Predicting Bleeding and Thrombosis Complications in Patients with Continuous Flow Left Ventricular Assist Devices

Background: Left ventricular assist device (LVAD) therapy has been proven to relieve heart failure symptoms and improve survival, but is not devoid of bleeding and/or thrombotic complications. Risk stratification tools have been utilized in other cardiovascular disease populations to estimate the risk of bleeding and thrombosis with and without anticoagulation, including the HAS-BLED, HEMORR2HAGES, CHADS2 and CHA2DS2-VASc models. The study objective was to evaluate the predictive value of available risk models for bleeding and thrombotic complications in patients with an LVAD within one year of implantation. Methods: This was a retrospective, single-center analysis of patients implanted with the HeartMate II continuous-flow LVAD from July 2011 to June 2016. All patients who received an LVAD within the study period were eligible for inclusion. The primary endpoint was the first occurrence of bleeding or thrombosis within one year from implantation. Baseline risk model scores were calculated at the time of LVAD implantation. Chi-square and student’s t-test were used to measure baseline differences and compare mean risk model scores between patients who had an event. A receiver operator characteristic (ROC) curve analysis was performed to evaluate the accuracy of the risk models to predict an event. Results: A total of 129 patients underwent LVAD implantation within the study time period. Mean CHADS2, CHA2DS2-VASc, and HAS-BLED scores were not significantly different in patients with and without an event. The mean HEMORR2HAGES score was 3.09 and 2.51 in those with and without a bleeding event, respectively (p = 0.008). The ROC curve area for the HEMORR2HAGES model was the highest at 0.620. Conclusion: The HAS-BLED, HEMORR2HAGES, CHADS2and CHA2DS2-VASc risk stratification models did not accurately predict bleeding or thrombosis events in our population. The mean HEMORR2HAGES model score was higher in patients who experienced a bleeding event. However, this model did not have strong positive predictive value. Better risk models are needed to predict bleeding and thrombotic events in this patient population

A cluster analysis of harmony in the McGill Billboard dataset

We set out to perform a cluster analysis of harmonic structures (specifically, chord-to-chord transitions) in the McGill Billboard dataset, to determine whether there is evidence of multiple harmonic grammars and practices in the corpus, and if so, what the optimal division of songs, according to those harmonic grammars, is. We define optimal as providing meaningful, specific information about the harmonic practices of songs in the cluster, but being general enough to be used as a guide to songwriting and predictive listening. We test two hypotheses in our cluster analysis — first that 5–9 clusters would be optimal, based on the work of Walter Everett (2004), and second that 15 clusters would be optimal, based on a set of user-generated genre tags reported by Hendrik Schreiber (2015). We subjected the harmonic structures for each song in the corpus to a K-means cluster analysis. We conclude that the optimal clustering solution is likely to be within the 5–8 cluster range. We also propose that a map of cluster types emerging as the number of clusters increases from one to eight constitutes a greater aid to our understanding of how various harmonic practices, styles, and sub-styles comprise the McGill Billboard dataset

Structurally complex farms support high avian functional diversity in tropical montane Ethiopia

Of all feeding guilds, understorey insectivores are thought to be most sensitive to disturbance and forest conversion. We compared the composition of bird feeding guilds in tropical forest fragments with adjacent agro-ecosystems in a montane region of south-west Ethiopia. We used a series of point counts to survey birds in 19 agriculture and 19 forest sites and recorded tree species within each farm across an area of 40 × 35 km. Insectivores (~17 spp. per plot), frugivores (~3 spp. per plot) and omnivores (~5 spp. per plot) maintained species density across habitats, while granivores and nectarivores increased in the agricultural sites by factors of 7 and 3 respectively. Species accumulation curves of each guild were equal or steeper in agriculture, suggesting that agricultural and forest landscapes were equally heterogeneous for all bird guilds. Counter to most published studies, we found no decline in insectivore species richness with forest conversion. However, species composition differed between the two habitats, with certain forest specialists replaced by other species within each feeding guild. We suggest that the lack of difference in insectivorous species numbers between forest and agriculture in this region is due to the benign nature of the agricultural habitat, but also due to a regional species pool which contains many bird species which are adapted to open habitats

Symmetry Breaking in Few Layer Graphene Films

Recently, it was demonstrated that the quasiparticle dynamics, the layer-dependent charge and potential, and the c-axis screening coefficient could be extracted from measurements of the spectral function of few layer graphene films grown epitaxially on SiC using angle-resolved photoemission spectroscopy (ARPES). In this article we review these findings, and present detailed methodology for extracting such parameters from ARPES. We also present detailed arguments against the possibility of an energy gap at the Dirac crossing ED.Comment: 23 pages, 13 figures, Conference Proceedings of DPG Meeting Mar 2007 Regensburg Submitted to New Journal of Physic

The DESI One-Percent Survey: Exploring the Halo Occupation Distribution of Luminous Red Galaxies and Quasi-Stellar Objects with AbacusSummit

We present the first comprehensive Halo Occupation Distribution (HOD) analysis of the DESI One-Percent survey Luminous Red Galaxy (LRG) and Quasi-Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 Mpc/h in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of fsat = 11+-1%, a mean halo mass of log10 Mh = 13.40+0.02-0.02, and a linear bias of blin = 1.93+0.06-0.04. For LRGs in 0.6 < z < 0.8, we find fsat = 14+-1%, log10 Mh = 13.24+0.02-0.02, and blin = 2.08+0.03-0.03. For QSOs, we infer fsat = 3+8-2%, log10 Mh = 12.65+0.09-0.04, and blin = 2.63+0.37-0.26 in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high-fidelity galaxy mocks. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealing significant and interesting trends in mean halo mass, linear bias, and satellite fraction.Comment: Submitted to MNRAS, comments welcom