Altered porphyrin excretion and histopathology of greylag geese (Anser anser) exposed to soil contaminated with lead and arsenic in the Guadalquivir Marshes, southwestern Spain

Greylag geese (Anser anser) in the Guadalquivir Marshes (southwestern Spain) can be exposed to sources of inorganic pollution such as heavy metals and arsenic from mining activities or Pb shot used for hunting. We have sampled 270 fecal excreta in different areas of the marshes in 2001 to 2002 to evaluate the exposure to Pb, Zn, Cu, Mn, and As and to determine its relationship with soil ingestion and with the excretion of porphyrins and biliverdin as biomarkers. These effects and the histopathology of liver, kidney, and pancreas were also studied in 50 geese shot in 2002 to 2004. None of the geese had ingested Pb shot in the gizzard. This contrasts with earlier samplings before the ban of Pb shot for waterfowl hunting in 2001 and the removal of Pb shot in points of the Doñana National Park (Spain) in 1999 to 2000. The highest exposure through direct soil ingestion to Pb and other studied elements was observed in samples from Entremuros, the area of the Doñana Natural Park affected by the Aznalcóllar mine spill in 1998. Birds from Entremuros also more frequently showed mononuclear infiltrates in liver and kidney than birds from the unaffected areas, although other more specific lesions of Pb or Zn poisoning were not observed. The excretion of coproporphyrins, especially of the isomer I, was positively related to the fecal As concentration, and the ratio of coproporphyrin III/I was positively related to fecal Pb concentration. Biliary protoporphyrin IX concentration was also slightly related to hepatic Pb concentration. This study reflects biological effects on terrestrial animals by the mining pollution in Doñana that can be monitored with the simple noninvasive sampling of feces.

Distinguished algebraic semantics for t-norm based fuzzy logics:Methods and algebraic equivalencies

This paper is a contribution to Mathematical fuzzy logic, in particular to the algebraic study of t-norm based fuzzy logics. In the general framework of propositional core and ?-core fuzzy logics we consider three properties of completeness with respect to any semantics of linearly ordered algebras. Useful algebraic characterizations of these completeness properties are obtained and their relations are studied. Moreover, we concentrate on five kinds of distinguished semantics for these logics-namely the class of algebras defined over the real unit interval, the rational unit interval, the hyperreals (all ultrapowers of the real unit interval), the strict hyperreals (only ultrapowers giving a proper extension of the real unit interval) and finite chains, respectively-and we survey the known completeness methods and results for prominent logics. We also obtain new interesting relations between the real, rational and (strict) hyperreal semantics, and good characterizations for the completeness with respect to the semantics of finite chains. Finally, all completeness properties and distinguished semantics are also considered for the first-order versions of the logics where a number of new results are proved. © 2009 Elsevier B.V. All rights reserved.

Communicating open systems

Just as conventional institutions are organisational structures for coordinating the activities of multiple interacting individuals, electronic institutions provide a computational analogue for coordinating the activities of multiple interacting software agents. In this paper, we argue that open multi-agent systems can be effectively designed and implemented as electronic institutions, for which we provide a comprehensive computational model. More specifically, the paper provides an operational semantics for electronic institutions, specifying the essential data structures, the state representation and the key operations necessary to implement them. We specify the agent workflow structure that is the core component of such electronic institutions and particular instantiations of knowledge representation languages that support the institutional model. In so doing, we provide the first formal account of the electronic institution concept in a rigorous and unambiguous way.

A multiagent network for peer norm enforcement

In a multiagent system where norms are used to regulate the actions agents ought to execute, some agents may decide not to abide by the norms if this can benefit them. Norm enforcement mechanisms are designed to counteract these benefits and thus the motives for not abiding by the norms. In this work we propose a distributed mechanism through which agents in the multiagent system that do not abide by the norms can be ostracised by their peers. An ostracised agent cannot interact anymore and looses all benefits from future interactions. We describe a model for multiagent systems structured as networks of agents, and a behavioural model for the agents in such systems. Furthermore, we provide analytical results which show that there exists an upper bound to the number of potential norm violations when all the agents exhibit certain behaviours. We also provide experimental results showing that both stricter enforcement behaviours and larger percentage of agents exhibiting these behaviours reduce the number of norm violations, and that the network topology influences the number of norm violations. These experiments have been executed under varying scenarios with different values for the number of agents, percentage of enforcers, percentage of violators, network topology, and agent behaviours. Finally, we give examples of applications where the enforcement techniques we provide could be used.

Constraint rule-based programming of norms for electronic institutions

Norms constitute a powerful coordination mechanism among heterogeneous agents. In this paper, we propose a rule language to specify and explicitly manage the normative positions of agents (permissions, prohibitions and obligations), with which distinct deontic notions and their relationships can be captured. Our rule-based formalism includes constraints for more expressiveness and precision and allows to supplement (and implement) electronic institutions with norms. We also show how some normative aspects are given computational interpretation. © 2008 Springer Science+Business Media, LLC.

Multi-Modal CTL:Completeness, Complexity, and an Application

We define a multi-modal version of Computation Tree Logic (ctl) by extending the language with path quantifiers E and A where d denotes one of finitely many dimensions, interpreted over Kripke structures with one total relation for each dimension. As expected, the logic is axiomatised by taking a copy of a ctl axiomatisation for each dimension. Completeness is proved by employing the completeness result for ctl to obtain a model along each dimension in turn. We also show that the logic is decidable and that its satisfiability problem is no harder than the corresponding problem for ctl. We then demonstrate how Normative Systems can be conceived as a natural interpretation of such a multi-dimensional ctl logic. © 2009 Springer Science+Business Media B.V.

Self-disclosure decision making based on intimacy and privacy

Autonomous agents may encapsulate their principals' personal data attributes. These attributes may be disclosed to other agents during agent interactions, producing a loss of privacy. Thus, agents need self-disclosure decision-making mechanisms to autonomously decide whether disclosing personal data attributes to other agents is acceptable or not. Current self-disclosure decision-making mechanisms consider the direct benefit and the privacy loss of disclosing an attribute. However, there are many situations in which the direct benefit of disclosing an attribute is a priori unknown. This is the case in human relationships, where the disclosure of personal data attributes plays a crucial role in their development. In this paper, we present self-disclosure decision-making mechanisms based on psychological findings regarding how humans disclose personal information in the building of their relationships. We experimentally demonstrate that, in most situations, agents following these decision-making mechanisms lose less privacy than agents that do not use them. (C) 2012 Elsevier Inc. All rights reserved.

Evidence for a non-replicative intracellular stage of nontypable Haemophilus influenzae in epithelial cells

Nontypable Haemophilus influenzae (NTHi) is a Gram-negative, non-capsulated human bacterial pathogen, a major cause of a repertoire of respiratory infections, and intimately associated with persistent lung bacterial colonization in patients suffering from chronic obstructive pulmonary disease (COPD). Despite its medical relevance, relatively little is known about its mechanisms of pathogenicity. In this study, we found that NTHi invades the airway epithelium by a distinct mechanism, requiring microtubule assembly, lipid rafts integrity, and activation of phosphatidylinositol 3-kinase (PI3K) signalling. We found that the majority of intracellular bacteria are located inside an acidic subcellular compartment, in a metabolically active and non-proliferative state. This NTHi-containing vacuole (NTHi-CV) is endowed with late endosome features, co-localizing with LysoTracker, lamp-1, lamp-2, CD63 and Rab7. The NTHi-CV does not acquire Golgi- or autophagy-related markers. These observations were extended to immortalized and primary human airway epithelial cells. By using NTHi clinical isolates expressing different amounts of phosphocholine (PCho), a major modification of NTHi lipooligosaccharide, on their surfaces, and an isogenic lic1BC mutant strain lacking PCho, we showed that PCho is not responsible for NTHi intracellular location. In sum, this study indicates that NTHi can survive inside airway epithelial cells.

Nontypeable Haemophilus influenzae clearance by alveolar macrophages is impaired by exposure to cigarette smoke

Nontypeable Haemophilus influenzae (NTHI) is an opportunistic gram-negative pathogen that causes respiratory infections and is associated with progression of respiratory diseases. Cigarette smoke is a main risk factor for development of respiratory infections and chronic respiratory diseases. Glucocorticoids, which are anti-inflammatory drugs, are still the most common therapy for these diseases. Alveolar macrophages are professional phagocytes that reside in the lung and are responsible for clearing infections by the action of their phagolysosomal machinery and promotion of local inflammation. In this study, we dissected the interaction between NTHI and alveolar macrophages and the effect of cigarette smoke on this interaction. We showed that alveolar macrophages clear NTHI infections by adhesion, phagocytosis, and phagolysosomal processing of the pathogen. Bacterial uptake requires host actin polymerization, the integrity of plasma membrane lipid rafts, and activation of the phosphatidylinositol 3-kinase (PI3K) signaling cascade. Parallel to bacterial clearance, macrophages secrete tumor necrosis factor alpha (TNF-alpha) upon NTHI infection. In contrast, exposure to cigarette smoke extract (CSE) impaired alveolar macrophage phagocytosis, although NTHI-induced TNF-alpha secretion was not abrogated. Mechanistically, our data showed that CSE reduced PI3K signaling activation triggered by NTHI. Treatment of CSE-exposed cells with the glucocorticoid dexamethasone reduced the amount of TNF-alpha secreted upon NTHI infection but did not compensate for CSE-dependent phagocytic impairment. The deleterious effect of cigarette smoke was observed in macrophage cell lines and in human alveolar macrophages obtained from smokers and from patients with chronic obstructive pulmonary disease.

AgentSpeak+: AgentSpeak with Probabilistic Planning

AgentSpeak is a logic-based programming language, based on the Belief-Desire-Intention (BDI) paradigm, suitable for building complex agent-based systems. To limit the computational complexity, agents in AgentSpeak rely on a plan library to reduce the planning problem to the much simpler problem of plan selection. However, such a plan library is often inadequate when an agent is situated in an uncertain environment. In this paper, we propose the AgentSpeak+ framework, which extends AgentSpeak with a mechanism for probabilistic planning. The beliefs of an AgentSpeak+ agent are represented using epistemic states to allow an agent to reason about its uncertain observations and the uncertain effects of its actions. Each epistemic state consists of a POMDP, used to encode the agent’s knowledge of the environment, and its associated probability distribution (or belief state). In addition, the POMDP is used to select the optimal actions for achieving a given goal, even when facing uncertainty.

Plan Selection for Probabilistic BDI Agents

When an agent wants to fulfill its desires about the world, the agent usually has multiple plans to choose from and these plans have different pre-conditions and additional effects in addition to achieving its goals. Therefore, for further reasoning and interaction with the world, a plan selection strategy (usually based on plan cost estimation) is mandatory for an autonomous agent. This demand becomes even more critical when uncertainty on the observation of the world is taken into account, since in this case, we consider not only the costs of different plans, but also their chances of success estimated according to the agent's beliefs. In addition, when multiple goals are considered together, different plans achieving the goals can be conflicting on their preconditions (contexts) or the required resources. Hence a plan selection strategy should be able to choose a subset of plans that fulfills the maximum number of goals while maintaining context consistency and resource-tolerance among the chosen plans. To address the above two issues, in this paper we first propose several principles that a plan selection strategy should satisfy, and then we present selection strategies that stem from the principles, depending on whether a plan cost is taken into account. In addition, we also show that our selection strategy can partially recover intention revision.

A Syntactic Approach to Revising Epistemic States with Uncertain Inputs

Revising its beliefs when receiving new information is an important ability of any intelligent system. However, in realistic settings the new input is not always certain. A compelling way of dealing with uncertain input in an agent-based setting is to treat it as unreliable input, which may strengthen or weaken the beliefs of the agent. Recent work focused on the postulates associated with this form of belief change and on finding semantical operators that satisfy these postulates. In this paper we propose a new syntactic approach for this form of belief change and show that it agrees with the semantical definition. This makes it feasible to develop complex agent systems capable of efficiently dealing with unreliable input in a semantically meaningful way. Additionally, we show that imposing restrictions on the input and the beliefs that are entailed allows us to devise a tractable approach suitable for resource-bounded agents or agents where reactiveness is of paramount importance.

Incorporating PGMs into a BDI Architecture

In this paper, we present a hybrid BDI-PGM framework, in which PGMs (Probabilistic Graphical Models) are incorporated into a BDI (belief-desire-intention) architecture. This work is motivated by the need to address the scalability and noisy sensing issues in SCADA (Supervisory Control And Data Acquisition) systems. Our approach uses the incorporated PGMs to model the uncertainty reasoning and decision making processes of agents situated in a stochastic environment. In particular, we use Bayesian networks to reason about an agent’s beliefs about the environment based on its sensory observations, and select optimal plans according to the utilities of actions defined in influence diagrams. This approach takes the advantage of the scalability of the BDI architecture and the uncertainty reasoning capability of PGMs. We present a prototype of the proposed approach using a transit scenario to validate its effectiveness.