37,201 research outputs found

    Improved Time-Domain Accuracy Standards for Model Gravitational Waveforms

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    Model gravitational waveforms must be accurate enough to be useful for detection of signals and measurement of their parameters, so appropriate accuracy standards are needed. Yet these standards should not be unnecessarily restrictive, making them impractical for the numerical and analytical modelers to meet. The work of Lindblom, Owen, and Brown [Phys. Rev. D 78, 124020 (2008)] is extended by deriving new waveform accuracy standards which are significantly less restrictive while still ensuring the quality needed for gravitational-wave data analysis. These new standards are formulated as bounds on certain norms of the time-domain waveform errors, which makes it possible to enforce them in situations where frequency-domain errors may be difficult or impossible to estimate reliably. These standards are less restrictive by about a factor of 20 than the previously published time-domain standards for detection, and up to a factor of 60 for measurement. These new standards should therefore be much easier to use effectively.Comment: 10 pages, 5 figure

    Ancient DNA from coral-hosted Symbiodinium reveal a static mutualism over the last 172 years.

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    Ancient DNA (aDNA) provides powerful evidence for detecting the genetic basis for adaptation to environmental change in many taxa. Among the greatest of changes in our biosphere within the last century is rapid anthropogenic ocean warming. This phenomenon threatens corals with extinction, evidenced by the increasing observation of widespread mortality following mass bleaching events. There is some evidence and conjecture that coral-dinoflagellate symbioses change partnerships in response to changing external conditions over ecological and evolutionary timescales. Until now, we have been unable to ascertain the genetic identity of Symbiodinium hosted by corals prior to the rapid global change of the last century. Here, we show that Symbiodinium cells recovered from dry, century old specimens of 6 host species of octocorals contain sufficient DNA for amplification of the ITS2 subregion of the nuclear ribosomal DNA, commonly used for genotyping within this genus. Through comparisons with modern specimens sampled from similar locales we show that symbiotic associations among several species have been static over the last century, thereby suggesting that adaptive shifts to novel symbiont types is not common among these gorgonians, and perhaps, symbiotic corals in general

    Intellectual Property Disclosure as 'Threat'

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    This paper models the disclosure of knowledge via licensing to outsiders or fringe firms as a threat, useful in ensuring firms keep their commitments. We show that firms holding intellectual property are better able to enforce agreements than firms that don't. In markets requiring innovation to make a product, IP disclosure presents a more powerful threat than entry by the punishing firm alone. Occasionally, a punishing firm won't be able to translate its intellectual property into a full-blown product, making it impossible for it to enter the cheating firm's market and punish. Even if it can't make a product itself, the punishing firm can always credibly threaten to license the intellectual property it has on hand to someone else. With this intellectual property as a springboard, chances are at least one fringe firm will be able to do the translation, make the product and enter the cheating firm's market. In short, the potential for licensing increases the likelihood of punishment for uncooperative behavior.In the model, firms contract explicitly to ex-change knowledge and tacitly to coordinate the introduction of innovations to the marketplace. We find conditions under which firms can self-enforce both agreements. The enforcement conditions are weaker when (1) firms possess knowledge and (2) knowledge is easily transferable to other firms. The disclosure threat has implications for antitrust law generally, which are considered.

    Intellectual Property Disclosure as “Threat”

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    This paper models the disclosure of knowledge as a "threat", useful in ensuring firms keep their commitments. We show that firms holding knowledge are better able to enforce agreements than firms that don’t. In markets requiring innovation to make a product, disclosure is a more powerful threat than entry by the punishing firm alone. Occasionally, the punishing firm won’t be able to innovate, making it impossible for it to enter the cheating firm’s market and punish. The punishing firm, however, can through disclosure credibly ensure that one, if not many, firms enter the cheating firm’s market. In the model, firms contract explicitly to exchange knowledge and tacitly to coordinate the introduction of innovations to the marketplace. We find conditions under which firms can self-enforce both agreements. The enforcement conditions are weaker when (1) firms possess knowledge and (2) knowledge is easily transferable to other firms. The disclosure threat has implication for antitrust law generally, which are considered.

    Guest Editorial

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    Vaccination saves lives – dare we allow the anti-vaccine lobbyists to prevent it

    When is an error not a prediction error? An electrophysiological investigation

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    A recent theory holds that the anterior cingulate cortex (ACC) uses reinforcement learning signals conveyed by the midbrain dopamine system to facilitate flexible action selection. According to this position, the impact of reward prediction error signals on ACC modulates the amplitude of a component of the event-related brain potential called the error-related negativity (ERN). The theory predicts that ERN amplitude is monotonically related to the expectedness of the event: It is larger for unexpected outcomes than for expected outcomes. However, a recent failure to confirm this prediction has called the theory into question. In the present article, we investigated this discrepancy in three trial-and-error learning experiments. All three experiments provided support for the theory, but the effect sizes were largest when an optimal response strategy could actually be learned. This observation suggests that ACC utilizes dopamine reward prediction error signals for adaptive decision making when the optimal behavior is, in fact, learnable
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