No description available.

No description available.

München, Techn. University, Diss., 2004.

Berlin, Humboldt-Universiẗat, Diss., 2002.

No description available.

In evolutionary biology, genetic sequences carry with them a trace of the underlying tree that describes their evolution from a common ancestral sequence. Inferring this underlying tree is challenging. We investigate some curious cases in which different methods like Maximum Parsimony, Maximum Likelihood and distance-based methods lead to different trees. Moreover, we state that in some cases, ancestral sequences can be more reliably reconstructed when some of the leaves of the tree are ignored - even if these leaves are close to the root. While all these findings show problems inherent to either the assumed model or the applied method, sometimes an inaccurate tree reconstruction is simply due to insufficient data. This is particularly problematic when a rapid divergence event occurred in the distant past. We analyze an idealized form of this problem and determine a tight lower bound on the growth rate for the sequence length required to resolve the tree (independent of any particular branch length). Finally, we investigate the problem of intermediates in the fossil record. The extent of ‘gaps’ (missing transitional stages) has been used to argue against gradual evolution from a common ancestor. We take an analytical approach and demonstrate why, under certain sampling conditions, we may not expect intermediates to be found.

Diese empirische Arbeit untersucht Determinanten des Renteneintritts. Sie basiert auf einem Optionswertmodell, um die Bedeutung finanzieller Überlegungen für ein Aufschieben des Renteneintritts zu analysieren. Zusätzlich wird der Einfluss institutioneller Rahmenbedingungen betrachtet. Ein neu verfügbarer Datensatz des Verbands Deutscher Rentenversicherungsträger wird dazu verwendet. Die Ergebnisse zeigen, dass Arbeitslosigkeit und Krankheit zu einem großen Teil einen frühen Renteneintritt erklären. Zusätzlich hat der Optionswert einen großen Erklärungsgehalt. / This paper empirically investigates determinants of retirement decisions. It is based on the option value approach to assess the importance of financial considerations for delaying immediate retirement. In addition, the impact of institutional conditions is considered. Newly available data from the data base of the statutory pension organization providing exact information about income, pension claims, and unemployment spells is used. The results indicate that unemployment and illness explain a great portion of early retirements. Additionally, the option value has explanatory power.

We consider the problem of maximum likelihood estimation of logistic sinusoidal regression models and develop some asymptotic theory including the consistency and joint rates of convergence for the maximum likelihood estimators. The key techniques build upon a synthesis of the results of Walker and Song and Li for the widely studied sinusoidal regression model and on making a connection to a result of Radchenko. Monte Carlo simulations are also presented to demonstrate the finite-sample performance of the estimators

Philosophiae Doctor - PhD / Malaria is a common infection in tropical areas, transmitted between humans through female anopheles mosquito bites as it seeks blood meal to carry out egg production. The infection forms a direct threat to the lives of many people in South Sudan. Reports show that malaria caused a large proportion of morbidity and mortality in the fledgling nation, accounting for 20% to 40% morbidity and 20% to 25% mortality, with the majority of the affected people being children and pregnant mothers. In this thesis, we construct and analyze mathematical models for malaria transmission in South Sudan context incorporating national malaria control strategic plan. In addition, we investigate important factors such as climatic conditions and population mobility that may drive malaria in South Sudan. Furthermore, we study a stochastic version of the deterministic model by introducing a white noise.

Novel Turbo Equalization Methods for the Magnetic Recording Channel Elizabeth Chesnutt 95 Pages Directed by Dr. John R. Barry The topic of this dissertation is the derivation, development, and evaluation of novel turbo equalization techniques that address the colored noise problem on the magnetic recording channel. One new algorithm presented is the noise-predictive BCJR, which is a soft-output detection strategy that mitigates colored noise in partial-response equalized magnetic recording channels. This algorithm can be viewed as a combination of the traditional BCJR algorithm with the notion of survivors and noise prediction. Additionally, an alternative equalization architecture for magnetic recording is presented that addresses the shortcomings of the PRML approach, which dominates magnetic recording. Specifically, trellis-based equalizers are abandoned in favor of simple equalization strategies based on nonlinear filters whose complexity grows only linearly with their length. This research focuses on the linear-complexity SFE algorithm and on investigating the possibility of lowering the SFE filter calculation complexity. The results indicate that with using the proposed novel SFE method, it is possible to increase the information density on magnetic media without raising the complexity. The most important result presented is that partial-response equalization needs to be reconsidered because of the amount of noise enhancement problems that it adds to the overall system. These results are important for the magnetic recording industry, which is trying to attain a 1 Tb/cm2 information storage goal.