Public announcement logic is an extension of multiagent epistemic logic with dynamic operators to model the informational consequences of announcements to the entire group of agents. We propose an extension of public announcement logic with a dynamic modal operator that expresses what is true after any announcement: ⋄φ expresses that there is a truthful announcement ψ after which φ is true. This logic gives a perspective on Fitch's knowability issues: For which formulas φ, does it hold that φ → ⋄Kφ? We give various semantic results and show completeness for a Hilbert-style axiomatization of this logic. There is a natural generalization to a logic for arbitrary events.

Public announcement logic extends multi-agent epistemic logic with dynamic operators to model the informational consequences of announcements to the entire group of agents. In this article we propose a labelled tableau calculus for this logic, and show that it decides satisfiability of formulas in deterministic polynomial space. Since this problem is known to be PSPACE-complete, it follows that our proof method is optimal.

Public announcement logic is an extension of multi-agent epistemic logic with dynamic operators to model the informational consequences of announcements to the entire group of agents. We propose an extension of public announcement logic with a dynamic modal operator that expresses what is true after any announcement: ϕ expresses that ϕ is true after an arbitrary announcement ψ. As this includes the trivial announcement , one might as well say that ϕ expresses what remains true after any announcement: it therefore corresponds to truth persistence after (definable) relativisation. The dual operation ♦ϕ expresses that there is an announcement after which ϕ. This gives a perspective on Fitch's knowability issues: for which formulas ϕ does it hold that ϕ → ♦Kϕ? We give various semantic results, and we show completeness for a Hilbert-style axiomatisation of this logic.

The COVID-19 pandemic is increasing negative emotions and decreasing positive emotions globally. Left unchecked, these emotional changes may have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we will examine the impact of reappraisal, a widely studied and highly effective form of emotion regulation. Participants from 55 countries (expected N = 25,448) will be randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing), an active control condition, or a passive control condition. We predict that both reappraisal interventions will reduce negative emotions and increase positive emotions relative to the control conditions. We further predict that reconstrual will decrease negative emotions more than repurposing, and that repurposing will increase positive emotions more than reconstrual. We hope to inform efforts to create a scalable intervention for use around the world to build resilience during the pandemic and beyond.

We provide an efficient protocol for obtaining mitotic chromosomes with well-defined morphology in 17 different taxa of the class Reptilia. We also show that there is no need for adjustments among taxa and no need to sacrifice the animals studied.

We start from Reiter's solution to the frame problem in terms of successor state axioms and Scherl& Levesque's extension to knowledge, as formulated by Lakemeyer&Levesque in their logic ES. While it was believed up to now that quantification over actions is a characteristic feature of Reiter's solution, we here show that for a reasonably large subset of Reiter's basic action theories one can do without. We do so by recasting restricted basic action theories in a propositional modal logic, viz. dynamic epistemic logic with public announcements and public assignments.

Public announcement logic is an extension of multi-agent epistemic logic with dynamic operators to model the informational consequences of announcements to the entire group of agents. We propose a labelled tableau-calculus for this logic. We also present an extension of the calculus for a logic of arbitrary announcements.

Dengue fever represents a great challenge for many countries, and methodologies to prevent and/or control its transmission have been largely discussed by the research community. Modeling is a powerful tool to understand epidemic dynamics and to evaluate costs, benefits and effectiveness of control strategies. In order to assist decision-makers and researchers in the evaluation of different methodologies, we developed DengueME, a collaborative open source platform to simulate dengue disease and its vector's dynamics. DengueME provides a series of compartmental and individual-based models, implemented over a GIS database, that represents the Aedes aegypti's life cycle, human demography, human mobility, urban landscape and dengue transmission. The platform is designed to allow easy simulation of intervention scenarios. A GUI was developed to facilitate model configuration and data input.