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4,480 results for “initiative”
80 Initial Data-set Studies SMS Strategy CG
<p>Initial Data set of 80 primary studies SMS: "Empirical Strategies in Software Engineering Research: A Literature Survey", by Cathy Guevara-Vega<br> </p>
Fig. 2. Scuba diver using a in Are Abrolhos no-take area sites of naïve fish? An evaluation using flight initiation distance of labrids
Fig. 2. Scuba diver using a wooden handle to simulate the spearfisher behavior.
Data from: Plant selection initiates alternative successional trajectories in the soil microbial community after disturbance
Because interactions between plants and microbial organisms can influence species diversity and rates of nutrient cycling, how plants shape microbial communities is fundamental to understanding the structure of ecosystems. Despite this, the spatial and temporal scales over which plants influence microbial communities is poorly understood, particularly whether past abiotic or biotic legacies strongly constrain microbial community development. We examined biogeochemical cycling and microbial community structure in a coastal landscape where historical patterns of vegetation transition after a large fire in 1995 are well known, allowing us to account for past abiotic and biotic conditions. We found that alternative states in microbial community structure and ecosystem processes emerged under different plant species, regardless of past conditions. Greenhouse studies further demonstrated that these differences arise from direct plant selection of microbes, with selection stronger in roots compared with soils, especially for bacteria. Correlation of microbial community structure with seedling growth rates was also stronger for fungi compared to bacteria. Despite these effects, minimal overlap between seedling and field microbial communities indicates that the effects of initial plant selection are not stable, rather plant selection initiated alternative successional trajectories after the fire. Using data from a guild where we have abundant natural history information - ectomycorrhizal fungi - we show that greenhouse communities are dominated by ruderal taxa that are also common in the field after the fire, and that these ruderal fungi strongly alter spatial patterns in plant-soil feedback, enabling invasion and transformation of soils previously occupied by heterospecific plants, thus potentially acting as keystone mutualists.
Dataset of the European Light Microscopy Initiative 2019 Core Facility Large Survey
<p>In occasion of the 2019 ELMI meeting held in Brno, Czech Republic the organizers of the Core Facility day (Laurent Gelman, Marco Marcello, Roland Nitschke, Laure Plantard, Stefan Terjung) launched a Large Core Facility Survey.<br> This repository contains the screenshots of the original survey, a formatted list of questions, and the anonymised data from this survey, a total of 226 responses from 25 countries distributed over 5 continents. Results are subdivided in 5 Areas, Staff, Finances, Equipment, Quality control, IT and Data Management.</p>
Data from: Phenotypic plasticity facilitates initial colonization of a novel environment
Phenotypic plasticity can allow organisms to respond to environmental changes by producing better matching phenotypes without any genetic change. Because of this, plasticity is predicted to be a major mechanism by which a population can survive the initial stage of colonizing a novel environment. We tested this prediction by challenging wild Drosophila melanogaster with increasingly extreme larval environments and then examining expression of alcohol dehydrogenase (ADH) and its relationship to larval survival in the first generation of encountering a novel environment. We found that most families responded in the adaptive direction of increased ADH activity in higher alcohol environments and families with higher plasticity were also more likely to survive in the highest alcohol environment. Thus, plasticity of ADH activity was positively selected in the most extreme environment and was a key trait influencing fitness. Furthermore, there was significant heritability of ADH plasticity which can allow plasticity to evolve in subsequent generations after initial colonization. The adaptive value of plasticity, however, was only evident in the most extreme environment and had little impact on fitness in less extreme environments. The results provide one of the first direct test of the adaptive role of phenotypic plasticity in colonizing a novel environment.
Data from: Initial nitrous oxide, carbon dioxide, and methane costs of converting conservation reserve program grassland to row crops under no-till vs. conventional tillage
Around 4.4 million ha of land in USDA Conservation Reserve Program (CRP) contracts will expire between 2013 and 2018 and some will likely return to crop production. No-till (NT) management offers the potential to reduce the global warming costs of CO2 , CH4 , and N2 O emissions during CRP conversion, but to date there have been no CRP conversion tillage comparisons. In 2009, we converted portions of three 9-21 ha CRP fields in Michigan to conventional tillage (CT) or NT soybean production and reserved a fourth field for reference. Both CO2 and N2 O fluxes increased following herbicide application in all converted fields, but in the CT treatment substantial and immediate N2 O and CO2 fluxes occurred after tillage. For the initial 201-day conversion period, average daily N2 O fluxes (g N2 O-N ha-1 d-1 ) were significantly different in the order: CT (47.5 ± 6.31, n = 6) ≫ NT (16.7 ± 2.45, n = 6) ≫ reference (2.51 ± 0.73, n = 4). Similarly, soil CO2 fluxes in CT were 1.2 times those in NT and 3.1 times those in the unconverted CRP reference field. All treatments were minor sinks for CH4 (-0.69 ± 0.42 to -1.86 ± 0.37 g CH4 -C ha-1 d-1 ) with no significant differences among treatments. The positive global warming impact (GWI) of converted soybean fields under both CT (11.5 Mg CO2 e ha-1 ) and NT (2.87 Mg CO2 e ha-1 ) was in contrast to the negative GWI of the unconverted reference field (-3.5 Mg CO2 e ha-1 ) with on-going greenhouse gas (GHG) mitigation. N2 O contributed 39.3% and 55.0% of the GWI under CT and NT systems with the remainder contributed by CO2 (60.7% and 45.0%, respectively). Including foregone mitigation, we conclude that NT management can reduce GHG costs by ~60% compared to CT during initial CRP conversion.
Initial release of open-science notebook
<p>Initial release of open-science notebook of research on comparative phylogeographical model choice.</p>
Meshes and initial data for 2D and 3D experiments with PyNosh
<p>Data files used in Experiments with PyNosh.</p>
Molecular architecture of the 40S⋅eIF1⋅eIF3 translation initiation complex
<p>Eukaryotic translation initiation requires the recruitment of the large, multiprotein eIF3 complex to the 40S ribosomal subunit. Using X-ray structures of all major components of the minimal, six-subunit <em>Saccharomyces cerevisiae</em> eIF3 core, together with cross-linking coupled to mass spectrometry, we were able to use IMP to position and orient all eIF3 components on the 40S•eIF1 complex, revealing an extended, modular arrangement of eIF3 subunits.</p> <p>For more information about how to reproduce this modeling, see https://salilab.org/40S-eIF1-eIF3 or the README file.</p>
Initial Set of Open Digital Science indicators
<p>Initial set of indicators developed in the Open Digital Science Study. Since the indicators proposed differed considerably in terms of their scope, granularity, specificity, and measurability, it was stated in the introductory part of the assessment that they should be considered a starting point for further development rather than a mature set of indicators</p> <p> </p> <p> </p>
DICE H2020 Deliverable 3.8 — Initial version
<p>The data hereby published supports the results of the European research<br /> project DICE H2020 deliverable D3.8, which can be downloaded at http://www.dice-h2020.eu/deliverables/.<br /> When referring to the data, please cite the above mentioned deliverable.</p>
Characteristics of the initial stage and return stroke currents of rocket-triggered lightning flashes in southern China
<p>This study investigates the initial stage (IS) and return stroke (RS) currents of 50 triggered lightning flashes (TLFs) that were conducted in southern China. The IS of the negative TLFs has a longer duration, and larger average current, charge transfer, and action integral than those reported elsewhere, with geometric means (GMs) of 347.9 ms, 132.5 A, 45.1 C, and 10.0 × 10<sup>3</sup> A<sup>2</sup> s, respectively. Two positive TLFs containing no RS have much greater average currents, charge transfers, and action integrals in the IS when compared with the negative TLFs. The RS has a greater peak current (17.2 kA; GM, same to below), charge transfer within 1 ms (1.3 C), and action integral within 1 ms (5.8 × 10<sup>3</sup> A<sup>2</sup> s), and shorter 10% to 90% rise time (0.4 μs) than elsewhere. The peak current is prominently correlated with the rate of rise, charge transfer within 1 ms, and action integral within 1 ms. Furthermore, when the total duration of the RS and any following continuing currents is longer than 40 ms, the peak current, charge transfer within 1 ms, and action integral within 1 ms of the RS are seldom greater than 25 kA, 2.6 C, and 15 × 10<sup>3</sup> A<sup>2</sup> s, respectively. It is indicated that TLFs containing RSs tend to have a longer duration but a smaller charge transfer during the IS than those without RS. The peak current of the RS is weakly correlated with its preceding silence period when there was no channel base current.</p>
Protein Structure Initiative - TargetTrack 2000-2017 - all data files
<p><strong>Protein Structure Initiative - TargetTrack protein target registration database (795 MB, gzipped tarball)</strong></p> <p>The Protein Structure Initiative was a high-throughput structural genomics effort from 2000-2015 focused on developing technologies to enable greater coverage of protein structure space. Over its 15-year tenure, over 100 investigators at 35 centers (see ContributingCenters.xls) declared over 350,000 protein sequences (targets) that they would study using state-of-the-art protein production and structure determination methods. Many of these targets were selected through bioinformatics-based methods to serve as representatives for sequence and structure clusters. </p> <p>From 2003-2010, these selected sequences and some basic identifying metadata were kept in a database called TargetDB, created at the Research Collaboratory for Structural Bioinformatics at Rutgers University. In 2008, a second database named PepcDB was created to track detailed experimental trial history and the standard protocols used by the PSI centers. These two databases became the principal structural genomics target databases, and were rolled into the <strong>PSI Structural Biology Knowledgebase</strong> in 2008. </p> <p>As part of the third phase of the PSI, TargetDB and PepcDB were merged into a single resource, <strong>TargetTrack</strong>, to facilitate one-stop access to the data as well as expanding the schema to include new required data items. Participating centers deposited the latest status on their active targets and the protocols that were used (along with any deviations) on a weekly or quarterly basis. TargetTrack provided a variety of pre-computed data downloads on a weekly basis as well. </p> <p>In July 2017, the Structural Biology Knowledgebase ceased operations. The files provided in this tarball represent the final datafiles generated by TargetTrack (timestamp June 30, 2017). <strong>Please read the README included in this dataset for descriptions of each file. </strong></p> <p><strong>The entire TargetTrack datafile in XML format can be found in /TargetTrack XML files/tt.xml.gz</strong></p> <p>Key documentation can be found in the /Documentation folder.<br> TargetTrack schema: targetTrack-v1.4.1.pdf<br> Spreadsheet with TargetTrack enumerations for relevant fields: targetTrackEnumeratedDataItems-v1.4.1-1.xls<br> Image depicted the XML data schema: targetTrack-v1.4.1.jpg</p> <p>These files are 868 MB in total size, uncompressed. <br> To open the tarball, use the command 'tar -zxvf TargetTrack-1Jul2017.tar.gz'</p> <p>-- created by the PSI Structural Biology Knowledgebase, July 5, 2017</p>
Dissection of core promoter syntax through single nucleotide resolution modeling of transcription initiation (CLIPNET data)
<div>This contains data necessary to reproduce the figures in the CLIPNET paper (preprint <a href="https://www.biorxiv.org/content/10.1101/2024.03.13.583868">here</a>) as well as processed data used to train and evaluate CLIPNET. To preserve subdirectory structure, we've packaged the data into tar archives. Please refer to the README documents in our manuscript GitHub repo for more details on file contents: <a href="https://github.com/Danko-Lab/clipnet_paper/">https://github.com/Danko-Lab/clipnet_paper/</a></div> <div> </div> <div>Pretrained CLIPNET models are archived separately at <a href="../doi/10.5281/zenodo.10408622">DOI 10.5281/zenodo.10408622</a></div> <div> </div> <div>V5: Fixed bug in calculation of profile attribution scores causing them to be off by a factor of exactly 500. Genome-wide DeepSHAP tracks & TF-MoDISco tracks have been accordingly updated. I have not updated the individual examples, as these can be quickly fixed by simply multiplying by 500 when plotting. Additionally, I have uploaded profile and quantity motif calls, which contain genome-wide seqlet annotations. The columns in these files are [chrom, start, end, peak_idx, motif_annotation].</div> <div>V4: Uploaded individual bigWigs. These have been lifted over using CrossMap from the original hg19 (GSE110638) to hg38 and RPM normalized.</div> <div>V3: Final version prior to journal submission. Don't recall exact details of what's changed.</div> <div>V2: evaluation_metrics.tar.gz and evaluation_data.tar.gz have been replaced. Previously, we benchmarked the models by treating each peak in each individual as a separate data point. Here, we instead predicted from the reference genome and compared against the averaged bigWigs.</div>
jtextor/trialMinRand: Initial release
<p>Implementation used in the MIND-DC trial (NCT02993315).</p>
Initial experiments with Uroprint tensile tester V1- Nanoidentation 2c
<p>Nanoindentation data on the Pavone for one of the soft PDMS samples. Area is estimated from the included images with reference on the metal grips with a width of 4.4 mm and thickness of 0.3 mm.</p>
Initial experiments with Uroprint tensile tester V1- Nanoidentation 2b
<p>Nanoindentation data on the Pavone for one of the soft PDMS samples. Area is estimated from the included images with reference on the metal grips with a width of 4.4 mm and thickness of 0.3 mm.</p>
Initial experiments with Uroprint tensile tester V1-1
<p>Data for tensile tests on PLMA samples as measured on the version 1 tensile tester. Data is contained within two columns with voltages for position (column 2)and force (column 1). Conversion to position in mm is by the equation 15.66-position_voltage*4.2. Conversion to force in Newtons is by force_voltage*100*261*1.71*(-1/1000000). Data for tensile tests on PLMA, whole mouse bladder, and soft PDMS as measured on the version 1 tensile tester. Area is estimated from the included images with reference on the metal grips with a width of 4.4 mm and thickness of 0.3 mm.</p>
Initial experiments with Uroprint tensile tester V1-2b
<p>Data for tensile tests on soft PDMS samples as measured on the version 1 tensile tester. Data is contained within two columns with voltages for position (column 2)and force (column 1). Conversion to position in mm is by the equation 15.66-position_voltage*4.2. Conversion to force in Newtons is by force_voltage*100*261*1.71*(-1/1000000). Data for tensile tests on PLMA, whole mouse bladder, and soft PDMS as measured on the version 1 tensile tester. Area is estimated from the included images with reference on the metal grips with a width of 4.4 mm and thickness of 0.3 mm.</p>
Initial experiments with Uroprint tensile tester V1- Nanoidentation 2a
<p>Nanoindentation data on the Pavone for one of the soft PDMS samples. Area is estimated from the included images with reference on the metal grips with a width of 4.4 mm and thickness of 0.3 mm.</p>
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.