196 resultados para Cellular automata model
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Side population (SP) cells in the adult kidney are proposed to represent a progenitor population. However, the size, origin, phenotype, and potential of the kidney SP has been controversial. In this study, the SP fraction of embryonic and adult kidneys represented 0.1 to 0.2% of the total viable cell population. The immunophenotype and the expression profile of kidney SP cells was distinct from that of bone marrow SP cells, suggesting that they are a resident nonhematopoietic cell population. Affymetrix expression profiling implicated a role for Notch signaling in kidney SP cells and was used to identify markers of kidney SP. Localization by in situ hybridization confirmed a primarily proximal tubule location, supporting the existence of a tubular niche, but also revealed considerable heterogeneity, including the presence of renal macrophages. Adult kidney SP cells demonstrated multilineage differentiation in vitro, whereas microinjection into mouse metanephroi showed that SP cells had a 3.5- to 13-fold greater potential to contribute to developing kidney than non-SP main population cells. However, although reintroduction of SP cells into an Adriamycin-nephropathy model reduced albuminuria:creatinine ratios, this was without significant tubular integration, suggesting a humoral role for SP cells in renal repair. The heterogeneity of the renal SP highlights the need for further fractionation to distinguish the cellular subpopulations that are responsible for the observed multilineage capacity and transdifferentiative and humoral activities.
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Brugada syndrome (BS) is a genetic disease identified by an abnormal electrocardiogram ( ECG) ( mainly abnormal ECGs associated with right bundle branch block and ST-elevation in right precordial leads). BS can lead to increased risk of sudden cardiac death. Experimental studies on human ventricular myocardium with BS have been limited due to difficulties in obtaining data. Thus, the use of computer simulation is an important alternative. Most previous BS simulations were based on animal heart cell models. However, due to species differences, the use of human heart cell models, especially a model with three-dimensional whole-heart anatomical structure, is needed. In this study, we developed a model of the human ventricular action potential (AP) based on refining the ten Tusscher et al (2004 Am. J. Physiol. Heart Circ. Physiol. 286 H1573 - 89) model to incorporate newly available experimental data of some major ionic currents of human ventricular myocytes. These modified channels include the L-type calcium current (ICaL), fast sodium current (I-Na), transient outward potassium current (I-to), rapidly and slowly delayed rectifier potassium currents (I-Kr and I-Ks) and inward rectifier potassium current (I-Ki). Transmural heterogeneity of APs for epicardial, endocardial and mid-myocardial (M) cells was simulated by varying the maximum conductance of IKs and Ito. The modified AP models were then used to simulate the effects of BS on cellular AP and body surface potentials using a three-dimensional dynamic heart - torso model. Our main findings are as follows. (1) BS has little effect on the AP of endocardial or mid-myocardial cells, but has a large impact on the AP of epicardial cells. (2) A likely region of BS with abnormal cell AP is near the right ventricular outflow track, and the resulting ST-segment elevation is located in the median precordium area. These simulation results are consistent with experimental findings reported in the literature. The model can reproduce a variety of electrophysiological behaviors and provides a good basis for understanding the genesis of abnormal ECG under the condition of BS disease.
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Langerhans cells (LCs) can be targeted with DNA-coated gold micro-projectiles ("Gene Gun") to induce potent cellular and humoral immune responses. It is likely that the relative volumetric distribution of LCs and keratinocytes within the epidermis impacts on the efficacy of Gene Gun immunization protocols. This study quantified the three-dimensional (3D) distribution of LCs and keratinocytes in the mouse skin model with a near-infrared multiphoton laser-scanning microscope (NIR-MPLSM). Stratum corneum (SC) and viable epidermal thickness measured with MPLSM was found in close agreement with conventional histology. LCs were located in the vertical plane at a mean depth of 14.9 mum, less than 3 mum above the dermo-epidermal boundary and with a normal histogram distribution. This likely corresponds to the fact that LCs reside in the suprabasal layer (stratum germinativum). The nuclear volume of keratinocytes was found to be approximately 1.4 times larger than that of resident LCs (88.6 mum3). Importantly, the ratio of LCs to keratinocytes in mouse ear skin (1:15) is more than three times higher than that reported for human breast skin (1:53). Accordingly, cross-presentation may be more significant in clinical Gene Gun applications than in pre-clinical mouse studies. These interspecies differences should be considered in pre-clinical trials using mouse models.
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The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.
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The University of Queensland, Australia has developed Fez, a world-leading user-interface and management system for Fedora-based institutional repositories, which bridges the gap between a repository and users. Christiaan Kortekaas, Andrew Bennett and Keith Webster will review this open source software that gives institutions the power to create a comprehensive repository solution without the hassle..
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We investigate here a modification of the discrete random pore model [Bhatia SK, Vartak BJ, Carbon 1996;34:1383], by including an additional rate constant which takes into account the different reactivity of the initial pore surface having attached functional groups and hydrogens, relative to the subsequently exposed surface. It is observed that the relative initial reactivity has a significant effect on the conversion and structural evolution, underscoring the importance of initial surface chemistry. The model is tested against experimental data on chemically controlled char oxidation and steam gasification at various temperatures. It is seen that the variations of the reaction rate and surface area with conversion are better represented by the present approach than earlier random pore models. The results clearly indicate the improvement of model predictions in the low conversion region, where the effect of the initially attached functional groups and hydrogens is more significant, particularly for char oxidation. It is also seen that, for the data examined, the initial surface chemistry is less important for steam gasification as compared to the oxidation reaction. Further development of the approach must also incorporate the dynamics of surface complexation, which is not considered here.
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The classical model of surface layering followed by capillary condensation during adsorption in mesopores, is modified here by consideration of the adsorbate solid interaction potential. The new theory accurately predicts the capillary coexistence curve as well as pore criticality, matching that predicted by density functional theory. The model also satisfactorily predicts the isotherm for nitrogen adsorption at 77.4 K on MCM-41 material of various pore sizes, synthesized and characterized in our laboratory, including the multilayer region, using only data on the variation of condensation pressures with pore diameter. The results indicate a minimum mesopore diameter for the surface layering model to hold as 14.1 Å, below which size micropore filling must occur, and a minimum pore diameter for mechanical stability of the hemispherical meniscus during desorption as 34.2 Å. For pores in-between these two sizes reversible condensation is predicted to occur, in accord with the experimental data for nitrogen adsorption on MCM-41 at 77.4 K.
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The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).
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View of model for competition entry.
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View of model for competition entry.
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View of model for competition entry.
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The quantitative description of the quantum entanglement between a qubit and its environment is considered. Specifically, for the ground state of the spin-boson model, the entropy of entanglement of the spin is calculated as a function of α, the strength of the ohmic coupling to the environment, and ɛ, the level asymmetry. This is done by a numerical renormalization group treatment of the related anisotropic Kondo model. For ɛ=0, the entanglement increases monotonically with α, until it becomes maximal for α→1-. For fixed ɛ>0, the entanglement is a maximum as a function of α for a value, α=αM
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We present a resonating-valence-bond theory of superconductivity for the Hubbard-Heisenberg model on an anisotropic triangular lattice. Our calculations are consistent with the observed phase diagram of the half-filled layered organic superconductors, such as the beta, beta('), kappa, and lambda phases of (BEDT-TTF)(2)X [bis(ethylenedithio)tetrathiafulvalene] and (BETS)(2)X [bis(ethylenedithio)tetraselenafulvalene]. We find a first order transition from a Mott insulator to a d(x)(2)-y(2) superconductor with a small superfluid stiffness and a pseudogap with d(x)(2)-y(2) symmetry.
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A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.
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In this second counterpoint article, we refute the claims of Landy, Locke, and Conte, and make the more specific case for our perspective, which is that ability-based models of emotional intelligence have value to add in the domain of organizational psychology. In this article, we address remaining issues, such as general concerns about the tenor and tone of the debates on this topic, a tendency for detractors to collapse across emotional intelligence models when reviewing the evidence and making judgments, and subsequent penchant to thereby discount all models, including the ability-based one, as lacking validity. We specifically refute the following three claims from our critics with the most recent empirically based evidence: (1) emotional intelligence is dominated by opportunistic academics-turned-consultants who have amassed much fame and fortune based on a concept that is shabby science at best; (2) the measurement of emotional intelligence is grounded in unstable, psychometrically flawed instruments, which have not demonstrated appropriate discriminant and predictive validity to warrant/justify their use; and (3) there is weak empirical evidence that emotional intelligence is related to anything of importance in organizations. We thus end with an overview of the empirical evidence supporting the role of emotional intelligence in organizational and social behavior.