Summary:

This paper contains the quantitative data from several interviews along with a used questionnaire for empirically investigating the software quality models created in the project Quamoco.

Summary: This dataset represents oyster density measurements of restored reef edge/interior in Quonochontaug Pond, Rhode Island, USA determined by scuba divers in May of 2019. Reef relief and quadrat relief were calculated by subtracting water depth at each quadrat (quadrat relief) or the highest point on the reef (reef relief) from water depth on the adjacent unstructured bottom. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/881536

Summary: Abundance and proportion of ichthyoplankton of the Northeast U.S. Shelf. Ichthyoplankton data from several surveys conducted during the Marine Resources Monitoring, Assessment, and Prediction (MARMAP; 1977-1987) and Ecosystem Monitoring (EcoMon; 1999-2008) programs. The Northeast Fisheries Science Center (NEFSC) has conducted several ichthyoplankton collection programs on the NEUS Shelf over the past forty years including the Marine Resources Monitoring, Assessment, and Prediction program (MARMAP, 1977 - 1987) and Ecosystem Monitoring (EcoMon, 1999 - present) program (Richardson et al. 2010). Both MARMAP and EcoMon were designed as multi-species plankton surveys, and sampling effort covered the entire NEUS Shelf from Cape Hatteras, North Carolina, to Cape Sable, Nova Scotia (Figure 1, Sibunka and Silverman 1984, 1989; Richardson et al. 2010). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/560448

Summary: This dataset summarizes independent studies of nekton taxa associated with oyster reefs off of the Atlantic and Gulf Coasts of the United States. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/845755

Summary: Zooplankton data are the number of organisms beneath 10 m^2 of sea surface from several surveys including: ICNAF, MARMAP, HERRING, ECOMON as well as perhaps several others, and hundreds of cruises. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/3327

Summary: Daily temperature measurements were collected on restored oyster reefs in Quonochontaug Pond, Rhode Island, USA in the summer (July-August) 2018 and the fall (September-October) of 2018. Bottom water temperatures were collected hourly during tray deployment using one Onset Tidbit v2 HOBO temperature logger per block in summer 2018 and one logger at both the edge and interior of 3 reefs (one per block) in fall 2018. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/881834

Summary: This dataset describes phenotypic plasticity in sand dollars in response to predators at the Friday Harbor Laboratories, WA, USA and in sea urchins from Southern Maine, USA from 2018 to 2019. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/877780

Summary: Abundance and proportion of adult fish species of the Northeast U.S. Shelf; bottom trawl surveys were conducted by the Northeast Fisheries Science Center (NEFSC) during 1977-1987 and 1999-2008. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/560342

Summary: This dataset contains results from experiments comparing reef-associated community colonization among oyster reef and sand habitats in Quonochontaug Pond, Rhode Island, USA. Experimental sampling trays were deployed and assigned to four experimental treatments. Trays were deployed by divers on SCUBA on July 10, 2018 (summer) and September 7, 2018 (fall) and were leveled with the surrounding substrate by carefully excavating the surrounding reef material (interior treatment) or sediment (edge, shell, and sand treatments). After 28-29 days, divers collected the trays and associated fauna were measured. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/881801

Summary: Conductivity, temperature, depth and salinity data from the TBeam A1 mooring deployed in 4768-m of water in the Tasman Sea between January 10 and February 28, 2015. Data is provided in both NetCDF and Matlab format. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/818958

Summary: ADCP data from the TBeam A1 mooring deployed in 4768-m of water in the Tasman Sea between January 10 and February 28, 2015. Data is provided in both NetCDF and Matlab format. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/818953

Summary: Zooplankton data are the number of organisms per 100 m^3 of water sampled from several surveys including: ICNAF, MARMAP, HERRING, ECOMON as well as perhaps several others, and hundreds of cruises. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/3328

Summary:

A major refactor of the build infrastructure.

Summary: Fixed

• FlowETL QA checks with template sections conditional on the cdr_type argument now render correctly. #3479

Summary:

Structural Models (PDB) of SARS-CoV-2 Spike RBD bound to ACE2 receptors of 215 animals.

Structural model of Human TMPRSS2.

Modelled using the FunMod pipeline and referenced in the preprint

SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals

 

Summary: Added

• The issuer name can now be set for FlowAuth's 2factor authentication using the FLOWAUTH_TWO_FACTOR_ISSUER environment variable.

• FlowAPI's internal port can now be set using the FLOWAPI_PORT environment variable, but continues to default to 9090. #2723

  With thanks to JIPS for supporting this work.

• FlowETL's default port can now be set using the FLOWETL_PORT environment variable, but continues to default to 8080. #2724

  With thanks to JIPS for supporting this work.

Changed

• Test and synthetic DFS data now uses the same pool of subscribers as CDR data. #2713

  With thanks to JIPS for supporting this work.

Summary: Added

• histogram_aggregate added to FlowAPI and FlowClient. Allows the user to obtain a histogram over a per-subscriber metric. #1076

Summary:

nbgrader version 0.5.5 is a release for the Journal of Open Source education,
with the following PRs merged:

• PR #1057: Ensure consistency in capitalizing Jupyter Notebook
• PR #1049: Update test builds on Travis
• PR #1047: JOSE paper bib updates
• PR #1045: Dev requirements and spelling tests
• PR #1016: Fix anaconda link
• PR #973: Create a paper on nbgrader

Thanks to the following users who submitted PRs or reported issues that were fixed for the 0.5.5 release:

• jedbrown
• jhamrick
• swarnava
• willingc

Summary:

This repository contains all publicly available numerical relativity surrogate data for waveforms produced by the Spectral Einstein Code. The base method for building surrogate models can be found in Field et al., PRX 4, 031006 (2014).

Several numerical relativity surrogate models are currently available in this catalog:

1. SpEC_q1_10_NoSpin_nu5thDegPoly_exclude_2_0.h5 — A surrogate model for binary black hole mergers with non-spinning black holes. This is described in Blackman et al., PRL 115, 121102 (2015). It is evaluated with the gwsurrogate python package, which can be found on PyPI. Instructions for evaluating this surrogate can be found in tutorials included with the gwsurrogate package and in this example IPython code.

2. NRSur4d2s_FDROM_grid12.h5 and NRSur4d2s_TDROM_grid12.h5 — These are fast frequency-domain and time-domain (respectively) surrogate models for binary black hole mergers where the black holes may be spinning, but the spins are restricted to a parameter subspace which includes some but not all precessing configurations. NRSur4d2s_FDROM_grid12.h5 is the NRSur4d2s_FDROM model described in Blackman et al., PRD 95, 104023, (2017), and NRSur4d2s_TDROM_grid12.h5 is built from the underlying (slower) NRSur4d2s time-domain model in the same way but without the FFTs. These surrogates are also evaluated using gwsurrogate, and a tutorial can be found in this example IPython code.

3. NRSur7dq2.h5 — This is a surrogate model for binary black hole mergers with generic spins. A paper describing it can be found at Blackman et al., PRD 96, 024058 (2017). This surrogate is evaluated through a standalone python package contained in NRSur7dq2.tar.gz, which has simple installation instructions in its README file. A tutorial can be found for evaluating this surrogate in this example IPython code.

 

If you find these surrogate models useful in your own research please cite the Field et al., PRX (2014) paper as well as the relevant paper describing the specific numerical relativity surrogate model, if available (e.g., the Blackman et al. 2015 paper for non-spinning binary black hole coalescences).

Caveats:

1. Evaluating surrogate models outside of the ranges they were trained upon may give inaccurate results. Please use with caution when extrapolating.

2. The surrogate data available here for non-spinning binary black holes produced in Blackman et al. 2015 contains the (2,0) mode. However, this mode was not used in the paper. While this surrogate can predict a (2,0) mode, current numerical relativity simulations may not yet be able to accumulate (non-oscillatory) Christodoulou memory sufficiently. The surrogate (2,0) mode is founded upon basis SpEC waveforms that have been hybridized with leading order post-Newtonian waveforms. Therefore, the (2,0) mode can be included in the mode’s output but should be used with caution. Currently, the default option to evaluate this surrogate (using GWSurrogate) is to exclude all m=0 modes.