cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48436/pkcsg-7e637
title: Modelled emissions, river loads and river concentrations for PFOA and PFOS in 2016/2017 in Austrian surface waters

description: The data set contains the emission per pathway into surface waters, the resulting annual river loads and the mean annual concentrations for the substances perfluorooctanoic acid (PFOA, CAS-No. 335-67-1) and perfluorooctanesulfonic acid (PFOS, CAS-No. 1763-23-1) for the years 2016 and 2017 modelled with the MoRE model (adapted from Fuchs et al. 2017) for Austria and some neighboring catchments.
Three variants of model results are available in the data set: The Median model variant giving the most probable values, based on median values for the model input data and a Best-case and Worst-case variant which are based on the first and third quartile of the input monitoring data.
The spatial resolution of the data are hydrologic catchments with an average size of 105 km². Emissions are sums of emissions for the respective catchment. River loads and river concentrations are valid for the main river at the respective catchment outlet (tributaries and main river within the catchments may have higher or lower concentrations).
CSV-files use semicolon as field delimiter and comma as decimal separator. The catchments are supplied as geodata in format of ESRI-Shapefile and Geography Markup Language (GML). The coordinate reference system is ETRS_1989_LAEA (EPSG-Code: 3035).
DOI: 10.48436/basmj-35g92
title: CAD files for 3D-printed well plates

description: Dataset contains CAD-files in stl format for 3D-printing of well plates with 6 inserts
DOI: 10.48436/cvv9h-tww97
title: Data and scripts for "General Shiba mapping for on-site four-point correlation functions"

description: This data repository contains the original figures, numerical (raw) data, scripts that where used to calculate this data, and plot scripts to reproduce the figures from the publication "General Shiba mapping for on-site four-point correlation functions" at Physical Review Research. The preprint is available on arXiv where also the LaTeX source files can be found. Additional information can be found in the README.

 

License

The CC-BY license applies to all the data and pdf files. All distributed code is under the MIT license.
DOI: 10.48436/hxzpq-zcp49
title: Numerical results for: Non-perturbative intertwining between spin and charge correlations: A "smoking gun" single-boson-exchange result

description: This data repository contains the original numerical (raw) data, and plot scripts to reproduce the figures from the publication "Non-perturbative intertwining between spin and charge correlations: A "smoking gun" single-boson-exchange result" at SciPost Physics.
The LaTeX source files of the preprint available on arXiv can be found at the TU gitlab.
Licenses
The data is licensed under CC BY 4.0, the code is licensed under MIT.
DOI: 10.48436/mpygj-6xt72
title: CAD files for 3D-printed well plates

description: Dataset contains CAD-files in stl format for 3D-printing of well plates with 6 inserts
DOI: 10.48436/t52d9-cne21
title: Numerical results for: Non-perturbative intertwining between spin and charge correlations: A "smoking gun" single-boson-exchange result

description: This data repository contains the original numerical (raw) data, and plot scripts to reproduce the figures from the publication "Non-perturbative intertwining between spin and charge correlations: A "smoking gun" single-boson-exchange result" at SciPost Physics.
The LaTeX source files of the preprint available on arXiv can be found at the TU gitlab.
Licenses
The data is licensed under CC BY 4.0, the code is licensed under MIT.
DOI: 10.48436/hynng-zdj28
title: IFC4.3 Beispiel mit IfcAlignment, Signal und Fahrbahn

description: Description:

Die vorliegenden IFC 4.3 Dateien stellen gemäß ISO 16739:2024 ein IfcAlignment mit Signalplatzierung und der Definition eines Fahrbahnbelags dar.

Context and methodology:

Sie wurden im Zuge der Bachelorarbeit "Analyse und Anwendung von Industry Foundation Classes IFC 4.3 für Linienbauwerke" entwickelt. Vorlageprojekte von buildingSMART und ACCA software bildeten die Grundlage für die Implementierung.
DOI: 10.48436/9eeve-r1z39
title: Virtual Annotated Cooking Environment Dataset - Ego Perspective

description: This dataset is the Ego Perspective version of the Virtual Annotated Cooking Environment Dataset (DOI: 10.48436/r5d7q-bdn48) and was recorded in the Virtual Annotated Cooking Environment (VACE), a new open-source virtual reality dataset (https://sites.google.com/view/vacedataset) and simulator (https://github.com/michaelkoller/vacesimulator) for object interaction tasks in a rich kitchen environment.  We use the Unity-based VR simulator to create thoroughly annotated video sequences of a virtual human avatar performing food preparation activities. Based on the MPII Cooking 2 dataset, it enables the recreation of recipes for meals such as sandwiches, pizzas, fruit salads and smaller activity sequences such as cutting vegetables. For complex recipes, multiple samples are present, following different orderings of valid partially ordered plans. The dataset includes an RGB and depth camera view, bounding boxes, object masks segmentation, human joint poses and object poses, as well as ground truth interaction data in the form of temporally labeled semantic predicates (holding, on, in, colliding, moving, cutting). In our effort to make the simulator accessible as an open-source tool, researchers are able to expand the setting and annotation to create additional data samples.
The research leading to these results has received funding from the Austrian Science Fund (FWF) under grant agreement No. I3969-N30 InDex and the project Doctorate College TrustRobots by TU Wien. Thanks go out to Simon Schreiberhuber for sharing his Unity expertise and to the colleagues at the TU Wien Center for Research Data Management for data hosting and support.
DOI: 10.48436/9y2x1-q4n71
title: Virtual Annotated Cooking Environment Dataset - Ego Perspective

description: This dataset is the Ego Perspective version of the Virtual Annotated Cooking Environment Dataset (DOI: 10.48436/r5d7q-bdn48) and was recorded in the Virtual Annotated Cooking Environment (VACE), a new open-source virtual reality dataset (https://sites.google.com/view/vacedataset) and simulator (https://github.com/michaelkoller/vacesimulator) for object interaction tasks in a rich kitchen environment.  We use the Unity-based VR simulator to create thoroughly annotated video sequences of a virtual human avatar performing food preparation activities. Based on the MPII Cooking 2 dataset, it enables the recreation of recipes for meals such as sandwiches, pizzas, fruit salads and smaller activity sequences such as cutting vegetables. For complex recipes, multiple samples are present, following different orderings of valid partially ordered plans. The dataset includes an RGB and depth camera view, bounding boxes, object masks segmentation, human joint poses and object poses, as well as ground truth interaction data in the form of temporally labeled semantic predicates (holding, on, in, colliding, moving, cutting). In our effort to make the simulator accessible as an open-source tool, researchers are able to expand the setting and annotation to create additional data samples.
The research leading to these results has received funding from the Austrian Science Fund (FWF) under grant agreement No. I3969-N30 InDex and the project Doctorate College TrustRobots by TU Wien. Thanks go out to Simon Schreiberhuber for sharing his Unity expertise and to the colleagues at the TU Wien Center for Research Data Management for data hosting and support.
DOI: 10.48436/p7fh3-ca180
title: Virtual Annotated Cooking Environment Dataset

description: This dataset was recorded in the Virtual Annotated Cooking Environment (VACE), a new open-source virtual reality dataset (https://sites.google.com/view/vacedataset) and simulator (https://github.com/michaelkoller/vacesimulator) for object interaction tasks in a rich kitchen environment.  We use the Unity-based VR simulator to create thoroughly annotated video sequences of a virtual human avatar performing food preparation activities. Based on the MPII Cooking 2 dataset, it enables the recreation of recipes for meals such as sandwiches, pizzas, fruit salads and smaller activity sequences such as cutting vegetables. For complex recipes, multiple samples are present, following different orderings of valid partially ordered plans. The dataset includes an RGB and depth camera view, bounding boxes, object masks segmentation, human joint poses and object poses, as well as ground truth interaction data in the form of temporally labeled semantic predicates (holding, on, in, colliding, moving, cutting). In our effort to make the simulator accessible as an open-source tool, researchers are able to expand the setting and annotation to create additional data samples.
The research leading to these results has received funding from the Austrian Science Fund (FWF) under grant agreement No. I3969-N30 InDex and the project Doctorate College TrustRobots by TU Wien. Thanks go out to Simon Schreiberhuber for sharing his Unity expertise and to the colleagues at the TU Wien Center for Research Data Management for data hosting and support.
DOI: 10.48436/r5d7q-bdn48
title: Virtual Annotated Cooking Environment Dataset

description: This dataset was recorded in the Virtual Annotated Cooking Environment (VACE), a new open-source virtual reality dataset (https://sites.google.com/view/vacedataset) and simulator (https://github.com/michaelkoller/vacesimulator) for object interaction tasks in a rich kitchen environment.  We use the Unity-based VR simulator to create thoroughly annotated video sequences of a virtual human avatar performing food preparation activities. Based on the MPII Cooking 2 dataset, it enables the recreation of recipes for meals such as sandwiches, pizzas, fruit salads and smaller activity sequences such as cutting vegetables. For complex recipes, multiple samples are present, following different orderings of valid partially ordered plans. The dataset includes an RGB and depth camera view, bounding boxes, object masks segmentation, human joint poses and object poses, as well as ground truth interaction data in the form of temporally labeled semantic predicates (holding, on, in, colliding, moving, cutting). In our effort to make the simulator accessible as an open-source tool, researchers are able to expand the setting and annotation to create additional data samples.
The research leading to these results has received funding from the Austrian Science Fund (FWF) under grant agreement No. I3969-N30 InDex and the project Doctorate College TrustRobots by TU Wien. Thanks go out to Simon Schreiberhuber for sharing his Unity expertise and to the colleagues at the TU Wien Center for Research Data Management for data hosting and support.
DOI: 10.48436/8gs29-07743
title: NMR data and fluorescence microscopy data

description: The provided data includes the FID files for all recorded NMR spectra and all fluorescence microscopy images as reported in 10.1002/cbic.202200363 (freely accessible). The NMR datasets are organized as obtained directly after the measurement, allowing further processing with commonly used software. The files and folders are named after the original experiment. For the assignment of the data to the respective compound numbers as specified in 10.1002/cbic.202200363 please see the provided PDF file ‘file_names_for_compound_numbers.pdf’. In addition, copies of the spectra are provided in the PDF file ‘NMR_spectra_and_file_names.pdf’.

Fluorescene microscopy images are provided as TIF files.

For details on the used compounds and all compound numbers see 10.1002/cbic.202200363.

 

Technical information

- NMR: 1H and 13C NMR spectra were recorded on a Bruker Ascend 600 MHz spectrometer at 20 °C.

- Fluorescence microscopy: HT1080 cells were seeded into a 96-well plate at 3,000 cells per well and allowed to grow overnight. The medium was removed, and the cells were treated with a 200 nM solution of sulfo-cTCO-DMEDA-CA4 (compound 12) in media. In situ click-to-release was initiated by addition of DMT (compound 7) at a final concentration of 10 µM. As controls, cells were left untreated or incubated with either the parent drug CA4 (200 nM) or 10 µM DMT (compound 7). After an incubation time of 6 h cells were stained with SiR-tubulin (a fluorogenic, cell permeable and highly specific probe for microtubules). An 11X stock solution of the probe was directly added to the growth medium to obtain a final concentration of 1 µM and incubation was carried out for 1 h. Subsequently, the medium was removed, and cells were stained with Hoechst 33342 nuclear dye (Invitrogen, 5 µM in growth medium) for 10 minutes and washed once with PBS. Multichannel imaging of the cells was carried out in FluoroBrite DMEM medium (Gibco) on an Olympus IX82 microscope.

 

Summary of results

- NMR: The obtained data confirmed the chemical structures of all synthesized compounds. Results of data analysis are provided in 10.1002/cbic.202200363 (freely accessible).

- Fluorescence microscopy: Cell imaging via fluorescence microscopy (scale bars: 50 µm) upon staining with Hoechst 33342 (blue, nuclei) and SiR-tubulin (red, microtubules) shows comparable depletion of tubulin signals after 6 h treatment with CA4 (200 nM) or bioorthogonal activation of prodrug 12 (200 nM) by in situ reaction with DMT (compound 7). No significant change (compared to untreated cells) was observed after treatment with DMT (compound 7) or prodrug 12.
DOI: 10.48436/zpd37-97a95
title: Wayfinding Stages: The Role of Familiarity, Gaze Events, and Visual Attention

description: How to Cite?

The paper is accepted for presenetation at COSIT2024, but it is not yet published.

Abstract

Understanding the cognitive processes involved in wayfinding is crucial for both theoretical advances and practical applications in navigation systems development. This study explores how gaze behavior and visual attention contribute to our understanding of cognitive states during wayfinding. Based on the model proposed by Downs and Stea, which segments wayfinding into four distinct stages: self-localization, route planning, monitoring, and goal recognition, we conducted an outdoor wayfinding experiment with 56 participants. Given the significant role of spatial familiarity in wayfinding behavior, each participant navigated six different routes in both familiar and unfamiliar environments, with their eye movements being recorded. We provide a detailed examination of participants’ gaze behavior and the actual objects of focus. Our findings reveal distinct gaze behavior patterns and visual attention, differentiating wayfinding stages while emphasizing the impact of spatial familiarity. This examination of visual engagement during wayfinding explains adaptive cognitive processes, demonstrating how familiarity influences navigation strategies. The results enhance our theoretical understanding of wayfinding and offer practical insights for developing navigation aids capable of predicting different wayfinding stages. 

Data

The data used in this paper is a CSV file (licensed under CC BY 4.0) that contains the following information:



world_index: the scene video frame index

fixation_duration: duration of the fixation

x_fixation: corrected x coordinate of the fixation from the head movement impact

y_fixation: corrected y coordinate of the fixation from the head movement impact

synced_timestamp: timestamp of the event

stage: the wayfinding stage according to Downs and Stea theory 

yolo_label: predicted label by Yolo

segmentation_label: predicted label by Mask2Former

semantic_label: the selected semantic label detected by MYFix

duration: duration of the stage

saccade_duration: duration of the corrected saccade

saccade_length: length of the corrected saccade

participant_id: anonymized id for the participants

familiarity: spatial familiarity of the participants (binary)

routeID: id of the routes
DOI: 10.48436/ez2zc-pqa36
title: Measurements of hydro-chemical parameters and selected trace contaminants in water samples within the Wulka river estuary and two littoral transects of Lake Neusiedl

description: The dataset contains the results of the chemical analyses carried out in water samples collected in three areas of the Lake Neusiedl (in the estuary of the main tributary Wulka and in two transects from the open lake to isolated sampling sites within the reed belt on the western and eastern shores) between October 2017 and September 2019 within the Interreg project REBEN.
The data set is composed of two data files containing:

measurements for the traditional hydro-chemical parameters: general physico-chemical parameters (water temperature: WT, dissolved oxygen: DO, electric conductivity: EC, pH), main ions (calcium: Ca2+, magnesium: Mg2+, sodium: Na+, potassium: K+, chloride: Cl–, sulphate-sulphur: SO4-S), acid-neutralizing capacity (ANC), phosphorus (total: TP, dissolved: DP, soluble reactive: SRP, soluble unreactive: SUP, particulate: PP), nitrogen (total: TN, dissolved organic: DON, nitrate-nitrogen: NO3-N, nitrite-nitrogen: NO2-N, ammonium-nitrogen: NH4-N, particulate: PN), soluble reactive silica (SRSi), total organic carbon (TOC), dissolved organic carbon (DOC),  suspended solids (particulate matter: PM, particulate inorganic matter: PIM, particulate organic matter: POM), and chlorophyll-a (Chl a);
measurements for selected trace contaminants: metals (cadmium: Cd, copper: Cu, lead: Pb, mercury: Hg, nickel: Ni, zinc: Zn), two industrial organic chemicals (perfluorooctanoic acid: PFOA, CAS 335-67-1 and perfluorooctanesulfonic acid: PFOS, CAS 1763-23-1), the sweetener Acesulfame K (CAS 55589-62-3) and two pharmaceuticals (Carbamazepine, CAS 298-46-4 and Diclofenac, CAS 15307-86-5).
CSV-files use semicolon as field delimiter and comma as decimal separator.
DOI: 10.48436/v8amh-ka560
title: Measurements of hydro-chemical parameters and selected trace contaminants in water samples within the Wulka river estuary and two littoral transects of Lake Neusiedl

description: The dataset contains the results of the chemical analyses carried out in water samples collected in three areas of the Lake Neusiedl (in the estuary of the main tributary Wulka and in two transects from the open lake to isolated sampling sites within the reed belt on the western and eastern shores) between October 2017 and September 2019 within the Interreg project REBEN.
The data set is composed of two data files containing:

measurements for the traditional hydro-chemical parameters: general physico-chemical parameters (water temperature: WT, dissolved oxygen: DO, electric conductivity: EC, pH), main ions (calcium: Ca2+, magnesium: Mg2+, sodium: Na+, potassium: K+, chloride: Cl–, sulphate-sulphur: SO4-S), acid-neutralizing capacity (ANC), phosphorus (total: TP, dissolved: DP, soluble reactive: SRP, soluble unreactive: SUP, particulate: PP), nitrogen (total: TN, dissolved organic: DON, nitrate-nitrogen: NO3-N, nitrite-nitrogen: NO2-N, ammonium-nitrogen: NH4-N, particulate: PN), soluble reactive silica (SRSi), total organic carbon (TOC), dissolved organic carbon (DOC),  suspended solids (particulate matter: PM, particulate inorganic matter: PIM, particulate organic matter: POM), and chlorophyll-a (Chl a);
measurements for selected trace contaminants: metals (cadmium: Cd, copper: Cu, lead: Pb, mercury: Hg, nickel: Ni, zinc: Zn), two industrial organic chemicals (perfluorooctanoic acid: PFOA, CAS 335-67-1 and perfluorooctanesulfonic acid: PFOS, CAS 1763-23-1), the sweetener Acesulfame K (CAS 55589-62-3) and two pharmaceuticals (Carbamazepine, CAS 298-46-4 and Diclofenac, CAS 15307-86-5).
CSV-files use semicolon as field delimiter and comma as decimal separator.
DOI: 10.48436/mczqb-mx896
title: Numerical results for "Compressing the two-particle Green's function using wavelets: Theory and application to the Hubbard atom"

description: This data repository contains the original figures, numerical (raw) data, and plot scripts to reproduce the figures from the publication "Compressing the two-particle Green's function using wavelets: Theory and application to the Hubbard atom" in the European Physical Journal Plus. LaTeX source files of the preprint can be found on the corresponding arXiv page.

Licenses

The CC-BY license applies to all the data. All distributed code is under the MIT license.
DOI: 10.48436/2cd8d-bmd42
title: Hydro-sedimentary processes of a plunging hyperpycnal river plume revealed by synchronized remote imagery and gridded current measurements - supporting data and scripts

description: Dataset description
Raw and treated data reported in the paper "Hydro-sedimentary processes of a plunging hyperpycnal river plume revealed by synchronized remote imagery and gridded current measurements" can be downloaded here for validation and further analysis. The scripts used to open, treat and visualize the data are included, as well as the figures included in the paper and the underlying data. The structure and contents of the folders are described in the README file. In order to run the scripts (.m) and open some of the treated data (.mat) successfully, the MATLAB software package is necessary. The MATLAB scripts are based on and include scripts from the adcptools software package (Bart Vermeulen, 2015; Vermeulen et al., 2014; https://sourceforge.net/projects/adcptools/).
All data are protected under the Creative Commons Attribution 4.0 International license. All scripts are protected under the GNU General Public License v3.0 (or later).
DOI: 10.48436/pvq67-tkf44
title: Hydro-sedimentary processes of a plunging hyperpycnal river plume revealed by synchronized remote imagery and gridded current measurements - supporting data and scripts

description: Dataset description
Raw and treated data reported in the paper "Hydro-sedimentary processes of a plunging hyperpycnal river plume revealed by synchronized remote imagery and gridded current measurements" can be downloaded here for validation and further analysis. The scripts used to open, treat and visualize the data are included, as well as the figures included in the paper and the underlying data. The structure and contents of the folders are described in the README file. In order to run the scripts (.m) and open some of the treated data (.mat) successfully, the MATLAB software package is necessary. The MATLAB scripts are based on and include scripts from the adcptools software package (Bart Vermeulen, 2015; Vermeulen et al., 2014; https://sourceforge.net/projects/adcptools/).
All data are protected under the Creative Commons Attribution 4.0 International license. All scripts are protected under the GNU General Public License v3.0 (or later).