4 resultados para Cumulative time

em CentAUR: Central Archive University of Reading - UK


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A study was conducted to estimate variation among laboratories and between manual and automated techniques of measuring pressure on the resulting gas production profiles (GPP). Eight feeds (molassed sugarbeet feed, grass silage, maize silage, soyabean hulls, maize gluten feed, whole crop wheat silage, wheat, glucose) were milled to pass a I mm screen and sent to three laboratories (ADAS Nutritional Sciences Research Unit, UK; Institute of Grassland and Environmental Research (IGER), UK; Wageningen University, The Netherlands). Each laboratory measured GPP over 144 h using standardised procedures with manual pressure transducers (MPT) and automated pressure systems (APS). The APS at ADAS used a pressure transducer and bottles in a shaking water bath, while the APS at Wageningen and IGER used a pressure sensor and bottles held in a stationary rack. Apparent dry matter degradability (ADDM) was estimated at the end of the incubation. GPP were fitted to a modified Michaelis-Menten model assuming a single phase of gas production, and GPP were described in terms of the asymptotic volume of gas produced (A), the time to half A (B), the time of maximum gas production rate (t(RM) (gas)) and maximum gas production rate (R-M (gas)). There were effects (P<0.001) of substrate on all parameters. However, MPT produced more (P<0.001) gas, but with longer (P<0.001) B and t(RM gas) (P<0.05) and lower (P<0.001) R-M gas compared to APS. There was no difference between apparatus in ADDM estimates. Interactions occurred between substrate and apparatus, substrate and laboratory, and laboratory and apparatus. However, when mean values for MPT were regressed from the individual laboratories, relationships were good (i.e., adjusted R-2 = 0.827 or higher). Good relationships were also observed with APS, although they were weaker than for MPT (i.e., adjusted R-2 = 0.723 or higher). The relationships between mean MPT and mean APS data were also good (i.e., adjusted R 2 = 0. 844 or higher). Data suggest that, although laboratory and method of measuring pressure are sources of variation in GPP estimation, it should be possible using appropriate mathematical models to standardise data among laboratories so that data from one laboratory could be extrapolated to others. This would allow development of a database of GPP data from many diverse feeds. (c) 2005 Published by Elsevier B.V.

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This investigation deals with the question of when a particular population can be considered to be disease-free. The motivation is the case of BSE where specific birth cohorts may present distinct disease-free subpopulations. The specific objective is to develop a statistical approach suitable for documenting freedom of disease, in particular, freedom from BSE in birth cohorts. The approach is based upon a geometric waiting time distribution for the occurrence of positive surveillance results and formalizes the relationship between design prevalence, cumulative sample size and statistical power. The simple geometric waiting time model is further modified to account for the diagnostic sensitivity and specificity associated with the detection of disease. This is exemplified for BSE using two different models for the diagnostic sensitivity. The model is furthermore modified in such a way that a set of different values for the design prevalence in the surveillance streams can be accommodated (prevalence heterogeneity) and a general expression for the power function is developed. For illustration, numerical results for BSE suggest that currently (data status September 2004) a birth cohort of Danish cattle born after March 1999 is free from BSE with probability (power) of 0.8746 or 0.8509, depending on the choice of a model for the diagnostic sensitivity.

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Substantial resources are used for surveillance of bovine spongiform encephalopathy (BSE) despite an extremely low detection rate, especially in healthy slaughtered cattle. We have developed a method based on the geometric waiting time distribution to establish and update the statistical evidence for BSE-freedom for defined birth cohorts using continued surveillance data. The results suggest that currently (data included till September 2004) a birth cohort of Danish cattle born after March 1999 is free from BSE with probability (power) of 0.8746 or 0.8509, depending on the choice of a model for the diagnostic sensitivity. These results apply to an assumed design prevalence of 1 in 10,000 and account for prevalence heterogeneity. The age-dependent, diagnostic sensitivity for the detection of BSE has been identified as major determinant of the power. The incorporation of heterogeneity was deemed adequate on scientific grounds and led to improved power values. We propose our model as a decision tool for possible future modification of the BSE surveillance and discuss public health and international trade implications.

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Parties to the United Nations Framework Convention on Climate Change (UNFCCC) have requested guidance on common greenhouse gas metrics in accounting for Nationally determined contributions (NDCs) to emission reductions1. Metric choice can affect the relative emphasis placed on reductions of ‘cumulative climate pollutants’ such as carbon dioxide versus ‘short-lived climate pollutants’ (SLCPs), including methane and black carbon2, 3, 4, 5, 6. Here we show that the widely used 100-year global warming potential (GWP100) effectively measures the relative impact of both cumulative pollutants and SLCPs on realized warming 20–40 years after the time of emission. If the overall goal of climate policy is to limit peak warming, GWP100 therefore overstates the importance of current SLCP emissions unless stringent and immediate reductions of all climate pollutants result in temperatures nearing their peak soon after mid-century7, 8, 9, 10, which may be necessary to limit warming to “well below 2 °C” (ref. 1). The GWP100 can be used to approximately equate a one-off pulse emission of a cumulative pollutant and an indefinitely sustained change in the rate of emission of an SLCP11, 12, 13. The climate implications of traditional CO2-equivalent targets are ambiguous unless contributions from cumulative pollutants and SLCPs are specified separately.