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A layer-by-layer analysis of the structures, the phase compositions, and the defect substructures of differentially hardened rails has been carried by optical and transmission electron microscopy. It is found that the material volume of the rail head fillet is cooled faster than the volume located along the central axis.  相似文献   
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Lobster krill (Munida genus) represents an under‐valued crustacean frequently caught on European fishing banks. In this work, its sensory, microbiological and biochemical qualities were evaluated during chilled storage. Additionally, the effects of a prestorage antimelanosic treatment consisting of soaking in sodium metabisulphite (SMB) solutions at two different concentrations (0.25% and 0.75%) were also studied. SMB prestorage treatment provided lobster specimens that still exhibited acceptable sensory quality after 10 days of storage, while control specimens were unacceptable at that time. SMB treatment also resulted in a significant (P < 0.05) inhibition of microbial growth, mainly of Enterobacteriaceae, psychrotrophes and proteolytic bacteria. Low lipid oxidation levels were observed for all batches; however, a significantly higher (P < 0.05) retention of polyunsaturated fatty acids was found in SMB‐treated lobster, especially in the 0.75% SMB batch. The results presented here open the way to the potential commercialisation of currently under‐utilised lobster krill as a chilled product.  相似文献   
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Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.  相似文献   
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Metallurgical and Materials Transactions A - The influence of the chemical composition on the crystallization process, amorphous phase formation, and the anticorrosion properties of Al-Zr-Ni-Fe-Y...  相似文献   
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Hussien  O. S.  Elamy  M. I. 《Strength of Materials》2020,52(3):470-479
Strength of Materials - The use of a damping system is one of the seismic protection systems that improve the seismic response of structures. The proposed methodology estimates the location (which...  相似文献   
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Powder Metallurgy and Metal Ceramics - The infiltration of aluminum melts into porous metal skeletons produced by powder metallurgy methods, including 3D printing, under a pressure gradient was...  相似文献   
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