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UnrealGaussianStat: Synthetic dataset for statistical analysis on Novel View Synthesis
No full textThe dataset comprises three dynamic scenes characterized by both simple and complex lighting conditions. The quantity of cameras ranges from 4 to 512, including 4, 6, 8, 10, 12, 14, 16, 32, 64, 128, 256, and 512. The point clouds are randomly generated
Replication Data for: Wake merging and turbulence transition downstream of side-by-side porous discs
No full textThese are the streamwise velocity time series measured in the wakes of two sets of porous discs in side-by-side setting as used in the manuscript ``Wake merging and turbulence transition downstream of side-by-side porous discs´´ which is accepted by Journal of Fluid Mechanics.
Data was obtained by means of hot-wire anemometry in the Large Scale Wind Tunnel at the Norwegian University of Science and Technology in near-laminar inflow (background turbulence intensity of approximately 0.3%) at an inflow velocity of 10m/s (diameter-based Reynolds number 125000). Two types of porous discs with diameters D = 0.2m, one with uniform blockage and one with radially changing blockage, were used. Three spacings, namely 1.5D, 2D and 3D, were investigated. Span-wise profiles were measured at 8D and 30D downstream for each case, and a streamwise profile along the centerline between the discs was additionally obtained.
In addition, measurements downstream of both disc types (singe disc setting) are provided as comparison.
The scope of these experiments was to study the merging mechanisms of the turbulence when the two wakes are meeting
Height (H) map for 2020
No full textThis dataset provides a high-resolution (10 m) pan-European map of forest Height (H) for the year 2020, along with an accompanying standard deviation layer. It is part of the PathFinder collection of forest structure maps, which integrates Sentinel-2 satellite imagery, auxiliary geospatial layers, and National Forest Inventory (NFI) data to deliver detailed forest attribute predictions across Europe. The map supports applications in forest management, biomass estimation, carbon accounting, and ecological modeling. For methodology and data integration details, see the documentation dataset of the PathFinder collection (https://doi.org/10.18710/OEYKEG) and the following publication: Miettinen, J., Breidenbach, J. et al. (2025). PathFinder's High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data. Zenodo. https://doi.org/10.5281/zenodo.17107267
Replication data for: Measure schematicity through information content: A quantitative approach to grammaticalization
No full textThis is a study to propose a quantitative method to compute the schematicity of constructions, which is a key indicator of the level of grammaticalization of morphemes. In this method, to estimate the schematicity of a schema made up of two morphemes, i.e., X_ (X is the target morpheme and _ represents an open slot), we need to know the total token frequency of all types of X_, and the token frequencies of all kinds of elements occurring in the open slot. For example, if we are interested in the schematicity of “_ment”. We need to know the total token frequency of “_ment”, which is the sum of the frequencies of “shipment”, “equipment”, “employment”, “appointment” … (all types of “_ment”). We also need to know the token frequencies of “ship”, “equip”, “employ”, “appoint” … (all types of elements occurring in the open slot). Therefore, the data are morpheme bigrams (2-gram) generated from the English and Chinese corpora showing what morphemes can each morpheme combine with, together with the token frequency of each bigram, and the token frequencies of its two components respectively
Picea (P_Pic) map for 2020
No full textThis dataset provides a high-resolution (10 m) pan-European map of forest Picea (P_Pic) for the year 2020, along with an accompanying standard deviation layer. It is part of the PathFinder collection of forest structure maps, which integrates Sentinel-2 satellite imagery, auxiliary geospatial layers, and National Forest Inventory (NFI) data to deliver detailed forest attribute predictions across Europe. The map supports applications in forest management, biomass estimation, carbon accounting, and ecological modeling. For methodology and data integration details, see the documentation dataset of the PathFinder collection (https://doi.org/10.18710/OEYKEG) and the following publication: Miettinen, J., Breidenbach, J. et al. (2025). PathFinder's High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data. Zenodo. https://doi.org/10.5281/zenodo.17107267
German universal concessive conditionals with wh-clause-initial and wh-clause-medial marking
No full textThese are the data analysed in Chapter 6 of Vander Haegen's dissertation entitled "Konstruktionsgrammatik und Variation. Eine Mikrotypologie universaler Irrelevanzgefüge im Gegenwartsdeutschen".
The dataset includes an annotated sample of N = 3000 German written universal concessive conditionals (e.g. "Was immer auch passiert, ich bin für dich da!" 'Whatever happens, I will be there for you!') from the German Reference Corpus DeReKo. Concessive conditionals (CCs) can basically be defined as conditionals with quantification, as they express a (usually exhaustive) set of antecedent values in the protasis, instead of only one antecedent value as in prototypical conditionals. In universal concessive conditionals (UCCs), the antecedent set is evoked through a combination of a free-choice-expression (here: the complex particle "immer auch" '-ever') and a variable in the guise of a wh word (here: "was" 'what').
German UCCs can either be marked wh-clause-medially (using the particles "auch" and/or "immer" as above – both mean '-ever') or wh-clause-initially (with an expression of irrelevance like "egal" 'no matter', "gleichgültig" 'no matter', "wurscht' 'no matter (lit.: sausage) etc.). The wh-clause-initial and -medial marking strategies are in near-complementary distribution.
The dataset was compiled in the context of a doctoral dissertation project which sought to, inter alia, determine functional and formal differences (apart from the position and lexical specification of the free-choice marking) between wh-clause-initially and -medially marked UCCs in contemporary German. It comprises n = 1500 tokens of wh-clause-initially and n = 1500 tokens of wh-clause-medially marked UCCs. The data are annotated for over 20 formal and functional variables.
The full dataset (including the corpus data) and a dataset including only ID numbers and annotations (to facilitate processing with statistical software) are shared in two separate .csv-files. An R Markdown file with the data analysis and an html file with the R code and output are shared as well.<p
Medium-Frequency Acoustic Attenuation and Natural Convection in Nanofluids: Effect of Aggregate Size (ONESTEP)
No full textThis dataset contains acoustic information generated for the ONESTEP MSCA project relating to the attenuation of medium-frequency acoustic signals in carbon nanofluids. In ONESTEP (May 2023 to October 2025), we were interested in understanding the physics of photothermal boiling (boiling with light) through non-invasive acoustic techniques. However, early results indicated that higher frequencies were attenuated substantially, leading to further investigation and this dataset.
The specific contents of this dataset are all relevant acoustic data (namely, amplitudes and frequencies) and data not used in the publication that were generated in the AEwin software (e.g., rise time, RMS, etc.). It is a stand-alone dataset and contains all relevant data to re-produce the associated publication or be reused for other research interests. Note that both the .DTA (AEwin software) and .CSV (plain text) file formats are available. See the Read Me file for further information
PHITS simulations for miniNOVO design: Explorations of performance implications of design decisions for a demonstrator plastic-scintillator-based dual-particle detection system
No full textThis 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 system is composed of an array of long bars (rectangular prisms) made of a plastic scintillation material that produces light when radiation interacts with it. This light is detected by readout electronics placed on the ends of each bar, and further processing ultimately allows determination of where the interaction occurred along the bar's length, when it happened, and how much energy was deposited in the interaction, all these values with some level of systematic uncertainty. In simulation, however, none of these uncertainties are present, allowing iterative design of the detector system in ideal conditions (not to mention at substantially lower costs and times than doing so experimentally). The ultimate goal of this information—from the detected secondary radiation (fast neutrons and prompt gamma rays) produced by the proton beam in the patient—is to be used in reconstruction of the proton beam's range (stopping location) and dose inside a patient, to verify that the treatment actually delivered conforms to the treatment planned. More information about the NOVO project can be found at: https://www.novo-project.eu/about
The simulations in this dataset form the basis of early design studies testing various sizes, spacings, quantities, and arrangements of bars for smaller-scale versions of the final envisioned NOVO detector array, helping the project make design decisions for its "demonstrator" detector system developed and iterated upon, ultimately culminating in a neutron imaging experiment at the Physikalisch-Technische Bundesanstalt (PTB) Braunschweig. These simulations, rather than studying imaging, sought to inform design decisions by providing information on relative event rates, detection efficiency, time/energy/flightpath-distance distributions, etc. to better understand how various design decisions (bar length, width, spacing, arrangement, etc.) impacted these raw physical values (which subsequently would impact imaging performance)
Regnbed langs veg og gate i nordisk klima : utforming og vegetasjon
No full textExamination of the optimal design of rain gardens in road environments in Nordic climates, with a particular focus on suitable plant species and soil properties. The background is the increasing occurrence of extreme rainfall due to climate change, as well as the growing need for nature-based solutions to mitigate flooding. Despite the rising interest in rain gardens as a stormwater management solution, there is limited knowledge about which designs works best in road environments within Nordic climates. This dataset supports a thesis addressing this knowledge gap through field and case studies, particularly focusing on the first large-scale implementation of rain gardens in a street environment in Norway, at Bjørnstjerne Bjørnsons Street in Drammen. Additionally, supplementary investigations were conducted at Kanalveien in Bergen
Quadratic mean diameter (DBH) map for 2020
No full textThis dataset provides a high-resolution (10 m) pan-European map of forest Quadratic mean diameter (DBH) for the year 2020, along with an accompanying standard deviation layer. It is part of the PathFinder collection of forest structure maps, which integrates Sentinel-2 satellite imagery, auxiliary geospatial layers, and National Forest Inventory (NFI) data to deliver detailed forest attribute predictions across Europe. The map supports applications in forest management, biomass estimation, carbon accounting, and ecological modeling. For methodology and data integration details, see the documentation dataset of the PathFinder collection (https://doi.org/10.18710/OEYKEG) and the following publication: Miettinen, J., Breidenbach, J. et al. (2025). PathFinder's High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data. Zenodo. https://doi.org/10.5281/zenodo.17107267