Institution
University of Seville
Education•Seville, Andalucía, Spain•
About: University of Seville is a education organization based out in Seville, Andalucía, Spain. It is known for research contribution in the topics: Population & Context (language use). The organization has 20098 authors who have published 47317 publications receiving 947007 citations. The organization is also known as: Universidad de Sevilla.
Topics: Population, Context (language use), Model predictive control, Nonlinear system, Control theory
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the stabilization of soils with natural polymers and fibres to produce a composite, sustainable, non-toxic and locally sourced building material has been studied using a clay soil supplied by a Scottish brick manufacture.
243 citations
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TL;DR: In the present review, an update of the knowledge about the pathogenicity, antimicrobial resistance and clinical aspects of this ‘old friend’ was presented.
Abstract: Escherichia coli is one of the most-studied microorganisms worldwide but its characteristics are continually changing. Extraintestinal E. coli infections, such as urinary tract infections and neonatal sepsis, represent a huge public health problem. They are caused mainly by specialized extraintestinal pathogenic E. coli (ExPEC) strains that can innocuously colonize human hosts but can also cause disease upon entering a normally sterile body site. The virulence capability of such strains is determined by a combination of distinctive accessory traits, called virulence factors, in conjunction with their distinctive phylogenetic background. It is conceivable that by developing interventions against the most successful ExPEC lineages or their key virulence/colonization factors the associated burden of disease and health care costs could foreseeably be reduced in the future. On the other hand, one important problem worldwide is the increase of antimicrobial resistance shown by bacteria. As underscored in the last WHO global report, within a wide range of infectious agents including E. coli, antimicrobial resistance has reached an extremely worrisome situation that ‘threatens the achievements of modern medicine’. In the present review, an update of the knowledge about the pathogenicity, antimicrobial resistance and clinical aspects of this ‘old friend’ was presented.
242 citations
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TL;DR: In this article, the authors examined the long-term correlates of victimization in school with aspects of functioning in adult life, using a specially designed Retrospective Bullying Questionnaire, which also included questions about short-term effects (e.g. suicidal ideation and intrusive memories) and victimization experiences in adulthood.
Abstract: This study examined the long-term correlates of victimization in school with aspects of functioning in adult life, using a specially designed Retrospective Bullying Questionnaire, which also included questions about short-term effects (e. g. suicidal ideation and intrusive memories) and victimization experiences in adulthood. Current relationship quality was assessed in terms of self-perception, attachment style and friendship quality. In total, 884 adults (35% male) from two occupations (teacher, student) and three countries (Spain, Germany, UK) participated. Victims and especially stable victims (in both primary and secondary school) scored lower on general self-esteem and higher on emotional loneliness, and reported more difficulties in maintaining friendships, than non-victims. Victims in secondary school had a lower self-esteem in relation to the opposite sex and were more often fearfully attached. The data revealed additional differences by gender, occupation and country level, but no further interactions with victim status. This indicates a general association between victimization in school and quality of later life predominately robust to variations in gender, occupation and country. Possible limitations caused by the retrospective nature of victimization reports are acknowledged.
242 citations
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TL;DR: Pattern recognition methods such as principal component analysis (PCA), linear discriminant analysis (LDA), and artificial neural networks (ANN), were applied to differentiate the tea types and provided the best results in the classification of tea varieties.
Abstract: The metal content of 46 tea samples, including green, black, and instant teas, was analyzed. Al, Ba, Ca, Cu, Fe, K, Mg, Mn, Na, Sr, Ti, and Zn were determined by ICP-AES. Potassium, with an average content of 15145.4 mg kg(-1) was the metal with major content. Calcium, magnesium, and aluminum had average contents of 4252.4, 1978.2, and 1074.0 mg kg(-1), respectively. The average amount of manganese was 824.8 mg kg(-1). There were no clear differences between the metal contents of green and black teas. Pattern recognition methods such as principal component analysis (PCA), linear discriminant analysis (LDA), and artificial neural networks (ANN), were applied to differentiate the tea types. LDA and ANN provided the best results in the classification of tea varieties. These chemometric procedures were also useful for distinguishing between Asian and African teas and between the geographical origin of different Asian teas.
242 citations
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TL;DR: A review of the main dead-time compensators (DTC) described in literature is presented in this article, where the basic Smith predictor (SP) showing its advantages and drawbacks is analyzed.
242 citations
Authors
Showing all 20465 results
Name | H-index | Papers | Citations |
---|---|---|---|
Russel J. Reiter | 169 | 1646 | 121010 |
Aaron Dominguez | 147 | 1968 | 113224 |
Jose M. Ordovas | 123 | 1024 | 70978 |
Detlef Lohse | 104 | 1075 | 42787 |
Miroslav Krstic | 95 | 955 | 42886 |
María Vallet-Regí | 95 | 711 | 41641 |
John S. Sperry | 93 | 160 | 35602 |
Jose Rodriguez | 93 | 803 | 58176 |
Shun-ichi Amari | 90 | 495 | 40383 |
Michael Ortiz | 87 | 467 | 31582 |
Bruce J. Paster | 84 | 261 | 28661 |
Floyd E. Dewhirst | 81 | 229 | 42613 |
Joan Montaner | 80 | 489 | 22413 |
Francisco B. Ortega | 79 | 503 | 26069 |
Luis Paz-Ares | 77 | 592 | 31496 |