The George Washington dataset contains 20 pages of letters written by George Washington and his associates in 1755 and thereby categorized into historical collection. The images are annotated at word level and contain approximately 5,000 words.

GW

## Overview

GW is a dataset for object detection tasks - it contains GreatWall annotations for 261 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Groundwater basin divides within the Floridan Aquifer System include the Dougherty Plain Apalachicola, Southeast Georgia, Northeast Florida, South Carolina, Panhandle, Thomsville-Tallahasse Suwannee, West Central Florida, East Central Florida and South Florida.

A dataset of HOMO/LUMO energies of the QM9 dataset computed at GW level of theory.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

The Hunter groundwater model. This was created using the preprocess.py script in the "HUN GW Model code v01" acting on the index.xml file contained in the top-level directory of this dataset. The index.xml file contains provenance information for the raw-data (HUN GW Model Mines raw data v01) and tells the preprocessing scripts where to find this raw data. As the groundwater model is successively built using the python scripts, provenance is successively added to the files generated (as headers, or similar data structures). The exception to this is the finite-element mesh (mesh3D/mesh3D.*) which is the main output of the process, and which eventually contains such an enormous amount of provenance that the code suffers from buffer overflows: therefore its provenance is dumped to mesh3D/provenance_dump periodically.

As the scripts gradually build the groundwater model, they modify index.xml: it acts as a journal file for model creation, allowing provenance backtracking when using any standard xml viewer.

The final MOOSE input files are found in the "simulate" directory, and an example of the final MOOSE output is the "HUN GW Model simulate ua999 pawsey v01" dataset.

Dataset History

Created using preprocess.py found in the "HUN GW Model code v01" dataset, acting on the index.xml file, and hence using the raw data found in the "HUN GW Model Mines raw data v01" dataset.

Dataset Citation

Bioregional Assessment Programme (XXXX) HUN GW Model v01. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/90554dbf-4992-49ec-98b1-53c6067e97a2.

Dataset Ancestors

• Derived From HUN GW Model code v01

• Derived From HUN GW Model Mines raw data v01

Kalinka, Cube+GW

## Overview

Kalinka, Cube+GW is a dataset for object detection tasks - it contains Bacteriosis annotations for 655 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset tracks annual distribution of students across grade levels in G.w.stout Elementary School

In 2020, GW Pharmaceuticals reported a net loss of around 58 million U.S. dollars, which is a significant improvement from nearly 300 million U.S. dollars of reported loss in 2018. This statistic illustrates the net loss of GW Pharmaceuticals worldwide from 2017 to 2020. In May 2021, the company was acquired by Ireland-based biopharma company Jazz Pharmaceuticals.

This dataset tracks annual diversity score from 1992 to 2023 for G.w.stout Elementary School vs. New Mexico and Silver City School District

This shapefile forms part of the output from the Stampriet Transboundary Aquifer System Project: http://wis.orasecom.org/stas

This dataset tracks annual distribution of students across grade levels in Gw Long Elementary School

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

Shapefile of Hunter mine footprints used for Groundwater modeling.

Dataset History

Kmz files from the source data were converted to shapefile polygons using ArcGIS conversion tools.

Dataset Citation

Bioregional Assessment Programme (XXXX) HUN Mine footprints for GW modelling v01. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/93f99710-e84a-41c0-9c4f-4da9712c3263.

Dataset Ancestors

• Derived From HUN Groundwater footprint kmz files v01

• Derived From HUN Groundwater footprint polygons v01

LangAGI-Lab/step-wise-eval-description-with-refined-tao-raw-neg_actions-gw dataset hosted on Hugging Face and contributed by the HF Datasets community

Data set is a delination of groundwater basins in NM. Updated September 2005 with the declaration of all the existing declared basins by extension.

GEF Project gw

As of December 2020, GW Pharmaceuticals had around 753 employees in the United Kingdom, while there were 358 employees in North America. This statistic illustrates the number of employees at GW Pharmaceuticals worldwide, by geography. In May 2021, the company was acquired by Ireland-based biopharma company Jazz Pharmaceuticals.

As of December 2020, GW Pharmaceuticals had around 355 employees in the area of research and development, while there were 218 employees in management and administration. This statistic illustrates the number of employees at GW Pharmaceuticals worldwide, by function. In May 2021, the company was acquired by Ireland-based biopharma company Jazz Pharmaceuticals.

Sendal Gw Hilang

## Overview

Sendal Gw Hilang is a dataset for object detection tasks - it contains Shoe Sendal annotations for 483 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The GW domain or cell wall targeting (CWT) signal is a module of about 80-90 amino acids named for a conserved Gly-Trp (GW) dipeptide. GW domains have only been identified in Gram-positive bacteria and form a small protein family. They are divergent members of the SH3 family. However, GW domains are unlikely to mimic SH3 domains functionally, as their potential peptide-binding sites are destroyed or blocked. GW domains constitute a motif for cell-surface anchoring in Listeria and other Gram-positive bacteria . The GW domains bind polyanions, including lipoteichoic acid (LTA), on the bacterial surface and heparan sulfate of host cell surface heparan sulfate proteoglycans (HSPGs); binding to the latter enhances human receptor tyrosine kinase MET activation through the internalin domain .The GW domain is composed of seven β-strands, five of which are organized into an open barrel conformation like the SH3 domains one. The eponymous GW dipeptide, located in the fourth β-strand, is more conserved in GW domains than in SH3 domains. Both the glycine and tryptophan are buried in GW proteins, while the equivalent residues in SH3 proteins are surface accessible, perhaps explaining the greater conservation in GW proteins .

This dataset tracks annual total students amount from 1987 to 2023 for G.w.stout Elementary School