961 resultados para Non-reversible stochastic dynamics


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Résumant mon travail de thèse, l'article qui suit décrit un nouveau modèle animal servant à étudier l'impact combiné d'une ventilation mécanique (VM), d'une oxygénothérapie et d'une inflammation sur des poumons immatures. Cette étude permet, pour la première fois, de mesurer l'expression de gènes à distance d'une VM pour en analyser la cinétique. La VM représente un traitement intégral dans la prise en charge de prématurés. Sauvant des vies, elle est cependant non-physiologique et décrite comme nocive à court et à long terme, empêchant le bon développement pulmonaire. Nombreuses études se sont intéressées à l'impact immédiat de la VM sur les poumons, mais il n'existe à ce jour aucun modèle de rongeur pour en analyser les effets tardifs. Par analogie avec la clinique, nous avons créé un modèle avec un animal dont le stade développemental pulmonaire est comparable aux prématurés humains et consistant en une oxygénothérapie, une VM modérée avec intubation non chirurgicale, similaire à la pratique quotidienne, et un contexte inflammatoire mimant celui de chorioamnionite dans lequel bien des prématurés naissent. Nous avons ensuite réalisé une extubation pour permettre une période de rétablissement, puis fait des analyses et sur le plan structurel par histologie conventionnelle et en 3D, et sur le plan biologique, par analyse de l'expression de gènes et de protéines. Ce travail a permis de valider ce nouveau modèle comme outil de recherche pour réaliser des mesures à distance d'une VM chez des rats nouveau-nés. Comparant ces mesures à celles prises à la fin de la VM, nous observons: une augmentation initiale et transitoire des médiateurs impliqués dans la cascade inflammatoire dont le corrélat histologique est une maladie inflammatoire pulmonaire et, tardivement, une altération plus développementale de la structure pulmonaire avec diminution de l'alvéolarisation. Ceci pourrait être en partie dû à une expression asynchrone de gènes décrits comme importants pour la formation des alvéoles (matrix metalloproteinase 9, elastine). Offrant une nouvelle approche pour la recherche pulmonaire chez les rongeurs, ce modèle servira comme futur outil pour approfondir nos connaissances de la physiopathologie conduisant aux altérations structurelles retrouvées dans les poumons d'anciens prématurés soumis à une VM (dysplasie broncho-pulmonaire), pour tester l'influence de certains traitements (p.ex. surfactant) et pour étudier les effets de la VM en l'appliquant à des modèles transgéniques.

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Résumé: At least since the Great Depression, explaining why there are business fluctuations has been one of the biggest challenges that the science of economics has had to face. The hope is that if we could better understand recessions, then we could also be more successful in overcoming them. This dissertation consists of three papers that are part of the general endeavor of economists to understand these fluctuations. The first paper discusses, for a particular model, whether a result related to fluctuations would still hold if time were modeled as continuous rather than discrete. The two other papers focus on price stickiness. The second paper discusses why, after a large devaluation, prices of non-tradables may change by only a small amount in comparison to the magnitude of the devaluation. The third paper examines price adjustment in a model in which information is imperfect and it is costly to change prices.

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Building and sustaining competitive advantage through the creation of market imperfections is challenging in a constantly changing business environment - particularly since the sources of such advantages are increasingly knowledge-based. Facilitated by improved networks and communication, knowledge spills over to competitors more easily than before,thus creating an appropriability problem: the inability of an innovating firm to utilize its innovations commercially. Consequently, as the importance of intellectual assets increases, their protection also calls for new approaches. Companies have various means of protection at their disposal, and by taking advantage of them they can make intangibles more non-transferable and prevent, or at leastdelay, imitation of their most crucial intellectual assets. However, creating barriers against imitation has another side to it, and the transfer of knowledge in situations requiring knowledge sharing may be unintentionally obstructed. Theaim of this thesis is to increase understanding of how firms can balance knowledge protection and sharing so as to benefit most from their knowledge assets. Thus, knowledge protection is approached through an examination of the appropriability regime of a firm, i.e., the combination of available and effective means ofprotecting innovations, their profitability, and the increased rents due to R&D. A further aim is to provide a broader understanding of the formation and structure of the appropriability regime. The study consists of two parts. The first part introduces the research topic and the overall results of the study, and the second part consists of six complementary research publications covering various appropriability issues. The thesis contributes to the existing literature in several ways. Although there is a wide range of prior research on appropriability issues, a lot of it is restricted either to the study of individual appropriability mechanisms, or to comparing certain features of them. These approaches are combined, and the relevant theoretical concepts are clarified and developed. In addition, the thesis provides empirical evidence of the formation of the appropriability regime, which is consequently presented as an adaptive process. Thus, a framework is provided that better corresponds to the complex reality of the current business environment.

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Although neuroimaging research has evidenced specific responses to visual food stimuli based on their nutritional quality (e.g., energy density, fat content), brain processes underlying portion size selection remain largely unexplored. We identified spatio-temporal brain dynamics in response to meal images varying in portion size during a task of ideal portion selection for prospective lunch intake and expected satiety. Brain responses to meal portions judged by the participants as 'too small', 'ideal' and 'too big' were measured by means of electro-encephalographic (EEG) recordings in 21 normal-weight women. During an early stage of meal viewing (105-145ms), data showed an incremental increase of the head-surface global electric field strength (quantified via global field power; GFP) as portion judgments ranged from 'too small' to 'too big'. Estimations of neural source activity revealed that brain regions underlying this effect were located in the insula, middle frontal gyrus and middle temporal gyrus, and are similar to those reported in previous studies investigating responses to changes in food nutritional content. In contrast, during a later stage (230-270ms), GFP was maximal for the 'ideal' relative to the 'non-ideal' portion sizes. Greater neural source activity to 'ideal' vs. 'non-ideal' portion sizes was observed in the inferior parietal lobule, superior temporal gyrus and mid-posterior cingulate gyrus. Collectively, our results provide evidence that several brain regions involved in attention and adaptive behavior track 'ideal' meal portion sizes as early as 230ms during visual encounter. That is, responses do not show an increase paralleling the amount of food viewed (and, in extension, the amount of reward), but are shaped by regulatory mechanisms.

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We derive a one dimensional formulation of the Planck-Nernst-Poisson equation to describe the dynamics of of a symmetric binary electrolyte in channels whose section is of nanometric section and varies along the axial direction. The approach is in the spirit of the Fick-Jacobs di fusion equation and leads to a system of coupled equations for the partial densities which depends on the charge sitting at the walls in a non trivial fashion. We consider two kinds of non uniformities, those due to the spatial variation of charge distribution and those due to the shape variation of the pore and report one and three-dimensional solutions of the electrokinetic equations.

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ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

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By appealing to renewal theory we determine the equations that the mean exit time of a continuous-time random walk with drift satisfies both when the present coincides with a jump instant or when it does not. Particular attention is paid to the corrections ensuing from the non-Markovian nature of the process. We show that when drift and jumps have the same sign the relevant integral equations can be solved in closed form. The case when holding times have the classical Erlang distribution is considered in detail.

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Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

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The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.

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A rotating machine usually consists of a rotor and bearings that supports it. The nonidealities in these components may excite vibration of the rotating system. The uncontrolled vibrations may lead to excessive wearing of the components of the rotating machine or reduce the process quality. Vibrations may be harmful even when amplitudes are seemingly low, as is usually the case in superharmonic vibration that takes place below the first critical speed of the rotating machine. Superharmonic vibration is excited when the rotational velocity of the machine is a fraction of the natural frequency of the system. In such a situation, a part of the machine’s rotational energy is transformed into vibration energy. The amount of vibration energy should be minimised in the design of rotating machines. The superharmonic vibration phenomena can be studied by analysing the coupled rotor-bearing system employing a multibody simulation approach. This research is focused on the modelling of hydrodynamic journal bearings and rotorbearing systems supported by journal bearings. In particular, the non-idealities affecting the rotor-bearing system and their effect on the superharmonic vibration of the rotating system are analysed. A comparison of computationally efficient journal bearing models is carried out in order to validate one model for further development. The selected bearing model is improved in order to take the waviness of the shaft journal into account. The improved model is implemented and analyzed in a multibody simulation code. A rotor-bearing system that consists of a flexible tube roll, two journal bearings and a supporting structure is analysed employing the multibody simulation technique. The modelled non-idealities are the shell thickness variation in the tube roll and the waviness of the shaft journal in the bearing assembly. Both modelled non-idealities may cause subharmonic resonance in the system. In multibody simulation, the coupled effect of the non-idealities can be captured in the analysis. Additionally one non-ideality is presented that does not excite the vibrations itself but affects the response of the rotorbearing system, namely the waviness of the bearing bushing which is the non-rotating part of the bearing system. The modelled system is verified with measurements performed on a test rig. In the measurements the waviness of bearing bushing was not measured and therefore it’s affect on the response was not verified. In conclusion, the selected modelling approach is an appropriate method when analysing the response of the rotor-bearing system. When comparing the simulated results to the measured ones, the overall agreement between the results is concluded to be good.

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Conservation laws in physics are numerical invariants of the dynamics of a system. In cellular automata (CA), a similar concept has already been defined and studied. To each local pattern of cell states a real value is associated, interpreted as the “energy” (or “mass”, or . . . ) of that pattern.The overall “energy” of a configuration is simply the sum of the energy of the local patterns appearing on different positions in the configuration. We have a conservation law for that energy, if the total energy of each configuration remains constant during the evolution of the CA. For a given conservation law, it is desirable to find microscopic explanations for the dynamics of the conserved energy in terms of flows of energy from one region toward another. Often, it happens that the energy values are from non-negative integers, and are interpreted as the number of “particles” distributed on a configuration. In such cases, it is conjectured that one can always provide a microscopic explanation for the conservation laws by prescribing rules for the local movement of the particles. The onedimensional case has already been solved by Fuk´s and Pivato. We extend this to two-dimensional cellular automata with radius-0,5 neighborhood on the square lattice. We then consider conservation laws in which the energy values are chosen from a commutative group or semigroup. In this case, the class of all conservation laws for a CA form a partially ordered hierarchy. We study the structure of this hierarchy and prove some basic facts about it. Although the local properties of this hierarchy (at least in the group-valued case) are tractable, its global properties turn out to be algorithmically inaccessible. In particular, we prove that it is undecidable whether this hierarchy is trivial (i.e., if the CA has any non-trivial conservation law at all) or unbounded. We point out some interconnections between the structure of this hierarchy and the dynamical properties of the CA. We show that positively expansive CA do not have non-trivial conservation laws. We also investigate a curious relationship between conservation laws and invariant Gibbs measures in reversible and surjective CA. Gibbs measures are known to coincide with the equilibrium states of a lattice system defined in terms of a Hamiltonian. For reversible cellular automata, each conserved quantity may play the role of a Hamiltonian, and provides a Gibbs measure (or a set of Gibbs measures, in case of phase multiplicity) that is invariant. Conversely, every invariant Gibbs measure provides a conservation law for the CA. For surjective CA, the former statement also follows (in a slightly different form) from the variational characterization of the Gibbs measures. For one-dimensional surjective CA, we show that each invariant Gibbs measure provides a conservation law. We also prove that surjective CA almost surely preserve the average information content per cell with respect to any probability measure.

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Background: Insects respond to the spatial and temporal dynamics of a pheromone plume, which implies not only a strong response to"odor on", but also to"odor off". This requires mechanisms geared toward a fast signal termination. Several mechanisms may contribute to signal termination, among which odorant-degrading enzymes. These enzymes putatively play a role in signal dynamics by a rapid inactivation of odorants in the vicinity of the sensory receptors, although direct in vivo experimental evidences are lacking. Here we verified the role of an extracellular carboxylesterase, esterase-6 (Est-6), in the sensory physiological and behavioral dynamics of Drosophila melanogaster response to its pheromone, cis-vaccenyl acetate (cVA). Est-6 was previously linked to post-mating effects in the reproductive system of females. As Est-6 is also known to hydrolyze cVA in vitro and is expressed in the main olfactory organ, the antenna, we tested here its role in olfaction as a putative odorant-degrading enzyme. Results: We first confirm that Est-6 is highly expressed in olfactory sensilla, including cVA-sensitive sensilla, and we show that expression is likely associated with non-neuronal cells. Our electrophysiological approaches show that the dynamics of olfactory receptor neuron (ORN) responses is strongly influenced by Est-6, as in Est-6° null mutants (lacking the Est-6 gene) cVA-sensitive ORN showed increased firing rate and prolonged activity in response to cVA. Est-6° mutant males had a lower threshold of behavioral response to cVA, as revealed by the analysis of two cVAinduced behaviors. In particular, mutant males exhibited a strong decrease of male-male courtship, in association with a delay in courtship initiation. Conclusions: Our study presents evidence that Est-6 plays a role in the physiological and behavioral dynamics of sex pheromone response in Drosophila males and supports a role of Est-6 as an odorant-degrading enzyme (ODE) in male antennae. Our results also expand the role of Est-6 in Drosophila biology, from reproduction to olfaction, and highlight the role of ODEs in insect olfaction. Keywords: carboxylesterase, esterase 6, olfaction, pheromone, signal termination

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The annual elimination of large numbers of Argentine ant queens near the advance front of an invasion could be a useful tool for weakening the species’ dispersion and, therefore, limiting its establishment in non-invaded areas. However, before carrying out trials to test the effectiveness of this method it would be essential to have sufficient knowledge of the effect of seasonal dynamics acting on the queens’ densities of the species in order to determine the most favourable period of the year to act. We analyzed the seasonal densities and nest dynamics of Argentine ant queens in an invaded Mediterranean natural ecosystem. We observed that the queens’ density varied depending on the season of the year and that this variation was mainly due to the seasonal dynamics of nest aggregations in winter and ant dispersions in summer. The greatest densities per litre of nest soil were observed in winter (December to March, approximately) and the lowest densities were observed in summer ( June to July). This information is essential for improving current knowledge of the Argentine ant’s biology and developing control methods based on the elimination of queens in invaded natural areas

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Biofilm communities are exposed to long periods of desiccation in temporary streams. We investigated how water flow intermittency affected the bacterial community structure colonizing three different streambed compartments in a Mediterranean stream. Massive parallel sequencing revealed different bacterial communities in biofilms from sand sediments and cobbles. Bacterial communities were similar (62% of shared operational taxonomic units) in the epipsammic and hyporheic biofilms, and more diverse than those in the epilithic biofilms. The non-flow phase caused a decrease of bacterial diversity in the biofilms, when communities included only bacterial taxa assumed to be adapted to water stress. The most sensitive bacterial communities to flow intermittency were in the epilithic, where the exposure to physical stress was the highest. In sand sediments a wide group of bacterial taxa was tolerant to desiccation. During non-flow the proliferation of opportunistic taxa in the superficial compartments evidenced the biological link with the terrestrial environment. Bacterial communities better tolerate rewetting than desiccation, since a major number of taxa tolerant to rewetting occurred in all biofilms. Overall, bacterial communities in sandy compartments showed higher resistance to flow intermittency than those in epilithic biofilms

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The Practical Stochastic Model is a simple and robust method to describe coupled chemical reactions. The connection between this stochastic method and a deterministic method was initially established to understand how the parameters and variables that describe the concentration in both methods were related. It was necessary to define two main concepts to make this connection: the filling of compartments or dilutions and the rate of reaction enhancement. The parameters, variables, and the time of the stochastic methods were scaled with the size of the compartment and were compared with a deterministic method. The deterministic approach was employed as an initial reference to achieve a consistent stochastic result. Finally, an independent robust stochastic method was obtained. This method could be compared with the Stochastic Simulation Algorithm developed by Gillespie, 1977. The Practical Stochastic Model produced absolute values that were essential to describe non-linear chemical reactions with a simple structure, and allowed for a correct description of the chemical kinetics.