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8,537 results for “Openness”
Data for "Open Access impact on citations: a case study"
<p>This dataset is a list of 347 papers published in 2010 and retrieved from the Web of Science, Scopus and Google Scholar. For each paper, the number of citations and the citation date(s) have been collected. If the full-text is available online, the date of "liberation" and the URL of the file have been retrieved as well. The objective was to assess the impact of Open access on citation rate and more particularly the impact before and after full-text "liberation".</p> <p> </p>
PIR data and EEG scoring for Wellcome Open Research methods paper (Brown et al 2016)
<p>PIR data and EEG-scored sleep in the Wellcome Open Research article:</p> <p>'COMPASS: Continuous Open Mouse Phenotyping of Activity and Sleep Status'</p> <p> </p> <p>1sensorPIRvsEEGdata.csv - PIR based actigraphy for mice to compare to EEG-scored sleep</p> <p>EEG_4mice10sec.csv - Manually scored sleep from EEG files (.edf) from 10.5281/zenodo.160118</p> <p>blandAltLandD.csv - paired estimates of sleep by PIR and EEG methods (sum of 4 mice over 1 day in 30min bins)</p> <p><br> 1monthPIRsleep.csv - 1 month of activity for for figure 4</p> <p><br> 24mice_activity_LD1week.csv - activity and sleep for 24 wt mice (for hierarchical clustering in figure 4)<br> 24mice_sleep_LD1week.csv </p> <p> </p> <p> </p>
JDC2015 (ERRATUM 2) - A multimodal dataset from facilitating multi-tabletop lessons in an open-doors day
<p>This dataset is a complement (a correction, actually) to the "JDC2015 - A multimodal dataset from facilitating multi-tabletop lessons in an open-doors day" dataset, also published in Zenodo (see https://zenodo.org/record/198709 for further info on the dataset). This erratum contains a zip file that substitutes the (incomplete) JDC2015-CodingData.zip file in the original dataset.</p>
JDC2015 (ERRATUM) - A multimodal dataset from facilitating multi-tabletop lessons in an open-doors day
<p>This dataset is a complement (a correction, actually) to the "JDC2015 - A multimodal dataset from facilitating multi-tabletop lessons in an open-doors day" dataset, also published in Zenodo (see https://zenodo.org/record/198709 for further info on the dataset). This erratum contains a zip file that substitutes the (corrupt) JDC2015-EyetrackingData.zip file in the original dataset.</p>
Overcoming the Dichotomy: New Insights into the Genomic Diversity of Open and Isolated European Populations
<p>The dataset includes autosomal data of 227 individuals of 9 Italian populations (Aosta, Benetutti, Carloforte, Lessinia Cimbrians, North Sardinia, Sappada, Sauris, Sulcis Iglesiente and Timau) genotyper with the GenoChip 2.0.</p>
Supplementary material 1: Animation of BrainBox's workflow from: Open Neuroimaging Laboratory - Research Ideas and Outcomes 2: e9113 (08 May 2016) https://doi.org/10.3897/rio.2.e9113
Animation showing the different functionalities of BrainBox: opening a Magnetic Resonance Imaging volume, viewing it, and editing it collaboratively online.
Supplementary material 2: BrainBox Cartoon from: Open Neuroimaging Laboratory - Research Ideas and Outcomes 2: e9113 (08 May 2016) https://doi.org/10.3897/rio.2.e9113
Cartoon showing the idea of distributed collaboration on Magnetic Resonance Imaging data.
The organophosphate pesticide methamidophos opens the blood-testis barrier and covalently binds to ZO-2 in mice
<p>We studied biological effects and post-translational modifications of proteins after treating mice with the pesticide methamidophos.</p> <p>This data set provides evidence for the modification of ZO-2, indicating that the blood-testis barrier in mouse was crossed.</p>
Convergence plot Crack Release Energy for Mode-I opening
<p>Convergence plot for the mode-I opening of the infinite body with planar crack. The exact analytical solution is compared with analysis from crack propagation module. </p>
Transient Optoelectronic Analysis of the Impact of Material Energetics and Recombination Kinetics on the Open-Circuit Voltage of Hybrid Perovskite Solar Cells
<p>This is the data presented in the article 'Transient Optoelectronic Analysis of the Impact of Material Energetics and Recombination Kinetics on the Open-Circuit Voltage of Hybrid Perovskite Solar Cells' published in The Journal of Physical Chemistry C, DOI: 10.1021/acs.jpcc.7b02411.</p>
An Open Access User Generated Video Dataset from 2016 Edinburgh Festival
<p>A user generated video dataset captured during the 2016 Edinburgh festival. The provided dataset was collected using a smart phone and is available with no post-processing. The videos mainly cover the Edinburgh streets and the festival atmosphere, and do not cover any performances. The dataset can be used for evaluation of various research tools, such as video quality assessment and enhancement.</p>
Drivers and Barriers for Open Access Publishing - WoS 2016 Dataset
<p>Answers to a survey on gold Open Access run from July to October 2016. The dataset contains 15,235 unique responses from Web of Science published authors. This survey is part of a PhD thesis from the University of Granada in Spain. More details about the study can be found in the full text document, also available in Zenodo.</p> <p>Following are listed the questions related to the WoS 2016 dataset. Please note that countries with less than 40 answers are listed as "Other" in order to preserve anonymity.</p> <p><strong>* 1. How many years have you been employed in research?</strong></p> <ul> <li>Fewer than 5 years</li> <li>5-14 years</li> <li>15-24 years</li> <li>25 years or longer</li> </ul> <p>Many of the questions that follow concern Open Access publishing. For the purposes of this survey, an article is Open Access if its final, peer-reviewed, version is published online by a journal and is free of charge to all users without restrictions on access or use.</p> <p><strong>* 2. Do any journals in your research field publish Open Access articles?</strong></p> <ul> <li>Yes</li> <li>No</li> <li>I do not know</li> </ul> <p><strong>* 3. Do you think your research field benefits, or would benefit from journals that publish Open Access articles?</strong></p> <ul> <li>Yes</li> <li>No</li> <li>I have no opinion</li> <li>I do not care</li> </ul> <p><strong>* 4. How many peer reviewed research articles (Open Access or not Open Access) have you published in the last five years?</strong></p> <ul> <li>1-5</li> <li>6-10</li> <li>11-20</li> <li>21-50</li> <li>More than 50</li> </ul> <p><strong>* 5. What factors are important to you when selecting a journal to publish in?</strong></p> <p><strong>[Each factor may be rated “Extremely important”, “Important”, “Less important” or “Irrelevant”. The factors are presented in random order.]</strong></p> <ul> <li>Importance of the journal for academic promotion, tenure or assessment</li> <li>Recommendation of the journal by my colleagues</li> <li>Positive experience with publisher/editor(s) of the journal</li> <li>The journal is an Open Access journal</li> <li>Relevance of the journal for my community</li> <li>The journal fits the policy of my organisation</li> <li>Prestige/perceived quality of the journal</li> <li>Likelihood of article acceptance in the journal</li> <li>Absence of journal publication fees (e.g. submission charges, page charges, colour charges)</li> <li>Copyright policy of the journal</li> <li>Journal Impact Factor</li> <li>Speed of publication of the journal</li> </ul> <p><strong>6. Who usually decides which journals your articles are submitted to? (Choose more than one answer if applicable)</strong></p> <ul> <li>The decision is my own</li> <li>A collective decision is made with my fellow authors</li> <li>I am advised where to publish by a senior colleague</li> <li>The organisation that finances my research advises me where to publish</li> <li>Other (please specify) [Text box follows]</li> </ul> <p><strong>7. Approximately how many Open Access articles have you published in the last five years?</strong></p> <ul> <li>0</li> <li>1-5</li> <li>6-10</li> <li>More than 10</li> <li>I do not know</li> </ul> <p>[If the answer is “0”, the survey jumps to Q10.]</p> <p><strong>* 8. What publication fee was charged for the last Open Access article you published?</strong></p> <ul> <li>No charge</li> <li>Up to €250 ($275)</li> <li>€251-€500 ($275-$550)</li> <li>€501-€1000 ($551-$1100)</li> <li>€1001-€3000 ($1101-$3300)</li> <li>More than €3000 ($3300)</li> <li>I do not know</li> </ul> <p>[If the answer is “No charge or I don’t know” the survey jumps to Q20. ]</p> <p><strong>* 9. How was this publication fee covered? (Choose more than one answer if applicable)</strong></p> <ul> <li>My research funding includes money for paying such fees</li> <li>I used part of my research funding not specifically intended for paying such fees</li> <li>My institution paid the fees</li> <li>I paid the costs myself</li> <li>Other (please specify) [Text box follows]</li> </ul> <p><strong>* 10. How easy is it to obtain funding if needed for Open Access publishing from your institution or the organisation mainly responsible for financing your research?</strong></p> <ul> <li>Easy</li> <li>Difficult</li> <li>I have not used these sources</li> </ul> <p><strong>* 11. Listed below are a series of statements, both positive and negative, concerning Open Access publishing. Please indicate how strongly you agree/disagree with each statement.</strong></p> <p>[Each statement may be rated “Strongly agree”, “Agree”, “Neither agree nor disagree”, “Disagree” or “Strongly disagree”. The statements are presented in random order.]</p> <ul> <li>Researchers should retain the rights to their published work and allow it to be used by others</li> <li>Open Access publishing undermines the system of peer review</li> <li>Open Access publishing leads to an increase in the publication of poor quality research</li> <li>If authors pay publication fees to make their articles Open Access, there will be less money available for research</li> <li>It is not beneficial for the general public to have access to published scientific and medical articles</li> <li>Open Access unfairly penalises research-intensive institutions with large publication output by making them pay high costs for publication</li> <li>Publicly-funded research should be made available to be read and used without access barrier</li> <li>Open Access publishing is more cost-effective than subscription-based publishing and so will benefit public investment in research</li> <li>Articles that are available by Open Access are likely to be read and cited more often than those not Open Access</li> </ul> <p>This study and its questionnaire are based on the SOAP Project (http://project-soap.eu). An article describing the highlights of the SOAP Survey is available at: https://arxiv.org/abs/1101.5260. The dataset of the SOAP survey is available at http://bit.ly/gSmm71. A manual describing the SOAP dataset is available at http://bit.ly/gI8nc.</p>
NBM: an Open Dataset for the Acoustic Monitoring of Nocturnal Migratory Birds in Europe
<p>This is the dataset presented in the paper "NBM: an Open Dataset for the Acoustic Monitoring of Nocturnal Migratory Birds in Europe", which can be found here: <a href="https://arxiv.org/pdf/2412.03633">https://arxiv.org/pdf/2412.03633</a>.</p> <p> </p> <p><strong>Update 2025, June 13th</strong></p> <p>- A <strong>metadata file</strong> can now be found alongside the dataset ("metadata.csv"): it contains the recording date for original NBM files whenever available, and date and location for all but two of the files originating from Xeno-Canto. All audio samples in the train_nbm_orig folder were recorded in France, but no precise location is available for this collection.</p> <p>- Irregularities due to unconstrained text input in several annotation files have been fixed; in particular all annotated parasitic and background noise are now gathered in two classes: <strong>0: Background </strong>and<strong> 0: Other biophonia</strong>. Unidentified bird vocalizations fall under the <strong>Other </strong>category.</p> <p> </p> <p><strong>File description</strong></p> <p>Files come in three directories: train_nbm_orig, train_nbm_xc and test.</p> <p>Each is composed of a list of .wav files with its .txt annotations file. All bird vocalizations are linked to a <strong>species </strong>and are annotated both in <strong>time </strong>and <strong>frequency</strong>.</p> <p>The train dataset is composed of a total of 2,077 audio files and 13,359 annotations, for a total of ~38 hours of recording. Among these, 883 files were downloaded from Xeno-canto and finely hand-annotated.</p> <p> </p> <p><strong>Citation </strong>(Bibtex)</p> <pre>@article{airale2024nbm, title={NBM: an Open Dataset for the Acoustic Monitoring of Nocturnal Migratory Birds in Europe}, author={Airale, Louis and Pajot, Adrien and Linossier, Juliette}, journal={arXiv preprint arXiv:2412.03633}, year={2024} }<br><br></pre> <p><strong>License</strong></p> <p>This dataset is distributed under a non-commercial, non-derivative license (CC BY-NC-ND 3.0).</p> <p> </p> <p><strong>Acknowledgments</strong></p> <p><span lang="EN-US">Special thanks to all contributors to the initial NBM database: Adrien Pajot, Aymeric Mousseau, Christophe Mercier, Frédéric Cazaban, Gaëtan Mineau, Ghislain Riou, Guillaume Bigayon, Hervé Renaudineau, Kévin Leveque, Lionel Manceau, Mathurin Aubry, Maxence Pajot, Nidal Issa, Willy Raitière, and equal thanks to all anonymous further contributors.</span></p> <p><span lang="EN-US">Acknowledgments also go to all contributors of the Xeno-Canto database whose recordings where used to build this dataset:</span></p> <p><span lang="EN-US">Joost van Bruggen, Ricardo Hevia, Paul Kelly, Franck Hollander, Frédéric Cazaban, Ireneusz Oleksik, Irish Wildlife Sounds, Stanislas Wroza, Cedric Mroczko, Will Scott, Sergi, Chris Batty, Martin Billard, Juha Saari, Julien Bottinelli, Mark Pearson, Uku Paal, Christophe Mercier, Thierry THOMAS, Samuel Levy, Paul Coiffard, Lluís Brotons, Jorge Leitão, Alan Dalton, David Tattersley, Xavier Riera, Lars Mogensen, Feliu López i Gelats, José Manuel Reyes Páez, Jon Sparshott, Sergi Carreras, Marta Celej, julien Rochefort, Chèvremont Fabian, MILLON Xavier, Ed Stubbs, Niels Van Doninck, Jarek Matusiak, Anthony ROUX, Dan Lombard, C PAL, Ray Tsu </span><span lang="EN-US">诸仁</span><span lang="EN-US">, Martijn Verdoes, Pierrick Devoucoux, Manceau Lionel, Lionel Manceau, Vandousselaere Patrick, Volker Arnold, Lars Edenius, Krzysztof Deoniziak, Albert Noorlander, Robert Ekman, Oriol Baena, Mr Mark Shorten, Beatrix Saadi-Varchmin, Simon Kiesé, Robert Manzano, Martin Fousert, Simon Gillings, Lisette, Marco Dragonetti, Cédric PEIGNOT, Adrien CHARBONNEAU, Gosse Hoekstra, Christian Kerihuel, Koen Lepla, Daniele Baroni, Peter van Vlaardingen, Albert Subirà, Alain Malengreau, Julien Piette, Calum Mckellar, Mikael Litsgård, Martin Grienenberger, Sven Kransel, Oliwier Myka, Susanne Kuijpers, Pierre Foulquier, Paolo Zucca, Maties, Geoffrey Monchaux, Jean COURTIN, Pere Josa, Stein Ø. Nilsen, florent yvert, John Sirrett, Toby Carter, Grzegorz Lorek, Tom Jordan, Miguel Tirado, Helder Cardoso, Ignaas Robbe, James P, Corentin Rivière, Romuald Mikusek, David Santamaría Urbano, Diego Fernandez Martinez, Tanguy Loïs, Camille Vacher, Frank Pierik, Testaert Dominique, Piotr Szczypinski, Rafael Costas, Patrick Franke, Ad Hilders, J. Veeken, Thijs Calu, David Pennington, Nic Hallam, Albert Lastukhin, Dominique Guillerme, W. Agster, Nittert van de Water, Marcos Prada Arias, Francesco Barberini, Enrico Hübner, Luca Forneris, Graham Clarke, Mike Douglas, Johan Willner, Sébastien Arriubergé, Rafał Szczerbik, Alessandro Pavesi, Jarred Johnson, Tomasz Wałachowski, Cédric JOUVE, Tom Gheskiere, jesus carrion, David Darrell-Lambert, Graham Sparshott, Théo Hervé, Martin Sutherland, Quentin Giraud, Kévin Giraudin, LE ROY Renaud, August Thomasson, Marcin Sołowiej, Filippo Ceccolini, BirdingAlbufera, Armin Kreusel, Robert Thorpe, Sannier, Oscar Vilches, Paweł Szymański, Jerome Fischer, Matt Slaymaker, Gil Lissens, Sidney M, Matthias Feuersenger, JC Paniagua, Anita Rakitić, david m, Maxime Pirio, brickegickel, Mark Newsome, Sophie REVERDIAU, Oriol, Michaël Bridoux, Sonothèque ADVL, Kieran Nixon, Jochem verweij, Sjouke Scholten, Michael Brunhøj Hansen, Peter Stronach, Pere Josa Anguera, Esperanza Poveda, Johannes Dag Mayer, Pablo Valverde, Friedemann Arndt, Tristan Guillebot de Nerville, Adam Cross, Richard Drew, Cindie Arlaud, Petr Večeřa, Domagoj Tomičić, Guillaume Petitjean, riou, Peter Mattsson, Michał Jezierski, SCECB NATURA-Z, Karol Łanocha, Twan Mols, Klaus Fink, Dawid Jablonski, Arnold Meijer, Paul Ehlers, José Carlos Sires, manuel Grosselet, Birding The Strait, Charlie Bodin, Juan Carlos Paniagua, Nabholz Benoit, Fergus Crystal, Agris Celmins, Albert Cama, Iván Vega, John Muddeman, Adrien Mauss, Gerard Troost, Serge Hoste, Stefano Miceli, Joan Balfagon, Ace, Frank A. Roos, Tom Wulf, Vincent Palomares, Marcel Tenhaeff, Gabriel Hasan, James Lidster, Frank van de Weijer, Herman van Oosten, Alain Verneau, Herman van der Meer, Romain SPELLER, Johan Lorentzon, Thomas ARMAND, Chris Beach, Jacob Spinks, András Schmidt, Jonathan van Erkel, James Spencer, Rowan Wakefield, LEPAGE Frédéric, Itziar Gutiérrez, Severin Racky, NEVILLE MADON, B Whyte, Bodhuin Maxime, Benoit Paepegaey, Ruysschaert, Soulier Pierrick, Frederik Fluyt, Thomas Roux, Eduardo Realinho, Simon Elliott, Oscar Vilches Mendoza, Juan Pita-Romero Caamaño, Gary Elton, Marc Hughes, Raul Pascual, Nicolas Selosse, Arnaud Hedel, Gaëtan Mineau, Peter Boesman, Steve Flynn, Gerry p oneill, Andy Hultberg, Helmut Schaffer, Luca Giussani, edouard dansette, Gavia Stellata, Robert Schouw, Sławomir Karpicki-Ignatowski, mvallespirc, Mark Plummer, Chacron, Seynaeve Adriaan, Kristian Whittaker, Andreas Pettersson, Rafał Kurowski, Delpit, Anja van Halbeek, Lars Burnus, Benjamin Schedl, Sreekumar Chirukandoth, Mathias Götz, Mikhail Velikanov, Paul Bourdin, Török Tamás, Mehmet Ali Demiral, Manuel Grosselet, Olivier Swift, Yoann Blanchon, Jacob Bosma, Alexis Bukowski, Götz Ellwanger, Guillaume Bigayon, Charlie BODIN, Olivier SWIFT, Manuel Grosselet, Tero Linjama, Ad Postma, Eetu Paljakka, Jan Hein van Steenis, Alwin van Lubeck, Jacobo Ramil MIllarengo, Andrew Cobley, guus van duin, Meinolf Ottensmann, Steve Thorpe, Antoine Salmon, Alain Beuget, Simon Busuttil, Bertrand Dallet, Bill Haines, Robbin van Dijk, Jacopo Barchiesi, Johan Jordaans, Simon BAUDOUIN, Nelson Conceição, Teet Sirotkin, Dean McDonnell, Jocce Ekstrom, Michael John O Mahony, Fred Prak, Joachim Pintens, Christophe Legrand, Daniel Beuker, G Berger, Steve Blain, Boris Delahaie, Will Langdon, David Melichar, Emmanuel Roy, Jonas Brüggeshemke, YvesDS, FRIEDRICH Richard</span></p>
LSD4WSD : An Open Dataset for Wet Snow Detection with SAR Data and Physical Labelling
<p><strong>LSD4WSD V2.0</strong></p><p><strong>L</strong>earning <strong>S</strong>AR <strong>D</strong>ataset for <strong>W</strong>et <strong>S</strong>now <strong>D</strong>etection - Full Analysis Version. </p><p>The aim of this dataset is to provide a basis for automatic learning to detect wet snow. It is based on Sentinel-1 SAR GRD satellite images acquired between August 2020 and August 2021 over the French Alps. The new version of this dataset is no longer simply restricted to a classification task, and provides a set of metadata for each sample.</p><p>Modification and improvements of the version 2.0.0 :</p><ul><li><i>Number of massif:</i> add 7 new massif to cover the all Sentinel-1 images (cf `info.pdf`).</li><li><i>Acquisition:</i> add images of the descending pass in addition to those originally used in the ascending pass.</li><li><i>Sample: </i>reduction in the size of the samples considered to 15 by 15 to facilitate evaluation at the central pixel.</li><li><i>Sample: </i>increased density of extracted windows, with a distance of approximately 500 meters between the centers of the windows.</li><li><i>Sample:</i> removal of the pre-processing involving the use of logarithms.</li><li><i>Sample:</i> removal of the pre-processing involving the normalisation.</li><li><i>Labels:</i> new structure for the labels part: dictionary with keys: `topography`, `metadata` and `physics`.</li><li><i>Labels:</i> `physics`: addition of direct information from the CROCUS model for 3 simulations: Liquid Water Content, snow height and minimum snowpack temperature.</li><li><i>Labels:</i> `topography`: information on the slope, altitude and average orientation of the sample.</li><li><i>Labels:</i> `metadata` : information on the date of the sample, the mountain massif and the run (ascending or descending).</li><li><i>Dataset</i>: removal of the train/test split*</li></ul><p>*We leave it up to the user to use the Group Kfold method to validate the models using the alpine massif information.</p><p>Finally, it consists of 2467516 samples of size 15 by 15 by 9. For each sample, the 9 metadata are provided, using in particular the <a href="https://www.umr-cnrm.fr/spip.php?article265&lang=en">Crocus</a> physical model:</p><ul><li>topography:<ul><li>elevation (meters) (average),</li><li>orientation (degrees) (average),</li><li>slope (degrees) (average),</li></ul></li><li>metadata:<ul><li>name of the alpine massif,</li><li>date of acquisition,</li><li>type of acquisition (ascending/descending),</li></ul></li><li>physics<ul><li>Liquid Water Content (km/m2),</li><li>snow height (m),</li><li>minimum snowpack temperature (Celsius degree).</li></ul></li></ul><p>The 9 channels are in the following order:</p><ul><li>Sentinel-1 polarimetric channels: VV, VH and the combination C: VV/VH in linear,</li><li>Topographical features: altitude, orientation, slope</li><li>Polarimetric ratio with a reference summer image: VV/VVref, VH/VHref, C/Cref**</li></ul><p>** The reference image selected is that of August 9th 2020, as a reference image without snow (cf. <a href="https://ieeexplore.ieee.org/document/842004">Nagler&al</a>)</p><p>An overview of the distribution and a summary of the sample statistics can be found in the file info.pdf.</p><p>The data is stored in .hdf5 format with gzip compression. We provide a python script to read and request the data. The script is dataset_load.py. It is based on the h5py, numpy and pandas libraries. It allows to select a part or the whole dataset using requests on the metadata. The script is documented and can be used as described in the README.md file</p><p>The processing chain is available at the following <a href="https://github.com/Matthieu-Gallet/LSD4WSD-dataset"><strong>Github</strong></a> address.</p><p>The authors would like to acknowledge the support from the National Centre for Space Studies (CNES) in providing computing facilities and access to SAR images via the PEPS platform.</p><p>The authors would like to deeply thank Mathieu Fructus for running the Crocus simulations.</p><p><strong>Erratum :</strong></p><p>In the dataloader file, the name of the "aquisition" column must be added twice, see the correction below.:</p><blockquote><p>dtst_ld = Dataset_loader(path_dataset,shuffle=False,descrp=["date","massif","aquisition","aquisition","elevation","slope","orientation","tmin","hsnow","tel",],) </p></blockquote><p>If you have any comments, questions or suggestions, please contact the authors: </p><ul><li>matthieu.gallet@univ-smb.fr</li><li>fatima.karbou@meteo.fr</li><li>abdourrahmane.atto@univ-smb.fr</li><li>emmanuel.trouve@univ-smb.fr</li></ul>
LICROX- Consortium General Assembly and Open Symposium_17-18 July 2023
<p>Final video of the LICROX project, with images and interviews from the final Consortium Meeting and Open Symposiums held in Tarragona on 17 and 18 July 2023.</p>
Fig.ç3.R elationships of (A) barbel length and (B) pectoral- n length to standard length in Upeneus guttatus (closed symbols: stars from Japan, squares from Indo–West Paci c) and U. japonicus (open circles). in First Records of the Two-tone Goatfish, Upeneus guttatus, from Japan, and Comparisons with U. japonicus (Perciformes: Mullidae)
Fig.ç3.R elationships of (A) barbel length and (B) pectoral- n length to standard length in Upeneus guttatus (closed symbols: stars from Japan, squares from Indo–West Paci c) and U. japonicus (open circles).
(Open) Data literacy: Dataset for a systematic review of the literature
<p>This dataset presents data used for a systematic review of the literature.</p><p>We conducted a comprehensive literature review, in which we identified the following: a) the role of data literacy as one of several barriers to use; and b) open data-related activities that foster informal learning by assisting in the development of critical data literacy as a surrogate for citizens' continued engagement with open data. Following the screening and selection of 66 articles through the use of keyword mapping, the articles were coded and subjected to quantitative analysis. On the one hand, our findings demonstrate that inadequate data literacy hinders the utilisation of open data. Conversely, it seems that open data initiatives create pertinent prospects for fostering technical data literacy among the general public, enabling them to comprehend and engage with decision-making processes that are informed by data. However, critical data literacy as a primary catalyst for the strategic and transformative utilisation of open government data receives scant attention. In conclusion, this research has the potential to provide a foundation for interventions that promote open data literacy and lifelong learning.</p>
ThermoCyte: an inexpensive open-source temperature control system for in vitro live cell imaging
<p>Live-cell imaging is a common technique in microscopy to investigate dynamic cellular behaviour and permits the accurate and relevant analysis of a wide range of cellular and tissue parameters, such as motility, cell division, wound healing responses, and calcium (Ca2+) signalling in cell lines, primary cell cultures, and ex vivo preparations. Furthermore, this can take place under many experimental conditions, making live-cell imaging indispensable for biological research. Systems which maintain cells at physiological conditions outside of a CO<sub>2</sub> incubator are often bulky, expensive, and use proprietary components. Here we present an inexpensive, open-source temperature control system for in vitro live cell imaging. Our system 'ThermoCyte', which is constructed from standard electronic components, enables precise tuning, control, and logging of a temperature 'set point' for imaging cells at physiological temperature. We achieved stable thermal dynamics, with reliable temperature cycling and a standard deviation of 0.42°C over 1 hour. Furthermore, the device is modular in nature, and is adaptable to the researcher's specific needs. This represents simple, inexpensive, and reliable tool for laboratories to carry out custom live-cell imaging protocols, on a standard lab bench, at physiological temperature.</p>
WaivOps EDM-TR9: Open Audio Resources for Machine Learning in Music
<p><strong>EDM-TR9 Dataset</strong></p> <p>EDM-TR9 is an open audio dataset composed of a series of drum recordings in the style of electronic dance music (EDM). This dataset primarily focuses on the distinctive sounds and rhythm patterns of the Roland TR-909 drum machine within the subgenres of dance, house and techno music. The dataset contains 3780 audio loops recorded in uncompressed stereo WAV format, produced with custom drum samples and MIDI-programmed rhythms at various tempo rates.</p> <p><strong>Dataset</strong></p> <p>The primary objective of this dataset is to provide accessible content for machine learning applications in music and audio research. Some potential use cases for this dataset include tempo detection and classification, drum rhythm analysis, audio-to-MIDI conversion, source separation, automated mixing, music information retrieval, AI music generation, sound design and signal processing.</p> <p><strong>Specifications</strong></p> <ul> <li>3780 audio loops (approximately 8 hours)</li> <li>24-bit WAV format</li> <li>BPM labeled</li> <li>Tempo range: 120–140bpm</li> <li>Variational drum patterns</li> <li>EDM drum rhythms</li> </ul> <p><strong>License</strong></p> <p>This dataset was compiled by WaivOps, a crowdsourced music project managed by the sound label company Patchbanks. All recordings have been compiled by verified sources for copyright clearance.</p> <p>The EDM-TR9 dataset is licensed under Creative Commons Attribution 4.0 International <a href="https://creativecommons.org/licenses/by/4.0/">(CC BY 4.0)</a>.</p> <p><strong>Additional Info</strong></p> <p>For audio examples or more information about this dataset, please refer to the <a href="https://github.com/patchbanks/WaivOps-EDM-TR9">GitHub repository</a>.</p>
Techno-economic dataset for open modelling of decarbonization pathways in The Philippines
<p><span>This</span><span> file contains the data and data sources updated for the paper :</span></p> <p> </p> <p><span>'</span><span>The Philippines’ Energy Transition: Assessing Emerging Technology Options using OSeMOSYS (Open Source Energy Modelling System)'</span></p> <p><span>All other data in the model used for the paper is from the Philippines Starter Data kit (Allington, 2021). Renewable Energy Costs are updated from (Alexander, 2023).</span></p> <p> </p>
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