A new dry biomedical electrode

Electronic circuitry contains new operational amplifier which incorporates monolithic super-gain transistors. Electrode does not provide voltage amplification; instead, it acts as current amplifier to make it possible to pick up electrical potentials from surface of highly resistant dry skin

PROJECTION OF COTTON WAREHOUSE FACILITIES FOR OKLAHOMA: A MARKOV PROCESS

Agribusiness,

Selection of neutralizing antibody escape mutants with type A influenza virus HA-specific polyclonal antisera: possible significance for antigenic drift

Ten antisera were produced in rabbits by two or three intravenous injections of inactivated whole influenza type A virions. All contained haemagglutination-inhibition (HI) antibody directed predominantly to an epitope in antigenic site B and, in addition, various amounts of antibodies to an epitope in site A and in site D. The ability of untreated antisera to select neutralization escape mutants was investigated by incubating virus possessing the homologous haemagglutinin with antiserum adjusted to contain anti-B epitope HI titres of 100, 1000 and 10000 HIU/ml. Virus-antiserum mixtures were inoculated into embryonated hen's eggs, and progeny virus examined without further selection. Forty percent of the antisera at a titre of 1000 HIU/ml selected neutralizing antibody escape mutants as defined by their lack of reactivity to Mab HC10 (site B), and unchanged reactivity to other Mabs to site A and site D epitopes. All escape mutant-selecting antisera had a ratio of anti-site B (HC10)-epitope antibody[ratio]other antibodies of [gt-or-equal, slanted]2·0[ratio]1. The antiserum with the highest ratio (7·4[ratio]1) selected escape mutants in all eggs tested in four different experiments. No antiserum used at a titre of 10000 HIU/ml allowed multiplication of any virus. All antisera used at a titre of 100 HIU/ml permitted virus growth, but this was wild-type (wt) virus. We conclude that a predominant epitope-specific antibody response, a titre of [gt-or-equal, slanted]1000 HIU/ml, and a low absolute titre of other antibodies ([less-than-or-eq, slant]500 HIU/ml) are three requirements for the selection of escape mutants. None of the antisera in this study could have selected escape mutants without an appropriate dilution factor, so the occurrence of an escape mutant-selecting antiserum in nature is likely to be a rare event

A Bayesian spatio-temporal model of panel design data: airborne particle number concentration in Brisbane, Australia

This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected, as part of the Ultrafine Particles from Transport Emissions and Child Health (UPTECH) project. Two weeks of continuous measurements were taken at each of a number of government primary schools in the Brisbane Metropolitan Area. The monitoring equipment was taken to each school sequentially. The school data are augmented by data from long term monitoring stations at three locations in Brisbane, Australia. Fitting the model helps describe the spatial and temporal variability at a subset of the UPTECH schools and the long-term monitoring sites. The temporal variation is modelled hierarchically with penalised random walk terms, one common to all sites and a term accounting for the remaining temporal trend at each site. Parameter estimates and their uncertainty are computed in a computationally efficient approximate Bayesian inference environment, R-INLA. The temporal part of the model explains daily and weekly cycles in PNC at the schools, which can be used to estimate the exposure of school children to ultrafine particles (UFPs) emitted by vehicles. At each school and long-term monitoring site, peaks in PNC can be attributed to the morning and afternoon rush hour traffic and new particle formation events. The spatial component of the model describes the school to school variation in mean PNC at each school and within each school ground. It is shown how the spatial model can be expanded to identify spatial patterns at the city scale with the inclusion of more spatial locations.Comment: Draft of this paper presented at ISBA 2012 as poster, part of UPTECH projec

Impact of New Madrid Seismic Zone Earthquakes on the Central USA, Vol. 1 and 2

The information presented in this report has been developed to support the Catastrophic Earthquake Planning Scenario workshops held by the Federal Emergency Management Agency. Four FEMA Regions (Regions IV, V, VI and VII) were involved in the New Madrid Seismic Zone (NMSZ) scenario workshops. The four FEMA Regions include eight states, namely Illinois, Indiana, Kentucky, Tennessee, Alabama, Mississippi, Arkansas and Missouri. The earthquake impact assessment presented hereafter employs an analysis methodology comprising three major components: hazard, inventory and fragility (or vulnerability). The hazard characterizes not only the shaking of the ground but also the consequential transient and permanent deformation of the ground due to strong ground shaking as well as fire and flooding. The inventory comprises all assets in a specific region, including the built environment and population data. Fragility or vulnerability functions relate the severity of shaking to the likelihood of reaching or exceeding damage states (light, moderate, extensive and near-collapse, for example). Social impact models are also included and employ physical infrastructure damage results to estimate the effects on exposed communities. Whereas the modeling software packages used (HAZUS MR3; FEMA, 2008; and MAEviz, Mid-America Earthquake Center, 2008) provide default values for all of the above, most of these default values were replaced by components of traceable provenance and higher reliability than the default data, as described below. The hazard employed in this investigation includes ground shaking for a single scenario event representing the rupture of all three New Madrid fault segments. The NMSZ consists of three fault segments: the northeast segment, the reelfoot thrust or central segment, and the southwest segment. Each segment is assumed to generate a deterministic magnitude 7.7 (Mw7.7) earthquake caused by a rupture over the entire length of the segment. US Geological Survey (USGS) approved the employed magnitude and hazard approach. The combined rupture of all three segments simultaneously is designed to approximate the sequential rupture of all three segments over time. The magnitude of Mw7.7 is retained for the combined rupture. Full liquefaction susceptibility maps for the entire region have been developed and are used in this study. Inventory is enhanced through the use of the Homeland Security Infrastructure Program (HSIP) 2007 and 2008 Gold Datasets (NGA Office of America, 2007). These datasets contain various types of critical infrastructure that are key inventory components for earthquake impact assessment. Transportation and utility facility inventories are improved while regional natural gas and oil pipelines are added to the inventory, alongside high potential loss facility inventories. The National Bridge Inventory (NBI, 2008) and other state and independent data sources are utilized to improve the inventory. New fragility functions derived by the MAE Center are employed in this study for both buildings and bridges providing more regionally-applicable estimations of damage for these infrastructure components. Default fragility values are used to determine damage likelihoods for all other infrastructure components. The study reports new analysis using MAE Center-developed transportation network flow models that estimate changes in traffic flow and travel time due to earthquake damage. Utility network modeling was also undertaken to provide damage estimates for facilities and pipelines. An approximate flood risk model was assembled to identify areas that are likely to be flooded as a result of dam or levee failure. Social vulnerability identifies portions of the eight-state study region that are especially vulnerable due to various factors such as age, income, disability, and language proficiency. Social impact models include estimates of displaced and shelter-seeking populations as well as commodities and medical requirements. Lastly, search and rescue requirements quantify the number of teams and personnel required to clear debris and search for trapped victims. The results indicate that Tennessee, Arkansas, and Missouri are most severely impacted. Illinois and Kentucky are also impacted, though not as severely as the previous three states. Nearly 715,000 buildings are damaged in the eight-state study region. About 42,000 search and rescue personnel working in 1,500 teams are required to respond to the earthquakes. Damage to critical infrastructure (essential facilities, transportation and utility lifelines) is substantial in the 140 impacted counties near the rupture zone, including 3,500 damaged bridges and nearly 425,000 breaks and leaks to both local and interstate pipelines. Approximately 2.6 million households are without power after the earthquake. Nearly 86,000 injuries and fatalities result from damage to infrastructure. Nearly 130 hospitals are damaged and most are located in the impacted counties near the rupture zone. There is extensive damage and substantial travel delays in both Memphis, Tennessee, and St. Louis, Missouri, thus hampering search and rescue as well as evacuation. Moreover roughly 15 major bridges are unusable. Three days after the earthquake, 7.2 million people are still displaced and 2 million people seek temporary shelter. Direct economic losses for the eight states total nearly $300 billion, while indirect losses may be at least twice this amount. The contents of this report provide the various assumptions used to arrive at the impact estimates, detailed background on the above quantitative consequences, and a breakdown of the figures per sector at the FEMA region and state levels. The information is presented in a manner suitable for personnel and agencies responsible for establishing response plans based on likely impacts of plausible earthquakes in the central USA.Armu W0132T-06-02unpublishednot peer reviewe

Spectral Lags Obtained by CCF of Smoothed Lightcurves

We present a new technique to calculate the spectral lags of gamma-ray bursts (GRBs). Unlike previous processing methods, we first smooth the light curves of gamma-ray bursts in high and low energy bands using the "Loess" filter, then, we directly define the spectral lags as such to maximize the cross-correlation function (CCF) between two smoothed light curves. This method is suitable for various shapes of CCF; it effectively avoids the errors caused by manual selections for the fitting function and fitting interval. Using the method, we have carefully measured the spectral lags of individual pulses contained in BAT/Swift gamma-ray bursts with known redshifts, and confirmed the anti-correlation between the spectral lag and the isotropy luminosity. The distribution of spectral lags can be well fitted by four Gaussian components, with the centroids at 0.03 s, 0.09 s, 0.15 s, and 0.21 s, respectively. We find that some spectral lags of the multi-peak GRBs seem to evolve with time