The Emergence of Norms via Contextual Agreements in Open Societies

This paper explores the emergence of norms in agents' societies when agents play multiple -even incompatible- roles in their social contexts simultaneously, and have limited interaction ranges. Specifically, this article proposes two reinforcement learning methods for agents to compute agreements on strategies for using common resources to perform joint tasks. The computation of norms by considering agents' playing multiple roles in their social contexts has not been studied before. To make the problem even more realistic for open societies, we do not assume that agents share knowledge on their common resources. So, they have to compute semantic agreements towards performing their joint actions. %The paper reports on an empirical study of whether and how efficiently societies of agents converge to norms, exploring the proposed social learning processes w.r.t. different society sizes, and the ways agents are connected. The results reported are very encouraging, regarding the speed of the learning process as well as the convergence rate, even in quite complex settings

Variability Abstraction and Refinement for Game-Based Lifted Model Checking of Full CTL

One of the most promising approaches to fighting the configuration space explosion problem in lifted model checking are variability abstractions. In this work, we define a novel game-based approach for variability-specific abstraction and refinement for lifted model checking of the full CTL, interpreted over 3-valued semantics. We propose a direct algorithm for solving a 3-valued (abstract) lifted model checking game. In case the result of model checking an abstract variability model is indefinite, we suggest a new notion of refinement, which eliminates indefinite results. This provides an iterative incremental variability-specific abstraction and refinement framework, where refinement is applied only where indefinite results exist and definite results from previous iterations are reused. The practicality of this approach is demonstrated on several variability models

A Framework for Compositional Verification of Multi-valued Systems via Abstraction-Refinement

We present a framework for fully automated compositional verification of µ-calculus specifications over multi-valued systems, based on multivalued abstraction and refinement. Multi-valued models are widely used in many applications of model checking. They enable a more precise modeling of systems by distinguishing several levels of uncertainty and inconsistency. Successful verification tools such as STE (for hardware) and YASM (for software) are based on multi-valued models. Our compositional approach model checks individual components of a system. Only if all individual checks return indefinite values, the parts of the components which are responsible for these values, are composed and checked. Thus the construction of the full system is avoided. If the latter check is still indefinite, then a refinement is needed. We formalize our framework based on bilattices, consisting of a truth lattice and an information lattice. Formulas interpreted over a multi-valued model are evaluated w.r.t. to the truth lattice. On the other hand, refinement is now aimed at increasing the information level of model details, thus also increasing the information level of the model checking result. Based on the two lattices, we suggest how multi-valued models should be composed, checked, and refined

Revision and Update of the Consensus Definitions of Invasive Fungal Disease From the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium.

BACKGROUND: Invasive fungal diseases (IFDs) remain important causes of morbidity and mortality. The consensus definitions of the Infectious Diseases Group of the European Organization for Research and Treatment of Cancer and the Mycoses Study Group have been of immense value to researchers who conduct clinical trials of antifungals, assess diagnostic tests, and undertake epidemiologic studies. However, their utility has not extended beyond patients with cancer or recipients of stem cell or solid organ transplants. With newer diagnostic techniques available, it was clear that an update of these definitions was essential. METHODS: To achieve this, 10 working groups looked closely at imaging, laboratory diagnosis, and special populations at risk of IFD. A final version of the manuscript was agreed upon after the groups' findings were presented at a scientific symposium and after a 3-month period for public comment. There were several rounds of discussion before a final version of the manuscript was approved. RESULTS: There is no change in the classifications of "proven," "probable," and "possible" IFD, although the definition of "probable" has been expanded and the scope of the category "possible" has been diminished. The category of proven IFD can apply to any patient, regardless of whether the patient is immunocompromised. The probable and possible categories are proposed for immunocompromised patients only, except for endemic mycoses. CONCLUSIONS: These updated definitions of IFDs should prove applicable in clinical, diagnostic, and epidemiologic research of a broader range of patients at high-risk

Beyond the jab: A need for global coordination of pharmacovigilance for COVID-19 vaccine deployment Comment

Commentary - No abstract available

Global and regional brain metabolic scaling and its functional consequences

Background: Information processing in the brain requires large amounts of metabolic energy, the spatial distribution of which is highly heterogeneous reflecting complex activity patterns in the mammalian brain. Results: Here, it is found based on empirical data that, despite this heterogeneity, the volume-specific cerebral glucose metabolic rate of many different brain structures scales with brain volume with almost the same exponent around -0.15. The exception is white matter, the metabolism of which seems to scale with a standard specific exponent -1/4. The scaling exponents for the total oxygen and glucose consumptions in the brain in relation to its volume are identical and equal to $0.86\pm 0.03$, which is significantly larger than the exponents 3/4 and 2/3 suggested for whole body basal metabolism on body mass. Conclusions: These findings show explicitly that in mammals (i) volume-specific scaling exponents of the cerebral energy expenditure in different brain parts are approximately constant (except brain stem structures), and (ii) the total cerebral metabolic exponent against brain volume is greater than the much-cited Kleiber's 3/4 exponent. The neurophysiological factors that might account for the regional uniformity of the exponents and for the excessive scaling of the total brain metabolism are discussed, along with the relationship between brain metabolic scaling and computation.Comment: Brain metabolism scales with its mass well above 3/4 exponen

Infection-mediated priming of phagocytes protects against lethal secondary Aspergillus fumigatus challenge

Phagocytes restrict the germination of Aspergillus fumigatus conidia and prevent the establishment of invasive pulmonary aspergillosis in immunecompetent mice. Here we report that immunecompetent mice recovering from a primary A. fumigatus challenge are protected against a secondary lethal challenge. Using RAGγc knock-out mice we show that this protection is independent of T, B and NK cells. In protected mice, lung phagocytes are recruited more rapidly and are more efficient in conidial phagocytosis and killing. Protection was also associated with an enhanced expression of CXCR2 and Dectin-1 on bone marrow phagocytes. We also show that protective lung cytokine and chemokine responses are induced more rapidly and with enhanced dynamics in protected mice. Our findings support the hypothesis that following a first encounter with a non-lethal dose of A. fumigatus conidia, the innate immune system is primed and can mediate protection against a secondary lethal infection