1,074 research outputs found

    Eco-refuges as Anarchist’s Promised Land or the End of Dialectical Anarchism

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    Since the early Medieval Time people contested theological legitimation and rational discursive discours on authority as well as retreated to refuges to escape from any secular or ecclesiastical authority. Modern attempts formulated rational legitimation of authority in several ways: pragmatic authority by Monteigne, Bodin and Hobbes, or the contract authority of Locke and Rousseou. However, Enlightened Anarchism, first formulated in 1793 by the English philosopher William Godwin fulminated against all rational restrictions of human freedom and self-determination. However, we do not analyze anarchism by the ‘what’ and the ‘why’, but by looking for the best actual approach of Anarchist’s ‘Promised Land’. Furthermore, we follow the footsteps of Thoreau’s Walden Pond experiment considered as a place of salvation and prototype of 19th century romantic’s extreme individualism towards Leopold’s ethics of the land. Indeed, Thoreau’s and later Muir’s concepts of refuges are tightly connected to territorial and temporal bio-regional constraints and imply an internally organized public area based on mutualism and Hannah Arendt’s agape. From these ideas of refuges, Aldo Leopold formulated his Land-ethics that claimed integrity and autonomy of the ‘Land’. His foundation is a prototype of the eco-centric free space version of eco-anarchism as formulated by Bookchin. In order to formulate a philosophical foundation of eco-anarchism we reject Newtonian homogeneous space-temporal conception, preceding the whole Modern discours about authority and state. On the contrary, we adopt the pluralistic Leibnizian space-time from which thinking-humans do not dissociate themselves, but participate as part of the rational infrastructure of eco-refuges. In eco-refuges, citizen belong to the civil society that stays in equilibrium with the landscape and all forms of biological life. Space is the boundary condition of human activity and determines how borders, environmental organization and institutes are sustained. Space has its proper essence of sustainability, unity and integrity. The individual feelings of security are embedded in a timelike tradition and evolution of the free space, while individual particular conceptions of space and time integrate into the social processes of identification with the refuge. Therefore, the creation of eco-refuges transforms the actual world of national authorities into a world of anarchistic democratic eco-regional homelands

    Allostatic load and preterm birth

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    Preterm birth is a universal health problem that is one of the largest unmet medical needs contributing to the global burden of disease. Adding to its complexity is that there are no means to predict who is at risk when pregnancy begins or when women will actually deliver. Until these problems are addressed, there will be no interventions to reduce the risk because those who should be treated will not be known. Considerable evidence now exists that chronic life, generational or accumulated stress is a risk factor for preterm delivery in animal models and in women. This wear and tear on the body and mind is called allostatic load. This review explores the evidence that chronic stress contributes to preterm birth and other adverse pregnancy outcomes in animal and human studies. It explores how allostatic load can be used to, firstly, model stress and preterm birth in animal models and, secondly, how it can be used to develop a predictive model to assess relative risk among women in early pregnancy. Once care providers know who is in the highest risk group, interventions can be developed and applied to mitigate their risk

    Dynamic clustering of time series with Echo State Networks

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    In this paper we introduce a novel methodology for unsupervised analysis of time series, based upon the iterative implementation of a clustering algorithm embedded into the evolution of a recurrent Echo State Network. The main features of the temporal data are captured by the dynamical evolution of the network states, which are then subject to a clustering procedure. We apply the proposed algorithm to time series coming from records of eye movements, called saccades, which are recorded for diagnosis of a neurodegenerative form of ataxia. This is a hard classification problem, since saccades from patients at an early stage of the disease are practically indistinguishable from those coming from healthy subjects. The unsupervised clustering algorithm implanted within the recurrent network produces more compact clusters, compared to conventional clustering of static data, and provides a source of information that could aid diagnosis and assessment of the disease.Universidad de MĂĄlaga. Campus de Excelencia Internacional AndalucĂ­a Tec

    Hierarchical Temporal Representation in Linear Reservoir Computing

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    Recently, studies on deep Reservoir Computing (RC) highlighted the role of layering in deep recurrent neural networks (RNNs). In this paper, the use of linear recurrent units allows us to bring more evidence on the intrinsic hierarchical temporal representation in deep RNNs through frequency analysis applied to the state signals. The potentiality of our approach is assessed on the class of Multiple Superimposed Oscillator tasks. Furthermore, our investigation provides useful insights to open a discussion on the main aspects that characterize the deep learning framework in the temporal domain.Comment: This is a pre-print of the paper submitted to the 27th Italian Workshop on Neural Networks, WIRN 201

    Anthocyanins inhibit tumor necrosis alpha-induced loss of Caco-2 cell barrier integrity

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    An increased permeability of the intestinal barrier is proposed as a major event in the pathophysiology of conditions characterized by chronic gut inflammation. This study investigated the capacity of pure anthocyanins (AC), and berry and rice extracts containing different types and amounts of AC, to inhibit tumor necrosis alpha (TNFα)-induced permeabilization of Caco-2 cell monolayers. Caco-2 cells differentiated into intestinal epithelial cell monolayers were incubated in the absence/presence of TNFα, with or without the addition of AC or AC-rich plant extracts (ACRE). AC and ACRE inhibited TNFα-induced loss of monolayer permeability as assessed by changes in transepithelial electrical resistance (TEER) and paracellular transport of FITC-dextran. In the range of concentrations tested (0.25–1 ÎŒM), O-glucosides of cyanidin, and delphinidin, but not those of malvidin, peonidin and petunidin protected the monolayer from TNFα-induced decrease of TEER and increase of FITC-dextran permeability. Cyanidin and delphinidin acted by mitigating TNFα-triggered activation of transcription factor NF-ÎșB, and downstream phosphorylation of myosin light chain (MLC). The protective actions of the ACRE on TNFα-induced TEER increase was positively correlated with the sum of cyanidins and delphinidins (r2 = 0.83) content in the ACRE. However, no correlation was observed between TEER and ACRE total AC, malvidin, or peonidin content. Results support a particular capacity of cyanidins and delphinidins in the protection of the intestinal barrier against inflammation-induced permeabilization, in part through the inhibition of the NF-ÎșB pathway.Fil: Cremonini, Eleonora. University of California at Davis; Estados UnidosFil: Mastaloudis, Angela. Nu Skin Enterprises; Estados UnidosFil: Hester, Shelly N.. Nu Skin Enterprises; Estados UnidosFil: Verstraeten, Sandra Viviana. Universidad de Buenos Aires. Facultad de Farmacia y BioquĂ­mica. Departamento de QuĂ­mica BiolĂłgica; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Houssay. Instituto de QuĂ­mica y FĂ­sico-QuĂ­mica BiolĂłgicas "Prof. Alejandro C. Paladini". Universidad de Buenos Aires. Facultad de Farmacia y BioquĂ­mica. Instituto de QuĂ­mica y FĂ­sico-QuĂ­mica BiolĂłgicas; ArgentinaFil: Anderson, Maureen. University of California at Davis; Estados UnidosFil: Wood, Steven M.. Nu Skin Enterprises; Estados UnidosFil: Waterhouse, Andrew L.. University of California at Davis; Estados UnidosFil: Fraga, CĂ©sar Guillermo. University of California at Davis; Estados Unidos. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Houssay. Instituto de BioquĂ­mica y Medicina Molecular. Universidad de Buenos Aires. Facultad de Farmacia y BioquĂ­mica. Instituto de BioquĂ­mica y Medicina Molecular; ArgentinaFil: Oteiza, Patricia Isabel. University of California at Davis; Estados Unidos. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; Argentin

    Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games

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    Many real-world multi-agent interactions consider multiple distinct criteria, i.e. the payoffs are multi-objective in nature. However, the same multi-objective payoff vector may lead to different utilities for each participant. Therefore, it is essential for an agent to learn about the behaviour of other agents in the system. In this work, we present the first study of the effects of such opponent modelling on multi-objective multi-agent interactions with non-linear utilities. Specifically, we consider two-player multi-objective normal form games with non-linear utility functions under the scalarised expected returns optimisation criterion. We contribute novel actor-critic and policy gradient formulations to allow reinforcement learning of mixed strategies in this setting, along with extensions that incorporate opponent policy reconstruction and learning with opponent learning awareness (i.e., learning while considering the impact of one's policy when anticipating the opponent's learning step). Empirical results in five different MONFGs demonstrate that opponent learning awareness and modelling can drastically alter the learning dynamics in this setting. When equilibria are present, opponent modelling can confer significant benefits on agents that implement it. When there are no Nash equilibria, opponent learning awareness and modelling allows agents to still converge to meaningful solutions that approximate equilibria.Comment: Under review since 14 November 202
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