86 resultados para target market


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Recent research has begun to provide support for the assumptions that memories are stored as a composite and are accessed in parallel (Tehan & Humphreys, 1998). New predictions derived from these assumptions and from the Chappell and Humphreys (1994) implementation of these assumptions were tested. In three experiments, subjects studied relatively short lists of words. Some of the Lists contained two similar targets (thief and theft) or two dissimilar targets (thief and steal) associated with the same cue (ROBBERY). AS predicted, target similarity affected performance in cued recall but not free association. Contrary to predictions, two spaced presentations of a target did not improve performance in free association. Two additional experiments confirmed and extended this finding. Several alternative explanations for the target similarity effect, which incorporate assumptions about separate representations and sequential search, are rejected. The importance of the finding that, in at least one implicit memory paradigm, repetition does not improve performance is also discussed.

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While a considerable number of candidate Myb target genes have been reported to date, most of these are likely to play little or no role in transformation by myb oncogenes. Here we have used a conditionally myb-transformed myeloid cell line (ERMYB) to further examine Myb regulation of one candidate target gene-c-myc-that has the potential to affect cell proliferation. It was found that the major influence on c-myc expression was the presence of cytokine (GM-CSF) rather than Myb activity. We also describe the application of PCR-based subtractive hybridization and low-density cDNA array screening, in conjunction with the ERMYB line, to the identification of additional Myb target genes. Preliminary identification of a number of candidates is reported; these include myeloperoxidase, which is known to have essential Myb-binding sites in its regulatory region. (C) 2001 Academic Press.

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Realistic time frames in which management decisions are made often preclude the completion of the detailed analyses necessary for conservation planning. Under these circumstances, efficient alternatives may assist in approximating the results of more thorough studies that require extensive resources and time. We outline a set of concepts and formulas that may be used in lieu of detailed population viability analyses and habitat modeling exercises to estimate the protected areas required to provide desirable conservation outcomes for a suite of threatened plant species. We used expert judgment of parameters and assessment of a population size that results in a specified quasiextinction risk based on simple dynamic models The area required to support a population of this size is adjusted to take into account deterministic and stochastic human influences, including small-scale disturbance deterministic trends such as habitat loss, and changes in population density through processes such as predation and competition. We set targets for different disturbance regimes and geographic regions. We applied our methods to Banksia cuneata, Boronia keysii, and Parsonsia dorrigoensis, resulting in target areas for conservation of 1102, 733, and 1084 ha, respectively. These results provide guidance on target areas and priorities for conservation strategies.

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In a magnetic resonance imaging equipment, gradient and shim coils are needed to produce a spatially varying magnetic field throughout the sample being imaged. Such coils consist of turns of wire wound on the surface of a cylindrical tube. Shim coils in particular, must sometimes be designed to produce complicated magnetic fields to correct for impurities. Streamline patterns for shim coils are much more complicated than those for gradient coils, In this work we present a detailed analysis of streamline methods and their application to shim coil design, A method is presented for determining the winding patterns to generate these complicated fields. (C) 2002 John Wiley & Sons, Inc.

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This article examines the efficiency of the National Football League (NFL) betting market. The standard ordinary least squares (OLS) regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows us to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In-sample tests indicate that probit-based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out-of-sample testing, there is some inconsistency among the remaining out-of-sample predictions. Our results also suggest that widely documented inefficiencies in this market tend to dissipate over time.

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