1,376 research outputs found

    A systematic study of the lizards of the deppei group (Genus Cnemidophorus) in Mexico and Guatemala

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    http://deepblue.lib.umich.edu/bitstream/2027.42/56355/1/MP111.pd

    Decentralized Supply Chain Formation: A Market Protocol and Competitive Equilibrium Analysis

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    Supply chain formation is the process of determining the structure and terms of exchange relationships to enable a multilevel, multiagent production activity. We present a simple model of supply chains, highlighting two characteristic features: hierarchical subtask decomposition, and resource contention. To decentralize the formation process, we introduce a market price system over the resources produced along the chain. In a competitive equilibrium for this system, agents choose locally optimal allocations with respect to prices, and outcomes are optimal overall. To determine prices, we define a market protocol based on distributed, progressive auctions, and myopic, non-strategic agent bidding policies. In the presence of resource contention, this protocol produces better solutions than the greedy protocols common in the artificial intelligence and multiagent systems literature. The protocol often converges to high-value supply chains, and when competitive equilibria exist, typically to approximate competitive equilibria. However, complementarities in agent production technologies can cause the protocol to wastefully allocate inputs to agents that do not produce their outputs. A subsequent decommitment phase recovers a significant fraction of the lost surplus

    Resistant tissues of modern marchantioid liverworts resemble enigmatic Early Paleozoic microfossils

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    Absence of a substantial pretracheophyte fossil record for bryophytes (otherwise predicted by molecular systematics) poses a major problem in our understanding of earliest land-plant structure. In contrast, there exist enigmatic Cambrian–Devonian microfossils (aggregations of tubes or sheets of cells or possibly a combination of both) controversially interpreted as an extinct group of early land plants known as nematophytes. We used an innovative approach to explore these issues: comparison of tube and cell-sheet microfossils with experimentally degraded modern liverworts as analogues of ancient early land plants. Lower epidermal surface tissues, including rhizoids, of Marchantia polymorpha and Conocephalum conicum were resistant to breakdown after rotting for extended periods or high-temperature acid treatment (acetolysis), suggesting fossilization potential. Cell-sheet and rhizoid remains occurred separately or together depending on the degree of body degradation. Rhizoid break-off at the lower epidermal surface left rimmed pores at the centers of cell rosettes; these were similar in structure, diameter, and distribution to pores characterizing nematophyte cell-sheet microfossils known as Cosmochlaina. The range of Marchantia rhizoid diameters overlapped that of Cosmochlaina pores. Approximately 14% of dry biomass of Marchantia vegetative thalli and 40% of gametangiophores was resistant to acetolysis. Pre- and posttreatment cell-wall autofluorescence suggested the presence of phenolic compounds that likely protect lower epidermal tissues from soil microbe attack and provide dimensional stability to gametangiophores. Our results suggest that at least some microfossils identified as nematophytes may be the remains of early marchantioid liverworts similar in some ways to modern Marchantia and Conocephalum

    Rational bidding using reinforcement learning: an application in automated resource allocation

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    The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one decentralized

    Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services

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    The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms

    Being proven wrong elicits learning in children - but only in those with higher executive function skills

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    This study investigated whether prompting children to generate predictions about an outcome facilitates activation of prior knowledge and improves belief revision. 51 children aged 9-12 were tested on two experimental tasks in which generating a prediction was compared to closely matched control conditions, as well as on a test of executive functions (EF). In Experiment 1, we showed that children exhibited a pupillary surprise response to events that they had predicted incorrectly, hypothesized to reflect the transient release of noradrenaline in response to cognitive conflict. However, children\u27s surprise response was not associated with better belief revision, in contrast to a previous study involving adults. Experiment 2 revealed that, while generating predictions helped children activate their prior knowledge, only those with better inhibitory control skills learned from incorrectly predicted outcomes. Together, these results suggest that good inhibitory control skills are needed for learning through cognitive conflict. Thus, generating predictions benefits learning - but only among children with sufficient EF capacities to harness surprise for revising their beliefs. (DIPF/Orig.

    Using models of the ocean's mean dynamic topography to identify errors in coastal geodetic levelling

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    Identifying errors (blunders and systematic errors) in coastal geodetic levelling networks has often been problematic. This is because (1) mean sea level (MSL) at tide gauges cannot be directly compared to height differences from levelling because the geoid/quasigeoid and MSL are not parallel, being separated by the ocean’s mean dynamic topography (MDT) and (2) the lack of redundancy at the edge of the levelling network. This paper sets out a methodology to independently identify blunders and/or systematic errors (over long distances) in geodetic levelling using MDT models to account for the separation between the geoid/quasigeoid and MSL at tide gauges. This method is then tested in a case study using an oceanographic MDT model, MSL observations, GNSS data and a quasigeoid model. The results are significant because the errors found could not be detected by standard levelling misclosure checks alone, with supplementary data from an MDT model, with cross-validation from GNSS-quasigeoid allowing their detection. In addition, it appears that an oceanographic-only MDT is as effective as GNSS and a quasigeoid model for detecting levelling errors, which could be particularly useful for countries with coastal levelling errors in their levelling networks that cannot be identified by conventional levelling closure checks

    The practical other : teleology and its development

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    We argue for teleology as a description of the way in which we ordinarily understand others’ intentional actions. Teleology starts from the close resemblance between the reasoning involved in understanding others’ actions and one’s own practical reasoning involved in deciding what to do. We carve out teleology’s distinctive features more sharply by comparing it to its three main competitors: theory theory, simulation theory, and rationality theory. The plausibility of teleology as our way of understanding others is underlined by developmental data in its favour
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