14 resultados para May, George (Doc)

em Boston University Digital Common


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A sermon preached to the General Assembly reporting on the mission efforts of the church.

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sermon text; MS Word document

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http://www.archive.org/details/bolengeastoryofg00dyeeuoft

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http://www.archive.org/details/metlakahtltruena00davirich

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http://www.archive.org/details/equatorssnowype00crawuoft

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Boston University Theology Library

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http://www.archive.org/details/addressesofrevdr00parkuoft

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http://www.archive.org/details/hawaiianislandsa00peabiala

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Postal card to George Whitaker. Mailed from Ocean Grove, NJ. Dated June 27, 1881.

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The problem of discovering frequent poly-regions (i.e. regions of high occurrence of a set of items or patterns of a given alphabet) in a sequence is studied, and three efficient approaches are proposed to solve it. The first one is entropy-based and applies a recursive segmentation technique that produces a set of candidate segments which may potentially lead to a poly-region. The key idea of the second approach is the use of a set of sliding windows over the sequence. Each sliding window covers a sequence segment and keeps a set of statistics that mainly include the number of occurrences of each item or pattern in that segment. Combining these statistics efficiently yields the complete set of poly-regions in the given sequence. The third approach applies a technique based on the majority vote, achieving linear running time with a minimal number of false negatives. After identifying the poly-regions, the sequence is converted to a sequence of labeled intervals (each one corresponding to a poly-region). An efficient algorithm for mining frequent arrangements of intervals is applied to the converted sequence to discover frequently occurring arrangements of poly-regions in different parts of DNA, including coding regions. The proposed algorithms are tested on various DNA sequences producing results of significant biological meaning.

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Co-release of the inhibitory neurotransmitter GABA and the neuropeptide substance-P (SP) from single axons is a conspicuous feature of the basal ganglia, yet its computational role, if any, has not been resolved. In a new learning model, co-release of GABA and SP from axons of striatal projection neurons emerges as a highly efficient way to compute the uncertainty responses that are exhibited by dopamine (DA) neurons when animals adapt to probabilistic contingencies between rewards and the stimuli that predict their delivery. Such uncertainty-related dopamine release appears to be an adaptive phenotype, because it promotes behavioral switching at opportune times. Understanding the computational linkages between SP and DA in the basal ganglia is important, because Huntington's disease is characterized by massive SP depletion, whereas Parkinson's disease is characterized by massive DA depletion.