Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Structural and operational optimisation : applications in energy systems

In this work mathematical programming models for structural and operational optimisation of energy systems are developed and applied to a selection of energy technology problems. The studied cases are taken from industrial processes and from large regional energy distribution systems. The models are based on Mixed Integer Linear Programming (MILP), Mixed Integer Non-Linear Programming (MINLP) and on a hybrid approach of a combination of Non-Linear Programming (NLP) and Genetic Algorithms (GA). The optimisation of the structure and operation of energy systems in urban regions is treated in the work. Firstly, distributed energy systems (DES) with different energy conversion units and annual variations of consumer heating and electricity demands are considered. Secondly, district cooling systems (DCS) with cooling demands for a large number of consumers are studied, with respect to a long term planning perspective regarding to given predictions of the consumer cooling demand development in a region. The work comprises also the development of applications for heat recovery systems (HRS), where paper machine dryer section HRS is taken as an illustrative example. The heat sources in these systems are moist air streams. Models are developed for different types of equipment price functions. The approach is based on partitioning of the overall temperature range of the system into a number of temperature intervals in order to take into account the strong nonlinearities due to condensation in the heat recovery exchangers. The influence of parameter variations on the solutions of heat recovery systems is analysed firstly by varying cost factors and secondly by varying process parameters. Point-optimal solutions by a fixed parameter approach are compared to robust solutions with given parameter variation ranges. In the work enhanced utilisation of excess heat in heat recovery systems with impingement drying, electricity generation with low grade excess heat and the use of absorption heat transformers to elevate a stream temperature above the excess heat temperature are also studied.

Histomorphometric analysis of the response of rat skeletal muscle to swimming, immobilization and rehabilitation

The objective of the present study was to determine to what extent, if any, swimming training applied before immobilization in a cast interferes with the rehabilitation process in rat muscles. Female Wistar rats, mean weight 260.52 ± 16.26 g, were divided into 4 groups of 6 rats each: control, 6 weeks under baseline conditions; trained, swimming training for 6 weeks; trained-immobilized, swimming training for 6 weeks and then immobilized for 1 week; trained-immobilized-rehabilitated, swimming training for 6 weeks, immobilized for 1 week and then remobilized with swimming for 2 weeks. The animals were then sacrificed and the soleus and tibialis anterior muscles were dissected, frozen in liquid nitrogen and processed histochemically (H&E and mATPase). Data were analyzed statistically by the mixed effects linear model (P < 0.05). Cytoarchitectural changes such as degenerative characteristics in the immobilized group and regenerative characteristics such as centralized nucleus, fiber size variation and cell fragmentation in the groups submitted to swimming were more significant in the soleus muscle. The diameters of the lesser soleus type 1 and type 2A fibers were significantly reduced in the trained-immobilized group compared to the trained group (P < 0.001). In the tibialis anterior, there was an increase in the number of type 2B fibers and a reduction in type 2A fibers when trained-immobilized rats were compared to trained rats (P < 0.001). In trained-immobilized-rehabilitated rats, there was a reduction in type 2B fibers and an increase in type 2A fibers compared to trained-immobilized rats (P < 0.009). We concluded that swimming training did not minimize the deleterious effects of immobilization on the muscles studied and that remobilization did not favor tissue re-adaptation.

How do Young People Choose College Majors?

Previous studies on the determinants of the choice of college major have assumed a constant probability of success across majors or a constant earnings stream across majors. Our model disregards these two restrictive assumptions in computing an expected earnings variable to explain the probability that a student will choose a specific major among four choices of concentrations. The construction of an expected earnings variable requires information on the student s perceived probability of success, the predicted earnings of graduates in all majors and the student s expected earnings if he (she) fails to complete a college program. Using data from the National Longitudinal Survey of Youth, we evaluate the chances of success in all majors for all the individuals in the sample. Second, the individuals' predicted earnings of graduates in all majors are obtained using Rumberger and Thomas's (1993) regression estimates from a 1987 Survey of Recent College Graduates. Third, we obtain idiosyncratic estimates of earnings alternative of not attending college or by dropping out with a condition derived from our college major decision-making model applied to our sample of college students. Finally, with a mixed multinominal logit model, we explain the individuals' choice of a major. The results of the paper show that the expected earnings variable is essential in the choice of a college major. There are, however, significant differences in the impact of expected earnings by gender and race.

Vérification temporelle des systèmes cycliques et acycliques basée sur l’analyse des contraintes

Nous présentons une nouvelle approche pour formuler et calculer le temps de séparation des événements utilisé dans l’analyse et la vérification de différents systèmes cycliques et acycliques sous des contraintes linéaires-min-max avec des composants ayant des délais finis et infinis. Notre approche consiste à formuler le problème sous la forme d’un programme entier mixte, puis à utiliser le solveur Cplex pour avoir les temps de séparation entre les événements. Afin de démontrer l’utilité en pratique de notre approche, nous l’avons utilisée pour la vérification et l’analyse d’une puce asynchrone d’Intel de calcul d’équations différentielles. Comparée aux travaux précédents, notre approche est basée sur une formulation exacte et elle permet non seulement de calculer le maximum de séparation, mais aussi de trouver un ordonnancement cyclique et de calculer les temps de séparation correspondant aux différentes périodes possibles de cet ordonnancement.

Développement d’un algorithme de branch-and-price-and-cut pour le problème de conception de réseau avec coûts fixes et capacités

De nombreux problèmes en transport et en logistique peuvent être formulés comme des modèles de conception de réseau. Ils requièrent généralement de transporter des produits, des passagers ou encore des données dans un réseau afin de satisfaire une certaine demande tout en minimisant les coûts. Dans ce mémoire, nous nous intéressons au problème de conception de réseau avec coûts fixes et capacités. Ce problème consiste à ouvrir un sous-ensemble des liens dans un réseau afin de satisfaire la demande, tout en respectant les contraintes de capacités sur les liens. L'objectif est de minimiser les coûts fixes associés à l'ouverture des liens et les coûts de transport des produits. Nous présentons une méthode exacte pour résoudre ce problème basée sur des techniques utilisées en programmation linéaire en nombres entiers. Notre méthode est une variante de l'algorithme de branch-and-bound, appelée branch-and-price-and-cut, dans laquelle nous exploitons à la fois la génération de colonnes et de coupes pour la résolution d'instances de grande taille, en particulier, celles ayant un grand nombre de produits. En nous comparant à CPLEX, actuellement l'un des meilleurs logiciels d'optimisation mathématique, notre méthode est compétitive sur les instances de taille moyenne et supérieure sur les instances de grande taille ayant un grand nombre de produits, et ce, même si elle n'utilise qu'un seul type d'inégalités valides.

Labor supply, biased technological change and economic growth

Se utiliza un modelo de innovaciones sesgadas para estudiar los efectos de cambios exógenos en la oferta laboral. En un contexto de innovaciones sesgadas, a medida que las economías acumulan capital, el trabajo se hace relativamente más escaso y más caro, por este motivo, hay incentivos para adoptar tecnologías ahorradoras de trabajo. Del mismo modo un cambio en la oferta laboral afecta la abundancia de factores y sus precios relativos. En general, una reducción de la oferta laboral, hace que el trabajo sea más caro y genera incentivos para cambio tecnológico ahorrador de trabajo. Así, el efecto inicial que tiene el cambio en la oferta laboral sobre los precios de los factores es mitigado por el cambio tecnológico. Finalmente, los movimientos en la remuneración a los factores afectan las decisiones de ahorro y, por lo tanto, la dinámica del crecimiento. En este trabajo se exploran las consecuencias de una reducción de la oferta laboral en dos contextos teóricos diferentes: un modelo de agentes homogéneos y horizonte infinito y un modelo de generaciones traslapadas.

A practical approach to a multi-level analysis with a sparse binary outcome within a large surgical trial

Objectives: To assess the potential source of variation that surgeon may add to patient outcome in a clinical trial of surgical procedures. Methods: Two large (n = 1380) parallel multicentre randomized surgical trials were undertaken to compare laparoscopically assisted hysterectomy with conventional methods of abdominal and vaginal hysterectomy; involving 43 surgeons. The primary end point of the trial was the occurrence of at least one major complication. Patients were nested within surgeons giving the data set a hierarchical structure. A total of 10% of patients had at least one major complication, that is, a sparse binary outcome variable. A linear mixed logistic regression model (with logit link function) was used to model the probability of a major complication, with surgeon fitted as a random effect. Models were fitted using the method of maximum likelihood in SAS((R)). Results: There were many convergence problems. These were resolved using a variety of approaches including; treating all effects as fixed for the initial model building; modelling the variance of a parameter on a logarithmic scale and centring of continuous covariates. The initial model building process indicated no significant 'type of operation' across surgeon interaction effect in either trial, the 'type of operation' term was highly significant in the abdominal trial, and the 'surgeon' term was not significant in either trial. Conclusions: The analysis did not find a surgeon effect but it is difficult to conclude that there was not a difference between surgeons. The statistical test may have lacked sufficient power, the variance estimates were small with large standard errors, indicating that the precision of the variance estimates may be questionable.

The constrained compartmentalized knapsack problem: mathematical models and solution methods

The constrained compartmentalized knapsack problem can be seen as an extension of the constrained knapsack problem. However, the items are grouped into different classes so that the overall knapsack has to be divided into compartments, and each compartment is loaded with items from the same class. Moreover, building a compartment incurs a fixed cost and a fixed loss of the capacity in the original knapsack, and the compartments are lower and upper bounded. The objective is to maximize the total value of the items loaded in the overall knapsack minus the cost of the compartments. This problem has been formulated as an integer non-linear program, and in this paper, we reformulate the non-linear model as an integer linear master problem with a large number of variables. Some heuristics based on the solution of the restricted master problem are investigated. A new and more compact integer linear model is also presented, which can be solved by a branch-and-bound commercial solver that found most of the optimal solutions for the constrained compartmentalized knapsack problem. On the other hand, heuristics provide good solutions with low computational effort. (C) 2011 Elsevier BM. All rights reserved.

Performance of balanced two-stage empirical predictors of realized cluster latent values from finite populations: A simulation study

Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.

Realized volatility: evidence from Brazil

Using intraday data for the most actively traded stocks on the São Paulo Stock Market (BOVESPA) index, this study considers two recently developed models from the literature on the estimation and prediction of realized volatility: the Heterogeneous Autoregressive Model of Realized Volatility (HAR-RV), developed by Corsi (2009), and the Mixed Data Sampling model (MIDAS-RV), developed by Ghysels et al. (2004). Using measurements to compare in-sample and out-of-sample forecasts, better results were obtained with the MIDAS-RV model for in-sample forecasts. For out-of-sample forecasts, however, there was no statistically signi cant di¤erence between the models. We also found evidence that the use of realized volatility induces distributions of standardized returns that are closer to normal

Comparação de critérios de seleção para precocidade de crescimento em bovinos da raça Guzerá

Objetivou-se com este estudo comparar a seleção com base no ganho médio diário de peso na pré-desmama (GMD) e no número de dias para ganhar 160 kg nessa fase (D160), com e sem correção para efeitos de grupos de contemporâneos (GC), em bovinos da raça Guzerá. Utilizou-se o banco de dados de desenvolvimento ponderal da Associação Brasileira de Criadores de Zebu (ABCZ) para esta raça. A obtenção dos parâmetros e valores genéticos foi feita pelo método da máxima verossimilhança restrita utilizando-se modelo unicaracterístico com equações de modelos mistos. O modelo utilizado foi composto pelo efeito fixo de grupo genético e pelos efeitos aleatórios, genético aditivo direto e de ambiente permanente, além do erro residual. A média para D160 foi de 270,5 dias e para GMD, 642,3 g. As correlações de Spearman entre ganho médio diário e a precocidade em dias para ganhar 160 kg na pré-desmama (PD160), e GMD e PD160c (PD160 corrigido para o efeito de grupo de contemporâneo), foram iguais a 0,91 e 0,94, respectivamente. A seleção para PD160 favorece touros que produzem progênie com desempenho superior e menos variável e a padronização deste critério com base no grupo de contemporâneos melhorou sua eficiência. A classificação dos touros varia de acordo com o critério de seleção utilizado, GMD ou PD160, principalmente nos extremos, onde ocorrem seleção e descarte de reprodutores.

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.

Multistage and coordinated planning of the expansion of transmission systems

In this paper, an efficient genetic algorithm (GA) is presented to solve the problem of multistage and coordinated transmission expansion planning. This is a mixed integer nonlinear programming problem, difficult for systems of medium and large size and high complexity. The GA presented has a set of specialized genetic operators and an efficient form of generation of the initial population that finds high quality suboptimal topologies for large size and high complexity systems. In these systems, multistage and coordinated planning present a lower investment than static planning. Tests results are shown in one medium complexity system and one large size high complexity system.

Reactive power dispatch and planning using a non-linear branch-and-bound algorithm

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