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FIGURE 6. Classification Tree results and predictions for the five fossil localities. A in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)
FIGURE 6. Classification Tree results and predictions for the five fossil localities. A) Results and predictions for CT1, vegetative cover. B) Results and predictions for CT2, biogeographic realm. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.
Inverse Model Results for WAIS
<div> <p>This page contains the results of a basal drag inversion performed for the West Antarctic Ice Sheet (WAIS). We provide the results in NetCDF files of our six conducted experiments in the associated (not yet published) study, showing the basal drag and basal drag coefficient, as well as the outputs of the 1D steady-state thermal model. In addition, the Matlab scripts used to generate the figures in our manuscript and the finite element mesh are uploaded. </p> <p>To perform the inversion and L-curve analysis, we rely on the inversion model presented in Wolovick et al. (2023) (available at https://doi.org/10.5281/zenodo.7798650). All parameters and the added code are included in an uploaded spreadsheet (Parameters_ISSMInversion.xlsx). </p> <p><strong>Name conventions </strong></p> <ul> <li>m#: Describes the exponent in the sliding law. The values can bet set to m1 (linear sliding) or m3 (non-linear sliding).</li> <li>Ntype: Describes the effective pressure source in the sliding law. Values are "noN" (i.e., Weertman sliding), "Nop" (i.e., parameterized effective pressure) and "Ncuas" (i.e., effective pressure used from subglacial hydrology CUAS-MPI).</li> <li>Budd, Weertman: Describes the two different sliding laws we use in this manuscript. Budd uses an effective pressure source and Weertman does not use an effective pressure field. </li> </ul> <p><strong>Figure scripts</strong></p> <p>The following scripts generate all figures shown in the manuscript: </p> <ul> <li> <p>AllLcurveFigures_v1.m: Creates Figure 6 in the manuscript. </p> </li> <li> <p>BestDragFigure_v1.m: Creates Figure 13, Figure 14 and Figure 16 in the manuscript. </p> </li> <li> <p>BestInversionComparisonFigure_v1.m: Creates Figure 15 in the manuscript. </p> </li> <li> <p>ConvergenceFigure_v1.m: Creates Figure 7 in the manuscript. </p> </li> <li> <p>DragCoeffComparisonFigure_N_m_v1.m: Creates Figure 11 in the manuscript. </p> </li> <li> <p>DragLakeCandidatesFigure_v1.m: Creates Figure 17 and 18 in the manuscript. </p> </li> <li> <p>EffectivePressureFigure_v1.m: Creates Figure 5 in the manuscript. </p> </li> <li> <p>LcurveComparisonFigure_m_Ncuas_v1.m: Creates Figure 12 in the manuscript. </p> </li> <li> <p>LcurveComparisonFigure_N_m_v1.m: Creates Figure 9 and Figure 10, as well as the Table 1 in the manuscript. </p> </li> <li> <p>MeshFigure_v1.m: Creates Figure 3 in the manuscript. </p> </li> <li> <p>ModelSetupFigure_v1.m: Creates Figure 2 in the manuscript. </p> </li> <li> <p>SubdomainLcurveFigure_v1.m: Creates the subfigures of Figure 8 in the manuscript. </p> </li> <li> <p>ThermalFigure_v1.m: Creates Figure 4 in the manuscript. </p> </li> </ul> <p><strong>Input</strong> </p> <ul> <li> <p>Mesh_WAIS_500m-19km.mat: mat-file of finite-element mesh for WAIS study domain. </p> </li> </ul> <p><strong>Inversion results </strong></p> <ul> <li> <p>BestInversionResult_WAIS_m3_Ncuas_bestlambda-0.5.nc: Best basal drag and squared drag coefficient result for the experiment m=3, Ncuas evaluated at the best lambda value 0.5 determined with the L-curve analysis. </p> </li> <li> <p>BestInversionResult_WAIS_m3_Ncuas_lambda-0.562.nc: Best basal drag and squared drag coefficient result for the experiment m=3, Ncuas evaluated at the lambda value 0.562 determined with the L-curve analysis. </p> </li> <li> <p>InversionResult_WAIS_m1_Ncuas_lambda-1.nc: Basal drag and squared drag coefficient result for the experiment m=1, Ncuas evaluated at the lambda value 1 determined with the L-curve analysis. </p> </li> <li> <p>InversionResult_WAIS_m3_Nop_lambda-0.1.nc: Basal drag and squared drag coefficient result for the experiment m=3, Nop evaluated at the lambda value 0.1 determined with the L-curve analysis. </p> </li> <li> <p>InversionResult_WAIS_m1_Nop_lambda-3.16.nc: Basal drag and squared drag coefficient result for the experiment m=1, Nop evaluated at the lambda value 3.16 determined with the L-curve analysis. </p> </li> <li> <p>InversionResult_WAIS_m3_noN_lambda-3.16.nc: Basal drag and squared drag coefficient result for the experiment m=3, using a Weertman sliding-law evaluated at the lambda value 3.16 determined with the L-curve analysis. </p> </li> <li> <p>InversionResult_WAIS_m1_noN_lambda-0.316.nc: Basal drag and squared drag coefficient result for the experiment m=1, using a Weertman sliding-law evaluated at the lambda value 0.316 determined with the L-curve analysis. </p> </li> <li> <p>ThermalOutput_WAIS.nc: Basal temperature, basal melt rates and depth-averaged rheology output from the used 1D thermal model, as well as the parameterized effective pressure Nop and the effective pressure Ncuas determined from a subglacial hydrology model. </p> </li> </ul> <p> </p> </div>
Input data and results of the RECC v2.5 model for the transformation scenarios of the global building stock
<p>This dataset contains the input data and core results of the RECC v2.5 model for the transformation scenarios of the global building stock. For details abou the RECC model, see DOI <a href="https://doi.org/10.1111/jiec.13023" target="_blank" rel="noopener">https://doi.org/10.1111/jiec.13023</a> and the RECC model landing page: <a href="https://www.industrialecology.uni-freiburg.de/odym-recc" target="_blank" rel="noopener">https://www.industrialecology.uni-freiburg.de/odym-recc</a></p> <p>The following data are included in this dataset:</p> <ul> <li>The entire model input database (120 model parameters)</li> <li>The parameters for the sensitivity analysis (8 parameters)</li> <li>The 70 folders with the core results</li> <li>The master classification file RECC_Classifications_Master_V2.0.xlsx</li> <li>The model config file RECC_Config.xlsx</li> <li>The list of scenario configurations RECC_ModelConfig_List.xlsx</li> <li>The result compilation and exporting configuration file RECCv2.5_EXPORT_Combine_Select.xlsx</li> <li>The main result summary file (extracted from the 70 result folders) Results_Extracted_RECCv2.5_10Regs_sep.xlsx</li> <li>The result summary file for comparison with the CRAFT model timber supply RECCv2.5_10Regs_CRAFT_Coupling_SHARE.xlsx</li> <li>The results of the sensitivity analysis: Results_Extracted_RECCv2.5_10Regs_Sensitivity_sep.xlsx</li> </ul> <p>Note that the result folders of the sensitivity analysis are not archived here (too little information in relation to the data volume). They can be requested from the author. The results can also be recreated by running the RECC model with the sensitivity analysis parameters.</p> <p>The model itself is available as Python code from <a href="https://github.com/IndEcol/RECC-ODYM" target="_blank" rel="noopener">https://github.com/IndEcol/RECC-ODYM</a></p>
Figure 4. CFD simulation results for Models A in Drag of suction cup tags on swimming animals: Modeling and measurement
Figure 4. CFD simulation results for Models A (panels A and C) and B (panels B and D) in steady 5.6 m/s flow. The blue, yellow, and green regions are areas of reduced flow speed that generate forces on the tags. The upper panels show the flow speed over a horizontal cross-section at the tag midline. The lower panels show flow speed over a vertical cross-section at the centerline of the tag. The improved flow around Model B is evident in the smaller magnitude of blue coloration in the wake behind the tag.
Fig. 1 in Mixing male lures results in an effective multispecies bait for trapping Bactrocera (Diptera: Tephritidae) fruit flies
Fig. 1. Numbers of Bactrocera dorsalis male flies captured in traps baited with methyl eugenol (ME) alone or a mixture of ME and raspberry ketone (RK, a natural analogue of cue lure). Comparisons involved 3 mixtures in ME:RK ratios (wt:wt) of 95:5, 90:10, and 85:15. Symbols represent means (± SE) of 15 traps per lure type at 2 wk intervals over an 8 wk sampling period.
Supplemental Results for Assembly, Annotation, and Analysis from HiFi reads of Gulf Toadfish Genome and Transcriptome fOpsBet2.1
<p>This repository contains gzipped tarballs of the results of the various assembly, annotation, and analysis steps performed during the assembly of the fOpsBet2.1 genome assembly for Opsanus beta at the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science for the McDonald Toadfish Lab. These results are too numerous to include as supplemental data for a journal publication and so are available here for review. In this repository you will find results for:</p><p>Scripts:</p><p>-all bash and LSF scheduler job scripts used as part of the analysis, both exploratory and final. </p><p>QC:</p><p>-GenomeScope2 estimation of genome metrics from HiFi Reads</p><p>-QUAST genome statistics for each assembly step</p><p>-BUSCO completeness assessments for each assembly step </p><p>-inspector logs for polishing of initial assembly</p><p>-logs from Kraken2 contaminant screen</p><p>Assembly and Scaffolding:</p><p>-ntLINKS logs and intermediates for initial scaffolding</p><p>-ragtag logs and metrics for super-scaffolding to the ThaAma1.1 T. amazonica reference assembly</p><p>-mitoHIFI results for mitogenome assembly from HiFi reads, primary assembly, and purged alternate assembly</p><p>Annotation:</p><p>-PASA directory with full input and output for SQLite PASA assembly of transcriptome for gene predictors</p><p>-Results folder for Funannotate::annotate for gene models, annotations, and CDS/mRNA/protein fastas</p><p>-InterProSCan5 results for protein annotation used as input into Funannotate</p><p>-ghostKOALA KEGG assignment results for predicted proteins from funannotate results</p><p>Repetitive Elements:</p><p>-tidk telomere repeat analysis results</p><p>-TRAH satellite DNA analysis with subsequent analysis with HiCAT and StainedGlass</p><p>-RepeatModeler results for de novo TE prediction</p><p>-repclassifier results for TE curation</p><p>Comparative Analysis:</p><p>-OrthoFinder ortholog search for O. beta to several other vertebrates</p><p>-CAFE5 gene family expansion and contraction of Orthogroups from OrthoFinder results</p><p> </p>
Results of a Galaxy metagenomic analysis of bee gut microbiome data from PRJNA977416
<p>This dataset contains the outputs of a metagenomic Galaxy workflow run on the raw data of the project PRJNA977416, including the CSV file of associated metadata and the workflow.ga used for the analysis.</p> <p>Firstly, it has information on taxonomic assignment with :</p> <ul> <li>the reports of all samples for Kraken2, Bracken, and MetaPhlan taxonomic profilers. </li> <li>two tabular files obtained with Taxpasta, which merge samples and standardize taxonomic abundances.</li> <li>for the Bracken standardised abundance, a file with the measures of alpha diversity calculated </li> <li>two HTML files giving access to the Krona diagram for this taxonomic composition.</li> </ul> <p>Secondly, it contains functional informations with :</p> <ul> <li>a tabular file with the relative abundance of all GO terms for all samples</li> <li>a directory detailing pathways and genes families detected.</li> </ul>
Fig. 5 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 5. Absolute counts of Eosinophils. The dotted horizontal lines represent reference ranges based on average values ± 2 × S.D. of values of foxes from groups A3, B and D at 0 wpi. Error bars (S.E.M).
Fig. 2 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 2. Arithmetic mean worm burden at necropsy per group. Foxes of groups A were inoculated once and necropsied at 9 wpi (A1), 13 wpi (A2) or 23 wpi (A3), while foxes of groups challenged once (B) or twice (D) and the control foxes of the first (C) and second challenge (E) were necropsied 23 wpi. Bar indicates mean with outlier excluded. Error bars = S.E.M.
Fig. 3 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 3. Arithmetic mean worm fecundity (expressed as final LPG/number female worms at necropsy) per group. Foxes of groups A were inoculated once and necropsied at 9 wpi (A1), 13 wpi (A2) or 23 wpi (A3), while foxes of groups challenged once (B) or twice (D) and the control foxes of the first (C) and second challenge (E) were necropsied 23 wpi. Bar indicates mean with outlier excluded. Error bars = S.E.M.
Fig. 1 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 1. Experimental design: inoculations with 100 third stage larvae (L3) of Angiostrongylus vasorum are indicated by triangles, challenge inoculations (also with 100 L3) by circles and the differing group termination times by squares.
Fig. 4 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 4. Arithmetic mean larval counts (first stage larvae per gram of feces) of foxes dogs experimentally inoculated at 0 wpi and challenged once (group B) or twice (group D) with 100 third stage larvae of Angiostrongylus vasorum from 6 to 22 wpi. Y-axis log10 transformed. Arrows indicate the challenge time points.
Рис. 2. ΔоΛговременная Αинамика весенней чисΛенности трех виΑов уток (A — трескунка; B — касатки; C — шиΛохвости) на ΑебеΑинском стационаре Хинганского заповеΑника (показаны уровень значимости и 95-процентный ΑоверитеΛьный интерваΛ) Fig. 2. Long-term spring number dynamics of three duck species at the Lebedinsky Station of Khingansky State Nature Reserve with p-values and 0.95 confidence intervals. A — Gargany; B — Falcated Duck; C — Pintail in The results of long-term observation of waterfowl spring migration in Khingan Nature Reserve, Eastern Russia
Рис. 2. ΔоΛговременная Αинамика весенней чисΛенности трех виΑов уток (A — трескунка; B — касатки; C — шиΛохвости) на ΑебеΑинском стационаре Хинганского заповеΑника (показаны уровень значимости и 95-процентный ΑоверитеΛьный интерваΛ) Fig. 2. Long-term spring number dynamics of three duck species at the Lebedinsky Station of Khingansky State Nature Reserve with p-values and 0.95 confidence intervals. A — Gargany; B — Falcated Duck; C — Pintail
Рис. 1. Регион иссΛеΑований: A — его поΛожение на карте Восточной Азии; B — общий виΑ Буреинско-Хинганской низменности; C — карта-схема ΑебеΑинского стационара Хинганского заповеΑника. УсΛовные обозначения: I — Хинганский заповеΑник (вкΛючает Αва кΛастера); II — заказник «Ганукан». 1 — Антоновское воΑохраниΛище; 2 — оз. ΔоΛгое; 3 — оз. Гусиное; 4 — оз. Третье ΑебеΑиное Fig. 1. Study region: A — study region on the map of the East Asia; B — Burea-Khingan (Arkhara) lowland; C — Lebedinsky Station. Notes: I — two clusters of Khingan Nature Reserve; II — Ganukan Sanctuary. 1 — Antonovskoye Reservoir; 2 — Dolgoye Lake; 3 — Gusinoye Lake; 4 — Lebedinoye Lake in The results of long-term observation of waterfowl spring migration in Khingan Nature Reserve, Eastern Russia
Рис. 1. Регион иссΛеΑований: A — его поΛожение на карте Восточной Азии; B — общий виΑ Буреинско-Хинганской низменности; C — карта-схема ΑебеΑинского стационара Хинганского заповеΑника. УсΛовные обозначения: I — Хинганский заповеΑник (вкΛючает Αва кΛастера); II — заказник «Ганукан». 1 — Антоновское воΑохраниΛище; 2 — оз. ΔоΛгое; 3 — оз. Гусиное; 4 — оз. Третье ΑебеΑиное Fig. 1. Study region: A — study region on the map of the East Asia; B — Burea-Khingan (Arkhara) lowland; C — Lebedinsky Station. Notes: I — two clusters of Khingan Nature Reserve; II — Ganukan Sanctuary. 1 — Antonovskoye Reservoir; 2 — Dolgoye Lake; 3 — Gusinoye Lake; 4 — Lebedinoye Lake
Figure A1- snapshot of the SPARQL query result for eateries suitable for groups and that have children menu
<p>snapshot of the SPARQL query result for eateries suitable for groups and that have children's menus. The table of the Image is generated using open source ontology editor Protégé (https://protege.stanford.edu/) </p>
Fig. 6. Strict consensus tree resulting from 20 in A new species of Afrolaophonte (Copepoda, Harpacticoida, Laophontidae) from Korea and cladistic tests of species-groups
Fig. 6. Strict consensus tree resulting from 20 equally parsimonious trees from an analysis of 15 weighted morphological characters (Table 1) for 13 species of Afrolaophonte Chappuis, 1960 and one outgroup, Arenolaophonte stygia Lang, 1965. Characters 0, 2-4, and 11-14 were down-weighted to 0.5, while others were left at the default weight of 1. Full circles represent presumed synapomorphies, empty circles presumed plesiomorphies or homoplasies, Arabic numerals above circles characters, and Arabic numerals below circles character states.
species according to Broadley (1994). These may well be the result of continuing confusion over the placement of Keta. Given the localities known from Lunda Norte, it seems likely that the species occurs in other northern regions of Angola. MAP 363. Distribution of Scaphiophis albopunctatus in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
species according to Broadley (1994). These may well be the result of continuing confusion over the placement of Keta. Given the localities known from Lunda Norte, it seems likely that the species occurs in other northern regions of Angola. MAP 363. Distribution of Scaphiophis albopunctatus in Angola.
Data and results for manuscript "Imaging groundwater infiltration dynamics in karst vadose zone with long-term ERT monitoring"
<p>This data set contains raw and inverted data from an Electrical Resistivity Tomography (ERT) monitoring experiment conducted over a period of three years at the Rochefort Cave Laboratory (RCL) site in South Belgium. It highlights variable hydrodynamics in the karst vadose zone of Lorette Cave. More conventional hydrological measurements (drip discharge monitoring, soil moisture and water conductivity data sets) are also included in the package, which aims at provide a thorough understanding of the groundwater infiltration. Seasonal changes affect all the imaged areas leading to increases in resistivity in spring/summer attributed to enhanced evapotranspiration, whereas winter is characterised by a general decrease in resistivity associated with a groundwater recharge of the vadose zone. This study provides detailed images of the sources of drip discharge spots traditionally monitored in caves and aims to support modelling approaches of karst hydrological processes.</p>
BRAIN Journal-Electrophysiological Neuroimaging using sLORETA Comparing 100 Schizophrenia Patients to 48 Patients with Major Depression -Figure 3. Resulting comparisons isolating the Dopamine D2 Mesolimbic Pathway
<p>Moreover, a study in Prague identified that Toxoplasmosis triggers schizophrenia in<br> predisposed subjects (Flegr et al., 2014). It may very well be that the Toxoplasmosis parasite<br> increasing dopamine secretions in the frontal lobes may very well lead to decreased cerebral<br> volumes. Cat feces, sexual contact, and eating raw or undercooked pork are well known transmitters<br> of the Toxoplasmosis parasite and may be advisable that patients take precautions of the possibility<br> of these triggering symptoms of psychosis with these possible routes of infection. Another adjunct to Atypical Antipsychotics may be to treat the potential cerebral Toxoplasmosis infection with<br> Cotrimoxazole or Pyrimethamine/Clindamycin.</p>
Figure 3. Result of first fraction-Data Conflict Resolution among Same Entities in Web of Data
<p>Finally we count the entities that contain any words in the synonyms list. The result of first<br> the fraction in equation 4 is shown in figure 3.</p>
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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.