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2,986 results on '"Durward A"'

1. cantnlp@LT-EDI-2024: Automatic Detection of Anti-LGBTQ+ Hate Speech in Under-resourced Languages

Author

Wong, Sidney G. -J. and Durward, Matthew

Subjects
Computer Science - Computation and Language
Abstract

This paper describes our homophobia/transphobia in social media comments detection system developed as part of the shared task at LT-EDI-2024. We took a transformer-based approach to develop our multiclass classification model for ten language conditions (English, Spanish, Gujarati, Hindi, Kannada, Malayalam, Marathi, Tamil, Tulu, and Telugu). We introduced synthetic and organic instances of script-switched language data during domain adaptation to mirror the linguistic realities of social media language as seen in the labelled training data. Our system ranked second for Gujarati and Telugu with varying levels of performance for other language conditions. The results suggest incorporating elements of paralinguistic behaviour such as script-switching may improve the performance of language detection systems especially in the cases of under-resourced languages conditions., Comment: Accepted EACL 2024 Workshop LTEDI

Published
2024

3. cantnlp@LT-EDI-2023: Homophobia/Transphobia Detection in Social Media Comments using Spatio-Temporally Retrained Language Models

Author

Wong, Sidney G. -J., Durward, Matthew, Adams, Benjamin, and Dunn, Jonathan

Subjects
Computer Science - Computation and Language
Abstract

This paper describes our multiclass classification system developed as part of the LTEDI@RANLP-2023 shared task. We used a BERT-based language model to detect homophobic and transphobic content in social media comments across five language conditions: English, Spanish, Hindi, Malayalam, and Tamil. We retrained a transformer-based crosslanguage pretrained language model, XLMRoBERTa, with spatially and temporally relevant social media language data. We also retrained a subset of models with simulated script-mixed social media language data with varied performance. We developed the best performing seven-label classification system for Malayalam based on weighted macro averaged F1 score (ranked first out of six) with variable performance for other language and class-label conditions. We found the inclusion of this spatio-temporal data improved the classification performance for all language and task conditions when compared with the baseline. The results suggests that transformer-based language classification systems are sensitive to register-specific and language-specific retraining.

Published
2023

7. The anatomy of Boris type solvers and the Lie operator formalism for deriving large time-step magnetic field integrators

Author

Chin, Siu A. and Cator, Durward

Subjects
Physics - Plasma Physics, Mathematics - Numerical Analysis
Abstract

This work gives a Lie operator derivation of various Boris solvers via a detailed study of trajectory errors in a constant magnetic field. These errors in the gyrocenter location and the gyroradius are the foundational basis for why Boris solvers existed, independent of any finite-difference schemes. This work shows that there are two distinct ways of eliminating these errors so that the trajectory of a charged particle in a constant magnetic field is exactly on the cyclotron orbit. One way reproduces the known second-order symmetric Boris solver. The other yields a previously unknown, but also on-orbit solver, not derivable from finite-difference schemes. By revisiting some historical calculations, it is found that many publications do not distinguish the poorly behaved leap-frog Boris solver from the symmetric second-order Boris algorithm. This symmetric second-order Boris solver's trajectory is much more accurate and remains close to the exact orbit in a combined $nonuniform$ electric and magnetic field at time-steps greater than the cyclotron period. Finally, this operator formalism showed that Buneman's cycloid fitting scheme is mathematically identical to Boris' on-orbit solver and that Boris' E-B splitting is unnecessary., Comment: Completely revised with 32 pages and 18 figures

Published
2021
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8. A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread

Author

Tan, Yukun, Cator III, Durward, Ndeffo-Mbah, Martial, and Braga-Neto, Ulisses

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Social and Information Networks, Quantitative Biology - Populations and Evolution
Abstract

Mathematical models are widely recognized as an important tool for analyzing and understanding the dynamics of infectious disease outbreaks, predict their future trends, and evaluate public health intervention measures for disease control and elimination. We propose a novel stochastic metapopulation state-space model for COVID-19 transmission, based on a discrete-time spatio-temporal susceptible/exposed/infected/recovered/deceased (SEIRD) model. The proposed framework allows the hidden SEIRD states and unknown transmission parameters to be estimated from noisy, incomplete time series of reported epidemiological data, by application of unscented Kalman filtering (UKF), maximum-likelihood adaptive filtering, and metaheuristic optimization. Experiments using both synthetic data and real data from the Fall 2020 Covid-19 wave in the state of Texas demonstrate the effectiveness of the proposed model., Comment: 17 pages, 5 figures

Published
2021

10. Extracorporeal Life Support Organization Registry International Report 2022: 100,000 Survivors

Author

Tonna, Joseph E., Boonstra, Philip S., MacLaren, Graeme, Paden, Matthew, Brodie, Daniel, Anders, Marc, Hoskote, Aparna, Ramanathan, Kollengode, Hyslop, Rob, Fanning, Jeffrey J., Rycus, Peter, Stead, Christine, Barrett, Nicholas A., Mueller, Thomas, Gómez, Rene D., Malhotra Kapoor, Poonam, Fraser, John F., Bartlett, Robert H., Alexander, Peta M.A., Barbaro, Ryan P., Abbasi, Adeel, Said Abdalmohsen, Ahmad, Abdelbary, Akram M., Abecasis, Francisco, Abel, Peter, Abu-Omar, Yasir, Adams, Douglas R, Manuel Africano, Juan, Aganga, Devon, Agati, Salvatore, Agerstrand, Cara, Aguillon, Mario V., Akers, Crystal S., Akhtarekhavari, Julia, Alazzam, Mohammad Izzat Salah, Albert, Martin, Alberti, Angela, Al-Fares, Abdulrahman A., Alfoudri, Huda, Allaert, Silvie, Allbert, Keesha N., Allen, Christopher T., Lescano Alva, Miguel Ángel, Alwardt, Cory M., Amigoni, Angela, Anandamurthy, Balaram, Anastasiadis, Kyriakos, Anders, Nicholas R., Anderson, Scott A., Anderson, Patricia L., Andrijević, Ana, Annoni, Alice, Anselmi, Michael, Anstey, James R., Antonini, Marta V., Antonitsis, Polychronis, Stein Araujo, Tays, Arcalas, Rhodney, Areinamo, Igor, Martin Arias, Anibal, Armijo-Garcia, Veronica, Aronsky, Vladimir, Arora, Lovkesh, Arora, Madhur, Leigh Aspenleiter, Marit, Atik, Fernando A., AugustGeorg Auzinger, Erin Colleen, Azzam, Ismail, Bacchetta, Matthew, Bak, Erica I., Balcells, Joan, Sánchez Ballesteros, Jesús, Banjac, Igor S., Barbaria, Jacqueline M., Barrigoto, Cleide L., Bass, Stephanie D., Batranović, Uroš, Bauer, Matthew H., Fernando Bautista, Diego, Beck, Robert M., Giraldo Bejarano, Estefania, Belohlavek, Jan, Bembea, Melania M., Benes, Jan, Benharash, Peyman, Benish, Lynne A., Bennett, Suzanne, Bento, Luís F.N., Bermudez, Christian A., Bertini, Pietro, Best, Derek, Bharat, Ankit, Bhutta, Omar J., Bizzell, Samantha J., Blakeman, Stephanie A., Blanco-Schweizer, Pablo, Blanton, Jessica K., Blood, Peggy S., Bohlmann, Allison S., Kyle Bohman, John, Bombino, Michela, Kathleen Bonadonna, Desiree, Bond, Ashley, Borgmann, Kristina M., Bourgoin, Pierre, Boville, Brian M., Boza, Raquel, Brady, Heather L., Brady, Alison, Braunlich, Jessica M., Bridges, Brian C., Brinkley, Karen K., Brookshire, Robert S., Brozzi Nicole Brueggemann, Nicolas A., Buckley, Dwight P., Jr., Buckley, Klayton, Budhani, Irfan B., Bukamal, Nazar, Burgos, Lucrecia M, Burša, Filip, Busby, Landon K., Buscher, Hergen, Butler, Menoly, Butt, Warwick W., Byrnes, Jonathan W., Calaritis, Christos, Caldwell, Lisa R., Calligaro, Gregory L., Campbell, Patrick T., Camporota, Luigi, Fernando Caneo, Luiz, Jovo Carapic, Vladimir, Carrasco-Carrasco, Cristina, Ivan Carrizo, Nestor, Carrow, Heidi, Carton, Edmund G., Casabella, Christian, Gomez Casal, Vanesa, Casey, Francis L., III, Castillo, Andres, Castleberry, Anthony W., Alexandros Cavayas, Yiorgos, Cerqua, Karey, Ming Chan, Kai Man ChanWai, Brian Chapman, Jason, Brahma Chari, Hari, Cheifetz, Omair ChaudharyIra M., Chen, Robin H.S, Chen, Weiting, Cheung, Eva W., Cheung, Anson, Chico, Juan I., Chiletti, Roberto, Jin Cho, Hwa, Cholette, Jill M., Christensen, Steffen, Chui, Betty S., Circelli, Alessandro, Clement, Katherine C., Cleuziou, Julie, Clouse, Brian, Cole, Gwendolen, Coles, Garrett M., Collins, Monika F., Collins, Monika F., Connelly, James, Conrad, Steven A., Cook, Marlene, Copeland, Hannah, Copus, Scott C., Cox, Charles S., Jr, Craig, Lynne K., Crain, Natasha, Cremonese, Ricardo V., Criswell, Emily A., Cross, Lisa M., Crowley, Moira A., Crowley, Jerome C., Cruz, Leonora, Cypel, Marcelo, Czarnik, Tomasz, Czuczwa, Miroslaw E., Sica da Rocha, Taís, Daddow, Samuel, Dali, Dante C., Dalton, Heidi J., Daly, Kathleen J.R., Damuth, Emily, Daniel, Dennis A., Daniel IV, John M., Daniel, Josiane M., Danis, Max D., Danko, Melissa E., Rodrigues Dantas, Joao Alberto, Daoust, Isabelle, Dauwe, Dieter F., Davidson, Mark, Davis, Joel C., Davis, Mitchell, D’Cunha, Jonathan, de Arruda Bravim, Bruno, de BoodeKim T. De La Cruz, Willem P., Gray DeAngelis, Kathryn, Debeuckelaere, Gerdy, Deitemyer, Matthew A., DellaVolpe, Jeffrey, Deneau, Jamie L., DeNino, Walter F., Denmark, Christopher G., Denney, Derek, DeValeria, Patrick A., Dewulf, Petra, Di Nardo, Matteo, DiBardino, Daniel J., DiMartino, Joseph, Dimopoulos, Stavros, Domico, Michele B., Dominy, Meaghan E., Donker, Dirk W., Dresbach, Till, Droogh, Joep M., Dunlap, Tiffany W., Dupon, Allsion, Durham, Lucian A., III, Durward, Andrew, Dvorak, Anna, Dyett, John F., Dziedzina, Carol L., Eaken, Carmen L., Eaton, Jonathan S., Eberle, Christopher J., Edwards, Linda, Efseviou, Christakis, Eigner, Juliann M., Ahmed Elhamrawi, Hazem, Elhazmi, Alyaa M., Elizondo, Tammy, Ellersick, Beverly L., Emling, Jonathan A., Ernst, Andreas, Pablo Escalante, Juan, Espinoza, Otoniel, Evey, Lee W., Fan, Eddy, Fang, Gary, Faulkner, Gail M., Fauman, Karen R, Ferguson, Niall, Ferreira, Benigno, Fiane, Arnt E., Andrade Fierro, Dario, Martha Filippi, María, Findeisen, Michael C., Finlay, Katie, Finlayson, Gordon, Fischer, Gwenyth A., Fischer, Courtney D., Fischer, William J., III, Fisher, Caleb M., Fitriasari, Reni, Fitzgerald, Jillian, Fix, Melissa K., Fleming, Sarah B., Flynn, Brigid C., Forst, Beth A., Fortuna, Philip P., Foti, Giuseppe, Fox, Matthew P., Franco, Thais O., David Freeland, C., Fried, Justin A., Friedman, Matthew L., Furlanetto, Beatriz, Fux, Thomas, Gaião, Sérgio, Gale, Michael J., Garcia, Joann Kathleen G., Garcia-Montilla, Romel, Gardner, Eric R., Garg, Meena, Garrison, Lawrence L., Gavrilovic, Srdjan M., Gawda, Ryszard, Geer, Laura W., Gelandt, Elton A., Gelvin, Michael G., Genovese, Bradley M., George, Jeffrey A., George, Timothy J, George, Sangley, Ghimire, Anup, Giani, Marco, Gill, Baljit S., Glikes, Erin, Golecki, Michael, Gongora, Enrique, Govener, Sara, Graf, Amanda, Grasselli, Giacomo, Gray, Brian W., Greenlee, Joseph A., III, Gregoric, Igor D., Gregory, Melinda, Grins, Edgars, Volker Groesdonk, Heinrich, Group, Kimberly F., Guarracino, Fabio, Joy Guidi-Solloway, Alexandra, Gunn, Tyler M., Guru, Pramod K, Haddle, John C., Haft, Jonathan W., Haisz, Emma, Hall, Julie L., Hall, Cameron, Hamaguchi, Jun, Hammond, Terese C., Han, Peggy K., Hardison, Daphne C., Harischandra, Dickwelle T., Hart, Shaun M., Harting, Matthew T., Hartley, Louise, Harvey, Chris J., Hasan, Zubair, Fawzy Hassan, Ibrahim, Hastings, Jennifer R., Hatcher, Renee’, Hatton, Kevin W., Haught, Christopher K., Awori Hayanga, Jeremiah, Peter Haydon, Timothy, Healy, Aaron H., Heard, Micheal L., Heather, Beth M., Hendrix, Rik H.J., Hennig, Felix, Hermens, Greet HermansJeannine A.J., Hernandez, Deborah A., Hernandez-Montfort, Jaime, Herrera, Guillermo, Hickman, Keri, Hittel, Ashley, Hobbs, Crystal, Hoffman, Jordan R.H., Hollinger, Laura E., Homishak, Michael, Horigoshi, Nelson K., Hoshino, Kota, Huang, Shu-Chien, Huenges, Katharina, Hussey, Alexander D., Hyslop, Robert W., Ihle, Rayan E., Ingemansson, Ola, Ivulich, Daniel, Jackson, Amanda L., Garcia Jacques, Rogelio, Jain, Harsh, Jakobs, Sharon M., Jan, Robert, Janowiak, Lisa M., Jara, Claire B., Jarden, Angela M., Jarzembowski, Jamie L., Jaudon, Andrew, Kishore Jayanthi, Venkata Krishna, Jennings, Joseph A., Jeong, Inseok, Meza Jiménez, Rafael, Jimenez-Rodriguez, Gian M., Joachim, Sabrina, Joelsons, Daniel, Johnson, Caroline A., Johnson, Andrea L., Jones, Jeffry H., Joseph, Mark, Joseph, Sunimol, Joshi, Raja, Joyce, Christopher J., Seung Jung, Jae, Carone Junior, José, Kallas, Harry J., KamerkarPilje Kang, Asavari, Kar, Biswajit, Karapanagiotidis, Georgios T., Kattan, Javier, Kaufman, David A., Kawauchi, Akira, Keene, Sarah D., Keller, Norma M., Keller, Roberta, Kelley, Emily W., Kelley, Kellie, Kelly-Geyer, Janet F., Kenderessy, Peter, Kenny, Laura E., Keshavjee, Shaf, Kessel, D., Kessler, Heather, Keuler, Suzanne, Khicha, Sanjay, Wan Kim, Do, Kim, Richard Y., Maxwell Kime, Aaron, Kincade, Robert C., Kipfmueller, Florian, Kirk, Douglas A., Klein, Liviu, Knapp, Randall S., Knapp, Randall S., Kneyber, Martin C.J., Knowles, Andrea L., Koch, Jillian M., Koepke, Stephanie, Kogelmann, Klaus M., Elzo Kraemer, Carlos, Krauklis, Amanda, Krumroy, Samantha L., Kumar, Madhan, Kumar, Arun, Kumpf, Matthias E, Kyle, Kimberly, Laffin, Anna, Kees Lagrand, Wim, Lahiji, Parshawn A., Keung Lai, Peter Chi, Ka Lai, Cally Ho, Danielle Laird, Amanda, Landsberg, Michelle LaMarreDavid M., Lanmueller, Pia, Oude Lansink-Hartgring, Annemieke, Beth Larson, Sharon, Laufenberg, De’Ann M., Lavana, Jayshree, Layne, Tracie L., John Lazar, Michael, Ledoux, Matthew R., Lee, Raymond C., Leek, Thomas M., Lequier, Laurance, Lesbekov, Timur, Leslie, Robert, Anne Leung, Kit Hung, Lillie, Jon, Phang Lim, Yeong, Lim, Sang-Hyun, Lin, Ling, Lindsey, Thomas, Ho Ling, Steven Kin, Lingle, Kaitlyn J., Lipes, Jed, Liu, Songqiao, Llevadias, Judit, Lomas, Erin A., Longenecker, Robert D., Lorusso, Roberto, Ann Low, Tracy, Steven Lubinsky, Anthony, Lucas, Matthias LubnowMark T., Lucchini, Alberto, Luze, Lisa E., Lynch, William R., Manoj, M.C., Maas, Jacinta J., MacNamara, Vanessa, Madden, Jesse L., Maimone, Justin, Malhotra, Rajiv, Malone, Matthew P., Mangukia, Chirantan, Manzur-Sandoval, Daniel, Maráczi, Veronika, Marinaro, Jonathan L., Marinucci, Christina R., Marshall, Tammy, Martin, Mark, Marwali, Eva M., Maslach-Hubbard, Anna, Matijašević, Jovan, Mattke, Adrian, Mattucci, Joseph, Maul, Timothy M., Maybauer, Marc O., Mayette, Michael, Mayville, Joni R., McAllister, Catherine, McBride, Martha W., Scott McCaul, David, McClelland, Samantha L.S., Gregory McCloskey, Colin, McGregor, Randy, McKamie, Wesley A., McKee, Andrew D., McMahon, Chelsea M., McMullin, Kaye, McNicol, Jane, McNulty, John P., McRae, Thomas, Meade, Maureen E., Meersseman, Philippe, Mekeirele, Michael, Ito Mendes, Elisa, Menon, Anuradha P., Meyer, Jason P., Meyers, Jourdan E., Meyns, Bart, Mignone, John L., Miller, Brittany D., Miller, Malcolm G.A., Miller, Deborah, Mintak, Renee, Minter, Sarah M., Reis Miranda, Dinis, Mirza, Farrukh, Mishkin, Joseph D., Modelewski, Paul, Mohan, Rajeev C., Hui Mok, Yee, Money, Dustin, Monteagudo, Julie, Moores, Russell R., Jr., Moran, Patrick, Morelock, Shawn, Moreno, Marsha R., Blanco Morillo, Juan, Morrison, Tracy, Morton, John M., Morton, Brenda, Moscatelli, Andrea, Mosier, Jarrod M., Muellenbach, Ralf M., Mueller, Andreas, Mueller, Dale, Musca, Steven C., Nagpal, Dave, Najaf, Tasnim, Narasimhan, Mangala, Nater, Melissa, Natividad, Zynthia, Nedeljkov, Djordje, Nelson, Bryan D., Newman, Sally F., Newton, Debra E., Neyman, Jonathan L., George Ng, Wing Yiu, Nicholson, Meghan C., Nicolaas, Christine, Nix, Charlie, Nkwantabisa, Raymond, Nolan, Shirley, Norese, Mariano, Norton, Bridget M., Norton, Bridget M., O’Brien, Serena G., O’Callaghan, Maura, Oishi, Peter, O’Leary, Tony D., Olia, Salim E., O’Meara, Carlisle, Oppel, Emily E., Arias Ortiz, Julian, Oza, Pranay L., Ozment, Caroline P., Pacific, Marjorie, Pálizas, Fernando, Palmer, David, Paoletti, Luca, Pardo, Diego H., Paredes, Pablo, Patel, Thomas PasgaardMrunal G., Patel, Sandeep M., Patel, Vijay S., Patel, Brijesh V., PatelDrisya Paul, Sameer, Pawale, Amit A., Pearson, Nicole M., Renee Pearson, Crystal, Peek, Giles J., Pellecchia, Crescens M., Pellegrino, Vincent, Peperstraete, Harlinde, Perkins, Rebecca L., Perkins, Brandon, Peterec, Steven, Peterman, Claire, Phillips, Cooper W., Piekutowski, Richard R., Pilan, María L., Luisa Pilan, Maria, Mark Pincus, Jason, Pino, Melissa, Plambeck, Robert W., Plisco, Michael S., Plumley, Donald A., Plunkett, Mark D., Poffo, Robinson, Poh, Pei-Fen, Polito, Angelo, Pollema, Travis L, Pozzi, Matteo, Pozzi, Matteo, Pranikoff, Thomas, Prekker, Matthew E., Prossen, Erik F., Puligandla, Pramod S., Puslecki, Mateusz, Raheel Qureshi, Muhammad, Emilia Rabanal, Lily, Abdulhamid Rabie, Ahmed, Rackley, Craig R., Radovancevic, Rajko, Raes, Matthias, Allen Raff, Lauren Desiree, Rahban, Youssef, Raimer, Patricia L., Rajbanshi, Bijoy G., Ramanan, Raj, Rambaud, Jerome, Ramírez-Arce, Jorge A., Simões Ramos, Ana Carolina, Rao, Suresh G., Rector, Raymond, Redfors, Bengt, Regmi, Ashim, Alejandro Rey, Jose, Miguel Ribeiro, Joao, Richards, Chelsea E, Joan Richardson, C., Riddle, Christy C., Riera, Jordi, Ripardo, Marina, Rivas, Fernando M., Roan, Ronald M., Robertson, Elizabeth, Robinson, Megan, Röder, Daniel, Rodrigus, Inez E.R., Paul Roeleveld, Peter, Romano, Jennifer C., Rona, Roberto, Ann Rosenberg, Carol, Rosenow, Felix, Rowe, Robert J., Rower, Katy E., Rudolph, Kristina L., Fernando Rueda, Luis, Ruf, Bettina, Russell, Hyde M., Russell, Nichole, Ryan, Kathleen, Saberi, Asif A., Said, Ahmed S., Sailor, Caitlin, Sakal, Angela, Lujan Salas, Gisela, Salazar, Leonardo, Saleem, Kashif, Samoukovic, Gordan, Sanchez, Pablo G., Marie Santiago, Lian, Sargin, Murat, Miguel Sassine, Assad, Satou, Nancy L., Saunders, Paul C., Schachinger, Scott, Schaible, Thomas, Schellongowski, Peter, Schlager, Gerald W., Schmid, Christof, Schmitt, Joachim, Schnell, LeeAndra, Schnur, Janos, Schroeder, Lukas, Schubach, Scott, Schuetz, Michael T., Schwartz, Gary S., Schwarz, Patricia, Scriven, Nicole M., Seabrook, Ruth B., Seefeldt, Cassandra, Seelhammer, Troy G., Segura-Matute, Susana, Sen, Ayan, Adrian Seoane, Leonardo, Shaffer, Jamie, Shafi, Bilal M., Shambley, Shannon, Shankar, Shyam, Shapland, Amanda, Sharng, Yih, Shavelle, David, Sheldrake, Jayne, Mohan Shetty, Rajesh, Shiber, Joseph R., Shimzu, Naoki, Lou Short, Billie, Sichting, Kay A., Sidehamer, Keith E., Siebenaler, Teka, Silvestry, Scott C., Sinclair, Jennifer T, Sinclair, Andrew, Singh, Aalok R., Singh, Gurmeet, Skinner, Sean C., Smart, Alexandra, Smith, Reanna M., Smith, Adam, Smith, Karen, Sommer-Candelario, Sherri, Song, Seunghwan, Sorensen, Gro, Sousa, Eduardo, Sower, Christopher T., Spadea, Nicholas V, Spangle, April, Speicher, David G., Spieth, Peter M., Srivastava, Ankur, Srivastava, Neeraj, Stahl, Mark, Stallkamp, Eric D., Jr, Stanley, Vanessa J., Starr, Joanne P., Staudinger, Thomas, Stevens, Berkeley E., Stevens, Kimberly, Stocker, Christian, Strickland, Richard, Suarez, Erik E., Kumar Subramanian, Rakesh, Sudakevych, Serhii, Summerall, Charlene, Sundararajan, Santosh, Susupaus, Attapoom, Suzuki, Hiroyuki, Sweberg, Todd, Sydzyik, Troy, Anh Ta, Tuan, Tagliari, Luciana, Tanaka, Hiroyuki, Tanski, Christopher T., Tasset, Mark, Taylor, Donna M., Teman, Nicholas R., Ramesh Thangaraj, Paul, Thiagarajan, Ravi R., Thiruchelvam, Timothy, Thomas, James A., Thomas, Owain D., Thompson, Shaun L., Thomson, David A., Thukaram, Roopa, Todd, Mark L., Toeg, Hadi, Torres, Silvio F., Trautner, Simon, Trombino, Terry, Tuazon, Divina M., Tuel, Julie, Tukacs, Monika, Turner, April N., Tyree, Melissa M., Uchiyama, Prashant Vaijyanath, Makoto, van den Brule, Judith M.D., van Dyck, Marlice A., van Gijlswijk, Mascha, Van Meurs, Krisa P., VanDyck, Tyler J., Vardi, Amir, Vega, Alejandra, Ventetuolo, Corey E., Vera, Magdalena, Vercaemst, Leen, Vets, Philippe, Viamonte, Heather, Vidlund, Mårten, Vitali, Sally H., Vlaa, Alexander P.J., Vuylsteke, Alain, Loon Wan, Kah, Watkins, Reuben, Watson, Pia, Weast, Travis A., Weaver, Karen E., Welkovics, Norbert, Wellner, Heidi L., Wells, Jason C., Welter, Karen, Westpheling, Amber G., Whalen, Lesta D.S., Whebell, Stephen, Wiersema, Ubbo, Wiisanen, Matthew E., Eugene Wilcox, Bradley, Wille, Keith, Jan Will, Ellyne, Wilson, Brock J., Win, April M., Winearls, James R., Wise, Linda J., Witter, Tobias, Ruby Wong, Hoi Mei, Worku, Berhane, Wright, Tina M, Wu, James K., Yalon, Larissa A., Yantosh, Garrett, Yaranov, Dmitry M., Yee, Pat, Yi, Cassia, Yost, Christian C., Young, John, Younger, Katrina, Zaborowski, Steven, Zachmann, Brenda, Zainab, Asma, Zanai, Rosanna, Zhao, Ju, Zhou, Chengbin, and Zinger, Marcia

Published
2024
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11. 451 Identification of candidate sudden arrhythmic death -causing variants in a spontaneous animal model

Author

Sian Durward-Akhurst, Joy Stock, Freya Stein, Christopher Stauthammer, and Samuel Dudley

Subjects
Medicine
Abstract

OBJECTIVES/GOALS: 1. Identify candidate AN-SAD-causing variants. 2. Estimate the variant effect size of and genotypic relative risk for arrhythmias and AN-SAD. METHODS/STUDY POPULATION: We performed whole genome sequencing (WGS) on 59 Thoroughbred AN-SAD cases and 58 controls. WGS was mapped and variants identified using a modified version of the Genome Analysis Toolkit best practices. Variants will be selected based on case-control analysis using SnpSift and presence in candidate genes. The top 400 candidate AN-SAD-causing variants will be selected based on being common in cases and rare or absent in controls, and uncommon (allele frequency less than 10%) in a catalog of genetic variation for the horse. The 400 variants will be genotyped in our cohort of 1,200 racehorses to determine variant effect size and genotypic relative risk. RESULTS/ANTICIPATED RESULTS: 17,182,003 variants were identified. 230 variants had significantly different allele frequencies (AF) between cases and controls (SnpSift). 723 high and 4,824 moderate impact variants were identified in 1,072 candidate genes. 3,681 variants were present at an AF 10% in the equine variant catalog. Variant effect prediction is ongoing to select the final 400 variants. Cardiac phenotyping (cardiac auscultation and ECG before, during, and after exercise) was performed on 790 racehorses and we will have 1,200 racehorses with cardiac phenotypes and/or AN-SAD. We will genotype the top 400 candidate AN-SAD-causing variants in these 1,200 horses to identify variants of large effect size. DISCUSSION/SIGNIFICANCE: Identification of candidate AN-SAD variants in a spontaneous animal model can facilitate interpretation of candidate variants in humans and horses. This project will provide further support for the racehorse AN-SAD model and will support future work exploring the genetic and environmental risk factors contributing to AN-SAD in this animal model.

Published
2024
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13. Labouring Over The Loophole: The Labour Government's Proposed Reform Of Carried Interest Taxation

Author

Durward-Thomas, Matthew

Subjects
Capital gains tax -- Laws, regulations and rules, Tax reform -- Laws, regulations and rules, Tax rates -- Statistics -- Laws, regulations and rules, Tax law -- Interpretation and construction, Government regulation, Tax law, Business, international
Abstract

Reform In Motion The Chancellor's announcement on Wednesday that the UK's capital gains tax (CGT) rate for carried interest would be increased by only a few percentage points from 28% [...]

Published
2024

14. Individual-based modeling of COVID-19 transmission in college communities

Author

Durward Cator, Qimin Huang, Anirban Mondal, Martial Ndeffo-Mbah, and David Gurarie

Subjects
covid-19, individual-based model, non-pharmaceutical interventions, vaccine, college, Biotechnology, TP248.13-248.65, Mathematics, QA1-939
Abstract

The ongoing COVID-19 pandemic has created major public health and socio-economic challenges across the United States. Among them are challenges to the educational system where college administrators are struggling with the questions of how to mitigate the risk and spread of diseases on their college campus. To help address this challenge, we developed a flexible computational framework to model the spread and control of COVID-19 on a residential college campus. The modeling framework accounts for heterogeneity in social interactions, activities, environmental and behavioral risk factors, disease progression, and control interventions. The contribution of mitigation strategies to disease transmission was explored without and with interventions such as vaccination, quarantine of symptomatic cases, and testing. We show that even with high vaccination coverage (90%) college campuses may still experience sizable outbreaks. The size of the outbreaks varies with the underlying environmental and socio-behavioral risk factors. Complementing vaccination with quarantine and mass testing was shown to be paramount for preventing or mitigating outbreaks. Though our quantitative results are likely provisional on our model assumptions, sensitivity analysis confirms the robustness of their qualitative nature.

Published
2022
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18. A Functional Single-Nucleotide Polymorphism Upstream of the Collagen Type III Gene Is Associated with Catastrophic Fracture Risk in Thoroughbred Horses

Author

Esther Palomino Lago, Arabella Baird, Sarah C. Blott, Rhona E. McPhail, Amy C. Ross, Sian A. Durward-Akhurst, and Deborah J. Guest

Subjects
fracture risk, horse, genetic variation, bone, osteoblast, in vitro model, Veterinary medicine, SF600-1100, Zoology, QL1-991
Abstract

Fractures caused by bone overloading are a leading cause of euthanasia in Thoroughbred racehorses. The risk of fatal fracture has been shown to be influenced by both environmental and genetic factors but, to date, no specific genetic mechanisms underpinning fractures have been identified. In this study, we utilised a genome-wide polygenic risk score to establish an in vitro cell system to study bone gene regulation in horses at high and low genetic risk of fracture. Candidate gene expression analysis revealed differential expression of COL3A1 and STAT1 genes in osteoblasts derived from high- and low-risk horses. Whole-genome sequencing of two fracture cases and two control horses revealed a single-nucleotide polymorphism (SNP) upstream of COL3A1 that was confirmed in a larger cohort to be significantly associated with fractures. Bioinformatics tools predicted that this SNP may impact the binding of the transcription factor SOX11. Gene modulation demonstrated SOX11 is upstream of COL3A1, and the region binds to nuclear proteins. Furthermore, luciferase assays demonstrated that the region containing the SNP has promoter activity. However, the specific effect of the SNP depends on the broader genetic background of the cells and suggests other factors may also be involved in regulating COL3A1 expression. In conclusion, we have identified a novel SNP that is significantly associated with fracture risk and provide new insights into the regulation of the COL3A1 gene.

Published
2023
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21. A missense mutation in MYH1 is associated with susceptibility to immune-mediated myositis in Quarter Horses

Author

Finno, Carrie J, Gianino, Giuliana, Perumbakkam, Sudeep, Williams, Zoë J, Bordbari, Matthew H, Gardner, Keri L, Burns, Erin, Peng, Sichong, Durward-Akhurst, Sian A, and Valberg, Stephanie J

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Human Genome, Autoimmune Disease, 2.1 Biological and endogenous factors, Amino Acid Sequence, Animals, Autoimmune Diseases, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Haplotypes, Horse Diseases, Horses, Male, Muscle Fibers, Skeletal, Mutation, Missense, Myosin Heavy Chains, Myositis, Pedigree, Sequence Alignment, Equine, Genome-wide association, Immunology, Myopathy, Myosin heavy chain 1, Medical physiology
Abstract

BackgroundThe cause of immune-mediated myositis (IMM), characterized by recurrent, rapid-onset muscle atrophy in Quarter Horses (QH), is unknown. The histopathologic hallmark of IMM is lymphocytic infiltration of myofibers. The purpose of this study was to identify putative functional variants associated with equine IMM.MethodsA genome-wide association (GWA) study was performed on 36 IMM QHs and 54 breed matched unaffected QHs from the same environment using the Equine SNP50 and SNP70 genotyping arrays.ResultsA mixed model analysis identified nine SNPs within a ~ 2.87 Mb region on chr11 that were significantly (Punadjusted

Published
2018

23. The Rules of the Game: Great Power Competition and international Law

Author

Johnson, Durward Elton

Subjects
International law -- Military aspects, Great powers -- Evaluation, Military and naval science
Abstract

The varieties of skullduggery which make up the repertoire of the totalitarian government are just about as unlimited as human ingenuity itself, and just about as unpleasant. For, as you [...]

Published
2022

25. A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread

Author

Yukun Tan, Durward Cator III, Martial Ndeffo-Mbah, and Ulisses Braga-Neto

Subjects
epidemic model, seird model, nonlinear stochastic model, unscented kalman filter, maximum likelihood, adaptive filtering, parameter estimation, Biotechnology, TP248.13-248.65, Mathematics, QA1-939
Abstract

Mathematical models are widely recognized as an important tool for analyzing and understanding the dynamics of infectious disease outbreaks, predict their future trends, and evaluate public health intervention measures for disease control and elimination. We propose a novel stochastic metapopulation state-space model for COVID-19 transmission, which is based on a discrete-time spatio-temporal susceptible, exposed, infected, recovered, and deceased (SEIRD) model. The proposed framework allows the hidden SEIRD states and unknown transmission parameters to be estimated from noisy, incomplete time series of reported epidemiological data, by application of unscented Kalman filtering (UKF), maximum-likelihood adaptive filtering, and metaheuristic optimization. Experiments using both synthetic data and real data from the Fall 2020 COVID-19 wave in the state of Texas demonstrate the effectiveness of the proposed model.

Published
2021
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26. Underweight and early childhood caries among young children in rural Cambodia: a pilot study

Author

Yu Kubota, Nhep San Pech, Callum Durward, and Hiroshi Ogawa

Subjects
Dentistry, RK1-715
Abstract

Abstract Objectives To investigate the association between underweight and early childhood caries (ECC) among children aged one to three years in rural Cambodia. Materials and methods A total of 200 Cambodian children aged one to three years at several villages in Kampong Cham province participated in this study. The children whose Z scores were below two and three standard deviations were considered as moderately-underweight and severely-underweight. Children whose mid-upper arm circumstance (MUAC) was below 12.5 cm, were regarded as having malnutrition. ECC was recorded following the WHO guidelines. Associated factors were obtained through interviews with caregivers. Results 33.5% and 7.0% of the children were identified as being moderately-underweight and severely-underweight, respectively. The prevalence of ECC was 61.5%. ECC was significantly associated with children being moderately-underweight (P

Published
2021
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29. Caries arrest and lesion appearance using two different silver fluoride therapies on primary teeth with and without potassium iodide: 12‐month results

Author

Bathsheba Turton, Rithvitou Horn, and Callum Durward

Subjects
arrest of caries, lesion appearance, potassium iodide, silver diamine fluoride, Dentistry, RK1-715
Abstract

Abstract Background Globally, has been an increase in the use of silver fluoride products to arrest carious lesions and a variety of products are available. Objectives To examine differences in caries arrest and lesion colour of primary tooth carious lesions. Material and Methods A four‐armed, parallel‐design cluster‐randomised controlled trial which investigated four protocols for caries arrest at 6m and 12m. Children in Group 1 and Group 2 received Rivastar Silver Diammine Fluoride (SDF), and children in Group 3 and Group 4 received a stabilised aqueous silver fluoride solution (AgF). Children in Group 2 and Group 4 received an additional application of KI immediately after the fluoride. Differences in caries arrest and lesion appearance were examined at 6m and 12m using two level logistic regression modelling. Results The arrest rate varied by group membership; group 1 and group 3 had higher arrest rates (77.3% and 75.3% respectively) than group 2 and group 4 (65.4% and 51.2% respectively). The use of KI was also associated with lower odds of arrest (12m OR 0.25; CI 0.19, 0.34) and higher odds of avoiding black discolouration (12m OR 6.08; 2.36, 15.67). Conclusions Globally, has been an increase in the use of silver fluoride products to arrest carious lesions and a variety of products are available. This study demonstrated that both AgF and SDF can effectively arrest carious lesions on primary teeth. The use of KI is associated with poorer caries control but better aesthetic outcomes.

Published
2021
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30. Pilot Test of an Online ASA24 Training with EFNEP Educators

Author

Spruance, Lori Andersen, Atoloye, Abiodun, Douglass, Deirdre, Zimmerman, Thea Palmer, Guenther, Patricia M., Franck, Karen, Henson, Teresa, Moore, Carla J., Wood, Gina, and Durward, Carrie M.

Abstract

The purpose of this study was to evaluate the acceptability and usability of an online training to prepare Expanded Food and Nutrition Education Program (EFNEP) educators to collect 24-hr dietary recalls using the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24). Fifty-eight educators in 17 states were recruited to take the training; 29 completed the online training, assisted two individuals in completing a 24-hr recall using ASA24, and completed a survey about their experiences. The sample included 26 respondents. The majority (n = 16; 61.5%) of the sample was EFNEP educators with college education. The majority of the respondents indicated that they found the readings and videos acceptable for learning (n = 21; 80.7%). Half of the participants (n = 13) felt prepared to collect data using ASA24. The majority (n = 22; 84.6%) had positive feedback about the training content. The training may be acceptable for preparing EFNEP educators with at least some college education to collect 24-hr recalls using ASA24. Because of potential bias due to self-selection and nonresponse, the training has been revised and is now intended to be used to train trainers of EFNEP paraprofessionals.

Published
2019
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31. Tracheomalacia

Author

Drake, D. P., Durward, A., Ameh, Emmanuel A., editor, Bickler, Stephen W., editor, Lakhoo, Kokila, editor, Nwomeh, Benedict C., editor, and Poenaru, Dan, editor

Published
2020
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32. Given-Find-In Order To-Subjected To (GFIS) method for the problem statement in set-based design.

Author

Fernández-Caballero, Juan Carlos, Hernández-Luna, Alberto A., Sobek II, Durward K., and Ramírez-Mendoza, Ricardo A.

Subjects
CONCURRENT engineering, LABEL design, FUZZY sets, UNDERGRADUATES, DECISION making
Abstract

The Given-Find-Solution (GFS) method is a widely used procedure to systematically understand "what the problem is" in engineering problems. Nevertheless, the GFS method does not provide a clear guide on how to handle uncertainty, feasibility, and preference for design problems. Addressing this issue is crucial since the designer usually requires making assumptions to be able to propose functional solutions. The Given-Find-In Order To-Subjected To (GFIS) method and roadmap are here proposed to systematically state a design problem and requirements using fuzzy desirability functions to handle uncertainty, feasibility, and preference. The GFIS method lists the parameters, variables, specifications, restrictions, and preferences to facilitate the decision-making process. A comparative study was conducted with undergraduate students from Tecnológico de Monterrey enrolled in the course Design Methodologies. The students solved a band brake design problem before and after applying the GFIS method, and their performance was compared. The results showed a significant improvement in their decision-making ability, their capability to find feasible solutions, and the time required to make a design proposal. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Clinical Considerations in the Approach to Vancomycin-Resistant Enterococci: A Narrative Review

Author

John W. Beale and Marina Durward-Diioia

Subjects
Vancomycin-resistant enterococci, Enterococcus faecalis, Enterococcus faecium, Vancomycin resistance, Healthcare-associated infection, Nosocomial infection, Medicine (General), R5-920, Public aspects of medicine, RA1-1270
Abstract

Vancomycin-Resistant Enterococci (VRE) increasingly colonize and infect assorted patient populations throughout the world, maintaining a continual reservoir of opportunistic pathogens with varying antibiotic resistance. Here we present the current general epidemiology and classification of these pathogens within the scope of healthcare-associated infections (HAIs). Risk factors for colonization and conditions for subsequent infection are reviewed, along with infection characteristics. Current infection control protocols and their effectiveness, selected evidence-based medical therapies, and ongoing research into alternative therapies are summarized.

Published
2022
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41. Major Histocompatibility Complex I and II Expression and Lymphocytic Subtypes in Muscle of Horses with Immune‐Mediated Myositis

Author

Durward‐Akhurst, SA, Finno, CJ, Barnes, N, Shivers, J, Guo, LT, Shelton, GD, and Valberg, SJ

Subjects
Veterinary Sciences, Agricultural, Veterinary and Food Sciences, Muscular Dystrophy, Rare Diseases, 2.1 Biological and endogenous factors, Animals, Gene Expression Regulation, Horse Diseases, Horses, Lymphocyte Subsets, Major Histocompatibility Complex, Muscle, Skeletal, Myositis, Atrophy, Immunology, Inflammatory, Myopathy, Veterinary sciences
Abstract

BackgroundMajor histocompatibility complex (MHC) I and II expression is not normally detected on sarcolemma, but is detected with lymphocytic infiltrates in immune-mediated myositis (IMM) of humans and dogs and in dysferlin-deficient muscular dystrophy.Hypothesis/objectivesTo determine if sarcolemmal MHC is expressed in active IMM in horses, if MHC expression is associated with lymphocytic subtype, and if dysferlin is expressed in IMM.AnimalsTwenty-one IMM horses of Quarter Horse-related breeds, 3 healthy and 6 disease controls (3 pasture myopathy, 3 amylase-resistant polysaccharide storage myopathy [PSSM]).MethodsImmunohistochemical staining for MHC I, II, and CD4+, CD8+, CD20+ lymphocytes was performed on archived muscle of IMM and control horses. Scores were given for MHC I, II, and lymphocytic subtypes. Immunofluorescent staining for dysferlin, dystrophin, and a-sarcoglycan was performed.ResultsSarcolemmal MHC I and II expression was detected in 17/21 and 15/21 of IMM horses, respectively, and in specific fibers of PSSM horses, but not healthy or pasture myopathy controls. The CD4+, CD8+, and CD20+ cells were present in 20/21 IMM muscles with CD4+ predominance in 10/21 and CD8+ predominance in 6/21 of IMM horses. Dysferlin, dystrophin, and a-sarcoglycan staining were similar in IMM and control muscles.Conclusions and clinical importanceDeficiencies of dysferlin, dystrophin, and a-sarcoglycan are not associated with IMM. Sarcolemmal MHC I and II expression in a proportion of myofibers of IMM horses in conjunction with lymphocytic infiltration supports an immune-mediated etiology for IMM. The MHC expression also occured in specific myofibers in PSSM horses in the absence of lymphocytic infiltrates.

Published
2016

43. How metabolic acidosis and kidney disease may accelerate the aging process

Author

Frassetto, Lynda Ann, Sebastian, Anthony, and DuBose Jr, Thomas Durward

Subjects
Diseases, Acidosis, Phosphates, Carbonates, Telomeres, Enzymes, Telomerase, Kidney diseases
Abstract

Author(s): Lynda Ann Frassetto [sup.1], Anthony Sebastian [sup.1], Thomas Durward DuBose Jr [sup.2] Author Affiliations: (1) University of California San Francisco, San Francisco, USA (2) Wake Forest School of Medicine, [...], Consuming a lower acid (and particularly lower phosphate) diet and/or supplementing the diet with base precursors, such as bicarbonate, might have a number of mitigating effects on the aging process. These include: (1) slowing progression of fibrosis by reduction of high endogenous acid production to preserve net acid excretion and minimize the degree of systemic acidosis; (2) avoiding the downregulation of klotho, a membrane and soluble factor associated with aging. Klotho declines when constant high dietary phosphate intake leads to an increase in FGF23 production; and (3) increasing activity of the enzyme telomerase, an important factor in maintaining telomere length, another factor associated with longer lifespan. Current evidence is based on studies in invertebrate and small animal models. These results, and extrapolations of associated human studies, suggest that low acid-producing diets, or neutralization of the low grade metabolic acidosis seen in humans with age-related renal dysfunction could potentially lead to a longer, healthier lifespan.

Published
2020
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46. Peer Tutoring for Anatomy Workshops in Cambodia

Author

Pickles, Kylie, Ivanusic, Jason J., Xiao, Junhua, Durward, Callum, Ryan, Andrea B., and Hayes, Jennifer A.

Abstract

Historical loss of staff and teaching resources in Cambodia has resulted in significant challenges to anatomy education. Small group anatomy teaching opportunities are limited. A visit to Cambodia by a teaching team from the University of Melbourne in 2010 demonstrated it was possible to implement well-resourced anatomy workshops for this purpose. However, continuation of the workshop program was inhibited by the limited number of local teaching staff. In 2015, another team from the University of Melbourne returned to Cambodia to implement anatomy workshops that incorporated peer tutoring. The objective was to improve teacher-to-student ratios and to demonstrate that interactive anatomy workshops could be delivered successfully despite low staff numbers. The anatomy workshops were attended by 404 students of Medicine, Dentistry, Nursing, and Midwifery at the University of Puthisastra. Medical students were invited to act as peer tutors for nursing students. A five-point Likert scale questionnaire was used to determine student satisfaction with both the workshops and peer tutoring. The overwhelming majority were positive about the workshops and keen for them to continue. Almost all medical students who acted as peer tutors agreed or strongly agreed that this role increased their anatomical knowledge (98%) and confidence (94%). Most nursing students agreed or strongly agreed with statements that they would like peer tutoring to continue (94%) and that they would like to be peer tutors themselves (88%). This report demonstrates that peer tutoring could be an effective tool in educational settings where poor staff-to-student ratios limit delivery of interactive workshops.

Published
2019
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47. Genetic Variation and the Distribution of Variant Types in the Horse

Author

S. A. Durward-Akhurst, R. J. Schaefer, B. Grantham, W. K. Carey, J. R. Mickelson, and M. E. McCue

Subjects
genetic variation, whole genome sequence, variant discovery, equine, breed differences, genetics, Genetics, QH426-470
Abstract

Genetic variation is a key contributor to health and disease. Understanding the link between an individual’s genotype and the corresponding phenotype is a major goal of medical genetics. Whole genome sequencing (WGS) within and across populations enables highly efficient variant discovery and elucidation of the molecular nature of virtually all genetic variation. Here, we report the largest catalog of genetic variation for the horse, a species of importance as a model for human athletic and performance related traits, using WGS of 534 horses. We show the extent of agreement between two commonly used variant callers. In data from ten target breeds that represent major breed clusters in the domestic horse, we demonstrate the distribution of variants, their allele frequencies across breeds, and identify variants that are unique to a single breed. We investigate variants with no homozygotes that may be potential embryonic lethal variants, as well as variants present in all individuals that likely represent regions of the genome with errors, poor annotation or where the reference genome carries a variant. Finally, we show regions of the genome that have higher or lower levels of genetic variation compared to the genome average. This catalog can be used for variant prioritization for important equine diseases and traits, and to provide key information about regions of the genome where the assembly and/or annotation need to be improved.

Published
2021
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