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11,506 results for “Dynamics”
Dataset for High-throughput combinatorial analysis of the spatiotemporal dynamics of nanoscale lithium metal plating
<p>This is a dataset for the manuscript High-throughput combinatorial analysis of the spatiotemporal dynamics of nanoscale lithium metal plating. This mansucript is currently under peer-review in ACS Nano. </p>
Fig. 8 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 8: Path diagram of the interaction between the abiotic (temperature, salinity) and biotic parameter (chlorophyll biomass, mesozooplankton and Aurelia solida) in Bizerte lagoon in 2013 and 2014.
Fig. 6 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 6: Prey selectivity of Aurelia solida in Bizerte Lagoon during the present study; Har = Harpacticoids; Biv = bivalve larvae; Gas = gastropods larvae; Lar = larvaceans; Fis = Fish larvae; Cru = crustacean larvae; Cal = Calanoids; Cla = Cladocerans.
Fig. 5 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 5: Relation between Aurelia solida bell diameter (cm) and (A) the prey in the gut contents and (B) the prey diversity.
Fig. 4 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 4: Variation of the diet composition of Aurelia solida in Bizerte Lagoon in (A) 2013 and (B) 2014; (n) number of analyzed specimens.
Fig. 7 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 7: Seasonal variation of Aurelia solida (A-B) feeding rate (prey consumed medusae-1) and (C-D) predation impact (% prey standing stock consumed day-1) in Bizerte Lagoon in 2013-2014.
Fig. 3 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 3: Seasonal variation of Aurelia solida (A) abundance and (B) bell diameter in Bizerte lagoon between November 2012 and August 2014; white spots: 0 ind.m-3.
Fig. 1 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 1: Map of the Mediterranean Sea showing with locations of the sampling station and the transect in the Bizerte Lagoon between November 2012 and August 2014.
Phylogeography and paleoclimatic range dynamics explain variable outcomes to contact across a species' range
<p>Files required to run analyses related to the journal article:" Phylogeography and paleoclimatic range dynamics explain variable outcomes to contact across a species’ range."<br><br>Code which utilizes these data are found at: https://github.com/k-lamb/Campanula-range-history</p> <p>DOI code link: https://doi.org/10.5281/zenodo.12097775</p>
Molecular Dynamics Simulations of Hydrophilic (QTY) Potassium Ion Channels in Water
<p>You can find here the molecular dynamics (MD) trajectories of QTY proteins in water performed for the "Computational engineering of water-soluble potassium ion channels through QTY transformation" manuscript. Please cite our paper and the previous Zenodo dataset when referring to or using this data. If you have any questions, please contact me (Eva Smorodina) at ribes.ev@gmail.com. Thank you!<br><br>Smorodina, E. (2024). Molecular Dynamics Simulations of Hydrophobic (cryo-EM and Native) and Hydrophilic (QTY) Potassium Ion Channels [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10592842</p>
Figure 4 in Dynamics of the impacts of Pratylenchus penetrans on Gisela® cherry rootstocks
Figure 4: Relationships between running average Pratylenchus penetrans population densities and trunk cross-sectional areas (TCSA) for three different cherry training systems on Gisela 3 (left), Gisela 5 (center), and Gisela 6 (right) rootstocks at the end of 2017 at the Summerland, British Columbia site. Training systems: KGB, Kym Greene Bush; TSA, Tall Spindle Axe; UFO, Upright Fruiting Offshoot.
Figure 3 in Dynamics of the impacts of Pratylenchus penetrans on Gisela® cherry rootstocks
Figure 3: Relationships between running average Pratylenchus penetrans population densities and trunk cross-sectional areas (TCSA) for three different cherry tree training systems on Gisela 3 rootstock from 2013 through 2016 at the Summerland, British Columbia site. Training systems: KGB, Kym Greene Bush; TSA, Tall Spindle Axe; UFO, Upright Fruiting Offshoots.
Figure 2 in Dynamics of the impacts of Pratylenchus penetrans on Gisela® cherry rootstocks
Figure 2: Temporal dynamics of the biomass of fine roots (<2 mm diameter) (g dry root/kg dry soil) under Gi.3, Gi.5, and Gi.6 trees during the course of the study, at the Summerland, British Columbia (BC, solid lines) and Kentville, Nova Scotia (NS, dashed lines) sites.
Figure 1 in Dynamics of the impacts of Pratylenchus penetrans on Gisela® cherry rootstocks
Figure 1: Population densities of Pratylenchus penetrans (per kg soil, roots inclusive) under Gi.3, Gi.5, and Gi.6 trees during the course of the study, at the Summerland, British Columbia (BC, solid lines) and Kentville, Nova Scotia (NS, dashed lines) sites. Error bars represent one standard deviation above the minimum value at each date.
Figure 5 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 5. Last Interglacial, Last Glacial Maximum, Present (1960–1990), and the Future (2050 and 2070) predictions of the potential distribution of two cacti species (C. hildmannianus and P. machrisii) based on 10% thresholding approaches. The abbreviations are defined as follows: LGM-Last Glacial Maximum, LIG-Last Interglacial.
Figure 2 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 2. Occurrence points used for ecological niche modeling are shown in red. Squares equal approximately 2 decimal degrees and the background image on thmap shows the elevational structure of Brazil.
Figure 1 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 1. Approximate distribution of D. gouveai (green area) showed Caatinga and Cerrado domains and the localities sampled for the species (based on Moraes et al., 2009), descriptive statistics (n, number of individuals; H, the number of haplotype; H d, haplotype diversity; pi, nucleotide diversity) and median joining network of 48 individuals of D. gouveai. All statistics based on nucleotide sequences were adopted from Moraes et al. (2009). MIR: Pirapotanga; FOR: Morro do Forno; FUR: Furnas; CEU: Vale do Céu; CRI: Cristalina; FER: Fercal; PIR: Pirenópolis; SER: Serrinha; IBO: Ibotirama; BAX: Baxio.
Figure 4 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 4. Last Interglacial, Last Glacial Maximum, Present (1960–1990), and the Future (2050 and 2070) predictions of the potential distribution of D. gouveai based on two thresholding approaches. Arrows shows very limited potential distribution of D. gouveai in 2050 and 2070. The abbreviations are defined as follows: LGM-Last Glacial Maximum, LIG-Last Interglacial. Additionally, specific climate models include LGM-cc (Community Climate System Model), LGM-me (MPI-ESM-P, General Circulation Models), and LGM-mr (Model for Interdisciplinary Research on Climate, Earth System version 2 for Long-term simulations).
Figure 3 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 3. Isolation-by-distance of populations of D. gouveai based on mtDNA. Linear regression lines were drawn for all comparisons among populations (full line), and for populations not included MIR (dotted line).
Figure 3 in Dynamics of meiobenthic fauna in a tropical sandy coast (Chennai, Bay of Bengal) with reference to the physicochemical parameters
Figure 3. Physicochemical parameters of the Chennai coast (a- Ammonia; b- Density of meiobenthic fauna).
ScienceDex guides
Understand access before you commit
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.