Ormosils-PVA BOD sensing film based on oxygen luminescence quenching

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Facile Synthesis of High Quality Graphene Nanoribbons

Graphene nanoribbons have attracted attention for their novel electronic and spin transport properties1-6, and because nanoribbons less than 10 nm wide have a band gap that can be used to make field effect transistors. However, producing nanoribbons of very high quality, or in high volumes, remains a challenge. Here, we show that pristine few-layer nanoribbons can be produced by unzipping mildly gas-phase oxidized multiwalled carbon nanotube using mechanical sonication in an organic solvent. The nanoribbons exhibit very high quality, with smooth edges (as seen by high-resolution transmission electron microscopy), low ratios of disorder to graphitic Raman bands, and the highest electrical conductance and mobility reported to date (up to 5e2/h and 1500 cm2/Vs for ribbons 10-20 nm in width). Further, at low temperature, the nanoribbons exhibit phase coherent transport and Fabry-Perot interference, suggesting minimal defects and edge roughness. The yield of nanoribbons was ~2% of the starting raw nanotube soot material, which was significantly higher than previous methods capable of producing high quality narrow nanoribbons1. The relatively high yield synthesis of pristine graphene nanoribbons will make these materials easily accessible for a wide range of fundamental and practical applications.Comment: Nature Nanotechnology in pres

microRNA-29b prevents liver fibrosis by attenuating hepatic stellate cell activation and inducing apoptosis through targeting PI3K/AKT pathway

microRNA-29b (miR-29b) is known to be associated with TGF-β-mediated fibrosis, but the mechanistic action of miR-29b in liver fibrosis remains unclear and is warranted for investigation. We found that miR-29b was significantly downregulated in human and mice fibrotic liver tissues and in primary activated HSCs. miR-29b downregulation was directly mediated by Smad3 through binding to the promoter of miR-29b in hepatic stellate cell (HSC) line LX1, whilst miR-29b could in turn suppress Smad3 expression. miR-29b transduction in the liver of mice prevented CCl4 induced-fibrogenesis, concomitant with decreased expression of α-SMA, collagen I and TIMP-1. Ectopic expression of miR-29b in activated HSCs (LX-1, HSC-T6) inhibited cell viability and colony formation, and caused cell cycle arrest in G1 phase by downregulating cyclin D1 and p21cip1. Further, miR-29b induced apoptosis in HSCs mediated by caspase-9 and PARP. miR-29b inhibited its downstream effectors of PIK3R1 and AKT3 through direct targeting their 3'UTR regions. Moreover, knockdown of PIK3R1 or AKT3 suppressed α-SMA and collagen I and induced apoptosis in both HSCs and in mice. In conclusion, miR-29b prevents liver fibrogenesis by inhibiting HSC activation and inducing HSC apoptosis through inhibiting PI3K/AKT pathway. These results provide novel mechanistic insights for the anti-fibrotic effect of miR-29b.published_or_final_versio

Decentralized Estimation over Orthogonal Multiple-access Fading Channels in Wireless Sensor Networks - Optimal and Suboptimal Estimators

Optimal and suboptimal decentralized estimators in wireless sensor networks (WSNs) over orthogonal multiple-access fading channels are studied in this paper. Considering multiple-bit quantization before digital transmission, we develop maximum likelihood estimators (MLEs) with both known and unknown channel state information (CSI). When training symbols are available, we derive a MLE that is a special case of the MLE with unknown CSI. It implicitly uses the training symbols to estimate the channel coefficients and exploits the estimated CSI in an optimal way. To reduce the computational complexity, we propose suboptimal estimators. These estimators exploit both signal and data level redundant information to improve the estimation performance. The proposed MLEs reduce to traditional fusion based or diversity based estimators when communications or observations are perfect. By introducing a general message function, the proposed estimators can be applied when various analog or digital transmission schemes are used. The simulations show that the estimators using digital communications with multiple-bit quantization outperform the estimator using analog-and-forwarding transmission in fading channels. When considering the total bandwidth and energy constraints, the MLE using multiple-bit quantization is superior to that using binary quantization at medium and high observation signal-to-noise ratio levels

Critical behavior at the dynamic Mott transition

RevTex4, 9 pages, 5 figuresRevTex4, 9 pages, 5 figuresWe investigate magnetoresistance of a square array of superconducting islands placed on a normal metal, which offers a unique tunable laboratory for realizing and exploring quantum many-body systems and their dynamics. A vortex Mott insulator where magnetic field-induced vortices are frozen in the dimples of the egg crate potential by their strong repulsion interaction is discovered. We find an insulator-to-metal transition driven by the applied electric current and determine critical exponents that exhibit striking similarity with the common thermodynamic liquid-gas transition. A simple and straightforward quantum mechanical picture is proposed that describes both tunneling dynamics in the deep insulating state and the observed scaling behavior in the vicinity of the critical point. Our findings offer a comprehensive description of dynamic Mott critical behavior and establish a deep connection between equilibrium and nonequilibrium phase transitions

Smad3 promotes cancer progression by inhibiting E4BP4-mediated NK cell development

published_or_final_versio

Feature selection for chemical sensor arrays using mutual information

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

Dry-air-stable lithium silicide-lithium oxide core-shell nanoparticles as high-capacity prelithiation reagents

Rapid progress has been made in realizing battery electrode materials with high capacity and long-term cyclability in the past decade. However, low first-cycle Coulombic efficiency as a result of the formation of a solid electrolyte interphase and Li trapping at the anodes, remains unresolved. Here we report LixSi-Li2O core-shell nanoparticles as an excellent prelithiation reagent with high specific capacity to compensate the first-cycle capacity loss. These nanoparticles are produced via a one-step thermal alloying process. LixSi-Li2O core-shell nanoparticles are processible in a slurry and exhibit high capacity under dry-air conditions with the protection of a Li2O passivation shell, indicating that these nanoparticles are potentially compatible with industrial battery fabrication processes. Both Si and graphite anodes are successfully prelithiated with these nanoparticles to achieve high first-cycle Coulombic efficiencies of 94% to 4100%. The LixSi-Li2O core-shell nanoparticles enable the practical implementation of high-performance electrode materials in lithium-ion batteries.open6

Minimum Sensitivity Based Robust Beamforming with Eigenspace Decomposition

An enhanced eigenspace-based beamformer (ESB) derived using the minimum sensitivity criterion is proposed with significantly improved robustness against steering vector errors. The sensitivity function is defined as the squared norm of the appropriately scaled weight vector and since the sensitivity function of an array to perturbations becomes very large in the presence of steering vector errors, it can be used to find the best projection for the ESB, irrespective of the distribution of additive noises. As demonstrated by simulation results, the proposed method has a better performance than the classic ESBs and the previously proposed uncertainty set based approach