Experimental approaches to referential domains and the on-line processing of referring expressions in unscripted conversation

Peer reviewedPublisher PD

The hippocampus and the flexible use and processing of language

Fundamental to all human languages is an unlimited expressive capacity and creative flexibility that allow speakers to rapidly generate novel and complex utterances. In turn, listeners interpret language “on-line,” incrementally integrating multiple sources of information as words unfold over time. A challenge for theories of language processing has been to understand how speakers and listeners generate, gather, integrate, and maintain representations in service of language processing. We propose that many of the processes by which we use language place high demands on and receive contributions from the hippocampal declarative memory system. The hippocampal declarative memory system is long known to support relational binding and representational flexibility. Recent findings demonstrate that these same functions are engaged during the real-time processes that support behavior in-the-moment. Such findings point to the hippocampus as a potentially key contributor to cognitive functions that require on-line integration of multiple sources of information, such as on-line language processing. Evidence supporting this view comes from findings that individuals with hippocampal amnesia show deficits in the use of language flexibly and on-line. We conclude that the relational binding and representational flexibility afforded by the hippocampal declarative memory system positions the hippocampus as a key contributor to language use and processing

Disentangling dark energy and cosmic tests of gravity from weak lensing systematics

We consider the impact of key astrophysical and measurement systematics on constraints on dark energy and modifications to gravity on cosmic scales. We focus on upcoming photometric "Stage III" and "Stage IV" large scale structure surveys such as DES, SuMIRe, Euclid, LSST and WFIRST. We illustrate the different redshift dependencies of gravity modifications compared to intrinsic alignments, the main astrophysical systematic. The way in which systematic uncertainties, such as galaxy bias and intrinsic alignments, are modelled can change dark energy equation of state and modified gravity figures of merit by a factor of four. The inclusion of cross-correlations of cosmic shear and galaxy position measurements helps reduce the loss of constraining power from the lensing shear surveys. When forecasts for Planck CMB and Stage IV surveys are combined, constraints on the dark energy equation of state and modified gravity model are recovered, relative to those from shear data with no systematic uncertainties, if fewer than 36 free parameters in total are used to describe the galaxy bias and intrinsic alignment models as a function of scale and redshift. To facilitate future investigations, we also provide a fitting function for the matter power spectrum arising from the phenomenological modified gravity model we consider.Comment: 18 pages, 8 figure

Largest M Dwarf Flares from ASAS-SN

The All-sky Automated Survey for Supernovae (ASAS-SN) is the only project in existence to scan the entire sky in optical light approximately every day, reaching a depth of g ~ 18 mag. Over the course of its first 4 yr of transient alerts (2013–2016), ASAS-SN observed 53 events classified as likely M dwarf flares. We present follow-up photometry and spectroscopy of all 53 candidates, confirming flare events on 47 M dwarfs, one K dwarf, and one L dwarf. The remaining four objects include a previously identified T Tauri star, a young star with outbursts, and two objects too faint to confirm. A detailed examination of the 49 flare star light curves revealed an additional six flares on five stars, resulting in a total of 55 flares on 49 objects ranging in V-band contrast from ΔV = −1 to −10.2 mag. Using an empirical flare model to estimate the unobserved portions of the flare light curve, we obtain lower limits on the V-band energy emitted during each flare, spanning log(E_V/erg) = 32–35, which are among the most energetic flares detected on M dwarfs. The ASAS-SN M dwarf flare stars show a higher fraction of Hα emission, as well as stronger Hα emission, compared to M dwarfs selected without reference to activity, consistent with belonging to a population of more magnetically active stars. We also examined the distribution of tangential velocities, finding that the ASAS-SN flaring M dwarfs are likely to be members of the thin disk and are neither particularly young nor old

The macroecology of infectious diseases: a new perspective on global-scale drivers of pathogen distributions and impacts

© 2016 John Wiley & Sons Ltd/CNRS. Identifying drivers of infectious disease patterns and impacts at the broadest scales of organisation is one of the most crucial challenges for modern science, yet answers to many fundamental questions remain elusive. These include what factors commonly facilitate transmission of pathogens to novel host species, what drives variation in immune investment among host species, and more generally what drives global patterns of parasite diversity and distribution? Here we consider how the perspectives and tools of macroecology, a field that investigates patterns and processes at broad spatial, temporal and taxonomic scales, are expanding scientific understanding of global infectious disease ecology. In particular, emerging approaches are providing new insights about scaling properties across all living taxa, and new strategies for mapping pathogen biodiversity and infection risk. Ultimately, macroecology is establishing a framework to more accurately predict global patterns of infectious disease distribution and emergence

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A

PERCHING syndrome: Clinical presentation in the first African patient confirmed by clinical whole genome sequencing.

peer reviewedPERCHING syndrome is a rare multisystem developmental disorder caused by autosomal recessive (AR) variants (truncating and missense) in the Kelch-like family member 7 gene (KLHL7). We report the first phenotypic and molecular description of PERCHING syndrome in a patient from Central Africa. The patient presented multiple dysmorphic features in addition to neurological, respiratory, gastroenteric, and dysautonomic disorders. Clinical Whole Genome Sequencing in the proband and his mother identified two novel heterozygous variants in the KLHL7 gene, including a maternally inherited intronic variant (NM_001031710.2:c.793 + 5G > C) classified as Variant of Uncertain Significance and a frameshift stop gain variant (NM_001031710.2:c.944delG; p.Ser315ThrfsTer23) of unknown inheritance classified as likely pathogenic. Although the diagnosis was only evoked after genomic testing, the review of published patients suggests that this disease could be clinically recognizable and maybe considered as an encephalopathy. Our report will allow expanding the phenotypic and molecular spectrum of Perching syndrome

Machine Learning in Drug Discovery and Development Part 1: A Primer

Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.Laboratorio de Investigación y Desarrollo de Bioactivo