4,772 results on '"Barnes, D."'
Search Results
2. A comparison of patient-reported outcomes in patients undergoing abdominal wall repair with either synthetic or biosynthetic mesh: a pilot study
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Kulkarni, G. V., Elliott, Z., Rudd, R., Barnes, D., and Hammond, T. M.
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- 2024
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3. Using Solar Orbiter as an upstream solar wind monitor for real time space weather predictions
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Laker, R., Horbury, T. S., O'Brien, H., Fauchon-Jones, E. J., Angelini, V., Fargette, N., Amerstorfer, T., Bauer, M., Möstl, C., Davies, E. E., Davies, J. A., Harrison, R., Barnes, D., and Dumbović, M.
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Physics - Space Physics - Abstract
Coronal mass ejections (CMEs) can create significant disruption to human activities and systems on Earth, much of which can be mitigated with prior warning of the upstream solar wind conditions. However, it is currently extremely challenging to accurately predict the arrival time and internal structure of a CME from coronagraph images alone. In this study, we take advantage of a rare opportunity to use Solar Orbiter, at 0.5\,AU upstream of Earth, as an upstream solar wind monitor. We were able to use real time science quality magnetic field measurements, taken only 12 minutes earlier, to predict the arrival time of a CME prior to reaching Earth. We used measurements at Solar Orbiter to constrain an ensemble of simulation runs from the ELEvoHI model, reducing the uncertainty in arrival time from 10.4\,hours to 2.5\,hours. There was also an excellent agreement in the $B_z$ profile between Solar Orbiter and Wind spacecraft, despite being separated by 0.5\,AU and 10$^{\circ}$ longitude. Therefore, we show that it is possible to predict not only the arrival time of a CME, but the sub-structure of the magnetic field within it, over a day in advance. The opportunity to use Solar Orbiter as an upstream solar wind monitor will repeat once a year, which should further help assess the efficacy upstream in-situ measurements in real time space weather forecasting.
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- 2023
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4. Development of an adverse outcome pathway network for nephrotoxicity
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Barnes, D. A., Firman, J. W., Belfield, S. J., Cronin, M. T. D., Vinken, M., Janssen, M. J., and Masereeuw, R.
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- 2024
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5. Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders
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Heras, E. Delgado de las, Martinez-Murcia, F. J., Illán, I. A., Jiménez-Mesa, C., Castillo-Barnes, D., Ramírez, J., and Górriz, J. M.
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Machine Learning - Abstract
This work proposes the use of 3D convolutional variational autoencoders (CVAEs) to trace the changes and symptomatology produced by neurodegeneration in Parkinson's disease (PD). In this work, we present a novel approach to detect and quantify changes in dopamine transporter (DaT) concentration and its spatial patterns using 3D CVAEs on Ioflupane (FPCIT) imaging. Our approach leverages the power of deep learning to learn a low-dimensional representation of the brain imaging data, which then is linked to different symptom categories using regression algorithms. We demonstrate the effectiveness of our approach on a dataset of PD patients and healthy controls, and show that general symptomatology (UPDRS) is linked to a d-dimensional decomposition via the CVAE with R2>0.25. Our work shows the potential of representation learning not only in early diagnosis but in understanding neurodegeneration processes and symptomatology., Comment: Accepted at 2023 ASPAI Conference
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- 2023
6. A Survey on EEG Phase Amplitude Coupling to Speech Rhythm for the Prediction of Dyslexia
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Gallego-Molina, N., Martinez-Murcia, F. J., Formoso, M. A., Castillo-Barnes, D., Ortiz, A., Ramírez, J., Górriz, J. M., Lopez-Perez, P. J., Luque, J. L., Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Ferrández Vicente, José Manuel, editor, Val Calvo, Mikel, editor, and Adeli, Hojjat, editor
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- 2024
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7. Multipoint interplanetary coronal mass ejections observed with Solar Orbiter, BepiColombo, Parker Solar Probe, Wind and STEREO-A
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Möstl, C., Weiss, A. J., Reiss, M. A., Amerstorfer, T., Bailey, R. L., Hinterreiter, J., Bauer, M., Barnes, D., Davies, J. A., Harrison, R. A., von Forstner, J. L. Freiherr, Davies, E. E., Heyner, D., Horbury, T., and Bale, S. D.
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Astrophysics - Solar and Stellar Astrophysics ,Physics - Space Physics - Abstract
We report the result of the first search for multipoint in situ and imaging observations of interplanetary coronal mass ejections (ICMEs) starting with the first Solar Orbiter (SolO) data in 2020 April - 2021 April. A data exploration analysis is performed including visualizations of the magnetic field and plasma observations made by the five spacecraft SolO, BepiColombo, Parker Solar Probe (PSP), Wind and STEREO-A, in connection with coronagraph and heliospheric imaging observations from STEREO-A/SECCHI and SOHO/LASCO. We identify ICME events that could be unambiguously followed with the STEREO-A heliospheric imagers during their interplanetary propagation to their impact at the aforementioned spacecraft, and look for events where the same ICME is seen in situ by widely separated spacecraft. We highlight two events: (1) a small streamer blowout CME on 2020 June 23 observed with a triple lineup by PSP, BepiColombo and Wind, guided by imaging with STEREO-A, and (2) the first fast CME of solar cycle 25 ($ \approx 1600$ km s$^{-1}$) on 2020 November 29 observed in situ by PSP and STEREO-A. These results are useful for modeling the magnetic structure of ICMEs and the interplanetary evolution and global shape of their flux ropes and shocks, and for studying the propagation of solar energetic particles. The combined data from these missions are already turning out to be a treasure trove for space weather research and are expected to become even more valuable with an increasing number of ICME events expected during the rise and maximum of solar cycle 25., Comment: in press at ApJ Letters (submitted 2021 September 15, revised 2021 November 24, accepted 2021 December 9). 11 pages, 3 figures, 1 table
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- 2021
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8. Immunomodulatory therapy in children with paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS, MIS-C; RECOVERY): a randomised, controlled, open-label, platform trial
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Faust, Saul N, Haynes, Richard, Jones, Christine E, Staplin, Natalie, Whittaker, Elizabeth, Jaki, Thomas, Juszczak, Ed, Spata, Enti, Wan, Mandy, Bamford, Alasdair, Dimitri, Paul, Finn, Adam, Furness, John, Ramanan, Athimalaipet V, Gale, Christopher, Cathie, Katrina, Drysdale, Simon, Bernatoniene, Jolanta, Murray, Clare, Roehr, Charles C, Fleming, Paul, Riordan, Andrew, Bandi, Srini, Jyothish, Deepthi, Evans, Jennifer, Emonts, Marieke, Kelly, Dominic, Pathan, Nazima, Davies, Patrick, Hague, Rosie, Pollock, Louisa, Semple, Malcolm G, Peto, Leon, Baillie, J Kenneth, Buch, Maya, Jeffery, Katie, Knight, Marian, Lim, Wei Shen, Montgomery, Alan, Mukherjee, Aparna, Mumford, Andrew, Rowan, Kathryn, Thwaites, Guy, Mafham, Marion, Emberson, Jonathan, Landray, Martin J, Horby, Peter W, Chappell, Lucy, Day, Jeremy, Dung, DV, Quang, NN, Binh, Prof, Burhan, E, Alisjahbana, B, Koirala, J, Basnet, S, Kestelyn, E, Basnyat, B, Gyanwali, P, Hamers, RL, Sandercock, P, Darbyshire, J, DeMets, D, Fowler, R, Lalloo, D, Munavvar, M, Roberts, I, Warris, A, Wittes, J, Craddock-Bamford, A, Barton, J, Basoglu, A, Brown, R, Brudlo, W, Denis, E, Fletcher, L, Howard, S, Musini, S, Taylor, K, Cui, G, Goodenough, B, King, A, Lay, M, Murray, D, Stevens, W, Wallendszus, K, Welsh, R, Crichton, C, Davies, J, Goldacre, R, Harper, C, Knight, F, Nunn, M, Salih, H, Welch, J, Campbell, M, Pessoa-Amorim, G, Zayed, M, Wiles, J, Bagley, G, Cameron, S, Chamberlain, S, Farrell, B, Freeman, H, Kennedy, A, Whitehouse, A, Wilkinson, S, Wood, C, Reith, C, Davies, K, Halls, H, Holland, L, Truell, R, Wilson, K, Lingwood, Emma, Howie, L, Lunn, M, Rodgers, Penelope, Amuasi, J, Baird, K, Bao, T, Bittaye, M, Bonney, J, D'Alessandro, U, Dhimal, M, Huyen, T, Jagne, A, Karkey, A, Maiga, O, Matey, E, Nadjm, B, Nel, J, Pant, S, Puspatriani, K, Rahardjani, M, Raijal, S, Rees, H, Rimainar, A, Roberts, C, Rocca, A, Shrestha, S, Usuf, E, Vidaillic, C, Wulandari, F, Alexander, A, Amezaga, M, Armah, C, Asghar, A, Aubrey, P, Barker-Williams, K, Barnard, A, Bartholomew, J, Beaumont-Jewell, D, Beddows, S, Beety, J, Birch, C, Boyle, P, Brend, M, Brookes, M, Callens, C, Campbell, D, Campbell, H, Cate, H, Chambers, E, Chapman, K, Coe, A, Collins, J, Crawshaw, S, Das, S, De Soyza, A, Denton, E, Dicks, P, Dolman, M, Donaldson, K, Dowden, L, Dowling, S, Drake, C, Duckles-Leech, H, Duffy, H, Gerdes, L, Gibbons, K, Gill, L, Gilmour, K, Goodwin, J, Graham, J, Green, C, Hall, C, Hall, A, Hampshire, K, Hanson, J, Harman, T, Harper, H, Harrison, S, Hicks, J, Hodgson, H, Hough, M, Jackson, S, Johnson, G, Kirk, J, Lemoine, N, Levett, C, Lock, S, Lockett, T, Logan, M, Lomme, K, Luo, J, McMillan, N, Membrey, H, Mguni, N, Minton, J, Monaghan, H, Murphy, S, Muzengi, N, Naz, M, Nickson, I, Odam, M, Ohia, U, Okell, E, Oliver, A, Pearson, K, Pine, K, Pleass, R, Porter, D, Porter, L, Potter, A, Poustie, V, Pratt, S, Price, A, Priest, A, Rodgers, A, Rook, C, Ryan, P, Sam, S, Sharratt, P, Sheffield, J, Shenton, J, Shirley, K, Skinner, T, Slade, H, Sutu, M, Taylor, J, Thomas, E, Tinkler, H, Unsworth, A, Usher, R, van't Hoff, W, Walker, S, Walters, J, Walton, E, Warmington, J, Wayman, E, Williams, P, Williamson, J, Williamson, D, Yelnoorkar, F, Knight, M, Hodson, K, Pavord, S, Williamson, C, Bowman, L, Chen, F, Clarke, R, Goonasekara, M, Herrington, W, Judge, P, Ng, S, Preiss, D, Sammons, E, Zhu, D, Arkley, C, Bowker, P, Bruce, J, Byrne-Watts, V, Chapman, G, Coleman, G, Denwood, T, Gray, J, Harrison, D, Mather, N, Pinches, H, Rees, A, Rees, S, Turner, G, Abani, O, Abbas, A, Abbas, F, Abbas, J, Abbas, K, Abbas, M, Abbasi, S, Abbass, H, Abbott, A, Abdallah, N, Abdelaziz, A, Abdelfattah, M, Abdelqader, B, Abdul, A, Abdul, B, Abdul, S, Abdul Rasheed, A, Abdulakeem, A, Abdul-Kadir, R, Abdullah, A, Abdulmumeen, A, Abdul-Raheem, R, Abdulshukkoor, N, Abdusamad, K, Abed El Khaleq, Y, Abedalla, M, Abeer Ul Amna, A, Abel, L, Abernethy, K, Abeywickrema, M, Abhinaya, C, Aboaba, A, Aboagye-Odei, A, Aboelela, H, Abo-Leyah, H, Abouelela, K, Abou-Haggar, A, Abouibrahim, M, Abousamra, A, Abouzaid, M, Abraham, M, Abraham, T, Abraheem, A, Abrams, J, Abrams, R, Abu, H, Abu-Arafeh, A, Abubacker, S, Abung, A, Abusamra, Y, Aceampong, Y, Achara, A, Acharya, D, Acheampong, S, Acheampong, P, Acheson, J, Achieng, S, Acosta, A, Acquah, R, Acton, C, Adabie-Ankrah, J, Adair, P, Adam, F, Adam, M, Adamali, H, Adamczyk, M, Adams, C, Adams, D, Adams, K, Adams, L, Adams, N, Adams, R, Adams, T, Adamu-Ikeme, L, Adati, K, Adcock, K, Addo, A, Adeagbo, O, Adebiyi, A, Adedeji, O, Adegeye, Y, Adegoke, K, Adell, V, Adenwalla, S, Adeoye, F, Adesemoye, O, Adewunmi, E, Adeyanju, A, Adeyemi, J, Adeyemo, T, Adhikary, R, Aditya, A, Adkins, G, Adnan, A, Aeron-Thomas, J, Affleck, D, Afnan, C, Afridi, M, Aftab, Z, Agarwal, M, Agbeko, R, Agbo, C, Aggarwal, S, Aghababaie, A, Aguilar Jimenez, L, Ahamed Sadiq, S, Ahammed Nazeer, M, Ahmed, A, Ahmed, B, Ahmed, F, Ahmed, H, Ahmed, I, Ahmed, K, Ahmed, L, Ahmad, M, Ahmed, N, Ahmed, O, Ahmed, R, Ahmad, S, Ahmed, S H, Ahmed Ali, R, Ahmed Mohamud, B, Ahmer, S, Ahonia, A, Aiken, C, Ail, D, Ainsworth, M, Aissa, M, Aitken, L, Ajay, B, Ajibode, A, Ajmi, A, Akhtar, N, Akili, S, Akinbiyi, B, Akindolie, O, Akinfenwa, Y, Akinkugbe, O, Akinpelu, I, Akram, M, Aktinade, O, Akudi, U, Al Aaraj, A, Al Balushi, A, Al Dakhola, M, Al Swaifi, A, Al-Abadi, E, Alabi, A, Aladangady, N, Alafifi, M, Alam, A, Alam, S, Al-Asadi, A, Alatzoglou, K, Albert, P, Albon, L, Alcala, A, Alcorn, G, Alcorn, S, Aldana, A, Alderdice, D, Aldesouki, A, Aldouri, R, Aldridge, J, Aldridge, N, Alegria, A, Alexander, C, Alexander, J, Alexander, P, Al-Fori, J, Alghazawi, L, Alhabsha, O, Al-Hakim, B, Alhameed, R, Al-Hayali, M, Al-Hity, S, Ali, A, Ali, F, Ali, J, Ali, M, Ali, N, Ali, O, Ali, R, Ali, S, Aliberti, E, Alin, J, Alina, A, Alipustain, A, Aliyuda, F, Alizaedeh, K, Al-Jibury, M, Al-Juboori, S, Al-Khalil, M, Alkhudhayri, A, Alkhusheh, M, Allan, F, Allan, N, Allanson, A, Allcock, R, Allen, E, Allen, J, Allen, K, Allen, L, Allen, P, Allen, R, Allen, S, Allen, T, Alli, A, Allison, K, Allman, B, Allsup, D, Allsop, H, Allsop, L, Almahroos, A, Al-Moasseb, H, Al-Obaidi, M, Alomari, L, Al-Rabahi, A, Al-Ramadhani, B, Al-Saadi, Z, Al-Sammarraie, R, Alshaer, I, Al-Shahi Salman, R, Al-Shamkhani, W, Alsheikh, F, Al-Sheklly, B, Altaf, S, Alty, A, Alvarez, M, Alvarez Corral, M, Alveyn, E, Alzetani, M, Amamou, S, Amar, N, Ambalavanan, S, Ambrogetti, R, Ambrose, C, Ameen, A, Ames, K, Amin, A, Amin, K, Amin, S, Amin, T, Amit, B, Amjad, A, Amjad, N, Amosun, V, Amsal, M, Amsha, K, Amutio Martin, N, Amy, P, Anada, A, Anand, A, Anandappa, S, Anantapatnaikuni, S, Anderson, E, Anderson, J, Anderson, L, Anderson, M, Anderson, N, Anderson, R, Anderson, S, Anderson, W, Andreou, P, Andrews, A, Andrews, J, Aneke, K, Ang, A, Ang, W, Angel, T, Angela, A, Angelini, P, Anguvaa, L, Anichtchik, O, Anim-Somuah, M, Aniruddhan, K, Annett, J, Anning, L, Anstey, P, Anstey, R, Anthony, A, Anthony-Pillai, A, Antill, P, Antonnia, Z, Anu, V, Anwar, M, Apetri, E, Apostolopoulos, A, Appleby, S, Appleyard, D, Aquino, M, Araba, B, Aransiola, S, Araujo, M, Archer, A, Archer, D, Archer, S, Arcoria, D, Ardley, C, Arias, A, Aribike, O, Arimoto, R, Armata, I, Armistead, J, Armitage, A, Armstrong, C, Armstrong, M, Armstrong, S, Armstrong, W, Armtrong, P, Arndt, H, Arnison-Newgass, C, Arnold, D, Arnold, R, Arnott, A, Arora, D, Arora, R, Arora, K, Arora, P, Arter, A, Arumaithurai, A, Arya, A, Arya, R, Asandei, D, Asghar, M, Ashab, M, Ashbrook-Raby, C, Ashby, H, Ashcroft, J, Ashcroft, S, Asher, G, Ashfak, Z, Ashfaq, A, Ashish, A, Ashley, D, Ashman-Flavell, S, Ashok, S, Ashour, A, Ashraf, S, Ashraf, M, Ashraq, M, Ashton, D, Ashton, S, Ashworth, A, Ashworth, F, Ashworth, R, Aslam, A, Aslam, I, Aslam, S, Aslett, L, Asogan, H, Asrar, A, Assaf, O, Astin-Chamberlain, R, Athorne, D, Atkins, B, Atkins, C, Atkins, S, Atkinson, J, Atkinson, V, Atomode, A, Atraskiewicz, B, Attia, A, Attubato, E, Attwood, M, Auer, Z, Aujayeb, A, Aung, A, Aung, H, Aung, K, Aung, N, Aung, Y, Aung, Z, Austin, E, Austin, K, Auwal, A, Avari, M, Avery, M, Aveyard, N, Avis, J, Aviss, G, Avram, C, Avram, P, Awadelkareem, A, Awadzi, G, Awaly, M, Awan, A, Awoseyila, A, Aya, A, Ayaz, E, Ayers, A, Azam, J, Azeem, A, Azharuddin, M, Aziz, A, Aziz, G, Aziz, I, Aziz, N, Azkoul, A, Azman Shah, A, Azzopardi, G, Azzoug, H, Babatunde, F, Babi, M, Babiker, B, Babington, G, Babirecki, M, Babores, M, Babs-Osibodu, A, Bacciarelli, S, Bachar, R, Bachour, M, Bacon, G, Bacon, J, Badal, B, Bader, M, Badhan, G, Badhrinarayanan, S, Bae, J, Baggaley, A, Baggott, A, Bagmane, D, Bagshaw, L, Bahadori, K, Bailey, A, Bailey, J, Bailey, K, Bailey, L, Bailey, M, Bailey, P, Bailey, S, Baillie, H, Baillie, J, Bain, J, Bains, V, Baird, D, Baird, E, Baird, S, Baird, T, Baird, Y, Bajandouh, A, Baker, D, Baker, E, Baker, J, Baker, K, Baker, M, Baker, R, Baker, T, Baker, V, Bakere, H, Bakerly, N, Baker-Moffatt, M, Bakhai, A, Bakhtiar, N, Bakoulas, P, Bakthavatsalam, D, Balachandran, N, Balan, A, Balasingam, P, Balaskas, T, Balasubramania, M, Balatoni, N, Balcombe, A, Baldwin, A, Baldwin, C, Baldwin, D, Baldwin, F, Baldwin-Jones, R, Bale, N, Balfour, J, Ball, R, Ball, M, Ballard, K, Balluz, I, Balmforth, C, Balogh, E, Baltmr, A, Baluwala, A, Bambridge, G, Bamford, P, Bamford, A, Bamgboye, A, Bancroft, H, Bancroft, E, Banda, J, Bandaru, K, Bandla, N, Bandyopadhyam, S, Banerjee, A, Banerjee, R, Bani-Saad, O, Banks, H, Banks, L, Banks, P, Bann, C, Bannister, H, Bannister, O, Banton, L, Baptist, M, Baqai, T, Baral, A, Baramova, D, Barbe, R, Barbon, E, Barbosa, M, Barbour, J, Barclay, A, Barclay, C, Bardsley, G, Bareford, S, Bari, S, Barker, A, Barker, D, Barker, E, Barker, H, Barker, J, Barker, L, Barker, O, Barkha, S, Barla, J, Barlow, G, Barlow, R, Barlow, V, Barnacle, J, Barnes, D, Barnes, N, Barnes, R, Barnes, T, Barnetson, C, Barnett, A, Barnett-Vanes, A, Barnsley, W, Barr, A, Barr, C, Barr, D, Barr, J, Barratt, N, Barratt, S, Barrera, M, Barrett, A, Barrett, F, Barrett, J, Barrett, S, Barrow, E, Bartlett, C, Bartlett, G, Bartlett, J, Bartlett, L, Bartley, S, Bartolmeu-Pires, S, Barton, A, Barton, G, Barton, L, Barton, R, Baruah, R, Baryschpolec, S, Bashir, H, Bashyal, A, Basker, B, Basran, A, Bassett, G, Bassett, J, Bassford, C, Bassoy, B, Bastion, V, Basumatary, A, Basvi, P, Bataduwaarachchi, V, Bate, T, Bateman, H, Bateman, K, Bateman, V, Bates, E, Bates, H, Bates, M, Bates, S, Batham, S, Batista, A, Batla, A, Batra, D, Batty, A, Batty, H, Batty, T, Baum, M, Baumbe, R, Bautista, C, Bawa, T, Bawa, F, Bawani, F, Bax, S, Baxter, M, Baxter, N, Baxter, Z, Bayes, H, Bayo, L-A, Bazari, F, Bazaz, R, Bazli, A, Beacham, L, Beadles, W, Beadon, K, Beak, P, Beale, A, Beard, K, Beardsal, K, Bearpark, J, Beasley, A, Beattie, S, Beaumont, K, Beaver, T, Beavis, S, Beazley, C, Beck, S, Beckett, V, Beckitt, R, Beckley, S, Beddall, H, Beeby, D, Beeby, S, Beech, G, Beecroft, M, Beer, S, Beer, N, Bega, G, Begg, A, Begg, S, Beghini, S, Begum, A, Begum, S, Behan, 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Varquez, R, Vasadi, V, Vassell, K, Vassell, O, Vasu, V, Vasudevan, V, Vatish, M, Vaughan, S, Vayalaman, H, Vayapooree, D, Vaz, C, Veale, N, Veerasamy, S, Velankar, S, Velauthar, L, Veli, N, Vella, N, Velugupati, A, Velusamy, A, Venables, I, Venditti, M, Venkataramakrishnan, R, Venn, R, Ventilacion, L, Vere, J, Veres, M, Vergnano, S, Verling, W, Verma, A, Vernall, R, Vernon, B, Vertue, M, Verueco, L, Verula, J, Vethanayagam, N, Vettikumaran, S, Veys, L, Vickers, C, Victor, S, Victoria, S, Vidler, J, Vijayakumar, B, Vijayaraghavan Nalini, V, Vilcinskaite, B, Vileito, A, Vilimiene, N, Vinall, L, Vinay, S, Vinayakarao, L, Vincent, O, Vincent, R, Virdee, P, Virgilio, E, Virk, A, Visentin, E, Vitaglione, M, Vithian, K, Vittoria, S, Vivekananthan, S, Vlad, E, Vlies, B, von Oven, L, Vooght, C, Vutipongsatorn, K, Vuylsteke, A, Vyras, E, W Hay, A, Wach, R, Wadams, B, Wadd, S, Waddington, N, Wade, P, Wadsley, J, Wadsworth, K, Wafa, S, Wagstaff, D, Wagstaff, L, Wahab, D, Wahbi, Z, Waheed Adigun, A, Waidyanatha, S, Waite, A, Wake, R, Wakefield, A, Wakeford, W, Wakinshaw, F, Waldeck, E, Walden, A, Walding, L, Waldron, A, Waldron, J, Wales, E, Wali, B, Walker, D, Walker, G, Walker, H, Walker, I, Walker, K, Walker, L, Walker, O, Walker, R, Wallace, G, Wallbutton, R, Wallen, J, Waller, A, Waller, R, Wallis, G, Wallis, L, Wallis, M, Walmsley, E, Walsh, D, Walsh, E, Walsh, L, Walstow, D, Walter, D, Walters, A, Walters, H, Walton, L, Walton, M, Walton, O, Walton, S, Wands, M, Wane, R, Wang, F, Wang, N, Wang, R, Wang, S, Warbrick, D, Warburton, S, Ward, C, Ward, D, Ward, E, Ward, H, Ward, J, Ward, L, Ward, N, Ward, R, Ward, T, Warden, S, Wardere, G, Wardle, S, Wardy, H, Waring, G, Waring, S, Warner, B, Warner, C, Warnock, L, Warran, S, Warren, J, Warren, L, Warren, R, Warren, Y, Warrender, D, Warren-Miell, H, Warwick, G, Wassall, H, Wasson, E, Wastson, E, Watchorn, H, Waterfall, H, Waters, A, Waters, D, Waterstone, M, Watkin, A, Watkins, C, Watkins, E, Watkins, K, Watkins, L, Watson, A, Watson, E, Watson, F, Watson, J, Watson, K, Watson, L, Watson, P, Watson, R, Watters, M, Watterson, D, Watts, D, Watts, J, Watts, M, Waugh, V, Wayman, M, Wazir, A, Weatherhead, M, Weatherly, N, Webb, C, Webb, H, Webb, K, Webb, S, Websdale, C, Webster, D, Webster, I, Webster, J, Webster, T, Wedlin, J, Wee, L, Weerakoon, R, Weerasinghe, T, Weeratunga, J, Weetman, M, Wei, S, Weichert, I, Welch, E, Welch, H, Welch, L, Welch, S, Welham, B, Weller, S, Wellings, L, Wells, B, Wellstead, S, Welsh, B, Welters, I, Welton, R, Wenn, V, Wentworth, L, Wesonga, J, Wesseldine, K, West, J, West, M, West, R, West, S, Western, L, Westhead, R, Weston, H, Westwood, A, Westwood, K, Westwood, S, Wetherill, B, Wheaver, S, Wheeler, H, Whelan, B, Whelband, M, Whileman, A, Whitcher, A, White, A, White, B, White, C, White, D, White, J, White, K, White, M, White, N, White, S, White, T, Whitehead, C, Whitehorn, K, Whitehouse, C, Whitehouse, T, Whiteley, J, Whiteley, L, Whiteley, S, Whitham, R, Whitlingum, G, Whitmore, D, Whittam, L, Whittington, A, Whittle, H, Whittle, R, Wiafe, E, Wiblin, L, Wickens, O, Widdrington, J, Wieboldt, J, Wieringa, H, Wiesender, C, Wiffen, L, Wight, A, Wignall, A, Wignall, C, Wilce, A, Wilcock, D, Wilcock, E, Wilcox, L, Wild, B, Wild, L, Wild, S, Wilde, M, Wilding, L, Wilding, P, Wildsmith, T, Wileman, J, Wiles, K, Wilhelmsen, E, Wiliams, T, Wilkie, J, Wilkin, D, Wilkins, H, Wilkins, J, Wilkins, S, Wilkinson, I, Wilkinson, L, Wilkinson, N, Wilkinson, T, Willetts, S, Williams, A, Williams, C, Williams, D, Williams, E, Williams, G, Williams, H, Williams, J, Williams, K, Williams, M, Williams, R, Williams, S, Williams, T, Williamson, A, Williamson, H, Williamson, R, Willis, E, Willis, H, Willis, J, Wills, L, Willsher, L, Willshire, C, Wilson, A, Wilson, B, Wilson, D, Willson, F, Wilson, I, Willson, J, Wilson, K-A, Wilson, L, Wilson, M, Wilson, T, Win, K, Win, M, Win, T, Win, W, Winckworth, L, Winder, L, Winder, P, Winearl, S, Winmill, H, Winn, S, Winpenny, C, 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P, Wubetu, J, Wulandari, R, Wurie, S, Wyatt, C, Wyn-Griffiths, F, Wynter, I, Xavier, B, Xhikola, A, Xia, B, Xia, Z, Y Ellis, T, Yacoba, E, Yakubi, M, Yan, M, Yanagisawa, Y, Yang, F, Yang, Y, Yanney, M, Yap, W, Yaqoob, N, Yasmin, S, Yates, B, Yates, D, Yates, E, Yates, H, Yates, M, Yates, T, Ye, J, Yearwood Martin, C, Yein, K, Yeoh, A, Yeung, C, Yew, P, Yewatkar, D, Ylquimiche Melly, L, Ynter, I, Yong, H, Yorke, J, Youens, J, Younes Ibrahim, A, Young, E, Young, G, Young, L, Yousafzar, A, Youssouf, S, Yousuf, A, Yu, C, Yuan, J, Yung, B, Yusef, D, Yusef, S, Yusuf, I, Zafar, A-M, Zagalo, S, Zaher, S, Zahoor, A, Zainab, M, Zak, T, Zaki, K, Zakir, N, Zalewska, K, Zamalloa, A, Zaman, M, Zaman, S, Zamikula, J, Zammit, L, Zammit-Mangion, M, Zawadzka, M, Zebracki, E, Zehnder, D, Zeidan, L, Zeinali, D, Zhang, J, Zhao, X, Zheng, D, Zia, M, Zibdeh, O, Zill-E-Huma, R, Zin, E, Zincone, E, Zindoga, G, Zinkin, E, Zinyemba, V, Zipitis, C, Zitter, L, Zmierczak, A, Zubikarai, G, Zubir, A, Zuhra, N, Zulaikha, R, Zulfikar, S, Zullo, C, and Zuriaga-Alvaro, A
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- 2024
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9. In situ multi-spacecraft and remote imaging observations of the first CME detected by Solar Orbiter and BepiColombo
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Davies, E. E., Möstl, C., Owens, M. J., Weiss, A. J., Amerstorfer, T., Hinterreiter, J., Bauer, M., Bailey, R. L., Reiss, M. A., Forsyth, R. J., Horbury, T. S., O'Brien, H., Evans, V., Angelini, V., Heyner, D., Richter, I., Auster, H-U., Magnes, W., Baumjohann, W., Fischer, D., Barnes, D., Davies, J. A., and Harrison, R. A.
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Physics - Space Physics ,Astrophysics - Solar and Stellar Astrophysics - Abstract
On 2020 April 19 a coronal mass ejection (CME) was detected in situ by Solar Orbiter at a heliocentric distance of about 0.8 AU. The CME was later observed in situ on April 20th by the Wind and BepiColombo spacecraft whilst BepiColombo was located very close to Earth. This CME presents a good opportunity for a triple radial alignment study, as the spacecraft were separated by less than 5$^\circ$ in longitude. The source of the CME, which was launched on April 15th, was an almost entirely isolated streamer blowout. STEREO-A observed the event remotely from -75.1$^\circ$ longitude, which is an exceptionally well suited viewpoint for heliospheric imaging of an Earth directed CME. The configuration of the four spacecraft has provided an exceptionally clean link between remote imaging and in situ observations of the CME. We have used the in situ observations of the CME at Solar Orbiter, Wind, and BepiColombo, and the remote observations of the CME at STEREO-A in combination with flux rope models to determine the global shape of the CME and its evolution as it propagated through the inner heliosphere. A clear flattening of the CME cross-section has been observed by STEREO-A, and further confirmed by comparing profiles of the flux rope models to the in situ data, where the distorted flux rope cross-section qualitatively agrees most with in situ observations of the magnetic field at Solar Orbiter. Comparing in situ observations of the magnetic field between spacecraft, we find that the dependence of the maximum (mean) magnetic field strength decreases with heliocentric distance as $r^{-1.24 \pm 0.50}$ ($r^{-1.12 \pm 0.14}$), in disagreement with previous studies. Further assessment of the axial and poloidal magnetic field strength dependencies suggests that the expansion of the CME is likely neither self-similar nor cylindrically symmetric.
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- 2020
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10. GLIS3 expression in the thyroid gland in relation to TSH signaling and regulation of gene expression
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Kang, Hong Soon, Grimm, Sara A., Liao, Xiao-Hui, and Jetten, Anton M.
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- 2024
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11. The Cluster HEritage project with XMM-Newton: Mass Assembly and Thermodynamics at the Endpoint of structure formation. I. Programme overview
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Collaboration, The CHEX-MATE, Arnaud, M., Ettori, S., Pratt, G. W., Rossetti, M., Eckert, D., Gastaldello, F., Gavazzi, R., Kay, S. T., Lovisari, L., Maughan, B. J., Pointecouteau, E., Sereno, M., Bartalucci, I., Bonafede, A., Bourdin, H., Cassano, R., Duffy, R. T., Iqbal, A., Maurogordato, S., Rasia, E., Sayers, J., Andrade-Santos, F., Aussel, H., Barnes, D. J., Barrena, R., Borgani, S., Burkutean, S., Clerc, N., Corasaniti, P. -S., Cuillandre, J. -C., De Grandi, S., De Petris, M., Dolag, K., Donahue, M., Ferragamo, A., Gaspari, M., Ghizzardi, S., Gitti, M., Haines, C. P., Jauzac, M., Johnston-Hollitt, M., Jones, C., Kéruzoré, F., Brun, A. M. C. Le, Mayet, F., Mazzotta, P., Melin, J. -B., Molendi, S., Nonino, M., Okabe, N., Paltani, S., Perotto, L., Pires, S., Radovich, M., Rubino-Martin, J. -A., Salvati, L., Saro, A., Sartoris, B., Schellenberger, G., Streblyanska, A., Tarrio, P., Tozzi, P., Umetsu, K., van der Burg, R. F. J., Vazza, F., Venturi, T., Yepes, G., and Zarattini, S.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation (CHEX-MATE) is a three mega-second Multi-Year Heritage Programme to obtain X-ray observations of a minimally-biased, signal-to-noise limited sample of 118 galaxy clusters detected by Planck through the Sunyaev-Zeldovich effect. The programme, described in detail in this paper, aims to study the ultimate products of structure formation in time and mass. It is composed of a census of the most recent objects to have formed (Tier-1: 0.05 < z < 0.2; 2 x 10e14 M_sun < M_500 < 9 x 10e14 M_sun), together with a sample of the highest-mass objects in the Universe (Tier-2: z < 0.6; M_500 > 7.25 x 10e14 M_sun). The programme will yield an accurate vision of the statistical properties of the underlying population, measure how the gas properties are shaped by collapse into the dark matter halo, uncover the provenance of non-gravitational heating, and resolve the major uncertainties in mass determination that limit the use of clusters for cosmological parameter estimation. We will acquire X-ray exposures of uniform depth, designed to obtain individual mass measurements accurate to 15-20% under the hydrostatic assumption. We present the project motivations, describe the programme definition, and detail the ongoing multi-wavelength observational (lensing, SZ, radio) and theoretical effort that is being deployed in support of the project., Comment: 27 pages, 11 figures; A&A, in press
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- 2020
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12. Magnetic Gradient Fluctuations from Quadrupolar $^{73}$Ge in Si/SiGe Exchange-Only Qubits
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Kerckhoff, J., Sun, B., Fong, B. H., Jones, C., Kiselev, A. A., Barnes, D. W., Noah, R. S., Acuna, E., Akmal, M., Ha, S. D., Wright, J. A., Thomas, B. J., Jackson, C. A. C., Edge, L. F., Eng, K., Ross, R. S., and Ladd, T. D.
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Quantum Physics ,Condensed Matter - Mesoscale and Nanoscale Physics - Abstract
We study the time-fluctuating magnetic gradient noise mechanisms in pairs of Si/SiGe quantum dots using exchange echo noise spectroscopy. We find through a combination of spectral inversion and correspondence to theoretical modeling that quadrupolar precession of the $^{73}$Ge nuclei play a key role in the spin-echo decay time $T_2$, with a characteristic dependence on magnetic field and the width of the Si quantum well. The $^{73}$Ge noise peaks appear at the fundamental and first harmonic of the $^{73}$Ge Larmor resonance, superimposed over $1/f$ noise due to $^{29}$Si dipole-dipole dynamics, and are dependent on material epitaxy and applied magnetic field. These results may inform the needs of dynamical decoupling when using Si/SiGe quantum dots as qubits in quantum information processing devices., Comment: 17 pages, 11 figures
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- 2020
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13. The high helium abundance and charge states of the interplanetary CME and its material source on the Sun
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Fu, Hui, Harrison, R. A., Davies, J. A., Xia, LiDong, Zhu, XiaoShuai, Li, Bo, Huang, ZhengHua, and Barnes, D.
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Astrophysics - Solar and Stellar Astrophysics ,Physics - Space Physics - Abstract
Identifying the source of the material within coronal mass ejections (CMEs) and understanding CME onset mechanisms are fundamental issues in solar and space physics. Parameters relating to plasma composition, such as charge states and He abundance (\ahe), may be different for plasmas originating from differing processes or regions on the Sun. Thus, it is crucial to examine the relationship between in-situ measurements of CME composition and activity on the Sun. We study the CME that erupted on 2014 September 10, in association with an X1.6 flare, by analyzing AIA imaging and IRIS spectroscopic observations and its in-situ signatures detected by Wind and ACE. We find that during the slow expansion and intensity increase of the sigmoid, plasma temperatures of 9 MK, and higher, first appear at the footpoints of the sigmoid, associated with chromospheric brightening. Then the high-temperature region extends along the sigmoid. IRIS observations confirm that this extension is caused by transportation of hot plasma upflow. Our results show that chromospheric material can be heated to 9 MK, and above, by chromospheric evaporation at the sigmoid footpoints before flare onset. The heated chromospheric material can transport into the sigmoidal structure and supply mass to the CME. The aforementioned CME mass supply scenario provides a reasonable explanation for the detection of high charge states and elevated \ahe\ in the associated ICME. The observations also demonstrate that the quasi-steady evolution in the precursor phase is dominated by magnetic reconnection between the rising flux rope and the overlying magnetic field structure., Comment: 10 pages, 5 figures, accepted for publication in ApJL
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- 2020
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14. A deep learning view of the census of galaxy clusters in IllustrisTNG
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Su, Y., Zhang, Y., Liang, G., ZuHone, J. A., Barnes, D. J., Jacobs, N. B., Ntampaka, M., Forman, W. R., Nulsen, P. E. J., Kraft, R. P., and Jones, C.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The origin of the diverse population of galaxy clusters remains an unexplained aspect of large-scale structure formation and cluster evolution. We present a novel method of using X-ray images to identify cool core (CC), weak cool core (WCC), and non cool core (NCC) clusters of galaxies, that are defined by their central cooling times. We employ a convolutional neural network, ResNet-18, which is commonly used for image analysis, to classify clusters. We produce mock Chandra X-ray observations for a sample of 318 massive clusters drawn from the IllustrisTNG simulations. The network is trained and tested with low resolution mock Chandra images covering a central 1 Mpc square for the clusters in our sample. Without any spectral information, the deep learning algorithm is able to identify CC, WCC, and NCC clusters, achieving balanced accuracies (BAcc) of 92%, 81%, and 83%, respectively. The performance is superior to classification by conventional methods using central gas densities, with an average BAcc = 81%, or surface brightness concentrations, giving BAcc = 73%. We use Class Activation Mapping to localize discriminative regions for the classification decision. From this analysis, we observe that the network has utilized regions from cluster centers out to r~300 kpc and r~500 kpc to identify CC and NCC clusters, respectively. It may have recognized features in the intracluster medium that are associated with AGN feedback and disruptive major mergers., Comment: Accepted for publication in MNRAS
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- 2020
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15. CMEs in the Heliosphere: III. A Statistical Analysis of the Kinematic Properties Derived from Stereoscopic Geometrical Modelling Techniques Applied to CMEs Detected in the Heliosphere from 2008 to 2014 by STEREO/HI-1
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Barnes, D., Davies, J. A., Harrison, R. A., Byrne, J. P., Perry, C. H., Bothmer, V., Eastwood, J. P., Gallagher, P. T., Kilpua, E. K. J., Möstl, C., Rodriguez, L., Rouillard, A. P., and Odstrcil, D.
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Astrophysics - Solar and Stellar Astrophysics ,Physics - Space Physics - Abstract
We present an analysis of coronal mass ejections (CMEs) observed by the Heliospheric Imagers (HIs) on board NASA's Solar Terrestrial Relations Observatory (STEREO) spacecraft. Between August 2008 and April 2014 we identify 273 CMEs that are observed simultaneously, by the HIs on both spacecraft. For each CME, we track the observed leading edge, as a function of time, from both vantage points, and apply the Stereoscopic Self-Similar Expansion (SSSE) technique to infer their propagation throughout the inner heliosphere. The technique is unable to accurately locate CMEs when their observed leading edge passes between the spacecraft, however, we are able to successfully apply the technique to 151, most of which occur once the spacecraft separation angle exceeds 180 degrees, during solar maximum. We find that using a small half-width to fit the CME can result in observed acceleration to unphysically high velocities and that using a larger half-width can fail to accurately locate the CMEs close to the Sun because the method does not account for CME over-expansion in this region. Observed velocities from SSSE are found to agree well with single-spacecraft (SSEF) analysis techniques applied to the same events. CME propagation directions derived from SSSE and SSEF analysis agree poorly because of known limitations present in the latter. This work was carried out as part of the EU FP7 HELCATS (Heliospheric Cataloguing, Analysis and Techniques Service) project (http://www.helcats-fp7.eu/).
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- 2020
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16. Interplanetary scintillation (IPS) analyses during LOFAR campaign mode periods that include the first three Parker Solar Probe close passes of the Sun
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Jackson, B.V., Tokumaru, M., Fallows, R.A., Bisi, M.M., Fujiki, K., Chashei, I., Tyul'bashev, S., Chang, O., Barnes, D., Buffington, A., Cota, L., and Bracamontes, M.
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- 2023
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17. Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends
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Górriz, J.M., Álvarez-Illán, I., Álvarez-Marquina, A., Arco, J.E., Atzmueller, M., Ballarini, F., Barakova, E., Bologna, G., Bonomini, P., Castellanos-Dominguez, G., Castillo-Barnes, D., Cho, S.B., Contreras, R., Cuadra, J.M., Domínguez, E., Domínguez-Mateos, F., Duro, R.J., Elizondo, D., Fernández-Caballero, A., Fernandez-Jover, E., Formoso, M.A., Gallego-Molina, N.J., Gamazo, J., González, J. García, Garcia-Rodriguez, J., Garre, C., Garrigós, J., Gómez-Rodellar, A., Gómez-Vilda, P., Graña, M., Guerrero-Rodriguez, B., Hendrikse, S.C.F., Jimenez-Mesa, C., Jodra-Chuan, M., Julian, V., Kotz, G., Kutt, K., Leming, M., de Lope, J., Macas, B., Marrero-Aguiar, V., Martinez, J.J., Martinez-Murcia, F.J., Martínez-Tomás, R., Mekyska, J., Nalepa, G.J., Novais, P., Orellana, D., Ortiz, A., Palacios-Alonso, D., Palma, J., Pereira, A., Pinacho-Davidson, P., Pinninghoff, M.A., Ponticorvo, M., Psarrou, A., Ramírez, J., Rincón, M., Rodellar-Biarge, V., Rodríguez-Rodríguez, I., Roelofsma, P.H.M.P., Santos, J., Salas-Gonzalez, D., Salcedo-Lagos, P., Segovia, F., Shoeibi, A., Silva, M., Simic, D., Suckling, J., Treur, J., Tsanas, A., Varela, R., Wang, S.H., Wang, W., Zhang, Y.D., Zhu, H., Zhu, Z., and Ferrández-Vicente, J.M.
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- 2023
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18. Empagliflozin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial
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Abani, O, Abbas, A, Abbas, F, Abbas, J, Abbas, K, Abbas, M, Abbasi, S, Abbass, H, Abbott, A, Abdallah, N, Abdelaziz, A, Abdelfattah, M, Abdelqader, B, Abdul, A, Abdul, B, Abdul, S, Abdul Rasheed, A, Abdulakeem, A, Abdul-Kadir, R, Abdullah, A, Abdulmumeen, A, Abdul-Raheem, R, Abdulshukkoor, N, Abdusamad, K, Abed El Khaleq, Y, Abedalla, M, Abeer Ul Amna, A, Abel, L, Abernethy, K, Abeywickrema, M, Abhinaya, C, Abidin, A, Aboaba, A, Aboagye-Odei, A, Aboah, C, Aboelela, H, Abo-Leyah, H, Abouelela, K, Abou-Haggar, A, Abouibrahim, M, Abousamra, A, Abouzaid, M, Abraham, M, Abraham, T, Abraheem, A, Abrams, J, Abrams, R, Abu, HJ, Abu-Arafeh, A, Abubacker, SM, Abung, A, Abusamra, Y, Aceampong, Y, Achara, A, Acharya, D, Acheampong, F, Acheampong, P, Acheampong, S, Acheson, J, Achieng, S, Acosta, A, Acquah, R, Acton, C, Adabie-Ankrah, J, Adair, P, Adam, AS, Adam, F, Adam, M, Adamali, H, Adamczyk, M, Adams, C, Adams, D, Adams, K, Adams, L, Adams, N, Adams, R, Adams, T, Adamu-Ikeme, L, Adatia, K, Adcock, K, Addai-Boampong, L, Addo, A, Adeagbo, O, Adebiyi, A, Adedeji, O, Adegeye, Y, Adegoke, K, Adell, V, Adenwalla, S, Adeoye, FW, Adesemoye, OA, Adewunmi, EO, Adeyanju, A, Adeyemi, J, Adeyemo, T, Adhikari, B, Adhikari, SA, Adhikary, R, Aditya, A, Adjepong, P, Adkins, G, Adnan, A, Adriaanse, M, Aeron-Thomas, J, Affleck, D, Afnan, C, Afridi, M, Afrim, P, Afriyie, FA, Aftab, ZA, Afum-Adjei Awuah, A, Agarwal, M, Agasiya, PN, Agbeko, R, Agbo, C, Aggarwal, S, Aghababaie, A, Aguilar Jimenez, L, Agyekum, JA, Agyen, K, Ahadome, EK, Ahamed Sadiq, S, Ahammed Nazeer, MH, Ahmad, M, Ahmad, S, Ahmed, A, Ahmed, BAR, Ahmed, B, Ahmed, F, Ahmed, H, Ahmed, I, Ahmed, K, Ahmed, L, Ahmed, M, Ahmed, MC, Ahmed, MS, Ahmed, N, Ahmed, O, Ahmed, RA, Ahmed, R, Ahmed, S, Ahmed, SG, Ahmed, SH, Ahmed Ali, R, Ahmed Mohamud, B, Ahmer, S, Ahonia, A, Aidoo, C, Aiken, C, Ail, D, Ainsworth, M, Aissa, M, Aitken, L, Ajay, B, Ajibode, A, Ajmi, A, Akhtar, N, Akili, S, Akinbiyi, B, Akindolie, O, Akinfenwa, Y, Akinkugbe, O, Akinpelu, I, Akram, M, Aktinade, O, Akudi, U, Al Aaraj, ASAR, Al Balushi, A, Al Dakhola, M, Al Swaifi, A, Al-Abadi, E, Alabi, A, Aladangady, N, Alafifi, M, Alam, A, Alam, S, Al-Asadi, A, Alatzoglou, K, Albert, P, Albertus, A, Albon, L, Alcala, A, Alcorn, G, Alcorn, S, Aldana, A, Alderdice, D, Aldesouki, A, Aldouri, R, Aldridge, J, Aldridge, N, Ale, RM, Alegria, A, Alexander, A, Alexander, C, Alexander, J, Alexander, PDG, Al-fori, J, Alghazawi, L, Alhabsha, O, Al-Hakim, B, Alhameed, R, Al-Hayali, M, Al-Hity, S, Ali, A, Ali, FR, Ali, J, Ali, M, Ali, MS, Ali, N, Ali, O, Ali, R, Ali, S, Aliberti, E, Alin, J, Alina, A, Alipustain, A, Alisjahbana, B, Aliyuda, F, Alizadeh, K, Al-Jibury, M, Al-Juboori, S, Al-Khalil, M, Alkhudhayri, A, Alkhusheh, M, Allan, F, Allan, N, Allanson, A, Allcock, R, Allen, E, Allen, J, Allen, K, Allen, L, Allen, P, Allen, R, Allen, S, Allen, T, Alli, A, Allison, K, Allman, B, Allsop, HK, Allsop, L, Allsup, D, Almahroos, AFT, Al-Moasseb, H, Al-Obaidi, M, Alomari, L, Al-Rabahi, A, Al-Ramadhani, B, Al-Saadi, Z, Al-Sammarraie, R, Alshaer, I, Al-Shahi Salman, R, Al-Shamkhani, W, Alsheikh, F, Al-Sheklly, B, Altaf, S, Alty, A, Alvarez, M, Alvarez Corral, M, Alveyn, E, Alzetani, M, Amamou, S, Amar, N, Ambalavanan, S, Ambrogetti, R, Ambrose, C, Ameen, A, Amelia Ganefianty, A, Ames, K, Amezaga, MR, Amin, A, Amin, K, Amin, S, Amin, T, Amit, B, Amjad, A, Amjad, N, Amoah-Dankwa, J, Amoako-Adusei, A, Amosun, V, Amsal, M, Amsha, K, Amuasi, J, Amutio Martin, N, Amy, P, Anada, A, Anand, A, Anandappa, S, Anantapatnaikuni, SD, Andari, NKN, Anderson, E, Anderson, J, Anderson, L, Anderson, M, Anderson, N, Anderson, R, Anderson, S, Anderson, W, Andreou, P, Andrews, A, Andrews, J, Aneke, K, Ang, A, Ang, WW, Angel, T, Angela, A, Angelini, P, Anguvaa, L, Anichtchik, O, Anim-Somuah, M, Aniruddhan, K, Annett, J, Anning, L, Ansah, M, Anstey, PJ, Anstey, R, Anthony, A, Anthony-Pillai, A, Antill, P, Antonina, Z, Anu, V, Anwar, M, Anwar, S, Apetri, E, Apostolopoulos, A, Appleby, S, Appleyard, D, Aquino, MF, Araba, B, Aransiola, S, Araujo, M, Archer, A, Archer, D, Archer, S, Arcoria, D, Ardley, C, Arhin-Sam, G, Arias, A-M, Aribike, O, Arimoto, R, Arisanti, NLPE, Arkley, C, Armah, C, Armata, I, Armistead, J, Armitage, A, Armstrong, C, Armstrong, M, Armstrong, S, Armstrong, W, Armtrong, P, Arndt, H, Arnison-Newgass, C, Arnold, D, Arnold, R, Arnott, A, Arora, D, Arora, K, Arora, P, Arora, R, Arter, A, Arthur, A, Artini, NM, Arumaithurai, A, Arya, A, Arya, R, Aryal, D, Asandei, D, Asare, GA, Asghar, A, Asghar, M, Ashab, A, Ashbrook-Raby, C, Ashby, H, Ashcroft, J, Ashcroft, S, Asher, G, Ashfak, Z, Ashfaq, A, Asiamah, HA, Ashish, A, Ashley, D, Ashman-Flavell, S, Ashok, S, Ashour, A-E-A, Ashraf, MZ, Ashraf, S, Ashraq, MB, Ashton, D, Ashton, S, Ashworth, A, Ashworth, FJ, Ashworth, R, Aslam, A, Aslam, I, Aslam, S, Aslett, L, Asogan, H, Asrar, A, Assaf, O, Astin-Chamberlain, R, Atabudzi, YE, Athavale, P, Athorne, D, Atkins, B, Atkins, C, Atkins, S, Atkinson, J, Atkinson, V, Atomode, A, Atraskiewicz, B, Attia, AA, Attubato, E, Attwood, M, Aubrey, P, Auer, Z, Aujayeb, A, Aung, AT, Aung, H, Aung, HWW, Aung, KK, Aung, KT, Aung, N, Aung, Y, Aung, ZM, Austin, E, Austin, K, Auwal, A, Avari, M, Avery, M, Aveyard, N, Avis, J, Aviss, G, Avram, C, Avram, P, Awadelkareem, A, Awadzi, G, Awaly, M, Awan, A, Awisi, S, Aya, A, Ayaz, E, Ayerh, JM, Ayers, A, Azam, J, Azeem, A, Azharuddin, M, Aziz, A, Aziz, G, Aziz, I, Aziz, N, Azkoul, A, Azman Shah, A, Azzopardi, G, Azzoug, H, Babatunde, F, Babi, M, Babiker, B, Babington, G, Babirecki, M, Babores, M, Babs-Osibodu, AO, Bac, T, Bacciarelli, S, Bachar, R, Bachour, M-E, Bachti, A, Bacon, G, Bacon, J, Badal, B, Badat, A, Bader, M, Badhan, GR, Badhrinarayanan, S, Bae, JP, Baggaley, A, Baggott, A, Bagley, G, Bagmane, D, Bagshaw, L, Bahadori, K, Bahurupi, Y, Bailey, A, Bailey, J, Bailey, K, Bailey, L, Bailey, MA, Bailey, M, Bailey, P, Bailey, S, Baillie, H, Baillie, JK, Bain, J, Bains, V, Baird, D, Baird, E, Baird, K, Baird, S, Baird, T, Baird, Y, Bajandouh, A, Baker, DC, Baker, E, Baker, J, Baker, K, Baker, M, Baker, R, Baker, T-A, Baker, V, Bakere, H, Bakerly, N, Baker-Moffatt, M, Bakhai, A, Bakhtiar, N, Bakoulas, P, Bakthavatsalam, D, Balachandran, N, Balan, A, Balasingam, P, Balaskas, T, Balasubramaniam, M, Balatoni, N, Balcombe, A, Baldwin, A, Baldwin, C, Baldwin, D, Baldwin, F, Baldwin-Jones, R, Bale, N, Balfour, J, Ball, M, Ball, Ro, Ballard, K, Balluz, I, Balmforth, C, Balogh, E, Baltmr, A, Baluwala, A, Bambridge, G, Bamford, A, Bamford, P, Bamgboye, A, Bancroft, E, Bancroft, H, Banda, J, Bandaru, K, Bandi, S, Bandla, N, Bandyopadhyam, S, Banerjee, A, Banerjee, R, Bang, P, Baniya, S, Bani-Saad, O, Banks, H, Banks, L, Banks, P, Bann, C, Bannister, H, Bannister, O, Banton, L, Bao, T, Baptist, M, Baqai, T, Baral, AM, Baral, SC, Baramova, D, Barber, R, Barbon, E, Barbosa, M, Barbour, J, Barclay, A, Barclay, C, Bardsley, G, Bareford, S, Bari, S, Barimbing, M, Barker, A, Barker, D, Barker, E, 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Yeung, CY, Yew, P, Yewatkar, D, Ylquimiche Melly, L, Ynter, I, Yong, H, Yorke, J, Youens, J, Younes Ibrahim, A, Young, E, Young, G, Young, L, Yousafzar, A, Youssouf, S, Yousuf, A, Yovita, H, Yu, C, Yuan, JSJ, Yufaniaputri, N, Yung, B, Yusef, D, Yusef, S, Yusuf, I, Zafar, A-S, Zagalo, S, Zaher, S, Zahoor, A, Zainab, M, Zak, T, Zaki, K, Zakir, N, Zalewska, K, Zamalloa, A, Zaman, M, Zaman, S, Zamikula, J, Zammit, L, Zammit-Mangion, M, Zawadzka, M, Zayed, M, Zebracki, E, Zehnder, D, Zeidan, L, Zeinali, D, Zhang, J, Zhao, X, Zheng, D, Zhu, D, Zia, M, Zibdeh, O, Zill-E-Huma, R, Zin, ET, Zincone, E, Zindoga, G, Zinkin, E, Zinyemba, V, Zipitis, C, Zitter, L, Zmierczak, A, Zubikarai, G, Zubir, A, Zuhra, N, Zulaikha, R, Zulfikar, S, Zullo, C, and Zuriaga-Alvaro, A
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- 2023
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19. Finite spatial-grid effects in energy-conserving particle-in-cell algorithms
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Barnes, D. C. and Chacon, L.
- Subjects
Physics - Plasma Physics - Abstract
Finite-grid (or aliasing) instabilities are pervasive in particle-in-cell (PIC) plasma simulation algorithms, and force the modeler to resolve the smallest (Debye) length scale in the problem regardless of dynamical relevance. These instabilities originate in the aliasing of interpolation errors between mesh quantities and particles (which live in the space-time continuum). Recently, strictly energy-conserving PIC (EC-PIC) algorithms have been developed that promise enhanced robustness against aliasing instabilities. In this study, we confirm by analysis that EC-PIC is stable against aliasing instabilities for stationary plasmas. For drifting plasmas, we demonstrate by analysis and numerical experiments that, while EC-PIC algorithms are not free from these instabilities in principle, they feature a benign stability threshold for finite-temperature plasmas that make them usable in practice for a large class of problems (featuring ambipolarity and realistic ion-electron mass ratios) without the need to resolve Debye lengths spatially. We also demonstrate that this threshold is absent for the popular momentum-conserving PIC algorithms, which are therefore unstable for both drifting and stationary plasmas., Comment: 17 pages, 12 figures
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- 2019
20. Management of purpura fulminans skin loss at a regional burns centre: Sixteen-year experience
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Goodall, RJ, Roberts, J, Correia Duarte, Marco, Frew, Q, Barnes, D, Dziewulski, P, Shelley, O, and El-Muttardi, N
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- 2023
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21. Immersive Virtual Reality Experiences for All-Sky Data
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Fluke, C. J. and Barnes, D. G.
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Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Solar and Stellar Astrophysics - Abstract
Spherical coordinate systems, which are ubiquitous in astronomy, cannot be shown without distortion on flat, two-dimensional surfaces. This poses challenges for the two complementary phases of visual exploration -- making discoveries in data by looking for relationships, patterns or anomalies -- and publication -- where the results of an exploration are made available for scientific scrutiny or communication. This is a long-standing problem, and many practical solutions have been developed. Our allskyVR approach provides a workflow for experimentation with commodity virtual reality head-mounted displays. Using the free, open source S2PLOT programming library, and the A-Frame WebVR browser-based framework, we provide a straightforward way to visualise all-sky catalogues on a user-centred, virtual celestial sphere. The allskyVR distribution contains both a quickstart option, complete with a gaze-based menu system, and a fully customisable mode for those who need more control of the immersive experience. The software is available for download from: https://github.com/cfluke/allskyVR, Comment: 11 pages, 3 figures, accepted for publication in Publications of the Astronomical Society of Australia
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- 2018
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22. CMEs in the Heliosphere: I. A Statistical Analysis of the Observational Properties of CMEs Detected in the Heliosphere from 2007 to 2017 by STEREO/HI-1
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Harrison, R. A., Davies, J. A., Barnes, D., Byrne, J. P., Perry, C. H., Bothmer, V., Eastwood, J. P., Gallagher, P. T., Kilpua, E. K. J., Möstl, C., Rodriguez, L., Rouillard, A. P., and Odstrcil, D.
- Subjects
Astrophysics - Solar and Stellar Astrophysics - Abstract
We present a statistical analysis of coronal mass ejections (CMEs) imaged by the Heliospheric Imager (HI) instruments aboard NASAs twin-spacecraft STEREO mission between April 2007 and August 2017 for STEREO-A and between April 2007 and September 2014 for STEREO-B. The analysis exploits a catalogue that was generated within the FP7 HELCATS project. Here, we focus on the observational characteristics of CMEs imaged in the heliosphere by the inner (HI-1) cameras. More specifically, in this paper we present distributions of the basic observational parameters - namely occurrence frequency, central position angle (PA) and PA span - derived from nearly 2000 detections of CMEs in the heliosphere by HI-1 on STEREO-A or STEREO-B from the minimum between Solar Cycles 23 and 24 to the maximum of Cycle 24; STEREO-A analysis includes a further 158 CME detections from the descending phase of Cycle 24, by which time communication with STEREO-B had been lost. We compare heliospheric CME characteristics with properties of CMEs observed at coronal altitudes, and with sunspot number. As expected, heliospheric CME rates correlate with sunspot number, and are not inconsistent with coronal rates once instrumental factors/differences in cataloguing philosophy are considered. As well as being more abundant, heliospheric CMEs, like their coronal counterparts, tend to be wider during solar maximum. Our results confirm previous coronagraph analyses suggesting that CME launch sites don't simply migrate to higher latitudes with increasing solar activity. At solar minimum, CMEs tend to be launched from equatorial latitudes while, at maximum, CMEs appear to be launched over a much wider latitude range; this has implications for understanding the CME/solar source association. Our analysis provides some supporting evidence for the systematic dragging of CMEs to lower latitude as they propagate outwards., Comment: 26 pages, 8 figures, in press at Solar Physics. The abstract has been shortened to comply with the allowed length at arxiv.org
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- 2018
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23. The Slagging Behaviour of Three UK Power Station Coals in an Ash Deposition Rig
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Barnes, D. I., primary, Lewit, M. W., additional, and Smith, M., additional
- Published
- 2022
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- View/download PDF
24. Sodium and Potassium Release From UK Coals During the Early Stages of Pulverised Coal Combustion
- Author
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Barnes, D. I., primary, Wardle, D. G., additional, and Kean, D., additional
- Published
- 2022
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25. Major burns: Part 1. Epidemiology, pathophysiology and initial management
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McCann, C., Watson, A., and Barnes, D.
- Published
- 2022
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26. Growing a `Cosmic Beast': Observations and Simulations of MACS J0717.5+3745
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Jauzac, M., Eckert, D., Schaller, M., Schwinn, J., Massey, R., Bahé, Y., Baugh, C., Barnes, D., Vecchia, C. Dalla, Ebeling, H., Harvey, D., Jullo, E., Kay, S. T., Kneib, J. -P., Limousin, M., Medezinski, E., Natarajan, P., Nonino, M., Robertson, A., Tam, S. I., and Umetsu, K.
- Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present a gravitational lensing and X-ray analysis of a massive galaxy cluster and its surroundings. The core of MACS\,J0717.5+3745 ($M(R<1\,{\rm Mpc})\sim$\,$2$$\times$$10^{15}\,\msun$, $z$=$0.54$) is already known to contain four merging components. We show that this is surrounded by at least seven additional substructures with masses ranging from $3.8-6.5\times10^{13}\,\msun$, at projected radii $1.6$ to $4.9$\,Mpc. We compare MACS\,J0717 to mock lensing and X-ray observations of similarly rich clusters in cosmological simulations. The low gas fraction of substructures predicted by simulations turns out to match our observed values of $1$--$4\%$. Comparing our data to three similar simulated halos, we infer a typical growth rate and substructure infall velocity. That suggests MACS\,J0717 could evolve into a system similar to, but more massive than, Abell\,2744 by $z=0.31$, and into a $\sim$\,$10^{16}\,\msun$ supercluster by $z=0$. The radial distribution of infalling substructure suggests that merger events are strongly episodic; however we find that the smooth accretion of surrounding material remains the main source of mass growth even for such massive clusters., Comment: 18 pages, 6 figures, 8 tables, Accepted for publication in MNRAS
- Published
- 2017
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27. Modeling observations of solar coronal mass ejections with heliospheric imagers verified with the Heliophysics System Observatory
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Möstl, C., Isavnin, A., Boakes, P. D., Kilpua, E. K. J., Davies, J. A., Harrison, R. A., Barnes, D., Krupar, V., Eastwood, J. P., Good, S. W., Forsyth, R. J., Bothmer, V., Reiss, M. A., Amerstorfer, T., Winslow, R. M., Anderson, B. J., Philpott, L. C., Rodriguez, L., Rouillard, A. P., Gallagher, P. T., and Zhang, T. L.
- Subjects
Astrophysics - Solar and Stellar Astrophysics ,Physics - Space Physics - Abstract
We present an advance towards accurately predicting the arrivals of coronal mass ejections (CMEs) at the terrestrial planets, including Earth. For the first time, we are able to assess a CME prediction model using data over 2/3 of a solar cycle of observations with the Heliophysics System Observatory. We validate modeling results of 1337 CMEs observed with the Solar Terrestrial Relations Observatory (STEREO) heliospheric imagers (HI) (science data) from 8 years of observations by 5 in situ observing spacecraft. We use the self-similar expansion model for CME fronts assuming 60 degree longitudinal width, constant speed and constant propagation direction. With these assumptions we find that 23%-35% of all CMEs that were predicted to hit a certain spacecraft lead to clear in situ signatures, so that for 1 correct prediction, 2 to 3 false alarms would have been issued. In addition, we find that the prediction accuracy does not degrade with the HI longitudinal separation from Earth. Predicted arrival times are on average within 2.6 +/- 16.6 hours difference of the in situ arrival time, similar to analytical and numerical modeling, and a true skill statistic of 0.21. We also discuss various factors that may improve the accuracy of space weather forecasting using wide-angle heliospheric imager observations. These results form a first order approximated baseline of the prediction accuracy that is possible with HI and other methods used for data by an operational space weather mission at the Sun-Earth L5 point., Comment: 27 pages, 7 figures, 3 tables, accepted for publication in the AGU journal "Space Weather" on 2017 July 1
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- 2017
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28. A COMPARATIVE ANALYSIS OF FOUR PROMS TO ASSESS MEDIUM TO LONG-TERM PATIENT SATISFACTION FOLLOWING OPEN MIDLINE INCISIONAL HERNIA REPAIR
- Author
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Kulkarni, G, primary, Attafi, W, additional, Nanthakumaran, P, additional, Barnes, D, additional, and Hammond, T, additional
- Published
- 2024
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29. Bronchoalveolar Lavage Fluid Eosinophilia Is Associated With Worse Outcomes After Lung Transplant
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Hwang, J., primary, Barnes, D., additional, Shitanishi, L., additional, Chen, P., additional, Rampolla, R., additional, and Zaffiri, L., additional
- Published
- 2024
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30. Cold Static Preservation at 10°C and Delirium Following Lung Transplant
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Kaderi, T., primary, Yuen, A., additional, Shitanishi, L., additional, Barnes, D., additional, Rampolla, R., additional, and Zaffiri, L., additional
- Published
- 2024
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31. A Two-Threshold dd-cfDNA Algorithm for Detection of Rejection After Heart Transplant
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Kim, P.J., primary, Olymbios, M., additional, Sideris, K., additional, Wever-Pinzon, O., additional, Tran, T., additional, Kaur, N., additional, Carey, S., additional, Chen, Y., additional, Barnes, D., additional, Ahmed, E., additional, Demko, Z.P., additional, Prewett, A., additional, Adler, E., additional, and Stehlik, J., additional
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- 2024
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32. Variation in zoobenthic blue carbon in the Arctic’s Barents Sea shelf sediments
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Souster, T. A., Barnes, D. K. A., and Hopkins, J.
- Published
- 2020
33. Verification of High-Rate Vertical Loading Laboratory Skeletal Fractures by Comparison with Theater Injury Patterns
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Danelson, K. A., Polich, J. G., Barnes, D. R., Bullock, G. S., Scott, A. T., Halvorson, J. J., O’Gara, T., Pilson, H. T., Babcock, S., Birkedal, J., McAllister, B., and Loftis, K. L.
- Published
- 2021
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34. Forecasting and modelling the terrestrial effects of space weather using STEREO and CMAT2
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Barnes, D.
- Subjects
523.5 - Abstract
The work presented in this thesis focuses on two aspects of space weather. The first of these uses NASA's Solar TErrestrial RElations Observatory (STEREO) to measure solar wind properties. The Heliospheric Imagers (HIs) on-board each of the two STEREO spacecraft are used to infer the density distribution within two Coronal Mass Ejections (CMEs) by tomographic inversion of white light images. The resulting densities from successive images are then used to determine how the CMEs evolve through the heliosphere and to make estimates of their speed and density at Earth, which are compared with measurements from near-Earth spacecraft. The second area of research involves modelling studies of how the neutral atmosphere responds to energy transfer from the solar wind. Data from the Super Dual Auroral Radar Network (SuperDARN) provide high spatial and temporal resolution measurements of Earth's high latitude electric field in both hemispheres. These data are used to drive the UCL Coupled Middle Atmosphere Thermosphere (CMAT2) General Circulation Model (GCM), which is used to study the effects of electric field variability and hemispheric asymmetry in ionosphere-thermosphere coupling. Results of simulations using this new version of CMAT2 are compared to ground- and space-based observations. As a means to connect these two areas of research, it was one original aim of this thesis to develop CMAT2 in such a way that STEREO observations could be used to drive its solar wind energy input. Chapter 5 shows that some limited information about geoeffective solar wind properties, such as speed and density, may be determined using HI data. However, detailed information about the interplanetary magnetic field (IMF) is required to accurately simulate energy transfer between the ionosphere and neutral atmosphere. Instead, a new electric field model has been developed, which allows CMAT2 to be driven using the IMF as an input. This model quantifies the electric field variability, as a means to accurately model Joule heating, which is a problem common to many GCMs.
- Published
- 2017
35. The XXL survey: first results and future
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Pierre, M., Adami, C., Birkinshaw, M., Chiappetti, L., Ettori, S., Evrard, A., Faccioli, L., Gastaldello, F., Giles, P., Horellou, C., Iovino, A., Koulouridis, E., Lidman, C., Brun, A. Le, Maughan, B., Maurogordato, S., McCarthy, I., Miyazaki, S., Pacaud, F., Paltani, S., Plionis, M., Reiprich, T., Sadibekova, T., Smolcic, V., Snowden, S., Surdej, J., Tsirou, M., Vignali, C., Willis, J., Alis, S., Altieri, B., Baran, N., Benoist, C., Bongiorno, A., Bremer, M., Butler, A., Cappi, A., Caretta, C., Ciliegi, P., Clerc, N., Corasaniti, P. S., Coupon, J., Delhaize, J., Delvecchio, I., Democles, J., Desai, Sh., Devriendt, J., Dubois, Y., Eckert, D., Elyiv, A., Farahi, A., Ferrari, C., Fotopoulou, S., Forman, W., Georgantopoulos, I., Guglielmo, V., Huynh, M., Jerlin, N., Jones, Ch., Lavoie, S., Fevre, J. -P. Le, Lieu, M., Kilbinger, M., Marulli, F., Mantz, A., McGee, S., Melin, J. -B., Melnyk, O., Moscardini, L., Novak, M., Piconcelli, E., Poggianti, B., Pomarede, D., Pompei, E., Ponman, T., Ceja, M. E. Ramos, Ranalli, P., Rapetti, D., Raychaudhury, S., Ricci, M., Rottgering, H., Sahlén, M., Sauvageot, J. -L., Schimd, C., Sereno, M., Smith, G. P., Umetsu, K., Valageas, P., Valotti, A., Valtchanov, I., Veropalumbo, A., Ascaso, B., Barnes, D., De Petris, M., Durret, F., Donahue, M., Ithana, M., Jarvis, M., Johnston-Hollitt, M., Kalfountzou, E., Kay, S., La Franca, F., Okabe, N., Muzzin, A., Rettura, A., Ricci, F., Ridl, J., Risaliti, G., Takizawa, M., Thomas, P., and Truong, N.
- Subjects
Astrophysics - Astrophysics of Galaxies ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The XXL survey currently covers two 25 sq. deg. patches with XMM observations of ~10ks. We summarise the scientific results associated with the first release of the XXL data set, that occurred mid 2016. We review several arguments for increasing the survey depth to 40 ks during the next decade of XMM operations. X-ray (z<2) cluster, (z<4) AGN and cosmic background survey science will then benefit from an extraordinary data reservoir. This, combined with deep multi-$\lambda$ observations, will lead to solid standalone cosmological constraints and provide a wealth of information on the formation and evolution of AGN, clusters and the X-ray background. In particular, it will offer a unique opportunity to pinpoint the z>1 cluster density. It will eventually constitute a reference study and an ideal calibration field for the upcoming eROSITA and Euclid missions., Comment: Proceeding of the XMM Next Decade Workshop held at ESAC, 9-11 May 2016
- Published
- 2016
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36. The Ultimate Display
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Fluke, C. J. and Barnes, D. G.
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
Astronomical images and datasets are increasingly high-resolution and multi-dimensional. The vast majority of astronomers perform all of their visualisation and analysis tasks on low-resolution, two-dimensional desktop monitors. If there were no technological barriers to designing the ultimate stereoscopic display for astronomy, what would it look like? What capabilities would we require of our compute hardware to drive it? And are existing technologies even close to providing a true 3D experience that is compatible with the depth resolution of human stereoscopic vision? We consider the CAVE2 (an 80 Megapixel, hybrid 2D and 3D virtual reality environment directly integrated with a 100 Tflop/s GPU-powered supercomputer) and the Oculus Rift (a low- cost, head-mounted display) as examples at opposite financial ends of the immersive display spectrum., Comment: 4 pages, 2 figures, to appear in Proceedings of ADASS XXV (Sydney, Australia; 2015), edited by N. P. F. Lorente & K. Shortridge (San Francisco: ASP), ASP Conf. Series
- Published
- 2016
37. Soybean Herbicide Development
- Author
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Barnes, D. L., primary
- Published
- 2022
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38. Overview of the JET results in support to ITER
- Author
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Litaudon, X, Abduallev, S, Abhangi, M, Abreu, P, Afzal, M, Aggarwal, KM, Ahlgren, T, Ahn, JH, Aho-Mantila, L, Aiba, N, Airila, M, Albanese, R, Aldred, V, Alegre, D, Alessi, E, Aleynikov, P, Alfier, A, Alkseev, A, Allinson, M, Alper, B, Alves, E, Ambrosino, G, Ambrosino, R, Amicucci, L, Amosov, V, Sundén, E Andersson, Angelone, M, Anghel, M, Angioni, C, Appel, L, Appelbee, C, Arena, P, Ariola, M, Arnichand, H, Arshad, S, Ash, A, Ashikawa, N, Aslanyan, V, Asunta, O, Auriemma, F, Austin, Y, Avotina, L, Axton, MD, Ayres, C, Bacharis, M, Baciero, A, Baião, D, Bailey, S, Baker, A, Balboa, I, Balden, M, Balshaw, N, Bament, R, Banks, JW, Baranov, YF, Barnard, MA, Barnes, D, Barnes, M, Barnsley, R, Wiechec, A Baron, Orte, L Barrera, Baruzzo, M, Basiuk, V, Bassan, M, Bastow, R, Batista, A, Batistoni, P, Baughan, R, Bauvir, B, Baylor, L, Bazylev, B, Beal, J, Beaumont, PS, Beckers, M, Beckett, B, Becoulet, A, Bekris, N, Beldishevski, M, Bell, K, Belli, F, Bellinger, M, Belonohy, É, Ayed, N Ben, Benterman, NA, Bergsåker, H, Bernardo, J, Bernert, M, Berry, M, Bertalot, L, Besliu, C, Beurskens, M, Bieg, B, Bielecki, J, Biewer, T, Bigi, M, Bílková, P, Binda, F, Bisoffi, A, Bizarro, JPS, and Björkas, C
- Subjects
Affordable and Clean Energy ,JET ,plasma ,fusion ,ITER ,Atomic ,Molecular ,Nuclear ,Particle and Plasma Physics ,Fluids & Plasmas - Abstract
The 2014-2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L-H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at β N ∼ 1.8 and n/n GW ∼ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D-T campaign and 14 MeV neutron calibration strategy are reviewed.
- Published
- 2017
39. Statistical Agnostic Mapping: A framework in neuroimaging based on concentration inequalities
- Author
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Gorriz, J.M., Jimenez-Mesa, C., Romero-Garcia, R., Segovia, F., Ramirez, J., Castillo-Barnes, D., Martinez-Murcia, F.J., Ortiz, A., Salas-Gonzalez, D., Illan, I.A., Puntonet, C.G., Lopez-Garcia, D., Gomez-Rio, M., and Suckling, J.
- Published
- 2021
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40. Development of an adverse outcome pathway network for nephrotoxicity
- Author
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Pharmacology, Afd Pharmacology, Barnes, D. A., Firman, J. W., Belfield, S. J., Cronin, M. T. D., Vinken, M., Janssen, M. J., Masereeuw, R., Pharmacology, Afd Pharmacology, Barnes, D. A., Firman, J. W., Belfield, S. J., Cronin, M. T. D., Vinken, M., Janssen, M. J., and Masereeuw, R.
- Published
- 2024
41. Rational SO(2)-Equivariant Spectra
- Author
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Barnes, D., Greenlees, J. P. C., Kedziorek, M., and Shipley, B.
- Subjects
Mathematics - Algebraic Topology ,55N91, 55P42, 55P60 - Abstract
We prove that the category of rational SO(2)-equivariant spectra has a simple algebraic model. Furthermore, all of our model categories and Quillen equivalences are monoidal, so we can use this classification to understand ring spectra and module spectra via the algebraic model., Comment: 29 pages. arXiv admin note: substantial text overlap with arXiv:1201.6610
- Published
- 2015
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42. The Murchison Widefield Array Correlator
- Author
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Ord, S. M., Crosse, B., Emrich, D., Pallot, D., Wayth, R. B., Clark, M. A., Tremblay, S. E., Arcus, W., Barnes, D., Bell, M., Bernardi, G., Bhat, N. D. R., Bowman, J. D., Briggs, F., Bunton, J. D., Cappallo, R. J., Corey, B. E., Deshpande, A. A., deSouza, L., Ewell-Wice, A., Feng, L., Goeke, R., Greenhill, L. J., Hazelton, B. J., Herne, D., Hewitt, J. N., Hindson, L., Hurley-Walker, H., Jacobs, D., Johnston-Hollitt, M., Kaplan, D. L., Kasper, J. C., Kincaid, B. B., Koenig, R., Kratzenberg, E., Kudryavtseva, N., Lenc, E., Lonsdale, C. J., Lynch, M. J., McKinley, B., McWhirter, S. R., Mitchell, D. A., Morales, M. F., Morgan, E., Oberoi, D., Offringa, A., Pathikulangara, J., Pindor, B., Prabu, T., Procopio, P., Remillard, R. A., Riding, J., Rogers, A. E. E., Roshi, A., Salah, J. E., Sault, R. J., Shankar, N. Udaya, Srivani, K. S., Stevens, J., Subrahmanyan, R., Tingay, S. J., Waterson, M., Webster, R. L., Whitney, A. R., Williams, A., Williams, C. L., and Wyithe, J. S. B.
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics ,Computer Science - Computational Engineering, Finance, and Science - Abstract
The Murchison Widefield Array (MWA) is a Square Kilometre Array (SKA) Precursor. The telescope is located at the Murchison Radio--astronomy Observatory (MRO) in Western Australia (WA). The MWA consists of 4096 dipoles arranged into 128 dual polarisation aperture arrays forming a connected element interferometer that cross-correlates signals from all 256 inputs. A hybrid approach to the correlation task is employed, with some processing stages being performed by bespoke hardware, based on Field Programmable Gate Arrays (FPGAs), and others by Graphics Processing Units (GPUs) housed in general purpose rack mounted servers. The correlation capability required is approximately 8 TFLOPS (Tera FLoating point Operations Per Second). The MWA has commenced operations and the correlator is generating 8.3 TB/day of correlation products, that are subsequently transferred 700 km from the MRO to Perth (WA) in real-time for storage and offline processing. In this paper we outline the correlator design, signal path, and processing elements and present the data format for the internal and external interfaces., Comment: 17 pages, 9 figures. Accepted for publication in PASA. Some figures altered to meet astro-ph submission requirements
- Published
- 2015
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43. Multivariate analysis of dual-point amyloid PET intended to assist the diagnosis of Alzheimer’s disease
- Author
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Segovia, F., Ramírez, J., Castillo-Barnes, D., Salas-Gonzalez, D., Gómez-Río, M., Sopena-Novales, P., Phillips, C., Zhang, Y., and Górriz, J.M.
- Published
- 2020
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- View/download PDF
44. Support Vector Machine Failure in Imbalanced Datasets
- Author
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Illan, I. A., Gorriz, J. M., Ramirez, J., Martinez-Murcia, F. J., Castillo-Barnes, D., Segovia, F., Salas-Gonzalez, D., 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, Ferrández Vicente, José Manuel, editor, Álvarez-Sánchez, José Ramón, editor, de la Paz López, Félix, editor, Toledo Moreo, Javier, editor, and Adeli, Hojjat, editor
- Published
- 2019
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45. Periodogram Connectivity of EEG Signals for the Detection of Dyslexia
- Author
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Martinez-Murcia, F. J., Ortiz, A., Morales-Ortega, R., López, P. J., Luque, J. L., Castillo-Barnes, D., Segovia, F., Illan, I. A., Ortega, J., Ramirez, J., Gorriz, J. M., 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, Ferrández Vicente, José Manuel, editor, Álvarez-Sánchez, José Ramón, editor, de la Paz López, Félix, editor, Toledo Moreo, Javier, editor, and Adeli, Hojjat, editor
- Published
- 2019
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46. Expectation–Maximization algorithm for finite mixture of [formula omitted]-stable distributions
- Author
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Castillo-Barnes, D., Martinez-Murcia, F.J., Ramírez, J., Górriz, J.M., and Salas-Gonzalez, D.
- Published
- 2020
- Full Text
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47. Granger causality-based information fusion applied to electrical measurements from power transformers
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Rodriguez-Rivero, J., Ramirez, J., Martínez-Murcia, F.J., Segovia, F., Ortiz, A., Salas, D., Castillo-Barnes, D., Illan, I.A., Puntonet, C.G., Jimenez-Mesa, C., Leiva, F.J., Carillo, S., Suckling, J., and Gorriz, J.M.
- Published
- 2020
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48. Using Solar Orbiter as an Upstream Solar Wind Monitor for Real Time Space Weather Predictions
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Laker, R., primary, Horbury, T. S., additional, O’Brien, H., additional, Fauchon‐Jones, E. J., additional, Angelini, V., additional, Fargette, N., additional, Amerstorfer, T., additional, Bauer, M., additional, Möstl, C., additional, Davies, E. E., additional, Davies, J. A., additional, Harrison, R., additional, Barnes, D., additional, and Dumbović, M., additional
- Published
- 2024
- Full Text
- View/download PDF
49. RF dispersion relations in FRC geometries and HHFW regime
- Author
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Ceccherini, F., primary, Galeotti, L., additional, Barnes, D. C., additional, and Dettrick, S. A., additional
- Published
- 2024
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- View/download PDF
50. Comparing the Heliospheric Cataloging, Analysis, and Techniques Service (HELCATS) Manual and Automatic Catalogues of Coronal Mass Ejections Using Solar Terrestrial Relations Observatory/Heliospheric Imager (STEREO/HI) Data
- Author
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Rodriguez, L., Barnes, D., Hosteaux, S., Davies, J. A., Willems, S., Pant, V., Harrison, R. A., Berghmans, D., Bothmer, V., Eastwood, J. P., Gallagher, P. T., Kilpua, E. K. J., Magdalenic, J., Mierla, M., Möstl, C., Rouillard, A. P., Odstrčil, D., and Poedts, S.
- Published
- 2022
- Full Text
- View/download PDF
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