727 research outputs found
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European Climate Pact Ambassador Survey (ECPAS) [Dataset]
No full textThis dataset contains the results from the European Climate Pact Ambassador Survey (ECPAS) based on 78 respondents. It contains socio-demographic background data of the European Climate Pact Ambassadors as well as information on their motivation and activities in the context of their mandate. The data was collected in November 2023
Circular dichroism of quantum defects in carbon nanotubes created by photocatalytic oxygen functionalization [data]
No full textThis repository contains the data of the publication "Circular dichroism of quantum defects in carbon nanotubes created by photocatalytic oxygen functionalization" (Nat. Commun. 2025, 16, 5107, doi: 10.1038/s41467-025-60342-y
Foreign and Security Policy of East Central Europe [Data]
No full textThe study examines diverging preferences of Eastern European EU member states towards a more closely integrated CFSP/CSDP despite similar threats from Russia and declining trust in the U.S. within NATO. The author demonstrates that party-political competition over societal value conflicts (GAL/TAN) are decisive in explaining foreign policy preferences. Through a comparative analysis, the study explains how the consequences of globalization and Europeanization have led to the formation of specific representation mechanisms that continue to shape the states' integration preferences to this day
MaiCuBeDa HT
No full textThe Mainz cuneiform Benchmark Dataset for the Haft Tappeh Collection (MaiCuBeDa HT), contains annotations of cuneiform signs on renderings of 3D models of cuneiform tablets excavated in the city of Haft Tappeh from the Middle Elamite period
The face of illusory truth: Repetition of information elicits affective facial reactions predicting judgments of truth [Dataset]
No full textPeople tend to judge repeated information as more likely being true compared to new information. A key explanation for this phenomenon, called the illusory truth effect, is that repeated information can be processed more fluently, causing it to appear more familiar and trustworthy. To consider the function of time in investigating its underlying cognitive and affective mechanisms, our design comprised two retention intervals. 75 participants rated the truth of new and repeated statements 10 minutes as well as 1 week after first exposure while spontaneous facial expressions were assessed via electromyography. Our data demonstrate that repetition results in specific facial reactions indicating increased positive affect, reduced mental effort, and increased familiarity (i.e., relaxations of musculus corrugator supercilii and frontalis), and subsequently increases the probability of judging information as true. The results moreover highlight the relevance of time: both repetition-induced truth effect and EMG activities decrease significantly after a longer interval
Genetic encoding and expression of RNA origami cytoskeletons in synthetic cells [Research Data]
No full textBottom-up synthetic biology seeks to engineer a cell from molecular building blocks. Using DNA nanotechnology, building blocks, such as cytoskeletons, have been reverse-engineered. However, DNA nanostructures rely on chemical synthesis and thermal annealing, and therefore synthetic cells cannot produce them from their constituents such as nucleotides. Here, we introduce RNA origami cytoskeleton mimics as alternative nucleic acid-based molecular hardware for synthetic cells, which we express directly inside GUVs containing a DNA template and a polymerase, chemically fuelled by feeding nucleotides from the outside. We designed RNA origami tiles that fold upon transcription and self-assemble into micrometer-long, 3D RNA origami nanotubes under isothermal conditions. We observe sequence mutations on the DNA template lead to RNA origami nanotubes and closed-ring phenotypes. Molecular dynamics simulations show that these phenotypic transitions are governed by alterations in the stability of RNA secondary structures. Additionally, we achieve cortex formation with aptamer-functionalized RNA nanotubes and show that nanotube polymerization leads to membrane deformation. Altogether, our data suggest that the expression of RNA origami-based hardware will help to explore active, evolvable, and RNA-based synthetic cells
[Ergänzungsdaten zu: Settlement development and food supply in the hinterland of Vindonissa]
No full textDigital supplements on the SIMFOOD model, diverse modelling examples and the data used as Excel files and PDF files
4D Printing of Self-Immolative Polymers
No full text4D printing has emerged as a powerful technique for fabricating complex 3D structures that evolve over time in response to external stimuli. In particular, "living" 4D printing strategies enable dynamic, reversible modulations of material properties such as size and mechanical stiffness via post-printing chemical modifications. However, current systems suffer from slow response times and limited reversibility, which restrict their practical applications. Herein, we present a new approach to address these limitations by integrating self-immolative polymers with light-based 3D printing. These polymers are programmed to undergo complete depolymerization in response to an external stimulus, providing a unique mechanism of “living” degrowth that expands the toolbox of adaptive transformations. To this aim, we synthesize photopolymerizable self-immolative polymers consisting of silyl end-capped poly-o-phthalaldehyde on the multi-gram scale and employ them in inks for digital light processing. Upon exposure to fluoride ions, which cleave the silyl end-caps, rapid depolymerization of the polymers results in significant degrowth of fabricated objects, accompanied by modulations of mechanical stiffness and optical transparency. Subsequent repolymerization enables regrowth of the objects. This study establishes self-immolative polymers as a platform for 4D printing and lays the groundwork for future development of dynamic, reconfigurable systems
Diverging roles of TRPV1 and TRPM2 in warm-temperature detection [data]
No full textThe accurate perception of innocuous temperatures, particularly those experienced as pleasantly warm, is essential for achieving thermal comfort and maintaining thermoregulatory balance. Warm-sensitive neurons (WSN) innervating the skin play a central role in non-painful warmth detection. The TRP ion channels TRPV1 and TRPM2 have been suggested as sensors of warm temperature in WSNs. However, the precise contribution of these channels to the process of warmth detection is not fully understood.
A significant challenge in analysing WSNs lies in their scarcity: fewer than 10 % of sensory neurons in the rodent dorsal root ganglion (DRG) respond to innocuous warm temperatures. In this study, we examined >20,000 cultured mouse DRG neurons using calcium imaging and discovered distinct contributions of TRPV1 and TRPM2 to warm temperature sensitivity. TRPV1 and TRPM2 affect the abundance of WSNs, with TRPV1 mediating the rapid, dynamic response to warmth.
By carefully tracking animal movement in a whole-body thermal preference paradigm, we observe that these cellular differences correlate with nuanced thermal behaviours. Utilizing a driftdiffusion model to quantitatively analyse the decision-making process of animals exposed to different environmental temperatures, we found that: TRPV1 primarily impairs the precision of evidence accumulation, whereas TRPM2 significantly increases the total duration of exposure to uncomfortably warm environments.
Our findings provide valuable insights into the distinct molecular responses to warmth stimuli, and underpin the subtle aspects of thermal decision-making when encountering minor temperature variations
Automating Feedback Analysis to Support Requirements Relation and Usage Understanding [data]
No full textContains all relevant data for the dissertation "Automating Feedback Analysis to Support Requirements Relation and Usage Understanding". ReadMe are provided for each section of dataset.
Software development often faces a gap between developers' assumptions
and users' real needs. While direct user involvement is valuable, it is
often impractical, making online user feedback a crucial but challenging
resource due to its unstructured nature. This dissertation addresses two
main challenges: identifying which functionalities users discuss in
their feedback and understanding how users interact with them. To tackle
these, two machine learning–based approaches are proposed: one relates
user feedback to existing software requirements, and the other extracts
detailed usage information using the TORE framework. Following a Design
Science methodology, the thesis includes systematic mapping studies, the
design and evaluation of automatic classifiers, and the development of a
supporting software prototype, Feed.UVL, along with a Jira plugin to
integrate into existing workflows. The contributions include new methods
for feedback analysis, evaluated classifiers, annotated datasets, and
insights into current research in the field