975 resultados para Response prediction
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The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. In this paper we show for the first time how the Ruelle linear response theory, developed for studying rigorously the impact of perturbations on general observables of non-equilibrium statistical mechanical systems, can be applied with great success to analyze the climatic response to general forcings. The crucial value of the Ruelle theory lies in the fact that it allows to compute the response of the system in terms of expectation values of explicit and computable functions of the phase space averaged over the invariant measure of the unperturbed state. We choose as test bed a classical version of the Lorenz 96 model, which, in spite of its simplicity, has a well-recognized prototypical value as it is a spatially extended one-dimensional model and presents the basic ingredients, such as dissipation, advection and the presence of an external forcing, of the actual atmosphere. We recapitulate the main aspects of the general response theory and propose some new general results. We then analyze the frequency dependence of the response of both local and global observables to perturbations having localized as well as global spatial patterns. We derive analytically several properties of the corresponding susceptibilities, such as asymptotic behavior, validity of Kramers-Kronig relations, and sum rules, whose main ingredient is the causality principle. We show that all the coefficients of the leading asymptotic expansions as well as the integral constraints can be written as linear function of parameters that describe the unperturbed properties of the system, such as its average energy. Some newly obtained empirical closure equations for such parameters allow to define such properties as an explicit function of the unperturbed forcing parameter alone for a general class of chaotic Lorenz 96 models. We then verify the theoretical predictions from the outputs of the simulations up to a high degree of precision. The theory is used to explain differences in the response of local and global observables, to define the intensive properties of the system, which do not depend on the spatial resolution of the Lorenz 96 model, and to generalize the concept of climate sensitivity to all time scales. We also show how to reconstruct the linear Green function, which maps perturbations of general time patterns into changes in the expectation value of the considered observable for finite as well as infinite time. Finally, we propose a simple yet general methodology to study general Climate Change problems on virtually any time scale by resorting to only well selected simulations, and by taking full advantage of ensemble methods. The specific case of globally averaged surface temperature response to a general pattern of change of the CO2 concentration is discussed. We believe that the proposed approach may constitute a mathematically rigorous and practically very effective way to approach the problem of climate sensitivity, climate prediction, and climate change from a radically new perspective.
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An NIR reflectance sensor, with a large field of view and a fibre-optic connection to a spectrometer for measuring light backscatter at 980 nm, was used to monitor the syneresis process online during cheese-making with the goal of predicting syneresis indices (curd moisture content, yield of whey and fat losses to whey) over a range of curd cutting programmes and stirring speeds. A series of trials were carried out in an 11 L cheese vat using recombined whole milk. A factorial experimental design consisting of three curd stirring speeds and three cutting programmes, was undertaken. Milk was coagulated under constant conditions and the casein gel was cut when the elastic modulus reached 35 Pa. Among the syneresis indices investigated, the most accurate and most parsimonious multivariate model developed was for predicting yield of whey involving three terms, namely light backscatter, milk fat content and cutting intensity (R2 = 0.83, SEy = 6.13 g/100 g), while the best simple model also predicted this syneresis index using the light backscatter alone (R2 = 0.80, SEy = 6.53 g/100 g). In this model the main predictor was the light backscatter response from the NIR light back scatter sensor. The sensor also predicted curd moisture with a similar accuracy.
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This paper explores the sensitivity of Atmospheric General Circulation Model (AGCM) simulations to changes in the meridional distribution of sea surface temperature (SST). The simulations are for an aqua-planet, a water covered Earth with no land, orography or sea-ice and with specified zonally symmetric SST. Simulations from 14 AGCMs developed for Numerical Weather Prediction and climate applications are compared. Four experiments are performed to study the sensitivity to the meridional SST profile. These profiles range from one in which the SST gradient continues to the equator to one which is flat approaching the equator, all with the same maximum SST at the equator. The zonal mean circulation of all models shows strong sensitivity to latitudinal distribution of SST. The Hadley circulation weakens and shifts poleward as the SST profile flattens in the tropics. One question of interest is the formation of a double versus a single ITCZ. There is a large variation between models of the strength of the ITCZ and where in the SST experiment sequence they transition from a single to double ITCZ. The SST profiles are defined such that as the equatorial SST gradient flattens, the maximum gradient increases and moves poleward. This leads to a weakening of the mid-latitude jet accompanied by a poleward shift of the jet core. Also considered are tropical wave activity and tropical precipitation frequency distributions. The details of each vary greatly between models, both with a given SST and in the response to the change in SST. One additional experiment is included to examine the sensitivity to an off-equatorial SST maximum. The upward branch of the Hadley circulation follows the SST maximum off the equator. The models that form a single precipitation maximum when the maximum SST is on the equator shift the precipitation maximum off equator and keep it centered over the SST maximum. Those that form a double with minimum on the equatorial maximum SST shift the double structure off the equator, keeping the minimum over the maximum SST. In both situations only modest changes appear in the shifted profile of zonal average precipitation. When the upward branch of the Hadley circulation moves into the hemisphere with SST maximum, the zonal average zonal, meridional and vertical winds all indicate that the Hadley cell in the other hemisphere dominates.
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The inclusion of the direct and indirect radiative effects of aerosols in high-resolution global numerical weather prediction (NWP) models is being increasingly recognised as important for the improved accuracy of short-range weather forecasts. In this study the impacts of increasing the aerosol complexity in the global NWP configuration of the Met Office Unified Model (MetUM) are investigated. A hierarchy of aerosol representations are evaluated including three-dimensional monthly mean speciated aerosol climatologies, fully prognostic aerosols modelled using the CLASSIC aerosol scheme and finally, initialised aerosols using assimilated aerosol fields from the GEMS project. The prognostic aerosol schemes are better able to predict the temporal and spatial variation of atmospheric aerosol optical depth, which is particularly important in cases of large sporadic aerosol events such as large dust storms or forest fires. Including the direct effect of aerosols improves model biases in outgoing long-wave radiation over West Africa due to a better representation of dust. However, uncertainties in dust optical properties propagate to its direct effect and the subsequent model response. Inclusion of the indirect aerosol effects improves surface radiation biases at the North Slope of Alaska ARM site due to lower cloud amounts in high-latitude clean-air regions. This leads to improved temperature and height forecasts in this region. Impacts on the global mean model precipitation and large-scale circulation fields were found to be generally small in the short-range forecasts. However, the indirect aerosol effect leads to a strengthening of the low-level monsoon flow over the Arabian Sea and Bay of Bengal and an increase in precipitation over Southeast Asia. Regional impacts on the African Easterly Jet (AEJ) are also presented with the large dust loading in the aerosol climatology enhancing of the heat low over West Africa and weakening the AEJ. This study highlights the importance of including a more realistic treatment of aerosol–cloud interactions in global NWP models and the potential for improved global environmental prediction systems through the incorporation of more complex aerosol schemes.
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We predicted that P-fertiliser residues will limit the establishment of native plant species and their mycorrhizas to old-fields in the wheat-growing region (i.e. the wheatbelt) of Western Australia. To test this prediction, we assessed the growth and P uptake of seedlings of three native plant species to phosphate addition and inoculation with arbuscular mycorrhizas (AM) in a pot study. The native plant species were Acacia acuminata Benth. (Mimosaceae), Eucalyptus loxophleba Benth. subsp. loxophleba (Myrtaceae) and Hakea preissii Meisn. (Proteaceae); and each pot contained one seedling. P was added to field soil to mimic pre-agricultural (P0), old-field (P1) and 10 times old-field (P10) soils. AM inoculant, which was a mix of Scutellospora calospora (Nicolson and Gerdemann) Walker and Sanders, Glomus intraradices Schenck and Smith and Glomus mosseae (Nicolson and Gerdemann) Gerdemann and Trappe, was added to half of the pots. After 12 weeks, the biomass and P uptake of the mycorrhizal A. acuminata were greater than those of the non-mycorrhizal plants across all P treatments. Plant biomass decreased significantly with increasing P addition, yet this species was apparently unable to suppress its mycorrhizal colonisation at high P despite this reduction in growth. In contrast, mycorrhizal and non-mycorrhizal E. loxophleba subsp. loxophleba were of a similar biomass after 12 weeks; maximum biomass was attained at intermediate (old-field) levels of P. P uptake increased with increasing P supply, beyond that required to attain maximum biomass. AM did not form on H. preissii. P uptake increased with increasing P supply for this species also. Overall, it is the apparent inability of these species to down-regulate P uptake rather than a lack of mycorrhizal symbiosis that will constrain their establishment on wheatbelt old-fields.
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Caulobacter crescentus sigma(E) belongs to the ECF (extracytoplasmic function) subfamily of RNA polymerase sigma factors, whose members regulate gene expression in response to distinct environmental stresses. During physiological growth conditions, data indicate that sigma(E) is maintained in reduced levels due to the action of ChrR, a negative regulator of rpoE gene expression and function. However, once bacterial cells are exposed to cadmium, organic hydroperoxide, singlet oxygen or UV-A irradiation, transcription of rpoE is induced in a sigma(E)-dependent manner. Site-directed mutagenesis indicated that residue C188 in ChrR is critical for the cadmium response while residues H140 and H142 are required for the bacterial response to organic hydroperoxide, singlet oxygen and UV-A. Global transcriptional analysis showed that sigma(E) regulates genes involved in protecting cells against oxidative damages. A combination of transcriptional start site identification and promoter prediction revealed that some of these genes contain a putative sigma(E)-dependent motif in their upstream regions. Furthermore, deletion of rpoE and two sigma(E)-dependent genes (cfaS and hsp20) impairs Caulobacter survival when singlet oxygen is constantly generated in the cells.
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Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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OBJECTIVE: To estimate the response in lung growth and vascularity after fetal endoscopic tracheal occlusion for severe congenital diaphragmatic hernia in the prediction of neonatal survival.METHODS: Between January 2006 and December 2010, fetal lung parameters (observed-to-expected lung-to-head ratio; observed-to-expected lung volume; and contralateral lung vascularization index) were evaluated before fetal tracheal occlusion and were evaluated longitudinally every 2 weeks in 72 fetuses with severe isolated congenital diaphragmatic hernia. Thirty-five fetuses underwent fetal endoscopic tracheal occlusion and 37 cases did not.RESULTS: Survival rate was significantly higher in the fetal endoscopic tracheal occlusion group (54.3%) than in the no fetal endoscopic tracheal occlusion group (5.4%, P<.01). Fetal endoscopic tracheal occlusion resulted in a significant improvement in fetal lung size and pulmonary vascularity when compared with fetuses that did not go to the fetal intervention (increase of the observed-to-expected lung-to-head ratio, observed-to-expected total lung volume, and contralateral pulmonary vascularization index 56.2% compared with 0.3%, 37.9% compared with 0.1%, and 98.6% compared with 0.0%, respectively; P<.01). Receiver operating characteristic curves indicated that the observed-to-expected total fetal lung volume was the single best predictor of neonatal survival before fetal endoscopic tracheal occlusion (cutoff 0.23, area under the curve [AUC] 0.88, relative risk 5.3, 95% confidence interval [CI] 1.4-19.7). However, the contralateral lung vascularization index at 4 weeks after fetal endoscopic tracheal occlusion was more accurate in the prediction of neonatal outcome (cutoff 24.0%, AUC 0.98, relative risk 9.9, 95% CI 1.5-66.9) with the combination of observed-to-expected lung volumes and contralateral lung vascularization index at 4 weeks being the best predictor of outcome (AUC 0.98, relative risk 16.6, 95% CI 2.5-112.3).CONCLUSION: Fetal endoscopic tracheal occlusion improves survival rate by increasing the lung size and pulmonary vascularity in fetuses with severe congenital diaphragmatic hernia. The pulmonary response after fetal endoscopic tracheal occlusion can be used to predict neonatal survival. (Obstet Gynecol 2012; 119: 93-101) DOI: 10.1097/AOG.0b013e31823d3aea
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In this paper, we extend the use of the variance dispersion graph (VDG) to experiments in which the response surface (RS) design must be blocked. Through several examples we evaluate the prediction performances of RS designs in non-orthogonal block designs compared with the equivalent unblocked designs and orthogonally blocked designs. These examples illustrate that good prediction performance of designs in small blocks can be expected in practice. Most importantly, we show that the allocation of the treatment set to blocks can seriously affect the prediction properties of designs; thus, much care is needed in performing this allocation.
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It is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.
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Torsional vibration predictions and measurements of a marine propulsion system, which has both damping and a highly flexible coupling, are presented in this paper. Using the conventional approach to stress prediction in the shafting system, the numerical predictions and the experimental torsional vibration stress curves in some parts of the shafting system are found to be quite different. The free torsional vibration characteristics and forced torsional vibration response of the system are analyzed in detail to investigate this phenomenon. It is found that the second to fourth natural modes of the shafting system have significant local deformation. This results in large torsional resonant responses in different sections of the system corresponding to different engine speeds. The results show that when there is significant local deformation in the shafting system for different modes, then multi-point measurements should be made, rather than the conventional method of using a single measurement at the free end of the shaft, to obtain the full torsional vibration characteristics of the shafting system.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)