9,529 research outputs found
The importance of scattering, surface potential, and vanguard counter-potential in terahertz emission from gallium arsenide
It is well established that under excitation by short (<1 ps), above-band-gap optical pulses, semiconductor surfaces may emit terahertz-frequency electromagnetic radiation via photocarrier diffusion (the dominant mechanism in InAs) or photocarrier drift (dominant in GaAs). Our three-dimensional ensemble Monte Carlo simulations allow multiple physical parameters to vary over wide ranges and provide unique direct insight into the factors controlling terahertz emission. We find for GaAs (in contrast to InAs), scattering and the surface potential are key factors. We further delineate in GaAs (as in InAs) the role of a vanguard counter-potential. The effects of varying dielectric constant, band-gap, and effective mass are similar in both emitter types. © 2012, American Institute of Physics
Characterizations of Super-regularity and its Variants
Convergence of projection-based methods for nonconvex set feasibility
problems has been established for sets with ever weaker regularity assumptions.
What has not kept pace with these developments is analogous results for
convergence of optimization problems with correspondingly weak assumptions on
the value functions. Indeed, one of the earliest classes of nonconvex sets for
which convergence results were obtainable, the class of so-called super-regular
sets introduced by Lewis, Luke and Malick (2009), has no functional
counterpart. In this work, we amend this gap in the theory by establishing the
equivalence between a property slightly stronger than super-regularity, which
we call Clarke super-regularity, and subsmootheness of sets as introduced by
Aussel, Daniilidis and Thibault (2004). The bridge to functions shows that
approximately convex functions studied by Ngai, Luc and Th\'era (2000) are
those which have Clarke super-regular epigraphs. Further classes of regularity
of functions based on the corresponding regularity of their epigraph are also
discussed.Comment: 15 pages, 2 figure
Plasma electrons above Saturn's main rings: CAPS observations
We present observations of thermal ( similar to 0.6 - 100eV) electrons observed near Saturn's main rings during Cassini's Saturn Orbit Insertion (SOI) on 1 July 2004. We find that the intensity of electrons is broadly anticorrelated with the ring optical depth at the magnetic footprint of the field line joining the spacecraft to the rings. We see enhancements corresponding to the Cassini division and Encke gap. We suggest that some of the electrons are generated by photoemission from ring particle surfaces on the illuminated side of the rings, the far side from the spacecraft. Structure in the energy spectrum over the Cassini division and A-ring may be related to photoelectron emission followed by acceleration, or, more likely, due to photoelectron production in the ring atmosphere or ionosphere
The reliability of inspiratory resistive load magnitude and detection testing
Objectives: To assess the test-retest reliability of inspiratory load detection and load magnitude perception tests in healthy volunteers. Design: Cohort of convenience. Setting: Respiratory physiology laboratory. Participants: Twenty healthy adults. Interventions: On two separate occasions participants performed tests of inspiratory loading. Participants breathed through custom made resistive tubing and were asked to indicate when they detected a different resistance during inspiration. In a second test participants rated the magnitude of presented inspiratory loads using the modified Borg score. Main Outcome Measures: Intra-class Correlation Coefficient (ICC2,1) values for repeated tests of inspiratory load detection threshold and load magnitude rating. Results: ICC2,1 values ranged from 0.657–0.786 for load detection testing and 0.739 to 0.969 for rating of load magnitude. Conclusions: The tests are simple and reliable measures of inspiratory load detection and magnitude rating. They can be used in future research to determine the effectiveness of interventions to reduce the effort of breathing in health and disease
A massive reservoir of low-excitation molecular gas at high redshift
Molecular hydrogen is an important component of galaxies because it fuels
star formation and accretion onto AGN, the two processes that generate the
large infrared luminosities of gas-rich galaxies. Observations of spectral-line
emission from the tracer molecule CO are used to probe the properties of this
gas. But the lines that have been studied in the local Universe, mostly the
lower rotational transitions of J = 1-0 and J = 2-1, have hitherto been
unobservable in high-redshift galaxies. Instead, higher transitions have been
used, although the densities and temperatures required to excite these higher
transitions may not be reached by much of the gas. As a result, past
observations may have underestimated the total amount of molecular gas by a
substantial amount. Here we report the discovery of large amounts of
low-excitation molecular gas around the infrared-luminous quasar, APM
08279+5255 at z = 3.91, using the two lowest excitation lines of 12CO (J = 1-0
and J = 2-1). The maps confirm the presence of hot and dense gas near the
nucleus, and reveal an extended reservoir of molecular gas with low excitation
that is 10 to 100 times more massive than the gas traced by higher-excitation
observations. This raises the possibility that significant amounts of
low-excitation molecular gas may lurk in the environments of high-redshift (z >
3) galaxies.Comment: To appear as a Letter to Nature, 4th January 200
Blind Biological Sequence Denoising with Self-Supervised Set Learning
Biological sequence analysis relies on the ability to denoise the imprecise
output of sequencing platforms. We consider a common setting where a short
sequence is read out repeatedly using a high-throughput long-read platform to
generate multiple subreads, or noisy observations of the same sequence.
Denoising these subreads with alignment-based approaches often fails when too
few subreads are available or error rates are too high. In this paper, we
propose a novel method for blindly denoising sets of sequences without directly
observing clean source sequence labels. Our method, Self-Supervised Set
Learning (SSSL), gathers subreads together in an embedding space and estimates
a single set embedding as the midpoint of the subreads in both the latent and
sequence spaces. This set embedding represents the "average" of the subreads
and can be decoded into a prediction of the clean sequence. In experiments on
simulated long-read DNA data, SSSL methods denoise small reads of
subreads with 17% fewer errors and large reads of subreads with 8% fewer
errors compared to the best baseline. On a real dataset of antibody sequences,
SSSL improves over baselines on two self-supervised metrics, with a significant
improvement on difficult small reads that comprise over 60% of the test set. By
accurately denoising these reads, SSSL promises to better realize the potential
of high-throughput DNA sequencing data for downstream scientific applications
Characterising hyperinsulinaemia induced insulin resistance in human skeletal muscle cells
Hyperinsulinaemia potentially contributes to insulin resistance in metabolic tissues, such as skeletal muscle. The purpose of these experiments was to characterise glucose uptake, insulin signalling and relevant gene expression in primary human skeletal muscle-derived cells (HMDCs), in response to prolonged insulin exposure (PIE) as a model of hyperinsulinaemia-induced insulin resistance. Differentiated HMDCs from healthy human donors were cultured with or without insulin (100 nM) for 3 days followed by an acute insulin stimulation. HMDCs exposed to PIE were characterised by impaired insulin-stimulated glucose uptake, blunted IRS-1 phosphorylation (Tyr612) and Akt (Ser473) phosphorylation in response to an acute insulin stimulation. Glucose transporter 1 (GLUT1), but not GLUT4, mRNA and protein increased following PIE. The mRNA expression of metabolic (PDK4) and inflammatory markers (TNF-α) was reduced by PIE but did not change lipid (SREBP1 and CD36) or mitochondrial (UCP3) markers. These experiments provide further characterisation of the effects of PIE as a model of hyperinsulinaemia-induced insulin resistance in HMDCs
Assailants or Saints?: Racial, Ethnic, and Gender Depictions on a Social Media Based City News Website
A large literature indicates that Black males are overrepresented as criminals in traditional newspapers and broadcast news. However, little scholarly attention has been paid to online-only city newspapers. The authors conducted a content analysis of a social media based city news website in a Southeastern state. Multiple coders assessed 8,142 stories that ran over the course of three years and found that, in line with previous research, Black males were disproportionately portrayed as criminals, were more likely to have mugshots accompanying their stories, and were more likely to have their race mentioned in the text of the story than any other demographic group. Furthermore, the website interface design exacerbated the portrayal of Black male criminality. The authors also found that White females were most likely to be portrayed as philanthropists and award winners. Our results offer strong support for scapegoat and power structure theories, and limited support for racial threat and market share theories. We argue that intersectional theoretical and methodological approaches are necessary to understand media portrayals of race/ethnicity, gender, social class, and other important social characteristics
An Efficient Local Search for Partial Latin Square Extension Problem
A partial Latin square (PLS) is a partial assignment of n symbols to an nxn
grid such that, in each row and in each column, each symbol appears at most
once. The partial Latin square extension problem is an NP-hard problem that
asks for a largest extension of a given PLS. In this paper we propose an
efficient local search for this problem. We focus on the local search such that
the neighborhood is defined by (p,q)-swap, i.e., removing exactly p symbols and
then assigning symbols to at most q empty cells. For p in {1,2,3}, our
neighborhood search algorithm finds an improved solution or concludes that no
such solution exists in O(n^{p+1}) time. We also propose a novel swap
operation, Trellis-swap, which is a generalization of (1,q)-swap and
(2,q)-swap. Our Trellis-neighborhood search algorithm takes O(n^{3.5}) time to
do the same thing. Using these neighborhood search algorithms, we design a
prototype iterated local search algorithm and show its effectiveness in
comparison with state-of-the-art optimization solvers such as IBM ILOG CPLEX
and LocalSolver.Comment: 17 pages, 2 figure
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