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Institution

Aix-Marseille University

EducationMarseille, France
About: Aix-Marseille University is a education organization based out in Marseille, France. It is known for research contribution in the topics: Population & Galaxy. The organization has 24326 authors who have published 54240 publications receiving 1455416 citations. The organization is also known as: University Aix-Marseille & université d'Aix-Marseille.


Papers
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Journal ArticleDOI
TL;DR: How different learning constraints, thought to be involved in optimizing the mapping of print to meaning during reading acquisition, might shape the nature of the orthographic code involved in skilled reading are examined.
Abstract: In the present theoretical note we examine how different learning constraints, thought to be involved in optimizing the mapping of print to meaning during reading acquisition, might shape the nature of the orthographic code involved in skilled reading. On the one hand, optimization is hypothesized to involve selecting combinations of letters that are the most informative with respect to word identity (diagnosticity constraint), and on the other hand to involve the detection of letter combinations that correspond to pre-existing sublexical phonological and morphological representations (chunking constraint). These two constraints give rise to two different kinds of prelexical orthographic code, a coarse-grained and a fine-grained code, associated with the two routes of a dual-route architecture. Processing along the coarse-grained route optimizes fast access to semantics by using minimal subsets of letters that maximize information with respect to word identity, while coding for approximate within-word letter position independently of letter contiguity. Processing along the fined-grained route, on the other hand, is sensitive to the precise ordering of letters, as well as to position with respect to word beginnings and endings. This enables the chunking of frequently co-occurring contiguous letter combinations that form relevant units for morpho-orthographic processing (prefixes and suffixes) and for the sublexical translation of print to sound (multi-letter graphemes).

335 citations

Journal ArticleDOI
Roel Aaij, Bernardo Adeva1, Marco Adinolfi2, C. Adrover3  +650 moreInstitutions (44)
TL;DR: An excess of Bs(0)→μ+ μ- signal candidates with respect to the background expectation is seen with a significance of 4.0 standard deviations, consistent with the standard model expectations.
Abstract: A search for the rare decays $B^0_s \to\mu^+\mu^-$ and $B^0 \to\mu^+\mu^-$ is performed at the LHCb experiment. The data analysed correspond to an integrated luminosity of 1 fb$^{-1}$ of $pp$ collisions at a centre-of-mass energy of 7 TeV and 2 fb$^{-1}$ at 8 TeV. An excess of $B^0_s \to\mu^+\mu^-$ signal candidates with respect to the background expectation is seen with a significance of 4.0 standard deviations. A time-integrated branching fraction of ${\cal B}(B^0_s \to\mu^+\mu^-) = (2.9^{+1.1}_{-1.0})\times 10^{-9}$ is obtained and an upper limit of ${\cal B}(B^0 \to\mu^+\mu^-) < 7.4\times 10^{-10}$ at 95% confidence level is set. These results are consistent with the Standard Model expectations.

334 citations

Journal ArticleDOI
TL;DR: It is deduced from a detailed analysis of the LEED patterns and the STM images that all these superstructures are given by a quasi-identical silicon single layer with a honeycomb structure with different rotations relative to the silver substrate.
Abstract: The deposition of one silicon monolayer on the silver (111) substrate in the temperature range 150-300 °C gives rise to a mix of (4 × 4), (2√3 × 2√3)R30° and (√13 × √13)R13.9° superstructures which strongly depend on the substrate temperature. We deduced from a detailed analysis of the LEED patterns and the STM images that all these superstructures are given by a quasi-identical silicon single layer with a honeycomb structure (i.e. a silicene-like layer) with different rotations relative to the silver substrate. The morphologies of the STM images are explained from the position of the silicon atoms relative to the silver atoms. A complete analysis of all possible rotations of the silicene layer predicts also a (√7 × √7)R19.1° superstructure which has not been observed so far.

333 citations

Journal ArticleDOI
TL;DR: Phoneme deletion and RAN were strong concurrent predictors of developmental dyslexia, while verbal ST/WM and general verbal abilities played a comparatively minor role, demonstrating how orthographic complexity exacerbates some symptoms of Dyslexia.
Abstract: Background: The relationship between phoneme awareness, rapid automatized naming (RAN), verbal short-term/working memory (ST/WM) and diagnostic category is investigated in control and dyslexic children, and the extent to which this depends on orthographic complexity. Methods: General cognitive, phonological and literacy skills were tested in 1,138 control and 1,114 dyslexic children speaking six different languages spanning a large range of orthographic complexity (Finnish, Hungarian, German, Dutch, French, English). Results: Phoneme deletion and RAN were strong concurrent predictors of developmental dyslexia, while verbal ST/WM and general verbal abilities played a comparatively minor role. In logistic regression models, more participants were classified correctly when orthography was more complex. The impact of phoneme deletion and RAN-digits was stronger in complex than in less complex orthographies. Conclusions: Findings are largely consistent with the literature on predictors of dyslexia and literacy skills, while uniquely demonstrating how orthographic complexity exacerbates some symptoms of dyslexia.

332 citations


Authors

Showing all 24784 results

NameH-indexPapersCitations
Didier Raoult1733267153016
Andrea Bocci1722402176461
Marc Humbert1491184100577
Carlo Rovelli1461502103550
Marc Besancon1431799106869
Jian Yang1421818111166
Josh Moss139101989255
Maksym Titov1391573128335
Bernard Henrissat139593100002
R. D. Kass1381920107907
Stylianos E. Antonarakis13874693605
Jean-Paul Kneib13880589287
Brad Abbott137156698604
Shu Li136100178390
Georges Aad135112188811
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023170
2022748
20215,607
20205,697
20195,288
20185,125