1,380 research outputs found

    Familial hemiplegic migraine with cerebellar ataxia and paroxysmal psychosis

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    Familial hemiplegic migraine is a rare autosomal dominant disorder associated with stereotypic neurologic au ra phenomena including hemiparesis, So far two chromosomal loci have been identified. Families linked to the chromosome 19 locus display missense mutations within the CACNL1A4 gene. Here we report on a family with familial hemiplegic migraine and cerebellar ataxia with recurrent episodes of acute paranoid psychosis with anxiety and visual hallucinations associated with migraine attacks. Based on the clinical and haplotype evidence indicating linkage to chromosome 19 in this family, we hypothesize that a dysfunction of the mutated calcium channel may be involved not only in the development of hemiplegic migraine but also in the acute psychotic episodes observed in these patients

    Semiotic Dynamics Solves the Symbol Grounding Problem

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    Language requires the capacity to link symbols (words, sentences) through the intermediary of internal representations to the physical world, a process known as symbol grounding. One of the biggest debates in the cognitive sciences concerns the question how human brains are able to do this. Do we need a material explanation or a system explanation? John Searle's well known Chinese Room thought experiment, which continues to generate a vast polemic literature of arguments and counter-arguments, has argued that autonomously establishing internal representations of the world (called 'intentionality' in philosophical parlance) is based on special properties of human neural tissue and that consequently an artificial system, such as an autonomous physical robot, can never achieve this. Here we study the Grounded Naming Game as a particular example of symbolic interaction and investigate a dynamical system that autonomously builds up and uses the semiotic networks necessary for performance in the game. We demonstrate in real experiments with physical robots that such a dynamical system indeed leads to a successful emergent communication system and hence that symbol grounding and intentionality can be explained in terms of a particular kind of system dynamics. The human brain has obviously the right mechanisms to participate in this kind of dynamics but the same dynamics can also be embodied in other types of physical systems

    Planning for coastal community resiliency : a partnership approach

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    Disaster planning and recovery programs and policies are becoming more important with the increase in numbers and frequency of disasters and their widespread damage throughout the world. Government alone no longer is the answer. The whole community needs to be involved. There are local "assets" that a community has available to assist in addressing natural and human-caused disasters. Asset-Based Community Development (ABCD) is an approach that involves both public and private sectors, with strong emphasis on using local resources. This whole community concept includes collaboration among agencies that provide services to disaster victims, educating residents about potential hazards and how to prepare for them, and developing a coordinated set of policies that can be communicated to the public. Engaging in sound community development practices that involves the whole community, including those who may be affected by the disaster (as well as youth and the elderly) is paramount to successful outcomes in post-disaster recovery. The southeastern United States had dealt with many disasters. This includes natural hazard events such as hurricanes, tropical storms, coastal floods, tornadoes, and wild fires, as well as human-caused disasters such as industrial accidents, and major oil spills. Educational programs, materials and best practices and principles have been developed for individuals and communities to become more resilient to these disasters through the preplanning and post-disaster recovery phases.Michael S. Spranger: Department of Family, Youth and Community Sciences, University of Florid

    Comparison and calibration of a real-time virtual stenting algorithm using Finite Element Analysis and Genetic Algorithms

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    In this paper, we perform a comparative analysis between two computational methods for virtual stent deployment: a novel fast virtual stenting method, which is based on a spring–mass model, is compared with detailed finite element analysis in a sequence of in silico experiments. Given the results of the initial comparison, we present a way to optimise the fast method by calibrating a set of parameters with the help of a genetic algorithm, which utilises the outcomes of the finite element analysis as a learning reference. As a result of the calibration phase, we were able to substantially reduce the force measure discrepancy between the two methods and validate the fast stenting method by assessing the differences in the final device configurations

    Circulating vaspin is unrelated to insulin sensitivity in a cohort of nondiabetic humans

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    Objective: To study the association of vaspin with glucose metabolism. Design: Cross-sectional and intervention study. Subjects and methods: The association of serum vaspin with metabolic and anthropometric characteristics was investigated in 108 volunteers. Euglycemic–hyperinsulinemic clamps (EHC) were performed in 83 of the participants. Changes of circulating vaspin levels were additionally studied in a crossover study using 300 min EHC with lipid versus saline infusion (n=10). Results: Neither glucose tolerance status nor insulin sensitivity, both as measured using EHCs and using homeostasis model assessment for insulin resistance (HOMA-IR), was significantly associated with serum vaspin in the cross-sectional study. Furthermore, there was no effect of short-term lipid-induced insulin resistance due to a 300 min intravenous lipid challenge on circulating vaspin. However, circulating vaspin levels were significantly elevated in women using oral contraceptives (OC), both compared to women without OC intake (1.17±0.26 vs 0.52±0.09 ng/ml, P=0.02) and males (1.17±0.26 vs 0.29±0.04 ng/ml, P=0.01). After exclusion of OC using females and stratification according to body mass index (BMI), a significant sexual dimorphism in subjects with a BMI <25 kg/m2 was observed (males 0.21±0.04 ng/ml versus females 0.70±0.16 ng/ml, P=0.009). Conclusion: Our results support the existence of a sexual dimorphism regarding circulating vaspin. The lack of an association of serum vaspin with HOMA-IR and M value indicates, however, no major role for vaspin concerning insulin sensitivity in nondiabetic humans

    Neural-symbolic computing: An effective methodology for principled integration of machine learning and reasoning

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    Current advances in Artificial Intelligence and machine learning in general, and deep learning in particular have reached unprecedented impact not only across research communities, but also over popular media channels. However, concerns about interpretability and accountability of AI have been raised by influential thinkers. In spite of the recent impact of AI, several works have identified the need for principled knowledge representation and reasoning mechanisms integrated with deep learning-based systems to provide sound and explainable models for such systems. Neural-symbolic computing aims at integrating, as foreseen by Valiant, two most fundamental cognitive abilities: the ability to learn from the environment, and the ability to reason from what has been learned. Neural-symbolic computing has been an active topic of research for many years, reconciling the advantages of robust learning in neural networks and reasoning and interpretability of symbolic representation. In this paper, we survey recent accomplishments of neural-symbolic computing as a principled methodology for integrated machine learning and reasoning. We illustrate the effectiveness of the approach by outlining the main characteristics of the methodology: principled integration of neural learning with symbolic knowledge representation and reasoning allowing for the construction of explainable AI systems. The insights provided by neural-symbolic computing shed new light on the increasingly prominent need for interpretable and accountable AI systems

    Global assessment of nitrogen deposition effects on terrestrial plant diversity : a synthesis

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    Atmospheric nitrogen (N) deposition is it recognized threat to plant diversity ill temperate and northern parts of Europe and North America. This paper assesses evidence from field experiments for N deposition effects and thresholds for terrestrial plant diversity protection across a latitudinal range of main categories of ecosystems. from arctic and boreal systems to tropical forests. Current thinking on the mechanisms of N deposition effects on plant diversity, the global distribution of G200 ecoregions, and current and future (2030) estimates of atmospheric N-deposition rates are then used to identify the risks to plant diversity in all major ecosystem types now and in the future. This synthesis paper clearly shows that N accumulation is the main driver of changes to species composition across the whole range of different ecosystem types by driving the competitive interactions that lead to composition change and/or making conditions unfavorable for some species. Other effects such its direct toxicity of nitrogen gases and aerosols long-term negative effects of increased ammonium and ammonia availability, soil-mediated effects of acidification, and secondary stress and disturbance are more ecosystem, and site-specific and often play a supporting role. N deposition effects in mediterranean ecosystems have now been identified, leading to a first estimate of an effect threshold. Importantly, ecosystems thought of as not N limited, such as tropical and subtropical systems, may be more vulnerable in the regeneration phase. in situations where heterogeneity in N availability is reduced by atmospheric N deposition, on sandy soils, or in montane areas. Critical loads are effect thresholds for N deposition. and the critical load concept has helped European governments make progress toward reducing N loads on sensitive ecosystems. More needs to be done in Europe and North America. especially for the more sensitive ecosystem types. including several ecosystems of high conservation importance. The results of this assessment Show that the Vulnerable regions outside Europe and North America which have not received enough attention are ecoregions in eastern and Southern Asia (China, India), an important part of the mediterranean ecoregion (California, southern Europe). and in the coming decades several subtropical and tropical parts of Latin America and Africa. Reductions in plant diversity by increased atmospheric N deposition may be more widespread than first thought, and more targeted Studies are required in low background areas, especially in the G200 ecoregions
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