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2,353 results for “channel”
FIGURE 4 in The main channel and river confluences as spawning sites for migratory fishes in the middle Uruguay River
FIGURE 4 | Proportion Capture (%) of the different larval development stages of fishes captured in the middle Uruguay River and tributaries, between October 2016 and January 2017. Degree of larval stages of development: LV = Yolk-sac larvae, PF = Preflexion, F = Flexion and PoF = Postflexion.
FIGURE 2 in The main channel and river confluences as spawning sites for migratory fishes in the middle Uruguay River
FIGURE 2 | Spatial distribution of median, first and third quartile, maximum and minimum densities of fish eggs and larvae collected in the middle Uruguay River and tributaries, between October 2016 and January 2017. Different letters within each graph indicate a statistically significant difference (p <0.05). A. Eggs; and B. Larvae.
FIGURE 1 in The main channel and river confluences as spawning sites for migratory fishes in the middle Uruguay River
FIGURE 1 | The Uruguay River basin, the study area in the middle Uruguay River, and the six sampling sites investigated (Chan-C, Trib-C, Chan-I, Trib-I, Chan-P, and Trib-P).
Seismic modeling of bedload transport in a gravel-bed alluvial channel
<p>This repository publishes data for 4 flow events at the Arroyo de Los Pinos on the paper "Seismic modeling of bedload transport in a sandy gravel-bed alluvial channel".</p>
UNSUPERVISED MACHINE LEARNING AND VECTOR MODELS IN DESIGNING AND OPTIMIZATION OF TELECOM RETAIL CHANNELS
<p>This paper examines the use of unsupervised machine learning and vector models in the design and optimization of retail channels for telecommunications services. Unsupervised machine learning allows you to analyze and identify hidden patterns in large volumes of untagged data, which is especially important in a dynamically changing consumer market. Vector models, in turn, provide high accuracy of demand forecasting and inventory management, contributing to an increase in the efficiency of trading channels. The synergy of these technologies allows companies to improve customer experience, optimize operational processes and increase competitiveness in the market. The main focus of the work is on data processing methods, including correlation analysis, the use of the support vector machine (SVM) method and its adaptation to solve problems related to predicting customer behavior and optimizing logistics processes.</p>
Linked collectors and determiners for: Caddisfly (Trichoptera) records from Britain (excluding Northern Ireland and Channel Islands) up to August 2022 from the National Trichoptera (Caddisfly) Recording Scheme.
Natural history specimen data linked to collectors and determiners held within, "Caddisfly (Trichoptera) records from Britain (excluding Northern Ireland and Channel Islands) up to August 2022 from the National Trichoptera (Caddisfly) Recording Scheme". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/bba60198-3eb5-4101-954d-3e2c87df4b73">https://bionomia.net/dataset/bba60198-3eb5-4101-954d-3e2c87df4b73</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/bba60198-3eb5-4101-954d-3e2c87df4b73">https://gbif.org/dataset/bba60198-3eb5-4101-954d-3e2c87df4b73</a>. Formatted as a Frictionless Data package.
ChannelLeveeModel: Decoupled Channel-levee Evolution Model for MATLAB
<h1>ChannelLeveeModel v1.0.1</h1> <p>This is the archive of a numerical model that decoupled channel bed and levee evolution with associated simulations, dataset, and figures using MATLAB</p> <p><strong>Features</strong></p> <ul> <li>Generate random weekly hydrographs and solve the divided channel method to compute the flooded water surface elevation (Lotter, 1933)</li> <li>Identify two flood styles: Front loading and Back loading</li> <li>Run advection-settling model (Han and Kim, 2022) for Front loading events and Ponded water model (Nicholas and Walling, 1996) for Back loading events</li> <li>Visualizes results with MATLAB plotting functions</li> </ul> <p><strong>File lists</strong></p> <ul> <li><strong>Main file:</strong> <code>DecoupledCLM.m</code></li> <li><strong>Function files:</strong> <code>HydraulicGeometry.m</code>, <code>Hydrograph.m</code>, <code>OverflowLevel.m</code>, <code>LeveeBimodal.m</code>, <code>Backloading_wellmix.m</code></li> <li><strong>Plotting files:</strong> <code>plot_BE.m</code>, <code>plot_ConfinedRelease.m</code>, <code>plot_figures.m</code></li> <li><strong>Output folder:</strong> <code>simulation_code/output/</code> contains example model simulations in <code>.m</code> format. and figures in <code>.pdf</code> format.</li> <li><code>README.md</code> and <code>LICENSE</code></li> </ul>
Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads. in Map of Guam
Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads.
MAP OF GUA:i\I Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads. in Map of Guam
MAP OF GUA:i\I Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads.
MAP OF GUAM Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads. in Map of Guam
MAP OF GUAM Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads.
Multi-channel Surface EMG Dataset for Fatigue analysis
<p>This is the data used in paper "Upper Limb Muscle Fatigue Analysis Using Multi-channel Surface EMG" DOI: 10.1109/NILES50944.2020.9257909</p> <p>Data can be found as a txt files for each subject separately or can be found as .mat file with all subjects included.</p> <p>Data details:</p> <ul> <li>Sampling Frequency= 200 Hz </li> <li>8-Bit resolution</li> <li>15 Healthy Subjects </li> <li>6 Kg Load with elbow flexed to a 90 angle</li> <li>120 Seconds Duration</li> <li>8 channels sEMG </li> <li>50 Hz Notch Filtered</li> </ul> <p>For more details and citation:</p> <p>A. Ebied, A. M. Awadallah, M. A. Abbass and Y. El-Sharkawy, "Upper Limb Muscle Fatigue Analysis Using Multi-channel Surface EMG," 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES), 2020, pp. 423-427, doi: 10.1109/NILES50944.2020.9257909.</p>
Figure 6 in First record of the hyperparasite Liriopsis pygmaea (Cryptoniscidae, Isopoda) from a rhizocephalan parasite of the false king crab Paralomis granulosa from the Beagle Channel (Argentina), with a redescription
Figure 6. Liriopsis pygmaea. (a, b) Habitus of early subadult female; (c) ventral habitus of advanced subadult female; (d, e) dorsal and ventral habitus of adult female; (f, g) adult female, details of anterior and posterior ends of the slit. Scale bars: 5 mm (a–e); 0.5 mm (f); 1 mm (g).
Figure 5 in First record of the hyperparasite Liriopsis pygmaea (Cryptoniscidae, Isopoda) from a rhizocephalan parasite of the false king crab Paralomis granulosa from the Beagle Channel (Argentina), with a redescription
Figure 5. Liriopsis pygmaea. Cryptoniscus larva. (a) Third pereopod; (b) sixth pereopod; (c) seventh pereopod, merus and carpus only; (d) first pleopod, (e) uropods. Scale bars: 0.1 mm (b and c, same scale).
Figure 3 in First record of the hyperparasite Liriopsis pygmaea (Cryptoniscidae, Isopoda) from a rhizocephalan parasite of the false king crab Paralomis granulosa from the Beagle Channel (Argentina), with a redescription
Figure 3. Liriopsis pygmaea. SEM photographs of the cryptoniscus larva. (a, b) Dorsal and ventral habitus; (c) ventral view of head, arrow shows the median plate partially covering the rostral teeth of the first antenna; (d) anterior part of first and second antennular articles, arrows show the first article with a rostral tooth completely exposed and the second article with a single median tooth; (e) ventral view showing the sixth (foreground) and seventh styliform pereopods; arrow indicates seventh coxal plate. Photographs (b) and (c) belong to the same specimen, the others to different specimens. Scale bars in mm.
Figure 1 in First record of the hyperparasite Liriopsis pygmaea (Cryptoniscidae, Isopoda) from a rhizocephalan parasite of the false king crab Paralomis granulosa from the Beagle Channel (Argentina), with a redescription
Figure 1. Liriopsis pygmaea. SEM photographs of the epicaridium larva. (a) Ventral habitus; (b) ventral view of abdomen; (c) detail of anal tube. All photographs belong to the same specimen.
Figure 2 in First record of the hyperparasite Liriopsis pygmaea (Cryptoniscidae, Isopoda) from a rhizocephalan parasite of the false king crab Paralomis granulosa from the Beagle Channel (Argentina), with a redescription
Figure 2. Liriopsis pygmaea. Epicaridium larva. (a) Second antenna; (b) sixth pereopod; (c) fourth pleopod; (d) uropods. Scale bars: 0.05 mm.
Figure 4 in First record of the hyperparasite Liriopsis pygmaea (Cryptoniscidae, Isopoda) from a rhizocephalan parasite of the false king crab Paralomis granulosa from the Beagle Channel (Argentina), with a redescription
Figure 4. Liriopsis pygmaea. Cryptoniscus larva. (a) Dorsal habitus; (b) first antenna; (c) second antenna; (d) first pereopod, with detail of distal process of propodus. Scale bars: 0.5 mm (a); 0.1 mm (b–d).
Source data for "Glacial isostatic adjustment directed incision of the Channeled Scabland by ice-age megafloods"
<p>The data provided in this repository is the source data for "Glacial isostatic adjustment directed incision of the Channeled Scabland by ice-age megafloods". This repository contains three directories for ANUGA simulations on (1) present-day topography, (2) glacial isostatic adjustment-corrected topography at 18 ka, and (3) glacial isostatic adjustment-corrected topography at 15.5 ka. Each directory includes hydrodynamic modeling data and topographic reconstruction data. This repository also contains MATLAB scripts for analyzing simulated discharge and shear stress values for replicating plots.</p> <p>Cite as: Pico. T., David, S.R., Larsen, I.J, Mix, A., Lehnigk, K., Lamb, M.P., Glacial isostatic adjustment directed incision of the Channeled Scabland by ice-age megafloods, PNAS, 2022.</p> <p> </p> <p><br> </p>
Fig. 3 in Habitat partitioning, habits and convergence among coastal nektonic fish species from the São Sebastião Channel, southeastern Brazil
Fig. 3. Dendrogram of ecomorphological relationships (similarity) for the 17 nektonic fish species studied. Cluster analysis is by the Euclidean distance measure and Group Average linkage method using the same scores (i.e., coordinates) calculated for PCA and plotted in Fig. 2 (cophenetic coefficient r = 0.86). Anc tri = Anchoa tricolor; Ath bra = Atherinella brasiliensis; Car lat = Caranx latus; Chl chr = Chloroscombrus chrysurus; Fis tab = Fistularia tabacaria; Har jag = Harengula jaguana; Hyp uni = Hyporhamphus unifasciatus; Lag lae = Lagocephalus laevigatus; Mug cur = Mugil curema; Oli sau = Oligoplites saurus; Pom sal = Pomatomus saltatrix; Sar jan = Sardinella janeiro; Sco bra = Scomberomorus brasiliensis; Sel vom = Selene vomer; Str tim = Strongylura timucu; Tra car = Trachinotus carolinus; Tri lep = Trichiurus lepturus. There is no scale among the fishes (see Table 2 for standard length range) (illustrations: Alexandre C. Ribeiro).
Fig. 2 in Habitat partitioning, habits and convergence among coastal nektonic fish species from the São Sebastião Channel, southeastern Brazil
Fig. 2. Distribution of the 17 nektonic fish species in ecomorphological space. Ordination is by the first two axes of PCA (cumulative % of variance = 73) (see Table 5). Anc tri = Anchoa tricolor; Ath bra = Atherinella brasiliensis; Car lat = Caranx latus; Chl chr = Chloroscombrus chrysurus; Fis tab = Fistularia tabacaria; Har jag = Harengula jaguana; Hyp uni = Hyporhamphus unifasciatus; Lag lae = Lagocephalus laevigatus; Mug cur = Mugil curema; Oli sau = Oligoplites saurus; Pom sal = Pomatomus saltatrix; Sar jan = Sardinella janeiro; Sco bra = Scomberomorus brasiliensis; Sel vom = Selene vomer; Str tim = Strongylura timucu; Tra car = Trachinotus carolinus; Tri lep = Trichiurus lepturus. There is no scale among the fishes (see Table 2 for standard length range) (illustrations: Alexandre C. Ribeiro).
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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.
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.