MPI parallel programming of mixed integer optimization problems using CPLEX with COIN-OR

The aim of this technical report is to present some detailed explanations in order to help to understand and use the Message Passing Interface (MPI) parallel programming for solving several mixed integer optimization problems. We have developed a C++ experimental code that uses the IBM ILOG CPLEX optimizer within the COmputational INfrastructure for Operations Research (COIN-OR) and MPI parallel computing for solving the optimization models under UNIX-like systems. The computational experience illustrates how can we solve 44 optimization problems which are asymmetric with respect to the number of integer and continuous variables and the number of constraints. We also report a comparative with the speedup and efficiency of several strategies implemented for some available number of threads.

Increased expression of cystine/glutamate antiporter in multiple sclerosis

Background: Glutamate excitotoxicity contributes to oligodendrocyte and tissue damage in multiple sclerosis (MS). Intriguingly, glutamate level in plasma and cerebrospinal fluid of MS patients is elevated, a feature which may be related to the pathophysiology of this disease. In addition to glutamate transporters, levels of extracellular glutamate are controlled by cystine/glutamate antiporter x(c)(-), an exchanger that provides intracellular cystine for production of glutathione, the major cellular antioxidant. The objective of this study was to analyze the role of the system x(c)(-) in glutamate homeostasis alterations in MS pathology. -- Methods: Primary cultures of human monocytes and the cell line U-937 were used to investigate the mechanism of glutamate release. Expression of cystine glutamate exchanger (xCT) was quantified by quantitative PCR, Western blot, flow cytometry and immunohistochemistry in monocytes in vitro, in animals with experimental autoimmune encephalomyelitis (EAE), the animal model of MS, and in samples of MS patients. -- Results and discussion: We show here that human activated monocytes release glutamate through cystine/glutamate antiporter x(c)(-) and that the expression of the catalytic subunit xCT is upregulated as a consequence of monocyte activation. In addition, xCT expression is also increased in EAE and in the disease proper. In the later, high expression of xCT occurs both in the central nervous system (CNS) and in peripheral blood cells. In particular, cells from monocyte-macrophage-microglia lineage have higher xCT expression in MS and in EAE, indicating that immune activation upregulates xCT levels, which may result in higher glutamate release and contribution to excitotoxic damage to oligodendrocytes. -- Conclusions: Together, these results reveal that increased expression of the cystine/glutamate antiporter system x(c)(-) in MS provides a link between inflammation and excitotoxicity in demyelinating diseases.

Pravastatin inhibits cell proliferation and increased MAT1A expression in hepatocarcinoma cells and in vivo models

Background: Statins may have therapeutic effects on hepatocarcinoma (HCC). This type of disorder is the most common malignant primary tumour in the liver. Our objective was to determine whether pravastatin had a therapeutic effect in vitro and in vivo models. Method: We design in vitro and in vivo model. In vitro we used PLC and determine cell proliferation. In vivo, we used and animal model to determined, PCNA and MAT1A expression and transaminases levels. Results: We found that pravastatin decreases cell proliferation in vitro (cell proliferation in pravastatin group was 82%, in sorafenib group 51% and in combined group 40%) and in vivo (in pravastatin group 80%, in sorafenib group 76.4% and in combined group 72.72%). The MAT1A levels, was significantly higher in Pravastatin group (D 62%, P 94%, S 71%, P + S 91%). The transaminases levels, decreased significantly in Pravastatin group (GOT and GPT levels D 619.5 U/L; 271 U/L) (P 117.5 U/L; 43.5 U/L) (S 147 U/L; 59 U/L) (P + S 142 U/L; 59 U/L). Conclusion: The combination of pravastatin + sorafenib were more effective than Sorafenib alone.

La gestión empresarial como factor clave de desarrollo de las spin-offs universitarias. Análisis organizativo y financiero

[ES] En las últimas décadas el número de spin-offs universitarias creadas en el Sistema Universitario Español ha aumentado considerablemente; sin embargo, estas empresas tienen que hacer frente a problemas como la falta de financiación o de capacidades empresariales por parte de los fundadores. A partir de los datos extraídos de una encuesta a 72 spin-offs creadas en España, tratamos de detectar y analizar cuáles son los problemas más habituales con los que se encuentran estas empresas, y proponemos posibles vías de solución.

A Passage to India: from novel to film. Some problems of "translation"

Eguíluz, Federico; Merino, Raquel; Olsen, Vickie; Pajares, Eterio; Santamaría, José Miguel (eds.)

Increased opioid dependence in a mouse model of panic disorder

[EN] Panic disorder is a highly prevalent neuropsychiatric disorder that shows co-occurrence with substance abuse. Here, we demonstrate that TrkC, the high-affinity receptor for neurotrophin-3, is a key molecule involved in panic disorder and opiate dependence, using a transgenic mouse model (TgNTRK3). Constitutive TrkC overexpression in TgNTRK3 mice dramatically alters spontaneous firing rates of locus coeruleus (LC) neurons and the response of the noradrenergic system to chronic opiate exposure, possibly related to the altered regulation of neurotrophic peptides observed. Notably, TgNTRK3 LC neurons showed an increased firing rate in saline-treated conditions and profound abnormalities in their response to met5-enkephalin. Behaviorally, chronic morphine administration induced a significantly increased withdrawal syndrome in TgNTRK3 mice. In conclusion, we show here that the NT-3/TrkC system is an important regulator of neuronal firing in LC and could contribute to the adaptations of the noradrenergic system in response to chronic opiate exposure. Moreover, our results indicate that TrkC is involved in the molecular and cellular changes in noradrenergic neurons underlying both panic attacks and opiate dependence and support a functional endogenous opioid deficit in panic disorder patients.

Increased physical activity is not enough to recover astrocytic population from dark-rearing. Synergy with multisensory enrichment is required

10 p.

Role of G protein coupled inwardly rectifier K+ channels (GIRK) on the neurobiology depression

353 págs.

Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

Problems when generating virtual models representing real objects: Hondarribia walls

[EN] This paper is based in the following project:

Climate Change, Responsibilities, and Defeatism and Complacency

16 p.

A common axiom for classical division rules for claims problems

In this paper we introduce a new axiom, denoted claims separability, that is satisfied by several classical division rules defined for claims problems. We characterize axiomatically the entire family of division rules that satisfy this new axiom. In addition, employing claims separability, we characterize the minimal overlap rule, given by O'Neill (1982), Piniles rule and the rules in the TAL-family, introduced by Moreno-Ternero and Villar (2006), which includes the uniform gains rule, the uniform losses rule and the Talmud rule.

Simulación del robot Delta mediante MATLAB

[ES]El presente Trabajo Fin de Grado: SIMULACIÓN DEL ROBOT DELTA MEDIANTE MATLAB trata sobre el robot Delta. El objetivo principal del trabajo es servir de base para futuros proyectos. Incluye información sobre los robots Delta, así como de sus aplicaciones. Este tipo de robots tienen numerosas aplicaciones y beneficios gracias a las numerosas características favorables que se mencionan a lo largo del trabajo, como lo es por ejemplo la gran velocidad a la que se puede mover. En el trabajo se verán las resoluciones de los problemas cinemáticos: directo e inverso. Además, se podrán describir trayectorias tomando como base los anteriores problemas cinemáticos. Finalmente, es especialmente interesante la introducción de los interpoladores en la generación de trayectorias y los beneficios que ello trae consigo.

On the optimal usage of labelled examples in semi-supervised multi-class classification problems

In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.