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6,175 results for “Composite”
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.
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).
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.
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.
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.
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.
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
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
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-
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
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
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-
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–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. </p>
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 =
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
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-
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
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
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
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
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.