An Integrated BiCMOS driver chip for medium power applications

The development of an integrated driver circuit intended for medium power switching applications is presented. The device contains, on one chip, CMOS digital control logic and bipolar drivers, with BiCMOS interface between the two technologies. The custom integrated circuit includes four outputs each capable of switching over 500 mA at 30 volts, at a frequency of up to 1 MHz. The development effort includes the design of the chip with its component circuits and cells. Standard cell CMOS logic gates along with drive and interface circuits were designed and characterized. An appropriate BiCMOS process was developed which utilizes an n-well based 4-micron polysilicon gate MOS technology and vertical NPNs with subcollector and double emitter implants. The chip performance specifications are evaluated with respect to technology requirements and device characteristics, and trade-offs in the design of the chip and the process are examined. Process and device modeling results are compared with the measured data, which show that the objectives of the design are successfully met for the various applications involving resistive, capacitive, and inductive loads

Patch-CNN: Training data-efficient deep learning for high-fidelity diffusion tensor estimation from minimal diffusion protocols

We propose a new method, Patch-CNN, for diffusion tensor (DT) estimation from only six-direction diffusion weighted images (DWI). Deep learning-based methods have been recently proposed for dMRI parameter estimation, using either voxel-wise fully-connected neural networks (FCN) or image-wise convolutional neural networks (CNN). In the acute clinical context -- where pressure of time limits the number of imaged directions to a minimum -- existing approaches either require an infeasible number of training images volumes (image-wise CNNs), or do not estimate the fibre orientations (voxel-wise FCNs) required for tractogram estimation. To overcome these limitations, we propose Patch-CNN, a neural network with a minimal (non-voxel-wise) convolutional kernel (3$\times$3$\times$3). Compared with voxel-wise FCNs, this has the advantage of allowing the network to leverage local anatomical information. Compared with image-wise CNNs, the minimal kernel vastly reduces training data demand. Evaluated against both conventional model fitting and a voxel-wise FCN, Patch-CNN, trained with a single subject is shown to improve the estimation of both scalar dMRI parameters and fibre orientation from six-direction DWIs. The improved fibre orientation estimation is shown to produce improved tractogram.Comment: 12 pages, 6 figure

Spiky oscillations in NF-kB signalling

The NF-kB signalling system is involved in a variety of cellular processes including immune response, inflammation, and apoptosis. Recent experiments have found oscillations in the nuclear-cytoplasmic translocation of the NF-kB transcription factor. How the cell uses the oscillations to differentiate input conditions and send specific signals to downstream genes is an open problem. We shed light on this issue by examining the small core network driving the oscillations, which, we show, is designed to produce periodic spikes in nuclear NF-kB concentration. The oscillations can be used to regulate downstream genes in a variety of ways. In particular, we show that genes to whose operator sites NF-kB binds and dissociates fast can respond very sensitively to changes in the input signal, with effective Hill coefficients in excess of 20.Comment: 11 pages, 13 figure

Gazealytics: A Unified and Flexible Visual Toolkit for Exploratory and Comparative Gaze Analysis

We present a novel, web-based visual eye-tracking analytics tool called Gazealytics. Our open-source toolkit features a unified combination of gaze analytics features that support flexible exploratory analysis, along with annotation of areas of interest (AOI) and filter options based on multiple criteria to visually analyse eye tracking data across time and space. Gazealytics features coordinated views unifying spatiotemporal exploration of fixations and scanpaths for various analytical tasks. A novel matrix representation allows analysis of relationships between such spatial or temporal features. Data can be grouped across samples, user-defined AOIs or time windows of interest (TWIs) to support aggregate or filtered analysis of gaze activity. This approach exceeds the capabilities of existing systems by supporting flexible comparison between and within subjects, hypothesis generation, data analysis and communication of insights. We demonstrate in a walkthrough that Gazealytics supports multiple types of eye tracking datasets and analytical tasks

The SAMI Galaxy Survey: Shocks and Outflows in a normal star-forming galaxy

We demonstrate the feasibility and potential of using large integral field spectroscopic surveys to investigate the prevalence of galactic-scale outflows in the local Universe. Using integral field data from SAMI and the Wide Field Spectrograph, we study the nature of an isolated disk galaxy, SDSS J090005.05+000446.7 (z = 0.05386). In the integral field datasets, the galaxy presents skewed line profiles changing with position in the galaxy. The skewed line profiles are caused by different kinematic components overlapping in the line-of-sight direction. We perform spectral decomposition to separate the line profiles in each spatial pixel as combinations of (1) a narrow kinematic component consistent with HII regions, (2) a broad kinematic component consistent with shock excitation, and (3) an intermediate component consistent with shock excitation and photoionisation mixing. The three kinematic components have distinctly different velocity fields, velocity dispersions, line ratios, and electron densities. We model the line ratios, velocity dispersions, and electron densities with our MAPPINGS IV shock and photoionisation models, and we reach remarkable agreement between the data and the models. The models demonstrate that the different emission line properties are caused by major galactic outflows that introduce shock excitation in addition to photoionisation by star-forming activities. Interstellar shocks embedded in the outflows shock-excite and compress the gas, causing the elevated line ratios, velocity dispersions, and electron densities observed in the broad kinematic component. We argue from energy considerations that, with the lack of a powerful active galactic nucleus, the outflows are likely to be driven by starburst activities. Our results set a benchmark of the type of analysis that can be achieved by the SAMI Galaxy Survey on large numbers of galaxies.Comment: 17 pages, 15 figures. Accepted to MNRAS. References update

Modelling negative linear compressibility in tetragonal beam structures

Copyright © 2012 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Mechanics of Materials. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Mechanics of Materials, Volume 46 (2012), DOI: 10.1016/j.mechmat.2011.12.007Most materials compress axially in all directions when loaded hydrostatically. Contrary to this, some materials have been discovered that exhibit negative linear compressibility and, as such, expand along a specific axis or plane. This paper analyses a fundamental mechanism by using a combination of finite element simulations and analytical derivations to show that negative linear compressibility can be found in a body-centred or face-centred tetragonal network of nodes connected by a network of beams. The magnitude and direction of this behaviour depends on the cross geometry in the network

The SAMI Galaxy Survey: a new method to estimate molecular gas surface densities from star formation rates

Stars form in cold molecular clouds. However, molecular gas is difficult to observe because the most abundant molecule (H_2) lacks a permanent dipole moment. Rotational transitions of CO are often used as a tracer of H_2, but CO is much less abundant and the conversion from CO intensity to H2 mass is often highly uncertain. Here we present a new method for estimating the column density of cold molecular gas (Σ_(gas)) using optical spectroscopy. We utilize the spatially resolved Hα maps of flux and velocity dispersion from the Sydney-AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey. We derive maps of Σ_(gas) by inverting the multi-freefall star formation relation, which connects the star formation rate surface density (Σ_(SFR)) with Σ_(gas) and the turbulent Mach number (M). Based on the measured range of Σ_(SFR) = 0.005-1.5M⊙ yr^(−1) kpc^(−2) and M=18–130, we predict Σ_(gas) = 7–200 M⊙ pc^(−2) in the star-forming regions of our sample of 260 SAMI galaxies. These values are close to previously measured Σ_(gas) obtained directly with unresolved CO observations of similar galaxies at low redshift. We classify each galaxy in our sample as ‘star-forming’ (219) or ‘composite/AGN/shock’ (41), and find that in ‘composite/AGN/shock’ galaxies the average Σ_(SFR), M and Σ_(gas) are enhanced by factors of 2.0, 1.6 and 1.3, respectively, compared to star-forming galaxies. We compare our predictions of Σ_(gas) with those obtained by inverting the Kennicutt–Schmidt relation and find that our new method is a factor of 2 more accurate in predicting Σ_(gas), with an average deviation of 32 per cent from the actual Σ_(gas)

Aggregation kinetics of human mesenchymal stem cells under wave motion

Human mesenchymal stem cells (hMSCs) are a primary candidate in cell therapy and regenerative medicine to treat a wide range of diseases in clinical trials. Recent studies showed that hMSC have innate ability to self-assemble into three-dimensional (3D) aggregates that enhances their therapeutic functions with augmented multi-lineage differentiation potential, migration ability, secretion of anti-inflammatory and angiogenic factors, and resistance to ischemic conditions post-transplantation. To date, many laboratory methods have been developed for hMSC aggregation, including hanging drops, centrifugation with microfabricated surface, cell suspension on a low attachment surface, thermal lifting, and microfluidic technologies. However, these methods have limited scalability and/or poor control in aggregate size, and cannot meet the required production in clinical trials. The objective of current study is to investigate the conditions for the scalable production of hMSC aggregates in non-adherent plates under wave motion. The repeated back and forth wave motion induced by rocking provides mixing of bulk medium under low shear stress that facilitates cell-cell collisions and subsequent aggregation. Our results showed that aggregate size can be controlled by adjusting the combination of rocking angle (3˚, 6˚, and 9˚) and rocking speed (10, 15, and 20 rpm). To quantify the impact of fluid shear stress on aggregation kinetics, simulation of shear stress distribution by COMSOL Multiphysics® showed a time-dependent oscillatory function under different rocking condition. In addition, an inverse correlation between aggregate size and maximum shear stress was observed and that both can be regressed by a two-variable linear regression of rocking angle and rocking speed. In the regression, the coefficient of rocking angle is much higher than that of rocking speed, revealing that rocking angle has a more significant effect than rocking speed on both aggregate size and shear stress. In addition to fluid shear stress, the effects of cell binding molecules, the frequency of cell-cell collision, and the extension of cultivation time on aggregate size distribution were also investigated. Analysis of the therapeutic functional supported that hMSCs derived from engineered aggregates in the wave motion system have enhanced their therapeutic properties compared to those from monolayer culture