820 research outputs found
A Neural Network Gravitational Arc Finder based on the Mediatrix filamentation Method
Automated arc detection methods are needed to scan the ongoing and
next-generation wide-field imaging surveys, which are expected to contain
thousands of strong lensing systems. Arc finders are also required for a
quantitative comparison between predictions and observations of arc abundance.
Several algorithms have been proposed to this end, but machine learning methods
have remained as a relatively unexplored step in the arc finding process. In
this work we introduce a new arc finder based on pattern recognition, which
uses a set of morphological measurements derived from the Mediatrix
Filamentation Method as entries to an Artificial Neural Network (ANN). We show
a full example of the application of the arc finder, first training and
validating the ANN on simulated arcs and then applying the code on four Hubble
Space Telescope (HST) images of strong lensing systems. The simulated arcs use
simple prescriptions for the lens and the source, while mimicking HST
observational conditions. We also consider a sample of objects from HST images
with no arcs in the training of the ANN classification. We use the training and
validation process to determine a suitable set of ANN configurations, including
the combination of inputs from the Mediatrix method, so as to maximize the
completeness while keeping the false positives low. In the simulations the
method was able to achieve a completeness of about 90% with respect to the arcs
that are input to the ANN after a preselection. However, this completeness
drops to 70% on the HST images. The false detections are of the order of
3% of the objects detected in these images. The combination of Mediatrix
measurements with an ANN is a promising tool for the pattern recognition phase
of arc finding. More realistic simulations and a larger set of real systems are
needed for a better training and assessment of the efficiency of the method.Comment: Updated to match published versio
Optical Emission Model for Binary Black Hole Merger Remnants Travelling through Discs of Active Galactic Nucleus
Active galactic nuclei (AGNs) have been proposed as plausible sites hosting a
sizable fraction of the binary black hole (BBH) mergers measured through
gravitational waves (GWs) by the LIGO-Virgo-Kagra (LVK) experiment. These GWs
could be accompanied by radiation feedback due to the interaction of the BBH
merger remnant with the AGN disc. We present a new predicted radiation
signature driven by the passage of a kicked BBH remnant throughout a thin AGN
disc. We analyse the situation of a merger occurring outside the thin disc,
where the merger is of second or higher generation in a merging hierarchical
sequence. The coalescence produces a kicked BH remnant that eventually plunges
into the disc, accretes material, and inflates jet cocoons. We consider the
case of a jet cocoon propagating quasi-parallel to the disc plane and study the
outflow that results when the cocoon emerges from the disc. Here we focus on
the long time-scale emission produced after the disc outflow expands and
becomes optically thin. The bolometric luminosity of such disc outflow evolves
as . Depending on the parameter configuration, the flare
produced by the disc outflow could be comparable to or exceed the AGN
background emission at near-infrared, optical, and extreme ultraviolet
wavelengths appearing [20-500] days after the GW event and lasting for
[1-200] days, accordingly.Comment: 11 pages, 8 figures. Submitted to MNRA
Allergenic Airborne Pollen in Portugal 2002-2004
Os calendários polínicos constituem instrumentos fundamentais para a orientação clínica de doentes alérgicos. Em Portugal, a sua elaboração de forma sistematizada teve início em 2002. Para tal foram colocados polinómetros volumétricos Burkard em cinco cidades do país: Porto, Coimbra, Lisboa, Évora e Portimão. O registo das contagens foi efectuado por método estandardizado. As contagens polínicas diárias expressam a concentração média por m3. Estas contagens foram objecto de análise descritiva e comparativa. O período de incidência polínica máxima decorre entre Março e Julho, sendo o pólen de Poaceae e de ervas silvestres os mais frequentemente identificados. Em Janeiro, Fevereiro e Dezembro existem níveis elevados de pólen de árvores em todo o território nacional. O Sul do país apresenta indicadores de polinização mais intensa
Strengths of breath-triggered inhalers in asthma management
publishersversionpublishe
Estudo da Variação Intradiária das Concentrações de Pólen de Gramíneas na Atmosfera de Portugal Continental
Introdução: O pólen da família das Poaceae (gramíneas) é uma das principais fontes de aeroalergénios no mundo,
particularmente na Europa Mediterrânica. Representa, por isso, um importante factor de risco de asma, rinite e/ou conjuntivite
alérgica e constitui a principal causa de polinose em Portugal. Objectivo: Analisar a variação intradiária das
concentrações de pólen de gramíneas na atmosfera das 5 estações de monitorização continentais da Rede Portuguesa
de Aerobiologia (RPA): Porto, Coimbra, Lisboa, Évora e Portimão. Métodos: Neste estudo utilizaram -se os dados diários
e horários das monitorizações de pólen de gramíneas das cinco estações de monitorização continentais da RPA, ao
longo de 7 anos (2002 -2008). Resultados: Entre as localidades encontraram -se diferenças significativas, em termos de
Estudo da variação intradiária das
concentrações de pólen de gramíneas
na atmosfera de Portugal Continental
O pólen atmosférico de gramíneas constitui a
principal causa de rinite, asma, conjuntivite e
eczema nos indivíduos alérgicos ao pólen na
área Mediterrânica1,2, nomeadamente em Portugal3,4.
Dado que o pólen, particularmente o pólen de gramíneas,
é um factor de risco para as doenças alérgicas
respiratórias exercendo um impacto negativo sobre a
qualidade de vida dos indivíduos sensibilizados, é de
particular interesse, quer dos profissionais de saúde,
quer do doente conhecer a sua distribuição intradiária,
ou seja a variação horária das concentrações de pólen
de gramíneas ao longo do dia, de modo a adequar de
forma mais eficaz medidas de evicção e de intervenção
terapêutica.
curvas horárias. O pólen encontrou -se presente na atmosfera durante 24 horas em todas as localidades, e os valores
das concentrações horárias variaram ao longo do dia e de ano para ano. As concentrações mais baixas registaram -se
entre as 22 e as 6 horas e as mais elevadas, entre as 7 e as 21 horas, as quais em Évora ultrapassaram os 30 grãos de
pólen/m3/hora. Em geral, registaram -se 2 picos de concentrações máximas, um de manhã (9 -10 horas) ou à tarde (12 -13
horas) e outro no final da tarde / início da noite (19 -20 horas). Conclusões: O ritmo diurno difere muito de local para
local. Cada localidade tem o seu próprio padrão de variação das concentrações horárias do pólen atmosférico de gramíneas
que se pode dever, quer às diferentes espécies presentes, quer às diferentes condições ambientais. O risco de
exposição variou de localidade para localidade e ao longo do dia, sendo o Porto a localidade onde este é menor, enquanto
Évora apresenta o maior risco
Developing a Victorious Strategy to the Second Strong Gravitational Lensing Data Challenge
Strong Lensing is a powerful probe of the matter distribution in galaxies and
clusters and a relevant tool for cosmography. Analyses of strong gravitational
lenses with Deep Learning have become a popular approach due to these
astronomical objects' rarity and image complexity. Next-generation surveys will
provide more opportunities to derive science from these objects and an
increasing data volume to be analyzed. However, finding strong lenses is
challenging, as their number densities are orders of magnitude below those of
galaxies. Therefore, specific Strong Lensing search algorithms are required to
discover the highest number of systems possible with high purity and low false
alarm rate. The need for better algorithms has prompted the development of an
open community data science competition named Strong Gravitational Lensing
Challenge (SGLC). This work presents the Deep Learning strategies and
methodology used to design the highest-scoring algorithm in the II SGLC. We
discuss the approach used for this dataset, the choice for a suitable
architecture, particularly the use of a network with two branches to work with
images in different resolutions, and its optimization. We also discuss the
detectability limit, the lessons learned, and prospects for defining a
tailor-made architecture in a survey in contrast to a general one. Finally, we
release the models and discuss the best choice to easily adapt the model to a
dataset representing a survey with a different instrument. This work helps to
take a step towards efficient, adaptable and accurate analyses of strong lenses
with deep learning frameworks.Comment: 14 pages, 12 figure
Search for the Radiative Capture d+d->^4He+\gamma Reaction from the dd\mu Muonic Molecule State
A search for the muon catalyzed fusion reaction dd --> ^4He +\gamma in the
dd\mu muonic molecule was performed using the experimental \mu CF installation
TRITON and NaI(Tl) detectors for \gamma-quanta. The high pressure target filled
with deuterium at temperatures from 85 K to 800 K was exposed to the negative
muon beam of the JINR phasotron to detect \gamma-quanta with energy 23.8 MeV.
The first experimental estimation for the yield of the radiative deuteron
capture from the dd\mu state J=1 was obtained at the level n_{\gamma}\leq
2\times 10^{-5} per one fusion.Comment: 9 pages, 3 Postscript figures, submitted to Phys. At. Nuc
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