Physical and biogeochemical oceanography data from Conductivity, Temperature, Depth (CTD) rosette deployments during the Antarctic Circumnavigation Expedition (ACE).
Contributors: Henry, Tahlia, Robinson, Charlotte, Haumann, F. Alexander, Thomas, Jenny, Hutchings, Jennifer, Schuback, Nina, Tsukernik, Maria, Leonard, Katherine
... ***** Dataset abstract ***** This data set contains measurements from various sensors mounted on the Conductivity, Temperature, Depth (CTD) rosette that was deployed in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE). 63 CTD casts were carried out during three legs in the period 21st December 2016 to 16th March 2017, including one test cast and one failed cast, for which no data is available. Data include temperature, salinity, pressure, dissolved oxygen, oxygen saturation, chlorophyll-a concentration, backscatter, and photosynthetically active radiation (PAR) and reported are also the computed variables density, depth, and sound velocity. All data has been quality controlled and post-cruise calibrated, except for the oxygen data. Data is provided at 1 dbar pressure intervals for the up- and down-casts separately and as a merged bottle file when Niskin bottles were closed. This circumpolar data set provides insights into the circumpolar hydrography and biogeochemistry of the Southern Ocean during one austral summer season. ***** Dataset contents ***** For transparency, the raw files and files produced at the intermediate stages of data processing have been provided, in addition to the final processed files. Raw data files: - ace_ctd_raw_files.zip - includes raw files direct from instrument and XMLCON configuration files Intermediate files: - files output at each stage of the SeaBird processing Processed data files: - ace_ctd_CTD20190805CURRSGCMR - one final set of files for the complete sensor data; - ACE_BOTTLE20190807CURRSGCM_hy1.csv - a merged bottle file extracted from the sensor data is also provided Metadata: - range of files describing the CTD deployments, sensors, water sampling, quality-checking and processing of the files. ***** Dataset license***** This physical and biogeochemical oceanography dataset is made available under the Open Data Commons Attribution License (ODC-By) v1.0 whose full text can be found at https://www.opendatacommons.org/licenses/by/1.0/index.html
Data for paper "Low Resource Technique for Measurement of H+ and O+ in the Terrestrial Magnetosphere"
Contributors: Fernandes, Philip A., Funsten, H.O., Dors, E.E., Harper, R.W., Larsen, B.A., MacDonald, E.A., Reisenfeld, D.B., Skoug, R.M., Steinberg, J.T., Thomsen, M.F.
... Data set for paper "Low Resource Technique for Measurement of H+ and O+ in the Terrestrial Magnetosphere" to be published in Journal of Geophysical Research: Space Physics (Technical Methods). Data set is a single Microsoft Excel file containing Data Set S1, Data Set S2, Data Set S3.
A neural network-based estimate of the seasonal variability of total alkalinity in the East China Sea shelf
... In order to estimate the seasonal variability of total alkalinity in the ECS shelf, an artificial neural network (ANN) model was developed using 5 cruise datasets from 2008 to 2018. The model used temperature, salinity, and dissolved oxygen to estimate AT with a root-mean-square error of ~7 umol kg-1, and was applied to fill missing alkalinity data for 8 cruises during 2013-2016. In addition, monthly water column AT for the period 2000-2016 was also obtained passing temperature, salinity, and dissolved oxygen from the Changjiang Biology Finite-Volume Coastal Ocean Model (FVCOM) Data. Spatial distributions, seasonal cycles and correlations of surface AT indicated that the seasonal fluctuation of the Changjiang River discharge is the major factor affecting seasonal variation of surface total alkalinity in the ECS shelf. The largest seasonal fluctuation of surface total alkalinity was found on the inner shelf near the Changjiang Estuary.
Top results from Data Repository sources. Show only results like these.
Retrieving monthly and interannual pHT in the East China Sea shelf using an artificial neural network: ANN-pHT-v1
... The reliability of the artificial neural network model was evaluated by independent sampled data from 3 cruises in 2018. Monthly water column pHT for the period 2000-2016 was obtained passing T, S, DO, N, P, and Si from the Finite-Volume Coastal Ocean Model with the European Regional Sea Ecosystem Model through the artificial neural network. The spatiotemporal resolution of monthly pHT is 1-10 km in the horizontal, 10 depth levels in the vertical, and 12 months. Seasonal pHT dynamics in the East China Sea shelf can be primarily attributed to temperature changes and the shifting balance of production and respiration processes.
Water concentration in single-crystal (Al,Fe)-bearing bridgmanite grown from the hydrous melt: implications for dehydration melting at the topmost lower mantle
Contributors: Fu, Suyu, Yang, Jing, Karato, Shun-ichiro, Vasiliev, Alexander, Presniakov, Mikhail Yu., Gavrilliuk, Alexander G., Ivanova, Anna G., Hauri, Erik H., Okuchi, Takuo, Purevjav, Narangoo
... Dataset for "Water concentration in single-crystal (Al,Fe)-bearing bridgmanite grown from the hydrous melt: implications for dehydration melting at the topmost lower mantle"
... These data were used for the study published in: Lugli, Ligeia. 2019. Words or terms? Models of terminology and the translation of Buddhist Sanskrit vocabulary. In Alice Collett (ed.) Buddhism and Translation: Historical and Contextual Perspectives, New York: SUNY. data include: 1. concordance lines for saṃjñā used for the study mentioned above. The concordance lines have been exported from the Sketch Engine and come from an automatically segmented corpus (segmenter = Lugli's version 1). They have not been proofread and contain segmentation errors. 2. csv file with Lugli's semantic annotation of the concordance lines for saṃjñā. The data was annotated by Ligeia Lugli in 2017; part of the data constitutes a much revised version of a dataset originally prepared by Roberto Garcia for the Buddhist Translators Workbench in 2016. 3. a pre-publication version of the study The creation of these data was funded by the British Academy through a Newton International Fellowship; the research was conducted at King's College London.
Contributors: Rieckermann, Jörg
... Questions asked to participants during the workshop What is your area of work? Where are you working? What is more important in using monitoring data for assessing water quality impacts from CSOs? What regulation is better: simple or complex? What are current barriers against data sharing? If you make your CSO data transparent [what happens?] Would be a regulatory push (similar to EPA) effective in the EU? Where do you see biggest gap in CSO management? What instruments would you personally prefer to improve CSO management? [not polled] CSO in your region/city are: [how visible?] When existing, data on CSO are accessible [by whom?] An assessment of CSO at EU scale is in your opinion: [how useful?] If you want to make data public, at which level should it be provided? How important is a common data model and format? What is more important in using monitoring data for assessing water quality impacts from CSOs? Where do you see biggest gap in CSO management? What are your preferred next steps? [word cloud]
Contributors: Riebensahm, Carlotta, Joosse, Simon A., Mohme, Malte, Hanssen, Annkathrin, Matschke, Jakob, Goy, Yvonne, Witzel, Isabell, Lamszus, Katrin, Kropidlowski, Jolanthe, Petersen, Cordula
... Background: The incidence of brain metastases in breast cancer (BCBM) patients is increasing. These patients have a very poor prognosis, and therefore, identification of blood-based biomarkers, such as circulating tumor cells (CTCs), and understanding the genomic heterogeneity could help to personalize treatment options.Methods: Both EpCAM-dependent (CellSearch® System) and EpCAM-independent Ficoll-based density centrifugation methods were used to detect CTCs from 57 BCBM patients. DNA from individual CTCs and corresponding primary tumors and brain metastases were analyzed by next-generation sequencing (NGS) in order to evaluate copy number aberrations and single nucleotide variations (SNVs).Results: CTCs were detected after EpCAM-dependent enrichment in 47.7% of the patients (≥ 5 CTCs/7.5 ml blood in 20.5%). The CTC count was associated with ERBB2 status (p = 0.029) of the primary tumor as well as with the prevalence of bone metastases (p = 0.021). EpCAM-independent enrichment revealed CTCs in 32.6% of the patients, especially among triple-negative breast cancer (TNBC) patients (70.0%). A positive CTC status after enrichment of either method was significantly associated with decreased overall survival time (p < 0.05). Combining the results of both enrichment methods, 63.6% of the patients were classified as CTC positive. In three patients, the matched tumor tissue and single CTCs were analyzed by NGS showing chromosomal aberrations with a high genomic clonality and mutations in pathways potentially important in brain metastasis formation.Conclusion: The detection of CTCs, regardless of the enrichment method, is of prognostic relevance in BCBM patients and in combination with molecular analysis of CTCs can help defining patients with higher risk of early relapse and suitability for targeted treatment.
Contributors: Baudry, Julien, Labarre, Nicolas
... Le jeu de données contient un questionnaire (texte en format odt) et les réponses à ce questionnaire (tableur au format ods) recueillies auprès de lecteur.trices, dans le cadre d'une expérience de lecture comparée entre les versions papier et numérique d'une même bande dessinée. L'objectif de l'expérience est d'identifier les différences de compréhension d'une version à l'autre. Plus de détail sur le protocole dans le fichier readme. Pour les conclusions, se reporter à l'article (en cours de parution)
... The following collection is used to demonstrate the HailPixel survey technique as part of an EGU ATM publication. The following is an abstract for this paper: A new technique, named "HailPixel," is introduced for measuring the maximum dimension and intermediate dimension of hailstones from aerial imagery. The photogrammetry procedure applies a convolutional neural network for robust detection of hailstones against complex backgrounds and an edge detection method for measuring the shape of identified hailstones. This semi-automated technique is capable of measuring many thousands of hailstones within a single survey, which is several orders of magnitude larger than population sizes from existing sensors (e.g., a hail pad). Comparison with a co-located hail pad for an Argentinan hailstorm event demonstrates the larger population size of the HailPixel survey significantly improves the shape and tails of the observed hail size distribution. When hailfall is sparse, such as during large and giant hail events, the large survey area of this technique is especially advantageous for resolving the hail size distribution. The dataset contains the DEM and orthomosaic imagery, processing reports, final location of hail centroids, final measurements of hail major and minor axis, subset offsets and hail pad data. For more information applying the subset offsets to calculate the true position of the hail centroids please see the paper.