Projectes de modelatge i simulació avançada de sistemes mitjançant l'entorn ARENA

En l’exercici de les funcions típiques de qualsevol activitat humana, l’home ha de prendre decisions d’un o altre tipus permanentment i aquesta situació porta afegit, per lo general risc i incertesa, el que compromet la qualitat i l’èxit de la decisió. Per ajudar i contrarestar aquesta situació, l’home ha desenvolupat a través del temps una diversitat d’eines que li permeten minimitzar el risc i la incertesa en la presa de decisions. La simulació és una d’aquestes eines. Mitjançant la seva aplicació no només s’aconsegueix la comesa anterior, sinó que també es minimitzen els costos involucrats en la decisió mitjançant un millor ús dels recursos, la disminució del temps emprat per a la seva realització i la minimització de les probabilitats de risc. Aquest projecte representa la continuació d’un primer estudi introductori de la simulació anomenat: Estudi i guia docent per a modelatge i simulació de sistemes mitjançant l’entorn ARENA [9]. Realitzat per l’alumna d’Enginyeria en Organització Industrial de la Universitat de Vic, Montse Carbonell Crosas, l’any 2008 i sota la codirecció del director d’aquest segon projecte, el professor Juli Ordeix Rigo. Aquest nou projecte s’inicia amb una primera part teòrica, continguda dins del primer volum, la qual reforça els conceptes teòrics referents a la simulació amb ARENA, ja vistos en l’anterior projecte. Complementant aquells considerats bàsics i els de més utilitat i finalitza introduint nous conceptes avançats. Els nous capítols de temàtica avançada, junt als primers més bàsics de la primera part són exercitats dins de la segona, formant el segon volum d’aquest projecte. El mateix requereix la participació activa de l’alumne, per tal de realitzar cadascun dels 89 exercicis pràctics que es plantegen i poder onsolidar l’aprenentatge teòric d’aquesta eina avançada de simulació fent consultes als apartats teòrics recomanats dins de cada exercici. La complexitat dels exercicis anirà augmentant gradualment i s’insisteix en seguir la metodologia presentada en el projecte per a realitzar-los tots de forma ordenada i ascendent. L’ alumne quan acabi la part pràctica, haurà consolidat tota la part teòrica i serà capaç d’exercir com analista per tal de generar els seus propis projecte de simulació.

Forward induction and the excess capacity puzzle: An experimental investigation.

While the theoretical industrial organization literature has long argued that excess capacity can be used to deter entry into markets, there is little empirical evidence that incumbent firms effectively behave in this way. Bagwell and Ramey (1996) propose a game with a specific sequence of moves and partially-recoverable capacity costs in which forward induction provides a theoretical rationalization for firm behavior in the field. We conduct an experiment with a game inspired by their work. In our data the incumbent tends to keep the market, in contrast to what the forward induction argument of Bagwell and Ramey would suggest. The results indicate that players perceive that the first mover has an advantage without having to pre-commit capacity. In our game, evolution and learning do not drive out this perception. We back these claims with data analysis, a theoretical framework for dynamics, and simulation results.

Wellposedness of a nonlinear, logarithmic Schrödinger equation of Doebner-Goldin type modeling quantum dissipation

This paper is concerned with the modeling and analysis of quantum dissipation phenomena in the Schrödinger picture. More precisely, we do investigate in detail a dissipative, nonlinear Schrödinger equation somehow accounting for quantum Fokker–Planck effects, and how it is drastically reduced to a simpler logarithmic equation via a nonlinear gauge transformation in such a way that the physics underlying both problems keeps unaltered. From a mathematical viewpoint, this allows for a more achievable analysis regarding the local wellposedness of the initial–boundary value problem. This simplification requires the performance of the polar (modulus–argument) decomposition of the wavefunction, which is rigorously attained (for the first time to the best of our knowledge) under quite reasonable assumptions.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

A protocol describing the genetic correction of somatic human cells and subsequent generation of IPS cell

The generation of patient-specific induced pluripotent stem cells (iPSCPSCPSCs) offers unprecedented opportunities for modeling and treating human disease. In combination with gene therapy, the iPSCPSCPSC technology can be used to generate disease-free progenitor cells of potential interest for autologous cell therapy. We explain a protocol for the reproducible generation of genetically corrected iPSCPSCPSCs starting from the skin biopsies of Fanconi anemia patients using retroviral transduction with OCT4, SOX2 and KLF4. Before reprogramming, the fibroblasts and/or keratinocytes of the patients are genetically corrected with lentiviruses expressing FANCA. The same approach may be used for other diseases susceptible to gene therapy correction. Genetically corrected, characterized lines of patient-specific iPSCPSCPSCs can be obtained in 4–5 months.

Forward induction and the excess capacity puzzle: An experimental investigation

While the theoretical industrial organization literature has long arguedthat excess capacity can be used to deter entry into markets, there islittle empirical evidence that incumbent firms effectively behave in thisway. Bagwell and Ramey (1996) propose a game with a specific sequence ofmoves and partially-recoverable capacity costs in which forward inductionprovides a theoretical rationalization for firm behavior in the field. Weconduct an experiment with a game inspired by their work. In our data theincumbent tends to keep the market, in contrast to what the forwardinduction argument of Bagwell and Ramey would suggest. The results indicatethat players perceive that the first mover has an advantage without havingto pre-commit capacity. In our game, evolution and learning do not driveout this perception. We back these claims with data analysis, atheoretical framework for dynamics, and simulation results.

Evaporation and coarsening dynamics with open boundaries

We present a study of the evaporation dynamics of a substance undergoing a coarsening process. The system is modeled by the Cahn-Hilliard equation with absorbing boundaries. We have found that the dynamics, although of a diffusive nature, is much slower than the usual one without coarsening. Analytical and simulation results are in reasonable agreement.

Evaporation and coarsening dynamics with open boundaries

We present a study of the evaporation dynamics of a substance undergoing a coarsening process. The system is modeled by the Cahn-Hilliard equation with absorbing boundaries. We have found that the dynamics, although of a diffusive nature, is much slower than the usual one without coarsening. Analytical and simulation results are in reasonable agreement.

Statistical modeling of bowing control applied to violin sound synthesis

Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis paradigmswould benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. Wepresent a framework for modeling bowing control parameters inviolin performance. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing control parameter signals.We model the temporal contour of bow velocity, bow pressing force, and bow-bridge distance as sequences of short Bézier cubic curve segments. Considering different articulations, dynamics, and performance contexts, a number of note classes are defined. Contours of bowing parameters in a performance database are analyzed at note-level by following a predefined grammar that dictates characteristics of curve segment sequences for each of the classes in consideration. As a result, contour analysis of bowing parameters of each note yields an optimal representation vector that is sufficient for reconstructing original contours with significant fidelity. From the resulting representation vectors, we construct a statistical model based on Gaussian mixtures suitable for both the analysis and synthesis of bowing parameter contours. By using the estimated models, synthetic contours can be generated through a bow planning algorithm able to reproduce possible constraints caused by the finite length of the bow. Rendered contours are successfully used in two preliminary synthesis frameworks: digital waveguide-based bowed stringphysical modeling and sample-based spectral-domain synthesis.

Hybrid model of a double-fed induction machine and back-to-back converter

This report details the port interconnection of two subsystems: a power electronics subsystem (a back-to-back AC/AC converter (B2B), coupled to a phase of the power grid), and an electromechanical subsystem (a doubly-fed induction machine (DFIM), coupled mechanically to a flywheel and electrically to the power grid and to a local varying load). Both subsystems have been essentially described in previous reports (deliverables D 0.5 and D 4.3.1), although some previously unpublished details are presented here. The B2B is a variable structure system (VSS), due to the presence of control-actuated switches: however from a modelling and simulation, as well as a control-design, point of view, it is sensible to consider modulated transformers (MTF in the bond-graph language) instead of the pairs of complementary switches. The port-Hamiltonian models of both subsystems are presents and coupled through a power-preserving interconnection, and the Hamiltonian description of the whole system is obtained; detailed bond-graphs of all the subsystems and the complete system are provided.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

Comparison of a deterministic and a data driven model to describe MBR fouling

Membrane bioreactors (MBRs) are a combination of activated sludge bioreactors and membrane filtration, enabling high quality effluent with a small footprint. However, they can be beset by fouling, which causes an increase in transmembrane pressure (TMP). Modelling and simulation of changes in TMP could be useful to describe fouling through the identification of the most relevant operating conditions. Using experimental data from a MBR pilot plant operated for 462days, two different models were developed: a deterministic model using activated sludge model n°2d (ASM2d) for the biological component and a resistance in-series model for the filtration component as well as a data-driven model based on multivariable regressions. Once validated, these models were used to describe membrane fouling (as changes in TMP over time) under different operating conditions. The deterministic model performed better at higher temperatures (>20°C), constant operating conditions (DO set-point, membrane air-flow, pH and ORP), and high mixed liquor suspended solids (>6.9gL-1) and flux changes. At low pH (<7) or periods with higher pH changes, the data-driven model was more accurate. Changes in the DO set-point of the aerobic reactor that affected the TMP were also better described by the data-driven model. By combining the use of both models, a better description of fouling can be achieved under different operating conditions