The Associations Between the Maladaptive Personality Dimensions of Neediness and Self-Criticism, Defense Styles, Selfobject Needs, and Attachment Styles in an Iranian Sample

The present study extends previous findings by examining whether defense styles, selfobject needs, attachment styles relate to Neediness and Self-Criticism, as maladaptive personality dimensions focused, respectively, on relatedness and self-definition in an Iranian sample. Three hundred and fifty two participants completed a socio-demographic questionnaire as well as the Persian forms of the Depressive Experiences Questionnaire, Experience of Close Relationships-Revised, Defense Style Questionnaire, Beck Depression Inventory–II and Selfobject Needs Inventory. Two Multiple Linear Regression Analyses, entering Self-criticism and Neediness as criterion variables, were computed. According to the results high Attachment anxiety, high Immature defenses, high depressive symptoms, and high need for idealization were related to self-criticism, and explained 47% of its variance. In addition, high attachment anxiety, low mature defenses, high neurotic defenses, high avoidance of mirroring, and low avoidance of idealization/twinship were related to neediness, and explained 40% of its variance. A Principal Component Analysis was performed, entering all the studied variables. Three factors emerged; one describing a maladaptive form of psychological functioning and two describing more mature modes of psychological functioning. The results are discussed in their implications for the understanding of neediness and self-criticism as maladaptive personality dimensions focused, respectively, on relatedness and self-definition.

The discovery of generalized causal models with mixed variables using MML criterion

One major difficulty frustrating the application of linear causal models is that they are not easily adapted to cope with discrete data. This is unfortunate since most real problems involve both continuous and discrete variables. In this paper, we consider a class of graphical models which allow both continuous and discrete variables, and propose the parameter estimation method and a structure discovery algorithm based on Minimum Message Length and parameter estimation. Experimental results are given to demonstrate the potential for the application of this method.

Is length of experience an appropriate criterion to identify level of expertise?

Clinical experience plays an important role in the development of expertise, particularly when coupled with reflection on practice. There is debate, however, regarding the amount of clinical experience that is required to become an expert. Various lengths of practice have been suggested as suitable for determining expertise, ranging from five years to 15 years. This study aimed to investigate the association between length of experience and therapists’ level of expertise in the field of cerebral palsy with upper limb hypertonicity using an empirical procedure named Cochrane–Weiss–Shanteau (CWS). The methodology involved re-analysis of quantitative data collected in two previous studies. In Study 1, 18 experienced occupational therapists made hypothetical clinical decisions related to 110 case vignettes, while in Study 2, 29 therapists considered 60 case vignettes drawn randomly from those used in Study 1. A CWS index was calculated for each participant's case decisions. Then, in each study, Spearman's rho was calculated to identify the correlations between the duration of experience and level of expertise. There was no significant association between these two variables in both studies. These analyses corroborated previous findings of no association between length of experience and judgemental performance. Therefore, length of experience may not be an appropriate criterion for determining level of expertise in relation to cerebral palsy practice.

Accelerometer data reduction : a comparison of four reduction algorithms on select outcome variables

Purpose Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. Methods The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. Results The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. Conclusions These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies

A strain-based failure criterion for pillar stability analysis

Strain-based failure criteria have several advantages over stress-based failure criteria: they can account for elastic and inelastic strains, they utilise direct, observables effects instead of inferred effects (strain gauges vs. stress estimates), and model complete stress-strain curves including pre-peak, non-linear elasticity and post-peak strain weakening. In this study, a strain-based failure criterion derived from thermodynamic first principles utilising the concepts of continuum damage mechanics is presented. Furthermore, implementation of this failure criterion into a finite-element simulation is demonstrated and applied to the stability of underground mining coal pillars. In numerical studies, pillar strength is usually expressed in terms of critical stresses or stress-based failure criteria where scaling with pillar width and height is common. Previous publications have employed the finite-element method for pillar stability analysis using stress-based failure criterion such as Mohr-Coulomb and Hoek-Brown or stress-based scalar damage models. A novel constitutive material model, which takes into consideration anisotropy as well as elastic strain and damage as state variables has been developed and is presented in this paper. The damage threshold and its evolution are strain-controlled, and coupling of the state variables is achieved through the damage-induced degradation of the elasticity tensor. This material model is implemented into the finite-element software ABAQUS and can be applied to 3D problems. Initial results show that this new material model is capable of describing the non-linear behaviour of geomaterials commonly observed before peak strength is reached as well as post-peak strain softening. Furthermore, it is demonstrated that the model can account for directional dependency of failure behaviour (i.e. anisotropy) and has the potential to be expanded to environmental controls like temperature or moisture.

Stream power criterion and design of sand bed channels at incipient motion

The critical stream power criterion may be used to describe the incipient motion of cohesionless particles of plane sediment beds. The governing equation relating ``critical stream power'' to ``shear Reynolds number'' is developed by using the present experimental data as well as the data from several other sources. Simultaneously, a resistance equation, relating the ``particle Reynolds number'' to the``shear Reynolds number'' is developed for plane sediment beds in wide channels with little or no transport. By making use of these relations, a procedure is developed to design plane sediment beds such that any two of the four design variables, including particle size, energy/friction slope, flow depth, and discharge per unit width in the channel should be known to predict the remaining two variables. Finally, a straightforward design procedure using design tables/design curves and analytical methods is presented to solve six possible design problems.

Quantum homogenization for continuous variables: Realization with linear optical elements

Recently Ziman et al. [Phys. Rev. A 65, 042105 (2002)] have introduced a concept of a universal quantum homogenizer which is a quantum machine that takes as input a given (system) qubit initially in an arbitrary state rho and a set of N reservoir qubits initially prepared in the state xi. The homogenizer realizes, in the limit sense, the transformation such that at the output each qubit is in an arbitrarily small neighborhood of the state xi irrespective of the initial states of the system and the reservoir qubits. In this paper we generalize the concept of quantum homogenization for qudits, that is, for d-dimensional quantum systems. We prove that the partial-swap operation induces a contractive map with the fixed point which is the original state of the reservoir. We propose an optical realization of the quantum homogenization for Gaussian states. We prove that an incoming state of a photon field is homogenized in an array of beam splitters. Using Simon's criterion, we study entanglement between outgoing beams from beam splitters. We derive an inseparability condition for a pair of output beams as a function of the degree of squeezing in input beams.

Modélisation des bi-grappes et sélection des variables pour des données de grande dimension : application aux données d’expression génétique

Les simulations ont été implémentées avec le programme Java.

Geostatistics for constrained variables: positive data, compositions and probabilities. Applications to environmental hazard monitoring

Aquesta tesi estudia com estimar la distribució de les variables regionalitzades l'espai mostral i l'escala de les quals admeten una estructura d'espai Euclidià. Apliquem el principi del treball en coordenades: triem una base ortonormal, fem estadística sobre les coordenades de les dades, i apliquem els output a la base per tal de recuperar un resultat en el mateix espai original. Aplicant-ho a les variables regionalitzades, obtenim una aproximació única consistent, que generalitza les conegudes propietats de les tècniques de kriging a diversos espais mostrals: dades reals, positives o composicionals (vectors de components positives amb suma constant) són tractades com casos particulars. D'aquesta manera, es generalitza la geostadística lineal, i s'ofereix solucions a coneguts problemes de la no-lineal, tot adaptant la mesura i els criteris de representativitat (i.e., mitjanes) a les dades tractades. L'estimador per a dades positives coincideix amb una mitjana geomètrica ponderada, equivalent a l'estimació de la mediana, sense cap dels problemes del clàssic kriging lognormal. El cas composicional ofereix solucions equivalents, però a més permet estimar vectors de probabilitat multinomial. Amb una aproximació bayesiana preliminar, el kriging de composicions esdevé també una alternativa consistent al kriging indicador. Aquesta tècnica s'empra per estimar funcions de probabilitat de variables qualsevol, malgrat que sovint ofereix estimacions negatives, cosa que s'evita amb l'alternativa proposada. La utilitat d'aquest conjunt de tècniques es comprova estudiant la contaminació per amoníac a una estació de control automàtic de la qualitat de l'aigua de la conca de la Tordera, i es conclou que només fent servir les tècniques proposades hom pot detectar en quins instants l'amoni es transforma en amoníac en una concentració superior a la legalment permesa.

Juvenile myoclonic epilepsy: The impact of clinical variables and psychiatric disorders on executive profile assessed with a comprehensive neuropsychological battery

Executive dysfunction is reported in juvenile myoclonic epilepsy (JME). However, batteries employed in previous studies included no more than three tests of executive function. In this study, we aimed to assess executive and attentional functions in JME using a comprehensive battery of eight tests (encompassing fifteen subtests). We also evaluated neuropsychological profiles using a clinical criterion of severity and correlated these findings with epilepsy clinical variables and the presence of psychiatric disorders. We prospectively evaluated 42 patients with JME and a matched control group with Digit Span tests (forward and backward), Stroop Color-Word Test, Trail Making Test, Wisconsin Card-Sorting Test, Matching Familiar Figures Test and Word Fluency Test. We estimated IQ with the Matrix Reasoning and Vocabulary subtests of the Wechsler Abbreviated Intelligence Scale. The patients with JME showed specific deficits in working memory, inhibitory control, concept formation, goal maintenance, mental flexibility, and verbal fluency. We observed attentional deficits in processes such as alertness and attention span and those requiring sustained and divided attention. We found that 83.33% of the patients had moderate or severe executive dysfunction. In addition, attentional and executive impairment was correlated with higher frequency of seizures and the presence of psychiatric disorders. Furthermore, executive dysfunction correlated with a longer duration of epilepsy. Our findings indicate the need for comprehensive neuropsychological batteries in patients with JME, in order to provide a more extensive evaluation of attentional and executive functions and to show that some relevant deficits have been overlooked. (C) 2012 Elsevier Inc. All rights reserved.

An Energy Optimization Criterion for Branching Water Networks

La dependencia energética de las redes hidráulicas para su explotación hace que, a lo largo de los años, sus costos variables lleguen a ensombrecer los costos de construcción o costos fijos. El objetivo de este artículo es la minimización de los costos de explotación en redes ramificadas simples ya existentes y estudia la aplicación de las técnicas de sectorización, junto con el uso de variadores de velocidad, como medida de eficiencia energética. Se sugiere un criterio para determinar bajo qué circunstancias resulta favorable aplicar la sectorización. Se aplica en un caso de estudio real: una red simple ramificada existente con cuatro zonas hidráulicas usada para regadío en la provincia de Segovia, España, resultando en un ahorro energético de un 7.52%, pudiéndose llegar hasta un 26.31%, ampliando la franja horaria del bombeo inicial.

Designs for generalized linear models with several variables and model uncertainty

Standard factorial designs sometimes may be inadequate for experiments that aim to estimate a generalized linear model, for example, for describing a binary response in terms of several variables. A method is proposed for finding exact designs for such experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search. Designs are assessed and compared by simulation of the distribution of efficiencies relative to locally optimal designs over a space of possible models. Exact designs are investigated for two applications, and their advantages over factorial and central composite designs are demonstrated.

The use of treatment process variables to differentiate between completers and dropouts for a guided self -change adolescent substance abuse intervention

This study documented differences between substance using adolescent participants who either completed or dropped out of a brief motivational intervention. Therapeutic alliance, working alliance and patient involvement were used to describe differences in treatment process ratings in a sample of majority Latino males who either (a) completed a adolescent substance abuse intervention called Alcohol Treatment Targeting Adolescents In Need (ATTAIN) or (b) dropped out after the first or second Guided Self-Change therapy session. Fifteen-minute segments were copied from the midpoint of previously recorded audio-tapes of Guided Self-Change therapy sessions. Raters were trained to a criterion level of interrater reliability for both the Working Alliance Inventory-Short and Vanderbilt Psychotherapy Process Scale. Correlations among Working Alliance Inventory- Short and Vanderbilt Psychotherapy Process Scale subscales reflected a general similarity in the assignment of ratings to client-therapist dyads. Findings underscore why these concepts are often used interchangeably in the treatment process literature. The Vanderbilt Psychotherapy Process Scale patient participation subscale demonstrated substantial empirical differentiation from overall therapeutic alliance. Discriminant function analysis demonstrated the Working Alliance Inventory-Short goal subscale and the Vanderbilt Psychotherapy Process Scale patient participation and therapist warmth and friendliness subscales as successful classifiers of groups of mostly Latino youth based on completion status. Follow-up logistic regression analyses confirmed major findings and successfully predicted group membership. Treatment process constructs can be used as clinical tools to identify participants who may be susceptible to dropping out of treatment services. Further investigation of treatment process may enhance understanding of the influence of alliance between clients and Guided Self-Change therapists. Investigating the role of treatment process as a critical component of brief motivational interventions for substance-using adolescents will inform both practitioners and researchers regarding the effectiveness of community-based substance abuse interventions for adolescents.

Applying Least Absolute Shrinkage Selection Operator and Akaike Information Criterion Analysis to Find the Best Multiple Linear Regression Models between Climate Indices and Components of Cow’s Milk

This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLI new), and respiratory rate predictor RRP) with three main components of cow’s milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors with p-value < 0.001 and R2 (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.