COMPUTER-GENERATED HOLOGRAM ETCHED IN GAAS FOR OPTICAL INTERCONNECTION OF VLSI CIRCUITS

By integrating, on a wafer plane, GaAs semiconductor optoelectronic modulators and detectors with computer-generated holograms between then, the potential for in-plane interconnections is proposed. We report the fabrication and characterisation of a binary-phase relief hologram etched in a GaAs wafer using an averaged Fresnel zone plate design to focus light to 2 x 2 spots for array interconnection. Efficiencies of 28% for this design of binary CGH etched in GaAs have been achieved, close to the theoretical maximum

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated by OKTAL-SE.1146Ysciescopu

Successive spin-flop transitions of a Neel-type antiferromagnet Li2MnO3 single crystal with a honeycomb lattice

We have carried out high magnetic field studies of single-crystalline Li2MnO3, a honeycomb lattice antiferromagnet. Its magnetic phase diagram was mapped out using magnetization measurements at applied fields up to 35 T. Our results show that it undergoes two successive meta-magnetic transitions around 9 T fields applied perpendicular to the ab plane (along the c* axis). These phase transitions are completely absent in the magnetization measured with the field applied along the ab plane. In order to understand this magnetic phase diagram, we developed a mean-field model starting from the correct Neel-type magnetic structure, consistent with our single crystal neutron diffraction data at zero field. Our model calculations succeeded in explaining the two meta-magnetic transitions that arise when Li2MnO3 enters two different spin-flop phases from the zero field Neel phase.open1187Nsciescopu

Simulating CO 2 profiles using NIES TM and comparison with HIAPER Pole-to-Pole Observations

We present a study on validation of the National Institute for Environmental Studies Transport Model (NIES TM) by comparing to observed vertical profiles of atmospheric CO2. The model uses a hybrid sigma-isentropic (σ–θ) vertical coordinate that employs both terrain-following and isentropic parts switched smoothly in the stratosphere. The model transport is driven by reanalyzed meteorological fields and designed to simulate seasonal and diurnal cycles, synoptic variations, and spatial distributions of atmospheric chemical constituents in the troposphere. The model simulations were run for biosphere, fossil fuel, air–ocean exchange, biomass burning and inverse correction fluxes of carbon dioxide (CO2) by GOSAT Level 4 product. We compared the NIES TM simulated fluxes with data from the HIAPER Pole-to-Pole Observations (HIPPO) Merged 10 s Meteorology, Atmospheric Chemistry, and Aerosol Data, including HIPPO-1, HIPPO-2 and HIPPO-3 from 128.0° E to −84.0° W, and 87.0° N to −67.2° S

Effects of Rosiglitazone on the Expression of PPAR-&#947 and the Production of IL-6 and IL-8 in Acute Lung Injury Model Using Human Pulmonary Epithelial Cells

Purpose: Peroxisome proliferator-activated receptor (PPAR)-γ ligand is known to repress the expression of pro-inflammatory mediators. However, it is unclear how it affects PPAR-γ expression and the inflammatory response in the human lung. We investigated the effects of rosiglitazone (synthetic PPAR-γ ligand) on the PPAR-γ expression and on the IL-6 and IL-8 production in acute lung injury model using human lung epithelial cells.Methods: A549 and Beas-2B cells were pre-treated with rosiglitazone and/or BADGE (selective PPAR-γ antagonist) and then treated with media control or cytokine mixture including TNF-α, IL-1 β, and IFN-γ. PPAR-γ expression was analyzed in cell lysates by Western blot. IL-6 and IL-8 production was measured in the culture supernatants by ELISA.Results: PPAR-γ expression was identified in all experimental groups except for the control. The cytokine mixture-induced IL-6 and IL-8 production was significantly inhibited by pre-treatment with rosiglitazone (P<0.01). However, this inhibitory effect of rosiglitazone was not reversed by BADGE.Conclusion: These suggest that rosiglitazone induces the PPAR-γ expression and it may inhibit the cytokine mixture-induced IL-6 and IL-8 production through the PPAR-γ independent pathway. The inhibitory mechanisms of rosiglitazone on the cytokine mixture-induced IL-6 and IL-8 production in human alveolar and bronchial epithelial cells remain to be further investigated.Keywords: Rosiglitazone, PPAR-γ, IL-6, IL-8, Acute lung injur

Effects of Rosiglitazone on the Expression of PPAR-&#947 and on the Production of IL-6 and IL-8 in Acute Lung Injury Model Using Human Pulmonary Epithelial Cells

Purpose: Peroxisome proliferator-activated receptor (PPAR)-γ ligand is known to repress the expression of pro-inflammatory mediators. However, it is unclear how it affects PPAR-γ expression and the inflammatory response in the human lung. We investigated the effects of rosiglitazone (synthetic PPAR-γ ligand) on the PPAR-γ expression and on the IL-6 and IL-8 production in acute lung injury model using human lung epithelial cells.Methods: A549 and Beas-2B cells were pre-treated with rosiglitazone and/or BADGE (selective PPAR-γ antagonist) and then treated with media control or cytokine mixture including TNF-α, IL-1β, and IFN-γ. PPAR-γ expression was analyzed in cell lysates by Western blot. IL-6 and IL-8 production was measured in the culture supernatants by ELISA.Results: PPAR-γ expression was identified in all experimental groups except for the control. The cytokine mixture-induced IL-6 and IL-8 production was significantly inhibited by pre-treatment with rosiglitazone (P<0.01). However, this inhibitory effect of rosiglitazone was not reversed by BADGE. Conclusion: These suggest that rosiglitazone induces the PPAR-γ expression and it may inhibit the cytokine mixture-induced IL-6 and IL-8 production through the PPAR-γ independent pathway. The inhibitory mechanisms of rosiglitazone on the cytokine mixture-induced IL-6 and IL-8 production in human alveolar, and bronchial epithelial cells remain to be further investigated.Keywords: Rosiglitazone, PPAR-γ expression, IL-6, IL-8, Acute lung injur

Biological potential of polyethylene glycol (Peg)-functionalized graphene quantum dots in in vitro neural stem/progenitor cells

Stem cell therapy is one of the novel and prospective fields. The ability of stem cells to differentiate into different lineages makes them attractive candidates for several therapies. It is essential to understand the cell fate, distribution, and function of transplanted cells in the local microenvironment before their applications. Therefore, it is necessary to develop an accurate and reliable labeling method of stem cells for imaging techniques to track their translocation after transplantation. The graphitic quantum dots (GQDs) are selected among various stem cell labeling and tracking strategies which have high photoluminescence ability, photostability, relatively low cytotoxicity, tunable surface functional groups, and delivering capacity. Since GQDs interact easily with the cell and interfere with cell behavior through surface functional groups, an appropriate surface modification needs to be considered to get close to the ideal labeling nanoprobes. In this study, polyethylene glycol (PEG) is used to improve biocompatibility while simultaneously maintaining the photoluminescent potentials of GQDs. The biochemically inert PEG successfully covered the surface of GQDs. The PEG-GQDs composites show adequate bioimaging capabilities when internalized into neural stem/progenitor cells (NSPCs). Furthermore, the bio-inertness of the PEG-GQDs is confirmed. Herein, we introduce the PEG-GQDs as a valuable tool for stem cell labeling and tracking for biomedical therapies in the field of neural regeneration