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610 results for “Static”
Fig. 1. Static and dynamic osteogenesis. A in Constraints on the lamina density of laminar bone architecture of large-bodied dinosaurs and mammals
Fig. 1. Static and dynamic osteogenesis. A. Static osteogenesis by static osteoblasts proliferating in situ from mesenchymal tissue. The random orientation of the osteoblasts creates a random local fibre orientation of the produced matrix. B. Static osteoblasts turn into static osteocytes as they become entrapped in the mineralizing woven bone matrix. C. Dynamic osteoblasts arrange themselves on the woven bone and start producing highly organized primary bone, occasionally trapping a dynamic osteoblast, which will then become a dynamic osteocyte. D. Static and dynamic osteocyte lacunae in a longitudinal section of a humerus of the titanosaur Alamosaurus. A–C modified from Marotti (2010), D modified from Stein and Prondvai (2014).
Static NLoS
<p>Measurements are performed in an environment where the user or mobile device does not have a clear and direct line of sight to the 5G network antenna. This scenario is important because it reflects real-world situations where obstacles such as buildings, trees or uneven terrain can obstruct the line of sight between the device and the antenna, which can significantly affect the quality and strength of the 5G signal. In this context, static measurements are performed, meaning that the device or user is not moving during data collection. This static condition allows 5G network performance to be evaluated in situations where users may be stationary, such as in homes, offices or work areas.</p>
Static LoS
<p>Measurements were performed in an environment where the user is at rest and does not move during data collection. Furthermore, in this scenario, there is a clear and direct line of sight between the user's terminal and the 5G network antenna, which means that there are no physical obstacles obstructing the signal between the device and the antenna. This scenario is important because it allows the performance of the 5G network to be evaluated under optimal signal conditions, where interference caused by obstacles such as buildings, trees or other physical elements is minimal or non-existent. By eliminating factors that could degrade signal quality, it is possible to more accurately analyze aspects such as speed, latency and reliability of the connection in an ideal environment.</p>
EBEC-MicroED: Static electron diffraction movies collected at different incident flux on a direct electron detector (DE Apollo) on crystals of (S,S) Jacobsen's salen ligand and Co(II) porphyrin, and diffraction tilt series recorded on the DE Apollo and CetaD detector for the same crystals of Jacobsen's Ligand
<p>This record contains static diffraction movies recorded from crystals of (S,S) Jacobsen's salen ligand, and crystals of Co(II) meso-tetraphenyl porphyrin, using a direct electron detector (DE Apollo) in counting mode. Data were acquired at varying different incident flux settings, referred to as "spotsize11" or "spot11" (0.01 electrons per square Angstoms per second), "spotsize10" or "spot10" (0.03 electrons per square Angstrom per second), "spotsize9" or "spot9" (0.045 electrons per square angstrom per second)", and "spotsize8" or "spot8" (0.084 electrons per sqaure Angstrom per second. For each compound these trials, the same crystal ("crystal1", "crystal2", etc.) was conserved across a dose series, and illuminated at each incident flux from lowest to highest in sequence.</p> <p>Additionally, this record contains diffraction tilt series acquired from crystals of (S,S) Jacobsen's ligand, first on the Ceta D and next on the DE Apollo, rotating at 2 degrees per second with an incident flux of either 0.01 or 0.045 electrons per square Angstrom per second.</p> <p>All data is saved in mrc file format, with the exception of movies from the Ceta D, which are saved in ser file format.</p>
GNSS RF Recordings Dataset from Static Antenna
<p>GNSS RF recordings dataset from the static antenna located on the rooftop of the Tampere Wireless Research Center. The recordings were performed using a NI USRP-2953R and an external clock reference Spectracom GSG-6. The files are provided in binary format. A non-selective gain from the USRP has been applied during the recordings.</p> <p>Novatel_20211130_resampled_10MHz_8bit_IQ_gain25</p> <ul> <li>Date: 2021/11/30 - 8:40 (UTC)</li> <li>Centre frequency: 1575.42 MHz</li> <li>Sampling frequency: 40 MHz</li> <li>Intermediate frequency: 0 Hz (Baseband)</li> <li>Quantization: 8 bits integers, I+Q </li> <li>Gain: 25 dB (non-selective)</li> <li>Note: The In-Phase and Quadraphase measurements are recorded in binary as follow: I_1 Q_1 I_2 Q_2, etc.</li> </ul> <p>Novatel_20240731_142746_40MHz_10MHz_8bit_real_gain15.bin</p> <ul> <li>Date: 2024/07/31 - 11:27 (UTC)</li> <li>Centre frequency: 1575.42 MHz</li> <li>Sampling frequency: 40 MHz</li> <li>Intermediate frequency: 10 MHz</li> <li>Quantization: 8 bits integers, real</li> <li>Gain: 15 dB (non-selective)</li> <li>Note: The real measurements are recorded in binary as follow: R_1 R_2 etc.</li> </ul> <p> </p>
The velocity boundary conditions of the model, the static Coulomb stress, displacement and the direction of the maximum principal stressin in Weiyuan area,China
<p>The velocity boundary conditions of the model, the displacement, the static coulomb stress and the direction of the maximum principal stress data in Weiyuan area, Sichuan Province, China, calculated by numerical simulation method. The calculation time is 10 years and 50 years after fracturing, respectively. The data include longitude, latitude, depth and corresponding calculation results. The parameters are: fracture volume-to-model volume ratio (θ) , the fractures distributed radius (γ) around the wells. </p>
Obtaining Better Static Word Embeddings Using Contextual Embedding Models
<p><strong>Obtaining Better Static Word Embeddings Using Contextual Embedding Models</strong></p> <p>This repository contains the dataset of pretrained word embeddings as well as datasets used to train them, released with the following <a href="https://arxiv.org/pdf/2106.04302.pdf">paper</a>.</p> <blockquote> <p>“Obtaining Better Static Word Embeddings Using Contextual Embedding Models” <em>ACL</em> (2021).</p> </blockquote> <p>The wikipedia datasets were preprocessed from the wikipedia dump downloaded from <a href="http://dumps.wikimedia.org">dumps.wikimedia.org</a> under Creative Commons Attribution-Share-Alike 3.0 License .</p> <p>If you found the provided resources useful, please cite the above paper. Here's a BibTeX entry you may use:</p> <blockquote> <p>@inproceedings{Gupta2021ObtainingPC,<br> title={Obtaining Better Static Word Embeddings Using Contextual Embedding Models},<br> author={Prakhar Gupta and Martin Jaggi},<br> booktitle={ACL},<br> year={2021}<br> }</p> </blockquote>
Figure 23. Scale morphology. A, B, Adscita statices. C, Inouela formosensis. D, Phauda mimica. E, Callizygaena auratus. F, Callizygaena splendens. G, H, Chalcosiopsis variata. I, Lactura dives. J, K, Himantopteris fuscinervis. L in The phylogenetic relationships of Chalcosiinae (Lepidoptera, Zygaenoidea, Zygaenidae)
Figure 23. Scale morphology. A, B, Adscita statices. C, Inouela formosensis. D, Phauda mimica. E, Callizygaena auratus. F, Callizygaena splendens. G, H, Chalcosiopsis variata. I, Lactura dives. J, K, Himantopteris fuscinervis. L, Anomoetes levis.
Figure 14. Antennae. A, Agalope trimacula. B, Rhodopsona rutila. C, D, Eterusia aedea formosana. E, Cyclosia midama. F, Heteropan scintillans. G, H, Callizygaena glacon. I, Adscita statices. J, Inouela formosensis. K, Zygaena filipendulae. L, Phauda mimica. M, N, Lactura dives. O, Anomoeotis levis. P, Himantopteus fuscinervis. Q, R in The phylogenetic relationships of Chalcosiinae (Lepidoptera, Zygaenoidea, Zygaenidae)
Figure 14. Antennae. A, Agalope trimacula. B, Rhodopsona rutila. C, D, Eterusia aedea formosana. E, Cyclosia midama. F, Heteropan scintillans. G, H, Callizygaena glacon. I, Adscita statices. J, Inouela formosensis. K, Zygaena filipendulae. L, Phauda mimica. M, N, Lactura dives. O, Anomoeotis levis. P, Himantopteus fuscinervis. Q, R, Chalcosiopsis variata.
Effects of population density on static allometry between horn length and body mass in mountain ungulates
<p class="MsoNoSpacing">Little is known about the effects of environmental variation on allometric relationships of condition-dependent traits, especially in wild populations. We estimated sex-specific static allometry between horn length and body mass in four populations of mountain ungulates that experienced periods of contrasting density over the course of the study. These species displayed contrasting sexual dimorphism in horn size; high dimorphism in <i>Capra ibex</i> and <i>Ovis canadensis</i> and low dimorphism in <i>Rupicapra rupicapra</i> and <i>Oreamnos americanus</i>. The effects of density on static allometric slopes were weak and inconsistent while allometric intercepts were generally lower at high density, especially in males from species with high sexual dimorphism in horn length. These results confirm that static allometric slopes are more canalized than allometric intercepts against environmental variation induced by changes in population density, particularly when traits appear more costly to produce and maintain.</p>
Evolution of static allometry and constraint on evolutionary allometry in a fossil stickleback
<p>Allometric scaling describes the relationship of trait size to body size within and among taxa. The slope of the population-level regression of trait size against body size (<em>i.e., </em>static allometry) is typically invariant among closely related populations and species. Such invariance is commonly interpreted to reflect a combination of developmental and selective constraints that delimit a phenotypic space into which evolution could proceed most easily. Thus, understanding how allometric relationships do eventually evolve is important to understanding phenotypic diversification. In a lineage of fossil Threespine Stickleback (<em>Gasterosteus doryssus</em>), we investigated the evolvability of static allometric slopes for nine traits (five armor, and four non-armor) that evolved significant trait differences across 10 samples over 8,500 years. The armor traits showed weak static allometric relationships and a mismatch between those slopes and observed evolution. This suggests that observed evolution in these traits was not constrained by relationships with body size, perhaps because prior, repeated adaptation to freshwater habitats by Threespine Stickleback had generated strong selection to break constraint. In contrast, for non-armor traits, we found stronger allometric relationships. Those allometric slopes did evolve on short time scales. However, those changes were small and fluctuating and the slopes remained strong predictors of the evolutionary trajectory of trait means over time (<em>i.e.,</em> evolutionary allometry), supporting the hypothesis of allometry as a constraint.</p>
Elevated Static Exposure Experiment Images
<p>Cross-sections of specimens exposed to various liquid metal droplets at 400°C for 3 days. File names indicate the liquid metal used first, followed by the metal or alloy tested. File names that include 'saturated' used liquid bismuth that had been pre-saturated with copper to the solubility limit at the test temperature. Scale bars are provided on each image. </p>
An Empirical Evaluation of Quasi-Static Executable Slices
<p>This artifact contains the dataset and scripts used to reproduce the experiments of the article "An Empirical Evaluation of Quasi-Static Executable Slices"</p>
Dataset: A Neutral pH Aqueous Biphasic System Applied to both Static and Flow Membrane-free Battery
<p>Dataset for the results shown in the publication "A Neutral pH Aqueous Biphasic System Applied to both Static and Flow Membrane-free Battery"</p>
Alert Type Frequency Assessment of Open-Source Static Analysis Tools and Codebases
<p>This includes all data needed to replicate and validate our frequency analysis of static analysis (SA) alerts produced using open-source SA tools on several OSS codebases. It includes instructions how to get and run the SA tools, a Dockerfile to conveniently get and use the SA tools, raw SA tool output, some python scripts to parse that output, parsed SA data and aggregate analyses, and SA data augmented with CERT coding rule and CWE data. </p> <p>The SA tools used:</p> <ul> <li>clang-tidy version 15.07 </li> <li>cppcheck version 2.9 </li> <li>CERT Rosecheckers </li> </ul> <p>The codebases analyzed:</p> <ul> <li>zeek version 5.1.1</li> <li>git version 2.39.0</li> <li>dos2unix version 7.4.3</li> </ul>
Predicting the Relative Static Permittivity: a Group Contribution Method Based on Perturbation Theory
<p>Permittivity-over-temperature diagram for the publication "Predicting the Relative Static Permittivity: a Group Contribution Method Based on Perturbation Theory" published under DOI 10.1021/acs.jced.3c00323 in the Journal of Chemical and Engineering Data.</p>
ONERA Numerical Database Configuration A1 (static propeller)
<p>This database contains the numerical results obtained by ONERA on the configuration A1, using ZDES mode 2 and ZDES mode 3 methods. The ZDES mode 3 approach offers an explicit resolution of the turbulent scales present in the outer region of the flat plate boundary layer and their interaction with the propeller.</p>
Quasi-Static and Fatigue Testing Dataset for soft bone cements according to ASTM F2118
<p>This Dataset features quasi-static and fatigue data of PMMA cements. All the tests were run on an MTS 858 Mini Bionix (MTS Systems Corporation, United States). In summary, this dataset contains:</p> <ul> <li>Videos captured for marker tracking used in a virtual extensometer (.mp4)</li> <li>Quasi-static testing data for the PMMA cements (.txt)</li> <li>Fatigue data for three different stress levels (5MPa, 7MPa, 9MPa) (.txt)</li> <li>An Excel sheet with corrected tensile properties (.xlsx)</li> </ul> <p>General Abbreviations:</p> <ul> <li>VS is the V-Steady Cement</li> <li>VSLA is the V-Steady Cement with 12%vol linoleic acid</li> </ul> <p>Abbreviations for Fatigue Data:</p> <ul> <li>B is the batch number</li> <li>S is the sample number</li> </ul>
Data for high-clay content submarine slope failure flume experiments. Experiment 25% clay, static 1, part 1.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 25% clay, static 1, part 2.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</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.