scispace - formally typeset
Search or ask a question
Institution

University of Alcalá

EducationAlcalá 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 & Context (language use). 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.


Papers
More filters
Journal ArticleDOI
TL;DR: The rational choice of immobilisation, transduction and biorecognition chemistries is demonstrated in this work to yield improved catalytic and affinity electrochemical biosensors for environmental applications.

98 citations

Journal ArticleDOI
TL;DR: This paper explores the joint use of GSA, Geographical Information Systems (GIS) and Multi‐Criteria Evaluation in a preliminary case study to find the best place to locate a hazardous waste landfill.
Abstract: A novel application of Sensitivity Analysis is presented. Useful applications of Global SA (GSA) already exist in the field of numerical modelling. In this paper, we explore the joint use of GSA, Geographical Information Systems (GIS) and Multi‐Criteria Evaluation. In this preliminary case study, 11 factors have been used to find the best place to locate a hazardous waste landfill. Two variance‐based methods (Sobol' and E‐FAST) are used to compute sensitivity indices in order to identify the factors that determine the variance of the model output. The results show that only three factors jointly account for 97% of the output variance. This information is employed to make a simplification of the original model, retaining only these three influential factors. In addition, if the SA is carried out in a pilot area where the spatial properties are similar to those of the whole region, we can infer the results to the whole area. This procedure achieves the goal of the study with an optimized allocation of resou...

98 citations

Journal ArticleDOI
15 Dec 2017-Spine
TL;DR: The Minimal Clinically Important Difference (MCID) for the physical (PCS) and mental (MCS) component summaries of Short Form SF-12, in patients with low back pain (LBP), is estimated and is smaller in patientsWith longer pain duration and better baseline quality of life.
Abstract: Study design Multicenter, prospective, cohort study. Objective To estimate the Minimal Clinically Important Difference (MCID) for the physical (PCS) and mental (MCS) component summaries of Short Form SF-12 (SF-12), in patients with low back pain (LBP). Summary of background data Quality of life is one of the core domains recommended to be assessed in patients with LBP. SF-12 is the most widely used instrument for this purpose, but its MCID was unknown. Methods A total of 458 patients with subacute and chronic LBP were consecutively recruited across 21 practices. LBP, referred pain, disability, PCS, and MCS were assessed upon recruitment and 12 months later. Self-reported health status change between baseline and 12 month-assessment, was used as the external criterion. The MCID for SF-12 was estimated following four anchor-based methods; minimal detectable change (MDC); average change (AC); change difference (CD); and receiver operating characteristic curve (ROC), for which the area under the curve (AUC) was calculated. The effect on MCID values of pain duration and baseline scores was assessed. Results Values for PCS were: MDC: 0.56, AC: 2.71, CD: 3.29, and ROC: 1.14. Values for MCS were: MDC: 3.77, AC: 3.54, CD: 1.13, and ROC: 4.23. AUC values were Conclusion Different methods for MCID calculation lead to different results. In patients with subacute and chronic LBP, improvements >3.77 in MCS and >3.29 in PCS, can be considered clinically relevant. MCID is smaller in patients with longer pain duration and better baseline quality of life. Level of evidence 2.

98 citations

Journal ArticleDOI
TL;DR: In this paper, the carbon fraction in the biomass, mean (±standard deviation), for the different pools varied between 38.5 and 49.7% (±3 and 3.8).
Abstract: Generic or default values to account for biomass and carbon accumulation in tropical forest ecosystems are generally recognized as a major source of errors, making site and species specific data the best way to achieve precise and reliable estimates. The objective of our study was to determine carbon in various components (leaves, branches, stems, structural roots and soil) of single-species plantations of Vochysia guatemalensis and Hieronyma alchorneoides from 0 to 16 years of age. Carbon fraction in the biomass, mean (±standard deviation), for the different pools varied between 38.5 and 49.7% (±3 and 3.8). Accumulated carbon in the biomass increased with the plantation age, with mean annual increments of 7.1 and 5.3 Mg ha -1 year -1 for forest plantations of V. guatemal- ensis and H. alchorneoides, respectively. At all ages, 66.3% (±10.6) of total biomass was found within the aboveground tree components, while 18.6% (±20.9) was found in structural roots. The soil (0-30 cm) contained 62.2 (±13) and 71.5% (±17.1) of the total carbon (biomass plus soil) under V. guatemalensis and H. alchorneoides, respectively. Mean annual increment for carbon in the soil was 1.7 and 1.3 Mg ha -1 year -1 in V. guatemalensis and H. alchorneoides. Allometric equations were constructed to estimate total biomass and carbon in the biomass which had an R 2 aj (adjusted R square) greater than 94.5%. Finally, we compare our results to those that could have resulted from the use of default values, showing how site and species specific data contribute to the overall goal of improving carbon estimates and providing a more reliable account of the mitigation potential of forestry activities on climate change.

98 citations

Proceedings ArticleDOI
03 Jun 2012
TL;DR: This paper presents a non-intrusive approach for drowsiness detection, based on computer vision, installed in a car, which works in a robust and automatic way, without prior calibration.
Abstract: This paper presents a non-intrusive approach for drowsiness detection, based on computer vision. It is installed in a car and it is able to work under real operation conditions. An IR camera is placed in front of the driver, in the dashboard, in order to detect his face and obtain drowsiness clues from their eyes closure. It works in a robust and automatic way, without prior calibration. The presented system is composed of 3 stages. The first one is preprocessing, which includes face and eye detection and normalization. The second stage performs pupil position detection and characterization, combining it with an adaptive lighting filtering to make the system capable of dealing with outdoor illumination conditions. The final stage computes PERCLOS from eyes closure information. In order to evaluate this system, an outdoor database was generated, consisting of several experiments carried out during more than 25 driving hours. A study about the performance of this proposal, showing results from this testbench, is presented.

98 citations


Authors

Showing all 10907 results

NameH-indexPapersCitations
José Luis Zamorano105695133396
Jesús F. San Miguel9752744918
Sebastián F. Sánchez9662932496
Javier P. Gisbert9599033726
Luis M. Ruilope9484197778
Luis M. Garcia-Segura8848427077
Alberto Orfao8559737670
Amadeo R. Fernández-Alba8331821458
Rafael Luque8069328395
Francisco Rodríguez7974824992
Andrea Negri7924235311
Rafael Cantón7857529702
David J. Grignon7830123119
Christophe Baudouin7455322068
Josep M. Argilés7331019675
Network Information
Related Institutions (5)
Complutense University of Madrid
90.2K papers, 2.1M citations

95% related

University of Valencia
65.6K papers, 1.7M citations

94% related

Autonomous University of Barcelona
80.5K papers, 2.3M citations

94% related

University of Barcelona
108.5K papers, 3.7M citations

93% related

University of Florence
79.5K papers, 2.3M citations

90% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20251
20243
202375
2022166
20211,660
20201,532