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3,822 results for “Japanese”
Impacts of Land Use on Japanese Barberry Invasion in Central Massachusetts 2005
Despite the recognized importance of historical factors in controlling many native species distributions, few studies have incorporated historical landscape changes into models of invasive species distribution and abundance. We explore the possibility that the current distribution of invasive species may reflect legacies of historical land use despite nearly a century of forest succession and subsequent disturbances. We evaluated the modern distribution and abundance of Berberis thunbergii DC. (Japanese barberry), a problematic non-native shrub in forests of the northeastern U.S., relative to two distinct periods of historical land use, modern forest harvesting activity, and environmental and edaphic characteristics. Species questions addressed in this study include: (1) Do patterns of historical land use influence modern barberry distribution and abundance? (2) What is the influence of disturbance type and timing relative to the timing of introduction on current barberry distribution and abundance? (3) Which disturbance, environmental and edaphic variables best predict modern barberry distribution and abundance? Japanese barberry occurred more frequently and was more abundant in sites historically cleared for agriculture than in historically wooded sites. This relationship was strongest for areas in agriculture in the early 20th century after barberry was introduced to the region. The strong relationship between modern distribution patterns and prior land use suggests historical colonization of abandoned agricultural lands and persistence through subsequent reforestation. Contrary to our expectations, recent forest harvesting did not influence the occurrence or abundance of barberry. Our results indicate that interpretations of both native community composition and modern plant invasions must consider the importance of historical landscape changes and the timing of species introduction along with current environmental and edaphic conditions.
Japanese "Olympic" and "Suga" Tweets from 2021-07-01 to 2021-09-02
<p><strong>Abstract</strong> (our paper)</p> <p>The Olympic Games are a typical media event and are seen as a festive occasion that monopolizes people’s attention through the mass media. The Games and their media coverage have a predetermined schedule that enhances the nation’s sense of unity by placing a temporary truce on political conflicts. Governments, especially those of Olympic host countries, tend to take advantage of this effect to garner support for their own policies. However, the effects of such media events may be weakening owing to changes in the media environment and increasing political polarization. Examining the 2020 Tokyo Olympic Games, this case study analyzes a large amount of Twitter data to probe Japanese social media users’ attitudes toward the Olympic Games and the relationship of these attitudinal changes with their attitudes toward the political leadership of the prime minister. The results showed that previously negative attitudes toward the Olympic Games improved as people enjoyed the event. However, this positive shift did not appear to be associated with their attitudes toward the prime minister. Users’ political predispositions strongly determined their attitudes toward the Olympic Games, indicating that the Olympic Games as a media event had limited implications for support for the administration.</p> <p><strong>Data</strong></p> <p>olympic.tsv.gz, suga.tsv.gz:<br> The first column is the tweet id, the second column is the tweet id of the retweet source, and the third column is the date and time (JST) when the tweet was posted.<br> This data was collected by giving the query "オリンピック OR パラリンピック OR 五輪 OR 聖火 OR オリパラ" or "スガ OR 菅 OR 総理 OR 首相" to the Twitter Search API. Therefore, most of the tweets are Japanese tweets. The second column is empty if the tweet is not a retweet.</p> <p><strong>Publication</strong></p> <p>This data set was created for our study. If you make use of this data set, please cite:<br> Takeshi Sakaki, Tetsuro Kobayashi, Mitsuo Yoshida, Fujio Toriumi. Do media events still unite the host nation’s citizens? The case of the Tokyo 2020 Olympic Games. <em>PLOS ONE</em>. vol.17, no.12, e0278911, 2022.<br> <a href="https://doi.org/10.1371/journal.pone.0278911">https://doi.org/10.1371/journal.pone.0278911</a></p>
Hydrological, physicochemical and metabolic activity data for streams in the Japanese Alps
<p>A series of files with hydrological, physicochemical and metabolic activity data from a study investigating the environmental dynamics of six stream systems in the Japanese Alps.</p>
Japanese "Abe" Tweets from 2019-02-10 to 2020-10-07 (15,407,811 tweets and 114,231,250 retweets)
<p><strong>Abstract</strong> (our paper)</p> <p>To examine conservative–liberal differences in the extent to which partisan tweets reach less partisan moderate users in a nonwestern context, we analyzed a network of retweets about former Japanese Prime Minister Shinzo Abe. The analyses consistently demonstrated that partisan tweets originating from the conservative cluster reach a wider range of moderate users than those from the liberal cluster. Network analyses revealed that while the conservative and the liberal clusters’ internal structures were similar, the conservative cluster reciprocated the follows from moderate accounts at a higher rate than the liberal cluster. In addition, moderate accounts reciprocated the conservative cluster’s following at a higher rate than they did for the liberal cluster. The analysis of tweet content showed no difference in the frequency of hashtag use between conservatives and liberals, but there were differences in the use of emotion words and linguistic expressions. In particular, emotion words related to the propagation of messages, such as those expressing “dislike”, were used more frequently by conservatives, while the use of adjectives by conservatives was closer to that of moderate users, indicating that conservative tweets are more palatable for moderate users than liberal tweets.</p> <p><strong>Data</strong></p> <p>Abe.tsv.gz:<br> The first column is the tweet id, the second column is the tweet id of the retweet source, and the third column is the date and time (JST) when the tweet was posted.<br> This data was collected by giving the query "安倍 OR アベ" to the Twitter Search API. Therefore, most of the tweets are Japanese tweets. The second column is empty if the tweet is not a retweet.</p> <p><strong>Publication</strong></p> <p>This data set was created for our study. If you make use of this data set, please cite:<br> Mitsuo Yoshida, Takeshi Sakaki, Tetsuro Kobayashi, Fujio Toriumi. Japanese conservative messages propagate to moderate users better than their liberal counterparts on Twitter. <em>Scientific Reports</em>. vol.11, article no.19224, 2021.<br> <a href="https://doi.org/10.1038/s41598-021-98349-2">https://doi.org/10.1038/s41598-021-98349-2</a></p>
Japanese Trend Queries and Its' Web Trends
<p><strong>Abstract</strong> (our paper)</p> <p>Many researchers work on studies for discovering trend keywords and queries on the web, i.e., search frequency and social media. Moreover, studies on trend query classifications are being conducted. However, the behavior of trend queries for various web resources is unclear. In this study, we investigate how trend queries appear in different resources on the web. We clarify the following. (1) Most trend queries are not registered with online dictionary services. (2) The trend converges in approximately two days. (3) Social media websites (such as Twitter) are responsive to trend queries.</p> <p><strong>Data</strong></p> <p><strong>Publication</strong></p> <p>This data set was created for our study. If you make use of this data set, please cite:<br /> Mitsuo Yoshida, Yuki Arase. Trend Query Analysis on Heterogeneous Web Resources. <em>IPSJ Transactions on Databases (in Japanese)</em>. vol.9, no.1, pp.20-30, 2016.</p>
Wikipedia Page Views of Japanese Comic
<p><strong>Abstract</strong> (our paper)</p> <p>This paper investigates the page view and interlanguage link at Wikipedia for Japanese comic analysis. This paper is based on a preliminary investigation, and obtained three results, but the analysis is insufficient to use the results for a market research immediately. I am looking for research collaborators in order to conduct a more detailed analysis.</p> <p><strong>Data</strong></p> <p><strong>Publication</strong></p> <p>This data set was created for our study. If you make use of this data set, please cite:<br> Mitsuo Yoshida. Preliminary Investigation for Japanese Comic Analysis using Wikipedia. <em>Proceedings of the Fifth Asian Conference on Information Systems (ACIS 2016)</em>. pp.229-230, 2016.</p>
The Audio and Video Files of Handbook of Japanese Basic Verbs
<p>"KIHONDOUSHI HANDBOOK (Handbook of Japanese Basic Verbs) [基本動詞ハンドブッ ク] is a digital reference resource developed by the members of three collaborative research projects funded by the National Institute for Japanese Language and Linguistics (NINJAL), Tokyo, Japan during Oct. 2009 to March 2022. The reference work was developed with an aim to deepen the understanding of highly polysemous basic verbs in Japanese by way of providing detailed description of syntax and semantics of multiple meanings of the verb in question. To foster the ease of understanding, each meaning of a polysemous basic verb is illustrated with a couple of illustrative examples with audio and a few meanings, which are deemed to be difficult to understand, are illustrated with the help of audio-visual animations. The handbook consists of 190 headwords and includes 2,154 meanings, 12, 492 illustrative examples with audio and 521 audio-visual animations. On this site the audio and video files of the handbook is made available for researchers, teachers, and learners of Japanese language for the purpose of research on and education of Japanese polysemous basic verbs. Other data such as headword data will be available from the NINJAL repository site very soon.</p>
Japanese Vowels
<p>This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers. The dataset consists of multivariate time series (12 variables) of length 29 time steps. Each time series is associated with a class (1-9) indicating the speaker. The dataset consists of 270 time series used for training and 370 for testing.</p> <p>This is a pre-processed version saved in numpy format. The original Japanese Vowels dataset and additional information can be found on <a href="https://archive.ics.uci.edu/dataset/128/japanese+vowels">UCI</a>.</p> <p>The data are 3-dimensional arrays of shape [n_samples, time_steps, n_variables]. The data can be loaded as follows:</p> <pre><code>loaded_data = np.load("Japanese_Vowels.npz") Xtr = loaded_data['Xtr'] # Training data of shape (270, 29, 12) Ytr = loaded_data['Ytr'] # Training labels of shape (270, 1) Xte = loaded_data['Xte'] # Test data of shape (370, 29, 12) Yte = loaded_data['Yte'] # Test labels of shape (370, 1)</code></pre>
Bag of pitch classes for Japanese enka songs
<p>This dataset is comprised of 827 songs, curated from the following publications:</p> <p>(a) Y. Goto (ed.), Grand Collection of Enka Songs by Female Singers 5th Ed. (in Japanese), Zen-on Music Co., 2016.<br> (b) Y. Goto (ed.), Grand Collection of Enka Songs by Male Singers 5th Ed. (in Japanese), Zen-on Music Co., 2016.</p> <p>Upon the use of this work, we kindly ask to explicitly cite/mention this paper, where the dataset was first used:</p> <p>[1] Eita Nakamura, Kentaro Shibata, Ryo Nishikimi, Kazuyoshi Yoshii, “Unsupervised melody style conversion,” Proc. 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 196-200, May 2019.</p> <p>** Data **</p> <p>EnkaDataBagOfPitchClasses.tsv</p> <p>Each line represents a song.</p> <p>The first column indicates the song's location in the publications. For example, EnkaF-030_p027 indicates the 30th song on page 27 by a female artist in (a).</p> <p>From the second column to the 13th column, the numbers represent the counts for pitch classes from C to B. Tied notes were merged and counted only once.</p>
Waveform data for centroid moment tensor solutions presented in publication "Bayesian seismic source inversion with a 3-D Earth model of the Japanese islands"
<p>The dataset includes waveform data for centroid moment tensor solutions inferred using Hamiltonian Monte Carlo and a 3-D Earth model in the Japanese islands. The data are provided as Green's strains at the maximum-likelihood location (indicated in the title of each text file) for all study events inverted at different periods. Inversion period is also indicated in the title. All the data are filtered between 15 s and 80 s. Additionally we provide a Python code to obtain displacement from strains given a moment tensor.</p>
CLDF Dataset derived from Hattori's "Japanese Dialects" from 1973
<p>Cite the source of the dataset as:</p> <blockquote> <p>Hattori, S. (1973): Japanese dialects. In: Diachronic, areal and typological linguistics. Edited by H. M. Hoenigswald and R. H. Langacre. 368-400.</p> </blockquote>
Hachidaishu Classical Japanese Poetic Vocabulary Dataset
<h1>Hachidaishu classical Japanese poetic vocabulary dataset</h1> <h2>Hilofumi Yamamoto, Ph.D. (Institute of Science Tokyo)</h2> <h2>Bor Hodošček, D.Engineering (The University of Osaka)</h2> <h3>Data offset</h3> <p>Example: # 1 Kokinshu</p> <pre><code>01:000001:0001 A00 BG-01-1630-01-0100 02 年 年 とし 年 とし 01:000001:0001 A10 BG-01-1911-03-1800 02 年 年 とし 年 とし 01:000001:0002 A00 BG-08-0061-07-0100 61 の の の の の 01:000001:0003 A00 BG-01-1770-01-0300 02 内 内 うち 内 うち 01:000001:0004 A00 BG-08-0061-05-0100 61 に に に に に 01:000001:0005 A00 BG-01-1624-02-0100 02 春 春 はる 春 はる 01:000001:0006 A00 BG-08-0065-07-0100 65 は は は は は 01:000001:0007 A00 BG-02-1527-01-0102 47 き 来 く 来 き 01:000001:0008 A00 BG-03-1200-02-0900 74 に ぬ ぬ に に 01:000001:0008 A10 BG-09-0010-01-0101 74 に ぬ ぬ に に 01:000001:0008 A20 BG-09-0010-03-0200 74 に ぬ ぬ に に 01:000001:0009 A00 BG-09-0010-04-0300 74 けり けり けり けり けり 01:000001:0010 B00 BG-01-1950-14-0100 02 一とせ 一年 ひととせ 一年 ひととせ 01:000001:0010 C00 BG-01-1950-01-0300 19 一 一 いち 一 いち 01:000001:0010 C01 BG-01-1630-01-0100 02 年 年 とし 年 とし 01:000001:0011 A00 BG-08-0061-10-0100 61 を を を を を 01:000001:0012 A00 BG-01-1642-02-0100 02 こそ 去年 こぞ 去年 こぞ 01:000001:0013 A00 BG-08-0061-04-0100 61 と と と と と 01:000001:0014 A00 BG-08-0065-14-0100 65 や や や や や 01:000001:0015 A00 BG-02-3120-01-0100 47 いは 言ふ いふ 言は いは 01:000001:0016 A00 BG-03-3012-03-2600 74 ん む む む む 01:000001:0016 A10 BG-09-0010-02-0102 74 ん む む む む 01:000001:0017 B00 BG-01-1641-02-0100 02 ことし 今年 ことし 今年 ことし 01:000001:0017 C00 BG-03-1000-01-0100 57 この この この この この 01:000001:0017 C01 BG-01-1630-01-0100 02 年 年 とし 年 とし 01:000001:0018 A00 BG-08-0061-04-0100 61 と と と と と 01:000001:0019 A00 BG-08-0065-14-0100 65 や や や や や 01:000001:0020 A00 BG-02-3120-01-0100 47 いは 言ふ いふ 言は いは 01:000001:0021 A00 BG-03-3012-03-2600 74 ん む む む む 01:000001:0021 A10 BG-09-0010-02-0102 74 ん む む む む </code></pre> <h3>A line consists of 7 columns separated by spaces.</h3> <pre><code>01:000001:0007 A00 BG-02-1527-01-0102 47 き 来 く 来 き </code></pre> <ul> <li>1st column "01:000001:0007" consists of 3 fields: 1) anthology, 2) number of poem, and 3) serial ID of the token. The anthology ID indicates respectively: 01..Kokinshu, 02..Gosenshu, 03..Shuishu, 04..Goshuishu, 05..Kin'yoshu, 06..Shikashu, 07..Senzaishu, and 08..Shinkokinshu.</li> <li>2nd column indicates type of token: A type is a single token; B type is a compound token; C type is a breakdown of B type. A00 indicates a single token; A01 indicates a single token and has another meaning; B00 indicates a compound token; B01 indicates a compound token which has another meaning; C00 indicates the first element of the B00/B01.. breakdown; C01 indicates the second element of the B00/B01.. breakdown.</li> <li>3rd column "BG-02-1527-01-0102": classification ID based on semantic categories according to Bunruigoihyo (Yamazaki et al. 2014).</li> <li>4th column indicates a Chasen POS number.</li> <li>5th column indicates surface form: a form appears in literary works.</li> <li>6th column indicates lemma in kanji writing.</li> <li>7th column indicates lemma in kana writing.</li> <li>8th column indicates conjugated form in kanji writing form.</li> <li>9th column indicates conjugated form in kana writing form.</li> </ul> <h2>Reference</h2> <ol> <li> <p>Yamamoto, Hilofumi (2007) Thesaurus of Japanese Poetic Vocabulary Based on the Semantic Classifications Chart, The 13th Annual Symposium for Database of the Humanities, 1-8, The Association for Database of the Humanities, Osaka.</p> </li> <li> <p>Yamamoto, Hilofumi (2009) Thesaurus for the Hachidaishu (ca. 905-1205) with the classification codes based on semantic principles, Nihongo no Kenkyu / Studies in the Japanese Language, 46-52, Society for Japanese Linguistics, 5, 1, ISSN1349-5119.</p> </li> <li> <p>Yamamoto, Hilofumi (2021) Hachidaishu vocabulary dataset, Zenodo, version 1.0.1, <a href="https://doi.org/10.5281/zenodo.4744170">https://doi.org/10.5281/zenodo.4744170</a></p> </li> <li> <p>Yamazaki, Makoto and Kashino, Wakako and Uchiyama, Kiyoko and Sunaoka, Kazuko, and Tajima, Ikudo and Yamamoto, Hilofumi and Han, Yoo-Sik and Seol, Geun-Su (2014) Bunruigoihyo zouhokaiteiban" e no anoteishion: kihongi no kettei (in Japanese), Keiryo Kokugo gakkai dai 58 kai taikai yokoshu, pp. 7--12.</p> </li> <li> <p><a href="http://kotenseki.nijl.ac.jp/biblio/200007092">国文学研究資料館二十一代集</a></p> </li> <li> <p><a href="http://codh.rois.ac.jp/pmjt/book/200007092/">二十一代集 DOI: 10.20730/200007092</a>: ROIS-DS人文学オープンデータ共同利用センター 新日本古典籍総合データベース(200007093)</p> </li> </ol> <p><!-- @dataset{yamamoto_hilofumi_2021_4735848, author = {Yamamoto, Hilofumi}, title = {Hachidaishu vocabulary dataset}, month = may, year = 2021, publisher = {Zenodo}, version = {1.0.0}, doi = {10.5281/zenodo.4735848}, url = {https://doi.org/10.5281/zenodo.4735848} } @Article{yamagen2009ae, author = {Yamamoto, Hilofumi}, title = {Thesaurus for the Hachidaishu (ca.\,905--1205) with the classification codes based on semantic principles}, journal = {Nihongo no Kenkyu / {S}tudies in the Japanese Language}, pages = {46--52}, OPTpublisher = {Society for Japanese Linguistics}, year = {2009}, volume = {5}, number = {1}, OPTedition = {ISSN1349-5119}, OPTmonth = {}, OPTnote = {}, OPTannote = {}, OPTlocation = {}, OPTmemo = {} } @InCollection{yamagen2007de, author = {Yamamoto, Hilofumi}, title = {Thesaurus of Japanese Poetic Vocabulary Based on the Semantic Classifications Chart}, year = {2007}, booktitle = {The 13th Annual Symposium for Database of the Humanities}, pages = {1--8}, publisher = {The Association for Database of the Humanities}, address = {Osaka}, OPTedition = {}, OPTmonth = {2007.12}, OPTmemo = {} }</p>
Wikipedia: wikipedia-ja (Japanese)
Wikipedia is a multilingual, web-based, free-content encyclopedia project supported by the Wikimedia Foundation and based on a model of openly editable content. EOL harvests articles from wikipedia that are indexed as species or higher taxa.<p></p>
Japanese Expressions Dataset from Human Rights Infringement on Internet
<p>Japanese Expressions Dataset from Human Rights Infringement on Internet</p> <p>これは、言語処理学会2023において”<a href="https://www.anlp.jp/proceedings/annual_meeting/2023/pdf_dir/D2-2.pdf"><strong>権利侵害と不快さの間:日本語人権侵害表現データセット</strong></a>”の発表で用いた、誹謗中傷等の表現を集めたデータセットです。</p> <p>仕様は変更される可能性があります</p> <p>Release Date</p> <p>Version 0.1 2023/03/09</p> <p>Version 0.2 2023/06/01</p> <p> </p> <p>1.調査対象</p> <p>民事事件</p> <ul> <li>発信者情報開示請求事件</li> <li>損害賠償等請求事件</li> </ul> <p>インターネット上の投稿による人権侵害を争った事件よりこのデータセットは作成されています。</p> <p>Annotation Scheme</p> <p>1: Text in Dispute </p> <p>Text in Dispute is transcribed from the list of articles submitted or the facts and reasons section of the court cases.<br> This text is what the plaintiff alleges is infringing his or her rights.<br> <br> For example, we use the tag [Plaintiff] for descriptions related to plaintiffs, the tag [Defandant] for descriptions related to defandantss and [Third Party] for any mention of third parties.<br> The tag [Other] is designated for texts involving anonymized place names and any other content not covered by the preceding tags. <br> If distinguishing between tags proves challenging, we advise the use of [Other]. <br> Should a URL be present in the text, it is substituted with the [URL] tag.</p> <p>2: Context Utilized in Adjudication</p> <p>In some cases, the history of the conversation and previous postings are taken into account in determining whether or not an infringement has occurred.<br> Such text is transcribed from the fact-finding and judgment portions of the court case.<br> Contextual information that can be used for tasks other than proper understanding of the issue and accurate learning and classification.<br> Anonymization is applied in the same way as for [1: Text in Dispute].</p> <p>3: Allegedly Infringed Right and Judgement on the Infringement Allegation</p> <p>This category provides a label indicating the types of personal rights infringement complained of by the plaintiff against Text in Dispute and whether or not the infringement of that right was recognized by the trial court.<br> If there are more than two types of infringement of rights complained of by the plaintiff against one text, up to two labels are given.</p> <p>3-1a: The types of Allegedly Infringed Right 1</p> <p>Labels are assigned from the above types of personal rights, the right of reputation, the sense of honor, the right of peaceful private life, and other personal rights, from the complaint of infringement of rights by the plaintiff.</p> <p>3-1b: Judgement on the Infringement Allegation 1</p> <p>This category indicates whether the trial court granted the plaintiff's complaint against the text under consideration.<br> The annotator reads the result of the Judgement for each case from the court's judgment in the case.<br> If we find that the court has admitted the plaintiff's claim, we assign "1" label to the case concerning the infringement of personal rights.<br> If we find that the court has dismissed the plaintiff's claim, we assign "0" label to those cases that are not infringing.<br> We assign the label "UNJUDGE" to cases where we cannot find the court's Judgement. <br> This appears in cases where the plaintiff alleges multiple infringements and only one of the claims is adjudicated, or where the complaint is found to have been dismissed based on factors other than a determination of infringement by textual expression.</p> <p>3-2a & b:The types of Allegedly Infringed Right and Judgement on the Infringement Allegation 2</p> <p>If two infringements are complained of, the annotator assigns a label for the second right.</p> <p><br> 4: Index Information of Court Cases</p> <p>This section contains information about the cited court case.</p> <p>4-1: Case Number</p> <p>This is the case number of the court case and the court in which the case was argued.</p> <p>4-2: Case Name</p> <p>This is the case name of the court case and the court in which the case was argued.<br> Either a case requesting for disclosure of sender's information. or a case requesting compensation for damages is applicable.</p> <p>4-3: Bibliography</p> <p>This is the bibliography of the cited case.</p> <p>4-4: Article Number</p> <p>This is the number assigned to Text in Dispute in the court case.</p> <p>4-5: Online Platform</p> <p>If the online platform where Text in Dispute is explicitly indicated in the court case, it is stated.<br> Since the form of the text and context differs from platform to platform, considering the uniqueness of each service is an important factor to be taken into account.</p>
Fig. 1 in Amage imajimai sp. nov., a new species of Ampharetidae (Annelida: Polychaeta) from Japanese waters
Fig. 1. Amage imajimai sp. nov. A. Anterior end of holotype, dorsal view. B. "ID card". C. Anterior end of holotype, lateral view. D. Thoracic uncinus, lateral view. E. Thoracic uncinus, frontal view. F. Abdominal uncinigers, lateral view (from paratype SMF 24086). G. Posteriormost abdominal uncinigers and pygidium, ventral view (from paratype SMF 24086).
Fig. 11 in Diversity and distribution of adeonid bryozoans (Cheilostomata: Adeonidae) in Japanese waters
Fig. 11. Adeonellopsis pentapora Canu & Bassler, 1929. A. Left, colony in Döderlein Collection (MZS 2-1); right, colony collected by NSMT (NSMT-TeS22). B. Colony on hydroid stalk, from Sagami Bay (NSMT-TeS20). C. Distal end of branch showing young autozooids with multiporous, denticulate spiramen (NSMT-Te761). D. Young autozooids with umbonate processes on frontal shield (NSMT- Te764). E. Mature autozooids with small suboral and other frontal avicularia (NSMT-Te761). F. Old autozooids, showing deeply immersed spiramen and orifices (NSMT-Te762). A–B = optical photographs; C–F = SEM images. Scale bars: A = 3 mm; B = 2 mm; C–D, F = 200 μm; E = 250 μm.
Fig. 8 in Diversity and distribution of adeonid bryozoans (Cheilostomata: Adeonidae) in Japanese waters
Fig. 8. Adeonellopsis japonica (Ortmann, 1890). A. Distal end of branch just starting to bifurcate, showing young autozooids and gonozooids (NSMT-BryR277). B. Enlargement of young gonozooids, showing peripheral rim with rows of granulation perpendicular to margin, and large multiporous spiramen (NSMT-BryR277). C. Autozooids in middle of branch, showing immersed spiramen (NSMT- Bry R 193). D. Basal part of branch, showing autozooids, and some kenozooids with closed orifice (NSMT-BryR36). E. Young gonozooids, showing distinct marginal pores and multiporous spiramen (NSMT-Te758). F. Distal end of branch, showing autozooid formation (NSMT-Te758). SEM images. Scale bars: A, C = 1 mm, B, D–E = 300 μm; F = 500 μm.
Fig. 4 in Diversity and distribution of adeonid bryozoans (Cheilostomata: Adeonidae) in Japanese waters
Fig. 4. Adeonella jahanai sp. nov. A. Holotype colony with narrow branches (NSMT-Te1050, Okinawa). B. Young autozooids at distal end of branch, showing primary orifices NSMT-Te889. C. Autozooids with elongate frontal avicularia (NSMT-Te889, Okinawa). D. Young autozooids with a single triangular avicularium abutting the proximal margin of the peristome (NSMT-Te889, Okinawa). A = optical photograph; B–D = SEM images. Scale bars: A = 1 cm; B–D = 100 μm.
Fig. 10. Interior frontal shield. A in Diversity and distribution of adeonid bryozoans (Cheilostomata: Adeonidae) in Japanese waters
Fig. 10. Interior frontal shield. A. Adeonellopsis japonica (Ortmann, 1890) (NSMT-Te1052). B. A. parvirostrum sp. nov. (NSMT-Te807). Arrowheads indicate ring scar. SEM images. Scale bars: A = 50 μm; B = 25 μm.
Fig. 6 in Diversity and distribution of adeonid bryozoans (Cheilostomata: Adeonidae) in Japanese waters
Fig. 6. Adeonellopsis arculifera (Canu & Bassler, 1929). A. Colonies collected SW of Yakushima Island (NSMT-Te789). B. Branch showing crenulate periphery (NSMT-Te781). C. Enlargement of bifurcation showing autozooids with oblique avicularium and single small spiramen (NSMT-Te781). D. Young autozooids showing peristomial rim and single small spiramen (NSMT-Te781). E. Old part of branch, showing various stages in formation of kenozooids (NSMT-Te781). F. Old part of branch, showing autozooids with depression containing avicularium and spiramen (NSMT-Te781). A = optical photograph; B–F = SEM images. Scale bars: A = 5 mm; B = 1 mm; C–D = 300 μm; E = 500 μm; F = 250 μm.
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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.