Virtualización de red basada en L2PNV para OpenStack

[ES]Este proyecto consiste en obtener un mayor control por parte del usuario a nivel de red en entornos con máquinas virtuales creadas a partir de la plataforma OpenStack. Cada vez que se arranca o inicia una máquina virtual en OpenStack, los parámetros de red se asignan por defecto, haciendo muy difícil su gestión y control tanto para investigación como para mantenimiento. Si estos parámetros siguieran un mismo patrón para cada proyecto o usuario sería mucho más sencillo tener controlado cada interfaz de red, pudiendo así gestionarlos de una manera más eficiente. Para realizar esta tarea será necesario introducir unos cambios en el código fuente de OpenStack, adaptándolo para que cumpla con nuestros requerimientos.

Scenario Cluster Lagrangian Decomposition in two stage stochastic mixed 0-1 optimization

In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian dual via solving scenario submodels once the nonanticipativity constraints have been dualized. Instead of considering a splitting variable representation over the set of scenarios, we propose to decompose the model into a set of scenario clusters. We compare the computational performance of the four Lagrange multiplier updating procedures, namely the Subgradient Method, the Volume Algorithm, the Progressive Hedging Algorithm and the Dynamic Constrained Cutting Plane scheme for different numbers of scenario clusters and different dimensions of the original problem. Our computational experience shows that the CLD bound and its computational effort depend on the number of scenario clusters to consider. In any case, our results show that the CLD procedures outperform the traditional LD scheme for single scenarios both in the quality of the bounds and computational effort. All the procedures have been implemented in a C++ experimental code. A broad computational experience is reported on a test of randomly generated instances by using the MIP solvers COIN-OR and CPLEX for the auxiliary mixed 0-1 cluster submodels, this last solver within the open source engine COIN-OR. We also give computational evidence of the model tightening effect that the preprocessing techniques, cut generation and appending and parallel computing tools have in stochastic integer optimization. Finally, we have observed that the plain use of both solvers does not provide the optimal solution of the instances included in the testbed with which we have experimented but for two toy instances in affordable elapsed time. On the other hand the proposed procedures provide strong lower bounds (or the same solution value) in a considerably shorter elapsed time for the quasi-optimal solution obtained by other means for the original stochastic problem.

Candida albicans Increases Tumor Cell Adhesion to Endothelial Cells In Vitro: Intraspecific Differences and Importance of the Mannose Receptor

The dimorphic fungus Candida albicans is able to trigger a cytokine-mediated pro-inflammatory response that increases tumor cell adhesion to hepatic endothelium and metastasis. To check the intraspecific differences in this effect, we used an in vitro murine model of hepatic response against C. albicans, which made clear that tumor cells adhered more to endothelium incubated with blastoconidia, both live and killed, than germ tubes. This finding was related to the higher carbohydrate/protein ratio found in blastoconidia. In fact, destruction of mannose ligand residues on the cell surface by metaperiodate treatment significantly reduced tumor cell adhesion induced. Moreover, we also noticed that the effect of clinical strains was greater than that of the reference one. This finding could not be explained by the carbohydrate/protein data, but to explain these differences between strains, we analyzed the expression level of ten genes (ADH1, APE3, IDH2, ENO1, FBA1, ILV5, PDI1, PGK1, QCR2 and TUF1) that code for the proteins identified previously in a mannoprotein-enriched pro-metastatic fraction of C. albicans. The results corroborated that their expression was higher in clinical strains than the reference one. To confirm the importance of the mannoprotein fraction, we also demonstrate that blocking the mannose receptor decreases the effect of C. albicans and its mannoproteins, inhibiting IL-18 synthesis and tumor cell adhesion increase by around 60%. These findings could be the first step towards a new treatment for solid organ cancers based on the role of the mannose receptor in C. albicans-induced tumor progression and metastasis.

Code-switching, Metalinguistics, and Translation in a Bilingual/Bicultural Novel: Sandra Cisneros' Caramelo or Puro Cuento

Raquel Merino Álvarez, José Miguel Santamaría, Eterio Pajares (eds.)

Optimisation of the first principle code Octopus for massive parallel architectures: application to light harvesting complexes

150 p.

PIM-SM extension for Source-Specific Multicast through non multicast networks

Barneko ikerkuntza-txostena