One minute of grief: Emotional processing in short-term dynamic psychotherapy for adjustment disorder.

OBJECTIVE: Depth of emotional processing has shown to be related to outcome across approaches to psychotherapy. Moreover, a specific emotional sequence has been postulated and tested in several studies on experiential psychotherapy (Pascual-Leone & Greenberg, 2007). This process-outcome study aims at reproducing the sequential model of emotional processing in psychodynamic psychotherapy for adjustment disorder and linking these variables with ultimate therapeutic outcome. METHOD: In this study, 32 patients underwent short-term dynamic psychotherapy. On the basis of reliable clinical change statistics, a subgroup (n = 16) presented with good outcome and another subgroup (n = 16) had a poor outcome in the end of treatment. The strongest alliance session of each case was rated using the observer-rated system Classification of Affective Meaning States. Reliability coefficients for the measure were excellent (κ = .82). RESULTS: Using 1 min as the fine-grained unit of analysis, results showed that the experience of fundamentally adaptive grief was more common in the in-session process of patients with good outcome, compared with those with poor outcomes (χ2 = 6.56, p = .01, d = 1.23). This variable alone predicted 19% of the change in depressive symptoms as measured by the Beck Depression Inventory at the end of treatment. Moreover, sequences of the original model were supported and related to outcome. CONCLUSIONS: These results are discussed within the framework of the sequential model of emotional processing and its possible relevance for psychodynamic psychotherapy. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Dynamic properties of human brain structure: learning-related changes in cortical areas and associated fiber connections.

Recent findings in neuroscience suggest that adult brain structure changes in response to environmental alterations and skill learning. Whereas much is known about structural changes after intensive practice for several months, little is known about the effects of single practice sessions on macroscopic brain structure and about progressive (dynamic) morphological alterations relative to improved task proficiency during learning for several weeks. Using T1-weighted and diffusion tensor imaging in humans, we demonstrate significant gray matter volume increases in frontal and parietal brain areas following only two sessions of practice in a complex whole-body balancing task. Gray matter volume increase in the prefrontal cortex correlated positively with subject's performance improvements during a 6 week learning period. Furthermore, we found that microstructural changes of fractional anisotropy in corresponding white matter regions followed the same temporal dynamic in relation to task performance. The results make clear how marginal alterations in our ever changing environment affect adult brain structure and elucidate the interrelated reorganization in cortical areas and associated fiber connections in correlation with improvements in task performance.

Combination of MRI and dynamic FET PET for initial glioma grading.

AIM: MRI and PET with 18F-fluoro-ethyl-tyrosine (FET) have been increasingly used to evaluate patients with gliomas. Our purpose was to assess the additive value of MR spectroscopy (MRS), diffusion imaging and dynamic FET-PET for glioma grading. PATIENTS, METHODS: 38 patients (42 ± 15 aged, F/M: 0.46) with untreated histologically proven brain gliomas were included. All underwent conventional MRI, MRS, diffusion sequences, and FET-PET within 3±4 weeks. Performances of tumour FET time-activity-curve, early-to-middle SUVmax ratio, choline / creatine ratio and ADC histogram distribution pattern for gliomas grading were assessed, as compared to histology. Combination of these parameters and respective odds were also evaluated. RESULTS: Tumour time-activity-curve reached the best accuracy (67%) when taken alone to distinguish between low and high-grade gliomas, followed by ADC histogram analysis (65%). Combination of time-activity-curve and ADC histogram analysis improved the sensitivity from 67% to 86% and the specificity from 63-67% to 100% (p < 0.008). On multivariate logistic regression analysis, negative slope of the tumour FET time-activity-curve however remains the best predictor of high-grade glioma (odds 7.6, SE 6.8, p = 0.022). CONCLUSION: Combination of dynamic FET-PET and diffusion MRI reached good performance for gliomas grading. The use of FET-PET/MR may be highly relevant in the initial assessment of primary brain tumours.

A dynamic model for stem cell homeostasis and patterning in Arabidopsis meristems.

Plants maintain stem cells in their meristems as a source for new undifferentiated cells throughout their life. Meristems are small groups of cells that provide the microenvironment that allows stem cells to prosper. Homeostasis of a stem cell domain within a growing meristem is achieved by signalling between stem cells and surrounding cells. We have here simulated the origin and maintenance of a defined stem cell domain at the tip of Arabidopsis shoot meristems, based on the assumption that meristems are self-organizing systems. The model comprises two coupled feedback regulated genetic systems that control stem cell behaviour. Using a minimal set of spatial parameters, the mathematical model allows to predict the generation, shape and size of the stem cell domain, and the underlying organizing centre. We use the model to explore the parameter space that allows stem cell maintenance, and to simulate the consequences of mutations, gene misexpression and cell ablations.

Faktorenanalytische Untersuchung und Rehabilitätsbestimmung der statischen und dynamischen Pupillometrie bei Normalpersonen und psychopathologischen Gruppen [Factor analytic study and determination of rehabilitation of static and dynamic pupillometry in normal persons and psychopathologic groups]

Variables measured during static and dynamic pupillometry were factor-analyzed. Following factors were obtained regardless whether investigations were carried out in normals or in psychiatric patients: A static factor, a dynamic factor, a stimulus-specific factor and a restitution-dependent factor. Evaluation of reliability in normals demonstrated a high reliability for the static variables of pupillometry.

The dynamic adjustment of local government budgets : Does Spain behave differently?

[spa] El objetivo de este trabajo es analizar si los municipios españoles se ajustan en presencia de un shock presupuestario y (si es así) qué elementos del presupuesto son los que realizan el ajuste. La metodología utilizada para contestar estas preguntas es un mecanismo de corrección del error, VECM, que estimamos con un panel de datos de los municipios españoles durante el período 1988-2006. Nuestros resultados confirman que, en primer lugar, los municipios se ajustan en presencia de un shock fiscal (es decir, el déficit es estacionario en el largo plazo). En segundo lugar, obtenemos que cuando el shock afecta a los ingresos el ajuste lo soporta principalmente el municipio reduciendo el gasto, las transferencias tienen un papel muy reducido en este proceso de ajuste. Por el contrario, cuando el shock afecta al gasto, el ajuste es compartido en términos similares entre el municipio – incrementado los impuestos – y los gobiernos de niveles superiores – incrementando las transferencias. Estos resultados sugieren que la viabilidad de las finanzas pública locales es factible con diferentes entornos institucionales.

Yield of intermittent versus continuous EEG in comatose survivors of cardiac arrest treated with hypothermia.

INTRODUCTION: Electroencephalography (EEG) has a central role in the outcome prognostication in subjects with anoxic/hypoxic encephalopathy following a cardiac arrest (CA). Continuous EEG monitoring (cEEG) has been consistently developed and studied; however, its yield as compared to repeated standard EEG (sEEG) is unknown. METHODS: We studied a prospective cohort of comatose adults treated with therapeutic hypothermia (TH) after a CA. cEEG data regarding background activity and epileptiform components were compared to two 20 minute sEEG extracted from the cEEG recording (one during TH, and one in early normothermia). RESULTS: In this cohort, 34 recordings were studied. During TH, the agreement between cEEG and sEEG was 97.1% (95% CI: 84.6 - 99.9%) for background discontinuity and reactivity evaluation, while it was 94.1% (95% CI 80.3 - 99.2%) regarding epileptiform activity. In early normothermia, we did not find any discrepancies. Thus, concordance was very good during TH (kappa 0.83), and optimal during normothermia (kappa=1). The median delay between CA and the first EEG reactivity testing was 18 hours (range: 4.75 - 25) for patients with perfect agreement and 10 hours (range: 5.75 - 10.5) for the three patients in whom there were discordant findings (P=0.02, Wilcoxon). CONCLUSION: Standard intermittent EEG has comparable performance than continuous EEG both for variables important for outcome prognostication (EEG reactivity) and identification of epileptiform transients in this relatively small sample of comatose survivors of CA. This finding has an important practical implication, especially for centers where EEG resources are limited.

Dynamic compact thermal models with multiple power sources: application to an ultrathin chip stacking technology

Whereas numerical modeling using finite-element methods (FEM) can provide transient temperature distribution in the component with enough accuracy, it is of the most importance the development of compact dynamic thermal models that can be used for electrothermal simulation. While in most cases single power sources are considered, here we focus on the simultaneous presence of multiple sources. The thermal model will be in the form of a thermal impedance matrix containing the thermal impedance transfer functions between two arbitrary ports. Eachindividual transfer function element ( ) is obtained from the analysis of the thermal temperature transient at node ¿ ¿ after a power step at node ¿ .¿ Different options for multiexponential transient analysis are detailed and compared. Among the options explored, small thermal models can be obtained by constrained nonlinear least squares (NLSQ) methods if the order is selected properly using validation signals. The methods are applied to the extraction of dynamic compact thermal models for a new ultrathin chip stack technology (UTCS).

Continuous phase shift of sinusoidal signals using injection locked oscillators

This work presents an alternative to generate continuous phase shift of sinusoidal signals based on the use of super harmonic injection locked oscillators (ILO). The proposed circuit is a second harmonic ILO with varactor diodes as tuning elements. In the locking state, by changing the varactor bias, a phase shift instead of a frequency shift is observed at the oscillator output. By combining two of these circuits, relative phases up to 90 could be achieved. Two prototypes of the circuit have been implemented and tested, a hybrid version working in the range of 200-300 MHz and a multichip module (MCM) version covering the 900¿1000 MHz band.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Non-constant discounting in finite horizon: The free terminal time case

This paper derives the HJB (Hamilton-Jacobi-Bellman) equation for sophisticated agents in a finite horizon dynamic optimization problem with non-constant discounting in a continuous setting, by using a dynamic programming approach. A simple example is used in order to illustrate the applicability of this HJB equation, by suggesting a method for constructing the subgame perfect equilibrium solution to the problem.Conditions for the observational equivalence with an associated problem with constantdiscounting are analyzed. Special attention is paid to the case of free terminal time. Strotz¿s model (an eating cake problem of a nonrenewable resource with non-constant discounting) is revisited.