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Anchoring challenges through citizen participation in regional challenge-based innovation policies
Get PDFThis study focuses on citizen participation as a co-productive and knowledge-intensive process in innovation policies concerned with regionally anchoring grand challenges. We apply a process-tracing approach and analyse citizen participation in two regional challenge-based innovation policies in the Ruhr, Germany. Local sensemaking, problem ownership, iterations and knowledge co-production are discussed as key mechanisms in the anchoring process. The results reveal the importance of a collective dimension in interpreting the local problem setting of a challenge achieved by reaching out to numerous citizens and how local, corrective and actionable knowledge facilitate the regional challenge anchoring. The policy formulation phase required the highest level of knowledge co-produced with citizens, followed by the implementation phase
We don’t need another (s)hero?: Role models, contradictions, discourses, and ideal feminine identity in entrepreneurial podcast dialogues
No full textJournalism and Advertising: On the Separation of Editorial Content and Commercial Communication
No full textAbstract
The principle of separation between editorial content and commercial communication protects both the democratic and the commercial function of mass media. This article compiles all available statutory and professional regulations in Germany as an example of the various aspects of the principle of separation, such as the labeling obligation, the prohibition of paid content and tying transactions, as well as the handling of numerous forms of presentation of editorial advertising. Subsequently, the state of research is reported for the individual aspects of the principle of separation, in particular with regard to description and effect. Finally, proposed solutions for current application and desiderata are compiled
When do those high on trait self-control suffer from strain? The interplay of trait self-control and multiple stressors
No full textExternbrink, K., Diestel, S., & Krings, M. (2019). When do those high on trait self-control suffer from strain? The interplay of trait self-control and multiple stressors. Journal of Personnel Psychology,18(1), 23–33
Impact of Team Members’ Competence on the Development of Team Mental Models and Team Performance
No full textContinuous and Scalable Laser Synthesis of Atom Clusters with Tunable Surface Oxidation for Electrocatalytic Water Splitting
No full textAn automated Calculation Pipeline for Differential Pair Interaction Energies with Molecular Force Fields using the Tinker Molecular Modeling Package
No full textAn automated pipeline for comprehensive calculation of intermolecular interaction energies based on molecular force-fields using the Tinker molecular modelling package is presented. Starting with non-optimized chemically intuitive monomer structures, the pipeline allows the approximation of global minimum energy monomers and dimers, configuration sampling for various monomer-monomer distances, estimation of coordination numbers by molecular dynamics simulations, and the evaluation of differential pair interaction energies. The latter are used to derive Flory-Huggins parameters and isotropic particle-particle repulsions for Dissipative Particle Dynamics (DPD). The computational results for force fields MM3, MMFF94, OPLS-AA and AMOEBA09 are analyzed with Density Functional Theory (DFT) calculations and DPD simulations for a mixture of the non-ionic polyoxyethylene alkyl ether surfactant C10E4 with water to demonstrate the usefulness of the approach
The DECIMER.ai Project
No full textOver the past few decades, the number of publications describing chemical structures and their metadata has increased significantly. Chemists have published the majority of this information as bitmap images along with other important information as human-readable text in printed literature and have never been retained and preserved in publicly available databases as machine-readable formats. Manually extracting such data from printed literature is error-prone, time-consuming, and tedious. The recognition and translation of images of chemical structures from printed literature into machine-readable format is known as Optical Chemical Structure Recognition (OCSR). In recent years, deep-learning-based OCSR tools have become increasingly popular. While many of these tools claim to be highly accurate, they are either unavailable to the public or proprietary. Meanwhile, the available open-source tools are significantly time-consuming to set up. Furthermore, none of these offers an end-to-end workflow capable of detecting chemical structures, segmenting them, classifying them, and translating them into machine-readable formats.
To address this issue, we present the DECIMER.ai project, an open-source platform that provides an integrated solution for identifying, segmenting, and recognizing chemical structure depictions within the scientific literature. DECIMER.ai comprises three main components: DECIMER-Segmentation, which utilizes a Mask-RCNN model to detect and segment images of chemical structure depictions; DECIMER-Image Classifier EfficientNet-based classification model identifies which images contain chemical structures and DECIMER-Image Transformer which acts as an OCSR engine which combines an encoder-decoder model to convert the segmented chemical structure images into machine-readable formats, like the SMILES string.
A key strength of DECIMER.ai is that its algorithms are data-driven, relying solely on the training data to make accurate predictions without any hand-coded rules or assumptions. By offering this comprehensive, open-source, and transparent pipeline, DECIMER.ai enables automated extraction and representation of chemical data from unstructured publications, facilitating applications in chemoinformatics and drug discovery
Studentische Nutzung(sangaben) von Large Language Models in Essays
Get PDFChatGPT & Co. haben sich im wissenschaftlichen Schreiben weit verbreitet. Hochschullehrende müssen darauf reagieren und auf den rechtssicheren Einsatz und die Risiken hinweisen. Diese Studie zeigt, wie Studierende diese 2023 einsetzen und (nicht) zitieren
Reducing Automotive Cooling System Complexity through an Adaptive Biomimetic Air Control Valve
Get PDFFuture automotive mobility is predominantly electric. Compared to existing systems, the requirements of subsystems change. Air flow for cooling components is needed predominantly when the car is in rest (i.e., charging) or at slow speeds. So far, actively driven fans consuming power and generating noise are used in this case. Here we propose a passive adaptive system allowing for convection-driven cooling. The developed system is a highly adaptive flat valve derived from the bordered pit. It was developed through an iterative design process including simulations, both structural and thermodynamic. In hardwoods and conifers, bordered pits enable the challenging transport of vertical fluids by locally limiting damage. Depending on the structure, these can close at sudden pressure changes and take the function of valves.
The result of the biomimetic abstraction process is a system-integrative, low-profile valve that is cheap to produce, long-lasting, lightweight, maintenance-free, and noise-free. It allows for the passive switching of air flow generation at the heat exchanger of the cooling between natural convection or an active airstream without the need for complex sensing and control systems. The geometric and material design factors allow for the simple tuning of the valve to the desired switching conditions during the design process