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2,967 results for “secondary”
Secondary Data from Insights from Publishing Open Data in Industry-Academia Collaboration
<h1>Secondary Data from Insights from Publishing Open Data in Industry-Academia Collaboration</h1> <h2>Authors</h2> <p>Per Erik Strandberg [1], Philipp Peterseil [2], Julian Karoliny [3], Johanna Kallio [4], and Johannes Peltola [4].</p> <p>[1] Westermo Network Technologies AB (Sweden).<br>[2] Johannes Kepler University Linz (Austria)<br>[3] Silicon Austria Labs GmbH (Austria).<br>[4] VTT Technical Research Centre of Finland Ltd. (Finland).</p> <h2>Description</h2> <p>This data is to accompany a paper submitted to Elsevier's data in brief in 2024, with the title <em>Insights from Publishing Open Data in Industry-Academia Collaboration</em>.</p> <p><em>Tentative Abstract:</em> Effective data management and sharing are critical success factors in industry-academia collaboration. This paper explores the motivations and lessons learned from publishing open data sets in such collaborations. Through a survey of participants in a European research project that published 13 data sets, and an analysis of metadata from almost 281 thousand datasets in Zenodo, we collected qualitative and quantitative results on motivations, achievements, research questions, licences and file types. Through inductive reasoning and statistical analysis we found that planning the data collection is essential, and that only few datasets (2.4%) had accompanying scripts for improved reuse. We also found that authors are not well aware of the importance of licences or which licence to choose. Finally, we found that data with a synthetic origin, collected with simulations and potentially mixed with real measurements, can be very meaningful, as predicted by Gartner and illustrated by many datasets collected in our research project.</p> <h2>Secondary data from Survey</h2> <p>The file <code>survey.txt</code> contains secondary data from a survey of participants that published open data sets in the 3-year European research project InSecTT.</p> <h2>Secondary data from Zenodo</h2> <p>The file <code>secondary_data_zenodo.json</code> contains secondary data from an analysis of data sets published in Zenodo. It is accompanied with a <code>py</code>-file and a <code>ipynb</code>-file to serve as examples.</p> <h2>License</h2> <p>This data is licenced with the Creative Commons Attribution 4.0 International license. You are free to use the data if you attribute the authors. Read the license text for details.</p>
Risk factor prediction for Secondary Glaucoma amongst patients presenting with Pseudo exfoliation Syndrome (PEX) at Ophthalmology OPD in a Tertiary Care Centre in Ahmedabad
<p>Here we are uploading a data sheet of the<strong> "Risk factor prediction for Secondary Glaucoma amongst patients presenting with Pseudo exfoliation Syndrome (PEX) at Ophthalmology OPD in a Tertiary Care Centre in Ahmedabad." </strong></p>
Rereferenced Chemical Shift files used to select dihedrals for the 5 secondary structure conformations used to calculate Conformational Variability (ConVa).
<p>These Chemical Shifts in this repository were processed with ShiftCrypt (1) and then processed as described in the manuscript. </p> <p> </p> <p>1- Gabriele Orlando, Daniele Raimondi, Luciano Porto Kagami, Wim F Vranken, ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values, <em>Nucleic Acids Research</em>, Volume 48, Issue W1, 02 July 2020, Pages W36–W40, <a href="https://doi.org/10.1093/nar/gkaa391">https://doi.org/10.1093/nar/gkaa391</a></p>
Model output from CAABA/MECCA study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)"
<p>This dataset includes the main data obtained during the study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)" (DOI:10.5194/gmd-2023-102). The updated model code can be found at zenodo.org (DOI:10.5281/zenodo.7944174). The data can be used to replicate the results shown in the manuscript. Contained are results produced by the updated CAABA/MECCA (version 4.7.0) and reference data from CAABA/MECCA version 4.5.5. In version 4.7.0, new biogenic and anthropogenic species are introduced to the model (limonene and long-chained alkanes) with refined multiphase chemistry, while new reaction pathways are added for existing compounds (isoprene, benzene and IEPOX). The output is generated to evaluate model results in terms of temperature- and NOx-dependency.</p>
Multiplexed Staining Dataset - OMAP 5 - Liver-Lanthanides-conjugated antibodies and C60-secondary ion mass spectrometry imaging
<p>This dataset contains images of multiplexed antibody panel on a human pediatric liver section including the nuclear marker and antibodies conjugated with lanthanides tags. The dataset is one example of serial experiments of multiplexed antibody staining and imaging. The antibody panel targets the major cell types and tissue structures in the liver tissue. Data acquisition was performed using single multiplexing imaging by C60-secondary ion mass spectrometry.</p> <p> </p>
Patterns of and controls over nitrogen inputs by green alder (Alnus viridis spp. fruticosa) to a secondary successional chronosequence in interior Alaska I - N2 Fixation and Soil Temperature
We measured rates of nitrogen fixation by Alnus viridis spp. fruticosa and concurrent subcanopy soil temperature at BNZ LTER. To do so we utilized replicate (n=3/stage) stands of a seral sequence of successional stages maintained by the Bonanza Creek Long-Term Ecological Research program (BNZ LTER). At each of the 9 replicate stands we selected a total of 70 individual shrubs. During each of 7 sampling periods, 3 across the growing season of 1997 and 4 during 1998, we randomly selected 10 of 70 A. viridis spp. fruticosa at each replicate stand. We used acetylene reduction assays (ARA) to estimate rates of N2 fixation at each of the selected shrubs and concurrently measured soil temperature at each shrub. The attached database may be utilized to (1) elucidate seasonal trends in rates of N2 fixation by A. viridis spp. fruticosa across a boreal forest chronosequence and (2) investigate soil temperature controls over rates of N2 fixation. It may also be used to statistically analyze differences between years, successional stages and replicates within successional stage in both rates of ARA and temperature. We developed this database to describe seasonal trends of rates of nitrogen fixation by A. viridis spp. fruticosa across a boreal forest chronosequence and to elucidate soil temperature controls over rates.
Patterns of and controls over nitrogen inputs by green alder (Alnus viridis spp. fruticosa) to a secondary successional chronosequence in interior Alaska II - Soil Physical and Chemical Properties
In September of 1999 we collected soil cores to identify stage, replicate stand, canopy, and soil horizon patterns of soil physical (color, bulk density, pH) and chemical (N, C, P) parameters.
Stand Dynamics and Radial Growth Measurements from Old-Growth and Secondary-Growth Forests at the Coweeta Hydrologic Laboratory and Joyce Kilmer Wilderness Area
Our objectives were to define disturbance causes, rates (percent disturbance per decade), magnitudes and frequency (time since last disturbance) for both secondary and old-growth mixed-oak stands, and to determine if all mixed oak stands experience similar disturbance history.
Secondary studies in the academic context: A systematic mapping and survey
<p>An online version of the survey executed in the paper "Secondary studies in the academic context: A systematic mapping and survey".</p>
Mapped read data and files and scripts from: Vicariance followed by secondary gene flow in a young gazelle species complex
<p>Grant's gazelles have recently been proposed to be a species complex comprising three highly divergent mtDNA lineages (<em>Nanger granti</em>, <em>N. notata</em> and <em>N. petersii</em>). The three lineages have non-overlapping distributions in East Africa, but without any obvious geographical divisions, making them an interesting model for studying the early stage evolutionary dynamics of allopatric speciation in detail. Here we use genomic data obtained by restriction site-associated (RAD) sequencing of 106 gazelle individuals to shed light on the evolutionary processes underlying Grant's gazelle divergence, to characterize their genetic structure and to assess the presence of gene flow between the main lineages in the species complex. We date the species divergence to 134,000 years ago, which is recent in evolutionary terms. We find population subdivision within <em>N. granti</em>, which coincides with the previously suggested two subspecies, <em>N.g. granti</em> and <em>N.g. robertsii</em>. Moreover, these two lineages seem to have hybridized in Masai Mara. Perhaps more surprisingly given their extreme genetic differentiation, <em>N. granti</em> and <em>N. petersii</em> also show signs of prolonged admixture in Mkomazi, which we identified as a hybrid population most likely founded by allopatric lineages coming into secondary contact. Despite the admixed composition of this population, elevated X-chromosomal differentiation suggests that selection may be shaping the outcome of hybridization in this population. Our results therefore provide detailed insights into the processes of allopatric speciation and secondary contact in a recently radiated species complex.</p>
Post-injury immunosuppression and secondary infections are caused by an AIM2 inflammasome-driven signaling cascade
<p>RAW FCS files for the manuscript:</p> <p>"Post-injury immunosuppression and secondary infections are caused by an AIM2 inflammasome-driven signaling cascade"</p> <p> </p>
Data from paper: Large carbon sink potential of Secondary Forests in Brazilian Amazon to mitigate climate change (public)
<p><strong>Title</strong>: Large carbon sink potential of Secondary Forests in the Brazilian Amazon to mitigate climate change</p> <p><strong>Contact:</strong> Viola Heinrich (viola.heinrich@bristol.ac.uk)</p> <p><strong>This repository contains</strong>:</p> <ol> <li>Zipped folder:<strong> Fig1_data_input.zip</strong> - all the files needed to produce Figure 1a-e of the main paper. Set the working directory to folder containing the file and use the script "Fig1a_f_plot.R" to run (see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 1 - these files are in the format "<strong><driver>_assessment_v2.csv</strong>". The columns in the files are: A: age of secondary forest; B: 50th percentile (median) of the modal Aboveground Biomass (AGB) value for the given age (note, units are in biomass not carbon: Mg/ha/yr); C: The bias-corrected AGB value, calculated by subtracting the lowest AGB value in column B such that the AGB data starts at or near 0Mg/ha/yr at age 1. D: the number of secondary forest pixels observed to have the given age, E: "Threshold" : the threshold limits of the given driver e.g. 0 Fires in fire_assessmentv2.csv implies the corresponding secondary forest pixels experienced 0 fires throughout the analysis period. The folder also contains the output regrowth models seen in Figure 1 in the format "<strong>regrowth_model_<driver_threshold>.RData" </strong>where driver_threshold refers to the driving variable name and the associated threshold limit for the given driver.</li> <li>Zipped folder:<strong> Fig2_regions_outline.zip</strong> - contains the boundaries of the 4 regions identified in Figure 2a of the main paper in a shapefile (.shp) format and the corresponding file formats needed to produce and load a shapefile. </li> <li>Zipped folder: <strong>Fig1g_2b_e_variable_importance.zip</strong> - contains the output files of the random forest analysis assessing the variable importance for the whole Amazon ("whole_Amazon" subfolder) and for the different regions identified in Figure2a. Files are given as .RDS files that can be loaded in R and the corresponding figures produced using the script "Fig1g_2b_e_plot.R". Files start with the region of interest e.g. "whole_Amazon" or "NE_sector". Middle part of the filename - importance_conditionalTrue/False - this determines whether the importance was calculated using the conditional permutation (True) or not (False). The end of the file name - seed<NUM> - denotes the number of the random seed that was set to extract the sample data. e.g. whole_Amazon_2500_cforest_important_conditionalTrue_seed200.RDS - shows the conditional permutation importance assessment using a sample size of 2500 when the setseed parameter was set to 200 to extract a random sample representing the whole Amazon. The remaining files are the random forest output - as .RDS file. Please note the code to produce the random forest model and the importance assessment has not been included here - this code takes multiple days to run, so only the input and outputs have been included here. Please contact the corresponding author (see end) for more information on this. </li> <li>Zipped folder: <strong>Fig3_data_input.zip</strong> - all the files needed to produce Figure 3a-d of the main paper. Set the working directory to folder containing the file and use the script "Fig3_plot.R" to run (see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 3 - these files are in the format "<strong><REGION>-Group.csv</strong>". See bullet point 1 for explanations for the columns in the file. Again column E -"threshold" denotes the code used to identify the the 4 subclasses of regrowth seen in the Figure. Where 11 = No disturbance; 12 = Only burning; 21 = Only (multiple) deforestations; 22 = Both burning and multiple deforestations as disturbance. The code takes data in AGB and converts to AGC. The folder also contains the output regrowth models seen in Figure 3 in the format <strong>"regrowth_model_<region_disturbance_type>.RData" </strong>where region_disturbance refers to the region and the type of disturbance experienced. </li> <li> Zipped folder: <strong>Fig4_5_carbon_sink_2017.zip </strong>- Contains two subfolders: a) <strong>Map_aggre_0.1deg</strong> -this folder contains .tiff files (and associated files) of the losses, gains and net change in AGC between 2016 - 2017 in secondary forests in Amazonia - this has been aggregated to 0.1 degree grid cells so each cell contains the total sum of the losses/gains experienced by secondary forests in that 0.1degree grid cell. b) <strong>secondary_forest_by_region_and_disturbance </strong>- this folder contains .tiff files (and associated files) of the secondary forest data at the original resolution (30m) for 2016 and 2017 split up according to the regions identified in Figure 2, and the type of disturbance (if any). The associated files include a .dbf file which includes additional data [read "README.txt" file in folder] - upon loading the data in a GIS software - the age of the secondary forest pixel will be displayed - open the attribute table to see more data associated with that given pixel e.g. modelled associated AGB for a given pixel. Files in this folder can be used to make Figure 4d and Figure 5 - see script "Fig4_Fig5_plot.R" in the code repository (see below). </li> </ol> <p><strong>Code: </strong>The corresponding code mentioned here can be access here: <a href="https://github.com/heinrichTrees/secondary-forest-regrowth-amazon-public">heinrichTrees/secondary-forest-regrowth-amazon-public (github.com)</a></p> <p><strong>Data usage: </strong>When using any code or data in this repository or another related to this study please cite Heinrich et al.2021 and the original paper as well as the DOI of this repository. </p> <p>If you need anything else, please contact the corresponding author: Viola Heinrich (viola.heinrich@bristol.ac.uk)</p>
Figure 7 in A new species of the genus Lasioseius (Acari: Blattisociidae) inhabiting litter of secondary rainforest in Sumatra, Indonesia
Figure 7 Lasioseius orangrimbaen. sp., adult male, lateral region of the dorsal shield, showing the insertion of the seta r6: a Seta r6 in the dorsal shield; b – Setar6 in unsclerotized lateral cuticle. No scale.
Figure 3 in A new species of the genus Lasioseius (Acari: Blattisociidae) inhabiting litter of secondary rainforest in Sumatra, Indonesia
Figure 3 Lasioseius orangrimbaen. sp., adult female: a – Pre-sternal region and sternal shield showing the punctuated area, arrow showing the narrow anteromedian strip; b – Genital shield with punctuations; c, d – Metapodal platelets, variant forms.
Figure 10 Tarsus II in A new species of the genus Lasioseius (Acari: Blattisociidae) inhabiting litter of secondary rainforest in Sumatra, Indonesia
Figure 10 Tarsus II with macroseta pl2 in adult females: a –Lasioseius orangrimbaen. sp.; b – Lasioseius laciniatus; c – Lasioseius tricuspidis. No scale. Images b–c taken from VIRMISCO (Deckeret al.2018).
Figure 1 in A new species of the genus Lasioseius (Acari: Blattisociidae) inhabiting litter of secondary rainforest in Sumatra, Indonesia
Figure 1 Lasioseius orangrimbaen. sp., adult female: Dorsal idiosoma. Note absence of setaeR1 andUR series.
Figure 9 in A new species of the genus Lasioseius (Acari: Blattisociidae) inhabiting litter of secondary rainforest in Sumatra, Indonesia
Figure 9 Lasioseius orangrimbaen. sp., adult male: a – Chelicera (antiaxial view); b – Gnathotectum.
Figure 4 in A new species of the genus Lasioseius (Acari: Blattisociidae) inhabiting litter of secondary rainforest in Sumatra, Indonesia
Figure 4 Lasioseius orangrimbaen. sp., adult female: a – Subcapitulum; b – Chelicera (antiaxial view); c – Gnathotectum.
North Atlantic Oscillation (NAO) climate index hidden in ocean generated secondary microseisms
<p>Datatsets associated with "North Atlantic Oscillation (NAO) climate index hidden in ocean generated secondary microseisms". The data include the daily seismic cross-correlograms for station pairs located on land and at the seafloor offshore Ireland, 3D models used for the numerical simulations and the associated synthetic seismic data.</p>
Primary and secondary carboxylic acids emissions
<p>Primary and secondary carboxylic acids emissions from various combustion scenarios were quantified</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.