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2,326 results for “clusters”
Figure 3 from: Nelson G, Paul D, Riccardi G, Mast A (2012) Five task clusters that enable efficient and effective digitization of biological collections. ZooKeys 209: 19-45. https://doi.org/10.3897/zookeys.209.3135
Figure 3 - Custom specimen holder. Museum of Compartive Zoology (MCZ) Rhopalocera (Lepidoptera) Rapid Digitization Project.
Figure 2 from: Nelson G, Paul D, Riccardi G, Mast A (2012) Five task clusters that enable efficient and effective digitization of biological collections. ZooKeys 209: 19-45. https://doi.org/10.3897/zookeys.209.3135
Figure 2 - Specimen image capture. Fossil specimen imaging, specimen label imaging. Two very different imaging set-ups. Yale Peabody Museum, University of Kansas - Entomology.
Figure 1 from: Nelson G, Paul D, Riccardi G, Mast A (2012) Five task clusters that enable efficient and effective digitization of biological collections. ZooKeys 209: 19-45. https://doi.org/10.3897/zookeys.209.3135
Figure 1 - Pre-digitization specimen curation and staging. Preparing barcodes and imaging labels, affixing barcodes, updating taxonomy. L to R: University of Kansas – Entomology, New York Botanical Garden and Yale Peabody Museum.
Figure 5 from: Nelson G, Paul D, Riccardi G, Mast A (2012) Five task clusters that enable efficient and effective digitization of biological collections. ZooKeys 209: 19-45. https://doi.org/10.3897/zookeys.209.3135
Figure 5 - Electronic data capture. Entering data straight from the specimen label into the database. New York Botanical Garden.
Figure 10 from: Seifert B, Csösz S (2015) Temnothorax crasecundus sp. n. – a cryptic Eurocaucasian ant species (Hymenoptera, Formicidae) discovered by Nest Centroid Clustering. ZooKeys 479: 37-64. https://doi.org/10.3897/zookeys.479.8510
Figure 10 - Temnothorax crasecundus sp. n. (grey branch) and Temnothorax crassispinus (black branch). NC-Ward clustering. Data set of Csösz: 99 nest samples and 10 characters considered. Arrows point to samples clustered in disagreement with the final species hypothesis. Figs 1 and 2 sum up to 203 different samples.
Figure 9 from: Seifert B, Csösz S (2015) Temnothorax crasecundus sp. n. – a cryptic Eurocaucasian ant species (Hymenoptera, Formicidae) discovered by Nest Centroid Clustering. ZooKeys 479: 37-64. https://doi.org/10.3897/zookeys.479.8510
Figure 9 - Temnothorax crasecundus sp. n. (grey branch) and Temnothorax crassispinus (black branch). NC-Ward clustering. Data set of Seifert: 104 nest samples investigated and 18 characters considered. Arrows point to samples clustered in disagreement with the final species hypothesis.
Figure 11 from: Seifert B, Csösz S (2015) Temnothorax crasecundus sp. n. – a cryptic Eurocaucasian ant species (Hymenoptera, Formicidae) discovered by Nest Centroid Clustering. ZooKeys 479: 37-64. https://doi.org/10.3897/zookeys.479.8510
Figure 11 - Temnothorax crasecundus sp. n. [black rectangles] and Temnothorax crassispinus [white rhombs]. The parapatric distribution is clearly shown.
Figures 25-27 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figures 25-27 - Nesomyrmex medusus sp. n. holotype worker (CASENT0455428). Lateral view of the body (25), head of the holotype worker in full-face view (26), dorsal view of the body (27). Scale 0.5 mm.
Figures 22-24 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figures 22-24 - Nesomyrmex hafahafa sp. n. holotype worker (CASENT0460666). Lateral view of the body (22) head of the holotype worker in full-face view (23), dorsal view of the body (24). Scale 0.5 mm.
Figures 19-21 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figures 19-21 - Nesomyrmex capricornis sp. n. holotype worker (CASENT0452741). Lateral view of the body (19), head of the holotype worker in full-face view (20), dorsal view of the body (21). Scale 0.5 mm.
Figures 15-18 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figures 15-18 - Anterodorsal view of the propodeal spines and anterodorsal spines on the petiolar node of Nesomyrmex spinosus sp. n. (15), Nesomyrmex hafahafa sp. n. (16), Nesomyrmex medusus sp. n. (17), Nesomyrmex capricornis sp. n. (18). Contour lines of propodeal spines, anterodorsal petiolar spines and the left lateral margin of the petiole are drawn.
Figure 13 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figure 13 - Dendrogram for NC-clustering scores with AU/BP values (%), classification of objects based on recursive partitioning with mesosomal profile of four species of hafahafa species-group is mapped on distributional map of Madagascar. Abbreviations: AU = approximately unbiased P-value, BP = bootstrap probabilities before statistical adjustments. Rectangles show the final species hypothesis. Color codes: Nesomyrmex capricornis sp. n. (yellow), Nesomyrmex hafahafa sp. n. (red), Nesomyrmex medusus sp. n. (blue), Nesomyrmex spinosus sp. n. (green).
Figure 14 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figure 14 - Scatterplot of discriminant scores DL1 and LD2 for Nesomyrmex capricornis sp. n. (red), Nesomyrmex hafahafa sp. n. (green), Nesomyrmex medusus sp. n. (blue), Nesomyrmex spinosus sp. n. (lilac) is illustrated. Convex hull graphically displays boundaries between sets of points forming different clusters. Classification functions for LD1 and LD2 are given in the text.
Figure 12 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figure 12 - Gap statistic for dataset of hafahafa species-group. Four-cluster solution is highly supported by the elbow at 4 components by the dispersion curve (left) and by the peak at cluster number four by the gap curve (right). Number of clusters in the data (X axis), the total within-cluster dispersion for each evaluated partition (Y axis for the left plot) and the vector of length Kmax giving the Gap statistic for each evaluated partition (Y axix for the right plot) is illustrated.
Figures 7-11 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figures 7-11 - Diagnostic characters for workers of all species-groups outlined in this paper. Lateral view of mesosoma, petiole and postpetiole of a member of the hafahafa species-group (7), dorsal view of mesosoma, petiole and postpetiole of angulatus species-group (8), dorsal view of mesosoma, petiole and postpetiole of madecassus species-group (9), lateral view of mesosoma, petiole and postpetiole of madecassus species-group (10), lateral view of mesosoma, petiole and postpetiole of sikorai species-group (11). For details see main text.
Figures 28-30 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figures 28-30 - Nesomyrmex spinosus sp. n. paratype worker (CASENT0443532). Lateral view of the body (28), head of the holotype worker in full-face view (29), dorsal view of the body (30). Scale 0.5 mm.
Figures 1-6 from: Csősz S, Fisher BL (2015) Diagnostic survey of Malagasy Nesomyrmex species-groups and revision of hafahafa group species via morphology based cluster delimitation protocol. ZooKeys 526: 19-59. https://doi.org/10.3897/zookeys.526.6037
Figures 1-6 - Measurement lines for metric characters. Head in dorsal view (1) with measurement lines for CL, CW, CWB and PoOC; frontal region of the head dorsum (2) with measurement lines for FRS; dorsal view of mesosoma (3) with measurement lines for NSTI, SPBA and SPTI; dorsal view of mesosoma (4) with measurement lines for MW, PSTI, PEW and PPW; lateral view of mesosoma (5) with measurement lines for ML and PEL; lateral view of mesosoma petiole and postpetiole (6) with measurement lines for MPST, NOL, PPL and SPST.
Reliable efficient cluster routing protocol based HTDE scheme for UWSN
<p>Underwater sensor networks (UWSNs) are recently recognized as a promising method for monitoring and exploring the underwater environment. Due to real-time remote data monitoring requirements, UWSN has become a preferred network to a large extent. But reliable and efficient secure data transmission to the receiver is one of the most important challenges for UWSNs, often suffer from irreplaceable batteries and high latency for long-distance communications. The most challenging task is extending network life, shortening transmission distances for each node. Thus, this paper presents the reliable efficient cluster routing (RECR) protocol, optimal shortest path finding (OSPF) algorithm and hill transformation data encryption (HTDE) algorithm for UWSNs. The proposed encryption algorithm encrypts the data from the source node, and the RECR protocol is used for reliable data delivery from source to destination. To extend the network's life, RECR employs autonomous underwater vehicle (AUV) from the sink node (SN) for data collection. The OSPF algorithm is used to find the shortest path for data transmission to avoid latency. The proposed RECR protocol, HTDE and OSPF algorithm enhance the secure data transmission efficiency, minimizing the energy consumption and improves the network life time. The proposed protocol decreases end-to-end latency, packet loss.</p>
Supplementary Materials for article on entitled 'Structure and usage do not explain each other: An analysis of German word-initial clusters', published in Linguistics
<p>See the article for a description of the data</p>
AGN Feedback in the Survey era: Insights into large samples of Clusters and Groups through LOFAR, MeerKAT and eROSITA
<p>In the last two decades, significant improvements have been made in the understanding of how AGN feedback operates in galaxy clusters. However, the vast majority of these studies involved observations of small samples, mostly lying in the high mass (M> 5 x 10^14 Msun) regime. We will present recent works in which we make use of survey observations performed by VLA, LOFAR and MeerKAT in the radio band, as well as eROSITA, Chandra and XMM-Newton in the X-rays, to investigate AGN feedback on the macro scale in large (N>200) samples of galaxy clusters and groups, down to masses of 2 x 10^13 Msun. We find a close relation between the X-ray emission -estimated within the whole cluster/group extent- and the radio emission produced by the central AGN. Statistical tests show that this correlation is not dominated by biases or selection effects. After converting the radio power into kinetic luminosity, we find an even tighter relation which seemingly exists for both disturbed and relaxed objects. Exploiting a subsample composed by COSMOS spectroscopic galaxy members, we find that Brightest Cluster Galaxies hosting strong AGN radio emission always lie within 0.2 virial radii from the cluster centre, and that there is an higher probability of stronger AGN being hosted in more massive systems. All these observations support the picture of a strong connection between the ICM and radio galaxies hosted in BCGs, which is also predicted by Chaotic Cold Accretion (CCA) models.</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.