Field performance of an all-semiconductor laser coherent Doppler lidar

We implement and test what, to our knowledge, is the first deployable coherent Doppler lidar (CDL) system based on a compact, inexpensive all-semiconductor laser (SL). To demonstrate the field performance of our SL-CDL remote sensor, we compare a 36 h time series of averaged radial wind speeds measured by our instrument at an 80 m dis-tance to those simultaneously obtained from an industry-standard sonic anemometer (SA). An excellent degree of correlation (R2 0.994 and slope 0.996) is achieved from a linear regression analysis of the CDL versus SA wind speed data. The lidar system is capable of providing high data availability, ranging from 85 % to 100 % even under varying outdoor (temperature and humidity) conditions during the test period. We also show the use of our SL-CDL for monitoring the dependence of aerosol backscatter on relative humidity. This work points to the feasibility of a more general class of low-cost, portable remote sensors based on all-SL emitters for applications that require demanding laser stability and coherence. © 2012 Optical Society of America OCIS codes: 010.3640, 140.5960. Light detection and ranging (lidar) is a well-known laser technology for a variety of remote sensing applications. A common lidar variant is the so-called coherent Doppler lidar (CDL) [1], which collects a portion of laser back

A physically meaningful method for the comparison of potential energy functions

In the study of the conformational behavior of complex systems, such as proteins, several related statistical measures are commonly used to compare two different potential energy functions. Among them, the Pearson's correlation coefficient r has no units and allows only semi-quantitative statements to be made. Those that do have units of energy and whose value may be compared to a physically relevant scale, such as the root mean square deviation (RMSD), the mean error of the energies (ER), the standard deviation of the error (SDER) or the mean absolute error (AER), overestimate the distance between potentials. Moreover, their precise statistical meaning is far from clear. In this article, a new measure of the distance between potential energy functions is defined which overcomes the aforementioned difficulties. In addition, its precise physical meaning is discussed, the important issue of its additivity is investigated and some possible applications are proposed. Finally, two of these applications are illustrated with practical examples: the study of the van der Waals energy, as implemented in CHARMM, in the Trp-Cage protein (PDB code 1L2Y) and the comparison of different levels of the theory in the ab initio study of the Ramachandran map of the model peptide HCO-L-Ala-NH2.Comment: 30 pages, 7 figures, LaTeX, BibTeX. v2: A misspelling in the author's name has been corrected. v3: A new application of the method has been added at the end of section 9 and minor modifications have also been made in other sections. v4: Journal reference and minor corrections adde

A clustering approach to automatic verb classification incorporating selectional preferences: model, implementation, and user manual

This report presents two variations of an innovative, complex approach to semantic verb classes that relies on selectional preferences as verb properties. The underlying linguistic assumption for this verb class model is that verbs which agree on their selectional preferences belong to a common semantic class. The model is implemented as a soft-clustering approach, in order to capture the polysemy of the verbs. The training procedure uses the Expectation-Maximisation (EM) algorithm (Baum, 1972) to iteratively improve the probabilistic parameters of the model, and applies the Minimum Description Length (MDL) principle (Rissanen, 1978) to induce WordNet-based selectional preferences for arguments within subcategorisation frames. One variation of the MDL principle replicates a standard MDL approach by Li and Abe (1998), the other variation presents an improved pruning strategy that outperforms the standard implementation considerably. Our model is potentially useful for lexical induction (e.g., verb senses, subcategorisation and selectional preferences, collocations, and verb alternations), and for NLP applications in sparse data situations. We demonstrate the usefulness of the model by a standard evaluation (pseudo-word disambiguation), and three applications (selectional preference induction, verb sense disambiguation, and semi-supervised sense labelling)

Stratification of adolescents across mental phenomena emphasizes the importance of transdiagnostic distress: a replication in two general population cohorts

Characterizing patterns of mental phenomena in epidemiological studies of adolescents can provide insight into the latent organization of psychiatric disorders. This avoids the biases of chronicity and selection inherent in clinical samples, guides models of shared aetiology within psychiatric disorders and informs the development and implementation of interventions. We applied Gaussian mixture modelling to measures of mental phenomena from two general population cohorts: the Avon Longitudinal Study of Parents and Children (ALSPAC, n=3,018) and the Neuroscience in Psychiatry Network (NSPN, n=2,023). We defined classes according to their patterns of both positive (e.g. wellbeing and self-esteem) and negative (e.g. depression, anxiety, psychotic experiences) phenomena. Subsequently, we characterized classes by considering the distribution of diagnoses and sex split across classes. Four well-separated classes were identified within each cohort. Classes primarily differed by overall severity of transdiagnostic distress rather than particular patterns of phenomena akin to diagnoses. Further, as overall severity of distress increased, so did within-class variability, the proportion of individuals with operational psychiatric diagnoses. These results suggest that classes of mental phenomena in the general population of adolescents may not be the same as those found in clinical samples. Classes differentiated only by overall severity support the existence of a general, transdiagnostic mental distress factor and have important implications for intervention

Regulation of pituitary MT1 melatonin receptor expression by gonadotrophin-releasing hormone (GnRH) and early growth response factor-1 (Egr-1) : in vivo and in vitro studies

Copyright: © 2014 Bae et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was funded by the UK Biotechnology and Biological Sciences Research Council (BBSRC; grant BB/F020309/1; http://www.bbsrc.ac.uk/home/home.aspx). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Informing the design of a national screening and treatment programme for chronic viral hepatitis in primary care: qualitative study of at-risk immigrant communities and healthcare professionals

n Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedThis paper presents independent research funded by the National Institute for Health Research (NIHR) under the Programme Grants for Applied Research programme (RP-PG-1209-10038).

Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)

Here we present a review of the literature of influenza modeling studies, and discuss how these models can provide insights into the future of the currently circulating novel strain of influenza A (H1N1), formerly known as swine flu. We discuss how the feasibility of controlling an epidemic critically depends on the value of the Basic Reproduction Number (R0). The R0 for novel influenza A (H1N1) has recently been estimated to be between 1.4 and 1.6. This value is below values of R0 estimated for the 1918–1919 pandemic strain (mean R0~2: range 1.4 to 2.8) and is comparable to R0 values estimated for seasonal strains of influenza (mean R0 1.3: range 0.9 to 2.1). By reviewing results from previous modeling studies we conclude it is theoretically possible that a pandemic of H1N1 could be contained. However it may not be feasible, even in resource-rich countries, to achieve the necessary levels of vaccination and treatment for control. As a recent modeling study has shown, a global cooperative strategy will be essential in order to control a pandemic. This strategy will require resource-rich countries to share their vaccines and antivirals with resource-constrained and resource-poor countries. We conclude our review by discussing the necessity of developing new biologically complex models. We suggest that these models should simultaneously track the transmission dynamics of multiple strains of influenza in bird, pig and human populations. Such models could be critical for identifying effective new interventions, and informing pandemic preparedness planning. Finally, we show that by modeling cross-species transmission it may be possible to predict the emergence of pandemic strains of influenza

Strong Ultraviolet Pulse From a Newborn Type Ia Supernova

Type Ia supernovae are destructive explosions of carbon oxygen white dwarfs. Although they are used empirically to measure cosmological distances, the nature of their progenitors remains mysterious, One of the leading progenitor models, called the single degenerate channel, hypothesizes that a white dwarf accretes matter from a companion star and the resulting increase in its central pressure and temperature ignites thermonuclear explosion. Here we report observations of strong but declining ultraviolet emission from a Type Ia supernova within four days of its explosion. This emission is consistent with theoretical expectations of collision between material ejected by the supernova and a companion star, and therefore provides evidence that some Type Ia supernovae arise from the single degenerate channel.Comment: Accepted for publication on the 21 May 2015 issue of Natur