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.

Psychophysiological activation during preparation, performance, and recovery in high- and low-anxious music students

The present study provides a comprehensive view of (a) the time dynamics of the psychophysiological responding in performing music students (n = 66) before, during, and after a private and a public performance and (b) the moderating effect of music performance anxiety (MPA). Heart rate (HR), minute ventilation (VE), and all affective and somatic self-report variables increased in the public session compared to the private session. Furthermore, the activation of all variables was stronger during the performances than before or after. Differences between phases were larger in the public than in the private session for HR, VE, total breath duration, anxiety, and trembling. Furthermore, while higher MPA scores were associated with higher scores and with larger changes between sessions and phases for self-reports, this association was less coherent for physiological variables. Finally, self-reported intra-individual performance improvements or deteriorations were not associated with MPA. This study makes a novel contribution by showing how the presence of an audience influences low- and high-anxious musicians' psychophysiological responding before, during and after performing. Overall, the findings are more consistent with models of anxiety that emphasize the importance of cognitive rather than physiological factors in MPA.

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.

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.

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.

Performance anxiety : cardiorespiratory activity in high- and low-anxious professional music students in a performance situation

Questionnaire studies indicate that high-anxious musicians may suffer from hyperventilation symptoms before and/or during performance. Reported symptoms include amongst others shortness of breath, fast or deep breathing, dizziness and thumping heart. A self-report study by Widmer, Conway, Cohen and Davies (1997) shows that up to seventy percent of the tested highly anxious musicians are hyperventilators during performance. However, no study has yet tested if these self-reported symptoms reflect actual cardiorespiratory changes just before and during performance. Disturbances in breathing patterns and hyperventilation may negatively affect the performance quality in stressful performance situations. The main goal of this study is to determine if music performance anxiety is manifest physiologically in specific correlates of cardiorespiratory activity. We studied 74 professional music students of Swiss Music Universities divided into two groups (high- and lowanxious) based on their self-reported performance anxiety (State-Trait Anxiety Inventory by Spielberger). The students were tested in three distinct situations: baseline, performance without audience, performance with audience. We measured a) breathing patterns, end-tidal carbon dioxide, which is a good non-invasive estimator for hyperventilation, and cardiac activation and b) self-perceived emotions and self-perceived physiological activation. Analyses of heart rate, respiratory rate, self-perceived palpitations, self-perceived shortness of breath and self-perceived anxiety for the 15 most and the 15 least anxious musicians show that high-anxious and low-anxious music students have a comparable physiological activation during the different measurement periods. However, highanxious music students feel significantly more anxious and perceive significantly stronger palpitations and significantly stronger shortness of breath just before and during a public performance. The results indicate that low- and high-anxious music students a) do not differ in the considered physiological responses and b) differ in the considered self-perceived physiological symptoms and the selfreported anxiety before and/or during a public performance.

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.