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174 results for “TV”
Star Tv kesintisiz izle
<p><strong>Türkiye’nin En Çok İzlenen Kanalı Star Tv</strong></p> <p>Doğuş yayın grubu bünyesinde yayın yapan Star TV Türkiye de ulusal bir kanaldır. Genel yayın yönetmeni de Ömer Özgüner’dir. 1 Mart 1989 tarihinde Ahmet Özal ve Cem Uzan tarafından kurulmuştur. Star TV Türkiye’nin ilk özel televizyonudur. Her evin televizyonun da Star TV’ye muhakkak rastlamaktayız.</p> <p>Star TV tüm Türkiye’ye yayın yapar. Dizileri, yarışmaları ve UEFA şampiyonlar ligi maçlarını yayınlar. İnsanların ilgiyle izlediği bir televizyon kanalıdır. <strong>Star TV izle</strong> konusunda hem televizyon hizmet verir hem de internetten üzerinden bu kanal rahatlıkla izlenebilmektedir. Star TV’nin Televizyon frekansı 12015 MHZ ve Symbol Rate 25500 ayarlarıyla yayın yapmaktadır. FEC değeri ise 5/6, polarizasyonu da H- Yatay. Bunun yanı sıra sadece ismi yazılarak internetten de izlenebilir.</p> <p>Star TV’yi <strong>online canlı izle</strong> konusunda internete bakmak yeterlidir. İnsanların en şikayetçi olduğu konu canlı yayınların donmasıdır. Bunun içinde iyi bir internet sitesi tercih edilmesi gerekir. Web tarayıcısından <strong>kesintisiz donmadan izle</strong> araması yapanlar uygun bir internet sitesine ulaşabileceklerdir. <a href="https://www.canlitvizleme.net">Canlı tv izle</a> me sayfasında sizleride görmek isteriz.</p> <p> </p> <p><a href="https://www.canlitvizleme.net/startv"><strong>https://www.canlitvizleme.net/startv</strong></a></p>
Nephrops (Nephrops norvegicus) Burrow object detection simple training dataset from Irish Underwater TV surveys
<div> <div> <div> <div> <h1>Training dataset</h1> <p>Norway prawns (<em>Nephrops norvegicus</em>), also known as the Dublin Bay prawn, are common around the Irish coast. They are found in distinct sandy/muddy areas where the sediment is suitable for them to construct their burrows. <em>Nephrops </em>spend a great deal of time in their burrows and their emergence from these is related to time of year, light intensity and tidal strength. The Irish <em>Nephrops </em>fishery is extremely valuable with landings recently worth around €55m at first sale, supporting an important Irish fishing industry. </p> <p><em>Nephrops</em> are managed in Functional Units (FUs). The Marine Institute has conducted under water television surveys since 2002 to independently estimate abundance, distribution and stock sizes of <em>Nephrops</em> <em>norvegicus </em>for:</p> <ul> <li>Irish Sea <em>Nephrops</em> Grounds (FU 14 and 15) in collaboration with <a title="Link to 'Fisheries and Aquatic Ecosystems' work in AFBI Northern Ireland" href="https://www.afbini.gov.uk/area-of-expertise/fisheries-and-aquatic-ecosystems">AFBI</a> an <a title="Link to Cefas (the Centre for Environment, Fisheries, and Aquaculture Science) in the UK" href="https://www.cefas.co.uk/">CEFAS</a>.</li> <li>Porcupine Bank <em>Nephrops</em> Grounds (FU16)</li> <li>Aran, Galway Bay and Slyne Head <em>Nephrops</em> Grounds (FU17)</li> <li>South and South west Ireland <em>Nephrops</em> Grounds (FU19)</li> <li>Labadie, Jones and Cockburn <em>Nephrops</em> Grounds (FU20 and 21)</li> <li>“Smalls” <em>Nephrops</em> Grounds (FU22)</li> </ul> <p>Each year during the summer months, on average 300 stations are surveyed each year, in three survey legs, covering all the FUs in depths from 20 to 650 metres.</p> <p>A high definition camera system is towed over the sea bed for 10 minutes travelling approx. 200m at 0.8 knots on a purpose built sledge. The UWTV survey follows survey protocols available <a title="Link to survey protocols" href="https://doi.org/10.17895/ices.pub.8014">here</a> agreed by International Council for the Exploration of the Sea (ICES) Working Group on <em>Nephrops </em>surveys (WGNEPS). </p> <p>As part of the iMagine project a selection of images from the Underwater TV survey Functional Units were annotated with bounding boxes and labels in YOLOv8 format to train an YOLOv8 Object Detection Models. The training dataset is saved in YOLOv8 format. It is intended to train a YOLOv8 Nephrrops burrow object detection model to assess the utility of an Object Detection model is assisting Prawn Survey work in the semi automated annotation of prawn burrow imagery.</p> </div> </div> </div> </div>
TV Series - Networks of characters
<p><strong>Description. </strong>This repository contains three sets of files related to the social networks of characters in the following episodes of 3 TV series:</p> <ul> <li><em>Breaking Bad</em> (BB): S01--S03;</li> <li><em>Game of Thrones</em> (GoT): S01--05;</li> <li><em>House of Cards</em> (HoC): S01--S02.</li> </ul> <p>The three separate Graphml files (`.graphml` extension) contain the static, cumulative, conversational networks at the end of the set of episodes considered. Three images (`.jpg` extension) of the resulting static, cumulative, conversational networks at the end of the first two seasons are also provided.<br><br>The compressed archives (`.tgz` extension) provide snapshots of the conversational network of characters (Graphml format) in every scene. These files come in three flavors:</p> <ol> <li><em>Narrative smoothing</em> based networks (denoted `ns`).</li> <li><em>Time-slice</em> based networks, where all interactions are agglomerated every <em>10 scenes </em>(denoted `'ts10`).</li> <li><em>Time-slice </em>based networks, where all interactions are agglomerated every <em>40 scenes </em>(denoted `ts40`).</li> </ol> <p>The video files (`.mp4` extension) contain short animations of the dynamic networks of characters as they evolve over the whole set of episodes considered:</p> <ul> <li>The nodes are represented by the names of the corresponding characters and the distance between two character names is inversely proportional to the weight of the corresponding edge: the closer they are at some point of the story, the more they interact then.</li> <li>The size of each character name is proportional to the local strength of the corresponding character at the moment considered.</li> <li>The color of each character name corresponds to his community at any moment.</li> </ul> <p>Each snapshot in these animations is based on our <em>narrative smoothing</em> approach.</p> <p>This dataset was used in the following articles:</p> <ol> <li>X. Bost, V. Labatut, S. Gueye, and G. Linarès, “Narrative smoothing: dynamic conversational network for the analysis of TV Series plots,” in <em>2nd International Workshop on Dynamics in Networks (DyNo/ASONAM)</em>, 2016, pp. 1111–1118. ⟨<a href="https://hal.archives-ouvertes.fr/hal-01276708">hal-01276708</a>⟩ DOI: <a href="http://doi.org/10.1109/ASONAM.2016.7752379">10.1109/ASONAM.2016.7752379</a></li> <li>X. Bost, V. Labatut, S. Gueye, and G. Linarès, “Extraction de réseaux dynamiques conversationnels par lissage narratif,” in <em>7ème Conférence sur les modèles et lánalyse de réseaux : approches mathématiques et informatiques</em>, 2016. ⟨<a href="https://hal.archives-ouvertes.fr/hal-01385215">hal-01385215</a>⟩</li> <li>X. Bost, V. Labatut, S. Gueye, and G. Linarès, “Extraction and analysis of dynamic conversational networks from TV series,” in <em>Social Network Based Big Data Analysis and Applications</em>, Springer, 2018, pp. 55–84. ⟨<a href="https://hal.archives-ouvertes.fr/hal-01543938">hal-01543938</a>⟩ DOI: <a href="http://doi.org/10.1007/978-3-319-78196-9_3">10.1007/978-3-319-78196-9_3</a></li> </ol> <p><strong>Citation. </strong>If you use this dataset, please cite the article [1]</p> <p><br><code>@InProceedings{Bost2016,</code><br><code> author = {Bost, Xavier and Labatut, Vincent and Gueye, Serigne and Linarès, Georges},</code><br><code> title = {Narrative smoothing: dynamic conversational network for the analysis of {TV} Series plots},</code><br><code> booktitle = {2nd ASONAM International Workshop on Dynamics in Networks},</code><br><code> year = {2016},</code><br><code> pages = {1111-1118},</code><br><code> address = {San Francisco, US},</code><br><code> publisher = {IEEE Publishing},</code><br><code> doi = {10.1109/ASONAM.2016.7752379},</code><br><code>}</code></p>
Serial Speakers: a Dataset of TV Series
<p><strong>Description. </strong>This dataset consists of 3 TV series with manual annotations:</p> <ol> <li><em>Breaking Bad</em>: S01--S05 (file 'bb.json');</li> <li><em>Game of Thrones</em>: S01--08 (file 'got.json');</li> <li><em>House of Cards</em>: S01--S02 (file 'hoc.json').</li> </ol> <p>All three files are in `.json` format and contain TV Series annotated data.</p> <p>Each TV Series is defined by its name, A TV Series contains seasons, defined by their ids. Every season is made of episodes, defined by their ids, titles, duration and fps. Each episode contains two basic kinds of data: scenes and speech segments. Scenes are defined by starting points and are made of shots (Seasons 1 only).<br>A shot is defined by:</p> <ul> <li>Starting and ending positions.</li> <li>Recurring shot ids.</li> </ul> <p>The speech segments are defined by their:</p> <ul> <li>Starting and ending points.</li> <li>Textual content (here encrypted for copyright reasons).</li> <li>Speaker.</li> <li>Possible interlocutors (for the following episodes only: bb: S01E04, S01E06, S02E03, S02E04; got: S01E03, S01E07, S01E08; hoc: S01E01, S01E07, S01E11).</li> </ul> <p>All timestamps are expressed in seconds and are valid for the video files extracted from the commercial DVDs (PAL 25 FPS), with recaps (unannotated) included at the beginning of the <em>House of Cards</em> episodes.</p> <p>A comprehensive description of the dataset can be found in the following paper:</p> <ul> <li>X. Bost, V. Labatut, and G. Linarès, “Serial Speakers: a Dataset of TV Series,” in <em>12th Language Resources and Evaluation Conference</em>, Marseille, FR, 2020, pp. 4249–4257. ⟨<a href="https://hal.archives-ouvertes.fr/hal-02477736">hal-02477736</a>⟩</li> </ul> <p><strong>Source code.</strong> If you are interested in the textual content of the dataset, please consider using our text recovering tool on GitHub: <a href="https://github.com/bostxavier/Serial-Speakers">https://github.com/bostxavier/Serial-Speakers</a></p> <p><strong>Citation. </strong>If you use these data or source code, please cite the above article.</p> <p><br><code>@InProceedings{Bost2020,</code><br><code> author = {Bost, Xavier and Labatut, Vincent and Linarès, Georges},</code><br><code> title = {Serial Speakers: a Dataset of {TV} Series},</code><br><code> booktitle = {12\textsuperscript{th} Language Resources and Evaluation Conference},</code><br><code> year = {2020},</code><br><code> pages = {4249-4257},</code><br><code> address = {Marseille, FR},</code><br><code> url= {http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.524.pdf},</code><br><code>}</code></p>
Graph 9: TV and Radio Broadcasts of Heiner Müller's Interviews.
<p>Graph 9 shows when and where Heiner Müller's interviews were initially broadcasted and with whom he recorded the respective interview.</p>
Dataset Graph 9: TV and Radio Broadcasts of Heiner Müller's Interviews.
<p>Dataset for Graph 9. Data collected based on the Heiner Müller Werkausgabe.</p> <p>Graph 9 shows when and where Heiner Müller's interviews were initially broadcasted and with whom he recorded the respective interview.</p>
A dataset with news messages from a Russian and a Ukrainian TV news channels
<p>This data was used in the following publications:</p> <p>1. Koltsova, O., & Pashakhin, S. (2019). Agenda divergence in a developing conflict: Quantitative evidence from Ukrainian and Russian TV newsfeeds. Media, War & Conflict, 1750635 21982987. <a href="https://doi.org/10.1177/1750635219829876">https://doi.org/10.1177/1750635219829876</a></p> <p>2.Pashakhin S. Topic Modeling for Frame Analysis of News Media // Proceedings of the AINL FRUCT 2016. С. 103-105 – URL: <a href="http://fruct.org/publications/abstract-AINL-FRUCT-2016/files/Pas.pdf">http://fruct.org/publications/abstract-AINL-FRUCT-2016/files/Pas.pdf</a></p> <p>The dataset contains 45,009 news messages collected from official websites of a Russian (Channel One) and a Ukrainian (Channel 5) TV channels. Ukrainian news items were translated into Russian.</p> <p>The dataset has six variables:</p> <ul> <li>text -- a news item;</li> <li>channel -- a source of an item ('first' -- Russian TV channel, 'five' -- Ukrainian TV channel);</li> <li>date -- the date of publishing;</li> <li>url -- links to original news messages.</li> </ul>
BreXLiMe: A Semantically Enriched Dataset With News Articles, Micro-Posts, and TV Shows Related to the Brexit
<p>We provide a <strong>large data set of media content metadata</strong> from various media sources (including online news sites, social media, and live-TV) in three languages (<strong>English, German, and Spanish</strong>). Overall, the data set contains rich metadata for about <strong>240 thousand news articles, 12 million micro-posts, and 900 TV shows</strong>. All media content information has been semantically enriched with annotations of both entities and categories from DBpedia.</p> <p>The data can be used as a valuable data basis for applications and studies of various disciplines (e.g., social studies, political science, and humanities) on the case of Brexit, particularly on the <strong>media landscape before the Brexit referendum held on June 23, 2016</strong>.</p> <p>We provide the data set in the RDF serialization format Turtle (.ttl) as well as in XML.</p> <p>If you use our data set, please <strong>cite</strong> it as follows:</p> <pre><code>Lei Zhang, Maribel Acosta, Michael Färber, Steffen Thoma and Achim Rettinger. "BreXearch: Exploring Brexit Data Using Cross-Lingual and Cross-Media Semantic Search". In: Proceedings of the ISWC 2017 Posters & Demonstrations Track within the 16th International Semantic Web Conference (ISWC 2017). Vienna, Austria, 2017.</code></pre> <p> </p>
Series y películas de TV y plataformas de streaming españolas lanzadas entre el año 2000 y 2022, valoradas por IMBD
<p>Este dataset recoge las valoraciones en IMDB, a fecha de publicación (11/04/2022), de las películas y series españolas emitidas desde el año 2000.</p>
Reanalysis accounting for clustering and nesting overturns conclusions in: "Watching TV Cooking Programs: Effects on Actual Food Intake Among Children"
<p>Stata code to reproduce results from Folkvord F, Anschütz D, Geurts M. Watching TV cooking programs: effects on actual food intake among children. <em>J Nutr Educ Behav</em>. 2020;52(1):3-9.</p>
Transkripte von elf Video-Ansprachen der Schweizer Regierung vor Volksabstimmungen. Transcripts of Eleven TV Addresses Given by the Swiss Government before Popular Votes
<p>Der Datensatz enthält Transkripte (doc, html, pdf, txt) von elf TV-Ansprachen der Schweizer Regierung vor Volksabstimmungen. Die Ansprachen wurden nach GAT 2 transkribiert. / The dataset contains transcripts (doc, html, pdf, txt) of eleven TV addresses given by the Swiss government before popular votes. The addresses were transcribed according to GAT 2.</p> <p> </p> <p><strong>Quellenangabe der Transkripte / Reference to the Transcripts</strong></p> <p>Schröter, Juliane, Keller, Stefan, 2018. Transkripte von elf Video-Ansprachen der Schweizer Regierung vor Volksabstimmungen. Transcripts of Eleven TV Addresses Given by the Swiss Government before Popular Votes. doi: 10.5281/zenodo.1324476.</p> <p><em>Falls Sie sich nur auf eines oder einige der elf Transkripte beziehen, passen Sie die Quellenangabe bitte entsprechend an. / If you are only referring to one or some of the eleven transcripts, please adopt the reference accordingly. </em></p> <p><em>Disclaimer: Die Mitglieder des Bundesrates haben mündliche Ansprachen gehalten. </em><em>Für den Wortlaut der Transkripte sind sie nicht verantwortlich. / The members of the Federal Council have delivered oral addresses. They are not responsible for the wording of the transcripts.</em></p> <p> </p> <p><strong>Quellenangaben der Videos / References to the Videos</strong></p> <p>Bundesrat, 2017a. [TV-Ansprache zum] Bundesgesetz „Unternehmenssteuerreform III“. Produziert von SRG SSR. <a href="https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170212/bundesgesetz-ueber-steuerliche-massnahmen-zur-staerkung-der-wett.html">https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170212/bundesgesetz-ueber-steuerliche-massnahmen-zur-staerkung-der-wett.html</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2017b. [TV-Ansprache zum] Energiegesetz. Produziert von SRG SSR. <a href="https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170521/Energiegesetz.html">https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170521/Energiegesetz.html</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2016. [TV-Ansprache zur] Initiative „Für Ehe und Familie gegen die Heiratsstrafe“. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/vorlage-heiratsstrafe-sendung-mit-gebaerdensprache?id=8e482ca4-52e3-4777-b956-529ce64f96d1">https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/vorlage-heiratsstrafe-sendung-mit-gebaerdensprache?id=8e482ca4-52e3-4777-b956-529ce64f96d1</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2015a. [TV-Ansprache zur] Änderung des Bundesgesetzes über Radio und Fernsehen. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen/video/br-ansprache-zum-rtvg?id=dd58817b-235b-472a-96a2-a67c721e6775&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7">https://www.srf.ch/play/tv/abstimmungen/video/br-ansprache-zum-rtvg?id=dd58817b-235b-472a-96a2-a67c721e6775&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2015b. [TV-Ansprache zur] Präimplantationsdiagnostik. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/ansprachen-bundesrat-in-gebaerdensprache/video/br-ueli-maurer-zum-fortpflanzungsmedizingesetz-fmedg-geb-?id=cbbecc0d-c210-41a9-8190-4d282926c3a8&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7">https://www.srf.ch/play/tv/ansprachen-bundesrat-in-gebaerdensprache/video/br-ueli-maurer-zum-fortpflanzungsmedizingesetz-fmedg-geb-?id=cbbecc0d-c210-41a9-8190-4d282926c3a8&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014a. [TV-Ansprache zur] Beschaffung des Kampfflugzeuges Gripen. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen/video/bundesrat-ueli-maurer-zur-beschaffung-des-kampfflugzeuges-gripen?id=febd8e03-d4c3-42e7-b163-37e9e0d0176c&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7">https://www.srf.ch/play/tv/abstimmungen/video/bundesrat-ueli-maurer-zur-beschaffung-des-kampfflugzeuges-gripen?id=febd8e03-d4c3-42e7-b163-37e9e0d0176c&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014b. [TV-Ansprache zur] Initiative „Für den Schutz fairer Löhne“. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/ansprache-von-bundesrat-johann-schneider-ammann-vom-20-04-2014?id=3ea16bd4-401d-4d68-9d06-b07b83582405">https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/ansprache-von-bundesrat-johann-schneider-ammann-vom-20-04-2014?id=3ea16bd4-401d-4d68-9d06-b07b83582405</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014c. [TV-Ansprache zur] Initiative „Gegen Masseneinwanderung“. Produziert von SRG SSR. <a href="https://www.youtube.com/watch?v=A91gPrFXFCs">https://www.youtube.com/watch?v=A91gPrFXFCs</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014d. [TV-Ansprache zur] Initiative „Pädophile sollen nicht mehr mit Kindern arbeiten dürfen“. Produziert von SRG SSR. <a href="https://www.bk.admin.ch/bk/de/home/dokumentation/volksabstimmungen/volksabstimmung-20140518.html">https://www.bk.admin.ch/bk/de/home/dokumentation/volksabstimmungen/volksabstimmung-20140518.html</a> (Abfrage: 18.04.2018).<br> <br> Bundesrat, 2013. [TV-Ansprache zum] Bundesbeschluss über die Familienpolitik. Produziert von SRG SSR. Video bereitgestellt von SRG SSR.<br> <br> Bundesrat, 2010. [TV-Ansprache] Zur Ausschaffungsinitiative und zum Gegenentwurf des Bundesrates. Produziert von SRG SSR. Video bereitgestellt von SRG SSR.</p> <p> </p> <p><strong>Quellenangabe des Transkriptionssystems / Reference to the Conventions of Transcription</strong></p> <p>Selting, Margret, Auer, Peter, Barth-Weingarten, Dagmar et al., 2009. Gesprächsanalytisches Transkriptionssystem 2 (GAT 2). Gesprächsforschung 10, 353-402.</p>
Instrumento de pesquisa para descrição de programa de TV
<p>Instrumento de pesquisa construído no software Evernote para coleta de dados da dissertação intitulada Gestão de acervos audiovisuais em repositórios, sob orientação da Prof.ª Dra. Maria Giovanna Guedes Farias e coorientação do Prof. Dr. Luiz Tadeu Feitosa.</p>
InVID TV Logo Dataset v2.0
<p>This dataset was created with the purpose of providing a training and evaluation benchmark for TV logo detection in videos. It contains the results from the segmentation and annotation of 2,749 YouTube videos originating from a large number of news TV channels, The videos have been annotated with respect to the TV channel logos they contain -specifically, by the name of the organization to which the logo belongs- and with shot boundary information. Furthermore, a set of logo templates has been extracted from the videos and organized alongside the corresponding channel information.</p> <p>As we do not own the rights to the videos, the dataset only contains the YouTube video IDs alongside the corresponding annotations. It further contains 503 logo template files and the corresponding metadata information (channel name, wikipedia link). See the README file for details.</p> <p>This is the second version of the dataset, including various corrections in annotation.</p>
VRTogether Pilot 2 TV Set Geommetry Unity package
<p>Unity package containing the TV set scene where all the pilot 2 happens.</p>
Text-fig. 15. Scanning electron microscope (SEM) images of seeds of Pazliopsis reyi (a–c) and Anaspermum operculatum gen. et sp. nov. (d–j). a) Seed in lateral view showing poorly preserved remains of fruit wall and rough surface of the exotesta; b) Section through the wall of a broken seed showing palisade cells of the exotesta; c) Seed surface showing sunken very deeply sinuous outlines of the exotesta cells; d–f, h, i) Seeds in lateral view (holotype figured in d) showing the pointed micropylar-hilar area, the rounded chalazal end, the smooth surface of the exotesta composed of cells with sinuous cell outlines, and the distinct course of the raphe; g) Surface of the exotesta showing the distinctive cell outlines formed by the sinuous anticlinal walls of the palisade cells; j) Apical view of seed showing the prominent operculum. Specimens, TV43-S171534 (a), TV44-S136683 (b), TV43-S136745 (c), TV43-S136740 (holotype; d), TV43-S136746 (e), TV43-S136739 (f), TV43-S170083 (g), TV S136743 (h), TV43-S136742 (i), TV38-S174608 (j). Scale bars 300 Μm (a, b, d–f, h, i), 50 Μm (j), 30 Μm (c, g). in The Early Cretaceous Mesofossil Flora Of Torres Vedras (Ne Of Forte Da Forca), Portugal: A Palaeofloristic Analysis Of An Early Angiosperm Community
Text-fig. 15. Scanning electron microscope (SEM) images of seeds of Pazliopsis reyi (a–c) and Anaspermum operculatum gen. et sp. nov. (d–j). a) Seed in lateral view showing poorly preserved remains of fruit wall and rough surface of the exotesta; b) Section through the wall of a broken seed showing palisade cells of the exotesta; c) Seed surface showing sunken very deeply sinuous outlines of the exotesta cells; d–f, h, i) Seeds in lateral view (holotype figured in d) showing the pointed micropylar-hilar area, the rounded chalazal end, the smooth surface of the exotesta composed of cells with sinuous cell outlines, and the distinct course of the raphe; g) Surface of the exotesta showing the distinctive cell outlines formed by the sinuous anticlinal walls of the palisade cells; j) Apical view of seed showing the prominent operculum. Specimens, TV43-S171534 (a), TV44-S136683 (b), TV43-S136745 (c), TV43-S136740 (holotype; d), TV43-S136746 (e), TV43-S136739 (f), TV43-S170083 (g), TV S136743 (h), TV43-S136742 (i), TV38-S174608 (j). Scale bars 300 Μm (a, b, d–f, h, i), 50 Μm (j), 30 Μm (c, g).
A Randomized, Double-Blind, Placebo-Controlled Study With an Open-Label, Long-Term Safety Phase to Evaluate the Efficacy and Safety of TV-44749 in Adults With Schizophrenia
ClinicalTrials.gov study NCT05693935. IPD Sharing: YES. Countries: 5. Publications: 2.
Study to Evaluate TV-46000 as Maintenance Treatment in Adult and Adolescent Participants With Schizophrenia
ClinicalTrials.gov study NCT03503318. IPD Sharing: YES. Countries: 2. Publications: 3.
A Study to Test if TV-46000 is Safe for Maintenance Treatment of Schizophrenia
ClinicalTrials.gov study NCT03893825. IPD Sharing: YES. Countries: 5. Publications: 3.
The use of TV remote control by older adults
<p>Table created with data obtained from a systematic review of articles, which address The use of TV remote control by older adults.</p>
TV led
Televicion led decorativa pero con opcion de textura para pantalla Source: Objaverse 1.0 / Sketchfab
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.