7,661 research outputs found
Concurrent bandits and cognitive radio networks
We consider the problem of multiple users targeting the arms of a single
multi-armed stochastic bandit. The motivation for this problem comes from
cognitive radio networks, where selfish users need to coexist without any side
communication between them, implicit cooperation or common control. Even the
number of users may be unknown and can vary as users join or leave the network.
We propose an algorithm that combines an -greedy learning rule with a
collision avoidance mechanism. We analyze its regret with respect to the
system-wide optimum and show that sub-linear regret can be obtained in this
setting. Experiments show dramatic improvement compared to other algorithms for
this setting
Polymer brush lubrication of the silicon nitride-steel contact: a colloidal force microscopy study
A greener lubrication solution for the steel–silicon nitride hybrid contact is proposed. The utilisation of surface-initiated (SI) activators-regenerated-by-electron-transfer (ARGET) atom-transfer radical polymerisation (ATRP) is employed to produce an oleophilic polymer brush which is based on methyl methacrylate. The current study presents the synthesis and characterisation of poly methyl methacrylate brushes. X-ray photoelectron spectroscopy, contact angle, gel permeation chromatography and atomic force microscopy were used to characterise the initiators and brushes. The lubricating effects of the polymer brushes under dry and swollen states were elucidated by lateral force microscopy with a steel colloid with a normal load in the nanoscale range. By testing in water and in poly α-olefin (PAO) this work shows that the frictional response of surface initiated polymers is highly dependent on the interaction between polymer brushes and fluid
A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition.
Recent years have witnessed the success of deep learning methods in human activity recognition (HAR). The longstanding shortage of labeled activity data inherently calls for a plethora of semisupervised learning methods, and one of the most challenging and common issues with semisupervised learning is the imbalanced distribution of labeled data over classes. Although the problem has long existed in broad real-world HAR applications, it is rarely explored in the literature. In this paper, we propose a semisupervised deep model for imbalanced activity recognition from multimodal wearable sensory data. We aim to address not only the challenges of multimodal sensor data (e.g., interperson variability and interclass similarity) but also the limited labeled data and class-imbalance issues simultaneously. In particular, we propose a pattern-balanced semisupervised framework to extract and preserve diverse latent patterns of activities. Furthermore, we exploit the independence of multi-modalities of sensory data and attentively identify salient regions that are indicative of human activities from inputs by our recurrent convolutional attention networks. Our experimental results demonstrate that the proposed model achieves a competitive performance compared to a multitude of state-of-the-art methods, both semisupervised and supervised ones, with 10% labeled training data. The results also show the robustness of our method over imbalanced, small training data sets
Fluorescent microsphere probe for rapid qualitative and quantitative detection of trypsin activity
Macroscopic Quantum Phase Interference in Antiferromagnetic Particles
The tunnel splitting in biaxial antiferromagnetic particles is studied with a
magnetic field applied along the hard anisotropy axis. We observe the
oscillation of tunnel splitting as a function of the magnetic field due to the
quantum phase interference of two tunneling paths of opposite windings. The
oscillation is similar to the recent experimental result with Fe}\textrm{\
molecular clusters.}Comment: 8 pages, 2 postscript figures, to appear in J. Phys.: Condes. Matte
Opportunities for use of exact statistical equations
Exact structure function equations are an efficient means of obtaining
asymptotic laws such as inertial range laws, as well as all measurable effects
of inhomogeneity and anisotropy that cause deviations from such laws. "Exact"
means that the equations are obtained from the Navier-Stokes equation or other
hydrodynamic equations without any approximation. A pragmatic definition of
local homogeneity lies within the exact equations because terms that explicitly
depend on the rate of change of measurement location appear within the exact
equations; an analogous statement is true for local stationarity. An exact
definition of averaging operations is required for the exact equations. Careful
derivations of several inertial range laws have appeared in the literature
recently in the form of theorems. These theorems give the relationships of the
energy dissipation rate to the structure function of acceleration increment
multiplied by velocity increment and to both the trace of and the components of
the third-order velocity structure functions. These laws are efficiently
derived from the exact velocity structure function equations. In some respects,
the results obtained herein differ from the previous theorems. The
acceleration-velocity structure function is useful for obtaining the energy
dissipation rate in particle tracking experiments provided that the effects of
inhomogeneity are estimated by means of displacing the measurement location.Comment: accepted by Journal of Turbulenc
Interplay of Spin-Orbit Interactions, Dimensionality, and Octahedral Rotations in Semimetallic SrIrO
We employ reactive molecular-beam epitaxy to synthesize the metastable
perovskite SrIrO and utilize {\it in situ} angle-resolved photoemission
to reveal its electronic structure as an exotic narrow-band semimetal. We
discover remarkably narrow bands which originate from a confluence of strong
spin-orbit interactions, dimensionality, and both in- and out-of-plane IrO
octahedral rotations. The partial occupation of numerous bands with strongly
mixed orbital characters signals the breakdown of the single-band Mott picture
that characterizes its insulating two-dimensional counterpart,
SrIrO, illustrating the power of structure-property relations for
manipulating the subtle balance between spin-orbit interactions and
electron-electron interactions
Infected Cell Killing by HIV-1 Protease Promotes NF-κB Dependent HIV-1 Replication
Acute HIV-1 infection of CD4 T cells often results in apoptotic death of infected cells, yet it is unclear what evolutionary advantage this offers to HIV-1. Given the independent observations that acute T cell HIV-1 infection results in (1) NF-κB activation, (2) caspase 8 dependent apoptosis, and that (3) caspase 8 directly activates NF-κB, we questioned whether these three events might be interrelated. We first show that HIV-1 infected T cell apoptosis, NF-κB activation, and caspase 8 cleavage by HIV-1 protease are coincident. Next we show that HIV-1 protease not only cleaves procaspase 8, producing Casp8p41, but also independently stimulates NF-κB activity. Finally, we demonstrate that the HIV protease cleavage of caspase 8 is necessary for optimal NF-κB activation and that the HIV-1 protease specific cleavage fragment Casp8p41 is sufficient to stimulate HIV-1 replication through NF-κB dependent HIV-LTR activation both in vitro as well as in cells from HIV infected donors. Consequently, the molecular events which promote death of HIV-1 infected T cells function dually to promote HIV-1 replication, thereby favoring the propagation and survival of HIV-1
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