Dielectrics in a time-dependent electric field: a real-time approach based on density-polarization functional theory

In the presence of a (time-dependent) macroscopic electric field the electron dynamics of dielectrics cannot be described by the time-dependent density only. We present a real-time formalism that has the density and the macroscopic polarization P as key quantities. We show that a simple local function of P already captures long-range correlation in linear and nonlinear optical response functions. Specifically, after detailing the numerical implementation, we examine the optical absorption, the second- and third-harmonic generation of bulk Si, GaAs, AlAs and CdTe at different level of approximation. We highlight links with ultranonlocal exchange-correlation functional approximations proposed within linear response time-dependent density functional theory framework.

Novel critical phenomena in optimization driven processes on networks

The work presented in this Ph.D thesis was developed in the context of complex network theory, from a statistical physics standpoint. We examine two distinct problems in this research field, taking a special interest in their respective critical properties. In both cases, the emergence of criticality is driven by a local optimization dynamics. Firstly, a recently introduced class of percolation problems that attracted a significant amount of attention from the scientific community, and was quickly followed up by an abundance of other works. Percolation transitions were believed to be continuous, until, recently, an 'explosive' percolation problem was reported to undergo a discontinuous transition, in [93]. The system's evolution is driven by a metropolis-like algorithm, apparently producing a discontinuous jump on the giant component's size at the percolation threshold. This finding was subsequently supported by number of other experimental studies [96, 97, 98, 99, 100, 101]. However, in [1] we have proved that the explosive percolation transition is actually continuous. The discontinuity which was observed in the evolution of the giant component's relative size is explained by the unusual smallness of the corresponding critical exponent, combined with the finiteness of the systems considered in experiments. Therefore, the size of the jump vanishes as the system's size goes to infinity. Additionally, we provide the complete theoretical description of the critical properties for a generalized version of the explosive percolation model [2], as well as a method [3] for a precise calculation of percolation's critical properties from numerical data (useful when exact results are not available). Secondly, we study a network flow optimization model, where the dynamics consists of consecutive mergings and splittings of currents flowing in the network. The current conservation constraint does not impose any particular criterion for the split of current among channels outgoing nodes, allowing us to introduce an asymmetrical rule, observed in several real systems. We solved analytically the dynamic equations describing this model in the high and low current regimes. The solutions found are compared with numerical results, for the two regimes, showing an excellent agreement. Surprisingly, in the low current regime, this model exhibits some features usually associated with continuous phase transitions.

Electromechanical properties of engineered lead free potassium sodium niobate based materials

K0.5Na0.5NbO3 (KNN), is the most promising lead free material for substituting lead zirconate titanate (PZT) which is still the market leader used for sensors and actuators. To make KNN a real competitor, it is necessary to understand and to improve its properties. This goal is pursued in the present work via different approaches aiming to study KNN intrinsic properties and then to identify appropriate strategies like doping and texturing for designing better KNN materials for an intended application. Hence, polycrystalline KNN ceramics (undoped, non-stoichiometric; NST and doped), high-quality KNN single crystals and textured KNN based ceramics were successfully synthesized and characterized in this work. Polycrystalline undoped, non-stoichiometric (NST) and Mn doped KNN ceramics were prepared by conventional ceramic processing. Structure, microstructure and electrical properties were measured. It was observed that the window for mono-phasic compositions was very narrow for both NST ceramics and Mn doped ceramics. For NST ceramics the variation of A/B ratio influenced the polarization (P-E) hysteresis loop and better piezoelectric and dielectric responses could be found for small stoichiometry deviations (A/B = 0.97). Regarding Mn doping, as compared to undoped KNN which showed leaky polarization (P-E) hysteresis loops, B-site Mn doped ceramics showed a well saturated, less-leaky hysteresis loop and a significant properties improvement. Impedance spectroscopy was used to assess the role of Mn and a relation between charge transport – defects and ferroelectric response in K0.5Na0.5NbO3 (KNN) and Mn doped KNN ceramics could be established. At room temperature the conduction in KNN which is associated with holes transport is suppressed by Mn doping. Hence Mn addition increases the resistivity of the ceramic, which proved to be very helpful for improving the saturation of the P-E loop. At high temperatures the conduction is dominated by the motion of ionized oxygen vacancies whose concentration increases with Mn doping. Single crystals of potassium sodium niobate (KNN) were grown by a modified high temperature flux method. A boron-modified flux was used to obtain the crystals at a relatively low temperature. XRD, EDS and ICP analysis proved the chemical and crystallographic quality of the crystals. The grown KNN crystals exhibit higher dielectric permittivity (29,100) at the tetragonal-to-cubic phase transition temperature, higher remnant polarization (19.4 μC/cm2) and piezoelectric coefficient (160 pC/N) when compared with the standard KNN ceramics. KNN single crystals domain structure was characterized for the first time by piezoforce response microscopy. It could be observed that <001> - oriented potassium sodium niobate (KNN) single crystals reveal a long range ordered domain pattern of parallel 180° domains with zig-zag 90° domains. From the comparison of KNN Single crystals to ceramics, It is argued that the presence in KNN single crystal (and absence in KNN ceramics) of such a long range order specific domain pattern that is its fingerprint accounts for the improved properties of single crystals. These results have broad implications for the expanded use of KNN materials, by establishing a relation between the domain patterns and the dielectric and ferroelectric response of single crystals and ceramics and by indicating ways of achieving maximised properties in KNN materials. Polarized Raman analysis of ferroelectric potassium sodium niobate (K0.5Na0.5)NbO3 (KNN) single crystals was performed. For the first time, an evidence is provided that supports the assignment of KNN single crystals structure to the monoclinic symmetry at room temperature. Intensities of A′, A″ and mixed A′+A″ phonons have been theoretically calculated and compared with the experimental data in dependence of crystal rotation, which allowed the precise determination of the Raman tensor coefficients for (non-leaking) modes in monoclinic KNN. In relation to the previous literature, this study clarifies that assigning monoclinic phase is more suitable than the orthorhombic one. In addition, this study is the basis for non-destructive assessments of domain distribution by Raman spectroscopy in KNN-based lead-free ferroelectrics with complex structures. Searching a deeper understanding of the electrical behaviour of both KNN single crystal and polycrystalline materials for the sake of designing optimized KNN materials, a comparative study at the level of charge transport and point defects was carried out by impedance spectroscopy. KNN single crystals showed lower conductivity than polycrystals from room temperature up to 200 ºC, but above this temperature polycrystalline KNN displays lower conductivity. The low temperature (T < 200 ºC) behaviour reflects the different processing conditions of both ceramics and single crystals, which account for less defects prone to charge transport in the case of single crystals. As temperature increases (T > 200 ºC) single crystals become more conductive than polycrystalline samples, in which grain boundaries act as barriers to charge transport. For even higher temperatures the conductivity difference between both is increased due to the contribution of ionic conduction in single crystals. Indeed the values of activation energy calculated to the high temperature range (T > 300 ºC) were 1.60 and 0.97 eV, confirming the charge transport due to ionic conduction and ionized oxygen vacancies in single crystals and polycrystalline KNN, respectively. It is suggested that single crystals with low defects content and improved electromechanical properties could be a better choice for room temperature applications, though at high temperatures less conductive ceramics may be the choice, depending on the targeted use. Aiming at engineering the properties of KNN polycrystals towards the performance of single crystals, the preparation and properties study of (001) – oriented (K0.5Na0.5)0.98Li0.02NbO3 (KNNL) ceramics obtained by templated grain growth (TGG) using KNN single crystals as templates was undertaken. The choice of KNN single crystals templates is related with their better properties and to their unique domain structure which were envisaged as a tool for templating better properties in KNN ceramics too. X-ray diffraction analysis revealed for the templated ceramics a monoclinic structure at room temperature and a Lotgering factor (f) of 40% which confirmed texture development. These textured ceramics exhibit a long range ordered domain pattern consisting of 90º and 180º domains, similar to the one observed in the single crystals. Enhanced dielectric (13017 at TC), ferroelectric (2Pr = 42.8 μC/cm2) and piezoelectric (d33 = 280 pC/N) properties are observed for textured KNNL ceramics as compared to the randomly oriented ones. This behaviour is suggested to be due to the long range ordered domain patterns observed in the textured ceramics. The obtained results as compared with the data previously reported on texture KNN based ceramics confirm that superior properties were found due to ordered repeated domain pattern. This study provides an useful approach towards properties improvement of KNN-based piezoelectric ceramics. Overall, the present results bring a significant contribution to the pool of knowledge on the properties of sodium potassium niobate materials: a relation between the domain patterns and di-, ferro-, and piezo-electric response of single crystals and ceramics was demonstrated and ways of engineering maximised properties in KNN materials, for example by texturing were established. This contribution is envisaged to have broad implications for the expanded use of KNN over the alternative lead-based materials.

The Pannonian Plain as a Source of Ambrosia Pollen in the Balkans

This study aims to find likely sources of Ambrosia pollen recorded during 2007 at five pollen-monitoring sites in central Europe, Novi Sad, Ruma, Negotin and Nis (Serbia) and Skopje (Macedonia). Ambrosia plants start flowering early in the morning and so Ambrosia pollen grains recorded during the day are likely to be from a local source. Conversely, Ambrosia pollen grains recorded at night or very early in the morning may have arrived via long-range transport. Ambrosia pollen counts were analysed in an attempt to find possible sources of the pollen and to identify Ambrosia pollen episodes suitable for further investigation using back-trajectory analysis. Diurnal variations and the magnitude of Ambrosia pollen counts during the 2007 Ambrosia pollen season showed that Novi Sad and Ruma (Pannonian Plain) and to a lesser degree Negotin (Balkans) were located near to sources of Ambrosia pollen. Mean bi-hourly Ambrosia pollen concentrations peaked during the middle of the day and concentrations at these sites were notably higher than at Nis and Skopje. Three episodes were selected for further analysis using back-trajectory analysis. Back-trajectories showed that air masses brought Ambrosia pollen from the north to Nis and, on one occasion, to Skopje (Balkans) during the night and early morning after passing to the east of Novi Sad and Ruma during the previous day. The results of this study identified the Southern part of the Pannonian Plain around Novi Sad and Ruma as being a potential source region for Ambrosia pollen recorded at Nis and Skopje in the Balkans.

Release of Bet v 1 from Birch Pollen 1 from 5 European 2 Countries. Results from the HIALINE Study

Exposure to allergens is pivotal in determining sensitization and allergic symptoms in individuals. Pollen grain counts in ambient air have traditionally been assessed to estimate airborne allergen exposure. However, the exact allergen content of ambient air is unknown. We therefore monitored atmospheric concentrations of birch pollen grain and the matched major birch pollen allergen Bet v 1 simultaneously across Europe within the EU-funded project HIALINE (Health Impacts of Airborne Allergen Information Network). Pollen count was assessed with Hirst type pollen traps at 10 l/min at sites in France, United Kingdom, Germany, Italy and Finland. Allergen concentrations in ambient air were sampled at 800l/min with a Chemvol high-volume cascade impactor equipped with stages PM>10μm, 10 μm>PM>2.5μm, and in Germany also 2.5 μm>PM>0.12μm. The major birch pollen allergen Bet v 1 was determined with an allergen specific ELISA. Bet v 1 isoform patterns were analyzed by 2D-SDS-PAGE blots and mass spectrometric identification. Basophil activation was tested in an FcεR1-humanized rat basophil cell line passively sensitized with serum of a birch pollen lmptomatic patient. Compared to 10 previous years, 2009 was a representative birch pollen season for all stations. About 90% of the allergen was found in the PM>10μm fraction at all stations. Bet v 1 isoforms pattern did not varied substantially neither during ripening of pollen nor between different geographical locations. The average European allergen release from birch pollen was 3.2 pg Bet v 1/pollen and did not vary much between the European countries. However, in all countries a >10-fold difference in daily allergen release per pollen was measured which could be explained by long range transport of pollen with a deviating allergen release. Basophil activation by ambient air extracts correlated better with airborne allergen than with pollen concentration. Although Bet v 1 is a mixture of different isoforms, its fingerprint is constant across Europe. Bet v 1 was also exclusively linked to pollen. Pollen from different days varied >10-fold in allergen release. Thus exposure to allergen is inaccurately monitored by only monitoring birch pollen grains. Indeed, a humanized basophil activation test correlated much better with allergen concentrations in ambient air than with pollen count. Monitoring the allergens themselves together with pollen in ambient air might be an improvement in allergen exposure assessment.

Micromorphology of the labellum and structure of the osmophore in a group of closely related species of the sexually deceptive Orchid genus Ophrys (orchidaceae)

Tese de doutoramento, Biologia (Biologia Celular), Universidade de Lisboa, Faculdade de Ciências, 2016

Why is “blindsight” blind? A new perspective on primary visual cortex, recurrent activity and visual awareness

The neuropsychological phenomenon of blindsight has been taken to suggest that the primary visual cortex (V1) plays a unique role in visual awareness, and that extrastriate activation needs to be fed back to V1 in order for the content of that activation to be consciously perceived. The aim of this review is to evaluate this theoretical framework and to revisit its key tenets. Firstly, is blindsight truly a dissociation of awareness and visual detection? Secondly, is there sufficient evidence to rule out the possibility that the loss of awareness resulting from a V1 lesion simply reflects reduced extrastriate responsiveness, rather than a unique role of V1 in conscious experience? Evaluation of these arguments and the empirical evidence leads to the conclusion that the loss of phenomenal awareness in blindsight may not be due to feedback activity in V1 being the hallmark awareness. On the basis of existing literature, an alternative explanation of blindsight is proposed. In this view, visual awareness is a “global” cognitive function as its hallmark is the availability of information to a large number of perceptual and cognitive systems; this requires inter-areal long-range synchronous oscillatory activity. For these oscillations to arise, a specific temporal profile of neuronal activity is required, which is established through recurrent feedback activity involving V1 and the extrastriate cortex. When V1 is lesioned, the loss of recurrent activity prevents inter-areal networks on the basis of oscillatory activity. However, as limited amount of input can reach extrastriate cortex and some extrastriate neuronal selectivity is preserved, computations involving comparison of neural firing rates within a cortical area remain possible. This enables “local” read-out from specific brain regions, allowing for the detection and discrimination of basic visual attributes. Thus blindsight is blind due to lack of “global” long-range synchrony, and it functions via “local” neural readout from extrastriate areas.

On the DNA of eleven mammals

This paper studies the DNA code of eleven mammals from the perspective of fractional dynamics. The application of Fourier transform and power law trendlines leads to a categorical representation of species and chromosomes. The DNA information reveals long range memory characteristics.

Symbolic fractional dynamics

Fractional dynamics reveals long range memory properties of systems described by means of signals represented by real numbers. Alternatively, dynamical systems and signals can adopt a representation where states are quantified using a set of symbols. Such signals occur both in nature and in man made processes and have the potential of a aftermath as relevant as the classical counterpart. This paper explores the association of Fractional calculus and symbolic dynamics. The results are visualized by means of the multidimensional technique and reveal the association between the fractal dimension and one definition of fractional derivative.

Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

The Persistence of Memory

This paper analyzes several natural and man-made complex phenomena in the perspective of dynamical systems. Such phenomena are often characterized by the absence of a characteristic length-scale, long range correlations and persistent memory, which are features also associated to fractional order systems. For each system, the output, interpreted as a manifestation of the system dynamics, is analyzed by means of the Fourier transform. The amplitude spectrum is approximated by a power law function and the parameters are interpreted as an underlying signature of the system dynamics. The complex systems under analysis are then compared in a global perspective in order to unveil and visualize hidden relationships among them.

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.

Fast subplasma membrane Ca2+ transients control exo-endocytosis of synaptic-like microvesicles in astrocytes

Astrocytes are the most abundant glial cell type in the brain. Although not apposite for long-range rapid electrical communication, astrocytes share with neurons the capacity of chemical signaling via Ca(2+)-dependent transmitter exocytosis. Despite this recent finding, little is known about the specific properties of regulated secretion and vesicle recycling in astrocytes. Important differences may exist with the neuronal exocytosis, starting from the fact that stimulus-secretion coupling in astrocytes is voltage independent, mediated by G-protein-coupled receptors and the release of Ca(2+) from internal stores. Elucidating the spatiotemporal properties of astrocytic exo-endocytosis is, therefore, of primary importance for understanding the mode of communication of these cells and their role in brain signaling. We here take advantage of fluorescent tools recently developed for studying recycling of glutamatergic vesicles at synapses (Voglmaier et al., 2006; Balaji and Ryan, 2007); we combine epifluorescence and total internal reflection fluorescence imaging to investigate with unprecedented temporal and spatial resolution, the stimulus-secretion coupling underlying exo-endocytosis of glutamatergic synaptic-like microvesicles (SLMVs) in astrocytes. Our main findings indicate that (1) exo-endocytosis in astrocytes proceeds with a time course on the millisecond time scale (tau(exocytosis) = 0.24 +/- 0.017 s; tau(endocytosis) = 0.26 +/- 0.03 s) and (2) exocytosis is controlled by local Ca(2+) microdomains. We identified submicrometer cytosolic compartments delimited by endoplasmic reticulum tubuli reaching beneath the plasma membrane and containing SLMVs at which fast (time-to-peak, approximately 50 ms) Ca(2+) events occurred in precise spatial-temporal correlation with exocytic fusion events. Overall, the above characteristics of transmitter exocytosis from astrocytes support a role of this process in fast synaptic modulation.