Electric-field-induced Mott insulating states in organic field-effect transistors

We consider the possibility that the electrons injected into organic field-effect transistors are strongly correlated. A single layer of acenes can be modeled by a Hubbard Hamiltonian similar to that used for the κ-(BEDT-TTF)2X family of organic superconductors. The injected electrons do not necessarily undergo a transition to a Mott insulator state as they would in bulk crystals when the system is half-filled. We calculate the fillings needed for obtaining insulating states in the framework of the slave-boson theory and in the limit of large Hubbard repulsion U. We also suggest that these Mott states are unstable above some critical interlayer coupling or long-range Coulomb interaction.

Axon navigation in the mammalian primary olfactory pathway: Where to next?

The process of establishing long-range neuronal connections can be divided into at least three discrete steps. First, axons need to be stimulated to grow and this growth must be towards appropriate targets. Second, after arriving at their target, axons need to be directed to their topographically appropriate position and in some cases, such as in cortical structures, they must grow radially to reach the correct laminar layer Third, axons then arborize and form synaptic connections with only a defined subpopulation of potential post-synaptic partners. Attempts to understand these mechanisms in the visual system have been ongoing since pioneer studies in the 1940s highlighted the specificity of neuronal connections in the retino-tectal pathway. These classical systems-based approaches culminated in the 1990s with the discovery that Eph-ephrin repulsive interactions were involved in topographical mapping. In marked contrast, it was the cloning of the odorant receptor family that quickly led to a better understanding of axon targeting in the olfactory system. The last 10 years have seen the olfactory pathway rise in prominence as a model system for axon guidance. Once considered to be experimentally intractable, it is now providing a wealth of information on all aspects of axon guidance and targeting with implications not only for our understanding of these mechanisms in the olfactory system but also in other regions of the nervous system.

alpha-conotoxins PnIA and [A10L] PnIA stabilize different states of the alpha 7-L247T nicotinic acetylcholine receptor

The effects of the native alpha-conotoxin PnIA, its synthetic derivative [ A10L] PnIA and alanine scan derivatives of [ A10L] PnIA were investigated on chick wild type alpha7 and alpha7-L247T mutant nicotinic acetylcholine receptors (nAChRs) expressed in Xenopus oocytes. PnIA and [A10L] PnIA inhibited acetylcholine (ACh)-activated currents at wtalpha7 receptors with IC50 values of 349 and 168 nM, respectively. Rates of onset of inhibition were similar for PnIA and [ A10L] PnIA; however, the rate of recovery was slower for [ A10L] PnIA, indicating that the increased potency of [ A10L] PnIA at alpha7 receptors is conveyed by its slower rate of dissociation from the receptors. All the alanine mutants of [ A10L] PnIA inhibited ACh-activated currents at wtalpha7 receptors. Insertion of an alanine residue between position 5 and 13 and at position 15 significantly reduced the ability of [ A10L] PnIA to inhibit ACh-evoked currents. PnIA inhibited the non-desensitizing ACh-activated currents at alpha7-L247T receptors with an IC50 194 nM. In contrast, [ A10L] PnIA and the alanine mutants potentiated the ACh-activated current alpha7-L247T receptors and in addition [ A10L] PnIA acted as an agonist. PnIA stabilized the receptor in a state that is non-conducting in both the wild type and mutant receptors, whereas [ A10L] PnIA stabilized a state that is non-conducting in the wild type receptor and conducting in the alpha7-L247T mutant. These data indicate that the change of a single amino acid side-chain, at position 10, is sufficient to change the toxin specificity for receptor states in the alpha7-L247T mutant.

ANTECEDENTS AND CONSEQUENCES OF HOUSEHOLD FINANCIAL MANAGEMENT IN BRAZILIAN LOWER-MIDDLE-CLASS

Through two complementary and exploratory studies – one qualitative and one quantitative – this research aims to understand the ways in which lower-middle-class families in Brazil manage their household finances. The study proposes an integrated framework that brings together various previously disconnected theoretical fragments. Based on a survey with a sample of 165 lower-middle-class female consumers of a retail company in São Paulo, we explored and tested, via a quantitative study, how antecedents such as personal characteristics affect the financial management process, as well as its consequences, either negatively as defaults or positively as savings. The model calibration and analysis were derived from a series of regression analyses. The results revealed the mediator role that financial management plays in the relationship between personal characteristics and defaults and savings. Compared to previous studies with consumers of more affluent countries, we identified peculiar findings among Brazilian lower-middle-class consumers: inadequate attention to control, weak or no focus on short- or long-range planning, widespread absence of budget surplus, and influence of critical events on episodes of default.

Ferromagnetic order in aged Co-doped TiO2 anatase nanopowders

Oxide based diluted magnetic semiconductor (DMS) materials have been a subject of increasing interest due to reports of room temperature ferromagnetism in several systems and their potential use in the development of spintronic devices. However, concerns on the stability of the magnetic properties of different DMS systems have been raised. Their magnetic moment is often unstable, vanishing with a characteristic decay time of weeks or months, which precludes the development of real applications. This paper reports on the ferromagnetic properties of two-year-aged Ti1-xCoxO2-δ reduced anatase nanopowders with different Co contents (0.03≤x≤0.10). Aged samples retain rather high values of magnetization, remanence and coercivity which provide strong evidence for a quite preserved long-range ferromagnetic order. In what concern Co segregation, some degree of metastability of the diluted Co doped anatase structure could be inferred in the case of the sample with the higher Co content.

The spin polarization of CrO2 revisited

Here, we use Andreev reflection spectroscopy to study the spin polarization of high quality CrO2 films. We study the spin polarization as a function of growth temperature, resulting in grain size and electrical resistivity. In these films low temperature growth appears to be a necessary but not sufficient condition to guarantee the observation of high spin polarization, and this is only observed in conjunction with suppressed superconducting gap values and anomalously low interface properties. We suggest that this combination of observations is a manifestation of the long range spin triplet proximity effect. (C) 2007 American Institute of Physics.

Magnetic properties of Co-doped TiO(2) anatase nanopowders

This letter reports on the magnetic properties of Ti(1-x)Co(x)O(2) anatase phase nanopowders with different Co contents. It is shown that oxygen vacancies play an important role in promoting long-range ferromagnetic order in the material studied in addition to the transition-metal doping. Furthermore, the results allow ruling out the premise of a strict connection between Co clustering and the ferromagnetism observed in the Co:TiO(2) anatase system.

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.

Colloidal dipolar interactions in 2D smectic-C films

We use a two-dimensional (2D) elastic free energy to calculate the effective interaction between two circular disks immersed in smectic-C films. For strong homeotropic anchoring, the distortion of the director field caused by the disks generates topological defects that induce an effective interaction between the disks. We use finite elements, with adaptive meshing, to minimize the 2D elastic free energy. The method is shown to be accurate and efficient for inhomogeneities on the length scales set by the disks and the defects, that differ by up to 3 orders of magnitude. We compute the effective interaction between two disk-defect pairs in a simple (linear) configuration. For large disk separations, D, the elastic free energy scales as similar to D-2, confirming the dipolar character of the long-range effective interaction. For small D the energy exhibits a pronounced minimum. The lowest energy corresponds to a symmetrical configuration of the disk-defect pairs, with the inner defect at the mid-point between the disks. The disks are separated by a distance that, is twice the distance of the outer defect from the nearest disk. The latter is identical to the equilibrium distance of a defect nucleated by an isolated disk.

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.

Estimation of infection rate in epidemic models with multiple populations

Dissertação para obtenção do Grau de Mestre em Matemática e Aplicações Especialização em Actuariado, Estatística e Investigação Operacional

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.