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379 research outputs found
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VINNA for Neonates - Orientation Independence through Latent Augmentations
No full textTraining checkpoints for VINNA4neonates (https://github.com/Deep-MI/VINNA4neonates) - please cite the paper when using this resource (https://arxiv.org/abs/2311.17546)
LTER Zöbelboden, Austria, Runoff Water Chemistry, 2020
No full textRunoff water chemistry data of the LTER station Zöbelboden from the year 202
LTER Zöbelboden, Austria, Runoff Water Chemistry, 2022
No full textRunoff water chemistry data of the LTER station Zöbelboden from the year 202
FastSurfer-HypVINN Segmentation Models for Sub-Segmentation of the Hypothalamus and Adjacent Sctructures
No full textThe hypothalamus plays a crucial role in the regulation of a broad range of physiological, behavioral, and cognitive functions. However, despite its importance, only a few small-scale neuroimaging studies have investigated its substructures, likely due to the lack of fully automated segmentation tools to address scalability and reproducibility issues of manual segmentation. While the only previous attempt to automatically sub-segment the hypothalamus with a neural network showed promise for 1.0 mm isotropic T1-weighted (T1w) magnetic resonance imaging (MRI), there is a need for an automated tool to sub-segment also high-resolutional (HiRes) MR scans, as they are becoming widely available, and include structural detail also from multi-modal MRI. We, therefore, introduce a novel, fast, and fully automated deep-learning method named HypVINN for sub-segmentation of the hypothalamus and adjacent structures on 0.8 mm isotropic T1w and T2w brain MR images that is robust to missing modalities. We extensively validate our model with respect to segmentation accuracy, generalizability, in-session test-retest reliability, and sensitivity to replicate hypothalamic volume effects (e.g., sex differences). The proposed method exhibits high segmentation performance both for standalone T1w images as well as for T1w/T2w image pairs. Even with the additional capability to accept flexible inputs, our model matches or exceeds the performance of state-of-the-art methods with fixed inputs. We, further, demonstrate the generalizability of our method in experiments with 1.0 mm MR scans from both the Rhineland Study and the UK Biobank—an independent dataset never encountered during training with different acquisition parameters and demographics. Finally, HypVINN can perform the segmentation in less than a minute (graphical processing unit [GPU]) and will be available in the open source FastSurfer neuroimaging software suite, offering a validated, efficient, and scalable solution for evaluating imaging-derived phenotypes of the hypothalamus.Training checkpoints for HypVINN (https://github.com/Deep-MI/FastSurfer) - please cite the paper when using this resource (https://doi.org/10.1162/imag_a_00034)
LTER Zöbelboden, Austria, Runoff Water Chemistry, 2021
No full textRunoff water chemistry data of the LTER station Zöbelboden from the year 202
Long-term monitoring of plant diversity data in the “Montagna di Torricchio” strict Nature Reserve, Italy
No full textLong-term monitoring is pivotal to fully understanding spatio-temporal changes in plant diversity, particularly in protected areas. Here we present a dataset including plant presence and abundance data collected using a probabilistic sampling design in the “Montagna di Torricchio” Nature strict Reserve, central Apennines, Italy. Five surveys were conducted in 35 plots during a period spanning 22 years (2002-2024). The dataset allows to study plant diversity changes over space and time across different habitat types by using statistical inference based on solid sampling theory
LTER Zöbelboden, Austria, Runoff Water Chemistry, 2019
No full textRunoff water chemistry data of the LTER station Zöbelboden from the year 201
Novel Signatures of Radiation Reaction in Electron-Laser Sidescattering
No full textIn this article we investigate novel signatures of radiation reaction via the angular deflection of an electron beam colliding at 90 degrees with an intense laser pulse. Due to the radiation reaction effect, the electrons can be deflected towards the beam axis for plane wave backgrounds, which is not possible in the absence of radiation reaction effects. The magnitude and size of the deflection angle can be controlled by tailoring the laser pulse shapes. The effect is first derived analytically using the Landau-Lifshitz equation, which allows to determine the important scaling behavior with laser intensity and particle energy. We then move on to full scale 3D Monte Carlo simulations to verify the effect is observable with present day laser technology. We investigate the opportunities for an indirect observation of laser depletion in such side scattering scenarios.
This record contains the SMILEI namelists for the 1D and 3D simulations we have performed for this study. The open source particle-in-cell code SMILEI which we employed for our study can be found here: https://github.com/SmileiPIC/Smile
DEIMS-SDR - Geodata Collection - July 2024
No full textThis record contains the boundaries and centroid/representative coordinates of all sites registered on DEIMS-SDR (www.deims.org). The provided shapefiles include information about the location and extent of sites as well as their names and IDs. This record will be updated periodically to reflect the stable snapshots of the geodata on DEIMS-SDR. The purpose of this record is to provide researchers with a simple way to have access to the geodata of DEIMS-SDR. While we aim for highest accuracy, we cannot guarantee that the provided information is always completely accurate. For the very latest version of geodata, please download the respective coordinates or boundaries from DEIMS.org.
For further information (citation, data licence, disclaimer) please refer to the following pages:
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CoE RAISE - data for actuated turbulent boundary layer flows
No full textThis data collection contains time-series of three-dimensional snapshots for a parametric study of flat plate turbulent boundary layer flow actuated by spanwise traveling transversal surface waves with the goal of friction drag reduction.Details regarding the numerical setup and the structure of the data are given at https://www.coe-raise.eu/od-tbl