48,321 to 48,330 of 72,668 Results
Tabular Data - 2.6 KB - 3 Variables, 101 Observations - UNF:6:0MaJTAm8ftzfdP9/1KCMzQ==
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Nov 20, 2021 - Wang You
Wang, You; Wouter Verstraelen, 2021, "Replication Data for: Giant Enhancement of Unconventional Photon Blockade in a Dimer Chain", https://doi.org/10.21979/N9/E0MILR, DR-NTU (Data), V1
Data and computer code used to produce the simulation and theory plots in the paper "Giant Enhancement of Unconventional Photon Blockade in a Dimer Chain" |
Nov 20, 2021 -
Replication Data for: Giant Enhancement of Unconventional Photon Blockade in a Dimer Chain
XZ Archive - 2.5 MB -
MD5: b5163dad718e182478a9cec2c10a13da
Read note.txt for description of contents. |
Nov 17, 2021 - ZHANG Baile
Xue, Haoran; Zhang, Baile, 2021, "Replication data for: Time-periodic corner states from Floquet higher-order topology", https://doi.org/10.21979/N9/YBSECE, DR-NTU (Data), V1
Experimental data for the paper "Time-periodic corner states from Floquet higher-order topology". |
RAR Archive - 890 B -
MD5: bf3bb765a68878d4ec2b88e0f25fb0ae
Data for Fig.2d |
RAR Archive - 1.7 KB -
MD5: 0b04680998fb8cdf9b73765bf1b13164
Data for Fig.3d |
RAR Archive - 845 B -
MD5: c77210bf732c47d1174689bdbdc72ca8
Data for Fig.4 |
Nov 16, 2021 - CRADLE - Centre for Research and Development in Learning
Puah, Shermain; Bin Mohmad Khalid, Muhammad Iskandar Shah; Looi, Chee Kit; Khor, Ean Teng, 2021, "Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance", https://doi.org/10.21979/N9/NZ8N7M, DR-NTU (Data), V2, UNF:6:qUPyfXjS0D9VcYSbOtGU+Q== [fileUNF]
Data set and R code script for the manuscript titled "Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance" |
Nov 16, 2021 -
Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance
Adobe PDF - 254.8 KB -
MD5: 30927cf4d599c3ce2cd92bfd2466e43c
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Nov 16, 2021 -
Working adults’ intentions to participate in microlearning: Assessing for measurement invariance and structural invariance
Adobe PDF - 107.3 KB -
MD5: 0cf0a56f0ab68008ae2444b1f6eb5721
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