Emission features in a B[e] binary system V2028 Cyg

We present a preliminary analysis of our six-year observation campaign of the B[e] stellar system V2028 Cyg (MWC 623). The time variability of spectral features is described

Iterative Graph Neural Network Enhancement via Frequent Subgraph Mining of Explanations

We formulate an XAI-based model improvement approach for Graph Neural Networks (GNNs) for node classification, called Explanation Enhanced Graph Learning (EEGL). The goal is to improve predictive performance of GNN using explanations. EEGL is an iterative self-improving algorithm, which starts with a learned "vanilla" GNN, and repeatedly uses frequent subgraph mining to find relevant patterns in explanation subgraphs. These patterns are then filtered further to obtain application-dependent features corresponding to the presence of certain subgraphs in the node neighborhoods. Giving an application-dependent algorithm for such a subgraph-based extension of the Weisfeiler-Leman (1-WL) algorithm has previously been posed as an open problem. We present experimental evidence, with synthetic and real-world data, which show that EEGL outperforms related approaches in predictive performance and that it has a node-distinguishing power beyond that of vanilla GNNs. We also analyze EEGL's training dynamics

Experimental validation of analytical wake and downstream turbine performance modelling

Wake effects in wind farms can cause significant power losses. In order to reduce these losses layout and control optimization can be applied. For this purpose, simple and fast prediction tools for the wake flow are needed. In the first part of this work, five analytical wind turbine wake models are compared to small-scale turbine wind tunnel measurements. The measurements are conducted at several downstream distances, varying the ambient turbulence intensity and upstream turbine blade pitch angle. Furthermore, an adjustment of a recently developed wake model is proposed. Subsequently, the adjusted model is found to perform best throughout all test cases. In the second part, the performance of an aligned downstream turbine is modelled based on the predicted wake flow using a Blade Element Momentum method with guaranteed convergence. In order to consider the non-uniform inflow velocity a mean-blade-element-velocity method is developed. Moreover, a blockage effect correction is applied. A comparison to wind tunnel measurement data shows that the wake velocity as well as the combined power of two aligned turbines are fairly well predicted. Additionally, the presented analytical framework of wake and downstream turbine performance modelling proposes several model improvements for state-of-the art wind farm simulation tools

Extrusion-Printing of Multi-Channeled Two-Component Hydrogel Constructs from Gelatinous Peptides and Anhydride-Containing Oligomers

The performance of artificial nerve guidance conduits (NGC) in peripheral nerve regeneration can be improved by providing structures with multiple small channels instead of a single wide lumen. 3D-printing is a strategy to access such multi-channeled structures in a defined and reproducible way. This study explores extrusion-based 3D-printing of two-component hydrogels from a single cartridge printhead into multi-channeled structures under aseptic conditions. The gels are based on a platform of synthetic, anhydride-containing oligomers for cross-linking of gelatinous peptides. Stable constructs with continuous small channels and a variety of footprints and sizes were successfully generated from formulations containing either an organic or inorganic gelation base. The adjustability of the system was investigated by varying the cross-linking oligomer and substituting the gelation bases controlling the cross-linking kinetics. Formulations with organic N-methyl-piperidin-3-ol and inorganic K2HPO4 yielded hydrogels with comparable properties after manual processing and extrusion-based 3D-printing. The slower reaction kinetics of formulations with K2HPO4 can be beneficial for extending the time frame for printing. The two-component hydrogels displayed both slow hydrolytic and activity-dependent enzymatic degradability. Together with satisfying in vitro cell proliferation data, these results indicate the suitability of our cross-linked hydrogels as multi-channeled NGC for enhanced peripheral nerve regeneration

Experimental validation of analytical wake and downstream turbine performance modelling

Wake effects in wind farms can cause significant power losses. In order to reduce these losses layout and control optimization can be applied. For this purpose, simple and fast prediction tools for the wake flow are needed. In the first part of this work, five analytical wind turbine wake models are compared to small-scale turbine wind tunnel measurements. The measurements are conducted at several downstream distances, varying the ambient turbulence intensity and upstream turbine blade pitch angle. Furthermore, an adjustment of a recently developed wake model is proposed. Subsequently, the adjusted model is found to perform best throughout all test cases. In the second part, the performance of an aligned downstream turbine is modelled based on the predicted wake flow using a Blade Element Momentum method with guaranteed convergence. In order to consider the non-uniform inflow velocity a mean-blade-element-velocity method is developed. Moreover, a blockage effect correction is applied. A comparison to wind tunnel measurement data shows that the wake velocity as well as the combined power of two aligned turbines are fairly well predicted. Additionally, the presented analytical framework of wake and downstream turbine performance modelling proposes several model improvements for state-of-the art wind farm simulation tools

B[e] Phenomenon in a Binary System V2028 Cyg

We present a preliminary analysis of our five-years observation campaign of the B[e] stellar system V2028 Cyg (MWC 623). The time variability of spectral features is described

Extrusion-Printing of Multi-Channeled Two-Component Hydrogel Constructs from Gelatinous Peptides and Anhydride-Containing Oligomers

The performance of artificial nerve guidance conduits (NGC) in peripheral nerve regeneration can be improved by providing structures with multiple small channels instead of a single wide lumen. 3D-printing is a strategy to access such multi-channeled structures in a defined and reproducible way. This study explores extrusion-based 3D-printing of two-component hydrogels from a single cartridge printhead into multi-channeled structures under aseptic conditions. The gels are based on a platform of synthetic, anhydride-containing oligomers for cross-linking of gelatinous peptides. Stable constructs with continuous small channels and a variety of footprints and sizes were successfully generated from formulations containing either an organic or inorganic gelation base. The adjustability of the system was investigated by varying the cross-linking oligomer and substituting the gelation bases controlling the cross-linking kinetics. Formulations with organic N-methyl-piperidin-3-ol and inorganic K2HPO4 yielded hydrogels with comparable properties after manual processing and extrusion-based 3D-printing. The slower reaction kinetics of formulations with K2HPO4 can be beneficial for extending the time frame for printing. The two-component hydrogels displayed both slow hydrolytic and activity-dependent enzymatic degradability. Together with satisfying in vitro cell proliferation data, these results indicate the suitability of our cross-linked hydrogels as multi-channeled NGC for enhanced peripheral nerve regeneration

Extrusion-Printing of Multi-Channeled Two-Component Hydrogel Constructs from Gelatinous Peptides and Anhydride-Containing Oligomers

The performance of artificial nerve guidance conduits (NGC) in peripheral nerve regeneration can be improved by providing structures with multiple small channels instead of a single wide lumen. 3D-printing is a strategy to access such multi-channeled structures in a defined and reproducible way. This study explores extrusion-based 3D-printing of two-component hydrogels from a single cartridge printhead into multi-channeled structures under aseptic conditions. The gels are based on a platform of synthetic, anhydride-containing oligomers for cross-linking of gelatinous peptides. Stable constructs with continuous small channels and a variety of footprints and sizes were successfully generated from formulations containing either an organic or inorganic gelation base. The adjustability of the system was investigated by varying the cross-linking oligomer and substituting the gelation bases controlling the cross-linking kinetics. Formulations with organic N-methyl-piperidin-3-ol and inorganic K2HPO4 yielded hydrogels with comparable properties after manual processing and extrusion-based 3D-printing. The slower reaction kinetics of formulations with K2HPO4 can be beneficial for extending the time frame for printing. The two-component hydrogels displayed both slow hydrolytic and activity-dependent enzymatic degradability. Together with satisfying in vitro cell proliferation data, these results indicate the suitability of our cross-linked hydrogels as multi-channeled NGC for enhanced peripheral nerve regeneration