411 to 420 of 495 Results
Jan 29, 2026 -
Replication Data for: Sensor Comparison for Multi-Modal Motion Estimation in Upper Body Stroke Rehabilitation
ZIP Archive - 71.1 MB -
MD5: 0cd926ab063aa0c8de4ec7b6f9ab0cd1
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Jan 29, 2026 -
Replication Data for: Sensor Comparison for Multi-Modal Motion Estimation in Upper Body Stroke Rehabilitation
ZIP Archive - 54.8 MB -
MD5: 95d9dc03ad1c9f8f82abc8ebedefd58a
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Plain Text - 2.5 KB -
MD5: 480ccc2a243e5f67d945bb91a2944fb7
README file generated by DataverseUrge |
Jan 26, 2026 - University of Oslo
Konestabo, Heidi Sjursen, 2026, "Supporting data for: Prior pesticide exposure reduces drought tolerance in Arctic and temperate springtails – effects of sequential stressors", https://doi.org/10.18710/ZOE3EA, DataverseNO, V1
This dataset was collected as part of the MULTICLIM project at the University of Oslo: https://www.mn.uio.no/ibv/english/research/sections/aqua/research-projects/144612/ The dataset contains raw data from experiments investigating the combined effects of imidacloprid, drought and increased temperature on the survival of two different springtail spe... |
Plain Text - 9.5 KB -
MD5: bfb9590bd63cf4d19ad2838fe9ee80cd
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Plain Text - 57.6 KB -
MD5: 3ec186ec80b7021d04195814baf79807
measurements of relative humidity and temperature |
Plain Text - 703 B -
MD5: 789a4e5c9ae7eb1ec004dac4cf0a1ff7
Nominal and measured concentrations of imidacloprid |
Plain Text - 18.6 KB -
MD5: ccc4fa80af048581b23e0145d1cd9eb0
Survival data for Hypogastrura viatica |
Plain Text - 13.0 KB -
MD5: e02578781db9c116b4d37484a20d4444
Survival data for Folsomia quadrioculata |
Jan 23, 2026 - UiT The Arctic University of Norway
Sartipzadeh, Kian; Kvammen, Andreas; Gustavsson, Björn; Gulbrandsen, Njål; Johnsen, Magnar G.; Huyghebaert, Devin; Vierinen, Juha, 2026, "Replication Data for: Plasma Density Estimation from Ionograms and Geophysical Parameters with Deep Learning", https://doi.org/10.18710/CFSVA2, DataverseNO, V1
This dataset contains the replication data and code for the article "Plasma Density Estimation from Ionograms and Geophysical Parameters with Deep Learning". The project introduces "Kian-Net", a deep learning model designed to estimate electron density profiles in the ionosphere by fusing ionogram images with geophysical parameters. The Kian-Net mo... |
