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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.

How to deposit?

Useful links: FAQs | Collection Guidelines | NTU Research Data Management | General terms of use and Privacy policy

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51,201 to 51,210 of 70,301 Results
longshort.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 - 252 B - MD5: 295c2248882063f8c886448581b5abbe
march2016_area_900-1-1-2.mat
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 Data - 338.8 KB - MD5: c586b822c7dfb82e33b5e7810af21680
march2016_area_900-1-2-5_change_angle.mat
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 Data - 254.8 KB - MD5: 427c120afc7e8c2259b1decaea71426b
march2016_area_900-1-5-5_change_angle.mat
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 Data - 367.3 KB - MD5: 70b5bf8a5e858b38e74bc67c36e92f63
mkprofile.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 - 5.2 KB - MD5: 58923ccca404cde9294a9a27f5887bf5
mkprofile_Os.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 - 2.1 KB - MD5: 65ceb45635532cdd1e7d6d2c26106afd
new400-1-1-2.mat
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 Data - 3.2 MB - MD5: 682ee2d098283ebcc68f9228169c486b
new400-1-2-5-area.mat
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 Data - 2.7 MB - MD5: a96faa3525d373e4ede81b000eeea484
new400-profile120-3zone.mat
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 Data - 2.0 MB - MD5: d55468a67021219419de9b5d3f0f0f56
new400-profiles80-2zones-1-1-2-digao.mat
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 Data - 1.4 MB - MD5: d1ab92d90fe2e1f03cff1708b39abec9
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