1,977 research outputs found

    The Semantics of Folksonomies: The Meaning in Social Tagging

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    Regulation Effect of Different Water Supply to the Nitrogen and Carbon Metabolism

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    Drought stress and flood result in the generation and accumulation of active oxygen species, the peroxidation of membrane lipids, and reduction of nitrogen metabolism, photosynthesis, growth, and development, causing a significant decline in the qualitative and quantitative production. The water availability influences the different component of NUE and photosynthetic system and its connections. The goal of this chapter is to summarize the effect of water supply to the nitrogen and carbon metabolisms. Knowing about the value of nitrogen use efficiency and photosynthetic parameters is really a useful essential for selecting and growing the best genotypes. But what will happen with these two crucial characteristics of plants, if the environment for growing is not ideal?

    The Effect of Deep Water Aqua Treadmill Training on the Plasma Biochemical Parameters of Show Jumpers

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    Aqua treadmill is mainly used for rehabilitation purposes, but research indicates that this equipment could be used for training as well. The few studies performed with aqua treadmill mainly followed lactate and heart rate changes. Therefore, the aim of this study was to test the effect of high water treadmill training on several blood parameters and on the correlations between them. Eight similarly trained Standardbred show jumper horse competing at the same level were selected with age between 6 to 11 years. The horses were subjected to a one week standardized exercise test which included normal training, training with show jumping and aqua treadmill training. The aqua treadmill training consisted of a 10 min walk (filling up, 4.5 km/h), 30 min trot (13 km/h) and 4 min walk (emptying, 4.5 km/h). Blood samples were taken from the jugular vein before aqua training, at the completion of each work bout, after drying and after one and two hour rest. Blood plasma were separated and lactate, LDH, CK, AST, glucose, cholesterol, triglyceride, total-bilirubin and cortisol level were determined. In conclusion plasma lactate response itself does not reflect correctly the intensity of workload in high water level aqua training, therefore measurement of several blood parameters is advisable. Further studies needed to understand the relationship of metabolic processes altered due to the effect of partial water submersion

    The Effect of Deep Water Aqua Treadmill Training on the Plasma Biochemical Parameters of Show Jumpers

    Get PDF
    Aqua treadmill is mainly used for rehabilitation purposes, but research indicates that this equipment could be used for training as well. The few studies performed with aqua treadmill mainly followed lactate and heart rate changes. Therefore, the aim of this study was to test the effect of high water treadmill training on several blood parameters and on the correlations between them. Eight similarly trained Standardbred show jumper horse competing at the same level were selected with age between 6 to 11 years. The horses were subjected to a one week standardized exercise test which included normal training, training with show jumping and aqua treadmill training. The aqua treadmill training consisted of a 10 min walk (filling up, 4.5 km/h), 30 min trot (13 km/h) and 4 min walk (emptying, 4.5 km/h). Blood samples were taken from the jugular vein before aqua training, at the completion of each work bout, after drying and after one and two hour rest. Blood plasma were separated and lactate, LDH, CK, AST, glucose, cholesterol, triglyceride, total-bilirubin and cortisol level were determined. In conclusion plasma lactate response itself does not reflect correctly the intensity of workload in high water level aqua training, therefore measurement of several blood parameters is advisable. Further studies needed to understand the relationship of metabolic processes altered due to the effect of partial water submersion

    Named Entity Extraction for Knowledge Graphs: A Literature Overview

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    An enormous amount of digital information is expressed as natural-language (NL) text that is not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for representing information in computer-processable form. Natural Language Processing (NLP) is therefore needed for mining (or lifting) knowledge graphs from NL texts. A central part of the problem is to extract the named entities in the text. The paper presents an overview of recent advances in this area, covering: Named Entity Recognition (NER), Named Entity Disambiguation (NED), and Named Entity Linking (NEL). We comment that many approaches to NED and NEL are based on older approaches to NER and need to leverage the outputs of state-of-the-art NER systems. There is also a need for standard methods to evaluate and compare named-entity extraction approaches. We observe that NEL has recently moved from being stepwise and isolated into an integrated process along two dimensions: the first is that previously sequential steps are now being integrated into end-to-end processes, and the second is that entities that were previously analysed in isolation are now being lifted in each other's context. The current culmination of these trends are the deep-learning approaches that have recently reported promising results.publishedVersio

    The Nuclear Localization Signal of NF-κB p50 Enters the Cells via Syndecan-Mediated Endocytosis and Inhibits NF-κB Activity

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    It is well established that cationic peptides can enter cells following attachment to polyanionic membrane components. We report that the basic nuclear localization signal (NLS) of the NF-κB p50 subunit is internalized via lipid raft-dependent endocytosis mediated by heparan sulfate proteoglycans and exerts significant NF-κB inhibitory activities both in vitro and in vivo. In vitro uptake experiments revealed that the p50 NLS peptide (CYVQRKRQKLMP) enters the cytoplasm and accumulates in the nucleus at 37 °C. Depleting cellular ATP pools or decreasing temperature to 4 °C abolished peptide internalization, confirming the active, energy-dependent endocytic uptake. Co-incubation with heparan sulfate or replacing the peptide’s basic residues with glycines markedly reduced the intracellular entry of the p50 NLS, referring to the role of polyanionic cell-surface proteoglycans in internalization. Furthermore, treatment with methyl-β-cyclodextrin greatly inhibited the peptide’s membrane translocation. Overexpression of the isoforms of the syndecan family of transmembrane proteoglycans, especially syndecan-4, increased the cellular internalization of the NLS, suggesting syndecans’ involvement in the peptide’s cellular uptake. In vitro , p50 NLS reduced NF-κB activity in TNF-α-induced L929 fibroblasts and LPS-stimulated RAW 264.7 macrophages. TNF-α-induced ICAM-1 expression of HMEC-1 human endothelial cells could also be inhibited by the peptide. Fifteen minutes after its intraperitoneal injection, the peptide rapidly entered the cells of the pancreas, an organ with marked syndecan-4 expression. In an acute pancreatitis model, an inflammatory disorder triggered by the activation of stress-responsive transcription factors like NF-κB, administration of the p50 NLS peptide reduced the severity of pancreatic inflammation by blocking NF-κB transcription activity and ameliorating the examined laboratory and histological markers of pancreatitis

    Towards a Big Data Platform for News Angles

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    Finding good angles on news events is a central journalistic and editorial skill. As news work becomes increasingly computer-assisted and big-data based, journalistic tools therefore need to become better able to support news angles too. This paper outlines a big-data platform that is able to suggest appropriate angles on news events to journalists. We first clarify and discuss the central characteristics of news angles. We then proceed to outline a big-data architecture that can propose news angles. Important areas for further work include: representing news angles formally; identifying interesting and unexpected angles on unfolding events; and designing a big-data architecture that works on a global scale.publishedVersio
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