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3,591 results on '"Thomas, Philip A."'

108. Approximating Probabilistic Constraints for Surgery Scheduling Using Neural Networks

Author

Runarsson, Thomas Philip, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nicosia, Giuseppe, editor, Pardalos, Panos, editor, Umeton, Renato, editor, Giuffrida, Giovanni, editor, and Sciacca, Vincenzo, editor

Published
2019
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112. Erratum: "Strong coupling-induced frequency shifts of highly detuned photonic modes in multimode cavities" [J. Chem. Phys. 160, 204303 (2024)].

Author

Thomas, Philip A. and Barnes, William L.

Subjects
*OSCILLATOR strengths, *CHEMISTRY experiments
Abstract

This document is an erratum for an article titled "Strong coupling-induced frequency shifts of highly detuned photonic modes in multimode cavities" published in the Journal of Chemical Physics. The erratum corrects an equation in the original article and provides updated figures. The corrections do not change the conclusions of the original article, which found that strong coupling can have a measurable effect on highly detuned photonic modes. The authors encourage experimental investigations to test their predictions. [Extracted from the article]

Published
2024
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116. Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces

Author

Mahadevan, Sridhar, Liu, Bo, Thomas, Philip, Dabney, Will, Giguere, Steve, Jacek, Nicholas, Gemp, Ian, and Liu, Ji

Subjects
Computer Science - Learning
Abstract

In this paper, we set forth a new vision of reinforcement learning developed by us over the past few years, one that yields mathematically rigorous solutions to longstanding important questions that have remained unresolved: (i) how to design reliable, convergent, and robust reinforcement learning algorithms (ii) how to guarantee that reinforcement learning satisfies pre-specified "safety" guarantees, and remains in a stable region of the parameter space (iii) how to design "off-policy" temporal difference learning algorithms in a reliable and stable manner, and finally (iv) how to integrate the study of reinforcement learning into the rich theory of stochastic optimization. In this paper, we provide detailed answers to all these questions using the powerful framework of proximal operators. The key idea that emerges is the use of primal dual spaces connected through the use of a Legendre transform. This allows temporal difference updates to occur in dual spaces, allowing a variety of important technical advantages. The Legendre transform elegantly generalizes past algorithms for solving reinforcement learning problems, such as natural gradient methods, which we show relate closely to the previously unconnected framework of mirror descent methods. Equally importantly, proximal operator theory enables the systematic development of operator splitting methods that show how to safely and reliably decompose complex products of gradients that occur in recent variants of gradient-based temporal difference learning. This key technical innovation makes it possible to finally design "true" stochastic gradient methods for reinforcement learning. Finally, Legendre transforms enable a variety of other benefits, including modeling sparsity and domain geometry. Our work builds extensively on recent work on the convergence of saddle-point algorithms, and on the theory of monotone operators., Comment: 121 pages

Published
2014

120. Deep Preference Neural Network for Move Prediction in Board Games

Author

Runarsson, Thomas Philip, Barbosa, Simone Diniz Junqueira, Series Editor, Chen, Phoebe, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Cazenave, Tristan, editor, Winands, Mark H.M., editor, and Saffidine, Abdallah, editor

Published
2018
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123. Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Author

Baigent, Colin, Lasserson, Daniel, Sullivan, Frank, Carrie, Johanna, Rojas, Javier, Amoils, Shannon, Bamford, John, Armitage, Jane, Rinkel, Gabriel, Lowe, Gordon, Emberson, Jonathan, Innes, Karen, Dinsmore, Lynn, Drever, Jonathan, Williams, Carol, Perry, David, McGill, Connor, Buchanan, David, Walker, Allan, Hutchison, Aidan, Matthews, Christopher, Fraser, Ruth, McGrath, Aileen, Deary, Ann, Anderson, Rosemary, Walker, Pauli, Hansen, Christian, Parker, Richard, Rodriguez, Aryelly, Macleod, Malcolm, Gattringer, Thomas, Palmer, Jeb, Sakka, Eleni, Adil-Smith, Jennifer, Minks, David, Mitra, Dipayan, Bhatnagar, Priya, du Plessis, Johannes, Joshi, Yogish, Lerpiniere, Christine, O'Brien, Richard, Burgess, Seona, Mead, Gillian, Paulton, Ruth, Doubal, Fergus, McCormick, Katrina, Hunter, Neil, Taylor, Pat, Parakramawansha, Ruwan, Perry, Jack, Blair, Gordon, MacRaild, Allan, Parry-Jones, Adrian, Johnes, Mary, Lee, Stephanie, Shaw, Kelly Marie, Burger, Ilse, Punter, Martin, Ingham, Andrea, Perez, Jane, Naing, Zin, Morell, Jordi, Marsden, Tracy, Hall, Andrea, Marshall, Sally, Harrison, Louise, Jarapa, Rowilson, Wood, Edith, O'Loughlin, Victoria, Cohen, David, Davies, Silvie, Njoku, Kelechi, Mpelembue, Mushiya, Burgess, Laura, Licenik, Radim, Ngwako, Mmua, Nisar, Nabeela, Niranchanan, Rangah, Roganova, Tatjana, Bathula, Rajaram, Devine, Joseph, David, Anette, Oshodi, Anne, Guo, Fenglin, Owoyele, Emmanuelle, Sukdeo, Varthi, Ballantine, Robert, Abbdul-saheb, Mudhar, Chamberlain, Angela, Chandrakumar, Aberami, Poku, Philip, Harkness, Kirsty, Blank, Catrin, Richards, Emma, Ali, Ali, Kibutu, Faith, Balitska, Olesia, Birchall, Kathryn, Bayliss, Pauline, Doyle, Clare, Stocks, Kathy, Majis, Arshad, Howe, Jo, Kamara, Christine, Barron, Luke, Maatouk, Ahmad, Lindert, Ralf, Dakin, Katy, Redgrave, Jessica, Bhaskaran, Biju, Salih, Isam, Kelly, Debs, Szabo, Susan, Tomlin, Dawn, Bearne, Helen, Buxton, Jean, Fitzell, Pauline, Ayres, Georgina, Saulat, Afaq, Horan, Kathleen, Garfield-Smith, Joanne, Bhakri, Harbens, Guyler, Paul, Sinha, Devesh, Loganathan, Thayalini, Siddiqui, Amber, Siddiqui, Anwer, Coward, Lucy, Kunhunny, Swapna, Tysoe, Sharon, Orath Prabakaran, Rajalakshmi, Kelavkar, Shyam, Rashmi, Sindhu, Ngo, David, Ng, Kheng Xiong, Menon, Nisha, Shah, Sweni, Barber, Mark, Esson, Derek, Brodie, Fiona, Anjum, Talat, Wani, Mushtaq, Krishnan, Manju, Quinn, Leanne, Spencer, Jayne, Jones, Terry, Thompson-Jones, Helen, Dacey, Lynne, Chenna, Srikanth, Storton, Sharon, Thomas, Sarah, Beaty, Teresa, Treadwell, Shelley, Davies, Caroline, Tucker, Susan, Connor, Lynda, Slade, Peter, Gainard, Glyn, Muddegowda, Girish, Sanyal, Ranjan, Remegoso, Alda, Abano, Nenette, Causley, Chelsea, Carpio, Racquel, Stevens, Stephanie, Butler, Adrian, Varquez, Resti, Denic, Hayley, Alipio, Francis, Moores, Andrew, Barry, Adrian, Maguire, Holly, Grocott, Jeanette, Finney, Kay, Lyjko, Sue, Roffe, Christine, Hiden, Joanne, Ferdinand, Phillip, Cvoro, Vera, Ullah, Khalil, Chapman, Nicola, Couser, Mandy, Pound, Susan, Mcauley, Sean, Raghunathan, Senthil, Shelton, Faye, Hedstrom, Amanda, Godfrey, Margi, Havard, Diane, Buck, Amanda, Krishnan, Kailash, Gilzeane, Nicola, Roffe, Jack, Clarke, Judith, Whittamore, Katherine, Sheikh, Saima, Sprigg, Nikola, Keshvara, Rekha, Jordan, Carla, Jackson, Benjamin, Wilkes, Gwendoline, Appleton, Jason, Law, Zhe, Matias, Oliver, Vasileiadis, Evangelos, Mason, Cathy, Parry, Anthea, Landers, Geraldine, Holden, Melinda, Aweid, Basaam, Rashed, Khalid, Balian, Linda, Vickers, Carinna, Keeling, Elizabeth, Board, Sarah, Allison, Joanna, Buckley, Clare, Williams-Yesson, Barbara, Board, Joanne, Pitt-Kerby, Tressy, Tanate, Alfonso, Wood, Diane, Kini, Manohar, Chadha, Dinesh, Walstow, Deborah, Fong, Rosanna, Luder, Robert, Adesina, Tolu, Gallagher, Jill, Bridger, Hayley, Murali, Elodie, Bhargava, Maneesh, van Someren, Chloe, Harrington, Frances, Mate, Abhijit, James, Ali, Courtauld, Gillian, Schofield, Christine, Adie, Katja, Lucas, Linda, Bond, Kirsty, Maund, Bev, Ellis, Sam, Mudd, Paul, James, Martin, Keenan, Samantha, Bowring, Angela, Cageao, Julie, Kingwell, Hayley, Roughan, Caroline, Hemsley, Anthony, Sword, Jane, Strain, David, Miller, Keniesha, Goff, Anita, Gupwell, Karin, Thorpe, Kevin, Emsley, Hedley, Punekar, Shuja, McLoughlin, Alison, Sultan, Sulaiman, Gregory, Bindu, Raj, Sonia, Doyle, Donna, Muir, Keith, Smith, Wilma, Welch, Angela, Moreton, Fiona, Cheripelli, Bharath Kumar, El Tawil, Salwa, Kalladka, Dheeraj, Huang, Xuya, Day, Nicola, Ramachandran, Sankaranarayanan, Crosbie, Caroline, Elliot, Jennifer, Rudd, Tony, Marks, Katherine, Bhalla, Ajay, Birns, Jonathan, Kullane, Sagal, Weir, Nic, Allen, Christopher, Pressly, Vanessa, Crawford, Pam, Battersby-Wood, Emma, Blades, Alex, Egerton, Shuna, Walters, Ashleigh, Evans, Sue, Marigold, James Richard, Smith, Fiona, Howard, Gabriella, Gartrell, Imogen, Smith, Simon, Creeden, Robyn, Cox, Chloe, Boxall, Cherish, Hewitt, Jonathan, Nott, Claire, Sarah, Procter, Whiteman, Jessica, Buckle, Steve, Wallace, Rebecca, Mardania, Rina, Gray, Jane, Triscott, Claire, Nair, Anand, Greig, Jill, Rana, Pratap, Robinson, Matthew, Alam, Mohammad Irfan, Werring, David, Wilson, Duncan, Watchurst, Caroline, Brezitski, Maria, Crook, Luci, Jones, Ifan, Banaras, Azra, Patel, Krishna, Erande, Renuka, Hogan, Caroline, Hostettler, Isabel, Ashton, Amy, Feerick, Shez, Francia, Nina, Oji, Nnebuife, Elliott, Emma, Al-Mayhani, Talal, Dennis, Martin, Sudlow, Cathie, Whiteley, William, Al-Shahi Salman, Rustam, Dutta, Dipankar, Brown, Pauline, Ward, Deborah, Davis, Fiona, Turfrey, Jennifer, Hughes, Chloe, Collins, Kayleigh, Bakawala, Rehana, O'Connell, Susan, Glass, Jon, Broughton, David, Tryambake, Dinesh, Dixon, Lynn, Chapman, Kath, Young, Andrew, Bergin, Adrian, Sigsworth, Andrew, Manoj, Aravind, Fletcher, Glyn, Lopez, Paula, Cox, Penelope, Wilkinson, Mark, Fitzsimmons, Paul, Sharma, Nikhil, Choulerton, James, Button, Denise, Dow, Lindsey, Gbadamoshi, Lukuman, Avis, Joanne, Madigan, Barbara, McCann, Stephanie, Shaw, Louise, Howcroft, Deborah, Lucas, Suzanne, Stone, Andrew, Cluckie, Gillian, Lovelock, Caroline, Clarke, Brian, Chopra, Neha, Clarke, Natasha, Patel, Bhavini, Kennedy, Kate, Williams, Rebecca, Blight, Adrian, O'Reilly, Joanna, Orefo, Chukwuka, Dayal, Nilofer, Ghatala, Rita, Adedoyin, Temi, Watson, Fran, Trippier, Sarah, Choy, Lillian, Moynihan, Barry, Khan, Usman, Jones, Val, Jeyaraj, Naomi, Kerin, Lourda, Thavanesan, Kamy, Tiwari, Divya, Cox, Chantel, Ljubez, Anja, Tucker, Laura, Iqbal, Arshi, Bagnall, Caroline, Keltos, Marketa, Roberts, Josh, Jupp, Becky, Ovington, Catherine, Rogers, Emily, David, Owen, Bell, Jo, Longland, Barbara, Hann, Gail, Cooper, Martin, Nasar, Mohammad, Rajapakse, Anoja, Wynter, Inez, Anwar, Ijaz, Skinner, Helen, Nozedar, Tarn, McArdle, Damian, Kumar, Balakrishna, Crawford, Susan, Annamalai, Arunkumar, Ramshaw, Alex, Holmes, Clare, Caine, Sarah, Osborn, Mairead, Dodd, Emily, Murphy, Peter, Devitt, Nicola, Baker, Pauline, Steele, Amy, Guthrie, Lucy Belle, Clarke, Samantha, Hassan, Ahamad, Waugh, Dean, Veraque, Emelda, Makawa, Linetty, Kambafwile, Mary, Randall, Marc, Papavasileiou, Vasileios, Cullen, Claire, Peters, Jenny, Thant, Hlaing, Ingram, Tanya, Zoe, Mellor, Durairaj, Ramesh, Harrison, Melanie, Stevenson, Sarah, Shackcloth, Daniela, Ewing, Jordan, Sutton, Victoria, McCarron, Mark, McKee, Jacqueline, Doherty, Mandy, McVerry, Ferghal, Blair, Caroline, MacLeod, Mary, Irvine, Janice, Gow, Heather, Furnace, Jacqueline, Joyson, Anu, Jagpal, Baljit, Ross, Sarah, Klaasen, Katrina, Nelson, Sandra, Clarke, Rebecca, Crouch, Nichola, MacLennan, Beverly, Taylor, Vicky, Epstein, Daniel, Shukla, Avani, Krishnamurthy, Vinodh, Nicholas, Paul, Qureshi, Sammie, Webber, Adam, Penge, Justin, Ramadan, Hawraman, Maguire, Stuart, Patterson, Chris, Bellfield, Ruth, Hairsine, Brigid, Stewart, Kelvin, Hooley, Michaela, Quinn, Outi, Richard, Bella, Moseley, Sally, Edwards, Mandy, Lawson, Heidi, Tayler, Michelle, Pai, Yogish, Dhakal, Mahesh, Esisi, Bernard, Dima, Sofia, Smith, Gemma Marie, Garside, Mark, Naeem, Muhammad, Baliga, Vidya, Rogers, Gill, Brown, Ellen, Bruce, David, Hayman, Rachel, Clayton, Susan, Gamble, Ed, Grue, Rebecca, Charles, Bethan, Hague, Adam, Blane, Sujata, Lambert, Caroline, Chaudhry, Afnan, Harrison, Thomas, Saastamoinen, Kari, Hove, Dionne, Howaniec, Laura, Grimwood, Gemma, Redjep, Ozlem, Humphries, Fiona, Argandona, Lucia, Cuenoud, Larissa, Erumere, Esther, Amlani, Sageet, Auld, Grace, Salek-Haddadi, Afraim, Schulz, Ursula, Kennedy, James, Ford, Gary, Mathieson, Philip, Reckless, Ian, Teal, Rachel, Lenti, Giulia, Harston, George, O'Brien, Eoin, Mcgee, Joanne, Mitchell, Jennifer, Amis, Elaine, Handley, Dominic, Kelly, Siobhan, Zachariah, George, Francis, Jobbin, Crisp, Sarah, Sesay, Juliana, Finlay, Sarah, Hayhoe, Helen, Hannon, Niamh, Hughes, Tom, Morse, Bethan, De Berker, Henry, Tallantyre, Emma, Osman, Ahmed, White, Susan, Schwarz, Stefan, Jelley, Benjamin, Yadava, Rajendra, Azhar, Khalid, Reddan, Julie, Sangombe, Mirriam, Stafford, Samantha, Fotherby, Ken, Morgan, Debbie, Baig, Farrukh, Jennings-Preece, Karla, Butler, Donna, Ahmad, Nasar, Willberry, Angela, Stevens, Angela, Rai, Baljinder, Siddegowda, Prasad, Howard, Peter, Hyatt, Lisa, Dobson, Tracey, Jarrett, David, Ponnambath, Suheil, Tandy, Jane, Harrington-Davies, Yasmin, Butler, Rebecca, James, Claire, Valentine, Stacey, Suttling, Anne, Langhorne, Peter, Kerr, Gillian, Wright, Fiona, Graham, Ruth, McAlpine, Christine, Iqbal, Mohammad Shahzad, Humphreys, Louise, Pasco, Kath, Balazikova, Olga, Nasim, Ashraf, Peixoto, Cassilda, Gallagher, Louise, Shahmehri, Shahrzad, Ghosh, Sandip, Barrie, Elizabeth, Gilmour, Danielle, Henry, Margo, Webb, Tom, Cowie, Linda, Rudenko, Hannah, McDonald, Shanni, Schumacher, Natasha, Walker, Susannah, Cosier, Tracey, Verrion, Anna, Beranova, Eva, Thomson, Audrey, Venter, Marius, Kar, Arindam, Mashate, Sheila, Harvey, Kirsten, Gardener, Léjeune, Nguyen, Vinh, Halse, Omid, Geraghty, Olivia, Hazel, Beth, Wilding, Peter, Tilley, Victoria, Cassidy, Tim, McClelland, Beverley, Bokhari, Maria, England, Timothy, Maddula, Mohana, Donnelly, Richard, Findlay, Paul, Macaden, Ashish, Shread, Ian, Barr, Charlotte, Mohd Nor, Azlisham, Brown, Claire, Persad, Nicola, Eglinton, Charlotte, Weinling, Marie, Hyams, Benjamin, Shah, Alex, Baker, John, Byrne, Anthony, McGhee, Caroline, Smart, Amanda, Copeland, Claire, Carpenter, Michael, Walker, Marion, Davey, Richard, Needle, Ann, Fathima, Razik, Bateman, Gavin, Datta, Prabal, Stanners, Andrew, Jackson, Linda, Ball, Julie, Davis, Michelle, Atkinson, Natalie, Fawcett, Michelle, Thompson, Teresa, Guy, Helen, Hogg, Valerie, Hays, Carole, Woodward, Stephen, Haque, Mohammad, Hakim, Eluzai, Symonds, Stuart, Maanoosi, Mehran, Herman, Jane, Black, Toby, Miriam, Skelton, Clarke, Caroline, Anthony, Alpha, Tribbeck, Michele, Cronin, Julie, Mead, Denise, Fennelly, Ruth, McIlmoyle, James, Dickinson, Christina, Jeffs, Carol, Anwar, Sajjad, Howard, Joanne, Jones, Kirsty, Dhar, Saikat, Clay, Caroline, Siddiq, Muhammad, Ivatts, Simone, Baird, Yolanda, Sally, Moore, Amey, Isobel, Newton, Sophie, Clayton-Evans, Lisa, Chadbourn, Indra, Rayessa, Rayessa, Naylor, Charde, Rodgers, Alicia, Wilson, Lisa, Wilson, Sarah, Clarkson, Emma, Davies, Ruth, Owings, Paula, Sangster, Graeme, Gott, Valerie, Little, Victoria, Weir, Pauline, Cherian, Suja, Jose, Deepa, Moroney, Helen, Downham, Susan, Dodd, Angela, Vettimootal Johnson, Venetia, Codd, Laura, Robinson, Naomi, Ahmed, Ashraf, Albazzaz, Mo, Johnson, Sharon, Denniss, Carol, Cunningham, Mishell, Zahoor, Tajammal, Webster, Timothy, Leason, Sandra, Haider, Syed, Chatterjee, Kausic, Nallasivan, Arumugam, Perkins, Charlotte, Seagrave, Samantha, Jenkins, Colin, Price, Fiona, Hughes, Claire, Mercer, Lily, Hussain, Malik, Brown, Sarah, Harvey, Miriam, Homan, Jane, Khan, Mohammad, Whiting, Robert, Foote, Leanne, Hunt, Nicholas, Durman, Helen, Brotherton, Lucy, Foot, Jayne, Pawley, Corinne, Foster, Eliza, Whitcher, Alison, Metcalf, Kneale, Jagger, Jenny, McDonald, Susan, Waterfield, Kelly, Sutton, Patrick, Shinh, Naval, Anversha, Ajmal, Ravenhill, Garth, Greenwood, Richard, Saada, Janak, Wiltshire, Alison, Perfitt, Rebekah, Andole, Sreeman, Gadapa, Naveen, Dunne, Karen, Krommyda, Magdalini, Burssens, Evelyne, King, Sam, Plewa, Catherine, Smyth, Nigel, Wilson, Jenny, Giallombardo, Elio, Sykes, Lucy, Kumar, Pradeep, Barker, James, Huggett, Isabel, Dunn, Linda, Culmsee, Charlotte, Thomas, Philip, Myint, Min, Brew, Helen, Majmudar, Nikhil, OConnell, Janice, Bunea, George, Fox, Charlotte, Gulliver, Diane, Smith, Andrew, Mokoena, Betty, Sattar, Naweed, Krishnamurthy, Ramesh, Osborne, Emily, Wilson, David, Wroath, Belinda, Dynan, Kevin, Power, Michael, Thompson, Susan, Adell, Victoria, Orugun, Enoch, Poultney, Una, Glover, Rachel, Crowther, Hannah, Thornthwaite, Sarah, Wiggam, Ivan, Wallace, Aine, Kerr, Enda, Fulton, Ailsa, Hunter, Annemarie, Tauro, Suzanne, Cuddy, Sarah, Mangion, David, Hardwick, Anne, Markova, Skarlet, Lawrence, Tara, Constantin, Carmen, Fletcher, Jo, Thomas, Isobel, Pettitt, Kerry, Sekaran, Lakshmanan, Tate, Margaret, Bharaj, Kiranjit, Simon, Rohan, Justin, Frances, Sethuraman, Sakthivel, Phiri, Duke, Mohammed, Niaz, Chauhan, Meena, Elfandi, Khaled, Khan, Uzma, Eveson, David, Mistri, Amit, Manning, Lisa, Khan, Shagufta, Patel, Champa, Moqsith, Mohammed, Sattar, Saira, Lam, Man Yee, Musarrat, Kashif, Stephens, Claire, Kalathil, Latheef, Miller, Richard, Salehin, Maqsud, Gautam, Nikki, Bailey, Duncan, Amor, Kelly, Meir, Julie, Nicolson, Anne, Imam, Javed, Wood, Lisa, White, Julie, Sajid, Mahmud, Ghaly, George, Ball, Margaret, Gascoyne, Rachel, Proeschel, Harald, Sharpe, Simon, Horton, Sarah, Beaves, Emily, Jones, Stephanie, Yip, Brigitte, Bell, Murdina, MacLiver, Linda, MacInnes, Brian, Sims, Don, Hurley, Jennifer, Willmot, Mark, Sutton, Claire, Littleton, Edward, Maiden, Susan, Jones, Rachael, Cunningham, James, Green, Carole, Bates, Michelle, Shekhar, Raj, Gilham, Ellie, Ahmed, Iman, Crown, Rachel, Fuller, Tracy, Goorah, Neetish, Bell, Angela, Kelly, Christine, Singh, Arun, Walford, Jamie, Tomlinson, Benjamin, Patel, Farzana, Duberley, Stephen, Kane, Ingrid, Rajkumar, Chakravarthi, Gaylard, Jane, Breeds, Joanna, Gainsborough, Nicola, Pitt-Ford, Alexandra, Barbon, Emma, Latter, Laura, Thompson, Philip, Hervey, Simon, Krishnamoorthy, Shrivakumar, Vassallo, Joseph, Walter, Deborah, Cochrane, Helen, Srinivasan, Meena, Campbell, Robert, Donaldson, Denise, Motherwell, Nichola, Hurford, Frances, Mukherjee, Indranil, Kenton, Antony, Nyabadza, Sheila, Martin, Irene, Hunt, Benjamin, Hassan, Hardi, O'Toole, Sarah, Dallol, Bander, Putterill, Janet, Jha, Ratneshwari, Gallifent, Rachel, Kakar, Puneet, Pusalkar, Aparna, Chan, kelly, Dangri, Puneet, Beadle, Hannah, Cook, Angela, Crabtree, Karen, Subramonian, Santhosh, Owusu-Agyei, Peter, Temple, Natalie, Butterworth-Cowin, Nicola, Ragab, Suzanne, Knops, Kerstin, Jinks, Emma, Dickson, Christine, Gleave, Laura, Dube, Judith, Leggett, Jacqui, Garcia, Tatiana, Ispoglou, Sissy, Evans, Rachel, Ankolekar, Sandeep, Hayes, Anne, Ni, Hlaing, Rahman, Bithi, Milligan, Josette, Graham, Carol, Jose, Josin, Keegan, Breffni, Kelly, Jim, Dewar, Richard, White, James, Thomas, Kelly, Minks, David P, Rodrigues, Mark A, du Plessis, Johann C, Dennis, Martin S, Murray, Gordon D, Newby, David E, Sandercock, Peter A G, Stephen, Jacqueline, Sudlow, Cathie L M, Werring, David J, Whiteley, William N, Wardlaw, Joanna M, and White, Philip M

Published
2019
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124. Bounding the Likelihood of Exceeding Ward Capacity in Stochastic Surgery Scheduling

Author

Asgeir Orn Sigurpalsson, Thomas Philip Runarsson, and Rognvaldur Johann Saemundsson

Subjects
surgery scheduling, uncertainty, downstream resource, Monte Carlo sampling, mixed integer programming, robust optimization, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

The stochastic high-patient-throughput surgery scheduling problem under a limited number of staffed ward beds is addressed in this paper. This work proposes a novel way to minimize the risk of last-minute cancellations by bounding the likelihood of exceeding the staffed ward beds. Given historical data, it is possible to determine an empirical distribution for the length of stay in the ward. Then, for any given combinations of patients, one can estimate the likelihood of exceeding the number of staffed ward beds using Monte Carlo sampling. As these ward patient combinations grow exponentially, an alternative, more efficient, worst-case robust ward optimization model is compared. An extensive data set was collected from the National University Hospital of Iceland for computational experiments, and the models were compared with actual scheduling data. The models proposed achieve high quality solutions in terms of overtime and risk of overflow in the ward.

Published
2022
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125. CFTR modulator theratyping: Current status, gaps and future directions

Author

Clancy, John Paul, Cotton, Calvin U., Donaldson, Scott H., Solomon, George M., VanDevanter, Donald R., Boyle, Michael P., Gentzsch, Martina, Nick, Jerry A., Illek, Beate, Wallenburg, John C., Sorscher, Eric J., Amaral, Margarida D., Beekman, Jeffrey M., Naren, Anjaparavanda P., Bridges, Robert J., Thomas, Philip J., Cutting, Garry, Rowe, Steven, Durmowicz, Anthony G., Mense, Martin, Boeck, Kris D., Skach, William, Penland, Christopher, Joseloff, Elizabeth, Bihler, Hermann, Mahoney, John, Borowitz, Drucy, and Tuggle, Katherine L.

Published
2019
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126. Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling

Author

Runarsson, Thomas Philip, Schoenauer, Marc, and Sebag, Michèle

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Greedy heuristics may be attuned by looking ahead for each possible choice, in an approach called the rollout or Pilot method. These methods may be seen as meta-heuristics that can enhance (any) heuristic solution, by repetitively modifying a master solution: similarly to what is done in game tree search, better choices are identified using lookahead, based on solutions obtained by repeatedly using a greedy heuristic. This paper first illustrates how the Pilot method improves upon some simple well known dispatch heuristics for the job-shop scheduling problem. The Pilot method is then shown to be a special case of the more recent Monte Carlo Tree Search (MCTS) methods: Unlike the Pilot method, MCTS methods use random completion of partial solutions to identify promising branches of the tree. The Pilot method and a simple version of MCTS, using the $\varepsilon$-greedy exploration paradigms, are then compared within the same framework, consisting of 300 scheduling problems of varying sizes with fixed-budget of rollouts. Results demonstrate that MCTS reaches better or same results as the Pilot methods in this context., Comment: Learning and Intelligent OptimizatioN (LION'6) 7219 (2012)

Published
2012

128. How to create 'buzz' without being branded a failure.

Author

Thomas, Philip

Subjects
PRODUCT failure, CONSUMER behavior, MARKETING, SENIOR leadership teams, LANGUAGE models, CHIEF marketing officers
Abstract

The article focuses on the challenges businesses face in navigating a divisive cultural and political landscape, exemplified by Apple's controversial ad for the new iPad Pro, emphasizing the delicate balance between generating buzz and avoiding backlash. It discusses the need for organizations to carefully calibrate their messaging, prioritize product superiority over purpose-led communications.

Published
2024

129. An alternative to Sage's worst-case scenario

Author

Thomas, Philip

Subjects
United Kingdom -- Health aspects, Epidemics -- Control -- Patient outcomes -- United Kingdom, Company distribution practices, General interest, News, opinion and commentary, Political science
Abstract

Barely six weeks after it was first discovered in Britain, the Omicron variant has changed everything. Cases have soared far beyond records made in the first wave. Hospital admissions are [...]

Published
2022

130. Paralogous Radiations of PIN Proteins with Multiple Origins of Noncanonical PIN Structure

Author

Bennett, Tom, Brockington, Samuel F, Rothfels, Carl, Graham, Sean W, Stevenson, Dennis, Kutchan, Toni, Rolf, Megan, Thomas, Philip, Wong, Gane Ka-Shu, Leyser, Ottoline, Glover, Beverley J, and Harrison, C Jill

Subjects
Biotechnology, Generic health relevance, Amino Acid Sequence, Conserved Sequence, Evolution, Molecular, Gene Duplication, Indoleacetic Acids, Models, Molecular, Multigene Family, Phylogeny, Plant Proteins, Plants, auxin, auxin transport, PIN protein, plant evolution, phylogeny, protein structure, Biochemistry and Cell Biology, Evolutionary Biology, Genetics
Abstract

The plant hormone auxin is a conserved regulator of development which has been implicated in the generation of morphological novelty. PIN-FORMED1 (PIN) auxin efflux carriers are central to auxin function by regulating its distribution. PIN family members have divergent structures and cellular localizations, but the origin and evolutionary significance of this variation is unresolved. To characterize PIN family evolution, we have undertaken phylogenetic and structural analyses with a massive increase in taxon sampling over previous studies. Our phylogeny shows that following the divergence of the bryophyte and lycophyte lineages, two deep duplication events gave rise to three distinct lineages of PIN proteins in euphyllophytes. Subsequent independent radiations within each of these lineages were taxonomically asymmetric, giving rise to at least 21 clades of PIN proteins, of which 15 are revealed here for the first time. Although most PIN protein clades share a conserved canonical structure with a modular central loop domain, a small number of noncanonical clades dispersed across the phylogeny have highly divergent protein structure. We propose that PIN proteins underwent sub- and neofunctionalization with substantial modification to protein structure throughout plant evolution. Our results have important implications for plant evolution as they suggest that structurally divergent PIN proteins that arose in paralogous radiations contributed to the convergent evolution of organ systems in different land plant lineages.

Published
2014

131. Long-term outcomes of definitive radiation with volumetric modulated arc therapy and concurrent chemotherapy for squamous cell carcinoma of the anus in a regional Australian cancer centre.

Author

Hsieh, Michael Ti, Shakespeare, Thomas Philip, Winkley, Lauren, Goonetilleke, Daniel, Shaun Zheng Liang Yap, and Mohd Tahir, Abdul Rahim

Subjects
*VOLUMETRIC-modulated arc therapy, *SQUAMOUS cell carcinoma, *OROPHARYNX, *ANUS, *OVERALL survival, *SURVIVAL rate
Abstract

Introduction: Concurrent chemoradiotherapy is the standard of care in the curative intent treatment of squamous cell carcinoma (SCC) of the anus. Volumetric arc therapy (VMAT) is a highly conformal radiation therapy technique that has been implemented to reduce toxicity for these patients. However, there are few reports evaluating the long-term outcomes of VMAT. Thus, we evaluated the survival and toxicity outcomes of anal cancer patients treated in our regional cancer centre undergoing curative intent chemoradiotherapy using VMAT and following the Australian EviQ guidelines. Methods: All consecutive patients treated with the VMAT technique for curative-intent definitive chemoradiotherapy for anal SCC at our institution from 2013 until 2022 were retrospectively reviewed for survival and toxicity outcomes. Kaplan–Meier estimates of locoregional control, distant metastasisfree survival, disease-free survival, anal cancer-specific survival and overall survival were obtained. Results: In total, 44 patients were analysed. The median follow-up was 48.9 months (Range 7.8–107). 97.7% of patients completed the prescribed radiation therapy and 88.6% chemotherapy. Five patients (11.4%) recurred. Four (9.1%) had isolated local failures, and one (2.3%) had an isolated distant failure. There were no regional nodal failures. The Kaplan–Meier estimates for locoregional control, distant metastasis-free survival, disease-free survival, anal cancer-specific survival and overall survival were 90.3%, 97.7%, 88.1%, 97.1% and 87% at 3 years, and 90.3%, 97.7%, 88.1%, 93.0% and 72.3% at 5 years, respectively. Acute grade 3 genitourinary (GU), gastrointestinal (GI) and skin toxicities occurred in 2.2%, 6.8% and 13.6% of patients, respectively. There were no acute grade 4 toxicities. Late grade 2 GU and GI toxicities occurred in 6.8% and 11.3% of patients, respectively. There were no late grade 3 or 4 toxicities or treatment-related deaths. The 5 -year colostomy-free survival rate was 86.4%. Conclusion: Outcomes for anal SCC after definitive chemoradiotherapy using VMAT in our regional cancer centre results in low rates of grade 3/4 toxicity, high rates of organ preservation and excellent survival outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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146. Comics, crime, and the moral self : an interdisciplinary study of criminal identity

Author

Giddens, Thomas Philip, Skinner, Stephen, Coyle, Sean, and Richardson, Janice

Subjects
364, criminal responsibility, law and aesthetics, legal philosophy, moral philosophy, law and literature, comics, Watchmen, Alan Moore, legal theory, Immanuel Kant, feminist philosophy, metaphysics, masculinity, Friedrich Nietzsche, identity, self, graphic fiction
Abstract

An ethical understanding of responsibility should entail a richly qualitative comprehension of the links between embodied, unique individuals and their lived realities of behaviour. Criminal responsibility theory broadly adheres to ‘rational choice’ models of the moral self which subsume individuals’ emotionally embodied dimensions under the general direction of their rational will and abstracts their behaviour from corporeal reality. Linking individuals with their behaviour based only on such understandings of ‘rational choice’ and abstract descriptions of behaviour overlooks the phenomenological dimensions of that behaviour and thus its moral significance as a lived experience. To overcome this ethical shortcoming, engagement with the aesthetic as an alternative discourse can help articulate the ‘excessive’ nature of lived reality and its relationship with ‘orthodox’ knowledge; fittingly, the comics form involves interaction of rational, non-rational, linguistic, and non-linguistic dimensions, modelling the limits of conceptual thought in relation to complex reality. Rational choice is predicated upon a split between a contextually embedded self and an abstractly autonomous self. Analysis of the graphic novel Watchmen contends that prioritisation of rational autonomy over sensual experience is symptomatic of a ‘rational surface’ that turns away from the indeterminate ‘chaos’ of complex reality (the unstructured universe), instead maintaining the power of rational and linguistic concepts to order the world. This ‘rational surface’ is maintained by masking that which threatens its stability: the chaos of the infinite difference of living individuals. These epistemological foundations are reconfigured, via Watchmen, enabling engagement beyond the ‘rational surface’ by accepting the generative potential of this living chaos and calling for models of criminal identity that are ‘restless’, acknowledging the unique, shifting nature of individuals, and not tending towards ‘complete’ or stable concepts of the self-as-responsible. As part of the aesthetic methodology of this reconfiguration, a radical extension of legal theory’s analytical canon is developed.

Published
2011

148. Eighty Years of Mycopathologia: A Retrospective Analysis of Progress Made in Understanding Human and Animal Fungal Pathogens

Author

Chaturvedi, Vishnu, Bouchara, Jean-Philippe, Hagen, Ferry, Alastruey-Izquierdo, Ana, Badali, Hamid, Bocca, Anamelia Lorenzetti, Cano-Lira, Jose F., Cao, Cunwei, Chaturvedi, Sudha, Chotirmall, Sanjay H., van Diepeningen, Anne D., Gangneux, Jean-Pierre, Guinea, Jesus, de Hoog, Sybren, Ilkit, Macit, Kano, Rui, Liu, Weida, Martinez-Rossi, Nilce M., de Souza Carvalho Melhem, Marcia, Ono, Mario Augusto, Ran, Yuping, Ranque, Stephane, de Almeida Soares, Celia Maria, Sugita, Takashi, Thomas, Philip A., Vecchiarelli, Anna, Wengenack, Nancy L., Woo, Patrick C. Y., Xu, Jianping, and Zancope-Oliveira, Rosely M.

Published
2018
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150. Constructing monogenic quasigroups with specified properties

Author

Cowhig, Thomas Philip

Subjects
512
Abstract

A monogenic quasigroup is one generated by a single element, and as such is not just non-associative but in general non power associative. We show that monogenic quasigroups or loops with various specified characteristics can exist, by demonstrating constructions and by giving examples. This often involves completing an associated partial latin square, or demonstrating that a completion is possible. It is shown that for every order n ≥ 4 there are monogenic quasigroups generated by each of any m ≤ n of their elements, and similarly for monogenic loops (n ≥ 6 , 2 ≤ m ≤ n −1). Any element in a quasigroup must have its powers unambiguous and distinct (called good) up to some degree j ≥ 2, and unambiguous but not necessarily distinct (called clear) up to some degree k ≥ j. The conditions for the existence of a quasigroup of order n having a generator with a good j th and clear k th power are determined. A monogenic quasigroup may be said to be g-good if every element has a good g th power. An algorithm for finding examples based on diagonally cyclic latin squares is developed, and a computer program used to find comprehensive solutions for g ≤ 16 and odd orders n ≤ 95 (and patchily to g = 17, n = 111), with particular reference to the lowest n affording a solution for any g. A maximally non power associative quasigroup has every element with all its bracketings up to some length distinct. A diagonally cyclic quasigroup of order 23 with all 23 products of length ≤ 5 distinct for every element is displayed,as is one of order 63 with 63 of the 65 bracketings up to length 6 distinct for each element. Properties of direct products of monogenic quasigroups, and the significance of parastrophy and isotopy, are considered. The existence or not of monogenic versions of particular types of quasigroups and loops (for example, totally symmetric, inverse property, entropic, Bol and Moufang, among others) is also explored.

Published
2009

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