495,959 research outputs found

    Consciousness as Recursive, Spatiotemporal Self-Location

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    At the phenomenal level, consciousness arises in a consistently coherent fashion as a singular, unified field of recursive self-awareness (subjectivity) with explicitly orientational characteristics—that of a subject located both spatially and temporally in an egocentrically-extended domain. Understanding these twin elements of consciousness begins with the recognition that ultimately (and most primitively), cognitive systems serve the biological self-regulatory regime in which they subsist. The psychological structures supporting self-located subjectivity involve an evolutionary elaboration of the two basic elements necessary for extending self-regulation into behavioral interaction with the environment: an orientative reference frame which consistently structures ongoing interaction in terms of controllable spatiotemporal parameters, and processing architecture that relates behavior to homeostatic needs via feedback. Over time, constant evolutionary pressures for energy efficiency have encouraged the emergence of anticipative feedforward processing mechanisms, and the elaboration, at the apex of the sensorimotor processing hierarchy, of self-activating, highly attenuated recursively-feedforward circuitry processing the basic orientational schema independent of external action output. As the primary reference frame of active waking cognition, this recursive self-locational schema processing generates a zone of subjective self-awareness in terms of which it feels like something to be oneself here and now. This is consciousness-as-subjectivity

    Why Does Dave Spend Ten Times More Time on Interaction with Industry than Paul? : Toward a Model of Social Capital Activation for Entrepreneurial Academics

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    This paper focuses on academics that are looking for entrepreneurial ways to pursue their teaching, research and commercialization interests, in particular by actively engaging in university-industry interactions. The paper aims to improve our knowledge of why some academics exploit their social networks with industry more actively than others. We develop a conceptual model that aims to explain a mechanism behind social capital activation, and to identify factors that are likely to have the highest predictive power. We theorize on how academic’s motivation, perceived social influence and perceived ability unite into readiness to activate social capital, and under what circumstances this readiness is likely to result in actual behavior. Specifically, the objective of this paper is to further develop the model constructs and to operationalize them into a set of measurable items. For each of the readiness constructs, we present a set of composite variables, as well as corresponding observable variables. We conclude with implications of our analysis for theory and practice, and set directions for future research

    Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks

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    A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One way of such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable to establish a common focus of attention and be able to use and integrate spoken instructions, visual perceptions, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and an modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.Comment: 7 pages, 8 figure

    Functional Diversity and Structural Disorder in the Human Ubiquitination Pathway

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    The ubiquitin-proteasome system plays a central role in cellular regulation and protein quality control (PQC). The system is built as a pyramid of increasing complexity, with two E1 (ubiquitin activating), few dozen E2 (ubiquitin conjugating) and several hundred E3 (ubiquitin ligase) enzymes. By collecting and analyzing E3 sequences from the KEGG BRITE database and literature, we assembled a coherent dataset of 563 human E3s and analyzed their various physical features. We found an increase in structural disorder of the system with multiple disorder predictors (IUPred - E1: 5.97%, E2: 17.74%, E3: 20.03%). E3s that can bind E2 and substrate simultaneously (single subunit E3, ssE3) have significantly higher disorder (22.98%) than E3s in which E2 binding (multi RING-finger, mRF, 0.62%), scaffolding (6.01%) and substrate binding (adaptor/substrate recognition subunits, 17.33%) functions are separated. In ssE3s, the disorder was localized in the substrate/adaptor binding domains, whereas the E2-binding RING/HECT-domains were structured. To demonstrate the involvement of disorder in E3 function, we applied normal modes and molecular dynamics analyses to show how a disordered and highly flexible linker in human CBL (an E3 that acts as a regulator of several tyrosine kinase-mediated signalling pathways) facilitates long-range conformational changes bringing substrate and E2-binding domains towards each other and thus assisting in ubiquitin transfer. E3s with multiple interaction partners (as evidenced by data in STRING) also possess elevated levels of disorder (hubs, 22.90% vs. non-hubs, 18.36%). Furthermore, a search in PDB uncovered 21 distinct human E3 interactions, in 7 of which the disordered region of E3s undergoes induced folding (or mutual induced folding) in the presence of the partner. In conclusion, our data highlights the primary role of structural disorder in the functions of E3 ligases that manifests itself in the substrate/adaptor binding functions as well as the mechanism of ubiquitin transfer by long-range conformational transitions. © 2013 Bhowmick et al

    Anticipation and Risk – From the inverse problem to reverse computation

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    Abstract. Risk assessment is relevant only if it has predictive relevance. In this sense, the anticipatory perspective has yet to contribute to more adequate predictions. For purely physics-based phenomena, predictions are as good as the science describing such phenomena. For the dynamics of the living, the physics of the matter making up the living is only a partial description of their change over time. The space of possibilities is the missing component, complementary to physics and its associated predictions based on probabilistic methods. The inverse modeling problem, and moreover the reverse computation model guide anticipatory-based predictive methodologies. An experimental setting for the quantification of anticipation is advanced and structural measurement is suggested as a possible mathematics for anticipation-based risk assessment
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