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82 results for “selection processes”
Numerical weather simulation using COSMOiso in June 2019 during L-WAIVE field campaign: selected model output and post-processed data.
<p>This dataset consists of extracts from a simulation with the isotope-enabled regional numerical weather prediction model COSMOiso, which covers the timespan of the Lacustrine-Water vApor Isotope inVentory Experiment (L-WAIVE) field campaign taking place in June 2019 in the Annecy valley in the French Alps (Chazette et al. 2021).The simulation has a horizontal resolution of 0.1° (~10km) and 40 vertical levels.</p><p>This COSMOiso simulation is used in Thurnherr et al. (submitted) to compare stable water isotope measurements from various platforms. Here, we provide selected model outputs and post-processed data used in this comparison study. The post-processed data contain:</p><ol><li>COSMOiso output files for time steps 20190612_12, 20190613_12, 20190615_13, 20190616_13, 20190617_12, 20190622_12.</li><li>Pressure weighted total and subcolumn averages for time steps 20190612_12, 20190613_12, 20190615_13, 20190616_13, 20190617_12, 20190622_12.</li><li>Vertical cross section of selected variables at Annecy, the location of the L-WAIVE field campaign, for the simulation time window.</li><li>Interpolated time series of subcolumn and total column averages at Annecy, the location of the L-WAIVE field campaign, for the simulation time window.</li><li>Interpolated variables along the flight tracks from the L-WAIVE campaign (see Sodemann and Seidl, 2023).</li></ol><p>See also README files for more details on the provided data.</p><p>To access further model output and post-processed data, please contact the dataset authors.</p>
Dataset: An Analytic Hierarchy Process-Based Multicriteria Model for Component Selection in a Computational Numerical Control (CNC) Machine
<p><i><strong>"An Analytic Hierarchy Process-Based Multicriteria Model for Component Selection in a Computational Numerical Control (CNC) Machine"</strong></i></p><p><i>CHILECON 2023 - </i><a href="https://site.ieee.org/chilesur/ieee-chilecon-2023/"><i>https://site.ieee.org/chilesur/ieee-chilecon-2023/</i></a><i> </i></p><p>---</p><p>En el marco del trabajo de referencia, los autores ponemos a disposición de los lectores la base de datos utilizada para el proceso de toma de decisión multicriterio para la selección del software y del MCU de una maquina CNC. </p><p>En el repositorio podrán encontrar los datos referentes a los criterios, subcriterios, indicadores, datos, fuentes de los datos extraídos, política de decisión, cálculos de las evaluaciones de los modelos AHP aplicados y el análisis de sensibilidad de estos. Además, podrán encontrar las gráficas utilizadas en el estudio en la mejor calidad posible. </p><p>El material fue puesto a disposición de todos los interesados para fines académicos y científicos. </p><p>Atte. </p><p>Los autores. </p><p>---</p>
Raw and processed hydro-meteorological variables of Jucar river basin for feature selection
<p>The dataset Processed data – input WQEISS.csv was employed for the input variable selection step in Zaniolo et al., 2018. It includes monthly values of 28 hydro-meteorological variables and indexes of Jucar river basin, Spain, for the period 1986-2000, namely:</p> <ul> <li>2 temporal features: day and month of the year;</li> <li>12 inputs to the Jucar State Index: average monthly storage and groundwater levels, average three months river runoff, and cumulated areal precipitation over 12 months;</li> <li>8 additional observed variables in the basin: three months average outflows from, and inflows to, the main reservoirs, and mean monthly areal temperatures;</li> <li>6 traditional drought indicators: Standardized Precipitation Index (SPI) and Standardized Precipitation and Evaporation Index (SPEI). SPI and SPEI indicators are computed on mean monthly data over the entire basin for 3, 6, and 12 months time aggregations.</li> </ul> <p>The last column of the dataset reports the target variable, i.e., the monthly nominal shortage of water conveyed to the irrigation districts simulated via AQUATOOL model. For further details on the dataset please consult Zaniolo et al., 2018, or the dedicated website <a href="http://www.nrm.deib.polimi.it/?page_id=2438">http://www.nrm.deib.polimi.it/?page_id=2438</a></p> <p>The unprocessed data used to compute indices and temporal cumulations in Processed data – input WQEISS.csv are reported in table Raw Data.csv. Public observations of rainfall, streamflows and storage levels come from the SAIH (Hydrological Automatic Information System) of the CHJ (Jucar Hydrological Confederation). Users can directly download data for the last 12 months on the dedicated webpage <a href="http://saih.chj.es/chj/saih/?f">http://saih.chj.es/chj/saih/?f</a> while previous data records are provided for free by CHJ upon request. Observations from piezometers are downloadable from the Piezometric Network Information section section of the CHJ <a href="https://www.chj.es/es-es/medioambiente/redescontrol/Paginas/Piezometr%C3%ADa.aspx">https://www.chj.es/es-es/medioambiente/redescontrol/Paginas/Piezometr%C3%ADa.aspx</a>.</p>
Dataset containing the results of the selection process of DSH and CSS articles 2018-2020
<p>Dataset containing the results of the selection process of Digital Scholarship of Humanities and Computational Social Science articles. It shows which articles use data and have a clear data section. These are used to create a corpus to help build and validate and evaluate the data model of data scopes.</p>
Effect of the Increased Nursing Attrition Rate on Nursing Administration Process during the Covid-19 Pandemic in a Selected Tertiary Care Hospital
<p><span>During<span> </span>the<span> </span>COVID-19<span> </span>outbreak,<span> </span>healthcare<span> </span>professionals,<span> </span>particularly<span> </span>nurses,<span> </span>were<span> </span>more<span> </span>prone to<span> </span>diseases.<span> </span>Globally<span> </span>attrition<span> </span>rate<span> </span>was<span> </span>high<span> </span>among<span> </span>nurses<span> </span>and<span> </span>during<span> </span>the<span> </span>pandemic,<span> </span>it<span> </span>increased because<span> </span>of<span> </span>various<span> </span>reasons<span> </span>such<span> </span>as<span> </span>the<span> </span>risk<span> </span>of<span> </span>infection,<span> </span>occupational<span> </span>and<span> </span>psychological<span> </span>stress, causing risk to their loved ones. This led to a chaotic situation where nurse managers were forced to implement specific strategic plans to deal with increased nurse attrition. This study aims<span> </span>to<span> </span>describe<span> </span>the<span> </span>impact<span> </span>of<span> </span>nurse<span> </span>attrition<span> </span>rate<span> </span>on<span> </span>nursing<span> </span>administration<span> </span>during<span> </span>COVID-19 at a selected tertiary care hospital. The research approach adopted in this study is descriptive cross-sectional. A total sample of 66 nurses involved in nursing administration. The data is collected through a structured questionnaire and the nurse attrition data during the COVID-19 pandemic period was collected from the interview method during the survey. Statistical tests used were frequency, percentage, mean, Standard Deviation (S.D). The study showed that there is a moderate impact of increased nurse attrition on nursing administration during the COVID-19 pandemic. The study led to the identification of gaps that need to be addressed in a similar crisis.</span></p>
Dataset used in the publication entitled "Decomposition Problem in Process of Selective Identification and Localization of Voltage Fluctuation Sources in Power Grids" presented at 2022 20th International Conference on Harmonics and Quality of Power (ICHQP)
<p>Dataset obtained from experimental research carried out in a real power grid. Based on the dataset, the problem of decomposition in identification of sources of voltage fluctuations has been presented in the publication: Kuwałek P., Decomposition Problem in Process of Selective Identification and Localization of Voltage Fluctuation Sources in Power Grids, <em>Proceedings of the 20th International Conference on Harmonics and Quality of Power</em>, IEEE , art. no. 43, 2022, Italy, Naples. The description of the power grid model is presented in this publication. The research results are part of the work under the project entitled "Voltage fluctuation diagnostic focused on identification and localization disturbing loads in power grids" funded by the National Science Centre, Poland - 2021/41/N/ST7/00397.</p>
Measurements, from CCE LTER process cruises in the California Current region, of dissolved inorganic concentrations of nutrient iron and of iron limitation at selected stations and depths, 2006 - 2021 (ongoing).
Measurements are made of dissolved iron, total iron and the potential for phytoplankton iron limitation on CCE LTER Process cruises (since 2006, ongoing) in coastal transition zones of the southern California Current System. This is a weak upwelling regime that is relatively low in nutrients and chlorophyll. Changes in phytoplankton (Chla response to Fe+) and nutrient parameters upon iron addition are also investigated.
Total dissolved organic carbon and nitrogen measurements at selected depths in the water column from CCE LTER process cruises in the California Current System, 2006 - 2021 (ongoing).
Water column bottle samples at multiple depths are taken during CCE Process cruises (since 2006, ongoing) at various CTD stations, and measurements of total organic carbon (TOC) and total nitrogen (TN) are performed onshore in the lab. TOC includes both dissolved and particulate organic carbon (DOC and POC, respectively). TN includes particulate and dissolved organic nitrogen as well as dissolved inorganic nitrogen species. In open ocean waters, POC is subtracted from TOC, and likely provides an accurate estimate of DOC because particles are typically small and homogeneously distributed in the sample. In coastal waters, and at stations where relatively high chlorophyll concentrations are present, the TOC measurement is not easily converted to DOC by subtracting POC values. Experience has shown that particles in these regions are large and inhomogeneously distributed. Therefore, samples collected in the CCE are reported as TOC and TN, expressed as micromoles of carbon (nitrogen) per liter of sea water.
Primary production estimates from 14C uptake (in situ), determined by the incorporation of inorganic carbon into particulate organic carbon (POC) due to photosynthesis at selected light levels from CCE LTER process cruises in the California Current System, 2006 - 2021 (ongoing).
Primary productivity samples of seawater are taken each day shortly before noon on the CTD rosette up-cast during the CCE Process crusies (since 2006, ongoing). Light penetration below the surface is estimated from the Secchi disk depth. Niskin bottles from depths with ambient light intensities corresponding to light levels simulated by on-deck incubators are identified and sampled. Primary production is estimated from 14C uptake using this simulated in situ technique (followed by filtering) by which the assimilation of dissolved inorganic carbon by phytoplankton yields a measure (in µg/L/day) of the rate of photosynthetic primary production (particulate organic carbon, POC) at selected light levels in the euphotic zone within the CCE study area.
Robot Self-Assembly as Adaptive Growth Process: Collective Selection of Seed Position and Self-Organizing Tree-Structures
<p>Autonomous self-assembly allows to create structures and scaffolds on demand and automatically. The desired structure may be predetermined or alternatively it is the result of an artificial growth process that adapts to environmental features and to the intermediate structure itself. In a self-organizing and decentralized control approach the robots interact only locally and form the structure collectively. Designing a complete approach that allows the robot group to collectively decide on where to start the self-assembly, that adapts at runtime to environmental conditions, and that guarantees the structural stability is challenging and does not yet exist. We present an approach to self-assembly inspired by diffusion-limited aggregation that generates an adaptive structure reacting to environmental conditions in an artificial growth process. During a preparatory stage the robots collectively decide where to start the self-assembly also depending on environmental conditions. In the actual self-assembly stage, the robots create tree-like structures that grow towards light. We report the results of robot self-assembly experiments with 50 Kilobots. Our results demonstrate how an adaptive growth process can be implemented in robots. We explain how our approach will be extended to a 3-d growth process and how robot self-assembly as an open-ended adaptive growth process opens up a multiplicity of future opportunities.</p>
Processed Data of "Selective laser melting of a Fe-Si-Cr-B-C-based complex-shaped amorphous soft-magnetic electric motor rotor with record dimensions"
<p>This data set includes the processed data of the pubblication. ABSTRACT: A record large amorphous rotor bearing an intricate 3D-geometry is produced through additive manufacturing via selecting laser melting using a powder of a traditional bulk metallic glass-forming composition of the Fe-Si-Cr-B-C system. Not only does this technique overcome the technical limitations characteristic of casting processes for amorphous alloys, but the possibility to print complex 3D geometries is expected to greatly facilitate the channeling of the magnetic flux, when such component is used as a rotor in an electric machine. The as-built part is characterized in comparison to the powder material as well as as-spun ribbons using a wide range of complementary techniques, including synchrotron x-ray diffraction, calorimetry, electron microscopy as well as room temperature ferromagnetic and hardness testing. The built part has extraordinarily high values of hardness (877 HV) and remarkable high magnetic susceptibility (9.17). This latter feature leads to a better magnetic response in the presence of an external magnetic field evidenced by a faster approach to saturation. The coercivity is small (0.51 kA/M) and the magnetic saturation relatively high (1.29 T). In addition, a large anisotropic effect on the magnetization reaction in connection with the partial crystallization in the melt pool areas is investigated experimentally.</p>
Processed RNA expression count data from Groen et al.: The strength and pattern of natural selection on rice gene expression
<p>We assessed transcriptome variation in populations of 216 accessions of rice, <em>Oryza sativa</em>, which represented all major varietal groups including indica and japonica. During the 2016 Philippines dry season the accessions were planted in triplicate (with two accessions planted in triplicate three times as replicated checks) in identical alpha-lattice layouts of 660 plots in two fields: a continuously wet paddy, and a field where plants were exposed to intermittent drought in the vegetative and reproductive stages. We measured transcript levels in leaf blades of 50-day-old plants at 33 days after seedling transplant, and 17 days after withholding water in the dry field, using a liquid automation-based 3’ mRNA-seq quantification approach. Samples were multiplexed in batches of 96 per library. Raw sequencing data are available at the SRA in BioProject accession number PRJNA588478. A key to the raw sequencing data in this BioProject can be found in the metadata of the processed RNA expression count data here.</p>
Dataset: Stimulus selection drives value-modulated somatosensory processing in superior colliculus
<p>Pluta Lab</p> <p>.mat data files used in the following paper</p> <p>Stimulus selection drives value-modulated somatosensory processing in superior colliculus </p> <p>Details can be found in readme.txt</p>
Selection process of articles for a systematic literature review on citizen science initiatives in school contexts
<p>Selection process of articles for a systematic literature review on citizen science initiatives in school contexts. Initial records are extracted from Web of Science database from 2000 to 2021. We used the keyword "citizen science" in the title mixed with some keywords in the topic of the search: “classroom” or “school” or “student*” or “pupil” or “learning”.</p> <p>The different database sheets inform about the application of the inclusion and exclusion criteria applied.</p>
Data from: Fruit resources shape sexual selection processes in a lek mating system
Open the record for dataset details and reuse information.
Selective laser melting process of tool steel powder
<p>The video demonstrates one of the most commercialised powder bed fusion techniques of additive manufacturing, the Selective Laser Melting (SLM). Tool steel powder (Gas atomized ASP2023®) is processed using a a commercial SLM instrument (AconityMINI). During the SLM process, the powder is delivered to the pre-heated powder bed through the powder delivery system and then selectively melted using the laser beam in a chamber filled with argon (see attached figure about the chamber and the key parts of the process). The delivered powder particles are solidified to form layers, as the process continues until the desired three-dimensional component is fabricated. </p>
Processed data for the study on "Observation of site-selective chemical bond changes via ultrafast chemical shifts"
<p>This repository contains the underlying data for the paper entitled "Observation of site-selective chemical bond changes via ultrafast chemical shifts". The uploaded data are preprocessed data measured at the LCLS SLAC facility. Each individual file contains the measurements at a set delay time and spectrometer setting on a shot-by-shot basis.</p> <p>The files contain the following keys:</p> <pre>['Ebeam_energy_MeV', 'Electron_orbit_probe_x', 'Electron_orbit_probe_y', 'Electron_orbit_pump_x', 'Electron_orbit_pump_y', 'Fiducial', 'Fit_quality', 'Gas_monitor_mJ', 'Group', 'N_electrons', 'Photon_energy_FEL_eV', 'Probe_energy_xtcav', 'Probe_pulse_energy_mJ', 'Probe_width_fs', 'Pump_energy_xtcav', 'Pump_pulse_energy_mJ', 'Pump_width_fs', 'TOF_CO_yield', 'TOF_Ne_yield', 'Time_delay_XTCAV']</pre> <p>Description of the individual entries is found in the supplementary materials of the publication. The following table assigns the time delay and measure electron kinetic energy for each dataset.</p> <table> <tbody> <tr> <td>Time delay</td> <td>Ek = 234eV</td> <td>Ek = 220eV</td> <td>Ek = 210eV</td> </tr> <tr> <td>40fs</td> <td>Run_210</td> <td>Run_212</td> <td>Run_213</td> </tr> <tr> <td>20fs</td> <td>Run_231</td> <td>Run_236</td> <td>Run_235</td> </tr> <tr> <td>15fs</td> <td>Run_239</td> <td>Run_242</td> <td>Run_241</td> </tr> <tr> <td>10fs</td> <td>Run_238</td> <td>Run_233</td> <td>Run_234</td> </tr> <tr> <td>5fs</td> <td>Run_228</td> <td>Run_226</td> <td>Run_225</td> </tr> <tr> <td>0</td> <td>Run_221</td> <td>Run_223</td> <td>Run_224</td> </tr> <tr> <td>-5fs</td> <td>Run_217</td> <td>Run_219</td> <td>Run_220</td> </tr> </tbody> </table> <p> </p>
Processed data for Evidence of horizontal gene transfer and environmental selection impacting antibiotic resistance evolution in soil-dwelling Listeria
<p>Processed/source data for the manuscript Evidence of horizontal gene transfer and environmental selection impacting antibiotic resistance evolution in soil-dwelling <em>Listeria</em>.</p>
Raw data for " Unnatural evolutionary processes of SARS-CoV-2 variants and possibility of deliberate natural selection" DOI 10.5281/zenodo.8248320
<p>Compressed raw data for " Unnatural evolutionary processes of SARS-CoV-2 variants and possibility of deliberate natural selection" </p> <p>DOI 10.5281/zenodo.8248320</p>
Confronting assumptions about prey selection by lunge-feeding whales using a process-based model
<ol> <li class="CH3AbstractCxSpFirst"><span>The relative energetic benefits of foraging on one type of prey rather than another are not easily measured, particularly for large free-ranging predators. Nonetheless, assumptions about preferred and alternative prey are frequently made when predicting how a predator may impact its environment, adapt to environmental change, or interact with human activities.</span></li> <li class="CH3AbstractCxSpMiddle"><span>We developed and implemented a process-based model to investigate the potential energetic benefit (PEB) of <i>in situ</i> foraging opportunities in rorqual whales. The model integrates and evaluates the energetic importance of measured prey patch characteristics (prey distribution, energy content and predator avoidance) and predator characteristics (morphometrics, foraging tactics and feeding rates). We applied the model to test the assumption that hatchery-released juvenile salmon are an "easy meal" for humpback whales compared to more common prey, herring and krill. </span></li> <li class="CH3AbstractCxSpMiddle"><span>In eleven out of the thirteen foraging situations considered, whales were found to be feeding in a manner where net energy gain was greater than the energetic costs of non-foraging swimming. Humpback whale PEB for hatchery-released juvenile salmon fell within the range of the PEB for krill and herring but varied by species, from relatively high PEB for chum salmon to relatively low for coho salmon. Our model provides behavioral insight as well, indicating that shallow feeding may be more important for reducing energy expenditure through slower lunge speeds than for increasing prey capture. The model also provides a means of identifying prey patch characteristics, with prey aggregation playing the largest role in determining PEB despite being a poor overall proxy for PEB, supporting the use of the complex model framework. </span></li> <li class="CH3AbstractCxSpLast"><span>Modeling approaches are especially valuable where they can use reasonable assumptions to substitute for lack of reliable observations, thereby integrating a range of interacting factors into a single framework. Additionally, because process-based models can make predictions outside the range of previously observed conditions, they will be increasingly useful in a changing climate.</span></li> </ol>
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.