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visualization and error compensation of demolition robot attachment changing
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Abstract Motivation Antibodies are widely used experimental reagents to test expression of proteins. However, they might not always provide the intended tests because they do not specifically bind to the target proteins that their providers designed them for, leading to unreliable and irreproducible research results. While many proposals have been developed to deal with the problem of antibody specificity, they may not scale well to deal with the millions of antibodies that have ever been designed and used in research. In this study, we investigate the feasibility of automatically extracting statements about antibody specificity reported in the literature by text mining, and generate reports to alert scientist users of problematic antibodies. Results We developed a deep neural network system called Antibody Watch and tested its performance on a corpus of more than two thousand articles that report uses of antibodies. We leveraged the Research Resource Identifiers (RRID) to precisely identify antibodies mentioned in an input article and the BERT language model to classify if the antibodies are reported as nonspecific, and thus problematic, as well as inferred the coreference to link statements of specificity to the antibodies that the statements referred to. Our evaluation shows that Antibody Watch can accurately perform both classification and linking with F-scores over 0.8, given only thousands of annotated training examples. The result suggests that with more training, Antibody Watch will provide useful reports about antibody specificity to scientists.
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Early detection of infectious diseases is the most cost-effective strategy in disease surveillance for reducing the risk of outbreaks. Latest deep learning and computer vision improvements are powerful tools that open up a new field of research in epidemiology and disease control. In this work, these techniques were employed to develop an algorithm aimed to track and compute individual animal motion in real time. This algorithm was used in experimental trials in order to assess African swine fever (ASF) infection course in Eurasian wild boar. Overall, the outcomes showed a strong correlation between motion reduction and fever caused by ASF infection. In addition, infected animals computed significant low movements compared to uninfected animals. The obtained results suggest that a motion monitoring system based on artificial intelligence may be used to trigger suspicions of fever. It would help farmers and animal health services to early detect clinical signs compatible with infectious diseases. This technology shows a promising start up for implementing non-intrusive, economic and real time solutions in the livestock industry with especial interest in ASF, considering the current concern in the world pig industry.
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Pequenos Cientistas em Casa Acompanha as atividades que o Centro Ciência Viva do Algarve publica para poderes fazer em casa. Diverte-te em família, fazendo as nossas atividade e partilha connosco os resultado através de fotografias ou vídeo. #PequenosCientistasEmCasa #PequenosCientistasCCVAlg HOJE: "Constrói o teu Herbário sem sair de casa" Vem descobrir o que é um herbário e como podes preservar as plantas que tens em casa. ATENÇÃO!! Não saias de casa para adquirir nenhum destes materiais. Se não os tiveres todos, aguarda pelo nosso próximo desafio! #PequenosCientistasEmCasa #PequenosCientistasCCVAlg #ccvalg #cienciaviva #ficaemcasa #herbário #plantas #papel #coleção #catalogo
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ADM 2654 - Aula de 24/03
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  • Video
Pequenos Cientistas em Casa Acompanha as atividades que o Centro Ciência Viva do Algarve publica para poderes fazer em casa. Diverte-te em família, fazendo as nossas atividade e partilha connosco os resultado através de fotografias ou vídeo. #PequenosCientistasEmCasa #PequenosCientistasCCVAlg HOJE: "O Jogo do moinho" Um jogo ancestral de estratégia para toda a família! Divirtam-se! ATENÇÃO!! Não saias de casa para adquirir nenhum destes materiais. Se não os tiveres todos, aguarda pelo nosso próximo desafio! #PequenosCientistasEmCasa #PequenosCientistasCCVAlg #ccvalg #cienciaviva #ficaemcasa #moinho #jogo #boardgame
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This is the video of the workshop (16 December 2019 – Vila-sana, Lleida, Spain) jointly organised by the Circular Agronomics project and the H2020 project Nutri2Cycle on European initiatives for nutrient recycling in agri-food systems. The event showcased the various strategies that exist across Europe to recycle nutrients and that the different EU-funded projects already working to achieve this can complement one another in order to attain a common goal. One of the experimental sites within the Catalonia case study of the Circular Agronomics project was visited.
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miRNAs and mRNA expression spectrum in tree shrew fungal keratitis
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Changes: Delete superfluous file and add DOI badge
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X-ray diffraction data analysis for high pressure and high temperature experiments
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