983 resultados para large reservoirs


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We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated with a Gaussian process with long-time memory. As an application we establish a large deviation principle (LDP) for capacities for such Gaussian rough paths. Together with Lyons' universal limit theorem, our results yield immediately the corresponding results for pathwise solutions to stochastic differential equations driven by such Gaussian process in the sense of rough paths. Moreover, our LDP result implies the result of Yoshida on the LDP for capacities over the abstract Wiener space associated with such Gaussian process.

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A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

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The purpose of this paper is to investigate several analytical methods of solving first passage (FP) problem for the Rouse model, a simplest model of a polymer chain. We show that this problem has to be treated as a multi-dimensional Kramers' problem, which presents rich and unexpected behavior. We first perform direct and forward-flux sampling (FFS) simulations, and measure the mean first-passage time $\tau(z)$ for the free end to reach a certain distance $z$ away from the origin. The results show that the mean FP time is getting faster if the Rouse chain is represented by more beads. Two scaling regimes of $\tau(z)$ are observed, with transition between them varying as a function of chain length. We use these simulations results to test two theoretical approaches. One is a well known asymptotic theory valid in the limit of zero temperature. We show that this limit corresponds to fully extended chain when each chain segment is stretched, which is not particularly realistic. A new theory based on the well known Freidlin-Wentzell theory is proposed, where dynamics is projected onto the minimal action path. The new theory predicts both scaling regimes correctly, but fails to get the correct numerical prefactor in the first regime. Combining our theory with the FFS simulations lead us to a simple analytical expression valid for all extensions and chain lengths. One of the applications of polymer FP problem occurs in the context of branched polymer rheology. In this paper, we consider the arm-retraction mechanism in the tube model, which maps exactly on the model we have solved. The results are compared to the Milner-McLeish theory without constraint release, which is found to overestimate FP time by a factor of 10 or more.

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Lake surface water temperatures (LSWTs) of 246 globally distributed large lakes were derived from Along-Track Scanning Radiometers (ATSR) for the period 1991–2011. The climatological cycles of mean LSWT derived from these data quantify on a global scale the responses of large lakes' surface temperatures to the annual cycle of forcing by solar radiation and the ambient meteorological conditions. LSWT cycles reflect the twice annual peak in net solar radiation for lakes between 1°S to 12°N. For lakes without a lake-mean seasonal ice cover, LSWT extremes exceed air temperatures by 0.5–1.7 °C for maximum and 0.7–1.9 °C for minimum temperature. The summer maximum LSWTs of lakes from 25°S to 35°N show a linear decrease with increasing altitude; −3.76 ± 0.17 °C km−1 (inline image = 0.95), marginally lower than the corresponding air temperature decrease with altitude −4.15 ± 0.24 °C km−1 (inline image = 0.95). Lake altitude of tropical lakes account for 0.78–0.83 (inline image) of the variation in the March to June LSWT–air temperature differences, with differences decreasing by 1.9 °C as the altitude increases from 500 to 1800 m above sea level (a.s.l.) We define an ‘open water phase’ as the length of time the lake-mean LSWT remains above 4 °C. There is a strong global correlation between the start and end of the lake-mean open water phase and the spring and fall 0 °C air temperature transition days, (inline image = 0.74 and 0.80, respectively), allowing for a good estimation of timing and length of the open water phase of lakes without LSWT observations. Lake depth, lake altitude and distance from coast further explain some of the inter-lake variation in the start and end of the open water phase.

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A truly variance-minimizing filter is introduced and its per for mance is demonstrated with the Korteweg– DeV ries (KdV) equation and with a multilayer quasigeostrophic model of the ocean area around South Africa. It is recalled that Kalman-like filters are not variance minimizing for nonlinear model dynamics and that four - dimensional variational data assimilation (4DV AR)-like methods relying on per fect model dynamics have dif- ficulty with providing error estimates. The new method does not have these drawbacks. In fact, it combines advantages from both methods in that it does provide error estimates while automatically having balanced states after analysis, without extra computations. It is based on ensemble or Monte Carlo integrations to simulate the probability density of the model evolution. When obser vations are available, the so-called importance resampling algorithm is applied. From Bayes’ s theorem it follows that each ensemble member receives a new weight dependent on its ‘ ‘distance’ ’ t o the obser vations. Because the weights are strongly var ying, a resampling of the ensemble is necessar y. This resampling is done such that members with high weights are duplicated according to their weights, while low-weight members are largely ignored. In passing, it is noted that data assimilation is not an inverse problem by nature, although it can be for mulated that way . Also, it is shown that the posterior variance can be larger than the prior if the usual Gaussian framework is set aside. However , i n the examples presented here, the entropy of the probability densities is decreasing. The application to the ocean area around South Africa, gover ned by strongly nonlinear dynamics, shows that the method is working satisfactorily . The strong and weak points of the method are discussed and possible improvements are proposed.

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BACKGROUND AND OBJECTIVE: Given the role of uncoupling protein 2 (UCP2) in the accumulation of fat in the hepatocytes and in the enhancement of protective mechanisms in acute ethanol intake, we hypothesised that UCP2 polymorphisms are likely to cause liver disease through their interactions with obesity and alcohol intake. To test this hypothesis, we investigated the interaction between tagging polymorphisms in the UCP2 gene (rs2306819, rs599277 and rs659366), alcohol intake and obesity traits such as BMI and waist circumference (WC) on alanine aminotransferase (ALT) and gamma glutamyl transferase (GGT) in a large meta-analysis of data sets from three populations (n=20 242). DESIGN AND METHODS: The study populations included the Northern Finland Birth Cohort 1966 (n=4996), Netherlands Study of Depression and Anxiety (n=1883) and LifeLines Cohort Study (n=13 363). Interactions between the polymorphisms and obesity and alcohol intake on dichotomised ALT and GGT levels were assessed using logistic regression and the likelihood ratio test. RESULTS: In the meta-analysis of the three cohorts, none of the three UCP2 polymorphisms were associated with GGT or ALT levels. There was no evidence for interaction between the polymorphisms and alcohol intake on GGT and ALT levels. In contrast, the association of WC and BMI with GGT levels varied by rs659366 genotype (Pinteraction=0.03 and 0.007, respectively; adjusted for age, gender, high alcohol intake, diabetes, hypertension and serum lipid concentrations). CONCLUSION: In conclusion, our findings in 20 242 individuals suggest that UCP2 gene polymorphisms may cause liver dysfunction through the interaction with body fat rather than alcohol intake.

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As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloud-resolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison of the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less top-heavy compared to those produced by the WTG simulations. These large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.

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Drought events are projected to increase in frequency and magnitude, which may alter the composition of ecological communities. Using a functional community metric that describes abundance, life history traits and conservation status, based upon Grime’s CSR (Competitive-Stress tolerant-Ruderal)¬ scheme, we investigated how British butterfly communities changed during an extreme drought in 1995. Throughout Britain, the total abundance of these insects had a significant tendency to increase, accompanied by substantial changes in community composition, particularly in more northerly, wetter sites. Communities tended to shift away from specialist, vulnerable species, and towards generalist, widespread species and, in the year following, communities had yet to return to equilibrium. Importantly, heterogeneity in surrounding landscapes mediated community responses to the drought event. Contrary to expectation, however, community shifts were more extreme in areas of greater topographic diversity, whilst land-cover diversity buffered community changes and limited declines in vulnerable specialist butterflies.

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Haptic devices tend to be kept small as it is easier to achieve a large change of stiffness with a low associated apparent mass. If large movements are required there is a usually a reduction in the quality of the haptic sensations which can be displayed. The typical measure of haptic device performance is impedance-width (z-width) but this does not account for actuator saturation, usable workspace or the ability to do rapid movements. This paper presents the analysis and evaluation of a haptic device design, utilizing a variant of redundant kinematics, sometimes referred to as a macro-micro configuration, intended to allow large and fast movements without loss of impedance-width. A brief mathematical analysis of the design constraints is given and a prototype system is described where the effects of different elements of the control scheme can be examined to better understand the potential benefits and trade-offs in the design. Finally, the performance of the system is evaluated using a Fitts’ Law test and found to compare favourably with similar evaluations of smaller workspace devices.

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The Southern Ocean is a critical region for global climate, yet large cloud and solar radiation biases over the Southern Ocean are a long-standing problem in climate models and are poorly understood, leading to biases in simulated sea surface temperatures. This study shows that supercooled liquid clouds are central to understanding and simulating the Southern Ocean environment. A combination of satellite observational data and detailed radiative transfer calculations is used to quantify the impact of cloud phase and cloud vertical structure on the reflected solar radiation in the Southern Hemisphere summer. It is found that clouds with supercooled liquid tops dominate the population of liquid clouds. The observations show that clouds with supercooled liquid tops contribute between 27% and 38% to the total reflected solar radiation between 40° and 70°S, and climate models are found to poorly simulate these clouds. The results quantify the importance of supercooled liquid clouds in the Southern Ocean environment and highlight the need to improve understanding of the physical processes that control these clouds in order to improve their simulation in numerical models. This is not only important for improving the simulation of present-day climate and climate variability, but also relevant for increasing confidence in climate feedback processes and future climate projections.

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A comparison tool has been developed by mapping the global GPS total electron content (TEC) and large coverage of ionospheric scintillations together on the geomagnetic latitude/magnetic local time coordinates. Using this tool, a comparison between large-scale ionospheric irregularities and scintillations are pursued during a geomagnetic storm. Irregularities, such as storm enhanced density (SED), middle-latitude trough and polar cap patches, are clearly identified from the TEC maps. At the edges of these irregularities, clear scintillations appeared but their behaviors were different. Phase scintillations (σsub{φ}) were almost always larger than amplitude scintillations (S4) at the edges of these irregularities, associated with bursty flows or flow reversals with large density gradients. An unexpected scintillation feature appeared inside the modeled auroral oval where S4 were much larger than σsub{φ}, most likely caused by particle precipitations around the exiting polar cap patches.

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Four hundred and forty-eight samples of total blood from wild monkeys living in areas where human autochthonous malaria cases have been reported were screened for the presence of Plasmodium using microscopy and PCR analysis. Samples came from the following distinct ecological areas of Brazil: Atlantic forest (N = 140), semideciduous Atlantic forest (N = 257) and Cerrado (a savannah-like habitat) (N = 51). Thick and thin blood smears of each specimen were examined and Plasmodium infection was screened by multiplex polymerase chain reaction (multiplex PCR). The frequency of Plasmodium infections detected by PCR in Alouatta guariba clamitans in the Sao Paulo Atlantic forest was 11.3% or 8/71 (5.6% for Plasmodium malariae and 5.6% for Plasmodium vivax) and one specimen was positive for Plasmodium falciparum (1.4%); Callithrix sp. (N = 30) and Cebus apella (N = 39) specimens were negative by PCR tests. Microscopy analysis was negative for all specimens from the Atlantic forest. The positivity rate for Alouatta caraya from semideciduous Atlantic forest was 6.8% (16/235) in the PCR tests (5.5, 0.8 and 0.4% for P. malariae, P. falciparum and P. vivax, respectively), while C apella specimens were negative. Parasitological examination of I he samples using thick smears revealed Plasmodium sp. infections in only seven specimens, which had few parasites (3.0%). Monkeys from the Cerrado (a savannah-like habitat) (42 specimens of A. caraya, 5 of Callithrix jacchus and 4 of C. apella) were negative in both tests. The parasitological prevalence of P. vivax and P. malariae in wild monkeys from Atlantic forest and semideciduous Atlantic forest and the finding of a positive result for P.falciparum in Alouatta from both types of forest support the hypothesis that monkeys belonging to this genus could be a potential reservoir. Furthermore, these findings raise the question of the relationship between simian and autochthonous human malaria in extra-Amazonian regions. (C) 2008 Elsevier B.V. All rights reserved.

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Aeromonads are inhabitants of aquatic ecosystems and are described as being involved in intestinal disturbances and other infections. A total of 200 drinking water samples from domestic and public reservoirs and drinking fountains located in Sao Paulo (Brazil), were analyzed for the presence of Aeromonas. Samples were concentrated by membrane filtration and enriched in APW. ADA medium was used for Aeromonas isolation and colonies were confirmed by biochemical characterization. Strains isolated were tested for hemolysin and toxin production. Aeromonas was detected in 12 samples (6.0%). Aeromonas strains (96) were isolated and identified as: A. caviae (41.7%), A. hydrophila (15.7%), A. allosacharophila (10.4%), A. schubertii (1.0%) and Aeromonas spp. (31.2%). The results revealed that 70% of A. caviare, 66.7% of A. hydrophila, 80% of A. allosacharophila and 46.6% of Aeromonas spp. were hemolytic. The assay for checking production of toxins showed that 17.5% of A. caviae, 73.3% of A. hydrophila, 60% of A. allosacharophila, 100% of A. schubertii, and 33.3% of Aeromonas spp. were able to produce toxins. The results demonstrated the pathogenic potential of Aeromonas, indicating that the presence of this emerging pathogen in water systems is a public health concern.

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The mechanisms resulting in large daily rainfall events in Northeast Brazil are analyzed using data filtering to exclude periods longer than 30 days. Composites of circulation fields that include all independent events do not reveal any obvious forcing mechanisms as multiple patterns contribute to Northeast Brazil precipitation variability. To isolate coherent patterns, subsets of events are selected based on anomalies that precede the Northeast Brazil precipitation events at different locations. The results indicate that at 10 degrees S, 40 degrees W, the area of lowest annual rainfall in Brazil, precipitation occurs mainly in association with trailing midlatitude synoptic wave trains originating in either hemisphere. Closer to the equator at 5 degrees S, 37.5 degrees W, an additional convection precursor is found to the west, with a spatial structure consistent with that of a Kelvin wave. Although these two sites are located within only several hundred kilometers of each other and the midlatitude patterns that induce precipitation appear to be quite similar, the dates on which large precipitation anomalies occur at each location are almost entirely independent, pointing to separate forcing mechanisms.