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The AusBeef model for beef production: II. sensitivity analysis
- H. C. DOUGHERTY, E. KEBREAB, M. EVERED, B. A. LITTLE, A. B. INGHAM, J. V. NOLAN, R. S. HEGARTY, D. PACHECO, M. J. MCPHEE
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- Journal:
- The Journal of Agricultural Science / Volume 155 / Issue 9 / November 2017
- Published online by Cambridge University Press:
- 03 August 2017, pp. 1459-1474
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The present study evaluated the behaviour of the AusBeef model for beef production as part of a 2 × 2 study simulating performance on forage-based and concentrate-based diets from Oceania and North America for four methane (CH4)-relevant outputs of interest. Three sensitivity analysis methods, one local and two global, were conducted. Different patterns of sensitivity were observed between forage-based and concentrate-based diets, but patterns were consistent within diet types. For the local analysis, 36, 196, 47 and 8 out of 305 model parameters had normalized sensitivities of 0, >0, >0·01 and >0·1 across all diets and outputs, respectively. No parameters had a normalized local sensitivity >1 across all diets and outputs. However, daily CH4 production had the greatest number of parameters with normalized local sensitivities >1 for each individual diet. Parameters that were highly sensitive for global and local analyses across the range of diets and outputs examined included terms involved in microbial growth, volatile fatty acid (VFA) yields, maximum absorption rates and their inhibition due to pH effects and particle exit rates. Global sensitivity analysis I showed the high sensitivity of forage-based diets to lipid entering the rumen, which may be a result of the use of a feedlot-optimized model to represent high-forage diets and warrants further investigation. Global sensitivity analysis II showed that when all parameter values were simultaneously varied within ±10% of initial value, >96% of output values were within ±20% of the baseline, which decreased to >50% when parameter value boundaries were expanded to ±25% of their original values, giving a range for robustness of model outputs with regards to potential different ‘true’ parameter values. There were output-specific differences in sensitivity, where outputs that had greater maximum local sensitivities displayed greater degrees of non-linear interaction in global sensitivity analysis I and less variance in output values for global sensitivity analysis II. For outputs with less interaction, such as the acetate : propionate ratio and microbial protein production, the single most sensitive term in global sensitivity analysis I contributed more to the overall total-order sensitivity than for outputs with more interaction, with an average of 49, 33, 15 and 14% of total-order sensitivity for microbial protein production, acetate : propionate ratio, CH4 production and energy from absorbed VFAs, respectively. Future studies should include data collection for highly sensitive parameters reported in the present study to improve overall model accuracy.
The AusBeef model for beef production: I. Description and evaluation
- H. C. DOUGHERTY, E. KEBREAB, M. EVERED, B. A. LITTLE, A. B. INGHAM, R. S. HEGARTY, D. PACHECO, M. J. MCPHEE
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- Journal:
- The Journal of Agricultural Science / Volume 155 / Issue 9 / November 2017
- Published online by Cambridge University Press:
- 03 August 2017, pp. 1442-1458
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As demand for animal products, such as meat and milk, increases, and concern over environmental impact grows, mechanistic models can be useful tools to better represent and understand ruminant systems and evaluate mitigation options to reduce greenhouse gas emissions without compromising productivity. The objectives of the present study were to describe the representation of processes for growth and enteric methane (CH4) production in AusBeef, a whole-animal, dynamic, mechanistic model for beef production; evaluate AusBeef for its ability to predict daily methane production (DMP, g/day), gross energy intake (GEI, MJ/day) and methane yield (MJ CH4/MJ GEI) using an independent data set; and to compare AusBeef estimates to those from the empirical equations featured in the current National Academies of Sciences, Engineering and Medicine (NASEM, 2016) beef cattle requirements for growth and the Ruminant Nutrition System (RNS), a dynamic, mechanistic model of Tedeschi & Fox, 2016. AusBeef incorporates a unique fermentation stoichiometry that represents four microbial groups: protozoa, amylolytic bacteria, cellulolytic bacteria and lactate-utilizing bacteria. AusBeef also accounts for the effects of ruminal pH on microbial degradation of feed particles. Methane emissions are calculated from net ruminal hydrogen balance, which is defined as the difference between inputs from fermentation and outputs due to microbial use and biohydrogenation. AusBeef performed similarly to the NASEM empirical model in terms of prediction accuracy and error decomposition, and with less root mean square predicted error (RMSPE) than the RNS mechanistic model when expressed as a percentage of the observed mean (RMSPE, %), and the majority of error was non-systematic. For DMP, RMSPE for AusBeef, NASEM and RNS were 24·0, 19·8 and 50·0 g/day for the full data set (n = 35); 25·6, 18·2 and 56·2 g/day for forage diets (n = 19); and 21·8, 21·5 and 41·5 g/day for mixed diets (n = 16), respectively. Concordance correlation coefficients (CCC) were highest for GEI, with all models having CCC > 0·66, and higher CCC for forage diets than mixed, while CCC were lowest for MY, particularly forage diets. Systematic error increased for all models on forage diets, largely due to an increase in error due to mean bias, and while all models performed well for mixed diets, further refinements are required to improve the prediction of CH4 on forage diets.
The Australian Square Kilometre Array Pathfinder: Performance of the Boolardy Engineering Test Array
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- D. McConnell, J. R. Allison, K. Bannister, M. E. Bell, H. E. Bignall, A. P. Chippendale, P. G. Edwards, L. Harvey-Smith, S. Hegarty, I. Heywood, A. W. Hotan, B. T. Indermuehle, E. Lenc, J. Marvil, A. Popping, W. Raja, J. E. Reynolds, R. J. Sault, P. Serra, M. A. Voronkov, M. Whiting, S. W. Amy, P. Axtens, L. Ball, T. J. Bateman, D. C.-J. Bock, R. Bolton, D. Brodrick, M. Brothers, A. J. Brown, J. D. Bunton, W. Cheng, T. Cornwell, D. DeBoer, I. Feain, R. Gough, N. Gupta, J. C. Guzman, G. A. Hampson, S. Hay, D. B. Hayman, S. Hoyle, B. Humphreys, C. Jacka, C. A. Jackson, S. Jackson, K. Jeganathan, J. Joseph, B. S. Koribalski, M. Leach, E. S. Lensson, A. MacLeod, S. Mackay, M. Marquarding, N. M. McClure-Griffiths, P. Mirtschin, D. Mitchell, S. Neuhold, A. Ng, R. Norris, S. Pearce, R. Y. Qiao, A. E. T. Schinckel, M. Shields, T. W. Shimwell, M. Storey, E. Troup, B. Turner, J. Tuthill, A. Tzioumis, R. M. Wark, T. Westmeier, C. Wilson, T. Wilson
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- Journal:
- Publications of the Astronomical Society of Australia / Volume 33 / 2016
- Published online by Cambridge University Press:
- 09 September 2016, e042
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We describe the performance of the Boolardy Engineering Test Array, the prototype for the Australian Square Kilometre Array Pathfinder telescope. Boolardy Engineering Test Array is the first aperture synthesis radio telescope to use phased array feed technology, giving it the ability to electronically form up to nine dual-polarisation beams. We report the methods developed for forming and measuring the beams, and the adaptations that have been made to the traditional calibration and imaging procedures in order to allow BETA to function as a multi-beam aperture synthesis telescope. We describe the commissioning of the instrument and present details of Boolardy Engineering Test Array’s performance: sensitivity, beam characteristics, polarimetric properties, and image quality. We summarise the astronomical science that it has produced and draw lessons from operating Boolardy Engineering Test Array that will be relevant to the commissioning and operation of the final Australian Square Kilometre Array Path telescope.
Contributors
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- By Brittany L. Anderson-Montoya, Heather R. Bailey, Carryl L. Baldwin, Daphne Bavelier, Jameson D. Beach, Jeffrey S. Bedwell, Kevin B. Bennett, Richard A. Block, Deborah A. Boehm-Davis, Corey J. Bohil, David B. Boles, Avinoam Borowsky, Jessica Bramlett, Allison A. Brennan, J. Christopher Brill, Matthew S. Cain, Meredith Carroll, Roberto Champney, Kait Clark, Nancy J. Cooke, Lori M. Curtindale, Clare Davies, Patricia R. DeLucia, Andrew E. Deptula, Michael B. Dillard, Colin D. Drury, Christopher Edman, James T. Enns, Sara Irina Fabrikant, Victor S. Finomore, Arthur D. Fisk, John M. Flach, Matthew E. Funke, Andre Garcia, Adam Gazzaley, Douglas J. Gillan, Rebecca A. Grier, Simen Hagen, Kelly Hale, Diane F. Halpern, Peter A. Hancock, Deborah L. Harm, Mary Hegarty, Laurie M. Heller, Nicole D. Helton, William S. Helton, Robert R. Hoffman, Jerred Holt, Xiaogang Hu, Richard J. Jagacinski, Keith S. Jones, Astrid M. L. Kappers, Simon Kemp, Robert C. Kennedy, Robert S. Kennedy, Alan Kingstone, Ioana Koglbauer, Norman E. Lane, Robert D. Latzman, Cynthia Laurie-Rose, Patricia Lee, Richard Lowe, Valerie Lugo, Poornima Madhavan, Leonard S. Mark, Gerald Matthews, Jyoti Mishra, Stephen R. Mitroff, Tracy L. Mitzner, Alexander M. Morison, Taylor Murphy, Takamichi Nakamoto, John G. Neuhoff, Karl M. Newell, Tal Oron-Gilad, Raja Parasuraman, Tiffany A. Pempek, Robert W. Proctor, Katie A. Ragsdale, Anil K. Raj, Millard F. Reschke, Evan F. Risko, Matthew Rizzo, Wendy A. Rogers, Jesse Q. Sargent, Mark W. Scerbo, Natasha B. Schwartz, F. Jacob Seagull, Cory-Ann Smarr, L. James Smart, Kay Stanney, James Staszewski, Clayton L. Stephenson, Mary E. Stuart, Breanna E. Studenka, Joel Suss, Leedjia Svec, James L. Szalma, James Tanaka, James Thompson, Wouter M. Bergmann Tiest, Lauren A. Vassiliades, Michael A. Vidulich, Paul Ward, Joel S. Warm, David A. Washburn, Christopher D. Wickens, Scott J. Wood, David D. Woods, Motonori Yamaguchi, Lin Ye, Jeffrey M. Zacks
- Edited by Robert R. Hoffman, Peter A. Hancock, University of Central Florida, Mark W. Scerbo, Old Dominion University, Virginia, Raja Parasuraman, George Mason University, Virginia, James L. Szalma, University of Central Florida
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- Book:
- The Cambridge Handbook of Applied Perception Research
- Published online:
- 05 July 2015
- Print publication:
- 26 January 2015, pp xi-xiv
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Effects of gestation on ovine fetal and maternal angiotensin receptor subtypes in the heart and major blood vessels
- J. H. Burrell, B. D. Hegarty, J. R. McMullen, E. R. Lumbers
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- Journal:
- Experimental Physiology / Volume 86 / Issue 1 / January 2001
- Published online by Cambridge University Press:
- 31 July 2001, pp. 71-82
- Print publication:
- January 2001
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Previous studies in fetal sheep have concluded that (a) the vascular AT1 angiotensin II (Ang II) receptor subtype is present in the external umbilical artery, but not in other systemic blood vessels, and (b) carotid arterial rings contract in vitro in response to Ang II. These contractions are blocked by the AT1 specific receptor antagonist losartan. The aim of the present study was to resolve the apparent contradiction of these earlier conclusions, by examining the distribution of Ang II receptor subtypes in different regions of the ovine fetal cardiovascular system, and to find out at what stage in development AT1 receptors first appear. We measured AT1 and AT2 receptors in hearts, carotid arteries, aortae and umbilical vessels from fetal sheep aged 65-144 days (term ~150 days), and in hearts and aortae from lambs, and adult pregnant and non-pregnant ewes. Both AT1 and AT2 receptors were present in aortae of fetuses > 118 days gestation, and carotid arteries of fetuses > 121 days gestation, while in younger fetuses only AT2 receptors were found. The proportion of carotid artery and aortic AT1 receptors increased with age, while the proportion of AT2 receptors decreased. The internal umbilical artery contained both subtypes, but there was no relationship between receptor density and gestational age. The external umbilical artery had only AT1 receptors. The highest density of Ang II receptors was found in the fetal heart where the AT2 subtype predominated. The density of fetal cardiac Ang II receptors declined with age (r = -0.44, P < 0.02) due to the decrease in the AT2 subtype. The density in late gestation fetal hearts was greater than in lamb or adult hearts (P < 0.001). Our study shows that fetal systemic blood vessels contain AT1 receptors, and we have documented for the first time that the appearance of AT1 receptors is both different in different regions of the fetal cardiovascular system and is developmentally regulated. Together with the in vitro contractile studies, this suggests that Ang II can play an important role in fetal blood pressure regulation via AT1 receptors in the fetal systemic vasculature, as well in the umbilicoplacental vessels. Experimental Physiology (2001) 86.1, 71-82.
Parieto-Occipital Syndrome Following Carbon Monoxide Poisoning
- G. D. F. Steele, A. B. Hegarty
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- Journal:
- Journal of Mental Science / Volume 96 / Issue 405 / October 1950
- Published online by Cambridge University Press:
- 08 February 2018, pp. 1015-1023
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- October 1950
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Suicidal attempts by coal-gas poisoning are very common. Carbon monoxide is a principal constituent of this gas, and can produce severe and permanent brain damage. It is surprising, therefore, to find so few cases of chronic organic psychosis attributed to this cause in mental hospital practice. Rosseter (1928) found only one example of permanent psychosis in 2,000 cases of carbon monoxide asphyxiation. Shillito, Drinker and Shaughnessy (1936) made a follow-up study of 21,000 cases of acute carbon monoxide poisoning. In only 43 of these were the after-effects sufficiently severe to warrant their admission to a mental hospital. Twenty-three subsequently recovered, 11 died, and 9 suffered permanent nervous and mental sequelae. They found that the ratio of psychosis following carbon monoxide poisoning to other psychoses was 1 in 2,000. Henderson and Gillespie (1944) could find only one such case in 5,000 consecutive admissions.