Fluid net models: from behavioral properties to structural objects

Increasing the production in manufacturing systems is one of the main demands in modern systems. The naive approach that this goal can be achieved when more or faster resources are used is not always valid. In fact, the complex interactions among system’s elements may lead to paradoxical behaviors; for example, using faster machines could reduce the equilibrium throughput (number of part fabricated per unit time in steady state) of the system, or even worse, block all system activities, reducing it to zero. This work leverages the concepts about fluidization and analysis techniques used in Timed Continuous Petri nets (TCPN) presented in earlier works to study the behavior of the equilibrium throughput when more/faster machines are used. Herein, we illustrate how discontinuities induced bifurcations of the equilibrium throughput are due to the existence of paths that can increase/decrease the marking of certain subnets. In particular, if paths gaining/losing tokens are fired without a particular balance, then the equilibrium throughput exhibits discontinuities since the equilibrium marking loses hyperbolicity. Moreover, these discontinuities imply other undesired throughput behaviors; for example, the existence of non-monotonicities of the equilibrium throughput (when more/faster resources are used in the system, its equilibrium throughput is reduced). The discontinuities together with a homothecy property are used to explain non-monotonicities in the equilibrium throughput. A relevant aspect is that these undesired system behaviors appear when the net has structural objects named problematic configurations that are associated with certain subnets in which there are no P-semiflows. Although the number of these configurations increase exponentially in the size of the net, some reduction rules are introduced to remove configurations, while the problematic ones are kept (or can be recovered) in the reduced net. This saves computation time in the analysis and, more importantly, provides useful insights about the root of undesired behaviors. This work focus on systems that can be modeled with fluid (or continuous) mono T-semiflow Timed Continuous Petri nets. Even if under certain constraints, they are capable of capturing many characteristics of modern systems, such as interleaving of cooperation and competition

Evolutionary q-Gaussian radial basis function neural networks for multiclassification

This paper proposes a radial basis function neural network (RBFNN), called the q-Gaussian RBFNN, that reproduces different radial basis functions (RBFs) by means of a real parameter q. The architecture, weights and node topology are learnt through a hybrid algorithm (HA). In order to test the overall performance, an experimental study with sixteen data sets taken from the UCI repository is presented. The q-Gaussian RBFNN was compared to RBFNNs with Gaussian, Cauchy and inverse multiquadratic RBFs in the hidden layer and to other probabilistic classifiers, including different RBFNN design methods, support vector machines (SVMs), a sparse classifier (sparse multinomial logistic regression, SMLR) and a non-sparse classifier (regularized multinomial logistic regression, RMLR). The results show that the q-Gaussian model can be considered very competitive with the other classification methods. © 2011 Elsevier Ltd

Epistemología y política en el discurso pedagógico

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Effect of equivalent sites on the dynamics of bimetallic nanoparticles

Using a Sutton and Chen interatomic potential, we study the molecular dynamics of Au- Pd nanoparticles with an initial icosahedral structure at different temperatures and concentrations, where each relative concentration of the 561-atom particles was made by placing atoms of the same species at equivalent sites, in order to identify under which conditions the melting transition temperature appears for each particle. In addition, we compute global order parameters in order to correlate the obtained results with the caloric curves of each particle. As a result, we observe that the melting transition temperature depends on the relative atomic positions of gold and palladium. The melting transition temperature of the Au-Pd alloy particles appears at higher temperature than that of the pure-gold particle. From the analysis of the structure of the particles, we found that the melting temperature increases with the proportion of gold atoms, and for those particles with a higher concentration of palladium on the surface, we observe an early migration of gold atoms before the melting transition temperature appears

Characterisation and expression analysis of cathepsins and ubiquitin-proteasome genes in gilthead sea bream (Sparus aurata) skeletal muscle

The proteolytic enzymes involved in normal protein turnover in fish muscle are also responsible for post-mortem softening of the flesh and are therefore potential determinants of product quality. The main enzyme systems involved are calpains, cathepsins, and the ubiquitin-proteasome (UbP). In this study on Sparus aurata (Sa), the coding sequences of cathepsins (SaCTSB and SaCTSDb) and UbP family members (SaN3 and SaUb) were cloned from fast skeletal muscle, and their expression patterns were examined during ontogeny and in a fasting/re-feeding experiment. The amino acid sequences identified shared 66-100% overall identity with their orthologues in other vertebrates, with well conserved characteristic functional domains and catalytic residues. SaCTSDb showed phylogenetic, sequence and tissue distribution differences with respect to its paralogue SaCTSDa, previously identified in the ovary. Expression of gilthead sea bream cathepsins (B, L, Da, Db) and UbP members (N3, Ub, MuRF1 and MAFbx) in fast skeletal muscle was determined at three different life-history stages and in response to fasting and re-feeding in juveniles. Most of the proteolytic genes analysed were significantly up-regulated during fasting, and down-regulated with re-feeding and, between the fingerling (15 g) and juvenile/adult stages (~50/500 g), consistent with a decrease in muscle proteolysis in both later contexts. In contrast, SaCTSDa and SaMuRF1 expression was relatively stable with ontogeny and SaUb had higher expression in fingerlings and adults than juveniles. The data obtained in the present study suggest that cathepsins and UbP genes in gilthead sea bream are co-ordinately regulated during ontogeny to control muscle growth, and indicate that feeding regimes can modulate their expression, providing a potential dietary method of influencing post-mortem fillet tenderisation, and hence, product quality

Ordinal regression methods: survey and experimental study

Abstract—Ordinal regression problems are those machine learning problems where the objective is to classify patterns using a categorical scale which shows a natural order between the labels. Many real-world applications present this labelling structure and that has increased the number of methods and algorithms developed over the last years in this field. Although ordinal regression can be faced using standard nominal classification techniques, there are several algorithms which can specifically benefit from the ordering information. Therefore, this paper is aimed at reviewing the state of the art on these techniques and proposing a taxonomy based on how the models are constructed to take the order into account. Furthermore, a thorough experimental study is proposed to check if the use of the order information improves the performance of the models obtained, considering some of the approaches within the taxonomy. The results confirm that ordering information benefits ordinal models improving their accuracy and the closeness of the predictions to actual targets in the ordinal scal