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493 results for “Iris”
Fig. 3. Iris tricolor Werner, 1923. a–c in An annotated type catalogue of praying mantises (Mantodea) in the Zoological Museum Hamburg (ZMH)
Fig. 3. Iris tricolor Werner, 1923. a–c. Holotype, ♀ (ZMH 841116). a. Labels. b. Dorsal view. c. Ventral view. d–f. Paratype, ♀ (ZMH 76962). d. Labels. e. Dorsal view. f. Ventral view. Scale bars = 10 mm.
Figures 1–2 in First record of Conognatha iris iris Olivier (Coleoptera: Buprestidae) for Venezuela
Figures 1–2. Conognatha (Conognatha) iris iris Olivier. 1) Specimen from Venezuela, habitus, dorsal view. Scale bar: 10 mm. 2) Distribution map. The question marks indicate imprecise location records in Guyana and Suriname.
IRIS DOD-SBIR database
<p>This database collects and links U.S. federal funded awards to U.S. utility patents, and such patents to virtual patent marking (VPM) pages, in line with two related project: 3PFL and IPRoduct. Specifically, this database looks at awards provided by the U.S. Department of Defense (DOD) within the Small Business Innovation Research (SBIR) and Small Business Technology Transfer Program (STTR) programs from 1984 to 2018.</p> <p>The database is part of a project, IRIS - Insights on the "Real" Impact of Science. The project aims at assessing how public investment in research and development (R&D) translates into commercial products for the final consumer.</p> <p>The database is composed of three main elements: awards; patents; and web pages. The database provides several information pieces. This has been possible by making use of several sources, that has been properly combined and further elaborated in a convenient way. Information about the awards comes from the Defense Contract Action Data System (DCADS), for the years 1984--2001, and from USAspending.gov, for the years 2001--2018. Most information about the patents is provided by PatentsView, while specific information comes from the Patent Examination Research Dataset (PatEx) or from PATSTAT.</p>
About Iris
<p>‘About Iris’ introduces the ancient Greek goddess, Iris. The ancient Greeks said that rainbows were caused by Iris streaking across the sky, leaving rainbows in her wake as she travelled to bring messages from one god to another, or from gods to mortals. This short documentary discusses how you can recognise Iris in ancient images, her appearances in the Trojan War, and ancient and modern ideas about the causes of rainbows.</p> <p>‘About Iris’ is a companion video for the Our Mythical Childhood animation 'Iris – Rainbow Goddess', which was created from a vase that was made in ancient Athens and is now housed in the National Museum in Warsaw, in Poland (number 142289).</p> <p>Subtitles are available for this video on YouTube: <a href="https://youtu.be/qHmFF5qgoc0">https://youtu.be/qHmFF5qgoc0</a></p>
Evolutionary insights into Felidae iris color through ancestral state reconstruction
<p>There have been almost no studies with an evolutionary perspective on eye (iris) color, outside of humans and domesticated animals. Extant members of the family Felidae have a great interspecific and intraspecific diversity of eye colors, in stark contrast to their closest relatives, all of which have only brown eyes. This makes the felids a great model to investigate the evolution of eye color in natural populations. Through machine learning cluster image analysis of publicly available photographs of all felid species, as well as a number of subspecies, five felid eye colors were identified: brown, hazel/green, yellow/beige, gray, and blue. Using phylogenetic comparative methods, the presence or absence of these colors was reconstructed on a phylogeny. Additionally, through a new color analysis method, the specific shades of the ancestors' eyes were quantitatively reconstructed. The ancestral felid population was predicted to have brown-eyed individuals, as well as a novel evolution of gray-eyed individuals, the latter being a key innovation that allowed the rapid diversification of eye color seen in modern felids, including numerous gains and losses of different eye colors. It was also found that the loss of brown eyes and the gain of yellow/beige eyes is associated with an increase in the likelihood of evolving round pupils, which in turn influence the shades present in the eyes. Along with these important insights, the unique methods presented in this work are widely applicable and will facilitate future research into phylogenetic reconstruction of color beyond irises.</p>
GMBAMU-IRIS DATASET
<p>The I Scan 2 scanner from Cross-Match Technologies was used to acquire all data. Iris images are captured in near-infrared wavelength band (700-900 nm) of the electromagnetic spectrum. All images were acquired in SAP laboratory of computer science and engineering department of Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. The subject images were acquired during the span of 7 to 8 months in years 2017 and 2018.</p> <p>GMBAMU-IRIS database contains total 5616 images from 312 subjects. This</p> <p>dataset contains left and right iris images (minimum 10 to maximum 20 images) per subject.</p> <p>Out of total 312 subjects, genders of 39 subjects were not noted at the time of the acquisition process, but all these 39 subjects have age range from 21 -30 years. All 312 subjects in the database are in the age-group 3-75 years.</p>
Figures 10–13 in A gynandromorph of Xylocopa augusti and an unusual record of X. iris from Brazil (Hymenoptera: Apidae: Xylocopini)
Figures 10–13. Female specimen of Xylocopa (Copoxyla) iris (Christ) possibly collected in Brazil. 10. Facial view. 11. Metasoma, dorsal view. 12. Detail of T2 and T3 showing gradulus. 13. Pygidial plate of T6. Scale: 2 mm.
Figure 9 in A gynandromorph of Xylocopa augusti and an unusual record of X. iris from Brazil (Hymenoptera: Apidae: Xylocopini)
Figure 9. Dorsal habitus and labels of female specimen of Xylocopa (Copoxyla) iris (Christ) possibly collected in Brazil. Scale: 2 mm.
Figures 5–8 in A gynandromorph of Xylocopa augusti and an unusual record of X. iris from Brazil (Hymenoptera: Apidae: Xylocopini)
Figures 5–8. Gynandromorph of Xylocopa (Neoxylocopa) augusti Lepeletier de Saint Fargeau. 5. Metasomal S6, ventral view. 6. Metasomal T7, dorsal view. 7. Genitalia, posterior view. 8. Genitalia, dorsal view. Scale bars: 2 mm in figures 5 and 6, 1 mm in figures 7 and 8.
Figures 1–4 in A gynandromorph of Xylocopa augusti and an unusual record of X. iris from Brazil (Hymenoptera: Apidae: Xylocopini)
Figures 1–4. Gynandromorph of Xylocopa (Neoxylocopa) augusti Lepeletier de Saint Fargeau. 1. Facial view. 2. Lateral habitus. 3. Dorsal habitus. 4. Ventral habitus. Scale bars: 2 mm in figure 1, 4 mm in remaining figures.
Graphic representation of data set for the project "IRI model performance evaluation for the Mexican region"
<p>Here, we illustrate the modeling and experimental results for vertical Total Electron Content (TEC) over Mexico during the five year period 2018-2022. The results were obtained for the UCOE GNSS receiver station (geographic coordinates: 19.6°N; 101.68°W ). The calculations were made each two hours during the whole period under considerations. The modeling results were obtained using the "International Reference Ionosphere (IRI)" model, which is an empirical climatological model based on ground and space observations of the ionosphere [Bilitza et al., 2022].</p>
Geographic and temporal morphological stasis in the latest Cretaceous ammonoid Discoscaphites iris from the U.S. Gulf and Atlantic Coastal Plains
Open the record for dataset details and reuse information.
Evolutionary insights into Felidae iris color through ancestral state reconstruction
Open the record for dataset details and reuse information.
Measurement of ocular counter-roll using iris images during binocular fixation and head tilt
<p>All images and datas used in the study "Measurement of ocular counter-roll using iris images during binocular fixation and head tilt"</p>
Data from: Sectional relationships in the Eurasian bearded iris (subgen. Iris) based on phylogenetic analyses of sequence data
Subgenus Iris is wholly Eurasian, distributed in temperate regions from northeastern China to eastern and southern Europe where they occur in mountainous and/or dry rocky sites from near sea level to elevations of 4,500 m. These species have an easily discerned synapomorphy, a multicellular beard on each petaloid sepal. Currently two large and relatively well known and four smaller and less known sections are recognized in the subgenus. This study investigated the monophyly of circumscribed sections and relationships among these sections. Seventy-one taxa, representing each of the six sections and about 80% of the recognized species in subgen. Iris, and 11 outgroup taxa were included in the study. Also included were five Asian species that share some morphological characteristics with subgen. Iris but are typically considered in other subgenera. Phylogenetic analyses of sequence data recovered six major clades but sects. Psammiris, Pseudoregelia, and Regelia, are not monophyletic as currently circumscribed. The sister clade to subgen. Iris is comprised of I. domestica and I. dichotoma, two beardless species that occur in eastern Asia. Iris verna, a species from the eastern United States is sister to I. domestica + I. dichotoma + subgen. Iris. The sepal of I. verna has pubescence but not a beard of multicellular trichomes.
University of Turin IRIS-registered Publications for co-authorship networks
<p>Data extracted from the University of Turin (UNITO) IRIS publication database (available at <a href="https://iris.unito.it/">www.iris.unito.it</a>) regarding publication authorship.<br>This data was generated in order to produce co-authorship networks of authors inside of UNITO.<br><br>The JSON-formatted dataset includes data regarding UNITO affiliated authors that have published from the year 2012 to roughly September 2023, along with a list of all of their publications in the same time period.The dataset encompasses 15807 authors and 66313 articles.<br><br>The JSON has the following structure:</p><ul><li>`authors` (list): A list of objects representing authors, each with the following structure:<ul><li>`name` (string): The author's given name, all in lowercase letters. This field is always populated;</li><li>`surname` (string): The author's family name, all in lowercase letters. This field is always populated;</li><li>`affiliation` (string): The string "university of turin";</li><li>`department` (string or NULL): Empty (`null`) or with a string indicating the author's <strong>current</strong> (as of data collection, roughly September 2023) work department;</li><li>`id` (string): Unique UUID4 of the author.</li></ul></li><li>`papers` (list): A list of object representing published articles, each with the following structure:<ul><li>`id` (string): Unique IRIS ID of the publication. This field is always populated;</li><li>`title` (string): Title of the publication. This field is always populated;</li><li>`year` (numeric): Year of the article's publication date. This field is always populated;</li><li>`authors` (list): A non-empty list of strings. Each string is one ID of one of the authors in the `authors` list.</li></ul></li></ul><p>The data was kindly provided by the IRIS office in September 2023 and preprocessed by Luca Visentin to a digestible JSON.</p>
The conservation genetics of Iris lacustris (Dwarf Lake Iris), a Great Lakes endemic
<p><em>Iris lacustris</em>, a northern Great Lakes endemic, is a rare species known from 165 occurrences across Lake Michigan and Huron in the United States and Canada. Due to multiple factors, including habitat loss, lack of seed dispersal, patterns of reproduction, and forest succession, the species is threatened. Early population genetic studies using isozymes and allozymes recovered no to limited genetic variation within the species. To better explore genetic variation across the geographic range of <em>I. lacustris </em>and to identify units for conservation, we used tunable Genotyping-by-Sequencing (tGBS) with 171 individuals across 24 populations from Michigan and Wisconsin, and because the species is polyploid, we filtered the single nucleotide polymorphism (SNP) matrices using polyRAD to recognize diploid and tetraploid loci. Based on multiple population genetic approaches, we resolved three to four population clusters that are geographically structured across the two ranges of the species. The species migrated from west to east across its geographic range, and minimal genetic exchange has occurred among populations. Four units for conservation are recognized, but nine adaptive units were identified, providing evidence for local adaptation across the geographic range of the species. Population genetic analyses with all, diploid, and tetraploid loci recovered similar results, which suggests that methods may be robust to variation in ploidy level. </p>
IRIS Carbon Mapping Project: Curated Dataset
<p>Dataset to support IRIS Carbon Mapping Project final report.</p>
Harmonized INSEE socio-demographic IRIS-level data and IRIS conversion file (2010-2020)
<p>The smallest level of aggregation for sociodemographic data made publicly available by the French INSEE is the IRIS. Data is downloadable on INSEE websites but decomposed by type of variable and by year. I thus combined all datasets into a single homogenous dataset for practicality. It includes on the period 2010-2020 :</p> <ul> <li>Population structure (age, gender...) data</li> <li>Economic occupation CSP data</li> <li>Available income data</li> <li>Family data</li> </ul> <p>Since a sizeable amount of IRIS change each year, timewise comparisons are limited. I therefore created a conversion file. Each IRIS is expressed as a % combination of previous IRIS. This allows to track IRIS merge, IRIS split and border changes. Measurement errors linked to border overlap were detected when the overlap of 2 IRIS was less than 1 percent. The IRIS overlap without the measurement error is the variable _ajuste (pardon my French). This allows to express the IRIS of a year as the wieghted sum of the IRIS of any other given year.</p> <p>You will also find the codes I used to create each of the files included in this project on my github. The annotation may be lacking, it is currently being improved. </p>
IRIS Multiple Instance Learning Dataset
<p>This dataset contains the data for the paper 'Using Multiple Instance Learning for Explainable Solar Flare Prediction' (<a href="https://arxiv.org/abs/2203.13896">arxiv pre-print</a>) . It comes as a compressed Python Numpy-File and contains the following variables:</p> <table> <thead> <tr> <th scope="col">Name</th> <th scope="col">Shape</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>data</td> <td>(10'000, 1100, 240)</td> <td>10'000 Bags of zero-padded spectrograms</td> </tr> <tr> <td>data_scaled</td> <td>(10'000, 1100, 240)</td> <td>Like data, but standard-scaled</td> </tr> <tr> <td>masks</td> <td>(10'000, 1100)</td> <td>Masks that indicate where spectrograms have been zero-padded</td> </tr> <tr> <td>groups</td> <td>(10'000,)</td> <td>Observation group the bag is assigned to</td> </tr> <tr> <td>obs_ids</td> <td>(10'000,)</td> <td>Observation ID the bag is assigned to</td> </tr> <tr> <td>obs_classes</td> <td>(10'000,)</td> <td>Observation class (AR/PF) the bag is assigned to</td> </tr> <tr> <td>raster_pos</td> <td>(10'000,)</td> <td>Raster position number the bag was taken from (always 0 for sit-and-stare)</td> </tr> <tr> <td>folds</td> <td>(10'000,)</td> <td>Validation fold for the particular observation group</td> </tr> </tbody> </table> <p> </p> <p>To load the e.g. the variable 'data', use Python and Numpy:</p> <pre><code class="language-python">import numpy as np f = np.load("IRISMIL_dataset_10000_bags.npz", allow_pickle=True) f['data']</code></pre> <p> </p>
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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.