8,182 research outputs found
A physics-based approach to flow control using system identification
Control of amplifier flows poses a great challenge, since the influence of environmental noise sources and measurement contamination is a crucial component in the design of models and the subsequent performance of the controller. A modelbased approach that makes a priori assumptions on the noise characteristics often yields unsatisfactory results when the true noise environment is different from the assumed one. An alternative approach is proposed that consists of a data-based systemidentification technique for modelling the flow; it avoids the model-based shortcomings by directly incorporating noise influences into an auto-regressive (ARMAX) design. This technique is applied to flow over a backward-facing step, a typical example of a noise-amplifier flow. Physical insight into the specifics of the flow is used to interpret and tailor the various terms of the auto-regressive model. The designed compensator shows an impressive performance as well as a remarkable robustness to increased noise levels and to off-design operating conditions. Owing to its reliance on only timesequences of observable data, the proposed technique should be attractive in the design of control strategies directly from experimental data and should result in effective compensators that maintain performance in a realistic disturbance environment
Properties of massive stars in four clusters of the VVV survey
The evolution of massive stars is only partly understood. Observational
constraints can be obtained from the study of massive stars located in young
massive clusters. The ESO Public Survey VISTA Variables in the Via Lactea (VVV)
discovered several new clusters hosting massive stars. We present an analysis
of massive stars in four of these new clusters. Our aim is to provide
constraints on stellar evolution and to better understand the relation between
different types of massive stars. We use the radiative transfer code CMFGEN to
analyse K-band spectra of twelve stars with spectral types ranging from O and B
to WN and WC. We derive the stellar parameters of all targets as well as
surface abundances for a subset of them. In the Hertzsprung-Russell diagram,
the Wolf-Rayet stars are more luminous or hotter than the O stars. From the
log(C/N) - log(C/He) diagram, we show quantitatively that WN stars are more
chemically evolved than O stars, WC stars being more evolved than WN stars.
Mass loss rates among Wolf-Rayet stars are a factor of 10 larger than for O
stars, in agreement with previous findings.Comment: paper accepted in New Astronom
The role of M cells and the long QT syndrome in cardiac arrhythmias: simulation studies of reentrant excitations using a detailed electrophysiological model
In this numerical study, we investigate the role of intrinsic heterogeneities
of cardiac tissue due to M cells in the generation and maintenance of reentrant
excitations using the detailed Luo-Rudy dynamic model. This model has been
extended to include a description of the long QT 3 syndrome, and is studied in
both one dimension, corresponding to a cable traversing the ventricular wall,
and two dimensions, representing a transmural slice. We focus on two possible
mechanisms for the generation of reentrant events. We first investigate if
early-after-depolarizations occurring in M cells can initiate reentry. We find
that, even for large values of the long QT strength, the electrotonic coupling
between neighboring cells prevents early-after-depolarizations from creating a
reentry. We then study whether M cell domains, with their slow repolarization,
can function as wave blocks for premature stimuli. We find that the inclusion
of an M cell domain can result in some cases in reentrant excitations and we
determine the lifetime of the reentry as a function of the size and geometry of
the domain and of the strength of the long QT syndrome
On Lightweight Privacy-Preserving Collaborative Learning for IoT Objects
The Internet of Things (IoT) will be a main data generation infrastructure
for achieving better system intelligence. This paper considers the design and
implementation of a practical privacy-preserving collaborative learning scheme,
in which a curious learning coordinator trains a better machine learning model
based on the data samples contributed by a number of IoT objects, while the
confidentiality of the raw forms of the training data is protected against the
coordinator. Existing distributed machine learning and data encryption
approaches incur significant computation and communication overhead, rendering
them ill-suited for resource-constrained IoT objects. We study an approach that
applies independent Gaussian random projection at each IoT object to obfuscate
data and trains a deep neural network at the coordinator based on the projected
data from the IoT objects. This approach introduces light computation overhead
to the IoT objects and moves most workload to the coordinator that can have
sufficient computing resources. Although the independent projections performed
by the IoT objects address the potential collusion between the curious
coordinator and some compromised IoT objects, they significantly increase the
complexity of the projected data. In this paper, we leverage the superior
learning capability of deep learning in capturing sophisticated patterns to
maintain good learning performance. Extensive comparative evaluation shows that
this approach outperforms other lightweight approaches that apply additive
noisification for differential privacy and/or support vector machines for
learning in the applications with light data pattern complexities.Comment: 12 pages,IOTDI 201
Creep motion of a granular pile induced by thermal cycling
We report a time-resolved study of the dynamics associated with the slow
compaction of a granular column submitted to thermal cycles. The column height
displays a complex behavior: for a large amplitude of the temperature cycles,
the granular column settles continuously, experiencing a small settling at each
cycle; By contrast, for small-enough amplitude, the column exhibits a
discontinuous and intermittent activity: successive collapses are separated by
quiescent periods whose duration is exponentially distributed. We then discuss
potential mechanisms which would account for both the compaction and the
transition at finite amplitude.Comment: 4 pages, 5 figures, accepted for publication in Physical Review
Letters (05sep08
Superconducting cascade electron refrigerator
The design and operation of an electronic cooler based on a combination of
superconducting tunnel junctions is described. The cascade extraction of
hot-quasiparticles, which stems from the energy gaps of two different
superconductors, allows for a normal metal to be cooled down to about 100 mK
starting from a bath temperature of 0.5 K. We discuss the practical
implementation, potential performance and limitations of such a device
Spin Hall effect of Photons in a Static Gravitational Field
Starting from a Hamiltonian description of the photon within the set of
Bargmann-Wigner equations we derive new semiclassical equations of motion for
the photon propagating in static gravitational field. These equations which are
obtained in the representation diagonalizing the Hamiltonian at the order
, present the first order corrections to the geometrical optics. The
photon Hamiltonian shows a new kind of helicity-magnetotorsion coupling.
However, even for a torsionless space-time, photons do not follow the usual
null geodesic as a consequence of an anomalous velocity term. This term is
responsible for the gravitational birefringence phenomenon: photons with
distinct helicity follow different geodesics in a static gravitational field.Comment: 6 page
Pulling and Stretching a Molecular Wire to Tune its Conductance
A scanning tunnelling microscope is used to pull a polythiophene wire from a
Au(111) surface while measuring the current traversing the junction. Abrupt
current increases measured during the lifting procedure are associated to the
detachment of molecular sub-units, in apparent contradiction with the expected
exponential decrease of the conductance with wire length. \textit{Ab initio}
simulations reproduce the experimental data and demonstrate that this
unexpected behavior is due to release of mechanical stress in the wire, paving
the way to mechanically gated single-molecule electronic devices
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