2,941 to 2,950 of 137,605 Results
Oct 27, 2025 - University of Inland Norway
Tange, Ane Christensen; Sjølie, Hanne K., 2025, "Replication Data for: "Riparian forest buffer management: Evaluating adherence to certification standards"", https://doi.org/10.18710/KXJCJF, DataverseNO, V1
This dataset contains research data collected from 27 forest stand next to watercourses. The data was sampled from randomly selected stands in South-Eastern Norway focusing on species composition, stand structure, and site conditions. All stands were harvested in 2020 and 2021. All the stands were logged as clearcuts subject to The Programme for th... |
Oct 27, 2025 -
Replication Data for: "Riparian forest buffer management: Evaluating adherence to certification standards"
Plain Text - 6.5 KB -
MD5: 77583db63b5276d3f3912eafa8bb8edc
Description of the data set |
Oct 27, 2025 -
Replication Data for: "Riparian forest buffer management: Evaluating adherence to certification standards"
Comma Separated Values - 70.3 KB -
MD5: dd830462d1b914bd297fc44c20202aba
Stand, plot and tree data |
Oct 24, 2025 - Western Norway University of Applied Sciences
Ratliff, Hunter N., 2025, "PHITS simulations for miniNOVO design: Explorations of performance implications of design decisions for a demonstrator plastic-scintillator-based dual-particle detection system", https://doi.org/10.18710/KBZZ9T, DataverseNO, V1
This dataset contains simulation inputs and outputs from the PHITS (Particle and Heavy Ion Transport code System) general purpose Monte Carlo particle transport code used in design studies of the detector system developed within the NOVO project (Next generation imaging for real-time dose verification enabling adaptive proton therapy). The detector... |
Plain Text - 20.3 KB -
MD5: 00c9ec8d98cf0aa51986d6072e494738
|
Adobe PDF - 4.1 MB -
MD5: c24c3dc0e0c84357faa51cd04b2a49d4
|
Adobe PDF - 2.4 MB -
MD5: 4895105e7cc3f035316887883d91dde8
|
Adobe PDF - 115.1 KB -
MD5: a56f9be5c3c09bef67e5eb7848e57798
|
MS Excel Spreadsheet - 50.2 KB -
MD5: 451fdabc47b84913bfaf64a23df347c2
|
Adobe PDF - 775.3 KB -
MD5: 4cf06a0991f32a5d92ee8e2337741236
|
