Motor Vehicle Crash Fatalities, April 15, 2011

Motor Vehicle Crash Fatalities

Motor Vehicle Crash Fatalities, April 8, 2011

Motor Vehicle Crash Fatalities

Motor Vehicle Crash Fatalities, April 22, 2011

Motor Vehicle Crash Fatalities

Motor Vehicle Crash Fatalities, April 29, 2011

Motor Vehicle Crash Fatalities

New predictions for inclusive heavy-quarkonium P-wave decays

We show that some nonrelativistic quantum chromodynamics color-octet matrix elements can be written in terms of (derivatives of) wave functions at the origin and of nonperturbative universal constants once the factorization between the soft and ultrasoft scales is achieved by using an effective field theory where only ultrasoft degrees of freedom are kept as dynamical entities. This allows us to derive a new set of relations between inclusive heavy-quarkonium P-wave decays into light hadrons with different principal quantum numbers and with different heavy flavors. In particular, we can estimate the ratios of the decay widths of bottomonium P-wave states from charmonium data.

New predictions for inclusive heavy-quarkonium p-wave decays

We show that some nonrelativistic quantum chromodynamics color-octet matrix elements can be written in terms of (derivatives of) wave functions at the origin and of nonperturbative universal constants once the factorization between the soft and ultrasoft scales is achieved by using an effective field theory where only ultrasoft degrees of freedom are kept as dynamical entities. This allows us to derive a new set of relations between inclusive heavy-quarkonium P-wave decays into light hadrons with different principal quantum numbers and with different heavy flavors. In particular, we can estimate the ratios of the decay widths of bottomonium P-wave states from charmonium data.

Crash Rates and Crash Densities on Secondary Roads in Iowa by Surface Type 2001 – 2009, July 6, 2010

Crash Rates and Crash Densities on Secondary Roads in Iowa by Surface Type produced by the Iowa Department of Transportation.

Crash Rates and Crash Densities on Secondary Roads in Iowa by Functional Class 2001 – 2009, July 6, 2010

Crash Rates and Crash Densities on Secondary Roads in Iowa by Functional Class produced by the Iowa Department of Transportation.

Worldwide trends in gastric cancer mortality (1980-2011), with predictions to 2015, and incidence by subtype.

Gastric cancer incidence and mortality decreased substantially over the last decades in most countries worldwide, with differences in the trends and distribution of the main topographies across regions. To monitor recent mortality trends (1980-2011) and to compute short-term predictions (2015) of gastric cancer mortality in selected countries worldwide, we analysed mortality data provided by the World Health Organization. We also analysed incidence of cardia and non-cardia cancers using data from Cancer Incidence in Five Continents (2003-2007). The joinpoint regression over the most recent calendar periods gave estimated annual percent changes (EAPC) around -3% for the European Union (EU) and major European countries, as well as in Japan and Korea, and around -2% in North America and major Latin American countries. In the United States of America (USA), EU and other major countries worldwide, the EAPC, however, were lower than in previous years. The predictions for 2015 show that a levelling off of rates is expected in the USA and a few other countries. The relative contribution of cardia and non-cardia gastric cancers to the overall number of cases varies widely, with a generally higher proportion of cardia cancers in countries with lower gastric cancer incidence and mortality rates (e.g. the USA, Canada and Denmark). Despite the favourable mortality trends worldwide, in some countries the declines are becoming less marked. There still is the need to control Helicobacter pylori infection and other risk factors, as well as to improve diagnosis and management, to further reduce the burden of gastric cancer.

Moving Beyond Teen Crash Fatality Statistics: The Go-Team Study, GOTM-000, 2013

Despite a trend of decreasing teen fatalities due to motor vehicle crashes over the past decade, they remain the leading cause of adolescent fatalities in Iowa. The purpose of this study was to create detailed case studies of each fatal motor vehicle crash involving a driver under the age of 20 that occurred in Iowa in 2009, 2010, and 2011. Data for each crash were gathered from media sources, law enforcement agencies, and the Iowa Department of Transportation. The driving records of the teens, which included their licensure history, prior traffic citations, and prior crashes, were also acquired. In addition, data about the charges filed against a teen as a result of being involved in a fatal crash were obtained. A total of 126 crashes involving 131 teen drivers that resulted in 143 fatalities were analyzed. Many findings for fatal crashes involving teen drivers in Iowa are consistent with national trends, including the overrepresentation of male drivers, crash involvement that increases with age, crash involvement per vehicle miles traveled that decreases with age, and prevalence of single-vehicle road departure crashes. Relative to national statistics, teen fatalities from crashes in Iowa are more likely to occur from midnight to 6am and from 9am to noon. Crash type varied by driver age and county population level. Teen drivers contributed to the fatal crashes at a rate of 74%; contribution of the teen driver was unknown for 11% of crashes. Speed was a factor for about 25% of the crashes for which a teen driver was at fault. The same was also true of alcohol/drug impairment. Only 20% of the rear-seat occupants of the teen drivers’ vehicles wore seat belts compared to 60% use for the front-seat occupants. Analysis of the teens’ driving records prior to the fatal crash suggests at-fault crashes and speeding violations are associated with contributing to the fatal crash.

Accuracy of plant assemblage predictions from species distribution models varies along environmental gradients

Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.