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12,393 results for “materiality”
Supporting Material for article "The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences"
<p>This data set is the Supporting Material referred to in the Supplementary Data for the article "The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences" (Drysdale, et al.) submitted for publication in April 2019.</p> <p> </p>
Combining statistical and mechanistic models to unravel the drivers of mortality within a rear-edge beech population - Supporting Material
<p>Supporting material for the study:</p> <p><strong>"Combining statistical and mechanistic models to unravel the drivers of mortality within a rear-edge beech population."</strong></p> <p><strong>Authors:</strong></p> <p>Cathleen Petit-Cailleux1, Hendrik Davi1, François Lefèvre1, Joseph Garrigue<strong>2</strong>, Jean-André Magdalou<strong>2</strong>, Christophe Hurson<strong>2,3</strong><strong>, </strong>Elodie Magnanou<strong>2,4</strong>, and Sylvie Oddou-Muratorio1.</p> <p> </p> <p>Adresses</p> <p>1INRA, UR 629 Ecologie des Forêts Méditerranéennes, URFM, Avignon, France</p> <p><strong>2</strong>Réserve Naturelle Nationale de la Forêt de la Massane, France</p> <p><strong>3</strong>Fédération des Réserves Naturelles Catalanes, Prades, France</p> <p><strong>4</strong>Sorbonne Université, CNRS, Biologie Intégrative des Organismes Marins, BIOM, F-66650 Banyuls-sur-Mer, France</p> <p><strong>ORCID:</strong></p> <p>Cathleen Petit-Cailleux: <a href="https://orcid.org/0000-0001-7714-6583">https://orcid.org/0000-0001-7714-6583</a></p> <p>François Lefèvre : <a href="https://orcid.org/0000-0003-2242-7251">https://orcid.org/0000-0003-2242-7251</a></p> <p>Sylvie Oddou-Muratorio <a href="https://orcid.org/0000-0003-2374-8313">https://orcid.org/0000-0003-2374-8313</a></p> <p> </p> <p>-------------</p> <p>Raw data of the Table_Massane_moratlity_trees.csv and climate can be obtained from Joseph Garrigue, Jean-André Magdalou and Christophe Hurson.</p> <p>The inventories files and daily climate are the input dataset to run CASTANEA models.</p> <p>All details are provided in the article.</p>
Supplementary material: Efficient in vivo screening method for the identification of C4 photosynthesis inhibitors based on cell suspensions of the single-cell C4 plant Bienertia sinuspersici
<p>Data described in Minges et al. (2019) Efficient <em>in vivo</em> screening method for the identification of C<sub>4</sub> photosynthesis inhibitors based on cell suspensions of the single-cell C<sub>4</sub> plant <em>Bienertia sinuspersici</em>. doi: <a href="https://doi.org/10.3389/fpls.2019.01350">10.3389/fpls.2019.01350</a></p> <p> </p>
Alternative plasmonic materials for fluorescence enhancement
<p>Dielectric functions for metals and semiconductors, as taken from the literature. We used these datasets for studying plasmonic fluorescence enhancement resulting from the coupling of a molecule with a spherical nanoparticle, out of each one of these materials. We have gathered them all in this repository so they will be easily accesible. </p>
Cretaceous-scope supplementary material to "The Cretaceous World: Plate Tectonics, Paleogeography, and Paleoclimate"
<p>Cretaceous Supplemental Materials for the study ‘<em>The Cretaceous World: Plate Tectonics, Paleogeography and Paleoclimate</em>’ by C.R. Scotese C. Vérard, L. Burgener, R. P. Elling and A.T. Kocsis (<a href="https://doi.org/10.1144/sp544-2024-28">https://doi.org/10.1144/sp544-2024-28</a>). Please cite this article if you use any material here in your publication.</p> <p>Please see the included '<em>Cretaceous Supplemental Materials Explanation.docx</em>' document for description of supplementary items and table of contents. </p>
Phanerozoic-scope supplementary material to "The Cretaceous World: Plate Tectonics, Paleogeography, and Paleoclimate" from the PALEOMAP project
<p>Phanerozoic Supplemental Materials for the study ‘<em>The Cretaceous World: Plate Tectonics, Paleogeography and Paleoclimate</em>’ by C.R. Scotese C. Vérard, L. Burgener, R. P. Elling and A.T. Kocsis (<a href="https://doi.org/10.1144/sp544-2024-28">https://doi.org/10.1144/sp544-2024-28</a>). Please cite this article if you use any material here in your publication.</p> <p>Please see the included '<em>Phanerozoic Supplemental Materials Explanation.docx</em>' document for description of supplementary items and table of contents. </p>
Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research (Supplementary Material: Full Paper Listing and Analysis)
<p>Supplementary material of the paper:</p> <p>Title: "Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research"<br>Subtitle: "A Survey of the IPIN's Reference Papers of 2022 and 2023 Editions"</p> <p>The paper is accepted to the "14th International Conference on Indoor Positioning and Indoor Navigation, IPIN 2024, Hong Kong, October 14-17, 2024, IEEE, 2024.</p> <p>An Author's accepted version of the manuscript is available here: <a href="../records/13684170" target="_blank" rel="noopener">https://zenodo.org/records/13684170</a> </p> <p>If you want to refer to this work, please cite this Zenodo entry as well as the published conference version.</p> <p> </p> <p>---------------------------------------</p> <p>This entry contains two files:</p> <ul> <li>"Paper Characterization Spreadsheet.xlsx": <strong>The spreadsheet of the full analysis of this work</strong>, as described in the paper. It characterizes various features of the analyzed papers and forms the raw data on which the analyses of our work were based.</li> <li>"Main features of the manuscripts analysed in Zenodo Record #12088175.pdf": A document summarizing the main features of the IPIN's Reference Papers of the 2022 and 2023 Editions, that contain some form of open resources (Open Data, Code, or Material).</li> </ul> <p> </p> <p> </p> <p> </p>
Repository of NbS guidance material
<p><strong>NbS Guidance Repository </strong></p> <p>The NbS Guidance Repository is a collection of guides, handbooks, manuals, toolboxes, and other guidance materials. These resources are specifically designed to facilitate knowledge brokering and capacity-building on Nature-based Solutions (NbS) for a diverse group of non-academic actors. The guidance materials contain information on specific actions supporting the governance, planning, implementation, management, and monitoring of NbS or related concepts that work with nature, such as Green Infrastructure, Urban Forestry, and Ecosystem-based Adaptation. Additionally, they address challenges related to planning and implementing NbS, including issues with climate change adaptation, biodiversity enhancement, and environmental justice.</p> <p>The repository is established as part of the European Union Horizon 2020 project, CONEXUS, to catalogue the current status of guidance materials. Many European-funded research and innovation projects similarly transferred their gained knowledge and perspectives on NbS through guidance materials. Different platforms, like OPPLA, bring these materials together, yet the focus is Europe-centric. However, as several projects have involved cases outside Europe, such as CONEXUS’ cooperation with Latin American cities, this repository specifically included guidance materials from or relevant to Latin America. Thus, the collected guidance material focuses on urban contexts in Latin America and Europe, but materials with a global emphasis are also included. The materials are available in digital format, as PDFs (portable digital documents) or websites, to ensure easy accessibility.</p> <p>The guidance materials were collected from different avenues, such as published literature like the review of European NbS projects by <a href="https://research-and-innovation.ec.europa.eu/knowledge-publications-tools-and-data/publications/all-publications/nature-based-solutions-state-art-eu-funded-projects_en" target="_blank" rel="noopener">Wild et al. (2020)</a> and resource databases like NetworkNature. To supplement the collected guidance materials with more examples relevant to Latin America, CONEXUS partners and practitioners from the region who were engaged were asked to mention the NbS guidance materials they know about. Additional materials were collected through an internet search using the Google search engine in Spanish and Portuguese and through snowballing. As the focus is on materials targeted at non-academic users, scientific databases were not consulted.</p>
Residential gasification of solid biomass: Influence of raw material on emissions
<p><strong>Submitted data was used to write an article: </strong>Drobniak, A., Jelonek, Z., Mastalerz, M., Jelonek, I., 2023. Residential gasification of solid biomass: Influence of raw material on emissions. International Journal of Coal Geology 271C, 104247. <a href="https://doi.org/10.1016/j.coal.2023.104247">https://doi.org/10.1016/j.coal.2023.104247</a></p> <p> </p> <p><strong>Funding acknowledgments: </strong>The project is co-financed by the Polish National Agency for Academic Exchange within the Polish Returns Programme (BPN/PPO/2021/1/00005/DEC/1), the National Science Center, Poland (2022/01/1/ST10/00024), funds granted under the Research Excellence Initiative of the<br>University of Silesia in Katowice, Poland and the Green Horizon Program, Poland.</p> <p> </p> <p><strong>Article Abstract: </strong>With interest rising in biomass use, biomass gasification has the potential to become an imperative mechanism to deliver clean conversion of various types of solid biomass to gas. But as biomass gasification attracts growing interest, it is important to focus not only on the technological feasibility but also fully understand its environmental impact to eliminate avoidable air pollution. In this study, we investigated relationships between the composition of 14 types of solid biomass fuels and their gasification emissions in a small-scale residential outdoor setting. Our results show that the amount and type of produced emissions are strongly influenced by the gasified feed. Combining chemical and petrographic analysis proved to be a robust quality assessment method of solid biomass fuels, allowing for quick detection of their contaminants. These impurities can be directly correlated with elevated particulate matter emissions, CO, H2S, HCHO, NH3, SO2, NOx, and respiratory tract irritants. These observations show that quality testing of biomass fuels is critical not only for ensuring their high quality but also for predicting avoidable air pollution during their utilization. Although our data revealed relationships between the type of biomass fuel and gasification emissions, in general, our experiments show that small-scale gasification in a residential setting is a safe technology, and potential hazards can be eliminated by using certified fuels and ensuring appropriate distance from the source of emissions.</p>
Supplementary Material: Knobs and dials of retrieving JWST transmission spectra. I. The importance of p-T profile complexity
<p>This is supplementary material to <a title="Schleich et al. (2024)" href="https://www.aanda.org/articles/aa/abs/2024/10/aa51845-24/aa51845-24.html" target="_blank" rel="noopener">Schleich et al. (2024)</a>. The content of the provided data repository (also described in the file "content.txt") is as follows:</p> <p> </p> <h2>ADDITIONAL ANALYSIS</h2> <p>This folder contains a collection of ancillary data products for the evaluation of the retrievals performed in this work.</p> <ul> <li>'bayes-factor' contains the data tables for evaluating the Bayes' factor for each separate collection of models(*)</li> <li>'corner-plots' contains a collection of all corner plots associated with the individual input cases</li> <li>'fit-residuals' contains all fit residuals for the individual atmospheric retrievals performed in this work (used to make Fig. C.1)</li> <li>'resampled-pt-profiles' contains resampled p-T profiles to generate Figs. 6 and F.1</li> <li>'retrieval-accuracy' contains additional plots related to the accuracy of each retrieval (used to make Fig. 5, as well as Figs. E.1 - E.5)</li> </ul> <p><br>(*) SIDE NOTE:<br>Table headers in the "bayes-factor" data tables reference evidence reported from MultiNest (variable "Z"), and calculated Bayes factor (variable R). The case with log(R) = 0 is necessarily the reference case, and outliers are marked in a binary table with 1 (|log(R)| > 5) or 0 (|log(R)| < 5). In all cases, "log" refers to the natural logarithm.</p> <ul> <li>If someone actually reads this, I'm sorry. I also spent way too much time trying to track down if the values reported in MultiNest are natural or base-10 logarithm. I have now been convinced that it is worth it, always, to either specify "ln" for the base-e logarithm, or give the base of your logarithm if your write it down (i.e. log_10(X)) -Simon.</li> </ul> <h1> </h1> <h2>RETRIEVAL RESULTS</h2> <p>This folder contains the data products associated with the retrieval runs for each synthetic spectrum. The sub-directories are aranged by the following keys:</p> <ul> <li>'drs' and 'pandexo' refere to the two noise cases considered</li> <li>'inv-t' and 'norm-t' refere to the two underlying p-T profiles used to make the synthetic spectra</li> <li>'hpc', 'mpc', and 'lpc' refere two the three cloud-top pressure cases considerd</li> </ul> <p>Each individual folder contains (1) the TauREx parameter files for running retrievals using the selection of p-T profiles, (2) a folder called 'results', which containts the associated data products, and (3) a folder called 'chains', which stores the ancillary data products associated with the MultiNest sampling runs of each retrieval.</p> <p> We note that for the "drs_inv-t_mpc" case, the chains for the isothermal, 2-point, and 4-point runs have been lost</p> <p> </p> <h2>SYNTHETIC SPECTRA</h2> <p>This folder contains data products associated with the sample of synthetic transmission spectra.</p> <ul> <li>'pt-profile_*.csv' are csv-files containing the p-T points used to make Figure 1 , and to generate the synthetic transmissions spectra</li> <li>'forward-models' contains TauREx parameter files and forward models for the sample of synthetic transmission spectra. Each of the sub-directories also contains a faux-spectrum representing the wavelength-map of NIRSpec PRISM <ul> <li>'no-clouds' contains contains the above for generating Figure 3.</li> <li>'inv-t' contains forward models using the "inverse" p-T profile</li> <li>'norm-t' contains forwrad models using the "monotonic" p-T profile</li> </ul> </li> </ul>
Comprehensive Evaluation of Alternative API, Excipient, and Packaging Material Sources: A Regulatory Perspective
<p>Incorporating alternative sources for Active Pharmaceutical Ingredients (API), excipients, and primary packaging materials in approved pharmaceutical products necessitates rigorous evaluation to ensure product quality, safety, and efficacy are maintained. Regulatory agencies, including the World Health Organization (WHO), the United States Food and Drug Administration (US FDA), the European Medicines Agency (EMA), and the UK Medicines and Healthcare products Regulatory Agency (UK MHRA), require comprehensive data to assess such changes. This abstract summarizes the key data requirements across these agencies, focusing on API, excipients, and primary packaging materials.</p> <p>For APIs, critical data include comparative analytical testing, impurity profiling, stability studies under ICH conditions, and bioequivalence studies when applicable. Agencies mandate risk assessments and process validation to ensure the new API source does not compromise the product's critical quality attributes (CQAs) or therapeutic performance.</p> <p>For excipients, regulatory bodies require detailed information on the new supplier’s compliance with Good Manufacturing Practices (GMP), certificate of analysis (CoA), and comparative studies to demonstrate equivalence in performance, stability, and compatibility with the drug product. Stability testing, extractables and leachables analysis, and risk assessment play crucial roles in ensuring the excipient change does not negatively impact product quality or patient safety.</p> <p>Primary packaging material changes require a thorough evaluation of mechanical and barrier properties, container-closure integrity (CCI), and extractables and leachables studies. Stability testing with the new packaging material under ICH conditions, risk assessments, and functional equivalence testing are essential to confirm the packaging material’s suitability in protecting the drug product throughout its shelf life.</p> <p>In conclusion, stringent regulatory expectations underscore the importance of comprehensive data generation and risk mitigation strategies when incorporating alternative sources for APIs, excipients, and packaging materials in pharmaceutical products. Adherence to these guidelines ensures product safety, efficacy, and compliance with global regulatory standards.</p>
Infrared Video of Bone Drilling - Supplementary material for article "Thermal Evaluation of Bone Drilling: Assessing Drill Bits and Sequential Drilling"
<p>Video 1 shows sequential bone drilling with 5 drill bits (⌀2.0 mm, ⌀2.5 mm, ⌀3.2 mm, ⌀3.7 mm, and ⌀4.1 mm) used in series following the manufacturer's recommended spindle speeds.</p> <p>Video 2 shows bone drilling with a single drill bit (⌀2.0 mm) with a spindle speed of 1500 rpm.</p> <p>These videos are supplementary to the article, "Thermal Evaluation of Bone Drilling: Assessing Drill Bits and Sequential Drilling" published in the journal <em>Bioengineering. </em></p>
Supplementary material for journal article "Challenge dose titration in a Mycobacterium bovis infection model in goats"
<p>Supplementary Figure and Table to Journal article. Figure shows daily rectal temperature of each animal after inoculation. Table 1 shows number and volume of pulmonary lesions for each animal as detected by computed tomography imaging. Table 2 gives details about scoring used at clinical examination.</p>
Data on the material characterization of cast and additively manufactured IN939 subjected to room-temperature low-cycle fatigue load
<p>The original data to the research paper termed "Room-temperature low-cycle fatigue behaviour of cast and additively manufactured IN939 superalloy" are enclosed. Two specimen orientations of L-PBF IN939 - horizontal and vertical, and two thermodynamical states - without subsequent heat treatment (non-treated) and standard aged according to Delargy et al., 1986, were investigated. The paper concerns the low-cycle fatigue performance of cast and additively manufactured IN939 superalloy. It brings a comprehensive account on the damage and deformation behaviour of the tested alloy, combining the test analyses with high-resolution SEM and TEM observations.</p>
Supplementary material (part 2): "Evaluation of AROME Model Valley Wind Simulations in the Inn Valley, Austria"
<p><em>Part 2</em> of supplementary material for the Master's Thesis: "Evaluation of AROME Model Valley Wind Simulations in the Inn Valley, Austria" (Wibmer 2024, available <a href="https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-151801">here</a>).</p> <p>Due to memory constraints, the supplementary material consists of two parts:</p> <ul> <li><em><strong>Part 1: </strong></em>(available <a href="https://doi.org/10.5281/zenodo.10849397" target="_blank" rel="noopener">here</a>) Includes Python scripts and model setup files, along with the first part of the datasets, including ERA-reanalysis data, observational data, and the preprocessed AROME model output (NetCDF files) of the <em>0.5-km</em> simulation.</li> <li><em><strong>Part 2: </strong></em>Includes the preprocessed AROME model output (NetCDF files) of the <em>1.0-km </em>and <em>2.5-km</em> simulations (see description below).</li> </ul> <p>To reproduce part of the figures, users must download the Python scripts and the preprocessed AROME model datasets (NetCDF files). <br>The Python scripts should be placed in the same parent folder because some of them depend on each other <strong>(!! Important !!).</strong><br>Original AROME model output files (GRIB2 format) are not published due to their large size.</p> <p>The naming convention for the AROME simulations uses OP* (where * represents the grid spacing in meters) to differentiate the model runs based on their horizontal<br>grid spacing:</p> <ul> <li><strong><em>OP2500:</em></strong> for 2.5 km</li> <li><em><strong>OP1000: </strong></em>for 1.0 km</li> <li><em><strong>OP500:</strong></em> for 0.5 km</li> </ul> <h3><strong>Datasets Part 2</strong></h3> <p>Due to memory constraints, the datasets needed for the analyses are split up into two parts. The second part of the supplementary material contains:</p> <ul> <li><strong>datasets_OP1000.tar.xz</strong>: Contains the preprocessed AROME-Aut model output data (NetCDF files) of the <em>1.0-km</em> simulation. </li> <li><strong>datasets_OP2500.tar.xz</strong>: Contains the preprocessed AROME-Aut model output data (NetCDF files) of the <em>2.5-km</em> simulation. </li> </ul> <p>The datasets of the<em> 0.5-km</em> simulation (<strong>datasets_OP500.tar.xz</strong>)<strong> </strong>can be found in Part 1 of the supplementary material (available <a href="https://doi.org/10.5281/zenodo.10849397" target="_blank" rel="noopener">here</a>).<br>The NetCDF datasets of the performed AROME-Aut simulations are packaged and compressed into <code><em><strong>.tar.xz</strong></em></code> files.<br>The Python scripts, available <a href="https://doi.org/10.5281/zenodo.10849397" target="_blank" rel="noopener">here</a>, require these NetCDF datasets for plotting and analyses routines.<br>The provided NetCDF datasets are preprocessed from the <em>GRIB2</em> output of the AROME-Aut simulations. <br>For the scripts to function properly, you need to adjust the path to the datasets within <code><strong>path_handling.py</strong></code><strong>.</strong></p> <p>Each <strong><code>datasets_OP*.tar.xz</code></strong> file contains NetCDF files for different type of levels: <em>surface, hybridPressure </em>(model levels)<em>, isobaricInhPa </em>(pressure levels),<em> meanSea </em>(mean sea level)<em>, heightAboveGround </em>(constant height levels)<em>. </em> The following naming convention for the datasets is used:</p> <ul> <li><strong>ds_OP*_<em>var</em>_hybridPressure_<em>[lon1, lon2, lat1, lat2]</em>.nc</strong>: Contains data on <em>hybrid pressure model levels</em> for a specific variable (<em>var</em>; e.g., <em>u, v, z, pres, q, t</em>) for the geographical extent defined in the brackets. </li> <li><strong>ds_OP*_interp_hybridPressure_<em>(lon,lat)</em>.nc</strong>: Combined dataset on <em>hybrid pressure model levels.</em> The data is bilinearly interpolated to the specified location <em>(lon, lat)</em>.</li> <li><strong>ds_OP*_<em>var</em>_surface_<em>whole</em>.nc</strong>: Contains data on <em>model surface </em>for a specified variable (<em>var</em>; e.g., <em>z, sp, t, tcc</em>) for the <em>whole </em>available domain extent.</li> <li><strong>ds_OP*_heightAboveGround_instant_<em>whole</em>.nc</strong>: Combined dataset on <em>height levels </em>(e.g., <em>2-m and 10-m</em>) for the <em>whole </em>available domain extent.</li> <li><strong>ds_OP*_<em>var</em>_meanSea_<em>whole</em>.nc</strong>: Contains data on <em>mean sea level</em> for specified variable (<em>var;</em> e.g., <em>prmsl</em>) for the <em>whole</em> available domain extent. </li> </ul> <p>The original GRIB2 files are not provided due to their large size. For further information about the GRIB2 files or the NetCDF datasets, please feel free to contact me.</p>
Supplementary Material for "A comparative high-resolution spectroscopic analysis of in situ and accreted globular clusters"
<p>This is a file containing supplementary material for the paper <em>A comparative high-resolution spectroscopic analysis of in situ and accreted globular clusters.</em> For each star in target globular clusters, it lists crucial information on the linelist analyzed. In particular:</p> <ol> <li>Star ID.</li> <li>Chemical element.</li> <li>Wavelength.</li> <li>log <em>gf</em></li> <li>Excitation potential.</li> <li>Measured equivalent width with uncertaintiy.</li> </ol>
The language of sound search: Examining User Queries in Audio Search Engines (supplementary materials)
<h2>Overview</h2> <p>This dataset accompanies the <a href="https://dcase.community/documents/workshop2024/proceedings/DCASE2024Workshop_Weck_54.pdf" target="_blank" rel="noopener">paper</a> titled <strong>"The Language of Sound Search: Examining User Queries in Audio Search Engines."</strong> The study investigates user-generated textual queries within the context of sound search engines, which are commonly used for applications such as foley, sound effects, and general audio retrieval.</p> <p>The paper addresses the gap in current research regarding the real-world needs and behaviors of users when designing text-based audio retrieval systems. By analyzing search queries collected from two sources — a custom survey and Freesound query logs — the study provides insights into user behavior in sound search contexts. Our findings reveal that users tend to formulate longer and more detailed queries when not constrained by existing systems, and that both survey and <a href="https://freesound.org/">Freesound</a> queries are predominantly keyword-based.</p> <p>This dataset contains the raw data collected from the survey and annotations of Freesound query logs.</p> <h2>Files in This Dataset</h2> <p>The dataset includes the following files:</p> <ol> <li> <p><strong><code>participants.csv</code></strong><br>Contains data from the survey participants. Columns:</p> <ul> <li><code>id</code>: A unique identifier for each participant.</li> <li><code>fluency</code>: Self-reported English language proficiency.</li> <li><code>experience</code>: Whether the participant has used online sound libraries before.</li> <li><code>passed_instructions</code>: Boolean value indicating whether the participant advanced past the instructions page in the survey.</li> </ul> </li> <li> <p><strong><code>annotations.csv</code></strong><br>Contains annotations of the survey responses, detailing the participants' interaction with the sound search tasks. Columns:</p> <ul> <li><code>id</code>: A unique identifier for each annotation.</li> <li><code>participant_id</code>: Links to the participant’s ID in <code>participants.csv</code>.</li> <li><code>stimulus_id</code>: Identifier for the stimulus presented to the participant (audio, image, or text description).</li> <li><code>stimulus_type</code>: The type of stimulus (audio, image, text).</li> <li><code>audio_result_id</code>: Identifier for the hypothetical audio result presented during the search task.</li> <li><code>query1</code>: Initial search query submitted based on the stimulus.</li> <li><code>query2</code>: Refined search query after seeing the hypothetical search result.</li> <li><code>aspects1</code>: Aspects considered important when formulating the initial query.</li> <li><code>aspects2</code>: Aspects considered important when refining the query.</li> <li><code>result_relevance</code>: Participant's rating of the hypothetical search result's relevance.</li> <li><code>time</code>: Time taken to complete the search task.</li> </ul> </li> <li> <p><strong><code>freesound_queries_annotated.csv</code></strong><br>Contains annotated Freesound search queries. Columns:</p> <ul> <li><code>query</code>: Text of the search query submitted to Freesound.</li> <li><code>count</code>: The number of times the specific query was submitted.</li> <li><code>topic</code>: Annotated topic of the query, based on an ontology derived from AudioSet, with an additional category, <code>Other</code>, which includes non-English queries and NSFW-related content.</li> </ul> </li> <li> <p><strong><code>survey_stimuli_data.zip</code></strong><br>This ZIP file contains three CSV files corresponding to the three stimulus types used in the survey:</p> <ul> <li><strong>Audio stimuli</strong>: Categorized sound recordings presented to participants.</li> <li><strong>Image stimuli</strong>: Annotated images that prompted sound-related queries.</li> <li><strong>Text stimuli</strong>: Summarized descriptions of sounds provided to participants.</li> </ul> </li> </ol> <p>More details on the stimuli and the survey methodology can be found in the accompanying paper.</p> <h2><strong>Citation</strong></h2> <p>If you use this dataset in your research, please cite the corresponding paper:</p> <div> <pre>B. Weck and F. Font, ‘The Language of Sound Search: Examining User Queries in Audio Search Engines’, in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2024 Workshop (DCASE2024), Tokyo, Japan, Oct. 2024, pp. 181–185.</pre> <pre><code>@inproceedings{Weck2024, author = "Weck, Benno and Font, Frederic", title = "The Language of Sound Search: Examining User Queries in Audio Search Engines", booktitle = "Proceedings of the Detection and Classification of Acoustic Scenes and Events 2024 Workshop (DCASE2024)", address = "Tokyo, Japan", month = "October", year = "2024", pages = "181--185" }</code></pre> </div>
Protein adsorption on biodegradable mikro/nanofibre materials for tissue engineering
<p><span>Due to their specific properties, nanofibrous materials are increasingly used in regenerative medicine and tissue engineering. Nanofibrous materials can be used as tissue scaffolds for injured (damaged) tissue. The main factor for tissue scaffolds is their biocompatibility. One of the main factors influencing the organism's physiological response is the interaction of the material with proteins. Proteins adsorbed on the material's surface give the tissue scaffolds a "biological identity"</span><span><span>. Cells in the organism subsequently interact with proteins adsorbed on the material's surface and determine the entire organism's response to the implanted material. This work deals with the influence of the morphology and chemical composition of polyester nanofibrous materials on the adsorption of proteins. The materials produced by electrospinning (DC spinning) were characterised from the point of view of morphology and wettability. Then, the adsorption of weakly and strongly bound proteins on the fibre surface was evaluated. Cell adhesion and proliferation on the tested materials were also observed. The results of protein adsorption were compared with the results of cell adhesion and proliferation to determine the effect of the amount of adsorbed proteins on the interaction of cells with the tested materials.</span></span></p>
Supplementary Materials associated with paper 'Complete linear mitochondrial genomes for Cephea cephea and Mastigias albipunctata (Scyphozoa: Rhizostomeae), with an analysis of phylogenetic relationships'
<p>This is a repository for coverage depth graphs and ML-phylogenetic trees that are associated with the paper 'Complete linear mitochondrial genomes for Cephea cephea and Mastigias albipunctata (Scyphozoa: Rhizostomeae), with an analysis of phylogenetic relationships' by Tan KC, Collins AG and Ames CL.</p>
Supplementary data to Challenges and Opportunities for the Recovery of Critical Raw Materials from Electronic Waste
<p>Content of the excell file:</p> <p>Table S1: Relationship between UNU-keys and MINCOTUR codes</p> <p>Table S2: UNU-Key composition and alpha and beta values for Weibull distributions</p> <p>Table S3: Metal prices used in this study.</p>
ScienceDex guides
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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.