298 research outputs found
Description of the idealized bed roughness effects on tracer transport in water flumes by applying the strange attractor multifractal analysis
River hydrodynamicsTurbulent open channel flow and transport phenomen
Efecto de la frecuencia del ritmo sinusal en la generación de reentradas en un modelo 3D de aurícula humana remodelada
Las arritmias auriculares son las taquiarritmias más comunes en humanos. Recientemente, se ha demostrado que una actividad ectópica alrededor de las venas pulmonares puede generar mecanismos reentrantes en presencia de un sustrato vulnerable. En este estudio, examinamos el efecto de la frecuencia del ritmo sinusal para contribuir en la generación de mecanismos reentrantes iniciados por actividad ectópica. Los efectos del remodelado en las corrientes iónicas se incorporaron en un modelo 3D de aurícula humana, altamente realista. Sólo a altas frecuencias del ritmo sinusal (longitud del ciclo base ≤ 300 ms), la actividad ectópica provocó la generación de reentradas en figura de ocho en la aurícula derecha. Nuestro estudio sugiere que la interacción de actividad ectópica con un ritmo sinusal a alta frecuencia facilita la generación de mecanismos reentrantes en aurícula humana remodelada
EEG characterization of the Alzheimer's disease continuum by means of multiscale entropies
Alzheimer's disease (AD) is a neurodegenerative disorder with high prevalence, known for its highly disabling symptoms. The aim of this study was to characterize the alterations in the irregularity and the complexity of the brain activity along the AD continuum. Both irregularity and complexity can be studied applying entropy-based measures throughout multiple temporal scales. In this regard, multiscale sample entropy (MSE) and refined multiscale spectral entropy (rMSSE) were calculated from electroencephalographic (EEG) data. Five minutes of resting-state EEG activity were recorded from 51 healthy controls, 51 mild cognitive impaired (MCI) subjects, 51 mild AD patients (ADMIL), 50 moderate AD patients (ADMOD), and 50 severe AD patients (ADSEV). Our results show statistically significant differences (p-values < 0.05, FDR-corrected Kruskal-Wallis test) between the five groups at each temporal scale. Additionally, average slope values and areas under MSE and rMSSE curves revealed significant changes in complexity mainly for controls vs. MCI, MCI vs. ADMIL and ADMOD vs. ADSEV comparisons (p-values < 0.05, FDR-corrected Mann-Whitney U-test). These findings indicate that MSE and rMSSE reflect the neuronal disturbances associated with the development of dementia, and may contribute to the development of new tools to track the AD progression.This research was supported by European Commission and European Regional Development Fund (FEDER) under project “Análisis y correlación entre el genoma completo y la actividad cerebral para la ayuda en el diagnóstico de la enfermedad de Alzheimer” (Cooperation Programme Interreg V-A Spain-Portugal, POCTEP 2014-2020); by “Ministerio de Ciencia, Innovación y Universidades” and FEDER under projects PGC2018-098214-A-I00 and DPI2017-84280-R; and by “Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Inovação” and FEDER under projects POCI-01-0145-FEDER-007274 and UID/MAT/00144/2013
The test of Random Rhythm Generation and neuropsychological performance in schizophrenic patients
Producción CientíficaThe objective of this study was the assessment of neuropsychological performance in a sample of schizophrenic patients using a new computer-administered instrument, the Test of Random Rhythm Generation (ARG). The test was applied to a group of 20 DSM-IV schizophrenic patients (SG) and 20 sex- and age-matched controls (CG). The Positive and Negative Syndrome Scale (PANSS) and Frankfurt Complaint Questionnaire (Frankfurter Beschwerdefragebogen, FBF) were used to study patients' psychopathology. The neuroleptic treatment received by each patient during the last month was converted into daily equivalents of chlorpromazine. In the ARG, the subject is asked to press the space key of the computer at a rhythm as irregular as possible. The test aims at assessing the individual's ability to create random rhythms by means of sequences of blows, which is hypothetically associated with a high neuropsychological performance. The data were analyzed by means of three different mathematical techniques. Results showed that schizophrenic patients generated more regular and rhythmic sequences than controls (correlation dimension in SG = 2.78 +/- 0.81, in CG = 3.69 +/- 0.64, p < 0.01). This suggests that neuropsychological performance measured by the ARG was worse in patients compared to controls. ARG is proposed as a new technique to evaluate neuropsychological performance with the following advantages: (1) its short-time application tit usually takes no more than 10 minutes), (2) personnel only require a short training to learn how to apply it, and (3) different analyses of the data are quickly carried out by the computer program
Regional coherence evaluation in mild cognitive impairment and Alzheimer's disease based on adaptively extracted magnetoencephalogram rhythms
This study assesses the connectivity alterations caused by Alzheimer's disease (AD) and mild cognitive impairment (MCI) in magnetoencephalogram (MEG) background activity. Moreover, a novel methodology to adaptively extract brain rhythms from the MEG is introduced. This methodology relies on the ability of empirical mode decomposition to isolate local signal oscillations and constrained blind source separation to extract the activity that jointly represents a subset of channels. Inter-regional MEG connectivity was analysed for 36 AD, 18 MCI and 26 control subjects in δ, θ, α and β bands over left and right central, anterior, lateral and posterior regions with magnitude squared coherence—c(f). For the sake of comparison, c(f) was calculated from the original MEG channels and from the adaptively extracted rhythms. The results indicated that AD and MCI cause slight alterations in the MEG connectivity. Computed from the extracted rhythms, c(f) distinguished AD and MCI subjects from controls with 69.4% and 77.3% accuracies, respectively, in a full leave-one-out cross-validation evaluation. These values were higher than those obtained without the proposed extraction methodology
Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures
Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz–Mancini–Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI
Visibility graphs of ground-level ozone time series: A multifractal analysis
A recent method based on the concurrence of complex networks and multifractal
analyses is applied for the first time to explore ground-level ozone behavior.
Ozone time series are converted into complex networks for their posterior
analysis. The searched purpose is to check the suitability of this
transformation and to see whether some features of these complex networks could
constitute a preliminary analysis before the more thorough multifractal
formalism. Results show effectively that the exposed transformation stores the
original information about the ozone dynamics and gives meaningful knowledge
about the time series. Based on these results, the multifractal analysis of the
complex networks is performed. Looking at the physical meaning of the
multifractal properties (such as fractal dimensions and singularity spectrum),
a relationship between those and the degree distribution of the complex
networks is found. In addition to all the promising results, this novel
connection between time series and complex networks can deal with both
stationary and non-stationary time series, overcoming one of the main
limitations of multifractal analysis. Therefore, this technique can be regarded
as an alternative to give supplementary information within the study of complex
signals.Comment: 34 pages, 8 figures, 1 graphical abstrac
Analysis of electroencephalograms in Alzheimer's disease patients with multiscale entropy
The aim of this study was to analyse the electroencephalogram (EEG) background activity of Alzheimer’s disease (AD) patients using the Multiscale Entropy (MSE). The MSE is a recently developed method that quantifies the regularity of a signal on different time scales. These time scales are inspected by means of several coarse-grained sequences formed from the analysed signals. We recorded the EEGs from 19 scalp electrodes in 11 AD patients and 11 age-matched controls and estimated the MSE profile for each epoch of the EEG recordings. The shape of the MSE profiles reveals the EEG complexity, and it suggests that the EEG contains information in deeper scales than the smallest one. Moreover, the results showed that the EEG background activity is less complex in AD patients than control subjects. We found significant difference
Assessing the contribution of understory sun-induced chlorophyll fluorescence through 3-D radiative transfer modelling and field data
A major international effort has been made to monitor sun-induced chlorophyll fluorescence (SIF) from space as a proxy for the photosynthetic activity of terrestrial vegetation. However, the effect of spatial heterogeneity on the SIF retrievals from canopy radiance derived from images with medium and low spatial resolution remains uncharacterised. In images from forest and agricultural landscapes, the background comprises a mixture of soil and understory and can generate confounding effects that limit the interpretation of the SIF at the canopy level. This paper aims to improve the understanding of SIF from coarse spatial resolutions in heterogeneous canopies by considering the separated contribution of tree crowns, understory and background components, using a modified version of the FluorFLIGHT radiative transfer model (RTM). The new model is compared with others through the RAMI model intercomparison framework and is validated with airborne data. The airborne campaign includes high-resolution data collected over a tree-grass ecosystem with the HyPlant imaging spectrometer within the FLuorescence EXplorer (FLEX) preparatory missions. Field data measurements were collected from plots with a varying fraction of tree and understory vegetation cover. The relationship between airborne SIF calculated from pure tree crowns and aggregated pixels shows the effect of the understory at different resolutions. For a pixel size smaller than the mean crown size, the impact of the background was low (R2 > 0.99; NRMSE 0.2). This study demonstrates that using a 3D RTM model improves the calculation of SIF significantly (R2 = 0.83, RMSE = 0.03 mW m−2 sr−1 nm−1) when the specific contribution of the soil and understory layers are accounted for, in comparison with the SIF calculated from mixed pixels that considers only one layer as background (R2 = 0.4, RMSE = 0.28 mW m−2 sr−1 nm−1). These results demonstrate the need to account for the contribution of SIF emitted by the understory in the quantification of SIF within tree crowns and within the canopy from aggregated pixels in heterogeneous forest canopies
P15 60. Accidente cerebrovascular tras cirugía coronaria aislada: capacidad predictiva de las escalas de riesgo chads2 y cha2ds2vasc
ObjetivosValidar las escalas de riesgo CHADS2 y CHA2DS2VASC como modelos predictivos de desarrollo de accidente cerebrovascular (ACV) en cirugía coronaria aislada (CCA).MétodosPacientes consecutivos con CCA entre enero de 2003 – octubre de 2011. Puntuaciones CHADS2 y CHA2DS2VASC computadas para todos los pacientes, considerándose variable de resultado la aparición de ACV perioperatorio precoz (primer mes postoperatorio y/o alta hospitalaria). Considerado ACV el evento neurológico con focalidad clínica (ictus/ataque isquémico transitorio [AIT]). Dos modelos específicos ya validados para la predicción de ACV tras CPC, Northern New England Cardiovascular Disease Study Group (NNECDSG) y Multicenter Study of Perioperative Ischemia (McSPI) Research Group, fueron asimismo computados para todos los pacientes y comparados con los previos. La capacidad discriminativa fue cuantificada por el cálculo del área bajo la curva ROC (AUC). Además, dicha capacidad predictiva de los esquemas fue estudiada por distribución de sus puntuaciones en tres estratos atendiendo a la incidencia de ACV postoperatorio: baja (<1%), intermedia (1–3%) y alta (≥ 3%).ResultadosDos mil novecientos diez pacientes, 62 desarrollaron ACV postoperatorio (2,1%). La incidencia de ACV en pacientes igual o mayores de 75 años fue superior (3,9%) que la comparada con los menores de 75 años (1,7%) (odds ratio [OR]: 2,2; p=0,01). La AUC para CHADS2 fue 0,71, CHA2DS2VASC 0,72, NNECDSG 0,69 y McSPI 0,73. NNECDSG y CHA2DS2VASC demostraron mejor asignación de los pacientes a los estratos de bajo y alto riesgo.ConclusionesAmbos sistemas de puntuación CHADS2 y CHA2DS2VASC son modelos utilizados en la práctica clínica cotidiana con capacidad de predicción del desarrollo de ACV postoperatorio tras CCA similar a modelos específicamente preestablecidos
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