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4,486 results for “exploration”
Exploration of historical mining site - Mezzano iron mines (San Bartolomeo, Cavargna Valley, Italy, 06/01/2024)
<p>Exploration of the historical mining site of Mezzano (San Bartolomeo, Cavargna Valley, Italy, 06/01/2024)</p> <p>- Main ore minerals: pyrite, chalcopyrite, siderite, aragonite</p> <p>- Provisional References:</p> <ul> <li>https://www.valcavargna.org/luoghi_di_interesse/miniere-di-mezzano/#:~:text=Le%20miniere%20di%20Mezzano&text=A%20partire%20dagli%20ultimi%20anni,Fratelli%20Campioni%20l'anno%20seguente.</li> <li>https://www.isprambiente.gov.it/it/attivita/museo/regioni/musei/miniera-di-mezzano</li> <li>https://www.valcavargna.org/tradizioni_popolari/vecchi-mestieri/siderurgia/</li> <li>https://www.research.unipd.it/handle/11577/3465257</li> <li>http://www.cmalpilepontine.it/cmvlarcer/zf/index.php/servizi-aggiuntivi/index/index/idtesto/13</li> </ul>
Reproduction package for the paper "Exploring the directly imaged HD 1160 system through spectroscopic characterization and high-cadence variability monitoring"
<p>This is a basic reproduction package for the paper <a href="https://doi.org/10.1093/mnras/stae1315">"Exploring the directly imaged HD 1160 system through spectroscopic characterization and high-cadence variability monitoring" by Sutlieff et al. (2024)</a>. It aims to provide the most important data products to check and reproduce the main results of the paper.</p>
The Netherlands - China Low Frequency Explorer signal chain pre launch test-data. (version 1.0)
<p>The Netherland Chinese Low Frequency Explorer Pre launch system ground test results with analog and digital signal chain. The tests include the instrument in various experiment settings that are avalable as pre-set functions during the observation phase.</p> <p>The data set is processed to L1B data, a script is provided together with the data to process this and plot the power spectra for all the monopole antennas.</p> <p> </p>
Exploring the Relationship Between Upper Ocean States and the Falling Ice Radiative Effects using ECCO Product and Global Climate Models
<p><strong><span>Sensitivity test using CESM1-CAM5 following CMIP5 protocool from 1980-2005</span></strong></p> <p><strong><span>NOS: no falling ice radiative effects (FIREs), four data sets</span></strong></p> <p><strong><span>SON: with FIREs, for data sets</span></strong></p> <p><strong><span> Xsize = 362 Ysize = 182 Zsize = 18</span></strong></p> <p><strong><span>Format: netcdf</span></strong></p> <p><strong><span>Upper 200 meter ocean variables</span></strong></p> <p><strong><span>Annual mean (ANN)</span></strong></p> <p><strong><span>CESM2-var-NOS (or SON)-ANN.nc, var = (UO, VO, WO, TO) = (zonal velocity, meridional velocity, ascending velocity, potential temperature) : (cm/s, cm/s, cm/s, K)</span></strong></p>
EFSA Project on the use of NAMs to explore interspecies metabolic differences on essential oils as feed additives (Annexes A, B, C, D)
<p>Raw data of phase I and II experiments and PBK model input data and simulation of the EFSA Project on the use of NAMs to explore interspecies metabolic differences on essential oils as feed additives (OC/EFSA/SCER/2021/14).</p>
Methodological and practical lessons learned from exploring the material criticality of two hydrogen-related products
<p>As the European Union embarks on the energy transition, several challenges need to be faced to ensure that this shift is conducted from a holistic perspective that avoids burden-shifting across sustainability dimensions. One of the main concerns refers to the future availability of materials that clean technologies require. Critical raw<br>material assessment serves to guide the management of such mineral resources in a new paradigm of increasing demand. This work delves into the methodological fundamentals of several product-level criticality indicators in order to discuss their implications within the context of the ecodesign of two hydrogen-related products. Overall, criticality is advised to be assessed making use of several indicators. In the case study of a proton exchange membrane fuel cell stack, the combined interpretation of criticality indicators leads to identifying platinum as the main hotspot, while yttrium and lanthanum account for the most relevant criticality contributions in the case<br>study of a solid oxide electrolysis cell stack.</p>
Dataset for: Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manusript:<br> Perrier L, Blondal E, MacDonald H. Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies. 2018; 40(3-4): 173-183. doi: 10.1016/j.lisr.2018.08.002</p> <p>Full-text available at: <a href="https://doi.org/10.1016/j.lisr.2018.08.002">https://doi.org/10.1016/j.lisr.2018.08.002</a> </p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset:</p> <ol> <li>Data Dictionary: RDMMetaEthnography_DataDictionary_v1.pdf</li> <li>Data Abstraction Sheet: RDMMetaEthnography_StudyCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_ParticipantCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_Outcomes.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_COREQ,csv</li> </ol> <p>Contact: Laure Perrier: <a href="https://orcid.org/0000-0001-9941-7129">orcid.org/0000-0001-9941-7129</a></p>
Exploring mechanisms that affect coral cooperation: symbiont transmission mode, cell density and community composition
<p>This repository contains code to accompany the manuscript titled</p> <p><strong>Exploring mechanisms that affect coral cooperation: symbiont transmission mode, cell density and community composition</strong></p> <p>by <strong>Carly D. Kenkel and Line K. Bay</strong><br> </p> <p>In this study, we used a phylogenetically controlled design to investigate the role of vertical symbiont transmission, an evolutionary mechanism predicted to enhance cooperation and holobiont fitness of reef-building corals. Six species of coral, three vertical transmitters and their closest horizontally transmitting relatives, were fragmented and subjected to a two-week thermal stress experiment. Symbiont cell density, photosynthetic function and translocation of photosynthetically fixed carbon between symbionts and hosts were quantified to assess changes in physiological metrics of fitness and cooperation. Amplicon sequencing of the <em>Symbiodinium</em> ITS-2 locus was used to investigate differences in symbiont community composition among focal species. We did not observe universally higher levels of cooperation in vertically transmitting species. However, the reduction in cooperation at the onset of bleaching was marginally associated with symbiont community diversity. Analysis of ITS2 amplicon sequence data suggest that it may not be vertical transmission <em>per se</em> that influences host-symbiont cooperation, but genetic uniformity of the symbiont community.</p> <p>Repository contents:</p> <ul> <li> <p><strong>TraitDataAnalysis.R:</strong> Annotated R script for generating figures and re-creating statistical analyses</p> <ul> <li> <p><strong>RsquaredGLMM.R:</strong> Accessory R script for running RsquaredGLMM analyses, called by <strong>TraitDataAnalysis.R</strong></p> </li> <li> <p><strong>NSF_RunningPam.csv</strong>: Input file for statistical analysis. Contains photophysiological data. Column headers are as follows:</p> <ul> <li> <p>Tank: Number of experimental tank in which experimental coral fragment was held</p> </li> <li> <p>Treatment: short-hand notation for sample treatments (e.g. ctrl1-5 = control temperature, genotypes 1-5)</p> </li> <li> <p>Water: source sump for temperature controlled water jackets for each set of treatment tanks</p> </li> <li> <p>Position: numerical rack position of coral fragment within experimental treatment tank</p> </li> <li> <p>Species: Coral species (Amil=<em>A. millepora</em>, Maqe=<em>M. aequituberculata</em>, Gast=<em>G. astreata</em>, Gach=<em>G. acrhelia</em>, Plob=<em>P. lobata</em>, Gcol=<em>G. columna</em>)</p> </li> <li> <p>Genotype: source colony origin of individual coral fragments within species</p> </li> <li> <p>Temp: experimental temperature treatment (ctrl: 27°C ; heat: 31°C)</p> </li> <li> <p>Treat: whether experimental corals received C14-labeled bicarbonate (bicarb), artemia or were sampled separately for Gene Expression Analysis (not presented in this manuscript)</p> </li> <li> <p>EQY: Effective quantum yield of <em>Symbiodinium</em> photosystem II as measured using PAM fluorometry</p> </li> <li> <p>Date: Actual calendar date of measure</p> </li> <li> <p>Transmission: coral symbiont transmission mode</p> </li> <li> <p>Reef: reef site of original coral collection</p> </li> <li> <p>Date: experimental date of measure</p> </li> </ul> </li> <li> <p><strong>TraitData.csv:</strong> Input file for statistical analysis. Contains all physiological trait data.</p> <ul> <li> <p>Includes columns as described above for the Running_Pam file in addition to columns containing raw trait data as described in the manuscript.</p> </li> </ul> </li> <li> <p><strong>TraitData_DaysAsCols.csv:</strong> Reformatted input file with trait data split by sampling day across columns</p> </li> </ul> </li> <li> <p><strong>DADA2Analysis.R:</strong> Annotated R script for generating figures and running ITS2 amplicon analyses</p> <ul> <li> <p>GeoSymbio_ITS2_LocalDatabase_verForPhyloseq.fasta: FASTA file of the GeoSymbio ITS2 reference database <a href="https://sites.google.com/site/geosymbio/">https://sites.google.com/site/geosymbio/</a>, formatted for use with the R prograom Phyloseq</p> </li> <li> <p>SeqVars_6Feb.fasta: FASTA file of identified sequence variants resulting from DADA2 analysis</p> </li> <li> <p>OutputDADA_6Feb.csv: Counts of sequence variants by sample</p> </li> <li> <p>Raw FASTQ paired end read files can be downloaded from NCBI's SRA: PRJNA338365</p> </li> </ul> </li> </ul>
Exploring the age dependent properties of M and L dwarfs using Gaia and SDSS: The Sample
<p>Sample from "Exploring the age dependent properties of M and L dwarfs using Gaia and SDSS". We present a sample of 74,216 M and L dwarfs constructed from two existing catalogs of cool dwarfs spectroscopically identified in the Sloan Digital Sky Survey (SDSS). We cross-matched the SDSS catalog with Gaia DR2 to obtain parallaxes and proper motions and modified the quality cuts suggested by the Gaia Collaboration to make them suitable for late-M and L dwarfs. </p>
Regional Aspects of a Climate and Energy Tax Reform in Norway—Exploring Double and Multiple Dividends
<p>Results for the different scenarios described in Table 4.</p>
Counting Words That Count: NLP for exploring Romanian Parliament Transcripts
<p>The data is obtained by scraping the cdep.ro website and contains 500k+ instances of speech from the parliament podium from 1996 to 2019. (Up to 2001 only the Chamber of Deputies published transcripts, after jan. 2001 Senate data is also included.) <br> <br> Columns: </p> <p>'index' - incremented integer as row number in order of scraping</p> <p>'title', - title of the scraped page, usually contains the name of the chamber and the exact data</p> <p>'name', - the name of the speaker, preappended with Mr. or Mrs. </p> <p>'speech', - the content of the speech, </p> <p>'gender', - the gender of the speaker</p> <p>'url' - the url to the profile of the speaker (useful for extending the data)</p> <p> </p> <p>CDEPs2.csv - Contains all transcripts, prone to parsing errors. 100% of data.</p> <p>validated-1.csv - Consists of 99% of original data. Less than 1% dropped for convenience. Ready to use.</p>
Extended data of the project "A survey exploring biomedical editors' perceptions of editorial interventions to improve adherence to reporting guidelines"
<p>Figure S1: Survey questionnaire</p> <p>Table S2: Barriers, facilitators and possible improvements of the interventions included in the survey</p>
Exploring chemical space in the search for improved Azoheteroarene-based photoswitches
<p>In the quest for improved photo switches, azoheteroarenes have emerged as a potential alternative to azobenzene. However, to date the number and types of these species that have subjected to study is insufficient to provide an in-depth understanding of the photochemical effects brought about by different substituents. Here, we computationally screen the optical properties and thermal stabilities of 512 azoheteroarenes that consist of eight different N-containing heteroarenes combined with 64 substitution patterns. The most promising compounds are identified and their properties rationalized based on the nature of the azoheteroarene core and the location and type of substitution patterns.</p>
NOAA NCCOS Assessment: Prioritizing Areas for Future Seafloor Mapping, Research, and Exploration Offshore of California, Oregon, and Washington from 2019-03-01 to 2019-04-01
<p>Spatial information about the seafloor is critical for decision-making by marine resource science, management and tribal organizations. Coordinating data needs can help organizations leverage collective resources to meet shared goals. To help enable this coordination, the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) developed a spatial framework, process and online application to identify common data collection priorities for seafloor mapping, sampling and visual surveys offshore of the West Continental United States Coast (WCC). Twenty-six participants from NOAA’s West Coast Deep Sea Coral Initiative (WCDSCI) and Expanding Pacific Research and Exploration of Submerged Systems (EXPRESS) entered their priorities in an online application, using virtual coins to denote their priorities in 10x10 minute grid cells. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important and what data types were needed. Results were analyzed and mapped using statistical techniques to identify significant relationships between priorities, reasons for those priorities and data needs. Ten high priority locations were broadly identified for future mapping, sampling and visual surveys. These locations were distributed throughout the WCC, primarily in depths less than 1,000 m. Participants consistently selected (1) Exploration, (2) Biota/Important Natural Area and (3) Research as their top reasons (i.e., justifications) for prioritizing locations, and (1) Benthic Habitat Map and (2) Bathymetry and Backscatter as their top data or product needs. This ESRI shapefile summarizes the results from this spatial prioritization effort. This information will enable NOAA WCDSCI, EXPRESS and other WCC organization to more efficiently leverage resources and coordinate their mapping of high priority locations along California, Oregon and Washington. </p> <p>This effort was funded by NOAA’s Deep Sea Coral Research and Technology Program (DSCRTP) through its WCDSCI. The overall goal of the project was to systematically gather and quantify suggestions for seafloor mapping, sampling and visual surveys for the WCDSCI and EXPRESS. The results are expected to help WCDSCI, EXPRESS and other organizations on the WCC to identify locations where their interests overlap with other organizations, to coordinate their data needs and to leverage collective resources to meet shared goals.</p> <p>There were four main steps in the WCC spatial prioritization process. The first step was to identify the technical advisory team, which included the 11 members of the DSCRTP WCDSCI Steering Committee and all of the participants involved in the EXPRESS campaign. This advisory team invited 37 participants for the prioritization. Step two was to develop the spatial framework and an online application. To do this, the WCC was divided into five subregions and 3,265 square grid cells approximately 10x10 minutes in size. Existing relevant spatial datasets (<em>e.g.</em>, bathymetry, protected area boundaries, etc.) were compiled to help participants understand information and data gaps and to identify areas they wanted to prioritize for future data collections. These spatial datasets were housed in the online application, which was developed using Esri’s Web AppBuilder. In step three, this online application was used by 26 participants to enter their priorities in each subregion of interest. Participants allocated virtual coins in the 10x10 minute grid cells to denote their priorities. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important and what data types were needed. Coin values were standardized across the subregions and used to identify spatial patterns across the WCC region as a whole. The number of coins were standardized because each subregion had a different number of grid cells and participants. Standardized coin values were analyzed and mapped using statistical techniques, including hierarchical cluster analysis, to identify significant relationships between priorities, reasons for those priorities and data needs. This ESRI shapefile contains the 10x10 minute grid cells used in this prioritization effort and associated the standardized coin values overall, as well as by organization, justification and product. For a complete description of the process and analyses please see: Costa <em>et al</em>. 2019.</p>
Monitoring and evaluation of UKRI's Open Access Policy: Exploring the use of open data sources to inform baseline values - Dataset
<p>This dataset accompanies the report <em>"Monitoring and evaluation of UKRI's Open Access Policy: Exploring the use of open data sources to inform baseline values"</em>, which is available via Zenodo.<br><br>It provides record-level data of UKRI-funded and UK-affiliated research output (limited to journal articles with Crossref DOIs) published between 2012 and 2022 - including bibliographic metadata as well as data on open access availability, publisher, national and international collaborations, citations, views and downloads, altmetrics and subjects (fields). All variables are documented in the data dictionary included in this Zenodo record.</p> <p>The code used to generate the dataset from open data sources is available on GitHub. </p> <p>The following data sources were used:</p> <ul> <li> <p>Gateway to Research (records downloaded between 2023-11-05 and 2023-11-13)</p> </li> <li> <p>Crossref (Metadata Plus snaphot 2023-10-31, Crossref member route API 2024-01-23)</p> </li> <li> <p>OpenAlex (data snapshot 2023-10-18)</p> </li> <li> <p>Unpaywall (data snapshot 2023-11-27)</p> </li> <li> <p>IRUS UK (2024-04-03)</p> </li> <li> <p>Crossref Event Data (2023-04-01)</p> </li> </ul> <p><strong></strong><br><br>The project made use of Curtin Open Knowledge Initiative (COKI) infrastructure, which is documented on GitHub: <a href="https://github.com/The-Academic-Observatory">https://github.com/The-Academic-Observatory</a>. </p>
Source Data for Manuscript: Identifying genomic data use with the Data Citation Explorer
<p>This page contains the source data for the manuscript describing the Data Citation Explorer, currently in review for publication. The preprint version can be found on this page.</p> <p>Files:</p> <p><strong>DCE_manual_eval_sample.xlsx:</strong></p> <p>This file was used to manually evaluate hits generated by the Data Citation Explorer. There are two separate sheets: one with publications returned by searches in PubMed and PubMed Central and another with publications returned by searches in Dimensions. Column descriptions can be found in the file itself. Each row in each evaluation sheet refers to a pair between a JAMO record and a linked publication.</p> <p><strong>DCE_citation_report.csv</strong></p> <p>Contains JAMO record IDs and PubMed IDs from the initial 2020 DCE trial run. There are 238,994 unique JAMO IDs and 30,641 unique PubMed IDs. 78,104 JAMO records are linked with publications.</p> <p>Columns:</p> <ul> <li>jamo_id - unique JAMO record ID</li> <li>sample_group - Sample strata from which manually evaluated records were pulled</li> <li>citation_count - Number of citations associated with each record</li> <li>citations - comma-delimited PubMed IDs for linked publications</li> <li>sampled - True/False, denoting which records were included in the initial evaluation sample</li> <li>notes - descriptions for why certain sampled records were excluded from manual evaluation</li> <li>unprocessed - True/False. These 7,890 records contained anomalous fields that caused them to be rejected for processing. They are represented as zero-length files in the archive.</li> </ul> <p><strong>DCE_source_files.zip:</strong></p> <p>This folder contains 3 files for each JAMO record in DCE_citation_report.tsv. For each JAMO record listed in the citation report, three files are provided:</p> <ol> <li>JAMO_ID_source.yaml - The fields extracted from the JAMO record that were relevant to the citation search, including any previously known PMIDs (manually curated).</li> <li>JAMO_ID_expand.yaml - The source record augmented with additional metadata discovered in other resources, including the citations that were discovered based on querying PubMed Central for the values in those metadata fields.</li> <li>JAMO_ID_audit.json - The audit path as a directed acyclic graph, in JSON.</li> </ol>
Reproduction package for: 'Exploring Waveform Variations among Neutron Star Ray-tracing Codes for Complex Emission Geometries'
<p>Data files, python scripts and notebooks to reproduce the code output comparisons performed in "Exploring Waveform Variations among Neutron Star Ray-tracing Codes for Complex Emission Geometries" by Choudhury et al. (2024; <a href="https://doi.org/10.3847/1538-4357/ad7255" target="_blank" rel="noopener"><em>ApJ</em> <strong>975</strong> 202</a>, <a href="https://doi.org/10.48550/arXiv.2406.07285" target="_blank" rel="noopener">arXiv.2406.07285</a>).</p> <p>Please refer to the README for detailed information.</p> <p>N.B. The neutral hydrogen column density (${\rm N}_{\rm H}$) value is mentioned in the paper to be $0.2 \times 10^{20} {\rm cm}^{-2}$, whereas all the analyses in the paper, as reflected in this Zenodo package, actually uses ${\rm N}_{\rm H} = 2 \times 10^{20} {\rm cm}^{-2}$.</p>
XRDs of Materials used in the Supplementary Information file of A. Lowe et al Exploring the Heat of Water Intrusion ... ACS Appl. Mater. Interfaces 2024, 16, 5286−5293
<p>Data plots were limited to 2theta range from 5 degrees to 50 degrees. CuKa</p>
Electrochemical and Spectroscopic Data supported by Computational Models for Exploring the Metal- and Ligand-Based Oxidation of Mackinawite Nanoparticles
<p>Supporting information to our study, where under anaerobic conditions, ferrous iron reacts with sulfide producing FeS precipitate, which can then undergo a temperature, redox potential, and pH dependent maturation process resulting in the formation of oxidized mineral phases such as gregite or pyrite. The dataset provide information about the chemical speciation of iron-sulfide by cyclic voltammetry, Raman and X-ray absorption spectroscopic techniques. Nanoparticulate FeS was found to get oxidized to a Fe<sup>3+</sup> containing FeS phase at -0.5 V vs. Ag/AgCl (pH = 7) and in a concomitant oxidation step, polysulfides are proposed to give a material described as Fe<sup>2+</sup><sub>(1−3x)</sub>Fe<sup>3+</sup><sub>(2x)</sub>S<sup>2-</sup><sub>(1-y)</sub>(S<sub>n</sub><sup>2-</sup>)<sub>y</sub>. The thermodynamic differences between ligand- and metal-based oxidation processes from density functional theory can be used to describe one- and two-electron electronic and structural transformations. These findings together point to the existence of a previously unknown, metastable FeS phase located between FeS and greigite (Fe<sup>2+</sup>Fe<sup>3+</sup><sub>2</sub>S<sup>2-</sup><sub>4</sub>) along a metal oxidation path, and Fe<sup>2+</sup>S<sup>2-</sup> and pyrite (Fe<sup>2+</sup>S<sub>2</sub><sup>2-</sup>) along a ligand oxidation path, respectively.</p>
Exploring the economic, social, and environmental dimensions of community-supported agriculture in Italy (dataset)
<p>Dataset inherent to the following article:</p> <p>Medici, M., Canavari, C., Castellini, A., 2021. <em>Exploring the economic, social, and environmental dimensions of community-supported agriculture in Italy</em>, Journal of Cleaner Production, 316, 128233, DOI: <a href="https://doi.org/10.1016/j.jclepro.2021.128233">10.1016/j.jclepro.2021.128233</a></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.