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.

Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease

OBJECTIVES: To develop a method for objective assessment of fine motor timing variability in Parkinson’s disease (PD) patients, using digital spiral data gathered by a touch screen device. BACKGROUND: A retrospective analysis was conducted on data from 105 subjects including65 patients with advanced PD (group A), 15 intermediate patients experiencing motor fluctuations (group I), 15 early stage patients (group S), and 10 healthy elderly subjects (HE) were examined. The subjects were asked to perform repeated upper limb motor tasks by tracing a pre-drawn Archimedes spiral as shown on the screen of the device. The spiral tracing test was performed using an ergonomic pen stylus, using dominant hand. The test was repeated three times per test occasion and the subjects were instructed to complete it within 10 seconds. Digital spiral data including stylus position (x-ycoordinates) and timestamps (milliseconds) were collected and used in subsequent analysis. The total number of observations with the test battery were as follows: Swedish group (n=10079), Italian I group (n=822), Italian S group (n = 811), and HE (n=299). METHODS: The raw spiral data were processed with three data processing methods. To quantify motor timing variability during spiral drawing tasks Approximate Entropy (APEN) method was applied on digitized spiral data. APEN is designed to capture the amount of irregularity or complexity in time series. APEN requires determination of two parameters, namely, the window size and similarity measure. In our work and after experimentation, window size was set to 4 and similarity measure to 0.2 (20% of the standard deviation of the time series). The final score obtained by APEN was normalized by total drawing completion time and used in subsequent analysis. The score generated by this method is hence on denoted APEN. In addition, two more methods were applied on digital spiral data and their scores were used in subsequent analysis. The first method was based on Digital Wavelet Transform and Principal Component Analysis and generated a score representing spiral drawing impairment. The score generated by this method is hence on denoted WAV. The second method was based on standard deviation of frequency filtered drawing velocity. The score generated by this method is hence on denoted SDDV. Linear mixed-effects (LME) models were used to evaluate mean differences of the spiral scores of the three methods across the four subject groups. Test-retest reliability of the three scores was assessed after taking mean of the three possible correlations (Spearman’s rank coefficients) between the three test trials. Internal consistency of the methods was assessed by calculating correlations between their scores. RESULTS: When comparing mean spiral scores between the four subject groups, the APEN scores were different between HE subjects and three patient groups (P=0.626 for S group with 9.9% mean value difference, P=0.089 for I group with 30.2%, and P=0.0019 for A group with 44.1%). However, there were no significant differences in mean scores of the other two methods, except for the WAV between the HE and A groups (P<0.001). WAV and SDDV were highly and significantly correlated to each other with a coefficient of 0.69. However, APEN was not correlated to neither WAV nor SDDV with coefficients of 0.11 and 0.12, respectively. Test-retest reliability coefficients of the three scores were as follows: APEN (0.9), WAV(0.83) and SD-DV (0.55). CONCLUSIONS: The results show that the digital spiral analysis-based objective APEN measure is able to significantly differentiate the healthy subjects from patients at advanced level. In contrast to the other two methods (WAV and SDDV) that are designed to quantify dyskinesias (over-medications), this method can be useful for characterizing Off symptoms in PD. The APEN was not correlated to none of the other two methods indicating that it measures a different construct of upper limb motor function in PD patients than WAV and SDDV. The APEN also had a better test-retest reliability indicating that it is more stable and consistent over time than WAV and SDDV.

A scenario-driven decision support system for serious crime investigation

Consideration of a wide range of plausible crime scenarios during any crime investigation is important to seek convincing evidence and hence to minimize the likelihood of miscarriages of justice. It is equally important for crime investigators to be able to employ effective and efficient evidence-collection strategies that are likely to produce the most conclusive information under limited available resources. An intelligent decision support system that can assist human investigators by automatically constructing plausible scenarios, and reasoning with the likely best investigating actions will clearly be very helpful in addressing these challenging problems. This paper presents a system for creating scenario spaces from given evidence, based on an integrated application of techniques for compositional modelling and Bayesian network-based evidence evaluation. Methods of analysis are also provided by the use of entropy to exploit the synthesized scenario spaces in order to prioritize investigating actions and hypotheses. These theoretical developments are illustrated by realistic examples of serious crime investigation.