cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35003/se84pg
title: Replication Data for: Regolith mixing by impacts: Lateral diffusion of basin melt.

description: • Cumulative impact gardening on presence of melt laterally and with depth is modeled by means of a Monte Carlo approach. • The quantitative abundance of the melt from three mid- to late-forming basin is estimated. • Burying and transportation play more important roles than re-melting process in melt diffusion. • The simulated abundance of basin melt is consistent with the radiometric ages from Apollo and Luna highland samples.
DOI: 10.35003/se84pg/rjz1it
title: figure 6.pdf

description: :unav
DOI: 10.35003/se84pg/pavua5
title: figure 3.png

description: :unav
DOI: 10.35003/se84pg/uye9vl
title: figure 5.png

description: :unav
DOI: 10.35003/se84pg/yeeplc
title: figure 8.pdf

description: :unav
DOI: 10.35003/se84pg/zanlia
title: figure 2.png

description: :unav
DOI: 10.35003/se84pg/wafhsb
title: figure 7.png

description: :unav
DOI: 10.35003/se84pg/84hiq8
title: figure 4.PNG

description: :unav
DOI: 10.35003/se84pg/rj5yh5
title: figure 10.pdf

description: :unav
DOI: 10.35003/se84pg/me9ouw
title: figure 1.PNG

description: :unav
DOI: 10.35003/se84pg/jjdlpy
title: figure 9.pdf

description: :unav
DOI: 10.35003/se84pg/h5rlxz
title: Table 1.docx

description: :unav
DOI: 10.35003/8l4tzc
title: Replication Data for: Ancient Bombardment of the Inner Solar System: Reinvestigation of the 'Fingerprints' of Different Impactor Populations on the Lunar Surface

description: Craterstats (.scc, .plt and .txt) files, GIS-ready .shp files based on Head et al. (2010) and Fassett et al. (2012)" Note: We reloaded all the CSFD measurements (GIS-ready files) into new shapefiles and recalculated the area and crater sizes in an updated CraterTools extension.
DOI: 10.35003/8l4tzc/pqx8ib
title: Orgel_etal_2017_Lunar_basins.zip

description: Craterstats (.scc, .plt and .txt) files, GIS-ready .shp files based on Head et al. (2010) and Fassett et al. (2012)" Note: We reloaded all the CSFD measurements (GIS-ready files) into new shapefiles and recalculated the area and crater sizes in an updated CraterTools extension.
DOI: 10.5281/zenodo.7822116
title: Dataset for: "Last century changes in annual precipitation in a Mediterranean area and their spatial variability. Insights from northern Tuscany (Italy)"

description: The version 1.0 contains the supporting data for the work (still under submission) "Last century changes in annual precipitation in a Mediterranean area and their spatial variability. Insights from northern Tuscany (Italy)". The following files are here available (all file are georeferenced in EPSG: 3003): - AVG_Rainfall_1990-2019.tif -&gt; Raster map of the mean annual precipitation for the northern Tuscany, Italy. It encompasses the portion of the Tuscany region northern of the cities of Livorno - Florence. The interpolation was validated via a leave one out cross-validation procedure. - D3-1_Area2_ApuanAlps.tif -&gt; Raster map of the differences in mean annual precipitation between the two 3-decades periods 1921 to 1950 and 1990 to 2019 for the Apuan Alps mountain ridge (Tuscany, Italy). - D3-2_Area2_ApuanAlps.tif -&gt; Raster map of the differences in mean annual precipitation between the two 3-decades periods 1951 to 1980 and 1990 to 2019 for the Apuan Alps mountain ridge (Tuscany, Italy). - DeltaSHP_Points_AVG_Annual_Rainfall.zip -&gt; Shape file of the raingauges locations with the mean annual precipitation values of the period 1990 to 2019. - RaingaugesSHP_Points_AVG_Annual_Rainfall_1990-2019.zip -&gt; Shape file of the raingauges locations with the following information: differences in the mean annual precipitation values between the two 3-decades periods 1951 to 1980 and 1990 to 2019 (named D3-2); p values of the t-test for significance of the differences between the mean annual precipitation ofthe two 3-decades periods 1951 to 1980 and 1990 to 2019; difference in the mean annual precipitation values between the two 3-decades periods 1921 to 1950 and 1990 to 2019 (named D3-1); p values of the t-test for significance of the differences between the mean annual precipitation ofthe two 3-decades periods 1921 to 1950 and 1990 to 2019.
DOI: 10.5281/zenodo.7822115
title: Dataset for: "Last century changes in annual precipitation in a Mediterranean area and their spatial variability. Insights from northern Tuscany (Italy)"

description: The version 1.0 contains the supporting data for the work (still under submission) "Last century changes in annual precipitation in a Mediterranean area and their spatial variability. Insights from northern Tuscany (Italy)". The following files are here available (all file are georeferenced in EPSG: 3003): - AVG_Rainfall_1990-2019.tif -&gt; Raster map of the mean annual precipitation for the northern Tuscany, Italy. It encompasses the portion of the Tuscany region northern of the cities of Livorno - Florence. The interpolation was validated via a leave one out cross-validation procedure. - D3-1_Area2_ApuanAlps.tif -&gt; Raster map of the differences in mean annual precipitation between the two 3-decades periods 1921 to 1950 and 1990 to 2019 for the Apuan Alps mountain ridge (Tuscany, Italy). - D3-2_Area2_ApuanAlps.tif -&gt; Raster map of the differences in mean annual precipitation between the two 3-decades periods 1951 to 1980 and 1990 to 2019 for the Apuan Alps mountain ridge (Tuscany, Italy). - DeltaSHP_Points_AVG_Annual_Rainfall.zip -&gt; Shape file of the raingauges locations with the mean annual precipitation values of the period 1990 to 2019. - RaingaugesSHP_Points_AVG_Annual_Rainfall_1990-2019.zip -&gt; Shape file of the raingauges locations with the following information: differences in the mean annual precipitation values between the two 3-decades periods 1951 to 1980 and 1990 to 2019 (named D3-2); p values of the t-test for significance of the differences between the mean annual precipitation ofthe two 3-decades periods 1951 to 1980 and 1990 to 2019; difference in the mean annual precipitation values between the two 3-decades periods 1921 to 1950 and 1990 to 2019 (named D3-1); p values of the t-test for significance of the differences between the mean annual precipitation ofthe two 3-decades periods 1921 to 1950 and 1990 to 2019.
DOI: 10.35003/f0itdi
title: Replication Data for: Lack of late-accreted material as the origin of 182W excesses in the Archean mantle: Evidence from the Pilbara Craton, Western Australia

description: • 182W and HSE indicate partial lack late-accreted material in Pilbara source. • Only of normal amount of late-accreted material present at 3.3 Ga. • Similar 182W characteristics of other mantle sources indicates common process. • 182W–HSE mismatch for other sources caused by dissimilar behaviors of HSE vs. W. • Moon and pre-late accretion BSE had similar 182W.
DOI: 10.35003/f0itdi/6omfgy
title: Table S5.tab

description: Parameters used for Monte Carlo simulation
DOI: 10.35003/f0itdi/u5dezi
title: Table S2.tab

description: Solution and rock standard data for 1 µg of JNdi and BCR-2. Errors are 2SE absolute internal precisions for individual analyses, or 2SD external precisions of the mean
DOI: 10.35003/f0itdi/nzhoft
title: Table S3.tab

description: Measured total analytical blanks for highly siderophile elements in nanograms
DOI: 10.35003/f0itdi/suiwk3
title: Table S1.tab

description: Yields following separation and purification of W
DOI: 10.35003/f0itdi/0bzrfh
title: Table S4.tab

description: Neodymium isotopic compositions of Pilbara volcanics
DOI: 10.35003/f0itdi/cjschz
title: Table 2.tab

description: Highly siderophile element abundances (in ng/g), Re-Os systematics and MgO contents for Pilbara volcanics
DOI: 10.35003/f0itdi/izrlsl
title: Table 1.tab

description: Tungsten isotopic compositions of Pilbara volcanics
DOI: 10.6084/m9.figshare.22220179.v1
title: Supplementary Material for: Identification of a splicing variant c.3813-3A&gt;G in NPHP3 by reanalysis of whole exome sequencing in a Chinese boy with nephronophthisis

description: Nephronophthisis is an autosomal recessive cystic kidney disease characterized by tubular injury and commonly results in kidney failure. We reported a case of 4-year-old Chinese boy presented with severe anemia, kidney and liver dysfunction. Whole exome sequencing (WES) was performed to identify the candidate variant with a negative result initially. After complete collection of clinical information, reanalysis of WES identified a homozygous NPHP3 variant c.3813-3A&gt;G (NM_153240.4). The effect on mRNA splicing of the intronic variant was predicted through software (three in silico splice tools). Furthermore, in vitro minigene assay was conducted to validate the predicted deleterious effects of the intronic variant. All of the splice prediction programs and minigene assay indicated that the variant had an impact on the normal splicing pattern of NPHP3. Our study confirmed the effect of the c.3813-3A&gt;G variant on NPHP3 splicing in vitro, which gives additional evidence for the clinical significance of the variant and provides a basis for genetic diagnosis of nephronophthisis 3. In addition, we think that it is essential to reanalyze WES data after the complete clinical information collection to avoid missing some important candidate variants.
DOI: 10.5285/f42021d7-f049-1b03-e053-6c86abc025be
title: Processed multibeam bathymetry grids from the Whittard Canyon (JC125, 2015).

description: Multibeam swath bathymetry data were collected with a hull-mounted Kongsberg EM120 and EM710 echosounder during RRS James Cook cruise JC125 (Chief Scientist Veerle Huvenne) August-September 2015. The cruise was conducted to map Whittard Canyon, a deep ocean canyon in the Bay of Biscay, in order to obtain a better insight in the biodiversity patterns, benthic habitat distributions and sediment transport processes of submarine canyons. The data were edited using Caris HIPS software by Catherine Wardell and gridded at 50m spacing (EM120) and 10m (EM710) in a WGS84 UTM Zone 29N projection. The vertical datum of the data is matched to mean sea level (MSL). They were exported as longitude-latitude-depth triples. Funding was provided by the European Research Council to CodeMap (Grant No 258482) and the UK's Natural Environment Research Council (NERC) to MAREMAP.
DOI: 10.3886/e188481
title: Revised reproduction package for Lowes and Montero (2021): The Legacy of Colonial Medicine in Central Africa

description: This is an attempt at a revised reproduction package for "The Legacy of Colonial Medicine in Central Africa' by Lowes and Montero (2021).
DOI: 10.3886/e188481v2
title: Revised reproduction package for Lowes and Montero (2021): The Legacy of Colonial Medicine in Central Africa

description: This is an attempt at a revised reproduction package for "The Legacy of Colonial Medicine in Central Africa' by Lowes and Montero (2021).
DOI: 10.35003/vkdspf
title: Replication Data for: Lunar megaregolith mixing by impacts: Evaluation of the non-mare component of mare soils

description: The source of the non-mare component in the lunar mare soil samples is still an open question. A spatially resolved numerical model tracing the diffusion of non-mare material was developed by means of the Monte Carlo method to study this issue in more detail. The vertically- and laterally-transported non-mare components are recorded separately to assess their concentration on the surface. We find a general higher efficiency of lateral transport than of vertical transport, but the opposite may occur within small zones of interest. The overall (background) distribution of non-mare component is estimated by averaging out regional variations of material composition caused by local impact mixing. We find that almost all the mare surface is mixed with non-mare material. If most of the mare regions have filled basaltic material about 500 m in thickness since the formation of basins, the average non-mare fraction in the top 5 m is about 0.1. The abundance of the non-mare component decreases with increasing distance from the mare-highland boundary, but the slope of the distance-dependence is shallower within ~100 km of the boundary than further away.
DOI: 10.35003/vkdspf/9ysnxu
title: fig4d_A17.txt

description: :unav
DOI: 10.35003/vkdspf/9ijyb4
title: vertical fractioin_t_(1).txt

description: :unav
DOI: 10.35003/vkdspf/ity5kv
title: lateral fraction_0.2Hdehon.txt

description: :unav
DOI: 10.35003/vkdspf/ef9st0
title: fig2c.xlsm

description: :unav
DOI: 10.35003/vkdspf/wrcxqm
title: lateral fraction_youngerpeak.txt

description: :unav
DOI: 10.35003/vkdspf/mqerd3
title: readme.txt

description: :unav
DOI: 10.35003/vkdspf/4huoio
title: fig2d.xlsm

description: :unav
DOI: 10.35003/vkdspf/itxkal
title: fig2a.xlsm

description: :unav
DOI: 10.35003/vkdspf/1khrju
title: fig4d_L16.txt

description: :unav
DOI: 10.35003/vkdspf/c6ymod
title: lateral fraction_1.5Hdehon.txt

description: :unav
DOI: 10.35003/vkdspf/aqg4oi
title: fig4d.xlsm

description: :unav
DOI: 10.35003/vkdspf/acgfuo
title: vertical fractioin_t_.txt

description: :unav
DOI: 10.35003/vkdspf/fvg6vj
title: vertical fractioin_youngerpeak.txt

description: :unav
DOI: 10.35003/vkdspf/txtspv
title: lateral fraction_Figure2.txt

description: :unav
DOI: 10.35003/vkdspf/tsywxp
title: fig4a.xlsm

description: :unav
DOI: 10.35003/vkdspf/crpezy
title: fig4b.xlsm

description: :unav
DOI: 10.35003/vkdspf/n6fhv4
title: fig4d_A15.txt

description: :unav
DOI: 10.35003/vkdspf/bl9olb
title: fig4d_A11.txt

description: :unav
DOI: 10.35003/vkdspf/tponer
title: vertical fractioin_0.2Hdehon.txt

description: :unav
DOI: 10.35003/vkdspf/oc2vo0
title: fig4d_L24.txt

description: :unav
DOI: 10.35003/vkdspf/edfxmp
title: lateral fraction_t_.txt

description: :unav
DOI: 10.35003/vkdspf/6amtbm
title: fig2b.xlsm

description: :unav
DOI: 10.35003/vkdspf/wdvpek
title: fig4c.xlsm

description: :unav
DOI: 10.35003/vkdspf/xxunsz
title: vertical fractioin_1.5Hdehon.txt

description: :unav
DOI: 10.35003/vkdspf/9b7ple
title: fig2e.xlsm

description: :unav
DOI: 10.35003/vkdspf/4leckb
title: fig4d_A12.txt

description: :unav
DOI: 10.35003/vkdspf/cv16oc
title: fig2f.xlsm

description: :unav
DOI: 10.35003/vkdspf/xavoeg
title: vertical fractioin_Figure2.txt

description: :unav
DOI: 10.35003/vkdspf/zwnlyx
title: lateral fraction_t_(1).txt

description: :unav
DOI: 10.35003/zpj73u
title: Replication Data for: Lunar megaregolith mixing by impacts: Spatial diffusion of basin melt and its implications for sample interpretation.

description: The formation ages of lunar impact basins are critical to understanding the late accretion history of the inner solar system. Furthermore, the correct interpretation of the provenance and isotopic dates of basin-derived impact melt (‘basin melt’) is essential for the calibration of lunar chronology function. However, abundances of basin melt in the lunar near-surface are not well understood. Basin melt has been gardened by a long sequence of subsequent impact events, altering its abundance and size distribution. We developed a numerical model to investigate this process by means of the Monte Carlo method in a spatially resolved model. The fraction of melt in ejecta was tracked globally and at the Apollo 14–17 and Luna 20 sampling sites and was compared with K-Ar age distributions of lunar impact melt breccias. It was found that melt produced by the very large SPA basin as well as the relatively late-forming Imbrium basin should be dominant in the near-surface (top one meter). The simulation shows that the melt component at the Apollo 14–17 and Luna 20 sites is strongly affected by nearby mid- to late-forming basins. Imbrium melt should be abundant in Apollo 14–17 samples; Crisium melt is the most significant component of basin-sourced melt in Luna 20 samples; all the Apollo 14–17 and Luna 20 samples could include melt from Serenitatis and the SPA basin; Nectaris melt should occur in Apollo 16, Apollo 17 and Luna 20 samples; and Orientale melt has no significant mixing in the Apollo 14–17 and Luna 20 sampling sites. In general, besides a prominent age peak at 3.9 Ga (related to the Imbrium basin), the model predicts pronounced abundance peaks of older basin melt (&gt;3.9 Ga) which tend to be absent from distributions of K-Ar ages of impactites from landing sites. The diffusion characteristics of basin melt suggest that for future sampling aimed at collecting early basin melt, the re-excavation zones of late impact craters larger than tens of kilometer in diameter inside basins may provide the highest abundances of melt from early basins.
DOI: 10.35003/zpj73u/lthprj
title: fig3f.txt

description: data
DOI: 10.35003/zpj73u/6vy4rb
title: fig1.tab

description: :unav
DOI: 10.35003/zpj73u/oumru1
title: fig4a.txt

description: data
DOI: 10.35003/zpj73u/gxe7aa
title: fig4e.txt

description: data
DOI: 10.35003/zpj73u/cjpnbf
title: fig3d.txt

description: data
DOI: 10.35003/zpj73u/iwzoia
title: fig4b.txt

description: data
DOI: 10.35003/zpj73u/ro9zdx
title: fig4c.txt

description: data
DOI: 10.35003/zpj73u/y9g0jt
title: fig5.txt

description: data
DOI: 10.35003/zpj73u/kysree
title: fig2b.txt

description: data
DOI: 10.35003/zpj73u/ltpury
title: fig4d.txt

description: data
DOI: 10.35003/zpj73u/svmv5u
title: fig3e.txt

description: data
DOI: 10.35003/zpj73u/rnyysi
title: fig2a.tab

description: data
DOI: 10.35003/zpj73u/jdckjt
title: fig3b.txt

description: data
DOI: 10.35003/zpj73u/utzs5i
title: fig3c.txt

description: data
DOI: 10.35003/zpj73u/h2tpmz
title: fig3a.txt

description: data
DOI: 10.35003/zpj73u/2xvpnd
title: fig2c.txt

description: data
DOI: 10.35003/zpj73u/ujiafp
title: LiuIcarus2020_Supp1_pub82.docx

description: supplementary information and tables
DOI: 10.35003/zpj73u/zffokk
title: fig2c_impact rate.txt

description: data
DOI: 10.35003/smheim
title: Replication Data for: The Bathymetry of Moray Sinus at Titan's Kraken Mare

description: Moray Sinus is an estuary located at the northern end of Titan’s Kraken Mare. The Cassini RADAR altimeter acquired three segments over this mare during the T104 flyby of Titan, on August 21st, 2014. Herein, we present a detailed analysis of the received echoes. Some of these waveforms exhibit a reflection from the seafloor, from up to 85 (−18, +28) m of depth (1σ error). Monte-Carlo simulations have been performed in order to assess the most probable values and estimation errors for the seafloor depth. Insights from this study, featuring the synergic use of the synthetic aperture radar images coupled to the altimetry and passive radiometry datasets, have been used to constrain the dielectric properties (i.e., absorptivity of the liquid) and roughness of this region of Kraken Mare. The resulting Ku-band specific attenuation of the liquid is 17 ± 3 dB/μs, corresponding to a loss tangent of (4.6 ± 0.9) ×10−5, which is very similar to the loss tangent estimated at Ligeia Mare. The data in hand do not permit us to discern the most likely explanation for the lack of a seafloor reflection from the main body of Kraken Mare: either a very deep sea or a more absorbing liquid composition. However, if the main body of Kraken Mare is characterized by an absorption similar to Moray Sinus, then based on models of the response to altimetry mode observations we can conclude that it exceeds 100 meters of depth, which is also compatible with radiometry observations.
DOI: 10.35003/smheim/3qawku
title: BIBQH52N010_D126_T028S01_V02.mat

description: Incidence angle and noise corrected T28 SAR image
DOI: 10.35003/smheim/whmhkv
title: BILQH52N010_D126_T028S01_V02.mat

description: :unav
DOI: 10.35003/smheim/0v4l1m
title: BINQH33N028_D120_T025S01_V02.mat

description: :unav
DOI: 10.35003/smheim/4qtoun
title: BINQH52N010_D126_T028S01_V02.mat

description: :unav
DOI: 10.35003/smheim/ei93oi
title: BISQH52N010_D126_T028S01_V02.mat

description: Noise corrected but not incidence angle corrected T28 SAR image
DOI: 10.35003/smheim/vhep1j
title: BIEQH33N028_D120_T025S01_V02.mat

description: :unav
DOI: 10.35003/smheim/a0ryh0
title: T028_Seg01_Res128pxd.txt

description: :unav
DOI: 10.35003/smheim/7p18vs
title: BIUQH33N028_D120_T025S01_V02.mat

description: :unav
DOI: 10.35003/smheim/1kf2ua
title: BILQH33N028_D120_T025S01_V02.mat

description: :unav
DOI: 10.35003/smheim/jolkda
title: BIBQH52N010_D126_T028S01_V02.IMG.png

description: :unav
DOI: 10.35003/smheim/lzwbyy
title: BITQH33N028_D120_T025S01_V02.mat

description: :unav
DOI: 10.35003/smheim/gsrngy
title: BIEQH52N010_D126_T028S01_V02.mat

description: :unav
DOI: 10.35003/smheim/7xwjyc
title: BIBQH33N028_D120_T025S01_V02.IMG.png

description: Incidence angle and noise corrected T25 SAR image
DOI: 10.35003/smheim/6b2hyj
title: BISQH33N028_D120_T025S01_V02.mat

description: Noise corrected but not incidence angle corrected T25 SAR image
DOI: 10.35003/smheim/rruia6
title: BIUQH52N010_D126_T028S01_V02.mat

description: :unav
DOI: 10.35003/smheim/qfeh5j
title: ALTIMETER_T104_DATA.mat

description: Matlab Workspace
DOI: 10.35003/smheim/lth5bn
title: BIMQH33N027_D120_T025S01_V03.mat

description: :unav
DOI: 10.35003/smheim/hkqktd
title: T025_Seg01_Res128pxd.txt

description: Text file
DOI: 10.35003/smheim/ukdkf3
title: BIMQH52N010_D126_T028S01_V02.mat

description: :unav
DOI: 10.35003/smheim/cexnu9
title: BIBQH33N028_D120_T025S01_V02.mat

description: :unav
DOI: 10.35003/smheim/ccxgtx
title: BITQH52N010_D126_T028S01_V02.mat

description: :unav
DOI: 10.35003/smheim/j9eleo
title: ALTIMETER_T104_RESULTS.tab

description: Microsoft Excel Table
DOI: 10.35003/smheim/tijdpp
title: ALTIMETER_T104_DATA_notes.txt

description: :unav
DOI: 10.6084/m9.figshare.22226182
title: Supplementary Material for: Genetic and environmental factors underlying parallel changes in body mass index and alcohol consumption: a 36-year longitudinal study of adult twins

description: Introduction: While the genetic and environmental underpinnings of body weight and alcohol use are fairly well-known, determinants of simultaneous changes in these traits are still poorly known. We sought to quantify the environmental and genetic components underlying parallel changes in weight and alcohol consumption, and to investigate potential covariation between them. Methods: The analysis comprised 4461 adult participants (58% women) from the Finnish Twin Cohort with four measures of alcohol consumption and body mass index (BMI) over a 36-year follow-up. Trajectories of each trait were described by growth factors, defined as intercepts (i.e., baseline) and slopes (i.e., change over follow-up), using Latent Growth Curve Modeling. Growth values were used for male (190 monozygotic pairs, 293 dizygotic pairs) and female (316 monozygotic pairs, 487 dizygotic pairs) same-sex complete twin pairs in multivariate twin modeling. The variances and covariances of growth factors were then decomposed into genetic and environmental components. Results: The baseline heritabilities were similar in men (BMI: h2=79% [95% Confidence Interval: 74,83]; alcohol consumption: h2=49% [32,67]) and women (h2=77% [73,81]; h2=45% [29,61]). Heritabilities of BMI change were similar in men (h2=52% [42,61]) and women (h2=57% [50,63]), but the heritability of change in alcohol consumption was significantly higher (p=0.03) in men (h2=45% [34,54]) than in women (h2=31% [22,38]). Significant additive genetic correlations between BMI at baseline and change in alcohol consumption were observed in both men (rA =-0.17 [-0.29,-0.04]) and women (rA=-0.18 [-0.31,-0.06]). Non-shared environmental factors affecting changes in alcohol consumption and BMI were correlated in men (rE=0.18 [0.06,0.30]). Among women, non-shared environmental factors affecting baseline alcohol consumption and the change in BMI were inversely correlated (rE=-0.11 [-0.20, -0.01]). Conclusions: Based on genetic correlations, genetic variation underlying BMI may affect change in alcohol consumption. Independent of genetic effects, change in BMI correlates with change in alcohol consumption in men, suggesting direct effects between them.