Stimulus competition in affective and relational learning

Evaluative learning theory states that affective learning, the acquisition of likes and dislikes, is qualitatively different from relational learning, the learning of predictive relationships among stimuli. Three experiments tested the prediction derived from evaluative learning theory that relational learning, but not affective learning, is affected by stimulus competition by comparing performance during two conditional stimuli, one trained in a superconditioning procedure and the other in a blocking procedure. Ratings of unconditional stimulus expectancy and electrodermal responses indicated stimulus competition in relational learning. Evidence for stimulus competition in affective learning was provided by verbal ratings of conditional stimulus pleasantness and by measures of blink startle modulation. Taken together, the present experiments demonstrate stimulus competition in relational and affective learning, a result inconsistent with evaluative learning theory. (C) 2001 Academic Press.

Effect of periparturient diseases accompanied by excessive vulval discharge and weaning to mating interval on sow reproductive performance

Objective To evaluate the effect of periparturient disease accompanied by vulval discharge, and weaning-to-mating intervals, on sow fertility and litter size. Design Reproductive data were collected and analysed from 19 Hungarian swine herds over a 4 year period. Conception rates, farrowing rates and litter sizes of sows with periparturient disease accompanied by vulval discharge were used to evaluate the relationship between duration of vulval discharge and subsequent fertility and litter size. The possibility of interactions between weaning-to-mating intervals and duration of vulval discharges was investigated to determine if there was any effect on subsequent fertility and litter size. Results and conclusions Both parity 1 and parity 2 to 8 sows having had periparturient disease accompanied by vulval discharge in excess of 6 days duration had significantly (P < 0.001) lower subsequent fertility (conception, farrowing and adjusted farrowing rates) compared with sows of similar parity where the duration of vulval discharge was < 4 or 4 to 6 days. There was no difference in fertility rates between sows, in both parity categories, with vulval discharge for < 4 days compared with 4 to 6 days. A duration of vulval discharge in excess of 6 days in parity 1 sows significantly reduced litter size (total born and live-born) in subsequent farrowings, but not in parity 2 to 8 sows. There was no interaction between the duration of vulval discharge and post-weaning to mating intervals. However sows with weaning to mating intervals between 7 and 10 days had smaller (P < 0.001) subsequent litter sizes compared with 3 to 6 or 11 to 14 day intervals. It was concluded that the duration of vulval discharge in excess of 6 days was an indication of a severe persistent endometritis adversely affecting fertility of sows.

Modeling and forecasting value-at-risk for the Portuguese stock market

The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Repeated assessment and practice effects of the written symbol digit modalities test using a short inter-test interval

The Symbol Digit Modalities Test (SDMT) is a widely used instrument to assess information processing speed, attention, visual scanning, and tracking. Considering that repeated evaluations are a common need in neuropsychological assessment routines, we explored test–retest reliability and practice effects of two alternate SDMT forms with a short inter-assessment interval. A total of 123 university students completed the written SDMT version in two different time points separated by a 150-min interval. Half of the participants accomplished the same form in both occasions, while the other half filled different forms. Overall, reasonable test–retest reliabilities were found (r = .70), and the subjects that completed the same form revealed significant practice effects (p < .001, dz = 1.61), which were almost non-existent in those filling different forms. These forms were found to be moderately reliable and to elicit a similar performance across participants, suggesting their utility in repeated cognitive assessments when brief inter-assessment intervals are required.

Arrhythmogenic cardiomyopathy of the right ventricle. Predictive value of QT interval dispersion to assess arrhythmogenic risk and sudden death

OBJECTIVE: To determine in arrhythmogenic right ventricular cardiomyopathy the value of QT interval dispersion for identifying the induction of sustained ventricular tachycardia in the electrophysiological study or the risk of sudden cardiac death. METHODS: We assessed QT interval dispersion in the 12-lead electrocardiogram of 26 patients with arrhythmogenic right ventricular cardiomyopathy. We analyzed its association with sustained ventricular tachycardia and sudden cardiac death, and in 16 controls similar in age and sex. RESULTS: (mean ± SD). QT interval dispersion: patients = 53.8±14.1ms; control group = 35.0±10.6ms, p=0.001. Patients with induction of ventricular tachycardia: 52.5±13.8ms; without induction of ventricular tachycardia: 57.5±12.8ms, p=0.420. In a mean follow-up period of 41±11 months, five sudden cardiac deaths occurred. QT interval dispersion in this group was 62.0±17.8, and in the others it was 51.9±12.8ms, p=0.852. Using a cutoff > or = 60ms to define an increase in the degree of the QT interval dispersion, we were able to identify patients at risk of sudden cardiac death with a sensitivity of 60%, a specificity of 57%, and positive and negative predictive values of 25% and 85%, respectively. CONCLUSION: Patients with arrhythmogenic right ventricular cardiomyopathy have a significant increase in the degree of QT interval dispersion when compared with the healthy population. However it, did not identify patients with induction of ventricular tachycardia in the electrophysiological study, showing a very low predictive value for defining the risk of sudden cardiac death in the population studied.

The Analysis of interval censoring and double censoring via Markov chain Monte Carlo methods

L'Anàlisi de la supervivència s'utilitza en diferents camps per analitzar el temps transcorregut entre dos esdeveniments. El que distingeix l'anàlisi de la supervivència d'altres àrees de l'estadística és que les dades normalment estan censurades. La censura en un interval apareix quan l'esdeveniment final d'interès no és directament observable i només se sap que el temps de fallada està en un interval concret. Un esquema de censura més complex encara apareix quan tant el temps inicial com el temps final estan censurats en un interval. Aquesta situació s'anomena doble censura. En aquest article donem una descripció formal d'un mètode bayesà paramètric per a l'anàlisi de dades censurades en un interval i dades doblement censurades així com unes indicacions clares de la seva utilització o pràctica. La metodologia proposada s'ilustra amb dades d'una cohort de pacients hemofílics que es varen infectar amb el virus VIH a principis dels anys 1980's.

A proposal for a new specification for a conditionally heteroskedastic variance model: the Quadratic Moving-Average Conditional Heteroskedasticity and an application to the D. Mark-U.S. dollar Exchange Rate

Ever since the appearance of the ARCH model [Engle(1982a)], an impressive array of variance specifications belonging to the same class of models has emerged [i.e. Bollerslev's (1986) GARCH; Nelson's (1990) EGARCH]. This recent domain has achieved very successful developments. Nevertheless, several empirical studies seem to show that the performance of such models is not always appropriate [Boulier(1992)]. In this paper we propose a new specification: the Quadratic Moving Average Conditional heteroskedasticity model. Its statistical properties, such as the kurtosis and the symmetry, as well as two estimators (Method of Moments and Maximum Likelihood) are studied. Two statistical tests are presented, the first one tests for homoskedasticity and the second one, discriminates between ARCH and QMACH specification. A Monte Carlo study is presented in order to illustrate some of the theoretical results. An empirical study is undertaken for the DM-US exchange rate.

Notch1 and T-cell development: insights from conditional knockout mice.

Notch proteins influence cell-fate decisions in many developmental systems. Gain-of-function studies have suggested a crucial role for Notch1 signaling at several stages during lymphocyte development, including the B/T, alphabeta/gammadelta and CD4/CD8 lineage choices. Here, we critically re-evaluate these conclusions in the light of recent studies that describe inducible and tissue-specific targeting of the Notch1 gene.

Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations

This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

Prevalence and determinants of QT interval prolongation in medical inpatients.

BACKGROUND: QT interval prolongation carries an increased risk of torsade de pointes and death. AIM: We sought to determine the prevalence of QT prolongation in medical inpatients and to identify determinants of this condition. METHODS: We enrolled consecutive patients who were admitted to the internal medicine ward and who had an electrocardiogram performed within 24 h of admission. We collected information on baseline patient characteristics and the use of QT-prolonging drugs. Two blinded readers manually measured the QT intervals. QT intervals were corrected for heart rate using the traditional Bazett formula and the linear regression-based Framingham formula. We used logistic regression to identify patient characteristics and drugs that were independently associated with QTc prolongation. RESULTS: Of 537 inpatients, 22.3% had a prolonged QTc based on the Bazett formula. The adjusted odds for QTc prolongation based on the Bazett correction were significantly higher in patients who had liver disease (OR 2.9, 95% CI: 1.5-5.6), hypokalaemia (OR 3.3, 95% CI: 1.9-5.6) and who were taking ≥1 QT-prolonging drug at admission (OR 1.7, 95% CI: 1.1-2.6). Overall, 50.8% of patients with QTc prolongation received additional QT-prolonging drugs during hospitalisation. CONCLUSIONS: The prevalence of QTc prolongation was high among medical inpatients but depended on the method used to correct for heart rate. The use of QT-prolonging drugs, hypokalaemia and liver disease increased the risk of QTc prolongation. Many patients with QTc prolongation received additional QT-prolonging drugs during hospitalisation, further increasing the risk of torsade de pointes and death.

Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.