1,848 research outputs found
Nivel de Actividad Física en personal de empleados de la Universidad Tecnológica de Pereira, UTP 2008.
En el marco del proyecto de investigación para la prevención de enfermedades crónicas no transmisibles de la Universidad Tecnológica de Pereira, se caracterizó la población de docentes y administrativos de planta, en torno a la práctica regular de actividad física
Galaxy clusters and groups in the ALHAMBRA Survey
We present a catalogue of 348 galaxy clusters and groups with
selected in the 2.78 ALHAMBRA Survey. The high precision of our
photometric redshifts, close to , and the wide spread of the seven
ALHAMBRA pointings ensure that this catalogue has better mass sensitivity and
is less affected by cosmic variance than comparable samples.
The detection has been carried out with the Bayesian Cluster Finder (BCF),
whose performance has been checked in ALHAMBRA-like light-cone mock catalogues.
Great care has been taken to ensure that the observable properties of the mocks
photometry accurately correspond to those of real catalogues. From our
simulations, we expect to detect galaxy clusters and groups with both
completeness and purity down to dark matter halo masses of
for . Cluster redshifts are
expected to be recovered with precision for . We also expect
to measure cluster masses with
precision down to , masses which are
smaller than those reached by similar work.
We have compared these detections with previous optical, spectroscopic and
X-rays work, finding an excellent agreement with the rates reported from the
simulations. We have also explored the overall properties of these detections
such as the presence of a colour-magnitude relation, the evolution of the
photometric blue fraction and the clustering of these sources in the different
ALHAMBRA fields. Despite the small numbers, we observe tentative evidence that,
for a fixed stellar mass, the environment is playing a crucial role at lower
redshifts (z0.5).Comment: Accepted for publication in MNRAS. Catalogues and figures available
online and under the following link:
http://bascaso.net46.net/ALHAMBRA_clusters.htm
Improving the Quality and Utility of Electronic Health Record Data through Ontologies
The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in other areas of the natural sciences have been successfully overcome by developing and using common ontologies. This White Paper presents the authors’ rationale for the use of ontologies with computable semantics for the improvement of clinical data quality and EHR usability formulated for researchers with a stake in clinical and translational science and who are advocates for the use of information technology in medicine but at the same time are concerned by current major shortfalls. This White Paper outlines pitfalls, opportunities, and solutions and recommends increased investment in research and development of ontologies with computable semantics for a new generation of EHRs
Measurement of the cosmic ray spectrum above eV using inclined events detected with the Pierre Auger Observatory
A measurement of the cosmic-ray spectrum for energies exceeding
eV is presented, which is based on the analysis of showers
with zenith angles greater than detected with the Pierre Auger
Observatory between 1 January 2004 and 31 December 2013. The measured spectrum
confirms a flux suppression at the highest energies. Above
eV, the "ankle", the flux can be described by a power law with
index followed by
a smooth suppression region. For the energy () at which the
spectral flux has fallen to one-half of its extrapolated value in the absence
of suppression, we find
eV.Comment: Replaced with published version. Added journal reference and DO
Statistics of extreme objects in the Juropa Hubble Volume simulation
We present the first results from the JUropa huBbLE volumE (Jubilee) project,
based a large N-body, dark matter-only cosmological simulation with a volume of
, containing 6000 particles, performed within
the concordance CDM cosmological model. The simulation volume is
sufficient to probe extremely large length scales in the universe, whilst at
the same time the particle count is high enough so that dark matter haloes down
to can be resolved. At we
identify over 400 million haloes. The cluster mass function is derived using
three different halofinders and compared to fitting functions in the
literature. The distribution of clusters of maximal mass across redshifts
agrees well with predicted masses of extreme objects, and we explicitly confirm
that the Poisson distribution is very good at describing the distribution of
rare clusters. The Poisson distribution also matches well the level to which
cosmic variance can be expected to affect number counts of high mass clusters.
We find that objects like the Bullet cluster exist in the far-tail of the
distribution of mergers in terms of relative collisional speed. We also derive
the number counts of voids in the simulation box for , and .Comment: Version 2. 12 pages, 9 figures. Accepted by MNRA
Interpretable surface-based detection of focal cortical dysplasias:a Multi-centre Epilepsy Lesion Detection study
One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy
Recent Progress and Next Steps for the MATHUSLA LLP Detector
We report on recent progress and next steps in the design of the proposed
MATHUSLA Long Lived Particle (LLP) detector for the HL-LHC as part of the
Snowmass 2021 process. Our understanding of backgrounds has greatly improved,
aided by detailed simulation studies, and significant R&D has been performed on
designing the scintillator detectors and understanding their performance. The
collaboration is on track to complete a Technical Design Report, and there are
many opportunities for interested new members to contribute towards the goal of
designing and constructing MATHUSLA in time for HL-LHC collisions, which would
increase the sensitivity to a large variety of highly motivated LLP signals by
orders of magnitude.Comment: Contribution to Snowmass 2021 (EF09, EF10, IF6, IF9), 18 pages, 12
figures. v2: included additional endorser
Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms
Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin
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