Conductance modulation in spin field-efect transistors under finite bias voltages

The conductance modulations in spin field-effect transistors under finite bias voltages were studied. It was shown that when a finite bias voltage is applied between two terminals of a spin field-effect transistor, the spin precession states of injected spin-polarized electrons in the semiconductor channel of the device will depend not only the gate-voltage controlled Rashba spin-orbit coupling but also depend on the bias voltage and, hence, the conductance modulation in the device due to Rashba spin-orbit coupling may also depend sensitively on the bias voltage.Comment: 7 pages, 3 figures, to appear in Physical Review B, (April, 2004

Quantitative proteomic analysis of sphere-forming stem-like oral cancer cells.

IntroductionThe purpose of this study is to identify target proteins that may play important functional roles in oral cancer stem-like cells (CSCs) using mass spectrometry-based quantitative proteomics.MethodsSphere-formation assays were performed on highly invasive UM1 and lowly invasive UM2 oral cancer cell lines, which were derived from the same tongue squamous cell carcinoma, to enrich CSCs. Quantitative proteomic analysis of CSC-like and non-CSC UM1 cells was carried out using tandem mass tagging and two-dimensional liquid chromatography with Orbitrap mass spectrometry.ResultsCSC-like cancer cells were found to be present in the highly invasive UM1 cell line but absent in the lowly invasive UM2 cell line. Stem cell markers SOX2, OCT4, SOX9 and CD44 were up-regulated, whereas HIF-1 alpha and PGK-1 were down-regulated in CSC-like UM1 cells versus non-CSC UM1 cells. Quantitative proteomic analysis indicated that many proteins in cell cycle, metabolism, G protein signal transduction, translational elongation, development, and RNA splicing pathways were differentially expressed between the two cell phenotypes. Both CREB-1-binding protein (CBP) and phosphorylated CREB-1 were found to be significantly over-expressed in CSC-like UM1 cells.ConclusionsCSC-like cells can be enriched from the highly invasive UM1 oral cancer cell line but not from the lowly invasive UM2 oral cancer cell line. There are significant proteomic alterations between CSC-like and non-CSC UM1 cells. In particular, CBP and phosphorylated CREB-1 were significantly up-regulated in CSC-like UM1 cells versus non-CSC UM1 cells, suggesting that the CREB pathway is activated in the CSC-like cells

Gain-constrained recursive filtering with stochastic nonlinearities and probabilistic sensor delays

This is the post-print of the Article. The official published version can be accessed from the link below - Copyright @ 2013 IEEE.This paper is concerned with the gain-constrained recursive filtering problem for a class of time-varying nonlinear stochastic systems with probabilistic sensor delays and correlated noises. The stochastic nonlinearities are described by statistical means that cover the multiplicative stochastic disturbances as a special case. The phenomenon of probabilistic sensor delays is modeled by introducing a diagonal matrix composed of Bernoulli distributed random variables taking values of 1 or 0, which means that the sensors may experience randomly occurring delays with individual delay characteristics. The process noise is finite-step autocorrelated. The purpose of the addressed gain-constrained filtering problem is to design a filter such that, for all probabilistic sensor delays, stochastic nonlinearities, gain constraint as well as correlated noises, the cost function concerning the filtering error is minimized at each sampling instant, where the filter gain satisfies a certain equality constraint. A new recursive filtering algorithm is developed that ensures both the local optimality and the unbiasedness of the designed filter at each sampling instant which achieving the pre-specified filter gain constraint. A simulation example is provided to illustrate the effectiveness of the proposed filter design approach.This work was supported in part by the National Natural Science Foundation of China by Grants 61273156, 61028008, 60825303, 61104125, and 11271103, National 973 Project by Grant 2009CB320600, the Fok Ying Tung Education Fund by Grant 111064, the Special Fund for the Author of National Excellent Doctoral Dissertation of China by Grant 2007B4, the State Key Laboratory of Integrated Automation for the Process Industry (Northeastern University) of China, the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. by Grant GR/S27658/01, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany