Influence of Zeeman splitting and thermally excited polaron states on magneto-electrical and magneto-thermal properties of magnetoresistive polycrystalline manganite La_{0.8}Sr_{0.2}MnO_3

Some possible connection between spin and charge degrees of freedom in magneto-resistive manganites is investigated through a thorough experimental study of the magnetic (AC susceptibility and DC magnetization) and transport (resistivity and thermal conductivity) properties. Measurements are reported in the case of well characterized polycrystalline La_{0.8}Sr_{0.2}MnO_3 samples. The experimental results suggest rather strong field-induced polarization effects in our material, clearly indicating the presence of ordered FM regions inside the semiconducting phase. Using an analytical expression which fits the spontaneous DC magnetization, the temperature and magnetic field dependences of both electrical resistivity and thermal conductivity data are found to be well reproduced through a universal scenario based on two mechanisms: (i) a magnetization dependent spin polaron hopping influenced by a Zeeman splitting effect, and (ii) properly defined thermally excited polaron states which have to be taken into account in order to correctly describe the behavior of the less conducting region. Using the experimentally found values of the magnetic and electron localization temperatures, we obtain L=0.5nm and m_p=3.2m_e for estimates of the localization length (size of the spin polaron) and effective polaron mass, respectively.Comment: Accepted for publication in Journal of Applied Physic

Spectroscopic Signatures of Electronic Excitations in Raman Scattering in Thin Films of Rhombohedral Graphite

Rhombohedral graphite features peculiar electronic properties, including persistence of low-energy surface bands of a topological nature. Here, we study the contribution of electron-hole excitations towards inelastic light scattering in thin films of rhombohedral graphite. We show that, in contrast to the featureless electron-hole contribution towards Raman spectrum of graphitic films with Bernal stacking, the inelastic light scattering accompanied by electron-hole excitations in crystals with rhombohedral stacking produces distinct features in the Raman signal which can be used both to identify the stacking and to determine the number of layers in the film.Comment: 15 pages in preprint format, 4 figures, accepted versio

Resolving structural variability in network models and the brain

Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar diagnostics presented in statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling---in addition to several summary statistics, including the mean clustering coefficient, shortest path length, and network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be embedded in anatomical brain regions tend to produce distributions that are similar to those extracted from the brain. We also find that network models hardcoded to display one network property do not in general also display a second, suggesting that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the statistical inference of brain network structure from neuroimaging data.Comment: 24 pages, 11 figures, 1 table, supplementary material

Energy solutions to one-dimensional singular parabolic problems with BVBV data are viscosity solutions

We study one-dimensional very singular parabolic equations with periodic boundary conditions and initial data in $BV$, which is the energy space. We show existence of solutions in this energy space and then we prove that they are viscosity solutions in the sense of Giga-Giga.Comment: 15 page

On the existence of traveling waves in the 3D Boussinesq system

We extend earlier work on traveling waves in premixed flames in a gravitationally stratified medium, subject to the Boussinesq approximation. For three-dimensional channels not aligned with the gravity direction and under the Dirichlet boundary conditions in the fluid velocity, it is shown that a non-planar traveling wave, corresponding to a non-zero reaction, exists, under an explicit condition relating the geometry of the crossection of the channel to the magnitude of the Prandtl and Rayleigh numbers, or when the advection term in the flow equations is neglected.Comment: 15 pages, to appear in Communications in Mathematical Physic

Multirelational Organization of Large-scale Social Networks in an Online World

The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a non-linear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multi-dimensional nature of these interactions has largely been ignored in empirical studies, mostly because of lack of data. Here, for the first time, we analyze a complete, multi-relational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering and fatter-tail degree distribution. We then proceed to explore how the inter-dependence of different network types determines the organization of the social system. In particular we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations.Comment: 7 pages, 5 figures, accepted for publication in PNA

Robust Detection of Dynamic Community Structure in Networks

We describe techniques for the robust detection of community structure in some classes of time-dependent networks. Specifically, we consider the use of statistical null models for facilitating the principled identification of structural modules in semi-decomposable systems. Null models play an important role both in the optimization of quality functions such as modularity and in the subsequent assessment of the statistical validity of identified community structure. We examine the sensitivity of such methods to model parameters and show how comparisons to null models can help identify system scales. By considering a large number of optimizations, we quantify the variance of network diagnostics over optimizations (`optimization variance') and over randomizations of network structure (`randomization variance'). Because the modularity quality function typically has a large number of nearly-degenerate local optima for networks constructed using real data, we develop a method to construct representative partitions that uses a null model to correct for statistical noise in sets of partitions. To illustrate our results, we employ ensembles of time-dependent networks extracted from both nonlinear oscillators and empirical neuroscience data.Comment: 18 pages, 11 figure

Remote participation during glycosylation reactions of galactose building blocks: Direct evidence from cryogenic vibrational spectroscopy

The stereoselective formation of 1,2‐cis‐glycosidic bonds is challenging. However, 1,2‐cis‐selectivity can be induced by remote participation of C4 or C6 ester groups. Reactions involving remote participation are believed to proceed via a key ionic intermediate, the glycosyl cation. Although mechanistic pathways were postulated many years ago, the structure of the reaction intermediates remained elusive owing to their short‐lived nature. Herein, we unravel the structure of glycosyl cations involved in remote participation reactions via cryogenic vibrational spectroscopy and first principles theory. Acetyl groups at C4 ensure α‐selective galactosylations by forming a covalent bond to the anomeric carbon in dioxolenium‐type ions. Unexpectedly, also benzyl ether protecting groups can engage in remote participation and promote the stereoselective formation of 1,2‐cis‐glycosidic bonds

Anomalous thermoelectric power of Mg1-xAlxB2 system with x = 0.0 to 1.0

Thermoelectric power, S(T) of the Mg1-xAlxB2 system has been measured for x = 0.0, 0.1, 0.2, 0.4, 0.6, 0.8 and 1.0. XRD, resistivity and magnetization measurements are also presented. It has been found that the thermoelectric power is positive for x = 0.4 and is negative for x = 0.6 over the entire temperature range studied up to 300 K. The thermoelectric power of x = 0.4 samples vanishes discontinuously below a certain temperature, implying existence of superconductivity. In general, the magnitude of the thermoelectric power increases with temperature up to a certain temperature, and then it starts to decrease towards zero base line. In order to explain the observed behavior of the thermoelectric power, we have used a model in which both diffusion and phonon drag processes are combined by using a phenomenological interpolation between the low and high temperature behaviors of the thermoelectric power. The considered model provides an excellent fit to the observed data. It is further found that Al doping enhances the Debye temperature.Comment: 19 pages Text + Figs. suggestions/comments([email protected]