971 resultados para mathematical modeling
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The dynamics of intracellular Ca²⁺ is driven by random events called Ca²⁺ puffs, in which Ca²⁺ is liberated from intracellular stores. We show that the emergence of Ca²⁺ puffs can be mapped to an escape process. The mean first passage times that correspond to the stochastic fraction of puff periods are computed from a novel master equation and two Fokker-Planck equations. Our results demonstrate that the mathematical modeling of Ca²⁺ puffs has to account for the discrete character of the Ca²⁺ release sites and does not permit a continuous description of the number of open channels.
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Réalisé en cotutelle avec l'École normale supérieure de Cachan – Université Paris-Saclay
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Este trabajo tiene como objetivo la mejora en la validación de la simulación numérica del flujo bifásico característico del transporte de lecho fluido, mediante la formulación y desarrollo de un modelo numérico combinado Volúmenes Finitos - Elementos Finitos. Para ello se simula numéricamente el flujo de mezcla sólido-gas en una Cámara de Lecho Fluido, bajo implementación en código COMSOL, cuyos resultados son mejores comparativamente a un modelo basado en el método de Elementos Discretos implementado en código abierto MFIX. El problema fundamental de la modelización matemática del fenómeno de lecho fluido es la irregularidad del dominio, el acoplamiento de las variables en espacio y tiempo y, la no linealidad. En esta investigación se reformula apropiadamente las ecuaciones conservativas del fenómeno, tales que permitan obtener un problema variacional equivalente y solucionable numéricamente. Entonces; se define una ecuación de estado en función de la presión hidrodinámica y la fracción volumétrica de sólidos, quedando desacoplado el sistema en tres sub-problemas, garantizando así la existencia de solución del problema general. Una vez aproximados numéricamente ambos modelos, se comparan los resultados de donde se observa que el modelo materia del presente artículo, verifica de forma más eficaz las condiciones de mezcla óptima, reflejada en la calidad del burbujeo y velocidad de mezcla.
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This study proposes to do a study on the mathematical modeling of permeation of films based on chitosan. To conduct the study were obtained membranes with various compositions: a virtually pure membrane-based chitosan; one of chitosan associated with poly (ethylene oxide (PEO). The membranes of pure chitosan were treated with plasma in atmospheres of oxygen, argon and methane. The various types of films were characterized as to its permeation regarding sufamerazina sodium. In the process of mathematical modeling were compared the standard method of obtaining the coefficient of permeation recital straight down the slope of the plot obtained by extinction / time with a the integration process of numerical permeability rate will be calculated from the spectroscopy UV
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Modeling transport of particulate suspensions in porous media is essential for understanding various processes of industrial and scientific interest. During these processes, particles are retained due to mechanisms like size exclusion (straining), adsorption, sedimentation and diffusion. In this thesis, a mathematical model is proposed and analytical solutions are obtained. The obtained analytic solutions for the proposed model, which takes pore and particle size distributions into account, were applied to predict the particle retention, pore blocking and permeability reduction during dead-end microfiltration in membranes. Various scenarios, considering different particle and pore size distributions were studied. The obtained results showed that pore blocking and permeability reduction are highly influenced by the initial pore and particle size distributions. This feature was observed even when different initial pore and particle size distributions with the same average pore size and injected particle size were considered. Finally, a mathematical model for predicting equivalent permeability in porous media during particle retention (and pore blocking) is proposed and the obtained solutions were applied to study permeability decline in different scenarios
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Objective: To compare the effects of biliopancreatic diversion (BPD) and laparoscopic gastric banding (LAGB) on insulin sensitivity and secretion with the effects of laparoscopic gastric plication (P). Methods: A total of 52 obese women (age 30-66 years) suffering from type 2 diabetes mellitus (T2DM) were prospectively recruited into three study groups: 16 BPD; 16 LAGB, and 20 P. Euglycemic clamps and mixed meal tolerance tests were performed before, at 1 month and at 6 months after bariatric surgery. Beta cell function derived from the meal test parameters was evaluated using mathematical modeling. Results: Glucose disposal per kilogram of fat free mass (a marker of peripheral insulin sensitivity) increased significantly in all groups, especially after 1 month. Basal insulin secretion decreased significantly after all three types of operations, with the most marked decrease after BPD compared with P and LAGB. Total insulin secretion decreased significantly only following the BPD. Beta cell glucose sensitivity did not change significantly post-surgery in any of the study groups. Conclusion: We documented similar improvement in insulin sensitivity in obese T2DM women after all three study operations during the 6-month postoperative follow-up. Notably, only BPD led to decreased demand on beta cells (decreased integrated insulin secretion), but without increasing the beta cell glucose sensitivity.
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This is a CoLab Workshop organized as an initiative of the UT Austin | Portugal Program to reinforce the Portuguese competences in Nonlinear Mechanics and in complex problems arising from applications to the mathematical modeling and simulations in the Life Sciences. The Workshop provides a place to exchange recent developments, discoveries and progresses in this challenging research field. The main goal is to bring together doctoral candidates, postdoctoral scientists and graduates interested in the field, giving them the opportunity to make scientific interactions and new connections with established experts in the interdisciplinary topics covered by the event. Another important goal of the Workshop is to promote collaboration between members of the different areas of the UT Austin | Portugal community.
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In this school, we introduced the basis of the mathematical analysis to study
differential equations (ordinary and partial). One aim to prepare students and staff members for more concrete problems arising in mathematical modeling in engineering and biological processes. Theoretical and numerical lectures were given, with a presentation of free scientific computing software using Python.
A website and a drive were created to facilitate exchanges between students, lecturers and organizers:
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We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the mathematical model. Our main conclusion is that mathematical and computational models are good complements for research in social sciences. Indeed, while computational models are extremely useful to extend the scope of the analysis to complex scenarios hard to analyze mathematically, formal models can be useful to verify and to explain the outcomes of computational models.
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The work reported in this paper is motivated by the need to investigate general methods for pattern transformation. A formal definition for pattern transformation is provided and four special cases namely, elementary and geometric transformation based on repositioning all and some agents in the pattern are introduced. The need for a mathematical tool and simulations for visualizing the behavior of a transformation method is highlighted. A mathematical method based on the Moebius transformation is proposed. The transformation method involves discretization of events for planning paths of individual robots in a pattern. Simulations on a particle physics simulator are used to validate the feasibility of the proposed method.
Resumo:
The work reported in this paper is motivated by the need to investigate general methods for pattern transformation. A formal definition for pattern transformation is provided and four special cases namely, elementary and geometric transformation based on repositioning all and some agents in the pattern are introduced. The need for a mathematical tool and simulations for visualizing the behavior of a transformation method is highlighted. A mathematical method based on the Moebius transformation is proposed. The transformation method involves discretization of events for planning paths of individual robots in a pattern. Simulations on a particle physics simulator are used to validate the feasibility of the proposed method.
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A theoretical and numerical framework to model the foundation of marine offshore structures is presented. The theoretical model is composed by a system of partial differential equations describing coupling between seabed solid skeleton and pore fluids (water, air, oil,…) combined with a system of ordinary differential equations describing the specific constitutive relation of the seabed soil skeleton. Once the theoretical model is described, the finite element numerical procedure to achieve an approximate solution of the governing equations is outlined. In order to validate the proposed theoretical and numerical framework the seaward tilt mechanism induced by the action of breaking waves over a vertical breakwater is numerically reproduced. The results numerically attained are in agreement with the main conclusions drawn from the literature associated with this failure mechanism
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Several experimental studies have altered the phase relationship between photic and non-photic environmental, 24 h cycles (zeitgebers) in order to assess their role in the synchronization of circadian rhythms. To assist in the interpretation of the complex activity patterns that emerge from these ""conflicting zeitgeber'' protocols, we present computer simulations of coupled circadian oscillators forced by two independent zeitgebers. This circadian system configuration was first employed by Pittendrigh and Bruce (1959), to model their studies of the light and temperature entrainment of the eclosion oscillator in Drosophila. Whereas most of the recent experiments have restricted conflicting zeitgeber experiments to two experimental conditions, by comparing circadian oscillator phases under two distinct phase relationships between zeitgebers (usually 0 and 12 h), Pittendrigh and Bruce compared eclosion phase under 12 distinct phase relationships, spanning the 24 h interval. Our simulations using non-linear differential equations replicated complex non-linear phenomena, such as ""phase jumps'' and sudden switches in zeitgeber preferences, which had previously been difficult to interpret. Our simulations reveal that these phenomena generally arise when inter-oscillator coupling is high in relation to the zeitgeber strength. Manipulations in the structural symmetry of the model indicated that these results can be expected to apply to a wide range of system configurations. Finally, our studies recommend the use of the complete protocol employed by Pittendrigh and Bruce, because different system configurations can generate similar results when a ""conflicting zeitgeber experiment'' incorporates only two phase relationships between zeitgebers.
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Motivation: Understanding the patterns of association between polymorphisms at different loci in a population ( linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging. Results: We present a more practical method to build GM that describe LD. The method is based on learning weighted Bayesian network structures from haplotype data, extracting equivalence structure classes and using them to model LD. The results obtained in public data from the HapMap database showed that the method is a promising tool for modeling LD. The associations represented by the learned models are correlated with the traditional measure of LD D`. The method was able to represent LD blocks found by standard tools. The granularity of the association blocks and the readability of the models can be controlled in the method. The results suggest that the causality information gained by our method can be useful to tell about the conservability of the genetic markers and to guide the selection of subset of representative markers.
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The objective of this study was to estimate the first-order intrinsic kinetic constant (k(1)) and the liquid-phase mass transfer coefficient (k(c)) in a bench-scale anaerobic sequencing batch biofilm reactor (ASBBR) fed with glucose. A dynamic heterogeneous mathematical model, considering two phases (liquid and solid), was developed through mass balances in the liquid and solid phases. The model was adjusted to experimental data obtained from the ASBBR applied for the treatment of glucose-based synthetic wastewater with approximately 500 mg L-1 of glucose, operating in 8 h batch cycles, at 30 degrees C and 300 rpm. The values of the parameters obtained were 0.8911 min(-1) for k(1) and 0.7644 cm min(-1) for kc. The model was validated utilizing the estimated parameters with data obtained from the ASBBR operating in 3 h batch cycles, with a good representation of the experimental behavior. The solid-phase mass transfer flux was found to be the limiting step of the overall glucose conversion rate.