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FIGURE 5. Dorsal habitus photographs. a in Revised classification of the New World Cylapini (Heteroptera: Miridae: Cylapinae): taxonomic review of the genera Cylapinus, Cylapoides and Peltidocylapus and a morphology-based phylogenetic analysis of tribe Cylapini
FIGURE 5. Dorsal habitus photographs. a. Peltidocylapus nubilus (lectotype); b. Peltidocylapus pallidus (holotype); c. Peltidocylapus parallelus (holotype); d. Peltidocylapus picatus (holotype); e. Peltidocylapus politus (holotype).
FIGURE 6. Dorsal habitus photographs. a in Revised classification of the New World Cylapini (Heteroptera: Miridae: Cylapinae): taxonomic review of the genera Cylapinus, Cylapoides and Peltidocylapus and a morphology-based phylogenetic analysis of tribe Cylapini
FIGURE 6. Dorsal habitus photographs. a. Peltidocylapus rugosus (lectotype); b. Peltidocylapus scutellaris (♂, Costa Rica); c. Peltidocylapus simplex (holotype); d. Peltidocylapus spinosus (holotype).
FIGURE 1. Strict consensus tree obtained from 12 in Revised classification of the New World Cylapini (Heteroptera: Miridae: Cylapinae): taxonomic review of the genera Cylapinus, Cylapoides and Peltidocylapus and a morphology-based phylogenetic analysis of tribe Cylapini
FIGURE 1. Strict consensus tree obtained from 12 most parsimonious trees under equal weights. Bremer support values are indicated below branches.
FIGURE 4. Dorsal habitus photographs. a in Revised classification of the New World Cylapini (Heteroptera: Miridae: Cylapinae): taxonomic review of the genera Cylapinus, Cylapoides and Peltidocylapus and a morphology-based phylogenetic analysis of tribe Cylapini
FIGURE 4. Dorsal habitus photographs. a. Peltidocylapus calyciformis (paratype, ♂); b. Peltidocylapus caudatus (holotype); c. Peltidocylapus cerbereus (lectotype); d. Peltidocylapus ecuadorensis (holotype); e. Peltidocylapus festinabundus (♀, Peru).
FIGURE 9. Scanning electron micrographs. a–f in Revised classification of the New World Cylapini (Heteroptera: Miridae: Cylapinae): taxonomic review of the genera Cylapinus, Cylapoides and Peltidocylapus and a morphology-based phylogenetic analysis of tribe Cylapini
FIGURE 9. Scanning electron micrographs. a–f. Head and pronotum (left lateral view); g–i. Head (anterior view); j, k. Labium; l. Body (left lateral view). a. Valdasus flavinotum; b, h. Corcovadocola sp.; c, i. Vannius podager; d, k. Bothriomiris dissimulans; e. Fulvius pallens; f. Rhinomiris sp.; g. Valdasus schoechnerri; j. Cylapus tenuicornis Say; l. Cylapocoris sp..
FIGURE 8 in Revised classification of the New World Cylapini (Heteroptera: Miridae: Cylapinae): taxonomic review of the genera Cylapinus, Cylapoides and Peltidocylapus and a morphology-based phylogenetic analysis of tribe Cylapini
FIGURE 8. Head and pronotum, anterior (a–j, l, m) and lateral (k) views. a. Cylapinus yasunagai (paratype); b. Cylapoides unicolor (♀); c. Cylapus ruficeps Bergroth (♂); d. Cylapus tenuicornis (♂); e. Peltidocylapus calyciformis (paratype); f. Peltidocylapus caudatus (paratype); g. Peltidocylapus rugosus (holotype); h. Peltidocylapus simplex (paratype); i. Cylapomorpha sp. (♂); j, k. Vanniusoides clypeatus (paratype); l. Fulvius pallens (♂); m. Rhinocylapus vittatus (♀).
Image-based taxonomic classification of bulk biodiversity samples using deep learning and domain adaptation
<p>Complex bulk samples of insects from biodiversity surveys present a challenge for taxonomic identification, which could be overcome by high-throughput imaging combined with machine learning for rapid classification of specimens. These procedures require that taxonomic labels from an existing source data set are used for model training and prediction of an unknown target sample. However, such transfer learning may be problematic for the study of new samples not previously encountered in an image set, e.g. from unexplored ecosystems, and require methods of domain adaptation that reduce the differences in the feature distribution of the source and target domains (training and test sets). We assessed the efficiency of domain adaptation for family-level classification of bulk samples of Coleoptera, as a critical first step in the characterisation of biodiversity samples. Neural network models trained with images from a global database of Coleoptera were applied to a biodiversity sample from understudied forests in Cyprus as the target. Within-dataset classification accuracy reached 98% and depended on the number and quality of training images and on dataset complexity. The accuracy of between-datasets predictions (across disparate source-target pairs that do not share any species or genera) was at most 82% and depended greatly on the standardisation of the imaging procedure. Algorithms for domain adaptation significantly improved the prediction performance of models trained by non-standardised, low-quality images. Our findings demonstrate that existing databases can be used to train models and successfully classify images from unexplored biota, but the imaging conditions and classification algorithms need careful consideration.</p>
FIGURE 12 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 12. The scape transverse sections of the genus Tulipa (A˗R). A. T. agenensis. B. T. aleppensis. C. T. armena var. armena. D. T. armena var. galatica. E. T. julia. F. T. raddii. G. T. sintenisii. H. T. undulatifolia var. undulatifolia. I. T. clusiana. J. T. biflora. K. T. cinnabarina subsp. cinnabarina. L. T. humilis. M. T. koyuncui. N. T. orphanidea. O. T. pulchella. P. T. saxatilis. Q. T. sylvestris subsp. australis. R. T. sylvestris subsp. sylvestris, cu: cuticle, ep: epidermis, cl: collenchyma, co: cortex, ph: phloem, xy: xylem, sc: sclerenchyma.
FIGURE 13 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 13. The leaf transverse sections of the genus Tulipa (A˗R). A. T. agenensis. B. T. aleppensis. C. T. armena var. armena. D. T. armena var. galatica. E. T. julia. F. T. raddii. G. T. sintenisii. H. T. undulatifolia var. undulatifolia. I. T. clusiana. J. T. biflora. K. T. cinnabarina subsp. cinnabarina. L. T. humilis. M. T. koyuncui. N. T. orphanidea. O. T. pulchella. P. T. saxatilis. Q. T. sylvestris subsp. australis. R. T. sylvestris subsp. sylvestris, cu: cuticle, ue: upper epidermis, le: lower epidermis, p: parenchyma, ph: phloem, xy: xylem, st: stomata.
FIGURE 14 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 14. The leaf surface section of the genus Tulipa (each photo represents 1 mm2): 1˗T. agenensis, 2˗T. aleppensis, 3˗T. armena var. armena, 4˗T. armena var. galatica, 5˗T. julia, 6˗T. raddii, 7˗T. sintenisii, 8˗T. undulatifolia var. undulatifolia, 9˗T. clusiana, 10˗T. biflora, 11˗T. cinnabarina subsp. cinnabarina, 12˗T. humilis, 13˗T. koyuncui, 14˗T. orphanidea, 15˗T. pulchella, 16˗T. saxatilis, 17˗T. sylvestris subsp. australis, 18˗T. sylvestris subsp. sylvestris, a-lower epidermis, b-upper epidermis, epc: epidermis cell, st: stoma.
FIGURE 11 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 11. The root transverse sections of the genus Tulipa (A˗R). A. T. agenensis. B. T. aleppensis. C. T. armena var. armena. D. T. armena var. galatica. E. T. julia. F. T. raddii. G. T. sintenisii. H. T. undulatifolia var. undulatifolia. I. T. clusiana. J. T. biflora. K. T. cinnabarina subsp. cinnabarina. L. T. humilis. M. T. koyuncui. N. T. orphanidea. O. T. pulchella. P. T. saxatilis. Q. T. sylvestris subsp. australis. R. T. sylvestris subsp. sylvestris, ep: epidermis, ex: exodermis, co: cortex, en: endodermis, pe: pericycle, mx: metaxylem, ph: phloem, px: protoxylem.
FIGURE 10 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 10. Dendrogram of average linkage (between groups)-squared euclidean distance in the hierarchical cluster analysis of 42 populations (OTUs).
FIGURE 9 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 9. Dendrogram of average linkage (between groups)-Manhattan distance in the hierarchical cluster analysis of 42 populations (OTUs).
FIGURE 2 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 2. Measurements of quantitavive characters related to leaf (µm) ― 21˗RPL: row number of parenchymatous cells at leaf section, 22a˗UPW: width of upper epidermal cells at leaf section, 22b˗UPL: length of upper epidermal cells at leaf section, 23a˗LOW: width of lower epidermal cells at leaf section, 23b˗LOL: length of lower epidermal cells at leaf section, 24a˗PLW: width of parenchymatous cells at leaf section, 24b˗PLL: length of parenchymatous cells at leaf section, 25a˗XEW: width of xylem elements at leaf section, 25b˗XEL: length of xylem elements at leaf section, 26a˗PMW: width of phloem elements at leaf section, 26b˗PML: length of phloem elements at leaf section, 27˗RSI: ratio of stoma index (not indicated on figure).
FIGURE 1 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 1. Measurements of quantitavive characters (µm). A, B. Root; 1˗CXW: width of cortex region at root section, 2a˗ERW: width of epidermal cells at root section, 2b˗ERL: length of epidermal cells at root section, 3a˗EXW: width of exodermal cells at root section, 3b˗EXL: length of exodermal cells at root section, 4a˗COW: width of cortex parenchymatous cells at root section, 4b˗COL: length of cortex parenchymatous cells at root section, 5˗RER: row number of endodermal cells at root section, 6˗RPR: row number of pericycle cells at root section, 7a˗ENW: width of endodermal cells at root section, 7b˗ENL: length of endodermal cells at root section, 8a˗PEW: width of pericycle cells at root section, 8b˗PRL: length of pericycle cells at root section, 9˗NPR: number of protoxylem at root section, 10˗NMR: number of metaxylem elements at root section, 11a˗MXW: width of metaxylem elements at root section, 11b˗MXL: length of metaxylem elements at root section. C, D. Scape; 12˗DSS: diameter of scape section, 13˗ANP: the average number of cell in pith at scape section, 14a˗EPW: width of epidermal cells at scape section, 14b˗EPL: length of epidermal cells at scape section, 15a˗CLW: width of collenchyma cells at scape section, 15b˗CLL: length of collenchyma cells at scape section, 16a˗PAW: width of parenchymatous cells at scape section, 16b˗PAL: length of parenchymatous cells at scape section, 17˗RSS: row number of sclerenchyma cells at scape section, 18a˗PHW: width of phloem elements at scape section, 18b˗PEL: length of phloem elements at scape section, 19a˗SSW: width of sclerenchyma cells at scape section, 19b˗SSL: length of sclerenchyma cells at scape section, 20a˗XYW: width of xylem elements at scape section, 20b˗XYL: length of xylem elements at scape section.
FIGURE 3 in Taxonomic implications of anatomical characteristics of the genus Tulipa (Liliaceae) in Turkey and their place in the historical subgeneric classifications
FIGURE 3. Grouping and coding the character states of a quantitative character on a modified Whisker's graph.
FIGURE 5. Chamaecrista viscosa. A and B. Habit, C and D. Foliage, E. Leaves. Inflorescence, G in Taxonomic revision of Chamaecrista sect. Absus subsect. Absus (Leguminosae, Caesalpinioideae) with adjustments in the new classification
FIGURE 5. Chamaecrista viscosa. A and B. Habit, C and D. Foliage, E. Leaves. Inflorescence, G. Buds, DE. Flower, E. Fruits. Photographs by A.O. Souza.
FIGURE. Chamaecrista oligosperma. A. Fertile branch, B in Taxonomic revision of Chamaecrista sect. Absus subsect. Absus (Leguminosae, Caesalpinioideae) with adjustments in the new classification
FIGURE. Chamaecrista oligosperma. A. Fertile branch, B. Detail of the indumentum of the branch, C. Stipule, D and E. Leaflets, F. Bract, G. Bracteole, H. Bud, I. Flower, J. Sepal, K. Petals, L. Stamen, M. Gynoecium, N. Fruit. Drawned by Renato Galhardo.
FIGURE 6. Chamaecrista viscosa. A. Fertile branch, B in Taxonomic revision of Chamaecrista sect. Absus subsect. Absus (Leguminosae, Caesalpinioideae) with adjustments in the new classification
FIGURE 6. Chamaecrista viscosa. A. Fertile branch, B. Detail of the indumentum of the branch, C. Stipule, D. Leaf, E. Detail of the abaxial face of the leaflet, F. Bud, G. Flower, H. Sepal, I. Petals, J. Stamen, K. Gynoecium, L. Fruit. Drawned by Renato Galhardo.
FIGURE. Chamaecrista jacobinea. A. Fertile branch, B in Taxonomic revision of Chamaecrista sect. Absus subsect. Absus (Leguminosae, Caesalpinioideae) with adjustments in the new classification
FIGURE. Chamaecrista jacobinea. A. Fertile branch, B. Detail of the indumentum of the branch, C. Stipule, D. Leaf, E. Detail of the abaxial face of the leaflet, F. Bract, G. Bud, H. Flower, I. Sepal, J. Petals, K. Stamen, L. Gynoecium, M. Fruit. Drawned by Renato Galhardo.
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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)
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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.