Search

Your search keyword '"Driscoll M"' showing total 952 results
Start Over Author "Driscoll M"
952 results on '"Driscoll M"'

2. Indigo: A domain-specific language for fast, portable image reconstruction

Author

Driscoll, M, Brock, B, Ong, F, Tamir, J, Liu, HY, Lustig, M, Fox, A, and Yelick, K

Abstract

Linear operators used in iterative methods like conjugate gradient have typically been implemented either as ''matrix-driven'' subroutines backed by explicit sparse or dense matrices, or as ''matrix-free'' subroutines that implement specific linear operations directly (e.g. FFTs). The matrix-driven approach is generally more portable because it can target widely-Available BLAS libraries, but it can be inefficient in terms of time and space complexity. In contrast, the matrix-free approach is more performant because it leverages structure in operations, but it requires each operator be re-implemented on each new platform. To increase performance and portability, we propose a hybrid approach that represents linear operators as expression trees. Leaf nodes in the tree are either matrix-free or matrix-driven operators, and interior nodes represent mathematical compositions (sums, products, transposes) or structural compositions (stacks, block diagonals, etc.) of the leaf operators. This representation enables expert-guided reordering and fusion transformations that can improve performance or reduce memory pressure. We implement our approach in a domain-specific language called Indigo. We assess Indigo on image reconstruction problems arising in four application areas: magnetic resonance imaging, ptychography, magnetic particle imaging, and fluorescent microscopy. We give performance results from vendor BLAS libraries, and we introduce specializations to Sparse BLAS routines that achieve near-Roofline performance on multi-core, many-core, and GPU systems.

Published
2018

3. Snowflake: A lightweight portable stencil DSL

Author

Zhang, N, Driscoll, M, Markley, C, Williams, S, Basu, P, and Fox, A

Subjects
Scientific Computing, Domain-Specific Language, Python, GPU, Multicore
Abstract

Stencil computations are not well optimized by general-purpose production compilers and the increased use of multicore, manycore, and accelerator-based systems makes the optimization problem even more challenging. In this paper we present Snowflake, a Domain Specific Language (DSL) for stencils that uses a 'micro-compiler' approach, i.e., small, focused, domain-specific code generators. The approach is similar to that used in image processing stencils, but Snowflake handles the much more complex stencils that arise in scientific computing, including complex boundary conditions, higher-order operators (larger stencils), higher dimensions, variable coefficients, non-unit-stride iteration spaces, and multiple input or output meshes. Snowflake is embedded in the Python language, allowing it to interoperate with popular scientific tools like SciPy and iPython; it also takes advantage of built-in Python libraries for powerful dependence analysis as part of a just-in-time compiler. We demonstrate the power of the Snowflake language and the micro-compiler approach with a complex scientific benchmark, HPGMG, that exercises the generality of stencil support in Snowflake. By generating OpenMP comparable to, and OpenCL within a factor of 2x of hand-optimized HPGMG, Snowflake demonstrates that a micro-compiler can support diverse processor architectures and is performance-competitive whilst preserving a high-level Python implementation.

Published
2017

4. An Evaluation of the Implementation of a Parent-Led, Games-Based Physical Activity Intervention: The Active Play at Home Quasi-Randomized Trial

Author

Rubin, D. A., Wilson, K. S., Honea, K. E., Castner, D. M., McGarrah, J. G., Rose, D. J., and Dumont-Driscoll, M.

Abstract

Process evaluations provide insight into the implementation of complex interventions. This study is a process evaluation for the implementation of a parent-led physical activity intervention at home with youth with a rare neurodevelopmental disorder (Prader-Willi syndrome, PWS) and youth with non-syndromal obesity (NSO). Participants included 42 youth with PWS (10.9 ± 2.5 y; 24M: 18F) and 65 youth with NSO (9.8 ± 1.1 y; 34M: 31F), assigned to an intervention or a delayed intervention group. The 24-week intervention included parent training, receiving equipment and a pre-planned curriculum with playground games and interactive console-based games. We evaluated intervention implementation fidelity, dose (reported physical activity minutes), acceptability (perceived difficulty and enjoyment of the planned activities) and contextual factors (facilitators and barriers). Overall, 68.2% of participants (immediate and delayed intervention groups) completed = 70% of the planned physical activity sessions. The average length of the sessions was 44 ± 23 and = 49 ± 22 min for playground and console-based games, respectively. Most activities were more difficult for those with PWS than those with NSO. Common barriers to implementation included scheduling and the child's motivation, and facilitators included features of the curriculum and social support. This intervention modality (home-based, delivered by parents) appears suitable for families with children with and without neurodevelopmental disorders.

Published
2019
Full Text
View/download PDF

5. Movement, home range, and structural habitat use of the Largemouth Bass complex in two large Texas reservoirs.

Author

Driscoll, M. Todd, Norman, Jacob D., Bennett, Daniel L., Metz, Brian K., and Smith, David R.

Subjects
LARGEMOUTH bass, HABITAT selection, WATER depth, RADIO transmitters & transmission, HABITATS
Abstract

Objective: Angler complaints regarding perceived declines in angling quality prompted research to examine the home range, movement, water depth use, and structural habitat use and selection of the Largemouth Bass complex (LBC; Largemouth Bass Micropterus nigricans, Florida Bass M. salmoides, and Largemouth Bass × Florida Bass hybrids) in Toledo Bend and Lake Fork reservoirs, Texas. Methods: A total of 21 LBC individuals at Toledo Bend Reservoir (386–604 mm total length [TL]) and 22 LBC fish at Lake Fork Reservoir (364–545 mm TL) were implanted with radio transmitters and tracked over a 2‐year period. Result: At both reservoirs, LBC home range areas were small (<50 ha) and overall movement was low (~40–100 m/week). Fish primarily occupied water column depths of less than 2 m in both reservoirs and were found in the shallowest depths during the spring. Although overall structural habitat occurrence and selection of LBC fish varied between reservoirs, primarily due to differences at shorelines and creeks (two times higher in Toledo Bend Reservoir) and drops (three times higher in Lake Fork Reservoir), fish selected for the shoreline, drops, points, and creeks in both reservoirs, while drains and flats reflected avoidance. Seasonally, habitat occurrence of LBC fish varied at Toledo Bend Reservoir, primarily due to differences in shoreline use, and flats had the highest fish occurrences during all seasons. At Lake Fork Reservoir, LBC occurrences at flats and drops were high and similar during all seasons. Conclusion: Our estimates of small LBC home ranges and low movement in these large reservoirs were generally similar to those reported in previous studies, regardless of reservoir size. Fish preferred structural habitat types with abrupt slopes, were primarily located offshore, and occupied water column depths that are commonly targeted by LBC anglers. Impact statementThis study is the first to examine structural habitat use and selection by the Largemouth Bass complex (LBC). These results, coupled with estimates of home range and movement, increase the understanding of LBC behavior in larger reservoirs, have applied management implications, and provide information that is directly communicable to LBC anglers. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

12. SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

Author

Eales, O, Page, AJ, de Oliveira Martins, L, Wang, H, Bodinier, B, Haw, D, Jonnerby, J, Atchison, C, Robson, SC, Connor, TR, Loman, NJ, Golubchik, T, Nunez, RTM, Bonsall, D, Rambaut, A, Snell, LB, Livett, R, Ludden, C, Corden, S, Nastouli, E, Nebbia, G, Johnston, I, Lythgoe, K, Torok, ME, Goodfellow, IG, Prieto, JA, Saeed, K, Jackson, DK, Houlihan, C, Frampton, D, Hamilton, WL, Witney, AA, Bucca, G, Pope, CF, Moore, C, Thomson, EC, Harrison, EM, Smith, CP, Rogan, F, Beckwith, SM, Murray, A, Singleton, D, Eastick, K, Sheridan, LA, Randell, P, Jackson, LM, Ariani, CV, Gonçalves, S, Fairley, DJ, Loose, MW, Watkins, J, Moses, S, Nicholls, S, Bull, M, Amato, R, Smith, DL, Aanensen, DM, Barrett, JC, Aggarwal, D, Shepherd, JG, Curran, MD, Parmar, S, Parker, MD, Williams, C, Glaysher, S, Underwood, AP, Bashton, M, Pacchiarini, N, Loveson, KF, Byott, M, Carabelli, AM, Templeton, KE, de Silva, TI, Wang, D, Langford, CF, Sillitoe, J, Gunson, RN, Cottrell, S, O’Grady, J, Kwiatkowski, D, Lillie, PJ, Cortes, N, Moore, N, Thomas, C, Burns, PJ, Mahungu, TW, Liggett, S, Beckett, AH, Holden, MTG, Levett, LJ, Osman, H, Hassan-Ibrahim, MO, Simpson, DA, Chand, M, Gupta, RK, Darby, AC, Paterson, S, Pybus, OG, Volz, EM, de Angelis, D, Robertson, DL, Martincorena, I, Aigrain, L, Bassett, AR, Wong, N, Taha, Y, Erkiert, MJ, Chapman, MHS, Dewar, R, McHugh, MP, Mookerjee, S, Aplin, S, Harvey, M, Sass, T, Umpleby, H, Wheeler, H, McKenna, JP, Warne, B, Taylor, JF, Chaudhry, Y, Izuagbe, R, Jahun, AS, Young, GR, McMurray, C, McCann, CM, Nelson, A, Elliott, S, Lowe, H, Price, A, Crown, MR, Rey, S, Roy, S, Temperton, B, Shaaban, S, Hesketh, AR, Laing, KG, Monahan, IM, Heaney, J, Pelosi, E, Silviera, S, Wilson-Davies, E, Fryer, H, Adams, H, du Plessis, L, Johnson, R, Harvey, WT, Hughes, J, Orton, RJ, Spurgin, LG, Bourgeois, Y, Ruis, C, O’Toole, Á, Gourtovaia, M, Sanderson, T, Fraser, C, Edgeworth, J, Breuer, J, Michell, SL, Todd, JA, John, M, Buck, D, Gajee, K, Kay, GL, Peacock, SJ, Heyburn, D, Kitchman, K, McNally, A, Pritchard, DT, Dervisevic, S, Muir, P, Robinson, E, Vipond, BB, Ramadan, NA, Jeanes, C, Weldon, D, Catalan, J, Jones, N, da Silva Filipe, A, Fuchs, M, Miskelly, J, Jeffries, AR, Oliver, K, Park, NR, Ash, A, Koshy, C, Barrow, M, Buchan, SL, Mantzouratou, A, Clark, G, Holmes, CW, Campbell, S, Davis, T, Tan, NK, Brown, JR, Harris, KA, Kidd, SP, Grant, PR, Xu-McCrae, L, Cox, A, Madona, P, Pond, M, Randell, PA, Withell, KT, Graham, C, Denton-Smith, R, Swindells, E, Turnbull, R, Sloan, TJ, Bosworth, A, Hutchings, S, Pymont, HM, Casey, A, Ratcliffe, L, Jones, CR, Knight, BA, Haque, T, Hart, J, Irish-Tavares, D, Witele, E, Mower, C, Watson, LK, Collins, J, Eltringham, G, Crudgington, D, Macklin, B, Iturriza-Gomara, M, Lucaci, AO, McClure, PC, Carlile, M, Holmes, N, Storey, N, Rooke, S, Yebra, G, Craine, N, Perry, M, Alikhan, N - F, Bridgett, S, Cook, KF, Fearn, C, Goudarzi, S, Lyons, RA, Williams, T, Haldenby, ST, Durham, J, Leonard, S, Davies, RM, Batra, R, Blane, B, Spyer, MJ, Smith, P, Yavus, M, Williams, RJ, Mahanama, AIK, Samaraweera, B, Girgis, ST, Hansford, SE, Green, A, Beaver, C, Bellis, KL, Dorman, MJ, Kay, S, Prestwood, L, Rajatileka, S, Quick, J, Poplawski, R, Reynolds, N, Mack, A, Morriss, A, Whalley, T, Patel, B, Georgana, I, Hosmillo, M, Pinckert, ML, Stockton, J, Henderson, JH, Hollis, A, Stanley, W, Yew, WC, Myers, R, Thornton, A, Adams, A, Annett, T, Asad, H, Birchley, A, Coombes, J, Evans, JM, Fina, L, Gatica-Wilcox, B, Gilbert, L, Graham, L, Hey, J, Hilvers, E, Jones, S, Jones, H, Kumziene-Summerhayes, S, McKerr, C, Powell, J, Pugh, G, Taylor, S, Trotter, AJ, Williams, CA, Kermack, LM, Foulkes, BH, Gallis, M, Hornsby, HR, Louka, SF, Pohare, M, Wolverson, P, Zhang, P, MacIntyre-Cockett, G, Trebes, A, Moll, RJ, Ferguson, L, Goldstein, EJ, Maclean, A, Tomb, R, Starinskij, I, Thomson, L, Southgate, J, Kraemer, MUG, Raghwani, J, Zarebski, AE, Boyd, O, Geidelberg, L, Illingworth, CJ, Jackson, C, Pascall, D, Vattipally, S, Freeman, TM, Hsu, SN, Lindsey, BB, James, K, Lewis, K, Tonkin-Hill, G, Tovar-Corona, JM, Cox, MG, Abudahab, K, Menegazzo, M, MEng, BEWT, Yeats, CA, Mukaddas, A, Wright, DW, Colquhoun, R, Hill, V, Jackson, B, McCrone, JT, Medd, N, Scher, E, Keatley, J - P, Curran, T, Morgan, S, Maxwell, P, Smith, K, Eldirdiri, S, Kenyon, A, Holmes, AH, Price, JR, Wyatt, T, Mather, AE, Skvortsov, T, Hartley, JA, Guest, M, Kitchen, C, Merrick, I, Munn, R, Bertolusso, B, Lynch, J, Vernet, G, Kirk, S, Wastnedge, E, Stanley, R, Idle, G, Bradley, DT, Poyner, J, Mori, M, Jones, O, Wright, V, Brooks, E, Churcher, CM, Fragakis, M, Galai, K, Jermy, A, Judges, S, McManus, GM, Smith, KS, Westwick, E, Attwood, SW, Bolt, F, Davies, A, De Lacy, E, Downing, F, Edwards, S, Meadows, L, Jeremiah, S, Smith, N, Foulser, L, Charalampous, T, Patel, A, Berry, L, Boswell, T, Fleming, VM, Howson-Wells, HC, Joseph, A, Khakh, M, Lister, MM, Bird, PW, Fallon, K, Helmer, T, McMurray, CL, Odedra, M, Shaw, J, Tang, JW, Willford, NJ, Blakey, V, Raviprakash, V, Sheriff, N, Williams, L - A, Feltwell, T, Bedford, L, Cargill, JS, Hughes, W, Moore, J, Stonehouse, S, Atkinson, L, Lee, JCD, Shah, D, Alcolea-Medina, A, Ohemeng-Kumi, N, Ramble, J, Sehmi, J, Williams, R, Chatterton, W, Pusok, M, Everson, W, Castigador, A, Macnaughton, E, Bouzidi, KE, Lampejo, T, Sudhanva, M, Breen, C, Sluga, G, Ahmad, SSY, George, RP, Machin, NW, Binns, D, James, V, Blacow, R, Coupland, L, Smith, L, Barton, E, Padgett, D, Scott, G, Cross, A, Mirfenderesky, M, Greenaway, J, Cole, K, Clarke, P, Duckworth, N, Walsh, S, Bicknell, K, Impey, R, Wyllie, S, Hopes, R, Bishop, C, Chalker, V, Harrison, I, Gifford, L, Molnar, Z, Auckland, C, Evans, C, Johnson, K, Partridge, DG, Raza, M, Baker, P, Bonner, S, Essex, S, Murray, LJ, Lawton, AI, Burton-Fanning, S, Payne, BAI, Waugh, S, Gomes, AN, Kimuli, M, Murray, DR, Ashfield, P, Dobie, D, Ashford, F, Best, A, Crawford, L, Cumley, N, Mayhew, M, Megram, O, Mirza, J, Moles-Garcia, E, Percival, B, Driscoll, M, Ensell, L, Lowe, HL, Maftei, L, Mondani, M, Chaloner, NJ, Cogger, BJ, Easton, LJ, Huckson, H, Lewis, J, Lowdon, S, Malone, CS, Munemo, F, Mutingwende, M, Nicodemi, R, Podplomyk, O, Somassa, T, Beggs, A, Richter, A, Cormie, C, Dias, J, Forrest, S, Higginson, EE, Maes, M, Young, J, Davidson, RK, Jackson, KA, Turtle, L, Keeley, AJ, Ball, J, Byaruhanga, T, Chappell, JG, Dey, J, Hill, JD, Park, EJ, Fanaie, A, Hilson, RA, Yaze, G, Lo, S, Afifi, S, Beer, R, Maksimovic, J, McCluggage, K, Spellman, K, Bresner, C, Fuller, W, Marchbank, A, Workman, T, Shelest, E, Debebe, J, Sang, F, Zamudio, ME, Francois, S, Gutierrez, B, Vasylyeva, TI, Flaviani, F, Ragonnet-Cronin, M, Smollett, KL, Broos, A, Mair, D, Nichols, J, Nomikou, K, Tong, L, Tsatsani, I, O’Brien, PS, Rushton, S, Sanderson, R, Perkins, J, Cotton, S, Gallagher, A, Allara, E, Pearson, C, Bibby, D, Dabrera, G, Ellaby, N, Gallagher, E, Hubb, J, Lackenby, A, Lee, D, Manesis, N, Mbisa, T, Platt, S, Twohig, KA, Morgan, M, Aydin, A, Baker, DJ, Foster-Nyarko, E, Prosolek, SJ, Rudder, S, Baxter, C, Carvalho, SF, Lavin, D, Mariappan, A, Radulescu, C, Singh, A, Tang, M, Morcrette, H, Bayzid, N, Cotic, M, Balcazar, CE, Gallagher, MD, Maloney, D, Stanton, TD, Williamson, KA, Manley, R, Michelsen, ML, Sambles, CM, Studholme, DJ, Warwick-Dugdale, J, Eccles, R, Gemmell, M, Gregory, R, Hughes, M, Nelson, C, Rainbow, L, Vamos, EE, Webster, HJ, Whitehead, M, Wierzbicki, C, Angyal, A, Green, LR, Whiteley, M, Betteridge, E, Bronner, IF, Farr, BW, Goodwin, S, Lensing, SV, McCarthy, SA, Quail, MA, Rajan, D, Redshaw, NM, Scott, C, Shirley, L, Thurston, SAJ, Rowe, W, Gaskin, A, Le-Viet, T, Bonfield, J, Liddle, J, Whitwham, A, Ashby, D, Barclay, W, Taylor, G, Cooke, G, Ward, H, Darzi, A, Riley, S, Chadeau-Hyam, M, Donnelly, CA, Elliott, P, The COVID-19 Genomics UK (COG-UK) Consortium, Department of Health, Imperial College Healthcare NHS Trust- BRC Funding, Medical Research Council (MRC), Cancer Research UK, Commission of the European Communities, Wellcome Trust, National Institute for Health Research, and Imperial College Healthcare NHS Trust: Research Capability Funding (RCF)

Subjects
Delta variant, Science & Technology, SARS-CoV-2, COVID-19, 1103 Clinical Sciences, C500, Microbiology, Genetic diversity, B900, Infectious Diseases, England, COVID-19 Genomics UK (COG-UK) Consortium, 1108 Medical Microbiology, Mutation, Humans, Transmission advantage, Life Sciences & Biomedicine, Phylogeny, 0605 Microbiology
Abstract

Background Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.

Published
2022

26. The nucleus acts as a ruler tailoring cell responses to spatial constraints

Author

Lomakin, A. J., primary, Cattin, C. J., additional, Cuvelier, D., additional, Alraies, Z., additional, Molina, M., additional, Nader, G. P. F., additional, Srivastava, N., additional, Sáez, P. J., additional, Garcia-Arcos, J. M., additional, Zhitnyak, I. Y., additional, Bhargava, A., additional, Driscoll, M. K., additional, Welf, E. S., additional, Fiolka, R., additional, Petrie, R. J., additional, De Silva, N. S., additional, González-Granado, J. M., additional, Manel, N., additional, Lennon-Duménil, A. M., additional, Müller, D. J., additional, and Piel, M., additional

Published
2020
Full Text
View/download PDF

39. A model for the delivery of care for HIV-positive clients

Author

Dykeman, M.C., Sternberg, C, Jasek, J., McGee, D.S., Driscoll, M., Cohen, V., Lubin, B., Williamson, M., Cohen, M., and Sherer, R.

Subjects
HIV patients -- Care and treatment, Health, Cook County Hospital -- Services
Published
1996

42. Sequence and transmembrane topology of MEC-4, an ion channel subunit required for mechanotransduction in Caenorhabditis elegans

Author

Lai, C.-C., Hong, K., Kinnell, M., Chalfie, M., and Driscoll, M.

Subjects
Caenorhabditis elegans -- Research, Ion channels -- Research, Amino acid sequence -- Analysis, Mechanoreceptors -- Research, Proteins -- Structure, Biological sciences
Abstract

Sequence analysis reveals that the amino- and carboxy-terminal regions of MEC-4, an ion channel subunit necessary for touch reception in Caenorhabditis elegans, are located in the cytoplasm. A large domain constituting three Cys-rich residues is located in the extracellular region. MEC-4 is a protein with 768 amino acids and two hydrophobic regions that can span a lipid bilayer. The MEC-4 transmembrane topology shares similarities with mammalian channel subunits.

Published
1996

Catalog

Books, media, physical & digital resources
See catalog results