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1,511 results for “SINS”
S108 | SINLIST | SIN (Substitute It Now) list of hazardous chemicals by ChemSec
<p>This is the collection associated with list S108 SINLIST SIN (Substitute It Now) list of hazardous chemicals by ChemSec on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>SIN (Substitute It Now) list of hazardous chemicals used in a wide variety of articles, products and manufacturing processes around the globe.The SIN List consists of chemicals that have been identified by the non-profit <a href="https://sinlist.chemsec.org/">ChemSec</a> as being Substances of Very High Concern, based on the criteria defined within REACH, the EU chemicals legislation.The SIN abbreviation – Substitute It Now – implies that these chemicals should be removed as soon as possible as they pose a threat to human health and the environment.<br>The list was kindly provided by Anna Lennquist (ChemSec, Sweden) and Hans Peter Arp (NGI,NTNU, Norway).</p> <p>List updated with new substances on 08 May 2024</p>
Data supporting publication: Nanoscale Mechanical Manipulation of Ultrathin SiN Membranes Enabling Infrared Near-Field Microscopy of Liquid-Immersed samples
<p>This repository includes the data corresponding to the figures shown in the journal article entitled Nanoscale Mechanical Manipulation of Ultrathin SiN Membranes Enabling Infrared Near-Field Microscopy of Liquid-Immersed samples, published in small. </p>
Multispectral Images of the Euchologium Sinaiticum, Pars Nova (Codex Sin. Slav. NF 1)
<p>Multispectral Images of the Euchologium Sinaiticum, Pars Nova (Codex Sin. Slav. NF 1), acquired in St. Catherine's Monastery, Egypt, in 2007. Detailled descriptions of image acquisition and usage are found in<em> NF1_Images_Documentation.pdf</em>.</p>
Edge mode engineering for optimal ultracoherent SiN membrane designs
<p>Raw dataset for all the figures of the article entitled</p> <p>'Edge mode engineering for optimal ultracoherent SiN membrane designs',</p> <p>and corresponding scripts for data analysis.</p>
Podcast Club de Lectura "Literatura sin límites"
<p><strong>Capítulos:</strong></p> <p><strong>11. Cuentos cortos de FRANZ KAFKA </strong>En este podcast hablaremos sobre el autor checo Franz Kafka y su papel en la literatura de lengua alemana. Disfrutaremos con la lectura de dos de sus cuentos cortos.</p> <p><strong>12. Cuento: La mendiga de Locarno (HEINRICH VON KLEIST) </strong>A través de la lectura de un famoso cuento de fantasmas conoceremos quién fue el autor alemán Heinrich Von Kleist.</p> <p><strong>13. Microrrelatos alemanes </strong>Dos microrrelatos alemanes nos llevarán a descubrir el talento de dos grandes autores: Herman Hesse y Bertolt Brecht.</p>
Lám. 28.–Melia azedarach, a-f) cultivada, Madrid (MA 270877); g-k) cultivada, pr. Aledo, Murcia (MA 724626): a) rama con flores; b) detalle del envés y margen foliar; c) vista lateral de la flor; d) cáliz y tubo estaminal; e) flor, sin pétalos, abierta longitudinalmente; f) cara abaxial del pétalo; g) drupa; h) pireno; i) sección longitudinal de la drupa; j) sección transversal de la drupa; k) semilla. in Rhamnaceae- Polygalaceae
Lám. 28.–Melia azedarach, a-f) cultivada, Madrid (MA 270877); g-k) cultivada, pr. Aledo, Murcia (MA 724626): a) rama con flores; b) detalle del envés y margen foliar; c) vista lateral de la flor; d) cáliz y tubo estaminal; e) flor, sin pétalos, abierta longitudinalmente; f) cara abaxial del pétalo; g) drupa; h) pireno; i) sección longitudinal de la drupa; j) sección transversal de la drupa; k) semilla.
Lám. 86.–Oxalis purpurea, Cangas de Morrazo, Pontevedra (MA 408343): a) hábito; b) hoja, haz; c) hoja, envés; d) bráctea, cara abaxial; e) flor mediostila sin perianto; f) sépalo, cara abaxial; g) pé- talo; h) androceo abierto; i) estambre, vista lateral; j) gineceo. in Rhamnaceae- Polygalaceae
Lám. 86.–Oxalis purpurea, Cangas de Morrazo, Pontevedra (MA 408343): a) hábito; b) hoja, haz; c) hoja, envés; d) bráctea, cara abaxial; e) flor mediostila sin perianto; f) sépalo, cara abaxial; g) pé- talo; h) androceo abierto; i) estambre, vista lateral; j) gineceo.
Lám. 34.–Juglans regia, a) Montemayor del Río, Salamanca (MA 317826); b-e) Arnedillo, La Rioja (MA 353293); f, g) Redueña, Madrid (MA 447683); h-j) Arsèguel, Lérida (MA 529203): a) ápice de una rama con amento femenino; b) ápice de una rama con amentos femeninos y masculinos; c) flores masculinas; d) estambre, vista adaxial (ventral); e) estambre, cara abaxial (dorsal); f) flor femenina; g) indumento de la flor femenina; h) fruto; i) fruto, sin la mitad de la cáscara, dejan- do a la vista la nuez; j) una de las valvas de la nuez y la semilla. in Rhamnaceae- Polygalaceae
Lám. 34.–Juglans regia, a) Montemayor del Río, Salamanca (MA 317826); b-e) Arnedillo, La Rioja (MA 353293); f, g) Redueña, Madrid (MA 447683); h-j) Arsèguel, Lérida (MA 529203): a) ápice de una rama con amento femenino; b) ápice de una rama con amentos femeninos y masculinos; c) flores masculinas; d) estambre, vista adaxial (ventral); e) estambre, cara abaxial (dorsal); f) flor femenina; g) indumento de la flor femenina; h) fruto; i) fruto, sin la mitad de la cáscara, dejan- do a la vista la nuez; j) una de las valvas de la nuez y la semilla.
Lám. 85.–Oxalis bowiei, Cuart de les Valls, Valencia (MA 599047): a) hábito; b) bulbo antes de brotar; c) detalle de la base del tallo; d) indumento de la base del tallo e) indumento del pedúnculo; f) indumento foliar, envés; g) bráctea, cara abaxial; h) flor sin pétalos; i) flor sin perianto; j) sépalo, cara abaxial; k) gineceo. in Rhamnaceae- Polygalaceae
Lám. 85.–Oxalis bowiei, Cuart de les Valls, Valencia (MA 599047): a) hábito; b) bulbo antes de brotar; c) detalle de la base del tallo; d) indumento de la base del tallo e) indumento del pedúnculo; f) indumento foliar, envés; g) bráctea, cara abaxial; h) flor sin pétalos; i) flor sin perianto; j) sépalo, cara abaxial; k) gineceo.
Data and fitting script for "Direct measurement of a sin(2φ) current phase relation in a graphene superconducting quantum interference device"
<p>This repository contains data and Python analysis scripts used for the publication "Direct measurement of a sin(2\phi) current phase relation in a graphene superconducting quantum interference device (https://doi.org/10.48550/arXiv.2405.13642).</p> <p>The repository is organized as follows: the raw data are encapsulated in a QCoDes database (https://microsoft.github.io/Qcodes/) named 'D-SQUID-06.db'. Post-treated critical current data are included as .csv files and are indexed by measurement ids.</p> <p>The principal analysis is realized in the Jupyter notebook 'Fits_and_Figures.ipynb', which includes all article figures as well as fit functions for fitting both critical currents Ic- and Ic+ simulatenously, first using analytical expression from equation 3 then using numerical expression from equation 5. All fits mentionned in the article are performed there. The repository includes a generic notebook "Extract_Critical_Current.ipynb" used to explore the raw data in the Qcodes database and features an enhanced peak detection script that we used to automatically extract critical current data despite having some artifacts on raw differential conductance versus bias current and magnetic field.</p> <p>We acknowledge the contribution of R. Kerjouan for developing the Python fitting script.</p>
SINS database - Node 4 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 7 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 6 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 12 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 3 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://kuleuvenadvise.github.io/SINS_database/">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 13 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 10 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 9 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 2 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
SINS database - Node 8 - Daily activities in a home environment recorded using a Acoustic Sensor Network
<p>The SINS database contains continuous recordings of a single person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones.Recordings were manually annotated on the level of daily activities performed in the environment.<br> <br> To obtain more information on the database please visit <a href="https://github.com/KULeuvenADVISE/SINS_database">this website</a> and read the published paper.<br> <strong>Please read to license file (available in this repository) before using the database.</strong><br> <br> When using this database you should <strong>cite the following paper</strong>:<br> Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers, The SINS database for detection of daily activities in a home environment using an acoustic sensor network, Proceedings of the Detection and Classification of -Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 32–36, November 2017.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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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.