cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35003/zubecs
title: Replication Data for: Are the Moon's Nearside‐Farside Asymmetries the Result of a Giant Impact ?

description: •Giant impact on the nearside of the Moon can reproduce the crustal thickness asymmetry between the nearside and farside •The nearside lowlands and KREEP materials on the lunar surface can be explained by the giant impact scenario •Giant impact predicts that the Moon has a significant 182W anomaly after the Moon formation, as expected by the collision formation of the Moon
DOI: 10.35003/zubecs/8st28h
title: jgre21146-sup-0001-2018je005826-si.docx

description: :unav
DOI: 10.35003/zubecs/b08xdy
title: 10.1029-2018JE005826Figure211460008.pptx

description: The ejecta and crustal thickness after postexcavation movement for the impact of a 780-km diameter impactor at 6.4 km/s. The impact site is at 0°. The gray section from 0 to 60° represents the size of the transient crater (see Figure 6). Within the transient crater, the ~25- to 30-km-thick crust (average) includes the deposited (orange points) and excavated crustal material that underwent postemplacement transport (green points within 40-60 degrees). The impactor and ejecta thickness distribution are binned into discrete rings of 2-arc degree width from the impact site up to an arc distance of 180°. The orange line represents the impact-derived crustal thickness composed of the displaced crust (blue dashed line) and ejecta (green points), starting from 40° from the impact site. The blue dashed line represents the displaced crust that is originally adjacent to the crater rim and then was dragged by the outward material flow during the impact cratering process.
DOI: 10.35003/zubecs/xchh42
title: 10.1029-2018JE005826Figure211460009.pptx

description: (a) map of modeled crustal thickness distribution from the giant impact event; (b) the crustal thickness from Gravity Recovery and Interior Laboratory (GRAIL) observations (Wieczorek et al., 2013); (c) the comparison of the average crustal-thickness profiles from the modeled crustal thickness (a) and that derived from GRAIL observations (b); (d) the comparison of the average crustal-thickness profiles for swath 1 to 4 derived from both the modeled crustal thickness (a) and the crustal thickness derived from GRAIL observation (b). For (a) and (b), data are presented in Mollweide equal-area projection centered at 90°W longitude, with nearside on the right of center and farside on the left of center. The solid and dashed arrows along each swath represent the fit and prediction direction as shown in Table 2. Points on the swaths represent the centers. In (a), the yellow star represents the impact center and the thin white line represents the Procellarum KREEP Terrane boundary on the nearside; the black dashed line represents the South Pole-Aitken (SPA) terrain; the white dashed line represents the size of transient crater (r~1,800 km); the red dashed lines represents the final crater (r~2,800 km); the solid and dashed arrows along each swath represent the fit and prediction direction, respectively. In (c), the gray section from 0 to 60° represents the size of the transient crater; the error bars represent the standard errors for the average crustal-thickens profile. In (d), the thick black and blue lines (from -90 to 180°) represent the mean profiles of swaths derived from the modeled crustal thickness (a) and observed crustal thickness from GRAIL (b), respectively; the green lines (from -50 to 95° or 105°) represent the mean profiles of swaths plotted on (a) and the solid green lines (from 0 to 95° or 105°) represent mean profiles for the fit region.
DOI: 10.35003/zubecs/ew6vfd
title: 10.1029-2018JE005826Figure211460002.pptx

description: The thermal profiles of the Moon used in this work. Thermal profile 1 (TP1) represents the cold temperature profile of the Moon; TP2 represents the warm temperature profile.
DOI: 10.35003/zubecs/rchrnb
title: 10.1029-2018JE005826Figure211460010.pptx

description: (a) The melt distribution of the giant impact event. Colored sections represent the molten material; gray sections represent unmolten material (melt fraction of 0). The contours represent the melt fraction with 0.1 and 0.25. Point a and b indicates the boundary of the molten and unmolten material of the new crust. The radial distance is ~900 km for point a and ~1,600 km for point b from the impact site. The material of the new crust from point a to b is not molten. The complete molten material (melt fraction ~1.0) is located around the boundary of the basin, less than 0.1% of the total of the melt volume. (b) The topographic map of the Moon (left-farside, right-nearside). The black line represents the outline of mare on the nearside. The red dashed and solid blue circle, with a radius of 900 and 1,600 km, represents the boundaries of the molten and unmolten material of the new crust in A (point a and b), respectively; the black dashed line represents the boundary of final basin from the modeling. The star on the nearside represents the impact site.
DOI: 10.35003/zubecs/hwjuld
title: 10.1029-2018JE005826Figure211460011.pptx

description: The postimpact KREEP material distribution. For our model, the global KREEP material was initially resided at the bottom of crust with a thickness of 20 km. The giant impact excavated the crustal, KREEP, and mantle material. The ejected KREEP material, deposited close to the basin rim, slumped back into the basin and was emplaced below crust. Point a and b represent the boundaries of transient crater (~1,800 km) and final crater (~2,700 km) from the impact site. See Figure 6 for the boundaries of transient crater and final crater on the global crustal thickness map.
DOI: 10.35003/zubecs/wlthbb
title: 10.1029-2018JE005826Figure211460001.pptx

description: The (a) topographic, (b) crustal thickness, and thorium distribution of the Moon show a dichotomy between the nearside and farside. Data are presented in Mollweide equal-area projection centered at 90°W longitude, with nearside on the right of center and farside on the left of center. The star on the nearside represents the center of the proposed Procellarum basin (Wilhelms, 1987); the red dashed line and white solid line represent the boundary of transient crater with a radius of 850 km and final basin with a radius of 1,600 km of the proposed Procellarum basin, respectively (Wilhelms, 1987). The thin black line on the nearside of the Moon represents the Procellarum KREEP Terrane boundary. The black dashed lines represent the boundary of Imbrium (Im), Orientale (Or), and Apollo (Ap) basin, respectively. The topographic and crustal thickness distributiona are derived from the Lunar Orbiter Laser Altimeter (Smith et al., 2010) and Gravity Recovery and Interior Laboratory (GRAIL) observations (Wieczorek et al., 2013), respectively; the thorium distribution is from the observations of Lunar Prospector gamma ray spectrometer (Prettyman et al., 2006).
DOI: 10.35003/zubecs/ntx6dx
title: 10.1029-2018JE005826Figure211460006.pptx

description: (a) The ejected material provenance for the giant impact event (780-km diameter impactor with velocity of 6.4 km/s). The crustal thickness was assumed to be 40 km. The excavation cavity is the orange zone. The radius of the excavation cavity is the radial distance along the surface from the impact site to the boundary of excavation cavity. The dashed circle represents the size of impactor. (b) The boundary of transient (solid line) and final crater (black dashed line) for the giant impact event from this work; the transient crater with a radius of 850 km for the proposed Procellarum basin is also plotted as the red dashed circle for the comparison (Wilhelms, 1987). Data are presented in Mollweide equal-area projection centered at 90°W longitude, with nearside on the right of center and farside on the left of center. The background is the topographic distribution observed by Lunar Orbiter Laser Altimeter (Smith et al., 2010). The star on the nearside represents the assumed impact site.
DOI: 10.35003/zubecs/cbdha6
title: 10.1029-2018JE005826Figure211460005.pptx

description: The basin-forming process for an impactor 780 km in diameter (200-km diameter of iron core) with an impact velocity of 6.4 km/s using the warmer profile Thermal profile 2 (TP2). The Moon was assumed to be a 3,500-km-diameter sphere with 700-km-diameter of iron core. The crustal thickness is assumed to be 40 km. In each panel, the left halves represent the materials used in the model: the gabbroic anorthosite (pale green), dunite (blue), and iron (orange) represent the lunar crust, mantle, and core, respectively. The gabbroic anorthosite (pale yellow) also represents the impactor material. The right halves represent the temperature variation during the impact process. The arrows in (c) and (d) represent the local crustal materials that were displaced and form the new crust together with deposited ejecta.
DOI: 10.35003/zubecs/bak5jj
title: 10.1029-2018JE005826Figure211460003.pptx

description: (a) The launch position (p0), velocity (v), and angle (θ) estimation for the ejecta. The launch time (t0), landing time (tl), flight distance (tf), and landing position of the ejecta are also calculated. Note that pf defines the flight distance along the lunar surface. (b) The elliptical trajectory for each ejecta for the best fit model in this work.
DOI: 10.35003/zubecs/kduo4t
title: 10.1029-2018JE005826Figure211460007.pptx

description: The ejecta thickness distribution before and after the consideration of ejecta sliding. The gray area represents the extent of the transient cavity. Within the basin (0-90 arc distance), we exclude the mantle material in the postsliding ejecta.
DOI: 10.35003/zubecs/4gktuq
title: 10.1029-2018JE005826Figure211460012.pptx

description: The predicted μ182W of the Moon prior to impact and effects for different impactor compositions and different differentiation timescales after solar system formation. The grey horizontal bar represents the μ182W = 24 ± 5 ppm for the Moon (Kruijer et al., 2015; Touboul et al., 2015). Calculations assume a mass of the impactor 7.6 × 1020 kg and that the impactor mixed with a mass of 3 × 1021 kg of lunar mantle material (within the volume of ~25% melt fraction; see Figure 10a). Assumed mantle W concentration were 19 ppb (Moon) and 5 (reduced, red lines) and 55 (oxidized, blue lines) ppb in the impactor mantle (see the details in the main text).
DOI: 10.35003/zubecs/tkztb8
title: 10.1029-2018JE005826Figure211460004.pptx

description: The carton shows the methods used for the ejecta sliding calculation and the structure of the new crust. The red blocks represent the local crust material over the surface of the Moon. The dark blocks represent the ejecta. The arrows show the directions of movements or the displacements of these blocks. When the ejecta lands on the local material, it follows the movement of the local material. The ejecta, as a new layer covering on the displaced crustal material, and the displaced crust form the postimpact crust.
DOI: 10.35003/zubecs/5k7akm
title: Tables.tab

description: Table 1: Material Parameters for iSALE-2-D Numerical Model Used in This Work Table 2: Swath Dimensions From Garrick-Bethell et al (2010)
DOI: 10.6084/m9.figshare.13567412.v1
title: Supplementary data and research materials for "Geo-political conflicts, sanctions, and international knowledge flows: EU-Russia collaboration during the Ukraine crisis"

description: ZIP-File with study data and STATA replication codes for: <br> "Geo-political conflicts, sanctions, and international knowledge flows: EU-Russia collaboration during the Ukraine crisis" <br> by Teemu Makkonen and Timo Mitze (2023). <br> Contact: tmitze@sam.sdu.dk
DOI: 10.35003/oit7zo
title: Replication Data for: Layering by double-diffusive convection in the subsurface oceans of mid-sized icy satellites

description: Datatype: Source code. Source code for double diffusive convection with finite Prandtl number and the input file.
DOI: 10.35003/oit7zo/6apiqs
title: README

description: :unav
DOI: 10.35003/oit7zo/7wcizh
title: fixedCBC_coldIC.f

description: :unav
DOI: 10.35003/oit7zo/xheihy
title: fixedCBC_warmIC.f

description: :unav
DOI: 10.35003/oit7zo/ctgshp
title: nofluxCBC_warmIC.f

description: :unav
DOI: 10.35003/oit7zo/zxuh9f
title: infile

description: :unav
DOI: 10.35003/oit7zo/ikhu6f
title: README

description: :unav
DOI: 10.35003/oit7zo/tkufpe
title: nofluxCBC_coldIC.f

description: :unav
DOI: 10.5522/04/22336657
title: TB Social Enterprise Financial Sustainability Model

description: This dataset provides the financial modleing analysis for a TB social-enterprise model in Pakistan. This data was generated by collating statistics from the project partners financial book keeping software. Summary statistics were complied using MS Excel and provided from the finance team. <br> The dataset includes detailed financial projections to evaluate the financial feasbility of the intervention.
DOI: 10.5522/04/22336657.v1
title: TB Social Enterprise Financial Sustainability Model

description: This dataset provides the financial modleing analysis for a TB social-enterprise model in Pakistan. This data was generated by collating statistics from the project partners financial book keeping software. Summary statistics were complied using MS Excel and provided from the finance team. <br> The dataset includes detailed financial projections to evaluate the financial feasbility of the intervention.
DOI: 10.35003/idup4r
title: The Earth-Moon late-accretion conundrum

description: Nature Geoscience, News & Views, Published: 19 August 2019 // The Earth–Moon late-accretion conundrum: The distribution of iron-loving elements between the mantles of the Moon and Earth may differ from established belief, suggest two studies that determine the hafnium–tungsten ratio and sulfide–silicate melt partitioning of elements in the lunar mantle.// Nature Geoscience volume 12, pages 683–684(2019) (2019).
DOI: 10.35003/idup4r/enxx81
title: Philipp Glei ner_The Earth-Moon late-accretion conundrum_Nature Geoscience 2019.pdf

description: :unav
DOI: 10.6084/m9.figshare.22633234
title: Tree biodiversity of warm drylands is likely to decline in a drier world

description: <strong>Abstract.</strong> Warm drylands represent 19% of land surfaces worldwide and host ca. 1,100 tree species. The risk of decline due to climate aridification of this neglected biodiversity has been overlooked despite its ecological and societal importance. To fill this gap, we assessed the risk of decline due to climate aridification of tree species in warm drylands based on spatialized occurrence data and climate models. We considered both species vulnerability and exposure, compared the risk of tree species decline across five bioregions and searched for phylogenetic correlates. Depending on the future climate model, from 44% to 88% of warm drylands’ tree species will undergo climate aridification with a high risk of decline even under the most optimistic conditions. On a regional scale, the rate of species that will undergo climate aridification in the future varies from 21% in the Old World North, to 90% in Australia, with a risk of decline confirming the high level of risk predicted at the global scale. Using generalized linear mixed models, we found that, species more exposed to climate aridification will be more at risk, but also that species vulnerability is a key driver of their risk of decline. Indeed, the warm drylands specialist species will be less at risk due to climate aridification than species being marginal in warm drylands. We also found that the risk of decline is widespread across the main clades of the phylogeny and involves several evolutionary distinct species. Estimating a high risk of decline for numerous tree species in all warm drylands, including emblematic dryland endemics, our work warns that future increase in aridity could result in an extensive erosion of tree biodiversity in these ecosystems. <br> <strong>Table S3.</strong> The seven risk of decline, vulnerability and exposure metrics (RDA, ANO, ANB, Range size, Exp1, Exp2 and Exp3) for tree species submitted to climate aridification in warm drylands (Exp1 &gt; 0) for each GCM and RCP, and distribution (bioregions,) and evolutionary distinctness for each of the whole 1,016 species list. [tableS3.xlsx]
DOI: 10.5522/04/22336660
title: Summary Data for TB Social Enterprise Model Analysis

description: This dataset provides summary statistics for case-detection and revenue generated from a TB social-enterprise model in Pakistan. This data was generated by collating statistics from the project partners HMIS that is available online. Summary statistics were complied using MS Excel.
DOI: 10.5522/04/22336660.v1
title: Summary Data for TB Social Enterprise Model Analysis

description: This dataset provides summary statistics for case-detection and revenue generated from a TB social-enterprise model in Pakistan. This data was generated by collating statistics from the project partners HMIS that is available online. Summary statistics were complied using MS Excel.
DOI: 10.5281/zenodo.7827866
title: Genetic Characterization of the Norwegian Apple Collection

description: Commercial fruit production in Norway is located at around latitude 60° north, demanding careful choice of adapted cultivars. The most comprehensive collection of apple genetic resources in Norway is being kept in the Norwegian Apple Collection (NAC) at Njøs Fruit and Berry Centre (NJØS). The collection contains around 350 accessions and was recently genotyped with a single nucleotide polymorphism (SNP) array. Curated SNP data were used for structure assessment, diversity analysis, pedigree confirmation, and core collection development. In the subsequent SNP analysis, we identified several duplicates and parent–offspring relationships. The collection was equally diverse across the geographic regions represented. Different methods for analyzing population structure were applied. K-means clustering and a Bayesian modeling approach with prior assumptions of the data revealed five subpopulations associated with geographic breeding centers. The collection has a distinct genetic structure and low relatedness among the accessions; hence, two 100 accession core collections were created. These new core collections will allow breeders and researchers to use the NAC efficiently. The results from this study suggest that several of the accessions in the Norwegian Apple Collection could be of high importance for breeding programs.
DOI: 10.5281/zenodo.7827865
title: Genetic Characterization of the Norwegian Apple Collection

description: Commercial fruit production in Norway is located at around latitude 60° north, demanding careful choice of adapted cultivars. The most comprehensive collection of apple genetic resources in Norway is being kept in the Norwegian Apple Collection (NAC) at Njøs Fruit and Berry Centre (NJØS). The collection contains around 350 accessions and was recently genotyped with a single nucleotide polymorphism (SNP) array. Curated SNP data were used for structure assessment, diversity analysis, pedigree confirmation, and core collection development. In the subsequent SNP analysis, we identified several duplicates and parent–offspring relationships. The collection was equally diverse across the geographic regions represented. Different methods for analyzing population structure were applied. K-means clustering and a Bayesian modeling approach with prior assumptions of the data revealed five subpopulations associated with geographic breeding centers. The collection has a distinct genetic structure and low relatedness among the accessions; hence, two 100 accession core collections were created. These new core collections will allow breeders and researchers to use the NAC efficiently. The results from this study suggest that several of the accessions in the Norwegian Apple Collection could be of high importance for breeding programs.
DOI: 10.35003/qvol83
title: Replication Data for: Parameterising a Model of Clinopyroxene/Melt Partition Coefficients for Sodium to Higher Upper Mantle Pressure

description: This dataset encompasses two codes to replicate data published in Schmidt and Noack (2021): The code D_Na.m calculates clinopyroxene/melt partition coefficients for sodium thermodynamically. The code Param_variousF.ipynb uses a least square approximation to fit the calculated partition coefficients over various melt fractions to a scaling law.
DOI: 10.35003/qvol83/ffyigi
title: Param_variousF.ipynb

description: Param_variousF.ipynb uses a least square approximation to fit the calculated partition coefficients over various melt fractions to a scaling law.
DOI: 10.35003/qvol83/abhvz8
title: D_Na.m

description: Calculation of clinopyroxene/melt partition coefficients for sodium thermodynamically.
DOI: 10.35003/qvol83/2axtda
title: D_K.m

description: Calculation of clinopyroxene/melt partition coefficients for potassium with both the help of the thermodynamic model and the fitted scaling law.
DOI: 10.6084/m9.figshare.22633402
title: Base de datos ATLAS.ti - codificación de citas

description: Base de datos exportada del software ATLAS.ti que resultó de la codificación de las respuestas de podcasters independientes de Puerto Rico
DOI: 10.6084/m9.figshare.22633402.v1
title: Base de datos ATLAS.ti - codificación de citas

description: Base de datos exportada del software ATLAS.ti que resultó de la codificación de las respuestas de podcasters independientes de Puerto Rico
DOI: 10.35003/giazcq
title: Replication Data for: Clinopyroxene/Melt Partitioning: Models for Higher Upper Mantle Pressures Applied to Sodium and Potassium

description: This dataset encompasses five codes to replicate data published in Schmidt and Noack 2021 (accepted): The code D_Na.m calculates clinopyroxene/melt partition coefficients for sodium thermodynamically. The code Param_variousF.ipynb uses a least square approximation to fit the calculated partition coefficients over various melt fractions to a scaling law. The same least square approximation method is used in Parameterization_drySolidus.ipynb and Parameterization_Liquidus.ipynb, but applied to dry solidus and liquidus conditions (+,-50 K) respectively. The code D_K.m calculates clinopyroxene/melt partition coefficients for potassium with both the help of the thermodynamic model and the fitted scaling laws.
DOI: 10.35003/giazcq/ovduzr
title: Param_variousF.ipynb

description: Param_variousF.ipynb uses a least square approximation to fit the calculated partition coefficients over various melt fractions to a scaling law.
DOI: 10.35003/giazcq/x4dw6r
title: D_K.m

description: Calculation of clinopyroxene/melt partition coefficients for potassium with both the help of the thermodynamic model and the fitted scaling law.
DOI: 10.35003/giazcq/32m0gf
title: D_Na.m

description: Thermodynamic model for calculating sodium partition coefficients for clinopyroxene/melt.
DOI: 10.35003/giazcq/yjviie
title: Parameterization_drySolidus.ipynb

description: Parameterization_drySolidus.ipynb uses a least square approximation to fit the calculated partition coefficients over dry solidus P-T conditions (+,- 50 K) to a scaling law.
DOI: 10.35003/giazcq/jjjzzu
title: Parameterization_Liquidus.ipynb

description: :unav
DOI: 10.5281/zenodo.7827923
title: Comparison between the results from JGA analysis mitochondrial short variant discovery workflow and those from the compatible Terra workflow

description: Files starting from <code>NA12878.chrM</code> are the results from JGA analysis mitochondrial short variant discovery workflow. Files starting from <code>submissions_</code> are the results from the compatible Terra workflow. VCFs are identical between two workflows except for the header lines.
DOI: 10.5281/zenodo.7827922
title: Comparison between the results from JGA analysis mitochondrial short variant discovery workflow and those from the compatible Terra workflow

description: Files starting from <code>NA12878.chrM</code> are the results from JGA analysis mitochondrial short variant discovery workflow. Files starting from <code>submissions_</code> are the results from the compatible Terra workflow. VCFs are identical between two workflows except for the header lines.