A Model for Learning Description Logic Ontologies Based on Exact Learning

We investigate the problem of learning description logic (DL) ontologies in Angluin et al.’s framework of exact learning via queries posed to an oracle. We consider membership queries of the form “is a tuple a of individuals a certain answer to a data retrieval query q in a given ABox and the unknown target ontology?” and completeness queries of the form “does a hypothesis ontology entail the unknown target ontology?” Given a DL L and a data retrieval query language Q, we study polynomial learnability of ontologies in L using data retrieval queries in Q and provide an almost complete classification for DLs that are fragments of EL with role inclusions and of DL-Lite and for data retrieval queries that range from atomic queries and EL/ELI-instance queries to conjunctive queries. Some results are proved by non-trivial reductions to learning from subsumption examples

Reverse Engineering of Temporal Queries Mediated by LTL Ontologies

In reverse engineering of database queries, we aim to construct a query from a given set of answers and non-answers; it can then be used to explore the data further or as an explanation of the answers and non-answers. We investigate this query-by-example problem for queries formulated in positive fragments of linear temporal logic LTL over timestamped data, focusing on the design of suitable query languages and the combined and data complexity of deciding whether there exists a query in the given language that separates the given answers from non-answers. We consider both plain LTL queries and those mediated by LTL-ontologies.Comment: To be published in IJCAI 2023 proceeding

Interpolants and Explicit Definitions in Extensions of the Description Logic EL

We show that the vast majority of extensions of the description logic EL do not enjoy the Craig interpolation nor the projective Beth definability property. This is the case, for example, for EL with nominals, EL with the universal role, EL with role hierarchies and transitive roles, and for ELI. It follows in particular that the existence of an explicit definition of a concept or individual name cannot be reduced to subsumption checking via implicit definability. We show that nevertheless the existence of interpolants and explicit definitions can be decided in polynomial time for standard tractable extensions of EL (such as EL++) and in ExpTime for ELI and various extensions. It follows that these existence problems are not harder than subsumption which is in sharp contrast to the situation for expressive DLs. We also obtain tight bounds for the size of interpolants and explicit definitions and the complexity of computing them: single exponential for tractable standard extensions of EL and double exponential for ELI and extensions. We close with a discussion of Horn-DLs such as Horn-ALCI.</jats:p

Interpolants and Explicit Definitions in Extensions of the Description Logic EL

We show that the vast majority of extensions of the description logic $\mathcal{EL}$ do not enjoy the Craig interpolation nor the projective Beth definability property. This is the case, for example, for $\mathcal{EL}$ with nominals, $\mathcal{EL}$ with the universal role, $\mathcal{EL}$ with a role inclusion of the form $r\circ s\sqsubseteq s$, and for $\mathcal{ELI}$. It follows in particular that the existence of an explicit definition of a concept or individual name cannot be reduced to subsumption checking via implicit definability. We show that nevertheless the existence of interpolants and explicit definitions can be decided in polynomial time for standard tractable extensions of $\mathcal{EL}$ (such as $\mathcal{EL}^{++}$) and in ExpTime for $\mathcal{ELI}$ and various extensions. It follows that these existence problems are not harder than subsumption which is in sharp contrast to the situation for expressive DLs. We also obtain tight bounds for the size of interpolants and explicit definitions and the complexity of computing them: single exponential for tractable standard extensions of $\mathcal{EL}$ and double exponential for $\mathcal{ELI}$ and extensions. We close with a discussion of Horn-DLs such as Horn-$\mathcal{ALCI}$

Exact Learning of Light weight Description Logic Ontologies

We study the problem of learning description logic (DL) ontologies in Angluin et al.'s framework of exact learning via queries. We admit membership queries ("is a given subsumption entailed by the target ontology?") and equivalence queries ("is a given ontology equivalent to the target ontology?"). We present three main results: (1) ontologies formulated in (two relevant versions of) the description logic DL-Lite can be learned with polynomially many queries of polynomial size; (2) this is not the case for ontologies formulated in the description logic EL, even when only acyclic ontologies are admitted; and (3) ontologies formulated in a fragment of EL related to the web ontology language OWL 2 RL can be learned in polynomial time. We also show that neither membership nor equivalence queries alone are sufficient in cases (1) and (3)

Writing and Deleting Single Magnetic Skyrmions

Topologically nontrivial spin textures have recently been investigated for spintronic applications. Here, we report on an ultrathin magnetic film in which individual skyrmions can be written and deleted in a controlled fashion with local spin-polarized currents from a scanning tunneling microscope. An external magnetic field is used to tune the energy landscape, and the temperature is adjusted to prevent thermally activated switching between topologically distinct states. Switching rate and direction can then be controlled by the parameters used for current injection. The creation and annihilation of individual magnetic skyrmions demonstrates the potential for topological charge in future information-storage concepts

Writing and Deleting Single Magnetic Skyrmions

Topologically nontrivial spin textures have recently been investigated for spintronic applications. Here, we report on an ultrathin magnetic film in which individual skyrmions can be written and deleted in a controlled fashion with local spin-polarized currents from a scanning tunneling microscope. An external magnetic field is used to tune the energy landscape, and the temperature is adjusted to prevent thermally activated switching between topologically distinct states. Switching rate and direction can then be controlled by the parameters used for current injection. The creation and annihilation of individual magnetic skyrmions demonstrates the potential for topological charge in future information-storage concepts

Cell type-specific adhesion and migration on laser-structured opaque surfaces

Cytocompatibility is essential for implant approval. However, initial in vitro screenings mainly include the quantity of adherent immortalized cells and cytotoxicity. Other vital parameters, such as cell migration and an in-depth understanding of the interaction between native tissue cells and implant surfaces, are rarely considered. We investigated different laser-fabricated spike structures using primary and immortalized cell lines of fibroblasts and osteoblasts and included quantification of the cell area, aspect ratio, and focal adhesions. Furthermore, we examined the three-dimensional cell interactions with spike topographies and developed a tailored migration assay for long-term monitoring on opaque materials. While fibroblasts and osteoblasts on small spikes retained their normal morphology, cells on medium and large spikes sank into the structures, affecting the composition of the cytoskeleton and thereby changing cell shape. Up to 14 days, migration appeared stronger on small spikes, probably as a consequence of adequate focal adhesion formation and an intact cytoskeleton, whereas human primary cells revealed differences in comparison to immortalized cell lines. The use of primary cells, analysis of the cell–implant structure interaction as well as cell migration might strengthen the evaluation of cytocompatibility and thereby improve the validity regarding the putative in vivo performance of implant material. © 2020 by the authors. Licensee MDPI, Basel, Switzerland