cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/cnwv9hdspd.1
title: A Geospatiotemporal and Causal Inference Epidemiological Exploration of Substance and Cannabinoid Exposure as Drivers of Rising US Pediatric Cancer Rates - Final Dataset

description: Background. Age-adjusted US total pediatric cancer incidence rates (TPCIR) rose 49% 1975-2015 for unknown reasons. Prenatal cannabis exposure has been linked with several pediatric cancers which together comprise the majority of pediatric cancer types. We investigated whether cannabis use was related spatiotemporally and causally to TPCIR. Methods. State-based age-adjusted TPCIR data was taken from the CDC Surveillance, Epidemiology and End Results cancer database 2003-2017. Drug exposure was taken from the nationally-representative National Survey of Drug Use and Health, response rate 74.1%. Drugs included were: tobacco, alcohol, cannabis, opioid analgesics and cocaine. This was supplemented by cannabinoid concentration data from the Drug Enforcement Agency and ethnicity and median household income data from US Census. Results. TPCIR rose while all drug use nationally fell, except for cannabis which rose. TPCIR in the highest cannabis use quintile was greater than in the lowest (β-estimate=1.31 (95%C.I. 0.82, 1.80), P=1.80x10-7) and the time:highest two quintiles interaction was significant (β-estimate=0.1395 (0.82, 1.80), P=1.00x10-14). In robust inverse probability weighted additive regression models cannabis was independently associated with TPCIR (β-estimate=9.55 (3.95, 15.15), P=0.0016). In interactive geospatiotemporal models including all drug, ethnic and income variables cannabis use was independently significant (β-estimate=45.67 (18.77, 72.56), P=0.0009). In geospatial models temporally lagged to 1,2,4 and 6 years interactive terms including cannabis were significant. Cannabis interactive terms at one and two degrees of spatial lagging were significant (from β-estimate=3954.04 (1565.01, 6343.09), P=0.0012). The interaction between the cannabinoids THC and cannabigerol was significant at zero, 2 and 6 years lag (from β-estimate=46.22 (30.06, 62.38), P=2.10x10-8). Cannabis legalization was associated with higher TPCIR (β-estimate=1.51 (0.68, 2.35), P=0.0004) and cannabis-liberal regimes were associated with higher time:TPCIR interaction (β-estimate=1.87x10-4, (2.9x10-5, 2.45x10-4), P=0.0208). 33/56 minimum e-Values were &gt;5 and 6 were infinite. Conclusion. Data confirm a close relationship across space and lagged time between cannabis and TPCIR which was robust to adjustment, supported by inverse probability weighting procedures and accompanied by high e-Values making confounding unlikely and establishing the causal relationship. Cannabis-liberal jurisdictions were associated with higher rates of TPCIR and a faster rate of TPCIR increase. Data inform the broader general consideration of cannabinoid-induced genotoxicity.
DOI: 10.17632/sysz47grjj.1
title: PAG_LeTeil

description: PGA (H and V) measured in metropolitan France after the 11/11/2019 Le Teil earthquake (magnitude ML 5.4)
DOI: 10.17632/2tv7sm9cjy.1
title: Electric resistivity tomography and Seismic refraction tomography of mining tailings: Dataset
DOI: 10.17632/vrz65ryrg5.1
title: EWASP ver. 1 - Model, instructions, and example output

description: Space heating and DHW profile modelling tool for residential buildings with air source and ground source heat pumps. Runs in the MATLAB/Simulink environment. See 'EWASP Instructions.pdf' for guidance on installation and usage.
DOI: 10.17632/574x5mz3tr.2
title: Lateral pharyngoplasty vs UPPP

description: Tables and charts
DOI: 10.17632/tcfbwktjxz.2
title: Pig sclera stress-strain dataset under biaxial tensile testing
DOI: 10.17632/23wjfzb73m.2
title: Pig sclera biaxial tensile dataset - force vs displacement
DOI: 10.17632/m96d5b8d33.3
title: Dataset forIJGGC submission: Impacts of CO2 injection speed on two-phase flow and physical parameters in porous sandstone

description: Waveform data under lowest FR condition for all channels. Waveform data under all FR condition for all channels. Raw data of impedance under all FR conditions
DOI: 10.17632/xd8h7n9kkc.1
title: Analysis of Graphic and Textual Works for Informing the Population via Social Media during Covid-19

description: Analysis of Graphic and Textual Works for Informing the Population via Social Media during Covid-19 (in Ukranian)
DOI: 10.17632/x3fmrwxxy5.1
title: Sulu Arc-Basin System

description: Whole-rock geochemical and zircon U-Pb-Hf data for igneous rocks in northern Borneo
DOI: 10.17632/6932898d8g.1
title: Replication Data for: COVID-19 Death Surveillance using Official and Unofficial Newspaper-based Death Counts

description: Both daily and weekly confirmed COVID-19 death counts were collected from the Johns Hopkins Coronavirus Resource Center and CLI death counts based on newspaper-based surveys were collected from the Bangladesh Peace Observatory between March 8, 2020, and August 22, 2020.
DOI: 10.17632/y2xxjc9rj7.1
title: SIMS U–Pb isotopic data (Table S1) and LA-MC-ICPMS Hf and SIMS O isotopic data (Table S2) of zircons from the Hadanxun intrusive rock and Bieli'atun alkali-feldspar granite

description: It contains two Spreadsheet Tables S1 and S2.
DOI: 10.17632/s24y42424b.1
title: Supplemental Files: Melanoma In-Situ and Invasive Melanoma of the Vulva: an Analysis of the National Cancer Database

description: Full methods, results, discussion, and tables/figures for Melanoma In-Situ and Invasive Melanoma of the Vulva: an Analysis of the National Cancer Database
DOI: 10.17632/smt42dt7hd.1
title: De novo cutaneous connective tissue disease associated with immune checkpoint inhibitor therapy: a retrospective analysis

description: JAAD online-only supplemental figures for "De novo cutaneous connective tissue disease associated with immune checkpoint inhibitor therapy: a retrospective analysis"
DOI: 10.17632/vn599y9szb.1
title: High-resolution mapping of floodplain topography from space: A case study in the Amazon

description: This data set contains the following maps (in GeoTIFF format): 1) Bathymetry of the middle-lower Amazon River (River_Bathymetry.tif); Elevation in meters relative to the EGM2008 geoid. 2) Topography of the non-forested portion of the middle-lower Amazon floodplain after bias removed (Floodplain_Topography.tif); Elevation in meters relative to the EGM2008 geoid. 3) Topography of the non-forested portion of the middle-lower Amazon floodplain without bias removed (Floodplain_Topography_bias.tif); Elevation in meters relative to the EGM2008 geoid. 4) Flood frequency (or open water frequency) for the period 1984 to 2015 (FloodFreq_1984_2015.tif); Values ranging from 0 to 100%. 5) Amplitude of the water level in the middle-lower Amazon floodplain (WaterLevel_Amplitude.tif); Values in centimeters. 6) Water depth in the middle-lower Amazon floodplain for the period of high-water (Depth_HighW.tif) and low-water (Depth_LowW.tif); Values in centimeters. More information: Fassoni‐Andrade, A. C., Paiva, R. C. D., Rudorff, C. D., Barbosa, C. C. F., Novo, E. M. L M (2020) High-resolution mapping of floodplain topography from space: A case study in the Amazon, Remote Sens. Environ., 251(December 2020), https://doi.org/10.1016/j.rse.2020.112065.
DOI: 10.17632/36wc84t8gn.1
title: Data for : Hybrid Vibration Control of an Industrial CFRP Composite Robot-Manipulator System Based on Reduced Order Model

description: This dataset presents a total of 81 data of four types of experiments of the proposed hybrid vibration control study: (1) in robustness test; time, end point applied force data and root strain-gauge data were collected. (2) In hybrid vibration control strain-gauge test; Time, angular velocity input applied from Point-O and strain-gauge data at the root were collected. (3) In the hybrid vibration control accelerometer test; time, angular velocity input applied from Point-O and accelerometer data at Point-A were collected. (4) In sysetem identification test; Without the FLM system, only the data defined to the drive and the angular velocity data derived from the encoder were collected.
DOI: 10.17632/fxrx9wjxkd.1
title: Supplementary Table S2: Hurst exponents of all IMFs of arrhythmic and normal subjects estimated by R/S technique.

description: Empirical Mode Decomposition (EMD) technique was applied to each of the filtered ECG signal (Supplementary Table S1) decomposing them into a finite number of Intrinsic Mode Functions (IMFs) following the sifting process. To retrieve the maximum number of IMFs, the number of iterations was set to 150. The number of IMFs retrieved from most of the ECG signals was 12. However, it ranges between 10 and 14. The values of Hurst Exponent (H) of all IMFs of the ECG time-series were estimated by R/S techniques in order to quantitatively assess the regularity and scaling of the data. The estimated H values for each IMFs corresponding to diseased and normal patients’ ECG data are tabulated in Supplementary Table S2.
DOI: 10.6084/m9.figshare.12947516
title: Data Set (S1)

description: Sandstone composition, major-element geochemistry, Nd isotopic and detrital U-Pb age data for the manuscript of <i>Growth of the northeastern Tietan Plateau during the middle-late Miocene:Insight from the provenance analysis in the NE Qaidam Basin.</i><br>
DOI: 10.17632/s5ywd3525d.1
title: Rat Pak1 sequencing primers (supplemental table 1)

description: Rat Pak1 exonic sequencing primers
DOI: 10.17632/h9vdjh8tk7.1
title: Data for measuring e-learning systems success during the COVID-19 pandemic: Case of the Higher Education Institutions in Morocco

description: E-learning systems success data.
DOI: 10.17632/hfzvhd2f5p.1
title: U.S. Stock Market Data - Dow Jones (501 companies, 2010-2016)

description: The dataset consists of daily data from US Dow Jones for 501 large companies, over the time span 2010-2016, while monthly publicly available indexes are also used.
DOI: 10.17632/myf37k2x27.1
title: Supplementary Table S3: Correlation coefficients calculated between IMFs and original data series of arrhythmic and normal subjects.

description: The correlation coefficient between the IMFs of and the original signal (see the description of Supplementary Table S2) was calculated to identify the IMFs with the real components of the original signal (see Supplementary Table S1). The correlation coefficients were calculated using the following equations as described by Wharton et al., 2013 and Jha et al., 2006.
DOI: 10.17632/krvmtrps2z.1
title: Corrosion Behavior of Cold Sprayed Aluminum Alloys 2024 and 7075 in an Immersed Seawater Environment

description: This contains the processed results in an excel file, as well as raw results organized in folders by alloy composition (2024 or 7075), then by material (either wrought/stock or cold spray/CS), then by anodic or cathodic branch.
DOI: 10.17632/p58k2bd6t5.1
title: SARS-CoV-2 Infection of Pluripotent Stem Cell-derived Human Lung Alveolar Type 2 Cells Elicits a Rapid Epithelial-Intrinsic Inflammatory Response. Huang et al

description: Table S1
DOI: 10.17632/n66n5pj4f6.2
title: Antigen-specific adaptive immunity to SARS-CoV-2 in acute COVID-19 and associations with age and disease severity. Moderbacher et al.

description: We conducted an analysis of SARS-CoV-2 specific adaptive immune responses during acute COVID-19 in comparison with convalescent COVID-19 and unexposed, healthy controls and identified that coordination between SARS-CoV-2-specific CD4 T cells and CD8 T cells limits disease severity in COVID-19. Aged individuals more often exhibited uncoordinated adaptive responses, potentially tied to scarcity of naive T cells, highlighting immunologic risk factors linked to COVID-19 disease severity. The data available here include all of the supplementary tables and figures, as well as a simplified parameters sheet with experimental and donor information for the healthy unexposed, acute COVID-19, and convalescent COVID-19 donor samples included in this study. Additional information about the supplementary materials, fields, field names, calculations, and patient cohorts are all provided in the published paper.
DOI: 10.17632/p6nbn2hyz9.1
title: Boreal Chorus Frog Calling Activity in the Central Platte River Valley of Nebraska in Spring 2015 - 2017

description: Boreal chorus frog (Pseudacris maculata) calling activity and associated environmental variables collected in the Central Platte River Valley of Nebraska in the spring of 2015, 2016, and 2017. Calling activity derived from sound analysis. Vegetation phenology and wet meadow hydrology derived from image-analysis. Weather and river discharge obtained from NOAA and USGS, respectively. Metadata: Site: study sites; either slough or wet meadow Year: 2015, 2016, or 2017 Date: m/d/yyyy Missing: denotes 1 if calling activity is missing for the day and 0 if data is not missing Count: daily calling activity of boreal chorus frog scaled from 0 - 1 GCC: green chromatic coordinates, vegetation index derived from image analysis HYDRO: scaled 0 - 1 hydropattern; at slough this is USGS Platte River streamflow; at wet meadow this is water inundation from image-analysis WND: average windspeed in MPH PRCP: total daily precipitation accumulation SNOW: total daily snow accumulation (cm) SNWD: daily snow depth (cm) TAVG: daily average temperature (c) TMAX: maximum daily temp (c) TMIN: minimum daily temp (c) PRCP7: weekly precipitation accumulation (cm) PRCP1: day prior daily accumulation (cm) DOY: day of year For further details, see accompanying manuscript 'Assessing ecological and environmental influences on Boreal Chorus Frog (Pseudacris maculata) spring calling phenology using multimodal passive monitoring technologies' and Data-In-Brief.
DOI: 10.17632/szsc5pgxns.1
title: Supplementary files for 'comparative transcriptome of kidney in Coilia nasus under salinity stress'

description: DEGs in this study and primers used for qRT-PCR validation.
DOI: 10.6084/m9.figshare.7676090
title: Figure2

description: BGRD marks tumor-promoting genes.
DOI: 10.6084/m9.figshare.7676090.v4
title: Figure2

description: BGRD marks tumor-promoting genes.
DOI: 10.6084/m9.figshare.7676090.v3
title: Figure2

description: BGRD marks tumor-promoting genes.
DOI: 10.6084/m9.figshare.12218555
title: Suppl.Figure2

description: BGRDs
DOI: 10.6084/m9.figshare.12218555.v1
title: Suppl.Figure2

description: BGRDs
DOI: 10.6084/m9.figshare.12218558
title: Suppl.Figure2

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218558.v2
title: Suppl.Figure2

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218558.v1
title: Suppl.Figure2

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218561
title: Suppl.Figure3

description: BGRDs
DOI: 10.6084/m9.figshare.12218561.v2
title: Suppl.Figure3

description: BGRDs
DOI: 10.6084/m9.figshare.12218561.v1
title: Suppl.Figure3

description: BGRDs
DOI: 10.6084/m9.figshare.7683935.v3
title: Suppl.Figure5

description: Broad H3K27me3 marks oncogene.
DOI: 10.6084/m9.figshare.7683935
title: Suppl.Figure5

description: Broad H3K27me3 marks oncogene.
DOI: 10.6084/m9.figshare.7683935.v5
title: Suppl.Figure5

description: Broad H3K27me3 marks oncogene.
DOI: 10.6084/m9.figshare.7683935.v4
title: Suppl.Figure5

description: Broad H3K27me3 marks oncogene.
DOI: 10.6084/m9.figshare.7683929
title: Suppl.Figure6

description: BGRDs
DOI: 10.6084/m9.figshare.7683929.v5
title: Suppl.Figure6

description: BGRDs
DOI: 10.6084/m9.figshare.7683929.v4
title: Suppl.Figure6

description: BGRDs
DOI: 10.6084/m9.figshare.7683932
title: Suppl.Figure7

description: Broad H3K27me3 marks oncogene.
DOI: 10.6084/m9.figshare.7683932.v5
title: Suppl.Figure7

description: Broad H3K27me3 marks oncogene.
DOI: 10.6084/m9.figshare.7683932.v4
title: Suppl.Figure7

description: Broad H3K27me3 marks oncogene.
DOI: 10.6084/m9.figshare.12218564
title: Suppl.Figure8

description: BGRDs
DOI: 10.6084/m9.figshare.12218564.v2
title: Suppl.Figure8

description: BGRDs
DOI: 10.6084/m9.figshare.12218564.v1
title: Suppl.Figure8

description: BGRDs
DOI: 10.6084/m9.figshare.12218567
title: Suppl.Figure9

description: BGRDs
DOI: 10.6084/m9.figshare.12218567.v2
title: Suppl.Figure9

description: BGRDs
DOI: 10.6084/m9.figshare.12218567.v1
title: Suppl.Figure9

description: BGRDs
DOI: 10.6084/m9.figshare.12218570
title: Suppl.Figure10

description: BGRDs
DOI: 10.6084/m9.figshare.12218570.v3
title: Suppl.Figure10

description: BGRDs
DOI: 10.6084/m9.figshare.12218570.v2
title: Suppl.Figure10

description: BGRDs
DOI: 10.34740/kaggle/dsv/1481302
title: Learning Analytics Link Collection
DOI: 10.5281/zenodo.4025491
title: Aerocargo Trafic Argentina - from 2014 to 2019 (no covid-19 data included) Critical Infrastructure Risk Research Program

description: Proyectos Bianuales de Investigación Universidad Nacional de Cuyo Propuestas metodológicas y modelos de concepción, operación y gestión<br> para la reducción de vulnerabilidad e incremento de la resiliencia en la<br> nueva generación de infaestructuras crítica de américa latina.<br> Código Sigeva: B083<br> Resolución Nro.: Otorgamiento: RES 4142/2019-R- Expediente de pago: NOTA-<br> CUY:38892/2019<br>
description: Total de Vuelos Registrado con aeropuerto de partida y llegada. Existen menos del 2% de aeronaves que no emitieron su baliza ADSB que no fue captada por SDR. Despegaron y Aterrizaron en Locaciones no registradas como pistas habilitadas.
description: {"references": ["Risk and Critical Infrastructures An interpretation from the Transcurssive Logic 10.5281/zenodo.3354070"]}
DOI: 10.5281/zenodo.4025490
title: Aerocargo Trafic Argentina - from 2014 to 2019 (no covid-19 data included) Critical Infrastructure Risk Research Program

description: Proyectos Bianuales de Investigación Universidad Nacional de Cuyo Propuestas metodológicas y modelos de concepción, operación y gestión<br> para la reducción de vulnerabilidad e incremento de la resiliencia en la<br> nueva generación de infaestructuras crítica de américa latina.<br> Código Sigeva: B083<br> Resolución Nro.: Otorgamiento: RES 4142/2019-R- Expediente de pago: NOTA-<br> CUY:38892/2019<br>
description: Total de Vuelos Registrado con aeropuerto de partida y llegada. Existen menos del 2% de aeronaves que no emitieron su baliza ADSB que no fue captada por SDR. Despegaron y Aterrizaron en Locaciones no registradas como pistas habilitadas.
description: {"references": ["Risk and Critical Infrastructures An interpretation from the Transcurssive Logic 10.5281/zenodo.3354070"]}
DOI: 10.6084/m9.figshare.12218573
title: Suppl.Figure11

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218573.v2
title: Suppl.Figure11

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218573.v1
title: Suppl.Figure11

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218576
title: Suppl.Figure12

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218576.v2
title: Suppl.Figure12

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218576.v1
title: Suppl.Figure12

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218579
title: Suppl.Figure13

description: BGRDs
DOI: 10.6084/m9.figshare.12218579.v2
title: Suppl.Figure13

description: BGRDs
DOI: 10.6084/m9.figshare.12218579.v1
title: Suppl.Figure13

description: BGRDs
DOI: 10.6084/m9.figshare.12218582
title: Suppl.Figure14

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218582.v2
title: Suppl.Figure14

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218582.v1
title: Suppl.Figure14

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218585
title: Suppl.Figure15

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218585.v2
title: Suppl.Figure15

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218585.v1
title: Suppl.Figure15

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218600
title: Suppl.Figure17

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218600.v2
title: Suppl.Figure17

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218600.v1
title: Suppl.Figure17

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218603
title: Suppl.Figure18

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218603.v2
title: Suppl.Figure18

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218603.v1
title: Suppl.Figure18

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218609
title: Suppl.Figure19

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218609.v2
title: Suppl.Figure19

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218609.v1
title: Suppl.Figure19

description: BGRDs, tumor
DOI: 10.6084/m9.figshare.12218627
title: Suppl.Figure24

description: BGRDs, tumor<br>
DOI: 10.6084/m9.figshare.12218627.v3
title: Suppl.Figure24

description: BGRDs, tumor<br>
DOI: 10.6084/m9.figshare.12218627.v2
title: Suppl.Figure24

description: BGRDs, tumor<br>
DOI: 10.5519/qd.jg1jmafk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (209 records)
DOI: 10.21227/y2hj-8d56
title: Discriminative Concept Learning Network: Sample Source Code and Supplement (Project Archive)

description: Summary: The archive of DCLN project (https://sourceforge.net/projects/dcln/) is provided.Code & Script: Written in C/C++, running Shell scripts on Linux system. Mature package release v2.0 available for download. Check './dcln.sh' for usage info.Document: Details of hyperparameters tuning, data preprocessing and code compiling are given.Data: Four nonlinear simulation datasets are provided (Fig. 2 of the main paper). Each study has ~2000 training samples and ~2000 test samples.
DOI: 10.5287/bodleianjr8b.2
title: On A Working-Party

description: Typescript of poem in blue ink. This is a clean draft without corrections. Published in 'The Old Huntsman' (1917). Possibly inspired by Siegfried Sassoon's experiences with a working party near Festubert in 1916.
DOI: 10.17876/rave/dr.6/fields/20070319_1318m19
title: RAVE Field 20070319_1318m19

description: A field from the RAVE survey
DOI: 10.17614/q4ht2gf75
title: s-methyl-l-cysteine
DOI: 10.17632/s2nhh4fy9x.2
title: OCD Phenomenology in Children and Adolescents: A University Hospital Sample

description: Collected data from patients
DOI: 10.18749/dodis-34865
title: dodis.ch/34865
DOI: 10.7270/q2251hph
title: BindingDB Entry 50015192: Structure-activity relationships of piperazinebenzylamines as potent and selective agonists of the human melanocortin-4 receptor.

description: Small molecule binding data for protein Melanocortin receptor 3 (MC3R), Melanocortin receptor 4, Melanocortin receptor 5 (MC5R), and Melanocyte-stimulating hormone receptor, Uniprot P32245, P33032, P41968, and Q01726
DOI: 10.23725/vsvf-b886
title: NWD280206.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD280206.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.25491/hwyc-4055
title: GTEX-1497J-1926-SM-5TDCC

description: Sample ID: GTEX-1497J-1926-SM-5TDCC
DOI: 10.26304/366-u1491b-rgb
title: Expedition 366 Hole U1491B RGB channels (calculated from core photos) data file

description: Hole U1491B RGB - RGB channels (calculated from core photos) for Expedition 366 Hole U1491B
DOI: 10.26126/intervals.sef3da
title: Tooth coloration (ΔE and L*a*b* values) [Individual measurements]

description: This dataset was generated in an in vitro study where the impact of exposure to THS 2.2 TPM and CS TPM on bovine enamel was studied.
Changes in L*, a*, and b* values for enamel were measured after exposures and treatments. ΔE values were calculated based on L*, a*, and b*values.
This dataset includes single measurements for each sample.
DOI: 10.18112/openneuro.ds002741.v1.0.2
title: Animated caricatures fMRI study
DOI: 10.25550/v9a
title: Gene expression microarray - mouse E10.5 olfactory pit

description: Gene expression microarray using tissue obtained by laser capture microdissection (LCM) from the olfactory pit of mouse embryos at E10.5. See links to Genome Browser in the Additional Information section. This track represents 31 independent samples of different regions of developing craniofacial structures obtained from embryonic day 10.5 and 11.5 mouse embryos.