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4,594 results on '"A. A. Creasey"'

1. Geometric Framework for 3D Cell Segmentation Correction

Author

Chen, Peter, Chang, Bryan, Creasey, Olivia Annette, Sneddon, Julie Beth, and Liu, Yining

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

3D cellular image segmentation methods are commonly divided into non-2D-based and 2D-based approaches, the latter reconstructing 3D shapes from the segmentation results of 2D layers. However, errors in 2D results often propagate, leading to oversegmentations in the final 3D results. To tackle this issue, we introduce an interpretable geometric framework that addresses the oversegmentations by correcting the 2D segmentation results based on geometric information from adjacent layers. Leveraging both geometric (layer-to-layer, 2D) and topological (3D shape) features, we use binary classification to determine whether neighboring cells should be stitched. We develop a pre-trained classifier on public plant cell datasets and validate its performance on animal cell datasets, confirming its effectiveness in correcting oversegmentations under the transfer learning setting. Furthermore, we demonstrate that our framework can be extended to correcting oversegmentation on non-2D-based methods. A clear pipeline is provided for end-users to build the pre-trained model to any labeled dataset., Comment: 17 pages, 16 figures

Published
2025

2. Case studies to develop a highway-rail grade crossing analysis framework using microsimulation.

Author

Creasey, F. T.

Subjects
Highway-railroad grade crossings -- Illinois., Traffic congestion -- Simulation methods. -- Illinois, Traffic flow -- Simulation methods. -- Illinois, Highway-railroad grade crossings -- Texas., Traffic congestion -- Simulation methods. -- Texas, Traffic flow -- Simulation methods. -- Texas, Statistical matching., Highway-railroad grade crossings., Traffic congestion -- Simulation methods., Traffic flow -- Simulation methods.
Published
2023

3. DNA Methylation Variation after a Parenting Program for Child Conduct Problems: Findings from a Randomized Controlled Trial

Author

Nicole Creasey, Patty Leijten, Marieke S. Tollenaar, Marco P. Boks, and Geertjan Overbeek

Abstract

This study investigated associations of the Incredible Years (IY) parenting program with children's DNA methylation. Participants were 289 Dutch children aged 3-9 years (75% European ancestry, 48% female) with above-average conduct problems. Saliva was collected 2.5 years after families were randomized to IY or care as usual (CAU). Using an intention-to-treat approach, confirmatory multiple-regression analyses revealed no significant differences between the IY and CAU groups in children's methylation levels at the NR3C1 and FKBP5 genes. However, exploratory epigenome-wide analyses revealed nine differentially methylated regions between groups, coinciding with "SLAMF1, MITF, FAM200B, PSD3, SNX31," and "CELSR1." The study provides preliminary evidence for associations of IY with children's salivary methylation levels and highlights the need for further research into biological outcomes of parenting programs.

Published
2024
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4. HoneyDOC: An Efficient Honeypot Architecture Enabling All-Round Design

Author

Fan, Wenjun, Du, Zhihui, Smith-Creasey, Max, and Fernández, David

Subjects
Computer Science - Cryptography and Security, Computer Science - Networking and Internet Architecture, C.2.0, C.2.1
Abstract

Honeypots are designed to trap the attacker with the purpose of investigating its malicious behavior. Owing to the increasing variety and sophistication of cyber attacks, how to capture high-quality attack data has become a challenge in the context of honeypot area. All-round honeypots, which mean significant improvement in sensibility, countermeasure and stealth, are necessary to tackle the problem. In this paper, we propose a novel honeypot architecture termed HoneyDOC to support all-round honeypot design and implementation. Our HoneyDOC architecture clearly identifies three essential independent and collaborative modules, Decoy, Captor and Orchestrator. Based on the efficient architecture, a Software-Defined Networking (SDN) enabled honeypot system is designed, which supplies high programmability for technically sustaining the features for capturing high-quality data. A proof-of-concept system is implemented to validate its feasibility and effectiveness. The experimental results show the benefits by using the proposed architecture comparing to the previous honeypot solutions., Comment: None

Published
2024
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8. A Serious Game to Study Reduced Field of View in Keyhole Surgery: Development and Experimental Study

Author

Phoebe Whitley, Connor Creasey, Matthew J Clarkson, and Stephen Thompson

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundDuring keyhole surgery, the surgeon is required to perform highly demanding tasks while only being able to see part of the patient’s anatomy. This limited field of view is widely cited as a key limitation of the procedure, and many computational methods have been proposed to overcome it. However, the precise effects of a limited field of view on task performance remain unknown due to the lack of tools to study these effects effectively. ObjectiveThis paper describes our work on developing a serious game with 2 objectives: (1) to create an engaging game that communicates some of the challenges of keyhole surgery, and (2) to test the effect of a limited field of view on task performance. The development of a serious game that can be played by a wide range of participants will enable us to gather quantitative data on the effects of the reduced field of view on task performance. These data can inform the future development of technologies to help surgeons reduce the impact of a limited field of view on clinical outcomes for patients. The game is open source and may be adapted and used by other researchers to study related problems. MethodsWe implemented an open-source serious game in JavaScript, inspired by the surgical task of selectively cauterizing blood vessels during twin-to-twin transfusion surgery. During the game, the player is required to identify and cut the correct blood vessel under different fields of view and varying levels of vascular complexity. We conducted a quantitative analysis of task performance time under different conditions and a formative analysis of the game using participant questionnaires. ResultsWe recruited 25 players to test the game and recorded their task performance time, accuracy, and qualitative metrics. Reducing the field of view resulted in participants taking significantly longer (P

Published
2025
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9. Nebulization of 2% lidocaine has no detectable impact on the healthy equine respiratory microbiota.

Author

Lauren Holley, Hannah N Creasey, Daniela Bedenice, Sarah Reed, Debora Regina Romualdo da Silva, Victoria Trautwein, Melissa Mazan, and Giovanni Widmer

Subjects
Medicine, Science
Abstract

Glucocorticosteroids remain the most common pharmaceutical approach for the treatment of equine asthma but can be associated with significant side effects, including respiratory microbiome alterations. The goal of the study was to assess the impact of 2% lidocaine nebulization, a projected alternative treatment of equine asthma, on the healthy equine respiratory microbiota. A prospective, randomized, controlled, blinded, 2-way crossover study was performed, to assess the effect of 1 mg/kg 2% lidocaine (7 treatments over 4 days) on the equine respiratory microbiota compared to control horses (saline and no treatment). Clinical assessments and respiratory samples, including nasal wash, endoscopic tracheal aspirate and bronchoalveolar lavage fluid, were obtained at each sample collection timepoint. The profile of the respiratory bacterial microbiota was evaluated using 16S amplicon sequencing, and clinical data compared using related samples analyses, based on data normality. The treatment did not affect the clinical data or alter the tracheal and nasal microbiota in healthy horses. However, time explained 12.6% of microbiota variation among samples. A significant difference in bacterial composition was observed between nasal and tracheal samples, showing the greatest relative abundance of Actinobacteria and Firmicutes, respectively. Bacterial DNA from bronchoalveolar lavage fluid did not amplify with generic primers targeting the V4 variable region of the prokaryotic small subunit ribosomal RNA gene, despite attempting multiple DNA extraction methods and PCR protocols, and after excluding PCR inhibition. This observation indicates that bronchoalveolar lavage fluid of healthy horses has a low bacterial load.

Published
2025
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15. Do Good, Better: Making a Difference in Global Oral Health

Author

Donna Hackley, Christy Colburn, and Jean Creasey

Subjects
Global oral health, dentistry, mission trips, global health ethics, volunteerism, STEGH, Dentistry, RK1-715
Abstract

Short-term mission trips have long served as a way for oral health professionals to “give back,” using their abilities to address the heavy global burden of oral disease, a burden that disproportionately affects populations in low- and middle-income countries. These international volunteer programs may bring needed care to the communities they serve but can create challenges in ethical engagement, sustainability, and effectiveness. Currently, momentum is shifting away from the “clinical care elsewhere” model, where community context, relationship building, monitoring, and sustainability can be lacking, and moving toward approaches that focus on community collaboration, leadership, education, and advocacy. This paper aims to help clinicians evaluate their current and future short-term volunteer work through a new paradigm.

Published
2024
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17. The genomic and clinical consequences of replacing procarbazine with dacarbazine in escalated BEACOPP for Hodgkin lymphoma: a retrospective, observational study

Author

Santarsieri, Anna, Mitchell, Emily, Pham, My H, Sanghvi, Rashesh, Jablonski, Janina, Lee-Six, Henry, Sturgess, Katherine, Brice, Pauline, Menne, Tobias F, Osborne, Wendy, Creasey, Thomas, Ardeshna, Kirit M, Baxter, Joanna, Behan, Sarah, Bhuller, Kaljit, Booth, Stephen, Chavda, Nikesh D, Collins, Graham P, Culligan, Dominic J, Cwynarski, Kate, Davies, Andrew, Downing, Abigail, Dutton, David, Furtado, Michelle, Gallop-Evans, Eve, Hodson, Andrew, Hopkins, David, Hsu, Hannah, Iyengar, Sunil, Jones, Stephen G, Karanth, Mamatha, Linton, Kim M, Lomas, Oliver C, Martinez-Calle, Nicolas, Mathur, Abhinav, McKay, Pamela, Nagumantry, Sateesh K, Phillips, Elizabeth H, Phillips, Neil, Rudge, John F, Shah, Nimish K, Stafford, Gwyneth, Sternberg, Alex, Trickey, Rachel, Uttenthal, Benjamin J, Wetherall, Natasha, Zhang, Xiao-Yin, McMillan, Andrew K, Coleman, Nicholas, Stratton, Michael R, Laurenti, Elisa, Borchmann, Peter, Borchmann, Sven, Campbell, Peter J, Rahbari, Raheleh, and Follows, George A

Published
2025
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18. Tranexamic acid versus placebo to prevent bleeding in patients with haematological malignancies and severe thrombocytopenia (TREATT): a randomised, double-blind, parallel, phase 3 superiority trial

Author

Estcourt, Lise J, McQuilten, Zoe K, Bardy, Peter, Cole-Sinclair, Merrole, Collins, Graham P., Crispin, Philip J., Curnow, Elinor, Curnow, Jennifer, Degelia, Amber, Dyer, Claire, Friebe, Adam, Floro, Lajos, Grand, Effie, Hudson, Cara, Jones, Gail, Joseph, Joanne, Kallmeyer, Charlotte, Karakantza, Marina, Kerr, Paul, Last, Sara, Lobo-Clarke, Maria, Lumley, Matthew, McMullin, Mary F, Medd, Patrick G., Morton, Suzy M., Mumford, Andrew D., Mushkbar, Maria, Parsons, Joseph, Powter, Gillian, Sekhar, Mallika, Smith, Laura, Soutar, Richard, Stevenson, William S., Subramoniapillai, Elango, Szer, Jeff, Thomas, Helen, Waters, Neil A., Wei, Andrew H., Westerman, David A., Wexler, Sarah A., Wood, Erica M., Stanworth, Simon J., Abioye, Adrienne, Afghan, Rabia, Ai, Sylvia Ai, Akanni, Magbor, Alajangi, Rajesh, Alam, Usmaan, Al-Bubseeree, Bahaa, Alderson, Sophie, Alderson, Craig, Ali, Sayed, Ali, Kabir, Alighan, Rookmeen, Allam, Rebecca Allam, Allen, Tania, Al-Sakkaf, Wesam, Ames, Kate, Anderson, Jacqueline, Andrews, Colin, Angel, Ann-Marie, Anlya, Manuela Anlya, Ansari, Farah, Appleby, Rowan, Arnold, Claire, Asbjornsdottir, Hulda, Asfaw, Biruk, Atkins, Elissa, Atkinson, Leela, Aubrey, Clare, Ayesha, Noor, Babbola, Lola, Badcock, David, Badcock, Samuel, Baggio, Diva, Bailiff, Ben, Baines, Kizzy, Baker, Holly, Baker, Victoria, Ball, Lindsay, Ball, Martin, Balquin, Irwin, Banks, Emma, Banos, George, Barnett, Jaytee, Barrie, Claire, Barron, Claire, Barton, Rebecca, Bason, Nina, Batta, Bindu, Bautista, Dianne, Bayley, Angela, Bayly, Emma, Baynes, Fionnuala, Bazargan, Ali, Bazeley, Rachel, Beadle, Yvonne, Beardsmore, Claire, Beattie, Kate, Bedford, Caroline, Behal, Rachna, Behan, Daniel, Bejan, Lilihna, Bell, Sarah, Bell, Karen, Bell, Louise, Bell, Kaitlyn, Benjamin, Reuben, Bennett, Sam, Benson, Gary, Benson, Warwick, Bent, Cameron, Bergin, Krystal, Berry, Alex, Besenyei, Stephanie, Besley, Caroline, Betteridge, Scott, Beveridge, Leigh, Bhattacharyya, Abir, Billen, Annelies, Bilmon, Ian, Binns, Emma, Birt, Mark, Bishop, David, Blanco, Andrea, Bleby, Lisa, Blemnerhet, Richard, Blombery, Piers, Blyth, Emily, Blythe, Nicola, Boal, Lauren, Boden, Ali, Bokhari, Syed W.I., Bongetti, Elisa, Booth, Stephen, Borley, Jayne, Bowen, David, Bowers, Dawn, Boyd, Stephen, Bradley, Sarah, Bradman, Helen, Bretag, Peta, Brillante, Maria, Brockbank, Rachel, Brough, Yasmin, Brown, Ellen, Brown, Jo, Brown, Eleanor, Brown, Claire, Brown, Jenny, Brown, Susan, Browning, Joe, Brownsdon, Alex, Bruce, David, Brydon-Hill, Ruth, Buckwell, Andrea, Burgess, Dannielle, Burke, Glenda, Burley, Kate, Burney, Claire, Burns, David, Burrows, Samuel, burton, Kieran, Butler, Jason, Cambalova, Lenka, Camozzi, Maria C., Campbell, Philip, Campfield, Karen, Campion, Victoria, Cargo, Catherine, Carmona, Julia, Carney, Dennis, Casan, Joshua, Cashman, Helen, Catt, Lorraine, Cattell, Michael, Cavill, Megan, Chadbone, Rachel, Chaganti, Sridhar, Chai, Yee, Chai, Khai Li, Chang, Joshua, Chapman, Judith, Chapman, Oliver G., Chapter, Tamika, Charlton, Andrew, Chau, Celina, Chauhan, Saleena, Chavda, Nikesh, Chen, Frederick, Chen, Melody, Chen, Meng Xi, Chen, Melanie, Chen, Melissa, Cheok, Kathleen, Cheung, Mai, Chidgey, Luke, Chmielokliec, Karolina, Choi, Philip, Choi, Jae, Chok, Anne, Chopra, Ruchika, Christopherson, Louise, Chu, Vicky, Chua, Chong Chyn, Chudakou, Pavel, Chugh, Vidushi, Chung, Chi, Clark, Erin, Clarke, Peter, Clarke, Kathleen, Clay, Jennifer, Clayton, Laura, Clements, Mitch, Clemmens, Jonathan, Clifford, Ruth, Collett, Dave, Collins, Maia, Collyer, Emily, Connolly, Maureen, Cook, Mark, Coombs, Sarah, Coppell, Jason, Cornwell, Sophie, Corrigan, Claire, Coughlin, Elizabeth, Couling, Jennifer, Cousins, Tony, Cowan, Catriona, Cox, Christine, Cox, Catherine, Coyle, Luke, Craig, Emily, Creasey, Thomas, Croan, Laura, Croft, Jane, Crosbie, Nicola, Crowe, Josephine, Crowther, Helen, Crozier, Jane, Culleton, Naomi, Cullis, Jonathan, Cumming, Anita, Cummins, Michelle, Cunningham, Adam, Curley, Cameron, Curtis, Samantha, Cuthbert, Robert, Cuthill, Kirsty, Dahahayake, Dinusha A, Dang, Amy, Davies, Marc, Davies, Ceri, Dawson, Emily, Day, Tom, De Abrew, Kanchana, De Lavallade, Hugues, De Silva, Neelaskshi, Dean, Georgina, Deane, Christopher, Demosthenous, Lisa, Desai, Amisha, Desborough, Michael, Devanny, Ian, Dhanapal, Jay, Dhani, Sundip, Di Martino, Vicky, Dickens, Emmy, DiCorleto, Carmen, Dinnett, Louise, Dirisan, Divya, Dixon, Karen, Dixon, Kiri, Doal, Inderjit, Dobivh, J, Docanto, Maria, Doecke, Helve, Donaldson, David, Donaldson, Kylee, Donohoe, Carrie, Douglas, Ashley, Doung, Stephen, Downer, Susan, D'Rozario, James, Drummond, Malcolm, Drummond, Mark, Drummond, Samantha, Drysdale, Elizabeth, D'Souza, Ross, D'Souza, Eugene, Dunn, Alex, Dutton, David, Dyson, Martin, Ediriwicurena, Kushani, Edleston, Sharon, Edwards, Dawn, Edwards, Morgan, Edwards, Anita, Eise, Nicole, Ellis, Steven, Ellis, Hayley, Elmonley, Shareef, Enstone, Rosemarie, Eordogh, Agnes, Erb, Sharon, Evans, Shannon, Evans, Megan, Ewing, Joanne, Eyre, Toby, Facey, Adam, Fammy, Mina, Farman, Jon, Farnell, Rachel, Favero, Laura, Fay, Keith, Ferguson, Karen, Fernon, Laura, Filshie, Robin, Finnegan, Damian, Fisher, Lisa, Flanagan, Asia, Fleck, Emma, Fletcher, Simon, Flora, Harpreet, Flower, Catherine, Fodor, Ioana, Foley, Heather, Folland, Emma, Folorunso, Comfort, Forbes, Molly, Fordwor, Katrina, Foster, Polly, Fox, Vanessa, Fox, Thomas, Francis, Olesya, Fryearson, Louise, Fuery, Madonna, Fung, Jiin, Furtado, Michelle, Galloway-Browne, Leanne, Gamble, Louise, Gamgee, Jeanette, Ganapathy, Arundathi, Gardner, Hayley, Gardner, Clare, Gasmelsheed, Noha, Gately, Amy, Gaynor, Lynda, Gebreid, Alex, Geffens, Ruth, George, Rachel, Gertner, Aniko, Ghebeh, Manar, Ghirardini, Emanuela, Giddings, Melainie, Gillett, Sandra, Gillett, Karen, Giri, Pratyush, Glass, Chris, Glewis, Sarah, Gooding, Sarah, Gordon, Olivia, Gordon, Joanne, Gottlieb, David, Gowda, Koushik, Gower, Elysie, Gray, Nicola, Grayer, Jo, Greaves, Elaine, Greenaway, Sally Anne, Greenfield, Graeme, Greenwood, Matthew, Gregory, Gareth, Griffin, James, Griffith, Julia, Griffith, James, Griffiths, Lindsey, Grzegrzolka, Paulina, Gu, Yisu, Guest, Jo, Guinai, Rosanna, Gullapalli, Veena, Gunolr, A., Guo, Lina, H, Wayne, Hagua, Sophia, Haile, Senait, Hall, Richard, Hamdollah-Zadeh, Maryam, Hanif, Zahra, Hanlon, Kathleen, Hann, Nicholas, Hanna, Ramez, Hannah, Guy, Hapuarachchi, Sameera, Hardman, Jacinta, Hardy, Alison, Harris, Anthony, Harris, Kylie, Harrison, Beth, Harrison, Simon, Harrison, Lea-Anne, Harrop, Sean, Harvey, Caroline, Hatcliffe, Faye, Hawking, Jo, Hawkins, Matthew, Hayden, Janet, Hayman, Michelle, Haynes, Elizabeth, Heaney, Nicholas, Hebbard, Andrew, Hempton, Jenny, Hendunneti, Sasanka, Henry, Maeve, Heywood, Jonathan, Hildyard, Catherine, Hill, Lydia, Hilldrith, Annette, Hitev, Petar, Hiwase, Smita, Hiwase, Devendra, Hoare, Chris, Hodge, Renate, Holloway, Amy, Holt, Chloe, Holton, Kelly, Homer, Lauren, Horne, Gillian, Horvath, Noemi, Hotong, Linda, Houdyk, Kristen, Houseman, Katy, Hoxhallari, Ilda, Hsu, Hannah, Hsu, Nina, Huang, Gillian, Hudson, Kerryn, Hufton, Melanie, Hughes, Timothy, Hughes, Siobhan, Hurley, Kate, Huxley, Rosie, Ibitoye, Temitope, Ibrouf, Abubaken, Inam, Farha, Indran, Tishya, Ingham, Karen, Innes, Calum, Irvine, David, Jaafar, Sarah, Jain, Manish, Jameson, Laura, Janjua, Pardeep, Jarvis, Rebecca, Jatheendran, Abirami, Javed, Abbie, Jen, Sheila, Jobanpura, Shailesh, Jobson, Irene, John, Deborah, Johns, Sophie, Johnston, Amanda, Jones, Hollie, Jones, Francesca, Joniak, Karolina, Jovanovic, Michael, Jovic, Anita, Joyce, Lauren, Judd, Andrew, Kakarlamudi, Sudhakar, Kakaroubas, Nick, Kalita, Maggie, Kam, Shirly, Kan, Julie, Kandle, P, Kanellopoulos, Alex, Kao, Chien, Kaparou, Maria, Kartsios, Charamlampos, Katsioulas, Vicki, Kaye, Russell, Keen, Katie, Kelly, Richard, Kelly, Pauline, Kelly, Donna, Kelly, Melanie, Kennedy, Glen, Kennedy, Nola, Kenny, Angela, Kenworthy, Zoe, Kerridge, Ian, Kesavan, Murali, Khafizi, Angelika, Khakwani, Muhammad, Khalid, Amna, Khamly, Kate, Khan, Anjum, Khan, Dalia, Khan, Mojid, Khan, Lubna, Khoo, Mona, Khwaja, Asim, Kim, Grace, King, Andrew, King, Vicky, King, Donna, Kinsella, Francesca, Kipp, David, Kirandeep, Pachoo, Kirui, Laura C., Kishore, Bhuvan, Knectlhi, Christopher, Knot, Amy, Knot, Armit, Ko, Cathy, Kolaric, Caitlin, Koo, Ray, Kotadia, Mary, Kothari, Jaimal, Kottaridis, Panagiotis D., Kuiluinathan, Gajan, Kulasekararaj, Austin, Kwan, John, Kwok, Marwan, Kwok, Phillip, Kwok, Fiona, Laane, Kristiina, Lad, Deena, Laird, Jennifer, Lam, Ada, Lane, Mary, Lanenco, Monica, Lang, Susan, Langridge, Alex, Langton, Catherine, Lannon, Michelle, Latif, Annie, Latimer, Maya, Latter, Ruth, Lau, I-Jun, Lawless, Sarah, Lawless, Theresa, Leach, Mike, Leaney, Sarah, Leary, Heather, Leavy, James, LeBlanc, Abbey, Lee, Vivienne, Lee, Edwin, Lee, Jenny, Lee, Tamara, Leischkie, Marian, Leitinger, Emma, Leon, Christopher, Leonard, Jayne, Lewis, David, Lewis, Ian, Lewis, Tania, Lim, Daniel, Littlewood, Kelly, Liu, Dara, Loh, Joanna, Lokare, Anand, Lomas, Oliver, Lovell, Richard, Lowe, Theresa, Lowry, Lisa, Lubowiecki, Marcin, Lumb, Rebecca, Lynch, Gail, Macaulay, Amanda, MacDonald, Lyndsey, MacDonald-Burn, Jill, Macmillan, Margaret, Maddock, Karen, Mahaliyana, Tomas, Mahon, Cassandra, Maidment, Alison, Maier, Susie, Mairos, Michelle, Majid, Mahseeman, Mak, Ka L, Mak, Anne, Malendrayogau, Arunthrthy, Malham, Hana, Malyon, Felicity, Mandadapu, Vineela, Mandel, Laura, Mant, Sarah, Manton, Ruth, Maouche, Nadjoua, Maqbool, Muhammad G., Marchant, Gregory, Marinho, Mariana, Marks, David, Marner, Mike, Marr, Helen, Marshall, Gillian, Martin, Siobhan, Martin, Abigail, Marzolini, Maria, Mason, Kiara, Massie, Jonathan, Masson, Rebecca, Mathavan, Vidya, Mathew, Siju, Mathie, Judith, Mattocks, Lehenta, Maybury, Bernard, Mayer, Georgina, McAlister, Chyrelle, McAllister, Jo, McConnell, Stewart, McCracken, James, McCullagh, Liz, McCulloch, Rory, Mcdermott, Christopher, Mcdonald, Kerian, McGinniss, Laura, McGurk, Fiona, McIlwain, Jessica, McIver, Kirsten, Mckay, Pam, McKenna, Lorraine, Mclornan, Donal, McMahon, Coalon, McNeice, Linda, McNeill, Susan, McNickle, Molly, McQueen, Fiona, McRae, Simon, McTaggart, Bobby, Mehew, Jenny, Mehra, Varnn, Melly, Michelle, Menichelli, Tara, Micklethwatte, Ken, Mihailescue, Loredana, Mijovic, Aleksander, Millband, Hannah, Miller, Lucy, Millien, Samuel T., Milnthorpe, James, Minson, Adrian, Molnar, Eva, Monsour, Marc, Moody, Mary, Moon, Rebecca, Moore, Sally, Moore, Katy, Morgan, Kelly, Morralley, Rebecca, Morris, Denise, Morris, Kirk, Morrison, Nicole, Moss, Merinda, Mughal, Muhammad, Muir, Paul, Mukkath, David, Mulla, Aasiyu, Mulligan, Stephen, Mullings, Joanne, Mulqueen, Angela, Muluey, Caitlin, Murdoch, Sarah, Murrani, Sura, Murthy, Vidhya, Musngi, Jimmy, Mustafa, Nadreen, Mynes, Tracey, Nalpantidis, Anastasios, Nandurkar, Harshal, Nardone, Linda, Nasari, Latifa, Nash, Monica, Naylor, Georgina, Ngu, Loretta, Nguethina, Melissa, Nguyen, John, Nguyen, Joseph, Nichol, Wendy, Nicholls, Emma, Nicole, Catherine S., Nicolson, Phillip, Nielson, David, Nikolousis, Emmanouil, Nix, Georgina, Njoku, Rita, Norman, Jane, Norman, Amy, Norris, Phoebe, North, Daniel, Norwood, Megan, Notcheva, Gaynor, Novitzky-Basso, Igor, Nyaboko, Joseph, Nygren, Maria, Obu, Ingrid, O'Connell, Siobhan, O'Connor, Jody, O'Kelly, Deanna, O'Niell, Aideen, Ony, Jeremy, Oo, Kathy, Oo, April, Oppermann, Anne, Orr, Ruth, O'Sullivan, Mary, Page, Jennifer, Palfreyman, Emma, Paneesha, Shankaranarayana, Panicker, Shyam, Parbutt, Catherine, Parigi, Elesha, Paris, Gemma, Parker, Tracey, Parnell, Caroline, Parrish, Christopher, Parsons, Alex, Pasat, Mioara, Patel, Natasha, Patel, Vijay, Patel, Pooja, Patel, Chaya, Pati, Nalini, Patterson, Andrea, Paul, Lauren, Payet, Danielle, Payne, Elspeth, Peachey, Victoria, Pearson, Amanda, Peniket, Andy, Percy, Laura, Pereyra, Millicent, Pervaiz, Omer, Phalod, Gunjan D, Pham, Anh, Pho, Jason, Pickard, Keir, Pidcock, Michael, Piggin, Anna, Pishyar, Yalda, Pocock, Abigail, Pol, Ranjendres, Polzella, Paolo, Poolan, Sonia, Portingale, Vicki, Posnett, Claire, Potluri, Sandeep, Potter, Victoria, Pratt, Guy, Prodger, Catherine, Pueblo, Andres, Puliyayil, Anish, Puvanakumar, Pratheepan, Qadri, Abdul, Quach, Hang, Quinn, Michael, Rafferty, Mark, Rahman, Marzia, Raj, Kavita, Raj, Sonia, Rajendran, Ramina, Ramanan, Radha, Ramasamy, Karthik, Rampotas, Alexandros, Ranchhod, Natasha, Rashid, Sabia, Ratanjee, Sunita, Rathore, Gurpreet, Ratnasingam, Sumita, Rayat, Manjit, Rayner, Michael, Reddell-Denton, Rebecca, Redding, Nicola, Reddy, Udaya, Rehman, Atique, Rice, Carol, Riches, Iwona, Rider, Thomas, Riley, John, Rinaldi, Ciro, Roberts, Kayleigh, Roberts, Andrew, Robertson, Bryony, Robertson, Peter, Robinson, Dan, Robinson, Rebecca, Robjohns, Emma, Robledo, Laura, Rodrigues, Ana, Rofe, Chris, Roff, Bridie, Rogers, Rachel, Rolt, Jill, Rooney, Carmela, Rose, Kathy, Rose, Hannah, Ross, David, Rouf, Shahara, Rourke, Claire, Routledge, David, Ruggiero, Janet, Rule, Simon, Rumsey, Richard, Sagge, Cherry, Saldhana, Helen, Salisbury, Richard, Salisbury, Sarah, Salvaris, Ross, Sanders, Kay, Sangombe, Mirriam, Sanigorska, Anna, Santos, Kristine, Sarkis, Taylah, Sarma, Anita, Saunders, Natalie, Schmidt, Kara, Schmidtmann, Anja, Schumacher, Ann, Scorer, Tom Scorer, Scott, Asleigh, Seath, Ingrid, Sejman, Frances, Selim, Adrian, Shamim, Nadia, Shan, Jocelyn, Shanmuganathan, Naranie, Shanmugaranjan, Shaminie, Sharpe, Michelle, Sharpley, Faye, Shaw, Emma, Sheath, Cara, Sheehy, Oonagh, Shen, Vivian, Sherbide, Solomon, Sheridan, Mathew, Sheridan, Jane, Sheridon, Matthew, Shields, Tracy, Sim, Hau V, Sim, Shirlene, Sims, Matt, Singaraveloo, Lydia, Singh, Gurcharan, Singh, Jasmine, Sladesal, Shree, Sloan, Andrew, Slobodian, Peter, Smith, Sophie, Smith, Sarit, Smith, Claire, Smith, Alastair, Smith, Neil, Snowden, Katherine, Solis, Joel, Somios, Denise, Soo, Jade, Spanevello, Michelle, Spaulding, Madeleie, Spence, Laura, Spillane, Liz, Spiteri, Alisha, Sprigg, Naomi, Springett, Sally, Stafford, Lynn, Stainthorp, Katherine, Stark, Kate, Steeden, Louise, Stephen, Ella, Stephenson, Aisling, Stewart, Andrew, Stewart, Orla, Stobie, Emma, Stokes, Chelsea, Streater, Jacqui, Suddens, Charlie-Marie, Suntharalingam, Surenthini, Surana, Narinder, Sutherland, Robyn, Sutherland, Antony, Sutton, David, Sweeney, Connor, Sweet, Reilly, Szucs, Aniko P, Taheri, Leila E., Tailor, Hinesh, Tam, Constantine, Tambakis, George, Tamplin, Mary, Tan, Chee, Tan, Sui, Tan, Joanne, Tan, Zhi, Taran, Tatiana, Tarpey, Fiona, Taseka, Angela, Tasker, Suzy, Tatarczuch, Maciej, Tayabali, Sarrah, Taylor, Hannah, Taylor, Robert, Taylor, Melaine, Taylor-Moore, Ella, Teasdale, Lesley, Tebbet, Elizabeth, Tedjasepstra, Aditya, Tedjaseputra, Aditya, Tepkumkun, Oummy, Terpstra, Andrew, Thomas, Wayne, Thomas, Shanice, Thompson, Rachel, Thornton, Thomas, Thorp, Bronwyn, Thrift, Moi Yap, Thwaites, Phillipa, Timbres, Jasmine, Tindall, Lauren, Tiong, Ing Soo, Tippler, Nicole, Todd, Tony, Todd, Shirley, Toghill, Neil, Tomlinson, Eve, Tooth, Jacinta, Topp, M., Trail, Nicola, Tran, Nguyen, Tran, Elizabeth, Tran, Vi, Treder, Bona, Tribbeck, Michelle, Trochowski, Siobhan, Truslove, Maria, Tse, Tsun, Tseu, Bing, Tucker, David, Turner, Kelly, Turner, Dianne, Turner, Herleen, Turner, Gillian, Twohig, Julie, Tylee, Thomas, Uhe, Micheleine, Underhill, Lauren, V, Joanne, Van der Vliet, Georgina, Van Tonder, Tina, VanderWeyden, Carrie, Varghese, Jerry, Vaughan, Lachlan, Veale, David, Vickaryyous, Nicky, Vince, Kathryn, Von Welligh, Jacoba, Vora, Sona, Wadehra, Karan, Walker, Rebecca, Walker, Stephen, Wallace, Roslyn, Wallniosve, Stephanie, Wallwork, S., Walmsley, Zoe, Walters, Fiona, Wang, Joyce, Wang, Angela, Wang, Chen, Wanyika, Mercy, Warcel, Dana, Wardrobe, Katrina, Warnes, Kristian, Waterhouse, Christopher, Waterworth, Adam, Watson, Caroline, Watson, Edmund, Watts, Emily, Weaver, Emma, Weber, Nicholas, Webley, Kaytie, Welford, Anna, Wells, Matt, Westbury, Sarah, Westcott, Jackie, Western, Robyn, Weston, Julia, White, Jessica, White, Phillipa, Whitehead, Anna, Whitehouse, James, Wieringa, Samantha, Willan, John, Williams, Sandra, Williams, Bethany, Williamson, Stephanie, Willoughby, Brett, Wilmot, Gail, Wilmott, Rosalind, Wilson, Joanna, Wilson, Emma, Wilson, Suzy, Wilson, Heather, Wilson, Caroline, Wilson, Tanya, Wilton, Margaret, Wiltshire, Paula, Wincup, Joanne, Wolf, Julia, Wong, Henna, Wong, Cyndi, Wong, Daniel, Wong, Jonathan, Wong, Shi Qin, Wood, Sarah, Wood, Henry, Wooding, Jackie, Woolley, Kelly, Wright, Myles, Wynn-Williams, Roland, Yannakou, Costas, Yeoh, Zhi Han, Yeung, David, Young, Agnes, Yuen, Flora, Yuen, Agnes, Zaja, Oliver, Zhang, Xiao-Yin, and Zhang, Mei

Published
2025
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19. A longitudinal study on the relation between parenting and Toddler’s disruptive behavior: what is the role of Toddler’s negative emotionality and physiological stress reactivity?

Author

Marijke Huijzer-Engbrenghof, Loes van Rijn-van Gelderen, Hannah Spencer, Christiane Wesarg-Menzel, Nicole Creasey, Esmee S. Lalihatu, and Geertjan Overbeek

Subjects
disruptive behavior, parenting, temperament, stress reactivity, longitudinal, Psychology, BF1-990
Abstract

Harsh and unsupportive parenting is a risk factor for the development of disruptive behavior in children. However, little is known about how children’s temperament and stress reactivity influence this relation. In a three-wave longitudinal study, we examined whether the associations between parenting practices (supportive parenting, positive discipline, and harsh discipline) and child disruptive behavior were mediated by child temperament (negative emotionality) and stress reactivity (heart rate reactivity). In 72 families (Mage child = 14.6 months), living in the Netherlands, parents reported on their parenting practices and their children’s disruptive behavior and negative emotionality. Children’s heart rate reactivity was assessed through a series of stress-inducing tasks. Results from regression-based mediation analyses with bootstrapping showed that negative emotionality and stress reactivity did not mediate the relation between parenting and disruptive behavior. The results overall demonstrate that in a group of children this age, a reinforcing dynamic between parenting, child stress and disruptive behavior is not yet firmly established.

Published
2024
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20. Demonstrating the benefit of agricultural biotechnology in developing countries by bridging the public and private sectors

Author

Itam, Michael O., Iohannes, Sessen D., Albertsen, Marc, Andrade, Maria, Bor, Gilbert arap, Atta-Krah, Kwesi, Bertram, Robert, Danquah, Eric, Horvath, Diana M., Jones, Todd, Mugehu, Edith, Okwuonu, Ihuoma, Ooko-Ombaka, Amandla, Roberts, Richard J., Slamet-Loedin, Inez, Tripathi, Leena, Ubi, Benjamin Ewa, Varshney, Rajeev K., Venturi, Vittorio, Wagaba, Henry, Zeigler, Robert, and Creasey Krainer, Kate M.

Published
2024
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24. Brexucabtagene autoleucel for relapsed or refractory mantle cell lymphoma in the United Kingdom: A real‐world intention‐to‐treat analysis

Author

Maeve A. O'Reilly, William Wilson, David Burns, Andrea Kuhnl, Frances Seymour, Ben Uttenthal, Caroline Besley, Rajesh Alajangi, Thomas Creasey, Shankara Paneesha, Johnathon Elliot, Carlos Gonzalez Arias, Sunil Iyengar, Matthew R. Wilson, Alison Delaney, Lourdes Rubio, Jonathan Lambert, Khalil Begg, Stephen Boyle, Kathleen P. L. Cheok, Graham P. Collins, Claire Roddie, Rod Johnson, and Robin Sanderson

Subjects
Diseases of the blood and blood-forming organs, RC633-647.5
Abstract

Abstract Brexucabtagene autoleucel (brexu‐cel) is an autologous CD19 CAR T‐cell product, approved for relapsed/refractory (r/r) mantle cell lymphoma (MCL). In ZUMA‐2, brexu‐cel demonstrated impressive responses in patients failing ≥2 lines, including a bruton's tyrosine kinase inhibitor, with an overall and complete response rate of 93% and 67%, respectively. Here, we report our real‐world intention‐to‐treat (ITT) outcomes for brexu‐cel in consecutive, prospectively approved patients, from 12 institutions in the United Kingdom between February 2021 and June 2023, with a focus on feasibility, efficacy, and tolerability. Of 119 approved, 104 underwent leukapheresis and 83 received a brexu‐cel infusion. Progressive disease (PD) and/or manufacturing (MF) were the most common reasons for failure to reach harvest and/or infusion. For infused patients, best overall and complete response rates were 87% and 81%, respectively. At a median follow‐up of 13.3 months, median progression‐free survival (PFS) for infused patients was 21 months (10.1–NA) with a 6‐ and 12‐month PFS of 82% (95% confidence interval [CI], 71–89) and 62% (95% CI, 49–73), respectively. ≥Grade 3 cytokine release syndrome and neurotoxicity occurred in 12% and 22%, respectively. On multivariate analysis, inferior PFS was associated with male sex, bulky disease, ECOG PS > 1 and previous MF. Cumulative incidence of non‐relapse mortality (NRM) was 6%, 15%, and 25% at 6, 12, and 24 months, respectively, and mostly attributable to infection. Outcomes for infused patients in the UK are comparable to ZUMA‐2 and other real‐world reports. However, ITT analysis highlights a significant dropout due to PD and/or MF. NRM events warrant further attention.

Published
2024
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37. Secure Non-public Health Enterprise Networks

Author

Ghassemian, Mona, Smith-Creasey, Max, and Nekovee, Maziar

Subjects
Computer Science - Networking and Internet Architecture
Abstract

Increasing demand for secure remote operation in industry and technology advancements to support delivering efficient services and tele-mentoring have opened a new market in healthcare sector and emergency services based on 5G and Tactile internet capabilities. In a connected world, hospitals would benefit from providing the on-time availability either for continuous health monitoring or critical services to the citizens in need. In this paper, we propose a secure non-public health enterprise network concept to enable an end-to-end secure and location-agnostic communication between a patient and a healthcare service provider, and other contacts with patients consent either in case of an emergency or to be stored in the medical records. We present how applying non-public enterprise networks can address market demand in health care sector for improved end-to-end security and privacy when dealing with personal and critical information. We present the three tier architecture model describing continuous authentication mechanisms based on biometric collection as well as the dynamic network solutions in the healthcare domain. The biometric collection can be done using ambient or IoT sensors as well as wearable or implantable devices to monitor the patient unobtrusively. Furthermore, end-to-end security solutions should adapt dynamically based on the user profile and situation awareness to address the required level of security at the network side. We discuss the related research challenges for developing the presented non-public health enterprise platform and provide suggestions for future work based on the healthcare sector requirements and opportunities., Comment: Accepted for publication in Proceedings for 2020 IEEE International Conference on Communications (ICC)

Published
2020

38. Soft-Bubble grippers for robust and perceptive manipulation

Author

Kuppuswamy, Naveen, Alspach, Alex, Uttamchandani, Avinash, Creasey, Sam, Ikeda, Takuya, and Tedrake, Russ

Subjects
Computer Science - Robotics
Abstract

Manipulation in cluttered environments like homes requires stable grasps, precise placement and robustness against external contact. We present the Soft-Bubble gripper system with a highly compliant gripping surface and dense-geometry visuotactile sensing, capable of multiple kinds of tactile perception. We first present various mechanical design advances and a fabrication technique to deposit custom patterns to the internal surface of the sensor that enable tracking of shear-induced displacement of the manipuland. The depth maps output by the internal imaging sensor are used in an in-hand proximity pose estimation framework -- the method better captures distances to corners or edges on the manipuland geometry. We also extend our previous work on tactile classification and integrate the system within a robust manipulation pipeline for cluttered home environments. The capabilities of the proposed system are demonstrated through robust execution multiple real-world manipulation tasks. A video of the system in action can be found here: [https://youtu.be/G_wBsbQyBfc]., Comment: 8 pages, conference

Published
2020

39. Security of Input for Authentication in Extended Reality Environments

Author

Andrade, Tiago Martins, Roscoe, Jonathan Francis, Smith-Creasey, Max, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Yang, Xin-She, editor, Sherratt, R. Simon, editor, Dey, Nilanjan, editor, and Joshi, Amit, editor

Published
2023
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40. The Digital Afterlife: A Guide To Managing Digital Assets After A Loss

Author

Creasey, Bethan

Subjects
Crypto-currencies -- Laws, regulations and rules, Online assets -- Laws, regulations and rules, Government regulation, Business, international
Abstract

In an era where we live much of our lives online, it is no surprise that our digital footprints outlast us. From the photos we share on social media to [...]

Published
2025

42. T cell circuits that sense antigen density with an ultrasensitive threshold

Author

Hernandez-Lopez, Rogelio A, Yu, Wei, Cabral, Katelyn A, Creasey, Olivia A, Lopez Pazmino, Maria Del Pilar, Tonai, Yurie, De Guzman, Arsenia, Mäkelä, Anna, Saksela, Kalle, Gartner, Zev J, and Lim, Wendell A

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Biotechnology, Cancer, Gene Therapy, Women's Health, Genetics, Immunotherapy, 2.1 Biological and endogenous factors, 5.2 Cellular and gene therapies, Animals, Antigens, Neoplasm, Cell Engineering, Cell Line, Tumor, Humans, Immunotherapy, Adoptive, K562 Cells, Mice, Receptor, ErbB-2, Receptors, Artificial, Receptors, Chimeric Antigen, Receptors, Notch, Spheroids, Cellular, T-Lymphocytes, Cytotoxic, Xenograft Model Antitumor Assays, Receptor, erbB-2, General Science & Technology
Abstract

Overexpressed tumor-associated antigens [for example, epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2)] are attractive targets for therapeutic T cells, but toxic "off-tumor" cross-reaction with normal tissues that express low levels of target antigen can occur with chimeric antigen receptor (CAR)-T cells. Inspired by natural ultrasensitive response circuits, we engineered a two-step positive-feedback circuit that allows human cytotoxic T cells to discriminate targets on the basis of a sigmoidal antigen-density threshold. In this circuit, a low-affinity synthetic Notch receptor for HER2 controls the expression of a high-affinity CAR for HER2. Increasing HER2 density thus has cooperative effects on T cells-it increases both CAR expression and activation-leading to a sigmoidal response. T cells with this circuit show sharp discrimination between target cells expressing normal amounts of HER2 and cancer cells expressing 100 times as much HER2, both in vitro and in vivo.

Published
2021

43. High-resolution quantification of tissue structure and its variability in the pancreatic islet

Author

Creasey, Olivia Annette

Subjects
Bioengineering, Cellular biology, confocal, islet, microscopy, quantify, structure, tissue
Abstract

Appropriate 3D tissue structure supports cell and tissue function; inappropriate tissue structure correlates with cell and tissue dysfunction. Quantitative studies of this structure-function relationship are hampered by a paucity of techniques for tissue structure analysis. Using pancreatic islets as a model system, I have developed a novel method for high-resolution quantitative analysis of 3D tissue structure. Here, I summarize what is known about tissue structure in pancreatic islets, outline the processes of collecting high-resolution spatially quantitative 3D images of tissue and of extracting spatial data, detail qualitative observations of structural phenomena gleaned from observation of hundreds of 3D images of adult human and mouse pancreatic islets, and provide a proof-of-concept quantitative analysis of adult mouse and human islet tissue structure. My dissertation work sets the stage for quantitative study of tissue structure and function not just in healthy adult islets but also in other tissue types, and in unhealthy, developing, or engineered tissue. The rich image datasets acquired are also a valuable resource for both pancreatic biologists and those developing tools for image processing and image analysis.

Published
2024

44. Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

Author

Leongamornlert, Daniel, Gutiérrez-Abril, Jesús, Lee, SooWah, Barretta, Emilio, Creasey, Thomas, Gundem, Gunes, Levine, Max F., Arango-Ossa, Juan E., Liosis, Konstantinos, Medina-Martinez, Juan S., Zuborne Alapi, Krisztina, Kirkwood, Amy A., Clifton-Hadley, Laura, Patrick, Pip, Jones, David, O’Neill, Laura, Butler, Adam P., Harrison, Christine J., Campbell, Peter, Patel, Bela, Moorman, Anthony V., Fielding, Adele K., and Papaemmanuil, Elli

Published
2023
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47. Unravelling the genomic landscape of acute lymphoblastic leukaemia in older adults

Author

Creasey, Thomas

Abstract

The objectives of this study were to characterise the primary genetic abnormalities, genomic copy number changes and mutational landscape of ALL in older adults. The primary chromosomal abnormalities from patients aged ≥60 years recruited into the UKALL14 (n=94) and UKALL60+ (N=116) trials were first evaluated. B-cell precursor (BCP) ALL patients lacking a primary chromosomal abnormality (B-other ALL) were screened for ABL-class fusions, JAK-STAT abnormalities and other rearrangements using fluorescence in situ hybridisation (FISH). CRLF2 and ZNF384 rearrangements were detected in 17% and 7% of tested patients respectively. ABLclass fusions were notably absent. Next, single nucleotide polymorphism (SNP) arrays were performed to identify copy number abnormalities in patients with suitable material (n=83). Deletions were detected in IKZF1 (52%), CDKN2A/B (45%) and PAX5 (39%), as well as arm level events including del(9p) (21%), monosomy 7 (10%) and gain 1q (10%). Selected novel abnormalities were then validated using a customised sequencing approach. Recurrent novel deletions were confirmed in LEMD3, KDM6A and CXCR4, potentially contributing to leukaemogenesis. Separately, SNP arrays were performed on DNA from patients with low hypodiploidy or high hyperdiploidy (n=88) and machine-learning techniques were used to cluster cases based on log2 ratio data. Discrepancies between the cytogenetic-derived and SNP array-derived genetic subgroup were identified. A diagnostic classifier based on chromosomal log2 ratios was then designed using classification and regression tree analysis (CART). Finally, the mutational landscape of ALL in older adults was characterised in selected patients using exome sequencing (n=6) and a customised sequencing panel (n=30). Pathogenic variants were identified in TP53, NF1, JAK2 as well as members of the RAS signalling pathway, and were closely related to specific primary chromosomal abnormalities. This project has helped characterise the landscape of genetic prognostic biomarkers in older adults with ALL, and identified novel therapeutically actionable abnormalities meriting further assessment.

Published
2020

48. Continuous authentication on mobile devices

Author

Smith-Creasey, Max

Subjects
005.8, QA75 Electronic computers. Computer science
Abstract

Mobile devices are one of the most popular technologies in the world. Sales have increased yearly and almost all households have at least one. They are used for personal and business use, storing a plethora of private data. The data stored on these devices could be used for malicious purposes if obtained by attackers. Recently, traditional authentication techniques have been shown to have flaws that enable attackers to bypass them. Furthermore, traditional techniques only authenticate once, which enables attackers to steal an unlocked device and still maintain the ability to access private data. Researchers have proposed continuous authentication techniques to mitigate these issues, but there is work required to make such approaches both secure and usable. Most schemes currently are limited in modalities and lack the flexibility that can enhance both security and usability. This thesis focuses on advancing continuous authentication on mobile devices through providing new and novel mechanisms. In order to achieve this, the thesis proposes four novel contributions described in the following. The first contribution is a continuous authentication scheme based on a modality with little existing research: gesture typing. A novel set of six feature groupings are constructed to contain different types of features and capture the nuances word-gestures. The result shows the proposed technique performs better than other touchscreen-based features. Within this contribution, the activity performed during the typing sessions are also considered. The second contribution provides a scheme for continuous face authentication, including modules that current schemes were found to lack: liveness detection, contextual awareness and face tracking. Results show that each of these modules can provide significant benefits to security and usability (e.g.: detection of illumination or activity context allows a template from the same context to be selected for enhanced accuracy). The third contribution is a multi-modal behavioural authentication scheme using passively collected sensor data to authenticate users. A set of novel techniques for modelling the uncertainty in the scores obtained from the sensors is produced. The scores and the uncertainty in them can then be fused, using Dempster-Shafer theory. This scheme is shown to provide better accuracy than other commonly used fusion approaches due to the use of uncertainty. The last contribution joins the concepts of the previous contributions and employs touchscreen and face biometrics in an ensemble learning scheme to combine and enhance the biometrics. Furthermore, an adaptive threshold mechanism is introduced to compare the combined touchscreen and face score against. The threshold is adapted based on the score of the passively collected biometrics from the previous contribution. This approach is shown to yield enhanced and adaptable security and usability.

Published
2020

49. Kratosvirus quantuckense: the history and novelty of an algal bloom disrupting virus and a model for giant virus research

Author

Alexander R. Truchon, Emily E. Chase, Eric R. Gann, Mohammad Moniruzzaman, Brooke A. Creasey, Frank O. Aylward, Chuan Xiao, Christopher J. Gobler, and Steven W. Wilhelm

Subjects
harmful algal blooms, Nucleocytoviricota, strain heterogeneity, model system, marine microbiology, viral ecology, Microbiology, QR1-502
Abstract

Since the discovery of the first “giant virus,” particular attention has been paid toward isolating and culturing these large DNA viruses through Acanthamoeba spp. bait systems. While this method has allowed for the discovery of plenty novel viruses in the Nucleocytoviricota, environmental -omics-based analyses have shown that there is a wealth of diversity among this phylum, particularly in marine datasets. The prevalence of these viruses in metatranscriptomes points toward their ecological importance in nutrient turnover in our oceans and as such, in depth study into non-amoebal Nucleocytoviricota should be considered a focal point in viral ecology. In this review, we report on Kratosvirus quantuckense (née Aureococcus anophagefferens Virus), an algae-infecting virus of the Imitervirales. Current systems for study in the Nucleocytoviricota differ significantly from this virus and its relatives, and a litany of trade-offs within physiology, coding potential, and ecology compared to these other viruses reveal the importance of K. quantuckense. Herein, we review the research that has been performed on this virus as well as its potential as a model system for algal-virus interactions.

Published
2023
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