20,072 research outputs found
Valence Bond Entanglement and Fluctuations in Random Singlet Phases
The ground state of the uniform antiferromagnetic spin-1/2 Heisenberg chain
can be viewed as a strongly fluctuating liquid of valence bonds, while in
disordered chains these bonds lock into random singlet states on long length
scales. We show that this phenomenon can be studied numerically, even in the
case of weak disorder, by calculating the mean value of the number of valence
bonds leaving a block of contiguous spins (the valence-bond entanglement
entropy) as well as the fluctuations in this number. These fluctuations show a
clear crossover from a small regime, in which they behave similar to those
of the uniform model, to a large regime in which they saturate in a way
consistent with the formation of a random singlet state on long length scales.
A scaling analysis of these fluctuations is used to study the dependence on
disorder strength of the length scale characterizing the crossover between
these two regimes. Results are obtained for a class of models which include, in
addition to the spin-1/2 Heisenberg chain, the uniform and disordered critical
1D transverse-field Ising model and chains of interacting non-Abelian anyons.Comment: 8 pages, 6 figure
Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach
Recent years have witnessed the rapid development of human activity
recognition (HAR) based on wearable sensor data. One can find many practical
applications in this area, especially in the field of health care. Many machine
learning algorithms such as Decision Trees, Support Vector Machine, Naive
Bayes, K-Nearest Neighbor, and Multilayer Perceptron are successfully used in
HAR. Although these methods are fast and easy for implementation, they still
have some limitations due to poor performance in a number of situations. In
this paper, we propose a novel method based on the ensemble learning to boost
the performance of these machine learning methods for HAR
Epidermal growth factor (EGF)-like repeats of human tenascin-C as ligands for EGF receptor.
Signaling through growth factor receptors controls such diverse cell functions as proliferation, migration, and differentiation. A critical question has been how the activation of these receptors is regulated. Most, if not all, of the known ligands for these receptors are soluble factors. However, as matrix components are highly tissue-specific and change during development and pathology, it has been suggested that select growth factor receptors might be stimulated by binding to matrix components. Herein, we describe a new class of ligand for the epidermal growth factor (EGF) receptor (EGFR) found within the EGF-like repeats of tenascin-C, an antiadhesive matrix component present during organogenesis, development, and wound repair. Select EGF-like repeats of tenascin-C elicited mitogenesis and EGFR autophosphorylation in an EGFR-dependent manner. Micromolar concentrations of EGF-like repeats induced EGFR autophosphorylation and activated extracellular signal-regulated, mitogen-activated protein kinase to levels comparable to those induced by subsaturating levels of known EGFR ligands. EGFR-dependent adhesion was noted when the ligands were tethered to inert beads, simulating the physiologically relevant presentation of tenascin-C as hexabrachion, and suggesting an increase in avidity similar to that seen for integrin ligands upon surface binding. Specific binding to EGFR was further established by immunofluorescence detection of EGF-like repeats bound to cells and cross-linking of EGFR with the repeats. Both of these interactions were abolished upon competition by EGF and enhanced by dimerization of the EGF-like repeat. Such low affinity behavior would be expected for a matrix-tethered ligand; i.e., a ligand which acts from the matrix, presented continuously to cell surface EGF receptors, because it can neither diffuse away nor be internalized and degraded. These data identify a new class of insoluble growth factor ligands and a novel mode of activation for growth factor receptors
A Quantum Yield Map for Synthetic Eumelanin
The quantum yield of synthetic eumelanin is known to be extremely low and it
has recently been reported to be dependent on excitation wavelength. In this
paper, we present quantum yield as a function of excitation wavelength between
250 and 500 nm, showing it to be a factor of 4 higher at 250 nm than at 500 nm.
In addition, we present a definitive map of the steady-state fluorescence as a
function of excitation and emission wavelengths, and significantly, a
three-dimensional map of the specific quantum yield: the fraction of photons
absorbed at each wavelength that are subsequently radiated at each emission
wavelength. This map contains clear features, which we attribute to certain
structural models, and shows that radiative emission and specific quantum yield
are negligible at emission wavelengths outside the range of 585 and 385 nm (2.2
and 3.2 eV), regardless of excitation wavelength. This information is important
in the context of understanding melanin biofunctionality, and the quantum
molecular biophysics therein.Comment: 10 pages, 6 figure
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
Fuselage shell and cavity response measurements on a DC-9 test section
A series of fuselage shell and cavity response measurements conducted on a DC-9 aircraft test section are described. The objectives of these measurements were to define the shell and cavity model characteristics of the fuselage, understand the structural-acoustic coupling characteristics of the fuselage, and measure the response of the fuselage to different types of acoustic and vibration excitation. The fuselage was excited with several combinations of acoustic and mechanical sources using interior and exterior loudspeakers and shakers, and the response to these inputs was measured with arrays of microphones and accelerometers. The data were analyzed to generate spatial plots of the shell acceleration and cabin acoustic pressure field, and corresponding acceleration and pressure wavenumber maps. Analysis and interpretation of the spatial plots and wavenumber maps provided the required information on modal characteristics, structural-acoustic coupling, and fuselage response
On the calculation of the bandgap of periodic solids with MGGA functionals using the total energy
During the last few years, it has become more and more clear that functionals of the meta generalized gradient approximation (MGGA) are more accurate than GGA functionals for the geometry and energetics of electronic systems. However, MGGA functionals are also potentially more interesting for the electronic structure, in particular, when the potential is nonmultiplicative (i.e., when MGGAs are implemented in the generalized Kohn-Sham framework), which may help to get more accurate bandgaps. Here, we show that the calculation of bandgap of solids with MGGA functionals can also be done very accurately in a non-self-consistent manner. This scheme uses only the total energy and can, therefore, be very useful when the self-consistent implementation of a particular MGGA functional is not available. Since self-consistent MGGA calculations may be difficult to converge, the non-self-consistent scheme may also help to speed up the calculations. Furthermore, it can be applied to any other types of functionals, for which the implementation of the corresponding potential is not trivial
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
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
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