909 resultados para EVALUATION MODEL
Resumo:
An in vitro study was conducted to investigate the effect of tannins on the extent and rate of gas and methane production, using an automated pressure evaluation system (APES). In this study three condensed tannins (CT; quebracho, grape seed and green tea tannins) and four hydrolysable tannins (HT; tara, valonea, myrabolan and chestnut tannins) were evaluated, with lucerne as a control substrate. CT and HT were characterised by matrix assisted laser desorption ionisation-time of flight mass spectrometry (MALDI-TOF-MS). Tannins were added to the substrate at an effective concentration of 100 g/kg either with or without polyethylene glycol (PEG6000), and incubated for 72 h in pooled, buffered rumen liquid from four lactating dairy cows. After inoculation, fermentation bottles were immediately connected to the APES to measure total cumulative gas production (GP). During the incubation, 11 gas samples were collected from each bottle at 0, 1, 4, 7, 11, 15, 23, 30, 46, 52 and 72 h of incubation and analysed for methane. A modified Michaelis-Menten model was fitted to the methane concentration patterns and model estimates were used to calculate the total cumulative methane production (GPCH4). GP and GPCH4 curves were fitted using a modified monophasic Michaelis-Menten model. Addition of quebracho reduced GP (P=0.002), whilst the other tannins did not affect GP. Addition of PEG increased GP for quebracho (P=0.003), valonea (P=0.058) and grape seed tannins (P=0.071), suggesting that these tannins either inhibited or tended to inhibit fermentation. Addition of quebracho and grape seed tannins also reduced (P≤0.012) the maximum rate of gas production, indicating that microbial activity was affected. Quebracho, valonea, myrabolan and grape seed decreased (P≤0.003) GPCH4 and the maximum rate (0.001≤ P≤ 0.102) of CH4 production. Addition of chestnut, green tea and tara tannins did not affect total gas nor methane production. Valonea and myrabolan tannins have most promise for reducing methane production as they had only a minor impact on gas production.
Resumo:
Ice cloud representation in general circulation models remains a challenging task, due to the lack of accurate observations and the complexity of microphysical processes. In this article, we evaluate the ice water content (IWC) and ice cloud fraction statistical distributions from the numerical weather prediction models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office, exploiting the synergy between the CloudSat radar and CALIPSO lidar. Using the last three weeks of July 2006, we analyse the global ice cloud occurrence as a function of temperature and latitude and show that the models capture the main geographical and temperature-dependent distributions, but overestimate the ice cloud occurrence in the Tropics in the temperature range from −60 °C to −20 °C and in the Antarctic for temperatures higher than −20 °C, but underestimate ice cloud occurrence at very low temperatures. A global statistical comparison of the occurrence of grid-box mean IWC at different temperatures shows that both the mean and range of IWC increases with increasing temperature. Globally, the models capture most of the IWC variability in the temperature range between −60 °C and −5 °C, and also reproduce the observed latitudinal dependencies in the IWC distribution due to different meteorological regimes. Two versions of the ECMWF model are assessed. The recent operational version with a diagnostic representation of precipitating snow and mixed-phase ice cloud fails to represent the IWC distribution in the −20 °C to 0 °C range, but a new version with prognostic variables for liquid water, ice and snow is much closer to the observed distribution. The comparison of models and observations provides a much-needed analysis of the vertical distribution of IWC across the globe, highlighting the ability of the models to reproduce much of the observed variability as well as the deficiencies where further improvements are required.
Resumo:
Purpose – The purpose of this paper is to investigate the effect of choices of model structure and scale in development viability appraisal. The paper addresses two questions concerning the application of development appraisal techniques to viability modelling within the UK planning system. The first relates to the extent to which, given intrinsic input uncertainty, the choice of model structure significantly affects model outputs. The second concerns the extent to which, given intrinsic input uncertainty, the level of model complexity significantly affects model outputs. Design/methodology/approach – Monte Carlo simulation procedures are applied to a hypothetical development scheme in order to measure the effects of model aggregation and structure on model output variance. Findings – It is concluded that, given the particular scheme modelled and unavoidably subjective assumptions of input variance, that simple and simplistic models may produce similar outputs to more robust and disaggregated models. Evidence is found of equifinality in the outputs of a simple, aggregated model of development viability relative to more complex, disaggregated models. Originality/value – Development viability appraisal has become increasingly important in the planning system. Consequently, the theory, application and outputs from development appraisal are under intense scrutiny from a wide range of users. However, there has been very little published evaluation of viability models. This paper contributes to the limited literature in this area.
Resumo:
As in any technology systems, analysis and design issues are among the fundamental challenges in persuasive technology. Currently, the Persuasive Systems Development (PSD) framework is considered to be the most comprehensive framework for designing and evaluation of persuasive systems. However, the framework is limited in terms of providing detailed information which can lead to selection of appropriate techniques depending on the variable nature of users or use over time. In light of this, we propose a model which is intended for analysing and implementing behavioural change in persuasive technology called the 3D-RAB model. The 3D-RAB model represents the three dimensional relationships between attitude towards behaviour, attitude towards change or maintaining a change, and current behaviour, and distinguishes variable levels in a user’s cognitive state. As such it provides a framework which could be used to select appropriate techniques for persuasive technology.
Resumo:
This paper investigates the effect of choices of model structure and scale in development viability appraisal. The paper addresses two questions concerning the application of development appraisal techniques to viability modelling within the UK planning system. The first relates to the extent to which, given intrinsic input uncertainty, the choice of model structure significantly affects model outputs. The second concerns the extent to which, given intrinsic input uncertainty, the level of model complexity significantly affects model outputs. Monte Carlo simulation procedures are applied to a hypothetical development scheme in order to measure the effects of model aggregation and structure on model output variance. It is concluded that, given the particular scheme modelled and unavoidably subjective assumptions of input variance, that simple and simplistic models may produce similar outputs to more robust and disaggregated models.
Resumo:
This study investigates whether commercial offices designed by signature architects in the United States achieve rental premiums compared to commercial offices designed by nonsignature architects. Focusing on buildings designed by winners of the Prizker Prize and the Gold Medal awarded by the American Institute of Architects, we create a sample of commercial office buildings designed by signature architects drawing on CoStar's national database. We use a combination of hedonic regression model and a logit model to estimate the various rent determinants. While the first stage measures the typical rental price differential above the typical building in a particular sub-market over a specific timeframe, the second stage identifies a potential price differential over a set of buildings closely matched on important characteristics (such as age, size, location etc.). We find that in both stages offices design by signature architects exhibit a premium. However these results are preliminary. The premium could be indeed an effect of the name of the architect, but others factors such as micro-market conditions might be the cause. Further tests are needed to confirm the validity of our results.
Resumo:
Motivation: The ability of a simple method (MODCHECK) to determine the sequence–structure compatibility of a set of structural models generated by fold recognition is tested in a thorough benchmark analysis. Four Model Quality Assessment Programs (MQAPs) were tested on 188 targets from the latest LiveBench-9 automated structure evaluation experiment. We systematically test and evaluate whether the MQAP methods can successfully detect native-likemodels. Results: We show that compared with the other three methods tested MODCHECK is the most reliable method for consistently performing the best top model selection and for ranking the models. In addition, we show that the choice of model similarity score used to assess a model's similarity to the experimental structure can influence the overall performance of these tools. Although these MQAP methods fail to improve the model selection performance for methods that already incorporate protein three dimension (3D) structural information, an improvement is observed for methods that are purely sequence-based, including the best profile–profile methods. This suggests that even the best sequence-based fold recognition methods can still be improved by taking into account the 3D structural information.
Resumo:
An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km. The 15-year integrations were forced from reanalyses and observed sea surface temperature and sea ice (global model from sea surface only). The observational reference is based on 6400 rain gauge records (10–50 stations per grid box). Evaluation statistics encompass mean precipitation, wet-day frequency, precipitation intensity, and quantiles of the frequency distribution. For mean precipitation, the models reproduce the characteristics of the annual cycle and the spatial distribution. The domain mean bias varies between −23% and +3% in winter and between −27% and −5% in summer. Larger errors are found for other statistics. In summer, all models underestimate precipitation intensity (by 16–42%) and there is a too low frequency of heavy events. This bias reflects too dry summer mean conditions in three of the models, while it is partly compensated by too many low-intensity events in the other two models. Similar intermodel differences are found for other European subregions. Interestingly, the model errors are very similar between the two models with the same dynamical core (but different parameterizations) and they differ considerably between the two models with similar parameterizations (but different dynamics). Despite considerable biases, the models reproduce prominent mesoscale features of heavy precipitation, which is a promising result for their use in climate change downscaling over complex topography.
Resumo:
This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.
Resumo:
As in any technology systems, analysis and design issues are among the fundamental challenges in persuasive technology. Currently, the Persuasive Systems Development (PSD) framework is considered to be the most comprehensive framework for designing and evaluation of persuasive systems. However, the framework is limited in terms of providing detailed information which can lead to selection of appropriate techniques depending on the variable nature of users or use over time. In light of this, we propose a model which is intended for analysing and implementing behavioural change in persuasive technology called the 3D-RAB model. The 3D-RAB model represents the three dimensional relationships between attitude towards behaviour, attitude towards change or maintaining a change, and current behaviour, and distinguishes variable levels in a user’s cognitive state. As such it provides a framework which could be used to select appropriate techniques for persuasive technology.
Resumo:
Polyvinylpyrrolidone is a widely used in tablet formulations with the linear form acting as a wetting agent and disintegrant whereas the cross-linked form is a super-disintegrant. We have previously reported that simply mixing the commercial cross-linked polymer with ibuprofen disrupted drug crystallinity with consequent improvements in drug dissolution behavior. In this study, we have designed and synthesized novel cross-linking agents containing a range of oligoether moieties which have then be polymerized with vinylpyrrolidone to generate a suite of novel excipients with enhanced hydrogen-bonding capabilities. The polymers have a porous surface and swell in most common solvents and in water; properties which suggest their value as disintegrants. The polymers were evaluated in simple physical mixtures with ibuprofen as a model poorly-water soluble drug. The results show that the novel PVPs induce the drug to become “X-ray amorphous”, which increased dissolution to a greater extent than that seen with commercial cross-linked PVP. The polymers stabilize the amorphous drug with no evidence for recrystallization seen after 20 weeks storage.
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.
Resumo:
A manageable, relatively inexpensive model was constructed to predict the loss of nitrogen and phosphorus from a complex catchment to its drainage system. The model used an export coefficient approach, calculating the total nitrogen (N) and total phosphorus (P) load delivered annually to a water body as the sum of the individual loads exported from each nutrient source in its catchment. The export coefficient modelling approach permits scaling up from plot-scale experiments to the catchment scale, allowing application of findings from field experimental studies at a suitable scale for catchment management. The catchment of the River Windrush, a tributary of the River Thames, UK, was selected as the initial study site. The Windrush model predicted nitrogen and phosphorus loading within 2% of observed total nitrogen load and 0.5% of observed total phosphorus load in 1989. The export coefficient modelling approach was then validated by application in a second research basin, the catchment of Slapton Ley, south Devon, which has markedly different catchment hydrology and land use. The Slapton model was calibrated within 2% of observed total nitrogen load and 2.5% of observed total phosphorus load in 1986. Both models proved sensitive to the impact of temporal changes in land use and management on water quality in both catchments, and were therefore used to evaluate the potential impact of proposed pollution control strategies on the nutrient loading delivered to the River Windrush and Slapton Ley
Resumo:
We present a new approach to determine palaeotemperatures (mean annual surface temperatures) based on measurements of the liquid–vapour homogenisation temperature of fluid inclusions in stalagmites. The aim of this study is to explore the potential and the limitations of this new palaeothermometer and to develop a reliable methodology for routine applications in palaeoclimate research. Therefore, we have investigated recent fluid inclusions from the top part of actively growing stalagmites that have formed at temperatures close to the present-day cave air temperature. A precondition for measuring homogenisation temperatures of originally monophase inclusions is the nucleation of a vapour bubble by means of single ultra-short laser pulses. Based on the observed homogenisation temperatures (Th(obs)) and measurements of the vapour bubble diameter at a known temperature, we calculated stalagmite formation temperatures (Tf) by applying a thermodynamic model that takes into account the effect of surface tension on liquid–vapour homogenisation. Results from recent stalagmite samples demonstrate that calculated stalagmite formation temperatures match the present-day cave air temperature within ± 0.2 °C. To avoid artificially induced changes of the fluid density we defined specific demands on the selection, handling and preparation of the stalagmite samples. Application of the method is restricted to stalagmites that formed at cave temperatures greater than ~ 9–11 °C.
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We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.