611 to 620 of 816 Results
May 24, 2022 -
Related data for: Topologically Organized Networks in the Claustrum Reflect Functional Modularization
Unknown - 58.2 MB -
MD5: 0791ad5b25843eacac24db54627020d5
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May 24, 2022 -
Related data for: Topologically Organized Networks in the Claustrum Reflect Functional Modularization
PNG Image - 432.3 KB -
MD5: 7daa26c27dc40aa3bff771ff079e3493
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May 24, 2022 -
Related data for: Topologically Organized Networks in the Claustrum Reflect Functional Modularization
Unknown - 53.9 MB -
MD5: 1cc34930ebe1384842563d06687e4d67
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Jan 25, 2022 - Fang Yang
Smith, Helen Elizabeth; Fang, Yang, 2022, "Replication Data for: Retaining and re-engaging Singapore’s primary care doctors: a cross-sectional survey and qualitative analysis", https://doi.org/10.21979/N9/62LHEC, DR-NTU (Data), V1, UNF:6:uGhPaqwuBOgusckv209ksQ== [fileUNF]
Replication Data for: "Retaining and re-engaging Singapore’s primary care doctors: a cross-sectional survey and qualitative analysis" |
Jan 25, 2022 -
Replication Data for: Retaining and re-engaging Singapore’s primary care doctors: a cross-sectional survey and qualitative analysis
Tabular Data - 167.4 KB - 160 Variables, 355 Observations - UNF:6:uGhPaqwuBOgusckv209ksQ==
dataset |
Jan 25, 2022 -
Replication Data for: Retaining and re-engaging Singapore’s primary care doctors: a cross-sectional survey and qualitative analysis
MS Word - 40.0 KB -
MD5: 014bbb8ba03c11fd407939e7917a3f3e
questionnaire |
Sep 6, 2021 - Fang Yang
Teo, Boon See; Li, Esther; Khoo, Yi-Lin; Evaristo, Michelle M.P.; Fang, Yang; Smith, Helen E., 2021, "Replication Data for: A Mobile Swabbing Booth to Address Singapore GPs’ Concerns About Swabber Protection: Human-Centred Design during the COVID-19 Pandemic", https://doi.org/10.21979/N9/XRTKJV, DR-NTU (Data), V1, UNF:6:BUo0vTLJdenQaXUltMwtDA== [fileUNF]
Dataset and relevant materials for the study "A Mobile Swabbing Booth to Address Singapore GPs’ Concerns About Swabber Protection: Human-Centred Design during the COVID-19 Pandemic" |
Tabular Data - 91.8 KB - 88 Variables, 93 Observations - UNF:6:BUo0vTLJdenQaXUltMwtDA==
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MS Word - 20.8 KB -
MD5: 3fe6c853285d1bb41726800f438eef50
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Adobe PDF - 169.6 KB -
MD5: c51b4d71417475795589ca3dcc352e78
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