Extension Enforcement under Grounded Semantics in Abstract Argumentation

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Complexity Results and Algorithms for Extension Enforcement in Abstract Argumentation

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Towards Structural Reconstruction from X-Ray Spectra

We report a statistical analysis of Ge K-edge X-ray emission spectra simulated for amorphous GeO$_2$ at elevated pressures. We find that employing machine learning approaches we can reliably predict the statistical moments of the K$\beta''$ and K$\beta_2$ peaks in the spectrum from the Coulomb matrix descriptor with a training set of $\sim 10^4$ samples. Spectral-significance-guided dimensionality reduction techniques allow us to construct an approximate inverse mapping from spectral moments to pseudo-Coulomb matrices. When applying this to the moments of the ensemble-mean spectrum, we obtain distances from the active site that match closely to those of the ensemble mean and which moreover reproduce the pressure-induced coordination change in amorphous GeO$_2$. With this approach utilizing emulator-based component analysis, we are able to filter out the artificially complete structural information available from simulated snapshots, and quantitatively analyse structural changes that can be inferred from the changes in the K$\beta$ emission spectrum alone

Synthesizing Argumentation Frameworks from Examples

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MaxSAT-Based Bi-Objective Boolean Optimization

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Neural networks in interpretation of electronic core-level spectra

We explore the applicability of artificial intelligence for molecular structure - core-level spectrum interpretation. We focus on the electronic Hamiltonian using the H$_2$O molecule in the classical-nuclei approximation as our test system. For a systematic view we studied both predicting structures from spectra and, vice versa, spectra from structures, using polynomial approaches and neural networks. We find predicting spectra easier than predicting structures, where a tighter grid of the spectrum improves prediction. However, the accuracy of the structure prediction worsens when moving outwards from the center of mass of the training set in the structural parameter space

Influence of TMAO and urea on the structure of water studied by inelastic X-ray scattering

We present a study on the influence of the naturally occurring organic osmolytes tri-methylamine N-oxide (TMAO) and urea on the bulk structure of water using X-ray Raman scattering spectroscopy. Addition of TMAO is known to stabilize proteins in otherwise destabilizing aqueous urea solutions. The experimental X-ray Raman scattering spectra change systematically with increasing solute concentration revealing different effects on the structure of water due to the presence of the two osmolytes. Although these effects are distinct for both molecular species, they have mutually compensating influences on the spectra of the ternary water-TMAO-urea mixtures. This compensation effect seen in the spectra vanishes only at the highest studied ternary concentration of 4 M: 4 M (TMAO : urea). Our experiment shows that the hydrogen-bonding structure of water remains rather intact in the presence of the aforementioned osmolytes if both of them are present.Peer reviewe

Advanced Algorithms for Abstract Dialectical Frameworks based on Complexity Analysis of Subclasses and SAT Solving

dialectical frameworks (ADFs) constitute one of the most powerful formalisms in abstract argumentation. Their high computational complexity poses, however, certain challenges when designing efficient systems. In this paper, we tackle this issue by (i) analyzing the complexity of ADFs under structural restrictions, (ii) presenting novel algorithms which make use of these insights, and (iii) implementing these algorithms via (multiple) calls to SAT solvers. An empirical evaluation of the resulting implementation on ADF benchmarks generated from ICCMA competitions shows that our solver is able to outperform state-of-the-art ADF systems. (c) 2022 The Author(s). Published by Elsevier B.V.Peer reviewe

SAT-Based Approaches to Adjusting, Repairing, and Computing Largest Extensions of Argumentation Frameworks

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Synthesizing Argumentation Frameworks from Examples

Proceeding volume: 285Peer reviewe