41 research outputs found

    AIG Emails between Joe Cassano Andrew Forster William Dooley and Elias Habayeb regarding collateral calls

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    AIG Joe Cassano to Bill Dooley 2007 compensation email

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    Goldman Sachs Email from Thomas Harrop to Andrew Davilman Re AIG

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    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    The Importance of Getting Names Right: The Myth of Markets for Water

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    Estimation of Sparse Memory Taps for RF Power Amplifier Behavioral Models

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    When a larger than required dimension such as memory depth or order of nonlinearity, is specified during behavioral model extraction, redundant terms can be calculated when determining the weights of the model. Extraction of a behavioral model can therefore benefit from a priori knowledge of the system to be modeled. Conversely if there is a limitation in the hardware required to calculate model outputs a limit can be set for the maximum number of weights to be used. In this letter, an approach is proposed which allows the input delay vector to be reduced to a sparse vector including the delayed samples which are most important in the construction of the power amplifier model. Simulations of behavioral models for experimentally measured data of two different PAs demonstrates the sparse models extracted in this way are as accurate as a full model but have a more compact and as a result more computationally efficient structure

    Estimation of Sparse Memory Taps for RF Power Amplifier Behavioral Models

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