2,438 research outputs found
Comment on "Ising model on a small world network"
In the recent study of the Ising model on a small-world network by A.
P\c{e}kalski [Phys. Rev. E {\bf 64}, 057104 (2001)], a surprisingly small value
of the critical exponent has been obtained for the
temperature dependence of the magnetization. We perform extensive Monte Carlo
simulations of the same model and conclude, via the standard finite-size
scaling of various quantities,that the phase transition in the model is of the
mean-field nature, in contrast to the work by A. P\c{e}kalski but in accord
with other existing studies.Comment: to be published in PR
"SAMs meet MEMS": surface modification with self-assembled monolayers for the dry-demolding of photoplastic MEMS/NEMS
In this contribution we demonstrate the use of self-assembled monolayers (SAMs) as anti-adhesion coating to assist the removal of photoplastic MEMS/NEMS with a patterned metal layer from the surface without wet chemical sacrificial layer etching, so-called 'dry-demolding'. The SAMs functionality here is to reduce the stiction between the surface and a thin evaporated metal film. The double-layer SAM/metal provides enough stability to support subsequent micromachining step
Penalized Orthogonal-Components Regression for Large p Small n Data
We propose a penalized orthogonal-components regression (POCRE) for large p
small n data. Orthogonal components are sequentially constructed to maximize,
upon standardization, their correlation to the response residuals. A new
penalization framework, implemented via empirical Bayes thresholding, is
presented to effectively identify sparse predictors of each component. POCRE is
computationally efficient owing to its sequential construction of leading
sparse principal components. In addition, such construction offers other
properties such as grouping highly correlated predictors and allowing for
collinear or nearly collinear predictors. With multivariate responses, POCRE
can construct common components and thus build up latent-variable models for
large p small n data.Comment: 12 page
Lattice effects on the current-voltage characteristics of superconducting arrays
The lattice effects on the current-voltage characteristics of two-dimensional
arrays of resistively shunted Josephson junctions are investigated. The lattice
potential energies due to the discrete lattice structure are calculated for
several geometries and directions of current injection. We compare the energy
barrier for vortex-pair unbinding with the lattice pinning potential, which
shows that lattice effects are negligible in the low-current limit as well as
in the high-current limit. At intermediate currents, on the other hand, the
lattice potential becomes comparable to the barrier height and the lattice
effects may be observed in the current-voltage characteristics.Comment: 5 pages including 5 figures in two columns, to appear in Phys. Rev.
Photoplastic SU-8 probes for Near-Field Optical Applications
We propose a new attempt to solve the manufacturing problem of SNOM probes by a novel wafer-scale microfabrication process for sharp pyramidal and bright photoplastic probes. The probes are fabricated of a transparent photoplastic material (SU-8) which allows simple batch fabrication based on spin coating and subsequent near-ultraviolet exposure and development steps. SU-8 consists of the epoxy-based EPON SU-8 resin photosensitized with a triaryl sulfonium salt. The main interest for MOEMS applications is that SU-8 is transparent. These combined advantages are used here to define a sharp, transparent and high aspect ratio probe dedicated for near-field optical application
Boundary Effects on Dynamic Behavior of Josephson-Junction Arrays
The boundary effects on the current-voltage characteristics in
two-dimensional arrays of resistively shunted Josephson junctions are examined.
In particular, we consider both the conventional boundary conditions (CBC) and
the fluctuating twist boundary conditions (FTBC), and make comparison of the
obtained results. It is observed that the CBC, which have been widely adopted
in existing simulations, may give a problem in scaling, arising from rather
large boundary effects; the FTBC in general turn out to be effective in
reducing the finite-size effects, yielding results with good scaling behavior.
To resolve the discrepancy between the two boundary conditions, we propose that
the proper scaling in the CBC should be performed with the boundary data
discarded: This is shown to give results which indeed scale well and are the
same as those from the FTBC.Comment: RevTex, Final version to appear in Phys. Rev.
Viability of primordial black holes as short period gamma-ray bursts
It has been proposed that the short period gamma-ray bursts, which occur at a
rate of , may be evaporating primordial black holes
(PBHs). Calculations of the present PBH evaporation rate have traditionally
assumed that the PBH mass function varies as . This mass
function only arises if the density perturbations from which the PBHs form have
a scale invariant power spectrum. It is now known that for a scale invariant
power spectrum, normalised to COBE on large scales, the PBH density is
completely negligible, so that this mass function is cosmologically irrelevant.
For non-scale-invariant power spectra, if all PBHs which form at given epoch
have a fixed mass then the PBH mass function is sharply peaked around that
mass, whilst if the PBH mass depends on the size of the density perturbation
from which it forms, as is expected when critical phenomena are taken into
account, then the PBH mass function will be far broader than . In this paper we calculate the present day PBH evaporation rate,
using constraints from the diffuse gamma-ray background, for both of these mass
functions. If the PBH mass function has significant finite width, as recent
numerical simulations suggest, then it is not possible to produce a present day
PBH evaporation rate comparable with the observed short period gamma-ray burst
rate. This could also have implications for other attempts to detect
evaporating PBHs.Comment: 5 pages, 2 figures, version to appear in Phys. Rev. D with additional
reference
In Vivo Photoacoustic Imaging of Anterior Ocular Vasculature: A Random Sample Consensus Approach
Visualizing ocular vasculature is important in clinical ophthalmology because ocular circulation abnormalities are early signs of ocular diseases. Photoacoustic microscopy (PAM) images the ocular vasculature without using exogenous contrast agents, avoiding associated side effects. Moreover, 3D PAM images can be useful in understanding vessel-related eye disease. However, the complex structure of the multi-layered vessels still present challenges in evaluating ocular vasculature. In this study, we demonstrate a new method to evaluate blood circulation in the eye by combining in vivo PAM imaging and an ocular surface estimation method based on a machine learning algorithm: a random sample consensus algorithm. By using the developed estimation method, we were able to visualize the PA ocular vascular image intuitively and demonstrate layer-by-layer analysis of injured ocular vasculature. We believe that our method can provide more accurate evaluations of the eye circulation in ophthalmic applications. ? The Author(s) 2017.1110Ysciescopu
Systems Level Modeling of the Cell Cycle Using Budding Yeast
Proteins involved in the regulation of the cell cycle are highly conserved across all eukaryotes, and so a relatively simple eukaryote such as yeast can provide insight into a variety of cell cycle perturbations including those that occur in human cancer. To date, the budding yeast Saccharomyces cerevisiae has provided the largest amount of experimental and modeling data on the progression of the cell cycle, making it a logical choice for in-depth studies of this process. Moreover, the advent of methods for collection of high-throughput genome, transcriptome, and proteome data has provided a means to collect and precisely quantify simultaneous cell cycle gene transcript and protein levels, permitting modeling of the cell cycle on the systems level. With the appropriate mathematical framework and sufficient and accurate data on cell cycle components, it should be possible to create a model of the cell cycle that not only effectively describes its operation, but can also predict responses to perturbations such as variation in protein levels and responses to external stimuli including targeted inhibition by drugs. In this review, we summarize existing data on the yeast cell cycle, proteomics technologies for quantifying cell cycle proteins, and the mathematical frameworks that can integrate this data into representative and effective models. Systems level modeling of the cell cycle will require the integration of high-quality data with the appropriate mathematical framework, which can currently be attained through the combination of dynamic modeling based on proteomics data and using yeast as a model organism
Scaling determination of the nonlinear I-V characteristics for 2D superconducting networks
It is shown from computer simulations that the current-voltage (-)
characteristics for the two-dimensional XY model with resistively-shunted
Josephson junction dynamics and Monte Carlo dynamics obeys a finite-size
scaling form from which the nonlinear - exponent can be determined to
good precision. This determination supports the conclusion , where
is the dynamic critical exponent. The results are discussed in the light of the
contrary conclusion reached by Tang and Chen [Phys. Rev. B {\bf 67}, 024508
(2003)] and the possibility of a breakdown of scaling suggested by Bormann
[Phys. Rev. Lett. {\bf 78}, 4324 (1997)].Comment: 6 pages, to appear in PR
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