Carga viral de seis tipos de Virus del Papiloma Humano de alto riesgo y su asociacion con lesiones cervicales

Introducción: La infección por un tipo de Virus del Papiloma Humano de alto riesgo (VPH-AR), es el factor principal en el desarrollo de Cáncer de Cérvix (CC). La carga viral puede modular esta asociación, por lo que resulta importante su cuantificación y el establecimiento de su relación con lesiones precursoras de CC. Metodología: 60 mujeres con lesiones escamosas intraepiteliales (LEI) y 120 mujeres sin LEI, confirmadas por colposcopia, fueron incluidas en el estudio. Se determinó la carga viral de 6 tipos de VPH-AR, mediante PCR en tiempo real. Se estimaron OR crudos y ajustados para evaluar la asociación entre la carga viral de cada tipo y las lesiones cervicales. Resultados: 93.22% de mujeres con LEI y 91.23% de mujeres negativas, fueron positivas para al menos un tipo de VPH. VPH-18 y VPH-16 fueron los tipos más prevalentes, junto con VPH-31 en mujeres sin LEI. No se encontraron diferencias estadísticamente significativas de las cargas virales entre éstos dos grupos, aunque se observó un mayor carga viral en lesiones para algunos tipos virales. Una mayor frecuencia de lesiones se asoció a infecciones con carga baja de VPH-16 (ORa: 3.53; IC95%: 1.16 – 10.74), en comparación a mujeres con carga alta de VPH-16, (ORa: 2.63; IC95%: 1.09 – 6.36). En infecciones por VPH-31, la presencia de carga viral alta, se asoció con una menor frecuencia de lesiones (ORa: 0.34; IC95%: 0.15 – 0.78). Conclusiones: La prevalencia tipo-específica de VPH se corresponde con las reportadas a nivel mundial. La asociación entre la carga viral del VPH y la frecuencia de LEI es tipo específica y podría depender de la duración de la infección, altas cargas relacionadas con infecciones transitorias, y bajas cargas con persistentes. Este trabajo contribuye al entendimiento del efecto de la carga viral en la historia natural del CC; sin embargo, estudios prospectivos son necesarios para confirmar estos resultados.

Front spreading in population dynamic models. Theory and application to the Neolithic transition

This thesis presents population dynamics models that can be applied to predict the rate of spread of the Neolithic transition (change from hunter-gathering to farming economics) across the European continent, which took place about 9000 to 5000 years ago. The first models in this thesis provide predictions at a continental scale. We develop population dynamics models with explicit kernels and apply realistic data. We also derive a new time-delayed reaction-diffusion equation which yields speeds about a 10% slower than previous models. We also deal with a regional variability: the slowdown of the Neolithic front when reaching the North of Europe. We develop simple reaction-diffusion models that can predict the measured speeds in terms of the non-homogeneous distribution of pre-Neolithic (Mesolithic) population in Europe, which were present in higher densities at the North of the continent. Such models can explain the observed speeds.

Genetic least squares for system identification

The recursive least-squares algorithm with a forgetting factor has been extensively applied and studied for the on-line parameter estimation of linear dynamic systems. This paper explores the use of genetic algorithms to improve the performance of the recursive least-squares algorithm in the parameter estimation of time-varying systems. Simulation results show that the hybrid recursive algorithm (GARLS), combining recursive least-squares with genetic algorithms, can achieve better results than the standard recursive least-squares algorithm using only a forgetting factor.

Relationship between åström control and the kalman linear regulator — Caines revisited

The relationship between minimum variance and minimum expected quadratic loss feedback controllers for linear univariate discrete-time stochastic systems is reviewed by taking the approach used by Caines. It is shown how the two methods can be regarded as providing identical control actions as long as a noise-free measurement state-space model is employed.

Weighted input predictive controller

A discrete-time algorithm is presented which is based on a predictive control scheme in the form of dynamic matrix control. A set of control inputs are calculated and made available at each time instant, the actual input applied being a weighted summation of the inputs within the set. The algorithm is directly applicable in a self-tuning format and is therefore suitable for slowly time-varying systems in a noisy environment.

An enhanced content selection mechanism for personalization of video news programmes

In this paper, we propose a content selection framework that improves the users` experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media`s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique`s limitations are minimized by other techniques` strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

RUMOR PROCESSES ON N

We study four discrete-time stochastic systems on N, modeling processes of rumor spreading. The involved individuals can either have an active or a passive role, speaking up or asking for the rumor. The appetite for spreading or hearing the rumor is represented by a set of random variables whose distributions may depend on the individuals. Our goal is to understand-based on the distribution of the random variables-whether the probability of having an infinite set of individuals knowing the rumor is positive or not.

Agregação de ume nitossolo vermelho distroférrico sob sistemas de plantio direto, preparo convencional e mata nativa

This study aimed to evaluate the effect of time since the adoption of the no-till system, in comparison with a native forest area and a conventional tillage area, using the distribution of soil aggregates in a Distroferric Red Nitosol. Treatments were as follows: native forest (NF), conventional tillage (CT), no-till for one year (NT1), no-till for four years (NT4), no-till for five years (NT5), and no-till for 12 years (NT12). Aggregate samples were collected randomly within each treatment at depths of 0-5 and 10-15 cm. After sifting the aggregates in water they were separated into the following aggregate classes > 2 mm; < 2 mm; 2-1 mm, and < 1 mm. The adoption time in the no-till system favored soil aggregation. The mean weighted diameter (MWD) of the soil aggregates and the percentage of aggregates greater than 2 mm increased with adoption time in the no-till system at the 0-5 cm depth. The NF and NT12 treatments had higher MWD values in the 0-5 cm layer. CT had the highest percentage of aggregates smaller than 1 mm.

Avaliação dos atributos físicos de um Nitossolo Vermelho distroférrico sob sistema plantio direto, preparo convencional e mata nativa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mitigation of symmetry condition in positive realness for adaptive control

Feasibility of nonlinear and adaptive control methodologies in multivariable linear time-invariant systems with state-space realization (A, B, C) is apparently limited by the standard strictly positive realness conditions that imply that the product CB must be positive definite symmetric. This paper expands the applicability of the strictly positive realness conditions used for the proofs of stability of adaptive control or control with uncertainty by showing that the not necessarily symmetric CB is only required to have a diagonal Jordan form and positive eigenvalues. The paper also shows that under the new condition any minimum-phase systems can be made strictly positive real via constant output feedback. The paper illustrates the usefulness of these extended properties with an adaptive control example. (C) 2006 Elsevier Ltd. All rights reserved.

Controlador adaptativo backstepping a estrutura variavel com Observadores de estado

This research aims at developing a variable structure adaptive backstepping controller (VS-ABC) by using state observers for SISO (Single Input Single Output), linear and time invariant systems with relative degree one. Therefore, the lters were replaced by a Luenberger Adaptive Observer and the control algorithm uses switching laws. The presented simulations compare the controller performance, considering when the state variables are estimated by an observer, with the case that the variables are available for measurement. Even with numerous performance advantages, adaptive backstepping controllers still have very complex algorithms, especially when the system state variables are not measured, since the use of lters on the plant input and output is not something trivial. As an attempt to make the controller design more intuitive, an adaptive observer as an alternative to commonly used K lters can be used. Furthermore, since the states variables are considered known, the controller has a reduction on the dependence of the unknown plant parameters on the design. Also, switching laws could be used in the controller instead of the traditional integral adaptive laws because they improve the system transient performance and increase the robustness against external disturbances in the plant input

Algorithms for network piecewise-linear programs: A comparative study

Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

Global optimization approach for the H2-norm model reduction problem

A branch and bound algorithm is proposed to solve the H2-norm model reduction problem for continuous-time linear systems, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through Linear Matrix Inequalities formulations. Examples illustrate the results.

Novos resultados sobre a estabilidade e controle de sistemas nao-lineares utilizando modelos fuzzy e LMI

Relaxed conditions for the stability study of nonlinear, continuous and discrete-time systems given by fuzzy models are presented. A theoretical analysis shows that the proposed method provides better or at least the same results of the methods presented in the literature. Digital simulations exemplify this fact. These results are also used for the fuzzy regulators design. The nonlinear systems are represented by the fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers are described by LMIs (Linear Matrix Inequalities), that can be solved efficiently by convex programming techniques. The specification of the decay rate, constraints on control input and output are also described by LMIs. Finally, the proposed design method is applied in the control of an inverted pendulum.

AI automates substation control

An overview is given on the possibility of controlling the status of circuit breakers (CB) in a substations with the use of a knowledge base that relates some of the operation magnitudes, mixing status variables with time variables and fuzzy sets. It is shown that even when all the magnitudes to be controlled cannot be included in the analysis, it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status.