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1,328 results for “motion”
Data from: Background matching can reduce responsiveness of jumping spiders to stimuli in motion
<p><span>Motion and camouflage were previously considered to be mutually exclusive, as sudden movements can be easily detected.</span> <span>Background matching, for instance, is a well-known, effective camouflage strategy where the color and pattern of a stationary animal match its surrounding background. However, background matching may lose its efficacy when the animal moves, as the boundaries of the animal become more defined against its background. Recent evidence shows otherwise, as camouflaged objects can be less detectable than uncamouflaged objects even while in motion.</span><span> Here, we explored if the detectability of computer-generated stimuli varies with the speed of motion, background (matching and unmatching) and size of stimuli in six species of jumping spiders </span><span>(Araneae: Salticidae)</span><span>. Our results showed that in general, the responsiveness of all six salticid species tested decreased with increasing stimulus speed regardless of whether the stimuli were conspicuousness or camouflaged. Importantly, salticid responses to camouflaged stimuli were significantly lower compared to conspicuous stimuli. There were significant differences in motion detectability across species when the stimuli were conspicuous, suggesting differences in visual acuity in closely related species of jumping spiders. Furthermore, small stimuli elicited significantly lower responses than large stimuli across species and speeds. </span><span>Our results thus suggest that background matching is effective even when stimuli are in motion, reducing the detectability of moving stimuli.</span></p>
Anisotropic interaction and motion states of locusts in a hopper band
<p>Swarming locusts present a quintessential example of animal collective motion. Juvenile locusts march and hop across the ground in coordinated groups called hopper bands. Composed of up to millions of insects, hopper bands exhibit coordinated motion and various collective structures. These groups are well-documented in the field, but the individual insects themselves are typically studied in much smaller groups in laboratory experiments. We present the first trajectory data that detail the movement of individual locusts within a hopper band in a natural setting. Using automated video tracking, we derive our data from footage of four distinct hopper bands of the Australian plague locust, <em>Chortoicetes terminifera</em>. We reconstruct nearly twenty-thousand individual trajectories composed of over 3.3 million locust positions. We classify these data into three motion states: stationary, walking, and hopping. Distributions of relative neighbor positions reveal anisotropies that depend on motion state. Stationary locusts have high-density areas distributed around them apparently at random. Walking locusts have a low-density area in front of them. Hopping locusts have low-density areas in front and behind them. Our results suggest novel interactions, namely that locusts change their motion to avoid colliding with neighbors in front of them.</p>
Data from: Cellects, a software to quantify cell expansion and motion
<p>Automated quantification offers unique opportunities to study biological phenomena, increasing reproducibility, replicability, accuracy, and throughput, while reducing observer biases. We present Cellects, a tool to quantify growth and motion in 2D. This software operates with image sequences containing specimens growing and moving on an immobile flat surface. Its user-friendly interface makes it easy to adjust the quantification parameters to cover a wide range of species and conditions, and includes tools to validate the results and correct mistakes if necessary. The software provides the region covered by the specimens at each point of time, as well as many geometrical descriptors that characterize it. We validated Cellects with <em>Physarum polycephalum</em>, which is particularly difficult to detect because of its complex shape and internal heterogeneity. This validation covered five different conditions with different background and lighting, and found Cellects to be highly accurate in all cases. Cellects' main strengths are its broad scope of action, automated computation of a variety of geometrical descriptors, easy installation and user-friendly interface.</p>
Top view of DR1/DR2 double riffle, each section contains a spawning ground made up of eight gravel-filled trays, a rest area. The "double riffle" was designed to accommodate two groups from 25 to 50 specimens of broodstock in strictly identical conditions. The spawning grounds are equipped with waterproof, motion-sensing cameras with infrared night vision, connected to a 1000 Gb recorder. The diurnal and nocturnal activities of the two groups can therefore be simultaneously recorded over a long period. in Reproduction of Zingel asper (Linnaeus, 1758) in controlled conditions: an assessment of the experiences realized since 2005 at the Besançon Natural History Museum
Top view of DR1/DR2 double riffle, each section contains a spawning ground made up of eight gravel-filled trays, a rest area. The "double riffle" was designed to accommodate two groups from 25 to 50 specimens of broodstock in strictly identical conditions. The spawning grounds are equipped with waterproof, motion-sensing cameras with infrared night vision, connected to a 1000 Gb recorder. The diurnal and nocturnal activities of the two groups can therefore be simultaneously recorded over a long period.
Figure 9 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 9. Model of masticatory motion of icriodontid I elements. A, oblique lateral view; B, 'anterior' view.
Figure 8 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 8. Motion of P1 elements of ozarkodinid apparatuses summarized from the literature. A, Idiognathodus (Pennsylvanian); B, Novispathodus (Early Triassic); C, Wurmiella excavata (Silurian); D, Pseudofurnishius murcianus (Middle–Late Triassic); E, Polygnathus xylus xylus (Middle Devonian). Grey dots mark the pivot point; black arrows indicate the direction of occlusion and interlocking of P1 elements, grey arrows its reversal.
Figure 7. Hypothetical apparatus reconstruction deduced from the element arrangement within the Caudicriodus woschmidti conodont cluster. A, Model 1 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 7. Hypothetical apparatus reconstruction deduced from the element arrangement within the Caudicriodus woschmidti conodont cluster. A, Model 1 with tips of coniform elements pointing dorsally and 'posterior' part of icriodontan elements oriented ventrally. B, Model 2 with tips of coniform elements and 'posterior' part of icriodontan elements oriented ventrally. C, Model 3 with tips of coniform elements pointing ventrally and 'posterior' part of icriodontan elements oriented dorsally. D, Model 4 with tips of coniform elements and 'posterior' part of icriodontan elements oriented ventrally. Coniform elements are arranged in multiple rows.
Figure 5 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 5. Denticle tip wear of icriodontid I elements. A–C, Icriodus aff. michiganus, dextral I element, lateral and oral view; Middle Devonian, Eifel, Germany; sample BL-12-29c-9. D–F, Icriodus sp., dextral I element, lateral and oral view; Middle Devonian, Eifel, Germany; sample BL-12-29c-3. Extent and orientation of tip wear are indicated by dotted lines and arrowheads.
Figure 6 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 6. Diagrams illustrating orientation and direction of denticle tip wear. A, Icriodus aff. michiganus; left-side illustration shows the orientation of the inclined facet plane, right-side illustration the direction of vertically inclined facet; Middle Devonian, Eifel, Germany; sample BL-12-29c-9. B, Icriodus sp. left-side illustration shows the orientation of the inclined facet plane, middle the direction of the vertically inclined facet, and right the orientation and direction of the facet plane of median row denticles; Middle Devonian, Eifel, Germany; sample BL-12-29c-3).
Figure 4. A in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 4. A, denticle tip wear of the dextral I element of Caudicriodus woschmidti; Early Devonian, southern Burgenland, Austria; Ki/ 4/2a-1, NHMW 2011/0374/0001. B, detailed view of oral surface of the dextral I element with extent and orientation of tip wear indicated by dotted line and arrow head.
Figure 3 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 3. Chronological listing of notation history for icriodontid apparatus elements. Morphologically similar coniform element types and the icriodontan element evaluated for this study are highlighted in different colours or shades.
Figure 2 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 2. Conodont cluster of Caudicriodus woschmidti, Early Devonian, southern Burgenland, Austria; Ki/4/2a-1, NHMW 2011/0374/ 0001. A, SEM scan of the conodont cluster. B, detailed view of the coniform elements (C1–C5) close to the dextral I element. C, D, computer microtomography-based three-dimensional reconstruction with identification of all elements. E, hypothetical arrangement of all elements preserved within the fused conodont cluster.
Figure 1 in A new icriodontid conodont cluster with specific mesowear supports an alternative apparatus motion model for Icriodontidae
Figure 1. Locality map and section log from the 'Kottwitz' quarry (southern Burgenland, Austria), where the Caudicriodus woschmidti conodont cluster was found.
Data for: Motion adaptive deblurring with single photon cameras
<p>Single-photon avalanche diodes (SPADs) are a rapidly developing image sensing technology with extreme lowlight sensitivity and picosecond timing resolution. These unique capabilities have enabled SPADs to be used in applications like LiDAR, non-line-of-sight imaging and fluorescence microscopy that require imaging in photon-starved scenarios. In this work we harness these capabilities for dealing with motion blur in a passive imaging setting in low illumination conditions. Our key insight is that the data captured by a SPAD array camera can be represented as a 3D spatio-temporal tensor of photon detection events which can be integrated along arbitrary spatio-temporal trajectories with dynamically varying integration windows, depending on scene motion. We propose an algorithm that estimates pixel motion from photon timestamp data and dynamically adapts the integration windows to minimize motion blur. Our simulation results show the applicability of this algorithm to a variety of motion profiles including translation, rotation and local object motion. We also demonstrate the real-world feasibility of our method on data captured using a 32 × 32 SPAD camera.</p>
Neurostimulation and Motion Sickness
<p>This is the dataset associated with the manuscript "Reduced Motion Sickness Using Multi-channel Brain Stimulation". This dataset includes all kinds of data mentioned in the manuscript.</p>
Data on: Impact of neurite alignment on organelle motion
<p><strong>Impact of neurite alignment on organelle motion.</strong></p> <p>Maria Mytiliniou, Joeri A. J. Wondergem, Thomas Schmidt, Doris Heinrich.<br>J. R. Soc. Interface <strong>19</strong>:20210617.<br>doi: https://doi.org/10.1098/rsif.2021.0617</p> <p><strong>Abstract</strong></p> <p>Intracellular transport is pivotal for cell growth and survival. Malfunctions in this process have been associated with devastating neurodegenerative diseases, posing a need for deeper understanding of the involved mechanisms. Here, we used an experimental methodology that lead neurites of differentiated PC12 cells in either of two configurations: an one-dimensional, where the neurites align along lines, or a two-dimensional configuration, where the neurites adopt a random orientation and shape on a flat substrate. We subsequently monitored the motion of functional organelles, the lysosomes, inside the neurites. Implementing a time-resolved analysis of the mean-squared displacement, we quantitatively characterized distinct motion modes of the lysosomes. Our results indicate that neurite alignment gives rise to faster diiffusive and super-diiffusive lysosomal motion in comparison to the situation where the neurites are randomly oriented. After inducing lysosome swelling through an osmotic challenge by sucrose, we confirmed the predicted slowdown in diffusive mobility. Surprisingly we found that the swelling-induced mobility change affected each of the (sub- /super-) diiffusive motion modes differently and depended on the alignment configuration of the neurites. Our findings imply that intracellular transport is significantly and robustly dependent on cell morphology, which might be in part controlled by the extracellular matrix.</p>
Sodium binding stabilizes the outward-open state of SERT by limiting bundle domain motions
<p>Measured distances, angles, RMSD, RMSF, vestibule diameters and principal components along with the structural representations in pymol pse files and the manuscript images. The measurements have a 1ns time resolution.</p> <p> </p> <p>DATA_sodium_stabilize_SERT.zip<br> ├── fig1<br> │ ├── fig1_v3.png<br> │ ├── occ_3ions_rmsf_TMH_fitted_250_500.xvg<br> │ ├── occ_Cl_rmsf_TMH_fitted_250_500.xvg<br> │ ├── occ_ionless_rmsf_TMH_fitted_250_500.xvg<br> │ ├── out_3ions_rmsf_TMH_fitted_250_500.xvg<br> │ ├── out_Cl_rmsf_TMH_fitted_250_500.xvg<br> │ └── out_ionles_rmsf_TMH_fitted_250_500.xvg<br> ├── fig2<br> │ ├── distances_n_angles_fig2.pse<br> │ ├── fig2_v2.png<br> │ ├── occ_apo_nosalt_3ions.rep1.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_3ions.rep1.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_3ions.rep4.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_3ions.rep4.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_3ions.rep5.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_3ions.rep5.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_Cl.rep4.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_Cl.rep4.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_Cl.rep5.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_Cl.rep5.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_ionless.rep4.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_ionless.rep4.TM1b-TM9up.dat<br> │ ├── occ_apo_nosalt_ionless.rep5.TM1b-TM8down.dat<br> │ ├── occ_apo_nosalt_ionless.rep5.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_3ions.rep4.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_3ions.rep4.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_3ions.rep5.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_3ions.rep5.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_Cl.rep4.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_Cl.rep4.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_Cl.rep5.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_Cl.rep5.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_ionless.rep4.TM1b-TM8down.dat<br> │ ├── out_apo_nosalt_ionless.rep4.TM1b-TM9up.dat<br> │ ├── out_apo_nosalt_ionless.rep5.TM1b-TM8down.dat<br> │ └── out_apo_nosalt_ionless.rep5.TM1b-TM9up.dat<br> ├── fig3<br> │ ├── fig3_v2.png<br> │ ├── occ_apo_nosalt_3ions.rep1.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep1.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_3ions.rep1.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep1.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_3ions.rep4.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep4.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_3ions.rep5.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep5.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep4.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep4.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_Cl.rep5.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep5.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM9-TM3-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM9-TM3-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep4.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep4.TM9-TM8-TM6a.dat<br> │ ├── occ_apo_nosalt_ionless.rep5.TM9-TM8-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep5.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep4.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep4.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_3ions.rep5.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep5.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep4.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep4.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_Cl.rep5.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep5.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM9-TM3-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM9-TM3-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep4.TM9-TM8-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep4.TM9-TM8-TM6a.dat<br> │ ├── out_apo_nosalt_ionless.rep5.TM9-TM8-TM1b.dat<br> │ └── out_apo_nosalt_ionless.rep5.TM9-TM8-TM6a.dat<br> ├── fig4<br> │ ├── cluster_centr_250_500_concat_bundle-fit_bundle-measure_in_fig4.pse<br> │ ├── fig4_v2.png<br> │ ├── occ_apo_nosalt_3ions.rep1.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep1.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_3ions.rep4.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep4.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_3ions.rep5.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_3ions.rep5.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_Cl.rep4.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep4.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_Cl.rep5.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_Cl.rep5.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_ionless.rep4.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep4.TM6a-TM6b.dat<br> │ ├── occ_apo_nosalt_ionless.rep5.TM1a-TM1b.dat<br> │ ├── occ_apo_nosalt_ionless.rep5.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep1.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep2.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep3.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_3ions.rep4.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep4.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_3ions.rep5.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_3ions.rep5.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep1.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep2.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep3.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_Cl.rep4.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep4.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_Cl.rep5.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_Cl.rep5.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep1.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep2.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep3.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_ionless.rep4.TM1a-TM1b.dat<br> │ ├── out_apo_nosalt_ionless.rep4.TM6a-TM6b.dat<br> │ ├── out_apo_nosalt_ionless.rep5.TM1a-TM1b.dat<br> │ └── out_apo_nosalt_ionless.rep5.TM6a-TM6b.dat<br> ├── fig5<br> │ ├── concat_0_500_dt_RMSF_bundle_fit_bundle_measure_colored.pse<br> │ ├── fig5_v3.png<br> │ ├── occ_apo_nosalt_3ions.concatenated_trajectories.rmsf_bundle_fitted_0_500_concat_protein.xvg<br> │ ├── occ_apo_nosalt_3ions.rep1.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_3ions.rep2.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_3ions.rep3.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_3ions.rep4.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_3ions.rep5.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_Cl.concatenated_trajectories.rmsf_bundle_fitted_0_500_concat_protein.xvg<br> │ ├── occ_apo_nosalt_Cl.rep1.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_Cl.rep2.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_Cl.rep3.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_Cl.rep4.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_Cl.rep5.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_ionless.concatenated_trajectories.rmsf_bundle_fitted_0_500_concat_protein.xvg<br> │ ├── occ_apo_nosalt_ionless.rep1.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_ionless.rep2.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_ionless.rep3.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_ionless.rep4.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── occ_apo_nosalt_ionless.rep5.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_3ions.concatenated_trajectories.rmsf_bundle_fitted_0_500_concat_protein.xvg<br> │ ├── out_apo_nosalt_3ions.rep1.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_3ions.rep2.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_3ions.rep3.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_3ions.rep4.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_3ions.rep5.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_Cl.concatenated_trajectories.rmsf_bundle_fitted_0_500_concat_protein.xvg<br> │ ├── out_apo_nosalt_Cl.rep1.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_Cl.rep2.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_Cl.rep3.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_Cl.rep4.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_Cl.rep5.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_ionless.concatenated_trajectories.rmsf_bundle_fitted_0_500_concat_protein.xvg<br> │ ├── out_apo_nosalt_ionless.rep1.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_ionless.rep2.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_ionless.rep3.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ ├── out_apo_nosalt_ionless.rep4.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> │ └── out_apo_nosalt_ionless.rep5.RMSD_fit-boundle_CA_measure-boundle_CA_preEQreference.xvg<br> ├── fig6<br> │ ├── fig6_v5.png<br> │ ├── occ_3ions_projected_scaffoldFIT_bundleMEASURE.xvg<br> │ ├── occ_Cl_projected_scaffoldFIT_bundleMEASURE.xvg<br> │ ├── occ_ionless_projected_scaffoldFIT_bundleMEASURE.xvg<br> │ ├── out_3ions_projected_scaffoldFIT_bundleMEASURE.xvg<br> │ ├── out_Cl_extreme_scaffoldFIT_bundleMEASURE1.pdb<br> │ ├── out_Cl_extreme_scaffoldFIT_bundleMEASURE2.pdb<br> │ ├── out_Cl_projected_scaffoldFIT_bundleMEASURE.xvg<br> │ ├── out_ionless_projected_scaffoldFIT_bundleMEASURE.xvg<br> │ └── scaffoldFIT_bundleMEASURE_global_covar_extrame1.pse<br> ├── fig7<br> │ ├── fig7_v2.png<br> │ ├── occ_apo_nosalt_3ions.rep1.radii_refitted.dat<br> │ ├── occ_apo_nosalt_3ions.rep2.radii_refitted.dat<br> │ ├── occ_apo_nosalt_3ions.rep3.radii_refitted.dat<br> │ ├── occ_apo_nosalt_3ions.rep4.radii_refitted.dat<br> │ ├── occ_apo_nosalt_3ions.rep5.radii_refitted.dat<br> │ ├── occ_apo_nosalt_Cl.rep1.radii_refitted.dat<br> │ ├── occ_apo_nosalt_Cl.rep2.radii_refitted.dat<br> │ ├── occ_apo_nosalt_Cl.rep3.radii_refitted.dat<br> │ ├── occ_apo_nosalt_Cl.rep4.radii_refitted.dat<br> │ ├── occ_apo_nosalt_Cl.rep5.radii_refitted.dat<br> │ ├── occ_apo_nosalt_ionless.rep1.radii_refitted.dat<br> │ ├── occ_apo_nosalt_ionless.rep2.radii_refitted.dat<br> │ ├── occ_apo_nosalt_ionless.rep3.radii_refitted.dat<br> │ ├── occ_apo_nosalt_ionless.rep4.radii_refitted.dat<br> │ ├── occ_apo_nosalt_ionless.rep5.radii_refitted.dat<br> │ ├── out_apo_nosalt_3ions.rep1.radii_refitted.dat<br> │ ├── out_apo_nosalt_3ions.rep2.radii_refitted.dat<br> │ ├── out_apo_nosalt_3ions.rep3.radii_refitted.dat<br> │ ├── out_apo_nosalt_3ions.rep4.radii_refitted.dat<br> │ ├── out_apo_nosalt_3ions.rep5.radii_refitted.dat<br> │ ├── out_apo_nosalt_Cl.rep1.radii_refitted.dat<br> │ ├── out_apo_nosalt_Cl.rep2.radii_refitted.dat<br> │ ├── out_apo_nosalt_Cl.rep3.radii_refitted.dat<br> │ ├── out_apo_nosalt_Cl.rep4.radii_refitted.dat<br> │ ├── out_apo_nosalt_Cl.rep5.radii_refitted.dat<br> │ ├── out_apo_nosalt_ionless.rep1.radii_refitted.dat<br> │ ├── out_apo_nosalt_ionless.rep2.radii_refitted.dat<br> │ ├── out_apo_nosalt_ionless.rep3.radii_refitted.dat<br> │ ├── out_apo_nosalt_ionless.rep4.radii_refitted.dat<br> │ └── out_apo_nosalt_ionless.rep5.radii_refitted.dat<br> └── Sfig1<br> ├── distances_n_angles_fig2.pse<br> ├── occ_apo_nosalt_3ions.rep1.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_3ions.rep1.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_3ions.rep2.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_3ions.rep2.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_3ions.rep3.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_3ions.rep3.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_3ions.rep4.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_3ions.rep4.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_3ions.rep5.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_3ions.rep5.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_Cl.rep1.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_Cl.rep1.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_Cl.rep2.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_Cl.rep2.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_Cl.rep3.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_Cl.rep3.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_Cl.rep4.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_Cl.rep4.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_Cl.rep5.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_Cl.rep5.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_ionless.rep1.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_ionless.rep1.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_ionless.rep2.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_ionless.rep2.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_ionless.rep3.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_ionless.rep3.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_ionless.rep4.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_ionless.rep4.TM6a-TM9up.dat<br> ├── occ_apo_nosalt_ionless.rep5.TM6a-TM8down.dat<br> ├── occ_apo_nosalt_ionless.rep5.TM6a-TM9up.dat<br> ├── out_apo_nosalt_3ions.rep1.TM6a-TM8down.dat<br> ├── out_apo_nosalt_3ions.rep1.TM6a-TM9up.dat<br> ├── out_apo_nosalt_3ions.rep2.TM6a-TM8down.dat<br> ├── out_apo_nosalt_3ions.rep2.TM6a-TM9up.dat<br> ├── out_apo_nosalt_3ions.rep3.TM6a-TM8down.dat<br> ├── out_apo_nosalt_3ions.rep3.TM6a-TM9up.dat<br> ├── out_apo_nosalt_3ions.rep4.TM6a-TM8down.dat<br> ├── out_apo_nosalt_3ions.rep4.TM6a-TM9up.dat<br> ├── out_apo_nosalt_3ions.rep5.TM6a-TM8down.dat<br> ├── out_apo_nosalt_3ions.rep5.TM6a-TM9up.dat<br> ├── out_apo_nosalt_Cl.rep1.TM6a-TM8down.dat<br> ├── out_apo_nosalt_Cl.rep1.TM6a-TM9up.dat<br> ├── out_apo_nosalt_Cl.rep2.TM6a-TM8down.dat<br> ├── out_apo_nosalt_Cl.rep2.TM6a-TM9up.dat<br> ├── out_apo_nosalt_Cl.rep3.TM6a-TM8down.dat<br> ├── out_apo_nosalt_Cl.rep3.TM6a-TM9up.dat<br> ├── out_apo_nosalt_Cl.rep4.TM6a-TM8down.dat<br> ├── out_apo_nosalt_Cl.rep4.TM6a-TM9up.dat<br> ├── out_apo_nosalt_Cl.rep5.TM6a-TM8down.dat<br> ├── out_apo_nosalt_Cl.rep5.TM6a-TM9up.dat<br> ├── out_apo_nosalt_ionless.rep1.TM6a-TM8down.dat<br> ├── out_apo_nosalt_ionless.rep1.TM6a-TM9up.dat<br> ├── out_apo_nosalt_ionless.rep2.TM6a-TM8down.dat<br> ├── out_apo_nosalt_ionless.rep2.TM6a-TM9up.dat<br> ├── out_apo_nosalt_ionless.rep3.TM6a-TM8down.dat<br> ├── out_apo_nosalt_ionless.rep3.TM6a-TM9up.dat<br> ├── out_apo_nosalt_ionless.rep4.TM6a-TM8down.dat<br> ├── out_apo_nosalt_ionless.rep4.TM6a-TM9up.dat<br> ├── out_apo_nosalt_ionless.rep5.TM6a-TM8down.dat<br> ├── out_apo_nosalt_ionless.rep5.TM6a-TM9up.dat<br> └── Sfig1_v2.png</p> <p> </p>
Chloroplast motion under dim light conditions
<p><em>Elodea densa </em>was kept in an aquatic culture. Ambient light conditions were applied 1h before image acquisition. <br> Imaging preparation: a low-light adapted leaf was detached and placed between two glass slides.<br> Lower cell layer is displayed. <br> Microscopy: Bright field microscopy was performed with a Nikon TI2 microscope using a halogen light source and a red-light 620nm cut-on wavelength filter at low light intensities of 7.2 W/cm^2 in combination with a Photometrics BSI Express sCMOS camera with high quantum yield to enable imaging every 1s with a $63\times$ water-immersion objective (NA=1.2) and pixel resolution of 0.1µm/px. <br> <br> Description:<br> Chloroplast.zip:<br> Contains ome.tiff files for 3600 frames of chloroplast motion (total duration 1h)<br> The dense chloroplasts (dark circular objects) inside the plant cells move by actin-mediated propulsion mechanism. <br> <br> 211013_CP_rawLabelMeasures.csv:<br> Analysis of segmented data (3600 frames) <br> <br> 211013_CP_tracks_vel.csv:<br> Trajectories (with velocities) constructed by trackpy from center-of-mass positions of the 211013_CP_rawLabelMeasures.csv. <br> Velocities where calculated using the first derivative of 3rd order Savitzky-Golay filtered data (Kernel width 11s). </p> <p><br> <br> </p>
Evaluating 3D Human Motion Capture using Apple ARKit against the Vicon System: A Dataset
<p><strong>A journal paper which was published in Applied Sciences gives detailed information about the dataset.</strong></p> <p>Reimer, L.M.; Kapsecker, M.; Fukushima, T.; Jonas, S.M. Evaluating 3D Human Motion Capture on Mobile Devices. Appl. Sci. <em>(2022)</em></p> <p><a href="https://www.mdpi.com/2076-3417/12/10/4806">https://www.mdpi.com/2076-3417/12/10/4806</a></p> <p>Please cite the corresponding paper when using the dataset.</p> <p> </p> <p>A dataset containing anonymized exercise data for eight exercises from ten subject. The exercise data was recorded with two iPads 11" (2021 version, Apple Inc., Cupertino, CA, USA) and a Vicon system. The two iPads were positioned frontal and in a 30° angle to the left side of the subject. The Vicon system used 14 cameras and captured the motion using the Full-body Plug-in-gait model.</p> <p>The dataset contains 220 files, 22 per subject. The structure of the dataset contains 10 folders, one per subject. Each folder contains two subfolders: ARKit and Vicon. Each ARKit folder holds two CSV files. Each Vicon folder holds 16 files, two per exercise: a .csv file with the motion data and a .xcp file containing meta data about the recording, including the camera setup and start/stop timestamps.</p> <p>Du to export problems, the ARKit files for the Side View do not always contain all joint data. The upper body joints are only available for three out of the ten subjects for the Side View.</p>
Assets for 'Phase correlation on the edge for estimating cloud motion' submitted to Atmospheric Measurement Techniques
<p>1. CMV-26-07-2016_ARM-SGP.gif Sample cloud motion vectors from TSI camera images over the United States Atmospheric Radiation Measurement user facility’s Southern Great Plains site.</p> <p>2. raindrop_02-01-2017_ARM-SGP.gif Rotation of cloud motion vectors from raindrop contaminated TSI camera.</p>
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.