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155
datasets available to search
ShareScore release 0.9.0
Dataset results
155 results for “structure control”
Data from: Resolving patterns of population genetic and phylogeographic structure to inform control and eradication initiatives for brown rats Rattus norvegicus on South Georgia
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Data from: Genetic structure of introduced American mink (Neovison vison) in Patagonia: colonisation insights and implications for control and management strategies
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Water availability rather than temperature control soil fauna community structure and prey-predator interactions
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Structure vs. chemistry: Alternate mechanisms for controlling leaf microbiomes
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Data from: Structural controls on photosynthetic capacity through juvenile-to-adult transition and needle aging in Mediterranean pines
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Data from: Palaeobiogeographical structuration of Smithian (Early Triassic) ammonoid faunas within the western USA basin and its controlling parameters
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Species diversity and food web structure jointly shape natural biological control in agricultural landscapes
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Evaluating the educational effectiveness of a structured, simulator-assisted, peer-led training on cardiovascular physical examination in third-year medical students: A randomized, controlled trial
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Data from: Controlled fluorescence in a beetle's photonic structure and its sensitivity to environmentally induced changes
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Data from: Canopy leaf area index at its higher end: dissection of structural controls from leaf to canopy scales in bryophytes
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Variable Structure Control of a Small Ducted Wind Turbine in the Whole Wind Speed Range Using a Luenberger Observer
<p>1) Files.csv : Dataset acquired on the experimental laboratory setup used for the emulation of a Ducted Horizontal Axis Wind Turbine.</p> <p>2) DHAWT.xlsx : aerodynamic characteristics of the Ducted Horizontal Axis Wind Turbine chosen as case of study.</p>
Data from: Environmental and genetic control of brain and song structure in the zebra finch
Birdsong is a classic example of a learned trait with cultural inheritance, with selection acting on trait expression. To understand how song responds to selection, it is vital to determine the extent to which variation in song learning and neuroanatomy is attributable to genetic variation, environmental conditions, or their interactions. Using a partial cross fostering design with an experimental stressor, we quantified the heritability of song structure and key brain nuclei in the song control system of the zebra finch and the genotype-by-environment (G × E) interactions. Neuroanatomy and song structure both showed low levels of heritability and are unlikely to be under selection as indicators of genetic quality. HVC, in particular, was almost entirely under environmental control. G × E interaction was important for brain development and may provide a mechanism by which additive genetic variation is maintained, which in turn may promote sexual selection through female choice. Our study suggests that selection may act on the genes determining vocal learning, rather than directly on the underlying neuroanatomy, and emphasizes the fundamental importance of environmental conditions for vocal learning and neural development in songbirds.
Synthetic datasets with controlled structures at first and second order
<p>These are the synthetic datasets analyzed in "Covariance based information processing in reservoir computing systems" (https://doi.org/10.1101/2021.04.30.441789)</p>
Figure 4 from: Zhao L, Yi D, Li C, Sun D, Xu H, Gao T (2017) Phylogeography and population structure of - grypotus (Richardson, 1846) as revealed by mitochondrial control region sequences. ZooKeys 705: 143-158. https://doi.org/10.3897/zookeys.705.13001
Figure 4 - Observed and expected mismatch distribution under the sudden expansions model of the control region haplotypes in J. grypotus.
Figure 3 from: Zhao L, Yi D, Li C, Sun D, Xu H, Gao T (2017) Phylogeography and population structure of - grypotus (Richardson, 1846) as revealed by mitochondrial control region sequences. ZooKeys 705: 143-158. https://doi.org/10.3897/zookeys.705.13001
Figure 3 - Minimum spanning network showing genetic relationship among mtDNA control region haplotypes in J. grypotus (Circles represent haplotypes with sizes proportional to their respective frequencies. Tick marks represent deduced numbers of nucleotide substitutions along each branch)
Figure 2 from: Zhao L, Yi D, Li C, Sun D, Xu H, Gao T (2017) Phylogeography and population structure of - grypotus (Richardson, 1846) as revealed by mitochondrial control region sequences. ZooKeys 705: 143-158. https://doi.org/10.3897/zookeys.705.13001
Figure 2 - Phylogenetic tree of control region haplotypes constructed using neighbor-joining algorithms of J. grypotus.
Figure 5 from: Zhao L, Yi D, Li C, Sun D, Xu H, Gao T (2017) Phylogeography and population structure of - grypotus (Richardson, 1846) as revealed by mitochondrial control region sequences. ZooKeys 705: 143-158. https://doi.org/10.3897/zookeys.705.13001
Figure 5 - Bayesian skyline plots showing NefT (Nef=effective female population size; T=generation time) changes through time in J. grypotus populations. Black lines are median estimates of NefT; light lines represent the upper and lower 95% highest posterior density (HPD) limits of NefT.
Dataset: An integrated picture of the structural pathways controlling the heart performance
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Controlling grain structure in metallic additive manufacturing using a simple, inexpensive process control system
<p>Raw data associated with a paper submission.<br> "Hardness Variation in Inconel 718 Produced by Laser Directed Energy Deposition" submitted to Nature Communications.</p> <p>Contained are all the raw data used in the analysis, as well as csv's of any data plotted in graphs.</p> <p>Raw coaxial images captured during printing of various processing parameters<br> EBSD scans (.crc and .oip) of all disucssed samples, as well as matlab (MTEX) files of the EBSD map subsets<br> Raw Hardness Data<br> Position/Power logs from the build</p> <p>Samples built were:<br> Control samples - 3, 6, 10 hatches wide, with No control, Power control and Velocity control<br> Varying Thickness samples - 1, 2, 3, 4, 6, 8 hatches wide, all with constant parameters</p>
Figures 37-46. – Carassius auratus. Figures 37-40. – TEM Control scales. Figure 37 in The elasmoid scales of teleosts: from structure to bioinspired materials
Figures 37-46. – Carassius auratus. Figures 37-40. – TEM Control scales. Figure 37. – Flat hyposquamal scleroblasts (hs) synthesise the thick collagen fibrils of the plywood-like structure of the basal plate and the thin TC fibres (tc) crossing the plywood-like structure. Figure 38. – Collagen fibrils are coaligned with the Mts and micro- filaments (arrows) underlying the plasma membrane of the hyposquamal scleroblast. Figure 39. – Detail of the secretory surface of a hyposquamal scleroblast. The microfibrils and the Mts have changed their direction and are coaligned with the newly synthesized collagen fibrils forming a new layer. Figure 40. – Detail of the secretory surface of a hyposquamal scleroblast. Mts (arrowhead) located in the vicinity of the plasma membrane are in parallel with the innermost thick collagen fibrils. Figures 41- 44. – Four-day-regenerating scale. Figure 41. – TEM. The hyposquamal scleroblasts are tall prismatic cells with well-developed RER and Golgi areas. Figure 42. – Freeze-fracture. Gap junction between two hyposquamal scleroblasts. Figure 43. – TEM. The innermost collagen fibrils and the Mts
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.