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 $\sim$ 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 $L\propto t^{-7/2}$. 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 $\sim$[20-500] days after the GW event and lasting for $\sim$[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

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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