Seizure semiology: an overview of the 'inverse problem'.

In clinical practice, a classification of seizures based on clinical signs and symptoms leads to an improved understanding of epilepsy-related issues and therefore strongly contributes to a better patient care. The inverse problem involves inferring the anatomical brain localization of a seizure from the scalp surface EEG, a concept we apply here to correlate seizure origin with seizure semiology. The spheres of sensorium, motor features, consciousness changes and autonomic alterations during ictal and postictal manifestations are reviewed, including several subdivisions used to better categorize particular features. Particular attention is given to behavioral features, as well as to features occurring in idiopathic generalized epileptic syndromes and psychogenic nonepileptic spells.

Magnetic superelasticity and inverse magnetocaloric effect in Ni-Mn-In

Applying a magnetic field to a ferromagnetic Ni50Mn34In16 alloy in the martensitic state induces a structural phase transition to the austenitic state. This is accompanied by a strain which recovers on removing the magnetic field, giving the system a magnetically superelastic character. A further property of this alloy is that it also shows the inverse magnetocaloric effect. The magnetic superelasticity and the inverse magnetocaloric effect in Ni-Mn-In and their association with the first-order structural transition are studied by magnetization, strain, and neutron-diffraction studies under magnetic field.

Determination of hydraulic properties of a tropical soil of Hawaii using column experiments and inverse modeling

A method for determining soil hydraulic properties of a weathered tropical soil (Oxisol) using a medium-sized column with undisturbed soil is presented. The method was used to determine fitting parameters of the water retention curve and hydraulic conductivity functions of a soil column in support of a pesticide leaching study. The soil column was extracted from a continuously-used research plot in Central Oahu (Hawaii, USA) and its internal structure was examined by computed tomography. The experiment was based on tension infiltration into the soil column with free outflow at the lower end. Water flow through the soil core was mathematically modeled using a computer code that numerically solves the one-dimensional Richards equation. Measured soil hydraulic parameters were used for direct simulation, and the retention and soil hydraulic parameters were estimated by inverse modeling. The inverse modeling produced very good agreement between model outputs and measured flux and pressure head data for the relatively homogeneous column. The moisture content at a given pressure from the retention curve measured directly in small soil samples was lower than that obtained through parameter optimization based on experiments using a medium-sized undisturbed soil column.

Constitutive activity and inverse agonism at the alpha1adrenoceptors.

Mutations of G protein-coupled receptors (GPCR) can increase their constitutive (agonist-independent) activity. Some of these mutations have been artificially introduced by site-directed mutagenesis, others occur spontaneously in human diseases. The alpha(1B)adrenoceptor was the first GPCR in which point mutations were shown to trigger receptor activation. This article briefly summarizes some of the findings reported in the last several years on constitutive activity of the alpha(1)adrenoceptor subtypes, the location where mutations have been found in the receptors, the spontaneous activity of native receptors in recombinant as well as physiological systems. In addition, it will highlight how the analysis of the pharmacological and molecular properties of the constitutively active adrenoceptor mutants provided an important contribution to our understanding of the molecular mechanisms underlying the mechanism of receptor activation and inverse agonism.

The mean-variance model from the inverse of the variance-covariance matrix

En este artículo, a partir de la inversa de la matriz de varianzas y covarianzas se obtiene el modelo Esperanza-Varianza de Markowitz siguiendo un camino más corto y matemáticamente riguroso. También se obtiene la ecuación de equilibrio del CAPM de Sharpe.