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Component-resolved dynamics of glass-forming dipeptide-water-mixtures
No full textDatasets of the figures shown in the article with the same title as this submission. Original manuscript submitted to The Journal of Chemical Physics in October 2025. Revised version submitted to The Journal of Chemical Physics on December 202
Pressure-induced pKa shifts influence conformations of pH-sensitive polymers
No full textThis dataset contains input scripts and files to generate the data for the publication titled "Pressure-induced pKa shifts influence conformations of pH-sensitive polymers"
Simulation codes for 'Automated decision-making by chemical echolocation in active droplets'
No full textMotile microorganisms, like bacteria and algae, unify abilities like self-propulsion,
autonomous navigation, and decision-making on the micron scale. While recent breakthroughs have
led to the creation of synthetic microswimmers and nanoagents that can also self-propel, they still lack
the functionality and sophistication of their biological counterparts. This study pioneers a mechanism
enabling synthetic agents to autonomously navigate and make decisions, allowing them to solve mazes
and transport cargo through complex environments without requiring external cues or guidance. The
mechanism exploits chemo-hydrodynamic signals, produced by agents like active droplets or colloids,
to remotely sense and respond to their environment - similar to echolocation. Our research paves the
way for endowing autonomous, motile synthetic agents with functionalities that have been so far
exclusive to biological organisms.
This dataset contains codes that run time-dependent simulations of a synthetic agent producing a chemical field and then responding to it dynamically via chemorepulsion inside maze-shaped domains. Supports moving and static point sources, optional advection, chemotactic response, wall avoidance, and self-propulsion. Writes per-timestep concentration (data/conc_*.txt) and particle (data/part_*.txt) outputs and can render a trajectory video (data/particle_trajectory.mp4)
Turning Logic Against Itself : Probing Model Defenses Through Contrastive Questions
No full textCode and data associated with "Turning Logic Against Itself : Probing Model Defenses Through Contrastive Questions"
Machine Disturbances and Resilience Mechanisms Matrices
No full textThis dataset contains an Excel file with two matrices and a README. The first matrix links different machines to possible disturbances such as delivery delays, machine breakdowns, or staff shortages. The second matrix maps the same machines to resilience mechanisms like multiple sourcing, spare parts provision, or redundancy. Symbols (+, 0, –) indicate whether a disturbance or mechanism is relevant, negligible, or not applicable. The README explains how to interpret the sheets
Citation Failure: Definition, Analysis and Efficient Mitigation
No full textThis is the data for the CITECONTROL benchmark described in our paper "Citation Failure: Definition, Analysis and Efficient Mitigation". If you find our benchmark useful, please cite our paper.
Simultaneous Bacteria Sensing and On-Demand Antimicrobial Peptide Release: Public Data
No full textPowerPoint File of the public data of the paper, including responsive Origin Data. (In addition, there is a zip-archive including the raw data for the figures.
Requirements analysis: Transcript of the interview with an expert in management systems and documentation at the BGZ Gesellschaft für Zwischenlagerung
Full text linkBackground:
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 goal of the requirements analysis was to gain in-depth insights into the current state of Knowledge Management in the German nuclear industry. In addition, the requirements for an Extended Reality-based information system to support Knowledge Management in nuclear facilities were examined. Care was taken in selecting interview partners to cover all relevant stakeholders. This includes perspectives from the most important types of nuclear facilities (nuclear power plants, interim storage facilities, final repositories, research facilities) as well as other stakeholders, including federal authorities and engineering service providers.
Regarding the transcript "Interview with an expert in management systems and documentation at the BGZ Gesellschaft für Zwischenlagerung":
The expert interviewed is a quality manager at an interim storage facility and previously worked in the management systems department of a nuclear power plant for 20 years. His core tasks include creating regulations and manuals, overseeing supervisory procedures, and introducing a document management system. The discussion covered the special role of the BGZ Gesellschaft für Zwischenlagerung at power plant sites, the extensive documentation requirements under the Radiation Protection Ordinance and the KTA 1404, a safety standard issued by the Nuclear Safety Standards Commission (Kerntechnischer Ausschuss). The challenges and advantages of the document management system used and identification systems for equipment and containers were also discussed.
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
Dataset for automated material flow characterization of shredded WEEE: RGB raw data of an industrial sensor-based sorting machine
No full textThree datasets containing raw RGB image data from an industrial sensor-based sorting machine. The images contain particles of shredded WEEE, including ferrous metals (FEM), non-ferrous metals (NFM), printed circuit boards (PCB), and plastics (PLA), in two particle size ranges of 12.5 mm - 25 mm (SML) and 25 mm - 50 mm (LRG). Each dataset is structured by material types and particle size ranges.
- Dataset 1 (DS1) contains images that were used to train and test convolutional neural networks to identify the four material types through image classification, object detection, and instance segmentation.
- Dataset 2 (DS2) contains images that were used in the training and testing of regression models for particle mass prediction. Due to its size, this dataset is split into four files for the individual material types.
- Dataset 3 (DS3) contains images of particles from three predefined mixed samples to validate the models trained on the two previous datasets.
The images were recorded with an industry-sized sensor-based sorting machine (Sesotec Varisort Compact [Schoenberg, Germany]) at the pilot-scale sorting plant at Fraunhofer IWKS in Alzenau.1.0.
Expert Preference-based Evaluation of Automated Related Work Generation
No full textThe components of this dataset are used in the experiments of the paper "Expert Preference-based Evaluation of Automated Related Work Generation". Please see README.md for more information