Prediction of postprandial blood glucose under intra-patient variability and uncertainty and its use in the design of insulin dosing strategies for type 1 diabetic patients

In this thesis I propose a novel method to estimate the dose and injection-to-meal time for low-risk intensive insulin therapy. This dosage-aid system uses an optimization algorithm to determine the insulin dose and injection-to-meal time that minimizes the risk of postprandial hyper- and hypoglycaemia in type 1 diabetic patients. To this end, the algorithm applies a methodology that quantifies the risk of experiencing different grades of hypo- or hyperglycaemia in the postprandial state induced by insulin therapy according to an individual patient’s parameters. This methodology is based on modal interval analysis (MIA). Applying MIA, the postprandial glucose level is predicted with consideration of intra-patient variability and other sources of uncertainty. A worst-case approach is then used to calculate the risk index. In this way, a safer prediction of possible hyper- and hypoglycaemic episodes induced by the insulin therapy tested can be calculated in terms of these uncertainties.

Dynamic diagnosis based on interval analytical redundancy relations and signs of the symptoms

A model-based approach for fault diagnosis is proposed, where the fault detection is based on checking the consistencyof the Analytical Redundancy Relations (ARRs) using an interval tool. The tool takes into account the uncertainty in theparameters and the measurements using intervals. Faults are explicitly included in the model, which allows for the exploitation of additional information. This information is obtained from partial derivatives computed from the ARRs. The signs in the residuals are used to prune the candidate space when performing the fault diagnosis task. The method is illustrated using a two-tank example, in which these aspects are shown to have an impact on the diagnosis and fault discrimination, since the proposed method goes beyond the structural methods

Computationally reliable approaches of contractive MPC for discrete-time systems

La tesis pretende explorar acercamientos computacionalmente confiables y eficientes de contractivo MPC para sistemas de tiempo discreto. Dos tipos de contractivo MPC han sido estudiados: MPC con coacción contractiva obligatoria y MPC con una secuencia contractiva de conjuntos controlables. Las técnicas basadas en optimización convexa y análisis de intervalos son aplicadas para tratar MPC contractivo lineal y no lineal, respectivamente. El análisis de intervalos clásicos es ampliado a zonotopes en la geometría para diseñar un conjunto invariante de control terminal para el modo dual de MPC. También es ampliado a intervalos modales para tener en cuenta la modalidad al calcula de conjuntos controlables robustos con una interpretación semántica clara. Los instrumentos de optimización convexa y análisis de intervalos han sido combinados para mejorar la eficacia de contractive MPC para varias clases de sistemas de tiempo discreto inciertos no lineales limitados. Finalmente, los dos tipos dirigidos de contractivo MPC han sido aplicados para controlar un Torneo de Fútbol de Copa Mundial de Micro Robot (MiroSot) y un Tanque-Reactor de Mezcla Continua (CSTR), respectivamente.

Constrained intervals and interval spaces

Constrained intervals, intervals as a mapping from [0, 1] to polynomials of degree one (linear functions) with non-negative slopes, and arithmetic on constrained intervals generate a space that turns out to be a cancellative abelian monoid albeit with a richer set of properties than the usual (standard) space of interval arithmetic. This means that not only do we have the classical embedding as developed by H. Radström, S. Markov, and the extension of E. Kaucher but the properties of these polynomials. We study the geometry of the embedding of intervals into a quasilinear space and some of the properties of the mapping of constrained intervals into a space of polynomials. It is assumed that the reader is familiar with the basic notions of interval arithmetic and interval analysis. © 2013 Springer-Verlag Berlin Heidelberg.

Pushover analysis for the seismic response prediction of cable-stayed bridges under multi-directional excitation

Cable-stayed bridges represent nowadays key points in transport networks and their seismic behavior needs to be fully understood, even beyond the elastic range of materials. Both nonlinear dynamic (NL-RHA) and static (pushover) procedures are currently available to face this challenge, each with intrinsic advantages and disadvantages, and their applicability in the study of the nonlinear seismic behavior of cable-stayed bridges is discussed here. The seismic response of a large number of finite element models with different span lengths, tower shapes and class of foundation soil is obtained with different procedures and compared. Several features of the original Modal Pushover Analysis (MPA) are modified in light of cable-stayed bridge characteristics, furthermore, an extension of MPA and a new coupled pushover analysis (CNSP) are suggested to estimate the complex inelastic response of such outstanding structures subjected to multi-axial strong ground motions.

Violência e desigualdade social: mortalidade por homicídios e condições de vida em Salvador, Brasil

OBJETIVO: A relação entre pobreza e violência tem sido questionada por alguns autores. Nesse sentido, foi realizado estudo com o objetivo de analisar os diferenciais intra-urbanos de mortalidade por homicídio segundo as condições de vida. MÉTODOS: Estudo de agregados referente aos anos de 1991 e 1994, considerando as 75 zonas de informação de Salvador, BA, e a classificação de sua população em quatro estratos de condições de vida, a partir das variáveis renda e escolaridade. Para cada estrato, foram calculados a taxa de mortalidade por homicídios e o risco relativo de morte para o estrato de piores condições de vida em relação aos demais. Os dados foram obtidos de declarações de óbito, dos registros do Instituto Médico Legal e do Censo Demográfico de 1991. Foram calculados os intervalos de confiança a 95%, mediante o aplicativo Confidence Interval Analysis. RESULTADOS: As taxas de mortalidade por homicídio mais elevadas foram registradas nas áreas mais pobres da cidade. O risco relativo de morte por essa causa entre o estrato de piores e o de melhores condições de vida variou entre 2,9 e 5,1, sendo essa relação estatisticamente significante em nível de 5%. CONCLUSÃO: Os achados são sugestivos das possíveis relações entre homicídios e desigualdades sociais, o que levou a discussões sobre a relevância de iniciativas organizadas para a redução da violência.

Constraint reasoning with local search for continuous optimization

Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.

Probabilistic constraint reasoning with Monte Carlo integration to robot localization

This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Constraint satisfaction techniques under uncertain conditions for fault diagnosis in nonlinear dynamic systems

The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented

Growth and reproduction of the dolphinfish (Coryphaena equiselis and Coryphaena hippurus) in the Canary Islands, Central-East Atlantic (preliminary results)

The size, growth and spawning characteristics of pompano dolphin (N=150) and common dolphinfish (N=36) caught off the Canary Islands between May and September 1995 and between July and September 1996 were examined. Fork length (FL) of pompano dolphin was in the range 28.3-62.8 cm. In 1995, the mean length increased significantly from June to September. However, in 1996, the mean length was significantly larger in July than in September. The overall length-weight relationship was W=0.0287*FL2.774 (r=0.97), while these relationships by sex were as follows: W=0.031*FL2.758 (r=0.98) and W=0.0282*FL2.776 (r=0.97), for males and females respectively. Spawning takes place at the beginning of the Summer (June-July). All the individuals obtained showed developing gonads, but females showed a higher gonadosomatic index (GSI) than males. The highest GSI values were obtained in June (x- =3.10±1.73), and decreased progressively towards the end of the season (September), when the average of this index was x- = 1.86±0.87. Similarly, the condition index decreased significantly from June to September. The proportion of females was always significantly higher than males, except in July 1996 when it was 1:1. There was a high correspondence between growth rates determined by annuli scale interpretation and modal progression analysis. According to scale annuli interpretation, the individuals caught showed more than five age classes. However, there are doubts about age assignation from scales. Fork length of common dolphinfish was in the range of 76.5-103.0 cm. The length-weight relationships obtained for all the specimens caught was W=0.00095FL3.527 (r=0.96), while these relationships by sex were as follows: W=0.00398FL3.222 (r=0.94) and W=0.01656FL2.873 (r=0.91), for males and females respectively. Spawning probably takes place at the beginning of the Summer. All the individuals obtained showed developing gonads, although the GSI of females were higher than males. The highest GSI values were obtained in June (x- =5.50±2.17). In the same way, the condition index decreased from May to June. The proportion of females was always slightly higher than males (1:1.4), but the ratio was not significantly different from 1:1

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

Constraint satisfaction techniques under uncertain conditions for fault diagnosis in nonlinear dynamic systems

The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Motion of the dayside polar cap boundary during substorm cycles: I. Observations of pulses in the magnetopause reconnection rate

Using data from the EISCAT (European Incoherent Scatter) VHF radar and DMSP (Defense Meteorological Satellite Program) spacecraft passes, we study the motion of the dayside open-closed field line boundary during two substorm cycles. The satellite data show that the motions of ion and electron temperature boundaries in EISCAT data, as reported by Moen et al. (2004), are not localised around the radar; rather, they reflect motions of the open-closed field line boundary at all MLT throughout the dayside auroral ionosphere. The boundary is shown to erode equatorward when the IMF points southward, consistent with the effect of magnetopause reconnection. During the substorm expansion and recovery phases, the dayside boundary returns poleward, whether the IMF points northward or southward. However, the poleward retreat was much faster during the substorm for which the IMF had returned to northward than for the substorm for which the IMF remained southward – even though the former substorm is much the weaker of the two. These poleward retreats are consistent with the destruction of open flux at the tail current sheet. Application of a new analysis of the peak ion energies at the equatorward edge of the cleft/cusp/mantle dispersion seen by the DMSP satellites identifies the dayside reconnection merging gap to extend in MLT from about 9.5 to 15.5 h for most of the interval. Analysis of the boundary motion, and of the convection velocities seen near the boundary by EISCAT, allows calculation of the reconnection rate (mapped down to the ionosphere) from the flow component normal to the boundary in its own rest frame. This reconnection rate is not, in general, significantly different from zero before 06:45 UT (MLT<9.5 h) – indicating that the X line footprint expands over the EISCAT field-of-view to earlier MLT only occasionally and briefly. Between 06:45 UT and 12:45UT (9.5