Klinische Parameter und Laborprofile bei der Abklärung des Verdachts auf eine Heparin-induzierte Thrombozytopenie (HIT) Typ II bei Patienten nach herzchirurgischen Eingriffen

Magdeburg, Univ., Med. Fak., Diss., 2012

Anwendung des EM-Algorithmus zur Schätzung der Parameter von Fluoreszenzlebensdauerfunktionen

Die Bachelorarbeit behandelt die Schätzung der Parameter von Fluoreszenzlebensdauerfunktionen mit Hilfe des EM-Algorithmus. Dabei wird der Algorithmus sowohl auf simulierte als auch auf gemessene Daten angewandt. Die Schätzung der Parameter erfolgt zunächst global für die gesamte Probe mit Hilfe eines Simplex-Verfahrens, um dann das Verhältnis der Komponenten der Fluoreszenzlebensdauer, also die Wahrscheinlichkeit, mit der ein Photon von einer Komponente stammt, für jedes Pixel eines Bildes durch den EM-Algorithmus zu bestimmen. Die Messungen liegen als Anzahl der gemessenen Photonen in diskreten Zeitintervallen vor, dabei fehlt jedoch die Information, wie viele der Photonen in einem der Intervalle zu einer Komponente gehören. Durch die Nutzung bedingter Erwartungswerte ist der EM-Algorithmus in der Lage, ohne Verzerrung mit diesen unbekannten Daten umzugehen. Weiterhin wird die Schätzung dadurch erschwert, dass die Daten durch Faltung der Fluoreszenzlebensdauerfunktion mit einer so genannten Apparatefunktion zustandekommen und das Modell somit sehr komplex wird. Auch für dieses Problem wird im Laufe der Arbeit eine Lösung vorgestellt.

Optimal experimental design for parameter identification and model selection

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2014

Experiments in square lattice with a common treatment in all blocks

This paper deals with a generalization of square lattice designs, with k² treatments in blocks of k + 1 plots, the extra plot in each block receiving a standard treatment, the same for all blocks. The new design leads to lower variances for contrasts between adjusted treatment means

Untersuchungen zur Perzeption musikalischer Parameter von Cochlea-Implantat-Trägern mit den Sprachkodierungsstrategien ACE und MP3000 im Vergleich zu normalhörenden Probanden

Magdeburg, Univ., Med. Fak., Diss., 2014

Aging and growth parameter from the Piaractus mesopotamicus (pacu) from the Cuiabá river, Mato Grosso, Brazil

This study has aims to determine the age and to estimate the growth parameters using scales of the species. Individuals of Piaractus mesopotamicus (Holmberg, 1887) used in this study were captured in the commercial fishery conducted in the region, along the year 2006. The model selected to express the growth of the species was the von Bertalanffy Sl= Sl∞*[1-exp-k(t-to)]. To determine if scales are suitable for studying the growth of pacu, we analyzed the relation between standard length (Sl) and the radius of the scales through linear regression. The period of annuli formation was determined analyzing the variations in the marginal increment and evaluating the consistency of the readings through the analysis of the coefficient of variations (CVs) for the average standard lengths of each age (number of rings) observed in the scales. The relationship between Ls of the fish and the radius of the scales showed that scales can be used to study the age and growth of P. mesopotamicus (R= 0.79). CVs were always below 20%, demonstrating the consistency of the readings. Annuli formation occurred in February, probably related to trophic migration that occurs in this month in the region. Equations that represents the growth in length obtained for P. mesopotamicus are Sl=50.00*[1-exp-0.18(t-(-3.00)] for males and Sl=59.23*[1-exp-0.14(t-(-3.36)] for females. The growth parameters obtained in this study were lower compared to other studies previously conducted for the same species and can related to overexploitation that species is submitted by fishing in the region. These values show also that females of pacu attain greater asymptotic length than males that growth faster.

The existence of periodic solutions of a two dimensional Lattice

We consider a two dimensional lattice coupled with nearest neighbor interaction potential of power type. The existence of infinite many periodic solutions is shown by using minimax methods.

Large Time-Varying Parameter VARs

In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

Hierarchical Shrinkage in Time-Varying Parameter Models

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.

Diseño de filtros de onda acústica basados en estructuras "half lattice"

En los últimos tiempos la telefonía móvil ha experimentado una reducción de los terminales gracias a la miniaturización de los filtros a frecuencias de microondas. Los filtros pasa banda más utilizados son los basados en la tecnología SAW, sin embargo son incompatibles con tecnologías de silicio y su comportamiento se degrada a frecuencias superiores de 3 GHz, por ello los estudios actuales se centran en la tecnología BAW. Las dos arquitecturas convencionales de filtros basados en resonadores BAW unidos eléctricamente son el ladder y lattice. Sin embargo, en este proyecto se estudiará la topología half lattice, la cual presenta un mejor comportamiento y unas dimensiones más reducidas. Para ello se obtendrán las ecuaciones de diseño del filtro, y con ellas se realizará la implementación a partir de la frecuencia central y el ancho de banda relativo.

A parameter-free approach for solving combinatorial optimization problems through biased randomization of efficient heuristics

This paper discusses the use of probabilistic or randomized algorithms for solving combinatorial optimization problems. Our approach employs non-uniform probability distributions to add a biased random behavior to classical heuristics so a large set of alternative good solutions can be quickly obtained in a natural way and without complex conguration processes. This procedure is especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods, both of exact and approximate nature, may fail to reach their full potential. The results obtained are promising enough to suggest that randomizing classical heuristics is a powerful method that can be successfully applied in a variety of cases.

Meaning of the λ parameter of skew–normal and log–skew normal distributions in fluid geochemistry

The literature related to skew–normal distributions has grown rapidly in recent yearsbut at the moment few applications concern the description of natural phenomena withthis type of probability models, as well as the interpretation of their parameters. Theskew–normal distributions family represents an extension of the normal family to whicha parameter (λ) has been added to regulate the skewness. The development of this theoreticalfield has followed the general tendency in Statistics towards more flexible methodsto represent features of the data, as adequately as possible, and to reduce unrealisticassumptions as the normality that underlies most methods of univariate and multivariateanalysis. In this paper an investigation on the shape of the frequency distribution of thelogratio ln(Cl−/Na+) whose components are related to waters composition for 26 wells,has been performed. Samples have been collected around the active center of Vulcanoisland (Aeolian archipelago, southern Italy) from 1977 up to now at time intervals ofabout six months. Data of the logratio have been tentatively modeled by evaluating theperformance of the skew–normal model for each well. Values of the λ parameter havebeen compared by considering temperature and spatial position of the sampling points.Preliminary results indicate that changes in λ values can be related to the nature ofenvironmental processes affecting the data

Total hemoglobin mass--a new parameter to detect blood doping?

PURPOSE: All kinds of blood manipulations aim to increase the total hemoglobin mass (tHb-mass). To establish tHb-mass as an effective screening parameter for detecting blood doping, the knowledge of its normal variation over time is necessary. The aim of the present study, therefore, was to determine the intraindividual variance of tHb-mass in elite athletes during a training year emphasizing off, training, and race seasons at sea level. METHODS: tHb-mass and hemoglobin concentration ([Hb]) were determined in 24 endurance athletes five times during a year and were compared with a control group (n = 6). An analysis of covariance was used to test the effects of training phases, age, gender, competition level, body mass, and training volume. Three error models, based on 1) a total percentage error of measurement, 2) the combination of a typical percentage error (TE) of analytical origin with an absolute SD of biological origin, and 3) between-subject and within-subject variance components as obtained by an analysis of variance, were tested. RESULTS: In addition to the expected influence of performance status, the main results were that the effects of training volume (P = 0.20) and training phases (P = 0.81) on tHb-mass were not significant. We found that within-subject variations mainly have an analytical origin (TE approximately 1.4%) and a very small SD (7.5 g) of biological origin. CONCLUSION: tHb-mass shows very low individual oscillations during a training year (<6%), and these oscillations are below the expected changes in tHb-mass due to Herythropoetin (EPO) application or blood infusion (approximately 10%). The high stability of tHb-mass over a period of 1 year suggests that it should be included in an athlete's biological passport and analyzed by recently developed probabilistic inference techniques that define subject-based reference ranges.