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6,175 results for “Composite”

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Fig. 4 in Species composition and distribution of medusae (Cnidaria: Medusozoa) along the Algerian coast between 2°E and 7°E (SW Mediterranean Sea) Abstract

Fig. 4: Correspondence analysis (CA) showing the repartitions of the medusa species between the central and eastern regions.

opencc-by-4.0Mar 2020View details →
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Fig. 2 in Species composition and distribution of medusae (Cnidaria: Medusozoa) along the Algerian coast between 2°E and 7°E (SW Mediterranean Sea) Abstract

Fig. 2: Fluctuation of the environmental parameters at the sampling stations along the Algerian coast (a: temperature; b: salinity; c: chlorophyll a).

opencc-by-4.0Mar 2020View details →
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Fig. 6 in Species composition and distribution of medusae (Cnidaria: Medusozoa) along the Algerian coast between 2°E and 7°E (SW Mediterranean Sea) Abstract

Fig. 6: Principal component analysis (PCA) showing the relationships between the medusae species and the environmental variables.

opencc-by-4.0Mar 2020View details →
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Fig. 5 in Species composition and distribution of medusae (Cnidaria: Medusozoa) along the Algerian coast between 2°E and 7°E (SW Mediterranean Sea) Abstract

Fig. 5: Spatial distribution of the main species: a. A. hemistoma; b. L. tetraphylla; c. R. velatum; and d. P. noctiluca along the Algerian coast (2°E -7°E) during the surveyed period. Table 3. Segregation values (D index) recorded between pairs of dominant species along the Algerian coast.

opencc-by-4.0Mar 2020View details →
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Dataset: TPI Composites, Inc. (TPIC) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-zeroJun 2024View details →
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Dataset: Fidelity Nasdaq Composite Index ETF (ONEQ) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-zeroJun 2024View details →
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Fig. 1 in Extinction Disorders The Species Composition Of Metacommunities

Fig. 1. Changes of nestedness in relation to the exclusion of the rarest species from the metacommunity. A = orthopterans, B = butterflies, C = beetles, D = birds, D(st) is the standardized difference between the average temperature of 100 random matrices and the actual matrix temperature, divided by the standard deviation of the random matrices. Triangles indicate non-significant nestedness

opencc-by-4.0Nov 2003View details →
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Fig. 2 in Diet Composition Of Otters (Lutra Lutra L.) Living On Small Watercourses In Southwestern Hungary

Fig. 2. The diet pattern of otters living by streams and channels in the Dráva region. For locations (W1–5) see Fig. 1, n = number of spraint samples

opencc-by-4.0Sep 2009View details →
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Fig. 1 in Diet Composition Of Otters (Lutra Lutra L.) Living On Small Watercourses In Southwestern Hungary

Fig. 1. Locality of the small watercourses studied in the Drava region. 1 = Dombó-channel (W1, Gyékényes), 2 = Dombó-channel (W2, Berzence), 3 = Babócsai stream (W3, Babócsa), 4 = Barcs-Kom-

opencc-by-4.0Sep 2009View details →
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Fig. 3 in Diet Composition Of Otters (Lutra Lutra L.) Living On Small Watercourses In Southwestern Hungary

Fig. 3. Percentage biomass consumption (mean±SE) of fish prey in the diet of otters living by streams and channels, on the basis of fish weight (a) and guild (b). Fish guilds: RE – reophilic or flow preferring, EU – eurytopic or tolerant for rivers and stagnant waters and ST – stagnophilic or stagnant water

opencc-by-4.0Sep 2009View details →
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Fig. 2 in Spatial Variation In Prey Composition And Its Possible Effect On Reproductive Success In An Expanding Eastern Imperial Eagle (Aquila Heliaca) Population

Fig. 2. Cluster analyses of imperial eagle breeding areas based on prey composition data. Region codes are presented in Fig. 1. Codes with bold characters represent mountainous habitats. The single breeding pair of the Cserehát Mountains was excluded from the analysis, because of low sample size

opencc-by-4.0May 2010View details →
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Fig. 3 in Spatial Variation In Prey Composition And Its Possible Effect On Reproductive Success In An Expanding Eastern Imperial Eagle (Aquila Heliaca) Population

Fig. 3. Frequency of the three main prey species (a-c) and reproductive success (d) of imperial eagles in two East-Hungarian regions. Boxplots presents the minimum-maximum (whiskers), lower and upper quartiles (box) and the median (line) of the data. Dots are outliers. Significance of difference is in-

opencc-by-4.0May 2010View details →
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Fabrication, Characterization and Evaluation of an Alginate–Lignin Composite for Rare-Earth Elements Recovery

<p>This dataset contains the raw data for the publication "Fabrication, Characterization and Evaluation of an Alginate&ndash;Lignin Composite for Rare-Earth Elements Recovery" by Fila et al, published in Materials. The upload includes raw data of physicochemical characterizations of alginate-based composite, i.e. alginate-lignin, including BET, SEM, TG, XPS and XRD analyses.&nbsp;</p>

opencc-by-4.0Jan 2022View details →
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Fig. 24 in Subtribal, Generic And Subgeneric Composition Of Darkling Beetles Of The Tribe Helopini (Coleoptera: Tenebrionidae) In The Eastern Palaearctic Region

Fig. 24. Asialassus tsushimanus, male, holotype: A = habitus, B = protibia, laterally, C = protibia, ventrally, D = mesotibia, E = aedeagus, dorsal view, F = prothorax, ventral view, G =

opencc-by-4.0Oct 2018View details →
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Fig. 23 in Subtribal, Generic And Subgeneric Composition Of Darkling Beetles Of The Tribe Helopini (Coleoptera: Tenebrionidae) In The Eastern Palaearctic Region

Fig. 23. Asialassus kimurai, details of structure, male: A = head, ventral view, B = prothorax, ventral view, C = prosternal process, D = protibia, ventrally

opencc-by-4.0Oct 2018View details →
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Fig. 21 in Subtribal, Generic And Subgeneric Composition Of Darkling Beetles Of The Tribe Helopini (Coleoptera: Tenebrionidae) In The Eastern Palaearctic Region

Fig. 21. Asialassus kimurai, holotype and paratype: A = holotype, male, habitus, B = paratype, female, habitus, C = male protibia, dorsally, D = male protibia, ventrally, E = male mesotibia, F = male prothorax ventro-laterally, G = male prothorax, ventrally, H = aedea-

opencc-by-4.0Oct 2018View details →
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Fig. 19 in Subtribal, Generic And Subgeneric Composition Of Darkling Beetles Of The Tribe Helopini (Coleoptera: Tenebrionidae) In The Eastern Palaearctic Region

Fig. 19. Asialassus amamiensis, holotype, female: A = habitus, B = protibia, C = prothorax, ventral view, D = labels of the holotype

opencc-by-4.0Oct 2018View details →
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Fig. 26 in Subtribal, Generic And Subgeneric Composition Of Darkling Beetles Of The Tribe Helopini (Coleoptera: Tenebrionidae) In The Eastern Palaearctic Region

Fig. 26. Asialassus adachii, male, holotype: A = habitus, B = protibia dorsally, C = protibia ventrally, D = mesotibia, E = prothorax, ventral view, F = prosternal process, lateral view, G = aedeagus, H = labels of the holotype

opencc-by-4.0Oct 2018View details →
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Fig. 16 in Subtribal, Generic And Subgeneric Composition Of Darkling Beetles Of The Tribe Helopini (Coleoptera: Tenebrionidae) In The Eastern Palaearctic Region

Fig. 16. Nalassus (Nipponalassus) lewisi (A, C–F) and N. (Nipponalassus) andoi (B), details of structure: A = head, ventral view, B = male abdominal ventrite 5, C = male meso- and metaventrite, middle legs basally, D = male abdominal ventrites, E = male profemur, inner side, F = male profemur dorsally

opencc-by-4.0Oct 2018View details →
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Fig. 13 in Subtribal, Generic And Subgeneric Composition Of Darkling Beetles Of The Tribe Helopini (Coleoptera: Tenebrionidae) In The Eastern Palaearctic Region

Fig. 13. Nalassus (Nipponalassus) andoi, holotype and paratype. A = male, holotype, habitus, B = female paratype, habitus, C = male fore leg, dorsal margin, D = male profemur, inner side, E = aedeagus, dorsal view, F = prothorax, ventral view, G = abdominal ventrite 5, H = labels of the holotype

opencc-by-4.0Oct 2018View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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Your academic CV and NIH biosketch

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