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Deposit, archive and share your final research data in DR-NTU (Data)

DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

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55,451 to 55,460 of 74,567 Results
figure2.fig
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Figure - 59.6 KB - MD5: 9ed4605a3dfea4110694b7899443a2bd
fit_ellipse.m
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Source Code - 9.7 KB - MD5: c3faaad19318bf8a0a34df6aad524833
gray_ana.m
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Source Code - 555 B - MD5: 30453b554834762b3f6bdecd1601b8a2
gray_sort.m
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Source Code - 282 B - MD5: cba3d9ac4f76996b488717256840384a
gudao40-rimgao.tab
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
Tabular Data - 3.1 KB - 2 Variables, 200 Observations - UNF:6:oQnBIWCSC8FnFZmsj7X6pA==
high-rim-low-rim.fig
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Figure - 26.1 KB - MD5: e325074426b73861e0d85e420e253e8d
hist_number_side.m
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Source Code - 474 B - MD5: 9f34bbc685376f0b504e6e789a07ceac
hist_number_zone.m
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Source Code - 993 B - MD5: 4ccea9fb35df4fbce75c1a2c4a2d53d8
hist_zone_area.m
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Source Code - 1.3 KB - MD5: 0faee7e21a2f289524d2380b2bd136c8
howmanycrystalformaps.m
Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach
MATLAB Source Code - 1.3 KB - MD5: c4d171d269e12d149079fa3869afd4fc
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