25 resultados para Mixed Type Variables Clustering
Resumo:
Many studies warn that climate change may undermine global food security. Much work on this topic focuses on modelling crop-weather interactions but these models do not generally account for the ways in which socio-economic factors influence how harvests are affected by weather. To address this gap, this paper uses a quantitative harvest vulnerability index based on annual soil moisture and grain production data as the dependent variables in a Linear Mixed Effects model with national scale socio-economic data as independent variables for the period 1990-2005. Results show that rice, wheat and maize production in middle income countries were especially vulnerable to droughts. By contrast, harvests in countries with higher investments in agriculture (e.g higher amounts of fertilizer use) were less vulnerable to drought. In terms of differences between the world's major grain crops, factors that made rice and wheat crops vulnerable to drought were quite consistent, whilst those of maize crops varied considerably depending on the type of region. This is likely due to the fact that maize is produced under very different conditions worldwide. One recommendation for reducing drought vulnerability risks is coordinated development and adaptation policies, including institutional support that enables farmers to take proactive action.
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Binary mixed-metal variants of the one-dimensional MCN compounds (M = Cu, Ag, and Au) have been prepared and characterized using powder X-ray diffraction, vibrational spectroscopy, and total neutron diffraction. A solid solution with the AgCN structure exists in the (CuxAg1–x)CN system over the range (0 ≤ x ≤ 1). Line phases with compositions (Cu1/2Au1/2)CN, (Cu7/12Au5/12)CN, (Cu2/3Au1/3)CN, and (Ag1/2Au1/2)CN, all of which have the AuCN structure, are found in the gold-containing systems. Infrared and Raman spectroscopies show that complete ordering of the type [M–C≡N–M′–N≡C−]n occurs only in (Cu1/2Au1/2)CN and (Ag1/2Au1/2)CN. The sense of the cyanide bonding was determined by total neutron diffraction to be [Ag–NC–Au–CN−]n in (Ag1/2Au1/2)CN and [Cu–NC–Au–CN−]n in (Cu1/2Au1/2)CN. In contrast, in (Cu0.50Ag0.50)CN, metal ordering is incomplete, and strict alternation of metals does not occur. However, there is a distinct preference (85%) for the N end of the cyanide ligand to be bonded to copper and for Ag–CN–Cu links to predominate. Contrary to expectation, aurophilic bonding does not appear to be the controlling factor which leads to (Cu1/2Au1/2)CN and (Ag1/2Au1/2)CN adopting the AuCN structure. The diffuse reflectance, photoluminescence, and 1-D negative thermal expansion (NTE) behaviors of all three systems are reported and compared with those of the parent cyanide compounds. The photophysical properties are strongly influenced both by the composition of the individual chains and by how such chains pack together. The NTE behavior is also controlled by structure type: the gold-containing mixed-metal cyanides with the AuCN structure show the smallest contraction along the chain length on heating.
Resumo:
Objective To highlight the contribution of the gut microbiota to the modulation of host metabolism by dietary inulin-type fructans (ITF prebiotics) in obese women. Methods A double blind, placebo controlled, intervention study was performed with 30 obese women treated with ITF prebiotics (inulin/oligofructose 50/50 mix; n=15) or placebo (maltodextrin; n=15) for 3 months (16 g/day). Blood, faeces and urine sampling, oral glucose tolerance test, homeostasis model assessment and impedancemetry were performed before and after treatment. The gut microbial composition in faeces was analysed by phylogenetic microarray and qPCR analysis of 16S rDNA. Plasma and urine metabolic profiles were analysed by 1H-NMR spectroscopy. Results Treatment with ITF prebiotics, but not the placebo, led to an increase in Bifidobacterium and Faecalibacterium prausnitzii; both bacteria negatively correlated with serum lipopolysaccharide levels. ITF prebiotics also decreased Bacteroides intestinalis, Bacteroides vulgatus and Propionibacterium, an effect associated with a slight decrease in fat mass and with plasma lactate and phosphatidylcholine levels. No clear treatment clustering could be detected for gut microbial analysis or plasma and urine metabolomic profile analyses. However, ITF prebiotics led to subtle changes in the gut microbiota that may importantly impact on several key metabolites implicated in obesity and/or diabetes. Conclusions ITF prebiotics selectively changed the gut microbiota composition in obese women, leading to modest changes in host metabolism, as suggested by the correlation between some bacterial species and metabolic endotoxaemia or metabolomic signatures.
Resumo:
A new technique for objective classification of boundary layers is applied to ground-based vertically pointing Doppler lidar and sonic anemometer data. The observed boundary layer has been classified into nine different types based on those in the Met Office ‘Lock’ scheme, using vertical velocity variance and skewness, along with attenuated backscatter coefficient and surface sensible heat flux. This new probabilistic method has been applied to three years of data from Chilbolton Observatory in southern England and a climatology of boundary-layer type has been created. A clear diurnal cycle is present in all seasons. The most common boundary-layer type is stable with no cloud (30.0% of the dataset). The most common unstable type is well mixed with no cloud (15.4%). Decoupled stratocumulus is the third most common boundary-layer type (10.3%) and cumulus under stratocumulus occurs 1.0% of the time. The occurrence of stable boundary-layer types is much higher in the winter than the summer and boundary-layer types capped with cumulus cloud are more prevalent in the warm seasons. The most common diurnal evolution of boundary-layer types, occurring on 52 days of our three-year dataset, is that of no cloud with the stability changing from stable to unstable during daylight hours. These results are based on 16393 hours, 62.4% of the three-year dataset, of diagnosed boundary-layer type. This new method is ideally suited to long-term evaluation of boundary-layer type parametrisations in weather forecast and climate models.
Resumo:
For a Lévy process ξ=(ξt)t≥0 drifting to −∞, we define the so-called exponential functional as follows: Formula Under mild conditions on ξ, we show that the following factorization of exponential functionals: Formula holds, where × stands for the product of independent random variables, H− is the descending ladder height process of ξ and Y is a spectrally positive Lévy process with a negative mean constructed from its ascending ladder height process. As a by-product, we generate an integral or power series representation for the law of Iξ for a large class of Lévy processes with two-sided jumps and also derive some new distributional properties. The proof of our main result relies on a fine Markovian study of a class of generalized Ornstein–Uhlenbeck processes, which is itself of independent interest. We use and refine an alternative approach of studying the stationary measure of a Markov process which avoids some technicalities and difficulties that appear in the classical method of employing the generator of the dual Markov process.
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In accord with the general program of researching factors relating to ultimate attainment and maturational constraints in adult language acquisition, this commentary highlights the importance of input differences in amount, type, and setting between naturalistic and classroom learners of an L2. It is suggested that these variables are often confounded with age factors. Herein, we wish to call attention to the possible deterministic role that the differences in the grammatical quality of classroom input have on development and on competence outcomes. Framing what we see as greater formal complexity of the learning task for classroom learners, we suggest that one might benefit from focusing less on difference and more on how classroom L2 learners, at least some of them, come to acquire all that they do despite crucial qualitative differences in their input.
Resumo:
Many studies evaluating model boundary-layer schemes focus either on near-surface parameters or on short-term observational campaigns. This reflects the observational datasets that are widely available for use in model evaluation. In this paper we show how surface and long-term Doppler lidar observations, combined in a way to match model representation of the boundary layer as closely as possible, can be used to evaluate the skill of boundary-layer forecasts. We use a 2-year observational dataset from a rural site in the UK to evaluate a climatology of boundary layer type forecast by the UK Met Office Unified Model. In addition, we demonstrate the use of a binary skill score (Symmetric Extremal Dependence Index) to investigate the dependence of forecast skill on season, horizontal resolution and forecast leadtime. A clear diurnal and seasonal cycle can be seen in the climatology of both the model and observations, with the main discrepancies being the model overpredicting cumulus capped and decoupled stratocumulus capped boundary-layers and underpredicting well mixed boundary-layers. Using the SEDI skill score the model is most skillful at predicting the surface stability. The skill of the model in predicting cumulus capped and stratocumulus capped stable boundary layer forecasts is low but greater than a 24 hr persistence forecast. In contrast, the prediction of decoupled boundary-layers and boundary-layers with multiple cloud layers is lower than persistence. This process based evaluation approach has the potential to be applied to other boundary-layer parameterisation schemes with similar decision structures.
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Replacing dietary grass silage (GS) with maize silage (MS) and dietary fat supplements may reduce milk concentration of specific saturated fatty acids (SFA) and can reduce methane production by dairy cows. The present study investigated the effect of feeding an extruded linseed supplement on milk fatty acid (FA) composition and methane production of lactating dairy cows, and whether basal forage type, in diets formulated for similar neutral detergent fiber and starch, altered the response to the extruded linseed supplement. Four mid-lactation Holstein-Friesian cows were fed diets as total mixed rations, containing either high proportions of MS or GS, both with or without extruded linseed supplement, in a 4 × 4 Latin square design experiment with 28-d periods. Diets contained 500 g of forage/kg of dry matter (DM) containing MS and GS in proportions (DM basis) of either 75:25 or 25:75 for high MS or high GS diets, respectively. Extruded linseed supplement (275 g/kg ether extract, DM basis) was included in treatment diets at 50 g/kg of DM. Milk yields, DM intake, milk composition, and methane production were measured at the end of each experimental period when cows were housed in respiration chambers. Whereas DM intake was higher for the MS-based diet, forage type and extruded linseed had no significant effect on milk yield, milk fat, protein, or lactose concentration, methane production, or methane per kilogram of DM intake or milk yield. Total milk fat SFA concentrations were lower with MS compared with GS-based diets (65.4 vs. 68.4 g/100 g of FA, respectively) and with extruded linseed compared with no extruded linseed (65.2 vs. 68.6 g/100 g of FA, respectively), and these effects were additive. Concentrations of total trans FA were higher with MS compared with GS-based diets (7.0 vs. 5.4 g/100 g of FA, respectively) and when extruded linseed was fed (6.8 vs. 5.6 g/100 g of FA, respectively). Total n-3 FA were higher when extruded linseed was fed compared with no extruded linseed (1.2 vs. 0.8 g/100 g of FA, respectively), whereas total n-6 polyunsaturated FA were higher when feeding MS compared with GS (2.5 vs. 2.1 g/100 g of FA, respectively). Feeding extruded linseed and MS both provided potentially beneficial decreases in SFA concentration of milk, and no significant interactions were found between extruded linseed supplementation and forage type. However, both MS and extruded linseed increased trans FA concentration in milk fat. Neither MS nor extruded linseed had significant effects on methane production or yield, but the amounts of supplemental lipid provided by extruded linseed were relatively small.
Resumo:
Changes in diet carbohydrate amount and type (i.e., starch vs. fiber) and dietary oil supplements can affect ruminant methane emissions. Our objectives were to measure methane emissions, whole-tract digestibility, and energy and nitrogen utilization from growing dairy cattle at 2 body weight (BW) ranges, fed diets containing either high maize silage (MS) or high grass silage (GS), without or with supplemental oil from extruded linseed (ELS). Four Holstein-Friesian heifers aged 13 mo (BW range from start to finish of 382 to 526 kg) were used in experiment 1, whereas 4 lighter heifers aged 12 mo (BW range from start to finish of 292 to 419 kg) were used in experiment 2. Diets were fed as total mixed rations with forage dry matter (DM) containing high MS or high GS and concentrates in proportions (forage:concentrate, DM basis) of either 75:25 (experiment 1) or 60:40 (experiment 2), respectively. Diets were supplemented without or with ELS (Lintec[AU1: Add manufacturer name and location.]; 260 g of oil/ kg of DM) at 6% of ration DM. Each experiment was a 4 × 4 Latin square design with 33-d periods, with measurements during d 29 to 33 while animals were housed in respiration chambers. Heifers fed MS at a heavier BW (experiment 1) emitted 20% less methane per unit of DM intake (yield) compared with GS (21.4 vs. 26.6, respectively). However, when repeated with heifers of a lower BW (experiment 2), methane yield did not differ between the 2 diets (26.6 g/kg of DM intake). Differences in heifer BW had no overall effect on methane emissions, except when expressed as grams per kilogram of digestible organic matter (OMD) intake (32.4 vs. 36.6, heavy vs. light heifers). Heavier heifers fed MS in experiment 1 had a greater DM intake (9.4 kg/d) and lower OMD (755 g/kg), but no difference in N utilization (31% of N intake) compared with heifers fed GS (7.9 kg/d and 799 g/kg, respectively). Tissue energy retention was nearly double for heifers fed MS compared with GS in experiment 1 (15 vs. 8% of energy intake, respectively). Heifers fed MS in experiment 2 had similar DM intake (7.2 kg/d) and retention of energy (5% of intake energy) and N (28% of N intake), compared with GS-fed heifers, but OMD was lower (741 vs. 765 g/kg, respectively). No effect of ELS was noted on any of the variables measured, irrespective of animal BW, and this was likely due to the relatively low amount of supplemental oil provided. Differences in heifer BW did not markedly influence dietary effects on methane emissions. Differences in methane yield were attributable to differences in dietary starch and fiber composition associated with forage type and source.
Resumo:
Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.