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Institution

University of Seville

EducationSeville, 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 & Model predictive control. The organization has 20098 authors who have published 47317 publications receiving 947007 citations. The organization is also known as: Universidad de Sevilla.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a global Delphi study, a multidisciplinary group of experts developed consensus statements and recommendations, which a larger group of collaborators reviewed over three rounds until consensus was achieved.
Abstract: Non-alcoholic fatty liver disease (NAFLD) is a potentially serious liver disease that affects approximately one-quarter of the global adult population, causing a substantial burden of ill health with wide-ranging social and economic implications. It is a multisystem disease and is considered the hepatic component of metabolic syndrome. Unlike other highly prevalent conditions, NAFLD has received little attention from the global public health community. Health system and public health responses to NAFLD have been weak and fragmented, and, despite its pervasiveness, NAFLD is largely unknown outside hepatology and gastroenterology. There is only a nascent global public health movement addressing NAFLD, and the disease is absent from nearly all national and international strategies and policies for non-communicable diseases, including obesity. In this global Delphi study, a multidisciplinary group of experts developed consensus statements and recommendations, which a larger group of collaborators reviewed over three rounds until consensus was achieved. The resulting consensus statements and recommendations address a broad range of topics - from epidemiology, awareness, care and treatment to public health policies and leadership - that have general relevance for policy-makers, health-care practitioners, civil society groups, research institutions and affected populations. These recommendations should provide a strong foundation for a comprehensive public health response to NAFLD.

195 citations

Journal ArticleDOI
TL;DR: This paper proposes two mathematical programming formulations which generalize the non-periodic train timetabling problem on a single line under a dynamic demand pattern and introduces a fast adaptive large neighborhood search (ALNS) metaheuristic, demonstrating the computational superiority of the ALNS compared with a truncated branch-and-cut algorithm.
Abstract: Railway planning is a complex activity which is usually decomposed into several stages, traditionally network design, line design, timetabling, rolling stock, and staffing. In this paper, we study the design and optimization of train timetables for a rail rapid transit (RRT) line adapted to a dynamic demand environment, which focuses on creating convenient timetables for passengers. The objective is to minimize the average passenger waiting time at the stations, thus focusing on passenger welfare. We first propose two mathematical programming formulations which generalize the non-periodic train timetabling problem on a single line under a dynamic demand pattern. We then analyze the properties of the problem before introducing a fast adaptive large neighborhood search (ALNS) metaheuristic in order to solve large instances of the problem within short computation times. The algorithm yields timetables that may not be regular or periodic, but are adjusted to a dynamic demand behavior. Through extensive computational experiments on artificial and real-world based instances, we demonstrate the computational superiority of our ALNS compared with a truncated branch-and-cut algorithm. The average reduction in passenger waiting times is 26%, while the computational time of our metaheuristic is less than 1% of that required by the alternative CPLEX-based algorithm. Out of 120 open instances, we obtain 84 new best known solutions and we reach the optimum on 10 out of 14 instances with known optimal solutions.

195 citations

Journal ArticleDOI
TL;DR: The authors used author co-citation analysis (ACA) to identify different research trends within the field, studying all the papers published in the Family Business Review from its foundation in 1988 through to the December 2005 issue, finding that despite the literature being fragmented and showing a lack of consensus, we are facing a development of the research frontier by enlarging the number of approaches used for understanding the family business.
Abstract: This article aims at identifying the characteristics of the family business as a differentiated field within management. For that aim, we use author co-citation analysis (ACA) to identify different research trends within the field, studying all the papers published in the Family Business Review from its foundation in 1988 through to the December 2005 issue. Results show that despite the literature being fragmented and showing a lack of consensus, we are facing, in Kuhn's words, a development of the research frontier by enlarging the number of approaches used for understanding the family business.

194 citations

Journal ArticleDOI
TL;DR: Four complexity classes for cellular computing systems with membranes are introduced and the usefulness of these classes is illustrated by solving two NP–completeproblems, namely HPP and SAT, in both variants of P systems.
Abstract: In this paper we introduce four complexity classes for cellular computing systems with membranes: the first and the second ones contain all decision problems solvable in polynomial time by a family of deterministic P systems, without and with an input membrane, respectively; the third and fourth classes contain all decision problems solvable in polynomial time by a family of non-deterministic P systems, without and with an input membrane, respectively. We illustrate the usefulness of these classes by solving two NP–complete problems, namely HPP and SAT, in both variants of P systems.

194 citations

Journal ArticleDOI
TL;DR: Single-cell analysis reveals that phenotypic heterogeneity is common in bacteria, and appears to be frequent during adaptation to harsh environments, including the colonization of animals by bacterial pathogens.

194 citations


Authors

Showing all 20465 results

NameH-indexPapersCitations
Russel J. Reiter1691646121010
Aaron Dominguez1471968113224
Jose M. Ordovas123102470978
Detlef Lohse104107542787
Miroslav Krstic9595542886
María Vallet-Regí9571141641
John S. Sperry9316035602
Jose Rodriguez9380358176
Shun-ichi Amari9049540383
Michael Ortiz8746731582
Bruce J. Paster8426128661
Floyd E. Dewhirst8122942613
Joan Montaner8048922413
Francisco B. Ortega7950326069
Luis Paz-Ares7759231496
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023143
2022567
20213,357
20203,480
20193,032
20182,766