886 resultados para Multiple state models


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Background: Inflammatory bowel disease (IBD) is characterized by chronic intestinal inflammation due to dysregulation of the mucosal immune system. The cytokines IL-1β and IL-18 appear early in intestinal inflammation and their pro-forms are processed via the caspase-1-activating multiprotein complex, the Nlrp3 inflammasome. Previously, we reported that the uptake of dextran sodium sulfate (DSS) by macrophages activates the Nlrp3 inflammasome and that Nlrp3(-/-) mice are protected in the acute DSS colitis model. Of note, other groups have reported opposing effects in regards to DSS susceptibility in Nlrp3(-/-) mice. Recently, mice lacking inflammasomes were found to develop a distinct intestinal microflora. Methods: To reconcile the contradicting observations, we investigated the role of Nlrp3 deficiency in two different IBD models: acute DSS colitis and TNBS (2,4,6-trinitrobenzene sulfonic acid)-induced colitis. In addition, we investigated the impact of the intestinal flora on disease severity by performing cohousing experiments of wild-type and Nlrp3(-/-) mice, as well as by antibiotic treatment. Results: Nlrp3(-/-) mice treated with either DSS or TNBS exhibited attenuated colitis and lower mortality. This protective effect correlated with an increased frequency of CD103+ lamina propria dendritic cells expressing a tolerogenic phenotype in Nlrp3(-/-) mice in steady state conditions. Interestingly, after cohousing, Nlrp3(-/-) mice were as susceptible as wild-type mice, indicating that transmission of endogenous bacterial flora between the two mouse strains might increase susceptibility of Nlrp3(-/-) mice towards DSS-induced colitis. Accordingly, treatment with antibiotics almost completely prevented colitis in the DSS model. Conclusions: The composition of the intestinal microflora significantly influences disease severity in IBD models comparing wild-type and Nlrp3(-/-) mice. This observation may - at least in part - explain contradictory results concerning the role of the inflammasome in different labs. Further studies are required to define the role of the Nlrp3 inflammasome in noninflamed mucosa under steady state conditions and in IBD.

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The development of the field-scale Erosion Productivity Impact Calculator (EPIC) model was initiated in 1981 to support assessments of soil erosion impacts on soil productivity for soil, climate, and cropping conditions representative of a broad spectrum of U.S. agricultural production regions. The first major application of EPIC was a national analysis performed in support of the 1985 Resources Conservation Act (RCA) assessment. The model has continuously evolved since that time and has been applied for a wide range of field, regional, and national studies both in the U.S. and in other countries. The range of EPIC applications has also expanded greatly over that time, including studies of (1) surface runoff and leaching estimates of nitrogen and phosphorus losses from fertilizer and manure applications, (2) leaching and runoff from simulated pesticide applications, (3) soil erosion losses from wind erosion, (4) climate change impacts on crop yield and erosion, and (5) soil carbon sequestration assessments. The EPIC acronym now stands for Erosion Policy Impact Climate, to reflect the greater diversity of problems to which the model is currently applied. The Agricultural Policy EXtender (APEX) model is essentially a multi-field version of EPIC that was developed in the late 1990s to address environmental problems associated with livestock and other agricultural production systems on a whole-farm or small watershed basis. The APEX model also continues to evolve and to be utilized for a wide variety of environmental assessments. The historical development for both models will be presented, as well as example applications on several different scales.

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The choice of a research path in attacking scientific and technological problems is a significant component of firms’ R&D strategy. One of the findings of the patent races literature is that, in a competitive market setting, firms’ noncooperative choices of research projects display an excessive degree of correlation, as compared to the socially optimal level. The paper revisits this question in a context in which firms have access to trade secrets, in addition to patents, to assert intellectual property rights (IPR) over their discoveries. We find that the availability of multiple IPR protection instruments can move the paths chosen by firms engaged in an R&D race toward the social optimum.

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This paper presents several algorithms for joint estimation of the target number and state in a time-varying scenario. Building on the results presented in [1], which considers estimation of the target number only, we assume that not only the target number, but also their state evolution must be estimated. In this context, we extend to this new scenario the Rao-Blackwellization procedure of [1] to compute Bayes recursions, thus defining reduced-complexity solutions for the multi-target set estimator. A performance assessmentis finally given both in terms of Circular Position Error Probability - aimed at evaluating the accuracy of the estimated track - and in terms of Cardinality Error Probability, aimed at evaluating the reliability of the target number estimates.

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BACKGROUND: Multiple epiphyseal dysplasia (MED) is one of the more common generalised skeletal dysplasias. Due to its clinical heterogeneity diagnosis may be difficult. Mutations of at least six separate genes can cause MED. Joint deformities, joint pain and gait disorders are common symptoms. CASE PRESENTATION: We report on a 27-year-old male patient suffering from clinical symptoms of autosomal recessive MED with habitual dislocation of a multilayered patella on both sides, on the surgical treatment and on short-term clinical outcome. Clinical findings were: bilateral hip and knee pain, instability of femorotibial and patellofemoral joints with habitual patella dislocation on both sides, contractures of hip, elbow and second metacarpophalangeal joints. Main radiographic findings were: bilateral dislocated multilayered patella, dysplastic medial tibial plateaus, deformity of both femoral heads and osteoarthritis of the hip joints, and deformity of both radial heads. In the molecular genetic analysis, the DTDST mutation g.1984T > A (p.C653S) was found at the homozygote state. Carrier status was confirmed in the DNA of the patient's parents. The mutation could be considered to be the reason for the patient's disease. Surgical treatment of habitual patella dislocation with medialisation of the tibial tuberosity led to an excellent clinical outcome. CONCLUSIONS: The knowledge of different phenotypes of skeletal dysplasias helps to select genes for genetic analysis. Compared to other DTDST mutations, this is a rather mild phenotype. Molecular diagnosis is important for genetic counselling and for an accurate prognosis. Even in case of a multilayered patella in MED, habitual patella dislocation could be managed successfully by medialisation of the tibial tuberosity.

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Experimental animal models offer possibilities of physiology knowledge, pathogenesis of disease and action of drugs that are directly related to quality nursing care. This integrative review describes the current state of the instrumental and ethical aspects of experimental research with animal models, including the main recommendations of ethics committees that focus on animal welfare and raises questions about the impact of their findings in nursing care. Data show that, in Brazil, the progress in ethics for the use of animals for scientific purposes was consolidated with Law No. 11.794/2008 establishing ethical procedures, attending health, genetic and experimental parameters. The application of ethics in handling of animals for scientific and educational purposes and obtaining consistent and quality data brings unquestionable contributions to the nurse, as they offer subsidies to relate pathophysiological mechanisms and the clinical aspect on the patient.

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Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities.

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Synaptic plasticity involves a complex molecular machinery with various protein interactions but it is not yet clear how its components give rise to the different aspects of synaptic plasticity. Here we ask whether it is possible to mathematically model synaptic plasticity by making use of known substances only. We present a model of a multistable biochemical reaction system and use it to simulate the plasticity of synaptic transmission in long-term potentiation (LTP) or long-term depression (LTD) after repeated excitation of the synapse. According to our model, we can distinguish between two phases: first, a "viscosity" phase after the first excitation, the effects of which like the activation of NMDA receptors and CaMKII fade out in the absence of further excitations. Second, a "plasticity" phase actuated by an identical subsequent excitation that follows after a short time interval and causes the temporarily altered concentrations of AMPA subunits in the postsynaptic membrane to be stabilized. We show that positive feedback is the crucial element in the core chemical reaction, i.e. the activation of the short-tail AMPA subunit by NEM-sensitive factor, which allows generating multiple stable equilibria. Three stable equilibria are related to LTP, LTD and a third unfixed state called ACTIVE. Our mathematical approach shows that modeling synaptic multistability is possible by making use of known substances like NMDA and AMPA receptors, NEM-sensitive factor, glutamate, CaMKII and brain-derived neurotrophic factor. Furthermore, we could show that the heteromeric combination of short- and long-tail AMPA receptor subunits fulfills the function of a memory tag.

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El projecte realitzat se situa en el marc de la història contemporània, i s’ha centrat en primer lloc, en l’anàlisi, des d’una perspectiva comparativa, del desenvolupament dels discursos de gènere a Catalunya durant la Dictadura Franquista i a la Irlanda postcolonial. Mitjançant l’anàlisi del discurs, s’han estudiat els models de feminitat imposats pel Franquisme i les seves bases ideològiques com són el valors catòlics i l’antindividualisme. En el cas irlandès, s’ha analitzat com, a través de determinades institucions gestionades per l’Església Catòlica, es controlaven aquelles dones que es desviaven del model de gènere que propugnava l’Estat Irlandès, molt similar al proposat pel Franquisme i també basat en els catolicisme. De la mateix manera, s’ha estudiat com el feminisme Català i irlandès dels anys 1970 i 1980 van contrarestar aquests models de gènere imposats, a través de l’anàlisi d’un conjunt d’expressions culturals produïdes per ambdós moviments feministes. La perspectiva comparativa del projecte ha permès: El coneixement dels mecanismes culturals de repressió de les dones així com la seva institucionalització. Revelant els paral•lelismes pel que fa a les polítiques de gènere entre els dos casos estudiats malgrat diferències significatives entre els dos contextos (Catalunya es troba sota una dictadura, Irlanda és un Estat democràtic). La importància de l’agència de les dones i les seves diverses estratègies de resistència, especialment a través d’expressions culturals més efímeres o considerades frívoles que, malgrat el poc reconeixement que han obtingut, són molt eficaces en la deconstrucció de discursos de gènere repressius envers les dones. Ha posat de manifest, també, la importància de l’experiència i les pràctiques personals i íntimes com a pràctiques de resistència. Així mateix, ha visibilitzat les dinàmiques pròpies de moviments feministes.

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The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

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The first generation models of currency crises have often been criticized because they predict that, in the absence of very large triggering shocks, currency attacks should be predictable and lead to small devaluations. This paper shows that these features of first generation models are not robust to the inclusion of private information. In particular, this paper analyzes a generalization of the Krugman-Flood-Garber (KFG) model, which relaxes the assumption that all consumers are perfectly informed about the level of fundamentals. In this environment, the KFG equilibrium of zero devaluation is only one of many possible equilibria. In all the other equilibria, the lack of perfect information delays the attack on the currency past the point at which the shadow exchange rate equals the peg, giving rise to unpredictable and discrete devaluations.

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A new algorithm called the parameterized expectations approach(PEA) for solving dynamic stochastic models under rational expectationsis developed and its advantages and disadvantages are discussed. Thisalgorithm can, in principle, approximate the true equilibrium arbitrarilywell. Also, this algorithm works from the Euler equations, so that theequilibrium does not have to be cast in the form of a planner's problem.Monte--Carlo integration and the absence of grids on the state variables,cause the computation costs not to go up exponentially when the numberof state variables or the exogenous shocks in the economy increase. \\As an application we analyze an asset pricing model with endogenousproduction. We analyze its implications for time dependence of volatilityof stock returns and the term structure of interest rates. We argue thatthis model can generate hump--shaped term structures.

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In this work I study the stability of the dynamics generated by adaptivelearning processes in intertemporal economies with lagged variables. Iprove that determinacy of the steady state is a necessary condition for the convergence of the learning dynamics and I show that the reciprocal is not true characterizing the economies where convergence holds. In the case of existence of cycles I show that there is not, in general, a relationship between determinacy and convergence of the learning process to the cycle. I also analyze the expectational stability of these equilibria.

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We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t-statistics and may induce investigators to select false models. We examine whether different objective functions affect identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to detect identification failures and apply them to a state-of-the-art model.

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This paper provides an analytical characterization of Markov perfectequilibria in a politico-economic model with repeated voting, whereagents vote over distortionary income redistribution. The key featureof the theory is that the future constituency of redistributive policiesdepends positively on the current level of redistribution, since thisaffects both private investments and the future distribution of voters.Agents vote rationally and fullly anticipate the effects of their politicalchoice on both private incentives and future voting outcomes. The modelfeatures multiple equilibria. In "pro-welfare" equilibria, both welfarestate policies and their effects on distribution persist forever. In"anti-welfare equilibria", even a majority of beneficiaries ofredistributive policies vote strategically so as to induce the formationof a future majority that will vote for zero redistribution.