847 research outputs found
Malliavin calculus for fractional heat equation
In this article, we give some existence and smoothness results for the law of
the solution to a stochastic heat equation driven by a finite dimensional
fractional Brownian motion with Hurst parameter . Our results rely on
recent tools of Young integration for convolutional integrals combined with
stochastic analysis methods for the study of laws of random variables defined
on a Wiener space.Comment: Dedicated to David Nualart on occasion of his 60th birthda
The naturalistic approach to laughter in humans and other animals: towards a unified theory
This opinion piece aims to tackle the biological, psychological, neural and
cultural underpinnings of laughter from a naturalistic and evolutionary
perspective. A naturalistic account of laughter requires the revaluation of
two dogmas of a longstanding philosophical tradition, that is, the quintessen tial link between laughter and humour, and the uniquely human nature of
this behaviour. In the spirit of Provine’s and Panksepp’s seminal studies,
who firstly argued against the anti-naturalistic dogmas, here we review com pelling evidence that (i) laughter is first and foremost a social behaviour
aimed at regulating social relationships, easing social tensions and establish ing social bonds, and that (ii) homologue and homoplasic behaviours of
laughter exist in primates and rodents, who also share with humans the
same underpinning neural circuitry. We make a case for the hypothesis
that the contagiousness of laughter and its pervasive social infectiousness
in everyday social interactions is mediated by a specific mirror mechanism.
Finally, we argue that a naturalistic account of laughter should not be
intended as an outright rejection of classic theories; rather, in the last part
of the piece we argue that our perspective is potentially able to integrate
previous viewpoints—including classic philosophical theories—ultimately
providing a unified evolutionary explanation of laughter
Cracking the laugh code: laughter through the lens of biology, psychology and neuroscience
Preface to the theme issue which tackles the biological, psychological, neural, and cultural underpinnings of laughter in humans and other animals from a naturalistic and evolutionary perspective
The MUSE-Wide Survey: A first catalogue of 831 emission line galaxies
We present a first instalment of the MUSE-Wide survey, covering an area of
22.2 arcmin (corresponding to 20% of the final survey) in the
CANDELS/Deep area of the Chandra Deep Field South. We use the MUSE integral
field spectrograph at the ESO VLT to conduct a full-area spectroscopic mapping
at a depth of 1h exposure time per 1 arcmin pointing. We searched for
compact emission line objects using our newly developed LSDCat software based
on a 3-D matched filtering approach, followed by interactive classification and
redshift measurement of the sources. Our catalogue contains 831 distinct
emission line galaxies with redshifts ranging from 0.04 to 6. Roughly one third
(237) of the emission line sources are Lyman emitting galaxies with , only four of which had previously measured spectroscopic redshifts.
At lower redshifts 351 galaxies are detected primarily by their [OII] emission
line (), 189 by their [OIII] line (), and 46 by their H line (). Comparing our spectroscopic redshifts to photometric redshift estimates
from the literature, we find excellent agreement for with a median
of only and an outlier rate of 6%, however a
significant systematic offset of and an outlier rate of 23%
for Ly emitters at . Together with the catalogue we also release
1D PSF-weighted extracted spectra and small 3D datacubes centred on each of the
831 sources.Comment: 24 pages, 14 figures, accepted for publication in A&A, data products
are available for download from http://muse-vlt.eu/science/muse-wide-survey/
and later via the CD
The MUSE-Wide Survey: Survey Description and First Data Release
We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the
CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth
of 1 hour and hence targets more extreme and more luminous objects over 10
times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of
MUSE-Wide lies in providing "spectroscopy of everything" without photometric
pre-selection. We describe the data reduction, post-processing and PSF
characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released
with this publication. Using a 3D matched filtering approach we detected 1,602
emission line sources, including 479 Lyman- (Lya) emitting galaxies
with redshifts . We cross-match the emission line
sources to existing photometric catalogs, finding almost complete agreement in
redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high
redshift, we only find ~55% matches to photometric catalogs. We encounter a
higher outlier rate and a systematic offset of z0.2 when
comparing our MUSE redshifts with photometric redshifts. Cross-matching the
emission line sources with X-ray catalogs from the Chandra Deep Field South, we
find 127 matches, including 10 objects with no prior spectroscopic
identification. Stacking X-ray images centered on our Lya emitters yielded no
signal; the Lya population is not dominated by even low luminosity AGN. A total
of 9,205 photometrically selected objects from the CANDELS survey lie in the
MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are
able to determine the spectroscopic redshift of 98% of 772 photometrically
selected galaxies brighter than 24th F775W magnitude. All the data in the first
data release - datacubes, catalogs, extracted spectra, maps - are available on
the website https://musewide.aip.de. [abridged]Comment: 25 pages 15+1 figures. Accepted, A&A. Comments welcom
Validation of Genotyping by Sequencing Using Transcriptomics for Diversity and Application of Genomic Selection in Tetraploid Potato
Potato is an important food crop due to its increasing consumption, and as a result, there is demand for varieties with improved production. However, the current status of breeding for improved varieties is a long process which relies heavily on phenotypic evaluation and dated molecular techniques and has little emphasis on modern genotyping approaches. Evaluation and selection before a cultivar is commercialized typically takes 10–15 years. Molecular markers have been developed for disease and pest resistance, resulting in initial marker-assisted selection in breeding. This study has evaluated and implemented a high-throughput transcriptome sequencing method for dense marker discovery in potato for the application of genomic selection. An Australian relevant collection of commercial cultivars was selected, and identification and distribution of high quality SNPs were examined using standard bioinformatic pipelines and a custom approach for the prediction of allelic dosage. As a result, a large number of SNP markers were identified and filtered to generate a high-quality subset that was then combined with historic phenotypic data to assess the approach for genomic selection. Genomic selection potential was predicted for highly heritable traits and the approach demonstrated advantages over the previously used technologies in terms of markers identified as well as costs incurred. The high-quality SNP list also provided acceptable genome coverage which demonstrates its applicability for much larger future studies. This SNP list was also annotated to provide an indication of function and will serve as a resource for the community in future studies. Genome wide marker tools will provide significant benefits for potato breeding efforts and the application of genomic selection will greatly enhance genetic progress
Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors
We investigate the application of hierarchical classification schemes to the
annotation of gene function based on several characteristics of protein
sequences including phylogenic descriptors, sequence based attributes, and
predicted secondary structure. We discuss three Bayesian models and compare
their performance in terms of predictive accuracy. These models are the
ordinary multinomial logit (MNL) model, a hierarchical model based on a set of
nested MNL models, and a MNL model with a prior that introduces correlations
between the parameters for classes that are nearby in the hierarchy. We also
provide a new scheme for combining different sources of information. We use
these models to predict the functional class of Open Reading Frames (ORFs) from
the E. coli genome. The results from all three models show substantial
improvement over previous methods, which were based on the C5 algorithm. The
MNL model using a prior based on the hierarchy outperforms both the
non-hierarchical MNL model and the nested MNL model. In contrast to previous
attempts at combining these sources of information, our approach results in a
higher accuracy rate when compared to models that use each data source alone.
Together, these results show that gene function can be predicted with higher
accuracy than previously achieved, using Bayesian models that incorporate
suitable prior information
Investigating knowledge management factors affecting Chinese ICT firms performance: An integrated KM framework
This is an Author's Accepted Manuscript of an article published in the Journal of Information Systems Management, 28(1), 19 - 29, 2011, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/10580530.2011.536107.This article sets out to investigate the critical factors of Knowledge Management (KM) which are considered to have an impact on the performance of Chinese information and communication technology (ICT) firms. This study confirms that the cultural environment of an enterprise is central to its success in the context of China. It shows that a collaborated, trusted, and learning environment within ICT firms will have a positive impact on their KM performance
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