data_UMR
Aaron Beller
Welcome to data_UMR!
Data_UMR is a cross faculty publication hub. We collect scientific resources and research data from members of Philipps-University Marburg and make it openly accessible. To ensure high standards of quality and re-usability, submissions to data_UMR are subject to curation.
Select a community to browse its collections.
Recent Submissions
Dopamine D2 receptor antagonism modulates antidepressant placebo effects on reward sensitivity in healthy participants
(Philipps-Universität Marburg) Augustat, Nick; Lee, Eunhwi; Ahn, Woo-Young; Chuang, Li-Ching; Endres, Dominik; Müller, Erik Malte
Content: Open code and data for the manuscript "Augustat, N., Lee, E., Ahn, W. Y., Chuang, L. C., Endres, D., Mueller, E.: Dopamine D2 receptor antagonism modulates antidepressant placebo effects on reward sensitivity in healthy participants". Instructions can be found in the file "readme.txt", and a preprint in the file "RL_Manuscript.tar".
Summary: The data set consists of 272 participants allocated in a 2x2 between-subjects design (expectation: high/low, substance: placebo/sulpiride 400mg) who performed a probabilistic selection task. We fit a total of 74 hierarchical Bayesian reinforcement learning models with different sets of parameters to participants' choice data and conducted a model comparison, including recovery checks, across all models. The winning model consisted of three parameters (learning rate, inverse temperature, forgetting rate) and yielded an increase in learning rates under high expectations in the placebo group but not in the sulpiride group. Higher learning rates may indicate an increase in reward sensitivity, suggesting an expectation-induced improvement in reward sensitivity. Sulpiride 400mg blocked this effect, supporting a modulatory role of dopamine.
Evaluation zum Workshop "Openness in the Higher Education Classroom – Perspektivenvielfalt für offene Lehre"
(Philipps-Universität Marburg) Hercher, Sophia; Riedl, Lydia; Binder, Lucie
Openness umfasst alle Aspekte, die üblicherweise mit Open Science und Open Education assiziiert werden. Es handelt sich um ein Mindset, welches die Öffnung von Forschung und Lehre für die Allgemeinheit anstrebt. Hierbei betrifft Öffnung sowohl enstandenes Material als auch die Teilhabe an der Gestaltung von Bildungsprozessen. Im verknüpften Workshop-Konzept wird die Umfänglichkeit des Konzepts durch einen interdisziplinären Zugang adressiert, welcher durch Mitarbeitende aus Wissenschaft, Bibliothek und E-Learning-Support gemeinsam gestaltet und durchgeführt wird.
Hier wird die Evaluation zu diesem Workshopkonzept veröffentlicht und die darauf aufbauenden Anpassungen am Workshopkonzept beschrieben.
Das Marburger Urkundenrepositorium. Eine exemplarische Analyse der Urkunden.
(Philipps-Universität Marburg) Löhden, Eike Martin
This dataset mainly contains a Jupyter Notebook which provides examples for analyzing the content of the "Marburger Urkundenrepositorium". The following analysis were made: general information about the repository (How many charters exist? From which collections do they come from?); Where are the physical representation of the charters currently stored (a list of the most common archives)? Are there geographical information connected to the charters? What do we know about the persons connected to the charters? And from which years do we have charters in the repository?
Additionally to the jupyter notebook you can find the text file kleio-example_11480.txt serving as an example for a record of the old kleio database, the document requirements.txt file listing the python requirements necessary for running the jupyter notebook and a README.md providing information about running the notebook. There are also two html files (cao-charters_map.html and lba-charters_map.html) attached, which includes geographic visualizations of the charter's origins.
Additionally to the jupyter notebook you can find the text file kleio-example_11480.txt serving as an example for a record of the old kleio database, the document requirements.txt file listing the python requirements necessary for running the jupyter notebook and a README.md providing information about running the notebook. There are also two html files (cao-charters_map.html and lba-charters_map.html) attached, which includes geographic visualizations of the charter's origins.
Image data
(Philipps-Universität Marburg) Schikora, Juliane; Dort, Aaron; Nickel, Antonia; Bergert, Jasmin; Schayan-Araghi, Stella Y.; Banerjee, Pratiti; Wolf, Hannah N.; May-Simera, Helen; Pauly, Diana
This subset of the repository contains the image data of the study in zip folders. This includes several replicates of the recorded 16-bit stacks as tif-files of the immunostainings that can be opened using Fiji. It further contains summary images as jpg-files used for image analysis. And it includes Fiji macros used for generation of merged and single channel stacks (Generation_summary_images.ijm), measurement of nuclei area in ARPE-19 cells (Image_analysis_ARPE-19_NA.ijm), nuclei area in iPSC-RPE cells (Image_analysis_iPSC-RPE_NA.ijm), measurement of cell area (Image_analysis_CA.ijm), and measurement of GT335 ciliary area (Image_analysis_GT335-A.ijm).
Synthetic Meteosat First Generation MVIRI Visible Band Images (Level 1.5)
(Philipps-Universität Marburg) Jung, Ivo; Gaurav, Sheetabh; Bendix, Jörg
The data comprises synthetic and harmonized Meteosat First Generation (MFG) MVIRI VIS reflectance Image data from 2006 - 2020. The dataset was created with the intent to extent the existing MFG MVIRI VIS image time series (https://navigator.eumetsat.int/product/EO:EUM:DAT:0080) for long-term climate research. The temporal resolution of the data is 30 minutes per image. Each image covers the WMO VI region up to 62°N. The images are stored as .nc files with reflectance values and geographic and temporal information. Due to the size of the dataset, it is compressed into annual archives. The dataset was created using a trained Random Forest Regressor Model and Meteosat Second Generation VIS channel data (https://data.eumetsat.int/product/EO:EUM:DAT:MSG:HRSEVIRI?query=SEVIRI&s=extended#). No data was created for pixels with Solar-Zenith Angles above 80° due to parallax effects and atmospheric distortion. Additional metadata can be found in the readme file. The data can be used like MFG MvIRI VIS image data i.e. using programming languages like python. The scripts for preprocessing, model training and synthesizing can be found at https://gitlab.uni-marburg.de/fb19/ag-bendix/harmonizing_synthesizing_mfg_vis.