Avalanche dynamics of fiber bundle models

We present a detailed analytical and numerical study of the avalanche distributions of the continuous damage fiber bundle model CDFBM . Linearly elastic fibers undergo a series of partial failure events which give rise to a gradual degradation of their stiffness. We show that the model reproduces a wide range of mechanical behaviors. We find that macroscopic hardening and plastic responses are characterized by avalanche distributions, which exhibit an algebraic decay with exponents between 5/2 and 2 different from those observed in mean-field fiber bundle models. We also derive analytically the phase diagram of a family of CDFBM which covers a large variety of potential avalanche size distributions. Our results provide a unified view of the statistics of breaking avalanches in fiber bundle models

Critical ruptures in a bundle of slowly relaxing fibers

We study the damage enhanced creep rupture of disordered materials by means of a fiber bundle model. Broken fibers undergo a slow stress relaxation modeled by a Maxwell element whose stress exponent m can vary in a broad range. Under global load sharing we show that due to the strength disorder of fibers, the lifetime ʧ of the bundle has sample-to-sample fluctuations characterized by a log-normal distribution independent of the type of disorder. We determine the Monkman-Grant relation of the model and establish a relation between the rupture life tʄ and the characteristic time tm of the intermediate creep regime of the bundle where the minimum strain rate is reached, making possible reliable estimates of ʧ from short term measurements. Approaching macroscopic failure, the deformation rate has a finite time power law singularity whose exponent is a decreasing function of m. On the microlevel the distribution of waiting times is found to have a power law behavior with m-dependent exponents different below and above the critical load of the bundle. Approaching the critical load from above, the cutoff value of the distributions has a power law divergence whose exponent coincides with the stress exponent of Maxwell elements

Driven fragmentation of granular gases

The dynamics of homogeneously heated granular gases which fragment due to particle collisions is analyzed. We introduce a kinetic model which accounts for correlations induced at the grain collisions and analyze both the kinetics and relevant distribution functions these systems develop. The work combines analytical and numerical studies based on direct simulation Monte Carlo calculations. A broad family of fragmentation probabilities is considered, and its implications for the system kinetics are discussed. We show that generically these driven materials evolve asymptotically into a dynamical scaling regime. If the fragmentation probability tends to a constant, the grain number diverges at a finite time, leading to a shattering singularity. If the fragmentation probability vanishes, then the number of grains grows monotonously as a power law. We consider different homogeneous thermostats and show that the kinetics of these systems depends weakly on both the grain inelasticity and driving. We observe that fragmentation plays a relevant role in the shape of the velocity distribution of the particles. When the fragmentation is driven by local stochastic events, the longvelocity tail is essentially exponential independently of the heating frequency and the breaking rule. However, for a Lowe-Andersen thermostat, numerical evidence strongly supports the conjecture that the scaled velocity distribution follows a generalized exponential behavior f (c)~exp (−cⁿ), with n ≈1.2, regarding less the fragmentation mechanisms

Role of Particle Shape on the Stress Propagation in Granular Packings

We present an experimental and numerical study on the influence that particle aspect ratio has on the mechanical and structural properties of granular packings. For grains with maximal symmetry (squares), the stress propagation in the packing localizes forming chainlike forces analogous to the ones observed for spherical grains. This scenario can be understood in terms of stochastic models of aggregation and random multiplicative processes. As the grains elongate, the stress propagation is strongly affected. The interparticle normal force distribution tends toward a Gaussian, and, correspondingly, the force chains spread leading to a more uniform stress distribution reminiscent of the hydrostatic profiles known for standard liquids

Avaluació de l’ estat ambiental de la Riera d’Aubi i propostes de millora

Aquest projecte pretén desenvolupar una proposta d’índexs ambientals per a l’avaluació de l’estat ecològic de la riera de l’Aubi; avaluar l’estat ambiental, classificar els diferents trams, identificar els punts crítics i definir les propostes de millora ambiental per a la riera d’Aubi. La riera de l’ Aubi es troba entre els termes municipals de Mont-ras, Palafrugell i Palamós, a les comarques del Baix Empordà i Gironès

Antimicrobial peptide genes in Bacillus strains from plant environments

The presence of the antimicrobial peptide (AMP) biosynthetic genes srfAA (surfactin), bacA (bacylisin), fenD (fengycin), bmyB (bacyllomicin), spaS (subtilin), and ituC (iturin) was examined in 184 isolates of Bacillus spp. obtained from plant environments (aerial, rhizosphere, soil) in the Mediterranean land area of Spain. Most strains had between two and four AMP genes whereas strains with five genes were seldom detected and none of the strains had six genes. The most frequent AMP gene markers were srfAA, bacA, bmyB, and fenD, and the most frequent genotypes srfAA-bacA-bmyB and srfAAbacA-bmyB-fenD. The dominance of these particular genes in Bacillus strains associated with plants reinforces the competitive role of surfactin, bacyllomicin, fengycin, and bacilysin in the fitness of strains in natural environments. The use of these AMP gene markers may assist in the selection of putative biological control agents of plant pathogens

BIMS: Biomedical Information Management System

This final year project presents the design principles and prototype implementation of BIMS (Biomedical Information Management System), a flexible software system which provides an infrastructure to manage all information required by biomedical research projects.The BIMS project was initiated with the motivation to solve several limitations in medical data acquisition of some research projects, in which Universitat Pompeu Fabra takes part. These limitations,based on the lack of control mechanisms to constraint information submitted by clinicians, impact on the data quality, decreasing it.BIMS can easily be adapted to manage information of a wide variety of clinical studies, not being limited to a given clinical specialty. The software can manage both, textual information, like clinical data (measurements, demographics, diagnostics, etc ...), as well as several kinds of medical images (magnetic resonance imaging, computed tomography, etc ...). Moreover, BIMS provides a web - based graphical user interface and is designed to be deployed in a distributed andmultiuser environment. It is built on top of open source software products and frameworks.Specifically, BIMS has been used to represent all clinical data being currently used within the CardioLab platform (an ongoing project managed by Universitat Pompeu Fabra), demonstratingthat it is a solid software system, which could fulfill requirements of a real production environment.

SIIMTA, Sistema Integrat d’Interacció de cos sencer generada en temps real i MusicoTeràpia per a persones amb discapacitats com l’Autisme

L’objectiu d’aquest Projecte Final de Carrera és el poder desenvolupar una nova eina de treball, segons el paradigme de l’interacció a cos sencer, per als terapeutes de la Fundació Tekhnikós, per a poder afavorir nous processos d’expressió, comunicació i interactivitat entre elpacient i el terapeuta en les sessions de Musicoteràpia.El Projecte tracta d’un sistema d’interacció a cos sencer per a pacients amb diferentspatologies o síndromes de conducta. Mitjançant un sistema de captura que treballa en el camp dels infrarojos, el pacient és capaç d’interactuar amb els elements de l’aplicació a través de lagesticulació. El moviment d’aquestes partícules (vegis el Glossari de termes en l’Annexe)generarà diferents sons segons posició i direcció en l’espai de la pantalla motivant al pacient a explorar el comportament el sistema de diferents maneres. Aquests estímuls sonors estan basatsen l’experiència prèvia de la Fundació amb les seves sessions de Musitoràpia, basades enl’observació de les reaccions del pacient davant estímuls sonors. Aquesta eina permetràexperimentat tot un món nou d’estímuls per al pacient, tant sonors, com visuals gràcies a la possibilitat de configuració de molts dels paràmetres del sistema. Gràcies al sistema de visió artifical s’aconsegueix una interacció màquina / pacient a cos sencer no intrusiu, molt interessant tenint en compte que l’aplicació està destinada a un gran espectre de patologies o síndromes. A més tenint en compte la tipologia general del pacient s’haoptat per una estètica molt minimalista, evitant qualsevol referència icònica per tal de no sobre estimular al pacient abans de que pugui interactuar amb el sistema.

La Comprenssió discursiva en la interpretació simultània anglès-espanyol

Aquest treball estudia l'extensió dels discursos meta de diferents intèrprets respecte de l'extensió d'un discurs original, així com les unitats de sentit i altres paràmetres, per tal d'esbrinar si els discursos meta tendeixen a escurçar-se i a esdevenir més econòmics que l'original.

On Certain Greedoid Polyhedra, Partially Indexable Scheduling Problems, and Extended Restless Bandit Allocation Indices

We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid (whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then the problem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.

Drug Utilization Studies and Data Registries in Primary Care.

This article reviews the methodology of the studies on drug utilization with particular emphasis on primary care. Population based studies of drug inappropriateness can be done with microdata from Health Electronic Records and e-prescriptions. Multilevel models estimate the influence of factors affecting the appropriateness of drug prescription at different hierarchical levels: patient, doctor, health care organization and regulatory environment. Work by the GIUMAP suggest that patient characteristics are the most important factor in the appropriateness of prescriptions with significant effects at the general practicioner level.

La voz flamenca del violín

Este proyecto representa una aproximación al flamenco desde la música clásica, y más concretamente desde el punto de vista violinístico. Se trata de una visión personal sobre los elementos técnicos e interpretativos a seguir para adentrarnos en la estilística flamenca. Ampliar los conocimientos musicales para así enriquecernos y crecer, tanto como personas como músicos. De la fusión musical emergen nuevos horizontes con los que poder expresarnos. Esto nos abre las puertas a la creatividad.

The achievable region approach to the optimal control of stochastic systems

The achievable region approach seeks solutions to stochastic optimisation problems by: (i) characterising the space of all possible performances(the achievable region) of the system of interest, and (ii) optimisingthe overall system-wide performance objective over this space. This isradically different from conventional formulations based on dynamicprogramming. The approach is explained with reference to a simpletwo-class queueing system. Powerful new methodologies due to the authorsand co-workers are deployed to analyse a general multiclass queueingsystem with parallel servers and then to develop an approach to optimalload distribution across a network of interconnected stations. Finally,the approach is used for the first time to analyse a class of intensitycontrol problems.

Beyond Smith's rule: An optimal dynamic index, rule for single machine stochastic scheduling with convex holding costs

Most research on single machine scheduling has assumedthe linearity of job holding costs, which is arguablynot appropriate in some applications. This motivates ourstudy of a model for scheduling $n$ classes of stochasticjobs on a single machine, with the objective of minimizingthe total expected holding cost (discounted or undiscounted). We allow general holding cost rates that are separable,nondecreasing and convex on the number of jobs in eachclass. We formulate the problem as a linear program overa certain greedoid polytope, and establish that it issolved optimally by a dynamic (priority) index rule,whichextends the classical Smith's rule (1956) for the linearcase. Unlike Smith's indices, defined for each class, ournew indices are defined for each extended class, consistingof a class and a number of jobs in that class, and yieldan optimal dynamic index rule: work at each time on a jobwhose current extended class has larger index. We furthershow that the indices possess a decomposition property,as they are computed separately for each class, andinterpret them in economic terms as marginal expected cost rate reductions per unit of expected processing time.We establish the results by deploying a methodology recentlyintroduced by us [J. Niño-Mora (1999). "Restless bandits,partial conservation laws, and indexability. "Forthcomingin Advances in Applied Probability Vol. 33 No. 1, 2001],based on the satisfaction by performance measures of partialconservation laws (PCL) (which extend the generalizedconservation laws of Bertsimas and Niño-Mora (1996)):PCL provide a polyhedral framework for establishing theoptimality of index policies with special structure inscheduling problems under admissible objectives, which weapply to the model of concern.

Shared knowledge

Agents use their knowledge on the history of the economy in orderto choose what is the optimal action to take at any given moment of time,but each individual observes history with some noise. This paper showsthat the amount of information available on the past evolution of theeconomy is an endogenous variable, and that this leads to overconcentrationof the investment, which can be interpreted as underinvestment in research.It presents a model in which agents have to invest at each period in one of$K$ sectors, each of them paying an exogenous return that follows a welldefined stochastic path. At any moment of time each agent receives an unbiasednoisy signal on the payoff of each sector. The signals differ across agents,but all of them have the same variance, which depends on the aggregate investmentin that particular sector (so that if almost everybody invests in it theperceptions of everybody will be very accurate, but if almost nobody doesthe perceptions of everybody will be very noisy). The degree of hetereogeneityacross agents is then an endogenous variable, evolving across time determining,and being determined by, the amount of information disclosed.As long as both the level of social interaction and the underlying precisionof the observations are relatively large agents behave in a very preciseway. This behavior is unmodified for a huge range of informational parameters,and it is characterized by an excessive concentration of the investment ina few sectors. Additionally the model shows that generalized improvements in thequality of the information that each agent gets may lead to a worse outcomefor all the agents due to the overconcentration of the investment that thisproduces.