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635 results for “Attributes”
FIGURES 12–22. Mallinella species. 12–15. M. exornata comb. nov., male holotype. 16. M in Notes on Burmese spiders formerly attributed to the genus Storena (Zodariidae, Araneae)
FIGURES 12–22. Mallinella species. 12–15. M. exornata comb. nov., male holotype. 16. M. exornata comb. nov., female (= S. suavis per Thorell) from Teinzo. 17–20. M. fronto comb. nov., male (= S. exornata per Thorell) from Carin Bia-po. 21. M. fronto comb. nov., female holotype. 22. M. fronto comb. nov., female (= S. exornata per Thorell) from Mt. Karen. 12, 17. Right male palp, ventral view. 13, 18. TA, ventral view, 14. prolateral view, 19. retrolateral view. 15. Part of embolus, prolateral view. 16, 21. Epigyne, ventral view. 20. Palpal tibia showing RTA, retrolateral view. 22. Internal genitalic structures, posterior view. Scale lines = 0.1 mm.
FIGURES 9–11. Mallinella suavis comb. nov., female holotype. 9. Internal genital structures, dorsal view. 10. Left spermatheca, lateral view. 11 in Notes on Burmese spiders formerly attributed to the genus Storena (Zodariidae, Araneae)
FIGURES 9–11. Mallinella suavis comb. nov., female holotype. 9. Internal genital structures, dorsal view. 10. Left spermatheca, lateral view. 11. Right spermatheca, anterior view. Scale lines = 0.1 mm.
FIGURES 1–8. Mallinella species. 1. Mallinella fronto comb. nov. female holotype. 2, 3. M in Notes on Burmese spiders formerly attributed to the genus Storena (Zodariidae, Araneae)
FIGURES 1–8. Mallinella species. 1. Mallinella fronto comb. nov. female holotype. 2, 3. M. fronto comb. nov., female (= S. exornata per Thorell) from Mt. Karen. 4. M. fronto comb. nov., female from Carin Bia-po. 5. M. fronto comb. nov., female (= S. exornata per Thorell) from Carin Bia-po. 6. M. fronto comb. nov., female (= S. exornata per Thorell) from Carin Ghecu. 7. M. suavis comb. nov., female holotype. 8. M. exornata comb. nov., female (= S. suavis per Thorell) from Teinzo. 1, 2. Epigyne, dorsal view. 3-8. Epigyne, ventral view. Scale lines = 0.1 mm.
FIGURES 20–23 in A new species of Laelaspis Berlese (Acari: Mesostigmata: Laelapidae) from Iran, with a revised generic concept and notes on significant morphological attributes in the genus
FIGURES 20–23. Laelaspis morazae sp. nov. Male. 20. Subcapitulum; 21. Dorsal idiosoma, part of posterior region; 22. Ventral idiosoma; 23. Chelicera.
FIGURES 1–4. Laelaspis persicus. Female. 1 in A new species of Laelaspis Berlese (Acari: Mesostigmata: Laelapidae) from Iran, with a revised generic concept and notes on significant morphological attributes in the genus
FIGURES 1–4. Laelaspis persicus. Female. 1. Dorsal idiosoma; 2. Details of some dorsal shield setae; 3. Palp; 4. Epistome.
FIGURES 5–9. Laelaspis persicus. Female. 5 in A new species of Laelaspis Berlese (Acari: Mesostigmata: Laelapidae) from Iran, with a revised generic concept and notes on significant morphological attributes in the genus
FIGURES 5–9. Laelaspis persicus. Female. 5. Ventral idiosoma; 6. Peritrematal shield; 7. Spermatheca; 8. Subcapitulum; 9. Chelicera.
FIGURE 12 in Reappraisal of species attributed to Halicarcinus White, 1846 (Crustacea: Decapoda: Brachyura: Hymenosomatidae) with diagnosis of four new genera and one new species from New Ireland, Papua New Guinea
FIGURE 12. Stimpsoplax setirostris (Stimpson, 1858). Male, 3.6 mm, CBM-ZC 295: a, dorsal carapace; b, thoracic sternum; c, rostrum, antennules, antennae, eyestalks, proepistome and epistome, ventral view; d, posterior part of epistome, anterior view; e, maxilliped, 3; f, left cheliped, upper; g, left chela, outer face; h, gonopod 1; i, left gonopod 2, outer (ventral) view. Scale bars = 1 mm.
FIGURE 10 in Reappraisal of species attributed to Halicarcinus White, 1846 (Crustacea: Decapoda: Brachyura: Hymenosomatidae) with diagnosis of four new genera and one new species from New Ireland, Papua New Guinea
FIGURE 10. Lucascinus coralicola (Rathbun, 1909). Male, 4.7 mm, CBM-ZC 3632: a, carapace, dorsal view, b, frontal region, ventral view; c, thoracic sternum; d, left cheliped, upper view; e, chela, lateral view; f, gonopod 2, outer (ventral) view; g, same, inner (dorsal) view. Lucascinus keijibabai (Takeda & Miyake, 1971). Male, ZLKU 13089 (holotype, male, 2.1 mm: h, frontal region, ventral view. Scale bars a–e, h = 1 mm; f, g = 0.5 mm.
FIGURE 4 in Reappraisal of species attributed to Halicarcinus White, 1846 (Crustacea: Decapoda: Brachyura: Hymenosomatidae) with diagnosis of four new genera and one new species from New Ireland, Papua New Guinea
FIGURE 4. Micas filholi (De Man, 1888). Holotype of Elamena filholi De Man, 1888, male, cl 4.0 mm, SMF ZMG 805: a, carapace and right pereopods; b, rostrum and anterior carapace; c, right pereopod 3, dactylus; d, pleon; e, gonopod 1. Scale bars a–d = 1 mm, e = 0.5 mm.
FIGURE 1 in Reappraisal of species attributed to Halicarcinus White, 1846 (Crustacea: Decapoda: Brachyura: Hymenosomatidae) with diagnosis of four new genera and one new species from New Ireland, Papua New Guinea
FIGURE 1. Halicarcinus cookii (Filhol, 1885): a–c, lectotype of Hymenicus cookii Filhol, 1885, MNHN IU-2014-7143 (B32572), (female, 6.1 mm). Halicarcinus planatus (Fabricius, 1775): d, holotype of Elamena mexicana (H. Milne Edwards, 1853), MNHN IU-2000-655 (B655), (male, 7.3 mm). Halicarcinus quoyi (H. Milne Edwards, 1853): e, lectotype of Elamena quoyi H. Milne Edwards, 1853, MNHN-2000-667 (B667), (male without rostrum, 6.4 mm); f, paralectotype, MNHN-2000- 32609 (B32609), (sex unknown, dry fragments).
DAM-IN: Comprehensive Dam Catchment Attributes in India
<p>We present one of the most comprehensive datasets of dams in India, “DAM-IN”. The dam attributes for India (DAM-IN) consist of six important catchment characteristics, including topography, geology and groundwater, soil, Land Use and Land Cover (LULC), climate, and human-induced activities. These six catchment characteristics were developed using various reanalysis, observed, and remote-sensing data for more than 5700 dams in India. Moreover, a large number of attributes were estimated for each catchment characteristic of the dam. Overall, the comprehensive DAM-IN dataset consists of high-quality catchment attributes for each dam in India for multi-temporal and spatial resolution. The DAM-IN data is useful for various stakeholders to conduct scientific research, dam safety, and impact analysis in India. Moreover, the DAM-IN data can be used for reservoir management, various water quantity and quality studies, environmental risk assessment, and climate change risk analysis. The catchment and meteorological attributes can be used as input for hydrological, hydraulic, and machine-learning modeling. Using the developed attributes, the effective planning and management of sustainable river infrastructure and water resource allocation can be performed.</p>
The data of Emoji Use, Empathy, Attribution of Responsibility, and Forgiveness in Apologies
<p>This is the data for paper: Can Emoji Promote Forgiveness? The Relationship between Emoji Use, Empathy, Attribution of Responsibility, and Forgiveness in Apologies. A total of 323 participants were recruited in that study, and a recall method (Study 1) and scenario simulation method (Study 2) were used to explore the effect of emoji use during apologies on forgiveness, and the mediating role of empathy and attribution of responsibility. The results showed that (a) people chose emoji that resembled real remorseful facial expressions when apologizing; (b) using emoji that expressed remorse when apologizing could promote forgiveness; and (c) empathy mediated the process of emoji promoting forgiveness, while attribution of responsibility did not play a mediating role.</p>
Codes for the study "Attribution of Recent Heatwave Increases to Ocean Modulation"
<p>This is the code for data processing and plotting for the paper titled "Attribution of Recent Heatwave Increases to Ocean Modulation", which was submitted to <em>Communications Earth & Environment</em>.</p>
BULL Database – Spanish Basin attributes for Unraveling Learning in Large-sample hydrology
<p>We present a novel basin dataset for large-sample hydrological studies in Spain. BULL<br>comprises data for … basins, combining hydrometeorological time series (streamflow and …<br>climatic variables) with … attributes related to geology, soil, topography, land cover,<br>anthropogenic influence and hydroclimatology.</p>
Evaluating Feature Attribution Methods in the Image Domain: Benchmark results and model parameters
<p>This dataset contains the experimental results, adversarial patches and model parameters used in the paper Evaluating Feature Attribution Methods in the Image Domain.</p>
Extreme Weather Event Real-time Attribution Machine (EWERAM) forecasts for Cyclone Gabrielle
<p>These files contain the hourly precipitation, wind, humidity, and pressure data as well as the land-sea mask, orography, and regional council data supporting the investigation into the human role in Cyclone Gabrielle performed by the EWERAM (Extreme Weather Event Real-time Attribution Machine) consortium. The EWERAM experiment design is outline by Tradowsky and co-authors (2023, 10.1088/2752-5295/acf4b4).</p> <p>Directory and data format follows the conventions of the Climate of the 20th Century Plus Detection and Attribution (C20C+ D&A) Project. Details are provided at https://portal.nersc.gov/c20c/experiment.html and in Stone and co-authors (2019, 10.1016/j.wace.2019.100206).</p>
ELTeC for Authorship Attribution
<p>Selected texts from multiple ELTeC collections, prepared as simple test datasets for authorship attribution. Each set contains between 24 and 33 novels by 8 to 11 different authors (3 novels per author) in plain text. The languages represented are English, German, French, Hungarian, Portuguese, Slovenian, Romanian. </p>
Morph_CNeT: A new GIS tool to extract morphometric attributes characterising channel network topology of Indian catchments
<p><span>Morph_CNeT” (Morphometric Channel Network Extraction Tool) can facilitate extraction of the topology based new morphometric attributes by processing DEM datasets within GIS framework. Morph_CNeT tool is used to create a repository named as Morph_CNeT-India of topological catchment attributes for 1749 gauging stations maintained by the Central Water Commission (CWC) across 22 River basin Systems of India.</span></p>
A Survey of Emotional and Mental Health Effects Women Attribute to Their Pregnancy Outcomes
<h2>Materials and Methods</h2> <p><span>Experts in abortion and mental health research were consulted in preparing a questionnaire into the prevalence and effects of abortions that conflict with women’s own maternal preferences and moral beliefs. </span></p> <h3>Study Population</h3> <p><span>Invitations to complete a topic blind survey were electronically distributed to Cint.com panelists over a three-day period in July of 2024. Cint panelists are persons who voluntarily complete surveys using their own electronic devices in exchange for small rewards with a value, for this invitation, of under $2 per completed survey. The Cint survey panels include over 28 million U.S. residents. For this survey, a random sample of United States residents Cint pre-identified as females 41 to 45 years of age were invited to complete a survey housed on the LimeSurvey.org platform without any disclosure of the subject matter. The narrow age range, 41-45 years of age, was chosen to (a) eliminate the confounding effects of age, and (b) to maximize the proportion of respondents with a history of abortion since this age group will have completed the majority of their reproductive lives. Investigation of younger women has been deferred until we can test the survey instrument with this limited age group. </span></p> <p><span>The survey exposure rate, response rates, and exclusion rates are shown in Figure 1. Respondents who did not complete all questions were excluded from the analysis, as were any respondents who were out of our gender and age range. Among the 2,361 people who completed the first page of demographic questions, 123 (5.2%) dropped by failing to complete the psychiatric history and another 25 (1.1%) dropped out when presented with questions relating to abortion. Another 22 (1.0%) dropped out when asked their own pregnancy outcomes histories and 166 (7.0%) dropped out, after reporting their pregnancy histories, before completing the survey. The survey was designed to be completed in approximately five to seven minutes by respondents reporting any pregnancies. Of those who completed the survey, 100 (4.6%) were excluded for completing the survey in an unreasonably short period of time, under four minutes. The exclusion of these “speedsters” reflected the likelihood that some respondents, seeking to earn credit for completing the survey as quickly as possible, were randomly responding without reading or considering the questions.</span></p> <p> </p> <p><span></span></p> <p><span> </span></p> <p><span>Figure </span><span><span>1</span></span><span>: Study Population</span></p> <h3>Variables used</h3> <p><span>The first page of the questionnaire asked about age and gender to qualify respondents. The second page included a list of eleven mental health diagnoses and asked respondents to identify which, if any, they had ever been diagnosed. </span></p> <p><span>Only after this page were respondents asked if they had ever had an “unplanned, mistimed, unwanted, or otherwise difficult pregnancy,” which was defined and thereafter referred to as a “problematic pregnancy.” They were then asked to identify the number of times they had “given birth to a live born child,” “had a miscarriage, still birth or other pregnancy loss” and “had an induced abortion.” From this pregnancy history women were divided by a program algorithm into one of five groups, by order of priority: those who had a history of induced abortions, had experienced natural pregnancy losses, had problematic pregnancies carried to term, or had live births, or had never been pregnant. Results from this grouping is shown in Table 1. Notably, given the algorithm prioritization, women in the abortion group may also have had one or more live births, natural pregnancy losses, and problematic pregnancies ending in a live birth. But women were included in the live birth group only if they had none of the other pregnancy outcomes. </span></p> <p><span>The rest of the variables are described in the repository document "2nd USA Survey Instrument.pdf" and in the limesurvey code, "2nd USA survey limesurvey.lss."</span></p>
URA dataset - 40 Basque Country catchments hourly hydro-meteorological data + Catchments Attributes
<p>Basque Country is located in north of Spain on the Atlantic coast. This region, characterized by its humid climatology, has abundant water resources. The catchments, noted for their flashy and humid characteristics, span an area of 4494 Km<sup>2</sup> and include a diverse range of basin sizes from 4 to 1000 Km<sup>2</sup>.</p> <p>The Basque Water Agency (URA), a regional governmental entity in the Basque Country, is responsible for managing water policies and resources in this territory. To support water resources planning and management, URA has compiled a high-quality dataset suitable for data mining using deep learning models. This dataset includes hourly hydro-meteorological timeseries, reflecting the region’s steep, flashy, and humid hydrological dynamics.</p> <p>URA catchments are situated between the Cantabrian Mountains (reaching up to 1300 meters in elevation) in the northwest and the Atlantic Ocean to the north. The region is predominantly covered by grasslands and evergreen forests and benefits from the warming effects of the Gulf Stream. The climate is humid and temperate, with mean annual temperatures ranging from 9°<sup>C</sup> in the mountains to 15°<sup>C</sup> in lower regions. Annual rainfall varies between 1200 and 1600 millimeters, primarily due to the advection of North Atlantic fronts.</p> <p>URA has collected hourly hydro-meteorological timeseries from approximately 100 stations distributed across the region, including rain gauges and water level measurement sites. Accurate rainfall-runoff modeling is critical in this region due to its susceptibility to flash floods. This dataset presents 21 years of hourly timeseries from 40 catchments within the region. This extensive temporal coverage and high-resolution data offer valuable insights into the region’s hydrological dynamics.</p> <p>This Dataset is published with the papers:</p> <p>1- <span>Hosseini, F.; Prieto, C.; Álvarez, C. (2025). </span><span><strong>Ensemble learning of catchment-wise optimized LSTMs enhances regional rainfall-runoff modelling</strong>—Case Study: Basque Country, Spain. </span><span>J. Hydrol. 132269. doi: </span><span><a href="https://doi.org/10.1016/j.jhydrol.2024.132269"><span>10.1016/j.jhydrol.2024.132269</span></a></span></p> <p>2- <span>Hosseini, F., Prieto, C., & Álvarez, C. (2024a). <strong>Hyperparameter optimization of regional hydrological LSTMs by random search</strong>: A case study from Basque Country, Spain. Journal of Hydrology, 132003. doi: </span><span><a href="https://doi.org/10.1016/j.jhydrol.2024.132003"><span>10.1016/j.jhydrol.2024.132003</span></a></span></p> <p> </p>
ScienceDex guides
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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.