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711 results on '"George, Mike"'

1. Global needs for nitrogen fertilizer to improve wheat yield under climate change

Author

Martre, Pierre, Dueri, Sibylle, Guarin, Jose Rafael, Ewert, Frank, Webber, Heidi, Calderini, Daniel, Molero, Gemma, Reynolds, Matthew, Miralles, Daniel, Garcia, Guillermo, Brown, Hamish, George, Mike, Craigie, Rob, Cohan, Jean-Pierre, Deswarte, Jean-Charles, Slafer, Gustavo, Giunta, Francesco, Cammarano, Davide, Ferrise, Roberto, Gaiser, Thomas, Gao, Yujing, Hochman, Zvi, Hoogenboom, Gerrit, Hunt, Leslie A., Kersebaum, Kurt C., Nendel, Claas, Padovan, Gloria, Ruane, Alex C., Srivastava, Amit Kumar, Stella, Tommaso, Supit, Iwan, Thorburn, Peter, Wang, Enli, Wolf, Joost, Zhao, Chuang, Zhao, Zhigan, and Asseng, Senthold

Published
2024
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2. The GL service: Web service to exchange GL string encoded HLA & KIR genotypes with complete and accurate allele and genotype ambiguity.

Author

Milius, Robert P, Heuer, Michael, George, Mike, Pollack, Jane, Hollenbach, Jill A, Mack, Steven J, and Maiers, Martin

Subjects
Humans, HLA-C Antigens, Computational Biology, Genotype, Alleles, Software, Databases, Genetic, Receptors, KIR, Genetic Loci, Web Browser, GL string, HLA, KIR, RESTful service, Genetics, Immunology
Abstract

Genotype list (GL) Strings use a set of hierarchical character delimiters to represent allele and genotype ambiguity in HLA and KIR genotypes in a complete and accurate fashion. A RESTful web service called genotype list service was created to allow users to register a GL string and receive a unique identifier for that string in the form of a URI. By exchanging URIs and dereferencing them through the GL service, users can easily transmit HLA genotypes in a variety of useful formats. The GL service was developed to be secure, scalable, and persistent. An instance of the GL service is configured with a nomenclature and can be run in strict or non-strict modes. Strict mode requires alleles used in the GL string to be present in the allele database using the fully qualified nomenclature. Non-strict mode allows any GL string to be registered as long as it is syntactically correct. The GL service source code is free and open source software, distributed under the GNU Lesser General Public License (LGPL) version 3 or later.

Published
2016

6. Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment

Author

Dueri, Sibylle, Brown, Hamish, Asseng, Senthold, Ewert, Frank, Webber, Heidi, George, Mike, Craigie, Rob, Guarin, Jose Rafael, Pequeno, Diego N.L., Stella, Tommaso, Ahmed, Mukhtar, Alderman, Phillip D., Basso, Bruno, Berger, Andres G., Mujica, Gennady Bracho, Cammarano, Davide, Chen, Yi, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Gaiser, Thomas, Gao, Yujing, Garcia-Vila, Margarita, Gayler, Sebastian, Hochman, Zvi, Hoogenboom, Gerrit, Kersebaum, Kurt C., Nendel, Claas, Olesen, Jørgen E., Padovan, Gloria, Palosuo, Taru, Priesack, Eckart, Pullens, Johannes W.M., Rodríguez, Alfredo, Rötter, Reimund P., Ramos, Margarita Ruiz, Semenov, Mikhail A., Senapati, Nimai, Siebert, Stefan, Srivastava, Amit Kumar, Stöckle, Claudio, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Wang, Enli, Weber, Tobias Karl David, Xiao, Liujun, Zhao, Chuang, Zhao, Jin, Zhao, Zhigan, Zhu, Yan, Martre, Pierre, Rebetzke, Greg, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), The New Zealand Institute for Plant & Food Research Limited [Auckland] (Plant & Food Research), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Brandenburg University of Technology [Cottbus – Senftenberg] (BTU), Foundation for Arable Research (FAR), University of Florida [Gainesville] (UF), Earth Institute at Columbia University, Columbia University [New York], International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Swedish University of Agricultural Sciences (SLU), Pir Mehr Ali Shah Arid Agriculture University = PMAS-Arid Agriculture University Rawalpindi (AAUR), Oklahoma State University [Stillwater] (OSU), Michigan State University [East Lansing], Michigan State University System, Instituto Nacional de Investigación Agropecuaria (INIA), Georg-August-University = Georg-August-Universität Göttingen, Aarhus University [Aarhus], Institute of geographical sciences and natural resources research [CAS] (IGSNRR), Chinese Academy of Sciences [Beijing] (CAS), Gembloux Agro-Bio Tech [Gembloux], Université de Liège, Instituto de Agricultura Sostenible - Institute for Sustainable Agriculture (IAS CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Universidad de Córdoba = University of Córdoba [Córdoba], Department of Agriculture, Food, Environment and Forestry (DAGRI), Università degli Studi di Firenze = University of Florence (UniFI), Institute of Crop Science and Resource Conservation [Bonn] (INRES), University of Hohenheim, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Global Change Research Centre (CzechGlobe), University of Potsdam = Universität Potsdam, Natural Resources Institute Finland (LUKE), Helmholtz Zentrum München = German Research Center for Environmental Health, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Institute of Biochemical Plant Pathology (BIOP), Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios y Medioambientales (CEIGRAM), Universidad Politécnica de Madrid (UPM), Universidad de Castilla-La Mancha = University of Castilla-La Mancha (UCLM), Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Rothamsted Research, Biotechnology and Biological Sciences Research Council (BBSRC), Washington State University (WSU), Wageningen University and Research [Wageningen] (WUR), Zhejiang University, Nanjing Agricultural University (NAU), China Agricultural University (CAU), Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 and was supported by the French National Research Institute for Agriculture, Food (INRAE) and the International Maize and Wheat Improvement Center (CIMMYT) through the International Wheat Yield Partnership (IWYP, grant IWYP115)., metaprogram Agriculture and forestry in the face of climate change: adaptation and mitigation (CLIMAE) of INRAE, grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) through Designing Future Wheat [BB/P016855/1] and Achieving Sustainable Agricultural Systems [NE/N018125/1] jointly funded with NERC, DivCSA project funded by the Academy of Finland (decision no. 316215)., National Natural Science Foundation of China (No. 31761143006), financial support from BARISTA project (031B0811A) through ERA-NET SusCrop under EU-FACCE JPI, German Federal Ministry of Education and Research (BMBF) through the BonaRes project ’’I4S’’ (031B0513I), German Federal Ministry of Education and Research (BMBF) through the BonaRes Project 'Soil3' (FKZ 031B0026A), Ministry of Education, Youth and Sports of Czech Republic through SustES—Adaption strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/000797), Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2070 – 390732324', German Research Foundation (DFG, Grant Agreement SFB 1253/1 2017), European Project: 618105,EC:FP7:KBBE,FP7-ERANET-2013-RTD,FACCE ERA NET PLUS(2013), Institut National de la Recherche Agronomique (France), International Maize and Wheat Improvement Center, International Wheat Yield Partnership, National Natural Science Foundation of China, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Education, Youth and Sports (Czech Republic), German Research Foundation, Biotechnology and Biological Sciences Research Council (UK), Natural Environment Research Council (UK), and Academy of Finland

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Physiology, Climate Change, sowing date, Plant Science, CHINA, Multi-model Ensemble, New Zealand, Sowing Date, Sowing Density, Tiller Mortality, Tillering, Wheat, Yield Potential, tillering, wheat, USE EFFICIENCY, sowing density, Life Science, Biomass, ADAPTATION, PLANT-DENSITY, Triticum, METAANALYSIS, Multi-model ensemble, WIMEK, CLIMATE-CHANGE, tiller mortality, PRODUCTIVITY, Temperature, CROP MODELS, yield potential, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, ROTATION, GROWTH, Water Systems and Global Change, Seasons
Abstract

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures., This study was a part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 and was supported by the French National Research Institute for Agriculture, Food (INRAE) and the International Maize and Wheat Improvement Center (CIMMYT) through the International Wheat Yield Partnership (IWYP, grant IWYP115). SD and PM acknowledge support from the metaprogram Agriculture and forestry in the face of climate change: adaptation and mitigation (CLIMAE) of INRAE. YC and FT acknowledge support from the National Natural Science Foundation of China (No. 31761143006). RPR and GBM acknowledge financial support from BARISTA project (031B0811A) through ERA-NET SusCrop under EU-FACCE JPI. KCK was funded by the German Federal Ministry of Education and Research (BMBF) through the BonaRes project ’’I4S’’ (031B0513I). AS and TG acknowledge funding by the German Federal Ministry of Education and Research (BMBF) through the BonaRes Project “Soil3” (FKZ 031B0026A). KCK and JEO were supported by the Ministry of Education, Youth and Sports of Czech Republic through SustES—Adaption strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/000797). FE acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2070 – 390732324”. TKDW was funded by the German Research Foundation (DFG, Grant Agreement SFB 1253/1 2017). MAS and NS at Rothamsted Research received grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) through Designing Future Wheat [BB/P016855/1] and Achieving Sustainable Agricultural Systems [NE/N018125/1] jointly funded with NERC. TP and FT are supported by the DivCSA project funded by the Academy of Finland (decision no. 316215).

Published
2022
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7. The nitrogen price of improved wheat yield under climate change

Author

Martre, Pierre, primary, Dueri, Sibylle, additional, Guarin, Jose, additional, Ewert, F, additional, Webber, Heidi, additional, Calderini, Daniel, additional, Molero, Gemma, additional, Reynolds, Matthew, additional, Miralles, Daniel, additional, Garcia, Guillermo, additional, Brown, Hamish, additional, George, Mike, additional, Craigie, Rob, additional, Cohan, Jean-Pierre, additional, Deswarte, Jean-Charles, additional, Slafer, Gustavo, additional, Giunta, F, additional, Cammarano, Davide, additional, Ferrise, Roberto, additional, GAISER, Thomas, additional, Gao, Yujing, additional, Hochman, Zvi, additional, Hoogenboom, Gerrit, additional, Hunt, Leslie A, additional, Kersebaum, Kurt, additional, Nendel, Claas, additional, Padovan, Gloria, additional, Ruane, Alex, additional, Stella, Tommaso, additional, Supit, Iwan, additional, Srivast, Amit, additional, Thorburn, Peter, additional, Wang, Enli, additional, Wolf, Joost, additional, Zhao, Chuang, additional, Zhao, Zhigan, additional, and Asseng, Senthold, additional

Published
2023
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8. Phenotyping early-vigour in oat cover crops to assess plant-trait effects across environments

Author

Teixeira, Edmar, primary, George, Mike, additional, Johnston, Paul, additional, Malcolm, Brendon, additional, Liu, Jian, additional, Ward, Robert, additional, Brown, Hamish, additional, Cichota, Rogerio, additional, Kersebaum, Kurt Christian, additional, Richards, Kate, additional, Maley, Shane, additional, Zyskowski, Robert, additional, Khaembah, Edith, additional, Sood, Abha, additional, and Johnstone, Paul, additional

Published
2023
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9. Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment

Author

Institut National de la Recherche Agronomique (France), International Maize and Wheat Improvement Center, International Wheat Yield Partnership, National Natural Science Foundation of China, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Education, Youth and Sports (Czech Republic), German Research Foundation, Biotechnology and Biological Sciences Research Council (UK), Natural Environment Research Council (UK), Academy of Finland, Dueri, Sibylle, Brown, Hamish, Asseng, Senthold, Ewert, Frank, Webber, Heidi, George, Mike, Craigie, Rob, Guarin, Jose Rafael, Pequeño, Diego N. L., Stella, Tommaso, Ahmed, Mukhtar, Alderman, Phillip, Basso, Bruno, Berger, Andres G., Mujica, Gennady Bracho, Cammarano, Davide, Chen, Yi, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres Castiel, Elías, Ferrise, Roberto, Gaiser, Thomas, Gao, Yujing, García Vila, Margarita, Gayler, Sebastian, Hochman, Zvi, Hoogenboom, Gerrit, Kersebaum, Kurt C., Nendel, Claas, Olesen, Jørgen E., Padovan, Gloria, Palosuo, Taru, Priesack, Eckart, Pullens, Johannes W.M., Rodríguez, Alfredo, Rötter, Reimund P., Ruiz Ramos, Margarita, Semenov, Mikhail A., Senapati, Nimai, Siebert, Stefan, Srivastava, Amit Kumar, Stöckle, Claudio, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Wang, Enli, Weber, Tobias Karl David, Xiao, Liujun, Zhao, Chuang, Zhao, Jin, Zhao, Zhigan, Zhu, Yan, Martre, Pierre, Institut National de la Recherche Agronomique (France), International Maize and Wheat Improvement Center, International Wheat Yield Partnership, National Natural Science Foundation of China, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Education, Youth and Sports (Czech Republic), German Research Foundation, Biotechnology and Biological Sciences Research Council (UK), Natural Environment Research Council (UK), Academy of Finland, Dueri, Sibylle, Brown, Hamish, Asseng, Senthold, Ewert, Frank, Webber, Heidi, George, Mike, Craigie, Rob, Guarin, Jose Rafael, Pequeño, Diego N. L., Stella, Tommaso, Ahmed, Mukhtar, Alderman, Phillip, Basso, Bruno, Berger, Andres G., Mujica, Gennady Bracho, Cammarano, Davide, Chen, Yi, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres Castiel, Elías, Ferrise, Roberto, Gaiser, Thomas, Gao, Yujing, García Vila, Margarita, Gayler, Sebastian, Hochman, Zvi, Hoogenboom, Gerrit, Kersebaum, Kurt C., Nendel, Claas, Olesen, Jørgen E., Padovan, Gloria, Palosuo, Taru, Priesack, Eckart, Pullens, Johannes W.M., Rodríguez, Alfredo, Rötter, Reimund P., Ruiz Ramos, Margarita, Semenov, Mikhail A., Senapati, Nimai, Siebert, Stefan, Srivastava, Amit Kumar, Stöckle, Claudio, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Wang, Enli, Weber, Tobias Karl David, Xiao, Liujun, Zhao, Chuang, Zhao, Jin, Zhao, Zhigan, Zhu, Yan, and Martre, Pierre

Abstract

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures.

Published
2022

10. Data from the winter wheat potential yield experiment in New Zealand and response to variable sowing dates and densities: field experiments and AgMIP-Wheat multi-model simulations

Author

Dueri, Sibylle, Brown, Hamish, Asseng, Senthold, Ewert, Frank, Webber, Heidi, George, Mike, Craigie, Rob, Guarin, Jose Rafael, Pequeno, Diego, Stella, Tommaso, Ahmed, Mukhtar, Alderman, Phillip D., Basso, Bruno, Berger, Andres G., Bracho Mujica, Gennady, Cammarano, Davide, Chen, Yi, Dumont, Benjamin, Eyshi Rezaei, Ehsan, Fereres, Elias, Ferrise, Roberto, Gaiser, Thomas, Gao, Yujing, Garcia-Vila, Margarita, Gayler, Sebastian, Hochman, Zvi, Hoogenboom, Gerrit, Kersebaum, Kurt C., Nendel, Claas, Olesen, Jørgen E., Padovan, Gloria, Palosuo, Taru, Priesack, Eckart, Pullens, Johannes W.M., Rodríguez, Alfredo, Rötter, Reimund P., Ruiz Ramos, Margarita, Semenov, Mikhail A., Senapati, Nimai, Siebert, Stefan, Srivastava, Amit Kumar, Stöckle, Claudio, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Wang, Enli, Weber, Tobias Karl David, Xiao, Liujun, Zhao, Chuang, Zhao, Jin, Zhao, Zhigan, Zhu, Yan, Martre, Pierre, Dueri, Sibylle, Brown, Hamish, Asseng, Senthold, Ewert, Frank, Webber, Heidi, George, Mike, Craigie, Rob, Guarin, Jose Rafael, Pequeno, Diego, Stella, Tommaso, Ahmed, Mukhtar, Alderman, Phillip D., Basso, Bruno, Berger, Andres G., Bracho Mujica, Gennady, Cammarano, Davide, Chen, Yi, Dumont, Benjamin, Eyshi Rezaei, Ehsan, Fereres, Elias, Ferrise, Roberto, Gaiser, Thomas, Gao, Yujing, Garcia-Vila, Margarita, Gayler, Sebastian, Hochman, Zvi, Hoogenboom, Gerrit, Kersebaum, Kurt C., Nendel, Claas, Olesen, Jørgen E., Padovan, Gloria, Palosuo, Taru, Priesack, Eckart, Pullens, Johannes W.M., Rodríguez, Alfredo, Rötter, Reimund P., Ruiz Ramos, Margarita, Semenov, Mikhail A., Senapati, Nimai, Siebert, Stefan, Srivastava, Amit Kumar, Stöckle, Claudio, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Wang, Enli, Weber, Tobias Karl David, Xiao, Liujun, Zhao, Chuang, Zhao, Jin, Zhao, Zhigan, Zhu, Yan, and Martre, Pierre

Abstract

The dataset contains 6 growing seasons of a local winter wheat cultivar ‘Wakanui’ at two farms located in the Canterbury Region of New Zealand. The data of the experiment was used in the AgMIP-Wheat Phase 4 project to evaluate the performance of an ensemble of 29 crop models to predict the effect of changing sowing dates and rates on yield and yield components, in a high-yielding environment. The treatments were managed for non-stress conditions. Data include local daily weather, soil characteristics and initial soil N conditions, crop measurements (anthesis and maturity dates, total above-ground biomass, final grain yield, and yield components), and cultivar information. Simulations include both daily in-season and end-of-season results from 29 wheat crop models.

Published
2022

13. How Mathematics Teaching Can Be Like Improv Theater

Author

George, Mike

Abstract

When this author first began to take classes in theater and comedy improvisation, his motives were largely creative and social, though there was some supposition that his mathematics teaching (at a community college) could benefit as well. Students are known to tout their favorite teachers as "funny." Taking improv classes would presumably loosen him up a little and make him more confident about his stage presence, thereby helping to facilitate the occasional joke or witty aside that could make for moments of shared humor between the teacher and the class. Now, some years and many improv classes later, he has come to recognize that the art of improvising and the art of teaching share fundamental themes. In fact, he believes that they can be seen as crafts that share some fundamental rules. The "rules" involved in improv are somewhat less rigidly defined than those in mathematics, but they are rules, nevertheless, and one stands out above the others: the rule of affirmation. If an instructor wishes to develop an interactive rapport with the students, eliciting their participation and facilitating discussion, one should exhibit sensitivity to students' feelings and egos. By affirming some aspect of any student's input, one also pushes the mathematical "scene" forward, into possibly unexpected and rhetorically rich directions.

Published
2012

15. Evaluation of User Interface and Workflow Design of a Bedside Nursing Clinical Decision Support System

Author

Yuan, Michael Juntao, Finley, George Mike, Long, Ju, Mills, Christy, and Johnson, Ron Kim

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Medical technology, R855-855.5
Abstract

BackgroundClinical decision support systems (CDSS) are important tools to improve health care outcomes and reduce preventable medical adverse events. However, the effectiveness and success of CDSS depend on their implementation context and usability in complex health care settings. As a result, usability design and validation, especially in real world clinical settings, are crucial aspects of successful CDSS implementations. ObjectiveOur objective was to develop a novel CDSS to help frontline nurses better manage critical symptom changes in hospitalized patients, hence reducing preventable failure to rescue cases. A robust user interface and implementation strategy that fit into existing workflows was key for the success of the CDSS. MethodsGuided by a formal usability evaluation framework, UFuRT (user, function, representation, and task analysis), we developed a high-level specification of the product that captures key usability requirements and is flexible to implement. We interviewed users of the proposed CDSS to identify requirements, listed functions, and operations the system must perform. We then designed visual and workflow representations of the product to perform the operations. The user interface and workflow design were evaluated via heuristic and end user performance evaluation. The heuristic evaluation was done after the first prototype, and its results were incorporated into the product before the end user evaluation was conducted. First, we recruited 4 evaluators with strong domain expertise to study the initial prototype. Heuristic violations were coded and rated for severity. Second, after development of the system, we assembled a panel of nurses, consisting of 3 licensed vocational nurses and 7 registered nurses, to evaluate the user interface and workflow via simulated use cases. We recorded whether each session was successfully completed and its completion time. Each nurse was asked to use the National Aeronautics and Space Administration (NASA) Task Load Index to self-evaluate the amount of cognitive and physical burden associated with using the device. ResultsA total of 83 heuristic violations were identified in the studies. The distribution of the heuristic violations and their average severity are reported. The nurse evaluators successfully completed all 30 sessions of the performance evaluations. All nurses were able to use the device after a single training session. On average, the nurses took 111 seconds (SD 30 seconds) to complete the simulated task. The NASA Task Load Index results indicated that the work overhead on the nurses was low. In fact, most of the burden measures were consistent with zero. The only potentially significant burden was temporal demand, which was consistent with the primary use case of the tool. ConclusionsThe evaluation has shown that our design was functional and met the requirements demanded by the nurses’ tight schedules and heavy workloads. The user interface embedded in the tool provided compelling utility to the nurse with minimal distraction.

Published
2013
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18. Understanding water losses from irrigated pastures on loess-derived hillslopes

Author

Langer, Stephanie, primary, Cichota, Rogerio, additional, Thomas, Steve, additional, Wallace, Dirk, additional, Van der Klei, Gina, additional, George, Mike, additional, Johns, Tom, additional, Almond, Peter, additional, Maley, Shane, additional, Arnold, Nathan, additional, Hu, Wei, additional, Srinivasan, MS, additional, Rajanayaka, Channa, additional, Dodson, Matt, additional, Hayman, Roderick, additional, and Ghimire, Chandra, additional

Published
2020
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22. Water and nitrogen stress effects on canopy development and biomass allocation in fodder beet (Beta vulgaris L.).

Author

Khaembah, Edith N., Maley, Shane, Gillespie, Richard, George, Mike, Michel, Alexandre J., Chakwizira, Emmanuel, de Ruiter, John, and Teixeira, Edmar

Subjects
NITROGEN in water, BEETS, ANIMAL feeds, WATER supply, BIOMASS, LEAF growth
Abstract

The effects of water stress on fodder beet (Beta vulgaris L.) production in the field are confounded by the influences of variable inter- and intra-season rainfall. In this study, a rain shelter experiment investigated the effect of water and nitrogen (N) stress on dry matter (DM) production, DM allocation and N partitioning in fodder beet ('Rivage'). Two water-management treatments, irrigated (replacement of the profile water lost weekly) and unirrigated (limited water applied only during fertigation), and three fertiliser N treatments (0, 50 and 300 kg N ha−1 (hereafter, 0N, 50N, 300N)) were evaluated during the 2016–2017 season. Under irrigation, the yield was greater (P =.02) for the 50N than 0N treatments (29.4 and 24.9 t DM ha−1, respectively). Yield did not differ (P =.42) between irrigated 50N and 300N (30.6 t DM ha−1) treatments, indicating surplus N application to the latter. Water and N stress restricted leaf growth, lowered N uptake and reduced yield by 48%–51%. Surplus N in irrigated 300N treatments resulted in increased N uptake and leaf proportion but reduced the storage root proportion. These results demonstrate the plasticity of fodder beet biomass and N allocation in adapting to the availability of water and N. [ABSTRACT FROM AUTHOR]

Published
2022
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27. Get real

Author

George, Mike

Published
1999

29. Description of Panel Method Code ANTARES

Author

Ulbrich, Norbert and George, Mike

Subjects
Research And Support Facilities (Air)
Abstract

Panel method code ANTARES was developed to compute wall interference corrections in a rectangular wind tunnel. The code uses point doublets to represent blockage effects and line doublets to represent lifting effects of a wind tunnel model. Subsonic compressibility effects are modeled by applying the Prandtl-Glauert transformation. The closed wall, open jet, or perforated wall boundary condition may be assigned to a wall panel centroid. The tunnel walls can be represented by using up to 8000 panels. The accuracy of panel method code ANTARES was successfully investigated by comparing solutions for the closed wall and open jet boundary condition with corresponding Method of Images solutions. Fourier transform solutions of a two-dimensional wind tunnel flow field were used to check the application of the perforated wall boundary condition. Studies showed that the accuracy of panel method code ANTARES can be improved by increasing the total number of wall panels in the circumferential direction. It was also shown that the accuracy decreases with increasing free-stream Mach number of the wind tunnel flow field.

Published
2000

35. Home help

Author

George, Mike

Published
1998

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