2,836 research outputs found

    Beyond persons: extending the personal / subpersonal distinction to non-rational animals and artificial agents

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    The distinction between personal level explanations and subpersonal ones has been subject to much debate in philosophy. We understand it as one between explanations that focus on an agent’s interaction with its environment, and explanations that focus on the physical or computational enabling conditions of such an interaction. The distinction, understood this way, is necessary for a complete account of any agent, rational or not, biological or artificial. In particular, we review some recent research in Artificial Life that pretends to do completely without the distinction, while using agent-centered concepts all the way. It is argued that the rejection of agent level explanations in favour of mechanistic ones is due to an unmotivated need to choose among representationalism and eliminativism. The dilemma is a false one if the possibility of a radical form of externalism is considered

    On conformal measures and harmonic functions for group extensions

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    We prove a Perron-Frobenius-Ruelle theorem for group extensions of topological Markov chains based on a construction of σ\sigma-finite conformal measures and give applications to the construction of harmonic functions.Comment: To appear in Proceedings of "New Trends in Onedimensional Dynamics, celebrating the 70th birthday of Welington de Melo

    Facilitating return to work through early specialist health-based interventions (FRESH): protocol for a feasibility randomised controlled trial

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    Background Over one million people sustain traumatic brain injury each year in the UK and more than 10 % of these are moderate or severe injuries, resulting in cognitive and psychological problems that affect the ability to work. Returning to work is a primary rehabilitation goal but fewer than half of traumatic brain injury survivors achieve this. Work is a recognised health service outcome, yet UK service provision varies widely and there is little robust evidence to inform rehabilitation practice. A single-centre cohort comparison suggested better work outcomes may be achieved through early occupational therapy targeted at job retention. This study aims to determine whether this intervention can be delivered in three new trauma centres and to conduct a feasibility, randomised controlled trial to determine whether its effects and cost effectiveness can be measured to inform a definitive trial. Methods/design Mixed methods study, including feasibility randomised controlled trial, embedded qualitative studies and feasibility economic evaluation will recruit 102 people with traumatic brain injury and their nominated carers from three English UK National Health Service (NHS) trauma centres. Participants will be randomised to receive either usual NHS rehabilitation or usual rehabilitation plus early specialist traumatic brain injury vocational rehabilitation delivered by an occupational therapist. The primary objective is to assess the feasibility of conducting a definitive trial; secondary objectives include measurement of protocol integrity (inclusion/exclusion criteria, intervention adherence, reasons for non-adherence) recruitment rate, the proportion of eligible patients recruited, reasons for non-recruitment, spectrum of TBI severity, proportion of and reasons for loss to follow-up, completeness of data collection, gains in face-to-face Vs postal data collection and the most appropriate methods of measuring primary outcomes (return to work, retention) to determine the sample size for a larger trial. Discussion To our knowledge, this is the first feasibility randomised controlled trial of a vocational rehabilitation health intervention specific to traumatic brain injury. The results will inform the design of a definitive trial

    Assessing the Health of Richibucto Estuary with the Latent Health Factor Index

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    The ability to quantitatively assess the health of an ecosystem is often of great interest to those tasked with monitoring and conserving ecosystems. For decades, research in this area has relied upon multimetric indices of various forms. Although indices may be numbers, many are constructed based on procedures that are highly qualitative in nature, thus limiting the quantitative rigour of the practical interpretations made from these indices. The statistical modelling approach to construct the latent health factor index (LHFI) was recently developed to express ecological data, collected to construct conventional multimetric health indices, in a rigorous quantitative model that integrates qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modelling approach allows (a) statistical inference of health for observed sites and (b) prediction of health for unobserved sites, all accompanied by formal uncertainty statements. Thus far, the LHFI approach has been demonstrated and validated on freshwater ecosystems. The goal of this paper is to adapt this approach to modelling estuarine ecosystem health, particularly that of the previously unassessed system in Richibucto in New Brunswick, Canada. Field data correspond to biotic health metrics that constitute the AZTI marine biotic index (AMBI) and abiotic predictors preconceived to influence biota. We also briefly discuss related LHFI research involving additional metrics that form the infaunal trophic index (ITI). Our paper is the first to construct a scientifically sensible model to rigorously identify the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content --- all regarded a priori as qualitatively important abiotic drivers --- towards site health in the Richibucto ecosystem.Comment: On 2013-05-01, a revised version of this article was accepted for publication in PLoS One. See Journal reference and DOI belo

    A Human Development Framework for CO2 Reductions

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    Although developing countries are called to participate in CO2 emission reduction efforts to avoid dangerous climate change, the implications of proposed reduction schemes in human development standards of developing countries remain a matter of debate. We show the existence of a positive and time-dependent correlation between the Human Development Index (HDI) and per capita CO2 emissions from fossil fuel combustion. Employing this empirical relation, extrapolating the HDI, and using three population scenarios, the cumulative CO2 emissions necessary for developing countries to achieve particular HDI thresholds are assessed following a Development As Usual approach (DAU). If current demographic and development trends are maintained, we estimate that by 2050 around 85% of the world's population will live in countries with high HDI (above 0.8). In particular, 300Gt of cumulative CO2 emissions between 2000 and 2050 are estimated to be necessary for the development of 104 developing countries in the year 2000. This value represents between 20% to 30% of previously calculated CO2 budgets limiting global warming to 2{\deg}C. These constraints and results are incorporated into a CO2 reduction framework involving four domains of climate action for individual countries. The framework reserves a fair emission path for developing countries to proceed with their development by indexing country-dependent reduction rates proportional to the HDI in order to preserve the 2{\deg}C target after a particular development threshold is reached. Under this approach, global cumulative emissions by 2050 are estimated to range from 850 up to 1100Gt of CO2. These values are within the uncertainty range of emissions to limit global temperatures to 2{\deg}C.Comment: 14 pages, 7 figures, 1 tabl

    Is a Calorie Really a Calorie? Metabolic Advantage of Low-Carbohydrate Diets

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    The first law of thermodynamics dictates that body mass remains constant when caloric intake equals caloric expenditure. It should be noted, however, that different diets lead to different biochemical pathways that are not equivalent when correctly compared through the laws of thermodynamics. It is inappropriate to assume that the only thing that counts in terms of food consumption and energy balance is the intake of dietary calories and weight storage. Well-controlled studies suggest that calorie content may not be as predictive of fat loss as is reduced carbohydrate consumption. Biologically speaking, a calorie is certainly not a calorie. The ideal weight loss diet, if it even exists, remains to be determined, but a high-carbohydrate/low-protein diet may be unsatisfactory for many obese individuals

    Genetic Covariance Structure of Reading, Intelligence and Memory in Children

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    This study investigates the genetic relationship among reading performance, IQ, verbal and visuospatial working memory (WM) and short-term memory (STM) in a sample of 112, 9-year-old twin pairs and their older siblings. The relationship between reading performance and the other traits was explained by a common genetic factor for reading performance, IQ, WM and STM and a genetic factor that only influenced reading performance and verbal memory. Genetic variation explained 83% of the variation in reading performance; most of this genetic variance was explained by variation in IQ and memory performance. We hypothesize, based on these results, that children with reading problems possibly can be divided into three groups: (1) children low in IQ and with reading problems; (2) children with average IQ but a STM deficit and with reading problems; (3) children with low IQ and STM deficits; this group may experience more reading problems than the other two

    Genome variations: Effects on the robustness of neuroevolved control for swarm robotics systems

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    Manual design of self-organized behavioral control for swarms of robots is a complex task. Neuroevolution has proved a viable alternative given its capacity to automatically synthesize controllers. In this paper, we introduce the concept of Genome Variations (GV) in the neuroevolution of behavioral control for robotic swarms. In an evolutionary setup with GV, a slight mutation is applied to the evolving neural network parameters before they are copied to the robots in a swarm. The genome variation is individual to each robot, thereby generating a slightly heterogeneous swarm. GV represents a novel approach to the evolution of robust behaviors, expected to generate more stable and robust individual controllers, and bene t swarm behaviors that can deal with small heterogeneities in the behavior of other members in the swarm. We conduct experiments using an aggregation task, and compare the evolved solutions to solutions evolved under ideal, noise-free conditions, and to solutions evolved with traditional sensor noise.info:eu-repo/semantics/acceptedVersio
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