The Modal Logic of Stepwise Removal

We investigate the modal logic of stepwise removal of objects, both for its intrinsic interest as a logic of quantification without replacement, and as a pilot study to better understand the complexity jumps between dynamic epistemic logics of model transformations and logics of freely chosen graph changes that get registered in a growing memory. After introducing this logic ($\textsf{MLSR}$) and its corresponding removal modality, we analyze its expressive power and prove a bisimulation characterization theorem. We then provide a complete Hilbert-style axiomatization for the logic of stepwise removal in a hybrid language enriched with nominals and public announcement operators. Next, we show that model-checking for $\textsf{MLSR}$ is PSPACE-complete, while its satisfiability problem is undecidable. Lastly, we consider an issue of fine-structure: the expressive power gained by adding the stepwise removal modality to fragments of first-order logic

Changing a semantics: opportunism or courage?

The generalized models for higher-order logics introduced by Leon Henkin, and their multiple offspring over the years, have become a standard tool in many areas of logic. Even so, discussion has persisted about their technical status, and perhaps even their conceptual legitimacy. This paper gives a systematic view of generalized model techniques, discusses what they mean in mathematical and philosophical terms, and presents a few technical themes and results about their role in algebraic representation, calibrating provability, lowering complexity, understanding fixed-point logics, and achieving set-theoretic absoluteness. We also show how thinking about Henkin's approach to semantics of logical systems in this generality can yield new results, dispelling the impression of adhocness. This paper is dedicated to Leon Henkin, a deep logician who has changed the way we all work, while also being an always open, modest, and encouraging colleague and friend.Comment: 27 pages. To appear in: The life and work of Leon Henkin: Essays on his contributions (Studies in Universal Logic) eds: Manzano, M., Sain, I. and Alonso, E., 201

Symbolic Model Checking for Dynamic Epistemic Logic

Dynamic Epistemic Logic (DEL) can model complex information scenarios in a way that appeals to logicians. However, existing DEL implementations are ad-hoc, so we do not know how the framework really performs. For this purpose, we want to hook up with the best available model-checking and SAT techniques in computational logic. We do this by first providing a bridge: a new faithful representation of DEL models as so-called knowledge structures that allow for symbolic model checking. Next, we show that we can now solve well-known benchmark problems in epistemic scenarios much faster than with existing DEL methods. Finally, we show that our method is not just a matter of implementation, but that it raises significant issues about logical representation and update

Graded Interface Models for More Accurate Determination of van der Waals-London Dispersion Interactions Across Grain Boundaries

Attractive van der Waals–London dispersion interactions between two half crystals arise from local physical property gradients within the interface layer separating the crystals. Hamaker coefficients and London dispersion energies were quantitatively determined for Σ5 and near-Σ13 grain boundaries in SrTiO3 by analysis of spatially resolved valence electron energy-loss spectroscopy (VEELS) data. From the experimental data, local complex dielectric functions were determined, from which optical properties can be locally analyzed. Both local electronic structures and optical properties revealed gradients within the grain boundary cores of both investigated interfaces. The results show that even in the presence of atomically structured grain boundary cores with widths of less than 1 nm, optical properties have to be represented with gradual changes across the grain boundary structures to quantitatively reproduce accurate van der Waals–London dispersion interactions. London dispersion energies of the order of 10% of the apparent interface energies of SrTiO3 were observed, demonstrating their significance in the grain boundary formation process. The application of different models to represent optical property gradients shows that long-range van der Waals–London dispersion interactions scale significantly with local, i.e., atomic length scale property variations

Surface characteristics of phenolic resin coatings

Phenolic resins are commonly used as polymer binders for metal, paper and mineral wool substrates. For such applications, mechanical, adhesive and thermal properties are considered most important, and the effect of synthesis and structural parameters on such end-use characteristics are well-documented. However, surface characteristics of cured phenolic resins can be equally relevant and are often overlooked. Widely used resins are phenol-urea-formaldehyde (PUF) and phenol-formaldehyde (PF). It is believed that the inherent chemistry and curing procedure of these resins result in coatings with distinct surface properties and wettability. To gain more insight into surface characteristics such as morphology, chemical composition and wettability of cured PUF and PF resins, different binder formulations were applied on glass substrates and subsequently characterised by Scanning Electron Microscopy (SEM), Contact Angle Goniometry (CAG) and X-Ray Photoelectron Spectroscopy (XPS). The effect of catalyst, chemical composition and curing conditions on surface characteristics of various PUF and PF coatings were investigated. The curing temperature was found to have a strong influence on surface properties; curing at 200 °C yields a surface with varying degrees of oxidation, differences in linkages between phenolic and urea species, and a lower overall nitrogen content in case of urea-containing coatings, resulting in stronger fluctuations in water-wettability compared to surfaces hardened at lower temperatures.</p

Trait–demography relationships underlying small mammal population fluctuations

1.Large-scale fluctuations in abundance are a common feature of small mammal populations and have been the subject of extensive research. These demographic fluctuations are often associated with concurrent changes in the average body mass of individuals, sometimes referred to as the “Chitty effect”. Despite the long-standing recognition of this phenomenon, an empirical investigation of the underlying coupled dynamics of body mass and population growth has been lacking. 2.Using long-term life-history data combined with a trait-based demographic approach, we examined the relationship between body mass and demography in a small mammal population that exhibits non-cyclic, large-scale fluctuations in abundance. We used data from the male segment of a 25-year study of the monogamous prairie vole, Microtus ochrogaster, in Illinois, USA. Specifically, we investigated how trait–demography relationships and trait distributions changed between different phases of population fluctuations, and the consequences of these changes for both trait and population dynamics. 3.We observed phase-specific changes in male adult body mass distribution in this population of prairie voles. Our analyses revealed that these changes were driven by variation in ontogenetic growth, rather than selection acting on the trait. The resulting changes in body mass influenced most life-history processes, and these effects varied among phases of population fluctuation. However, these changes did not propagate to affect the population growth rate due to the small effect of body mass on vital rates, compared to the overall differences in vital rates between phases. The increase phase of the fluctuations was initiated by enhanced survival, particularly of juveniles, and fecundity whereas the decline phase was driven by an overall reduction in fecundity, survival and maturation rates. 4.Our study provides empirical support, as well as a potential mechanism, underlying the observed trait changes accompanying population fluctuations. Body size dynamics and population fluctuations resulted from different life-history processes. Therefore, we conclude that body size dynamics in our population do not drive the observed population dynamics. This more in-depth understanding of different components of small mammal population fluctuations will help us to better identify the mechanistic drivers of this interesting phenomenon