21,932 research outputs found
Initial correlations in nonequilibrium Falicov-Kimball model
The Keldysh boundary problem in a nonequilibrium Falicov-Kimball model in
infinite dimensions is studied within the truncated and self-consistent
perturbation theories, and the dynamical mean-field theory. Within the model
the system is started in equilibrium, and later a uniform electric field is
turned on. The Kadanoff-Baym-Wagner equations for the nonequilibrium Green
functions are derived, and numerically solved. The contributions of initial
correlations are studied by monitoring the system evolution. It is found that
the initial correlations are essential for establishing full electron
correlations of the system and independent on the starting time of preparing
the system in equilibrium. By examining the contributions of the initial
correlations to the electric current and the double occupation, we find that
the contributions are small in relation to the total value of those physical
quantities when the interaction is weak, and significantly increase when the
interaction is strong. The neglect of initial correlations may cause artifacts
in the nonequilibrium properties of the system, especially in the strong
interaction case
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Oxidative stress specifically downregulates survivin to promote breast tumour formation.
BackgroundBreast cancer, a heterogeneous disease has been broadly classified into oestrogen receptor positive (ER+) or oestrogen receptor negative (ER-) tumour types. Each of these tumours is dependent on specific signalling pathways for their progression. While high levels of survivin, an anti-apoptotic protein, increases aggressive behaviour in ER- breast tumours, oxidative stress (OS) promotes the progression of ER+ breast tumours. Mechanisms and molecular targets by which OS promotes tumourigenesis remain poorly understood.ResultsDETA-NONOate, a nitric oxide (NO)-donor induces OS in breast cancer cell lines by early re-localisation and downregulation of cellular survivin. Using in vivo models of HMLE(HRAS) xenografts and E2-induced breast tumours in ACI rats, we demonstrate that high OS downregulates survivin during initiation of tumourigenesis. Overexpression of survivin in HMLE(HRAS) cells led to a significant delay in tumour initiation and tumour volume in nude mice. This inverse relationship between survivin and OS was also observed in ER+ human breast tumours. We also demonstrate an upregulation of NADPH oxidase-1 (NOX1) and its activating protein p67, which are novel markers of OS in E2-induced tumours in ACI rats and as well as in ER+ human breast tumours.ConclusionOur data, therefore, suggest that downregulation of survivin could be an important early event by which OS initiates breast tumour formation
Chemical pre-processing of cluster galaxies over the past 10 billion years in the IllustrisTNG simulations
We use the IllustrisTNG simulations to investigate the evolution of the
mass-metallicity relation (MZR) for star-forming cluster galaxies as a function
of the formation history of their cluster host. The simulations predict an
enhancement in the gas-phase metallicities of star-forming cluster galaxies
(10^9< M_star<10^10 M_sun) at z<1.0 in comparisons to field galaxies. This is
qualitatively consistent with observations. We find that the metallicity
enhancement of cluster galaxies appears prior to their infall into the central
cluster potential, indicating for the first time a systematic "chemical
pre-processing" signature for {\it infalling} cluster galaxies. Namely,
galaxies which will fall into a cluster by z=0 show a ~0.05 dex enhancement in
the MZR compared to field galaxies at z<0.5. Based on the inflow rate of gas
into cluster galaxies and its metallicity, we identify that the accretion of
pre-enriched gas is the key driver of the chemical evolution of such galaxies,
particularly in the stellar mass range (10^9< M_star<10^10 M_sun). We see
signatures of an environmental dependence of the ambient/inflowing gas
metallicity which extends well outside the nominal virial radius of clusters.
Our results motivate future observations looking for pre-enrichment signatures
in dense environments.Comment: 5 pages, 4 figures, accepted for publication in MNRAS Letter
Sea state bias in altimeter sea level estimates determined by combining wave model and satellite data
This study documents a method for increasing the precision of satellite-derived sea level measurements. Results are achieved using an enhanced three-dimensional (3-D) sea state bias (SSB) correction model derived from both Jason-1 altimeter ocean observations (i.e., sea state and wind) and estimates of mean wave period from a numerical ocean wave model, NOAA’s WAVEWATCH III. A multiyear evaluation of Jason-1 data indicates sea surface height variance reduction of 1.26 (±0.2) cm2 in comparison to the commonly applied two-parameter SSB model. The improvement is similar for two separate variance reduction metrics and for separate annual data sets spanning 2002–2004. Spatial evaluation of improvement shows skill increase at all latitudes. Results indicate the new model can reduce the total Jason-1 and Jason-2 altimeter range error budgets by 7.5%. In addition to the 2-D (two-dimensional) and 3-D model differences in correcting the range for wavefield variability, mean model regional differences also occur across the globe and indicate a possible 1–2 cm gradient across ocean basins linked to the zonal variation in wave period (short fetch and period in the west, swells and long period in the east). Overall success of this model provides first evidence that operational wave modeling can support improved ocean altimetry. Future efforts will attempt to work within the limits of wave modeling capabilities to maximize their benefit to Jason-1 and Jason-2 SSB correction methods
Supporting User-Defined Functions on Uncertain Data
Uncertain data management has become crucial in many sensing and scientific applications. As user-defined functions (UDFs) become widely used in these applications, an important task is to capture result uncertainty for queries that evaluate UDFs on uncertain data. In this work, we provide a general framework for supporting UDFs on uncertain data. Specifically, we propose a learning approach based on Gaussian processes (GPs) to compute approximate output distributions of a UDF when evaluated on uncertain input, with guaranteed error bounds. We also devise an online algorithm to compute such output distributions, which employs a suite of optimizations to improve accuracy and performance. Our evaluation using both real-world and synthetic functions shows that our proposed GP approach can outperform the state-of-the-art sampling approach with up to two orders of magnitude improvement for a variety of UDFs. 1
A portable platform for accelerated PIC codes and its application to GPUs using OpenACC
We present a portable platform, called PIC_ENGINE, for accelerating
Particle-In-Cell (PIC) codes on heterogeneous many-core architectures such as
Graphic Processing Units (GPUs). The aim of this development is efficient
simulations on future exascale systems by allowing different parallelization
strategies depending on the application problem and the specific architecture.
To this end, this platform contains the basic steps of the PIC algorithm and
has been designed as a test bed for different algorithmic options and data
structures. Among the architectures that this engine can explore, particular
attention is given here to systems equipped with GPUs. The study demonstrates
that our portable PIC implementation based on the OpenACC programming model can
achieve performance closely matching theoretical predictions. Using the Cray
XC30 system, Piz Daint, at the Swiss National Supercomputing Centre (CSCS), we
show that PIC_ENGINE running on an NVIDIA Kepler K20X GPU can outperform the
one on an Intel Sandybridge 8-core CPU by a factor of 3.4
Number Fluctuation in an interacting trapped gas in one and two dimensions
It is well-known that the number fluctuation in the grand canonical ensemble,
which is directly proportional to the compressibility, diverges for an ideal
bose gas as T -> 0. We show that this divergence is removed when the atoms
interact in one dimension through an inverse square two-body interaction. In
two dimensions, similar results are obtained using a self-consistent
Thomas-Fermi (TF) model for a repulsive zero-range interaction. Both models may
be mapped on to a system of non-interacting particles obeying the Haldane-Wu
exclusion statistics. We also calculate the number fluctuation from the ground
state of the gas in these interacting models, and compare the grand canonical
results with those obtained from the canonical ensemble.Comment: 11 pages, 1 appendix, 3 figures. Submitted to J. Phys. B: Atomic,
Molecular & Optica
The Network Operations Control Center upgrade task: Lessons learned
This article synthesizes and describes the lessons learned from the Network Operations Control Center (NOCC) upgrade project, from the requirements phase through development and test and transfer. At the outset, the NOCC upgrade was being performed simultaneously with two other interfacing and dependent upgrades at the Signal Processing Center (SPC) and Ground Communications Facility (GCF), thereby adding a significant measure of complexity to the management and overall coordination of the development and transfer-to-operations (DTO) effort. Like other success stories, this project carried with it the traditional elements of top management support and exceptional dedication of cognizant personnel. Additionally, there were several NOCC-specific reasons for success, such as end-to-end system engineering, adoption of open-system architecture, thorough requirements management, and use of appropriate off-the-shelf technologies. On the other hand, there were several difficulties, such as ill-defined external interfaces, transition issues caused by new communications protocols, ambivalent use of two sets of policies and standards, and mistailoring of the new JPL management standard (due to the lack of practical guidelines). This article highlights the key lessons learned, as a means of constructive suggestions for the benefit of future projects
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