1000 resultados para agents


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Antibiotics are used extensively in the treatment of various infections. Consequently, they can be considered among the most important agents involved in adverse reactions to drugs, including both allergic and non-allergic drug hypersensitivity [J Allergy Clin Immunol 113:832–836, 2004]. Most studies published to date deal mainly with reactions to the beta-lactam group, and information on hypersensitivity to each of the other antimicrobial agents is scarce. The present document has been produced by the Special Committee on Drug Allergy of the World Allergy Organization to present the most relevant information on the incidence, clinical manifestations, diagnosis, possible mechanisms, and management of hypersensitivity reactions to non beta-lactam antimicrobials for use by practitioners worldwide.

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Recent progress in understanding the molecular basis of autophagy has demonstrated its importance in several areas of human health. Affordable screening techniques with higher sensitivity and specificity to identify autophagy are, however, needed to move the field forward. In fact, only laborious and/or expensive methodologies such as electron microscopy, dye-staining of autophagic vesicles, and LC3-II immunoblotting or immunoassaying are available for autophagy identification. Aiming to fulfill this technical gap, we describe here the association of three widely used assays to determine cell viability - Crystal Violet staining (CVS), 3-[4, 5-dimethylthiaolyl]-2, 5-diphenyl-tetrazolium bromide (MTT) reduction, and neutral red uptake (NRU) - to predict autophagic cell death in vitro. The conceptual framework of the method is the superior uptake of NR in cells engaging in autophagy. NRU was then weighted by the average of MTT reduction and CVS allowing the calculation of autophagic arbitrary units (AAU), a numeric variable that correlated specifically with the autophagic cell death. The proposed strategy is very useful for drug discovery, allowing the investigation of potential autophagic inductor agents through a rapid screening using mammalian cell lines B16-F10, HaCaT, HeLa, MES-SA, and MES-SA/Dx5 in a unique single microplate.

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Aspergillus flavus, a haploid organism found worldwide in a variety of crops, including maize, cottonseed, almond, pistachio, and peanut, causes substantial and recurrent worldwide economic liabilities. This filamentous fungus produces aflatoxins (AFLs) B1 and B2, which are among the most carcinogenic compounds from nature, acutely hepatotoxic and immunosuppressive. Recent efforts to reduce AFL contamination in crops have focused on the use of nonaflatoxigenic A. flavus strains as biological control agents. Such agents are applied to soil to competitively exclude native AFL strains from crops and thereby reduce AFL contamination. Because the possibility of genetic recombination in A. flavus could influence the stability of biocontrol strains with the production of novel AFL phenotypes, this article assesses the diversity of vegetative compatibility reactions in isolates of A. flavus to identify heterokaryon self-incompatible (HSI) strains among nonaflatoxigenic isolates, which would be used as biological controls of AFL contamination in crops. Nitrate nonutilizing (nit) mutants were recovered from 25 A. flavus isolates, and based on vegetative complementation between nit mutants and on the microscopic examination of the number of hyphal fusions, five nonaflatoxigenic (6, 7, 9 to 11) and two nontoxigenic (8 and 12) isolates of A. flavus were phenotypically characterized as HSI. Because the number of hyphal fusions is reduced in HSI strains, impairing both heterokaryon formation and the genetic exchanges with aflatoxigenic strains, the HSI isolates characterized here, especially isolates 8 and 12, are potential agents for reducing AFL contamination in crops

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Agent Communication Languages (ACLs) have been developed to provide a way for agents to communicate with each other supporting cooperation in Multi-Agent Systems. In the past few years many ACLs have been proposed for Multi-Agent Systems, such as KQML and FIPA-ACL. The goal of these languages is to support high-level, human like communication among agents, exploiting Knowledge Level features rather than symbol level ones. Adopting these ACLs, and mainly the FIPA-ACL specifications, many agent platforms and prototypes have been developed. Despite these efforts, an important issue in the research on ACLs is still open and concerns how these languages should deal (at the Knowledge Level) with possible failures of agents. Indeed, the notion of Knowledge Level cannot be straightforwardly extended to a distributed framework such as MASs, because problems concerning communication and concurrency may arise when several Knowledge Level agents interact (for example deadlock or starvation). The main contribution of this Thesis is the design and the implementation of NOWHERE, a platform to support Knowledge Level Agents on the Web. NOWHERE exploits an advanced Agent Communication Language, FT-ACL, which provides high-level fault-tolerant communication primitives and satisfies a set of well defined Knowledge Level programming requirements. NOWHERE is well integrated with current technologies, for example providing full integration for Web services. Supporting different middleware used to send messages, it can be adapted to various scenarios. In this Thesis we present the design and the implementation of the architecture, together with a discussion of the most interesting details and a comparison with other emerging agent platforms. We also present several case studies where we discuss the benefits of programming agents using the NOWHERE architecture, comparing the results with other solutions. Finally, the complete source code of the basic examples can be found in appendix.

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Sustainable computer systems require some flexibility to adapt to environmental unpredictable changes. A solution lies in autonomous software agents which can adapt autonomously to their environments. Though autonomy allows agents to decide which behavior to adopt, a disadvantage is a lack of control, and as a side effect even untrustworthiness: we want to keep some control over such autonomous agents. How to control autonomous agents while respecting their autonomy? A solution is to regulate agents’ behavior by norms. The normative paradigm makes it possible to control autonomous agents while respecting their autonomy, limiting untrustworthiness and augmenting system compliance. It can also facilitate the design of the system, for example, by regulating the coordination among agents. However, an autonomous agent will follow norms or violate them in some conditions. What are the conditions in which a norm is binding upon an agent? While autonomy is regarded as the driving force behind the normative paradigm, cognitive agents provide a basis for modeling the bindingness of norms. In order to cope with the complexity of the modeling of cognitive agents and normative bindingness, we adopt an intentional stance. Since agents are embedded into a dynamic environment, things may not pass at the same instant. Accordingly, our cognitive model is extended to account for some temporal aspects. Special attention is given to the temporal peculiarities of the legal domain such as, among others, the time in force and the time in efficacy of provisions. Some types of normative modifications are also discussed in the framework. It is noteworthy that our temporal account of legal reasoning is integrated to our commonsense temporal account of cognition. As our intention is to build sustainable reasoning systems running unpredictable environment, we adopt a declarative representation of knowledge. A declarative representation of norms will make it easier to update their system representation, thus facilitating system maintenance; and to improve system transparency, thus easing system governance. Since agents are bounded and are embedded into unpredictable environments, and since conflicts may appear amongst mental states and norms, agent reasoning has to be defeasible, i.e. new pieces of information can invalidate formerly derivable conclusions. In this dissertation, our model is formalized into a non-monotonic logic, namely into a temporal modal defeasible logic, in order to account for the interactions between normative systems and software cognitive agents.

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Actual trends in software development are pushing the need to face a multiplicity of diverse activities and interaction styles characterizing complex and distributed application domains, in such a way that the resulting dynamics exhibits some grade of order, i.e. in terms of evolution of the system and desired equilibrium. Autonomous agents and Multiagent Systems are argued in literature as one of the most immediate approaches for describing such a kind of challenges. Actually, agent research seems to converge towards the definition of renewed abstraction tools aimed at better capturing the new demands of open systems. Besides agents, which are assumed as autonomous entities purposing a series of design objectives, Multiagent Systems account new notions as first-class entities, aimed, above all, at modeling institutional/organizational entities, placed for normative regulation, interaction and teamwork management, as well as environmental entities, placed as resources to further support and regulate agent work. The starting point of this thesis is recognizing that both organizations and environments can be rooted in a unifying perspective. Whereas recent research in agent systems seems to account a set of diverse approaches to specifically face with at least one aspect within the above mentioned, this work aims at proposing a unifying approach where both agents and their organizations can be straightforwardly situated in properly designed working environments. In this line, this work pursues reconciliation of environments with sociality, social interaction with environment based interaction, environmental resources with organizational functionalities with the aim to smoothly integrate the various aspects of complex and situated organizations in a coherent programming approach. Rooted in Agents and Artifacts (A&A) meta-model, which has been recently introduced both in the context of agent oriented software engineering and programming, the thesis promotes the notion of Embodied Organizations, characterized by computational infrastructures attaining a seamless integration between agents, organizations and environmental entities.

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Questa tesi prende spunto da altri studi realizzati nel campo delle esattamente nel campo delle “Swam Intelligence”, una branca delle intelligenze artificiali prende spunto dal comportamento di animali sociali, sopratutto insetti come termini, formiche ed api, per trarne interessanti metafore per la creazione di algoritmi e tecniche di programmazione. Questo tipo di algoritmi, come per gli esempi tratti dalla biologia, risultano dotati di interessanti proprietà adatte alla risoluzione di certi problemi nell'ambito dell'ingegneria. Lo scopo della tesi è quello di mostrare tramite un esempio pratico le proprietà dei sistemi sviluppati tramite i principi delle Swarm Intelligence, evidenziando la flessibilità di questi sistemi. Nello specifico, la mia tesi analizzerà il problema della suddivisione del lavoro in una colonia di formiche, fornendo un esempio pratico quale il compito di cattura di prede in un determinato ambiente. Ho sviluppato un'applicazione software in Java che simula tale comportamento, i dati utilizzati durante le diverse simulazioni possono essere modificati tramite file di testo, in modo da ottenere risultati validi per diversi contesti.

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In this investigation I look at patents and software agents as a way to study broader relation between law and science (the latter term broadly understood as inclusive of science and technology). The overall premise framing the entire discussion, my basic thesis, is that this relation, between law and science, cannot be understood without taking into account a number of intervening factors identifying which makes it necessary to approach the question from the standpoint of fields and disciplines other than law and science themselves.

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While the use of distributed intelligence has been incrementally spreading in the design of a great number of intelligent systems, the field of Artificial Intelligence in Real Time Strategy games has remained mostly a centralized environment. Despite turn-based games have attained AIs of world-class level, the fast paced nature of RTS games has proven to be a significant obstacle to the quality of its AIs. Chapter 1 introduces RTS games describing their characteristics, mechanics and elements. Chapter 2 introduces Multi-Agent Systems and the use of the Beliefs-Desires-Intentions abstraction, analysing the possibilities given by self-computing properties. In Chapter 3 the current state of AI development in RTS games is analyzed highlighting the struggles of the gaming industry to produce valuable. The focus on improving multiplayer experience has impacted gravely on the quality of the AIs thus leaving them with serious flaws that impair their ability to challenge and entertain players. Chapter 4 explores different aspects of AI development for RTS, evaluating the potential strengths and weaknesses of an agent-based approach and analysing which aspects can benefit the most against centralized AIs. Chapter 5 describes a generic agent-based framework for RTS games where every game entity becomes an agent, each of which having its own knowledge and set of goals. Different aspects of the game, like economy, exploration and warfare are also analysed, and some agent-based solutions are outlined. The possible exploitation of self-computing properties to efficiently organize the agents activity is then inspected. Chapter 6 presents the design and implementation of an AI for an existing Open Source game in beta development stage: 0 a.d., an historical RTS game on ancient warfare which features a modern graphical engine and evolved mechanics. The entities in the conceptual framework are implemented in a new agent-based platform seamlessly nested inside the existing game engine, called ABot, widely described in Chapters 7, 8 and 9. Chapter 10 and 11 include the design and realization of a new agent based language useful for defining behavioural modules for the agents in ABot, paving the way for a wider spectrum of contributors. Chapter 12 concludes the work analysing the outcome of tests meant to evaluate strategies, realism and pure performance, finally drawing conclusions and future works in Chapter 13.