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Data for "Molecular and mechanical insights into gecko seta adhesion: multi-scale simulations combining molecular dynamics and the finite element method"
No full textContains all the data and code needed to reproduce the study
Supplementary Material (Figure Data): "Rule-Based Fault Diagnosis of Modular Process Plants"
No full textSupplementary material for the figures in the publication "Rule-Based Fault Diagnosis of Modular Process Plants" using plotID.
All relevant figures, data and code is organized in individual folders marked by their plotID.first submissio
Conformal Prediction for Semantically-Aware Autonomous Perception in Urban Environments
No full textThis repository contains the raw code accompanying the paper "Conformal Prediction for Semantically-Aware Autonomous Perception in Urban Environments", published in the Proceedings of the Conference on Robot Learning (CoRL) 2024, hosted by PMLR.
The experiments in the paper utilize large-scale public datasets that are curated by third-party organizations and are not part of the authors’ original contribution. As such, the datasets are not included in this repository. Please refer to the paper for detailed information on the datasets and their sources.
For a structured and documented version of the codebase, please visit the Git repository: https://gitlab.com/achref.d/krps
Benchmarking the Attribution Quality of Vision Models
No full textAttribution maps are one of the most established tools to explain the functioning of computer vision models. They assign importance scores to input features, indicating how relevant each feature is for the prediction of a deep neural network. While much research has gone into proposing new attribution methods, their proper evaluation remains a difficult challenge. In this work, we propose a novel evaluation protocol that overcomes two fundamental limitations of the widely used incremental-deletion protocol, i.e., the out-of-domain issue and lacking inter-model comparisons. This allows us to evaluate 23 attribution methods and how different design choices of popular vision backbones affect their attribution quality. We find that intrinsically explainable models outperform standard models and that raw attribution values exhibit a higher attribution quality than what is known from previous work. Further, we show consistent changes in the attribution quality when varying the network design, indicating that some standard design choices promote attribution quality
Ionization potentials of metal clusters studied with a broad range, tunable vacuum ultraviolet light source.
No full textIn this work, we present an alternative to complex laser setups or synchrotron light sources to accurately measure the ionization potentials of metal clusters. The setup is based on a commercial Xe flash lamp, combined with a vacuum monochromator, and has been applied to determine the ionization potentials of Snn clusters with n = 8–12 atoms. The uncertainty in the determination of the ionization potentials is mainly caused by the bandwidth of the monochromator. The adiabatic ionization potentials (AIPs) are extracted from experimental photoionization efficiency curves. Franck–Condon simulations are additionally used to interpret the shape and onset of the photo-ion yield. The obtained AIPs are (all energies are in eV) Sn8 (6.53 ± 0.05), Sn9 (6.69 ± 0.04), Sn10 (6.93 ± 0.03), Sn11 (6.34 ± 0.05), and Sn12 (IsoI 6.64 ± 0.04 and IsoIII 6.36 ± 0.05). Furthermore, the impact of multiple isomers present in the experiment on the photo-ion yield is addressed and compared with other experimental data in the literature
Data for ''Quantitative measurements of thermo-chemical states in turbulent lean and rich premixed NH3/H2/N2-air jet flames"
No full textThis dataset contains the results published in the paper ''Quantitative measurements of thermo-chemical states in turbulent lean and rich premixed NH3/H2/N2-air jet flames'' in the journal of Proceedings of the Combustion Institute in 2024 (DOI: 10.1016/j.proci.2024.105571
TET dioxygenases localize at splicing speckles and promote RNA splicing
No full textThe dynamic regulation of RNA metabolism plays a crucial part in cellular function, with emerging evidence suggesting an important role for RNA modifications in this process. This study explores the relationship between RNA splicing and the TET dioxygenase activity, shedding light on the role of hm5C (RNA 5-hydroxymethylcytosine), and TET proteins in RNA metabolism. Integrating data from mass spectrometry, AlphaFold structural modeling, microscopic analysis, and different functional assays, including in vitro splicing, TET proteins were found to regulate splicing. We show that TET1, TET2, and TET3 interact with the splicing factors U2AF1 and U2AF2. Interestingly, TET dioxygenases localize in splicing speckles in mammalian and Drosophila cells. TET speckles association was found to be RNA-dependent, but also rely on its interaction with splicing factors. Furthermore, cellular splicing assays revealed that all three TET proteins promote splicing efficiency independent of their catalytic activity. Interestingly, though, the oxidation of m5C to hm5C restores splicing efficiency in vitro. The latter highlights the regulatory role of cytosine modifications in RNA metabolism. These findings provide insights into the complex interplay between RNA modifications and splicing, suggesting a multifaceted role for TET proteins in RNA metabolism beyond their canonical function in the oxidation of 5mC in DNA.Final version after revie
ARR Data Collection Initiative 2025
No full textDataset of peer review reports, meta-reviews, reviewer-author discussions, and paper drafts collected from ACL Rolling Review within the context of the new data collection initiative (https://arr-data.aclweb.org/protocol/). All included data is explicitly licensed by the authors and reviewers for publication. This dataset is not meant for commercial purposes. This dataset should not be used for pre-training of neural models such as large language models. The newly released version v1.1 is the data from ACL 2025
Size-Dependent Contact Angles of Microscopic Droplets on Ultra-Smooth Silanized Surfaces Probed by Atomic Force Microscopy
No full textThis dataset contains the raw and processed results from atomic force microscopy (AFM) investigations of microscopic droplets on engineered solid substrates. The data were generated in the context of a study on wetting, dewetting, and contact angle determination at the nanoscale, focusing on the interplay between liquid properties and surface chemistry. Three different liquid categories were systematically investigated on various substrates that are fully characterized in the corresponding research paper.
The dataset includes:
Droplet AFM profiles: CSV files of two-dimensional droplet cross-sections obtained from AFM scans, enabling direct visualization of the liquid–solid interface and droplet curvature.
Contact angle values: Extracted from AFM profiles, reported as the final measured contact angle for each droplet.
Substrate information: Each file is linked to the substrate type (hydrophilic, hydrophobic, or hybrid coatings), which is discussed in detail in the publication.
Python analysis code: Scripts for reproducing the figures and numerical results reported in the paper. The code allows re-plotting of droplet profiles, recalculation of contact angles, and comparison across liquids and substrates.
The dataset is intended to provide both reproducibility of the results presented in the paper and a resource for further methodological development. Researchers can reuse the raw droplet profiles to test alternative fitting routines, compare with theoretical models, or extend the analysis to other wetting systems.
All files are provided in open formats (CSV for numerical data, Python scripts in .py) to ensure accessibility. File naming conventions indicate the liquid type, substrate, and replicate number. Together, the data and code establish a complete workflow from AFM measurement to quantitative contact angle extraction.
This dataset is directly relevant to the fields of surface science, interfacial physics, coating technology, and micro/nanoscale wetting phenomena, and may be of interest to both experimentalists and modelers investigating droplet behavior on functional surfaces
Evaluation: Transcript of the interview with the Knowledge Management group of the Bundesgesellschaft für Endlagerung
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As part of the doctoral thesis "XR-KIS: An Extended Reality-based Information System for Knowledge Management in Nuclear Facilities," expert interviews were conducted for both requirements analysis and evaluation. The aim of the evaluation was to determine the extent to which the developed XR-KIS application is applicable to different nuclear facilities, as intended in the concept, in light of its implementation in the Mont Terri underground rock laboratory in Switzerland. Half of the interview partners had already been interviewed during the requirements phase, which ensures a balanced ratio of experts who were familiar with the concept from the outset and those who only became acquainted with the application after its completion.
Regarding the transcript "Interview with the Knowledge Management group of the Bundesgesellschaft für Endlagerung":
The Knowledge Management Group at the Bundesgesellschaft für Endlagerung was established in 2019 as a cross-departmental unit. It implements Knowledge Management tools within the Bundesgesellschaft für Endlagerung. The interview was important for discussing the possible application of XR-KIS in a final repository, using Mont Terri as an example. As expected, the interview focused largely on the technical concept and the aspect of long-term archiving.
Note:
The interview partner(s) has/have given written consent to the publication of this anonymized transcript as part of an authorization process. The German version represents the original text