Institution
University of Alcalá
Education•Alcalá de Henares, Spain•
About: University of Alcalá is a education organization based out in Alcalá de Henares, Spain. It is known for research contribution in the topics: Population & Receptor. The organization has 10795 authors who have published 20718 publications receiving 410089 citations. The organization is also known as: University of Alcala & University of Alcala de Henares.
Topics: Population, Receptor, Band-pass filter, Species richness, Dendrimer
Papers published on a yearly basis
Papers
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TL;DR: A new tool designed to reinforce students' knowledge by means of self-assessment improves student achievement, especially amongst younger learners, with a relatively low impact on current teaching activities and methodology.
Abstract: Mobile learning is considered an evolution of e-learning that embraces the ubiquitous nature of current computational systems in order to improve teaching and learning. Within this context it is possible to develop mobile applications oriented to learning, but it is also important to assess to what extent such applications actually work. In this paper we present a new tool designed to reinforce students' knowledge by means of self-assessment. Improvement in student achievement was evaluated and an attitudinal survey was also carried out to measure student attitudes towards this new tool. Three different experimental groups were selected for this research, with students aged from 14 to 21 years old, including high-school and university students. Results show that this kind of tool improves student achievement, especially amongst younger learners, with a relatively low impact on current teaching activities and methodology.
92 citations
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TL;DR: The effects of atypical or second-generation antipsychotics (SGA), such as clozapine, risperidone, and ziprasid one, on intracellular lipid metabolism in different cell lines are investigated, finding that these effects of SGAs on lipid homeostasis may be relevant in the metabolic side effects of antippsychotics, especially hypertriglyceridemia.
92 citations
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TL;DR: The endocrine profile of the intrauterine growth retardation newborns and its association with anthropometric parameters at birth is investigated.
Abstract: Objective. To investigate the endocrine profile of the intrauterine growth retardation newborns and its association with anthropometric parameters at birth.Study design. This is a case-control study of 76 full term gestations, of which 31 were diagnosed as intrauterine growth retardation (IUGR) confirmed at birth, and 45 as normal births. Insulin, insulin-like growth factor I (IGF-I), growth hormone (GH), thyroid stimulating hormone (TSH), hydrocortisone, prolactin and 15 metabolic parameters were measured in maternal blood antepartum, amniotic fluid and umbilical cord blood at birth.Results. Blood taken from the umbilical cord in the IUGR group had statistically significant lower levels of IGF-I, insulin and TSH, but higher levels of GH. In amniotic fluid and maternal blood, IUGR babies had lower levels of cortisol. The changes in GH and glucose levels in cord blood of IUGR babies were independently associated to birth weight variability (Adjusted regression coefficient-squared=0.09 and 0.17 respectively...
92 citations
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TL;DR: Fractal type features were the most robust family of parameters (in the sense of accuracy vs. computational load) for the automatic detection of murmurs from phonocardiographic signals.
Abstract: This work presents a comparison of different approaches for the detection of murmurs from phonocardiographic signals. Taking into account the variability of the phonocardiographic signals induced by valve disorders, three families of features were analyzed: (a) time-varying & time-frequency features; (b) perceptual; and (c) fractal features. With the aim of improving the performance of the system, the accuracy of the system was tested using several combinations of the aforementioned families of parameters. In the second stage, the main components extracted from each family were combined together with the goal of improving the accuracy of the system. The contribution of each family of features extracted was evaluated by means of a simple k-nearest neighbors classifier, showing that fractal features provide the best accuracy (97.17%), followed by time-varying & time-frequency (95.28%), and perceptual features (88.7%). However, an accuracy around 94% can be reached just by using the two main features of the fractal family; therefore, considering the difficulties related to the automatic intrabeat segmentation needed for spectral and perceptual features, this scheme becomes an interesting alternative. The conclusion is that fractal type features were the most robust family of parameters (in the sense of accuracy vs. computational load) for the automatic detection of murmurs. This work was carried out using a database that contains 164 phonocardiographic recordings (81 normal and 83 records with murmurs). The database was segmented to extract 360 representative individual beats (180 per class).
92 citations
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TL;DR: A series of carbosilane dendritic compounds Gn-ONNMem, containing one (n = 0), four, eight, eight and sixteen terminal pyridylimine ligands, substituted with m methyl groups (m = 0, 2, 3, 4, 5, 6, 7, 8, 9,
92 citations
Authors
Showing all 10907 results
Name | H-index | Papers | Citations |
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José Luis Zamorano | 105 | 695 | 133396 |
Jesús F. San Miguel | 97 | 527 | 44918 |
Sebastián F. Sánchez | 96 | 629 | 32496 |
Javier P. Gisbert | 95 | 990 | 33726 |
Luis M. Ruilope | 94 | 841 | 97778 |
Luis M. Garcia-Segura | 88 | 484 | 27077 |
Alberto Orfao | 85 | 597 | 37670 |
Amadeo R. Fernández-Alba | 83 | 318 | 21458 |
Rafael Luque | 80 | 693 | 28395 |
Francisco Rodríguez | 79 | 748 | 24992 |
Andrea Negri | 79 | 242 | 35311 |
Rafael Cantón | 78 | 575 | 29702 |
David J. Grignon | 78 | 301 | 23119 |
Christophe Baudouin | 74 | 553 | 22068 |
Josep M. Argilés | 73 | 310 | 19675 |