a mathematical study of IMP in the context of binary genes with respect to the coefficient of determination (CoD), which measures the predictive power of a set of genes with respect to a target gene. A set of predictor genes is said to be IMP for a target gene if all properly contained subsets of the predictor set are bad predictors of the target but the full predictor set predicts the target with great accuracy. We show that logic of prediction, predictive power, covariance between predictors, and the entropy of the joint probability distribution of the predictors jointly affect the appearance of IMP genes. In particular, we show that high-predictive power, small covariance among predictors, a large entropy of the joint probability distribution of predictors, and certain logics, such as XOR in the 2-predictor case, are factors that favor the appearance of IMP. The IMP concept is applied to characterize the behavior of the gene DUSP1, which exhibits control over a central, process-integrating signaling pathway, thereby providing preliminary evidence that IMP can be used as a criterion for discovery of canalizing genes.

An information-theoretic approach to statistical dependence: Copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009

A compound class of Weibull and power series distributions

In this paper we introduce the Weibull power series (WPS) class of distributions which is obtained by compounding Weibull and power series distributions where the compounding procedure follows same way that was previously carried out by Adamidis and Loukas (1998) This new class of distributions has as a particular case the two-parameter exponential power series (EPS) class of distributions (Chahkandi and Gawk 2009) which contains several lifetime models such as exponential geometric (Adamidis and Loukas 1998) exponential Poisson (Kus 2007) and exponential logarithmic (Tahmasbi and Rezaei 2008) distributions The hazard function of our class can be increasing decreasing and upside down bathtub shaped among others while the hazard function of an EPS distribution is only decreasing We obtain several properties of the WPS distributions such as moments order statistics estimation by maximum likelihood and inference for a large sample Furthermore the EM algorithm is also used to determine the maximum likelihood estimates of the parameters and we discuss maximum entropy characterizations under suitable constraints Special distributions are studied in some detail Applications to two real data sets are given to show the flexibility and potentiality of the new class of distributions (C) 2010 Elsevier B V All rights reserved

Surface active ionic liquids: Study of the micellar properties of 1-(1-alkyl)-3-methylimidazolium chlorides and comparison with structurally related surfactants

The impetus for the increasing interest in studying surface active ionic liquids (SAILs; ionic liquids with long-chain ""tails"") is the enormous potential for their applications, e.g., in nanotechnology and biomedicine. The progress in these fields rests on understanding the relationship between surfactant structure and solution properties, hence applications. This need has prompted us to extend our previous study on 1-(1-hexadecyl)-3-methylimidazolium chloride to 1-(1-alkyl)-3-methylimidazolium chlorides, with alkyl chains containing 10, 12, and 14 carbons. In addition to investigating relevant micellar properties, we have compared the solution properties of the imidazolium-based surfactants with: 1-(1-alkyl)pyridinium chlorides, and benzyl (2-acylaminoethyl)dimethylammonium chlorides. The former series carries a heterocyclic ring head-group, but does not possess a hydrogen that is as acidic as H2 of the imidazolium ring. The latter series carries an aromatic ring, a quaternary nitrogen and (a hydrogen-bond forming) amide group. The properties of the imidazolium and pyridinium surfactants were determined in the temperature range from 15 to 75 degrees C. The techniques employed were conductivity, isothermal titration calorimetry, and static light scattering. The results showed the important effects of the interactions in the interfacial region on the micellar properties over the temperature range studied. (C) 2011 Elsevier Inc. All rights reserved.

A physical organic chemistry approach to dissolution of cellulose: effects of cellulose mercerization on its properties and on the kinetics of its decrystallization

The effects of alkali treatment on the structural characteristics of cotton linters and sisal cellulose samples have been studied. Mercerization results in a decrease in the indices of crystallinity and the degrees of polymerization, and an increase in the alpha-cellulose contents of the samples. The relevance of the structural properties of cellulose to its dissolution is probed by studying the kinetics of cellulose decrystallization, prior to its solubilization in LiCl/N,N-dimethylacetamide (DMAc). Our data show that the decrystallization rate constants and activation parameters are only slightly dependent on the physico-chemical properties of the starting celluloses. This multi-step reaction is accompanied by a small enthalpy and large, negative, entropy of activation. These results are analyzed in terms of the interactions within the biopolymer chains during decrystallization, as well as those between the two ions of the electrolyte and both DMAc and cellulose.

Micellar properties of surface active ionic liquids: A comparison of 1-hexadecyl-3-methylimidazolium chloride with structurally related cationic surfactants

Ionic liquids, ILs, carrying long-chain alkyl groups are surface active, SAIIs. We investigated the micellar properties of the SAIL 1-hexadecyl-3-methylimidazolium chloride, C(16)MeImCl, and compared the data with 1-hexadecylpyridinium chloride, C(16)PYCl, and benzyl (3-hexadecanoylaminoethyl)dimethylammonium chloride, C(15)AEtBzMe(2)Cl. The properties compared include critical micelle concentration, cmc; thermodynamic parameters of micellization; empirical polarity and water concentrations in the interfacial regions. In the temperature range from 15 to 75 degrees C, the order of cmc in H(2)O and in D(2)O is C(16)PYCl > C(16)MeImCl > C(15)AEtBzMe(2)Cl. The enthalpies of micellization, Delta H(mic)(degrees), were calculated indirectly from by use of the van`t Hoff treatment; directly by isothermal titration calorimetry, ITC. Calculation of the degree of counter-ion dissociation, alpha(mic), from conductivity measurements, by use of Evans equation requires knowledge of the aggregation numbers, N(agg), at different temperatures. We have introduced a reliable method for carrying out this calculation, based on the volume and length of the monomer, and the dependence of N(agg) on temperature. The N(agg) calculated for C(16)PyCl and C(16)MeImCl were corroborated by light scattering measurements. Conductivity- and ITC-based Delta H(mic)(degrees) do not agree; reasons for this discrepancy are discussed. Micelle formation is entropy driven: at all studied temperatures for C(16)MeImCl; only up to 65 degrees C for C(16)PyCl; and up to 55 degrees C for C(15)AEtBzMe(2)Cl. All these data can be rationalized by considering hydrogen-bonding between the head-ions of the monomers in the micellar aggregate. The empirical polarities and concentrations of interfacial water were found to be independent of the nature of the head-group. (C) 2010 Elsevier Inc. All rights reserved.

On the interaction of bovine serum albumin with ionic surfactants: Temperature induced EPR changes of a maleimide nitroxide reflect local protein dynamics and probe solvent accessibility

The interaction of bovine serum albumin (BSA) with the ionic surfactants sodium dodecylsulfate (SDS, anionic), cetyltrimethylammonium chloride (CTAC, cationic) and N-hexadecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (HPS, zwitterionic) was studied by electron paramagnetic resonance (EPR) spectroscopy of spin label covalently bound to the single free thiol group of the protein. EPR spectra simulation allows to monitor the protein dynamics at the labeling site and to estimate the changes in standard Gibbs free energy, enthalpy and entropy for transferring the nitroxide side chain from the more motionally restricted to the less restricted component. Whereas SDS and CTAC showed similar increases in the dynamics of the protein backbone for all measured concentrations. HPS presented a smaller effect at concentrations above 1.5 mM. At 10 mM of surfactants and 0.15 mM BSA, the standard Gibbs free energy change was consistent with protein backbone conformations more expanded and exposed to the solvent as compared to the native protein, but with a less pronounced effect for HPS. In the presence of the surfactants, the enthalpy change, related to the energy required to dissociate the nitroxide side chain from the protein, was greater, suggesting a lower water activity. The nitroxide side chain also detected a higher viscosity environment in the vicinity of the paramagnetic probe induced by the addition of the surfactants. The results suggest that the surfactant-BSA interaction, at higher surfactant concentration, is affected by the affinities of the surfactant to its own micelles and micelle-like aggregates. Complementary DLS data suggests that the temperature induced changes monitored by the nitroxide probe reflects local changes in the vicinity of the single thiol group of Cys-34 BSA residue. (C) 2011 Elsevier B.V. All rights reserved.

Deactivation of Ferrylmyoglobin by Vanillin as Affected by Vanillin Binding to beta-Lactoglobulin

Vanillin was found to be efficient as a deactivator of ferrylmyoglobin with a second-order rate constant of k(2) = S7 +/- 1 L mol(-1) s(-1) for reduction to metmyoglobin with Delta H(double dagger) = 58.3 +/- 0.3 kJ mol(-1) and Delta S(double dagger) = -14 +/- 1 J mol(-1) K(-1) in aqueous pH 7.4 solution at 25 degrees C. Binding to beta-lactoglobulin (AG) was found to affect the reactivity of vanillin at 25 degrees C only slightly to k(2) = 48 +/- 2 L mol(-1) s(-1) (Delta H(double dagger) = 68.4 +/- 0.4 kJ mol(-1) and Delta S(double dagger) = 17 +/- 1 J mol(-1) K(-1)) for deactivation of ferrylmyoglobin. Binding of vanillin to beta LG was found to have a binding stoichiometry vanillin/beta LG > 10 with K(A) = 6 x 10(2) L mol(-1) and an apparent total Delta H degrees of approximately -38 kJ mol(-1) and Delta S degrees = -S5.4 +/- 4J mol(-1) K(-1) at 25 degrees C and Delta C(p), (obs) = -1.02 kJ mol(-1) K(-1) indicative of increasing ordering in the complex, as determined by isothermal titration microcalorimetry. From tryptophan fluorescence quenching for beta LG by vanillin, approximately one vanillin was found to bind to each beta LG far stronger with K(A) = 5 x 10(4) L, mol(-1) and a Delta H degrees = 10.2 kJ mol(-1) and Delta S degrees = 55J mol(-1) K(-1) at 25 degrees C. The kinetic entropy/enthalpy compensation effect seen for vanillin reactivity by binding to beta LG is concluded to relate to the weakly bound vanillin oriented through hydrogen bonds on the beta LG surface with the phenolic group pointing toward the solvent, in effect making both Delta H(double dagger) and Delta S(double dagger) more positive. The more strongly bound vanillin capable of tryptophan quenching in the fiLG calyx seems less or nonreactive.

Financial time series analysis : Chaos and neurodynamics approach

This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

Speech Assessment for the Classification of Hypokinetic Dysthria in Parkinson Disease

The aim of this thesis is to investigate computerized voice assessment methods to classify between the normal and Dysarthric speech signals. In this proposed system, computerized assessment methods equipped with signal processing and artificial intelligence techniques have been introduced. The sentences used for the measurement of inter-stress intervals (ISI) were read by each subject. These sentences were computed for comparisons between normal and impaired voice. Band pass filter has been used for the preprocessing of speech samples. Speech segmentation is performed using signal energy and spectral centroid to separate voiced and unvoiced areas in speech signal. Acoustic features are extracted from the LPC model and speech segments from each audio signal to find the anomalies. The speech features which have been assessed for classification are Energy Entropy, Zero crossing rate (ZCR), Spectral-Centroid, Mean Fundamental-Frequency (Meanf0), Jitter (RAP), Jitter (PPQ), and Shimmer (APQ). Naïve Bayes (NB) has been used for speech classification. For speech test-1 and test-2, 72% and 80% accuracies of classification between healthy and impaired speech samples have been achieved respectively using the NB. For speech test-3, 64% correct classification is achieved using the NB. The results direct the possibility of speech impairment classification in PD patients based on the clinical rating scale.

A home environment test battery for status assessment in patients with motor fluctuations

Background and aims Evaluating status in patients with motor fluctuations is complex and occasional observations/measurements do not give an adequate picture as to the time spent in different states. We developed a test battery to assess advanced Parkinson patients' status consisting of diary assessments and motor tests. This battery was constructed and implemented on a handheld computer with built-in mobile communication. In fluctuating patients, it should typically be used several times daily in the home environment, over periods of about one week. The aim of this battery is to provide status information in order to evaluate treatment effects in clinical practice and research, follow up treatments and disease progression and predict outcome to optimize treatment strategy. Methods Selection of diary questions was based on a previous study with Duodopa® (DIREQT). Tapping tests (with and without visual cueing) and a spiral drawing test were added. Rapid prototyping was used in development of the user interface. An evaluation with two pilot patients was performed before and after receiving new treatments for advanced disease (one received Duodopa® and one received DBS). Speed and proportion missed taps were calculated for the tapping tests and entropy of the radial drawing velocity was calculated for the spiral tests. Test variables were evaluated using non-parametric statistics. Results Post-treatment improvement was detected in both patients in many of the test variables. Conclusions Although validation work remains, preliminary results are promising and the test battery is currently being evaluated in a long-term health economics study with Duodopa® (DAPHNE).

Computerized identification of motor complications in Parkinson's disease

Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.