Dispersion entropy (DispEn) is a recently introduced entropy metric to quantify the uncertainty of time series. It is fast and, so far, it has demonstrated very good performance in the ...characterisation of time series. It includes a mapping step, but the effect of different mappings has not been studied yet. Here, we investigate the effect of linear and nonlinear mapping approaches in DispEn. We also inspect the sensitivity of different parameters of DispEn to noise. Moreover, we develop fluctuation-based DispEn (FDispEn) as a measure to deal with only the fluctuations of time series. Furthermore, the original and fluctuation-based forbidden dispersion patterns are introduced to discriminate deterministic from stochastic time series. Finally, we compare the performance of DispEn, FDispEn, permutation entropy, sample entropy, and Lempel–Ziv complexity on two physiological datasets. The results show that DispEn is the most consistent technique to distinguish various dynamics of the biomedical signals. Due to their advantages over existing entropy methods, DispEn and FDispEn are expected to be broadly used for the characterization of a wide variety of real-world time series. The MATLAB codes used in this paper are freely available at http://dx.doi.org/10.7488/ds/2326.
Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in ...different ways. Building on these trends, we propose the so-called refined composite multivariate multiscale fuzzy entropy (RCmvMFE) whose coarse-graining step uses variance (RCmvMFEσ2) or mean (RCmvMFEμ). We investigate the behavior of these multivariate methods on multichannel white Gaussian and 1/f noise signals, and two publicly available biomedical recordings. Our simulations demonstrate that RCmvMFEσ2 and RCmvMFEμ lead to more stable results and are less sensitive to the signals’ length in comparison with the other existing multivariate multiscale entropy-based methods. The classification results also show that using both the variance and mean in the coarse-graining step offers complexity profiles with complementary information for biomedical signal analysis. We also made freely available all the Matlab codes used in this paper.
•We propose refined composite multivariate multiscale fuzzy entropy (RCmvMFE).•The coarse-graining step of RCmvMFE uses variance (RCmvMFEσ2) or mean (RCmvMFEμ).•The introduced fuzzy membership function significantly decreases the running time.•Our simulations demonstrate that RCmvMFEσ2 and RCmvMFEμ lead to more stable results.•RCmvMFEσ2 and RCmvMFEμ are less sensitive to the length of signals.
Olive (Olea europaea L.) is one of the first domesticated and cultivated tree species and has historical, social and economical relevance. However, its future as a strategic commodity in ...Mediterranean agriculture is threatened by diverse biotic (traditional and new/emerging pests and diseases) and abiotic (erosion, climate change) menaces. These problems could also be of relevance for new geographical areas where olive cultivation is not traditional but is increasingly spreading (i.e., South America, Australia, etc). One of the major constraints for olive cultivation is Verticillium wilt, a vascular disease caused by the soil-borne fungus Verticillium dahliae Kleb. In this review we describe how Verticillium wilt of olive (VWO) has become a major problem for olive cultivation during the last two decades. Similar to other vascular diseases, VWO is difficult to manage and single control measure are mostly ineffective. Therefore, an integrated disease management strategy that fits modern sustainable agriculture criteria must be implemented. Multidisciplinary research efforts and advances to understand this pathosystem and to develop appropriate control measures are summarized. The main conclusion is that a holistic approach is the best strategy to effectively control VWO, integrating biological, chemical, physical, and cultural approaches.
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•Flow information is acquired non-intrusively by a multimodality measurement system.•Flow models are established to accurately calculate phase flow rates.•Phase fractions are measured ...by a conductance sensor and an ultrasonic sensor.•Interfacial velocity and oil velocity are extracted from the Doppler shift signal.•The accuracy of the proposed model is validated through dynamic experiments.
Water-based dispersed wavy flow, whereby the water with dispersed oil droplets moves along the bottom of the pipe and the gas concurrently on the top, is a frequently encountered horizontal oil-gas-water three-phase flow pattern in petroleum production and transportation. Accurate flow metering of each individual phase is significant to academic research and industrial flow assurance. Therefore, we present a combined electrical and ultrasonic sensor to simultaneously and non-intrusively acquire online flowing information. This information includes: the water fraction estimated by the normalized voltage from a conductance sensor, the gas fraction calculated by locating the gas-liquid interface through a pulse-wave ultrasonic sensor consisting of three transducers, and the coupled velocity of oil droplets and gas-liquid interface from Doppler shift signal acquired by a continuous wave ultrasonic Doppler sensor. Based on the limited flowing information obtained by multimodality sensors, a novel theoretical model is established based on the analysis of the momentum balance between different phases to solve phase fractions and phase actual velocities for calculating phase flow rates. To make the model closed and solvable, the interfacial velocity and oil velocity are respectively extracted by decoupling the Doppler shift signal through amplitude-aware permutation entropy and noise assisted multivariate empirical mode decomposition methods. Finally, the phase flow rates are calculated by the solutions of the established model. Dynamic experiments are performed to verify the effectiveness and accuracy of the proposed method and theoretical model. This study could provide a potential solution for non-intrusive phase flow metering of industrial three phase flow.
We investigate the problem of achieving robust control of hand prostheses by the electromyogram (EMG) of transradial amputees in the presence of variable force levels, as these variations can have a ...substantial impact on the robustness of the control of the prostheses. We also propose a novel set of features that aim at reducing the impact of force level variations on the prosthesis controlled by amputees. These features characterize the EMG activity by means of the orientation between a set of spectral moments descriptors extracted from the EMG signal and a nonlinearly mapped version of it. At the same time, our feature extraction method processes the EMG signals directly from the time-domain to reduce computational cost. The performance of the proposed features is tested on EMG data collected from nine transradial amputees performing six classes of movements each with three force levels. Our results indicate that the proposed features can achieve significant reductions in classification error rates in comparison to other well-known feature extraction methods, achieving improvements of ≈ 6% to 8% in the average classification performance across all subjects and force levels, when training with all forces.
Due to the non-linearity of numerous physiological recordings, non-linear analysis of multi-channel signals has been extensively used in biomedical engineering and neuroscience. Multivariate ...multiscale sample entropy (MSE–mvMSE) is a popular non-linear metric to quantify the irregularity of multi-channel time series. However, mvMSE has two main drawbacks: (1) the entropy values obtained by the original algorithm of mvMSE are either undefined or unreliable for short signals (300 sample points); and (2) the computation of mvMSE for signals with a large number of channels requires the storage of a huge number of elements. To deal with these problems and improve the stability of mvMSE, we introduce multivariate multiscale dispersion entropy (MDE–mvMDE), as an extension of our recently developed MDE, to quantify the complexity of multivariate time series. We assess mvMDE, in comparison with the state-of-the-art and most widespread multivariate approaches, namely, mvMSE and multivariate multiscale fuzzy entropy (mvMFE), on multi-channel noise signals, bivariate autoregressive processes, and three biomedical datasets. The results show that mvMDE takes into account dependencies in patterns across both the time and spatial domains. The mvMDE, mvMSE, and mvMFE methods are consistent in that they lead to similar conclusions about the underlying physiological conditions. However, the proposed mvMDE discriminates various physiological states of the biomedical recordings better than mvMSE and mvMFE. In addition, for both the short and long time series, the mvMDE-based results are noticeably more stable than the mvMSE- and mvMFE-based ones. For short multivariate time series, mvMDE, unlike mvMSE, does not result in undefined values. Furthermore, mvMDE is faster than mvMFE and mvMSE and also needs to store a considerably smaller number of elements. Due to its ability to detect different kinds of dynamics of multivariate signals, mvMDE has great potential to analyse various signals.
Research into binary network analysis of brain function faces a methodological challenge in selecting an appropriate threshold to binarise edge weights. For EEG phase-based functional connectivity, ...we test the hypothesis that such binarisation should take into account the complex hierarchical structure found in functional connectivity. We explore the density range suitable for such structure and provide a comparison of state-of-the-art binarisation techniques, the recently proposed Cluster-Span Threshold (CST), minimum spanning trees, efficiency-cost optimisation and union of shortest path graphs, with arbitrary proportional thresholds and weighted networks. We test these techniques on weighted complex hierarchy models by contrasting model realisations with small parametric differences. We also test the robustness of these techniques to random and targeted topological attacks. We find that the CST performs consistenty well in state-of-the-art modelling of EEG network topology, robustness to topological network attacks, and in three real datasets, agreeing with our hypothesis of hierarchical complexity. This provides interesting new evidence into the relevance of considering a large number of edges in EEG functional connectivity research to provide informational density in the topology.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background and aims The olive root endophyte Pseudomonas fluorescens PICF7 is an effective biocontrol agent of Verticillium wilt of olive (VWO). Colonization of olive roots either by strain PICF7 or ...by Verticillium dahliae triggers differential systemic transcriptomic responses, many of them related with defense-related genes. The aims were to develop an olive split-root system for assessing VWO development and biocontrol effectiveness of strain PICF7 in plants with a divided root architecture, and for evaluating systemic defense responses during this tripartite interaction when strain PICF7 and V. dahliae are spatially separated. Methods An olive split-root system was generated and disease development, biocontrol effectiveness and systemic genetic responses in these plants upon strain PICF7 and V. dahliae colonization were compared to those reported and observed in olive plants grown under standard conditions (single pots). Specific defense-related genes, previously identified during PICF7- and/ or V. dahliae-olive root interactions were selected and their expression patterns assessed in above-ground tissues by real-time qPCR analyses. Results Symptoms of VWO developed similarly both in split-root and single-root plants. However, even though PICF7 triggered systemic defense responses in aerial tissues prior to the infection by V. dahliae, effective biocontrol was not observed under these experimental conditions. While most of studied genes showed similar expression patterns along time in both systems (i.e. split root and single pot), some of them (e.g. the caffeoyl-O-methyltransferase coding gene) varied depending on whether strain PICF7 and V. dahliae were spatially separated or shared the same compartment. Conclusions A successful split-root system was generated to investigate genetic events taking place during the tripartite interaction olive-V. dahliae-P. fluorescens PICF7. VWO biocontrol by strain PICF7 must rely on mechanisms other than induction of systemic resistance responses. The expression pattern of specific defense-related olive genes depended on whether or not the biocontrol agent and the pathogen share the same root/soil region.
•No varietal resistance to olive knot within the considered germplasm.•Different disease incidence and severity in different varieties and groves.•Incidence and severity of olive knot were correlated ...with frost damage.•Frost damage was more severe in oldest branches than in young 2-yrs old branches.•Deacclimation by mild winter followed by late frost; likely the cause of frost damage.
Olive knot is among the most relevant diseases affecting olive cultivation. Pseudomonas savastanoi pv. savastanoi (Pss) is recognized as the causative agent of this disease. Its penetration in the plant occurs through wounds in all the aerial plant tissues. Frost, or hailstorm damages to the bark of shoots, branches and trunk might expose plants to higher risks of infection. In the coldest regions where freezing events may occur regularly, an employment of tolerant varieties to cold, or to Pss infection represents a valuable approach for limiting tree damages. However, the relationship between the tolerance to different frost types and the susceptibility to Pss disease in different organs (trunk, branches of different age) might be not univocal and rather change among olive tree varieties. In the Marche region of central Italy, the damages occurring during late winter frosts (end of February) and caused by olive knot disease were investigated. Our work considered 10 locally, nationally and internationally known cultivars that were studied under field conditions in 6 different groves in Marche region. In all the groves, olive knot incidence and severity were positively correlated with frost damaged organs. All the varieties were damaged by the late winter frost and showed olive knot disease symptoms after 6 months. ‘Piantone di Mogliano’, ‘FS-17’ and ‘Frantoio’ were the most affected cultivars. ‘Carboncella’, ‘Maurino’ and ‘Arbequina’ showed an intermediate susceptibility, whereas ‘Ascolana Tenera’ ‘Leccino’, ‘Piantone di Falerone’, ‘Rosciola Colli Esini’ resulted tolerant to this peculiar late frost and olive knot infection. The >3-year-old branches were generally more damaged in comparison to younger branches.
We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during ...a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10-20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1-db20), Symlets (sym1-sym20), and Coiflets (coif1-coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using "sym9" across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.
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