Estudi del model de representació XML/RDF

L'objectiu fonamental d'aquest treball és estudiar les relacions que hi ha a nivell teòric entre XML (eXtensible Markup Language) i RDF (Resource Description Language).

Anàlisi de Requeriments per un Model de Xarxa de Telecomunicacions amb aplicació des d'un Sistema d'Informació Geogràfica

La idea principal és crear un model d'una xarxa de telecomunicacions gestionable des d'un programari d'informació geogràfica (GIS). Es tracta de dissenyar una xarxa simple de fibra òptica similar a les que es fan per a la connexió directa de clients amb aquesta tecnologia.

Estudi del model dinàmic d’un robot submarí d’intervenció (IAUV) composat per un vehicle i un braç manipulador

Fins a la data d’avui, el grup VICOROB de la Universitat de Girona ha desenvolupat diversos vehicles autònoms (GARBÍ, URIS i ICTINEU). El projecte que comença aquest any té com objectiu desenvolupar un nou vehicle submarí autònom amb capacitat d’intervenció (I-AUV) gràcies a un braç manipulador. Aquest projecte final de carrera té com objectiu desenvolupar en entorn MATLAB un simulador d’un I-AUV, format per un AUV i un braç manipulador de n graus de llibertat per tal d’avaluar les reaccions dels moviments del braç, amb càrrega i sense, sobre el robot, iviceversa

The neurobiological basis of prefrontal cortex impairment in the phencyclidine model of schizophrenia : convergent reduction of synaptic glutamate release, energy metabolism and cognitive performance

RÉSUMÉ : Le traitement répété à la phencyclidine (PCP), un bloqueur du récepteur NMDA (NMDAR), reproduit chez les rongeurs une partie de la symptomatologie typique de la schizophrénie. Le blocage prolongé du NMDAR par la PCP mime une hypofunction du NMDAR, une des principales altérations supposées exister dans les cerveaux des patients schizophréniques. Le but de notre étude était d'examiner les conséquences neurochimiques, métaboliques et fonctionnelles du traitement répété à la phencyclidine in vivo, au niveau du cortex préfrontal (cpf), une région cérébrale qui joue un rôle dans les déficits cognitifs observés chez les patients schizophréniques. Pour répondre à cette question, les rats ou les souris ont reçu chaque jour une injection soit de PCP (5 mg/kg), soit de solution saline, pendant 7 ou 14 jours. Les animaux ont ensuite été sacrifiés au moins 24 heures après le dernier traitement. Des tranches aiguës du cpf ont été préparées rapidement, puis stimulées avec une concentration élevée de KCI, de manière à induire une libération de glutamate à partir des terminaisons synaptiques excitatrices. Les résultats montrent que les tranches du cpf des animaux traités à la PCP ont libéré une quantité de glutamate significativement inférieure par rapport à celles des animaux contrôle. Ce déficit de libération a persisté 72 heures après la fin du traitement, tandis qu'il n'était pas observé dans le cortex visuel primaire, une autre région corticale. En outre, le traitement avec des antipsychotiques, l'halopéridol ou l'olanzapine, a supprimé le déficit induit par la PCP. Le même déficit de libération a été remarqué sur des synaptosomes obtenus à partir du cpf des animaux traités à la phenryclidine. Cette observation indique que la PCP induit une modification plastique adaptative du mécanisme qui contrôle la libération du glutamate dans les terminaisons synaptiques. Nous avons découvert que cette modification implique la sous-régulation d'un NMDAR présynaptique, qui serait doué d'un rôle d'autorécepteur stimulateur de la libération du glutamate. Grâce à des tests comportementaux conduits en parallèle et réalisés pour évaluer la fonctionnalité du cpf, nous avons observé chez les souris traitées à la PCP une flexibilité comportementale réduite lors d'un test de discrimination de stimuli visuels/tactiles. Le déficit cognitif était encore présent 4 jours après la dernière administration de PCP. La technique de l'autoradiographie quantitative du [14C]2-deoxyglucose a permis d'associer ce déficit à une réduction de l'activité métabolique cérébrale pendant le déroulement du test, particulièrement au niveau du cpf. Dans l'ensemble, nos résultats suggèrent que le blocage prolongé du NMDAR lors de l'administration répétée de PCP produit un déficit de libération du glutamate au niveau des terminaisons synaptiques excitatrices du cpf. Un tel déficit pourrait être provoqué par la sousrégulation d'un NMDAR présynaptique, qui aurait une fonction de stimulateur de libération; la transmission excitatrice du cpf s'en trouverait dans ce cas réduite. Ce résultat est en ligne avec l'activité métabolique et fonctionnelle réduite du cpf et l'observation de déficits cognitifs induits lors de l'administration de la PCP. ABSTRACT : Sub-chronic treatment with phencyclidine (PCP), an NMDA receptor (NMDAR) channel blocker, reproduces in rodents part of the symptomatology associated to schizophrenia in humans. Prolonged pharmacological blockade of NMDAR with PCP mimics NMDAR hypofunction, one of the main alterations thought to take place in the brains of schizophrenics. Our study was aimed at investigating the neurochemical, metabolic and behavioral consequences of repeated PCP administration in vivo, focusing on the functioning of the prefrontal cortex (pfc), a brain region highly relevant for the cognitive deficits observed in schizophrenic patients. Rats or mice received a daily administration of either PCP (5 mg/kg) or saline for 7 or 14 days. At least 24 hours after the last treatment the animals were sacrificed. Acute slices of the pfc were quickly prepared and challenged with high KCl to induce synaptic glutamate release. Pfc slices from PCP-treated animals released significantly less glutamate than slices from salinetreated animals. The deficit persisted 72 hours after the end of the treatment, while it was not observed in another cortical region: the primary visual cortex. Interestingly, treatment with antipsychotic drugs, either haloperidol or olanzapine, reverted the glutamate release defect induced by PCP treatment. The same release defect was observed in synaptosomes prepared from the pfc of PCP-treated animals, indicating that PCP induces a plastic adaptive change in the mechanism controlling glutamate release in the glutamatergic terminals. We discovered that such change most likely involves the down-regulation of a newly identified, pre-synaptic NMDAR with stimulatory auto-receptor function on glutamate release. In parallel sets of behavioral experiments challenging pfc function, mice sub-chronically treated with PCP displayed reduced behavioral flexibility (reversal learning) in a visual/tactile-cued discrimination task. The cognitive deficit was still evident 4 days after the last PCP administration and was associated to reduced brain metabolic activity during the performance of the behavioral task, notably in the pfc, as determined by [14C]2-deoxyglucose quantitative autoradiography. Clverall, our findings suggest that prolonged NMDAR blockade by repeated PCP administration results in a defect of glutamate release from excitatory afferents in the pfc, possibly ascribed to down-regulation of apre-synaptic stimulatory NMDAR. Deficient excitatory neurotransmission in the pfc is consistent with the reduced metabolic and functional activation of this area and the observed PCP-induced cognitive deficits.

Malignant pleural mesothelioma: leukocyte recruitment is not required for drug delivery induced by photodynamic therapy in a human xenograft model

Objective: The pre-treatment of tumor neo-vessels by photodynamic therapy (PDT) was shown to improve the distribution of chemotherapy administered subsequently. However, the precise mechanism by which PDT modifies the tumor vasculature is unknown. We have recently shown that leukocyteendothelial cell interaction was essential for PDT induced drug delivery to normal tissue. Our purpose was to determine if PDT could enhance drug distribution in malignant mesothelioma and if a comparable role for leucocytes existed.Methods: We grew human mesothelioma xenografts (H-meso-1) in the dorsal skinfold chambers of nude mice (n = 28). The rolling, sticking and recruitment of leucocytes was assessed in tumor and normal vessels following PDT (Visudyne 0?4 mg/kg, fluence rate 200 mW/cm2, fluence 60 J/cm2) using intravital microscopy. In parallel, the distribution of a macromolecule (FITC dextran, 2000 kDa) administered after PDT was determined. We compared these variables in control (no PDT), PDT + IgG (non specific antibody) and PDT + pan-selectin antibody (monoclonal P-E-L selectin antibody).Results: PDT significantly enhanced the distribution of FITC dextran in mesothelioma xenografts compared to controls. Interestingly, PDT enhanced the leukocyte-endothelial interaction significantly (rolling and recruitment)in tumor and surrounding normal vessels compared to controls. Leukocyte recruitment was significantly down-regulated by pan-selectin antibodies in tumor tissues. However, the suppression of leucocyte recruitement did not affect the extravasation of FITC-dextran in tumor tissue.Conclusion:PDTpre-treatment of the mesothelioma vasculature can enhance the distribution of macromolecular drugs administered subsequently. However, unlike normal vessels, leukocyte-endothelial cell interaction is not required for PDT induced leakage.

Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Parallel scheduling of multiclass M/M/m queues: Approximate and heavy-traffic optimization of achievable performance

We address the problem of scheduling a multiclass $M/M/m$ queue with Bernoulli feedback on $m$ parallel servers to minimize time-average linear holding costs. We analyze the performance of a heuristic priority-index rule, which extends Klimov's optimal solution to the single-server case: servers select preemptively customers with larger Klimov indices. We present closed-form suboptimality bounds (approximate optimality) for Klimov's rule, which imply that its suboptimality gap is uniformly bounded above with respect to (i) external arrival rates, as long as they stay within system capacity;and (ii) the number of servers. It follows that its relativesuboptimality gap vanishes in a heavy-traffic limit, as external arrival rates approach system capacity (heavy-traffic optimality). We obtain simpler expressions for the special no-feedback case, where the heuristic reduces to the classical $c \mu$ rule. Our analysis is based on comparing the expected cost of Klimov's ruleto the value of a strong linear programming (LP) relaxation of the system's region of achievable performance of mean queue lengths. In order to obtain this relaxation, we derive and exploit a new set ofwork decomposition laws for the parallel-server system. We further report on the results of a computational study on the quality of the $c \mu$ rule for parallel scheduling.

Concepts of metastasis in flux: the stromal progression model.

The ability of tumor cells to leave a primary tumor, to disseminate through the body, and to ultimately seed new secondary tumors is universally agreed to be the basis for metastasis formation. An accurate description of the cellular and molecular mechanisms that underlie this multistep process would greatly facilitate the rational development of therapies that effectively allow metastatic disease to be controlled and treated. A number of disparate and sometimes conflicting hypotheses and models have been suggested to explain various aspects of the process, and no single concept explains the mechanism of metastasis in its entirety or encompasses all observations and experimental findings. The exciting progress made in metastasis research in recent years has refined existing ideas, as well as giving rise to new ones. In this review we survey some of the main theories that currently exist in the field, and show that significant convergence is emerging, allowing a synthesis of several models to give a more comprehensive overview of the process of metastasis. As a result we postulate a stromal progression model of metastasis. In this model, progressive modification of the tumor microenvironment is equally as important as genetic and epigenetic changes in tumor cells during primary tumor progression. Mutual regulatory interactions between stroma and tumor cells modify the stemness of the cells that drive tumor growth, in a manner that involves epithelial-mesenchymal and mesenchymal-epithelial-like transitions. Similar interactions need to be recapitulated at secondary sites for metastases to grow. Early disseminating tumor cells can progress at the secondary site in parallel to the primary tumor, both in terms of genetic changes, as well as progressive development of a metastatic stroma. Although this model brings together many ideas in the field, there remain nevertheless a number of major open questions, underscoring the need for further research to fully understand metastasis, and thereby identify new and effective ways of treating metastatic disease.

Hybrid consumption paths in the attribute space: A model and application with scanner data

This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.

On the throughput-WIP trade-off in queueing systems, diminishing returns and the threshold property: A linear programming approach

We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

Revenue management under general discrete choice model of consumer behavior

Customer choice behavior, such as 'buy-up' and 'buy-down', is an importantphe-nomenon in a wide range of industries. Yet there are few models ormethodologies available to exploit this phenomenon within yield managementsystems. We make some progress on filling this void. Specifically, wedevelop a model of yield management in which the buyers' behavior ismodeled explicitly using a multi-nomial logit model of demand. Thecontrol problem is to decide which subset of fare classes to offer ateach point in time. The set of open fare classes then affects the purchaseprobabilities for each class. We formulate a dynamic program todetermine the optimal control policy and show that it reduces to a dynamicnested allocation policy. Thus, the optimal choice-based policy caneasily be implemented in reservation systems that use nested allocationcontrols. We also develop an estimation procedure for our model based onthe expectation-maximization (EM) method that jointly estimates arrivalrates and choice model parameters when no-purchase outcomes areunobservable. Numerical results show that this combined optimization-estimation approach may significantly improve revenue performancerelative to traditional leg-based models that do not account for choicebehavior.

Risk management under a two-factor model of the term structure of interest rates

This paper presents several applications to interest rate risk managementbased on a two-factor continuous-time model of the term structure of interestrates previously presented in Moreno (1996). This model assumes that defaultfree discount bond prices are determined by the time to maturity and twofactors, the long-term interest rate and the spread (difference between thelong-term rate and the short-term (instantaneous) riskless rate). Several newmeasures of ``generalized duration" are presented and applied in differentsituations in order to manage market risk and yield curve risk. By means ofthese measures, we are able to compute the hedging ratios that allows us toimmunize a bond portfolio by means of options on bonds. Focusing on thehedging problem, it is shown that these new measures allow us to immunize abond portfolio against changes (parallel and/or in the slope) in the yieldcurve. Finally, a proposal of solution of the limitations of conventionalduration by means of these new measures is presented and illustratednumerically.

Photodynamic therapy enhances lipodoxorubcin distribution in sarcoma lung metastasis by lowering tumor interstitial fluid pressure in a rodent model

Objective: The management of sarcoma metastasis by systemic chemotherapy is often unsatisfactory. This has paradoxally been attributed to the leakiness of tumor neovessels which induce high intratumor interstitial fluid pressure (IFP) and limit convection forces that are important for drug distribution. In a rodent model, we have recently shown that photodynamic (PDT) pre treatment of lung metastasis could enhance their uptake of chemotherapy. We hypothesized that PDT transiently decreases tumor IFP which enhances convection and promotes drug distribution.Methods: Sarcoma tumors were generated sub-pleurally in the lungs of 12 rats. Animals were randomized at 10 days into i. no pre-treatment (control) and ii. low dose PDT pre-treatment (0・0625 mg/kg Visudyne, 10J/cm2 and 35 mW/cm2) followed by intravenous Liposomal doxorubicin (LiporubicinTM) administration. Using the wick-in-needle technique, we determined tumor and normal tissue IFP before, during and after PDT. In parallel, the uptake of LiporubicinTM was determined by high performance liquid chromatography in tumor and lung tissues.Results: Tumor IFP was significantly higher than normal tissue IFP in all animals. PDT pre-treatment did not affect normal tissue IFP but caused a significant decrease in tumor IFP (mean decrease by 2+/− 1mmHg) which lasted an average of 30 minutes before reaching baseline values. Tumor but not normal lung tissue LiporubicinTM uptake was significantly increased by 67% with PDT pre-treatment when liporubicin was allowed to circulate for one hour.Conclusion: Photodynamic therapy pre-treatment enhances LiporubicinTM uptake in sarcoma lung metastasis by transiently decreasing tumor IFP. These PDT conditions seem to specifically modulate tumor neovessels but not normal lung vessels.