On the Uncontended Complexity of Anonymous Consensus

Consensus is one of the central distributed abstractions. By enabling a collection of processes to agree on one of the values they propose, consensus can be used to implement any generic replicated service in a consistent and fault-tolerant way. In this paper, we study uncontended complexity of anonymous consensus algorithms, counting the number of memory locations used and the number of memory updates performed in operations that encounter no contention. We assume that contention-free operations on a consensus object perform "fast" reads and writes, and resort to more expensive synchronization primitives, such as CAS, only when contention is detected. We call such concurrent implementations interval-solo-fast and derive one of the first nontrivial tight bounds on space complexity of anonymous interval-solo-fast consensus

DeepPrecip: A deep neural network for precipitation retrievals

Remotely-sensed precipitation retrievals are critical for advancing our understanding of global energy and hydrologic cycles in remote regions. Radar reflectivity profiles of the lower atmosphere are commonly linked to precipitation through empirical power laws, but these relationships are tightly coupled to particle microphysical assumptions that do not generalize well to different regional climates. Here, we develop a robust, highly generalized precipitation retrieval from a deep convolutional neural network (DeepPrecip) to estimate 20-minute average surface precipitation accumulation using near-surface radar data inputs. DeepPrecip displays high retrieval skill and can accurately model total precipitation accumulation, with a mean square error (MSE) 99 % lower, on average, than current methods. DeepPrecip also outperforms a less complex machine learning retrieval algorithm, demonstrating the value of deep learning when applied to precipitation retrievals. Predictor importance analyses suggest that a combination of both near-surface (below 1 km) and higher-altitude (1.5 &ndash; 2 km) radar measurements are the primary features contributing to retrieval accuracy. Further, DeepPrecip closely captures total precipitation accumulation magnitudes and variability across nine distinct locations without requiring any explicit descriptions of particle microphysics or geospatial covariates. This research reveals the important role for deep learning in extracting relevant information about precipitation from atmospheric radar retrievals.</p

Ensemble Properties of Comets in the Sloan Digital Sky Survey

We present the ensemble properties of 31 comets (27 resolved and 4 unresolved) observed by the Sloan Digital Sky Survey (SDSS). This sample of comets represents about 1 comet per 10 million SDSS photometric objects. Five-band (u,g,r,i,z) photometry is used to determine the comets' colors, sizes, surface brightness profiles, and rates of dust production in terms of the Af{\rho} formalism. We find that the cumulative luminosity function for the Jupiter Family Comets in our sample is well fit by a power law of the form N(< H) \propto 10(0.49\pm0.05)H for H < 18, with evidence of a much shallower fit N(< H) \propto 10(0.19\pm0.03)H for the faint (14.5 < H < 18) comets. The resolved comets show an extremely narrow distribution of colors (0.57 \pm 0.05 in g - r for example), which are statistically indistinguishable from that of the Jupiter Trojans. Further, there is no evidence of correlation between color and physical, dynamical, or observational parameters for the observed comets.Comment: 19 pages, 8 tables, 11 figures, to appear in Icaru

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

Diagnostic Value of (18)F-Fluorodeoxyglucose Positron Emission Tomography Computed Tomography in Prosthetic Pulmonary Valve Infective Endocarditis

OBJECTIVES: The aim of this study was to assess the diagnostic performances of (18)F-fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET)/computed tomography (CT) in congenital heart disease (CHD) patients with pulmonary prosthetic valve or conduit endocarditis (PPVE) suspicion. BACKGROUND: PPVE is a major issue in the growing CHD population. Diagnosis is challenging, and usual imaging tools are not always efficient or validated in this specific population. Particularly, the diagnostic yield of (18)F-FDG PET/CT remains poorly studied in PPVE. METHODS: A retrospective multicenter study was conducted in 8 French tertiary centers. Children and adult CHD patients who underwent (18)F-FDG PET/CT in the setting of PPVE suspicion between January 2010 and May 2020 were included. The cases were initially classified as definite, possible, or rejected PPVE regarding the modified Duke criteria and finally by the Endocarditis Team consensus. The result of (18)F-FDG PET/CT had been compared with final diagnosis consensus used as gold-standard in our study. RESULTS: A total of 66 cases of PPVE suspicion involving 59 patients (median age 23 years, 73% men) were included. Sensitivity, specificity, positive predictive value, and negative predictive value of (18)F-FDG PET/CT in PPVE suspicion were respectively: 79.1% (95% CI: 68.4%-91.4%), 72.7% (95% CI: 60.4%-85.0%), 91.9% (95% CI: 79.6%-100.0%), and 47.1% (95% CI: 34.8%-59.4%). (18)F-FDG PET/CT findings would help to correctly reclassify 57% (4 of 7) of possible PPVE to definite PPVE. CONCLUSIONS: Using (18)F-FDG PET/CT improves the diagnostic accuracy of the Duke criteria in CHD patients with suspected PPVE. Its high positive predictive value could be helpful in routine to shorten diagnosis and treatment delays and improve clinical outcomes.L'Institut de Rythmologie et modélisation Cardiaqu

Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition

A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009-2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, www.ebi.ac.uk/ena). The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world's planktonic ecosystems

Rare coding variants in ten genes confer substantial risk for schizophrenia

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, PPeer reviewe

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways