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Supplementary material 4 from: Demetriou J, Georgiadis C, Martinou AF, Roy HE, Wetterer JK, Borowiec L, Economo EP, Triantis KA, Salata S (2023) Running rampant: the alien ants (Hymenoptera, Formicidae) of Cyprus. NeoBiota 88: 17-73. https://doi.org/10.3897/neobiota.88.106750
Description of Solenopsis CYP139 and morphometric data for future comparisons
Supplementary material 1 from: Demetriou J, Georgiadis C, Martinou AF, Roy HE, Wetterer JK, Borowiec L, Economo EP, Triantis KA, Salata S (2023) Running rampant: the alien ants (Hymenoptera, Formicidae) of Cyprus. NeoBiota 88: 17-73. https://doi.org/10.3897/neobiota.88.106750
Georeferenced records of alien ant species in Cyprus
Supplementary material 2 from: Demetriou J, Georgiadis C, Martinou AF, Roy HE, Wetterer JK, Borowiec L, Economo EP, Triantis KA, Salata S (2023) Running rampant: the alien ants (Hymenoptera, Formicidae) of Cyprus. NeoBiota 88: 17-73. https://doi.org/10.3897/neobiota.88.106750
Alien ant species in protected NATURA 2000 and RAMSAR areas
Data for running HaploC-tools
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Model hydrodynamic outputs and example codes for running different Lagrangian particle tracking packages
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Datasets for running ProSmith for ESP task
<p>Datasets that are required for running ProSmith for ESP task</p>
Gene Embed Experiment Runs
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DFT run directory for H doped VO2 phases
<p>VASP calculation directory for hydrogenated VO2 phases.</p>
Run and analysis scripts for (Disentangling the drivers behind the post-2000 retreat of Sermeq Kujalleq, Greenland (Jakobshavn Isbrae))
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Dataset: Running Oak Efficient Growth ETF (RUNN) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Cooling run (years 0001-0266) from Eisenman & Armour (2024)
<p>The following information is also included in the README.txt file accompanying the data.</p> <p><br>Citation for data:</p> <p>I. Eisenman and K. Armour (2024). The radiative feedback continuum from Snowball Earth to an ice-free hothouse. Nature Communications, https://doi.org/10.1038/s41467-024-50406-w</p> <p><br>Description of data:</p> <p>The Warming and Cooling simulations are both branched from the end of year 500 of a preexisting CESM2 pre-industrial (PI) simulation ("b.e21.B1850.f09_g17.CMIP6-piControl.001" by Danabasoglu et al., 2020). The kernel analysis uses the mean annual cycle averaged over years 480-499 of this PI simulation as the reference climate. Output from this PI simulation can be downloaded from<br>https://www.earthsystemgrid.org/dataset/ucar.cgd.cesm2.b.e21.B1850.f09_g17.CMIP6-piControl.001.atm.proc.monthly_ave.html</p> <p>For the first 150 years of the Warming run, we use a preexisting CESM2 simulation with CO2 increasing at 1%/year ("b.e21.B1PCT.f09_g17.CMIP6-1pctCO2.001" by Danabasoglu, 2019); data from this simulation is shared elsewhere and is mirrored here for convenience. This is followed by our simulation "WARMING1ppyCESM2cheyenne", which we ran until it failed with an error after year 0279. Hence the data for the Warming run comes from the following simulations:<br>- Year 0001-0150: b.e21.B1PCT.f09_g17.CMIP6-1pctCO2.001<br>- Year 0151-0279: WARMING1ppyCESM2cheyenne</p> <p>For the Cooling run, we decreased CO2 at 1%/year in the simulation "COOLING1ppyCESM2cheyenne". After year 140, we adjusted the processor (PE) layout for a more economical (but slower) load balancing, which required us to branch to a new case, "COOLING1ppyCESM2cheyenne2". This simulation failed with an error after year 278, and we commented out a line in the model code and re-ran starting from 12 years earlier using the case name "COOLING1ppyCESM2cheyenne3". This simulation failed with an error after year 332, and we commented out another line in the model code and re-ran starting in year 333 using the case name "COOLING1ppyCESM2cheyenne5" (there is no simulation "COOLING1ppyCESM2cheyenne4" in this collection). This simulation failed with an error after year 514. Hence the data for the Cooling run comes from the following simulations:<br>- Year 0001-0140: COOLING1ppyCESM2cheyenne<br>- Year 0141-0266: COOLING1ppyCESM2cheyenne2 [ignore the additional years 0267-0278 in this simulation)<br>- Year 0267-0332: COOLING1ppyCESM2cheyenne3<br>- Year 0333-0514: COOLING1ppyCESM2cheyenne5</p> <p>Further details regarding these simulations are given in the "Methods" section of the paper (Eisenman & Armour, 2024).</p> <p><br>Downloading the data:</p> <p>Model output from the Warming and Cooling runs, including all fields used in the kernel analysis, is split into three downloadable records on Zenodo:<br>- Warming run (years 0001-0279)<br>- Cooling run part 1 (years 0001-0266)<br>- Cooling run part 2 (years 0267-0514)<br>Links to the three records can be found at https://eisenman-group.github.io</p> <p><br>Please contact Ian Eisenman (eisenman@ucsd.edu) for model output fields not included in this collection.</p>
Fig. 10 in Ballomma, a new Afrotropical genus in the Cryptothelinae (Araneae, Zodariidae): eyes on the run
Fig. 10. Ballomma legala gen. et sp. nov. Holotype, ♀. A. Epigyne, ventral view. B. As preceding, ventral view. C. Epigyne, digested, dorsal view. D. As preceding, dorsolateral view. Scale bars: 0.2 mm.
Fig. 6 in Ballomma, a new Afrotropical genus in the Cryptothelinae (Araneae, Zodariidae): eyes on the run
Fig. 6. Ballomma haddadi gen. et sp. nov. A–B. Holotype, ♂. C–F. ♀ (MRAC 132641). A. Habitus, dorsal view. B. As preceding, ventral view. C. Habitus, dorsal view. D. As preceding, ventral view. E. Prosoma, frontal view. F. Prosoma, dorsolateral view. Scale bars: 1 mm.
EVO-NANO modified PhysiCell simulation run with 100K vasculature agents
<p>PhysiCell modifications:</p> <p>- added CSC</p> <p>-added vasculature</p> <p> </p> <p>this run:</p> <p>Cell cycle speed increased to 1/10 (default is 0.0432/60 = 0,00072)<br> snapshot is taken each 180 minutes (of simulation time)<br> There are 100000 vasculature agents with 1000 branches<br> oxygen secretion rate for each fasculature agent is: phenotype.secretion.secretion_rates[0] = 10</p>
Text-fig. 4. Properca prisca, scales. a – specimen IGP 2011/6b, scale 1; b – specimen IGP 2011/6b, scale 2, c – specimen IGP 2011/6b, scale 3; d – specimen IGP 2011/4a; e – specimen IGP 2011/7; f – specimen IGP 2011/1; g – specimen IGP 2011/8, scale 1; h – specimen IGP 2011/8, scale 3; i – specimen IGP 2011/8, scale 2; j – specimen IGP 2011/5a, scale 1; k – specimen IGP 2011/2a; l – specimen IGP 2011/3a; m – specimen IGP 2011/6b, group of scales; n – specimen IGP 2011/5a, group of scales; o – specimen IGP 2011/8, group of scales; p – specimen IGP 2011/7, lateral line scale; q – reconstruction of the running of the lateral line according to the NMP Pc 68; r-s – reconstruction of the scales according to Obrhelová (1976); t-z – reconstruction of the scales according to Obrhelová (1971). Head should be in the left. Scale bars represent 0.5 mm. in Lepidological Review On The Fish Fauna Of The Kučlín Locality (Upper Eocene, Czech Republic)
Text-fig. 4. Properca prisca, scales. a – specimen IGP 2011/6b, scale 1; b – specimen IGP 2011/6b, scale 2, c – specimen IGP 2011/6b, scale 3; d – specimen IGP 2011/4a; e – specimen IGP 2011/7; f – specimen IGP 2011/1; g – specimen IGP 2011/8, scale 1; h – specimen IGP 2011/8, scale 3; i – specimen IGP 2011/8, scale 2; j – specimen IGP 2011/5a, scale 1; k – specimen IGP 2011/2a; l – specimen IGP 2011/3a; m – specimen IGP 2011/6b, group of scales; n – specimen IGP 2011/5a, group of scales; o – specimen IGP 2011/8, group of scales; p – specimen IGP 2011/7, lateral line scale; q – reconstruction of the running of the lateral line according to the NMP Pc 68; r-s – reconstruction of the scales according to Obrhelová (1976); t-z – reconstruction of the scales according to Obrhelová (1971). Head should be in the left. Scale bars represent 0.5 mm.
Team running performance while scoring and conceding goals in the UEFA Champions League: Analysis of five-minute intervals.
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Specializing when it counts: comparing the dose-time-effect of distance variety between swimming and track running
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Test datasets to run the DuReS package
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Data from: Strong divergence in trait means but not in plasticity across hatchery and wild populations of sea-run brown trout Salmo trutta
There is ample evidence that organisms adapt to their native environment when gene flow is restricted. However, evolution of plastic responses across discrete environments is less well examined. We studied divergence in means and plasticity across wild and hatchery populations of sea-run brown trout (Salmo trutta) in a common garden experiment with two rearing environments (hatchery and a nearly natural experimental stream). Since natural and hatchery environments differ, this arrangement provides an experiment in contemporary adaptation across the two environments. A QST-FST approach was used to investigate local adaptation in survival and growth over the first summer. We found evidence for divergent selection in survival in one year and in body length in both years and rearing environments. In general, the hatchery populations had higher survival and larger body size in both environments. QST in body size did not differ between the rearing environments and constitutive divergence in the means was in all cases stronger than divergence in the plastic responses. These results suggest that in this system constitutive changes in mean trait values are more important for local adaptation than increased plasticity. In addition, ex-situ rearing conditions induce changes in trait means that are adaptive in the hatchery, but potentially harmful in the wild, suggesting that hatchery rearing is likely to be a sub-optimal management strategy for trout populations facing selection in the stream environment.
movement in A 3D interactive method for estimating body segmental parameters in animals: Application to the turning and running performance of Tyrannosaurus rex
movement
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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.