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Institution

University of Oviedo

EducationOviedo, Spain
About: University of Oviedo is a education organization based out in Oviedo, Spain. It is known for research contribution in the topics: Population & Catalysis. The organization has 13423 authors who have published 31649 publications receiving 844799 citations. The organization is also known as: Universidá d'Uviéu & Universidad de Oviedo.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the digital divide across the regions of the 27 Member States and within each country and explained the observed regional disparities, and identified Dutch regions as the Top-10 in ICT, while Greece and Bulgaria occupied the Bottom-10.

171 citations

Journal ArticleDOI
TL;DR: Evidence is provided that well-defined DNA methylation profiles enable breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.
Abstract: Introduction Identification of gene expression-based breast cancer subtypes is considered a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene-expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and only a limited understanding exists of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and to deliver specific epigenotypes associated with particular breast cancer subtypes.

171 citations

Journal ArticleDOI
TL;DR: In this paper, surface-modified CdSe semiconductor quantum dots (QDs), with nanoparticle size distribution in the order of 2-7nm, have been synthesized for optical determination of cyanide ions.

170 citations

Journal ArticleDOI
TL;DR: The frequency of the ACE I allele was significantly increased among elite athletes and it is concluded that the ACE polymorphism represents a genetic factor that contributes to the development of an elite athlete.
Abstract: The D allele at the angiotensin-I-converting enzyme (ACE)-insertion/deletion polymorphism has been associated with an increased risk of developing several pathological processes, such as coronary heart disease and ventricular hypertrophy. Individuals with the DD genotype show a significantly increased left-ventricular mass in response to physical training, compared to the II genotype (which would be associated with the lowest plasma ACE levels) and the ID genotype. The II genotype has been linked to a greater anabolic response. In accordance with a role for ACE in the response to rigorous physical training, a higher frequency of the I allele has been reported to exist among elite rowers and high-altitude mountaineers. Sixty elite (professional) athletes (25 cyclists, 20 long-distance runners, and 15 handball players), and 400 healthy controls were genotyped for the DNA polymorphisms of the ACE, angiotensinogen (Ang) and angiotensin receptor type 1 (AT1) genes. Plasma ACE levels showed a strong correlation with the I/D genotype in our population. The I-allele occurred at a significantly higher frequency in athletes compared to controls (P=0.0009). Gene and genotype frequencies for the Ang and AT1 polymorphisms did not differ between athletes and controls. Since the frequency of the ACE I allele was significantly increased among our elite athletes, we conclude that the ACE polymorphism represents a genetic factor that contributes to the development of an elite athlete.

170 citations

Proceedings ArticleDOI
19 Jun 2000
TL;DR: It is proved that no uniprocessor scheduling algorithm/allocation algorithm pair can provide a higher worst-case achievable utilization than that of EDF-FF.
Abstract: Presents the utilization bound for earliest deadline first (EDF) scheduling on homogeneous multiprocessor systems with partitioning strategies. Assuming that tasks are pre-emptively scheduled on each processor according to the EDF algorithm, and allocated according to the first-fit (FF) heuristic, we prove that the worst-case achievable utilization is 0.5(n+1), where n is the number of processors. This bound is valid for arbitrary utilization factors. Moreover, if all the tasks have utilization factors under a value /spl alpha/, the previous bound is raised, and the new utilization bound considering /spl alpha/ is calculated. In addition, we prove that no uniprocessor scheduling algorithm/allocation algorithm pair can provide a higher worst-case achievable utilization than that of EDF-FF. Finally, simulation provides the average-case achievable utilization for EDF-FF.

170 citations


Authors

Showing all 13643 results

NameH-indexPapersCitations
Russel J. Reiter1691646121010
Carlo Rovelli1461502103550
J. González-Nuevo144500108318
German Martinez1411476107887
Roland Horisberger1391471100458
Francisco Herrera139100182976
Javier Cuevas1381689103604
Teresa Rodrigo1381831103601
L. Toffolatti13637695529
Elias Campo13576185160
Gabor Istvan Veres135134996104
Francisco Matorras134142894627
Joe Incandela134154993750
Nikhil C. Munshi13490667349
Luca Scodellaro134174198331
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202396
2022268
20211,825
20201,913
20191,806
20181,721