6,008 research outputs found
Cosmological constant from gauge fields on extra dimensions
We present a new model of dark energy which could explain the observed
accelerated expansion of our Universe. We show that a five-dimensional
Einstein-Yang-Mills theory defined in a flat Friedmann-Robertson-Walker
universe compactified on a circle possesses degenerate vacua in four
dimensions. The present Universe could be trapped in one of these degenerate
vacua. With the natural requirement that the size of the extra dimension could
be of the GUT scale or smaller, the energy density difference between the
degenerate vacua and the true ground state can provide us with just the right
amount of dark energy to account for the observed expansion rate of our
Universe.Comment: 5 pages, minor change
Scalar field fluctuations in Schwarzschild-de Sitter space-time
We calculate quantum fluctuations of a free scalar field in the
Schwarzschild-de Sitter space-time, adopting the planar coordinates that is
pertinent to the presence of a black hole in an inflationary universe. In a
perturbation approach, doing expansion in powers of a small black hole event
horizon compared to the de Sitter cosmological horizon, we obtain time
evolution of the quantum fluctuations and then derive the scalar power
spectrum.Comment: 16 pages and 4 figures, accepted by Classical and Quantum Gravit
The Transformation of Trust in China’s Alternative Food Networks: Disruption, Reconstruction, and Development
Food safety issues in China have received much scholarly attention, yet few studies systematically examined this matter through the lens of trust. More importantly, little is known about the transformation of different types of trust in the dynamic process of food production, provision, and consumption. We consider trust as an evolving interdependent relationship between different actors. We used the Beijing County Fair, a prominent ecological farmers’ market in China, as an example to examine the transformation of trust in China’s alternative food networks. We argue that although there has been a disruption of institutional trust among the general public since 2008 when the melamine-tainted milk scandal broke out, reconstruction of individual trust and development of organizational trust have been observed, along with the emergence and increasing popularity of alternative food networks. Based on more than six months of fieldwork on the emerging ecological agriculture sector in 13 provinces across China as well as monitoring of online discussions and posts, we analyze how various social factors—including but not limited to direct and indirect reciprocity, information, endogenous institutions, and altruism—have simultaneously contributed to the transformation of trust in China’s alternative food networks. The findings not only complement current social theories of trust, but also highlight an important yet understudied phenomenon whereby informal social mechanisms have been partially substituting for formal institutions and gradually have been building trust against the backdrop of the food safety crisis in China
Transverse Bragg-reflector injection lasers
A GaAs-GaAlAs injection laser has been tested that confines light in the lateral dimension (normal to junction plane) by a multilayer Bragg reflector. In the past, light has been confined as a result of the higher-index guiding region and resulting evanescent fields
Supercurves
The TST-dual of the general 1/4-supersymmetric D2-brane supertube is
identified as a 1/4-supersymmetric IIA `supercurve': a string with arbitrary
transverse displacement travelling at the speed of light. A simple proof is
given of the classical upper bound on the angular momentum, which is also
recovered as the semi-classical limit of a quantum bound. The classical bound
is saturated by a `superhelix', while the quantum bound is saturated by a
bosonic oscillator state in a unique SO(8) representation.Comment: 1+14 pages, LaTe
Atypical breasts cancers
AbstractIntroductionWith increasing incidence of breast cancers there are now a larger number of cases diagnosed with rare malignancies. These can be diagnostic dilemmas and management strategy can be different by various breast multi-disciplinary teams (MDT).We aim to discuss the evidence-based approach for management of these atypical breast cancers which were identified in patients from a single breast screening unit.MethodPatient with unusual breast malignancies (all types except invasive ductal and lobular) treated under the care of a single surgeon were identified during the breast multi-disciplinary discussion from 2011 to 2015. The histology and management of these cases were reviewed and literature search of electronic databases via PubMed and the search engines Google/Google Scholar was performed. Emphasis on keywords based on the histology type was used to limit search. Search was focused on the diagnosis, management and prognosis of these unusual breast cancers.ConclusionThis series aims to focus on the evidence-based management of these rare breast malignancies; the diagnosis of which is crucial as it affects the overall treatment and prognosis
Predicting Out-of-Domain Generalization with Local Manifold Smoothness
Understanding how machine learning models generalize to new environments is a
critical part of their safe deployment. Recent work has proposed a variety of
complexity measures that directly predict or theoretically bound the
generalization capacity of a model. However, these methods rely on a strong set
of assumptions that in practice are not always satisfied. Motivated by the
limited settings in which existing measures can be applied, we propose a novel
complexity measure based on the local manifold smoothness of a classifier. We
define local manifold smoothness as a classifier's output sensitivity to
perturbations in the manifold neighborhood around a given test point.
Intuitively, a classifier that is less sensitive to these perturbations should
generalize better. To estimate smoothness we sample points using data
augmentation and measure the fraction of these points classified into the
majority class. Our method only requires selecting a data augmentation method
and makes no other assumptions about the model or data distributions, meaning
it can be applied even in out-of-domain (OOD) settings where existing methods
cannot. In experiments on robustness benchmarks in image classification,
sentiment analysis, and natural language inference, we demonstrate a strong and
robust correlation between our manifold smoothness measure and actual OOD
generalization on over 3,000 models evaluated on over 100 train/test domain
pairs.Comment: 18 pages, 3 figure
Mixtures of Regression Models for Time-Course Gene Expression Data: Evaluation of Initialization and Random Effects
Finite mixture models are routinely applied to time course microarray data.
Due to the complexity and size of this type of data the choice of good starting values plays
an important role. So far initialization strategies have only been investigated for data
from a mixture of multivariate normal distributions. In this work several initialization
procedures are evaluated for mixtures of regression models with and without random
effects in an extensive simulation study on different artificial datasets. Finally these
procedures are also applied to a real dataset from E. coli
Centre Effects in Peritoneal Dialysis
Peritoneal dialysis (PD)-related complications and outcomes have been shown to be influenced by both patient- and centre-level factors. There is a significant variability in outcomes across different centres, which is not explained by patient factors alone. This chapter aims to evaluate those modifiable centre-level factors that have been shown to impact PD outcomes, focussing specifically on peritonitis and technique failure, and the evidence that addressing these centre effects may lead to appreciable improvements in PD patient outcomes. Peritonitis rates have been shown to be related to a centre’s degree of automated PD (APD) use, extent of icodextrin use, performance of home visits prior to PD commencement, the presence of a specialised PD nurse and duration of PD training. Better peritonitis outcomes have been shown to be associated with larger centre size, greater share of PD patients among dialysis cohorts and treatment of peritonitis with comprehensive empiric antimicrobial therapy. PD technique failure has been shown to be related to centre size and degree of PD experience. Although there is little evidence currently available to demonstrate that prospectively modifying centre factors improves PD outcomes, an Australian continuous quality improvement initiative has been associated with progressively improved peritonitis and technique failure outcomes
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