Enzyme-free glucose biosensor based on low density CNT forest grown directly on a Si/SiO2 substrate

A highly sensitive nonenzymatic amperometric glucose sensor was fabricated by using Ni nanoparticles homogeneously dispersed within and on the top of a vertically aligned CNT forest (CNT/Ni nanocomposite sensor), which was directly grown on a Si/SiO2 substrate. The surface morphology and elemental analysis were characterized using scanning electron microscopy and energy dispersive spectroscopy, respectively. Cyclic voltammetry and chronoamperometry were used to evaluate the catalytic activities of CNT/Ni electrode. The CNT/Ni nanocomposite sensor exhibited a great enhancement of anodic peak current after adding 5 mM glucose in alkaline solution. The sensor can also be applied to the quantification of glucose content with a linear range covering from 5 μM to 7 mM, a high sensitivity of 1433 μA mM-1 cm-2, and a low detection limit of 2 μM. The CNT/Ni nanocomposite sensor exhibits good reproducibility and long-term stability, moreover, it was also relatively insensitive to commonly interfering species, such as uric acid, ascorbic acid, acetaminophen, sucrose and d-fructose. © 2013 Elsevier B.V.

Model-based influences on humans' choices and striatal prediction errors.

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.

High contrast holograms using nanotube forest

Nanotube forest behaves as highly absorbent material when they are randomly placed in sub-wavelength scales. Furthermore, it is possible to create diffractive structures when these bulks are patterned in a substrate. Here, we introduce an alternative to fabricate intensity holograms by patterning fringes of nanotube forest on a substrate. The result is an efficient intensity hologram that is not restricted to sub-wavelength patterning. Both the theoretical and experimental analysis was performed with good agreement. The produced holograms show a uniform behaviour throughout the visible spectra. © 2013 AIP Publishing LLC.

Unconstrained monocular 3D human pose estimation by action detection and cross-modality regression forest

This work addresses the challenging problem of unconstrained 3D human pose estimation (HPE) from a novel perspective. Existing approaches struggle to operate in realistic applications, mainly due to their scene-dependent priors, such as background segmentation and multi-camera network, which restrict their use in unconstrained environments. We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video. Action detection offers spatiotemporal priors to 3D human pose estimation by both recognising and localising actions in space-time. Instead of holistic features, e.g. silhouettes, we leverage the flexibility of deformable part model to detect 2D body parts as a feature to estimate 3D poses. A new unconstrained pose dataset has been collected to justify the feasibility of our method, which demonstrated promising results, significantly outperforming the relevant state-of-the-arts. © 2013 IEEE.

The Random Forest Kernel and other kernels for big data from random partitions

We present Random Partition Kernels, a new class of kernels derived by demonstrating a natural connection between random partitions of objects and kernels between those objects. We show how the construction can be used to create kernels from methods that would not normally be viewed as random partitions, such as Random Forest. To demonstrate the potential of this method, we propose two new kernels, the Random Forest Kernel and the Fast Cluster Kernel, and show that these kernels consistently outperform standard kernels on problems involving real-world datasets. Finally, we show how the form of these kernels lend themselves to a natural approximation that is appropriate for certain big data problems, allowing $O(N)$ inference in methods such as Gaussian Processes, Support Vector Machines and Kernel PCA.

Fiber Dispersion and Nonlinearity Influences on Transmissions of AM and FM Data Modulation Signals in Radio-Over-Fiber System

Transmission properties of data amplitude modulation (AM) and frequency modulation (FM) in radio-over-fiber (RoF) system are studied numerically. The influences of fiber dispersion and nonlinearity on different microwave modulation schemes, including double side band (DSB), single side band (SSB) and optical carrier suppression (OCS), are investigated and compared. The power penalties at the base station (BS) and the eye opening penalties of the recovered data at the end users are both calculated and analyzed. Numerical simulation results reveal that the power penalty of FM can be drastically decreased due to the larger modulation depth it can achieve than that of AM. The local spectrum broadening around subcarrier microwave frequency of AM due to fiber nonlinearity can also be eliminated with FM. It is demonstrated for the first time that the eye openings of the FM recovered data can be controlled by its modulation depths and the coding formats. Negative voltage encoding format was used to further decrease the RF frequency thus increase the fluctuation period considering their inverse relationship.

Intraband relaxation and its influences on quantum dot lasers

A comprehensive two-level numerical model is developed to describe carrier distribution in a quantum-dot laser. Light-emission spectra with different intraband relaxation rates (2ps, 7.5ps and 20ps) are calculated and analysed to investigate the influence of relaxation rates on performance of the quantum-dot laser. The results indicate that fast intraband relaxation favours not only the ground state single mode operation but also the higher injection efficiency.

Influences of As flux on the lattice constants, magnetic and transport properties of (Ga, Mn)As epilayers

A series of (Ga, Mn)As epilayers have been prepared on semi-insulating GaAs (001) substrates at 230 degrees C by molecular-beam epitaxy under fixed temperatures of Ga and Mn cells and varied temperatures of the As cell. By systematically studying the lattice constants, magnetic and magneto-transport properties in a self-consistent manner, we find that the concentration of As antisites monotonically increases with increasing As flux, while the concentration of interstitial Mn defects decreases with it. Such a trend sensitively affects the properties of (Ga, Mn)As epilayers. (c) 2006 Elsevier Ltd. All rights reserved.

Influences of quantum noises on direct-modulated properties of 1.3-mu m InGaAsP/InP laser diodes

Due to the zero dispersion point at 1.3-mu m in optical fibres, 1.3-mu m InGaAsP/InP laser diodes have become main light sources in fibre communication systems recently. In fluences of quantum noises on direct-modulated properties of single-mode 1.3-mu m InGaAsP/InP laser diodes are investigated in this article. Considering the carrier and photon noises and the cross-correlation between the two noises, the power spectrum of the photon density and the signal-to-noise ratio (SNR) of the direct-modulated single-mode laser system are calculated using the linear approximation method. We find that the stochastic resonance (SR) always appears in the dependence of the SNR on the bias current density, and is strongly affected by the cross-correlation coeffcient between the carrier and photon noises, the frequency of modulation signal, and the photon lifetime in the laser cavity. Hence, it is promising to use the SR mechanism to enhance the SNR of direct-modulated InGaAsP/InP laser diodes and improve the quality of optical fibre communication systems.

Influences of reactor pressure of GaN buffer layers on morphological evolution of GaN grown by MOCVD

The morphological evolution of GaN thin films grown on sapphire by metalorganic chemical vapor deposition was demonstrated to depend strongly on the growth pressure of GaN nucleation layer (NL). For the commonly used two-step growth process, a change in deposition pressure of NL greatly influences the growth mode and morphological evolution of the following GaN epitaxy. By means of atomic force microscopy and scanning electron microscope, it is shown that the initial density and the spacing of nucleation sites on the NL and subsequently the growth mode of FIT GaN epilayer may be directly controlled by tailoring the initial low temperature NL growth pressure. A mode is proposed to explain the TD reduction for NL grown at relatively high reactor pressure. (C) 2003 Elsevier B.V. All rights reserved.

Influences of initial nitridation process on the optical and structural characterization of GaN layer grown on sapphire (0001) by metalorganic chemical vapor deposition

In this paper. we investigate the influences of the initial nitridation of sapphire substrates on the optical and structural characterizations in GaN films. Two GaN samples with and without 3 min nitridation process were investigated by photoluminescence (PL) spectroscopy in the temperature range of 12-300 K and double-crystal X-ray diffraction (XRD). In the 12 K PL spectra of the GaN sample without nitridation, four dominant peaks at 3.476, 3.409 3.362 and 3.308 eV were observed, which were assigned to donor bound exciton, excitons bound to stacking faults and extended structural defects. In the sample with nitridation, three peaks at 3.453, 3.365. and 3.308 eV were observed at 12 K, no peak related to stacking faults. XRD results at different reflections showed that there are more stacking faults in the samples without nitridation.

Influences of initial buffer layer deposition on electrical and optical properties in cubic GaN grown on GaAs(100) by metalorganic chemical vapor deposition

We present some results on the effect of initial buffer layer on the crystalline quality of Cubic GaN epitaxial layers grown on GaAs(100) substrates by metalorganic chemical vapor deposition. Photoluminescence and Hall measurements were performed to characterize the electrical and optical properties of cubic GaN. The crystalline quality subsequently grown high-temperature (HT) cubic GaN layers strongly depended on thermal effects during the temperature ramping process after low temperature (LT) growth of the buffer layers. Atomic force microscope (AFM) and reflection high-energy electron diffraction (RHEED) were employed to investigate this temperature ramping process. Furthermore, the role of thermal treatment during the temperature ramping process was identified. Using the optimum buffer layer, the full width at half maxim (FWHM) at room temperature photoluminescence 5.6 nm was achieved. To our knowledge, this is the best FWHM value for cubic GaN to date. The background carrier concentration was as low as 3 x 10(13) cm(-3). (C) 2000 Published by Elsevier Science S.A. All rights reserved.