57 resultados para Additive
em CentAUR: Central Archive University of Reading - UK
Resumo:
With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.
Resumo:
Electrospinning is a route to polymer fibres with diameters considerably smaller than available from most fibre-producing techniques. We explore the use of a low molecular weight compound as an effective control additive during the electrospinning of poly(epsilon-caprolactone). This approach extends the control variables for the electrospinning of nanoscale fibres from the more usual ones such as the polymer molecular weight, solvent and concentration. We show that through the use of dual solvent systems, we can alter the impact of the additive on the electrospinning process so that finer as well as thicker fibres can be prepared under otherwise identical conditions. As well as the size of the fibres and the number of beads, the use of the additive allows us to alter the level of crystallinity as well as the level of preferred orientation of the poly(epsilon-caprolactone) crystals. This approach, involving the use of a dual solvent and a low molar mass compound, offers considerable potential for application to other polymer systems. (C) 2010 Society of Chemical Industry
Resumo:
This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.
Resumo:
Objectives A pharmacy Central Intravenous Additives Service (CIVAS) provides ready to use injectable medicines. However, manipulation of a licensed injectable medicine may significantly alter the stability of drug(s) in the final product. The aim of this study was to develop a stability indicating assay for CIVAS produced dobutamine 500 mg in 50 ml dextrose 1% (w/v) prefilled syringes, and to allocate a suitable shelf life. Methods A stability indicating high performance liquid chromatography (HPLC) assay was established for dobutamine. The stability of dobutamine prefilled syringes was evaluated under storage conditions of 4°C (protected from light), room temperature (protected from light), room temperature (exposed to light) and 40°C (protected from light) at various time points (up to 42 days). Results An HPLC method employing a Hypersil column, mobile phase (pH=4.0) consisting of 82:12:6 (v/v/v) 0.05 M KH2PO4:acetonitrile:methanol plus 0.3% (v/v) triethylamine with UV detection at λ=280 nm was specific for dobutamine. Under different storage conditions only samples stored at 40°C showed greater than 5% degradation (5.08%) at 42 days and had the shortest T95% based on this criterion (44.6 days compared with 111.4 days for 4°C). Exposure to light also reduced dobutamine stability. Discolouration on storage was the limiting factor in shelf life allocation, even when dobutamine remained within 5% of the initial concentration. Conclusions A stability indicating HPLC assay for dobutamine was developed. The shelf life recommended for the CIVAS product was 42 days at 4°C and 35 days at room temperature when protected from light.
Resumo:
A procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) is proposed for operational rainfall estimation using rain gauges and radar data. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on Barnes' objective analysis scheme (OAS), whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, a spatially variable adjustment with multiplicative factors, and ordinary cokriging.
Resumo:
Dietary intervention studies have shown that flavanols and inorganic nitrate can improve vascular function, suggesting that these two bioactives may be responsible for beneficial health effects of diets rich in fruits and vegetables. We aimed to study interactions between cocoa flavanols (CF) and nitrate, focusing on absorption, bioavailability, excretion, and efficacy to increase endothelial function. In a double-blind randomized, dose-response crossover study, flow-mediated dilation (FMD) was measured in 15 healthy subjects before and at 1, 2, 3, and 4 h after consumption of CF (1.4-10.9 mg/kg bw) or nitrate (0.1-10 mg/kg bw). To study flavanol-nitrate interactions, an additional intervention trial was performed with nitrate and CF taken in sequence at low and high amounts. FMD was measured before (0 h) and at 1h after ingestion of nitrate (3 or 8.5 mg/kg bw) or water. Then subjects received a CF drink (2.7 or 10.9 mg/kg bw) or a micro- and macronutrient-matched CF-free drink. FMD was measured at 1, 2, and 4 h thereafter. Blood and urine samples were collected and assessed for CF and nitric oxide (NO) metabolites with HPLC and gas-phase reductive chemiluminescence. Finally, intragastric formation of NO after CF and nitrate consumption was investigated. Both CF and nitrate induced similar intake-dependent increases in FMD. Maximal values were achieved at 1 h postingestion and gradually decreased to reach baseline values at 4 h. These effects were additive at low intake levels, whereas CF did not further increase FMD after high nitrate intake. Nitrate did not affect flavanol absorption, bioavailability, or excretion, but CF enhanced nitrate-related gastric NO formation and attenuated the increase in plasma nitrite after nitrate intake. Both flavanols and inorganic nitrate can improve endothelial function in healthy subjects at intake amounts that are achievable with a normal diet. Even low dietary intake of these bioactives may exert relevant effects on endothelial function when ingested together.
Resumo:
Sudden stratospheric warmings (SSWs) are usually considered to be initiated by planetary wave activity. Here it is asked whether small-scale variability (e.g., related to gravity waves) can lead to SSWs given a certain amount of planetary wave activity that is by itself not sufficient to cause a SSW. A highly vertically truncated version of the Holton–Mass model of stratospheric wave–mean flow interaction, recently proposed by Ruzmaikin et al., is extended to include stochastic forcing. In the deterministic setting, this low-order model exhibits multiple stable equilibria corresponding to the undisturbed vortex and SSW state, respectively. Momentum forcing due to quasi-random gravity wave activity is introduced as an additive noise term in the zonal momentum equation. Two distinct approaches are pursued to study the stochastic system. First, the system, initialized at the undisturbed state, is numerically integrated many times to derive statistics of first passage times of the system undergoing a transition to the SSW state. Second, the Fokker–Planck equation corresponding to the stochastic system is solved numerically to derive the stationary probability density function of the system. Both approaches show that even small to moderate strengths of the stochastic gravity wave forcing can be sufficient to cause a SSW for cases for which the deterministic system would not have predicted a SSW.
Resumo:
We show that small quantities of 1,3:2,4-di(4-chlorobenzylidene) sorbitol dispersed in poly(epsilon-caprolactone) provide a very effective self-assembling nanoscale framework which, with a flow field, yields extremely high levels of polymer crystal orientation. During modest shear flow of the polymer melt, the additive forms highly extended nano-particles which adopt a preferred alignment with respect to the flow field. On cooling, polymer crystallisation is directed by these particles. This chloro substituted dibenzylidene sorbitol is considerably more effective at directing the crystal growth of poly(epsilon-caprolactone) than the unsubstituted compound.
Resumo:
Forty-multiparous Holstein cows were used in a 16-wk continuous design study to determine the effects of either selenium (Se) source, selenized yeast (SY) (derived from a specific strain of Saccharomyces cerevisiae CNCM I-3060 Sel-Plex®) or sodium selenite (SS), or inclusion rate of SY on Se concentration and speciation in blood, milk and cheese. Cows received ad libitum a TMR with 1:1 forage:concentrate ratio on a dry matter (DM) basis. There were four diets (T1-T4) which differed only in either source or dose of Se additive. Estimated total dietary Se for T1 (no supplement), T2 (SS), T3 (SY) and T4 (SY) was 0.16, 0.30, 0.30 and 0.45 mg/kg DM, respectively. Blood and milk samples were taken at 28 day intervals and at each time point there were positive linear effects of SY on Se concentration in blood and milk. At day 112 blood and milk Se values for T1-T4 were 177, 208, 248, 279 ± 6.6 and 24, 38, 57, 72 ± 3.7 ng/g fresh material, respectively and indicate improved uptake and incorporation of Se from SY. While selenocysteine (SeCys) was the main selenised amino acid in blood its concentration was not markedly affected by treatment, but the proportion of total Se as selenomethionine (SeMet) increased with increasing inclusion rate of SY. In milk, there were no marked treatment effects on SeCys content, but Se source had a marked effect on the proportion of total Se as SeMet. At day 112 replacing SS (T2) with SY (T3) increased the SeMet concentration of milk from 36 to 111 ng Se/g and its concentration increased further to 157 ng Se/g as the inclusion rate of SY increased further (T4) to provide 0.45 mg Se/kg TMR. Neither Se source nor inclusion rate effected the keeping quality of milk. At day 112, milk from T1, T2, and T3 was made into a hard cheese and Se source had a marked effect on total Se and the proportion of total Se comprised as either SeMet or SeCys. Replacing SS (T2) with SY (T3) increased total Se, SeMet and SeCys content from 180 to 340 ng Se/g, 57 to 153 ng Se/g and 52 to 92 ng Se/g, respectively. Key words: dairy cow, milk and cheese, selenomethionine, selenocysteine, milk keeping quality
Resumo:
This study examined anxiety as a potential moderator of stereotype change. Previous work has independently demonstrated an increase in stereotyping under conditions of high anxiety as well as following attempts to suppress stereotypic thought. The combination of these two antecedent conditions might thus be expected to produce an additive increase in stereotyping. In contrast to an additive pattern, however, we observed an interaction between anxiety and suppression task instruction. Whilst both the instruction to suppress (in the absence of anxiety) or anxiety (in the absence of the instruction to suppress) did independently increase stereotyping, when the two co-occurred, there was no change. We explain this interaction by considering work from neuropsychological domain on response perseverance: cognitive overload (one consequence of anxiety) may inhibit the ability to switch between modes of perception. These findings suggest a potentially important moderator for attempts to suppress social stereotypes, and point to the efficacy of integrating work from diverse domains for understanding the operation of executive processes in person perception.
Resumo:
This paper presents a new analysis of ocean heat content changes over the last 50 yr using isotherms by calculating the mean temperature above the 148C isotherm and the depth of the 148C isotherm as separate variables. A new quantity called the ‘‘relative heat content’’ (‘‘RHC’’) is introduced, which represents the minimum local heat content change over time, relative to a fixed isotherm. It is shown how mean temperature and isotherm depth changes make separable and additive contributions to changes in RHC. Maps of RHC change between 1970 and 2000 show similar spatial patterns to a traditional fixed-depth ocean heat content change to 220 m. However, the separate contributions to RHC suggest a more spatially uniform contribution from warming above the isotherm, while isotherm depth changes show wind-driven signals, of which some are identifiable as being related to the North Atlantic Oscillation. The time series show that the warming contribution to RHC dominates the global trend, while the depth contribution only dominates on the basin scale in the North Atlantic. The RHC shows minima associated with the major volcanic eruptions (particularly in the Indian Ocean), and these are entirely contributed by mean temperature changes rather than isotherm depth changes. The depth change contributions to RHC are strongly affected by the recently reported XBT fall-rate bias, whereas the mean temperature contributions are not. Therefore, only the isotherm depth change contributions toRHCwill need to be reassessed as fall-rate-corrected data become available.
Resumo:
An extensive statistical ‘downscaling’ study is done to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in SW France for 51 gauging stations ranging from nival (snow-dominated) to pluvial (rainfall-dominated) river-systems. This study helps to select the appropriate statistical method at a given spatial and temporal scale to downscale hydrology for future climate change impact assessment of hydrological resources. The four proposed statistical downscaling models use large-scale predictors (derived from climate model outputs or reanalysis data) that characterize precipitation and evaporation processes in the hydrological cycle to estimate summary flow statistics. The four statistical models used are generalized linear (GLM) and additive (GAM) models, aggregated boosted trees (ABT) and multi-layer perceptron neural networks (ANN). These four models were each applied at two different spatial scales, namely at that of a single flow-gauging station (local downscaling) and that of a group of flow-gauging stations having the same hydrological behaviour (regional downscaling). For each statistical model and each spatial resolution, three temporal resolutions were considered, namely the daily mean flows, the summary statistics of fortnightly flows and a daily ‘integrated approach’. The results show that flow sensitivity to atmospheric factors is significantly different between nival and pluvial hydrological systems which are mainly influenced, respectively, by shortwave solar radiations and atmospheric temperature. The non-linear models (i.e. GAM, ABT and ANN) performed better than the linear GLM when simulating fortnightly flow percentiles. The aggregated boosted trees method showed higher and less variable R2 values to downscale the hydrological variability in both nival and pluvial regimes. Based on GCM cnrm-cm3 and scenarios A2 and A1B, future relative changes of fortnightly median flows were projected based on the regional downscaling approach. The results suggest a global decrease of flow in both pluvial and nival regimes, especially in spring, summer and autumn, whatever the considered scenario. The discussion considers the performance of each statistical method for downscaling flow at different spatial and temporal scales as well as the relationship between atmospheric processes and flow variability.
Resumo:
The arthropod species richness of pastures in three Azorean islands was used to examine the relationship between local and regional species richness over two years. Two groups of arthropods, spiders and sucking insects, representing two functionally different but common groups of pasture invertebrates were investigated. The local-regional species richness relationship was assessed over relatively fine scales: quadrats (= local scale) and within pastures (= regional scale). Mean plot species richness was used as a measure of local species richness (= alpha diversity) and regional species richness was estimated at the pasture level (= gamma diversity) with the 'first-order-Jackknife' estimator. Three related issues were addressed: (i) the role of estimated regional species richness and variables operating at the local scale (vegetation structure and diversity) in determining local species richness; (ii) quantification of the relative contributions of alpha and beta diversity to regional diversity using additive partitioning; and (iii) the occurrence of consistent patterns in different years by analysing independently between-year data. Species assemblages of spiders were saturated at the local scale (similar local species richness and increasing beta-diversity in richer regions) and were more dependent on vegetational structure than regional species richness. Sucking insect herbivores, by contrast, exhibited a linear relationship between local and regional species richness, consistent with the proportional sampling model. The patterns were consistent between years. These results imply that for spiders local processes are important, with assemblages in a particular patch being constrained by habitat structure. In contrast, for sucking insects, local processes may be insignificant in structuring communities.