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Control generation of eddy available potential energy
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FIGURES 1–3 in Ascidae, Blattisociidae and Melicharidae (Acari: Mesostigmata): zoogeographic analyses based on newly available databases
FIGURES 1–3. Cladograms representing the unique consensus trees obtained from the PAE analysis carried out (1) on the family Ascidae: CI = 0.84, RI = 0.34, RC = 0.29; (2) on the family Blattisociidae: CI = 0.81, RI = 0.19, RC = 0.16; (3) on the family Melicharidae: CI = 0.88, RI = 0.52, RC = 0.45. The numbers at the nodes correspond to bootstrap values.
FIGURE 6 in Ascidae, Blattisociidae and Melicharidae (Acari: Mesostigmata): zoogeographic analyses based on newly available databases
FIGURE 6. Zoogeographic region distribution analysis carried out on the genera of the family Melicharidae.
FIGURES 4–5 in Ascidae, Blattisociidae and Melicharidae (Acari: Mesostigmata): zoogeographic analyses based on newly available databases
FIGURES 4–5. Zoogeographic region distribution analysis carried out on the genera of the families (4) Ascidae, (5) Blattisociidae.
Supplementary material 1 from: Rosenfeld S, Marambio J, Ojeda J, Rodríguez JP, González-Wevar C, Gerard K, Contador T, Pizarro G, Mansilla A (2018) Trophic ecology of two coexisting Sub-Antarctic limpets of the genus Nacella: Spatio-temporal variation in food availability and diet composition of Nacella magellanica and N. deaurata in the Sub-Antarctic Ecoregion of Magellan . ZooKeys 738: 1-25. https://doi.org/10.3897/zookeys.738.21175
Tables S1–S11 : Explanation note: This is a DOC file with all the temporal information of the occurrence of the algae taxa in both localities, and all the information of the PERMANOVA analyzes used in this study.
Survival under conditions of variable food availability: Resource utilization and storage in the cold‐water coral Lophelia pertusa
<p>Abstract</p> <p>Cold-water coral (CWC) reefs are hotspots of biodiversity and productivity in the deep sea, but their distribution is limited by the availability of food, which undergoes complex local and temporal variability. We studied the resource utilization, metabolism, and tissue storage of CWC Lophelia pertusa during an experimentally simulated 3-day food pulse, of 13C15N-enriched phytodetritus, followed by a 4-week food deprivation. Oxygen consumption (0.145 μmol O2 [mmol organic carbon {OC}]−1 h−1), release of particulate organic matter (0.029 μmol particulate organic carbon [POC] [mmol OC]−1 h−1 and 0.005 μmol particulate organic nitrogen [mmol OC]−1 h−1), ammonium excretion (0.004 μmol NH4 + [mmol OC]−1 h−1), tissue C and N content, and fatty acid (FA) and amino acid composition did not change significantly during the experiment. Metabolization of the labeled phytodetritus, however, underwent distinct temporal dynamics. Initially, L. pertusa preferentially used phytodetritus-derived C for respiration (2.2 0.36 nmol C [mmol OC]−1 h−1) and mucus production (0.94 0.52 nmol C [mmol OC]−1 h−1), but those tracer fluxes declined exponentially to <20% within 2 weeks after feeding and then remained stable, indicating that the remainder of the incorporated phytodetritus had entered a tissue pool with lower turnover. Analysis of 13C in individual FAs revealed a mismatch between the FAs incorporated from phytodetritus and the FA requirements of the coral.We suggest that feeding on other resources, such as lipid-rich zooplankton, could fill this deficiency. A release of 10% of their total OC as respired C and POC during the 4-week food deprivation underlines the importance of regular food pulses for CWC reefs. </p>
Stock Availability of Farms and Slaughtering
<p>Stock Availability of Farms and Slaughtering stats</p>
DTU 10MW reference turbine HAWC2 simulations for Model-free estimation of available power with deep learning training
<p>The time series of DTU 10MW HAWC2 model simulations of two channels: hub-height wind speed and produced power. They are generated to train model-free estimation of available power approach, using wind speed and its moving standard deviation as inputs. They include 3-hour length 100Hz simulations of 3 mean wind speeds (7 m/s, 9m/s and 11m/s) as well as 3 levels of turbulence intensity (TI = 7%, 10% and 20%). </p> <p>The dataset and the training algorithm can also be found here: <a href="https://gitlab.windenergy.dtu.dk/tuhf/deep-learning-for-available-power-estimation/tree/master">https://gitlab.windenergy.dtu.dk/tuhf/deep-learning-for-available-power-estimation/tree/master</a></p>
Fig. 2 in Survival of termites (Isoptera) exposed to various levels of relative humidity (RH) and water availability, and their RH preferences
Fig. 2. Materials for determining relative humidity (RH) level preferences of four termite species. A) Arena with chamber lids in place: a: chamber lid; b: rubber stopper; c: jar chamber. B) Arena with chamber lids removed: d: filter paper semicircle; e: Drierite introduction chamber; f: H2O chamber; g: MgCl2 camber; h: Mg(NO3)2 chamber; i: NaCl chamber. C) Close-up of arena components housing termites: j: connecting tube; k: holding dish; l: filter paper food source.
Fig. 1 in Survival of termites (Isoptera) exposed to various levels of relative humidity (RH) and water availability, and their RH preferences
Fig. 1. Experimental units to examine termite survival when exposed to various relative humidity (RH) levels: A) Humidity chambers with lids removed: a: H2O dish with filter paper ring (92.0 ± 0.07% RH); b: NaCl dish (72.9 ± 0.08% RH); c: Mg(NO3)2 dish (55.7 ± 0.09% RH); d: MgCl2 dish (34.3 ± 0.04% RH); e: silica gel layer (18.2 ± 0.14% RH); f: wood food source; g: holding dish with modified lid. B) Humidity chambers with lids in place: h: rubber stopper; i: temperature/humidity probe; j: chamber lid.
What KOS can do, with the proper tools available. About AGROVOC, edited in VocBench and used in the AGRIS web application
<p>The AIMS (Agricultural Information Management Standards) team in FAO has been working for the last 12 years towards two goals:<br>● using Knowledge Organization Systems to create better Information<br>Systems, and<br>● developing tools to maintain and produce better Knowledge Organization<br>Systems.<br>Our talk will initially demonstrate AGRIS, the International Information System for Agricultural Science and Technology. AGRIS has been developed<br>from a bibliographical database to a Linked Open Data application with more than 6 million web pages on topics from Agricultural Science and Technology.<br>This development was made possible by exploiting the various Knowledge Organization Systems embedded in the bibliographical database, most<br>notably AGROVOC. Parallel to creating AGRIS Linked Open Data we developed the VocBench, an advanced tool to maintain and improve SKOS<br>vocabularies (and more). The newest feature of the VocBench is now the automatic alignment of different vocabularies. Our talk will show the<br>advanced features of VocBench, and also the underlying philosophy and community.</p>
FIGURE 1 in On the availability of the family-group name Agathemeridae (Phasmatodea)
FIGURE 1. Photograph of a live adult male of Agathemera luteola Camousseight from Capilla del Monte, Argentina (courtesy of Bruno Kneubühler).
FIGURE 4 in Studies on Parmulariaceae I. A phylogeny based on available sequence data; introducing Parmulariales ord. nov., and Hemigraphaceae, Melaspileellaceae and Stictographaceae fam. nov.
FIGURE 4. Inocyclus psychotriae (NY 01102760, isolectotype). a. Herbarium material. b, c. Ascostromata on leaves. D. Squash mount of dark brown to black ascostroma. e, f. Hand section of ascostroma (Note: the peridium without apical cells). g–h. Asci with ascospores immersed in water. i. Asci with ascospores immersed in KOH. j–l. ascospores. Scale bars: b = 1 mm, c = 100 μm, d–f = 20 μm, g–l = 5 μm.
FIGURE 2 in Studies on Parmulariaceae I. A phylogeny based on available sequence data; introducing Parmulariales ord. nov., and Hemigraphaceae, Melaspileellaceae and Stictographaceae fam. nov.
FIGURE 2. Hemigrapha asteriscus (G 00292584, syntype). a. Herbarium material. b–d. Appearance of ascostromata on host surface. c, d. Ascostromata in the water. e–j. Section of ascostroma. h. Asci with hamathecial tissues. i–m. Asci. n, o. Ascospores. Scale bars: a = 20 mm, b–d = 500 μm, e–g = 50 μm, h–o = 5 μm.
FIGURE 1 in Studies on Parmulariaceae I. A phylogeny based on available sequence data; introducing Parmulariales ord. nov., and Hemigraphaceae, Melaspileellaceae and Stictographaceae fam. nov.
FIGURE 1. Maximum likelihood phylogenetic tree generated by RAxML (GTR+G model) based on analysis of combined LSU and SSU sequence data. ML values (>50 %) resulting from 1000 bootstrap replicates and Bayesian posterior probabilities greater than 0.80 are given at the nodes. The strain numbers are noted after the species names. The tree is rooted to Dendrographa decolorans (DUKE 0047570).
FIGURE 3 in Studies on Parmulariaceae I. A phylogeny based on available sequence data; introducing Parmulariales ord. nov., and Hemigraphaceae, Melaspileellaceae and Stictographaceae fam. nov.
FIGURE 3. Inocyclus psychotriae (K 180637, lectotype). a, b. Herbarium material. c, d. Ascostromata on leaves. E. Squash mount of dark brown to black ascostromata. f, g. Hand section of ascostroma (Note: the peridium without apical cells). h–l. Ascospores immersed in KOH. m–q. Asci with ascospores immersed in KOH. Scale bars: c =500 μm, d = 200 μm, e = 100 μm, f = 50 μm, g = 20 μm, h–l = 5 μm, m–q = 10 μm.
FIGURE 5 in Studies on Parmulariaceae I. A phylogeny based on available sequence data; introducing Parmulariales ord. nov., and Hemigraphaceae, Melaspileellaceae and Stictographaceae fam. nov.
FIGURE 5. Parmularia styracis (S F21306). A. Herbarium material. B. Appearance of ascostromata on upper of leaf surface. c, e, f. Black shield-like ascostroma. d. Dark brown ascostroma wall. G. Sections of ascostroma showing multi-locules. H. Wall cells of ascostroma. i, j. Asci with ascospores. K. Pseudoparaphyses with brown swollen apices. l–n. Immature hyaline ascospores. Scale bars: b =10 mm, c =1 mm, d = 5 μm, e, f = 500 μm, g=100 μm, h = 50 μm, i–k = 10 μm, l–n = 10 μm.
Differential molecular interactions between iberiotoxin and human SLO3 and SLO1 potassium channels: Data and Software Availability
<p>Considering the need for new male contraceptives, we evaluated the molecular interactions between the human SLO3 and SLO1 potassium channels and iberiotoxin, to provide structural insights for drug development. Here, we provide the supporting data of our manuscript.</p>
FIGURE 7 in A new species of planthopper in the genus Platocerella (Hemiptera: Auchenorrhyncha: Derbidae) from palms in Costa Rica, a key to the genus and an updated molecular phylogeny of available New World Otiocerinae
FIGURE 7. Maximum Likelihood phylogenetic trees based on 1000 replicates; A) 18S rRNA, B) D9-D10 expansion region of 28S rRNA, C) 5' region of COI, and D) consensus tree for concatenated sequence data for all three loci; scale bar = percent nucleotide difference.
FIGURE 2 in A new species of planthopper in the genus Platocerella (Hemiptera: Auchenorrhyncha: Derbidae) from palms in Costa Rica, a key to the genus and an updated molecular phylogeny of available New World Otiocerinae
FIGURE 2. Adult male habitus of Platocerella sordida sp. nov.; A) dorsal view and B) lateral view; scale bar = 1 mm.
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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.