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566 results for “analytics”
Dataset for publication "Parallel experiments in electrochemical CO2 reduction enabled by standardized analytics"
<p>Dataset for the publication: "<strong>Parallel experiments in electrochemical CO<sub>2</sub> reduction </strong><strong>enabled by standardized analytics</strong>", https://doi.org/10.1038/s41929-024-01172-x,<strong> </strong>divided by paper Figure. The dataset contains data that are both raw and processed using the open-source software available at http://dgbowl.github.io </p>
Sample Records (Analytical procedure): Disinformation as a strategy of obstructionism on climate action: analysis of the limitations of the scientific literature for a systemic understanding of the phenomenon
<p>This dataset includes t<span>he online form and the results from the quantitative phase of the study: Disinformation as an obstructionist strategy in climate change mitigation: A review of the scientific literature for a systemic understanding of the phenomenon</span></p> <p>To duplicate the form you can use: https://forms.office.com/Pages/ShareFormPage.aspx?id=6sSEXw03nkuDDHVvi_G1Hw0s3dVrMb1NsO12gDNTB9BUREo4WENRMFFDN1lOSlRSU0xJNkVHWURWUS4u&sharetoken=rg4Qfg19O4UgYzUB084C </p>
GALAKSIENN: the G.A.S semi-analytical model associtated library
<p>The GALAKSIENN library contains data sets generated by the G.A.S. semi-analytical model of galaxy formation and evolution. The G.A.S. model is fully described in a set of three Astronomy & Astrophysics papers: G.A.S. I: A prescription for turbulence-regulated star formation and its impact on galaxy properties; G.A.S. II: Dust extinction in galaxies, luminosity functions and InfraRed Excess and G.A.S. III: The panchromatic view of galaxies, Stellar/dust continua and main gas emission lines. The library stores mock galaxy catalogues and ascii tables (stellar mass functions, luminosity functions, number counts ...).</p>
Data and supplementary files of the publication: "What Goes Around Should Not Move Around: Immobilizing Microplastics as a New Approach for Analytical Ring Trials"
<p>Accompanying materials for the publication: <a href="https://doi.org/10.1021/acs.est.4c09427">https://doi.org/10.1021/acs.est.4c09427</a></p>
RDF version of the data from Anastasios G. et al. Computational enrichment of physicochemical data for the development of a zeta-potential read-across predictive model with Isalos Analytics Platform. NanoImpact (2021).
<p>This is an RDFied version of the dataset published by Anastasios G. et al. Computational enrichment of physicochemical data for the development of a zeta-potential read-across predictive model with Isalos Analytics Platform. NanoImpact (2021).</p> <p>The original dataset publication DOI: <a href="https://doi.org/10.1016/j.impact.2021.100308">https://doi.org/10.1016/j.impact.2021.100308</a></p> <p>The Original publication authors: Anastasios G. Papadiamantis, Antreas Afantitis, Andreas Tsoumanis, Eugenia Valsami-Jones, Iseult Lynch, Georgia Melagraki</p>
RDF version of the data from Anastasios G. Papadiamantis et al. Predicting Cytotoxicity of Metal Oxide Nanoparticles Using Isalos Analytics Platform (2020)
<p>This is an RDFied version of the dataset published in Papadiamantis, A.G. et al. Predicting Cytotoxicity of Metal Oxide Nanoparticles Using Isalos Analytics Platform. <em>Nanomaterials</em> <strong>2020</strong>, <em>10</em>, 2017.</p> <p>The original dataset publication DOI: <a href="https://doi.org/10.3390/nano10102017">https://doi.org/10.3390/nano10102017</a></p> <p>The Original publication authors: Papadiamantis, A.G.; Jänes, J.; Voyiatzis, E.; Sikk, L.; Burk, J.; Burk, P.; Tsoumanis, A.; Ha, M.K.; Yoon, T.H.; Valsami-Jones, E.; Lynch, I.; Melagraki, G.; Tämm, K.; Afantitis, A.</p>
Data, Analytical Code, and Model Outputs From: "Green is the New Black: Outcomes of Post-Fire Tree Planting Across the Interior West, USA"
<p>This archive includes data (locations of tree plantings, one-year survival records, remotely sensed canopy cover change), statistical code, and model outputs from Rodman et al. (2024). For more information on specific information, processing methods, and data formats, see "README.md" or "README.html" files associated with this archive</p>
Artifact Description/Artifact Evaluation/Computational Artifact for paper, entitled Analytic Roofline Modeling and Energy Analysis of the LULESH Proxy Application on Multi-Core Clusters
We provide reproducibility initiative dependencies (Artifact Description or Artifact Evaluation or Computational Results Analysis) appendix. To allow a third party to duplicate the findings, this article provides our extensive performance data artifact and describes further details regarding the software environments, experimental design, and methodology employed for the results shown in the paper. The computational artifacts will enable experienced performance engineers to reproduce and interpret the data shown in the paper in the appropriate way and to follow the conclusions we draw from it.
Supplementary Material to the PhD Thesis of Luz, Zoneibe (University of Lausanne): Characterizing conodont bioapatite from the Early-Triassic: an analytical and palaeoclimatological approach
<p>The present dataset contains the Supplements cited in the PhD Thesis of Zoneibe Augusto Silva Luz (University of Lausanne), entitled '<em>Characterizing conodont bioapatite from the Early-Triassic: an analytical and palaeoclimatological approach</em>', defended the 29th of June in Lausanne. Three table of contents (TOC) are provided for each of the three thesis chapters. The main thesis is deposited at the Bibliothèque cantonale et universitaire de Lausanne, Section des thèses imprimées et des échanges,and digitally at the SERveur Académique Lausannois (Serval) ().</p> <p>Le présent set de données contient les Suppléments cités dans la thèse de doctorat de Zoneibe Augusto Silva Luz (Université de Lausanne), intitulée 'Characterizing conodont bioapatite from the Early-Triassic : an analytical and palaeoclimatological approach', soutenue le 29 juin à Lausanne. Trois tables des matières (TOC) sont fournies pour chacun des trois chapitres de la thèse. La thèse principale est déposée dans la Bibliothèque cantonale et universitaire de Lausanne, Section des thèses imprimées et des échanges, et électroniquement dans le SERveur Académique Lausannois (Serval) ().</p>
Analytical expressions for thermophysical properties of solid and liquid aluminum relevant for fusion applications
<p>Aluminum is being actively employed by the fusion community as a non-toxic chemical proxy to beryllium, since both materials form covalent hydrides, high-melting oxides as well as alloys with tungsten [1]. Characteristic examples include studies of in situ cleaning of diagnostic first mirrors [2,3], investigations of hydrogen retention or deposited layer formation [4,5] and experiments dedicated to sputtered material transport in diagnostic ducts [6]. Aluminum has also served as a surrogate for beryllium in high heat flux tests, given its low melting point and low mass density. Characteristic examples concern experiments on the interaction of adhered Al dust with transient and stationary plasmas carried out in Magnum-PSI [7] and the controlled melting of Al blocks exposed in the DIII-D divertor under steady L-mode discharge conditions using the DiMES manipulator [8]. In order to reliably model the macroscopic metallic melt motion realized in the sloped geometry Al L-mode exposures in the DIII-D divertor, the material library of the MEMENTO melt dynamics code, that previously concerned tungsten [9], beryllium [10], niobium [11,12] and iridium [11,12], has to be extended to aluminum.</p> <p>Reliable experimental data have been analyzed for the specific isobaric heat capacity, electrical resistivity, thermal conductivity, mass density, vapor pressure, latent heat of fusion, enthalpy of vaporization, work function, total hemispherical emissivity and absolute thermoelectric power from the room temperature up to the normal boiling point of aluminum as well as for the surface tension and the dynamic viscosity across the liquid state. Analytical expressions are recommended for the temperature dependence of these thermophysical properties, which involve high temperature extrapolations given the absence of extended liquid aluminum measurements. The analytical expressions, the details of their construction and the main references are included in the accompanying pdf.</p> <p>[1] L. Marot, C. Linsmeier, B. Eren, L. Moser, R. Steiner and E. Meyer, "Can aluminium or magnesium be a surrogate for beryllium: A critical investigation of their chemistry", Fus. Eng. Des. 88 (2013) 1718.<br> [2] A. Maffini, L. Moser, L. Marot, R. Steiner, D. Dellasega, A. Uccello, E. Meyer and M. Passoni, "In situ cleaning of diagnostic first mirrors: an experimental comparison between plasma and laser cleaning in ITER-relevant conditions", Nucl. Fusion 57 (2017) 046014.<br> [3] A. Litnovsky, V. S. Voitsenya, R. Reichle et al., "Diagnostic mirrors for ITER: research in the frame of International Tokamak Physics Activity", Nucl. Fusion 59 (2019) 066029.<br> [4] A. Kreter, T. Dittmar, D. Nishijima, R. P. Doerner, M. J. Baldwin and K. Schmid, "Erosion, formation of deposited layers and fuel retention for beryllium under the influence of plasma impurities" Phys. Scr. T159 (2014) 014039.<br> [5] C. Quirós, J. Mougenot, G. Lombardi, M. Redolfi, O. Brinza, Y. Charles, A. Michau and K. Hassouni, "Blister formation and hydrogen retention in aluminium and beryllium: A modeling and experimental approach", Nucl. Mater. Energy 12 (2017) 1178.<br> [6] N. A. Babinov, A. G. Razdobarin, I. M. Bukreev et al, "Three-dimensional modeling of sputtered materials transport in diagnostic ducts of fusion devices", Nucl. Fusion 62 (2022) 126004.<br> [7] S. Ratynskaia, P. Tolias, M. De Angeli, D. Ripamonti, G. Riva, D. Aussems and T. W. Morgan, "Interaction of adhered beryllium proxy dust with transient and stationary plasmas", Nucl. Mater. Energy 17 (2018) 222.<br> [8] D. L. Rudakov, T. Abrams, I. Bykov et al., "Controlled low-Z metal melting in the DIII-D divertor", Abstract submitted for the 19th International Conference on Plasma-Facing Materials and Components for Fusion Applications, 22-26 May 2023, Bonn, Germany.<br> [9] P. Tolias, "Analytical expressions for thermophysical properties of solid and liquid tungsten relevant for fusion applications", Nucl. Mater. Energy 13 (2017) 42.<br> [10] P. Tolias, "Analytical expressions for thermophysical properties of solid and liquid beryllium relevant for fusion applications", Nucl. Mater. Energy 31 (2022) 101195.<br> [11] P. Tolias, S. Ratynskaia and K. Paschalidis, "Thermophysical properties for the published article - Experiments and modelling on ASDEX Upgrade and WEST in support of tool development for tokamak reactor armour melting assessments", Zenodo. https://doi.org/10.5281/zenodo.6778824.<br> [12] S. Ratynskaia, K. Paschalidis, P. Tolias et al., "Experiments and modelling on ASDEX Upgrade and WEST in support of tool development for tokamak reactor armour melting assessments", Nucl. Mater. Energy 33 (2022) 101303.<br> </p>
Dataset - Analytic Network Process in economics, finance and management
<p><em>This data set presents the recent use of the Analytic Network Process (ANP) in the decision process in the areas of economics, finance and management. It has 434 ANP studies for a 10-year period (2012-2021) within the Scopus database. They were identified using the keyword “Analytic Network Process” in articles indexed in the following two database categories: "Business, Management and Accounting"; and "Economics, Econometrics and Finance". </em></p> <p> </p>
Analytical Center of University Cultural Productions in the Context of the Conflict (caPAZ) - Temporality
<p>This dataset comprises a collection of journalistic articles written by young university students in Colombia, which is a product of the project: Analytical Center of University Cultural Productions in the Context of the Conflict (caPAZ), funded by the Ministry of Science, Technology and Innovation (Minciencias) and the National Center for Historical Memory (CNM) of Colombia (under the code: 1349-872-76354, agreement 872 of 2020) This corpus includes news written by the 24 colleges media of the Colombian Network of College Journalism from 2012 to 2016. The dataset includes digital news, for a total of <strong>589 </strong>news items related to the armed conflict, the memory of the victims and the peace process in Colombia. These news items were collected through a web-scraping technique, using 3 lemmatized keywords (conflicto armado, memoria de las víctimas y proceso de paz), with the aim of identifying these regular expressions in the logical operators that run through the HTML structure of each Web page</p>
CLImate for Maize OMICS: CLIM4OMICS Analytics and Database (v2.0)
<p>CLIM4OMICS Analytics and Database is Improved database of G2F data repository that contains OMICs (genetic and phenotypic) and environmental data for maize yield predictability across 84 experimental fields in the U.S. and province of ON in Canada between 2014-2021. The goal of this pipeline is to aggregate, improve, and synthesize multi-dimensional G2F data including Geno-type, Phenotype and Environmental data for GxE modeling. This dataset contains 79,122 phenotype measurements, 378 genotypes of maize lines, environmental data of 178 locations and Python Scripts for Quality control (QC), Consistency control (CC) steps and ML models for GxE interactions. The Environmental data is extracted from NWS, DayMet and NSRDB databases and processed for QC and CC. The environmental dataset contains the minimum temperature (<em>T<sub>min</sub></em>)<em>,</em> average temperature (<em>T<sub>mean</sub></em>)<em>, </em>maximum temperature (<em>T<sub>max</sub></em>)<em>,</em> minimum dew point (<em>DP<sub>min</sub></em>)<em>,</em> average dew point (<em>DP<sub>mean</sub></em>)<em>, </em>maximum dew point (<em>DP<sub>max</sub></em>)<em>, </em>minimum relative humidity (<em>RH<sub>min</sub></em>)<em>, </em>average relative humidity (<em>RH<sub>mean</sub></em>)<em>, </em>maximum relative humidity (<em>RH<sub>max</sub></em>)<em>, </em>minimum solar radiation (<em>SR<sub>min</sub></em>)<em>, </em>average solar radiation (<em>SR<sub>mean</sub></em>)<em>, </em>maximum solar radiation (<em>SR<sub>max</sub></em>)<em>, </em>accumulative rainfall (<em>R<sub>acc</sub></em>)<em>, </em>average wind speed (<em>WS<sub>mean</sub></em>), and average wind direction (<em>WD<sub>mean</sub></em>). This package also contains the raw G2F data and preprocessing pipeline.</p>
CLImate for Maize OMICS: CLIM4OMICS Analytics and Database
<p>CLIM4OMICS Analytics and Database is Improved database of G2F data repository that contains OMICs (genetic and phenotypic) and environmental data for maize yield predictability across 84 experimental fields in the U.S. and province of ON in Canada between 2014-2021. The goal of this pipeline is to aggregate, improve, and synthesize multi-dimensional G2F data including Geno-type, Phenotype and Environmental data for GxE modeling. This dataset contains 79,122 phenotype measurements, 378 genotypes of maize lines, environmental data of 178 locations and Python Scripts for Quality control (QC), Consistency control (CC) steps and ML models for GxE interactions. The Environmental data is extracted from NWS, DayMet and NSRDB databases and processed for QC and CC. The environmental dataset contains the minimum temperature (<em>T<sub>min</sub></em>)<em>,</em> average temperature (<em>T<sub>mean</sub></em>)<em>, </em>maximum temperature (<em>T<sub>max</sub></em>)<em>,</em> minimum dew point (<em>DP<sub>min</sub></em>)<em>,</em> average dew point (<em>DP<sub>mean</sub></em>)<em>, </em>maximum dew point (<em>DP<sub>max</sub></em>)<em>, </em>minimum relative humidity (<em>RH<sub>min</sub></em>)<em>, </em>average relative humidity (<em>RH<sub>mean</sub></em>)<em>, </em>maximum relative humidity (<em>RH<sub>max</sub></em>)<em>, </em>minimum solar radiation (<em>SR<sub>min</sub></em>)<em>, </em>average solar radiation (<em>SR<sub>mean</sub></em>)<em>, </em>maximum solar radiation (<em>SR<sub>max</sub></em>)<em>, </em>accumulative rainfall (<em>R<sub>acc</sub></em>)<em>, </em>average wind speed (<em>WS<sub>mean</sub></em>), and average wind direction (<em>WD<sub>mean</sub></em>). This package also contains the raw G2F data and preprocessing pipeline.</p>
Accompanying Dataset migr_asyappctzm for Efficient Analytical Queries on Semantic Web Data Cubes
<p>This dataset shows how the Eurostat data cube in the orginal publicatin is modelled in QB4OLAP.</p> <p>This data is based on statistical data about asylum applications to the European Union, provided by Eurostat on</p> <p><a href="http://ec.europa.eu/eurostat/web/products-datasets/-/migr_asyappctzm">http://ec.europa.eu/eurostat/web/products-datasets/-/migr_asyappctzm</a></p> <p>Further data has been integrated from: https://github.com/lorenae/qb4olap/tree/master/examples</p>
H2020 ENODISE: DLR Analytical Aeroacoustic Database BLI Configuration A1 and A2
<p>This database contains the acoustic prediction results of DLR for a single operating point of the A1 and A2 configurations investigated in the framework of the European project ENODISE. In these configurations, a single two-bladed propeller is immersed in a boundary layer. The present results can be compared to the measurements carried out by the University of Bristol and the University of Twente for different boundary layer characteristics. The experimental results are saved elsewhere on the ZENODO repository.</p> <p>The investigated operating point as calculated in the prediction is:</p> <ul> <li>Uinf = 33 m/s, 6500 rpm, advance ratio J=1.</li> </ul> <p>The experimental measurements were conducted at a slightly lower freestream velocity.</p> <p>The DLR prediction results were obtained using the analytical approach implemented in the DLR in-house program PropNoise coupled to the blade element momentum theory. The calculations were informed by the hot-wire measurements carried out in the boundary-layer as the propeller was removed.</p> <p>Refer to the two references cited below to obtain more information about the theory that was applied to obtain the results: </p> <ol> <li> S. Guérin, T. Lade, L. Castelucci, I. Zaman, Tonal noise emission by a low-Mach low-Reynolds number propeller ingesting a boundary layer, 29th International Congress on Sound and Vibration, 10-13 July 2023, Prague (CZ).</li> <li> S. Guérin, T. Lade, L. Castelucci, I. Zaman, Broadban noise emission by a low-Mach low-Reynolds number propeller ingesting a boundary layer, Inter-Noise 2023, 20-23 August 2023, Chiba (Great Tokyo), Japan.</li> </ol> <p>The results for tonal and broadband noise are saved separately. The DLR results are saved into an h5 file, which can be read with e.g. python.</p> <p>Further details can be found in the file <em>DLR_documentation_A1_A2.pptx</em></p>
H2020 ENODISE: DLR Analytical Aeroacoustic Database Configuration B1
<p>This database contains the acoustic prediction results of DLR for a single operating point of the B1 configuration investigated in the framework of the European project ENODISE. In this configuration, three identical propellers with 6 blades are mounted at leading-edge of a wing (puller configuration). The results presented here can be compared to the measurements carried out by the Technical University of Delft, when these are available. The experimental results should be also saved on the ZENODO repository (use the key word ENODISE).</p> <p>The investigated operating point as calculated in the prediction is:</p> <ul> <li>Uinf = 30 m/s, advance ratio J=0.8.</li> </ul> <p>The DLR prediction results were obtained using the analytical approach implemented in the DLR in-house program PropNoise coupled to the blade element momentum theory.</p> <p>The interaction with the wing is accounted for in a simplistic way as explained in the detailed documentation <em>B_documentation.pptx.</em></p> <p>Only, the results for tonal noise are available in this database. Three cases can be investigated separately: a single isolated propeller, 3 distributed propellers, three distributed propellers interacting with the wing.</p> <p> </p> <p>The DLR results are saved in h5 files, which can be read with e.g. Python.</p>
Combining Analytical Modeling, Realistic Simulation and Real Experimentation for the Optimization of Monte-Carlo Applications on the European Grid Infrastructure
<p>Data and scripts used to generate figures presented in the paper "Combining Analytical Modeling, Realistic Simulation and Real Experimentation for the Optimization of Monte-Carlo Applications on the European Grid Infrastructure" submitted to the Future Generation Computer Systems Journal.</p>
Illustrative dataset for the article: Vieira, R., McDonald, S., Araujo-Soares, V., Sniehotta, F., Henderson, R. (2017) "Dynamic modelling of n-of-1 data: Powerful and flexible data analytics applied to individualised studies"
<p>This dataset is supplementary material of the manuscript "Dynamic modelling of n-of-1 data: Powerful and flexible data analytics applied to individualised studies. McDonald et al. (2016) presents a series of novel n-of-1 studies that intended to explore the relationship between physical activity change during the retirement transition. The file contains the data of one participant. The column names correspond to the following variables:</p> <p>time: duration of follow-up (minutes);<br> minute: time of day (hours and minutes);<br> day_num: day since beginning of follow-up (the first two days were considered as adaptation phase and therefore removed); <br> PAscore: accelerometer raw score; <br> startBout: 1 (a bout of PA was initiated in this minute) or 0 (a bout of PA wasn't <br> initiated in this minute); <br> nPAbouts_day: number of PA bouts per day; <br> nPAbouts_day.l1: number of PA bouts in previous day (lag 1); <br> nPAbouts_day.l2: number of PA bouts two day before (lag 2); <br> nBoutsLast2hours: number of PA bouts in previous 2 hours; <br> retirement: 0 (before retirement) or 1 (after retirement)<br> weekday: 0 (workday) or 1 (weekend)<br> sleepLength: number of hours of sleep last night<br> sleepLength.l1: number of hours of sleep the night before<br> sleepLength.l2: number of hours of sleep two nights before<br> pers: personalised measure of partner's influence (scale 0-1)<br> periodDay: morning, evening or afternoon</p> <p>McDonald, S., Vieira, R., O'Brien, N., White, M., & Sniehotta, F. F. (2016). Does physical activity and sedentary behavior change during the retirement transition? Findings from a series of novel n-of-1 natural experiments. <em>International Journal of Behavioral Medicine, 23</em>, S261-S261.</p> <p> </p>
SURFBIO Training: "Analytical methods for the study of microbial cell-Surface and Surface-colloid interactions" (2021)
<p>2021. SURFBIO project training within WP1.</p><p>Content:</p><ul><li><strong>Webinar on Vertical scanning interferometry: a microscopic technique to analyze surface reactivity, </strong>by Dr. Cornelius Fischer (HZDR, Germany) </li><li><strong>Webinar on An introduction to radiolabelling as a versatile tool in colloid tracing, </strong>by Stefan Schymura (HZDR, Germany).</li><li><strong>Webinar on Development and construction of biocarriers and aggregates for potential industrial applications</strong>, by Dr. Andre Skirtach and Dr. Bogdan Parakhonskiy (GHENT University). </li><li><strong>Materials and fluidic design to study artificially functionalized microorganisms</strong>, by Dr. Andre Skirtach and Dr. Bogdan Parakhonskiy (GHENT University). </li></ul>
ScienceDex guides
Understand access before you commit
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.