Self-validating technique for the measurement of the linewidth enhancement factor in semiconductor lasers

A new method for measuring the linewidth enhancement factor (α-parameter) of semiconductor lasers is proposed and discussed. The method itself provides an estimation of the measurement error, thus self-validating the entire procedure. The α-parameter is obtained from the temporal profile and the instantaneous frequency (chirp) of the pulses generated by gain switching. The time resolved chirp is measured with a polarization based optical differentiator. The accuracy of the obtained values of the α-parameter is estimated from the comparison between the directly measured pulse spectrum and the spectrum reconstructed from the chirp and the temporal profile of the pulse. The method is applied to a VCSEL and to a DFB laser emitting around 1550 nm at different temperatures, obtaining a measurement error lower than ± 8%.

‘This square is our home!’: the organisation of urban space in the spanish 15M movement

Why should a progressive planner/urbanist pay attention to the Spanish 15M movement? From a disciplinary standpoint, its most complex and interesting aspect, which could hypothetically be transferred to other contexts (as in fact happened in the Occupy Wall Street and Occupy London movements), is its 'spatiality'. This article analyses the spatial practices of the so called #spanishrevolution, one of the 2011 social movements that showed the possibility for a new collective appropriation and self-management (autogestion) of urban public space. Although the political goals of the movement were vague at the time of its inception, the practices and spatial imaginaries deployed by it have become consolidated and proven to be yet another of its more successful facets in promoting the spreading and organisation of the protest, making it a phenomenon that calls for reflection on the part of urban thinkers and planners.

Self-consistent numerical dispersion relation of the ablative Rayleigh-Taylor instability of double ablation fronts in inertial confinement fusion

The linear stability analysis of accelerated double ablation fronts is carried out numerically with a self-consistent approach. Accurate hydrodynamic profiles are taken into account in the theoretical model by means of a fitting parameters method using 1D simulation results. Numerical dispersión relation is compared to an analytical sharp boundary model [Yan˜ez et al., Phys. Plasmas 18, 052701 (2011)] showing an excellent agreement for the radiation dominated regime of very steep ablation fronts, and the stabilization due to smooth profiles. 2D simulations are presented to validate the numerical self-consistent theory.

Influence of some oenological practices on the aromatic and sensorial characteristics of white Verdejo wines

Changes in the aromatic composition as well as sensory characteristics in Verdejo white wines were analysed based on two factors: the winemaking methodology and the storing time of wine in bottles. The volatile components were determined by GLC-MS, and the sensory profile was designed and assessed according to the ISO 11035 standard. The results showed that when wines were made in oak barrels, either completely or partially, which means the wines were in contact with the lees, the levels of 1-octanol, ethyl heptanoate and ethyl decanoate were significantly affected (P menor que 0.05); the softness sensation was also influenced (P menor que 0.05). However, the amount of time the wines were stored in bottles significantly affected (P menor que 0.05) the levels of 1-hexanol, ethyl heptanoate, ethyl octanoate, ethyl decanoate, hexyl acetate, isoamyl acetate and isoamyl lactate and also an odour note (tropical fruit). The compounds with higher OAV values belong to the groups of esters and fatty acids. For these reasons, the composition and the quality of the aroma of Verdejo white wines appear to be significantly affected both by use of oak barrels in winemaking and the time the wines are stored in bottles.

Effect of five enological practices and of the general phenolic composition on fermentation-related aroma compounds in Mencia young red wines

The effects of five technological procedures and of the contents of total anthocyanins and condensed tan- nins on 19 fermentation-related aroma compounds of young red Mencia wines were studied. Multifactor ANOVA revealed that levels of those volatiles changed significantly over the length of storage in bottles and, to a lesser extent, due to other technological factors considered; total anthocyanins and condensed tannins also changed significantly as a result of the five practices assayed. Five aroma compounds pos- sessed an odour activity value >1 in all wines, and another four in some wines. Linear correlation among volatile compounds and general phenolic composition revealed that total anthocyanins were highly related to 14 different aroma compounds. Multifactor ANOVA, considering the content of total anthocy- anins as a sixth random factor, revealed that this parameter affected significantly the contents of ethyl lactate, ethyl isovalerate, 1-pentanol and ethyl octanoate. Thus, the aroma of young red Mencia wines may be affected by levels of total anthocyanins

On the generative equations of fractal self-similarity in granular media and the related PSD models

The physical appearance of granular media suggests the existence of geometrical scale invariance. The paper discuss how this physico-empirical property can be mathematically encoded leading to different generative models: a smooth one encoded by a differential equation and another encoded by an equation coming from a measure theoretical property.

The effects of cocaine self-administration on dendritic spine density in the rat hippocampus are dependent on genetic background

Chronic exposure to cocaine induces modifications to neurons in the brain regions involved in addiction. Hence, we evaluated cocaine-induced changes in the hippocampal CA1 field in Fischer 344 (F344) and Lewis (LEW) rats, 2 strains that have been widely used to study genetic predisposition to drug addiction, by combining intracellular Lucifer yellow injection with confocal microscopy reconstruction of labeled neurons. Specifically, we examined the effects of cocaine self-administration on the structure, size, and branching complexity of the apical dendrites of CA1 pyramidal neurons. In addition, we quantified spine density in the collaterals of the apical dendritic arbors of these neurons. We found differences between these strains in several morphological parameters. For example, CA1 apical dendrites were more branched and complex in LEW than in F344 rats, while the spine density in the collateral dendrites of the apical dendritic arbors was greater in F344 rats. Interestingly, cocaine self-administration in LEW rats augmented the spine density, an effect that was not observed in the F344 strain. These results reveal significant structural differences in CA1 pyramidal cells between these strains and indicate that cocaine self-administration has a distinct effect on neuron morphology in the hippocampus of rats with different genetic backgrounds.

One-dimensional self-similar solution of the dynamics of axisymmetric slender liquid bridges

In this paper the dynamics of axisymmetric, slender, viscous liquid bridges having volume close to the cylindrical one, and subjected to a small gravitational field parallel to the axis of the liquid bridge, is considered within the context of one-dimensional theories. Although the dynamics of liquid bridges has been treated through a numerical analysis in the inviscid case, numerical methods become inappropriate to study configurations close to the static stability limit because the evolution time, and thence the computing time, increases excessively. To avoid this difficulty, the problem of the evolution of these liquid bridges has been attacked through a nonlinear analysis based on the singular perturbation method and, whenever possible, the results obtained are compared with the numerical ones.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Low initial aspect-ratio direct-drive target designs for shock- or self-ignition in the context of the laser Megajoule

Analysis of low initial aspect ratio direct-drive target designs is carried out by varying the implosion velocity and the fuel mass. Starting from two different spherical targets with a given 300?g-DT mass, optimization of laser pulse and drive power allows to obtain a set of target seeds referenced by their peak implosion velocities and initial aspect ratio (A = 3 and A = 5). Self-ignition is achieved with higher implosion velocity for A = 5-design than for A = 3-design. Then, rescaling is done to extend the set of designs to a huge amount of mass, peak kinetic energies and peak areal densities. Self-ignition kinetic energy threshold Ek is characterized by a dependance of Ek ? v? with ?-values which depart from self-ignition models. Nevertheless, self-ignition energy is seen lower for smaller initial aspect ratio. An analysis of Two-Plasmons Decay threshold and Rayleigh?Taylor instability e-folding is carried out and it is shown that two-plasmon decay threshold is always overpassed for all designs. The hydrodynamic stability analysis is performed by embedded models to deal with linear and non-linear regime. It is found that the A = 5-designs are always at the limit of disruption of the shell.

Self-consistent relativistic band structure of the CH3NH3PbI3 perovskite

The electronic structure and properties of the orthorhombic phase of the CH 3 NH 3 PbI 3 perovskite are computed with density functional theory. The structure, optimized using a van der Waals functional, reproduces closely the unit cell volume. The experimental band gap is reproduced accurately by combining spin-orbit effects and a hybrid functional in which the fraction of exact exchange is tuned self-consistently to the optical dielectric constant. Including spin-orbit coupling strongly reduces the anisotropy of the effective mass tensor, predicting a low electron effective mass in all crystal directions. The computed binding energy of the unrelaxed exciton agrees with experimental data, and the values found imply a fast exciton dissociation at ambient temperature. Also polaron masses for the separated carriers are estimated. The values of all these parameters agree with recent indications that fast dynamics and large carrier diffusion lengths are key in the high photovoltaic efficiencies shown by these materials.

Redox state is a central modulator of the balance between self-renewal and differentiation in a dividing glial precursor cell

We have discovered that intracellular redox state appears to be a necessary and sufficient modulator of the balance between self-renewal and differentiation in dividing oligodendrocyte-type-2 astrocyte progenitor cells. The intracellular redox state of freshly isolated progenitors allows prospective isolation of cells with different self-renewal characteristics. Redox state is itself modulated by cell-extrinsic signaling molecules that alter the balance between self-renewal and differentiation: growth factors that promote self-renewal cause progenitors to become more reduced, while signaling molecules that promote differentiation cause progenitors to become more oxidized. Moreover, pharmacological antagonists of the redox effects of these cell-extrinsic signaling molecules antagonize their effects on self-renewal and differentiation, indicating that cell-extrinsic signaling molecules that modulate this balance converge on redox modulation as a critical component of their effector mechanism.