fNIRS complexity analysis for the assessment of motor imagery and mental arithmetic tasks

Conventional methods for analyzing functional near-infrared spectroscopy (fNIRS) signals primarily focus on characterizing linear dynamics of the underlying metabolic processes. Nevertheless, linear analysis may underrepresent the true physiological processes that fully characterizes the complex and nonlinear metabolic activity sustaining brain function. Although there have been recent attempts to characterize nonlinearities in fNIRS signals in various experimental protocols, to our knowledge there has yet to be a study that evaluates the utility of complex characterizations of fNIRS in comparison to standard methods, such as the mean value of hemoglobin. Thus, the aim of this study was to investigate the entropy of hemoglobin concentration time series obtained from fNIRS signals and perform a comparitive analysis with standard mean hemoglobin analysis of functional activation. Publicly available data from 29 subjects performing motor imagery and mental arithmetics tasks were exploited for the purpose of this study. The experimental results show that entropy analysis on fNIRS signals may potentially uncover meaningful activation areas that enrich and complement the set identified through a traditional linear analysis

Complexity Analysis on Functional-Near Infrared Spectroscopy Time Series: A Preliminary Study on Mental Arithmetic

It is well known that physiological systems show complex and nonlinear behaviours. In spite of that, functional near-infrared spectroscopy (fNIRS) is usually analyzed in the time and frequency domains with the assumption that metabolic activity is generated from a linear system. To leverage the full information provided by fNIRS signals, in this study we investigate topological entropy in fNIRS series collected from 10 healthy subjects during mental mental arithmetic task. While sample entropy and fuzzy entropy were used to estimate time series irregularity, distribution entropy was used to estimate time series complexity. Our findings show that entropy estimates may provide complementary characterization of fNIRS dynamics with respect to reference time domain measurements. This finding paves the way to further investigate functional activation in fNIRS in different case studies using nonlinear and complexity system theory

The tropospheric processing of acidic gases and hydrogen sulphide in volcanic gas plumes as inferred from field and model investigations

Improving the constraints on the atmospheric fate and depletion rates of acidic compounds persistently emitted by non-erupting (quiescent) volcanoes is important for quantitatively predicting the environmental impact of volcanic gas plumes. Here, we present new experimental data coupled with modelling studies to investigate the chemical processing of acidic volcanogenic species during tropospheric dispersion. Diffusive tube samplers were deployed at Mount Etna, a very active open-conduit basaltic volcano in eastern Sicily, and Vulcano Island, a closed-conduit quiescent volcano in the Aeolian Islands (northern Sicily). Sulphur dioxide (SO₂), hydrogen sulphide (H₂S), hydrogen chloride (HCl) and hydrogen fluoride (HF) concentrations in the volcanic plumes (typically several minutes to a few hours old) were repeatedly determined at distances from the summit vents ranging from 0.1 to ~10 km, and under different environmental conditions. At both volcanoes, acidic gas concentrations were found to decrease exponentially with distance from the summit vents (e.g., SO₂ decreases from ~10 000 μg/m³at 0.1 km from Etna's vents down to ~7 μg/m³ at ~10 km distance), reflecting the atmospheric dilution of the plume within the acid gas-free background troposphere. Conversely, SO₂/HCl, SO₂/HF, and SO₂/H₂S ratios in the plume showed no systematic changes with plume aging, and fit source compositions within analytical error. Assuming that SO₂ losses by reaction are small during short-range atmospheric transport within quiescent (ash-free) volcanic plumes, our observations suggest that, for these short transport distances, atmospheric reactions for H₂S and halogens are also negligible. The one-dimensional model MISTRA was used to simulate quantitatively the evolution of halogen and sulphur compounds in the plume of Mt. Etna. Model predictions support the hypothesis of minor HCl chemical processing during plume transport, at least in cloud-free conditions. Larger variations in the modelled SO₂/HCl ratios were predicted under cloudy conditions, due to heterogeneous chlorine cycling in the aerosol phase. The modelled evolution of the SO₂/H₂S ratios is found to be substantially dependent on whether or not the interactions of H₂S with halogens are included in the model. In the former case, H₂S is assumed to be oxidized in the atmosphere mainly by OH, which results in minor chemical loss for H₂S during plume aging and produces a fair match between modelled and measured SO₂/H₂S ratios. In the latter case, fast oxidation of H₂S by Cl leads to H₂S chemical lifetimes in the early plume of a few seconds, and thus SO₂ to H₂S ratios that increase sharply during plume transport. This disagreement between modelled and observed plume compositions suggests that more in-detail kinetic investigations are required for a proper evaluation of H₂S chemical processing in volcanic plumes

Inhomogeneous point-process entropy: an instantaneous measure of complexity in discrete systems

Measures of entropy have been widely used to characterize complexity, particularly in physiological dynamical systems modeled in discrete time. Current approaches associate these measures to finite single values within an observation window, thus not being able to characterize the system evolution at each moment in time. Here, we propose a new definition of approximate and sample entropy based on the inhomogeneous point-process theory. The discrete time series is modeled through probability density functions, which characterize and predict the time until the next event occurs as a function of the past history. Laguerre expansions of the Wiener-Volterra autoregressive terms account for the long-term nonlinear information. As the proposed measures of entropy are instantaneously defined through probability functions, the novel indices are able to provide instantaneous tracking of the system complexity. The new measures are tested on synthetic data, as well as on real data gathered from heartbeat dynamics of healthy subjects and patients with cardiac heart failure and gait recordings from short walks of young and elderly subjects. Results show that instantaneous complexity is able to effectively track the system dynamics and is not affected by statistical noise properties

Ab initio simulations of the Ag(111)/Al2O3 interface at intermediate oxygen partial pressures

The relative stability of different realizations of the Ag(111)/Alumina interfaces with varying oxygen partial pressures is investigated by means of ab initio density functional theory (DFT) simulations. Previous theoretical studies of similar systems always involve oversimplified geometries like stoichiometric Al-terminated, Al-rich, or O-terminated alumina interfaces. Such framework cannot explain the experimental behavior observed at intermediate oxygen partial pressure. Our approach, instead, suggests that the oxygen at the interface can play an important role at intermediate concentrations, leading to a more realistic interpretation of the experimental dat

Prestress and experimental tests on fractional viscoelastic materials

Creep and/or Relaxation tests on viscoelastic materials show a power-law trend. Based upon Boltzmann superposition principle the constitutive law with a power-law kernel is ruled by the Caputo's fractional derivative. Fractional constitutive law posses a long memory and then the parameters obtained by best fitting procedures on experimental data are strongly influenced by the prestress on the specimen. As in fact during the relaxation test the imposed history of deformation is not instantaneously applied, since a unit step function may not be realized by the test machine. Aim of this paper, it is shown that, the experimental procedure, and in particular the initial ramp to reach the constant stress (or strain) strongly influences the best fitting procedure and the coefficients of the power-law

Dynamic effective mass of granular media

We develop the concept of frequency dependent effective mass, M(omega), of jammed granular materials which occupy a rigid cavity to a filling fraction of 48%, the remaining volume being air of normal room condition or controlled humidity. The dominant features of M(omega) provide signatures of the dissipation of acoustic modes, elasticity and aging effects in the granular medium. We perform humidity controlled experiments and interpret the data in terms of a continuum model and a "trap" model of thermally activated capillary bridges at the contact points. The results suggest that attenuation in the granular materials is influenced significantly by the kinetics of capillary condensation between the asperities at the contacts.Comment: 4 pages, 3 figure

Recognizing motor imagery tasks from EEG oscillations through a novel ensemble-based neural network architecture

Brain-Computer Interfaces (BCI) provide effective tools aimed at recognizing different brain activities, translate them into actions, and enable humans to directly communicate through them. In this context, the need for strong recognition performances results in increasingly sophisticated machine learning (ML) techniques, which may result in poor performance in a real application (e.g., limiting a real-time implementation). Here, we propose an ensemble approach to effectively balance between ML performance and computational costs in a BCI framework. The proposed model builds a classifier by combining different ML models (base-models) that are specialized to different classification sub-problems. More specifically, we employ this strategy with an ensemble-based architecture consisting of multi-layer perceptrons, and test its performance on a publicly available electroencephalography-based BCI dataset with four-class motor imagery tasks. Compared to previously proposed models tested on the same dataset, the proposed approach provides greater average classification performances and lower inter-subject variability

Effects of anodizing surface treatment on the mechanical strength of aluminum alloy 5083 to fibre reinforced composites adhesive joints

In this study, the anodizing process based on the use of tartaric sulfuric acid solution (TSA) was carried out on metal substrate to evaluate for the first time its effect on the adhesion strength and corrosion resistance of aluminium alloy (i.e., AA5083) to fibre (i.e., basalt or glass) reinforced composite adhesive joints for nautical applications. Furthermore, some TSA anodized samples were soaked in a NaOH solution to investigate the influence of this post-immersion step on the joint performances. With the aim to improve the fibre-matrix adhesion in the composite substrate thus further increasing the overall mechanical response of the joint, glass and basalt fibres were treated with a silane coupling agent solution. The corrosion behaviour of the aluminium alloy was studied by electrochemical techniques. Samples morphology was analysed by scanning electron microscopy, while the interaction between aluminium alloy substrate and epoxy resin was studied through contact angle analysis and resin uptake tests. The effectiveness of the silane treatment was examined by means of Fourier transform infrared spectroscopy and quasi-static tensile tests carried out on dry glass and basalt fabrics. The mechanical response of the resulting joints was evaluated by means of quasi-static tensile tests in accordance to ASTM D3528 standard