4,796 research outputs found

    Lineage Differentiation Program of Invariant Natural Killer T Cells

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    Invariant natural killer T (iNKT) cells are innate T cells restricted by CD1d molecules. They are positively selected in the thymic cortex and migrate to the medullary area, in which they differentiate into 3 different lineages. Promyelocytic leukemia zinc finger (PLZF) modulates this process, and PLZFhigh, PLZFintermediate, and PLZFlow iNKT cells are designated as NKT2, NKT17, and NKT1 cells, respectively. Analogous to conventional helper CD4 T cells, each subset expresses distinct combinations of transcription factors and produces different cytokines. In lymphoid organs, iNKT subsets have unique localizations, which determine their cytokine responses upon antigenic challenge. The lineage differentiation programs of iNKT cells are differentially regulated in various mice strains in a cell-intrinsic manner, and BALB/c mice contain a high frequency of NKT2 cells. In the thymic medulla, steady state IL-4 from NKT2 cells directly conditions CD8 T cells to become memory-like cells expressing Eomesodermin, which function as premade memory effectors. The genetic signature of iNKT cells is more similar to that of γδ T cells and innate lymphoid cells (ILCs) than of conventional helper T cells, suggesting that ILCs and innate T cells share common developmental programs.115Ysciescopuskc

    Functionalized Graphene Sheet / Polyurethane Nanocomposites

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    Double resonance of Raman transitions in a degenerate Fermi gas

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    We measure momentum-resolved Raman spectra of a spin-polarized degenerate Fermi gas of 173^{173}Yb atoms for a wide range of magnetic fields, where the atoms are irradiated by a pair of counterpropagating Raman laser beams as in the conventional spin-orbit coupling scheme. Double resonance of first- and second-order Raman transitions occurs at a certain magnetic field and the spectrum exhibits a doublet splitting for high laser intensities. The measured spectral splitting is quantitatively accounted for by the Autler-Townes effect. We show that our measurement results are consistent with the spinful band structure of a Fermi gas in the spatially oscillating effective magnetic field generated by the Raman laser fields.Comment: 7 pages, 6 figure

    Robust Digital Predistortion in Saturation Region of Power Amplifiers

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    This paper proposes a digital predistortion (DPD) technique to improve linearization performance when the power amplifier (PA) is driven near the saturation region. The PA is a non-linear device in general, and the nonlinear distortion becomes severer as the output power increases. However, the PA’s power efficiency increases as the PA output power increases. The nonlinearity results in spectral regrowth, which leads to adjacent channel interference, and degrades the transmit signal quality. According to our simulation, the linearization performance of DPD is degraded abruptly when the PA operates in its saturation region. To relieve this problem, we propose an improved DPD technique. The proposed technique performs on/off control of the adaptive algorithm based on the magnitude of the transmitted signal. Specifically, the adaptation normally works for small and medium signals while it stops for large signals. Therefore, harmful coefficient updates by saturated signals can be avoided. A computer simulation shows that the proposed method can improve the linearization performance compared with the conventional DPD method in highly driven PAs

    A Polynomial Digital Pre-Distortion Technique Based on Iterative Architecture

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    A digital predistortion (DPD) technique based on an iterative adaptation structure is proposed for linearizing power amplifiers (PAs). To obtain proper DPD parameters, a feedback path that converts the PA’s output to a baseband signal is required, and memory is also needed to store the baseband feedback signals. DPD parameters are usually found by an adaptive algorithm by using the transmitted signals and the corresponding feedback signals. However, for the adaptive algorithm to converge to a reliable solution, long feedback samples are required, which increases hardware complexity and cost. Considering that the convergence time of the adaptive algorithm highly depends on the initial condition, we propose a DPD technique that requires relatively shorter feedback samples. Specifically, the proposed DPD iteratively utilizes the short feedback samples in memory while keeping and using the DPD parameters found at the former iteration as the initial condition at the next iteration. Computer simulation shows that the proposed technique performs better than the conventional technique, as the former requires much shorter feedback memory than the latter
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