Toxicity Of Foundry Sand Wastes Using The Luminescent Bacteria Vibrio Fischeri Assay [toxicidade Do Resíduo Areia De Fundição Utilizando O Teste Com A Bactéria Luminescente Vibrio Fischeri]

Wastes foundry sand can be contaminated by metals, depending on the kind of metal that is molten in the casting industry and/or organics from chemical bindings used in these process. Because of the complexity of these mixtures it is difficult to characterize using only chemical analyses. In order to obtain information about the ecological hazard of those samples, biological tests can be used. The acute toxicity test with the luminescent bacteria Vibrio fischeri is a good choice due to its simplicity, low cost and rapid response. In this work virgin and used foundry sands from four different mold-making industries were analyzed. The aqueous extract of the nine virgin sands tested showed negative results for the luminescent bacteria. Ten out of the eighteen used sand samples were positive and they all belonged to the organics chemical-bounded sand process. The samples derived from the green sand mold-making process showed negative responses. Our work confirms that the Vibrio fischeri acute test can be used as an additional tool to evaluate the ecotoxicological hazard of foundry sands and that the toxicity seems to be related to the mold-making process. ©Sociedade Brasileira de Toxicologia.231-21721Scheunemann, R., (2005) Regeneração de Areia de Fundição Através de Tratamento Químico Via Processo Fentom, , [Dissertação] Florianópolis: Universidade Federal de Santa Catarina(1999) Manual de Regeneração e Reuso de Areias de Fundição, , ABIFA. (Associação Brasileira de Fundição). São Paulo: ABIFA(2010) Guia ABIFA de Fundição: Anuário 2010, , ABIFA. (Associação Brasileira de Fundição). São Paulo: ABIFAArmange, L.C., Neppel, L.F., Gemelli, E., Camargo, N.H.A., Utilização de areia de fundição residual para uso em argamassa (2005) Revista Matéria, 10, pp. 51-62http://www.materia.coppe.ufrj.br/sarra/artigos/artigo10631, Disponível em Acessado em 10/dez/2006Bastian, K.C., Alleman, J.E., Microtox(TM) characterization of foundry sand residuals (1998) Waste Management, 18 (4), pp. 227-234. , DOI 10.1016/S0956-053X(98)00030-0, PII S0956053X98000300Umbuzeiro, G.A., Rodrigues, P.F., O teste de toxicidade com bactérias luminescentes e o controle da poluição das águas (2004) O Mundo Da Saúde, 28, pp. 444-449(1992) Environmental Protection Series. Biological Test Method: Toxicity Test Using Luminescent Bacteria, p. 56. , Environment Canada. Canada: Método Analítico(1999) MicrotoxOmni™ Software, , Azur Environmental. CD-ROMHung, Y.T., Jiang, Z., Lo, H.H., Microtox bioassay of foundry sand residuals (2003) The Ohio J Science, 103, pp. 39-41(2002) Beneficial Reuse of Foundry Sand: A Review of State Practices and Regulations, p. 35. , USEPA (United States Environmental Protection Agency). Washington, DC(1991) Methods for Aquatic Toxicity Identification Evaluations: Phase I. Toxicity Characterization Procedures, p. 87. , USEPA (United States Environmental Protection Agency). 2nd ed. Final Report. Duluth, MN: Environment Research Laboratory, EPA/600/6-91/003(1992) Methods for Aquatic Toxicity Identification Evaluations: Phase II. Toxicity Identification Procedures for Samples Exhibiting Acute and Chronic Toxicity, p. 30. , USEPA (United States Environmental Protection Agency). Duluth, MN: Environment Research Laboratory, EPA/600/6-92/080(1993) Methods for Aquatic Toxicity Identification Evaluations: Phase III. Toxicity Confirmation Procedures for Samples Exhibiting Acute and Chronic Toxicity, p. 40. , USEPA (United States Environmental Protection Agency). Duluth, MN: Environment Research Laboratory, EPA/600/R-92/081(2007) Sediment Toxicity Identification Evaluation (TIE): Phases I, II and III. Guidance Document, p. 145. , USEPA (United States Environmental Protection Agency). Washington, DC: Office of Research and Development, EPA/600/R-07/08

Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

Measurements of electrons from νe interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of missing energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons

Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

Measurements of electrons from νe interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of missing energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons

Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

Measurements of electrons from νe interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of missing energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press