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3,145 results for “Well Being”
Control of Electron State Coupling in Asymmetric Ge/GeSi Quantum Wells - DataSet
<p>Relevant dataset (FTIR data as TM/TE vs energy) for the publication "Control of electron state coupling in asymmetric Ge/GeSi quantum wells" published in Physical Review Applied (10.5281/zenodo.2319242)</p>
Carbon-isotope, geochemical, and biostratigraphic data from the Anchor 3 well, Green Canyon protraction area, Gulf of Mexico
<p>Dataset that accompanies "Carbon-isotope chemostratigraphy, geochemistry, and biostratigraphy of the Paleocene-Eocene Thermal Maximum, deep-water Wilcox Group, Gulf of Mexico (U.S.A.)"</p> <p>To be submitted to <em>Climate of the Past</em></p>
Data from: A well-studied parasitoid fly of field crickets uses multiple alternative hosts in its introduced range
<p>Organisms and their natural enemies can have dynamic coevolutionary trajectories, but anthropogenic effects like species introductions interrupt existing coevolutionary relationships. For parasites in particular, if they are introduced to a location without their hosts, they can only persist in the new environment if alternative hosts are 1) present, 2) detectable to parasites, and 3) capable of sustaining parasites. The circumstances surrounding the addition of alternative hosts to a parasite's repertoire are rarely observed. The parasitoid fly Ormia ochracea locates its field cricket hosts by orienting acoustically to their conspicuous mating songs. In Hawaii, O. ochracea is only known to parasitize one species, Teleogryllus oceanicus, but rapid evolution of T. oceanicus mating song over the past 20 years has led to several prevalent morphs of the cricket that produce no song or novel songs that the flies cannot detect. Yet flies persist in populations that lack ancestral singing T. oceanicus, prompting us to investigate the possibility of alternative hosts in Hawaii. We demonstrate first that three potential alternative hosts (Gryllodes sigillatus, Gryllus bimaculatus, and Modicogryllus pacificus) are present. Second, O. ochracea exhibits a positive phonotactic response to all three species' songs in the field and in the lab. And third, O. ochracea can successfully develop to pupae and emerge as adults in all three species. Our discovery of alternative hosts for O. ochracea in Hawaii infuses the system with intriguing complexity and offers extensive opportunities for future work.</p>
Source data for the publication "SiGe quantum wells with oscillating Ge concentrations for quantum dot qubits"
<p>This repository contains data reported in the figures of the publication "SiGe quantum wells with oscillating Ge concentrations for quantum dot qubits."</p>
Text-fig. 37. Scanning electron microscope (SEM) images of "Stamen with tricolpate pollen sp. 1"; Catefica locality, Portugal. a) Stamen fragment showing the elongate, tetrasporangiate anther but with the base and apex poorly preserved; b–d) Pollen grains from stamen fragment in equatorial view showing the long colpi and well-developed, heterobrochate reticulum with very distinct large and small lumina; e) Detail of pollen wall showing orbicules with irregular projections; f) Detail of pollen wall showing smooth muri supported by short, densely spaced columellae. Specimen, Catefica 50-S170419 (a–f). Scale bars = 600 Μm (a), 6 Μm (b–d), 1.5 Μm (e, f). in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 37. Scanning electron microscope (SEM) images of "Stamen with tricolpate pollen sp. 1"; Catefica locality, Portugal. a) Stamen fragment showing the elongate, tetrasporangiate anther but with the base and apex poorly preserved; b–d) Pollen grains from stamen fragment in equatorial view showing the long colpi and well-developed, heterobrochate reticulum with very distinct large and small lumina; e) Detail of pollen wall showing orbicules with irregular projections; f) Detail of pollen wall showing smooth muri supported by short, densely spaced columellae. Specimen, Catefica 50-S170419 (a–f). Scale bars = 600 Μm (a), 6 Μm (b–d), 1.5 Μm (e, f).
Text-fig. 13. Scanning electron microscope (SEM) images of "Staminate inflorescence fragment with Clavatipollenites-type pollen sp. 4"; Catefica locality, Portugal. a) Fragment of stamen whorl from staminate inflorescence showing several closely packed, almost sessile stamens that lack a well-developed filament; b, c) Distal and proximal views of pollen grains showing poorly defined aperture with verrucate aperture membrane; d) Detail of pollen wall showing the semitectate-reticulate tectum and long, scattered columellae supporting the narrow muri with finely verrucate supratectal ornamentation. Specimen, Catefica 49-S107782 (a–d). Scale bars = 600 Μm (a), 6 Μm (b, c), 1.5 Μm (d). in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 13. Scanning electron microscope (SEM) images of "Staminate inflorescence fragment with Clavatipollenites-type pollen sp. 4"; Catefica locality, Portugal. a) Fragment of stamen whorl from staminate inflorescence showing several closely packed, almost sessile stamens that lack a well-developed filament; b, c) Distal and proximal views of pollen grains showing poorly defined aperture with verrucate aperture membrane; d) Detail of pollen wall showing the semitectate-reticulate tectum and long, scattered columellae supporting the narrow muri with finely verrucate supratectal ornamentation. Specimen, Catefica 49-S107782 (a–d). Scale bars = 600 Μm (a), 6 Μm (b, c), 1.5 Μm (d).
Text-fig. 3. Synchrotron radiation X-ray tomographic microscopy (SRXTM) images of fruits of Canrightia foveolata sp. nov.; Catefica locality, Portugal. a) Volume rendering of fruit showing prominent rim around the middle of the fruit with reduced tepals (arrowheads) and partly abraded fruit wall exposing the pitted endotesta surface of one of two seeds (arrow); note two of the vascular bundles (vb) extending from the base of the fruit to the tepals; b) Voltex of fruit showing prominent rim around the fruit (arrowhead) and dense precipitation of crystals in the endothelium cells of one of the two seeds in the fruit; c) Longitudinal section of fruit (orthoslice yz0520) showing the inferred hypanthium rim (arrow head) and two seeds, one with a dense precipitation of crystals; note the prominent endothelium cells (asterisks) of the inner integument and the well-developed fruit wall above the seeds; d) Transverse section through basal part of fruit and seeds close to the micropyle (orthoslice xy0312) showing partly abraded fruit wall with five vascular bundles (vb) and details of the seed coat with endotesta (oi-end) surrounding the tegmen consisting of an outer epidermis (ii-o), middle layer (ii-m) and a distinct inner epidermis (endothelium) consisting of radially elongated cells (asterisk); e) Transverse section (orthoslice xy1680) through apical part of the fruit close to chalaza showing the tips of two seeds; note the endotesta (oi-end) surrounded by thick-walled cells of the exotesta (oi-o); f) Transverse section (orthoslice xy1485) through fruit in the region of the hypanthium rim showing sections through the two seeds close to the chalazal region; note endotesta (oi-end) surrounded by larger cells of exotesta (oi-o) and fruit wall (fr). Specimen, Catefica 49-S174249 (holotype, a–f). Scale bars = 300 Μm (a–c, e, f), 100 Μm (d). in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 3. Synchrotron radiation X-ray tomographic microscopy (SRXTM) images of fruits of Canrightia foveolata sp. nov.; Catefica locality, Portugal. a) Volume rendering of fruit showing prominent rim around the middle of the fruit with reduced tepals (arrowheads) and partly abraded fruit wall exposing the pitted endotesta surface of one of two seeds (arrow); note two of the vascular bundles (vb) extending from the base of the fruit to the tepals; b) Voltex of fruit showing prominent rim around the fruit (arrowhead) and dense precipitation of crystals in the endothelium cells of one of the two seeds in the fruit; c) Longitudinal section of fruit (orthoslice yz0520) showing the inferred hypanthium rim (arrow head) and two seeds, one with a dense precipitation of crystals; note the prominent endothelium cells (asterisks) of the inner integument and the well-developed fruit wall above the seeds; d) Transverse section through basal part of fruit and seeds close to the micropyle (orthoslice xy0312) showing partly abraded fruit wall with five vascular bundles (vb) and details of the seed coat with endotesta (oi-end) surrounding the tegmen consisting of an outer epidermis (ii-o), middle layer (ii-m) and a distinct inner epidermis (endothelium) consisting of radially elongated cells (asterisk); e) Transverse section (orthoslice xy1680) through apical part of the fruit close to chalaza showing the tips of two seeds; note the endotesta (oi-end) surrounded by thick-walled cells of the exotesta (oi-o); f) Transverse section (orthoslice xy1485) through fruit in the region of the hypanthium rim showing sections through the two seeds close to the chalazal region; note endotesta (oi-end) surrounded by larger cells of exotesta (oi-o) and fruit wall (fr). Specimen, Catefica 49-S174249 (holotype, a–f). Scale bars = 300 Μm (a–c, e, f), 100 Μm (d).
Data Set: Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation
<p>This is the Python code and plotted figure data used to create the figures for the submitted manuscript, "Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation" submitted to JGR: Solid Earth in 2022.</p> <p>The manuscript concerns a novel technique developed for EGS stimulation, called pore pressure or effective normal stress preconditioning, which preemptively alters the stress field along a fault prior to injection, such that the risk of induced seismicity is reduced. Using a slightly altered version of a preexisting model (a combination of an analytical pore pressure model and a linear slip weakening seismicity model) the effect of this kind of treatment is evaluated.</p>
Data package for Poromechanical analysis of oil well cements in CO2-rich environments
<p>Data package for the results obtained in Poromechanical analysis of oil well cements in CO2-rich environments.</p> <p>Juan Cruz Barría, Mohammadreza Bagheri, Diego Manzanal, Seyed M. Shariatipour, Jean-Michel Pereira,<br> Poromechanical analysis of oil well cements in CO2-rich environments,<br> International Journal of Greenhouse Gas Control, Volume 119, 2022, 103734, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103734.</p>
Psychological Well-being, Food Insecurity, Academic Performance, and Other Risk Factors in a Sample of College Students in Jordan during Covid-19
<p>This research investigated the occurrence of psychological well-being perception and its relationship with food insecurity, academic performance, and other correlates in a sample of university students in Amman, Jordan during Covid-19. A cross-sectional study was conducted in two phases. Phase-1 translated and validated an Arabic version of the Psychological General Wellbeing Index-Short version (PGWB-S) in 122 students from the University of Jordan. In Phase-2, 414 students completed demographic questionnaire, Arabic Versions of the PGWB-S, Ryff Psychological Wellbeing Scale, and Individual Food Insecurity Experience Scale.</p> <p>Ethical considerations: This manuscript has been read and approved by all authors. The authors confirm that there are no other persons, who satisfied the criteria for authorship, but are not listed. The order of authors listed in the manuscript has been approved by all of them. They also understand that the Corresponding Author is the sole contact for the Editorial process, and holds the responsibility for communicating with the other author about progress, submissions of revisions and final approval of proofs. Moreover, the authors declare that this manuscript is original, has not been published before, and is not currently being considered for publication elsewhere. Furthermore, all data used in the study is confidential and the lead author has full access to the data reported in the manuscript. We confirm that there are no known conflicts of interest associated with this publication, which did not receive any financial support. Finally, the reporting of this work is compliant with The Code of Ethics of the World Medical Association (Declaration of Helsinki). In addition to that, the protocol of this research is approved by the Institutional Review Board at the University of Jordan, Amman, Jordan (ref no.: 2021-89).</p>
How well must surface vorticity be organized for tornadogenesis?
<p>This study investigates whether quasi-random surface vertical vorticity is sufficient for tornadogenesis when combined with an updraft typical of tornadic supercells. The viability of this pathway could mean that a coherent process to produce well-organized surface vertical vorticity is rather unimportant. Highly idealized simulations are used to establish random noise as a possible seed for the production of tornado-like vortices (TLVs). A number of sensitivities are then examined across the simulations. The most explanatory predictor of whether a TLV will form (and how strong it will become) is the maximal value of initial surface circulation found near the updraft. Perhaps surprisingly, sufficient circulation for tornadogenesis is often present even when the surface vertical vorticity field lacks any obvious organized structure. The other key ingredient for TLV formation is confirmed to be a large vertical gradient in vertical velocity close to the ground (to promote stretching). Overall, it appears that random surface vertical vorticity is indeed sufficient for TLV formation given adequate stretching. However, it is shown that longer-wavelength noise is more likely to be associated with substantial surface circulation (because it is the areal integral of vertical vorticity). Thus, coherent vorticity sources that produce longer wavelength structures are likely to be the most supportive of tornadogenesis.</p>
Locating undocumented orphaned oil and gas wells with smartphones
<p>Majority of the estimated 3 million abandoned oil and gas wells in the U.S. have missing documents and lack surface equipment making them difficult to locate. However, most of them have casings made of iron alloys which are magnetic and can be sensed by magnetometers. Here we utilize an iPhone 12 mini smartphone as a magnetometer to locate two abandoned wells. We designed a simple unmanned aerial vehicle (UAV) survey setup where the iPhone 12 mini was hung from an inexpensive small drone. We surveyed the two sites by flying the drone at altitudes, 10 m, 15 m, and 20 m above ground level. Our results show that at altitude of 10 magl the smartphone magnetometer could pick the magnetic anomaly of either of the wells at intensities ≥ 52 μT; sufficient to accurately locate the wells. At altitude of 15 magl the smartphone could locate the wells within ~5 m radius of the actual wells’ location, and it was unable to detect any magnetic anomalies at 20 magl. Simplicity of the setup, minimal required scientific knowledge and low cost of the setup makes this setup an ideal tool for locating orphaned wells by citizen scientists.</p>
Data for: Ancient rapid radiation explains most conflicts among gene trees and well-supported phylogenomic trees of nostocalean cyanobacteria
<p>Prokaryotic genomes are often considered to be mosaics of genes that do not necessarily share the same evolutionary history due to widespread Horizontal Gene Transfers (HGTs). Consequently, representing evolutionary relationships of prokaryotes as bifurcating trees has long been controversial. However, studies reporting conflicts among gene trees derived from phylogenomic datasets have shown that these conflicts can be the result of artifacts or evolutionary processes other than HGT, such as incomplete lineage sorting, low phylogenetic signal, and systematic errors due to substitution model misspecification. Here, we present the results of an extensive exploration of phylogenetic conflicts in the cyanobacterial order Nostocales, for which previous studies have inferred strongly supported conflicting relationships when using different concatenated phylogenomic datasets. We found that most of these conflicts are concentrated in deep clusters of short internodes of the Nostocales phylogeny, where the great majority of individual genes have low resolving power. We then inferred phylogenetic networks to detect HGT events while also accounting for incomplete lineage sorting. Our results indicate that most conflicts among gene trees are likely due to incomplete lineage sorting linked to an ancient rapid radiation, rather than to HGTs. Moreover, the short internodes of this radiation fit the expectations of the anomaly zone, i.e., a region of the tree parameter space where a species tree is discordant with its most likely gene tree. We demonstrated that concatenation of different sets of loci can recover up to 17 distinct and well-supported relationships within the putative anomaly zone of Nostocales, corresponding to the observed conflicts among well-supported trees based on concatenated datasets from previous studies. Our findings highlight the important role of rapid radiations as a potential cause of strongly conflicting phylogenetic relationships when using phylogenomic datasets of bacteria. We propose that polytomies may be the most appropriate phylogenetic representation of these rapid radiations that are part of anomaly zones, especially when all possible genomic markers have been considered to infer these phylogenies.</p>
Files associated with Christopher Holder and Anand Gnanadesikan, How well do Earth System Models capture apparent relationships between phytoplankton biomass and environmental variables? [Version 1]
<p><strong>1. process_cmip_rf.m</strong> is a matlab script that reads a single file, generates a random forest using the parameters in the associated paper and computes permutation importance and sensitivities. Note- in order to get process_cmip_rf.m to work as written you must have the Statistics and Machine Learning toolbox installed on Matlab and download the table_modis.asc file below. </p> <p>Files 2-16 are tabular filew containing all datapoints used in Random Forest analysis for the NCAR CESM2 model. Columns are</p> <p> 1. Index of point, enabling a mapping back to the model grid if the resolution is known.</p> <p> 2. Longitude</p> <p> 3. Latitude</p> <p> 4. Month</p> <p> 5. Iron in mol/m<sup>3</sup>.</p> <p> 6. Mixed layer in m.</p> <p> 7. Ammonia in mol/m<sup>3</sup></p> <p> 8. Nitrate in mol/m<sup>3</sup>.</p> <p> 9. Phytoplankton carbon in mol/m<sup>3</sup>.</p> <p> 10. Phosphate in mol/m<sup>3</sup>.</p> <p> 11. Shortwave radiation (net solar radiation at ocean surface in W/m<sup>2</sup>).</p> <p> 12. Silicate in mol/m<sup>3</sup>.</p> <p> 13. Salinity in PSU</p> <p> 14. Temperature in C.</p> <p> 15. Upwelling velocity in m/s.</p> <p>If variable is not included in the dataset, the column will be filled with zeros.</p> <p><strong>2.table_cesm2.asc:</strong> Data created from Danabasoglu, G., 2019, NCAR CESM model output prepared for CMIP6 CMIP esm-pi-control <a href="http://doi.org/10.22033/ESGF/CMIP6.7579">http://doi.org/10.22033/ESGF/CMIP6.7579</a>. Grid is 360x180x12</p> <p><strong>3.table_cems2_fv2.asc:</strong> Data created from Danabasoglu, G., 2019, NCAR CESM-FV2 model output prepared for CMIP6 CMIP pi-control <a href="http://doi.org/10.22033/ESGF/CMIP6.11301">http://doi.org/10.22033/ESGF/CMIP6.11301</a>. Grid is 360x180x12</p> <p><strong>4. table_cesm2_waccm.asc: </strong>Data created from Danabasoglu, G., 2019, NCAR CESM2-WACCM model output prepared for CMIP6 CMIP piControl <a href="http://doi.org/10.22033/ESGF/CMIP6.10094">http://doi.org/10.22033/ESGF/CMIP6.10094</a>. Grid is 360x180x12</p> <p><strong>5. table_cesm2_waccm_fv2.asc</strong>: Data created from Danabasoglu, G., 2019, NCAR CESM-WACCM-FV2 model output prepared for CMIP CMIP piControl, <a href="http://doi.org/10.22033/ESGF/CMIP6.11302">http://doi.org/10.22033/ESGF/CMIP6.11302</a>. Grid is 360x180x12</p> <p><strong>6. table_gfdl_cm4.asc</strong>: Data created from Guo, Huan; John, Jasmin G; Blanton, Chris et al,2018, NOAA-GFDL GFDL-CM4 model output piControl, <a href="http://doi.org/10.22033/ESGF/CMIP6.8666">http://doi.org/10.22033/ESGF/CMIP6.8666</a>. Grid is 360x180x12</p> <p><strong>7.table_gfdl_esm4.asc</strong> Data created from Krasting, John P.; John, Jasmin G; Blanton, Chris et al., 2018, NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 CMIP piControl, <a href="http://doi.org/10.22033/ESGF/CMIP6.8669">http://doi.org/10.22033/ESGF/CMIP6.8669</a>. Grid 360x180x12</p> <p><strong>8. table_ipsl_cm5a2_inca.asc:</strong> Data created from Boucher, Olivier; Denvil, Sébastien; Levavasseur, Guillaume et al.: 2021, IPSL IPSL-CM5A2-INCA model output prepared for CMIP6 CMIP piControl <a href="http://doi.org/10.22033/ESGF/CMIP6.13683">http://doi.org/10.22033/ESGF/CMIP6.13683</a>. Grid is 182x149x12</p> <p><strong>9.</strong> <strong>table_ipsl_cm6a_lr.asc:</strong> Data created from Boucher, Olivier; Denvil, Sébastien; Levavasseur, Guillaume et al., 2018:, IPSL IPSL-CM6A-LR model output prepared for CMIP6 CMIP piControl, <a href="http://doi.org/10.22033/ESGF/CMIP6.5251">http://doi.org/10.22033/ESGF/CMIP6.5251</a>. Grid is 362x332x12.</p> <p><strong>10</strong>. <strong>table_mpi_esm1-2-ham.asc:</strong> Neubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe et al., 2019: HAMMOZ-Consortium MPI-ESM1.2-HAM model output prepared for CMIP6 CMIP piControl, <a href="http://doi.org/10.22033/ESGF/CMIP6.5037">http://doi.org/10.22033/ESGF/CMIP6.5037</a>. Grid is 256x220x12.</p> <p><strong>11</strong>. <strong>table_mpi_esm1-2-hr.asc:</strong> Data created from Jungclaus, Johann; Bittner, Matthias; Wieners, Karl-Hermann et al., 2019: MPI-M MPI-ESM1.2-HR model output prepared for CMIP6 CMIP piControl <a href="http://doi.org/10.22033/ESGF/CMIP6.6674">http://doi.org/10.22033/ESGF/CMIP6.6674</a>. Grid is 802x404x12.</p> <p><strong>12</strong>. <strong>table_mpi_esm1-2-lr.asc:</strong> Data created from Wieners, Karl-Hermann; Giorgetta, Marco; Jungclaus, Johann et al. 2019:MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP piControl</p> <p> <a href="http://doi.org/10.22033/ESGF/CMIP6.6675">http://doi.org/10.22033/ESGF/CMIP6.6675</a>. Grid is 256x220x12.</p> <p><strong>13. </strong><strong>table_noresm2-lm.asc: </strong>Seland, Øyvind; Bentsen, Mats; Oliviè, Dirk Jan Leo et al.,2019 NCC NorESM2-LM model output prepared for CMIP6 CMIP piControl, <a href="http://doi.org/10.22033/ESGF/CMIP6.8217">http://doi.org/10.22033/ESGF/CMIP6.8217</a>. Grid is 360x385x12</p> <p><strong>14.</strong><strong> table_noresm2-mm.asc</strong>: Data created from Bentsen, Mats; Oliviè, Dirk Jan Leo; Seland, Øyvind et al.,2019 <strong>:</strong> NCC NorESM2-MM model output prepared for CMIP6 CMIP piControl, <a href="http://doi.org/10.22033/ESGF/CMIP6.8221">http://doi.org/10.22033/ESGF/CMIP6.8221</a>. Grid is 360x385x12.</p> <p>15-16. <strong>table_kostadinov.asc, </strong><strong>table_modis.asc</strong> Data is a merger of observational products and model output Observational climatologies for temperature, salinity, mixed layer depth, silicate, phosphate, and nitrate were downloaded from the World Ocean Atlas (WOA) 2018 (Garcia et al., 2019; Locarnini et al., 2019; Zweng et al., 2019). MODIS-POC was downloaded from oceancolor.nasa.gov. Kostadinov POC is taken from <a href="https://doi.pangaea.de/10.1594/PANGAEA.859005">https://doi.org/10.1594/PANGAEA.859005</a> Grid is 360x180x12.</p>
Image dataset for cow identification, including code to train deep learning model, as well as analysis of results (SmARtview, 51088)
<p>This dataset and code was a result of the UKRI project "SmARtview: An AI-powered Augmented Reality Tool for Animal Health and Productivity", linked here: <a href="https://gtr.ukri.org/projects?ref=51088">https://gtr.ukri.org/projects?ref=51088</a></p> <p>These files are intended to be used for an accompanying publication in an academic journal.</p> <p>Anyone is free to use the contents for research and teaching purposes.</p>
Simulated Well Production Data using a Transient Well Model and a Developed Simulator
<p>This is a simulated dataset of transient well production data. This dataset was used in my Masters thesis at King Abullah University of Science and Technology (KAUST), and it is shared for academic use and research work.</p> <p>The dataset has 100 wells simulated at time steps of 0.2 hours for an entire year. This gives 43,800 observations per well, and grand total of 4,380,000 observations in the entire dataset. The resulting production data is then perturbed with systemic and random gauge errors to better simulate real-world gauge readings.</p> <p>The simulator code used to generate this dataset can be found at: <a href="https://github.com/ykh-1992/TransientNodalAnalysis.jl">https://github.com/ykh-1992/TransientNodalAnalysis.jl</a></p> <p>The data consists of three files:<br> - "wells.csv": This file details the input parameters for each simulated well.<br> - "data.zip": This file houses an 850 MB "data.csv" that includes the simulated well production data.<br> - "auxiliary.csv": This file includes information related to the simulation run.</p>
Fig. 11 in A well preserved pan-pleurodiran (Dortokidae) turtle from the English Lower Cretaceous and the first radiometric date for the Wessex Formation (Hauterivian-Barremian) of the Isle of Wight, United Kingdom
Fig. 11. Biogeographic distribution of dortokid turtles during the Early Cretaceous modified from Cadena and Joyce (2015), Perez-García et al. (2017) and Augustin et al. (2021).
Fig. 10 in A well preserved pan-pleurodiran (Dortokidae) turtle from the English Lower Cretaceous and the first radiometric date for the Wessex Formation (Hauterivian-Barremian) of the Isle of Wight, United Kingdom
Fig. 10. Appendicular elements of IWCMS 2018.44. A-F, Right humerus; G-L, proximal end of the left humerus; M-R, right femur; S-X, proximal end of the right fibula; Y-AD, distal end of the right tibia; in ventral (A,G,M,S,Y), posterior (B,H,N,T,Z), dorsal (C,I,O,U,AA), anterior (D,J,P,V,AB), medial (E,K,Q,W,AC), and distal (F,L,R,X,AD) views.
Fig. 8 in A well preserved pan-pleurodiran (Dortokidae) turtle from the English Lower Cretaceous and the first radiometric date for the Wessex Formation (Hauterivian-Barremian) of the Isle of Wight, United Kingdom
Fig. 8. Elements of the girdles of IWCMS 2018.44. A-F, right scapula; G-L, left scapula; M-R, proximal end of the right coracoid; S-X, left coracoid. These elements are shown in posterior (A,G,M,S), ventral (B,H,O,V), dorsal (C,I,P,T), anterior (D,J,N,U), proximal (E,K,Q,W), and distal (F,L,R,X) views.
Fig. 9 in A well preserved pan-pleurodiran (Dortokidae) turtle from the English Lower Cretaceous and the first radiometric date for the Wessex Formation (Hauterivian-Barremian) of the Isle of Wight, United Kingdom
Fig. 9. Visceral view of the left hypoplastron and xiphiplastron with the left pelvis (A), and virtually removing the pelvis (B) to show the pubic scar of IWCMS 2018.44. C-N, Left (C- H) and right (I-N) pelvis in posterior (C,I), anterior (D,J), dorsal (E,K), ventral (F,L), medial (G,M), and lateral (H,N) views. Abbreviations: hyp, hypoplastron; il, illium; is, ischium; ob, obturator foramen; ps, pubic scar; pu, pubis; xi, xiphiplastron.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.