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249 results for “pocket”
Amphora with "pockets"
ID no.: MAK/NH/30/52 Archaeological Museum in Kraków https://muzea.malopolska.pl/en/objects-list/1575 Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
Genomic resources for the little pocket mouse (Perognathus longimembris longimembris)
<p>The little pocket mouse, <em class="italic">Perognathus longimembris</em>, and its nine congeners are small heteromyid rodents found in arid and seasonally arid regions of Western North America. The genus is characterized by behavioral and physiological adaptations to dry and often harsh environments, including nocturnality, seasonal torpor, food caching, enhanced osmoregulation, and a well-developed sense of hearing. Here we present a genome assembly of <em class="italic">Perognathus longimembris longimembris</em> generated from PacBio HiFi long read and Omni-C chromatin-proximity sequencing as part of the California Conservation Genomics Project. The assembly has a length of 2.35 Gb, contig N50 of 11.6 Mb, scaffold N50 of 73.2 Mb, and includes 93.8% of the BUSCO Glires genes. Interspersed repetitive elements constitute 41.2% of the genome. A comparison with the highly endangered Pacific pocket mouse, <em class="italic">P. l. pacificus</em>, reveals broad synteny. These new resources will enable studies of local adaptation, genetic diversity, and conservation of threatened taxa.</p>
SiteMap pockets for the PDBbind dataset
<p>This dataset includes the protein pockets identified by using the SITEMAP approach [SITEMAP] for the PDBbind v.2020 dataset. <br>Only the proteins that were automatically processed by the tool, without generating any error, are included here.</p><p>[SITEMAP] T. Halgren, "New Method for Fast and Accurate Binding- site Identification and Analysis," Chemical Biology & Drug Design, vol. 69, no. 2, pp. 146–148, Feb. 2007, doi: 10.1111/j.1747-0285.2007.00483.x.</p>
Pocket watch for the blind
The presented pocket watch told the time without the need to look at the dial. The front of the case takes the form of a lid with a convex arrow and was used as a dial. From the clockwork side there is a flap blocking the lid rotation. In order to determine the time, the lid with the arrow rotated counterclockwise until resistance of the flap. On the circumference of the watch there are balls indicating the sequential hours. They are not differentiated, except at 12.00, which is determined by the jump ring used to hang the watch. The arrow indicated the appropriate ball representing the hour. The minutes are not marked; they can only be estimated based on the position of the arrow between the hour points. Creator: Abraham Louis Breguet (1747–1823) Time and place of creation: early 19th century, Paris Jagiellonian University Museum Collegium Maius Inventory number: 1721; 1434/V https://muzea.malopolska.pl/en/objects-list/2739 Source: Objaverse 1.0 / Sketchfab
Mikiphone pocket phonograph
ID no.: MIM 299/V-46 https://muzea.malopolska.pl/en/objects-list/83 Museum: The Municipal Engineering Museum Digitalisation: RDW MIC, Małopolska's Virtual Museums project Source: Objaverse 1.0 / Sketchfab
Pocket sextant
James Henri Steward late 19th century, London, Great Britain Jagiellonian University Museum Collegium Maius Inventory number: 17231; 2255/V https://muzea.malopolska.pl/en/objects-list/2786 Source: Objaverse 1.0 / Sketchfab
Kodak Pocket No3 E Camera circa 1912
My 3D reconstruction generated with photogrammetry software 3DF Zephyr v4.523 processing 128 images Source: Objaverse 1.0 / Sketchfab
A Comprehensive Dataset of protein-protein interactions and Ligand Binding Pockets for Advancing Drug Discovery
<p>This dataset presents a comprehensive collection of structural data related to protein-protein interactions (PPIs) and ligand binding pockets. The dataset includes high-quality structural information that can aid researchers in the fields of bioinformatics, structural biology, and drug discovery. It encompasses a diverse set of PPI complexes and associated ligands, enabling detailed investigations into molecular interactions at the atomic level. This article introduces an indispensable resource designed to unlock the full potential of PPIs while pioneering a novel metric for pocket similarity for repurposing protein partners.</p>
Discovering cryptic pocket opening and binding of a stimulant derivative in a vestibular site of the 5-HT3A receptor
<p>Raw MD simulation data of 4-Bromoamphetamine-5HT3A complex in two different forceeild, AMBER and CHARMM.</p> <p>Original paper title: "Discovering cryptic pocket opening and binding of a stimulant derivative in a vestibular site of the 5-HT3A receptor"</p> <p>Author list: <span>Nandan Haloi</span><span>,</span> <span>Emelia Karlsson</span><span>,</span> <span>Marc Delarue, </span><span>Rebecca J. Howard</span><span>,</span> <span>Erik Lindahl</span></p>
FOD CT Data: air pockets in avocado and stone in modelling clay
<p><strong>Summary</strong></p> <p>This submission contains X-ray CT data of avocado fruits and pieces of modelling clay containing pebble stones.<br> Data for every object include binned pre-processed projections and volume segmentations.<br> These datasets can be used for training and testing deep learning methods for foreign object detection.</p> <p>The data is made available as a part of the paper "CT-based data generation for foreign object detection on a single X-ray projection".</p> <p><strong>Data acquisition</strong></p> <p>A majority of raw data for modeling clay (excluding 10 samples without pebble stones in the Test subset) is taken from the dataset<br> "A collection of 131 CT datasets of pieces of modeling clay containing stones"<br> [](https://doi.org/10.5281/zenodo.5866228)</p> <p>The remaining pieces of modeling clay and all avocado fruits were scanned at the FleX-ray laboratory<br> of the Centrum Wiskunde & Informatica (CWI) in Amsterdam, the Netherlands (details can be found in [Coban 2020]).<br> For every fruit, we made scans with significantly different amounts of air pockets by waiting for a few days between experimental acquisitions.<br> The measurements were performed with the voltage of 90 kV, power of 45 W, exposure time of 300 ms per projection, and magnification factor of 1.3.<br> The original X-ray image size was 1912 px x 1520 px with a pixel size of 75 μm, 1440 images were acquired for every sample.<br> For faster deep learning model training, images and reconstructions were downsampled with a factor of 4, leading to the effective pixel size of 300 μm and voxel size of 230 μm.<br> Additional scans of the pieces of modeling clay were acquired with settings similar to the main collection.</p> <p><strong>Data Description</strong></p> <p>The submission is split into "Avocado" and "Playdoh" (pieces of modeling clay) datasets. Each dataset is further split into Training and Test subsets.</p> <p>The folder for every scanned object contains<br> - ./log/ - subfolder with logarithmed X-ray projections after darkfield and flatfield correction.<br> - ./segm/ - subfolder with slices of the segmented volume.<br> - ./scan settings.txt - a file with scanner metadata containing scan geometry<br> - ./volume_info.csv - a file with a voxel count for every class in the segmentation.</p> <p>For playdoh objects, the segmentation classes are modeling clay (Class 1) and pebble stone (Class 2). In this case, pebble stones are foreign objects.</p> <p>For avocado objects, the segmentation classes are peel (Class 1), avocado meat (Class 2), seed (Class 3) and air pockets (Class 4). Air pockets are considered a foreign object.</p> <p><strong>Additional Links</strong></p> <p>These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's GitHub page.</p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these datasets, please get in touch with<br> - vladyslav.andriiashen [at] cwi.nl</p> <p><strong>References</strong></p> <p>[Coban 2020] S. B. Coban, F. Lucka, W. J. Palenstijn, D. Van Loo, and K. J. Batenburg, “Explorative imaging and its implementation at the FleX-ray Laboratory,” J. Imaging, vol. 6, no. 18, 2020, doi: 10.3390/jimaging6040018.</p>
Target-focused library design by pocket-applied computer vision and fragment deep generative linking
<p>Data inputs and outputs used in</p> <pre>Target-focused library design by pocket-applied computer vision and fragment deep generative linking</pre> <p>Code: https://github.com/kimeguida/POEM</p> <p> </p>
Pocket first aid kit of Aleksander Mańkowski
ID no.: KGZ 138 Museum: The Museum of Pharmacy at the Jagiellonian University Medical College in Kraków https://muzea.malopolska.pl/en/objects-list/1715 Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
Joachim Liebermann's pocket watch
Before the outbreak of World War II, the Liebermanns and their related Druks were co-owners of Emil Kuźnicki's Roof Papa Factory in Brzezinka (established in 1888). In 1939, both families fled from the impending war to the East. Time of creation: 1st half of the 20th century https://muzea.malopolska.pl/en/objects-list/2059 Inventory number: MŻ 38 Museum: Auschwitz Jewish Centre Digitalisation: Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
Vintage Pocket Watch
A pocket watch modeled in Blender, the reference is Quartz Paul Jardin, Textured in SP. Source: Objaverse 1.0 / Sketchfab
Pocket chronometer watch
Time and place of creation: 1787–1796 Creator: John Arnold and Son Inventory number: 1708; 446/V Museum: Jagiellonian University Museum Collegium Maius https://muzea.malopolska.pl/en/objects-list/2741 Digitalisation: Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
Full inventory of ten permanent plots installed in pockets of different tree functional types along the Moni River transects (Yangambi, Democratic Republic of Congo)
<p>Most of the tropical forests of Central Africa are characterised by a remarkable abundance of light-demanding canopy species. A popular hypothesis is that these forests are still recovering from the intense slash-and-burn farming activities that ended abruptly in the 19th century with the arrival of the colonists. Today, it is assumed that the zones occupied by crop fields until the 19th century are covered by forests dominated by light-demanding species. However, this hypothesis of human disturbance has not yet been sufficiently tested using spatial distribution. So, using the 'Kernel Density Estimation' (KDE) tool in the SAGA GIS software, we mapped the density distribution of light-demanding species, subdivided into 3 tree functional types, along transects in the Moni river catchment. We also produced a similar map for a particular shade-tolerant species, 'Gilbertiodendron dewevrei'. The species were then divided into the following groups, known as 'functional tree types': LLP=Long-Lived Pioneer, NPLD=Non-Pioneer Light Demanding, SLP=Short-Lived Pioneer, and STS=Shade-Tolerant Species. At the end of this analysis, a density distribution map of the species of each tree functional type was produced. This map highlights the pockets (zones with a high density relative to the study site average) of tree functional types. For each type of pocket, we selected the pockets with a high density of trees of the group concerned and which were not on the edge between the forest and village crops or fallow land. This is how the location of the permanent plots was determined. Next, we installed a total of ten full forest inventory plots (1 ha each) inside and outside the pockets located by the KDE analysis along the Moni River transects. More specifically, we installed one plot in a pocket of short-lived pioneers (SLP-01), three plots in pockets of long-lived pioneers (LLP-01 to -03), two plots in pockets of NPLD (NPLD-01 and -02), two plots in pockets of the shade-tolerant species Gilbertiodendron dewevrei (GIL-01 and -02) and finally two plots were located in a mixed old-growth forest outside the pockets (MIX-01 and -02). These plots were established (1) for long-term monitoring of biodiversity and forest dynamics; and (2) to see if there is a difference in terms of species composition and abundance of light demanders between the forest inside the pockets and that outside the pockets.</p>
Unraveling silicate liquid immiscibility and apatite saturation in the mesostasis pocket of mare basalt: Evidences from Chang'E-5 lunar samples
<p><strong>Figure S1 </strong>Back scatter electron (BSE) images of Chang’E-5 breccia 136GP (top) and 143 GP (bottom)</p> <p><strong>Figure S2</strong> Chemical composition of silicate minerals in CE-5 136GP and 143 GP breccias and comparison with CE-5 mare basalts. A) Quadrilateral diagram of pyroxene in the Chang’E-5 mare basalt. B) Ternary diagram of feldspar from the Chang’E-5 mare basalts. C) Chemical compositions of olivine. The gray background areas represent the composition range of silicate minerals in Chang'e-5 basalts reported by previous studies (Che et al., 2021; He et al., 2022; Hu et al., 2021; Jiang et al., 2022; Tian et al., 2021).</p> <p><strong>Figure S3</strong> Element mapping of one representative mesostasis fragment in CE-5 136GP. a)-j) indicate the abundance maps of Si, Al, Mg, Na, K, Ca, Fe, Mn, Ti, and P within this lithic clast. All of them are in the same scale and the scale bar could be found in J. On each element map, the red or yellow color represents the relative elevated abundance of one specific element; the blue or black indicate its low abundance. k) is the BSE image of this clast and the yellow box outlines the mapping area.</p> <p><strong>Figure S4</strong> Predicted value of P<sub>2</sub>O<sub>5</sub> concentration (wt%) required for phosphate saturation in the Si-rich melts. The calculation is based on the equation built by Tollar et al. (2006). a) and b) represents the function of SiO<sub>2</sub> and CaO concentrations (wt%) respectively. The melt temperature is fixed at 1010 °C. The black circles indicate the data of Si-rich portion within the CE-5 mesostasis fragments investigated in the present study. These plots indicate that apatite crystallized in some of the Si-rich melts.</p> <p><strong>Table S1 Representative mineral EPMA analyses of major compositions (wt%) in the CE-5 mesostasis fragments.</strong></p> <p><strong>Table S2 Representative Raman spectra of minerals in the CE-5 mesostasis fragments.</strong></p>
GPCR-BSD: Predicted Pockets data
Open the record for dataset details and reuse information.
Dataset II related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP3P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7342311</p>
Dataset III related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP4P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7341954</p>
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International Brain Laboratory public data
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OpenNeuro
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