Z2Z4-additive cyclic codes, generator polynomials and dual codes

A ${\mathbb{Z}}_2{\mathbb{Z}}_4$-additive code ${\cal C}\subseteq{\mathbb{Z}}_2^\alpha\times{\mathbb{Z}}_4^\beta$ is called cyclic if the set of coordinates can be partitioned into two subsets, the set of ${\mathbb{Z}}_2$ and the set of ${\mathbb{Z}}_4$ coordinates, such that any cyclic shift of the coordinates of both subsets leaves the code invariant. These codes can be identified as submodules of the $\mathbb{Z}_4[x]$-module $\mathbb{Z}_2[x]/(x^\alpha-1)\times\mathbb{Z}_4[x]/(x^\beta-1)$. The parameters of a ${\mathbb{Z}}_2{\mathbb{Z}}_4$-additive cyclic code are stated in terms of the degrees of the generator polynomials of the code. The generator polynomials of the dual code of a ${\mathbb{Z}}_2{\mathbb{Z}}_4$-additive cyclic code are determined in terms of the generator polynomials of the code ${\cal C}$

El desarrollo de un esquema para caracterizar la competencia docente "mirar con sentido" el pensamiento matemático de los estudiantes

La competencia docente del maestro "mirar con sentido" el pensamiento matemático de los estudiantes implica identificar los hechos relevantes e interpretarlos para dotarlos de significado y poder tomar decisiones de acción. Este estudio se centra en caracterizar la competencia ?mirar con sentido? el pensamiento matemático de los estudiantes en el dominio específico del razonamiento proporcional. Los análisis realizados han permitido identificar y caracterizar cuatro niveles de desarrollo considerando la manera en la que los estudiantes para maestro identifican e interpretaban aspectos del razonamiento proporcional a partir de las respuestas de estudiantes a problemas proporcionales y no proporcionales

Evolutionary Studies in Business: A Presentation of a New Journal

The Journal of Evolutionary Studies in Business is a new open access journal led by an international interdisciplinary team of scholars located in eight institutions from three continents who wants to attract contributions that help shed light on the new questions, challenges, methodologies and realities, faced by businesses in an evolutionary perspective. The journal calls particularly for review essays that deal with new research topics about business, and provide useful overviews of the key ideas, scholars, and debates about important research topics concerning business and its environment. The strategic areas of interest for submissions from authors are: Management Challenges, Entrepreneurship, Science and Business, Creative Industries, International Business, Business History, and Latin American Businesses. JESB will also publish articles about relevant online resources that contain information of interest to academic scholars and business practitioners

Using a Mahalanobis-like distance to train Radial Basis Neural Networks

Proceeding of: International Work-Conference on Artificial Neural Networks (IWANN 2005)Radial Basis Neural Networks (RBNN) can approximate any regular function and have a faster training phase than other similar neural networks. However, the activation of each neuron depends on the euclidean distance between a pattern and the neuron center. Therefore, the activation function is symmetrical and all attributes are considered equally relevant. This could be solved by altering the metric used in the activation function (i.e. using non-symmetrical metrics). The Mahalanobis distance is such a metric, that takes into account the variability of the attributes and their correlations. However, this distance is computed directly from the variance-covariance matrix and does not consider the accuracy of the learning algorithm. In this paper, we propose to use a generalized euclidean metric, following the Mahalanobis structure, but evolved by a Genetic Algorithm (GA). This GA searches for the distance matrix that minimizes the error produced by a fixed RBNN. Our approach has been tested on two domains and positive results have been observed in both cases

Evolving generalized euclidean distances for training RBNN

In Radial Basis Neural Networks (RBNN), the activation of each neuron depends on the Euclidean distance between a pattern and the neuron center. Such a symmetrical activation assumes that all attributes are equally relevant, which might not be true. Non-symmetrical distances like Mahalanobis can be used. However, this distance is computed directly from the data covariance matrix and therefore the accuracy of the learning algorithm is not taken into account. In this paper, we propose to use a Genetic Algorithm to search for a generalized Euclidean distance matrix, that minimizes the error produced by a RBNN.Publicad

Evolving Generalized Euclidean Distances for Training RBNN

In Radial Basis Neural Networks (RBNN), the activation of each neuron depends on the Euclidean distance between a pattern and the neuron center. Such a symmetrical activation assumes that all attributes are equally relevant, which might not be true. Non-symmetrical distances like Mahalanobis can be used. However, this distance is computed directly from the data covariance matrix and therefore the accuracy of the learning algorithm is not taken into account. In this paper, we propose to use a Genetic Algorithm to search for a generalized Euclidean distance matrix, that minimizes the error produced by a RBNN

On ZprZps-additive cyclic codes

Publicació amb motiu de la 21st Conference on Applications of Computer Algebra (July 20-24, 2015, Kalamata, Greece

New Treatment for psoriasis: therapeutic efficiency in patients and antiinflammatory effect in vitro

Background: Psoriasis is a worldwide chronic inflammatory disease that is increasingly being considered as a systemic disorder. Antioxidant and anti-inflammatory molecules have been revealed as potential adjuvants for traditional therapies.Objectives: To evaluate the antiinflammatory action of selected antioxidant molecules and their beneficial effect as combination therapy in psoriatic patients. Materials & Methods: Thirty-five patients with mild (five), moderate (nine) and severe (twenty one) psoriasis were selected and treated with EP2311454 treatment. PASI, BSA and DLQI assessed the severity of psoriasis and the impact on quality of life. The antiinflammatory effect was tested in IFN-γ stimulated Raw264.7 macrophages that express human PPARG.Results: The combined use in vitro of several EP2311454 components exerts a synergistic inhibitory effect on the expression of the proinflammatory mediators Cox2, Nos2 and Cxcl9. Clinically, more than 80% reduction in DLQI levels is observed after treatment, and 100% of severe patients achieved PASI 75 and significant reduction of BSA levels after 15 days of treatment.Conclusion: EP2311454 treatment, composed by antioxidant molecules, proved to be antiinflammatory in vitro and showed efficacy in patients with mild to severe psoriasis, as demonstrated by a significant decrease in PASI, BSA and DLQI levels

Conceptual design of the EU-DEMO dual coolant lithium lead equatorial module

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Within the framework of EUROfusion Program, the Dual Coolant Lithium Lead (DCLL) is one of the four EU breeder blanket concepts that are being investigated as candidates for DEMO. DCLL uses PbLi as the main coolant, tritium breeder, tritium carrier, and neutron multiplier. The main structures, including the first wall, are cooled with helium. The EU program proposed for the next years will consider a DCLL version limited to 550 °C in order to allow the use of conventional materials and technologies. During the first year of EUROfusion activities, a draft design of the DCLL has been proposed. The main blanket performances were adapted to the new specifications and the CAD model of DEMO. The breeder zone has been toroidally divided into four parallel PbLi circuits, separated through stiffening grid radial walls. The PbLi flow routing has been designed to maximize the amount of thermal power extracted by flowing PbLi and to avoid the occurrence of reverse flows due to volumetric heating. Thermal hydraulics, magnetohydrodynamic and neutronics calculations have been performed for the first draft design. The new DCLL design employs Eurofer-alumina-Eurofer sandwich as flow channel insert (FCI).Postprint (published version