976 resultados para G-Functions
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"November 18 (legislative day, November 17), 2005."
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Mode of access: Internet.
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Mode of access: Internet.
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This note shows that, under appropriate conditions, preferences may be locally approximated by the linear utility or risk-neutral preference functional associated with a local probability transformation.
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Numerous studies in the last 60 years have investigated the relationship between land slope and soil erosion rates. However, relatively few of these have investigated slope gradient responses: ( a) for steep slopes, (b) for specific erosion processes, and ( c) as a function of soil properties. Simulated rainfall was applied in the laboratory on 16 soils and 16 overburdens at 100 mm/h to 3 replicates of unconsolidated flume plots 3 m long by 0.8 m wide and 0.15 m deep at slopes of 20, 5, 10, 15, and 30% slope in that order. Sediment delivery at each slope was measured to determine the relationship between slope steepness and erosion rate. Data from this study were evaluated alongside data and existing slope adjustment functions from more than 55 other studies from the literature. Data and the literature strongly support a logistic slope adjustment function of the form S = A + B/[1 + exp (C - D sin theta)] where S is the slope adjustment factor and A, B, C, and D are coefficients that depend on the dominant detachment and transport processes. Average coefficient values when interill-only processes are active are A - 1.50, B 6.51, C 0.94, and D 5.30 (r(2) = 0.99). When rill erosion is also potentially active, the average slope response is greater and coefficient values are A - 1.12, B 16.05, C 2.61, and D 8.32 (r(2) = 0.93). The interill-only function predicts increases in sediment delivery rates from 5 to 30% slope that are approximately double the predictions based on existing published interill functions. The rill + interill function is similar to a previously reported value. The above relationships represent a mean slope response for all soils, yet the response of individual soils varied substantially from a 2.5-fold to a 50-fold increase over the range of slopes studied. The magnitude of the slope response was found to be inversely related ( log - log linear) to the dispersed silt and clay content of the soil, and 3 slope adjustment equations are proposed that provide a better estimate of slope response when this soil property is known. Evaluation of the slope adjustment equations proposed in this paper using independent datasets showed that the new equations can improve soil erosion predictions.
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We have used the Two-Degree Field (2dF) instrument on the Anglo-Australian Telescope (AAT) to obtain redshifts of a sample of z < 3 and 18.0 < g < 21.85 quasars selected from Sloan Digital Sky Survey (SDSS) imaging. These data are part of a larger joint programme between the SDSS and 2dF communities to obtain spectra of faint quasars and luminous red galaxies, namely the 2dF-SDSS LRG and QSO (2SLAQ) Survey. We describe the quasar selection algorithm and present the resulting number counts and luminosity function of 5645 quasars in 105.7 deg(2). The bright-end number counts and luminosity functions agree well with determinations from the 2dF QSO Redshift Survey (2QZ) data to g similar to 20.2. However, at the faint end, the 2SLAQ number counts and luminosity functions are steeper (i.e. require more faint quasars) than the final 2QZ results from Croom et al., but are consistent with the preliminary 2QZ results from Boyle et al. Using the functional form adopted for the 2QZ analysis ( a double power law with pure luminosity evolution characterized by a second-order polynomial in redshift), we find a faint-end slope of beta =-1.78 +/- 0.03 if we allow all of the parameters to vary, and beta =-1.45 +/- 0.03 if we allow only the faint-end slope and normalization to vary (holding all other parameters equal to the final 2QZ values). Over the magnitude range covered by the 2SLAQ survey, our maximum-likelihood fit to the data yields 32 per cent more quasars than the final 2QZ parametrization, but is not inconsistent with other g > 21 deep surveys for quasars. The 2SLAQ data exhibit no well-defined 'break' in the number counts or luminosity function, but do clearly flatten with increasing magnitude. Finally, we find that the shape of the quasar luminosity function derived from 2SLAQ is in good agreement with that derived from Type I quasars found in hard X-ray surveys.
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Based on clues from epidemiology, low prenatal vitamin D has been proposed as a candidate risk factor for schizophrenia. Recent animal experiments have demonstrated that transient prenatal vitamin D deficiency is associated with persistent alterations in brain morphology and neurotrophin expression. In order to explore the utility of the vitamin D animal model of schizophrenia, we examined different types of learning and memory in adult rats exposed to transient prenatal vitamin D deficiency. Compared to control animals, the prenatally deplete animals had a significant impairment of latent inhibition, a feature often associated with schizophrenia. In addition, the deplete group was (a) significantly impaired on hole board habituation and (b) significantly better at maintaining previously learnt rules of brightness discrimination in a Y-chamber. In contrast, the prenatally deplete animals showed no impairment on the spatial learning task in the radial maze, nor on two-way active avoidance learning in the shuttle-box. The results indicate that transient prenatal vitamin D depletion in the rat is associated with subtle and discrete alterations in learning and memory. The behavioural phenotype associated with this animal model may provide insights into the neurobiological correlates of the cognitive impairments of schizophrenia. (c) 2005 Elsevier B.V. All rights reserved.
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Mutations in the Hedgehog receptor, Patched 1 (Ptch1), have been linked to both familial and sporadic forms of basal cell carcinoma (BCC), leading to the hypothesis that loss of Ptch1 function is sufficient for tumor progression. By combining conditional knockout technology with the inducible activity of the Keratin6 promoter, we provide in vivo evidence that loss of Ptch1 function from the basal cell population of mouse skin is sufficient to induce rapid skin tumor formation, reminiscent of human BCC. Elimination of Ptch1 does not promote the nuclear translocation of beta-catenin and does not induce ectopic activation or expression of Notch pathway constituents. In the absence of Ptch1, however, a large proportion of basal cells exhibit nuclear accumulation of the cell cycle regulators cyclin D1 and B1. Collectively, our data suggest that Ptch1 likely functions as a tumor suppressor by inhibiting G(1)-S phase and G(2)-M phase cell cycle progression, and the rapid onset of tumor progression clearly indicates Ptch1 functions as a gatekeeper. In addition, we note the high frequency and rapid onset of tumors in this mouse model makes it an ideal system for testing therapeutic strategies, such as Patched pathway inhibitors.
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The G-protein coupled receptors--or GPCRs--comprise simultaneously one of the largest and one of the most multi-functional protein families known to modern-day molecular bioscience. From a drug discovery and pharmaceutical industry perspective, the GPCRs constitute one of the most commercially and economically important groups of proteins known. The GPCRs undertake numerous vital metabolic functions and interact with a hugely diverse range of small and large ligands. Many different methodologies have been developed to efficiently and accurately classify the GPCRs. These range from motif-based techniques to machine learning as well as a variety of alignment-free techniques based on the physiochemical properties of sequences. We review here the available methodologies for the classification of GPCRs. Part of this work focuses on how we have tried to build the intrinsically hierarchical nature of sequence relations, implicit within the family, into an adaptive approach to classification. Importantly, we also allude to some of the key innate problems in developing an effective approach to classifying the GPCRs: the lack of sequence similarity between the six classes that comprise the GPCR family and the low sequence similarity to other family members evinced by many newly revealed members of the family.
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We address the important bioinformatics problem of predicting protein function from a protein's primary sequence. We consider the functional classification of G-Protein-Coupled Receptors (GPCRs), whose functions are specified in a class hierarchy. We tackle this task using a novel top-down hierarchical classification system where, for each node in the class hierarchy, the predictor attributes to be used in that node and the classifier to be applied to the selected attributes are chosen in a data-driven manner. Compared with a previous hierarchical classification system selecting classifiers only, our new system significantly reduced processing time without significantly sacrificing predictive accuracy.