"In-vitro" corrosion behaviour of the magnesium alloy with Al and Zn (AZ31) protected with a biodegradable polycaprolactone coating loaded with hydroxyapatite and cephalexin

Mg alloys are very susceptible to corrosion in physiological media. This behaviour limits its widespread use in biomedical applications as bioresorbable implants, but it can be controlled by applying protective coatings. On one hand, coatings must delay and control the degradation process of the bare alloy and, on the other hand, they must be functional and biocompatible. In this study a biocompatible polycaprolactone (PCL) coating was functionalised with nano hydroxyapatite (HA) particles for enhanced biocompatibility and with an antibiotic, cephalexin, for anti-bacterial purposes and applied on the AZ31 alloy. The chemical composition and the surface morphology of the coated samples, before and after the corrosion tests, were studied by scanning electron microscopy (SEM) coupled with energy dispersive x-ray analysis (EDX) and Raman. The results showed that the presence of additives induced the formation of agglomerates and defects in the coating that resulted in the formation of pores during immersion in Hanks' solution. The corrosion resistance of the coated samples was studied in Hank's solution by electrochemical impedance spectroscopy (EIS). The results evidenced that all the coatings can provide corrosion protection of the bare alloy. However, in the presence of the additives, corrosion protection decreased. The wetting behaviour of the coating was evaluated by the static contact angle method and it was found that the presence of both hydroxyapatite and cephalexin increased the hydrophilic behaviour of the surface. The results showed that it is possible to tailor a composite coating that can store an antibiotic and nano hydroxyapatite particles, while allowing to control the in-vitro corrosion degradation of the bioresorbable Mg alloy AZ31. (C) 2015 Elsevier Ltd. All rights reserved.

Characterisation and electrochemical behaviour of electrodeposited Cu-Fe foams applied as pseudocapacitor electrodes

Copper iron (Cu-Fe) 3D porous foams for supercapacitor electrodes were electrodeposited in the cathodic regime, on stainless steel current collectors, using hydrogen bubbling dynamic template. The foams were prepared at different current densities and deposition times. The foams were submitted to thermal conditioning at temperatures of 150 and 250 degrees C. The morphology, composition and structure of the formed films were studied by SEM, EDS and XRD, respectively. The electrochemical behaviour was studied by cyclic voltammetry, electrochemical impedance spectroscopy and chronopotentiometry. The morphology of the 3D Cu-Fe foams is sensitive to the electrodeposition current and time. The increase of the current density produces a denser, larger and more ramified dendritic structure. Thermal conditioning at high temperature induces a coarser grain structure and the formation of copper oxides, which affect the electrochemical behaviour. The electrochemical response reveals the presence of various redox peaks assigned to the oxidation and reduction of Cu and Fe oxides and hydroxides in the foams. The specific capacitance of the 3D Cu Fe foams was significantly enhanced by thermal conditioning at 150 degrees C. The highest specific capacitance values attained 297 Fg(-1) which are much above the ones typically observed for single Cu or Fe Oxides and hydroxides. These values highlight a synergistic behaviour resulting from the combination of Cu and Fe in the form of nanostructured metallic foams. Moreover, the capacitance retention observed in an 8000 charge/discharge cycling test was above 66%, stating the good performance of these materials and its enhanced electrochemical response as supercapacitor negative electrodes. (C) 2014 Elsevier B.V. All rights reserved.

Dynamic behaviour of soft core sandwich beam structures using kriging-based layerwise models

Sandwich structures with soft cores are widely used in applications where a high bending stiffness is required without compromising the global weight of the structure, as well as in situations where good thermal and damping properties are important parameters to observe. As equivalent single layer approaches are not the more adequate to describe realistically the kinematics and the stresses distributions as well as the dynamic behaviour of this type of sandwiches, where shear deformations and the extensibility of the core can be very significant, layerwise models may provide better solutions. Additionally and in connection with this multilayer approach, the selection of different shear deformation theories according to the nature of the material that constitutes the core and the outer skins can predict more accurately the sandwich behaviour. In the present work the authors consider the use of different shear deformation theories to formulate different layerwise models, implemented through kriging-based finite elements. The viscoelastic material behaviour, associated to the sandwich core, is modelled using the complex approach and the dynamic problem is solved in the frequency domain. The outer elastic layers considered in this work may also be made from different nanocomposites. The performance of the models developed is illustrated through a set of test cases. (C) 2015 Elsevier Ltd. All rights reserved.

Exciting dynamical behavior in a network of two coupled rings of Chen oscillators

We study exotic patterns appearing in a network of coupled Chen oscillators. Namely, we consider a network of two rings coupled through a “buffer” cell, with Z3×Z5 symmetry group. Numerical simulations of the network reveal steady states, rotating waves in one ring and quasiperiodic behavior in the other, and chaotic states in the two rings, to name a few. The different patterns seem to arise through a sequence of Hopf bifurcations, period-doubling, and halving-period bifurcations. The network architecture seems to explain certain observed features, such as equilibria and the rotating waves, whereas the properties of the chaotic oscillator may explain others, such as the quasiperiodic and chaotic states. We use XPPAUT and MATLAB to compute numerically the relevant states.

Aggregatory behaviour of platelets incubated with subcellular fractions of normal and chagasic human syncytiotrophoblast

The surface of human syncytiotrophoblast does not induce maternal blood platelet aggregation even though it is not an endothelium. It can be surmised that as occurs in endothelial injury the subcellular components of the syncytiotrophoblast may have pro-or antiaggregatory activity. During congenital Chagas' disease which is associated to trophoblast lesions, platelets may play a role in the development of T. cruzi-induced placentitis. In the present work the aggregatory behaviour of normal human blood platelets was recorded after their challenging with subcellular fractions of syncytiotrophoblast isolated from normal and chagasic women. Nuclear, Mitochondrial, Microsomal and Supernatant fractions isolated from normal and chagasic syncytiotrophoblast failed to induce per se any aggregatory reaction on platelets. When samples of platelet-rich plasma (PRP) were preincubated with normal and chagasic nuclear fractions and then stimulated with collagen at threshold level (CT-PRP) an inhibition of the aggregatory response was observed. Treatment of CT-PRP with normal and chagasic mitochondrial fractions induced inhibition of platelet aggregation whereas only chagasic fraction reduced latency time. Microsornal fraction from normal placentas showed no significant effects on platelet aggregation. It is concluded that subcellular fractions of normal human syncytiotrophoblast do not exhibit any effect on platelet aggregation, whereas those subcellular fractions enriched in intracellular membrane components isolated from chagasic placentas inhibit platelet aggregation.

Spectral invariants of periodic nonautonomous discrete dynamical systems

For an interval map, the poles of the Artin-Mazur zeta function provide topological invariants which are closely connected to topological entropy. It is known that for a time-periodic nonautonomous dynamical system F with period p, the p-th power [zeta(F) (z)](p) of its zeta function is meromorphic in the unit disk. Unlike in the autonomous case, where the zeta function zeta(f)(z) only has poles in the unit disk, in the p-periodic nonautonomous case [zeta(F)(z)](p) may have zeros. In this paper we introduce the concept of spectral invariants of p-periodic nonautonomous discrete dynamical systems and study the role played by the zeros of [zeta(F)(z)](p) in this context. As we will see, these zeros play an important role in the spectral classification of these systems.

A fractional perspective to financial indices

The application of mathematical methods and computer algorithms in the analysis of economic and financial data series aims to give empirical descriptions of the hidden relations between many complex or unknown variables and systems. This strategy overcomes the requirement for building models based on a set of ‘fundamental laws’, which is the paradigm for studying phenomena usual in physics and engineering. In spite of this shortcut, the fact is that financial series demonstrate to be hard to tackle, involving complex memory effects and a apparently chaotic behaviour. Several measures for describing these objects were adopted by market agents, but, due to their simplicity, they are not capable to cope with the diversity and complexity embedded in the data. Therefore, it is important to propose new measures that, on one hand, are highly interpretable by standard personal but, on the other hand, are capable of capturing a significant part of the dynamical effects.

Dynamical Stability and Predictability of Football Players: The Study of One Match

The game of football demands new computational approaches to measure individual and collective performance. Understanding the phenomena involved in the game may foster the identification of strengths and weaknesses, not only of each player, but also of the whole team. The development of assertive quantitative methodologies constitutes a key element in sports training. In football, the predictability and stability inherent in the motion of a given player may be seen as one of the most important concepts to fully characterise the variability of the whole team. This paper characterises the predictability and stability levels of players during an official football match. A Fractional Calculus (FC) approach to define a player’s trajectory. By applying FC, one can benefit from newly considered modeling perspectives, such as the fractional coefficient, to estimate a player’s predictability and stability. This paper also formulates the concept of attraction domain, related to the tactical region of each player, inspired by stability theory principles. To compare the variability inherent in the player’s process variables (e.g., distance covered) and to assess his predictability and stability, entropy measures are considered. Experimental results suggest that the most predictable player is the goalkeeper while, conversely, the most unpredictable players are the midfielders. We also conclude that, despite his predictability, the goalkeeper is the most unstable player, while lateral defenders are the most stable during the match.

Behaviour and fate of metals in urban wastewater treatment plants: a review

The concerns on metals in urban wastewater treatment plants (WWTPs) are mainly related to its contents in discharges to environment, namely in the final effluent and in the sludge produced. In the near future, more restrictive limits will be imposed to final effluents, due to the recent guidelines of the European Water Framework Directive (EUWFD). Concerning the sludge, at least seven metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) have been regulated in different countries, four of which were classified by EUWFD as priority substances and two of which were also classified as hazardous substances. Although WWTPs are not designed to remove metals, the study of metals behaviour in these systems is a crucial issue to develop predictive models that can help more effectively the regulation of pre-treatment requirements and contribute to optimize the systems to get more acceptable metal concentrations in its discharges. Relevant data have been published in the literature in recent decades concerning the occurrence/fate/behaviour of metals in WWTPs. However, the information is dispersed and not standardized in terms of parameters for comparing results. This work provides a critical review on this issue through a careful systematization, in tables and graphs, of the results reported in the literature, which allows its comparison and so its analysis, in order to conclude about the state of the art in this field. A summary of the main consensus, divergences and constraints found, as well as some recommendations, is presented as conclusions, aiming to contribute to a more concerted action of future research. © 2015, Islamic Azad University (IAU).

Phase behaviour of alternative solvents

Dissertation presented to obtain the Ph.D. degree in Chemistry (Physical Chemistry) at the Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa

Spectral and dynamical invariants in a complete clustered network

The main result of this work is a new criterion for the formation of good clusters in a graph. This criterion uses a new dynamical invariant, the performance of a clustering, that characterizes the quality of the formation of clusters. We prove that the growth of the dynamical invariant, the network topological entropy, has the effect of worsening the quality of a clustering, in a process of cluster formation by the successive removal of edges. Several examples of clustering on the same network are presented to compare the behavior of other parameters such as network topological entropy, conductance, coefficient of clustering and performance of a clustering with the number of edges in a process of clustering by successive removal.

Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Dynamical Analysis of Non-Repetitive Trajectories in Robotic Manipulation

A new method for the study and optimization of manu«ipulator trajectories is developed. The novel feature resides on the modeling formulation. Standard system desciptions are based on a set of differential equations which, in general, require laborious computations and may be difficult to analyze. Moreover, the derived algorithms are suited to "deterministic" tasks, such as those appearing in a repetitivework, and are not well adapted to a "random" operation that occurs in intelligent systems interacting with a non-structured and changing environment. These facts motivate the development of alternative models based on distinct concepts. The proposed embedding of statistics and Fourier trasnform gives a new perspective towards the calculation and optimization of the robot trajectories in manipulating tasks.

Fractional Dynamics in Forest Fires

Every year forest fires consume large areas, being a major concern in many countries like Australia, United States and Mediterranean Basin European Countries (e.g., Portugal, Spain, Italy and Greece). Understanding patterns of such events, in terms of size and spatiotemporal distributions, may help to take measures beforehand in view of possible hazards and decide strategies of fire prevention, detection and suppression. Traditional statistical tools have been used to study forest fires. Nevertheless, those tools might not be able to capture the main features of fires complex dynamics and to model fire behaviour [1]. Forest fires size-frequency distributions unveil long range correlations and long memory characteristics, which are typical of fractional order systems [2]. Those complex correlations are characterized by self-similarity and absence of characteristic length-scale, meaning that forest fires exhibit power-law (PL) behaviour. Forest fires have also been proved to exhibit time-clustering phenomena, with timescales of the order of few days [3]. In this paper, we study forest fires in the perspective of dynamical systems and fractional calculus (FC). Public domain forest fires catalogues, containing data of events occurred in Portugal, in the period 1980 up to 2011, are considered. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses. The frequency spectra of such signals are determined using Fourier transforms, and approximated through PL trendlines. The PL parameters are then used to unveil the fractional-order dynamics characteristics of the data. To complement the analysis, correlation indices are used to compare and find possible relationships among the data. It is shown that the used approach can be useful to expose hidden patterns not captured by traditional tools.