1000 resultados para Seasonal foods


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This paper investigates whether using natural logarithms (logs) of price indices for forecasting inflation rates is preferable to employing the original series. Univariate forecasts for annual inflation rates for a number of European countries and the USA based on monthly seasonal consumer price indices are considered. Stochastic seasonality and deterministic seasonality models are used. In many cases, the forecasts based on the original variables result in substantially smaller root mean squared errors than models based on logs. In turn, if forecasts based on logs are superior, the gains are typically small. This outcome sheds doubt on the common practice in the academic literature to forecast inflation rates based on differences of logs.

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A wealth of information has been gathered over the past 15 years on prebiotics through experimental, animal and human studies, with the aim to understand the mechanism of actions and elucidate their beneficial health effects to the human host. Significant amount of evidence exists for their ability to increase the bioavailability of minerals and stimulate the immune system, although there is less clear evidence so far for their prophylactic or therapeutic role in gastrointestinal infections. Moreover, the effect of the food delivery vehicle on the efficacy of prebiotics is an area that has been hardly investigated. Besides their beneficial effects, prebiotics influence the textural and organoleptic properties of the food products, such as dairy and baked products. To do this however, they need to be stable during food processing, in particular under conditions of high temperature and low pH.

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Seasonal sea-surface temperaturevariability for the Neoglacial (3300–2500 BP) and Roman WarmPeriod (RWP; 2500–1600 BP), which correspond to the Bronze and Iron Ages, respectively, was estimated using oxygen isotope ratios obtained from high-resolution samples micromilled from radiocarbon-dated, archaeological limpet (Patella vulgata) shells. The coldest winter months recorded in Neoglacial shells averaged 6.6 ± 0.3 °C, and the warmest summer months averaged 14.7 ± 0.4 °C. One Neoglacial shell captured a year without a summer, which may have resulted from a dust veil from a volcanic eruption in the Katla volcanic system in Iceland. RWP shells record average winter and summer monthly temperatures of 6.3 ± 0.1 °C and 13.3 ± 0.3 °C, respectively. These results capture a cooling transition from the Neoglacial to RWP, which is further supported by earlier studies of pine history in Scotland, pollen type analyses in northeast Scotland, and European glacial events. The cooling transition observed at the boundary between the Neoglacial and RWP in our study also agrees with the abrupt climate deterioration at 2800–2700 BP (also referred to as the Subboreal/Subatlantic transition) and therefore may have been driven by decreased solar radiation and weakened North Atlantic Oscillation conditions.

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There is evidence that consumption of fish, especially oily fish, has substantial beneficial effects on health. In particular an inverse relationship of oily fish intake to coronary heart disease incidence has been established. These beneficial effects are ascribed to fish oil components including long chain ω-3 polyunsaturated fatty acids. On the other hand it should be noted that oily fish also contains hazardous substances such as dioxins, PCBs and methylmercury. Soy consumption has been associated with potential beneficial and adverse effects. The claimed benefits include reduced risk of cardiovascular disease; osteoporosis, breast and prostate cancer whereas potential adverse effects include impaired thyroid function, disruption of sex hormone levels, changes in reproductive function and increased breast cancer risk The two cases of natural foods highlight the need to consider both risks and benefits in order to establish the net health impact associated to the consumption of specific food products. Within the Sixth Framework programme of the European Commission, the BRAFO project was funded to develop a framework that allows for the quantitative comparison of human health risks and benefits in relation to foods and food compounds. This paper describes the application of the developed framework to two natural foods, farmed salmon and soy protein. We conclude that the BRAFO methodology is highly applicable to natural foods. It will help the benefit-risk managers in selecting the appropriate dietary recommendations for the population.

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[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling.

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Objective: A phytoestrogen-rich diet has been suggested to protect against a variety of common diseases but UK intake data on phytoestrogens or their food sources is sparse. This study aims to estimate the average intake of isoflavones, lignans, enterolignans and coumestrol from 7-day food diaries (7dFD), and to provide data on total isoflavone, lignan and phytoestrogen consumption by food group. Design: Development of a food composition database for twelve phytoestrogens and analysis of soya food and phytoestrogen consumption in a population-based study. Setting: Men and women, aged 40-79 years from the general population participating in EPIC-Norfolk between 1993 and 1997, with nutrient and food data from 7dFD. Subjects: A subset of 20 437 participants. Results: The median daily phytoestrogen intake for men was 1.20mg (interquartile range (IQR) 0.93-1.54 mg; mean 1.50 mg, SD 1.50 mg) and 0.89 mg for women (IQR 0.71-1.14 mg; mean 1.20 mg, SD 1.70 mg). In soya-consumers (SC), median daily intakes were higher: 2.86 mg in men (IQR – 1.30-7.27mg; mean 5.05 mg, SD 5.03 mg) and 3.14 mg in women (IQR – 1.09-7.33mg; mean 5.40 mg, SD 6.09 mg). In both men and women, bread made the greatest contribution to phytoestrogen intake – 40.7% and 35.7% respectively. In SC men and women, vegetable dishes and soya/goat’s/sheep’s milks were the main contributors – 42.6% and 18.9% in men and 38.8% and 29.1% in women, respectively. Conclusions: The ability to estimate phytoestrogen intake in Western populations more accurately will aid investigations into their suggested effects on health.

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The sensitivity to the horizontal resolution of the climate, anthropogenic climate change, and seasonal predictive skill of the ECMWF model has been studied as part of Project Athena—an international collaboration formed to test the hypothesis that substantial progress in simulating and predicting climate can be achieved if mesoscale and subsynoptic atmospheric phenomena are more realistically represented in climate models. In this study the experiments carried out with the ECMWF model (atmosphere only) are described in detail. Here, the focus is on the tropics and the Northern Hemisphere extratropics during boreal winter. The resolutions considered in Project Athena for the ECMWF model are T159 (126 km), T511 (39 km), T1279 (16 km), and T2047 (10 km). It was found that increasing horizontal resolution improves the tropical precipitation, the tropical atmospheric circulation, the frequency of occurrence of Euro-Atlantic blocking, and the representation of extratropical cyclones in large parts of the Northern Hemisphere extratropics. All of these improvements come from the increase in resolution from T159 to T511 with relatively small changes for further resolution increases to T1279 and T2047, although it should be noted that results from this very highest resolution are from a previously untested model version. Problems in simulating the Madden–Julian oscillation remain unchanged for all resolutions tested. There is some evidence that increasing horizontal resolution to T1279 leads to moderate increases in seasonal forecast skill during boreal winter in the tropics and Northern Hemisphere extratropics. Sensitivity experiments are discussed, which helps to foster a better understanding of some of the resolution dependence found for the ECMWF model in Project Athena

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The cold equatorial SST bias in the tropical Pacific that is persistent in many coupled OAGCMs severely impacts the fidelity of the simulated climate and variability in this key region, such as the ENSO phenomenon. The classical bias analysis in these models usually concentrates on multi-decadal to centennial time series needed to obtain statistically robust features. Yet, this strategy cannot fully explain how the models errors were generated in the first place. Here, we use seasonal re-forecasts (hindcasts) to track back the origin of this cold bias. As such hindcasts are initialized close to observations, the transient drift leading to the cold bias can be analyzed to distinguish pre-existing errors from errors responding to initial ones. A time sequence of processes involved in the advent of the final mean state errors can then be proposed. We apply this strategy to the ENSEMBLES-FP6 project multi-model hindcasts of the last decades. Four of the five AOGCMs develop a persistent equatorial cold tongue bias within a few months. The associated systematic errors are first assessed separately for the warm and cold ENSO phases. We find that the models are able to reproduce either El Niño or La Niña close to observations, but not both. ENSO composites then show that the spurious equatorial cooling is maximum for El Niño years for the February and August start dates. For these events and at this time of the year, zonal wind errors in the equatorial Pacific are present from the beginning of the simulation and are hypothesized to be at the origin of the equatorial cold bias, generating too strong upwelling conditions. The systematic underestimation of the mixed layer depth in several models can also amplify the growth of the SST bias. The seminal role of these zonal wind errors is further demonstrated by carrying out ocean-only experiments forced by the AOCGCMs daily 10-meter wind. In a case study, we show that for several models, this forcing is sufficient to reproduce the main SST error patterns seen after 1 month in the AOCGCM hindcasts.

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The World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP) have identified collaborations and scientific priorities to accelerate advances in analysis and prediction at subseasonal-to-seasonal time scales, which include i) advancing knowledge of mesoscale–planetary-scale interactions and their prediction; ii) developing high-resolution global–regional climate simulations, with advanced representation of physical processes, to improve the predictive skill of subseasonal and seasonal variability of high-impact events, such as seasonal droughts and floods, blocking, and tropical and extratropical cyclones; iii) contributing to the improvement of data assimilation methods for monitoring and predicting used in coupled ocean–atmosphere–land and Earth system models; and iv) developing and transferring diagnostic and prognostic information tailored to socioeconomic decision making. The document puts forward specific underpinning research, linkage, and requirements necessary to achieve the goals of the proposed collaboration.

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This study evaluates the use of European Centre for Medium-Range Weather Forecasts (ECMWF) products in monitoring and forecasting drought conditions during the recent 2010–2011 drought in the Horn of Africa (HoA). The region was affected by a precipitation deficit in both the October–December 2010 and March–May 2011 rainy seasons. These anomalies were captured by the ERA-Interim reanalysis (ERAI), despite its limitations in representing the March–May interannual variability. Soil moisture anomalies of ERAI also identified the onset of the drought condition early in October 2010 with a persistent drought still present in September 2011. This signal was also evident in normalized difference vegetation index (NDVI) remote sensing data. The precipitation deficit in October–December 2010 was associated with a strong La Niña event. The ECMWF seasonal forecasts for the October–December 2010 season predicted the La Niña event from June 2010 onwards. The forecasts also predicted a below-average October–December rainfall, from July 2010 onwards. The subsequent March–May rainfall anomaly was only captured by the new ECWMF seasonal forecast system in the forecasts starting in March 2011. Our analysis shows that a recent (since 1999) drying in the region during the March–May season is captured by the new ECMWF seasonal forecast system and is consistent with recently published results. The HoA region and its population are highly vulnerable to future droughts, thus global monitoring and forecasting of drought, such as that presented here, will become increasingly important in the future. Copyright © 2012 Royal Meteorological Society

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Since 1990 multiresistant (MR) Salmonella enterica serotype Typhimurium definitive phage-type (DT) 104 (MR DT104) and closely related phage types have emerged as a worldwide health problem in humans and food animals. In this study the presence of the bla(CARB-2) (ampicillin), cmlA (chloramphenicol), aadA2 (streptomycin/spectinomycin), sul1 (sulphonamide), and tetG (tetracycline) resistance genes in isolates of one such phage type, U302, have been determined. In addition bla(TEM) I primers have been used for the detection of TEM-type beta-lactamases. Isolates have also been characterized by plasmid profile and pulsed field gel electrophoresis (PFGE). Thirty-three of 39 isolates were positive for blaCARB-2, cmlA, aadA2, sul1 and tetG, four for bla(TEM), aadA2 and sul1, one for aadA2 and sul1, and one for blaTEM only. bla(TEM)-mediated ampicillin resistance was transferred to Escherichia coli K12 from three isolates along with other resistance markers, including resistance to chloramphenicol, streptomycin, spectinomycin, sulphonamides, and tetracyclines. Strains carried up to 6 plasmids and 34 plasmid profiles were identified. Although the majority of strains (33/39) produced a PFGE profile identical to that predominant in MR DT104, six different patterns were generated demonstrating the presence of various clones within MR U302. The results show that the majority of the MR U302 strains studied possessed the same antibiotic resistance genes as MR DT104. However, isolates with distinctive PFGE patterns can have different mechanisms of resistance to ampicillin, chloramphenicol, streptomycin, sulphonamides, and tetracyclines. Such resistance genes may be borne on transmissible plasmids.

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By comparing annual and seasonal changes in precipitation over land and ocean since 1950 simulated by the CMIP5 (Coupled Model Intercomparison Project, phase 5) climate models in which natural and anthropogenic forcings have been included, we find that clear global-scale and regional-scale changes due to human influence are expected to have occurred over both land and ocean. These include moistening over northern high latitude land and ocean throughout all seasons and over the northern subtropical oceans during boreal winter. However we show that this signal of human influence is less distinct when considered over the relatively small area of land for which there are adequate observations to make assessments of multi-decadal scale trends. These results imply that extensive and significant changes in precipitation over the land and ocean may have already happened, even though, inadequacies in observations in some parts of the world make it difficult to identify conclusively such a human fingerprint on the global water cycle. In some regions and seasons, due to aliasing of different kinds of variability as a result of sub sampling by the sparse and changing observational coverage, observed trends appear to have been increased, underscoring the difficulties of interpreting the apparent magnitude of observed changes in precipitation.

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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.

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This paper proposes a method for describing the distribution of observed temperatures on any day of the year such that the distribution and summary statistics of interest derived from the distribution vary smoothly through the year. The method removes the noise inherent in calculating summary statistics directly from the data thus easing comparisons of distributions and summary statistics between different periods. The method is demonstrated using daily effective temperatures (DET) derived from observations of temperature and wind speed at De Bilt, Holland. Distributions and summary statistics are obtained from 1985 to 2009 and compared to the period 1904–1984. A two-stage process first obtains parameters of a theoretical probability distribution, in this case the generalized extreme value (GEV) distribution, which describes the distribution of DET on any day of the year. Second, linear models describe seasonal variation in the parameters. Model predictions provide parameters of the GEV distribution, and therefore summary statistics, that vary smoothly through the year. There is evidence of an increasing mean temperature, a decrease in the variability in temperatures mainly in the winter and more positive skew, more warm days, in the summer. In the winter, the 2% point, the value below which 2% of observations are expected to fall, has risen by 1.2 °C, in the summer the 98% point has risen by 0.8 °C. Medians have risen by 1.1 and 0.9 °C in winter and summer, respectively. The method can be used to describe distributions of future climate projections and other climate variables. Further extensions to the methodology are suggested.