6 research outputs found

    INFLUÊNCIA DOS TIPOS DE MATÉRIAS-PRIMAS E DAS CONDIÇÕES DE QUEIMA NA COR DO SUPORTE CERÂMICO

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    O desenvolvimento de formulações de massas cerâmicas é uma tarefa muitas vezes difícil, pois a seleção das matérias-primas é um fator determinante para a obtenção de massas adequadas ao processo produtivo e que atenda as características técnicas do produto a ser fabricado. Uma característica de uma massa cerâmica é sua coloração e está diretamente relacionada com o tipo de matéria-prima utilizada, mas principalmente a presença de óxidos corantes (ferro e titânio) em sua composição química. Frente a isto, o objetivo deste projeto é avaliar a influência dos óxidos corantes na coloração de uma massa cerâmica formada por feldspato sódico e argilito. Além da presença dos óxidos, avaliar também a influência da temperatura máxima de queima na cor da massa cerâmica. Foram elaboradas massas cerâmicas com concentrações de óxidos corantes de 0,36% até 3,03% e queimadas em temperaturas de 1100°C, 1150°C e 1175°C. Os resultados mostram que existe uma influência significativa da presença de óxidos corantes na coloração das massas e que as temperaturas mais elevadas não contribuem significativamente para uma alteração da cor de queima das massas cerâmicas

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

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    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 research.Peer reviewe

    Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study

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

    No full text

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

    No full text
    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
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