Methodological and Empirical Advances in the Quantitative Analysis of Spontaneous Responses in Psychophysiological Time Series

The aim of the present study was to advance the methodology and use of time series analysis to quantify dynamic structures in psychophysiological processes and thereby to produce information on spontaneously coupled physiological responses and their behavioral and experiential correlates. Series of analyses using both simulated and empirical cardiac (IBI), electrodermal (EDA), and facial electromyographic (EMG) data indicated that, despite potential autocorrelated structures, smoothing increased the reliability of detecting response coupling from an interindividual distribution of intraindividual measures and that especially the measures of covariance produced accurate information on the extent of coupled responses. This methodology was applied to analyze spontaneously coupled IBI, EDA, and facial EMG responses and vagal activity in their relation to emotional experience and personality characteristics in a group of middle-aged men (n = 37) during the administration of the Rorschach testing protocol. The results revealed new characteristics in the relationship between phasic end-organ synchronization and vagal activity, on the one hand, and individual differences in emotional adjustment to novel situations on the other. Specifically, it appeared that the vagal system is intimately related to emotional and social responsivity. It was also found that the lack of spontaneously synchronized responses is related to decreased energetic arousal (e.g., depression, mood). These findings indicate that the present process analysis approach has many advantages for use in both experimental and applied research, and that it is a useful new paradigm in psychophysiological research. Keywords: Autonomic Nervous System; Emotion; Facial Electromyography; Individual Differences; Spontaneous Responses; Time Series Analysis; Vagal System

Fast Accurate Transient Stability Simulations

The paper describes a Simultaneous Implicit (SI) approach for transient stability simulations based on an iterative technique using traingularised admittance matrix [1]. The reduced saliency of generator in the subtransient state is taken advantage of to speed up the algorithm. Accordingly, generator differential equations, except rotor swing, contain voltage proportional to fluxes in the main field, dampers and a hypothetical winding representing deep flowing eddy currents, as state variables. The simulation results are validated by comparison with two independent methods viz. Runge-Kutta simulation for a simplified system and a method based on modelling damper windings using conventional induction motor theory.

Ryhmäidentiteetin mittaaminen verkkoroolipelissä World of Warcraft

The objective of the study was to explore the dimensions of group identity in the guilds of World of Warcraft. Previous research shows that social interaction has an important role in playing games for many players. Social identities are an important aspect of self-concept and since group related cues are more salient than personal clues in computer-mediated communication, the social gaming experience was approached through group identity. In the study a new scale will be developed to measure the group identity in games. Secondary goal is to study how different guild attributes affect the group identity and third goal is to explore the connection between group identity and gaming experience and amount of play. Subjects were 1203 guild members and 106 players not in a guild. The data was gathered by an Internet survey which measured group identity with nine scales, gaming experience with three scales and guild attributes with four scales. Also various background data was gathered. The construct of group identity was analyzed with explorative factor analysis. The typical experiences of group identity was analyzed with cluster analysis and effects of guild attributes with multivariate analysis of covariance. As a result of the study a new scale was developed which measured group identity on six dimensions: self-stereotyping, public and private evaluation, importance, interconnection of self and others and awareness of content. Group identity was experienced strongest in elder middle-sized guilds that had formal rules and that emphasized social interaction. The players with strong group identity had more positive gaming experience and played World of Warcraft more per week than the players who were not in a guild or identified to guild weakly. This result encourages game developers to produce environments that enhance group identity as it seems to increase the enjoyment in games. As a whole this study proposes that group identity in guilds is constructed from the same elements as in traditional groups. If this is truly the case, guild membership may have similar positive effects on individual’s mental well-being as traditional positively evaluated group memberships have.

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

Genetic analysis for a shared biological basis between migraine and coronary artery disease

Objective: To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD). Methods: Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci. Results: We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP). Conclusions: The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders.

Shared genetic basis for migraine and ischemic stroke: A genome-wide analysis of common variants

OBJECTIVE To quantify genetic overlap between migraine and ischemic stroke (IS) with respect to common genetic variation. METHODS We applied 4 different approaches to large-scale meta-analyses of genome-wide data on migraine (23,285 cases and 95,425 controls) and IS (12,389 cases and 62,004 controls). First, we queried known genome-wide significant loci for both disorders, looking for potential overlap of signals. We then analyzed the overall shared genetic load using polygenic scores and estimated the genetic correlation between disease subtypes using data derived from these models. We further interrogated genomic regions of shared risk using analysis of covariance patterns between the 2 phenotypes using cross-phenotype spatial mapping. RESULTS We found substantial genetic overlap between migraine and IS using all 4 approaches. Migraine without aura (MO) showed much stronger overlap with IS and its subtypes than migraine with aura (MA). The strongest overlap existed between MO and large artery stroke (LAS; p = 6.4 x 10(-28) for the LAS polygenic score in MO) and between MO and cardioembolic stroke (CE; p = 2.7 x 10(-20) for the CE score in MO). CONCLUSIONS Our findings indicate shared genetic susceptibility to migraine and IS, with a particularly strong overlap between MO and both LAS and CE pointing towards shared mechanisms. Our observations on MA are consistent with a limited role of common genetic variants in this subtype.

Efficient implementations of a pseudodynamical stochastic filtering strategy for static elastography

A computationally efficient pseudodynamical filtering setup is established for elasticity imaging (i.e., reconstruction of shear modulus distribution) in soft-tissue organs given statically recorded and partially measured displacement data. Unlike a regularized quasi-Newton method (QNM) that needs inversion of ill-conditioned matrices, the authors explore pseudodynamic extended and ensemble Kalman filters (PD-EKF and PD-EnKF) that use a parsimonious representation of states and bypass explicit regularization by recursion over pseudotime. Numerical experiments with QNM and the two filters suggest that the PD-EnKF is the most robust performer as it exhibits no sensitivity to process noise covariance and yields good reconstruction even with small ensemble sizes.

The shared genetics of migraine and anxious depression

OBJECTIVES To investigate: - (1) whether shared genetic factors influence migraine and anxious depression; - (2) whether the genetic architecture of migraine depends on anxious depression; - (3) whether the association between migraine and anxious depression is causal. BACKGROUND Migraine and anxious depression frequently occur together, but little is known about the mechanisms causing this association. METHODS A twin study was conducted to model the genetic architecture of migraine and anxious depression and the covariance between them. Anxious depression was also added to the model as a moderator variable to examine whether anxious depression affects the genetic architecture of migraine. Causal models were explored with the co-twin control method. RESULTS Modest but significant phenotypic (rP=0.28), genetic (rG=0.30), and nonshared environmental (rE=0.26) correlations were found between the 2 traits. Interestingly, the heritability of migraine depended on the level of anxious depression: the higher the anxious depression score, the lower the relative contribution of genetic factors to the individual differences in migraine susceptibility. The observed risk patterns in discordant twins are most consistent with a bidirectional causal relationship. CONCLUSIONS These findings confirm the genetic association between migraine and anxious depression and are consistent with a syndromic association between the 2 traits. This highlights the importance of taking comorbidity into account in genetic studies of migraine, especially in the context of selection for large-scale genotyping efforts. Genetic studies may be most effective when migraine with and without comorbid anxious depression are treated as separate phenotypes.

Environmental and fishing effects on the dynamics of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia)

This analysis of the variations of brown tiger prawn (Penaeus esculentus) catch in Moreton Bay multispecies trawl fishery estimated catchability using a delay difference model. It integrated several factors responsible for variations in catchability: targeting of fishing effort, increasing fishing power and changing availability. An analysis of covariance was used to define fishing events targeted at brown tiger prawns. A general linear model estimated inter-annual variations of fishing power. Temperature-induced changes in prawn behaviour played an important role on the dynamics of this fishery. Maximum likelihood estimates of targeted catchability (4.09 ± 0.42 × 10−4 boat-day−1) were twice as large as non-targeted catchability (1.86 ± 0.25 × 10−4 boat-day−1). The causes of recent declines in fishing effort in this fishery were discussed.

Noncommutative Gravitation as a Gauge Theory of Twisted Poincaré Symmetry

Gravitaation kvanttiteorian muotoilu on ollut teoreettisten fyysikkojen tavoitteena kvanttimekaniikan synnystä lähtien. Kvanttimekaniikan soveltaminen korkean energian ilmiöihin yleisen suhteellisuusteorian viitekehyksessä johtaa aika-avaruuden koordinaattien operatiiviseen ei-kommutoivuuteen. Ei-kommutoivia aika-avaruuden geometrioita tavataan myös avointen säikeiden säieteorioiden tietyillä matalan energian rajoilla. Ei-kommutoivan aika-avaruuden gravitaatioteoria voisi olla yhteensopiva kvanttimekaniikan kanssa ja se voisi mahdollistaa erittäin lyhyiden etäisyyksien ja korkeiden energioiden prosessien ei-lokaaliksi uskotun fysiikan kuvauksen, sekä tuottaa yleisen suhteellisuusteorian kanssa yhtenevän teorian pitkillä etäisyyksillä. Tässä työssä tarkastelen gravitaatiota Poincarén symmetrian mittakenttäteoriana ja pyrin yleistämään tämän näkemyksen ei-kommutoiviin aika-avaruuksiin. Ensin esittelen Poincarén symmetrian keskeisen roolin relativistisessa fysiikassa ja sen kuinka klassinen gravitaatioteoria johdetaan Poincarén symmetrian mittakenttäteoriana kommutoivassa aika-avaruudessa. Jatkan esittelemällä ei-kommutoivan aika-avaruuden ja kvanttikenttäteorian muotoilun ei-kommutoivassa aika-avaruudessa. Mittasymmetrioiden lokaalin luonteen vuoksi tarkastelen huolellisesti mittakenttäteorioiden muotoilua ei-kommutoivassa aika-avaruudessa. Erityistä huomiota kiinnitetään näiden teorioiden vääristyneeseen Poincarén symmetriaan, joka on ei-kommutoivan aika-avaruuden omaama uudentyyppinen kvanttisymmetria. Seuraavaksi tarkastelen ei-kommutoivan gravitaatioteorian muotoilun ongelmia ja niihin kirjallisuudessa esitettyjä ratkaisuehdotuksia. Selitän kuinka kaikissa tähänastisissa lähestymistavoissa epäonnistutaan muotoilla kovarianssi yleisten koordinaattimunnosten suhteen, joka on yleisen suhteellisuusteorian kulmakivi. Lopuksi tutkin mahdollisuutta yleistää vääristynyt Poincarén symmetria lokaaliksi mittasymmetriaksi --- gravitaation ei-kommutoivan mittakenttäteorian saavuttamisen toivossa. Osoitan, että tällaista yleistystä ei voida saavuttaa vääristämällä Poincarén symmetriaa kovariantilla twist-elementillä. Näin ollen ei-kommutoivan gravitaation ja vääristyneen Poincarén symmetrian tutkimuksessa tulee jatkossa keskittyä muihin lähestymistapoihin.

Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering

The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.

A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweight: Application to robust clustering

We propose a family of multivariate heavy-tailed distributions that allow variable marginal amounts of tailweight. The originality comes from introducing multidimensional instead of univariate scale variables for the mixture of scaled Gaussian family of distributions. In contrast to most existing approaches, the derived distributions can account for a variety of shapes and have a simple tractable form with a closed-form probability density function whatever the dimension. We examine a number of properties of these distributions and illustrate them in the particular case of Pearson type VII and t tails. For these latter cases, we provide maximum likelihood estimation of the parameters and illustrate their modelling flexibility on simulated and real data clustering examples.

MACHAL [Mitnadvei Hutz LaAretz] and Aliyah Bet Records, undated, 1930-2011

The MACHAL, the acronym for “Mitnadvei Hutz LaAretz” ("Volunteers from Abroad"), consisted of about 3500 men and women from over 40 countries from a variety of social and religious backgrounds who volunteered to fight for the establishment of Israel. This collection is unique in that it deals specifically with the experience of MACHAL and Aliyah Bet volunteers from Canada and the United States and others living in the United States. The collections consists of files on 500 volunteers, over 2000 original and reproduction photographs, numerous audio-visual material, books, manuscripts, and memoirs.

Laminar and turbulent natural convection in rectangular cavities

A computer program has been developed for the prediction of buoyancy-driven laminar and turbulent flow in rectangular air-filled two-dimensional cavities with differentially heated side walls. Laminar flow predictions for a square cavity and Rayleigh numbers from Ra = 10^3 up to the onset of unsteady flow have been obtained. Accurate solutions for Ra = 5 x 10^6, 10^7, 5 x 10^7 and 10^8 are presented and an estimate for the critical Rayleigh number at which the steady laminar flow becomes unsteady is given for this geometry. Numerical predictions of turbulent flow have been obtained for RaH~0(10^9 -10^11 ) and compared with existing experimental data. A previously developed second moment closure model (Behnia et al. 1987) has been used to model the turbulence. Results indicate that a second moment closure model is capable of predicting the observed flow features.

Laminar and turbulent natural convection in rectangular cavities

"This chapter discusses laminar and turbulent natural convection in rectangular cavities. Natural convection in rectangular two-dimensional cavities has become a standard problem in numerical heat transfer because of its relevance in understanding a number of problems in engineering. Current research identified a number of difficulties with regard to the numerical methods and the turbulence modeling for this class of flows. Obtaining numerical predictions at high Rayleigh numbers proved computationally expensive such that results beyond Ra ∼ 1014 are rarely reported. The chapter discusses a study in which it was found that turbulent computations in square cavities can't be extended beyond Ra ∼ O (1012) despite having developed a code that proved very efficient for the high Ra laminar regime. As the Rayleigh number increased, thin boundary layers began to form next to the vertical walls, and the central region became progressively more stagnant and highly stratified. Results obtained for the high Ra laminar regime were in good agreement with existing studies. Turbulence computations, although of a preliminary nature, indicated that a second moment closure model was capable of predicting the experimentally observed flow features."--Publisher Summary