Spatial imaging of the spin Hall effect and current-induced polarization in two-dimensional electron gases

Spin-orbit coupling in semiconductors relates the spin of an electron to its momentum and provides a pathway for electrically initializing and manipulating electron spins for applications in spintronics and spin-based quantum information processing. This coupling can be regulated with quantum confinement in semiconductor heterostructures through band structure engineering. Here we investigate the spin Hall effect and current-induced spin polarization in a two-dimensional electron gas confined in (110) AlGaAs quantum wells using Kerr rotation microscopy. In contrast to previous measurements, the spin Hall profile exhibits complex structure, and the current-induced spin polarization is out-of-plane. The experiments map the strong dependence of the current-induced spin polarization to the crystal axis along which the electric field is applied, reflecting the anisotropy of the spin-orbit interaction. These results reveal opportunities for tuning a spin source using quantum confinement and device engineering in non-magnetic materials.Comment: Accepted for publication (2005

New perspectives on the ecology of tree structure and tree communities through terrestrial laser scanning

Terrestrial laser scanning (TLS) opens up the possibility of describing the three-dimensional structures of trees in natural environments with unprecedented detail and accuracy. It is already being extensively applied to describe how ecosystem biomass and structure vary between sites, but can also facilitate major advances in developing and testing mechanistic theories of tree form and forest structure, thereby enabling us to understand why trees and forests have the biomass and three-dimensional structure they do. Here we focus on the ecological challenges and benefits of understanding tree form, and highlight some advances related to capturing and describing tree shape that are becoming possible with the advent of TLS. We present examples of ongoing work that applies, or could potentially apply, new TLS measurements to better understand the constraints on optimization of tree form. Theories of resource distribution networks, such as metabolic scaling theory, can be tested and further refined. TLS can also provide new approaches to the scaling of woody surface area and crown area, and thereby better quantify the metabolism of trees. Finally, we demonstrate how we can develop a more mechanistic understanding of the effects of avoidance of wind risk on tree form and maximum size. Over the next few years, TLS promises to deliver both major empirical and conceptual advances in the quantitative understanding of trees and tree-dominated ecosystems, leading to advances in understanding the ecology of why trees and ecosystems look and grow the way they do

Which population level environmental factors are associated with asthma, rhinoconjunctivitis and eczema? Review of the ecological analyses of ISAAC Phase One.

The International Study of Asthma and Allergies in Childhood (ISAAC) Phase One showed large worldwide variations in the prevalence of symptoms of asthma, rhinoconjunctivitis and eczema, up to 10 to 20 fold between countries. Ecological analyses were undertaken with ISAAC Phase One data to explore factors that may have contributed to these variations, and are summarised and reviewed here.In ISAAC Phase One the prevalence of symptoms in the past 12 months of asthma, rhinoconjunctivitis and eczema were estimated from studies in 463,801 children aged 13 - 14 years in 155 centres in 56 countries, and in 257,800 children aged 6-7 years in 91 centres in 38 countries. Ecological analyses were undertaken between symptom prevalence and the following: Gross National Product per capita (GNP), food intake, immunisation rates, tuberculosis notifications, climatic factors, tobacco consumption, pollen, antibiotic sales, paracetamol sales, and outdoor air pollution.Symptom prevalence of all three conditions was positively associated with GNP, trans fatty acids, paracetamol, and women smoking, and inversely associated with food of plant origin, pollen, immunisations, tuberculosis notifications, air pollution, and men smoking. The magnitude of these associations was small, but consistent in direction between conditions. There were mixed associations of climate and antibiotic sales with symptom prevalence.The potential causality of these associations warrant further investigation. Factors which prevent the development of these conditions, or where there is an absence of a positive correlation at a population level may be as important from the policy viewpoint as a focus on the positive risk factors. Interventions based on small associations may have the potential for a large public health benefit

Mobile sink based fault diagnosis scheme for wireless sensor networks

Network diagnosis in Wireless Sensor Networks (WSNs) is a difficult task due to their improvisational nature, invisibility of internal running status, and particularly since the network structure can frequently change due to link failure. To solve this problem, we propose a Mobile Sink (MS) based distributed fault diagnosis algorithm for WSNs. An MS, or mobile fault detector is usually a mobile robot or vehicle equipped with a wireless transceiver that performs the task of a mobile base station while also diagnosing the hardware and software status of deployed network sensors. Our MS mobile fault detector moves through the network area polling each static sensor node to diagnose the hardware and software status of nearby sensor nodes using only single hop communication. Therefore, the fault detection accuracy and functionality of the network is significantly increased. In order to maintain an excellent Quality of Service (QoS), we employ an optimal fault diagnosis tour planning algorithm. In addition to saving energy and time, the tour planning algorithm excludes faulty sensor nodes from the next diagnosis tour. We demonstrate the effectiveness of the proposed algorithms through simulation and real life experimental results

Three-Dimensional Visualisation of Gas-water Two-phase Flow Based on Bubble Mapping Method and Size Projection Algorithm

Electrical impedance tomography (EIT) has been successfully applied on gas-water flow applications, but it is incapable to identify small bubbles or the sharp gas-water interface of a large bubble due to its relatively low spatial resolution. A new visualisation approach, bubble mapping method (BM3D), offers a good 3D visualisation of bubble size and distribution. However, the empirical thresholding value method used in BM3D might meet a challenging from various flow setups and conditions in practice. Recently, the size projection algorithm (SPA) was proposed to determine the closest thresholding value for each frame of tomogram by minimising projection error. In this paper, the performances of BM3D and SPA methods are individually analysed and evaluated. Then a new method based on the combination of BM3D and SPA methods is reported to achieve better visualisation of gas-water flow, where the SPA is employed to determine the optimised thresholding values for BM3D method. Experiments are conducted to evaluate the proposed combination method for typical gas-water pipeline flow regimes, including horizontal stratified, bubble, plug, slug, annular flow regimes and vertical bubble, slug, annular flow regimes. The results are compared with the BM3D method, colour mapping method, and high-speed camera video recorded from a transparent chamber. A brief discussion on the effects of reconstruction algorithms and thresholding value for horizontal and vertical flows visulaisation is also given

Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics

BACKGROUND: Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. RESULTS: We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. CONCLUSION: The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field

Ripple Texturing of Suspended Graphene Atomic Membranes

Graphene is the nature's thinnest elastic membrane, with exceptional mechanical and electrical properties. We report the direct observation and creation of one-dimensional (1D) and 2D periodic ripples in suspended graphene sheets, using spontaneously and thermally induced longitudinal strains on patterned substrates, with control over their orientations and wavelengths. We also provide the first measurement of graphene's thermal expansion coefficient, which is anomalously large and negative, ~ -7x10^-6 K^-1 at 300K. Our work enables novel strain-based engineering of graphene devices.Comment: 15 pages, 4 figure

X-chromosome Inactivation Patterns in Korean Women with Idiopathic Recurrent Spontaneous Abortion

Recurrent spontaneous abortion (RSA) defines as two or more consecutive losses at ≤20 weeks of gestation and affects an estimated 1 of every 100 couples wishing to have children. However, it remains a poorly understood phenomenon. Recent reports observed a significant association between highly skewed X chromosome and RSA, supporting that X chromosome inactivation might be an important and previously unknown cause of RSA. X-inactivation pattern, using polymeric X-linked women with idiopathic RSA and 80 control subjects with a single successful pregnancy and no history of spontaneous abortion. The ratio of heterozygotes was 68.2% (45/66) in women with RSA and 67.5% (54/80) in control group. Among 45 informative RSA cases, only 1 (2.2%) woman showed extreme skewed X inactivation (≥90%) and 4 (8.9%) had mild skewed inactivation (≥85%). In 54 heterozygous control subjects, 5 (9.3%) women showed extreme skewed X inactivation and 7 (13.0%) had mild one. The frequency of skewed X inactivation between RSA patients and control group was not significantly different (p>0.05). This finding suggests that skewed X chromosome be not associated with unexplained RSA patients