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1. Exploiting Boundary Loss for the Hierarchical Panoptic Segmentation of Plants and Leaves

Author

Darbyshire, Madeleine, Sklar, Elizabeth, and Parsons, Simon

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Precision agriculture leverages data and machine learning so that farmers can monitor their crops and target interventions precisely. This enables the precision application of herbicide only to weeds, or the precision application of fertilizer only to undernourished crops, rather than to the entire field. The approach promises to maximize yields while minimizing resource use and harm to the surrounding environment. To this end, we propose a hierarchical panoptic segmentation method that simultaneously determines leaf count (as an identifier of plant growth)and locates weeds within an image. In particular, our approach aims to improve the segmentation of smaller instances like the leaves and weeds by incorporating focal loss and boundary loss. Not only does this result in competitive performance, achieving a PQ+ of 81.89 on the standard training set, but we also demonstrate we can improve leaf-counting accuracy with our method. The code is available at https://github.com/madeleinedarbyshire/HierarchicalMask2Former., Comment: Presented at the 9th Workshop for Computer Vision in Plant Phenotyping and Agriculture (CVPPA) 2024 at the European Conference of Computer Vision (ECCV) 2024. arXiv admin note: text overlap with arXiv:2310.06582

Published
2024

2. Multispectral Fine-Grained Classification of Blackgrass in Wheat and Barley Crops

Author

Darbyshire, Madeleine, Coutts, Shaun, Hammond, Eleanor, Gokbudak, Fazilet, Oztireli, Cengiz, Bosilj, Petra, Gao, Junfeng, Sklar, Elizabeth, and Parsons, Simon

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

As the burden of herbicide resistance grows and the environmental repercussions of excessive herbicide use become clear, new ways of managing weed populations are needed. This is particularly true for cereal crops, like wheat and barley, that are staple food crops and occupy a globally significant portion of agricultural land. Even small improvements in weed management practices across these major food crops worldwide would yield considerable benefits for both the environment and global food security. Blackgrass is a major grass weed which causes particular problems in cereal crops in north-west Europe, a major cereal production area, because it has high levels of of herbicide resistance and is well adapted to agronomic practice in this region. With the use of machine vision and multispectral imaging, we investigate the effectiveness of state-of-the-art methods to identify blackgrass in wheat and barley crops. As part of this work, we provide a large dataset with which we evaluate several key aspects of blackgrass weed recognition. Firstly, we determine the performance of different CNN and transformer-based architectures on images from unseen fields. Secondly, we demonstrate the role that different spectral bands have on the performance of weed classification. Lastly, we evaluate the role of dataset size in classification performance for each of the models trialled. We find that even with a fairly modest quantity of training data an accuracy of almost 90% can be achieved on images from unseen fields., Comment: 19 pages, 6 figures

Published
2024

4. A biogeographical appraisal of the threatened South East Africa Montane Archipelago ecoregion

Author

Bayliss, Julian, Bittencourt-Silva, Gabriela B., Branch, William R., Bruessow, Carl, Collins, Steve, Congdon, T. Colin E., Conradie, Werner, Curran, Michael, Daniels, Savel R., Darbyshire, Iain, Farooq, Harith, Fishpool, Lincoln, Grantham, Geoffrey, Magombo, Zacharia, Matimele, Hermenegildo, Monadjem, Ara, Monteiro, Jose, Osborne, Jo, Saunders, Justin, Smith, Paul, Spottiswoode, Claire N., Taylor, Peter J., Timberlake, Jonathan, Tolley, Krystal A., Tovela, Érica, and Platts, Philip J.

Published
2024
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5. Hierarchical Mask2Former: Panoptic Segmentation of Crops, Weeds and Leaves

Author

Darbyshire, Madeleine, Sklar, Elizabeth, and Parsons, Simon

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Advancements in machine vision that enable detailed inferences to be made from images have the potential to transform many sectors including agriculture. Precision agriculture, where data analysis enables interventions to be precisely targeted, has many possible applications. Precision spraying, for example, can limit the application of herbicide only to weeds, or limit the application of fertiliser only to undernourished crops, instead of spraying the entire field. The approach promises to maximise yields, whilst minimising resource use and harms to the surrounding environment. To this end, we propose a hierarchical panoptic segmentation method to simultaneously identify indicators of plant growth and locate weeds within an image. We adapt Mask2Former, a state-of-the-art architecture for panoptic segmentation, to predict crop, weed and leaf masks. We achieve a PQ{\dag} of 75.99. Additionally, we explore approaches to make the architecture more compact and therefore more suitable for time and compute constrained applications. With our more compact architecture, inference is up to 60% faster and the reduction in PQ{\dag} is less than 1%., Comment: 6 pages, 5 figures, 2 tables, for code, see https://github.com/madeleinedarbyshire/HierarchicalMask2Former

Published
2023

6. Phylogenomics and the rise of the angiosperms

Author

Zuntini, Alexandre R., Carruthers, Tom, Maurin, Olivier, Bailey, Paul C., Leempoel, Kevin, Brewer, Grace E., Epitawalage, Niroshini, Françoso, Elaine, Gallego-Paramo, Berta, McGinnie, Catherine, Negrão, Raquel, Roy, Shyamali R., Simpson, Lalita, Toledo Romero, Eduardo, Barber, Vanessa M. A., Botigué, Laura, Clarkson, James J., Cowan, Robyn S., Dodsworth, Steven, Johnson, Matthew G., Kim, Jan T., Pokorny, Lisa, Wickett, Norman J., Antar, Guilherme M., DeBolt, Lucinda, Gutierrez, Karime, Hendriks, Kasper P., Hoewener, Alina, Hu, Ai-Qun, Joyce, Elizabeth M., Kikuchi, Izai A. B. S., Larridon, Isabel, Larson, Drew A., de Lírio, Elton John, Liu, Jing-Xia, Malakasi, Panagiota, Przelomska, Natalia A. S., Shah, Toral, Viruel, Juan, Allnutt, Theodore R., Ameka, Gabriel K., Andrew, Rose L., Appelhans, Marc S., Arista, Montserrat, Ariza, María Jesús, Arroyo, Juan, Arthan, Watchara, Bachelier, Julien B., Bailey, C. Donovan, Barnes, Helen F., Barrett, Matthew D., Barrett, Russell L., Bayer, Randall J., Bayly, Michael J., Biffin, Ed, Biggs, Nicky, Birch, Joanne L., Bogarín, Diego, Borosova, Renata, Bowles, Alexander M. C., Boyce, Peter C., Bramley, Gemma L. C., Briggs, Marie, Broadhurst, Linda, Brown, Gillian K., Bruhl, Jeremy J., Bruneau, Anne, Buerki, Sven, Burns, Edie, Byrne, Margaret, Cable, Stuart, Calladine, Ainsley, Callmander, Martin W., Cano, Ángela, Cantrill, David J., Cardinal-McTeague, Warren M., Carlsen, Mónica M., Carruthers, Abigail J. A., de Castro Mateo, Alejandra, Chase, Mark W., Chatrou, Lars W., Cheek, Martin, Chen, Shilin, Christenhusz, Maarten J. M., Christin, Pascal-Antoine, Clements, Mark A., Coffey, Skye C., Conran, John G., Cornejo, Xavier, Couvreur, Thomas L. P., Cowie, Ian D., Csiba, Laszlo, Darbyshire, Iain, Davidse, Gerrit, Davies, Nina M. J., Davis, Aaron P., van Dijk, Kor-jent, Downie, Stephen R., Duretto, Marco F., Duvall, Melvin R., Edwards, Sara L., Eggli, Urs, Erkens, Roy H. J., Escudero, Marcial, de la Estrella, Manuel, Fabriani, Federico, Fay, Michael F., Ferreira, Paola de L., Ficinski, Sarah Z., Fowler, Rachael M., Frisby, Sue, Fu, Lin, Fulcher, Tim, Galbany-Casals, Mercè, Gardner, Elliot M., German, Dmitry A., Giaretta, Augusto, Gibernau, Marc, Gillespie, Lynn J., González, Cynthia C., Goyder, David J., Graham, Sean W., Grall, Aurélie, Green, Laura, Gunn, Bee F., Gutiérrez, Diego G., Hackel, Jan, Haevermans, Thomas, Haigh, Anna, Hall, Jocelyn C., Hall, Tony, Harrison, Melissa J., Hatt, Sebastian A., Hidalgo, Oriane, Hodkinson, Trevor R., Holmes, Gareth D., Hopkins, Helen C. F., Jackson, Christopher J., James, Shelley A., Jobson, Richard W., Kadereit, Gudrun, Kahandawala, Imalka M., Kainulainen, Kent, Kato, Masahiro, Kellogg, Elizabeth A., King, Graham J., Klejevskaja, Beata, Klitgaard, Bente B., Klopper, Ronell R., Knapp, Sandra, Koch, Marcus A., Leebens-Mack, James H., Lens, Frederic, Leon, Christine J., Léveillé-Bourret, Étienne, Lewis, Gwilym P., Li, De-Zhu, Li, Lan, Liede-Schumann, Sigrid, Livshultz, Tatyana, Lorence, David, Lu, Meng, Lu-Irving, Patricia, Luber, Jaquelini, Lucas, Eve J., Luján, Manuel, Lum, Mabel, Macfarlane, Terry D., Magdalena, Carlos, Mansano, Vidal F., Masters, Lizo E., Mayo, Simon J., McColl, Kristina, McDonnell, Angela J., McDougall, Andrew E., McLay, Todd G. B., McPherson, Hannah, Meneses, Rosa I., Merckx, Vincent S. F. T., Michelangeli, Fabián A., Mitchell, John D., Monro, Alexandre K., Moore, Michael J., Mueller, Taryn L., Mummenhoff, Klaus, Munzinger, Jérôme, Muriel, Priscilla, Murphy, Daniel J., Nargar, Katharina, Nauheimer, Lars, Nge, Francis J., Nyffeler, Reto, Orejuela, Andrés, Ortiz, Edgardo M., Palazzesi, Luis, Peixoto, Ariane Luna, Pell, Susan K., Pellicer, Jaume, Penneys, Darin S., Perez-Escobar, Oscar A., Persson, Claes, Pignal, Marc, Pillon, Yohan, Pirani, José R., Plunkett, Gregory M., Powell, Robyn F., Prance, Ghillean T., Puglisi, Carmen, Qin, Ming, Rabeler, Richard K., Rees, Paul E. J., Renner, Matthew, Roalson, Eric H., Rodda, Michele, Rogers, Zachary S., Rokni, Saba, Rutishauser, Rolf, de Salas, Miguel F., Schaefer, Hanno, Schley, Rowan J., Schmidt-Lebuhn, Alexander, Shapcott, Alison, Al-Shehbaz, Ihsan, Shepherd, Kelly A., Simmons, Mark P., Simões, André O., Simões, Ana Rita G., Siros, Michelle, Smidt, Eric C., Smith, James F., Snow, Neil, Soltis, Douglas E., Soltis, Pamela S., Soreng, Robert J., Sothers, Cynthia A., Starr, Julian R., Stevens, Peter F., Straub, Shannon C. K., Struwe, Lena, Taylor, Jennifer M., Telford, Ian R. H., Thornhill, Andrew H., Tooth, Ifeanna, Trias-Blasi, Anna, Udovicic, Frank, Utteridge, Timothy M. A., Del Valle, Jose C., Verboom, G. Anthony, Vonow, Helen P., Vorontsova, Maria S., de Vos, Jurriaan M., Al-Wattar, Noor, Waycott, Michelle, Welker, Cassiano A. D., White, Adam J., Wieringa, Jan J., Williamson, Luis T., Wilson, Trevor C., Wong, Sin Yeng, Woods, Lisa A., Woods, Roseina, Worboys, Stuart, Xanthos, Martin, Yang, Ya, Zhang, Yu-Xiao, Zhou, Meng-Yuan, Zmarzty, Sue, Zuloaga, Fernando O., Antonelli, Alexandre, Bellot, Sidonie, Crayn, Darren M., Grace, Olwen M., Kersey, Paul J., Leitch, Ilia J., Sauquet, Hervé, Smith, Stephen A., Eiserhardt, Wolf L., Forest, Félix, and Baker, William J.

Published
2024
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7. Towards practical object detection for weed spraying in precision agriculture

Author

Salazar-Gomez, Adrian, Darbyshire, Madeleine, Gao, Junfeng, Sklar, Elizabeth I, and Parsons, Simon

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Robotics
Abstract

The evolution of smaller, faster processors and cheaper digital storage mechanisms across the last 4-5 decades has vastly increased the opportunity to integrate intelligent technologies in a wide range of practical environments to address a broad spectrum of tasks. One exciting application domain for such technologies is precision agriculture, where the ability to integrate on-board machine vision with data-driven actuation means that farmers can make decisions about crop care and harvesting at the level of the individual plant rather than the whole field. This makes sense both economically and environmentally. However, the key driver for this capability is fast and robust machine vision -- typically driven by machine learning (ML) solutions and dependent on accurate modelling. One critical challenge is that the bulk of ML-based vision research considers only metrics that evaluate the accuracy of object detection and do not assess practical factors. This paper introduces three metrics that highlight different aspects relevant for real-world deployment of precision weeding and demonstrates their utility through experimental results., Comment: 7 pages, 5 figures, 4 tables

Published
2021

8. A Taxonomically-verified and Vouchered Checklist of the Vascular Plants of the Republic of Guinea

Author

Gosline, George, Bidault, Ehoarn, van der Burgt, Xander, Cahen, Daniel, Challen, Gill, Condé, Nagnouma, Couch, Charlotte, Couvreur, Thomas L. P., Dagallier, Léo-Paul M. J., Darbyshire, Iain, Dawson, Sally, Doré, Tokpa Seny, Goyder, David, Grall, Aurélie, Haba, Pépé, Haba, Pierre, Harris, David, Hind, D. J. Nicholas, Jongkind, Carel, Konomou, Gbamon, Larridon, Isabel, Lewis, Gwilym, Ley, Alexandra, Lock, Michael, Lucas, Eve, Magassouba, Sékou, Mayo, Simon, Molmou, Denise, Monro, Alexandre, Onana, Jean Michel, Paiva, Jorge, Paton, Alan, Phillips, Sylvia, Prance, Ghillean, Quintanar, Alejandro, Rokni, Saba, Shah, Toral, Schrire, Brian, Schuiteman, André, Simões, Ana Rita Giraldes, Sosef, Marc, Stévart, Tariq, Stone, R. Doug, Utteridge, Tim, Wilkin, Paul, Xanthos, Martin, Nic Lughadha, Eimear, and Cheek, Martin

Published
2023
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9. Chinese Students' Cultural and Behavioural Differences among Domestic and Internationally Oriented Educational Institutions

Author

Haarms, Ron, Holtzman, J, Xue, Tiki, and Darbyshire, Dominic

Abstract

Research has found a link between active student participation in the classroom and memory retention. Participation can encompass many aspects, including asking questions in class and partaking in classroom activities. Extensive studies have been conducted on Chinese students concerning their overall involvement in class. When compared to their Western counterparts, Chinese students are often regarded as silent passive learners (i.e. not active), hence negatively affecting their ability to learn in the classroom environment. The changeability of education together with ongoing globalization has led to an increase in Chinese students going abroad. As a result, there has been an increase in demand for international high schools and other educational training centres that prepare Chinese students for tertiary education in the West. This research investigates classroom behaviours and face values of students attending a Chinese international high school and compares them with students attending a conventional Chinese public high school. A MANOVA is used to assess these differences based on a questionnaire submitted to 349 students from Taiyuan, Shanxi province in China. Results show that students following an international program ask more questions in class, but no difference is found in regards to the Chinese cultural value of face. Subsequently, auxiliary qualitative research was performed to clarify quantitative outcomes. These outcomes showed that efforts to save face, academic pressure, classroom environment, and pre-existing individual factors contribute to this found difference.

Published
2018

10. On the numerical solution of the Van der Pol equation using collocation

Author

Darbyshire, J Hamish M

Subjects
Mathematics - Numerical Analysis
Abstract

This study introduces the reader to the theory of approximating the solution(s) of a non-linear, second order, ordinary differential equation (ODE) with piecewise polynomial functions by using the collocation method. It then focuses on the application of the method to generate collocation approximations for the Van der Pol equation with initial conditions and with varying equation parameter, {\mu}. It is shown that the collocation method in its original form is impractical for generating these approximations due to the numerical costs of producing such an approximation, particularly as the stiffness of the equation increases with parameter, {\mu}. An adaptation to the method, termed segmented collocation, is proposed, reliant upon on the specific structure and convergence for initial value problems, and shown theoretically and numerically to be capable of generating equivalent approximations for much superior costs. Further study is proposed; to compare the segmented method to other numerical methods traditionally employed with equations of this type such as the Runge-Kutta family; and to develop and test the method in order to ascertain its complete usefulness and competitive standing in the context of approximating second order, ODEs with initial conditions., Comment: 48 pages

Published
2018

15. New Guinea has the world’s richest island flora

Author

Cámara-Leret, Rodrigo, Frodin, David G., Adema, Frits, Anderson, Christiane, Appelhans, Marc S., Argent, George, Arias Guerrero, Susana, Ashton, Peter, Baker, William J., Barfod, Anders S., Barrington, David, Borosova, Renata, Bramley, Gemma L. C., Briggs, Marie, Buerki, Sven, Cahen, Daniel, Callmander, Martin W., Cheek, Martin, Chen, Cheng-Wei, Conn, Barry J., Coode, Mark J. E., Darbyshire, Iain, Dawson, Sally, Dransfield, John, Drinkell, Clare, Duyfjes, Brigitta, Ebihara, Atsushi, Ezedin, Zacky, Fu, Long-Fei, Gideon, Osia, Girmansyah, Deden, Govaerts, Rafaël, Fortune-Hopkins, Helen, Hassemer, Gustavo, Hay, Alistair, Heatubun, Charlie D., Hind, D. J. Nicholas, Hoch, Peter, Homot, Peter, Hovenkamp, Peter, Hughes, Mark, Jebb, Matthew, Jennings, Laura, Jimbo, Tiberius, Kessler, Michael, Kiew, Ruth, Knapp, Sandra, Lamei, Penniel, Lehnert, Marcus, Lewis, Gwilym P., Linder, Hans Peter, Lindsay, Stuart, Low, Yee Wen, Lucas, Eve, Mancera, Jeffrey P., Monro, Alexandre K., Moore, Alison, Middleton, David J., Nagamasu, Hidetoshi, Newman, Mark F., Nic Lughadha, Eimear, Melo, Pablo H. A., Ohlsen, Daniel J., Pannell, Caroline M., Parris, Barbara, Pearce, Laura, Penneys, Darin S., Perrie, Leon R., Petoe, Peter, Poulsen, Axel Dalberg, Prance, Ghillean T., Quakenbush, J. Peter, Raes, Niels, Rodda, Michele, Rogers, Zachary S., Schuiteman, André, Schwartsburd, Pedro, Scotland, Robert W., Simmons, Mark P., Simpson, David A., Stevens, Peter, Sundue, Michael, Testo, Weston, Trias-Blasi, Anna, Turner, Ian, Utteridge, Timothy, Walsingham, Lesley, Webber, Bruce L., Wei, Ran, Weiblen, George D., Weigend, Maximilian, Weston, Peter, de Wilde, Willem, Wilkie, Peter, Wilmot-Dear, Christine M., Wilson, Hannah P., Wood, John R. I., Zhang, Li-Bing, and van Welzen, Peter C.

Published
2020
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17. Everyday Learning in the Kitchen. Everyday Learning Series. Volume 2, Number 4

Author

Darbyshire, Jo and Darbyshire, Jo

Abstract

The "Everyday Learning" series has been developed to focus attention on the everyday ways in which children can be supported in their growth and development. Many of one's earliest memories are likely to be about time spent in the kitchen. Licking the bowl, setting the table, doing the dishes, chatting about the day, eating a meal, peeling the vegetables, and experimenting with cooking are experiences familiar to many children. The kitchen is not only a place to prepare and store food but also can offer an unlimited number of learning opportunities for children. Science, language, maths, chemistry, physics, reading, nutrition and hygiene knowledge are being used and explored every day in the kitchen. Children who spend time with adults in the kitchen are being offered opportunities to explore all these topics. They will also enjoy sharing with the important people in their lives. This document outlines a range of ways in which babies, toddlers and preschoolers can be involved in the kitchen, stimulating their senses, their thinking and co-ordination skills. It gives parents, grandparents and caregivers ideas that they can share with young children to enhance their developing capacities and make everyday activities fun! Some of the topics highlighted in this issue include: (1) Learning in the kitchen; (2) Babies, Experiences--things to do; (3) Toddlers, Development--what to expect; (4) Preschoolers, Development--what to expect, things to do; and (6) Some useful recipes. A brief section listing resources and references is also included. [This document was produced by Early Childhood Australia, Inc., formerly known as the Australian Early Childhood Association.]

Published
2004

23. The influence of hospital volume on long-term oncological outcome after rectal cancer surgery

Author

Jonker, Frederik H. W., Hagemans, Jan A. W., Burger, Jacobus W. A., Verhoef, Cornelis, Borstlap, Wernard A. A., Tanis, Pieter J., Aalbers, A., Acherman, Y., Algie, G. D., Alting von Geusau, B., Amelung, F., Aukema, T. S., Bakker, I. S., Bartels, S. A., Basha, S., Bastiaansen, A. J. N. M., Belgers, E., Bemelman, W. A., Bleeker, W., Blok, J., Bosker, R. J. I., Bosmans, J. W., Boute, M. C., Bouvy, N. D., Bouwman, H., Brandt-Kerkhof, A., Brinkman, D. J., Bruin, S., Bruns, E. R. J., Burbach, J. P. M., Clermonts, S., Coene, P. P. L. O., Compaan, C., Consten, E. C. J., Darbyshire, T., de Mik, S. M. L., de Graaf, E. J. R., de Groot, I., de vos tot Nederveen Cappel, R. J. L., de Wilt, J. H. W., van der Wolde, J., den Boer, F. C., Dekker, J. W. T., Demirkiran, A., Derkx-Hendriksen, M., Dijkstra, F. R., van Duijvendijk, P., Dunker, M. S., Eijsbouts, Q. E., Fabry, H., Ferenschild, F., Foppen, J. W., Furnée, E. J. B., Gerhards, M. F., Gerven, P., Gooszen, J. A. H., Govaert, J. A., Van Grevenstein, W. M. U., Haen, R., Harlaar, J. J., Harst, E., Havenga, K., Heemskerk, J., Heeren, J. F., Heijnen, B., Heres, P., Hoff, C., Hogendoorn, W., Hoogland, P., Huijbers, A., Gooszen, J. A. H., Janssen, P., Jongen, A. C., Karthaus, E. G., Keijzer, A., Ketel, J. M. A., Klaase, J., Kloppenberg, F. W. H., Kool, M. E., Kortekaas, R., Kruyt, P. M., Kuiper, J. T., Lamme, B., Lange, J. F., Lettinga, T., Lips, D. J., Logeman, F., Lutke Holzik, M. F., Madsen, E., Mamound, A., Marres, C. C., Masselink, I., Meerdink, M., Menon, A. G., Mieog, J. S., Mierlo, D., Musters, G. D., Neijenhuis, P. A., Nonner, J., Oostdijk, M., Oosterling, S. J., Paul, P. M. P., Peeters, K. C. M. J. C., Pereboom, I. T. A., Polat, F., Poortman, P., Raber, M., Reiber, B. M. M., Renger, R. J., van Rossem, C. C., Rutten, H. J., Rutten, A., Schaapman, R., Scheer, M., Schoonderwoerd, L., Schouten, N., Schreuder, A. M., Schreurs, W. H., Simkens, G. A., Slooter, G. D., Sluijmer, H. C. E., Smakman, N., Smeenk, R., Snijders, H. S., Sonneveld, D. J. A., Spaansen, B., Spillenaar Bilgen, E. J., Steller, E., Steup, W. H., Steur, C., Stortelder, E., Straatman, J., Swank, H. A., Sietses, C., ten Berge, H. A., ten hoeve, H. G., ter Riele, W. W., Thorensen, I. M., Tip-Pluijm, B., Toorenvliet, B. R., Tseng, L., Tuynman, J. B., van Bastelaar, J., van beek, S. C., van de Ven, A. W. H., van de Weijer, M. A. J., van den Berg, C., van den Bosch, I., van der Bilt, J. D. W., van der Hagen, S. J., van der hul, R., van der Schelling, G., van der Spek, A., van der Wielen, N., van duyn, E., van Eekelen, C., van Essen, J. A., van Gangelt, K., van Geloven, A. A. W., van kessel, C., van Loon, Y. T., van Rijswijk, A., van Rooijen, S. J., van Sprundel, T., van Steensel, L., van Tets, W. F., van Westreenen, H. L., Veltkamp, S., Verhaak, T., Verheijen, P. M., Versluis-Ossenwaarde, L., Vijfhuize, S., Vles, W. J., Voeten, S., Vogelaar, F. J., Vrijland, W. W., Westerduin, E., Westerterp, M. E., Wetzel, M., Wevers, K., Wiering, B., Witjes, A. C., Wouters, M. W., Yauw, S. T. K., Zeestraten, E. C., Zimmerman, D. D., Zwieten, T., and Dutch Snapshot Research Group

Published
2017
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26. Reactions of the bioregulatory agent nitric oxide in oxygenated aqueous media: determination of the kinetics for oxidation and nitrosation by intermediates generated in the NO/O2 reaction.

Author

Wink, DA, Darbyshire, JF, Nims, RW, Saavedra, JE, and Ford, PC

Subjects
Biomedical and Clinical Sciences, Medicinal and Biomolecular Chemistry, Organic Chemistry, Chemical Sciences, Pharmacology and Pharmaceutical Sciences, Aerobiosis, Benzothiazoles, Diazonium Compounds, Ferrocyanides, Gases, Kinetics, Nitric Oxide, Nitroso Compounds, Oxidation-Reduction, Oxygen, Solutions, Spectrophotometry, Ultraviolet, Sulfanilamides, Sulfonic Acids, Inorganic Chemistry, Toxicology, Pharmacology and pharmaceutical sciences, Medicinal and biomolecular chemistry, Organic chemistry
Abstract

The reaction kinetics of nitric oxide autoxidation in aerobic solutions were investigated by direct observation of the nitrite ion product and by trapping the strongly oxidizing and nitrosating intermediates formed in this reaction. The rate behavior observed for nitrite formation [rate = k3[O2][NO]2, k3 = (6 +/- 1.5) x 10(6) M-2 s-1 at 22 degrees C] was the same as found for oxidation of Fe(CN)6(4-) and of 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and as for the nitrosation of sulfanilamide. There was a slight decrease in k3 to (3.5 +/- 0.7) x 10(6) M-2 s-1 at 37 degrees C. The second-order dependency for NO was observed at NO concentrations as low as 3 microM. The results of the competitive kinetics studies suggest that the key oxidizing intermediates, species which are both strong oxidants and nitrosating agents, are not one of those commonly proposed (NO2, N2O3, NO+, or O2NO-) but are one or more as yet uncharacterized NOx species.

Published
1993

31. Early Education Programs and Aboriginal Families in Victoria.

Author

Monash Univ., Clayton, Victoria (Australia)., Bernard Van Leer Foundation, The Hague (Netherlands)., Scott, Phyllis M., and Darbyshire, Margaret

Abstract

This report summarizes some of the thinking, data, problems and other factors affecting the field work of a 4-year study of preschool programs with aboriginal families in Victoria. The project aims included: (1) establishing positive communication with part-aboriginal families in Victoria, in order to understand what planned educational contributions might appropriately be made to families with young children; (2) developing tentative preschool programs which, while allowing such communication, would provide some immediate educational support and create bases for developing future work; (3) defining issues needing consideration in educational work with part-aboriginal adults and children, and trying to develop a frame of reference which would help resolve some of the current controversy surrounding experimental preschool programs; and (4) obtaining descriptive information relevant to these issues in education and psychological research. In addition, the emphasis of this report is a descriptive analysis of some current problems affecting progress with field work, such as: clarifying purposes and bases for action, selection and review of tests, teaching programs and field work problems, followup studies, and establishing guidelines for future action. (CS)

Published
1973

46. Detecting Vietnam War bomb craters in declassified historical KH-9 satellite imagery

Author

Barthelme, Philipp, Darbyshire, Eoghan, Spracklen, Dominick V., and Watmough, Gary R.

Abstract

Thousands of people are injured every year from explosive remnants of war which include unexploded ordnance (UXO) and abandoned ordnance. UXO has negative long-term impacts on livelihoods and ecosystems in contaminated areas. Exact locations of remaining UXO are often unknown as survey and clearance activities can be dangerous, expensive and time-consuming. In Vietnam, Lao PDR and Cambodia, about 20% of the land remains contaminated by UXO from the Vietnam War. Recently declassified historical KH-9 satellite imagery, taken during and immediately after the Vietnam War, now provides an opportunity to map this remaining contamination. KH-9 imagery was acquired and orthorectified for two study areas in Southeast Asia. Bomb craters were manually labeled in a subset of the imagery to train convolutional neural networks (CNNs) for automated crater detection. The CNNs achieved a F1-Score of 0.61 and identified more than 500,000 bomb craters across the two study areas. The detected craters provided more precise information on the impact locations of bombs than target locations available from declassified U.S. bombing records. This could allow for a more precise localization of suspected hazardous areas during non-technical surveys as well as a more fine-grained determination of residual risk of UXO. The method is directly transferable to other areas in Southeast Asia and is cost-effective due to the low cost of the KH-9 imagery and the use of open-source software. The results also show the potential of integrating crater detection into data-driven decision making in mine action across more recent conflicts.

Published
2024
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49. Can nursing educators learn to trust the world's most trusted profession?

Author

Darbyshire, P, Thompson, DR, Darbyshire, P, and Thompson, DR

Abstract

Nursing and nursing education face a paradox whereby the world's most trusted profession seems not to trust its own students and practitioners. Much of nursing education has adopted what has been memorably described as the 'cop shit' approach. This is the panoply of surveillance, anti-plagiarism and proctoring technologies that appear to be used more for policing and punishment of an inherently dishonest student body than to develop ethical and scholarly writing among future peers and colleagues. Nurses in practice may experience similar levels of distrust as they face growing micromanagement and control of both their appearance and nursing practice. We propose that these practices of distrust emerge, not from malice, but rather from the omnipresent neoliberalism and managerialism that engulf almost every aspect of health and university life. Neoliberalism's success has been to reformat academia and practice to the point where such ingrained mistrust has become merely a neutral recognition of 'the real world'. Dismantling nursing and education's 'cop shit' culture and replacing it with the trust and respect that the world's most trusted profession is accorded by wider society will not be easy, but it is vital for the future of nursing.

Published
2021

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