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Collection of spatial information and maps of human past and environment in the Uralic languages speaker area
<p>The collection of spatial information and maps of the past and environment in the Uralic languages speaker area consists excessive amount of multidisciplinary data related to the vast region extending from Eastern Europe to Siberia, encompassing countries like Russia, Finland, and parts of Scandinavia. Uralic speakers are predominantly found in this region, with historical roots in areas around the Ural Mountains and adjacent territories. These datasets can be integrated for multidisciplinary purposes, allowing to explore human-environment interactions, migration patterns, and cultural evolution over time. Datasets are collected initially by the BEDLAN team <a href="https://bedlan.net/">https://bedlan.net/</a> - a research group specialized in various disciplines - linguists, archaeologists, geneticists, and geographers. The data collection and mapmaking have grown beyond the initial stages (publications, applications, exhibitions), hence collaborative effort for data publishing is now crucial. As the data collections and mapmaking continue to evolve dynamically together with ongoing projects, the current repository will be updated accordingly.</p>
Collection de romans français du dix-huitième siècle (1751-1800) / Collection of Eighteenth Century French Novels 1751-1800
<p>This collection of Eighteenth-Century French Novels contains 200 digital texts of novels created or first published between 1751 and 1800. The collection is created in the context of <a href="https://www.mimotext.uni-trier.de/en">Mining and Modeling Text</a> (2019-2023), a project which is located at the Trier Center for Digital Humanities (<a href="https://tcdh.uni-trier.de/en">TCDH</a>) at Trier University.</p> <h2>Metadata</h2> <p>There is a short and an extensive metadata description in TSV for all TEI/XML files:</p> <ul> <li>Metadata, short version: <a href="https://github.com/MiMoText/roman18/blob/master/XML-TEI/xml-tei_metadata.tsv">https://github.com/MiMoText/roman18/blob/master/XML-TEI/xml-tei_metadata.tsv</a></li> <li>Metadata, long version: <a href="https://github.com/MiMoText/roman18/blob/master/XML-TEI/xml-tei_full_metadata.tsv">https://github.com/MiMoText/roman18/blob/master/XML-TEI/xml-tei_full_metadata.tsv</a></li> </ul> <p>Please find further information on our <a href="https://github.com/MiMoText/roman18/tree/v1.2.0">corpus balancing</a> .</p> <h2>Licence</h2> <p>All texts and scripts are in the public domain and can be reused without restrictions. We don't claim any copyright or other rights on the transcription, markup or metadata. If you use our texts, for example in research or teaching, please reference this collection using the citation suggestion below.</p> <h2>Citation suggestion</h2> <p><em>Collection de romans français du dix-huitième siècle (1751-1800) / Eighteenth-Century French Novels (1751-1800)</em>, edited by Julia Röttgermann, with contributions from Julia Dudar, Henning Gebhard, Anne Klee, Johanna Konstanciak, Damir Padieu, Amelie Probst, Sarah Rebecca Ondraszek and Christof Schöch. Release v 1.2.1. Trier: TCDH, 2023. URL: https://github.com/mimotext/roman18. DOI: https://doi.org/10.5281/zenodo.4061903.</p> <h2>Funding</h2> <p>Forschungsinitiative des Landes Rheinland-Pfalz 2019-2023</p>
Field data collected from pyroclastic and lahar deposits of the 472 AD (Pollena) and 1631 Vesuvius eruptions
<p><strong><span>Field data collected from pyroclastic and lahar deposits of the 472 AD (Pollena) and 1631 Vesuvius eruptions</span></strong></p> <p><span>Mauro A. Di Vito<sup>1</sup>, Ilaria Rucco<sup>2</sup>, Sandro de Vita<sup>1</sup>, Domenico M. Doronzo<sup>1</sup>, Marina Bisson<sup>3</sup>, Elena Zanella<sup>4</sup></span></p> <p><sup><span>1</span></sup><span> Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Vesuviano, Napoli, Italy</span></p> <p><sup><span>2</span></sup><span> Heriot-Watt University, School of Engineering and Physical Sciences, Edinburgh, United Kingdom</span></p> <p><sup><span>3</span></sup><span> Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Pisa, Italy</span></p> <p><sup><span>4</span></sup><span> Università di Torino, Dipartimento di Scienze della Terra, Torino, Italy</span></p> <p><span> </span></p> <p><span>This dataset is organized in an Excel file, and it includes all the data collected and reviewed during the last 20 years from drill cores, outcrops, archaeological excavations, stratigraphic trenches, and the existing literature. It focuses on the primary (pyroclastic) and secondary (lahar) deposits of the 472 AD (Pollena) and 1631 eruptions from the Somma-Vesuvius volcano. The aim is to collect stratigraphic, stratimetric, sedimentological, lithological and chronological data to generate distribution maps and to validate the numerical simulations and models for the risk assessment. In particular, this dataset is complementary to – and in support of – the full work by Di Vito et al. (2024), in which the distribution of those deposits all around the Somma-Vesuvius complex and further is presented and discussed. Such dataset was used to inform the shallow-water model of lahars by de’ Michieli Vitturi et al. (2024), which in turns was used by Sandri et al. (2024) to elaborate probabilistic maps of lahar invasion in the Somma-Vesuvius and Apennine areas.</span></p> <p><span>All the data are organized in columns: the first four aim to identify the sites, and so there is a numeric identification code (ID), the name of the site (NAME), and the metric coordinates (East-North) in the UTM WGS 84 – Zone 33 reference projection (X, Y). The last two columns are “MUNICIPALITY” and “PROVINCE” and give a spatial location to the points.</span></p> <p><span>For the two eruptions, several columns have been created:</span></p> <p><span><span>·<span> </span></span></span><span>“472_PRIM”, “1631_PRIM” and “472_ASH” and “1631_ASH” indicate, respectively, the fallout primary deposits of the eruptions and the primary ash, particularly the ash related to the last phases of the eruptions (generally phreatomagmatic).</span></p> <p><span><span>·<span> </span></span></span><span>“472_SYN” and “1631_SYN” indicate the syn-eruptive lahars related to the two eruptions, recognized from the similar composition between the primary deposit and the lahar and from the evidence of a short-term exposure between the two.</span></p> <p><span><span>·<span> </span></span></span><span>“472_POST” AND “1631_POST” indicate the post-eruptive lahars related to the two eruptions. They are considered “post” when in the deposit there are pumices belonging to older eruptions, indicating their involvement in the progressive erosion of the slopes and valleys, and when there is evidence of long periods without deposition, such as the presence of</span><span> </span><span>slightly humified surfaces or traces of human artifacts (excavations, ploughing).</span></p> <p><span><span>·<span> </span></span></span><span>“EROSION_fallout_472” refers to the sites where it was possible to find erosional unconformities between the pyroclastic deposit of the 472 AD eruption and the lahar, as well as between the lower and upper lahar flow units. The erosional features are for example the lack of one or more primary eruptive layers (eroded by the overlying deposit), a change in the granulometry, or lateral discontinuity of the deposit. </span></p> <p><span><span>·<span> </span></span></span><span>“Pdyn (kPa)”, “v (m/s)”, “C (%)” and “T” are all the parameters quantified to validate the numerical models and to assess the hazard from lahars. Pdyn is the flow dynamic pressure, which represents the capability of the flow to entrain a clast, and it depends on the velocity (v) and the flow density, which in turn results from a combination of the density of the particles and the water through the “C (%)”, that is the particle volume concentration. To calculate the flow dynamic pressure and the velocity, the parameters taken into account are the dimensions of the biggest clasts and the nature of the clasts (limestone, ceramic, brick, tephra, lava, sandstone, iron) found in the lahar deposits. The concentration is estimated considering some sites in which the flow expands in correspondence with some obstacles (for example a Roman wall). This can be assumed to be the initial height of the flow before the emplacement. Finally, “T” refers to the estimated deposition temperature of the deposit quantified by the magnetic analysis, in particular in some sites where the lahar interacted with anthropogenic structures.</span></p> <p><span><span>·<span> </span></span></span><span>“DEPOSIT (472)” indicates the type of lahar deposit (syn- or post-eruptive) of the 472 AD eruption in which the fragments were found.</span></p> <p><span><span>·<span> </span></span></span><span>“MULTIPLE LAHAR UNITS” indicates the sites in which multiple flow units are vertically identified in the lahar deposits. They are generally a result of rapid and progressive aggradation of multiple flow pulses, each one resulting from single-pulse “en masse” emplacement</span><span>.</span></p>
Painting. Gustave Van de Woestyne. Christ in the Wilderness. 1939. Oil on canvas. Collection MSK Gent. 2
<u>File Name</u>: PM_146217_B_Gent <br><u>Sublocation</u>: Museum voor Schone Kunsten <br><u>Location</u>: Gent <br><u>Province</u>: Oost-Vlaanderen <br><u>Country</u>: Belgium <br><u>Header</u>: Schilderij, Gustave Van de Woestyne, Christus in de woestijn, 1939, olieverf op doek, collectie MSK Gent <br><u>Description</u>: Painting. Gustave Van de Woestyne. Christ in the Wilderness. 1939. Oil on canvas. Collection MSK Gent. <br><u>Author</u>: Gustave Van de Woestyne (1881-1947) <br><u>Author Mail</u>: pmrmeaeyaert@gmail.com <br><u>Copyright</u>: © Paul M.R. Maeyaert,pmrmaeyaert@gmail.com <br><u>Keywords</u>: Europe|Belgium|Oost-Vlaanderen|Gent; Europe|Belgium|Oost-Vlaanderen; Europe|Belgium; Cultural heritage|Techniques|Painting; Cultural heritage|Museum/private collection; Cultural heritage|Techniques; Cultural heritage|Period|20th C; Cultural heritage|Period; Cultural heritage <br><u>Date of Generation</u>: 2022-09-25T14:08:24.052+02:00
Painting. Gustave Van de Woestyne. Christ in the Wilderness. 1939. Oil on canvas. Collection MSK Gent.
<u>File Name</u>: PM_146216_B_Gent <br><u>Sublocation</u>: Museum voor Schone Kunsten <br><u>Location</u>: Gent <br><u>Province</u>: Oost-Vlaanderen <br><u>Country</u>: Belgium <br><u>Header</u>: Schilderij, Gustave Van de Woestyne, Christus in de woestijn, 1939, olieverf op doek, collectie MSK Gent <br><u>Description</u>: Painting. Gustave Van de Woestyne. Christ in the Wilderness. 1939. Oil on canvas. Collection MSK Gent. <br><u>Author</u>: Gustave Van de Woestyne (1881-1947) <br><u>Author Mail</u>: pmrmeaeyaert@gmail.com <br><u>Copyright</u>: © Paul M.R. Maeyaert,pmrmaeyaert@gmail.com <br><u>Keywords</u>: Europe|Belgium|Oost-Vlaanderen|Gent; Europe|Belgium|Oost-Vlaanderen; Europe|Belgium; Cultural heritage|Techniques|Painting; Cultural heritage|Museum/private collection; Cultural heritage|Techniques; Cultural heritage|Period|20th C; Cultural heritage|Period; Cultural heritage <br><u>Date of Generation</u>: 2022-09-25T14:07:53+02:00
Raw planetary images and boulder labels data (as shapefiles) collected during the BOULDERING Marie Skłodowska-Curie Global fellowship
<p>This database contains 64 large images of craters on the lunar and martian surfaces and 3 images of boulder fields on Earth (see manuscript <a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023JE008013">https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023JE008013</a> for more information on those terrestrial locations). The data was collected during the BOULDERING Marie Skłodowska-Curie Global fellowship between October 2021 and 2024.</p> <p>For each image, the boulder outlines within specific tiles within the image were carefully mapped in QGIS. More information about the labelling procedure can be found in the following manuscript (<a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023JE008013">https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023JE008013</a>). This dataset differs from the previous dataset included along with the manuscript <a href="https://zenodo.org/records/8171052">https://zenodo.org/records/8171052</a>, as it contains more mapped images, especially of boulder populations around young impact structures on the Moon (cold spots). </p> <p>For each location, you will find a raster with a .tif format, and three shapefiles:</p> <ul> <li> <p>a boulder-mapping file, which is the manually digitized outline of boulders.</p> </li> <li> <p>a tiles-completely-mapped file, which depicts the patches/tiles/windows on which the boulder mapping has been conducted.</p> </li> <li> <p>a global-tiles file, which shows all of the image patches/tiles/windows (pick the term you are the most familiar with) within a raster.</p> </li> </ul> <p>In addition you will find .pkl (which stands for pickle), which contains some information about the patches/tiles/windows if you would need to clip those windows out from the original raster. You can find more information in the way we process this raw data into a format which can be ingested in a deep learning model (see <a href="https://zenodo.org/records/14250874" target="_blank" rel="noopener">https://zenodo.org/records/14250874</a>) in the two following github repositories (<a href="https://github.com/astroNils/YOLOv8-BeyondEarth" target="_blank" rel="noopener">https://github.com/astroNils/YOLOv8-BeyondEarth</a> and <a href="https://github.com/astroNils/MLtools/tree/main" target="_blank" rel="noopener">https://github.com/astroNils/MLtools</a>). If you don't plan in adding more training data, you can directly used the pre-processed database (see <a href="https://zenodo.org/records/14250874" target="_blank" rel="noopener">https://zenodo.org/records/14250874</a>).</p> <p>There are multiple locations/images per planetary body. Cold spots are located on the Moon, but they are saved in a folder of their own. </p> <p>Note that the cold spots boulder mapping shapefiles are partially manually mapped, and partially originating from predictions made from a deep learning model (which explains the outline of boulders are predicted within one pixel).</p> <p><strong>How to cite:</strong></p> <p>Please refer to the "how to cite" section of the readme file of <a href="https://github.com/astroNils/YOLOv8-BeyondEarth" target="_blank" rel="noopener">https://github.com/astroNils/YOLOv8-BeyondEarth.</a></p> <p><strong>Structure:</strong></p> <pre><code>. └── raw_data/ ├── coldspots/ │ └── image_name/ │ ├── shp/ │ │ ├── <image_name>-tiles-completely-mapped.shp │ │ ├── <image_name>-boulder-mapping.shp │ │ └── <image_name>-global-tiles.shp │ └── raster/ │ └── <image_name>.tif ├── earth/ │ └── image_name/ │ ├── shp/ │ │ ├── <image_name>-tiles-completely-mapped.shp │ │ ├── <image_name>-boulder-mapping.shp │ │ └── <image_name>-global-tiles.shp │ └── raster/ │ └── <image_name>.tif ├── mars/ │ └── image_name/ │ ├── shp/ │ │ ├── <image_name>-tiles-completely-mapped.shp │ │ ├── <image_name>-boulder-mapping.shp │ │ └── <image_name>-global-tiles.shp │ └── raster/ │ └── <image_name>.tif └── moon/ └── image_name/ ├── shp/ │ │ ├── <image_name>-tiles-completely-mapped.shp │ │ ├── <image_name>-boulder-mapping.shp │ │ └── <image_name>-global-tiles.shp └── raster/ └── <image_name>.tif</code></pre>
Variabilities of Dopamine (₯) I: Six Paper Collections in 2024
<ol> <li><a title="The Variabilities of Dopamine (₯) - PART V: MeSH: D005239 & NBO:0000209 (Fear Comes in to Play)" href="https://details-or-fragments.blogspot.com/2024/12/DAfear.html" target="_blank" rel="noopener"><strong>The Variabilities of Dopamine (₯) - PART V: MeSH: D005239 & NBO:0000209 (Fear Comes in to Play)</strong></a>: Do you still remember the 67-year-old dopamine girl in the history of dopamine science this year? She gradually became a spokesperson for happiness in her twenties. However, behind this happiness is actually a little fear. In the early stages of research, scientists used basic tools to explore dopamine's role, focusing on its relevance to psychosis and antipsychotic drugs. Initial claims that dopamine was involved in fear conditioning were dismissed due to the inadequacies of the drugs, tools, and techniques used. However, with the development of science, it turns out that the purple "Fear" in "Inside Out" also has some relationship with the dopamine girl. Let's do some brain teasers together this time! In "Dopamine at Forty," we learned that dopamine (DA) is more than just the "happy molecule" we once thought it was. Thanks to advancements in genetics, chemistry, and other technologies in the 21st century, scientists now understand dopamine and its interactions with neurons (DAN) and receptors much better. <a title="多變多巴胺&mdash;&mdash;第五部:恐懼也來湊一腳" href="https://case.ntu.edu.tw/blog/?p=44919" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-12-26 </li> <li><strong><a title="The Variabilities of Dopamine (₯) - PART IV: MeSH:D011954(Bound Receptors:D1~D5" href="https://details-or-fragments.blogspot.com/2024/12/dar.html" target="_blank" rel="noopener">The Variabilities of Dopamine (₯) - PART IV: MeSH:D011954(Bound Receptors:D1~D5</a>) : </strong>Dopamine is a pretty quirky character. Not only does it act as a neurotransmitter, but it also behaves differently depending on the "dopamine receptor" it binds to. Imagine these receptors as different doorways on the surface of a cell, each one changing how dopamine does its job. So, what's so special about these receptors? Well, think of them like the VIP passes that let dopamine into the cell club. You've probably heard about receptors because of the coronavirus (yep, the COVID-19 villain). The virus uses a special receptor called "ACE2" to sneak into our cells. Using this same idea, you can picture dopamine needing its own special receptors to get things done. In short, dopamine receptors are like the bouncers deciding who gets into the cell party, and without them, dopamine would just be left knocking on the door! <a title="多變多巴胺&mdash;&mdash;第四部:綁定的受體D1~D5" href="https://case.ntu.edu.tw/blog/?p=44815" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-11-14 <strong><br></strong></li> <li><strong><a title="The Variabilities of Dopamine (₯) - PART III: CL:0000700 & SIO:000823 (Curious detective DAN's aging)" href="https://details-or-fragments.blogspot.com/2024/09/curiosity.html" target="_blank" rel="noopener">The Variabilities of Dopamine (₯) - PART III: CL:0000700 & SIO:000823 (Curious detective DAN's aging)</a> : </strong>In the complex drama of the brain, there are many characters, but dopaminergic neurons (DAN) take the lead role. These neurons are always on the lookout for new things and solving puzzles, like a brainy Sherlock Holmes. Dopamine, the neurotransmitter, is their trusty sidekick, helping them stay curious and active. But, like in any good story, there's a twist. Over time, these once-energetic neurons start to lose their zest for new experiences. This decline in curiosity mirrors our own aging. It raises an important question: what happens in the brain to cause this loss? What makes our inner Sherlock Holmes lose interest in the unknown? <a title="多變多巴胺&mdash;&mdash;第三部:好奇偵探DAN的變老" href="https://case.ntu.edu.tw/blog/?p=44568" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-09-06 </li> <li><a title="The Variabilities of Dopamine (₯) - PART II: CL: 0000700" href="https://details-or-fragments.blogspot.com/2024/08/CL0000700.html"><strong>The Variabilities of Dopamine (₯) - PART II: CL: 0000700: </strong></a>What are dopaminergic neurons (DANs), the cells in your brain that help you do your job every day? Let’s give it a try . Let’s use the “Knowledge Manual” - the ontology. Starting from DAN’s ID, CL: 0000700, a few pictures will present the important relationship between DAN and dopamine. Once you have the concept of DAN-related knowledge graph, will it collide with the DAN and dopamine working in your mind to inspire a new cognitive world spark that belongs to you? | <a title="多變多巴胺&mdash;&mdash;第二部:工作細胞DAN " href="https://case.ntu.edu.tw/blog/?p=44411" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan (Chinese Publication)</a>, 2024-08-04</li> <li><a title="The Variabilities of Dopamine (₯) - PART I:ChEBI:18243" href="https://details-or-fragments.blogspot.com/2024/06/ChEBI18243.html"><strong>The Variabilities of Dopamine (₯) - PART I:ChEBI:18243:</strong> </a>What is the specific image of the charming and changeable dopamine among scientists? What is the family tree of dopamine established by chemists and information scientists? What is so called ontology? Let us try to brief in common words, knowledge ontology (ontology for short) is a basic computing model compiled by scientific experts in a specific field and fed to computers. Today, we try to use the knowledge architecture of these computers to feed human readers in the context of popular science for writing and reading. This is an innovative creative experiment that uses dopamine to open a new chapter in popular science. It’s so exciting, so nervous for me. What are the benefits of learning about dopamine through Ontology? (1) Telling stories by the graphical structure of the basic knowledge summary, let people understand the information quickly and clearly at a glance. (2) Linking to specific knowledge bases, the information can be “tasted” briefly and deeply by human choices. (3) Are you in urgent need of inspiration tools? Why not try the ontological popular science for different creativity? | <a title="多變多巴胺&mdash;&mdash;第一部:ChEBI:18243" href="https://case.ntu.edu.tw/blog/?p=44277" target="_blank" rel="noopener">CASE Science, Center for the Advancement of Science Education, National Taiwan(Chinese Publication)</a>, 2024-06-27 </li> <li><a title="Variabilities of Dopamine (₯) - Prequel" href="https://details-or-fragments.blogspot.com/2024/04/polymorphic-dopamine-prequel.html" target="_blank" rel="noopener"><strong>Variabilities of Dopamine (₯) - Prequel:</strong> </a>Dopamine should be the most well-known neurotransmitter in the human body. After all, who doesn’t like the “happy molecule”? But you know what? Dopamine is not that simple! There are still divergent opinions about the role she plays in the human body, and it is often said that her actions and reactions affect us in unexpected ways. This article uses the theme of anthropomorphic scientific information to observe and understand the development process of dopamine in the history of science and the different characteristics discovered at different stages. It uses the growth process of a girl as a metaphor to observe and understand it as a leading story to understand the complete knowledge structure of dopamine. | <a href="https://case.ntu.edu.tw/blog/?p=44043">CASE Science, Center for the Advancement of Science Education, National Taiwan(Chinese Publication)</a>, 2024-04-24 </li> </ol>
Single aerosol measurements from a wideband integrated bioaerosol sensor, collected during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This data set contains the time series of single particle data, measured by the wideband integrated bioaerosol sensor (WIBS-4, University of Hertfordshire, Hatfield, UK), during the Antarctic Circumnavigation Expedition (ACE), which was conducted between 20th of December 2016 and 19th of March 2017. WIBS provides aerosol optical diameter (5 μm - 14 μm), asymmetry factor and fluorescent signals on three different channels. WIBS measures single aerosol particles at a sampling rate of 125 Hz. More technical details about WIBS could be found in Kaye et al. (2005).</p> <p><strong>Dataset contents</strong></p> <ul> <li>part_1_Cape_Town_Kerguelen.csv, data file, comma-separated values</li> <li>part_2_Kerguelen_Hobart.csv, data file, comma-separated values</li> <li>part_3_Hobart_Mertz.csv, data file, comma-separated values</li> <li>part_4_Mertz_Punta Arenas.csv, data file, comma-separated values</li> <li>part_5_Punta_Arenas_Cape_Town.csv, data file, comma-separated value</li> <li>part_6_Cape_Town_Bremerhaven.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This aerosol measurement dataset collected using a WIBS during ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Humic acid like concentration in seawater samples, collected from the trace metal rosettes in the Southern Ocean during the austral summer of 2016/2017, on board the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>Humic acid like concentration (abbreviated HA) measured with respect to the Suwannee River Fulvic acid standards (µmol SRFA equivalent per litre).</p> <p>Seawater samples were collected from trace metal rosette (TMR) deployments at different depths in the water column during the Antarctic Circumnavigation Expedition (ACE). Humic acid like data from legs 1 and 2, from TMR cast numbers 3 to 16, were analysed by electrochemistry following standard additions of Suwannee River Fulvic Acid (standard 1, IHSS). This data is to support iron ligands and iron bioavailability as well as hydrolysable saccharides (TPZT) data, also collected during ACE.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_humics_data.csv, data file, comma-separated values</li> <li>ace_humics_data_visual_summary.png, metadata, portable network graphics</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This humics dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Navigation and meteorological data collected during the Tara Pacific Expedition 2016-2019
<p>The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples. The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide the continuous dataset originating from navigation and meteorological instruments acquiring continuously during the full course of the campaign.</p> <p> </p> <p>Variables/ descriptions and units:</p> <table> <tbody> <tr> <td>variable</td> <td>description</td> <td>units</td> </tr> <tr> <td>'dt'</td> <td>date-time stamp</td> <td>iso UTC</td> </tr> <tr> <td>'lat'</td> <td>latitude</td> <td>decimal degree</td> </tr> <tr> <td>'lon'</td> <td>longitude</td> <td>decimal degree</td> </tr> <tr> <td>'flag_origin_latlon'</td> <td>origin of the latitude and longitude</td> </tr> <tr> <td>'cog'</td> <td>course over ground</td> <td>degree</td> </tr> <tr> <td>'sog'</td> <td>speed over ground</td> <td>knots</td> </tr> <tr> <td>'sst_batos'</td> <td>Sea surface temperature measured by the navigation station</td> <td>°C</td> </tr> <tr> <td>'temperature_atm'</td> <td>Atmospheric temperature</td> <td>°C</td> </tr> <tr> <td>'pressure_sealevel'</td> <td>Atmospheric presure</td> <td>hp</td> </tr> <tr> <td>'relative_humidity'</td> <td>relative humidity </td> <td>%</td> </tr> <tr> <td>'apparent_windspeed_bow'</td> <td>apparent wind speed</td> <td>knots</td> </tr> <tr> <td>'apparent_winddir_bow'</td> <td>wind direction from the bow</td> <td>degree</td> </tr> <tr> <td>'apparent_wind_trueN'</td> <td>wind direction from north</td> <td>degree</td> </tr> <tr> <td>'true_wind_speed'</td> <td>knots</td> </tr> <tr> <td>'true_wind_dir'</td> <td>wind direction from north</td> <td>degree</td> </tr> <tr> <td>'sunzenith'</td> <td>sun position relative to zenith</td> <td>radian</td> </tr> <tr> <td>'sunazimuth'</td> <td>sun position relative to north</td> <td>radian</td> </tr> </tbody> </table>
Jingju a Cappella Recordings Collection
<p>The <strong>Jingju a Cappella Recordings Collection</strong> (<strong>JaCRC</strong>) is part of the <strong><a href="https://compmusic.upf.edu/corpora">Jingju Music Corpus</a></strong> created in the <a href="http://compmusic.upf.edu/">CompMusic project</a> at the Music Technology Group, Universitat Pompeu Fabra, Barcelona (MTG). The <strong>JaCRC</strong> was created for different research tasks, mostly concerning melodic characteristics of jingju arias and pronunciation in jingju, and parts of the collection have been used in several publications. The <strong>JaCRC </strong>contains 314 recordings of jingju a cappella singing, plus 76 recordings of the jinghu accompaniment for their corresponding vocal tracks. Except for 53 of them (see CONTENT below), all of the recordings were newly created for this collection. The <strong>JaCRC </strong>also contains the manual segmentation of 217 vocal recordings and lyrics files for 156, 67 of which include annotations for start and end of each lyrics line in a related music score (see the README file). The dataset is released under a Creative Commons license (see LICENSE below).</p> <p>The content of the <strong>JaCRC</strong> was previously published in three different parts (<a href="https://doi.org/10.5281/zenodo.780559">part 1</a>, <a href="https://doi.org/10.5281/zenodo.842229">part 2</a>, <a href="https://doi.org/10.5281/zenodo.1244732">part 3</a>). This new release puts all the data together under an unified structure in order to ease its usability.</p> <p><br> <strong>CONTENT</strong></p> <p>The main body of the <strong>JaCRC </strong>are 239 a cappella recordings of jingju arias. Among those, the main contribution of the collection are the 186 newly created a cappella recordings by professional or semi-professional actors. Some of the recordings contain incomplete arias because the performer decided to stop according to their own will. The aria is then completed in subsequent recording(s). In few occasions, the performer decided to record a second version of the same aria. Both versions are included in the collection.</p> <p>The performers for 76 of these recordings sung over a jinghu accompaniment played live in a different room. These accompaniments were also recorded and added to the <strong>JaCRC</strong>.</p> <p>To complement the collection, recordings from existing sources were also integrated to the <strong>JaCRC</strong>. 15 a cappella recordings were obtained from commercial releases by subtracting the instrumental accompaniment, published in separate tracks to be used as accompaniment by amateur singers, from the mixed track. These recordings are not included in the <strong>JaCRC </strong>for copyright issues, but can be shared for research purposes only (see CONTACT below). However, the metadata and the segmentation files for these 15 recordings have been included in the <strong>JaCRC</strong>. Besides, 53 a cappella jingju recordings from <a href="http://isophonics.net/SingingVoiceDataset">Singing Voice Audio Dataset</a> were included here with permission of their authors (see LICENSE and USE below).</p> <p>With the goal of developing technologies to aid learning of jingju singing, 75 recordings were created from amateur performers, both children and adults. These amateur performers, considered as ‘students,’ sung trying to imitate a reference model, considered as ‘teacher.’ The ‘teacher’ would be either present in the session, and their performances were also recorded, or an existing recording of the <strong>JaCRC </strong>was played as model. The 16 recordings of the teachers are part of the <strong>JaCRC </strong>and the anonymized recordings of the students are included in the <strong>JaCRC</strong>.</p> <p>All the artists recorded for the <strong>JaCRC </strong>manifested their written consent to the MTG for the public release of these recordings under Creative Common license.</p> <p>In order to be used for different research tasks, 142 recordings were manually segmented to the phrase and syllable level. Among these, 81 recordings, including those 16 ones used as ‘teacher’ recordings, were further segmented to the phoneme level. All ‘student’ recordings were also segmented to the phrase, syllable and phoneme level. These segmentations are included in the <strong>JaCRC </strong>as <a href="https://www.fon.hum.uva.nl/praat/">Praat</a> TextGrid files.</p> <p>For 156 recordings there are corresponding csv files containing the lyrics performed in the recording, one line per row. Among these, 67 csv files also contain annotations for the boundaries of each lyrics line in a related music score. The boundaries are annotated as offset according to the <a href="https://web.mit.edu/music21/">music21 toolkit</a>. The related music scores can be found in the <a href="https://doi.org/10.5281/zenodo.1285612">Jingju Music Scores Collection</a> with the same name as the one annotated in the csv files.</p> <p><br> <strong>COVERAGE</strong></p> <p>As part of the Jingju Music Corpus, the <strong>JaCRC </strong>was gathered with the purpose of studying the most representative characteristics of jingju vocal music, and therefore the most representative instances of the main elements of jingju vocal music, that is, role type, shengqiang and banshi, are well covered in the collection. Below some statistics about the coverage of these elements in the JaCRC are given. The numbers in brackets correspond to the number of recordings that include (not always exclusively) that element and its percentage with respect to the total 254 recordings in the collection. The numbers include the 15 recordings from commercial realeases not available in the collection (see CONTENT above).</p> <p>Regarding role types, the <strong>JaCRC </strong>includes 5 different ones. The two most extensively covered ones are dan (127, 50.0%), including male dan (27) and huadan (2), and laosheng (108, 42.5%), including female laosheng (8). The other role types included in the JaCRC are jing (17, 6.7%), most of them of female jing (16), xiaosheng (1, 0.4%) and chou (1, 0.4%).</p> <p>The two main shengqiang in jingju are extensively covered in the <strong>JaCRC</strong>, namely xipi (153, 60.2%) and erhuang (62, 24.4%). Besides, other 7 shengqiang are also present in the collection, namely sipingdiao (14, 5.5%), nanbangzi (11, 4.3%), fan’erhuang (8, 3.1%), fansipingdiao (2, 0.8%), fanxipi (4, 1.6%), gaobozi (1, 0.4%), and handiao (1, 0.4%).</p> <p>As for banshi, there are instances of 18 different ones included in the <strong>JaCRC</strong>. The 7 more extensively represented banshi are yuanban (76, 29.9%), liushui (63, 24.8%), manban (46, 18.1%), erliu (40, 15.7%), sanban (34, 13.4%), yaoban (34, 13.4%), and daoban (27, 10.6%). Other banshi also included in the collection are kuaiban (17, 6.7%), huilong (8, 3.1%), sanyan (7, 2.8%), kuaisanyan (7, 2.8%), mansanyan (3, 1.2%), zhongsanyan (3, 1.2%), pengban (2, 0.8%), gunban (1, 0.4%), duoban (1, 0.4%), shuban (1, 0.4%), and kuaisanban (1, 0.4%).</p> <p>In terms of content, the <strong>JaCRC </strong>contains recordings of 142 arias from 74 different plays.</p> <p>Finally, the recordings in the <strong>JaCRC </strong>are performed by 23 artists, including 8 professional actors, 2 graduated jingju students, 3 undergraduate jingju students in their 4th year, and 10 amateur performers. In terms of role types, there are 10 laosheng performers, one of them being the one who also performs the xiaosheng and jing recordings, and another one also performing the chou recording, 8 dan, one of them also performing the huadan recordings, 3 male dan, 1 female laosheng and 1 female jing.</p> <p><br> <strong>ANNOTATIONS</strong></p> <p>All the annotation files are named in the same exact manner as its corresponding recording, so that they can be easily matched. Besides, the metadata and information csv files indicate which annotations are available for which recordings.</p> <p>There are two types of annotations: segmentation and lyrics.</p> <p>The segmentation annotations were done manually and in three phases, corresponding to the subfolders in the “JaCRC-annotations” folder numbered ‘1,’ ‘2’ and ‘3.’ All the segmentations were done using the software <a href="https://www.fon.hum.uva.nl/praat/">Praat</a> and are available in the <strong>JaCRC </strong>as TextGrid files. The phoneme annotations follow the Extended Speech Assessment Methods Phonetic Alphabet (<a href="https://en.wikipedia.org/wiki/X-SAMPA">X-SAMPA</a>). Below is a description of the annotations contained in each of the subfolders:</p> <p>“1-phrase-syllable-phoneme” folder: all the recordings whose annotations are contained in this folder were segmented at least to the phrase (lyrics line), syllable and phoneme levels. Since the annotations were done for different research tasks, the TextGrid files might contain different numbers of tiers, but all of them have a tier named ‘line’ for the phrase level segmentation with lyrics line in Chinese characters as labels, a tier named ‘pinyin’ for the syllable level segmentation with syllables in the pinyin romanization system as labels, and a ‘details’ tier for phoneme segmentation and labels in X-SAMPA. In order to ease access to these annotations, tab-separated values files were generated from the TextGrid files and also included as txt files in this folder. The files that add “_phrase” to the recording’s name contain the phrase level annotations in pinyin. Those that add “_phrase_char” contain the same phrase level annotations, but in Chinese characters. Those that add “_syllable” contain the syllable level annotations in pinyin. And those that add “_phoneme” contain the phoneme level annotations in X-SAMPA.</p> <p>“2-phrase-syllable” folder: same case as in the previous folder, but without phoneme level annotations. In these TextGrid files, the phrase level annotations are still in tiers named ‘line,’ and the syllable level ones are in tiers named ‘dianSilence.’</p> <p>“3-students” folder: same case as in “1-phrase-syllable-phoneme” folder. In these TextGrid files, the phrase level annotations are still in tiers named ‘line,’ the syllable level ones are in tiers named ‘dianSilence,’ and the phoneme level ones in tiers named ‘details.’</p> <p>The lyrics annotations consist of csv files (semicolon as separator) containing the lyrics of their corresponding recordings in their original Chinese script. Each row corresponds to a lyrics line. The first three columns contain information for “Role type,” “Shengqiang” and “Banshi” (see the README file). In the fourth one, under the heading “Couplet line,” “s” (from shangju) indicates that the corresponding lyrics line is an opening line, “x” (from xiaju) indicates that it is a closing line, and “k” indicates is a kutou line. The fifth column, “Lyrics line,” contains the lyrics. If there is a matching music score in the <a href="https://doi.org/10.5281/zenodo.1285612">Jingju Music Scores Collection</a> (JMSC) for the aria performed in the corresponding recording, the sixth column, “Matched score lyrics line,” contains the lyrics for the same as they appear in the score. The seventh column, “Score XML” contains the name of the music score file in the JMSC. Finally, the eight and ninth columns, “Start” and “End,” contain the starting and ending boundaries of the lyrics line in the score. The boundaries are given as note offsets, according to <a href="https://web.mit.edu/music21/">music21</a>. With this information, the notation of each line can be retrieved from the score.</p> <p>For a thorough description of the <strong>JaCRC</strong>, including metadata and information, naming convention and sources, please see the README file.</p> <p><br> <strong>LICENSE</strong></p> <p>All the recordings newly created for the <strong>JaCRC</strong>, that is, all of them except for those from the Singing Voice Audio Dataset, are published under a <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International License</a>.</p> <p>For the license of the recordings from the Singing Voice Audio Dataset (those whose source in the metadata and information csv files is “SVAD”), included in the JaCRC with permission of the authors, please refer to its <a href="http://isophonics.net/SingingVoiceDataset">website</a>.</p> <p><br> <strong>REFERENCING THE JaCRC</strong></p> <p>If you use the recordings of the <strong>JaCRC </strong>in your research, please reference it in your publications using the text proposed in this website in the section “Cite as.”</p> <p>If you use the recordings from the Singing Voice Audio Dataset (those whose source in the metadata and information csv files is “SVAD”), please also include the following reference in your publications:</p> <blockquote> <p>Dawn A. A. Black, Ma Li and Mi Tian. "Automatic Identification of Emotional Cues in Chinese Opera Singing", in Proc. of 13th Int. Conf. on Music Perception and Cognition and the 5th Conference for the Asian-Pacific Society for Cognitive Sciences of Music (ICMPC 13-APSC0M 5 2014), Seoul, South Korea, August 2014.</p> </blockquote> <p><br> <strong>CONTACT</strong></p> <p>For more information, or to request access to the recordings from commercial sources, that can be shared only for research purposes, please contact Rafael Caro Repetto (rafael.caro at upf.edu).</p> <p><br> <strong>ACKNOWLEDGEMENTS</strong></p> <p>We express our deepest gratitude to all the professional and amateur performers who so generously contributed with their time and their art to the <strong>JaCRC</strong>.</p> <p>The creation of the <strong>JaCRC </strong>was funded by the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013), as part of the CompMusic project (ERC grant agreement 267583).</p>
Collection of Algae pictures - sea sample campain - Liguria 2020-2021
<p>The present dataset is the output of the project Euro Trans Bio @lgawarning (ETB-2017-028).</p> <p>@lgawarning amied to develop a web platform to collect all the water sample information obtained, i.e. algal cell type, number and toxicity potential, in order to rapidly observe Harmful Algal Bloom (HABs) distribution and risk.</p> <p>The project consisted of the design and development of a portable integrated hardware/software system for in situ monitoring of algal cells consisting of a glass plankton counting chamber, a portable microscpe to be used with a smartphone (DIPLE) and a specific mobile application for the acquisition and management of images. This system allow to view and photograph, in real time and in situ, individual microalgae and discriminating them from other non-hazardous organisms or organic matter (e.g. pollens). Images are automatically tracked on a dedicated web platform for data collection and analysis.</p> <p>The system was then adopted for mass use in the citizen-science activity of NAUTILOS project (European Union’s Horizon 2020 101000825)</p>
Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics
<p>Full-resolution representative data sufficient to repeat analyses for the work of: AE Wolf, MA Heinrich, IB Breinyn, TJ Zajdel, and DJ Cohen in "Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics".</p> <p>Please see the _README2.0.0.txt file for explanations on contents in this Zenodo repository.</p> <p>Relevant codes used in our analyses are available on Github (github.com/CohenLabPrinceton/ElectrotaxisSupracellularMemory).</p>
Arctic specimens in the NHMO Insect collection 2022 - Jan Mayen
<p>Arctic specimens from Jan Mayen in the NHMO Insect collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.</p>
* Arctic specimens in the NHMO Insect collection 2022 - Svalbard
<p>Arctic specimens from Svalbard in the NHMO Insect collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.</p>
Arctic specimens in the NHMO Fish collection 2022
<p>All Arctic specimens in the NHMO Fish collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the<br> zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.</p>
Arctic specimens in the NHMO Herptile collection 2022
<p>All Arctic specimens in the NHMO Herptile collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.</p>
Arctic specimens in the NHMO DNA bank Vascular plants collection 2022
<p>All Arctic specimens in the NHMO DNA bank Vascular plants collection as of August 2022. See Bjorå et al. 2023 "Collections of Arctic<br> plants, lichens and fungi in the Natural History Museum, University of Oslo, Norway" for further details.</p>
Arctic specimens in the NHMO DNA bank Fungi & Lichens collection 2022
<p>All Arctic specimens in the NHMO DNA bank Fungi & Lichens collection as of August 2022. See Bjorå et al. 2023 "Collections of Arctic plants, lichens and fungi in the Natural History Museum, University of Oslo, Norway" for further details.</p>
Drone-based photogrammetric survey raw data from ESA PANGAEA-X 2017 planetary analogue campaign - Data collected on 2017-11-19
<p>Drone-based photogrammetric survey data from ESA PANGAEA-X 2017 planetary analogue campaign. Data were collected in the framework of the ESA PANGAEA-X testing campaign held in November 2017: We acknowledge ESA for organising the campaign and providing scientific and logistic assistance on site. The authors would like also to thank the Geopark of Lanzarote, the touristic center of Cueva de Los Verdes, the Cabildo of Lanzarote, the National Park of Timanfaya and the IGEO-CSIC-UCM for providing the necessary permits. Data collected on 2017-11-19 during an aerial survey with a DJI Phantom 4 - data from AGPA experiments (AGPA-D) see http://www.agpa-project.eu</p>
ScienceDex guides
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OpenNeuro
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