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Fecal contamination is a significant source of water quality impairment globally. Aquatic ecosystems can provide an important ecosystem service of fecal contamination removal. Understanding the processes that regulate the removal of fecal contamination among river networks across flow conditions is critical. We applied a river network model, the Framework for Aquatic Modeling in the Earth System (FrAMES-Ecoli), to quantify removal of fecal indicator bacteria by river networks across flow conditions during summers in a series of New England watersheds of different characteristics. FrAMES-Ecoli simulates sources, transport, and riverine removal of Escherichia coli (E. coli). Aquatic E. coli removal was simulated in both the water column and the hyporheic zone, and is a function of hydraulic conditions, flow exchange rates with the hyporheic zone, and die-off in each compartment. We found that, at the river network scale during summers, removal by river networks can be high (19–99%) with variability controlled by hydrologic conditions, watershed size, and distribution of sources in the watershed. Hydrology controls much of the variability, with 68–99% of network scale inputs removed under base flow conditions and 19–85% removed during storm events. Removal by the water column alone could not explain the observed pattern in E. coli, suggesting that processes such as hyporheic removal must be considered. These results suggest that river network removal of fecal indicator bacteria should be taken into consideration in managing fecal contamination at critical downstream receiving waters. 

A bstract We calculate the two-loop QCD corrections to gg → ZZ involving a closed top-quark loop. We present a new method to systematically construct linear combinations of Feynman integrals with a convergent parametric representation, where we also allow for irreducible numerators, higher powers of propagators, dimensionally shifted integrals, and subsector integrals. The amplitude is expressed in terms of such finite integrals by employing syzygies derived with linear algebra and finite field techniques. Evaluating the amplitude using numerical integration, we find agreement with previous expansions in asymptotic limits and provide ab initio results also for intermediate partonic energies and non-central scattering at higher energies. 

First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range of applications of modern machine learning to event generation and simulation-based inference, including conceptional developments driven by the specific requirements of particle physics. New ideas and tools developed at the interface of particle physics and machine learning will improve the speed and precision of forward simulations, handle the complexity of collision data, and enhance inference as an inverse simulation problem. 

Abstract. The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID.