62 resultados para Gipps Car Following Model
Resumo:
The technique of relaxation of the tropical atmosphere towards an analysis in a month-season forecast model has previously been successfully exploited in a number of contexts. Here it is shown that when tropical relaxation is used to investigate the possible origin of the observed anomalies in June–July 2007, a simple dynamical model is able to reproduce the observed component of the pattern of anomalies given by an ensemble of ECMWF forecast runs. Following this result, the simple model is used for a range of experiments on time-scales of relaxation, variables and regions relaxed based on a control model run with equatorial heating in a zonal flow. A theory based on scale analysis for the large-scale tropics is used to interpret the results. Typical relationships between scales are determined from the basic equations, and for a specified diabatic heating a chain of deductions for determining the dependent variables is derived. Different critical time-scales are found for tropical relaxation of different dependent variables to be effective. Vorticity has the longest critical time-scale, typically 1.2 days. For temperature and divergence, the time-scales are 10 hours and 3 hours, respectively. However not all the tropical fields, in particular the vertical motion, are reproduced correctly by the model unless divergence is heavily damped. To obtain the correct extra-tropical fields, it is crucial to have the correct rotational flow in the subtropics to initiate the Rossby wave propagation from there. It is sufficient to relax vorticity or temperature on a time-scale comparable or less than their critical time-scales to obtain this. However if the divergent advection of vorticity is important in the Rossby Wave Source then strong relaxation of divergence is required to accurately represent the tropical forcing of Rossby waves.
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Larvae of Galleria mellonella (Greater Wax Moth) have been shown to be susceptible to Campylobacter jejuni infection and our study characterizes this infection model. Following infection with C. jejuni human isolates, bacteria were visible in the haemocoel and gut of challenged larvae, and there was extensive damage to the gut. Bacteria were found in the extracellular and cell-associated fraction in the haemocoel, and it was shown that C. jejuni can survive in insect cells. Finally, we have used the model to screen a further 67 C. jejuni isolates belonging to different MLST types. Isolates belonging to ST257 were the most virulent in the Galleria model, whereas those belonging to ST21 were the least virulent.
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Evidence from in vivo and in vitro studies suggests that the consumption of pro- and prebiotics may inhibit colon carcinogenesis; however, the mechanisms involved have, thus far, proved elusive. There are some indications from animal studies that the effects are being exerted during the promotion stage of carcinogenesis. One feature of the promotion stage of colorectal cancer is the disruption of tight junctions, leading to a loss of integrity across the intestinal barrier. We have used the Caco-2 human adenocarcinoma cell line as a model for the intestinal epithelia. Trans-epithelial electrical resistance measurements indicate Caco-2 monolayer integrity, and we recorded changes to this integrity following exposure to the fermentation products of selected probiotics and prebiotics, in the form of nondigestible oligosaccharides (NDOs). Our results indicate that NDOs themselves exert varying, but generally minor, effects upon the strength of the tight junctions, whereas the fermentation products of probiotics and NDOs tend to raise tight junction integrity above that of the controls. This effect was bacterial species and oligosaccharide specific. Bifidobacterium Bb 12 was particularly effective, as were the fermentation products of Raftiline and Raftilose. We further investigated the ability of Raftilose fermentations to protect against the negative effects of deoxycholic acid (DCA) upon tight junction integrity. We found protection to be species dependent and dependent upon the presence of the fermentation products in the media at the same time as or after exposure to the DCA. Results suggest that the Raftilose fermentation products may prevent disruption of the intestinal epithelial barrier function during damage by tumor promoters.
Resumo:
Statistical methods of inference typically require the likelihood function to be computable in a reasonable amount of time. The class of “likelihood-free” methods termed Approximate Bayesian Computation (ABC) is able to eliminate this requirement, replacing the evaluation of the likelihood with simulation from it. Likelihood-free methods have gained in efficiency and popularity in the past few years, following their integration with Markov Chain Monte Carlo (MCMC) and Sequential Monte Carlo (SMC) in order to better explore the parameter space. They have been applied primarily to estimating the parameters of a given model, but can also be used to compare models. Here we present novel likelihood-free approaches to model comparison, based upon the independent estimation of the evidence of each model under study. Key advantages of these approaches over previous techniques are that they allow the exploitation of MCMC or SMC algorithms for exploring the parameter space, and that they do not require a sampler able to mix between models. We validate the proposed methods using a simple exponential family problem before providing a realistic problem from human population genetics: the comparison of different demographic models based upon genetic data from the Y chromosome.
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The mechanisms involved in Atlantic meridional overturning circulation (AMOC) decadal variability and predictability over the last 50 years are analysed in the IPSL–CM5A–LR model using historical and initialised simulations. The initialisation procedure only uses nudging towards sea surface temperature anomalies with a physically based restoring coefficient. When compared to two independent AMOC reconstructions, both the historical and nudged ensemble simulations exhibit skill at reproducing AMOC variations from 1977 onwards, and in particular two maxima occurring respectively around 1978 and 1997. We argue that one source of skill is related to the large Mount Agung volcanic eruption starting in 1963, which reset an internal 20-year variability cycle in the North Atlantic in the model. This cycle involves the East Greenland Current intensity, and advection of active tracers along the subpolar gyre, which leads to an AMOC maximum around 15 years after the Mount Agung eruption. The 1997 maximum occurs approximately 20 years after the former one. The nudged simulations better reproduce this second maximum than the historical simulations. This is due to the initialisation of a cooling of the convection sites in the 1980s under the effect of a persistent North Atlantic oscillation (NAO) positive phase, a feature not captured in the historical simulations. Hence we argue that the 20-year cycle excited by the 1963 Mount Agung eruption together with the NAO forcing both contributed to the 1990s AMOC maximum. These results support the existence of a 20-year cycle in the North Atlantic in the observations. Hindcasts following the CMIP5 protocol are launched from a nudged simulation every 5 years for the 1960–2005 period. They exhibit significant correlation skill score as compared to an independent reconstruction of the AMOC from 4-year lead-time average. This encouraging result is accompanied by increased correlation skills in reproducing the observed 2-m air temperature in the bordering regions of the North Atlantic as compared to non-initialized simulations. To a lesser extent, predicted precipitation tends to correlate with the nudged simulation in the tropical Atlantic. We argue that this skill is due to the initialisation and predictability of the AMOC in the present prediction system. The mechanisms evidenced here support the idea of volcanic eruptions as a pacemaker for internal variability of the AMOC. Together with the existence of a 20-year cycle in the North Atlantic they propose a novel and complementary explanation for the AMOC variations over the last 50 years.
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Point mutations in LRRK2 cause autosomal dominant Parkinson's disease. Despite extensive efforts to determine the mechanism of cell death in patients with LRRK2 mutations, the aetiology of LRRK2 PD is not well understood. To examine possible alterations in gene expression linked to the presence of LRRK2 mutations, we carried out a case versus control analysis of global gene expression in three systems: fibroblasts isolated from LRRK2 mutation carriers and healthy, non-mutation carrying controls; brain tissue from G2019S mutation carriers and controls; and HEK293 inducible LRRK2 wild type and mutant cell lines. No significant alteration in gene expression was found in these systems following correction for multiple testing. These data suggest that any alterations in basal gene expression in fibroblasts or cell lines containing mutations in LRRK2 are likely to be quantitatively small. This work suggests that LRRK2 is unlikely to play a direct role in modulation of gene expression, although it remains possible that this protein can influence mRNA expression under pathogenic cicumstances.
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Advances in seasonal forecasting have brought widespread socio-economic benefits. However, seasonal forecast skill in the extratropics is relatively modest, prompting the seasonal forecasting community to search for additional sources of predictability. For over a decade it has been suggested that knowledge of the state of the stratosphere can act as a source of enhanced seasonal predictability; long-lived circulation anomalies in the lower stratosphere that follow stratospheric sudden warmings are associated with circulation anomalies in the troposphere that can last up to two months. Here, we show by performing retrospective ensemble model forecasts that such enhanced predictability can be realized in a dynamical seasonal forecast system with a good representation of the stratosphere. When initialized at the onset date of stratospheric sudden warmings, the model forecasts faithfully reproduce the observed mean tropospheric conditions in the months following the stratospheric sudden warmings. Compared with an equivalent set of forecasts that are not initialized during stratospheric sudden warmings, we document enhanced forecast skill for atmospheric circulation patterns, surface temperatures over northern Russia and eastern Canada and North Atlantic precipitation. We suggest that seasonal forecast systems initialized during stratospheric sudden warmings are likely to yield significantly greater forecast skill in some regions.
Resumo:
An in vitro colon extended physiologically based extraction test (CEPBET) which incorporates human gastrointestinal tract (GIT) parameters (including pH and chemistry, solid-to-fluid ratio, mixing and emptying rates) was applied for the first time to study the bioaccessibility of brominated flame retardants (BFRs) from the 3 main GIT compartments (stomach, small intestine and colon) following ingestion of indoor dust. Results revealed the bioaccessibility of γ-HBCD (72%) was less than that for α- and β-isomers (92% and 80% respectively) which may be attributed to the lower aqueous solubility of the γ-isomer (2 μg L−1) compared to the α- and β-isomers (45 and 15 μg L−1 respectively). No significant change in the enantiomeric fractions of HBCDs was observed in any of the studied samples. However, this does not completely exclude the possibility of in vivo enantioselective absorption of HBCDs, as the GIT cell lining and bacterial flora – which may act enantioselectively – are not included in the current CE-PBET model. While TBBP-A was almost completely (94%) bioaccessible, BDE-209 was the least (14%) bioaccessible of the studied BFRs. Bioaccessibility of tri-hepta BDEs ranged from 32–58%. No decrease in the bioaccessibility with increasing level of bromination was observed in the studied PBDEs.
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The surface mass balance for Greenland and Antarctica has been calculated using model data from an AMIP-type experiment for the period 1979–2001 using the ECHAM5 spectral transform model at different triangular truncations. There is a significant reduction in the calculated ablation for the highest model resolution, T319 with an equivalent grid distance of ca 40 km. As a consequence the T319 model has a positive surface mass balance for both ice sheets during the period. For Greenland, the models at lower resolution, T106 and T63, on the other hand, have a much stronger ablation leading to a negative surface mass balance. Calculations have also been undertaken for a climate change experiment using the IPCC scenario A1B, with a T213 resolution (corresponding to a grid distance of some 60 km) and comparing two 30-year periods from the end of the twentieth century and the end of the twenty-first century, respectively. For Greenland there is change of 495 km3/year, going from a positive to a negative surface mass balance corresponding to a sea level rise of 1.4 mm/year. For Antarctica there is an increase in the positive surface mass balance of 285 km3/year corresponding to a sea level fall by 0.8 mm/year. The surface mass balance changes of the two ice sheets lead to a sea level rise of 7 cm at the end of this century compared to end of the twentieth century. Other possible mass losses such as due to changes in the calving of icebergs are not considered. It appears that such changes must increase significantly, and several times more than the surface mass balance changes, if the ice sheets are to make a major contribution to sea level rise this century. The model calculations indicate large inter-annual variations in all relevant parameters making it impossible to identify robust trends from the examined periods at the end of the twentieth century. The calculated inter-annual variations are similar in magnitude to observations. The 30-year trend in SMB at the end of the twenty-first century is significant. The increase in precipitation on the ice sheets follows closely the Clausius-Clapeyron relation and is the main reason for the increase in the surface mass balance of Antarctica. On Greenland precipitation in the form of snow is gradually starting to decrease and cannot compensate for the increase in ablation. Another factor is the proportionally higher temperature increase on Greenland leading to a larger ablation. It follows that a modest increase in temperature will not be sufficient to compensate for the increase in accumulation, but this will change when temperature increases go beyond any critical limit. Calculations show that such a limit for Greenland might well be passed during this century. For Antarctica this will take much longer and probably well into following centuries.
Resumo:
Background. Within a therapeutic gene by environment (GxE) framework, we recently demonstrated that variation in the Serotonin Transporter Promoter Polymorphism; 5HTTLPR and marker rs6330 in Nerve Growth Factor gene; NGF is associated with poorer outcomes following cognitive behaviour therapy (CBT) for child anxiety disorders. The aim of this study was to explore one potential means of extending the translational reach of G×E data in a way that may be clinically informative. We describe a ‘risk-index’ approach combining genetic, demographic and clinical data and test its ability to predict diagnostic outcome following CBT in anxious children. Method. DNA and clinical data were collected from 384 children with a primary anxiety disorder undergoing CBT. We tested our risk model in five cross-validation training sets. Results. In predicting treatment outcome, six variables had a minimum mean beta value of 0.5: 5HTTLPR, NGF rs6330, gender, primary anxiety severity, comorbid mood disorder and comorbid externalising disorder. A risk index (range 0-8) constructed from these variables had moderate predictive ability (AUC = .62-.69) in this study. Children scoring high on this index (5-8) were approximately three times as likely to retain their primary anxiety disorder at follow-up as compared to those children scoring 2 or less. Conclusion. Significant genetic, demographic and clinical predictors of outcome following CBT for anxiety-disordered children were identified. Combining these predictors within a risk-index could be used to identify which children are less likely to be diagnosis free following CBT alone or thus require longer or enhanced treatment. The ‘risk-index’ approach represents one means of harnessing the translational potential of G×E data.
Resumo:
A Lagrangian model of photochemistry and mixing is described (CiTTyCAT, stemming from the Cambridge Tropospheric Trajectory model of Chemistry And Transport), which is suitable for transport and chemistry studies throughout the troposphere. Over the last five years, the model has been developed in parallel at several different institutions and here those developments have been incorporated into one "community" model and documented for the first time. The key photochemical developments include a new scheme for biogenic volatile organic compounds and updated emissions schemes. The key physical development is to evolve composition following an ensemble of trajectories within neighbouring air-masses, including a simple scheme for mixing between them via an evolving "background profile", both within the boundary layer and free troposphere. The model runs along trajectories pre-calculated using winds and temperature from meteorological analyses. In addition, boundary layer height and precipitation rates, output from the analysis model, are interpolated to trajectory points and used as inputs to the mixing and wet deposition schemes. The model is most suitable in regimes when the effects of small-scale turbulent mixing are slow relative to advection by the resolved winds so that coherent air-masses form with distinct composition and strong gradients between them. Such air-masses can persist for many days while stretching, folding and thinning. Lagrangian models offer a useful framework for picking apart the processes of air-mass evolution over inter-continental distances, without being hindered by the numerical diffusion inherent to global Eulerian models. The model, including different box and trajectory modes, is described and some output for each of the modes is presented for evaluation. The model is available for download from a Subversion-controlled repository by contacting the corresponding authors.
Resumo:
A range of possible changes in the frequency and characteristics of European wind storms under future climate conditions was investigated on the basis of a multi-model ensemble of 9 coupled global climate model (GCM) simulations for the 20th and 21st centuries following the IPCC SRES A1B scenario. A multi-model approach allowed an estimation of the (un)certainties of the climate change signals. General changes in large-scale atmospheric flow were analysed, the occurrence of wind storms was quantified, and atmospheric features associated with wind storm events were considered. Identified storm days were investigated according to atmospheric circulation, associated pressure patterns, cyclone tracks and wind speed patterns. Validation against reanalysis data revealed that the GCMs are in general capable of realistically reproducing characteristics of European circulation weather types (CWTs) and wind storms. Results are given with respect to frequency of occurrence, storm-associated flow conditions, cyclone tracks and specific wind speed patterns. Under anthropogenic climate change conditions (SRES A1B scenario), increased frequency of westerly flow during winter is detected over the central European investigation area. In the ensemble mean, the number of detected wind storm days increases between 19 and 33% for 2 different measures of storminess, only 1 GCM revealed less storm days. The increased number of storm days detected in most models is disproportionately high compared to the related CWT changes. The mean intensity of cyclones associated with storm days in the ensemble mean increases by about 10 (±10)% in the Eastern Atlantic, near the British Isles and in the North Sea. Accordingly, wind speeds associated with storm events increase significantly by about 5 (±5)% over large parts of central Europe, mainly on days with westerly flow. The basic conclusions of this work remain valid if different ensemble contructions are considered, leaving out an outlier model or including multiple runs of one particular model.
Resumo:
The present article addresses the following question: what variables condition syntactic transfer? Evidence is provided in support of the position that third language (L3) transfer is selective, whereby, at least under certain conditions, it is driven by the typological proximity of the target L3 measured against the other previously acquired linguistic systems (cf. Rothman and Cabrelli Amaro, 2007, 2010; Rothman, 2010; Montrul et al., 2011). To show this, we compare data in the domain of adjectival interpretation between successful first language (L1) Italian learners of English as a second language (L2) at the low to intermediate proficiency level of L3 Spanish, and successful L1 English learners of L2 Spanish at the same levels for L3 Brazilian Portuguese. The data show that, irrespective of the L1 or the L2, these L3 learners demonstrate target knowledge of subtle adjectival semantic nuances obtained via noun-raising, which English lacks and the other languages share. We maintain that such knowledge is transferred to the L3 from Italian (L1) and Spanish (L2) respectively in light of important differences between the L3 learners herein compared to what is known of the L2 Spanish performance of L1 English speakers at the same level of proficiency (see, for example, Judy et al., 2008; Rothman et al., 2010). While the present data are consistent with Flynn et al.’s (2004) Cumulative Enhancement Model, we discuss why a coupling of these data with evidence from other recent L3 studies suggests necessary modifications to this model, offering in its stead the Typological Primacy Model (TPM) for multilingual transfer.
Resumo:
Neurovascular coupling in response to stimulation of the rat barrel cortex was investigated using concurrent multichannel electrophysiology and laser Doppler flowmetry. The data were used to build a linear dynamic model relating neural activity to blood flow. Local field potential time series were subject to current source density analysis, and the time series of a layer IV sink of the barrel cortex was used as the input to the model. The model output was the time series of the changes in regional cerebral blood flow (CBF). We show that this model can provide excellent fit of the CBF responses for stimulus durations of up to 16 s. The structure of the model consisted of two coupled components representing vascular dilation and constriction. The complex temporal characteristics of the CBF time series were reproduced by the relatively simple balance of these two components. We show that the impulse response obtained under the 16-s duration stimulation condition generalised to provide a good prediction to the data from the shorter duration stimulation conditions. Furthermore, by optimising three out of the total of nine model parameters, the variability in the data can be well accounted for over a wide range of stimulus conditions. By establishing linearity, classic system analysis methods can be used to generate and explore a range of equivalent model structures (e.g., feed-forward or feedback) to guide the experimental investigation of the control of vascular dilation and constriction following stimulation.
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We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.