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6,691 to 6,700 of 146,502 Results
01_emoce.cz.csv
May 14, 2026 - Replication Data for: “Emotions in Context: A Semantic Field Viewed through Grammar and Collocation”
Comma Separated Values - 3.9 KB - MD5: 30e92bc08ffbb3fb48f20fef7e9c0802
This is the .csv file containing the data with the original Czech nouns.
02_emoce.en.csv
May 14, 2026 - Replication Data for: “Emotions in Context: A Semantic Field Viewed through Grammar and Collocation”
Comma Separated Values - 4.0 KB - MD5: 64a55e3a5492b3fbfc0c58afbbbeb532
This is the .csv file containing the data with (approximate) English equivalents.
03_Emoce.EURALEX.Rmd
May 14, 2026 - Replication Data for: “Emotions in Context: A Semantic Field Viewed through Grammar and Collocation”
R Notebook - 3.4 KB - MD5: 5b488c29c4e7a5ac9cae07bd1547a29d
This is the R markdown script for the analysis of 01_emoce.cz.csv and 02_emoce.en.csv.
04_Emoce.EURALEX.pdf
May 14, 2026 - Replication Data for: “Emotions in Context: A Semantic Field Viewed through Grammar and Collocation”
Adobe PDF - 584.5 KB - MD5: b63d4686de7ea9dfdd4c5c6cd4a152a0
This is the text of the R markdown script for the analysis of 01_emoce.cz.csv and 02_emoce.en.csv.
Background Data for: "UAV Icing: Numerical Simulations of Electrothermal Wing De-icing with Shedding Prediction"
May 10, 2026 - NTNU – Norwegian University of Science and Technology
Wallisch, Joachim; Hann, Richard, 2026, "Background Data for: "UAV Icing: Numerical Simulations of Electrothermal Wing De-icing with Shedding Prediction"", https://doi.org/10.18710/OAY9A2, DataverseNO, V2
This dataset contains the summarized simulation results used in the paper "UAV Icing: Numerical Simulations of Electrothermal Wing De-icing with Shedding Prediction". The aim of the paper is to numerically predict ice shedding from a wing with an electrothermal de-icing system. Based on experimental results, shedding is modeled when 76% of the inte...
00_Readme.txt
May 10, 2026 - Background Data for: "UAV Icing: Numerical Simulations of Electrothermal Wing De-icing with Shedding Prediction"
Plain Text - 7.0 KB - MD5: d68885067285923fc940f856bb629597
minus10_threshold76.csv
May 10, 2026 - Background Data for: "UAV Icing: Numerical Simulations of Electrothermal Wing De-icing with Shedding Prediction"
Comma Separated Values - 3.0 KB - MD5: b536b8136b187a35e37dc0e27bdff00a
minus5_threshold76.csv
May 10, 2026 - Background Data for: "UAV Icing: Numerical Simulations of Electrothermal Wing De-icing with Shedding Prediction"
Comma Separated Values - 2.4 KB - MD5: d7977e38165f50753f1aa7d0e9a4382b
threshold_identification.csv
May 10, 2026 - Background Data for: "UAV Icing: Numerical Simulations of Electrothermal Wing De-icing with Shedding Prediction"
Comma Separated Values - 645 B - MD5: 4c905fff53db5f16aff2947ef7b3e437
Boosting Zinc-Ion Hybrid Capacitors with Mesoporous Carbon Derived from Highly Graphitized Carbon Quantum Dots
May 8, 2026 - University of South-Eastern Norway
zhang, guoli, 2026, "Boosting Zinc-Ion Hybrid Capacitors with Mesoporous Carbon Derived from Highly Graphitized Carbon Quantum Dots", https://doi.org/10.18710/6FDKP9, DataverseNO, V1
This dataset contains electrochemical and structural characterization data that support the following publication: Zhang G., Li H., Wang K., Li G., Li K., Guan T., Wang K. Boosting Zinc-Ion Hybrid Capacitors with Mesoporous Carbon Derived from Highly Graphitized Carbon Quantum Dots. Energy & Environmental Materials, 2026. The dataset includes cycli...
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