Fe–Mn–Al–C Alloys: a Study of Their Corrosion Behaviour in SO2 Environments

The corrosion reaction of four Fe–Mn–Al alloys exposed to a cycling, dry–humid, SO₂ (0.001% by volume) polluted atmosphere was studied. ICEMS, XPS, AES-SAM and transmission Mössbauer spectroscopy at different temperatures were employed to characterize the corrosion products. The analytical results indicate that (i) ferrihydrite is the main component of the rust; (ii) there is an abundant presence of Mn²⁺ and SO₃ ^2–/SO₄ ^2– on the top of the corrosion layer, the concentration of SO₄ ^2– increasing with the number of cycles; and (iii) the magnetic hyperfine pattern exhibited by the series of low-temperature spectra of the rust is quite different from that observed in the rust formed under similar corrosive environments on iron and weathering steel. This latter finding is correlated with a slow rate of transformation of the Fe³⁺ species formed at the early stages of corrosion into -FeOOH, the usual final product of this type of corrosion processes. The sulphate anions, abundant inside the electrolyte during the wet periods, could be incorporated to the ferrihydrite structure being responsible for the Mössbauer spectral pattern recorded from the corrosion products at low temperatures.     

On the geometry of master-slave synchronization

In 1990, Pecora and Carroll reported the observation that one can synchronize the orbits of two identical dynamical systems, which may be chaotic, by feeding state variables of one of them to the other one with no feedback, a phenomenon often called master-slave synchronization. We report here some results on the theory of master-slave synchronization for maps and flows, which are all inspired by a similar geometric and coordinate independent point of view to the one introduced in master-slave synchronization by Tresser, Worfolk, and Bass. Our results are variations on the theme that projection often can compensate for expansion.(c) 2002 American Institute of Physics.     

Generating Multidirectional Variable Hidden Attractors via Newly Commensurate and Incommensurate Non-Equilibrium Fractional-Order Chaotic Systems

This article investigates a non-equilibrium chaotic system in view of commensurate and incommensurate fractional orders and with only one signum function. By varying some values of the fractional-order derivative together with some parameter values of the proposed system, different dynamical behaviors of the system are explored and discussed via several numerical simulations. This system displays complex hidden dynamics such as inversion property, chaotic bursting oscillation, multistabilty, and coexisting attractors. Besides, by means of adapting certain controlled constants, it is shown that this system possesses a three-variable offset boosting system. In conformity with the performed simulations, it also turns out that the resultant hidden attractors can be distributively ordered in a grid of three dimensions, a lattice of two dimensions, a line of one dimension, and even arbitrariness in the phase space. Through considering the Caputo fractional-order operator in all performed simulations, phase portraits in two- and three-dimensional projections, Lyapunov exponents, and the bifurcation diagrams are numerically reported in this work as beneficial exit results.     

Asymptotic Information-Theoretic Detection of Dynamical Organization in Complex Systems

The identification of emergent structures in complex dynamical systems is a formidable challenge. We propose a computationally efficient methodology to address such a challenge, based on modeling the state of the system as a set of random variables. Specifically, we present a sieving algorithm to navigate the huge space of all subsets of variables and compare them in terms of a simple index that can be computed without resorting to simulations. We obtain such a simple index by studying the asymptotic distribution of an information-theoretic measure of coordination among variables, when there is no coordination at all, which allows us to fairly compare subsets of variables having different cardinalities. We show that increasing the number of observations allows the identification of larger and larger subsets. As an example of relevant application, we make use of a paradigmatic case regarding the identification of groups in autocatalytic sets of reactions, a chemical situation related to the origin of life problem.     

EEG Fractal Analysis Reflects Brain Impairment after Stroke

Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.     

Increased Entropic Brain Dynamics during DeepDream-Induced Altered Perceptual Phenomenology

In recent years, the use of psychedelic drugs to study brain dynamics has flourished due to the unique opportunity they offer to investigate the neural mechanisms of conscious perception. Unfortunately, there are many difficulties to conduct experiments on pharmacologically-induced hallucinations, especially regarding ethical and legal issues. In addition, it is difficult to isolate the neural effects of psychedelic states from other physiological effects elicited by the drug ingestion. Here, we used the DeepDream algorithm to create visual stimuli that mimic the perception of hallucinatory states. Participants were first exposed to a regular video, followed by its modified version, while recording electroencephalography (EEG). Results showed that the frontal region’s activity was characterized by a higher entropy and lower complexity during the modified video, with respect to the regular one, at different time scales. Moreover, we found an increased undirected connectivity and a greater level of entropy in functional connectivity networks elicited by the modified video. These findings suggest that DeepDream and psychedelic drugs induced similar altered brain patterns and demonstrate the potential of adopting this method to study altered perceptual phenomenology in neuroimaging research.     

Remanent quantum correlations in dissipative qubits

Starting from the exact evolution of a Markovian dissipative quantum walk, a non-Markovian decoherence of two qubits interacting with a phonon thermal bath has been investigated analytically using quantum information tools. Concurrence and quantum discord are affected in a complex way, showing that entanglement decreases with dissipation. At the limit where dissipation dominates, quantum correlations survive in time as ∝t^−1/2$\propto t^{-1/2}$. Thus, even under the influence of dissipation, two qubits retain their quantumness for a long time. Quantum correlations could be therefore observed for a long time in related photonic experiments.     

Analytical Study of Raw Materials of Zinc Oxide Used for Enamels on Industrial Ceramics: Quantitative Analysis of Zinc,Lead, and Sulfur in These Samples by X‐ray Fluorescence and Flame Atomic Absorption Spectrometry

An analytical study is carried out to optimize X‐ray fluorescence (XRF) and flame atomic absorption spectrometry (FAAS) quantitative analysis of Zn, Pb, and S in ZnO samples commonly used to obtain industrial ceramic enamels. Pb and S in the raw materials often contaminate ZnO and are very detrimental in industrial applications. Thus, very accurate analytical determination of these elements in ceramic samples is extremely important. First of all, a mineralogical study by X‐ray diffraction (XRD) on the different components in these raw materials and the materials produced during the firing process is performed in order to establish the mineral forms in a reference sample for analysis by XRF spectrometry. The working conditions are optimized for XRF multielemental analysis, using the sample in the form of pellets, due to high loss on ignition (LOI) values. The preparation of suitable standards and working conditions for FAAS analysis have also been optimized. The content of these elements was determined by FAAS for the reference sample and several samples for industrial use, and the results were compared with those obtained by XRF. Comparison of the results obtained from XRF and FAAS analysis of Pb and Zn show more accurate values for FAAS. For ZnO, an accuracy of 0.11% with ±0.1% precision by FAAS and 0.46% accuracy with ±0.2% precision by XRF are found. For PbO, 1.06% accuracy and ±0.06% precision using FAAS and 5.6% accuracy and ±0.35% precision by XRF were found. For SO₃ determined only by XRF, accuracy was 4.76% with ±0.25% precision. These values are highly satisfactory given that these two elements are only found in small proportions.