c-Axis longitudinal magnetoresistance of the electron-doped superconductor Pr1.85Ce0.15CuO4

We report c-axis resistivity and longitudinal magnetoresistance measurements of superconducting Pr1.85Ce0.15CuO4 single crystals. In the temperature range 13K<T<32K, a negative magnetoresistance is observed at fields just above Hc2. Our studies suggest that this negative magnetoresistance is caused by superconducting fluctuations. At lower temperatures (T<13K), a different magnetoresistance behavior and a resistivity upturn are observed, whose origin is still unknown.Comment: Accepted for publication in Phys. Rev.

Alternative approach to computing transport coefficients: application to conductivity and Hall coefficient of hydrogenated amorphous silicon

We introduce a theoretical framework for computing transport coefficients for complex materials. As a first example, we resolve long-standing inconsistencies between experiment and theory pertaining to the conductivity and Hall mobility for amorphous silicon and show that the Hall sign anomaly is a consequence of localized states. Next, we compute the AC conductivity of amorphous polyanaline. The formalism is applicable to complex materials involving defects and band-tail states originating from static topological disorder and extended states. The method may be readily integrated with current \textit{ab initio} methods.Comment: 4 pages, 2 figures, submitted to Phys. Rev. Let

Topological Gauge Structure and Phase Diagram for Weakly Doped Antiferromagnets

We show that the topological gauge structure in the phase string theory of the {\rm t-J} model gives rise to a global phase diagram of antiferromagnetic (AF) and superconducting (SC) phases in a weakly doped regime. Dual confinement and deconfinement of holons and spinons play essential roles here, with a quantum critical point at a doping concentration $x_c\simeq 0.043$. The complex experimental phase diagram at low doping is well described within such a framework.Comment: 4 pages, 2 figures, modified version, to appear in Phys. Rev. Let

Spin Current and Shot Noise in Single-Molecule Quantum Dots with a Phonon Mode

In this paper we investigate the spin-current and its shot-noise spectrum in a single-molecule quantum dot coupled with a local phonon mode. We pay special attention on the effect of phonon on the quantum transport property. The spin-polarization dependent current is generated by a rotating magnetic filed applied in the quantum dot. Our results show the remarkable influence of phonon mode on the zero-frequency shot noise. The electron-phonon interaction leads to sideband peaks which are located exactly on the integer number of the phonon frequency and moreover the peak-height is sensitive to the electron-phonon coupling.Comment: 17 pages,5 figure

Temporal variability in composition and fluxes of Yellow River particulate organic matter

This study examines temporal variations of the abundance and carbon isotopic characteristics of particulate organic carbon (POC) and specific-source compounds in the context of hydrological variability in the Yellow River. The content and bulk carbon isotopic characteristics (13C and 14C) of POC were relatively uniform over the hydrologic (seasonal) cycle. We attribute these temporally invariant geochemical characteristics to the dominant contribution of loess material to the suspended particulate matter (SPM). In contrast, molecular-level signals revealed that hydrologic conditions exert a significant influence on the proportional contributions of petrogenic and especially fresh plant-derived OC, while pre-aged soil OC is mobilized via deeper erosion processes (e.g., gully erosion, mudslides) and is independent of hydrodynamics and surface runoff. A coupled biomarker-isotope mixing model was applied to estimate the time-varying supply of contemporary/modern biomass, pre-aged soil, and fossil OC components to Chinese marginal seas from the Yellow River. We found that natural (e.g., precipitation) and human-induced (e.g., water and sediment regulation) variations in hydrological regime strongly influence the flux with the magnitude of the corresponding annual fluxes of POC ranging between 0.343 ± 0.122 Mt yr−1 and 0.581 ± 0.213 Mt yr−1, but less strongly infleunce proportions of the different OC constituents. Inter-annual differences in pre-aged soil and fossil OC fluxes imply that extreme climate events (e.g., floods) modulate the exhumation and export of old carbon to the ocean, but the OC homogeneity in the pre-aged mineral soil-dominated watersheds facilitates robust predictions in terms of OC transport dynamics in the past (sediment cores) and in the future

Photopion reactions on deltas preexisting in nuclei

Reactions A(\gamma, pi^+p) are considered to proceed through the formation of pion-proton pairs on delta constituents in nuclei. We develop the nonrelativistic operator for \Delta^{++}(\gamma, pi^+)p process in an arbitrary frame. The calculated cross section for C12(\gamma, \pi^+p) reaction is compared to the existing experimental data.Comment: 8 pages, 3 figure

Fucosyltransferase 1 and 2 play pivotal roles in breast cancer cells.

FUT1 and FUT2 encode alpha 1, 2-fucosyltransferases which catalyze the addition of alpha 1, 2-linked fucose to glycans. Glycan products of FUT1 and FUT2, such as Globo H and Lewis Y, are highly expressed on malignant tissues, including breast cancer. Herein, we investigated the roles of FUT1 and FUT2 in breast cancer. Silencing of FUT1 or FUT2 by shRNAs inhibited cell proliferation in vitro and tumorigenicity in mice. This was associated with diminished properties of cancer stem cell (CSC), including mammosphere formation and CSC marker both in vitro and in xenografts. Silencing of FUT2, but not FUT1, significantly changed the cuboidal morphology to dense clusters of small and round cells with reduced adhesion to polystyrene and extracellular matrix, including laminin, fibronectin and collagen. Silencing of FUT1 or FUT2 suppressed cell migration in wound healing assay, whereas FUT1 and FUT2 overexpression increased cell migration and invasion in vitro and metastasis of breast cancer in vivo. A decrease in mesenchymal like markers such as fibronectin, vimentin, and twist, along with increased epithelial like marker, E-cadherin, was observed upon FUT1/2 knockdown, while the opposite was noted by overexpression of FUT1 or FUT2. As expected, FUT1 or FUT2 knockdown reduced Globo H, whereas FUT1 or FUT2 overexpression showed contrary effects. Exogenous addition of Globo H-ceramide reversed the suppression of cell migration by FUT1 knockdown but not the inhibition of cell adhesion by FUT2 silencing, suggesting that at least part of the effects of FUT1/2 knockdown were mediated by Globo H. Our results imply that FUT1 and FUT2 play important roles in regulating growth, adhesion, migration and CSC properties of breast cancer, and may serve as therapeutic targets for breast cancer

Mining association language patterns using a distributional semantic model for negative life event classification

AbstractPurposeNegative life events, such as the death of a family member, an argument with a spouse or the loss of a job, play an important role in triggering depressive episodes. Therefore, it is worthwhile to develop psychiatric services that can automatically identify such events. This study describes the use of association language patterns, i.e., meaningful combinations of words (e.g., <loss, job>), as features to classify sentences with negative life events into predefined categories (e.g., Family, Love, Work).MethodsThis study proposes a framework that combines a supervised data mining algorithm and an unsupervised distributional semantic model to discover association language patterns. The data mining algorithm, called association rule mining, was used to generate a set of seed patterns by incrementally associating frequently co-occurring words from a small corpus of sentences labeled with negative life events. The distributional semantic model was then used to discover more patterns similar to the seed patterns from a large, unlabeled web corpus.ResultsThe experimental results showed that association language patterns were significant features for negative life event classification. Additionally, the unsupervised distributional semantic model was not only able to improve the level of performance but also to reduce the reliance of the classification process on the availability of a large, labeled corpus