Conductance and persistent current in quasi-one-dimensional systems with grain boundaries: Effects of the strongly reflecting and columnar grains

We study mesoscopic transport in the Q1D wires and rings made of a 2D conductor of width W and length L >> W. Our aim is to compare an impurity-free conductor with grain boundaries with a grain-free conductor with impurity disorder. A single grain boundary is modeled as a set of the 2D-$\delta$-function-like barriers positioned equidistantly on a straight line and disorder is emulated by a large number of such straight lines, intersecting the conductor with random orientation in random positions. The impurity disorder is modeled by the 2D $\delta$-barriers with the randomly chosen positions and signs. The electron transmission through the wires is calculated by the scattering-matrix method, and the Landauer conductance is obtained. We calculate the persistent current in the rings threaded by magnetic flux: We incorporate into the scattering-matrix method the flux-dependent cyclic boundary conditions and we introduce a trick allowing to study the persistent currents in rings of almost realistic size. We mainly focus on the numerical results for L much larger than the electron mean-free path, when the transport is diffusive. If the grain boundaries are weakly reflecting, the systems with grain boundaries show the same (mean) conductance and the same (typical) persistent current as the systems with impurities, and the results also agree with the single-particle theories treating disorder as a white-noise-like potential. If the grain boundaries are strongly reflecting, the typical persistent currents can be about three times larger than the results of the white-noise-based theory, thus resembling the experimental results of Jariwala et al. (PRL 2001). We extend our study to the 3D conductors with columnar grains. We find that the persistent current exceeds the white-noise-based result by another one order of magnitude, similarly as in the experiment of Chandrasekhar et al. (PRL 1991)

Quantum and Boltzmann transport in the quasi-one-dimensional wire with rough edges

We study quantum transport in Q1D wires made of a 2D conductor of width W and length L>>W. Our aim is to compare an impurity-free wire with rough edges with a smooth wire with impurity disorder. We calculate the electron transmission through the wires by the scattering-matrix method, and we find the Landauer conductance for a large ensemble of disordered wires. We study the impurity-free wire whose edges have a roughness correlation length comparable with the Fermi wave length. The mean resistance and inverse mean conductance 1/ are evaluated in dependence on L. For L -> 0 we observe the quasi-ballistic dependence 1/ = = 1/N_c + \rho_{qb} L/W, where 1/N_c is the fundamental contact resistance and \rho_{qb} is the quasi-ballistic resistivity. As L increases, we observe crossover to the diffusive dependence 1/ = = 1/N^{eff}_c + \rho_{dif} L/W, where \rho_{dif} is the resistivity and 1/N^{eff}_c is the effective contact resistance corresponding to the N^{eff}_c open channels. We find the universal results \rho_{qb}/\rho_{dif} = 0.6N_c and N^{eff}_c = 6 for N_c >> 1. As L exceeds the localization length \xi, the resistance shows onset of localization while the conductance shows the diffusive dependence 1/ = 1/N^{eff}_c + \rho_{dif} L/W up to L = 2\xi and the localization for L > 2\xi only. On the contrary, for the impurity disorder we find a standard diffusive behavior, namely 1/ = = 1/N_c + \rho_{dif} L/W for L < \xi. We also derive the wire conductivity from the semiclassical Boltzmann equation, and we compare the semiclassical electron mean-free path with the mean free path obtained from the quantum resistivity \rho_{dif}. They coincide for the impurity disorder, however, for the edge roughness they strongly differ, i.e., the diffusive transport is not semiclassical. It becomes semiclassical for the edge roughness with large correlation length

Stability subtypes of callous–unemotional traits and conduct disorder symptoms and their correlates

Callous unemotional traits and conduct disorder symptoms tend to co-occur across development, with existing evidence pointing to individual differences in the co-development of these problems. The current study identified groups of at risk adolescents showing stable (i.e., high on both conduct disorder and callous-unemotional symptoms, high only on either callous-unemotional or conduct disorder symptoms) or increasing conduct disorder and callous-unemotional symptoms. Data were collected from a sample of 2038 community adolescents between 15 and 18 years (1070 females, Mage = 16) of age. A longitudinal design was followed in that adolescent reports were collected at two time points, one year apart. Increases in conduct disorder symptoms and callous-unemotional traits were accompanied by increases in anxiety, depressive symptoms, narcissism, proactive and reactive aggression and decreases in self-esteem. Furthermore, adolescents with high and stable conduct disorder symptoms and callous-unemotional traits were consistently at high risk for individual, behavioral and contextual problems. In contrast, youth high on callous-unemotional traits without conduct disorder symptoms remained at low-risk for anxiety, depressive symptoms, narcissism, and aggression, pointing to a potential protective function of pure callous-unemotional traits against the development of psychopathological problems

Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring

Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, overall when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this view, airborne or satellite remote sensing allow to gather information over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (beta-diversity) might add crucial information related to relative abundance of different species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript we propose novel techniques to measure beta-diversity from airborne or satellite remote sensing, mainly based on: i) multivariate statistical analysis, ii) the spectral species concept, iii) self-organizing feature maps, iv) multi- dimensional distance matrices, and the v) Rao's Q diversity. Each of these measures allow to solve one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating beta-diversity from remotely sensed imagery and potentially relate them to species diversity in the field

Measuring β-diversity by remote sensing: a challenge for biodiversity monitoring

Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, especially when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this context, airborne or satellite remote sensing allows information to be gathered over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (β‐diversity) might add crucial information related to relative abundance of different species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript, we propose novel techniques to measure β‐diversity from airborne or satellite remote sensing, mainly based on: (1) multivariate statistical analysis, (2) the spectral species concept, (3) self‐organizing feature maps, (4) multidimensional distance matrices, and the (5) Rao's Q diversity. Each of these measures addresses one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating β‐diversity from remotely sensed imagery and potentially relating them to species diversity in the field