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480 results for “mirrors”
Data from: Genes mirror geography in Daphnia magna
Identifying the presence and magnitude of population genetic structure remains a major consideration in evolutionary biology as doing so allows one to understand the demographic history of a species as well as make predictions of how the evolutionary process will proceed. Next-generation sequencing methods allow us to reconsider previous ideas and conclusions concerning the distribution of genetic variation, and what this distribution implies about a given species evolutionary history. A previous phylogeographic study of the crustacean Daphnia magna suggested that, despite strong genetic differentiation among populations at a local scale, the species shows only moderate genetic structure across its European range, with a spatially patchy occurrence of individual lineages. We apply RAD sequencing to a sample of D. magna collected across a wide swath of the species' Eurasian range and analyse the data using principle component analysis (PCA) of genetic variation and Procrustes analytical approaches, to quantify spatial genetic structure. We find remarkable consistency between the first two PCA axes and the geographic coordinates of individual sampling points, suggesting that, on a continent-wide scale, genetic differentiation is driven to a large extent by geographic distance. The observed pattern is consistent with unimpeded (i.e. no barriers, landscape or otherwise) migration at large spatial scales, despite the fragmented and patchy nature of favourable habitats at local scales. With high-resolution genetic data similar patterns may be uncovered for other species with wide geographic distributions, allowing an increased understanding of how genetic drift and selection have shaped their evolutionary history.
Data from: Population genetic inferences using immune gene SNPs mirror patterns inferred by microsatellites
Single nucleotide polymorphisms (SNPs) are replacing microsatellites for population genetic analyses, but it is not apparent how many SNPs are needed or how well SNPs correlate with microsatellites. We used data from the gopher tortoise, Gopherus polyphemus—a species with small populations, to compare SNPs and microsatellites to estimate population genetic parameters. Specifically, we compared one SNP data set (16 tortoises from four populations sequenced at 17 901 SNPs) to two microsatellite data sets, a full data set of 101 tortoises and a partial data set of 16 tortoises previously genotyped at 10 microsatellites. For the full microsatellite data set, observed heterozygosity, expected heterozygosity and FST were correlated between SNPs and microsatellites; however, allelic richness was not. The same was true for the partial microsatellite data set, except that allelic richness, but not observed heterozygosity, was correlated. The number of clusters estimated by structure differed for each data set (SNPs = 2; partial microsatellite = 3; full microsatellite = 4). Principle component analyses (PCA) showed four clusters for all data sets. More than 800 SNPs were needed to correlate with allelic richness, observed heterozygosity and expected heterozygosity, but only 100 were needed for FST. The number of SNPs typically obtained from next-generation sequencing (NGS) far exceeds the number needed to correlate with microsatellite parameter estimates. Our study illustrates that diversity, FST and PCA results from microsatellites can mirror those obtained with SNPs. These results may be generally applicable to small populations, a defining feature of endangered and threatened species, because theory predicts that genetic drift will tend to outweigh selection in small populations.
Data from: DNA from soil mirrors plant taxonomic and growth form diversity
Ecosystems across the globe are threatened by climate change and human activities. New rapid survey approaches for monitoring biodiversity would greatly advance assessment and understanding of these threats. Taking advantage of next-generation DNA sequencing, we tested an approach we call metabarcoding: high-throughput and simultaneous taxa identification based on a very short (usually less than 100 base pairs) but informative DNA fragment. Short DNA fragments allow the use of degraded DNA from environmental samples. All analyses included amplification using plant-specific versatile primers, sequencing and estimation of taxonomic diversity. We tested in three steps whether degraded DNA from dead material in soil has the potential of efficiently assessing biodiversity in different biomes. First, soil DNA from eight boreal plant communities located in two different vegetation types (meadow and heath) was amplified. Plant diversity detected from boreal soil was highly consistent with plant functional and structural diversity estimated from conventional above-ground surveys. Second, we assessed DNA persistence using samples from formerly cultivated soils in temperate environments. We found that number of crop DNA sequences retrieved strongly varied with years since last cultivation, and crop sequences were absent from nearby, uncultivated plots. Third, we assessed the universal applicability of DNA metabarcoding using soil samples from tropical environments: a large proportion of species and families from the study site was efficiently recovered. The results open unprecedented opportunities for large-scale DNA-based biodiversity studies across a range of taxonomic groups using standardized metabarcoding approaches.
Cscroll (from a girandole mirror)
Source: Objaverse 1.0 / Sketchfab
Alcove with mirror and tray
Source: Objaverse 1.0 / Sketchfab
[MIRROR] transcriptome assemblies for SOAPdenovo-Trans paper
<p>mirrored from ftp://public.genomics.org.cn/BGI/SOAPdenovo-Trans/SOAPdenovo-Trans_Supplementary_Assemblies.tar.gz to provide a faster CDN</p>
FIGURE 3. Cephalotes specularis n in Description of Cephalotes specularis n. sp. (Formicidae: Myrmicinae) — the mirror turtle ant
FIGURE 3. Cephalotes specularis n. sp. paratype major worker (soldier) in (a) face, (b) dorsal, and (c) profile view.
FIGURE 7 in Description of Cephalotes specularis n. sp. (Formicidae: Myrmicinae) — the mirror turtle ant
FIGURE 7. (a) Crematogaster ampla minor worker in defensive posture on a tree in the type locality of Cephalotes specularis n. sp. (b) Cephalotes. specularis n. sp. mirroring posture of its host C. ampla.
FIGURE 2. Cephalotes specularis n in Description of Cephalotes specularis n. sp. (Formicidae: Myrmicinae) — the mirror turtle ant
FIGURE 2. Cephalotes specularis n. sp. holotype minor worker in (a) face, (b) dorsal, and (c) profile view.
FIGURE 6. Cephalotes specularis n in Description of Cephalotes specularis n. sp. (Formicidae: Myrmicinae) — the mirror turtle ant
FIGURE 6. Cephalotes specularis n. sp. mature larva (a) head in full face, (b) detail of mouthparts and (c) total larva in profile view. Note the dorsal pairs of anchor-tipped hairs.
FIGURE 1 in Description of Cephalotes specularis n. sp. (Formicidae: Myrmicinae) — the mirror turtle ant
FIGURE 1. Minor workers of Cephalotes specularis n. sp. walking on a tree in the type-locality. Note the bright blue sky and clouds mirrored on the gaster. Picture taken by S. Powell.
Synthesis of arbitrary interference patterns using a single galvanometric mirror
<h3>Version 1</h3> <p>CAD model</p> <p>Speed accessment images (images of fluorescent beads using 100 X microscope) and postprocessing code in MATLAB</p> <p>Laser interference images and postprocessing code in MATLAB</p> <ul> <li>Two beam and hexagonal pattern images were repeated multiple times</li> <li>Three beam images were taken at different axial positions</li> </ul> <p>2D SIM data with 100 nm fluorescent beads (two examples, <em>2D 1ms 980Hz 400mW.tiff </em>and <em>2D 1ms 980Hz 400mW.tiff</em>, not TIRF) and reconstruction code in MATLAB (<em>SIM_reconstrcution_2D.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>The camera jittered during the measurements. The images were shifted to cancel the jitter using <a href="https://uk.mathworks.com/matlabcentral/fileexchange/18401-efficient-subpixel-image-registration-by-cross-correlation">Efficient subpixel image registration by cross-correlation - File Exchange - MATLAB Central</a>. For comparison, two images are reconstructed, with and without cancelling the jitter </li> <li>Each set of measurement contain multiple cycles of 11 frames, of which the 4th and 8th frames are discarded</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (<em>3D cell cropped.tiff), </em>widefield reference data (<em>WF cropped.tiff</em>) and reconstruction code in MATLAB (<em>SIM3D_cells.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Parameters are estimated from a subset of the image (which has higher SNR) using function <em>estimate_sim_parameters_3D_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim_3D_KG.m</em></li> <li>For reference, a widefield 3D image was captured by only illuminating the sample with one laser beam. The image is further processed using <em>WF3D_cells.m</em> and function <em>deconv_3D.m </em>to deconvolve the OTF</li> <li>The theorectial OTF is calculated using code from <a href="https://github.com/jdmanton/debye_diffraction_code">https://github.com/jdmanton/debye_diffraction_code</a> which is included in the package</li> </ul> <h3>Version 2</h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 3) and reconstruction code in MATLAB. I forgot to upload background noise image. Please use Version 3 to avoid error in running the code</p> <h3>Version 3 </h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 2) and reconstruction code including FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Raw data include two sets of measurements (<em>TIRF beads.tiff and TIRF beads 2.tiff</em>) and background noise image (<em>bg 1ms.tiff</em>)</li> <li>Each set of measurement (e.g. <em>TIRF beads.tiff</em>) contain two cycles of 11 frames, of which the 4th and 8th frames are discarded in each cycle</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (same as Version 1) and reconstruction code for FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Two subsets of the image were taken for FRC, one with even z steps and one with odd z steps</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>The two subsets are reconstructed independently (double z step size) and the centre z position of each image are used to calculate FRC</li> <li>Only subsets of the image are processed. Refer to Version 1 for larger range in z.</li> </ul> <p>Stability accessment images (two beam laser interference images taken over periods of time) and postprocessing code in MATLAB</p> <p>2D SIM (not TIRF) data with 200 nm fluorescent beads measured over the full FOV and reconstruction code in MATLAB</p> <ul> <li>Processed in almost the same way as 2D TIRF SIM</li> <li>Parameters were estimated using the centre of the FOV</li> <li>Sections with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul> <p>PSF data measured using 200 nm fluorescent beads and postprocessing code in MATLAB</p> <ul> <li>Individual bead images are picked and fit with theoretical PSF function to obtain resolution</li> <li>Beads with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul>
Mirror of "ENSPRESO - an open data, EU-28 wide, transparent and coherent database of wind, solar and biomass energy potentials"
<h2>Mirrored from Joint Research Centre Data Catalogue</h2><p><a href="https://data.jrc.ec.europa.eu/collection/id-00138#datasets">https://data.jrc.ec.europa.eu/collection/id-00138#datasets</a></p><blockquote><p>This collection contains datasets from ENSPRESO, an EU-28 wide, open dataset for energy models on renewable energy potentials, at national (NUTS0) and regional levels (NUTS2) for the 2010-2050 period. Within ENSPRESO, ENergy Systems Potential Renewable Energy SOurces, technical potentials are provided for wind, solar and biomass, based on coherent GIS-based land-restriction scenarios. For wind, resource evaluation also considers setback distances as well as high resolution geo-spatial wind speed data. For solar, potentials are derived from irradiation data and available area for solar applications. For biomass, agriculture, forestry and waste sectors are considered. The temporal resolution for wind and solar is both annual and year fractions (timeslices as used by JRC-EU-TIMES). ENSPRESO complements the EMHIRES collection, that provides meteorologically derived power time series at high temporal and spatial resolution. ENSPRESO can impact the results of any energy model by improving its analyses of the competition and complementarity of energy technologies.</p></blockquote><p><a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:RUIZ%20CASTELLO%20Pablo">RUIZ CASTELLO Pablo</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:NIJS%20Wouter">NIJS Wouter</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:TARVYDAS%20Dalius">TARVYDAS Dalius</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:SGOBBI%20Alessandra">SGOBBI Alessandra</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:ZUCKER%20Andreas">ZUCKER Andreas</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:PILLI%20Roberto">PILLI Roberto</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:CAMIA%20Andrea">CAMIA Andrea</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:THIEL%20Christian">THIEL Christian</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:HOYER-KLICK%20Carsten">HOYER-KLICK Carsten</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:DALLA%20LONGA%20Francesco">DALLA LONGA Francesco</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:KOBER%20Tom">KOBER Tom</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:BADGER%20Jake">BADGER Jake</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:VOLKER%20Patrick">VOLKER Patrick</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:ELBERSEN%20Berien">ELBERSEN Berien</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:BROSOWSKI%20Andre">BROSOWSKI Andre</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:THR%C3%84N%20Daniela">THRÄN Daniela</a>; <a href="https://publications.jrc.ec.europa.eu/repository/search/?filter=CONTRIBUTOR:JONSSON%20Klas">JONSSON Klas</a></p><h3>How to cite</h3><p>Ruiz Castello, P., Nijs, W., Tarvydas, D., Sgobbi, A., Zucker, A., Pilli, R., Camia, A., Thiel, C., Hoyer-Klick, C., Dalla Longa, F., Kober, T., Badger, J., Volker, P., Elbersen, B., Brosowski, A., Thrän, D. and Jonsson, K., ENSPRESO - an open data, EU-28 wide, transparent and coherent database of wind, solar and biomass energy potentials, European Commission, 2019, JRC116900.</p><p>European Commission</p><p>JRC116900</p><h3>Remarks</h3><p>The originator of this mirror requires stable and reliable URLs due to an integration of the dataset into an automated workflow. The data catalogue has frequent outages.</p>
11783 BM Nike Mirror
This is a 3D model of a bronze hand mirror in the British Museum, London, with a handle that resembles the goddess Nike. The mirror was made of polished bronze. The original handle was likely made of ivory. The presence of Nike possibly alludes to the triumph of feminine beauty. This object is dated to around 400 BCE. **Bibliography:** [British Museum](https://research.britishmuseum.org/research/collection_online/collection_object_details.aspx?objectId=461613&page=1&partId=1&searchText=Hand%20mirror%20with%20Nike) #Ancient World 3D This model posting is part of Ancient World 3D, a project that provides curated 3D open access content for Classical Studies. Each model has an etched catalog# and [3D Printable frame](https://skfb.ly/6RxV8) for building a library. The [original model was posted by Scan the World](http://mmf.io/o/17783). This entry was composed by Jennifer Hurley (Dr. Elizabeth Thill, advisor). Source: Objaverse 1.0 / Sketchfab
A hemoprotein with a zinc-mirror heme site ties heme availability to carbon metabolism in cyanobacteria- MD simulation files
<p>This folder contains the first and last frame of MD simulations conducted in this study. </p> <p>The Free-MD folder contains unconstrained MD simulation files for Dri1 (WT) and its variants (H16A, H21A, H79A, H16A:H21A, H16A:H79A, H21A:H79A and H79A:R90A)</p> <p>The SAXS-dirven MD folder contains SAXS data constrained MD simulation files for Dri1 WT, Dri1 H21A and Dri H79A:R90A with 3 different starting structures for variants. </p>
Figures for "The effect of parallel electron plateau on banded chorus generation: 1-D PIC simulations in mirror geometry"
<p>Figures for "The effect of parallel electron plateau on banded chorus generation: 1-D PIC simulations in mirror geometry"</p>
Detailed steps to simulate the mirror adjustments
<p>This is part of work for the preprint entitled "1887 Michelson-Morley experiment: a new analysis with computer assistance".</p> <p>In this dataset, the detailed simulation works for the mirror adjustments are presented in the Excel forms and the CAD drawings grouped under the same filenames. The sequential steps for the mentioned trials are described in Section "Pre-description" of the mentioned preprint.</p>
Scroll (from girandole mirror)
Original material: composition/compo Source: Objaverse 1.0 / Sketchfab
Fragment of the mirror NMK1B5
Fragment of the mirror NMK1B5. Russia, Republic of Bashkortostan, Kuyurgazinsky district. Excavations in 2004. Necropolis Novomusinsky. Kurgan # 1. Burial No. 5 (https://skfb.ly/6YnEP). Fragment of a bronze mirror. The handle has holes for attaching the handle. Chronology: Early Iron Age, IV-III centuries BC. Sarmatian culture. Russland, Republik Baschkortostan, Bezirk Kuyurgazinsky. Ausgrabungen im Jahr 2004. Nekropole Novomusinsky. Kurgan # 1. Beerdigung Nr. 5 (https://skfb.ly/6YnEP). Fragment eines Bronzespiegels. Der Griff hat Löcher zum Befestigen des Griffs. Chronologie: Frühe Eisenzeit, IV-III Jahrhunderte vor Christus. Sarmatische Kultur. Россия, Республика Башкортостан, Куюргазинский район. Раскопки 2004 года. Некрополь Новомусинский. Курган №1. Захоронение №5 (https://skfb.ly/6YnEP). Фрагмент бронзового зеркала. На ручке имеются отверстия для крепления рукояти. Хронология: ранний железный век, IV-III века до новой эры. Сарматская культура. Source: Objaverse 1.0 / Sketchfab
Mirror Datahub of https://portal.nersc.gov/project/m1982/HipMCL
<p>A mirror repo for https://portal.nersc.gov/project/m1982/HipMCL </p> <p>The original repo is pretty slow when accessing from the Euro.</p> <p>The matrix market files are compressed.</p> <p> </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.