6 research outputs found
Impact of pneumococcal conjugate vaccination on acute otitis media incidence and severity in young children
No full textFrom 2000 onwards, national childhood pneumococcal conjugate vaccination (PCV) has been introduced across the world to prevent invasive pneumococcal disease (IPD) and childhood pneumonia. Because Streptococcus pneumoniae (S. pneumoniae) is also one of the most common pathogens causing acute middle ear infections (acute otitis media; AOM), the preventive effects of PCV may be much more wide ranging: AOM is among the commonest childhood infections and a leading cause of antibiotic prescribing, specialist referrals and ENT surgery in children. Early and dense colonisation of the nasopharynx with S. pneumoniae as well as pneumococcal AOM occurring in early life (early life AOM) have been associated with an increased risk for subsequent and more complex AOM episodes caused by nonvaccine serotypes and other otopathogens. This has led to the hypothesis that by reducing or eliminating nasopharyngeal colonisation of S. pneumoniae and preventing early life AOM by PCV in infancy, the pathogenic pathway of middle-ear mucosal damage, biofilm formation and the occurrence of chronic/recurrent otitis media can be prevented. PCVs have, however, also been associated with a phenomenon called ‘replacement’, which is a shift in distribution of potential pathogenic bacteria in the nasopharynx from pneumococcal strains included in the vaccine (vaccine serotypes) towards nonvaccine pneumococcal serotypes and other bacteria. This phenomenon could erode the ‘net benefit’ of PCVs on overall AOM and therefore ongoing monitoring of the impact of PCVs on AOM incidence and severity is warranted. Recent and accurate estimates on the impact of PCV on childhood AOM are of utmost importance since cost-effectiveness of PCV is also driven by their potential capacity to prevent AOM. Using routinely collected longitudinal electronic health records and health insurance data of children pre and post introduction of the 7-valent PCV (PCV7) and the 10-valent PCV (PCV10) in the Dutch National Immunisation Programme (NIP), this thesis aims to provide these important estimates
Deep learning et authentification des textes
No full textInternational audienceUsing Deep Learning to attribute authorship of French literary texts While problems of attributing authorship or dating a text can be tackled using the usual methods of literary historians, it is equally possible to turn to statistical and computing tools. A range of intertextual measures have been proposed to describe variation within and across authors. To date no single method can claim an uncontested superiority comparable to the use of DNA in paternity suits or criminal investigations. The present study asks whether artificial intelligence may be able to play this role, and seeks the answer in research involving two corpora. The first concerns 20th century French literature: a deep learning algorithm is used on 50 texts by 25 authors (e.g., Roman Gary, Émile Ajar) with the goal of matching the two texts by the same author. Deep learning is perfectly accurate. The second corpus is drawn from French classical drama and here the algorithm also categorically distinguishes and matches plays by Racine, Corneille, and Molière. The only errors concern two plays (the French texts of Molière's Don Garcia of Navarre and Racine's The Litigants) where the comic genre takes precedence over authorial voice. This paper investigates the mechanisms of deep learning (with a more detailed treatment planned for a subsequent publication).Résumé. Deep Learning et authentification des textesLes problèmes de paternité ou de datation peuvent être abordés avec les moyens habituels de l’histoire littéraire, mais aussi en recourant aux ressources de la statistique et de l’informatique. Diverses mesures intertextuelles ont été proposées pour tenter de distinguer les distances intra (entre les textes d’un même auteur) et les distances inter (entre les auteurs). Malheureusement aucune jusqu’ici n’a pu prétendre au rang de juge suprême, comparable à l’ADN dans les recherches de paternité ou de criminalité. L’Intelligence artificielle peut-elle jouer ce rôle? C’est l’objet de la présente étude, menée conjointement dans deux corpus. Dans le premier, on aborde le roman au XXème siècle en proposant à l’algorithme du Deep Learning un panel de 50 textes et de 25 écrivains (parmi lesquels Roman Gary et Émile Ajar). Il s’agit de reconnaître les textes qui ont le même auteur. Le Deep Learning réussit l’épreuve sans faillir. Fort de cette réussite, le même algorithme est appliqué au théâtre classique. La conclusion est catégorique : Racine, Corneille et Molière se distinguent parfaitement sauf dans deux cas (Don Garcie et Les Plaideurs) où le genre vient brouiller la signature. Le présent article s’interroge sur les mécanismes mis en œuvre dans le Deep Learning. Un développement plus étendu est prévu dans une publication ultérieure
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Correction for Slik et al., Phylogenetic classification of the world’s tropical forests
No full textCorrection for "Phylogenetic classification of the world's tropical forests, " by J. W. Ferry Slik, Janet Franklin, Víctor Arroyo- Rodríguez, Richard Field, Salomon Aguilar, Nikolay Aguirre, Jorge Ahumada, Shin-Ichiro Aiba, Luciana F. Alves, Anitha K, Andres Avella, Francisco Mora, Gerardo A. Aymard C., Selene B?ez, Patricia Balvanera, Meredith L. Bastian, Jean-François Bastin, Peter J. Bellingham, Eduardo van den Berg, Polyanna da Conceição Bispo, Pascal Boeckx, Katrin Boehning-Gaese, Frans Bongers, Brad Boyle, Fabian Brambach, Francis Q. Brearley, Sandra Brown, Shauna-Lee Chai, Robin L. Chazdon, Shengbin Chen, Phourin Chhang, George Chuyong, Corneille Ewango, Indiana M. Coronado, Jurgi Crist?bal-Azkarate, Heike Culmsee, Kipiro Damas, H. S. Dattaraja, Priya Davidar, Saara J. DeWalt, Hazimah Din, Donald R. Drake, Alvaro Duque, Giselda Durigan, Karl Eichhorn, Eduardo Schmidt Eler, Tsutomu Enoki, Andreas Ensslin, Adand? Belarmain Fandohan, Nina Farwig, Kenneth J. Feeley, Markus Fischer, Olle Forshed, Queila Souza Garcia, Satish Chandra Garkoti, Thomas W. Gillespie, Jean- Francois Gillet, Christelle Gonmadje, Iñigo Granzow-de la Cerda, Daniel M. Griffith, James Grogan, Khalid Rehman Hakeem, David J. Harris, Rhett D. Harrison, Andy Hector, Andreas Hemp, J?rgen Homeier, M. Shah Hussain, Guillermo Ibarra-Manríquez, I. Faridah Hanum, Nobuo Imai, Patrick A. Jansen, Carlos Alfredo Joly, Shijo Joseph, Kuswata Kartawinata, Elizabeth Kearsley, Daniel L. Kelly, Michael Kessler, Timothy J. Killeen, Robert M. Kooyman, Yves Laumonier, Susan G. Laurance, William F. Laurance, Michael J. Lawes, Susan G. Letcher, Jeremy Lindsell, Jon Lovett, Jose Lozada, Xinghui Lu, Anne Mette Lykke, Khairil Bin Mahmud, Ni Putu Diana Mahayani, Asyraf Mansor, Andrew R. Marshall, Emanuel H. Martin, Darley Calderado Leal Matos, Jorge A.Meave, Felipe P. L. Melo, Zhofre Huberto Aguirre Mendoza, Faizah Metali, Vincent P. Medjibe, Jean Paul Metzger, Thiago Metzker, D. Mohandass, Miguel A. Munguía-Rosas, Rodrigo Muñoz, Eddy Nurtjahy, Eddie Lenza de Oliveira, Onrizal, Pia Parolin, Marc Parren, N. Parthasarathy, Ekananda Paudel, Rolando Perez, Eduardo A. P?rez-García, Ulf Pommer, Lourens Poorter, Lan Qi, Maria Teresa F. Piedade, Jos? Roberto Rodrigues Pinto, Axel Dalberg Poulsen, John R. Poulsen, Jennifer S. Powers, Rama Chandra Prasad, Jean-Philippe Puyravaud, Orlando Rangel, Jan Reitsma, Diogo S. B. Rocha, Samir Rolim, Francesco Rovero, Andes Rozak, Kalle Ruokolainen, Ervan Rutishauser, Gemma Rutten, Mohd. NizamMohd. Said, Felipe Z. Saiter, Philippe Saner, Braulio Santos, João Roberto dos Santos, Swapan Kumar Sarker, Christine B. Schmitt, Jochen Schoengart, Mark Schulze, Douglas Sheil, Plinio Sist, Alexandre F. Souza, Wilson Roberto Spironello, Tereza Sposito, Robert Steinmetz, Tariq Stevart, Marcio Seiji Suganuma, Rahayu Sukri, Aisha Sultana, Raman Sukumar, Terry Sunderland, Supriyadi, H. S. Suresh, Eizi Suzuki, Marcelo Tabarelli, Jianwei Tang, Ed V. J. Tanner, Natalia Targhetta, Ida Theilade, Duncan Thomas, Jonathan Timberlake, M?rcio de Morisson Valeriano, Johan van Valkenburg, Tran Van Do, Hoang Van Sam, John H. Vandermeer, Hans Verbeeck, Ole Reidar Vetaas, Victor Adekunle, Simone A. Vieira, Campbell O.Webb, Edward L. Webb, Timothy Whitfeld, Serge Wich, John Williams, Susan Wiser, FlorianWittmann, Xiaobo Yang, C. Yves Adou Yao, Sandra L. Yap, Rakan A. Zahawi, Rahmad Zakaria, and Runguo Zang, which was first published February 5, 2018; 10.1073/pnas.1714977115 (Proc Natl Acad Sci USA 115:1837-1842). The authors note that, due to a printer's error, an author name published incorrectly. The author name Lan Qi should instead appear as Lan Qie. The online version has been corrected
The Legacy of Iconoclasm: religious war and the relic landscape of Tours, Blois and Vendôme, 1550-1750
No full textThis study explores the process of physically rebuilding, renewing and reinventing the relic landscape in the regions around Tours, Blois and Vendôme following the widespread iconoclastic damage of the French religious wars. The author takes a long-term perspective exploring developments over two hundred years, from the mid-sixteenth through to the mid-eighteenth centuries. The book explores what the physical renewal of the landscape can tell us about evolving beliefs and practices concerning relics during the Catholic Reformation and what reconstruction activities reveal about the meaning and experience of relic veneration. It pays particular attention to how the relic landscape evolved through relic translations and how communities that oversaw relic shrines remembered the iconoclastic acts of the religious wars through liturgical and ritual commemorations, memorials, artistic renderings, oral traditions and written accounts.Publisher PD
The German Occupation in recent French fiction : an analysis of the literary “mode retro”
No full textThis thesis attempts to analyse and characterise the mode rétro, the remarkable renewal of interest in the German Occupation of France, which is coloured by an extensive re-evaluation of the period's significance. An introduction places this fashion in its literary, social and historical context, revealing how, from 1940 to 1969, a collective and predominantly Gaullist 'myth' of the Resistance became established, with the result that the national response to invasion was accepted to be one of wide-spread heroism and revolt. Part I studies the reaction to such résistancialisme, showing how this orthodox interpretation of events was undermined and, for many, discredited, and offering explanations of the timing and direction of the new view. Part II focuses on the fiction, memoirs, autobiographies and biographies of the younger authors, those who have no direct adult experience of the années noires. It is suggested that their obvious obsession with absent parent-figures reflects their awareness that the past has been misrepresented and their heritage rendered problematic. Their sole means of escape from this predicament, their only source of emotional relief is seen to lie in the creation of a personal account of the early 1940s running contrary to the prevalent orthodoxy, the fabrication of a 'counter-myth'. It is thus the notion of myth which links the various sections of the survey, and so gives the thesis its overall unity
Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks
No full textAdvances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha-1) at spatial scales ranging from 5 to 250 m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise. © Author(s) 2014
