A simple prescription for simulating and characterizing gravitational arcs

Simple models of gravitational arcs are crucial to simulate large samples of these objects with full control of the input parameters. These models also provide crude and automated estimates of the shape and structure of the arcs, which are necessary when trying to detect and characterize these objects on massive wide area imaging surveys. We here present and explore the ArcEllipse, a simple prescription to create objects with shape similar to gravitational arcs. We also present PaintArcs, which is a code that couples this geometrical form with a brightness distribution and adds the resulting object to images. Finally, we introduce ArcFitting, which is a tool that fits ArcEllipses to images of real gravitational arcs. We validate this fitting technique using simulated arcs and apply it to CFHTLS and HST images of tangential arcs around clusters of galaxies. Our simple ArcEllipse model for the arc, associated to a S\'ersic profile for the source, recovers the total signal in real images typically within 10%-30%. The ArcEllipse+S\'ersic models also automatically recover visual estimates of length-to-width ratios of real arcs. Residual maps between data and model images reveal the incidence of arc substructure. They may thus be used as a diagnostic for arcs formed by the merging of multiple images. The incidence of these substructures is the main factor preventing ArcEllipse models from accurately describing real lensed systems.Comment: 12 pages, 11 figures, accepted for publication in A&

Influências nas ideias de estudantes do 5o ano do ensino fundamental sobre ciências

Anais do II Seminário Seminário Estadual PIBID do Paraná: tecendo saberes / organizado por Dulcyene Maria Ribeiro e Catarina Costa Fernandes — Foz do Iguaçu: Unioeste; Unila, 2014O presente artigo apresenta e discute as ideias sobre ciências, expressas por meio de desenhos, de estudantes do 5o ano do ensino fundamental (EF) de uma escola da rede pública municipal da cidade Londrina – Paraná. Solicitou-se que por meio de desenhos, sem qualquer ajuda ou pesquisa, tentassem esboçar o que entendiam por ciência. Foram analisados 42 desenhos distribuídos em 3 categorias. Como resultado foi possível perceber que a ideia que os estudantes do 5o ano do EF desta escola possuem sobre ciências, decorre do que lhes é atribuído pela mídia, do ambiente familiar ou do próprio currículo escola

Construct Validity, Reliability, and Responsiveness of the 10-Item Well-being Instrument for Use in Economic Evaluation Studies

Objectives: Economic evaluations of interventions in health and social care require outcome measures that capture their full benefits, including those beyond health. This study aimed to assess construct validity, test-retest reliability, and responsiveness of the newly developed 10-item Well-being instrument (WiX). Methods: Data were gathered via an online survey in a representative sample of the adult general population in The Netherlands (N = 1045). Construct validity was assessed by inspecting convergent, structural, and discriminant validity, following the COnsensus-based Standards for the selection of health status Measurement INstruments methodology. Regression analyses of the WiX and its items on other validated measures of well-being were performed to assess the convergent validity of the instrument and the relevance of its items. Dimensionality of the WiX was assessed using exploratory factor analysis. To assess discriminant validity, several hypotheses in terms of well-being differences were assessed. Finally, a second survey was sent out 2 weeks after the initial survey (n = 563; 53.9% response rate) to assess the test-retest reliability and responsiveness of the WiX. Results: The WiX showed to be correlated with alternative well-being measures as expected and able to sufficiently differentiate between relevant subgroups in the population. Moreover, the dimensionality analysis indicated that the WiX captures a broad array of elements relevant to well-being, including physical and mental health. The test-retest reliability was good, with an intraclass correlation coefficient of 0.82. Conclusions: The results regarding the WiX are favorable and indicate that this new instrument may be a promising alternative for existing measures of well-being for evaluating interventions in health and social care.</p

Deep-pretrained-FWI: combining supervised learning with physics-informed neural network

An accurate velocity model is essential to make a good seismic image. Conventional methods to perform Velocity Model Building (VMB) tasks rely on inverse methods, which, despite being widely used, are ill-posed problems that require intense and specialized human supervision. Convolutional Neural Networks (CNN) have been extensively investigated as an alternative to solve the VMB task. Two main approaches were investigated in the literature: supervised training and Physics-Informed Neural Networks (PINN). Supervised training presents some generalization issues since structures, and velocity ranges must be similar in training and test set. Some works integrated Full-waveform Inversion (FWI) with CNN, defining the problem of VMB in the PINN framework. In this case, the CNN stabilizes the inversion, acting like a regularizer and avoiding local minima-related problems and, in some cases, sparing an initial velocity model. Our approach combines supervised and physics-informed neural networks by using transfer learning to start the inversion. The pre-trained CNN is obtained using a supervised approach based on training with a reduced and simple data set to capture the main velocity trend at the initial FWI iterations. We show that transfer learning reduces the uncertainties of the process, accelerates model convergence, and improves the final scores of the iterative process.Comment: Paper present at machine Learning and the Physical Sciences workshop, NeurIPS 202

Estimates of forest canopy height and aboveground biomass using ICESat

Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite (ICESat) has collected an unparalleled dataset of lidar waveforms over terrestrial targets, processing of ICESat data to estimate forest height is complicated by the pulse broadening associated with large-footprint, waveform-sampling lidar. We combined ICESat waveforms and ancillary topography from the Shuttle Radar Topography Mission to estimate maximum forest height in three ecosystems; tropical broadleaf forests in Brazil, temperate broadleaf forests in Tennessee, and temperate needleleaf forests in Oregon. Final models for each site explained between 59% and 68% of variance in field-measured forest canopy height (RMSE between 4.85 and 12.66 m). In addition, ICESat-derived heights for the Brazilian plots were correlated with field-estimates of aboveground biomass (r(2) = 73%, RMSE = 58.3 Mgha(-1))

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

Asthma-COPD overlap: A Portuguese survey

Introduction: The overlap between asthma and chronic obstructive pulmonary disease (COPD) (ACO) has been discussed for many years but clinical recommendations for this entity have been diverse. This study is intended to reach a consensus on diagnosis, treatment and patient orientation for ACO, within the Portuguese medical community. Methods: This study was conducted by a multidisciplinary panel of experts from three distinct medical specialties (Pulmonology, Family Medicine and Immunoallergology). This panel selected a total of 190 clinicians, based on their expertise in obstructive airway diseases, to participate in a Delphi structured survey with three rounds of questionnaires. These results were ultimately discussed, in a meeting with the panel of experts and some of the study participants, and consensus was reached in terms of classification criteria, treatment and orientation of ACO patients. Results: The majority of clinicians (87.2%) considered relevant the definition of an overlap entity between asthma and COPD. A consensus was achieved on the diagnosis of ACO – presence of simultaneous clinical characteristics of asthma and COPD together with a fixed airflow obstruction (FEV1/FVC 300 eosinophils/μL or >5% of leukocytes); elevation of specific IgEs or positive skin tests for common allergens). A combination of inhaled corticosteroid (ICS) with long-acting beta2-agonist (LABA) or long-acting muscarinic antagonist (LAMA) was considered as first line pharmacological treatment. Triple therapy with ICS plus LABA and LAMA should be used in more severe or symptomatic cases. Non-pharmacological treatment, similar to what is recommended for asthma and COPD, was also considered highly important. A hospital referral of ACO patients should be made in symptomatic or severe cases or when there is a lack of diagnostic resources. Conclusions: This study highlights the relevance of defining ACO, within the Portuguese medical community, and establishes diagnostic criteria that are important for future interventional studies. Recommendations on treatment and patient's orientation were also achieved.Actelion Pharmaceuticals (undefined)info:eu-repo/semantics/publishedVersio

Reduction of anti-K-mediated hemolytic disease of newborns after the introduction of a matched transfusion policy:A nation-wide policy change evaluation study in the Netherlands

Background: During pregnancy, maternal red blood cell (RBC) antibodies can lead to life-threatening fetal hemolysis and anemia. Women can become immunized by a pregnancy or an unmatched transfusion. Our aim was to quantify the effect of a nationwide K-matched transfusion policy for women of childbearing age potential to prevent K-immunization in pregnancy. Study Design and Methods: In this nation-wide policy change evaluation study we determined the occurrence of RBC antibodies before and after introduction of a K-matched transfusion policy and evaluated the cause K alloimmunization 10 years after introduction of this measure. K-matched transfusion for females under 45 years of age is advised in the Dutch transfusion guideline since 2004. We used laboratory data from pregnancies with RBC antibodies identified in the period 1999-2018 obtained as part of a population-based screening program in the Netherlands. Results: Tests of 36 286 pregnancies produced a positive antibody screening result which concerned anti-K in 1550 pregnancies. The occurrence of anti-K decreased from 67.9 to 20.2 per 100 000 pregnancies. The relative risk reduction was 0.70 which largely exceeded the relative risk reduction of 0.27 for antibodies against RBC antigens for which no preventive matching is required. The number of pregnancies at risk for anti-K-mediated disease decreased from 9.7 to 4.2 per 100 000 pregnancies. Conclusions: A K-matched transfusion policy is associated with a major decrease in a number of pregnant women with anti-K and pregnancies at risk for anti-K-mediated disease. A relatively simple measure is now shown to impact prevention of hemolytic disease in the fetus and newborn

Enhancement of Trichoderma harzianum CFAM-422 for cellulase and hemicellulase production by deletion of the carbon catabolite repressor gene cre1.

Carbon catabolite repression (CCR) is a mechanism by which microorganisms can utilize preferably highly energetic compounds over those of difficult degradation. For Trichoderma reesei, the protein that acts as repressor in the presence of glucose is CRE1. In this project, we aim to delete cre1 gene in Trichoderma harzianum CFAM-422 and obtain mutants with enhanced production of biomass degrading enzymes. Disruption of cre1 in T. harzianum CFAM-422 was performed by gene replacement of cre1 for hph (hygromycin B phosphotransferase) via homologous recombination. Hygromycin resistant mutants and parental strains enzyme production was evaluated in both inductive and repressive conditions in four different carbon sources. Enzymatic indexes (EI) were determined and compared. All genetically stable transformants showed increased enzymatic index under inductive conditions and modest inhibition under repressive conditions for most carbon sources, indicating that the deletion of cre1 in T. harzianum can be beneficial to cellulase and hemicellulase production with reduced product inhibition.SINAFERM; SHEB. 3 a 6 de setembro. Seção Trabalhos. Ref. 59019