10,851 research outputs found
Multiparticle Quantum Superposition and Stimulated Entanglement by Parity Selective Amplification of Entangled States
A multiparticle quantum superposition state has been generated by a novel
phase-selective parametric amplifier of an entangled two-photon state. This
realization is expected to open a new field of investigations on the
persistence of the validity of the standard quantum theory for systems of
increasing complexity, in a quasi decoherence-free environment. Because of its
nonlocal structure the new system is expected to play a relevant role in the
modern endeavor on quantum information and in the basic physics of
entanglement.Comment: 13 pages and 3 figure
Bars from the Inside Out: An HST Study of their Dusty Circumnuclear Regions
The results of bar-driven mass inflow are directly observable in
high-resolution HST observations of their circumnuclear regions. These
observations reveal a wealth of structures dominated by dust lanes, often with
a spiral-like morphology, and recent star formation. Recent work has shown that
some of these structures are correlated with the presence or absence of a bar.
I extend this work with an investigation of circumnuclear morphology as a
function of bar strength for a sample of 48 galaxies with both measured bar
strengths and ``structure maps'' computed from HST images. The structure maps
for these galaxies, which have projected spatial resolutions of 2 - 15 pc, show
that the fraction of galaxies with grand-design (GD) circumnuclear dust spirals
increases significantly with bar strength, while tightly wound dust spirals are
only present in the most axisymmetric galaxies. GD structure is only found at
the centers of galaxies classified as SB(s) or SB(rs) and not SB(r). SB(s)
galaxies on average have stronger bars than SB(r) galaxies. There is also a
modest increase in the fraction of loosely wound dust spirals at later
morphological types, which may reflect an increase in the fraction of galaxies
with circumnuclear, gaseous disks. (abridged)Comment: 10 pages, 6 figures. To appear in "Penetrating Bars through Masks of
Cosmic Dust: The Hubble Tuning Fork strikes a New Note" held June 7-12th,
2004 in Pilanesberg National Park, South Africa. Version with higher
resolution figures is available at
http://cfa-www.harvard.edu/~pmartini/professional/publications/safrica04.pd
An adaptive stigmergy-based system for evaluating technological indicator dynamics in the context of smart specialization
Regional innovation is more and more considered an important enabler of
welfare. It is no coincidence that the European Commission has started looking
at regional peculiarities and dynamics, in order to focus Research and
Innovation Strategies for Smart Specialization towards effective investment
policies. In this context, this work aims to support policy makers in the
analysis of innovation-relevant trends. We exploit a European database of the
regional patent application to determine the dynamics of a set of technological
innovation indicators. For this purpose, we design and develop a software
system for assessing unfolding trends in such indicators. In contrast with
conventional knowledge-based design, our approach is biologically-inspired and
based on self-organization of information. This means that a functional
structure, called track, appears and stays spontaneous at runtime when local
dynamism in data occurs. A further prototyping of tracks allows a better
distinction of the critical phenomena during unfolding events, with a better
assessment of the progressing levels. The proposed mechanism works if
structural parameters are correctly tuned for the given historical context.
Determining such correct parameters is not a simple task since different
indicators may have different dynamics. For this purpose, we adopt an
adaptation mechanism based on differential evolution. The study includes the
problem statement and its characterization in the literature, as well as the
proposed solving approach, experimental setting and results.Comment: mail: [email protected]
Input-Output Relations in Optical Cavities: a Simple Point of View
In this work we present a very simple approach to input-output relations in
optical cavities, limiting ourselves to one- and two-photon states of the
field.
After field quantization, we derive the non-unitary transformation between
{\em Inside} and {\em Outside} annihilation and creation operators. Then we
express the most general two-photon state generated by {\em Inside} creation
operators, through base states generated by {\em Outside} creation operators.
After renormalization of coefficients of inside two-photon state, we calculate
the outside photon-number probability distribution in a general case. Finally
we treat with some detail the single mode and symmetrical cavity case.Comment: 34 pages, 5 figures jpg, LaTe
Progressive impairment of CaV1.1 function in the skeletal muscle of mice expressing a mutant type 1 Cu/Zn superoxide dismutase (G93A) linked to amyotrophic lateral sclerosis
Background: Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disorder that is typically fatal
within 3–5 years of diagnosis. While motoneuron death is the defining characteristic of ALS, the events that
underlie its pathology are not restricted to the nervous system. In this regard, ALS muscle atrophies and weakens
significantly before presentation of neurological symptoms. Since the skeletal muscle L-type Ca2+ channel (CaV1.1) is
a key regulator of both mass and force, we investigated whether CaV1.1 function is impaired in the muscle of two
distinct mouse models carrying an ALS-linked mutation.
Methods: We recorded L-type currents, charge movements, and myoplasmic Ca2+ transients from dissociated flexor
digitorum brevis (FDB) fibers to assess CaV1.1 function in two mouse models expressing a type 1 Cu/Zn superoxide
dismutase mutant (SOD1G93A).
Results: In FDB fibers obtained from “symptomatic” global SOD1G93A mice, we observed a substantial reduction of
SR Ca2+ release in response to depolarization relative to fibers harvested from age-matched control mice. L-type
current and charge movement were both reduced by ~40 % in symptomatic SOD1G93A fibers when compared to
control fibers. Ca2+ transients were not significantly reduced in similar experiments performed with FDB fibers obtained
from “early-symptomatic” SOD1G93A mice, but L-type current and charge movement were decreased (~30 and ~20 %,
respectively). Reductions in SR Ca2+ release (~35 %), L-type current (~20 %), and charge movement (~15 %) were also
observed in fibers obtained from another model where SOD1G93A expression was restricted to skeletal muscle.
Conclusions: We report reductions in EC coupling, L-type current density, and charge movement in FDB fibers
obtained from symptomatic global SOD1G93A mice. Experiments performed with FDB fibers obtained from
early-symptomatic SOD1G93A and skeletal muscle autonomous MLC/SOD1G93A mice support the idea that events
occurring locally in the skeletal muscle contribute to the impairment of CaV1.1 function in ALS muscle independently
of innervation status
Using object-based image analysis to detect laughing gull nests
Remote sensing has long been used to study wildlife; however, manual methods of detecting wildlife in aerial imagery are often time-consuming and prone to human error, and newer computer vision techniques have not yet been extensively applied to wildlife surveys. We used the object-based image analysis (OBIA) software eCognition to detect laughing gull (Leucophaeus atricilla) nests in Jamaica Bay as part of an ongoing monitoring effort at the John F. Kennedy International Airport. Our technique uses a combination of high resolution 4-band aerial imagery captured via manned aircraft with a multispectral UltraCam Falcon M2 camera, LiDAR point cloud data, and land cover data derived from a bathymetric LiDAR point cloud to classify and extract laughing gull nests. Our ruleset uses the site (topographic position of nest objects), tone (spectral characteristic of nest objects), shape, size, and association (nearby objects commonly found with the objects of interest that help identify them) elements of image interpretation, as well as NDVI and a sublevel object examination to classify and extract nests. The ruleset achieves a producer’s accuracy of 98% as well as a user’s accuracy of 65% and a kappa of 0.696, indicating that it extracts a majority of the nests in the imagery while reducing errors of commission to only 35% of the final results. The remaining errors of commission are difficult for the software to differentiate without also impacting the number of nests successfully extracted and are best addressed by a manual verification of output results as part of a semi-automated workflow in which the OBIA is used to complete the initial search of the imagery and the results are then systematically verified by the user to remove errors. This eliminates the need to manually search entire sets of imagery for nests, resulting in a much more efficient and less error prone methodology than previous unassisted image interpretation techniques. Because of the extensibility of OBIA software and the increasing availability of imagery due to small unmanned aircraft systems (sUAS), our methodology and its benefits have great potential for adaptation to other species surveyed using aerial imagery to enhance wildlife population monitoring
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