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Figure 5 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 5. Pronota of Aneflomorpha Casey. a) A. aculeata (LeConte), holotype. b) A. arizonica Linsley. c) A. cazieri Chemsak. d) A. citrana Chemsak, holotype. e) A. crypta Lingafelter, n. sp. f) A. delongi (Champlain and Knull). g) A. fisheri Linsley. h) A. gilana Casey. i) A. linearis (LeConte), holotype. j) A. linsleyae Chemsak. k) A. luteicornis Linsley. l) A. minuta Chemsak.
Figure 6 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 6. Pronota of Aneflomorpha Casey. m) A. opacicornis Linsley (Neaneflus, herein). n) A. parkeri Knull, holotype. o) A. parowana Casey, lectotype. p) A. paralinearis Lingafelter, n. sp., holotype. q) A. rectilinea Casey, Arizona. r) A. rectilinea Casey, Texas. s) A. seminuda Casey, holotype. t) A. subpubescens (LeConte). u) A. tenuis (LeConte). v) A. unispinosa Casey, holotype. w) A. texana Linsley. x) A. yumae Giesbert and Hovore, paratype.
Figure 25 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 25. Basal antennomeres (a, b) and pronota (c, d) of Aneflomorpha. a) A. tenuis. b) A. cazieri. c) A. tenuis. d) A. cazieri.
Figure 3 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 3. Aneflomorpha Casey of the United States. a) A. subpubescens (LeConte). b) A. tenuis (LeConte). c) A. texana Linsley, holotype. d). A. texana Linsley, Davis Mountains, Texas specimen. e) A. unispinosa Casey, holotype. f) A. yumae Giesbert and Hovore, paratype.
Figure 13 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 13. Aneflomorpha gilana holotype compared to A. parkeri holotype. a) A. gilana holotype, dorsal and lateral views. b) A. parkeri holotype, dorsal and lateral views. c) A. gilana holotype, elytral apices. d) A. parkeri holotype, elytral apices.
Figure 32 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 32. Basal antennomeres and pronotum in Aneflomorpha. a) A. seminuda. b) A. cazieri. c) A. cazieri. d) A. seminuda.
Figure 10 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 10. Procoxal cavities and intercoxal prosternal processes of Aneflomorpha Casey. a) A. aculeata (LeConte), holotype. b) A. arizonica Linsley. c) A. cazieri Chemsak. d) A. citrana Chemsak, holotype. e) A. crypta Lingafelter, n. sp., holotype. f) A. delongi (Champlain and Knull). g) A. fisheri Linsley. h) A. gilana Casey. i) A. linearis (LeConte), holotype. j) A. linsleyae Chemsak. k) A. luteicornis Linsley. l) A. minuta Chemsak. m) A. opacicornis Linsley (Neaneflus, herein). n) A. parkeri Knull, holotype. o) A. parowana Casey, lectotype. p) A. paralinearis Lingafelter, n. sp., paratype. q) A. rectilinea Casey, Arizona. r) A. rectilinea Casey, Texas. s) A. seminuda Casey, holotype. t) A. subpubescens (LeConte). u) A. tenuis (LeConte). v) A. unispinosa Casey, holotype. w) A. texana Linsley. x) A. yumae Giesbert and Hovore, paratype.
Figure 34 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 34. Ventral structures of Aneflomorpha. a) A. crypta gula and prosternum. b) A. crypta, mesosternum. c) A. minuta, gula and prosternum. d) A. minuta, mesosternum.
Figure 4 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 4. Genera similar to Aneflomorpha Casey. a) Aneflus levettei (Casey). b) Anelaphus brevidens (Schaeffer). c) Anopliomorpha rinconia (Casey). d) Elaphidion mucronatum (Say). e) Micraneflus imbellis (Casey), holotype. f) Micranoplium unicolor (Haldeman). g) Neaneflus fuchsii (Wickham), holotype. h) Orwellion gibbulum arizonense (Casey). i) Parelaphidion incertum (Newman). j) Pseudoperiboeum lengi (Schaeffer). k) Psyrassa unicolor (Randall). l) Stenelaphus alienus (LeConte).
Figs 31-34 in New records of Cerceris LATREILLE, 1802 (Hymenoptera, Spheciformes) from the United Arab Emirates
Figs 31-34: (31-32) Cerceris vagula KOHL, 1906. (31) Female. L = 8.5 mm. (32) Male. L = 9.0 mm; (33-34) Cerceris vittata LEPELETIER, 1845. (33) Female. L = 8.0 mm. (34) Male. L = 7.0 mm.
Figs 25-30 in New records of Cerceris LATREILLE, 1802 (Hymenoptera, Spheciformes) from the United Arab Emirates
Figs 25-30: (25-26) Cerceris straminea DUFOUR, 1853. (25) Female. L = 14.5 mm. (26) Male. L = 13.0 mm; (27-28) Cerceris tricolorata MOCHI, 1938. (27) Female from Oman. L = 10 mm. (28) Male. L = 9.0 mm; (29-30) Cerceris vagans RADOSZKOWSKI, 1877. (29) Female. L = 8.7 mm. (30) Male. L = 9.0 mm.
Figs 1-6 in New records of Cerceris LATREILLE, 1802 (Hymenoptera, Spheciformes) from the United Arab Emirates
Figs 1-6: (1-2) Cerceris albicincta KLUG, 1845. (1) Female. L = 9.0 mm. (2) Male. L = 7.0 mm; (3-4) Cerceris alboatra MOCHI, 1938. (3) Female. L = 14.0 mm. (4) Male. L = 13.0 mm; (5-6) Cerceris chromatica SCHLETTERER, 1887. (5) Female. L = 9.5 mm. (6) Male. L = 9.0 mm.
New indicators of ecological resilience and invasion resistance to support prioritization and management in the sagebrush biome, United States
<p>Ecosystem transformations to altered or novel ecological states are accelerating across the globe. Indicators of ecological resilience to disturbance and resistance to invasion can aid in assessing risks and prioritizing areas for conservation and restoration. The sagebrush biome encompasses parts of 11 western states and is experiencing rapid transformations due to human population growth, invasive species, altered disturbance regimes, and climate change. We built on prior use of static soil moisture and temperature regimes to develop new, ecologically relevant and climate-responsive indicators of both resilience and resistance. Our new indicators were based on climate and soil water availability variables derived from process-based ecohydrological models that allow predictions of future conditions. We asked: (1) Which variables best indicate resilience and resistance? (2) What are the relationships among the indicator variables and resilience and resistance categories? (3) How do patterns of resilience and resistance vary across the area? We assembled a large database (n = 24,045) of vegetation sample plots from regional monitoring programs and derived multiple climate and soil water availability variables for each plot from ecohydrological simulations. We used USDA Natural Resources Conservation Service National Soils Survey Information, Ecological Site Descriptions, and expert knowledge to develop and assign ecological types and resilience and resistance categories to each plot. We used random forest models to derive a set of 19 climate and water availability variables that best predicted resilience and resistance categories. Our models had relatively high multiclass accuracy (80% for resilience; 75% for resistance). Top indicator variables for both resilience and resistance included mean temperature, coldest month temperature, climatic water deficit, and summer and driest month precipitation. Variable relationships and patterns differed among ecoregions but reflected environmental gradients; low resilience and resistance were indicated by warm and dry conditions with high climatic water deficits, and moderately high to high resilience and resistance were characterized by cooler and moister conditions with low climatic water deficits. The new, ecologically-relevant indicators provide information on the vulnerability of resources and likely success of management actions and can be used to develop new approaches and tools for prioritizing areas for conservation and restoration actions.</p>
Figs 19-24 in New records of Cerceris LATREILLE, 1802 (Hymenoptera, Spheciformes) from the United Arab Emirates
Figs 19-24: (19-20) Cerceris pulchella KLUG, 1845. (19) Female. L = 9.0 mm. (20) Male. L = 8.0 mm; (21-22) Cerceris sabulosa (PANZER, 1799). (21) Female from Turkey. L = 10.5 mm. (22) Male. L = 11.0 mm; (23-24) Cerceris solitaria DAHLBOM, 1845. (23) Female from Oman. L = 18.0 mm. (24) Male. L = 16.0 mm.
Data for "Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms"
<p>This repository contains the data and external data used by teams in the Kaggle competition "HuBMAP+HPA - Hacking the Human Body" and is part of the paper "Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms".</p> <p>The directories contain:</p> <p><strong>data.zip:</strong> The training and test data, including metadata, used in the Kaggle competition "HuBMAP + HPA - Hacking the Human Body".</p> <p><strong>Team_1.zip: </strong>External data used by the first place winning solution.</p> <p><strong>Team_2.zip: </strong>External data used by the second place winning solution.</p>
Trained Models for "Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms"
<p>This repository contains the trained model weights for the baseline model and the winning solutions in the Kaggle competition "HuBMAP+HPA - Hacking the Human Body", and is part of the paper "Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms".</p> <p>The directory contains:</p> <p><strong>trained_model_1_weights.zip: </strong>Trained model weights for first place solution (Team 1).</p> <p><strong>trained_model_2_weights.zip:</strong> Trained model weights for second place solution (Team 2).</p> <p><strong>trained_model_3_weights.zip: </strong>Trained model weights for third place solution (Team 3).</p> <p><strong>trained_model_weights_baseline.zip:</strong> Trained model weights for the baseline model.</p>
Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use
<p>Changes in climate and land-use and land-cover (LULC) are expected to influence surface water runoff and nutrient characteristics of estuarine watersheds, but the extent to which estuaries are vulnerable to altered nutrient loading under future conditions is poorly understood. The present work aims to address this gap through the development of a new vulnerability assessment framework that accounts for (1) estuarine exposure to projected changes in total nitrogen (TN) and total phosphorus (TP) loads as a function of LULC and climate change under several scenarios to altered nutrient loads, (2) sensitivity (i.e., how responsive estuaries are to altered nutrient loads), and (3) adaptive capacity (i.e., how the socio-ecological system can use existing resources to reduce the impacts associated with increased exposure). The framework was applied to 112 estuaries and their contributing watersheds across the contiguous U.S., specifically to look at regional variability in estuarine vulnerability to nutrient loading. Study findings revealed that the largest increases in estuarine nutrient loads are expected in the North and South Atlantic regions and eastern Gulf of Mexico, while the lowest increase is expected in the North and South Pacific regions and the western Gulf of Mexico. However, the North Atlantic and the South Pacific had the highest adaptive capacity, which could potentially counteract the effects of LULC and climate change on nutrient loads. Our findings illustrate the benefits of integrating natural and socio-ecological factors to identify opportunities to develop adaptation plans and policies to mitigate ecological degradation in vitally important estuaries. A<a href="https://lisemontefiore.shinyapps.io/estuarine_vulnerability/"> web-based application</a> has been developed to visualize and download the data.</p>
Radiometric dating of sediment cores from three alpine lakes in Utah, United States, with stable isotope data
<p>We collected sediment cores from three alpine lakes in Utah, United States, to isolate dormant <em>Daphnia </em>eggs for a resurrection ecology experiment. Our question was whether radioactive fallout from above-ground nuclear weapons testing at the Nevada Test Site in the 1950s and 1960s caused increased mutation rates and population evolution in <em>Daphnia</em>. That work is ongoing. Here, we publish radioisotope dating profiles from our sediment cores.</p>
FIG. 32. — A in The species of Lageninae Brady, 1881 (Foraminifera) from the Pliocene-Early Pleistocene of north-western France, Fécamp (Seine-Maritime, France) and St Erth (Cornwall, United Kingdom)
FIG. 32. — A, Lagena striata (d'Orbigny, 1839), SGB3, enlargement of the aboral tube; B, C, Lagena substriata Williamson, 1848, LRK2: B, basal internal view; C, enlargement of the aboral tube; D, E, Lagena sulcata (Walker & Jacob, 1798), SGB3; D, longitudinal section; E, enlargement of the aboral tube; F, G, Lagena variokoreana n. sp., LRK2: F, basal internal view; G, enlargement of the aboral view; H, I, Lagunculella grayi n. gen., n. sp., LRK2 (MNHN.F.F67688): H, basal internal view; I, enlargement of the aboral tube; J-M, Lagunculella baggi (Cushman & Gray, 1946), n. comb., SGB3: J, basal internal views; K, enlargement of the aboral tube; L, longitudinal section; M, enlargement of the aboral tube; N, Lagunculella doveyensis (Haynes, 1973), n. comb., Fécamp (MNHN.F.F67692), basal internal view; O, P, Lagunculella flexa (Cushman & Gray, 1946), n. comb., la Sautré (MNHN.F.F67695): O, basal internal view; P, enlargement of the aboral tube. Scale bars: A, I, P, 20 µm; B, D, F, 100 µm; C, E, K, M, 10 µm; G, 5 µm; H, J, L, N, 50 µm; O, 200 µm.
FIG. 33. — A, B in The species of Lageninae Brady, 1881 (Foraminifera) from the Pliocene-Early Pleistocene of north-western France, Fécamp (Seine-Maritime, France) and St Erth (Cornwall, United Kingdom)
FIG. 33. — A, B, Lagunculella flexa (Cushman & Gray, 1946), n. comb., Fécamp (MNHN.F.F6760): A, internal basal view; B, enlargement of the aboral view; C, D, Lagunculella ovoidea n. gen., n. sp., la Pugle; C, internal basal view; D, enlargement of the aboral view; E, F, Lagunculella redonensis n. gen., n. sp., la Groussinière: E, internal basal view; F, enlargement of the aboral tube; G, H, Lanterna crassicarinata n. gen., n. sp., la Groussinière: G, internal basal view; H, enlargement of the aboral tube; I, J, Lanterna novocrassicarinata n. gen., n. sp., la Groussinière (MNHN.F.F67707): I, internal basal view; J, enlargement of the aboral tube; K, L, Malumella oblonga n. gen., n. sp., la Groussinière: K, internal basal view; L, enlargement of the aboral tube; M, N, Verulagena similis (McCulloch, 1977), n. comb., la Bouillonnaie: M, internal basal view; N, enlargement of the aboral view; O, P, Verulagena laevis (Montagu, 1803), n. comb., St. Erth: O, longitudinal section showing the aboral tube; P, internal basal view. Scale bars: A, O, 50 µm; B, D, N, 10 µm; C, E, G, I, K, M, P, 100 µm; F, H, J, L, 20 µm.
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.