944 resultados para Fibonacci series and golden ratio


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This paper assesses the implications of climate policy for exposure to water resources stresses. It compares a Reference scenario which leads to an increase in global mean temperature of 4oC by the end of the 21st century with a Mitigation scenario which stabilises greenhouse gas concentrations at around 450ppm CO2e and leads to a 2oC increase in 2100. Associated changes in river runoff are simulated using a global hydrological model, for four spatial patterns of change in temperature and rainfall. There is a considerable difference in hydrological change between these four patterns, but the percentages of change avoided at the global scale are relatively robust. By the 2050s, the Mitigation scenario typically avoids between 16 and 30% of the change in runoff under the Reference scenario, and by 2100 it avoids between 43 and 65%. Two different measures of exposure to water resources stress are calculated, based on resources per capita and the ratio of withdrawals to resources. Using the first measure, the Mitigation scenario avoids 8-17% of the impact in 2050 and 20-31% in 2100; with the second measure, the avoided impacts are 5-21% and 15-47% respectively. However, at the same time, the Mitigation scenario also reduces the positive impacts of climate change on water scarcity in other areas. The absolute numbers and locations of people affected by climate change and climate policy vary considerably between the four climate model patterns.

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The PPARγ2 gene SNP Pro12Ala has shown variable association with metabolic syndrome traits in healthy subjects. We investigated the effect of interaction between genotype and the ratio of polyunsaturated:saturated (P:S) fatty acid intake on plasma lipids in 367 White subjects aged 30-70 y at increased cardiometabolic risk, in the RISCK study. Interaction was determined after habitual diet at recruitment, at baseline after a 4-week high-SFA (HS) diet and after 24-week reference (HS), high-MUFA (HM) and low-fat (LF) diets. At recruitment, there were no significant associations between genotype and plasma lipids, however, P:S x genotype interaction influenced plasma total cholesterol (TC) (P=0.02), LDL-cholesterol (LDL-C) (P=0.002) and triglyceride (TG) (P=0.02) concentrations. At P:S ratio ≤0.33, mean TC and LDL-C concentrations in Ala12 allele carriers were significantly higher than in non-carriers (respectively P=0.003; P=0.0001). Significant trends in reduction of plasma TC (P=0.02) and TG (P=0.002) concentrations occurred with increasing P:S (respectively ≤0.33 to >0.65 and 0.34 to >0.65) in Ala12 allele carriers. There were no significant differences between carriers and non-carriers after the 4-week HS diet or 24-week interventions. Plasma TC and TG concentrations in PPARG Ala12 allele carriers decrease as P:S increases, but are not dependent on a reduction in SFA intake.

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Drought characterisation is an intrinsically spatio-temporal problem. A limitation of previous approaches to characterisation is that they discard much of the spatio-temporal information by reducing events to a lower-order subspace. To address this, an explicit 3-dimensional (longitude, latitude, time) structure-based method is described in which drought events are defined by a spatially and temporarily coherent set of points displaying standardised precipitation below a given threshold. Geometric methods can then be used to measure similarity between individual drought structures. Groupings of these similarities provide an alternative to traditional methods for extracting recurrent space-time signals from geophysical data. The explicit consideration of structure encourages the construction of summary statistics which relate to the event geometry. Example measures considered are the event volume, centroid, and aspect ratio. The utility of a 3-dimensional approach is demonstrated by application to the analysis of European droughts (15 °W to 35°E, and 35 °N to 70°N) for the period 1901–2006. Large-scale structure is found to be abundant with 75 events identified lasting for more than 3 months and spanning at least 0.5 × 106 km2. Near-complete dissimilarity is seen between the individual drought structures, and little or no regularity is found in the time evolution of even the most spatially similar drought events. The spatial distribution of the event centroids and the time evolution of the geographic cross-sectional areas strongly suggest that large area, sustained droughts result from the combination of multiple small area (∼106 km2) short duration (∼3 months) events. The small events are not found to occur independently in space. This leads to the hypothesis that local water feedbacks play an important role in the aggregation process.

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Geophysical time series sometimes exhibit serial correlations that are stronger than can be captured by the commonly used first‐order autoregressive model. In this study we demonstrate that a power law statistical model serves as a useful upper bound for the persistence of total ozone anomalies on monthly to interannual timescales. Such a model is usually characterized by the Hurst exponent. We show that the estimation of the Hurst exponent in time series of total ozone is sensitive to various choices made in the statistical analysis, especially whether and how the deterministic (including periodic) signals are filtered from the time series, and the frequency range over which the estimation is made. In particular, care must be taken to ensure that the estimate of the Hurst exponent accurately represents the low‐frequency limit of the spectrum, which is the part that is relevant to long‐term correlations and the uncertainty of estimated trends. Otherwise, spurious results can be obtained. Based on this analysis, and using an updated equivalent effective stratospheric chlorine (EESC) function, we predict that an increase in total ozone attributable to EESC should be detectable at the 95% confidence level by 2015 at the latest in southern midlatitudes, and by 2020–2025 at the latest over 30°–45°N, with the time to detection increasing rapidly with latitude north of this range.

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A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

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Low variability of crop production from year to year is desirable for many reasons, including reduced income risk and stability of supplies. Therefore, it is important to understand the nature of yield variability, whether it is changing through time, and how it varies between crops and regions. Previous studies have shown that national crop yield variability has changed in the past, with the direction and magnitude dependent on crop type and location. Whilst such studies acknowledge the importance of climate variability in determining yield variability, it has been assumed that its magnitude and its effect on crop production have not changed through time and, hence, that changes to yield variability have been due to non-climatic factors. We address this assumption by jointly examining yield and climate variability for three major crops (rice, wheat and maize) over the past 50 years. National yield time series and growing season temperature and precipitation were de-trended and related using multiple linear regression. Yield variability changed significantly in half of the crop–country combinations examined. For several crop–country combinations, changes in yield variability were related to changes in climate variability.

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Worldwide, many people are zinc (Zn)-deficient. Dietary Zn intake can be increased by producing crops with higher concentrations of Zn in their edible portions. This can be achieved by applying Zn-fertilisers to varieties with an increased ability to acquire Zn and to accumulate Zn in their edible portions. Potato (Solanum tuberosum L.) is an important food crop and is, therefore, a target for bio-fortification with Zn. Field trials incorporating a core collection of 23 potato genotypes, performed over 4 years (2006 – 2009), indicated significant genotypic effects on tuber Zn concentration and suggested that tuber Zn concentration was influenced by environmental effects, but also found that genotype environment (G E) interactions were not significant. Tuber Zn concentrations averaged 10.8 mg kg–1 dry matter (DM), and the ratio between the lowest and the highest varietal tuber Zn-concentration averaged 1.76. Tuber Zn concentrations could be increased by foliar Zn-fertilisation. Tuber yields of ‘Maris Piper’ were unaffected by foliar applications of < 1.08 g Zn plant–1. The relationship between tuber Zn concentration and foliar Zn application followed a saturation curve, reaching a maximum at approx. 30 mg Zn kg–1 DM at a foliar Zn application rate of 1.08 g plant–1. Despite a 40-fold increase in shoot Zn concentration compared to the unfertilised controls following foliar Zn fertilisation with 2.16 g Zn plant–1, only a doubling in tuber Zn concentration was observed. This suggests that the biofortification of tubers with Zn was restricted by the limited mobility of Zn in the phloem. A significant positive linear relationship between tuber Zn concentration and tuber N concentration supported the hypothesis of co-transport of Zn and N-compounds in the phloem.

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We review the theory and observations related to the "superhump" precession of eccentric accretion discs in close binary systems. We agree with earlier work, although for different reasons, that the discrepancy between observation and dynamical theory implies that the effect of pressure in the disc cannot be neglected. We extend earlier work that investigates this effect to include the correct expression for the radius at which resonant orbits occur. Using analytic expressions for the accretion disc structure, we derive a relationship between the period excess and mass ratio with the pressure effects included. This is compared to the observed data, recently derived results for detailed integration of the disc equations and the equivalent empirically derived relations and used to predict values for the mass ratio based on measured values of the period excess for 88 systems.

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Medium range flood forecasting activities, driven by various meteorological forecasts ranging from high resolution deterministic forecasts to low spatial resolution ensemble prediction systems, share a major challenge in the appropriateness and design of performance measures. In this paper possible limitations of some traditional hydrological and meteorological prediction quality and verification measures are identified. Some simple modifications are applied in order to circumvent the problem of the autocorrelation dominating river discharge time-series and in order to create a benchmark model enabling the decision makers to evaluate the forecast quality and the model quality. Although the performance period is quite short the advantage of a simple cost-loss function as a measure of forecast quality can be demonstrated.

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In this paper an equation is derived for the mean backscatter cross section of an ensemble of snowflakes at centimeter and millimeter wavelengths. It uses the Rayleigh–Gans approximation, which has previously been found to be applicable at these wavelengths due to the low density of snow aggregates. Although the internal structure of an individual snowflake is random and unpredictable, the authors find from simulations of the aggregation process that their structure is “self-similar” and can be described by a power law. This enables an analytic expression to be derived for the backscatter cross section of an ensemble of particles as a function of their maximum dimension in the direction of propagation of the radiation, the volume of ice they contain, a variable describing their mean shape, and two variables describing the shape of the power spectrum. The exponent of the power law is found to be −. In the case of 1-cm snowflakes observed by a 3.2-mm-wavelength radar, the backscatter is 40–100 times larger than that of a homogeneous ice–air spheroid with the same mass, size, and aspect ratio.

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Aims: To assess the prevalence of primary headaches (HA) in adults with temporomandibular disorders (TMD) who were assessed in a specialty orofacial pain clinic, as well as in controls without TMD. Methods: The sample consisted of 158 individuals with TMD seen at a university-based specialty clinic, as well as 68 controls. The Research Diagnostic Criteria for TMD were used to diagnose the TMD patients. HAs were assessed using a structured interview and classified according to the Second Edition of the International Classification for Headache Disorders. Data were analyzed by chi-square tests with a significance level of 5% and odds ratio (OR) tests with a 95% confidence interval (CI). Results: HAs occurred in 45.6% of the control group (30.9% had migraine and 14.7% had tension-type headache [TTH]) and in 85.5% of individuals with TMD. Among individuals with TMD, migraine was the most prevalent primary HA (55.3%), followed by TTH (30.2%); 14.5% had no HA. In contrast to controls, the odds ratio (OR) for HA in those with TMD was 7.05 (95% confidence interval [CI] = 3.65-13.61; P = .000), for migraine, the OR was 2.76 (95% CI = 1.50-5.06; P = .001), and for TTH, the OR was 2.51 (95% CI = 1.18-5.35; P = .014). Myofascial pain/arthralgia was the most common TMD diagnosis (53.2%). The presence of HA or specific HAs was not associated with the time since the onset of TMD (P = .714). However, migraine frequency was positively associated with TMD pain severity (P = .000). Conclusion: TMD was associated with increased primary HA prevalence rates. Migraine was the most common primary HA diagnosis in individuals with TMD. J OROFAC PAIN 2010;24:287-292

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Social organization is an important component of the population biology of a species that influences gene flow, the spatial pattern and scale of movements, and the effects of predation or exploitation by humans. An important element of social structure in mammals is group fidelity, which can be quantified through association indices. To describe the social organization of marine tucuxi dolphins (Sotalia guianensis) found in the Cananeia estuary, southeastern Brazil, association indices were applied to photo-identification data to characterize the temporal stability of relationships among members of this population. Eighty-seven days of fieldwork were conducted from May 2000 to July 2003, resulting in direct observations of 374 distinct groups. A total of 138 dolphins were identified on 1-38 distinct field days. Lone dolphins were rarely seen, whereas groups were composed of up to 60 individuals (mean +/- 1 SD = 12.4 +/- 11.4 individuals per group). A total of 29,327 photographs were analyzed, of which 6,312 (21.5%) were considered useful for identifying individuals. Half-weight and simple ratio indices were used to investigate associations among S. guianensis as revealed by the entire data set, data from the core study site, and data from groups composed of <= 10 individuals. Monte Carlo methods indicated that only 3 (9.3%) of 32 association matrices differed significantly from expectations based on random association. Thus, our study suggests that stable associations are not characteristic of S. guianensis in the Cananeia estuary.

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Therapy with stem cells has showed to be promising for acute kidney injury (AKI), although how it works is still controversial. Modulation of the inflammatory response is one possible mechanism. Most of published data relies on early time and whether the protection is still maintained after that is not known. Here, we analyzed whether immune modulation continues after 24 h of reperfusion. MSC were obtained from male Wistar rats. After 3-5 passages, cells were screened for CD73, CD90, CD44, CD45, CD29 and CD 31. In addition, MSC were submitted to differentiation in adipocyte and in osteocyte. AKI was induced by bilaterally clamping of renal pedicles for 60 min. Six hours after injury, MSC (2 x 105 cells) were administered intravenously. MSC-treated animals presented the lowest serum creatinine compared to non-treated animals (24 h: 1.3 +/- 0.21 vs. 3.23 +/- 0.89 mg/dl, p<0.05). The improvement in renal function was followed by a lower expression of IL-1b, IL-6 and TNF-alpha and higher expression of IL-4 and IL-10. However, 48 h after reperfusion, this cytokine profile has changed. The decrease in Th1 cytokines was less evident and IL-6 was markedly up regulated. PCNA analysis showed that regeneration occurs faster in kidney tissues of MSC-treated animals than in controls at 24 h. And also ratio of Bcl-2/Bad was higher at treated animals after 24 and 48 h. Our data demonstrated that the immunomodulatory effects of MSC occur at very early time point, changing the inflammation profile toward a Th2 profile. (C) 2009 Elsevier B.V. All rights reserved.

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Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

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Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems. (C) 2010 Elsevier B.V. All rights reserved.