667 research outputs found
The High-Mass End of the Red Sequence at z~0.55 from SDSS-III/BOSS: completeness, bimodality and luminosity function
We have developed an analytical method based on forward-modeling techniques
to characterize the high-mass end of the red sequence (RS) galaxy population at
redshift , from the DR10 BOSS CMASS spectroscopic sample, which
comprises galaxies. The method, which follows an unbinned maximum
likelihood approach, allows the deconvolution of the intrinsic CMASS
colour-colour-magnitude distributions from photometric errors and selection
effects. This procedure requires modeling the covariance matrix for the i-band
magnitude, g-r colour and r-i colour using Stripe 82 multi-epoch data. Our
results indicate that the error-deconvolved intrinsic RS distribution is
consistent, within the photometric uncertainties, with a single point
() in the colour-colour plane at fixed magnitude, for a
narrow redshift slice. We have computed the high-mass end () of the -band RS Luminosity Function (RS LF) in several redshift
slices within the redshift range . In this narrow redshift range,
the evolution of the RS LF is consistent, within the uncertainties in the
modeling, with a passively-evolving model with Mpc mag, fading at a rate of mag per
unit redshift. We report RS completeness as a function of magnitude and
redshift in the CMASS sample, which will facilitate a variety of
galaxy-evolution and clustering studies using BOSS. Our forward-modeling method
lays the foundations for future studies using other dark-energy surveys like
eBOSS or DESI, which are affected by the same type of photometric
blurring/selection effects.Comment: 27 pages, 20 figures, accepted for publication in MNRA
Quantifying and filtering knowledge generated by literature based discovery
Background
Literature based discovery (LBD) automatically infers missed connections between concepts in literature. It is often assumed that LBD generates more information than can be reasonably examined.
Methods
We present a detailed analysis of the quantity of hidden knowledge produced by an LBD system and the effect of various filtering approaches upon this. The investigation of filtering combined with single or multi-step linking term chains is carried out on all articles in PubMed.
Results
The evaluation is carried out using both replication of existing discoveries, which provides justification for multi-step linking chain knowledge in specific cases, and using timeslicing, which gives a large scale measure of performance.
Conclusions
While the quantity of hidden knowledge generated by LBD can be vast, we demonstrate that (a) intelligent filtering can greatly reduce the number of hidden knowledge pairs generated, (b) for a specific term, the number of single step connections can be manageable, and (c) in the absence of single step hidden links, considering multiple steps can provide valid links
An investigation of exoskeleton robotic systems in assisting construction tasks
Whilst industrial robots have been widely used in many industrial sectors, they are predominantly used in a structured factory environment. In recent years, off-site robotics have been investigated extensively and there are some promising candidates emerging. One such category of robots is exoskeleton robots and this paper provides an in-depth assessment of their suitability in assisting human operators in undertaking manual operations typically found in the construction industry. This work aims to objectively assess the advantages and disadvantages of these two suits and provide recommendations for further improvements of similar system designs. The paper focuses on the passive exoskeleton robotic suits which are commercially available. Three types of activities are designed and a mechatronic methodology has been designed and implemented to capture visual data in order to assess these systems in comparison with normal human operations. The study suggests that these passive suits do reduce the effort required by human operators to undertake the same construction tasks as evidenced by the results from one focused study, though a number of improvements could be made to improve their performance for wider adoption
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Analysis of potential systematics
We analyze the density field of galaxies observed by the Sloan Digital Sky
Survey (SDSS)-III Baryon Oscillation Spectroscopic Survey (BOSS) included in
the SDSS Data Release Nine (DR9). DR9 includes spectroscopic redshifts for over
400,000 galaxies spread over a footprint of 3,275 deg^2. We identify,
characterize, and mitigate the impact of sources of systematic uncertainty on
large-scale clustering measurements, both for angular moments of the
redshift-space correlation function and the spherically averaged power
spectrum, P(k), in order to ensure that robust cosmological constraints will be
obtained from these data. A correlation between the projected density of stars
and the higher redshift (0.43 < z < 0.7) galaxy sample (the `CMASS' sample) due
to imaging systematics imparts a systematic error that is larger than the
statistical error of the clustering measurements at scales s > 120h^-1Mpc or k
< 0.01hMpc^-1. We find that these errors can be ameliorated by weighting
galaxies based on their surface brightness and the local stellar density. We
use mock galaxy catalogs that simulate the CMASS selection function to
determine that randomly selecting galaxy redshifts in order to simulate the
radial selection function of a random sample imparts the least systematic error
on correlation function measurements and that this systematic error is
negligible for the spherically averaged correlation function. The methods we
recommend for the calculation of clustering measurements using the CMASS sample
are adopted in companion papers that locate the position of the baryon acoustic
oscillation feature (Anderson et al. 2012), constrain cosmological models using
the full shape of the correlation function (Sanchez et al. 2012), and measure
the rate of structure growth (Reid et al. 2012). (abridged)Comment: Matches version accepted by MNRAS. Clarifications and references have
been added. See companion papers that share the "The clustering of galaxies
in the SDSS-III Baryon Oscillation Spectroscopic Survey:" titl
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A risk calculator to predict adult Attention-deficit/Hyperactivity disorder::Generation and external validation in three birth cohorts and one clinical sample.
AimFew personalised medicine investigations have been conducted for mental health. We aimed to generate and validate a risk tool that predicts adult attention-deficit/hyperactivity disorder (ADHD).MethodsUsing logistic regression models, we generated a risk tool in a representative population cohort (ALSPAC - UK, 5113 participants, followed from birth to age 17) using childhood clinical and sociodemographic data with internal validation. Predictors included sex, socioeconomic status, single-parent family, ADHD symptoms, comorbid disruptive disorders, childhood maltreatment, ADHD symptoms, depressive symptoms, mother's depression and intelligence quotient. The outcome was defined as a categorical diagnosis of ADHD in young adulthood without requiring age at onset criteria. We also tested Machine Learning approaches for developing the risk models: Random Forest, Stochastic Gradient Boosting and Artificial Neural Network. The risk tool was externally validated in the E-Risk cohort (UK, 2040 participants, birth to age 18), the 1993 Pelotas Birth Cohort (Brazil, 3911 participants, birth to age 18) and the MTA clinical sample (USA, 476 children with ADHD and 241 controls followed for 16 years from a minimum of 8 and a maximum of 26 years old).ResultsThe overall prevalence of adult ADHD ranged from 8.1 to 12% in the population-based samples, and was 28.6% in the clinical sample. The internal performance of the model in the generating sample was good, with an area under the curve (AUC) for predicting adult ADHD of 0.82 (95% confidence interval (CI) 0.79-0.83). Calibration plots showed good agreement between predicted and observed event frequencies from 0 to 60% probability. In the UK birth cohort test sample, the AUC was 0.75 (95% CI 0.71-0.78). In the Brazilian birth cohort test sample, the AUC was significantly lower -0.57 (95% CI 0.54-0.60). In the clinical trial test sample, the AUC was 0.76 (95% CI 0.73-0.80). The risk model did not predict adult anxiety or major depressive disorder. Machine Learning approaches did not outperform logistic regression models. An open-source and free risk calculator was generated for clinical use and is available online at https://ufrgs.br/prodah/adhd-calculator/.ConclusionsThe risk tool based on childhood characteristics specifically predicts adult ADHD in European and North-American population-based and clinical samples with comparable discrimination to commonly used clinical tools in internal medicine and higher than most previous attempts for mental and neurological disorders. However, its use in middle-income settings requires caution
Self-reported interoceptive deficits in eating disorders: A meta-analysis of studies using the eating disorder inventory
This document is the Accepted Manuscript version of the following article: Paul M. Jenkinson, Lauren Taylor, Keith R. Laws, ‘Self-reported interoceptive deficits in eating disorders: A meta-analysis of studies using the eating disorder inventory’, Journal of Psychosomatic Research, Vol. 110: 38-45, July 2018, under embargo until 19 April 2019. The Version of Record is available online at DOI: https://doi.org/10.1016/j.jpsychores.2018.04.005Objective: An impairment of the ability to sense the physiological condition of the body – interoception – has long been proposed as central to the onset and maintenance of eating disorders. More recent attention to this topic has generally indicated the presence of interoceptive deficits in individuals with an eating disorder diagnosis; however, possible links with specific diagnosis, BMI, age, illness duration, depression, and alexithymia remain unclear from individual studies. This meta-analysis aimed to provide a necessary quantitative overview of self-reported interoceptive deficits in eating disorder populations, and the relationship between these deficits and the previously mentioned factors. Methods: Using a random effects model, our meta-analysis assessed the magnitude of differences in interoceptive abilities as measured using the Eating Disorder Inventory in 41 samples comparing people with eating disorders (n=4308) and healthy controls (n=3459). Follow-up and moderator analysis was conducted, using group comparisons and meta-regressions. Results: We report a large pooled effect size of 1.62 for eating disorders with some variation between diagnostic groups. Further moderator analysis showed that BMI, age and alexithymia were significant predictors of overall effect size. Conclusion: This meta-analysis is the first to confirm that large interoceptive deficits occur in a variety of eating disorders and crucially, in those who have recovered. These deficits may be useful in identifying and distinguishing eating disorders. Future research needs to consider both objective and subjective measures of interoception across different types of eating disorders and may fruitfully examine interoception as a possible endophenotype and target for treatment.Peer reviewe
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: measuring structure growth using passive galaxies
We explore the benefits of using a passively evolving population of galaxies
to measure the evolution of the rate of structure growth between z=0.25 and
z=0.65 by combining data from the SDSS-I/II and SDSS-III surveys. The
large-scale linear bias of a population of dynamically passive galaxies, which
we select from both surveys, is easily modeled. Knowing the bias evolution
breaks degeneracies inherent to other methodologies, and decreases the
uncertainty in measurements of the rate of structure growth and the
normalization of the galaxy power-spectrum by up to a factor of two. If we
translate our measurements into a constraint on sigma_8(z=0) assuming a
concordance cosmological model and General Relativity (GR), we find that using
a bias model improves our uncertainty by a factor of nearly 1.5. Our results
are consistent with a flat Lambda Cold Dark Matter model and with GR.Comment: Accepted for publication in MNRAS (clarifications added, results and
conclusions unchanged
Online control of prehension predicts performance on a standardized motor assessment test in 8- to 12-Year-old children
Goal-directed hand movements are guided by sensory information and may be adjusted 'online,' during the movement. If the target of a movement unexpectedly changes position, trajectory corrections can be initiated in as little as 100 ms in adults. This rapid visual online control is impaired in children with developmental coordination disorder (DCD), and potentially in other neurodevelopmental conditions. We investigated the visual control of hand movements in children in a 'center-out' double-step reaching and grasping task, and examined how parameters of this visuomotor control co-vary with performance on standardized motor tests often used with typically and atypically developing children. Two groups of children aged 8-12 years were asked to reach and grasp an illuminated central ball on a vertically oriented board. On a proportion of trials, and at movement onset, the illumination switched unpredictably to one of four other balls in a center-out configuration (left, right, up, or down). When the target moved, all but one of the children were able to correct their movements before reaching the initial target, at least on some trials, but the latencies to initiate these corrections were longer than those typically reported in the adult literature, ranging from 211 to 581 ms. These later corrections may be due to less developed motor skills in children, or to the increased cognitive and biomechanical complexity of switching movements in four directions. In the first group (n = 187), reaching and grasping parameters significantly predicted standardized movement scores on the MABC-2, most strongly for the aiming and catching component. In the second group (n = 85), these same parameters did not significantly predict scores on the DCDQ'07 parent questionnaire. Our reaching and grasping task provides a sensitive and continuous measure of movement skill that predicts scores on standardized movement tasks used to screen for DCD
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey : baryon acoustic oscillations in the Data Releases 10 and 11 Galaxy samples
We present a one per cent measurement of the cosmic distance scale from the detections of the baryon acoustic oscillations (BAO) in the clustering of galaxies from the Baryon Oscillation Spectroscopic Survey, which is part of the Sloan Digital Sky Survey III. Our results come from the Data Release 11 (DR11) sample, containing nearly one million galaxies and covering approximately 8500 square degrees and the redshift range 0.2 < z < 0.7. We also compare these results with those from the publicly released DR9 and DR10 samples. Assuming a concordance Λ cold dark matter (ΛCDM) cosmological model, the DR11 sample covers a volume of 13 Gpc3 and is the largest region of the Universe ever surveyed at this density. We measure the correlation function and power spectrum, including density-field reconstruction of the BAO feature. The acoustic features are detected at a significance of over 7σ in both the correlation function and power spectrum. Fitting for the position of the acoustic features measures the distance relative to the sound horizon at the drag epoch, rd, which has a value of rd,fid = 149.28 Mpc in our fiducial cosmology. We find DV = (1264 ± 25 Mpc)(rd/rd,fid) at z = 0.32 and DV = (2056 ± 20 Mpc)(rd/rd,fid) at z = 0.57. At 1.0 per cent, this latter measure is the most precise distance constraint ever obtained from a galaxy survey. Separating the clustering along and transverse to the line of sight yields measurements at z = 0.57 of DA = (1421 ± 20 Mpc)(rd/rd,fid) and H = (96.8 ± 3.4 km s−1 Mpc−1)(rd,fid/rd). Our measurements of the distance scale are in good agreement with previous BAO measurements and with the predictions from cosmic microwave background data for a spatially flat CDM model with a cosmological constant.Publisher PDFPeer reviewe
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