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15,733 results for “article”
Data described in the article "Unraveling the diversity of hyphal explorative traits among Rhizophagus irregularis genotypes"
<p>The dataset includes supplementary Figures, tables and the results of two experiments published in the study titled "Unraveling the diversity of hyphal explorative traits among Rhizophagus irregularis genotypes", available here: https://doi.org/10.1007/s00572-024-01154-8</p> <p>The study compares seven homokaryotic isolates (genotypes) of Rhizophagus irregularis, aiming to characterize the range of intraspecific variability with respect to hyphal exploration of organic nitrogen (N) resources, and N supply to plants. Two experiments (one in vitro and one in open pots) were conducted, and 15N-chitin as the isotopically labeled organic N source was used.</p> <p>Experiment 1 (in vitro), mycelium of all arbuscular mycorrhizal (AM) fungal genotypes transferred a higher amount of 15N to the plants than the passive transfer of 15N measured in the non-mycorrhizal (NM) controls. Noticeably, certain genotypes (e.g., LPA9) showed higher extraradical mycelium biomass production but not necessarily greater 15N acquisition than the others. </p> <p>Experiment 2 (in pots) highlighted that some of the AM fungal genotypes (e.g., MA2, STSI) exhibited higher rates of targeted hyphal exploration of chitin-enriched zones, indicative of distinct N exploration patterns from the other genotypes. Dataset contain photos and other recorded parameters during the experiment 1 and experiment 2.</p>
AProtocol for Managing Orthodontic Complications in Patients with Thalassemia and Haemoglobin Disorder; Article Review
<p>Hemoglobinopathies are known as haemoglobin production disorders. Familial disorders caused by thalassemia or sickle cell anaemia are autosomal recessive disorders affecting haemoglobin production and structure. Objectives:This article review aimed to clarify protocols for managing orthodontic complications in patients with thalassemia and haemoglobin disorder. The article explains how to deal with common dental and orthodontic issues that patients with these conditions may experience.It provides guidance on diagnosing and treating these issues to ensure the best possible outcomes for these patients. Conclusion:Hemoglobinopathies can cause dental diseases, which can be particularly concerning for children with this condition. While specialists are responsible for treating dental diseases, prevention is the best approach. Physicians with adequate knowledge of the diseases can address this issue safely and effectively. Paying attention to this matter is essential to ensure the best possible patient outcomes.</p>
Data Set for the Journal Article "Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks"
<p>This data archive contains all data newly created in the following publication:</p> <p>Charlotte H. Müller, Miguel Steiner, Jan P. Unsleber, Thomas Weymuth, Moritz Bensberg, Katja-<br>Sophia Csizi, Maximilian Mörchen, Paul L. Türtscher, and Markus Reiher, "Heron: Visualizing and<br>Controlling Chemical Reaction Explorations and Networks", in preparation.</p> <p>The directory contents are as follows:</p> <ul> <li>steered_eschenmoser.tar.xz: Dump of the database created during the steered exploration</li> <li>steered_exploration_protocol_chemoton_3.1.json: Protocol used for the steered exploration</li> </ul>
Data & code repository for the article "A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes"
<p>This repository contains the relevant data and code supporting the study "A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes". </p> <p>In detail the following data sources have been included:</p> <ul> <li>the relevant code and supporting data (code_to_upload.zip and supporting_data.zip);</li> <li>supplementary materials of the paper, including: <ul> <li>individual enrichment results of the 93 exposures to the 31 ENMs (enrichments_results.zip);</li> <li>comparison between the mechanism of action retrieved from differentially expressed genes and network modelling (network_comparison_results.zip);</li> <li>overrepresented network edges in categories of networks (overrepresented_structures.zip)</li> </ul> </li> </ul>
Research data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach"
<div><strong>Research Data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em></strong></div> <div> </div> <div>Dear reader,</div> <div> </div> <div>reasearch data are provided for the research article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em> (https://doi.org/10.1016/j.advwatres.2024.104763). The authors hope that the research data allows for a better understanding of the modeling workflow. The research data covers the following files:</div> <div> <ul> <li>Python scripts to create the models <ul> <li>Model scripts using FloPy (Bakker et al., 2016) are stored as .py files in './model_data/flopy_scripts/', named 'model_variant_vXYZ.py', where 'XYZ' is a wildcard for the model number. </li> <li>--> Note that model numbers correspond to the different model variants as referred to in the article, see overview below.</li> <li>The model scripts require postfix files, stored in './model_data/flopy_scripts/postfix/', a PHREEQC database file, stored in './model_data/flopy_scripts/template_database/', as well as spreadsheets that contain the initial concentrations as well as reaction rate parameters needed by PHT3D, stored as .xlsx files in './model_data/flopy_scripts/', to create the models.</li> <li>Note that the .xlsx files are used by PHT3D-FSP in the model scripts to generate relevant PHT3D input files (compare https://doi.org/10.5281/zenodo.7559750 for more details).</li> </ul> </li> <li>SEAWAT/PHT3D input files <ul> <li>Original SEAWAT and PHT3D input files, which were created with the corresponding model scripts previously (see step before).</li> <li>Input files are stored in './model_data/model_files/vXYZ/model_files/' for each model variant, where 'XYZ' is a wildcard for the model number.</li> <li>SEAWAT/PHT3D executables can directly run the model files files. Thus, the files don't need to be re-created via the previous step.</li> </ul> </li> <li>Model outputs <ul> <li>Model output data is stored as NumPy arrays in './model_data/model_files/vXYZ/npy_arrays/', where 'XYZ' is a wildcard for the model number.</li> <li>The script './model_data/flopy_scripts/template_output/pht3d_output_hpc_v006.py' was used to generate the output files.</li> <li>2-D species concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/species/', where 'XYZ' is a wildcard for the model number.</li> <li>Species min./max. concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/min_max/', where 'XYZ' is a wildcard for the model number.</li> <li>2-D water budget arrays (CH & WEL boundaries) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/budgets/', where 'XYZ' is a wildcard for the model number.</li> <li>Model discretization information (ncol, nrow, nlay etc.) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/discretization/', where 'XYZ' is a wildcard for the model number.</li> </ul> </li> <li>Figure files <ul> <li>Original figure files as well as the corresponding Python scripts to create the figures are stored in the subfolder'./figures'.</li> </ul> </li> </ul> <p>Numbering of the model variants is as follows:<br><br>v401 --> VAR-conservative<br>v402 --> VAR-OM<br>v403 --> VAR-C/I<br>v404 --> VAR-C/I/S<br>v405 --> VAR-C/I/P<br>v406 --> VAR-C/I/P/H<br>v407 --> VAR-C/I/P/V<br>v408 --> VAR-C/I/P-Co<br>v409 --> VAR-all<br>v410 --> VAR-all (no C)</p> </div> <div> </div> <div>Literature:</div> <div> </div> <div>Bakker, M., Post, V., Langevin, C.D., Hughes, J.D., White, J.T., Starn, J.J. and Fienen, M.N., 2016. Scripting MODFLOW model development using Python and FloPy. Groundwater, 54(5), pp.733-739. https://doi.org/10.1111/gwat.12413</div> <div> </div> <div>Seibert, S.L., Massmann, G., Meyer, R., Post, V.E.A., Greskowiak, J., 2024. Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2024.104763</div> <div> </div> <div><strong>Contact one of the authors if you have further questions</strong>: Stephan L. Seibert (stephan.seibert@uol.de), Janek Greskowiak (janek.greskowiak@uol.de), Vincent E.A. Post (vincent@edinsi.nl), Rena Meyer (rena.meyer@uol.de) or Gudrun Massmann (gudrun.massmann@uol.de)</div>
Python scripts and datasets used in the article "Investigating the off-axis GRB afterglow scenario for extragalactic fast X-ray transients"
<p>This package includes datasets and python scripts used in the analysis and creation of figures in the A&A paper "Investigating the off-axis GRB afterglow scenario for extragalactic fast X-ray transients" (Wichern et al. 2024).</p>
Dataset for the article: Robotic Feet Modeled After Ungulates Improve Locomotion on Soft Wet Grounds
<div> <div>This repository contains data for three different experiments presented in the paper:</div> <br> <div>(1) moose_feet (40 files): The moose leg experiments are labeled as ax_y.nc,</div> <div>where 'a' indicates attached digits and 'f' indicates free digits. The</div> <div>number 'x' is either 1 (front leg) or 2 (hind leg), and the number 'y'</div> <div>is an increment from 0 to 9 representing the 10 samples of each set.</div> <br> <div>(2) synthetic_feet (120 files): The synthetic feet experiments are labeled</div> <div>as lw_a_y.nc, where 'lw' (Low Water content) can be replaced by 'mw'</div> <div>(Medium Water content) or 'vw' (Vast Water content). The 'a' can be 'o'</div> <div>(Original Go1 foot), 'r' (Rigid extended foot), 'f' (Free digits anisotropic</div> <div>foot), or 'a' (Attached digits). Similar to (1), the last number is an increment from 0 to 9.</div> <br> <div>(3) Go1 (15 files): The locomotion experiments of the quadruped robot on the</div> <div>track are labeled as condition_y.nc, where 'condition' is either 'hard_ground'</div> <div>for experiments on hard ground, 'bioinspired_feet' for the locomotion of the</div> <div>quadruped on mud using bio-inspired anisotropic feet, or 'original_feet' for</div> <div>experiments where the robot used the original Go1 feet. The 'y' is an increment from 0 to 4.</div> <br> <div>The files for moose_feet and synthetic_feet contain timestamp (s), position (m), and force (N) data.</div> <div>The files for Go1 contain timestamp (s), position (rad), velocity (rad/s), torque (Nm) data for all 12 motors, and the distance traveled by the robot (m).</div> <br> <div>All files can be read using xarray datasets (https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html).</div> </div>
Research data related to the article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems"
<p><strong>Research Data related to the article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems" by Seibert et al. (2024) published in <em>Earth's Future</em></strong></p> <p>Dear reader,</p> <p>reasearch data are provided for the research article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems" by Seibert et al. (2024) published in <em>Earth's Future</em>. The authors hope that the research data allows for a better understanding of the modeling workflow. Questions regarding the modeling approach etc. can be directed to the authors, see contact details below.</p> <p>The research data covers the following files:</p> <ul> <li>iMOD-Python (Visser and Bootsma, 2019) scripts to create the iMOD-WQ (Verkaik et al., 2021) input files for the n=566 model variants. Subfolders for each model variant and corresponding files are stored in the subfolder 'model_variants'. An overview regarding the set-up of the model variants is presented in the .xlsx spreadsheet 'model_variants_overview.xlsx' in the folder 'model_variants'.</li> <li>Base data files, used as input files to iMOD-WQ (Verkaik et al., 2021), stored in the subfolder 'imod_input'. However, in most cases no consent for re-distribution of these data sets exists, and they cannot be made freely available through this publication. Please, consider the corresponding meta-data files and/or get in touch with one of the authors for further information.</li> <li>Post-processed model output data, which was further used for model evaluation, stored in the subfolder 'model_output'.</li> <li>Figure files and the corresponding .py scripts, stored in the subfolder 'figures'.</li> </ul> <p>Meta-data files are provided with data files in the different subfolders for clarification.</p> <p>iMOD-WQ (Verkaik et al., 2021) input and .run-files were executed on the University Oldenburg High-Performance Cluster 'Rosa', funded by DFG through its Major Research Instrumentation Program, INST 184/225-1 FUGG, and the Ministry of Science and Culture (MWK) of the Lower Saxony State.</p> <p>Further information on the iMOD suite can be found here: https://deltares.github.io/iMOD-Documentation/</p> <p>The DFG is thanked for SALTSA project funding (DFG project number MA 3274/9-1) within the Priority Programme ‘Regional Sea Level Change and Society (SeaLevel)’. Research related to this article further benefited from funding of the projects WAKOS (BMBF; support code 01LR2003E) and the DFG research unit FOR 5094: The dynamic deep subsurface of high-energy beaches (DynaDeep).</p> <p>Literature:</p> <p>Verkaik, J., Hughes, J. D., van Walsum, P. E. V., Oude Essink, G. H. P., Lin, H. X., & Bierkens, M. F. P. (2021). Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument. Environmental Modelling & Software, 143, p.105092.</p> <p>Visser, M., & Bootsma, H. (2019). iMOD-Python: Work with iMOD MODFLOW models in Python. Retrieved from https://imod.xyz/</p> <p>Seibert, S. L., Greskowiak, J., Oude Essink, G. H. P., & Massmann, G. (2024). Understanding climate change and anthropogenic impacts on the salinization of low‐lying coastal groundwater systems. Earth's Future, 12, e2024EF004737. https://doi.org/10.1029/2024EF004737<br><br><strong>Contact one of the authors if you have further questions</strong>: Stephan L. Seibert (stephan.seibert@uol.de), Janek Greskowiak (janek.greskowiak@uol.de), Gualbert H.P. Oude Essink (Gualbert.OudeEssink@deltares.nl) or Gudrun Massmann (gudrun.massmann@uol.de)</p>
Article dataset: "Inclusion at Ukrainian universities: a view from the inside"
<p>This dataset accompanies the study "Inclusion at Ukrainian universities: a view from the inside," which investigates the state of inclusivity in Ukrainian universities. The study focuses on the perceptions of 820 university staff members from various professional roles, including academic, management, and support positions. It explores inclusivity through multiple lenses, such as work experience, interactions with students with disabilities, and self-identification with vulnerable groups. The research finds a generally positive outlook on inclusive practices, with moderate to high levels of perceived inclusivity. Perceptions vary slightly across different professional roles, but are not statistically significant. Personal experiences with students with disabilities and self-identification with vulnerable groups marginally influence perceptions of inclusivity.</p> <p><strong>Contents of the dataset:</strong></p> <p>1. Research program – a comprehensive outline of the research program detailing the study's objectives, methodology, and the analytical framework applied.</p> <p>2. Survey questionnaire – the instrument employed to gather data from university staff, encompassing questions about their professional roles, experiences, and perceptions of inclusivity.</p> <p>3. Raw responses – the unprocessed data obtained from 820 participants, including their anonymized answers to the survey questions.</p> <p>Note: all data is presented in Ukrainian.</p> <p><strong>Access and citation: </strong></p> <p>A preprint with the results of the study is available at the following link:<a href="https://doi.org/10.21203/rs.3.rs-3973705/v1"> https://doi.org/10.21203/rs.3.rs-3973705/v1</a>.</p> <p><strong>Usage notes:</strong></p> <p>Researchers and practitioners are encouraged to use this dataset to further explore inclusivity in higher education, especially in contexts undergoing significant social and political transformations. Proper attribution should be given when using this dataset in any publication or presentation.</p> <p><strong> </strong></p> <p><strong>For any questions or additional information regarding this dataset, please contact:</strong></p> <p>Dr. Yana Suchikova</p> <p>Vice-Rector for Research</p> <p>Berdyansk State Pedagogical University, Ukraine </p> <p><a href="mailto:yanasuchikova@gmail.com">yanasuchikova@gmail.com</a></p>
Fig. 4. Sinocorophium homoceratum, peduncular article 4 in A new record of the species Sinocorophium dongtanense (Crustacea: Amphipoda: Corophiidae) from Korean waters, with comparison to Sinocorophium homoceratum
Fig. 4. Sinocorophium homoceratum, peduncular article 4 of antenna 2 (MABIK CR00240676) from MABIK, analyzed by Ko et al., 2017. A, dorsal view; B, medial view.
Numerical dataset for the article "Single-photon absorption by single photosynthetic light-harvesting complexes"
<p>The numerical data for all figures presented in the article "Single-photon absorption by single photosynthetic light-harvesting complexes" published in the Journal of Physics B: Atomic, Molecular and Optical Physics (2018). Data include calculation runtimes and hardware specification, and are provided in csv. format.</p>
Data set for Plos One Article "Force sharing and other collaborative strategies in a dyadic force perception task"
<p>Data set for Plos One Article :</p> <p>Tatti, F., Baud-Bovy G. (2018) "Force sharing and other collaborative strategies in a dyadic force perception task". doi: 10.1371/journal.pone.0192754</p> <p>This study investigates how people might interact to extract information from the forces experienced while holding an object together. More specifically, the dyads (i.e. pairs formed two persons) participating to the study had to identify the direction of a small force applied to a jointly held object by a haptic device. This study included a condition where each participant responded independently and another one where the two participants had to agree upon a single negotiated response.</p> <p>The dataset (data.csv) contains the force produced by the haptic device and the average and standard deviation of the interaction force for all trials together with the responses of the participants. We also included the initial and final position of the haptic device and total distance traveled for each trial.</p> <p>The data are in comma separated text format and its description in a PDF document (readme.pdf).</p>
BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 2. Frequency of principal strong indices related to 102 'strong articles'
<p>We ordered the obtained data for the identified strengths and weaknesses. This was done by giving a point for each presence of an index, or not giving it for its absence. Thus, we quantified a total of 63 strengths and 91 weaknesses. In addition to finding a great diversity of views captured in the selected texts, the primary data analysis allowed us to set the parameters with the highest frequency. So, the most important for strengths is flexibility representing 29.7% of the total of studied bibliography and an occurrence frequency of 13.6% from the total of identified strengths (Figure 2). </p>
BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 3.Frequency of principal week indices related to the 101 'week articles'
<p>Reduced social interaction is the most important for weaknesses, representing 9.4% of the total of studied bibliography and an occurrence frequency of 5.5% (Figure3). A significant frequency difference of the weaknesses indices compared to the strengths indices was observed. If the top 5 strengths have frequencies ranging between 13.6% and 7%, none of the weaknesses has an occurrence frequency over 6%, all barely ranging between 5.5% and 3.4%, relative to the middle of strengths frequency range. For the practice of e-learning educational services, this may show either a still insufficient detection or theoretical analysis of weaknesses, or, indeed, the superiority of these services.</p>
BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 5. Frequency of common indices related to 102 'common articles'
<p>An additional and very interesting perspective is provided by the analysis of common indices (ambivalent), based on the 102 works-common articles type, and their frequencies (Figure 5). </p> <p>The data reading indicates 13 ambivalent indices as percentages in descending order: 1. flexibility, 19%; 2. interactivity, 15.4%; 3. cost, 13%; 4. accessibility, 12%; 5. time, 7%; 6. anxiety/reduce social impact, 7%; 7. usability, 6%; 8. connection, 4%; 9. develop skills, 4%; 10. responsibility, 4%; 11. quality, 4%; 12. diversity, 3%; 13. delivery, 1% (Figure 5).</p>
BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 4. Frequency of strong/weak indices related to the 102 'common articles'
<p>Based on the data presented in Figure 2 and Figure 3 and carrying out a comparative and cumulative analysis to identify ambivalent strengths and weaknesses, the 102 ambivalent strong/weak indices related to the 'common articles' in Figure 4 were highlighted. </p> <p>Their analysis shows that: 1. There are at least 13 ambivalent indicators identified in the studied literature (Table 1); 2. The strengths weight is 62% while the weight of weaknesses is 38.9%, resulting in a pretty big difference in favor of underlining and supporting the strengths, 23.1% more than in favor of weaknesses. These data indicate a significantly higher perception and approach in favor of appreciating the strengths of e-learning educational services, even in the case of their ambivalence. 3. In this context, the data illustrate the following three cases: 3.1. a huge gap between the perception and the interpretation of an index as strength and as weakness (e.g., flexibility is regarded 7.5 times more a strength rather than a weakness). It can be seen that this category of indices definitely belongs to strengths, acknowledged and validated by a large number of studies. In relation to these, efforts will be made for the development, improvement, elevation and obtaining superior parameters. 3.2. a relative correspondence between the perception and the interpretation of an index as strength and as weakness (e.g., the time required to design and implement educational services is considered a strength at a rate of 3.2% and a weakness at a rate of 3.3%). It results that this category of indices has to be studied thoroughly and watched in experimental studies, to replace the uncertainty area in their analysis, to determine which their area of predominance is, to what extent their identified limits and shortcomings have been reduced to allow their conversion into strengths or not; 3.3. a very large gap between the perception and interpretation of an index as a weakness and as a strength (e.g., lack of instructional delivery is considered as being a weakness 20 times more than a strength).This shows that this category of indices comes into focus as weaknesses which need to be analyzed, studied and experimented in order to reduce their negative impact. </p>
Supplemental material to the article "Improving silent reading performance through feedback on eye movements: A feasibility study"
<p>This repository accompanies the article:</p> <p>Korinth, S., & Fiebach, C.J. (2018). Improving silent reading performance through feedback on eye movements: A feasibility study. Scientific Studies of Reading.</p> <p>For a more convenient download files were zipped. Organized into four subfolders it provides the data and the R-scripts allowing the replication of all analyses and the manuscript's figures. For further information please refer to the README.txt files in the individual subfolders.</p> <p>Please note, a former version of this repository contained the same data and the same analyses and was used for manuscript review purposes. Changes to the current version concern only the manuscript structure (i.e., analyses presented in previous manuscript version as appendices were integrated into the main text). </p>
Numbers of Articles, Books and Dissertation theses indexed in BASE and percentages of items published Open Access, under Creative Commons Licenses and under Open Licenses (2013-2017)
<p>A look at the data provided by the Open Access search engine BASE (http://base-search.net) shows that the Open Science compliance among dissertation theses stagnates. BASE knows three categories of accessibility: Open Access, Unknown, Non-Open Access. In the following tables and graphs, figures reported as "Open Access" have been categorised by BASE as Open Access. The tables and graphics show data from BASE (as of 06.03.2018) as follows:</p> <p>a) Indexed theses, books and journal articles</p> <p>b) Indexed theses, books and journal articles published by Open Access</p> <p>c) indexed theses, books and journal articles under Creative Commons licenses.</p> <p>d) indexed theses, books and journal articles, which are published under open licenses in the sense of the Open License, i. e. reflect terms of use of the Open Source.</p> <p> </p> <p>Although doctoral theses already had a high share of open access by 2013 (43%), by 2017 it had risen by only 5% (2017:48%). At the same time, the proportion of books published in open access rose by 14% (from 20% to 34%) and articles by 17% from 44% (2013) to 61% (2017). The same effect can be seen in the proportion of CC-licensed items: Their share rose by 4% (from 9% to 13%) for doctoral theses, by 9% for books (from 4% to 13%) and 8% for articles (from 10% to 18%) between 2013 and 2017. However, the share of openly licensed items is most pronounced: it did not increase for doctoral theses, but remained at 2% between 2013 and 2017; in the same period it increased by 5% (from 1% to 6%) for books, and by 5% (from 5% to 10%) for articles.</p>
Y-chromosome and mitochondrial data for the article entitled: "The First Horse Herders and the Impact of Early Bronze Age Steppe Expansions into Asia"
<p>Y-chromosome and mitochondrial data for the article entitled: "The First Horse Herders and the Impact of Early Bronze Age Steppe Expansions into Asia"</p>
E-participation adoption quantitative articles
<p>The data-set contains a list of articles that studied e-participation adoption from the quantitative perspective from year 2000 onwards. The list provide a set of data that includes these fields: year of publication, source, theory, independent Variable name, dependent variable name, beta values, Significant/Not Significant, R square, method, keywords, type of study, findings from Abstract / Conclusion, ICT platform, sample population, kind of population, country of study. Based on this data-set, this article was published: "E-participation adoption models research in the last 17 years: A weight and meta-analytical review"</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.