56,960 research outputs found

    Reciprocatory magnetic reconnection in a coronal bright point

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    Coronal bright points (CBPs) are small-scale and long-duration brightenings in the lower solar corona. They are often explained in terms of magnetic reconnection. We aim to study the sub-structures of a CBP and clarify the relationship among the brightenings of different patches inside the CBP. The event was observed by the X-ray Telescope (XRT) aboard the Hinode spacecraft on 2009 August 22−-23. The CBP showed repetitive brightenings (or CBP flashes). During each of the two successive CBP flashes, i.e., weak and strong flashes which are separated by ∼\sim2 hr, the XRT images revealed that the CBP was composed of two chambers, i.e., patches A and B. During the weak flash, patch A brightened first, and patch B brightened ∼\sim2 min later. During the transition, the right leg of a large-scale coronal loop drifted from the right side of the CBP to the left side. During the strong flash, patch B brightened first, and patch A brightened ∼\sim2 min later. During the transition, the right leg of the large-scale coronal loop drifted from the left side of the CBP to the right side. In each flash, the rapid change of the connectivity of the large-scale coronal loop is strongly suggestive of the interchange reconnection. For the first time we found reciprocatory reconnection in the CBP, i.e., reconnected loops in the outflow region of the first reconnection process serve as the inflow of the second reconnection process.Comment: 13 pages, 8 figure

    A Crevice on the Crane Beach: Finite-Degree Predicates

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    First-order logic (FO) over words is shown to be equiexpressive with FO equipped with a restricted set of numerical predicates, namely the order, a binary predicate MSB0_0, and the finite-degree predicates: FO[Arb] = FO[<, MSB0_0, Fin]. The Crane Beach Property (CBP), introduced more than a decade ago, is true of a logic if all the expressible languages admitting a neutral letter are regular. Although it is known that FO[Arb] does not have the CBP, it is shown here that the (strong form of the) CBP holds for both FO[<, Fin] and FO[<, MSB0_0]. Thus FO[<, Fin] exhibits a form of locality and the CBP, and can still express a wide variety of languages, while being one simple predicate away from the expressive power of FO[Arb]. The counting ability of FO[<, Fin] is studied as an application.Comment: Submitte

    On the canonical base property

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    We give an example of a finite rank, in fact aleph-1 categorical theory where the CBP (canonical base property) does not hold. We include a "group-like" example. We also prove, in a finite Morley rank context, if all definable Galois groups are "rigid" then the theory has the CBP (in a strong sense).Comment: 15 page

    Overestimation in the Traditional GARCH Model During Jump Periods

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    The traditional continuous and smooth models, like the GARCH model, may fail to capture extreme returns volatility. Therefore, this study applies the bivariate poisson (CBP)-GARCH model to study jump dynamics in price volatility of crude oil and heating oil during the past 20 years. The empirical results indicate that the variance and covariance of the GARCH and CBP-GARCH models were found to be similar in low jump intensity periods and to diverge during jump events. Significant overestimations occur during high jump time periods in the GARCH model because of assumptions of continuity, and easily leading to excessive hedging and overly measuring risk. Nevertheless, in the CBP-GARCH model, the specific shocks are assumed to be independent of normal volatility and to reduce the persistence of abnormal volatility. Therefore, the CBP-GARCH model is appropriate and necessary in high volatility markets.Jumps Overestimation Volatility CBP-GARCH model

    National Evaluation of the Capacity Building Programme in English Local Government: Overall Final Report

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    This report is one of a series of outputs from the National Evaluation of the Capacity Building Programme for local government in England (CBP), undertaken by a team of researchers at the Policy Research Institute (PRI) at Leeds Metropolitan University and the Cities Research Unit at the University of West of England. This report summarises the findings from all four key strands of the evaluation. Because of the difficulties associated with quantifying the capacity of local authorities, much less the sector, in relation to the dynamic roles and objectives that they pursue, the report focuses on what has worked, why and in what circumstances, rather than providing a definitive assessment of the extent of change of capacity building enabled by the CBP. The CBP was launched in 2003 as a joint Department for Communities and Local Government/Local Government Association (LGA) initiative to support capacity building and improvement activities within local authorities in England. The CBP has supported four main streams of improvement and capacity building activity in local authorities (see Section 1.2; p13)

    Storing and Indexing Plan Derivations through Explanation-based Analysis of Retrieval Failures

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    Case-Based Planning (CBP) provides a way of scaling up domain-independent planning to solve large problems in complex domains. It replaces the detailed and lengthy search for a solution with the retrieval and adaptation of previous planning experiences. In general, CBP has been demonstrated to improve performance over generative (from-scratch) planning. However, the performance improvements it provides are dependent on adequate judgements as to problem similarity. In particular, although CBP may substantially reduce planning effort overall, it is subject to a mis-retrieval problem. The success of CBP depends on these retrieval errors being relatively rare. This paper describes the design and implementation of a replay framework for the case-based planner DERSNLP+EBL. DERSNLP+EBL extends current CBP methodology by incorporating explanation-based learning techniques that allow it to explain and learn from the retrieval failures it encounters. These techniques are used to refine judgements about case similarity in response to feedback when a wrong decision has been made. The same failure analysis is used in building the case library, through the addition of repairing cases. Large problems are split and stored as single goal subproblems. Multi-goal problems are stored only when these smaller cases fail to be merged into a full solution. An empirical evaluation of this approach demonstrates the advantage of learning from experienced retrieval failure.Comment: See http://www.jair.org/ for any accompanying file
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