66 resultados para Cognitive Linguistics. Situation Models. Mental Simulation. Frames and Schemes


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The existence of sting jets as a potential source of damaging surface winds during the passage of extratropical cyclones has recently been recognized However, there are still very few published studies on the subject Furthermore, although ills known that other models are capable of reproducing sting jets, in the published literature only one numerical model [the Met Office Unified Model (MetUM)] has been used to numerically analyze these phenomena This article alms to improve our understanding of the processes that contribute to the development of sting jets and show that model differences affect the evolution of modeled sting jets A sting jet event during the passage of a cyclone over the United Kingdom on 26 February 2002 has been simulated using two mesoscale models namely the MetUM and the Consortium for Small Scale Modeling (COSMO) model to compare their performance Given the known critical importance of vertical resolution in the simulation of sting jets the vertical resolution of both models has been enhanced with respect to their operational versions Both simulations have been verified against surface measurements of maximum gusts, satellite imagery and Met Office operational synoptic analyses, as well as operational analyses from the ECMWF It is shown that both models are capable of reproducing sting jets with similar, though not identical. features Through the comparison of the results from these two models, the relevance of physical mechanisms, such as evaporative cooling and the release of conditional symmetric instability, in the generation and evolution of sting jets is also discussed

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A novel Neuropredictive Teleoperation (NPT) Scheme is presented. The design results from two key ideas: the exploitation of the measured or estimated neural input to the human arm or its electromyograph (EMG) as the system input and the employment of a predictor of the arm movement, based on this neural signal and an arm model, to compensate for time delays in the system. Although a multitude of such models, as well as measuring devices for the neural signals and the EMG, have been proposed, current telemanipulator research has only been considering highly simplified arm models. In the present design, the bilateral constraint that the master and slave are simultaneously compliant to each other's state (equal positions and forces) is abandoned, thus obtaining a simple to analyzesuccession of only locally controlled modules, and a robustness to time delays of up to 500 ms. The proposed designs were inspired by well established physiological evidence that the brain, rather than controlling the movement on-line, programs the arm with an action plan of a complete movement, which is then executed largely in open loop, regulated only by local reflex loops. As a model of the human arm the well-established Stark model is employed, whose mathematical representation is modified to make it suitable for an engineering application. The proposed scheme is however valid for any arm model. BIBO-stability and passivity results for a variety of local control laws are reported. Simulation results and comparisons with traditional designs also highlight the advantages of the proposed design.

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Many numerical models for weather prediction and climate studies are run at resolutions that are too coarse to resolve convection explicitly, but too fine to justify the local equilibrium assumed by conventional convective parameterizations. The Plant-Craig (PC) stochastic convective parameterization scheme, developed in this paper, solves this problem by removing the assumption that a given grid-scale situation must always produce the same sub-grid-scale convective response. Instead, for each timestep and gridpoint, one of the many possible convective responses consistent with the large-scale situation is randomly selected. The scheme requires as input the large-scale state as opposed to the instantaneous grid-scale state, but must nonetheless be able to account for genuine variations in the largescale situation. Here we investigate the behaviour of the PC scheme in three-dimensional simulations of radiative-convective equilibrium, demonstrating in particular that the necessary space-time averaging required to produce a good representation of the input large-scale state is not in conflict with the requirement to capture large-scale variations. The resulting equilibrium profiles agree well with those obtained from established deterministic schemes, and with corresponding cloud-resolving model simulations. Unlike the conventional schemes the statistics for mass flux and rainfall variability from the PC scheme also agree well with relevant theory and vary appropriately with spatial scale. The scheme is further shown to adapt automatically to changes in grid length and in forcing strength.

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Summary Background and purpose: Phytocannabinoids in Cannabis sativa have diverse pharmacological targets extending beyond cannabinoid receptors and several exert notable anticonvulsant effects. For the first time, we investigated the anticonvulsant profile of the phytocannabinoid cannabidivarin (CBDV) in vitro and in in vivo seizure models. Experimental approach: The effect of CBDV (1-100μM) on epileptiform local field potentials (LFPs) induced in rat hippocampal brain slices by 4-AP application or Mg2+-free conditions was assessed by in vitro multi-electrode array recordings. Additionally, the anticonvulsant profile of CBDV (50-200 mg kg-1) in vivo was investigated in four rodent seizure models: maximal electroshock (mES) and audiogenic seizures in mice, and pentylenetetrazole (PTZ) and pilocarpine-induced seizures in rat. CBDV effects in combination with commonly-used antiepileptic drugs were investigated in rat seizures. Finally, the motor side effect profile of CBDV was investigated using static beam and gripstrength assays. Key results: CDBV significantly attenuated status epilepticus-like epileptiform LFPs induced by 4-AP and Mg2+-free conditions. CBDV had significant anticonvulsant effects in mES (≥100 mg kg-1), audiogenic (≥50 mg kg-1) and PTZ-induced seizures (≥100 mg kg-1). CBDV alone had no effect against pilocarpine-induced seizures, but significantly attenuated these seizures when administered with valproate or phenobarbital at 200 mg kg-1 CBDV. CBDV had no effect on motor function. Conclusions and Implications: These results indicate that CBDV is an effective anticonvulsant across a broad range of seizure models, does not significantly affect normal motor function and therefore merits further investigation in chronic epilepsy models to justify human trials.

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The goal of this research was to investigate the changes in neural processing in mild cognitive impairment. We measured phase synchrony, amplitudes, and event-related potentials in veridical and false memory to determine whether these differed in participants with mild cognitive impairment compared with typical, age-matched controls. Empirical mode decomposition phase locking analysis was used to assess synchrony, which is the first time this analysis technique has been applied in a complex cognitive task such as memory processing. The technique allowed assessment of changes in frontal and parietal cortex connectivity over time during a memory task, without a priori selection of frequency ranges, which has been shown previously to influence synchrony detection. Phase synchrony differed significantly in its timing and degree between participant groups in the theta and alpha frequency ranges. Timing differences suggested greater dependence on gist memory in the presence of mild cognitive impairment. The group with mild cognitive impairment had significantly more frontal theta phase locking than the controls in the absence of a significant behavioural difference in the task, providing new evidence for compensatory processing in the former group. Both groups showed greater frontal phase locking during false than true memory, suggesting increased searching when no actual memory trace was found. Significant inter-group differences in frontal alpha phase locking provided support for a role for lower and upper alpha oscillations in memory processing. Finally, fronto-parietal interaction was significantly reduced in the group with mild cognitive impairment, supporting the notion that mild cognitive impairment could represent an early stage in Alzheimer’s disease, which has been described as a ‘disconnection syndrome’.

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The paper reviews the leading diagramming methods employed in system dynamics to communicate the contents of models. The main ideas and historical development of the field are first outlined. Two diagramming methods—causal loop diagrams (CLDs) and stock/flow diagrams (SFDs)—are then described and their advantages and limitations discussed. A set of broad research directions is then outlined. These concern: the abilities of different diagrams to communicate different ideas, the role that diagrams have in group model building, and the question of whether diagrams can be an adequate substitute for simulation modelling. The paper closes by suggesting that although diagrams alone are insufficient, they have many benefits. However, since these benefits have emerged only as ‘craft wisdom’, a more rigorous programme of research into the diagrams' respective attributes is called for.

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By comparing annual and seasonal changes in precipitation over land and ocean since 1950 simulated by the CMIP5 (Coupled Model Intercomparison Project, phase 5) climate models in which natural and anthropogenic forcings have been included, we find that clear global-scale and regional-scale changes due to human influence are expected to have occurred over both land and ocean. These include moistening over northern high latitude land and ocean throughout all seasons and over the northern subtropical oceans during boreal winter. However we show that this signal of human influence is less distinct when considered over the relatively small area of land for which there are adequate observations to make assessments of multi-decadal scale trends. These results imply that extensive and significant changes in precipitation over the land and ocean may have already happened, even though, inadequacies in observations in some parts of the world make it difficult to identify conclusively such a human fingerprint on the global water cycle. In some regions and seasons, due to aliasing of different kinds of variability as a result of sub sampling by the sparse and changing observational coverage, observed trends appear to have been increased, underscoring the difficulties of interpreting the apparent magnitude of observed changes in precipitation.

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Undeniably, anticipation plays a crucial role in cognition. By what means, to what extent, and what it achieves remain open questions. In a recent BBS target article, Clark (in press) depicts an integrative model of the brain that builds on hierarchical Bayesian models of neural processing (Rao and Ballard, 1999; Friston, 2005; Brown et al., 2011), and their most recent formulation using the free-energy principle borrowed from thermodynamics (Feldman and Friston, 2010; Friston, 2010; Friston et al., 2010). Hierarchical generative models of cognition, such as those described by Clark, presuppose the manipulation of representations and internal models of the world, in as much detail as is perceptually available. Perhaps surprisingly, Clark acknowledges the existence of a “virtual version of the sensory data” (p. 4), but with no reference to some of the historical debates that shaped cognitive science, related to the storage, manipulation, and retrieval of representations in a cognitive system (Shanahan, 1997), or accounting for the emergence of intentionality within such a system (Searle, 1980; Preston and Bishop, 2002). Instead of demonstrating how this Bayesian framework responds to these foundational questions, Clark describes the structure and the functional properties of an action-oriented, multi-level system that is meant to combine perception, learning, and experience (Niedenthal, 2007).

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Theory and treatment for childhood anxiety disorders typically implicates children’s negative cognitions, yet little is known about the characteristics of thinking styles of clinically anxious children. In particular, it is unclear whether differences in thinking styles between children with anxiety disorders and non-anxious children vary as a function of child age, whether particular cognitive distortions are associated with childhood anxiety disorders at different child ages, and whether cognitive content is disorder-specific. The current study addressed these questions among 120 7 - 12 year old children (53% female) who met diagnostic criteria for social anxiety disorder, other anxiety disorder, or who were not currently anxious. Contrary to expectations, threat interpretation was not inflated amongst anxious compared to non-anxious children at any age, although older (10 - 12 year old) anxious children did differ from non-anxious children on measures of perceived coping. The notion of cognitive-content specificity was not supported across the age-range. The findings challenge current treatment models of childhood anxiety, and suggest that a focus on changing anxious children’s cognitions is not warranted in mid-childhood, and in late childhood cognitive approaches may be better focussed on promoting children’s perceptions of control rather than challenging threat interpretations.

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Real-time estimates of output gaps and inflation gaps differ from the values that are obtained using data available long after the event. Part of the problem is that the data on which the real-time estimates are based is subsequently revised. We show that vector-autoregressive models of data vintages provide forecasts of post-revision values of future observations and of already-released observations capable of improving estimates of output and inflation gaps in real time. Our findings indicate that annual revisions to output and inflation data are in part predictable based on their past vintages.

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The results of coupled high resolution global models (CGCMs) over South America are discussed. HiGEM1.2 and HadGEM1.2 simulations, with horizontal resolution of ~90 and 135 km, respectively, are compared. Precipitation estimations from CMAP (Climate Prediction Center—Merged Analysis of Precipitation), CPC (Climate Prediction Center) and GPCP (Global Precipitation Climatology Project) are used for validation. HiGEM1.2 and HadGEM1.2 simulated seasonal mean precipitation spatial patterns similar to the CMAP. The positioning and migration of the Intertropical Convergence Zone and of the Pacific and Atlantic subtropical highs are correctly simulated by the models. In HiGEM1.2 and HadGEM1.2, the intensity and locations of the South Atlantic Convergence Zone are in agreement with the observed dataset. The simulated annual cycles are in phase with estimations of rainfall for most of the six regions considered. An important result is that HiGEM1.2 and HadGEM1.2 eliminate a common problem of coarse resolution CGCMs, which is the simulation of a semiannual cycle of precipitation due to the semiannual solar forcing. Comparatively, the use of high resolution in HiGEM1.2 reduces the dry biases in the central part of Brazil during austral winter and spring and in most part of the year over an oceanic box in eastern Uruguay.

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Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

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Many urban surface energy balance models now exist. These vary in complexity from simple schemes that represent the city as a concrete slab, to those which incorporate detailed representations of momentum and energy fluxes distributed within the atmospheric boundary layer. While many of these schemes have been evaluated against observations, with some models even compared with the same data sets, such evaluations have not been undertaken in a controlled manner to enable direct comparison. For other types of climate model, for instance the Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS) experiments (Henderson-Sellers et al., 1993), such controlled comparisons have been shown to provide important insights into both the mechanics of the models and the physics of the real world. This paper describes the progress that has been made to date on a systematic and controlled comparison of urban surface schemes. The models to be considered, and their key attributes, are described, along with the methodology to be used for the evaluation.

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Although difference-stationary (DS) and trend-stationary (TS) processes have been subject to considerable analysis, there are no direct comparisons for each being the data-generation process (DGP). We examine incorrect choice between these models for forecasting for both known and estimated parameters. Three sets of Monte Carlo simulations illustrate the analysis, to evaluate the biases in conventional standard errors when each model is mis-specified, compute the relative mean-square forecast errors of the two models for both DGPs, and investigate autocorrelated errors, so both models can better approximate the converse DGP. The outcomes are surprisingly different from established results.

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This paper presents new 500 year interval palaeogeographic models for Britain, Ireland and the North West French coast from 11000 cal. BP to present. These models are used to calculate the varying rates of inundation for different geographical zones over the study period. This allows for consideration of the differential impact that Holocene sea-level rise had across space and time, and on past societies. In turn, consideration of the limitations of the models helps to foreground profitable areas for future research.