41 to 50 of 140,313 Results
Jun 3, 2026 -
Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian
Adobe PDF - 134.1 KB -
MD5: b2a8b05c0f7293eaa908592c2313ba90
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Jun 3, 2026 -
Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian
Adobe PDF - 272.4 KB -
MD5: 04c30a8447fa39ebb0b08cd7ff09ca75
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Jun 3, 2026 -
Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian
ZIP Archive - 3.1 MB -
MD5: 129b08122a77cb5db0266ed0b88da799
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Jun 3, 2026 -
Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian
Comma Separated Values - 7.1 KB -
MD5: a8de2afebcbeb10923e88c852d4b073d
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Jun 3, 2026 -
Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian
Comma Separated Values - 5.5 KB -
MD5: ab704f1b4f8c66d268405d6b3b1d06c7
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Jun 3, 2026 -
Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian
Comma Separated Values - 8.3 KB -
MD5: 4493980d2875b797b1579e64e0790d69
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Jun 3, 2026 - Norwegian University of Life Sciences (NMBU)
Aunbakk, Nikolai, 2026, "Supplementary material for "Heterogeneity in postprandial glucose-insulin and triacylglycerol dynamics and associations with plasma metabolome and body composition in obesity"", https://doi.org/10.18710/ZT8XZ7, DataverseNO, V2
This supplementary material accompanies the manuscript “Heterogeneity in postprandial glucose–insulin and triacylglycerol dynamics and associations with plasma metabolome and body composition in obesity.” The data originate from the CARBFUNC clinical trial (ClinicalTrials.gov identifier: NCT03401970), which included 190 adults with abdominal obesit... |
Plain Text - 12.8 KB -
MD5: 200cbb90622729f675c21c0943408e28
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Jun 3, 2026 - TROLLing
De Timmerman, Romeo; Verbeke, Gil, 2026, "Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning", https://doi.org/10.18710/RDU8M2, DataverseNO, V1
Dataset description This dataset contains replication data for the study "Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning" (De Timmerman & Verbeke, 2026). The study investigates how binary perceptual annotations of monophthongal versus diphthongal /aɪ/ relate to measurable acoustic variat... |
Plain Text - 15.1 KB -
MD5: 2d15149d3af5d14653033961ed323449
File documenting the dataset and the contents of each data file. |
