7,766 research outputs found

    Toward Cultural Oncology: The Evolutionary Information Dynamics of Cancer

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    'Racial' disparities among cancers, particularly of the breast and prostate, are something of a mystery. For the US, in the face of slavery and its sequelae, centuries of interbreeding have greatly leavened genetic differences between 'Blacks' and 'whites', but marked contrasts in disease prevalence and progression persist. 'Adjustment' for socioeconomic status and lifestyle, while statistically accounting for much of the variance in breast cancer, only begs the question of ultimate causality. Here we propose a more basic biological explanation that extends the theory of immune cognition to include elaborate tumor control mechanisms constituting the principal selection pressure acting on pathologically mutating cell clones. The interplay between them occurs in the context of an embedding, highly structured, system of culturally specific psychosocial stress which we find is able to literally write an image of itself onto disease progression. The dynamics are analogous to punctuated equilibrium in simple evolutionary proces

    Chronic infection: punctuated interpenetration and pathogen virulence

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    We apply an information dynamics formalism to the Levens and Lewontin vision of biological interpenetration between a 'cognitive condensation' including immune function embedded in social and cultural structure on the one hand, and an established, highly adaptive, parasite population on the other. We iterate the argument, beginning with direct interaction between cognitive condensation and pathogen, then extend the analysis to second order 'mutator' mechanisms inherent both to immune function and to certain forms of rapid pathogen antigenic variability. The methodology, based on the Large Deviations Program of applied probability, produces synergistic cognitive/adaptive 'learning plateaus' that represent stages of chronic infection, and, for human populations, is able to encompass the fundamental biological reality of culture omitted by other approaches. We conclude that, for 'evolution machine' pathogens like HIV and malaria, simplistic magic bullet 'medical' drug, vaccine, or behavior modification interventions which do not address the critical context of overall living and working conditions may constitute selection pressures triggering adaptations in life history strategy resulting in marked increase of pathogen virulenc

    Computability and Evolutionary Complexity: Markets As Complex Adaptive Systems (CAS)

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    The purpose of this Feature is to critically examine and to contribute to the burgeoning multi disciplinary literature on markets as complex adaptive systems (CAS). Three economists, Robert Axtell, Steven Durlauf and Arthur Robson who have distinguished themselves as pioneers in different aspects of how the thesis of evolutionary complexity pertains to market environments have contributed to this special issue. Axtell is concerned about the procedural aspects of attaining market equilibria in a decentralized setting and argues that principles on the complexity of feasible computation should rule in or out widely held models such as the Walrasian one. Robson puts forward the hypothesis called the Red Queen principle, well known from evolutionary biology, as a possible explanation for the evolution of complexity itself. Durlauf examines some of the claims that have been made in the name of complex systems theory to see whether these present testable hypothesis for economic models. My overview aims to use the wider literature on complex systems to provide a conceptual framework within which to discuss the issues raised for Economics in the above contributions and elsewhere. In particular, some assessment will be made on the extent to which modern complex systems theory and its application to markets as CAS constitutes a paradigm shift from more mainstream economic analysis

    TOWARDS INSTITUTIONAL INFRASTRUCTURES FOR E-SCIENCE: The Scope of the Challenge

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    The three-fold purpose of this Report to the Joint Information Systems Committee (JISC) of the Research Councils (UK) is to: • articulate the nature and significance of the non-technological issues that will bear on the practical effectiveness of the hardware and software infrastructures that are being created to enable collaborations in e- Science; • characterise succinctly the fundamental sources of the organisational and institutional challenges that need to be addressed in regard to defining terms, rights and responsibilities of the collaborating parties, and to illustrate these by reference to the limited experience gained to date in regard to intellectual property, liability, privacy, and security and competition policy issues affecting scientific research organisations; and • propose approaches for arriving at institutional mechanisms whose establishment would generate workable, specific arrangements facilitating collaboration in e-Science; and, that also might serve to meet similar needs in other spheres such as e- Learning, e-Government, e-Commerce, e-Healthcare. In carrying out these tasks, the report examines developments in enhanced computer-mediated telecommunication networks and digital information technologies, and recent advances in technologies of collaboration. It considers the economic and legal aspects of scientific collaboration, with attention to interactions between formal contracting and 'private ordering' arrangements that rest upon research community norms. It offers definitions of e-Science, virtual laboratories, collaboratories, and develops a taxonomy of collaborative e-Science activities which is implemented to classify British e-Science pilot projects and contrast these with US collaboratory projects funded during the 1990s. The approach to facilitating inter-organizational participation in collaborative projects rests upon the development of a modular structure of contractual clauses that permit flexibility and experience-based learning.

    A neural network based model for mass non-residential real estate price evaluation of Lisbon, Portugal

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementAn accurate estimation of the real estate value became very important to make correct purchase and sale transaction, calculate taxes, mortgages for loans. Mass appraisal systems that use modern methodology based on artificial intelligence significantly help to deal with these issues. Objectives of this article are: using artificial neural networks (AANs) build mass appraisal model to evaluate market price of non-residential real estate of Lisbon, Portugal; evaluate performance of AANs and compare it with results generated by other models based on different methodologies and prove AANs superiority in issues connected with real estate apprising

    Embodied Decisions and the Predictive Brain

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    Decision-making has traditionally been modelled as a serial process, consisting of a number of distinct stages. The traditional account assumes that an agent first acquires the necessary perceptual evidence, by constructing a detailed inner repre- sentation of the environment, in order to deliberate over a set of possible options. Next, the agent considers her goals and beliefs, and subsequently commits to the best possible course of action. This process then repeats once the agent has learned from the consequences of her actions and subsequently updated her beliefs. Under this interpretation, the agent’s body is considered merely as a means to report the decision, or to acquire the relevant goods. However, embodied cognition argues that an agent’s body should be understood as a proper part of the decision-making pro- cess. Accepting this principle challenges a number of commonly held beliefs in the cognitive sciences, but may lead to a more unified account of decision-making. This thesis explores an embodied account of decision-making using a recent frame- work known as predictive processing. This framework has been proposed by some as a functional description of neural activity. However, if it is approached from an embodied perspective, it can also offer a novel account of decision-making that ex- tends the scope of our explanatory considerations out beyond the brain and the body. We explore work in the cognitive sciences that supports this view, and argue that decision theory can benefit from adopting an embodied and predictive perspective
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