This repository contains the underlying data from benchmark experiments for Drifting Acoustic Instrumentation SYstems (DAISYs) in waves and currents described in "Performance of a Drifting Acoustic Instrumentation SYstem (DAISY) for Characterizing Radiated Noise from Marine Energy Converters" (https://link.springer.com/article/10.1007/s40722-024-00358-6). DAISYs consist of a surface expression connected to a hydrophone recording package by a tether. Both elements are instrumented to provide metadata (e.g., position, orientation, and depth). Information about how to build DAISYs is available at https://www.pmec.us/research-projects/daisy.

The repository's primary content is three compressed archives (.zip format), each containing multiple MATLAB binary data files (.mat format). A table relating individual data files to figures in the paper, as well as the structure of each file, is included in the repository as a Word document (Data Description MHK-DR.docx). Most of the files contain time series information for a single DAISY deployment (file naming convention: [site]_DAISY_[Drift #].mat) consisting of processed hydrophone data and associated metadata. For a limited number of DAISY deployments, the hydrophone package was replaced with an acoustic Doppler velocimeter (file naming convention: [site]_DAISY_[Drift #]_ADV.mat).

Data were collected over several years at three locations: (1) Sequim Bay at Pacific Northwest National Laboratory's Marine & Coastal Research Laboratory (MCRL) in Sequim, WA, the energetic tidal channel in Admiralty Inlet, WA (Admiralty Inlet), and the U.S. Navy's Wave Energy Test Site (WETS) in Kaneohe, HI. Brief descriptions of data files at each location follow.

• MCRL - (1) Drift #4 and #16 contrast the performance of a DAISY and a reference hydrophone (icListen HF Reson), respectively, in the quiescent interior of Sequim Bay (September 2020).
  (2) Drift #152 and #153 are velocity measurements for a drifting acoustic Doppler velocimeter in in the tidally-energetic entrance channel inside a flow shield and exposed to the flow, respectively (January 2018). (3) Two non-standard files are also included: DAISY_data.mat corresponds to a subset of a DAISY drift over an Adaptable Monitoring Package (AMP) and AMP_data.mat corresponds to approximately co-temporal data for a stationary hydrophone on the AMP (February 2019).

• Admiralty Inlet - (1) Drift #1-12 correspond to tests with flow shielded DAISYs, unshielded DAISYs, a reference hydrophone, and drifting acoustic Doppler velocimeter with 5, 10, and 15 m tether lengths between surface expression and hydrophone recording package (July 2022). (2) Drift #13-20 correspond to tests of flow shielded DAISYs with three different tether materials (rubber cord, nylon line, and faired nylon line) in lengths of 5, 10, and 15 m (July 2022).

• WETS - (1) Drift #30-32 correspond to tests with a heave plate incorporated into the tether (standard configuration for wave sites), rubber cord only, and rubber cord, but with a flow shielded hydrophone (November 2022). (2) Drift #49-58 and Drift #65-68 correspond to measurements around mooring infrastructure at the 60 m berth where time-delay-of-arrival localization was demonstrated for different DAISY arrangements and hydrophone depths (November 2022).

This data package contains data underlying the manuscript McDonald-Spicer et al., "Big data for a large clade: bioregionalisation and ancestral range estimation in the daisy family (Asteraceae)" presenting the results of research on the global biogeography and biogeographic history of the Asteraceae. It includes (1) a supermatrix of DNA sequence data obtained from GenBank and BOLD with partitioning information, (2) distribution data at the TDWG level 3, originally based on a database extract of the Global Compositae Checklist but subsequently cleaned and supplemented with additional data for some geographic areas, and (3) input files for ancestral area estimation using the R package BioGeoBEARS. Lineage: Spatial data

The spatial data set was based on data extracted from the GCC (compositae.landcareresearch.co.nz, accessed 15 Aug 2014), a database of distribution information for the Asteraceae family. We used OpenRefine (Huynh & Mazzocchi, 2014) to clean the dataset, correcting spelling of taxon names, collapsing varieties and subspecies to species level, and removing hybrids and taxa with distribution listed as ‘null’. Additional distribution information was added for New Zealand, the Cordoba Province in Argentina, Mongolia, South Africa, and Mexico. We removed species from regions where they are non-native. The final spatial dataset used in this study included 27,019 species representing 1,636 genera. All analyses were conducted using the TDWG level 3 of spatial resolution.

Phylogeny

Sequences from the nuclear ribosomal Internal Transcribed Spacer region (ITS) and three chloroplast regions (matK, rbcL, and trnL-trnF) were obtained from GenBank and BOLD (Ratnasingham & Hebert, 2007). We used genera as Operational Taxonomic Units and selected a representative sequence for each genus and locus.

Gene regions were individually aligned using MAFFT 7 (Katoh & Standley, 2013) and manually edited in Bioedit 7.0.5 (Hall, 1999). The four sequence regions were combined into a supermatrix of 1,273 genera and 9,030 characters. The phylogeny was inferred using RAxML (Stamatakis, 2014) under the GTRCAT model and partitioning by sequence region. The tree was rooted on the Barnadesieae, which are sister to the rest of the family (Funk et al., 2005).

Time calibration

We time calibrated our phylogeny using Penalized Likelood as implemented in the chronos function of the R package APE (Sanderson, 2002; Paradis et al., 2004; R Core Team, 2016). We set nine calibration points (Appendix S3 of the manuscript). We tested all three implemented clock models (relaxed, correlated, and discrete) and lambda values of 1 and 10. The favoured clock model was discrete with lambda = 10.

About this dataset

Context

The dataset tabulates the Daisy population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Daisy. The dataset can be utilized to understand the population distribution of Daisy by age. For example, using this dataset, we can identify the largest age group in Daisy.

Key observations

The largest age group in Daisy, GA was for the group of age 10 to 14 years years with a population of 77 (17.42%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Daisy, GA was the 25 to 29 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Daisy is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Daisy total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

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This dataset is a part of the main dataset for Daisy Population by Age. You can refer the same here

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This data package contains data underlying the manuscript McDonald-Spicer et al., "Big data for a large clade: bioregionalisation and ancestral range estimation in the daisy family (Asteraceae)" …Show full descriptionThis data package contains data underlying the manuscript McDonald-Spicer et al., "Big data for a large clade: bioregionalisation and ancestral range estimation in the daisy family (Asteraceae)" presenting the results of research on the global biogeography and biogeographic history of the Asteraceae. It includes (1) a supermatrix of DNA sequence data obtained from GenBank and BOLD with partitioning information, (2) distribution data at the TDWG level 3, originally based on a database extract of the Global Compositae Checklist but subsequently cleaned and supplemented with additional data for some geographic areas, and (3) input files for ancestral area estimation using the R package BioGeoBEARS. The metadata and files (if any) are available to the public.

Acoustic data and metadata from Drifting Acoustic Instrumentation SYstem (DAISY) testing in Agate Pass (separating the north end of Bainbridge Island and the Kitsap Peninsula in Puget Sound), WA in April 2022. The goal was to characterize radiated noise from a cross-flow turbine deployed from a moored vessel. As discussed in the accompanying report, sound produced by the turbine was below the ambient nose floor at the surveyed ranges.

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was not consistent for all children. There were 47 of the children who had samples taken and evaluated prior to IA (Pre-IA), and 131 children had measurements at or after IA, but prior to diagnosis of clinical T1D (Post-IA). The control children were frequency matched on HLA genotypes and age and sex with an observed lower frequency of first degree relatives within the control group versus the cases For machine learning the children that will develop islet autoantibodies the 40 control and 47 Pre-IA children were down-selected to a single sample time point. For the 40 control children this was the earliest sample collected and for the 47 Pre-IA children it was a random selection of the first or second time point prior to the detection of autoantibodies to assure the age distributions were not significantly different.

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The DAISIE - inventory of alien invasive species in Europe is a species checklist dataset published by the Research Institute for Nature and Forest (INBO) and the Centre for Ecology and Hydrology (CEH). It contains information on 12,104 taxa (mostly species and mostly introduced) occurring in the wild in Europe since 1500. It covers a broad taxonomic spectrum of terrestrial and aquatic free living and parasitic organisms. The collation of the alien species list is the result of the efforts of the DAISIE (http://www.europe-aliens.org/) project partners and more than 300 collaborators from Europe and neighbouring countries, involved in different fields of expertise and organisations. Here the DAISIE checklist is published as a standardized Darwin Core Archive and includes for each species: the scientific name, higher classification, and stable taxon identifier (in the taxon core), the vernacular names (in the vernacular names extension), the presence in a specific region, the year of the first introduction (first collection) and/or last assessment/observation in that region, as well as extra information (in the distribution extension), and the habitat, native range, and ecofunctional group (in the description extension). The DAISIE dataset is no longer maintained, but can be used as a historical archive for researching and managing alien plants or compiling regional and national registries of alien species. Issues with the dataset can be reported at https://github.com/trias-project/daisie-checklist

We have released this dataset under a Creative Commons Attribution license (CC-BY 4.0). We would appreciate it if you follow the GBIF citation guidelines (https://www.gbif.org/citation-guidelines) when using the data. If you have any questions regarding this dataset, don’t hesitate to contact us via the contact information provided in the metadata or via https://twitter.com/trias_project.

The publication of the checklist to GBIF was supported by the European Cooperation in Science and Technology (COST) action Alien CSI “CA17122 - Increasing understanding of alien species through citizen science” as a Short Term Scientific Mission “Publishing alien species checklist data for Europe through repeatable, open workflows”, with technical support provided by the Research Institute for Nature and Forest (INBO).

Acoustic data and metadata from Drifting Acoustic Instrumentation SYstem (DAISY) testing in Admiralty Inlet (connecting Puget Sound to the Strait of San Juan de Fuca) in July 2022. Tests focused on occurrences of flow noise for three hydrophone package variants and on the potential for alternative tether materials.

Here we present the map of potential suitable habitat for Parish’s daisy (Erigeron parishii). The data indicate both how many models predicted each location to be potentially suitable for the species and the average standardized habitat suitability score for each location.Data are presented at a spatial resolution of 10 m pixels, which was required to harmonize the original model inputs. However, maps of suitable habitat should be used at a resolution no smaller than 360 m (i.e., 36 pixels x 36 pixels), which corresponds with the resolution of the coarsest model input. These data are intended to be used only to target future plant surveys in areas where new occurrences are most likely to benefit future habitat modelling efforts. Complete methods and other additional information are provided in the article associated with this data release (Reese and others, 2019).

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About this dataset

Context

The dataset tabulates the Daisy population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Daisy.

Content

The dataset constitues the following two datasets across these two themes

• Daisy, GA Population Breakdown by Gender
• Daisy, GA Population Breakdown by Gender and Age

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

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