Validation of a clinical algorithm to identify low-risk patients with pulmonary embolism.

Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.

A fast Bayesian reconstruction algorithm for emission tomography with entropy prior converging to feasible images

The development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.

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.

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.

Numerical algorithm for Ginzburg-Landau equations with multiplicative noise: Application to domain growth

We consider stochastic partial differential equations with multiplicative noise. We derive an algorithm for the computer simulation of these equations. The algorithm is applied to study domain growth of a model with a conserved order parameter. The numerical results corroborate previous analytical predictions obtained by linear analysis.

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.

Majorization arrow in quantum-algorithm design

We apply majorization theory to study the quantum algorithms known so far and find that there is a majorization principle underlying the way they operate. Grover's algorithm is a neat instance of this principle where majorization works step by step until the optimal target state is found. Extensions of this situation are also found in algorithms based in quantum adiabatic evolution and the family of quantum phase-estimation algorithms, including Shor's algorithm. We state that in quantum algorithms the time arrow is a majorization arrow.

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.

Decision-making in pediatrics: a practical algorithm to evaluate complementary and alternative medicine for children.

We herein present a preliminary practical algorithm for evaluating complementary and alternative medicine (CAM) for children which relies on basic bioethical principles and considers the influence of CAM on global child healthcare. CAM is currently involved in almost all sectors of pediatric care and frequently represents a challenge to the pediatrician. The aim of this article is to provide a decision-making tool to assist the physician, especially as it remains difficult to keep up-to-date with the latest developments in the field. The reasonable application of our algorithm together with common sense should enable the pediatrician to decide whether pediatric (P)-CAM represents potential harm to the patient, and allow ethically sound counseling. In conclusion, we propose a pragmatic algorithm designed to evaluate P-CAM, briefly explain the underlying rationale and give a concrete clinical example.

Numerical algorithm for spectroscopic ellipsometry of thick transparent films

We present a numerical method for spectroscopic ellipsometry of thick transparent films. When an analytical expression for the dispersion of the refractive index (which contains several unknown coefficients) is assumed, the procedure is based on fitting the coefficients at a fixed thickness. Then the thickness is varied within a range (according to its approximate value). The final result given by our method is as follows: The sample thickness is considered to be the one that gives the best fitting. The refractive index is defined by the coefficients obtained for this thickness.

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.

Development and Demonstration of a Freezing Drizzle Algorithm for Roadway Environmental Sensing Systems, Final Report, October 2012

The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.