Single Top Production as a Probe of B-prime Quarks

We show how single top production at the LHC can be used to discover (and characterize the couplings of) B' quarks, which are an essential part of many natural models of new physics beyond the Standard Model. We present the B' effective model and concentrate on resonant production via a colored anomalous magnetic moment. Generally, B's preferentially decay into a single top quark produced in association with a W boson; thus, this production process makes associated single top production essential to B' searches at the LHC. We demonstrate the background processes are manageable and the signal cross section is sufficient to yield a large signal significance even during the 7 TeV LHC run. Specifically, we show that B' masses of 700 GeV or more can be probed. Moreover, if a B' is found, then the chirality of its coupling can be determined. Finally, we present signal cross sections for several different LHC energies.Comment: 19 pages, 7 figures, 1 tabl

Implications of Natural Categories for Natural Language Generation

Psychological research has shown that natural taxonomies contain a distinguished or basic level. Adult speakers use the names of these categories most frequently and can list a large number of attributes for them. They typically can list many attributes for superordinate categories and list few additional attributes for subordinate categories. Because natural taxonomies are important to human language, their use in natural language processing systems appears well founded. In the past, however, most AI systems have been implemented around uniform taxonomies in which there is no distinguished level. It has recently been demonstrated that natural taxonomies enhance natural language processing systems by allowing selection of appropriate category names and by providing the means to handle implicit focus. We propose that additional benefits from the use of natural categories can be realized in multi-sentential connected text generation systems. After discussing the psychological research on natural taxonomies that relates to natural language processing systems, the use of natural categorizations in current natural language processing systems is presented. We then describe how natural categories can be used in multiple sentence generation systems to allow the selection of appropriate category names, to provide the mechanism to help determine salience to aid in the selection of discourse schema. to provide for the shallow modeling audience expertise, and to increase the efficiency of taxonomy inheritance

Quantification of Temporal and Spatial Dynamics of Bean pod mottle virus at Different Spatial Scales

Bean pod mottle virus (BPMV) is the most prevalent virus infecting soybean (Glycine max) in the United States; however, the temporal and spatial dynamics in BPMV at varying spatial scales has not been elucidated. To quantify the temporal and spatial dynamics of BPMV at a field scale, a quadrat-based method was developed in which six soybean rows, each consisting of 30-cm-long quadrats, were established within soybean cv. NE3001 field plots (i.e., 150 quadrats per plot) in BPMV-inoculated and non-inoculated plots. Quadrats were sampled by selecting the youngest fully expanded leaflet from each of four plants within each quadrat beginning 25 days after planting, and continued at 8- to 11- day intervals until crop senescence. Leaf sap was extracted from each 4-leaflet (bulked) sample (from each quadrat), and tested for presence of the BPMV by ELISA. Quadrat position (plot, row, and quadrat number) and the date of sampling that each quadrat first tested positive for BPMV was recorded and mapped. The rate of BPMV incidence in 2006 ranged from 0.09 to 0.12 logits/day, indicating that BPMV incidence was doubling every 5.3 to 7.7 days in 2006. Doubling times for BPMV incidence in 2007 were slower, ranging from 17.3 to 34.7 days. Analysis of spatial patterns using ordinary runs revealed that BPMV-infected quadrats were predominantly clustered within both BPMV-inoculated and non-inoculated plots throughout both growing seasons. In addition to within field plot studies, a threeyear statewide disease survey (2005-2007) was conducted in Iowa to quantify county and field scale BPMV prevalence and incidence by systematically selecting 30 plants/soybean field (8 to 16 soybean fields per county). Leaf samples were then tested for BPMV by ELISA and county-level BPMV incidence maps were generated using ArcGIS software. End-of-season BPMV prevalence was 39/96 counties in 2005 (40%), 90/99 counties in 2006 (90.1%), and 74/99 counties in 2007 (74.7%). The incidence of BPMV within Iowa counties ranged from 0 to 100% and BPMV incidence significantly increased statewide from north to south. Spatial autocorrelation (dependence) analysis using Moran’s I revealed clustering for BPMV incidence among Iowa counties, indicating that BPMV incidence among counties was not random. The elucidation of the within-field temporal and spatial dynamics of BPMV and the statewide geographic distribution of BPMV in Iowa has important implications with regards to sampling, plant disease forensics, BPMV management, and risk prediction of BPMV

Quantifying the Within-Field Temporal and Spatial Dynamics of Bean pod mottle virus in Soybean

The prevalence and incidence of Bean pod mottle virus (BPMV) have been reported to be on the increase in the United States but little is known about the temporal and spatial dynamics of this virus within soybean (Glycine max) fields. A quadrat-based sampling method was developed to quantify the within-field spread of BPMV in soybean in 2006 and 2007. Twenty-five 30-cm-long quadrats were established within each row of soybean in field plots consisting of six rows, each 7.6 m long and spaced 0.76 m apart. Four treatments were used to influence the temporal and spatial dynamics of BPMV epidemics. Treatments were: (i) establishment of a point source of BPMV inoculum within soybean plots; (ii) lambda-cyhalothrin insecticide applied at the V1 and R2 growth stages; (iii) establishment of a BPMV inoculum point source, plus the application of foliar insecticide sprays at the V1 and R2 growth stages; and (iv) a nontreated, noninoculated control. All quadrats (census) were sampled beginning 25 days after planting; sampling continued every 8 to 11 days until plants were senescent. Sap from leaf samples was extracted and tested for BPMV by enzyme-linked immunosorbent assay. The incidence of BPMV per treatment was plotted against time to produce BPMV incidence curves for temporal analyses. In addition, positions of BPMV-positive quadrats were mapped for spatial analyses. BPMV was detected within soybean plots on the first sampling date in 2006 (30 May) and on the second sampling date in 2007 (21 June). The rate of BPMV temporal spread within treatments ranged from 0.11 to 0.13 logits/day in 2006 and from 0.05 to 0.07 logits/day in 2007. Doubling times for BPMV incidence among treatments ranged from 5.4 to 6.4 days in 2006 and from 10.0 to 14.1 days in 2007. Soybean plots that had the earliest dates of BPMV detection within quadrats (x) also had the highest BPMV incidence (y) at the end of the growing season (R2 = 66.5 and 70.4% for 2006 and 2007, respectively). Spatial analyses using ordinary runs, black-white join-counts, and spatial autocorrelation revealed highly aggregated spatial patterns of BPMV-infected quadrats over time. Bean leaf beetle population densities were linearly related to BPMV incidence (P \u3c 0.0001) in both years, indicating that BPMV epidemics were greatly influenced by bean leaf beetle population density. To our knowledge, this is the first study to quantify the seasonal temporal and spatial dynamics of BPMV spread within soybean

Prevalence, Incidence, and Spatial Dependence of Soybean mosaic virus in Iowa

The prevalence of soybean fields with plants infected with Soybean mosaic virus (SMV) in Iowa is assumed to be random, because the primary source of the virus is SMV-infected seed. Data collected from 2,500 soybean fields sampled over a 3-year period as part of the Iowa Soybean Disease Survey (2005 to 2007) were used to evaluate this assumption. SMV was first detected in early June of each year but counties in which it was first detected varied among years. Prevalence at the county scale at end of season was 32.3, 27.3, and 89.9% in 2005, 2006, and 2007, respectively. End-of-season incidence of SMV within SMV-positive counties was 1.5 to 25.0, 1.7 to 24, and 1.8 to 58% in 2005, 2006, and 2007, respectively. The number of fields in which plants infected with SMV were detected increased at the linear rate of approximately one new field every 2 days in 2007, compared with one new field every 22 days (2005) and 21 days (2006), with coefficients of determination (R2) of 93.2 to 96.8% using the linear model. Weak spatial dependence for end-of-season SMV incidence was detected using Moran\u27s Index, indicating that the risk for SMV incidence at the county scale within Iowa at the end of the growing season is not random

Evaluating the Importance of Stem Canker of Soybean in Iowa

The relative importance of stem canker of soybean in Iowa compared with other soybean diseases present in the state was assessed using data collected from over 3,400 soybean fields sampled in the Iowa Soybean Disease Survey that was conducted from 2005 to 2007. Symptomatic plant tissues from soybean plants with stem canker symptoms were cultured on acidified potato dextrose agar. The prevalence of stem canker on soybean in 2005 in Iowa was 2.6%; the disease was not detected in 2006 and 2007. In 2005, 63 isolates with Diaporthe/Phomopsis characteristics were collected. To identify isolates to fungal species and variety, single-spored isolates were subjected to polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) and sequencing of the internal transcribed spacer (ITS) region. Fourteen isolates were identified as D. phaseolorum var. caulivora (northern stem canker) and 49 as Phomopsis longicolla. To quantify and compare the aggressiveness of D. phaseolorum var. caulivora isolates collected in Iowa, nine isolates were arbitrarily selected for components analysis. Incubation period, rate of lesion expansion, final lesion length, and time to plant death for each isolate were quantified. Significant differences in components of aggressiveness were detected among the nine isolates. Results from this work suggest stem canker is a minor disease of soybean in Iowa