LUMINESCENCE PROPERTIES OF THE DINUCLEAR COPPER COMPLEX IN THE ACTIVE-SITE OF HEMOCYANINS

The deoxygenated form of hemocyanin, containing a dinuclear Cu(I) active site, emits luminescence in the red with maximum around 1.54 mu m(-1) (650 nm). The luminescence of deoxyhemocyanin (deoxy-Hc) from arthropod species is detectable at room temperature, the quantum yield being 2.4-2.7 X 10(-3); in contrast, the emission from molluscan proteins can be detected only at liquid nitrogen temperature. The luminescence emission is an inherent property of the bis[Cu(I)-(histidine)(3)] complex of the deoxygenated form of the protein to which both Cu(I) ions contribute equally to the overall emission. Luminescence is not observed with the oxygenated and the oxidized forms of hemocyanin, in which the metal is in the Cu(II) state, and in the metal-depleted or apo-Hc form. Based on steady-state and time-resolved measurements and references to Cu(I) model compounds, the luminescence emission is attributed to a triplet excited state of a Cu(I)-to-N (histidine) charge transfer transition (3)d-pi*. Acrylamide quenching experiments indicate that the metal active site is very shielded from the solvent. This property of deoxy-Hc enables us to directly follow reactions that modify either the copper oxidation number or the metal-to-protein stoichiometry

Generalized C<inf>F<inf>1</inf>F<inf>2</inf></inf>-integrals: From Choquet-like aggregation to ordered directionally monotone functions

© 2019 Elsevier B.V. This paper introduces the theoretical framework for a generalization of CF1F2-integrals, a family of Choquet-like integrals used successfully in the aggregation process of the fuzzy reasoning mechanisms of fuzzy rule based classification systems. The proposed generalization, called by gCF1F2-integrals, is based on the so-called pseudo pre-aggregation function pairs (F1,F2), which are pairs of fusion functions satisfying a minimal set of requirements in order to guarantee that the gCF1F2-integrals to be either an aggregation function or just an ordered directionally increasing function satisfying the appropriate boundary conditions. We propose a dimension reduction of the input space, in order to deal with repeated elements in the input, avoiding ambiguities in the definition of gCF1F2-integrals. We study several properties of gCF1F2-integrals, considering different constraints for the functions F1 and F2, and state under which conditions gCF1F2-integrals present or not averaging behaviors. Several examples of gCF1F2-integrals are presented, considering different pseudo pre-aggregation function pairs, defined on, e.g., t-norms, overlap functions, copulas that are neither t-norms nor overlap functions and other functions that are not even pre-aggregation functions

Recognizing and learning models of social exchange strategies for the regulation of social interactions in open agent societies

Regulation of social exchanges refers to controlling social exchanges between agents so that the balance of exchange values involved in the exchanges are continuously kept—as far as possible—near to equilibrium. Previous work modeled the social exchange regulation problem as a POMDP (Partially Observable Markov Decision Process), and defined the policyToBDIplans algorithm to extract BDI (Beliefs, Desires, Intentions) plans from POMDP models, so that the derived BDI plans can be applied to keep in equilibrium social exchanges performed by BDI agents. The aim of the present paper is to extend that BDI-POMDP agent model for self-regulation of social exchanges with a module, based on HMM (Hidden Markov Model), for recognizing and learning partner agents’ social exchange strategies, thus extending its applicability to open societies, where new partner agents can freely appear at any time. For the recognition problem, patterns of refusals of exchange pro- posals are analyzed, as such refusals are produced by the partner agents. For the learning problem, HMMs are used to capture probabilistic state transition and observation functions that model the social exchange strategy of the partner agent, in order to translate them into POMDP’s actionbased state transition and observation functions. The paper formally addresses the problem of translating HMMs into POMDP models and vice versa, introducing the translation algorithms and some examples. A discussion on the results of simulations of strategy-based social exchanges is presented, together with an analysis about related work on social exchanges in multiagent systems