Effect of excited states and applied magnetic fields on the measured hole mobility in an organic semiconductor

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An Analytic Solution of Hydrodynamic Equations with Source Terms in Heavy Ion Collisions

The energy and baryon densities in heavy ion collisions are estimated by analytically solving a 1+1 dimensional hydrodynamical model with source terms. Particularly, a competition between the energy and baryon sources and the expansion of the system is discussed in detail.Comment: LaTeX2e, 7 pages, 4 postscript figures, submitted to Int. J. Mod. Phys.

Anomalous change in leakage and displacement currents after electrical poling on lead-free ferroelectric ceramics

We report the polarization, displacement current and leakage current behavior of a trivalent nonpolar cation Al cation substituted lead free ferroelectric NBT-BT electroceramics with tetragonal phase and P4mm space group symmetry. Nearly three orders of magnitude decrease in leakage current were observed under electrical poling, which significantly improves microstructure, polarization, and displacement current. Effective poling neutralizes the domain pinning, traps charges at grain boundaries and fills oxygen vacancies with free charge carriers in matrix, thus saturated macroscopic polarization in contrast to that in upoled samples. E-poling changes bananas type polarization loops to real ferroelectric loops.Comment: 18 pages, 5 figure

Semi-supervised Analysis of Human fMRI Data

Kernel Canonical Correlation Analysis (KCCA) is a general technique for subspace learning that incorporates principal components analysis (PCA) and Fisher linear discriminant analysis (LDA) as special cases. By finding directions that maximize correlation, CCA learns representations tied more closely to underlying process generating the the data and can ignore high-variance noise directions. However, for data where acquisition in a given modality is expensive or otherwise limited, CCA may suffer from small sample effects. We propose to use semisupervised Laplacian regularization to utilize data that are present in only one modality. This approach is able to find highly correlated directions that also lie along the data manifold, resulting in a more robust estimate of correlated subspaces. Functional magnetic resonance imaging (fMRI) acquired data are naturally amenable to subspace techniques as data are well aligned. fMRI data of the human brain are a particularly interesting candidate. In this study we implemented various supervised and semi-supervised versions of CCA on human fMRI data, with regression to single and multivariate labels (corresponding to video content subjects viewed during the image acquisition). In each variate condition, the semi-supervised variants of CCA performed better than the supervised variants, including a supervised variant with Laplacian regularization. We additionally analyze the weights learned by the regression in order to infer brain regions that are important to different types of visual processing

MIDAS, prototype Multivariate Interactive Digital Analysis System, Phase 1. Volume 2: Diagnostic system

The MIDAS System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughout. The hardware and software generated in Phase I of the over-all program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating 2 x 105 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. Diagnostic programs used to test MIDAS' operations are presented

Crosstalk Cascades for Frame-rate Pedestrian Detection

Cascades help make sliding window object detection fast, nevertheless, computational demands remain prohibitive for numerous applications. Currently, evaluation of adjacent windows proceeds independently; this is suboptimal as detector responses at nearby locations and scales are correlated. We propose to exploit these correlations by tightly coupling detector evaluation of nearby windows. We introduce two opposing mechanisms: detector excitation of promising neighbors and inhibition of inferior neighbors. By enabling neighboring detectors to communicate, crosstalk cascades achieve major gains (4-30x speedup) over cascades evaluated independently at each image location. Combined with recent advances in fast multi-scale feature computation, for which we provide an optimized implementation, our approach runs at 35-65 fps on 640 x 480 images while attaining state-of-the-art accuracy

Bias-Dependent Generation and Quenching of Defects in Pentacene

We describe a defect in pentacene single crystals that is created by bias stress and persists at room temperature for an hour in the dark but only seconds with 420nm illumination. The defect gives rise to a hole trap at Ev + 0.38eV and causes metastable transport effects at room temperature. Creation and decay rates of the hole trap have a 0.67eV activation energy with a small (108 s-1) prefactor, suggesting that atomic motion plays a key role in the generation and quenching process.Comment: 10 pages, 3 figure

Study of molecular spin-crossover complex Fe(phen)2(NCS)2 thin films

We report on the growth by evaporation under high vacuum of high-quality thin films of Fe(phen)2(NCS)2 (phen=1,10-phenanthroline) that maintain the expected electronic structure down to a thickness of 10 nm and that exhibit a temperature-driven spin transition. We have investigated the current-voltage characteristics of a device based on such films. From the space charge-limited current regime, we deduce a mobility of 6.5x10-6 cm2/V?s that is similar to the low-range mobility measured on the widely studied tris(8-hydroxyquinoline)aluminium organic semiconductor. This work paves the way for multifunctional molecular devices based on spin-crossover complexes

Going beyond defining: Preschool educators\u27 use of knowledge in their pedagogical reasoning about vocabulary instruction

Previous research investigating both the knowledge of early childhood educators and the support for vocabulary development present in early childhood settings has indicated that both educator knowledge and enacted practice are less than optimal, which has grave implications for children\u27s early vocabulary learning and later reading achievement. Further, the nature of the relationship between educators\u27 knowledge and practice is unclear, making it difficult to discern the best path towards improved knowledge, practice, and children\u27s vocabulary outcomes. The purpose of the present study was to add to the existing literature by using stimulated recall interviews and a grounded approach to examine how 10 preschool educators used their knowledge to made decisions about their moment-to-moment instruction in support of children\u27s vocabulary development. Results indicate that educators were thinking in highly context-specific ways about their goals and strategies for supporting vocabulary learning, taking into account important knowledge of their instructional history with children and of the children themselves to inform their decision making in the moment. In addition, they reported thinking about research-based goals and strategies for supporting vocabulary learning that went beyond simply defining words for children. Implications for research and professional development are discussed