Intermediate-Term Risk of Stroke Following Cardiac Procedures in a Nationally Representative Data Set.

BACKGROUND: Studies on stroke risk following cardiac procedures addressed only perioperative and long-term risk following limited higher-risk procedures, were poorly generalizable, and often failed to stratify by stroke type. We calculated stroke risk in the intermediate risk period following cardiac procedures compared with common noncardiac surgeries and medical admissions. METHODS AND RESULTS: The Nationwide Readmissions Database contains readmission data for 49% of US admissions in 2013. We compared age-adjusted stroke readmission rates up to 90 days postdischarge. We used Cox regression to calculate hazard ratios, up to 1 year, of stroke risk comparing transcatheter aortic valve replacement versus surgical aortic valve replacement and coronary artery bypass graft versus percutaneous coronary intervention. Procedures and diagnoses were identified by International Classification of Disease, Ninth Revision, Clinical Modification codes. After cardiac procedures, 90-day ischemic stroke readmission rate was highest after transcatheter aortic valve replacement (2.05%); 90-day hemorrhagic stroke rate was highest after left ventricular assist device placement (0.09%). The hazard ratio for ischemic stroke after transcatheter aortic valve replacement, compared with surgical aortic valve replacement, in fully adjusted Cox models was 1.86 (95% confidence interval, 1.12-3.08; P=0.016) and 6.17 (95% confidence interval, 1.97-19.33; P=0.0018) for hemorrhagic stroke. There was no difference between coronary artery bypass graft and percutaneous coronary intervention. CONCLUSIONS: We demonstrated elevated readmission rates for ischemic and hemorrhagic stroke in the intermediate 30-, 60-, and 90-day risk periods following common cardiac procedures. Furthermore, we found an elevated risk of stroke after transcatheter aortic valve replacement compared with surgical aortic valve replacement up to 1 year

Identification of boosted, hadronically decaying W bosons and comparisons with ATLAS data taken at √s = 8 TeV

This paper reports a detailed study of techniques for identifying boosted, hadronically decaying W bosons using 20.3 fb −¹ of proton–proton collision data collected by the ATLAS detector at the LHC at a centre-of-mass energy √s = 8 TeV. A range of techniques for optimising the signal jet mass resolution are combined with various jet substructure variables. The results of these studies in Monte Carlo simulations show that a simple pairwise combination of groomed jet mass and one substructure variable can provide a 50 % efficiency for identifying W bosons with transverse momenta larger than 200 GeV while maintaining multijet background efficiencies of 2–4 % for jets with the same transverse momentum. These signal and background efficiencies are confirmed in data for a selection of tagging techniques

Search for charged Higgs bosons in the H±→tbH^{\pm} \rightarrow tb decay channel in pppp collisions at s=8\sqrt{s}=8 TeV using the ATLAS detector

Charged Higgs bosons heavier than the top quark and decaying via H ± → tb are searched for in proton-proton collisions measured with the ATLAS experiment at √s=8 TeV corresponding to an integrated luminosity of 20.3fb−1. The production of a charged Higgs boson in association with a top quark, gb → tH ±, is explored in the mass range 200 to 600 GeV using multi-jet final states with one electron or muon. In order to separate the signal from the Standard Model background, analysis techniques combining several kinematic variables are employed. An excess of events above the background-only hypothesis is observed across a wide mass range, amounting to up to 2.4 standard deviations. Upper limits are set on the gb → tH ± production cross section times the branching fraction BR(H ± → tb). Additionally, the complementary s-channel production, qq ′ → H ±, is investigated through a reinterpretation of W ′ → tb searches in ATLAS. Final states with one electron or muon are relevant for H ± masses from 0.4 to 2.0 TeV, whereas the all-hadronic final state covers the range 1.5 to 3.0 TeV. In these search channels, no significant excesses from the predictions of the Standard Model are observed, and upper limits are placed on the qq ′ → H ± production cross section times the branching fraction BR(H ± → tb)

Landscape and Insect Community Dataset

The dataset is arranged with rows separated by research site and year, with columns of data. The dataset consists of the following columns of data: research site ID (Farm ID), research year (Year; 1=2012, 2=2013), the area of the potato field sampled as a research site in square meters (FieldArea) initial number of plants infected (InitialInfected), the final number of plants infected (FinalInfected), the difference in the number of plants infected (Infected; FinalInfected-InitialInfected), the number of plants sampled (NPlants), the number of times the plants were sampled throughout the season (NSamples), the number of insect traps collected throughout the season (NTraps), the number of aphids collected throughout the season (Naphids), the number of aphids collected throughout the season that were identified to species or genera (NAphidsID), aphid species richness (NAphidSpp, meaning the count of aphid species collected throughout the season), the interpolated aphid species richness (AphidRichness), the Shannon diversity of the aphid community (ShannonDiversity), the number of coccinellids collected throughout the season (PredatorAbundance), the coccinellid species richness (Predator Richness, meaning the count of coccinellid species found throughout the season), the percentage of unmanaged land within a 500 m radius of the site (Nat500), the percentage of unmanaged land within a 1000 m radius of the site (Nat1000) the percentage of unmanaged land within a 1500 m radius of the site (Nat1500), the percentage of cropland within a 500 m radius of the site (Ag500), the percentage of cropland within a 1000 m radius of the site (Ag1000), and the percentage of cropland within a 1500m radius of the site (Ag1500)

Data from: Crop-dominated landscapes have higher vector-borne plant virus prevalence

Landscape composition affects local arthropod biodiversity, including herbivorous insects and their predators, yet to date landscape effects on insect-vectored plant diseases have received little attention. Here, we examine how landscape composition affects the prevalence of a viral pathogen in host plants, and the role the arthropod vector assemblage plays in mediating landscape effects. We measured the effect of landscape composition (measured as percentage of cropland and unmanaged land) on the plant virus Potato virus Y (PVY), its aphid vectors, and their coccinellid predators during the 2012 and 2013 field seasons at 19–21 farms. In both years, we found a positive relationship between final virus prevalence and percentage of cropland within 500, 1000 and 1500 m surrounding study sites. Percentage of cropland also had a significant negative effect on aphid species richness, and the aphid community composition in turn affected PVY prevalence. By contrast, landscape composition had no measurable effect on coccinellid abundance or species richness in this study. Synthesis and applications. Our work demonstrates that landscape composition plays an important role in vector-borne pathogen spread, and that pathogen spread appears to be mediated by the effects of the landscape on the insect vector community. The small spatial scale (≤1500 m) of the effects seen in our study indicates that on-farm management practices have the potential to reduce virus prevalence on small-scale farms. Farmers may be able to reduce Potato virus Y prevalence by on-farm diversification, by isolating potato fields from other agricultural crops, and by not using saved potato seed

Intra‐annual variation and landscape composition interactively affect aphid community composition

Abstract Agricultural intensification impacts local arthropod communities. The temporal and spatial variation of agricultural environments can have a significant impact on insect pest populations, yet little work has been done to date on the effect of intra‐annual variation (within season) or spatiotemporal effects on arthropod functional community composition. The aim of this research was to evaluate the effects of intra‐annual variation and landscape composition on the aphid community. To that end, we investigated the following research question: How do intra‐annual variation and landscape composition affect aphid abundance, species richness, and functional community composition? In this study, we quantified landscape composition as percent cropland, intra‐annual variation as sampling week measured throughout the growing season, and aphid functional community composition as crop virus transmission—or vectoring—ability. We collected data in two agricultural regions: a diversified agricultural region in New York State (NY) and an agriculturally intense potato‐growing region in Wisconsin (WI). We found that the interactive effect of landscape composition and intra‐annual variation significantly affected aphid abundance and species richness in both study regions, and functional community composition in NY. These results indicate that spatiotemporal shifts in agroecosystems have significant implications for aphid functional community composition