45 resultados para Ratio analysis

em CentAUR: Central Archive University of Reading - UK


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Carbon and nitrogen stable isotope ratios were measured in 157 fish bone collagen samples from 15 different archaeological sites in Belgium which ranged in ages from the 3rd to the 18th c. AD. Due to diagenetic contamination of the burial environment, only 63 specimens produced results with suitable C:N ratios (2.9–3.6). The selected bones encompass a wide spectrum of freshwater, brackish, and marine taxa (N = 18), and this is reflected in the δ13C results (−28.2‰ to −12.9%). The freshwater fish have δ13C values that range from −28.2‰ to −20.2‰, while the marine fish cluster between −15.4‰ and −13.0‰. Eel, a catadromous species (mostly living in freshwater but migrating into the sea to spawn), plots between −24.1‰ and −17.7‰, and the anadromous fish (living in marine environments but migrating into freshwater to spawn) show a mix of freshwater and marine isotopic signatures. The δ15N results also have a large range (7.2‰ to 16.7‰) indicating that these fish were feeding at many different trophic levels in these diverse aquatic environments. The aim of this research is the isotopic characterization of archaeological fish species (ecology, trophic level, migration patterns) and to determine intra-species variation within and between fish populations differing in time and location. Due to the previous lack of archaeological fish isotope data from Northern Europe and Belgium in particular, these results serve as an important ecological backdrop for the future isotopic reconstruction of the diet of human populations dating from the historical period (1st and 2nd millennium AD), where there is zooarchaeological and historical evidence for an increased consumption of marine fish.

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Previous experiments from our group have demonstrated that abomasal infusion of unsaturated free fatty acids (FFA) markedly decreases dry matter intake (DMI) in dairy cows. In contrast, experiments from other groups have noted smaller decreases in DMI when unsaturated triglycerides (TG) were infused postruminally. Our hypothesis was that unsaturated FFA would be more potent inhibitors of DMI than an equivalent amount of unsaturated TG. Four Holstein cows in late lactation were used in a single reversal design. Cows were fed a total mixed ration containing (DM basis) 23% alfalfa silage, 23% corn silage, 40.3% ground shelled corn, and 10.5% soybean meal. Two cows received soy FFA (UFA; 0, 200, 400, 600 g/d) and 2 received soy oil (TG) in the same amounts; cows then were switched to the other lipid source. Cows were abomasally infused with each amount for 5-d periods. The daily amount of lipid was pulse-dosed in 4 equal portions at 0600, 1000, 1700, and 2200 h; no emulsifiers were used and there was no sign of digestive disturbance. Both lipid sources linearly decreased DMI, with a significant interaction between lipid source and amount. Slope-ratio analysis indicated that UFA were about 2 times more potent in decreasing DMI than were TG. Decreased DMI led to decreased milk production. Milk fat content was increased linearly by lipid infusion. Milk fat yield decreased markedly for UFA infusion but was relatively unaffected by infusion of TG. Contents of short- and medium-chain fatty acids in milk fat decreased as the amount of either infusate increased. Contents of C-18:2 and C18: 3 in milk fat were increased linearly by abomasal infusion of either fat source; cis-9 C-18:1 was unaffected. Transfer of infused C18: 2 to milk fat was 35.6, 42.5, and 27.8% for 200, 400, and 600 g/d of UFA, and 34.3, 39.6, and 34.0% for respective amounts of TG. Glucagon-like peptide-1 (7-36) amide (GLP-1) concentration in plasma significantly increased as DMI decreased with increasing infusion amount of UFA or TG. Plasma concentration of cholecystokinin-octapeptide (CCK-8) was unaffected by lipid infusion. These results indicate that unsaturated FFA reaching the duodenum are more potent inhibitors of DMI than are unsaturated TG; the effect may be at least partially mediated by GLP-1.

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This thesis is an empirical-based study of the European Union’s Emissions Trading Scheme (EU ETS) and its implications in terms of corporate environmental and financial performance. The novelty of this study includes the extended scope of the data coverage, as most previous studies have examined only the power sector. The use of verified emissions data of ETS-regulated firms as the environmental compliance measure and as the potential differentiating criteria that concern the valuation of EU ETS-exposed firms in the stock market is also an original aspect of this study. The study begins in Chapter 2 by introducing the background information on the emission trading system (ETS), which focuses on (i) the adoption of ETS as an environmental management instrument and (ii) the adoption of ETS by the European Union as one of its central climate policies. Chapter 3 surveys four databases that provide carbon emissions data in order to determine the most suitable source of the data to be used in the later empirical chapters. The first empirical chapter, which is also Chapter 4 of this thesis, investigates the determinants of the emissions compliance performance of the EU ETS-exposed firms through constructing the best possible performance ratio from verified emissions data and self-configuring models for a panel regression analysis. Chapter 5 examines the impacts on the EU ETS-exposed firms in terms of their equity valuation with customised portfolios and multi-factor market models. The research design takes into account the emissions allowance (EUA) price as an additional factor, as it has the most direct association with the EU ETS to control for the exposure. The final empirical Chapter 6 takes the investigation one step further, by specifically testing the degree of ETS exposure facing different sectors with sector-based portfolios and an extended multi-factor market model. The findings from the emissions performance ratio analysis show that the business model of firms significantly influences emissions compliance, as the capital intensity has a positive association with the increasing emissions-to-emissions cap ratio. Furthermore, different sectors show different degrees of sensitivity towards the determining factors. The production factor influences the performance ratio of the Utilities sector, but not the Energy or Materials sectors. The results show that the capital intensity has a more profound influence on the utilities sector than on the materials sector. With regard to the financial performance impact, ETS-exposed firms as aggregate portfolios experienced a substantial underperformance during the 2001–2004 period, but not in the operating period of 2005–2011. The results of the sector-based portfolios show again the differentiating effect of the EU ETS on sectors, as one sector is priced indifferently against its benchmark, three sectors see a constant underperformance, and three sectors have altered outcomes.

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Discrepancies between recent global earth albedo anomaly data obtained from the climate models, space and ground observations call for a new and better earth reflectance measurement technique. The SALEX (Space Ashen Light Explorer) instrument is a space-based visible and IR instrument for precise estimation of the global earth albedo by measuring the ashen light reflected off the shadowy side of the Moon from the low earth orbit. The instrument consists of a conventional 2-mirror telescope, a pair of a 3-mirror visible imager and an IR bolometer. The performance of this unique multi-channel optical system is sensitive to the stray light contamination due to the complex optical train incorporating several reflecting and refracting elements, associated mounts and the payload mechanical enclosure. This could be further aggravated by the very bright and extended observation target (i.e. the Moon). In this paper, we report the details of extensive stray light analysis including ghosts and cross-talks, leading to the optimum set of stray light precautions for the highest signal-to-noise ratio attainable.

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A scheme to describe SDS−lysozyme complex formation has been proposed on the basis of isothermal titration calorimetry (ITC) and FTIR spectroscopy data. ITC isotherms are convoluted and reveal a marked effect of both SDS and lysozyme concentration on the stoichiometry of the SDS−lysozyme complex. The binding isotherms have been described with the aid of FTIR spectroscopy in terms of changes in the lysozyme structure and the nature of the SDS binding. At low SDS concentrations, ITC isotherms feature an exothermic region that corresponds to specific electrostatic binding of SDS to positively charged amino acid residues on the lysozyme surface. This leads to charge neutralization of the complex and precipitation. The number of SDS molecules that bind specifically to lysozyme is approximately 8, as determined from our ITC isotherms, and is independent of lysozyme solution concentration. At high SDS concentrations, hydrophobic cooperative association dominates the binding process. Saturated binding stoichiometries as a molar ratio of SDS per molecule of lysozyme range from 220:1 to 80:1, depending on the lysozyme solution concentration. A limiting value of 78:1 has been calculated for lysozyme solution concentrations above 0.25 mM.

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The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (k(l)), 3) growth (k(g)), and the efficiency of utilization of body stores for milk production (k(t)). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate k(g) and k(t). Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for k(g) and k(t) using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for k(g) and 0.82 to 0.84 for k(t). Using the estimated values of k(g) and k(t), the data were corrected to allow for body tissue changes. Based on the definition of k(l) as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and k(l) were determined. Meta-analysis of the pooled data showed that the average k(l) ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.

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OBJECTIVES: This contribution provides a unifying concept for meta-analysis integrating the handling of unobserved heterogeneity, study covariates, publication bias and study quality. It is important to consider these issues simultaneously to avoid the occurrence of artifacts, and a method for doing so is suggested here. METHODS: The approach is based upon the meta-likelihood in combination with a general linear nonparametric mixed model, which lays the ground for all inferential conclusions suggested here. RESULTS: The concept is illustrated at hand of a meta-analysis investigating the relationship of hormone replacement therapy and breast cancer. The phenomenon of interest has been investigated in many studies for a considerable time and different results were reported. In 1992 a meta-analysis by Sillero-Arenas et al. concluded a small, but significant overall effect of 1.06 on the relative risk scale. Using the meta-likelihood approach it is demonstrated here that this meta-analysis is due to considerable unobserved heterogeneity. Furthermore, it is shown that new methods are available to model this heterogeneity successfully. It is argued further to include available study covariates to explain this heterogeneity in the meta-analysis at hand. CONCLUSIONS: The topic of HRT and breast cancer has again very recently become an issue of public debate, when results of a large trial investigating the health effects of hormone replacement therapy were published indicating an increased risk for breast cancer (risk ratio of 1.26). Using an adequate regression model in the previously published meta-analysis an adjusted estimate of effect of 1.14 can be given which is considerably higher than the one published in the meta-analysis of Sillero-Arenas et al. In summary, it is hoped that the method suggested here contributes further to a good meta-analytic practice in public health and clinical disciplines.

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We introduce a procedure for association based analysis of nuclear families that allows for dichotomous and more general measurements of phenotype and inclusion of covariate information. Standard generalized linear models are used to relate phenotype and its predictors. Our test procedure, based on the likelihood ratio, unifies the estimation of all parameters through the likelihood itself and yields maximum likelihood estimates of the genetic relative risk and interaction parameters. Our method has advantages in modelling the covariate and gene-covariate interaction terms over recently proposed conditional score tests that include covariate information via a two-stage modelling approach. We apply our method in a study of human systemic lupus erythematosus and the C-reactive protein that includes sex as a covariate.

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1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

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The human D-2short (D-2S) dopamine receptor has been expressed together with the G proteins Gi2 and Go in insect cells using the baculovirus system. Levels of receptor were determined using [H-3]spiperone binding. Levels of G protein heterotrimer were determined using quantitative Western blot and using [S-35]GTPgammaS saturation binding experiments. Levels of the receptor and G protein and the receptor/G protein ratio were similar in the two preparations. Stimulation of [S-35]GTPgammaS binding by a range of agonists occurred with higher relative efficacy and in some cases higher potency in the preparation expressing Go, indicating that interaction of the D-2S receptor is more efficient with this G protein. The effects of various G protein-selective agents on 10,11-dihydroxy-N-n-propylnorapomorphine ([H-3]NPA) binding were used to examine the receptor/G protein complex in the two preparations. Suramin inhibited [H-3]NPA binding with slightly higher potency in the Gi2 preparation, whereas GppNHp inhibited [H-3]NPA binding with greater potency (similar to6-fold) in the Go preparation. This may imply that the G protein is more readily activated in the D-2S/Go preparation. [H-3]Spiperone binding occurred with an increased B-max in the presence of suramin in the Go preparation but not in the Gi2 preparation, suggesting a higher affinity interaction between the free receptor and this G protein. It is concluded that the higher efficiency activation of Go by the D-2S receptor may be a function of higher affinity receptor/G protein interaction as well as a greater ability to activate the G protein. (C) 2003 Elsevier Science Inc. All rights reserved.

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A scheme to describe SDS-lysozyme complex formation has been proposed on the basis of isothermal titration calorimetry (ITC) and FTIR spectroscopy data. ITC isotherms are convoluted and reveal a marked effect of both SDS and lysozyme concentration on the stoichiometry of the SDS-lysozyme complex. The binding isotherms have been described with the aid of FTIR spectroscopy in terms of changes in the lysozyme structure and the nature of the SDS binding. At low SDS concentrations, ITC isotherms feature an exothermic region that corresponds to specific electrostatic binding of SDS to positively charged amino acid residues on the lysozyme surface. This leads to charge neutralization of the complex and precipitation. The number of SDS molecules that bind specifically to lysozyme is approximately 8, as determined from our ITC isotherms, and is independent of lysozyme solution concentration. At high SDS concentrations, hydrophobic cooperative association dominates the binding process. Saturated binding stoichiometries as a molar ratio of SDS per molecule of lysozyme range from 220: 1 to 80: 1, depending on the lysozyme solution concentration. A limiting value of 78: 1 has been calculated for lysozyme solution concentrations above 0.25 mM.

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Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

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The distributions of times to first cell division were determined for populations of Escherichia coli stationary-phase cells inoculated onto agar media. This was accomplished by using automated analysis of digital images of individual cells growing on agar and calculation of the "box area ratio." Using approximately 300 cells per experiment, the mean time to first division and standard deviation for cells grown in liquid medium at 37 degrees C and inoculated on agar and incubated at 20 degrees C were determined as 3.0 h and 0.7 h, respectively. Distributions were observed to tail toward the higher values, but no definitive model distribution was identified. Both preinoculation stress by heating cultures at 50 degrees C and postinoculation stress by growth in the presence of higher concentrations of NaCl increased mean times to first division. Both stresses also resulted in an increase in the spread of the distributions that was proportional to the mean division time, the coefficient of variation being constant at approximately 0.2 in all cases. The "relative division time," which is the time to first division for individual cells expressed in terms of the cell size doubling time, was used as measure of the "work to be done" to prepare for cell division. Relative division times were greater for heat-stressed cells than for those growing under osmotic stress.

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A method is presented for determining the time to first division of individual bacterial cells growing on agar media. Bacteria were inoculated onto agar-coated slides and viewed by phase-contrast microscopy. Digital images of the growing bacteria were captured at intervals and the time to first division estimated by calculating the "box area ratio". This is the area of the smallest rectangle that can be drawn around an object, divided by the area of the object itself. The box area ratios of cells were found to increase suddenly during growth at a time that correlated with cell division as estimated by visual inspection of the digital images. This was caused by a change in the orientation of the two daughter cells that occurred when sufficient flexibility arose at their point of attachment. This method was used successfully to generate lag time distributions for populations of Escherichia coli, Listeria monocytogenes and Pseudomonas aeruginosa, but did not work with the coccoid organism Staphylococcus aureus. This method provides an objective measure of the time to first cell division, whilst automation of the data processing allows a large number of cells to be examined per experiment. (c) 2005 Elsevier B.V. All rights reserved.