381 research outputs found
Electrostatic considerations affecting the calculated HOMO-LUMO gap in protein molecules.
A detailed study of energy differences between the highest occupied and
lowest unoccupied molecular orbitals (HOMO-LUMO gaps) in protein systems and
water clusters is presented. Recent work questioning the applicability of
Kohn-Sham density-functional theory to proteins and large water clusters (E.
Rudberg, J. Phys.: Condens. Mat. 2012, 24, 072202) has demonstrated vanishing
HOMO-LUMO gaps for these systems, which is generally attributed to the
treatment of exchange in the functional used. The present work shows that the
vanishing gap is, in fact, an electrostatic artefact of the method used to
prepare the system. Practical solutions for ensuring the gap is maintained when
the system size is increased are demonstrated. This work has important
implications for the use of large-scale density-functional theory in
biomolecular systems, particularly in the simulation of photoemission, optical
absorption and electronic transport, all of which depend critically on
differences between energies of molecular orbitals.Comment: 13 pages, 4 figure
Localization and chiral symmetry in 2+1 flavor domain wall QCD
We present results for the dependence of the residual mass of domain wall
fermions (DWF) on the size of the fifth dimension and its relation to the
density and localization properties of low-lying eigenvectors of the
corresponding hermitian Wilson Dirac operator relevant to simulations of 2+1
flavor domain wall QCD. Using the DBW2 and Iwasaki gauge actions, we generate
ensembles of configurations with a space-time volume and an
extent of 8 in the fifth dimension for the sea quarks. We demonstrate the
existence of a regime where the degree of locality, the size of chiral symmetry
breaking and the rate of topology change can be acceptable for inverse lattice
spacings GeV.Comment: 59 Pages, 23 figures, 1 MPG linke
Studying the Physical Diversity of Late-M Dwarfs with Dynamical Masses
We present a systematic study of the physical properties of late-M dwarfs
based on high-quality dynamical mass measurements and near-infrared (NIR)
spectra. We use astrometry from Keck NGS and LGS AO imaging to determine orbits
for late-M binaries. We find that LP 349-25 (M7.5+M8) is a pair of young brown
dwarfs (Mtot = 0.120 Msun) for which Lyon and Tucson evolutionary models
jointly predict an age of 140+/-30 Myr. This is consistent with the age of the
Pleiades, but at least LP 349-25A defies the empirical Pleiades lithium
depletion boundary, implying that the system is in fact older and that
evolutionary models underpredict the component luminosities. We find that LHS
1901AB (M6.5+M6.5) is a pair of very low-mass stars (Mtot = 0.194 Msun) with
model-derived ages consistent with limits from its lack of activity (> 6 Gyr).
Our improved orbit for Gl 569Bab (M8.5+M9) results in a higher mass for this
binary (Mtot = 0.140 Msun) compared to previous work (0.125 Msun). We use these
masses along with our published results for 2MASS J2206-2047AB (M8+M8) to test
four sets of ultracool model atmospheres currently in use. Fitting these models
to our NIR integrated-light spectra provides temperature estimates warmer by
~250 K than those derived independently from Dusty evolutionary models given
the measured masses and luminosities. We propose that model atmospheres are
more likely to be the source of this discrepancy, as it would be difficult to
explain a uniform temperature offset over such a wide range of masses, ages,
and activity levels in the context of evolutionary models. Our results contrast
those of Konopacky et al. as we find an opposite and smaller mass discrepancy
from what they report when we adopt their model-testing approach since our Teff
estimates from fitting spectra are ~650 K higher than from their fitting of
broadband photometry alone.Comment: 53 pages, 12 figures, accepted to Ap
Galaxy formation in the Planck cosmology - III. The high-redshift universe
We present high-redshift predictions of the star formation rate distribution function (SFRDF), UV luminosity function (UVLF), galactic stellar mass function (GSMF), and specific star formation rates (sSFRs) of galaxies from the latest version of the Munich semi-analytic model L-GALAXIES. We find a good fit to both the shape and normalization of the SFRDF at z = 4–7, apart from a slight underprediction at the low-SFR end at z = 4. Likewise, we find a good fit to the faint number counts for the observed UVLF at brighter magnitudes our predictions lie below the observations, increasingly so at higher redshifts. At all redshifts and magnitudes, the raw (unattenuated) number counts for the UVLF lie above the observations. Because of the good agreement with the SFR we interpret our underprediction as an overestimate of the amount of dust in the model for the brightest galaxies, especially at high redshift. While the shape of our GSMF matches that of the observations, we lie between (conflicting) observations at z = 4–5, and underpredict at z = 6–7. The sSFRs of our model galaxies show the observed trend of increasing normalization with redshift, but do not reproduce the observed mass dependence. Overall, we conclude that the latest version of L-GALAXIES, which is tuned to match observations at z ≤ 3, does a fair job of reproducing the observed properties of galaxies at z ≥ 4. More work needs to be done on understanding observational bias at high redshift, and upon the dust model, before strong conclusions can be drawn on how to interpret remaining discrepancies between the model and observations
Analyzing networks of phenotypes in complex diseases: methodology and applications in COPD
Background: The investigation of complex disease heterogeneity has been challenging. Here, we introduce a network-based approach, using partial correlations, that analyzes the relationships among multiple disease-related phenotypes. Results: We applied this method to two large, well-characterized studies of chronic obstructive pulmonary disease (COPD). We also examined the associations between these COPD phenotypic networks and other factors, including case-control status, disease severity, and genetic variants. Using these phenotypic networks, we have detected novel relationships between phenotypes that would not have been observed using traditional epidemiological approaches. Conclusion: Phenotypic network analysis of complex diseases could provide novel insights into disease susceptibility, disease severity, and genetic mechanisms
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Allocentric versus egocentric spatial memory in autism spectrum disorder
Individuals with Autism Spectrum Disorder (ASD) present difficulties in forming relations among items and context. This capacity for relational binding is also involved in spatial navigation and research on this topic in ASD is scarce and inconclusive. Using a computerised version of the Morris Water Maze task, ASD participants showed particular difficulties in performing viewpoint independent (allocentric) navigation, leaving viewpoint dependent navigation (egocentric) intact. Further analyses showed that navigation deficits were not related to poor visual short-term memory or mental rotation in the ASD group. The results further confirm the need of autistic individuals for support at retrieval and have important implications for the design of signposts and maps
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