3,812 research outputs found
Arsenic in rice agrosystems (water, soil and rice plants) in Guayas and Los Rios provinces, Ecuador
Geogenic arsenic (As) can accumulate and reach high concentrations in rice grains, thus representing a potential threat to human health. Ecuador is one of the main consumers of rice in South America. However, there is no information available about the concentrations of As in rice agrosystems, although some water bodies are known to contain high levels of the element. We carried out extensive sampling of water, soil, rice plants and commercial rice (obtained from local markets). Water samples were analysed to determine physico-chemical properties and concentrations of dissolved arsenic. Soil samples were analysed to determine total organic C, texture, total Fe and amorphous Fe oxyhydroxides (Fe-ox), total arsenic (tAs) and the bioavailable fraction (As-Me). The different plant parts were analysed separately to determine total (tAs), inorganic (iAs) and organic arsenic (oAs). Low concentrations of arsenic were found in samples of water (generally 80%) in all parts of the rice plants. (C) 2016 Elsevier B.V. All rights reserved
Distinctive Features of Saccadic Intrusions and Microsaccades in Progressive Supranuclear Palsy
International audience; The eyes do not stay perfectly still during attempted fixation; fixational eye movements and saccadic intrusions (SIs) continuously change the position of gaze. The most common type of SI, square-wave jerks (SWJs), consists of saccade pairs that appear purely horizontal on clinical inspection: the first saccade moves the eye away from the fixation target, and after a short interval, the second saccade brings it back toward the target. SWJs are prevalent in certain neurological disorders, including progressive supranuclear palsy (PSP). Here, we developed an objective method to identify SWJs. We found that SWJs are more frequent, larger, and more markedly horizontal in PSP patients than in healthy human subjects. Furthermore, the loss of a vertical component in fixational saccades and SWJs was the eye movement feature that best distinguished PSP patients from controls. We moreover determined that, in PSP patients and controls, the larger the saccade the more likely it was part of a SWJ. Furthermore, saccades produced by PSP patients had equivalent properties whether they were part of a SWJ or not, suggesting that normal fixational saccades (microsaccades) are rare in PSP. We propose that fixational saccades and SIs are generated by the same neural circuit and that, both in PSP patients and in controls, SWJs result from a coupling mechanism that generates a second corrective saccade shortly after a large fixation saccade. Because of brainstem and/or cerebellum impairment, fixational saccades in PSP are abnormally large and thus more likely to trigger a corrective saccade, giving rise to SWJs
Net sea-air CO2 flux uncertainties in the Bay of Biscay based on the choice of wind speed products and gas transfer parameterizations
25 pĂĄginas, 4 figuras, 1 tablaThe estimation of sea-air CO2 fluxes are largely dependent on wind speed through the gas transfer velocity parameterization. In this paper, we quantify uncertainties in the estimation of the CO2 uptake in the Bay of Biscay resulting from using different sources of wind speed such as three different global reanalysis meteorological models (NCEP/NCAR 1, NCEP/DOE 2 and ERA-Interim), one regional high-resolution forecast model (HIRLAM-AEMet) and QuikSCAT winds, in combination with some of the most widely used gas transfer velocity parameterizations. Results show that net CO2 flux estimations during an entire seasonal cycle may differ up to 240% depending on the wind speed product and the gas exchange parameterization. The comparison of satellite and model derived winds with observations at buoys advises against the systematic overestimation of NCEP-2 and the underestimation of NCEP-1. In this region, QuikSCAT has the best performing, although ERA-Interim becomes the best choice in areas near the coastline or when the time resolution is the constraint.This work was developed and funded by the
ECO project (MCyT REN2002-00503/MAR) and EU FP7 project CARBOCHANGE âChanges
5 in carbon uptake and emissions by oceans in a changing climateâ under agreement no. 264879Peer reviewe
Paleotsunami evidence in the BahĂa Inglesa coast (Atacama, Chile) based on a multi-approach analysis
The Atacama coast is located in an area with a current high risk of tsunami, and the sedimentary deposits found in the BahĂa Inglesa area, in the Morro sector, clearly indicate that this was also the case in the past. This investigation analyzes a paleotsunami sedimentary deposit consisting of a block field associated with three sand lobes oriented towards land on top of a marine terrace at an altitude of 70â75 m, which originated from a tsunamigenic event occurred between interglacial periods MIS 7 (ca. 210 ± 10 ky) and MIS5e (ca. 125 ± 5 ky). The deposits have been studied using a multiple approach combining geomorphological, sedimentological, biological, and geochemical criteria. The first type of criteria clearly indicate that the energy required to move the blocks and form the sand lobes could only have been generated by a tsunami. Sedimentological criteria constitute direct evidences of a marine origin due to the presence of siliceous remains from diatom species and spicules from strictly marine sponges, while geochemical criteria, such as the stable isotope signature and chemical composition, constitute evidence of a marine intrusion. © 2022, The Author(s)
An ant colony-based semi-supervised approach for learning classification rules
Semi-supervised learning methods create models from a few labeled instances and a great number of unlabeled instances. They appear as a good option in scenarios where there is a lot of unlabeled data and the process of labeling instances is expensive, such as those where most Web applications stand. This paper proposes a semi-supervised self-training algorithm called Ant-Labeler. Self-training algorithms take advantage of supervised learning algorithms to iteratively learn a model from the labeled instances and then use this model to classify unlabeled instances. The instances that receive labels with high confidence are moved from the unlabeled to the labeled set, and this process is repeated until a stopping criteria is met, such as labeling all unlabeled instances. Ant-Labeler uses an ACO algorithm as the supervised learning method in the self-training procedure to generate interpretable rule-based modelsâused as an ensemble to ensure accurate predictions. The pheromone matrix is reused across different executions of the ACO algorithm to avoid rebuilding the models from scratch every time the labeled set is updated. Results showed that the proposed algorithm obtains better predictive accuracy than three state-of-the-art algorithms in roughly half of the datasets on which it was tested, and the smaller the number of labeled instances, the better the Ant-Labeler performance
SOFIAS â Herramienta para el anĂĄlisis de ciclo de vida y la calificaciĂłn ambiental de edificios
This paper describes the development process of a new software tool, called SOFIAS (Software for a Sustainable Architecture), funded by the Spanish Ministry of Economy and Competitivenes. Following CEN/TC 350 standard on environmental assessment of buildings, the tool aims at assisting building professionals on reducing the life-cycle environmental impact through the design of new buildings and the refurbishment of existing ones. In addition, SOFIAS provides a rating system based on the Life Cycle Assessment (LCA) methodology. This paper explains the innovative aspects of this software, the working methodology and the different type of results that can be obtained using SOFIAS.SOFIAS (Ref. number IPT-2011-0948-380000) project co financed by the Spanish Ministry of Economy and Competitiveness
Cloreto de cobre (CuCl2) como extrator de Al associado à matéria orgùnica em Espodossolos do litoral do Estado de São Paulo.
O estudo objetivou avaliar a capacidade extratora do CuCl2 como reagente seletivo de alumĂnio associado Ă matĂ©ria orgĂąnica em solos representativos sob vegetação de restinga do Estado de SĂŁo Paulo. Os resultados foram comparados ao pirofosfato de sĂłdio e a outros reagentes seletivos, seguindo-se as interpretaçÔes comumente observadas na literatura quanto Ă capacidade extratora e seletividade dos reagentes utilizados.bitstream/item/32367/1/Bol-PD-158.pd
MicroRNA expression profiling in Imatinib-resistant Chronic Myeloid Leukemia patients without clinically significant ABL1-mutations
The development of Imatinib Mesylate (IM), the first specific inhibitor of BCR-ABL1, has had a major impact in patients with Chronic Myeloid Leukemia (CML), establishing IM as the standard therapy for CML. Despite the clinical success obtained with the use of IM, primary resistance to IM and molecular evidence of persistent disease has been observed in 20-25% of IM treated patients. The existence of second generation TK inhibitors, which are effective in patients with IM resistance, makes identification of predictors of resistance to IM an important goal in CML. In this study, we have identified a group of 19 miRNAs that may predict clinical resistance to IM in patients with newly diagnosed CML
Triggers for displaced decays of long-lived neutral particles in the ATLAS detector
A set of three dedicated triggers designed to detect long-lived neutral particles decaying throughout the ATLAS detector to a pair of hadronic jets is described. The efficiencies of the triggers for selecting displaced decays as a function of the decay position are presented for simulated events. The effect of pile-up interactions on the trigger efficiencies and the dependence of the trigger rate on instantaneous luminosity during the 2012 data-taking period at the LHC are discussedFil: Aad, G.. Albert Ludwigs UniversitĂ€t; AlemaniaFil: Abajyan, T.. Universitaet Bonn; AlemaniaFil: Abbott, B.. University of Oklahoma; Estados UnidosFil: Abdallah, J.. Universitat AutĂČnoma de Barcelona; EspañaFil: Abdel Khalek, S.. Universite Paris Sud; FranciaFil: Alconada Verzini, MarĂa Josefina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - La Plata. Instituto de FĂsica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂsica La Plata; ArgentinaFil: Alonso, Francisco. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - La Plata. Instituto de FĂsica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂsica La Plata; ArgentinaFil: Anduaga, Xabier Sebastian. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - La Plata. Instituto de FĂsica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂsica La Plata; ArgentinaFil: Dova, Maria Teresa. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - La Plata. Instituto de FĂsica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂsica La Plata; ArgentinaFil: GonzĂĄlez Silva, MarĂa Laura. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de FĂsica; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Monticelli, Fernando Gabriel. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - La Plata. Instituto de FĂsica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂsica La Plata; ArgentinaFil: Otero y Garzon, Gustavo Javier. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de FĂsica; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Piegaia, Ricardo Nestor. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de FĂsica; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Romeo, Gaston Leonardo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de FĂsica; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Tripiana, Martin Fernando. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - La Plata. Instituto de FĂsica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂsica La Plata; ArgentinaFil: Zhuang, X.. Ludwig Maximilians Universitat; AlemaniaFil: Zhuravlov, V.. Max-Planck Institut fĂŒr Physik; AlemaniaFil: Zieminska, D.. Indiana University; Estados UnidosFil: Zimin, N. I.. Joint Institute for Nuclear Research; RusiaFil: Zimmermann, R.. Universitaet Bonn; AlemaniaFil: Zimmermann, S.. Universitaet Bonn; AlemaniaFil: Zimmermann, S.. Albert Ludwigs UniversitĂ€t; AlemaniaFil: Ziolkowski, M.. UniversitĂ€t Siegen; AlemaniaFil: Zitoun, R.. UniversitĂ© de Savoie; FranciaFil: ĆœivkoviÄ, L.. Columbia University; Estados UnidosFil: Zmouchko, V. V.. State Research Center Institute for High Energy Physics; RusiaFil: Zobernig, G.. University of Wisconsin; Estados UnidosFil: Zoccoli, A.. UniversitĂ di Bologna; ItaliaFil: zur Nedden, M.. Humboldt University; AlemaniaFil: Zutshi, V.. Northern Illinois University; Estados Unido
Medoid-based clustering using ant colony optimization
The application of ACO-based algorithms in data mining has been growing over the last few years, and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works about unsupervised learning have focused on clustering, showing the potential of ACO-based techniques. However, there are still clustering areas that are almost unexplored using these techniques, such as medoid-based clustering. Medoid-based clustering methods are helpfulâcompared to classical centroid-based techniquesâwhen centroids cannot be easily defined. This paper proposes two medoid-based ACO clustering algorithms, where the only information needed is the distance between data: one algorithm that uses an ACO procedure to determine an optimal medoid set (METACOC algorithm) and another algorithm that uses an automatic selection of the number of clusters (METACOC-K algorithm). The proposed algorithms are compared against classical clustering approaches using synthetic and real-world datasets
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