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3,145 results for “Well Being”

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zenodo36/100

Codes, Catalogues and Data for "Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"

<p><strong>Codes, Catalogues and Data available for:</strong>&nbsp;<br>"Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"</p> <p><strong>Catalog</strong> folder: Contains the CMM (beam-forming based) event catalogue as well as event and station information for the PNR-1z site.</p> <p><strong>Classification Test</strong> folder: Jupyter notebooks that run the classification tests and mseed input data of isolated phases (P, S, Noise).</p> <p><strong>DL_model_catalogues</strong> folder: Contains full catalogues for each DL phase picker (GPD, U-GPD, EQT and PhaseNet) and the LinMEF-filtered catalogues.</p> <p><strong>Model_run_docs</strong> folder: Util/core files for PhaseNet and EQTransformer to read data with different sampling frequencies (i.e., not 100 Hz)</p> <p><strong>Data</strong> folder: Contains one hour of continuous downhole data (11th December 2018, 9am-10am) from the PNR-1z dataset.</p>

opencc-by-4.0Jul 2024View details →
zenodo36/100

IODP Expedition 397, Hole U1587C - Well Logging Data

Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.

opencc-zeroJun 2024View details →
zenodo36/100

IODP Expedition 398, Hole U1589C - Well Logging Data

Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.

opencc-zeroJul 2024View details →
zenodo36/100

IODP Expedition 397, Hole U1586D - Well Logging Data

Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.

opencc-zeroJun 2024View details →
zenodo36/100

Changes in Permeability Caused by Two Consecutive Earthquakes – Insights from the Responses of a Well-Aquifer System to Seismic Waves

<p>All data used in paper &quot;Changes in Permeability Caused by Two Consecutive Earthquakes &ndash; Insights from the Responses of a Well-Aquifer System to Seismic Waves&quot;.</p>

opencc-by-4.0Aug 2019View details →
zenodo36/100

Fig. 1 in Biozonation And Correlation Of Two Wells In Niger Delta Using Calcareous Nannofossils

Fig. 1 Geologic map of the Niger Delta region (after Correldor et al. 2005)

opencc-by-4.0Jun 2016View details →
zenodo36/100

Figure. Study area and wells. in Investigation of zooplankton fauna in water wells of Yayladağı District (Hatay, Turkey)

Figure. Study area and wells.

opencc-by-4.0May 2019View details →
zenodo36/100

Figure 2 in Assessing population size and survival rate of Pelophylax bedriagae caralitanus, in a well-protected Nature Park in Türkiye

Figure 2. The view of the habitat surrounding Gölcük Lake.

opencc-by-4.0Apr 2024View details →
zenodo36/100

FIGURE 4 in Foraminifera biostratigraphy and paleoenvironment of Well 5, OML 34, Niger Delta, Nigeria

FIGURE 4. Sequence Stratigraphy chart showing paleobathymetry of deposition of studied well.

opencc-by-4.0Dec 2017View details →
zenodo36/100

FIGURE 3 in Foraminifera biostratigraphy and paleoenvironment of Well 5, OML 34, Niger Delta, Nigeria

FIGURE 3. Ranges of planktonic foraminifera showing biozones for the studied Well 5.

opencc-by-4.0Dec 2017View details →
zenodo36/100

FIGURE 1 in Foraminifera biostratigraphy and paleoenvironment of Well 5, OML 34, Niger Delta, Nigeria

FIGURE 1. Location of studied well (modified after Odemerho; Urhobo Historical Society, 2008).

opencc-by-4.0Dec 2017View details →
zenodo36/100

FIGURE 2 in A remarkably well-preserved terrestrial isopod (Peracarida: Isopoda: Armadillidiidae) from the upper Oligocene of Hungary, with remarks on the oniscidean taphonomy

FIGURE 2. Section exposed at the Wind Brickyard in Eger, Hungary. See text for comments.

opencc-by-4.0Mar 2017View details →
zenodo36/100

The groundwater-level anomalies observed by 446 monitoring wells in the North China Plain during 2003-2017

<p>The groundwater level anomalies observed by 446 monitoring wells in the North China Plain (NCP) during 2003-2017. The monthly GWL data were obtained from the Ministry of Water Resources of China and the groundwater yearbooks. The wells were relatively evenly distributed in NCP region . The GWL anomalies were calculated by subtracting the mean GWL values during 2003-2017 from the monthly time series values of each well. Unit: meter</p>

opencc-by-4.0Nov 2023View details →
zenodo36/100

On the cell broadening of mesoscale cellular convection in a well-mixed boundary layer

Open the record for dataset details and reuse information.

opencc-by-4.0Nov 2024View details →
dryad36/100

Optical traits perform equally well as directly-measured functional traits in explaining the impact of an invasive plant on litter decomposition

<p>1. Functional traits can help elucidate and predict the impact of invasive plant species on ecosystem functioning. Yet, this approach requires comprehensive and labor-intensive trait collection campaigns, covering intraspecific trait variation of both the invader and native species in the invaded community. One potential way to overcome these logistic constraints is using hyperspectral remote sensing technology to efficiently quantify functional trait values. Although such spectrally derived or 'optical' traits are known to closely link to directly-measured functional traits, little research has explored how well these optical traits perform in assessing invader-induced ecosystem impact. 2. Here, we explored the trait-mediated impact of the invasive Rosa rugosa on litter decomposition and evaluated whether optical traits perform equally well as directly-measured traits in predicting litter decomposition variation. We collected data on species-specific functional traits, leaf hyperspectral reflectance and standardized 'tea bag index' litter decomposition across 25 invaded and 25 uninvaded coastal grassland plots. The selected traits were all potentially related to litter decomposition and covered the leaf economics spectrum, additional leaf structural components and competitive ability. Optical traits were quantified through a combination of a physical radiative transfer model inversion and vegetation indices calculations. 3. Invasion significantly increased the stabilization factor, i.e. the amount of resulting recalcitrant litter. Invader impact on litter decomposition could be entirely explained by changes it induced in the functional traits of the native community, rather than by the invader's traits itself. More specifically, the invader pushed the invaded community towards traits associated with high litter quality. Optical traits performed equally well as directly-measured traits in explaining the invasion impact on the stabilization factor (R2= 41.9% vs. 38.5%). Furthermore, the interpretation of the results based on optical traits resulted in a similar functional understanding of the invader impact. 4. Synthesis: Our results indicate the potential of hyperspectral data to explain changes in ecosystem functioning. The combination of radiative transfer models and vegetation indices allowed to extract all relevant trait information from the hyperspectral data. This framework thus presents a practical short-cut to assess relevant leaf traits, requiring only a limited amount of field trait measurements.</p>

opencc-zeroMar 2020View details →
zenodo36/100

IODP Expedition 382, Hole U1536E - Well Logging Data

<p>Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,&hellip;) in any hole depends on the scientific objectives and operational constraints.</p>

opencc-zeroJun 2021View details →
zenodo36/100

IODP Expedition 374, Hole U1523D - Well Logging Data

<p>Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,&hellip;) in any hole depends on the scientific objectives and operational constraints.</p>

opencc-zeroJun 2021View details →
zenodo36/100

IODP Expedition 374, Hole U1522A - Well Logging Data

<p>Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,&hellip;) in any hole depends on the scientific objectives and operational constraints.</p>

opencc-zeroJun 2021View details →
zenodo36/100

IODP Expedition 371, Hole U1507B - Well Logging Data

<p>Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,&hellip;) in any hole depends on the scientific objectives and operational constraints.</p>

opencc-zeroJun 2021View details →
zenodo36/100

IODP Expedition 369, Hole U1514C - Well Logging Data

<p>Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,&hellip;) in any hole depends on the scientific objectives and operational constraints.</p>

opencc-zeroJun 2021View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record