6,667 research outputs found

    Fundamentals of the oxidation protection of columbium and tantalum Semiannual report, Apr. 1 - Oct. 1, 1967

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    Oxidation protection of niobium and tantalum by their silicide

    Fundamentals of the oxidation protection of columbium and tantalum Semiannual report, 1 Apr. - 1 Oct. 1969

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    Oxidation protection by silicides of niobium and tantalum, and thermochemical dat

    Fundamentals of the oxidation protection of tantalum Final report

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    Fundamentals of oxidation protection of tantalum by silicide

    The Magnitude of Random Appraisal Error in Commercial Real Estate Valuation

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    Analysis of more than seven hundred pairs of simultaneous independent appraisals of institutional-grade commercial properties shows that the standard deviation of the random component of appraisal error is approximately 2%. Random appraisal error appears constant across both time and the institutional-grade investment universe, except during infrequent periods of real estate market gridlock. Most appraisal error is deterministic in nature, even though it usually appears random in routine cross-sectional analysis. Such appraisal error can be constrained and reduced by investment management control systems.

    Serial Persistence in Equity REIT Returns

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    Annual and monthly REIT returns display statistically significant serial persistence, although the two types of persistence behavior are qualitatively different. By contrast, quarterly REIT returns do not display serial persistence. This strongly suggests that linear multifactor market models cannot describe REIT investment behavior. Annual REIT returns fail to reflect corresponding persistence behavior in underlying real estate returns precisely when the REITs are large enough to attract institutional investor interest. Institutional investors move in and out of large-capitalization REITs in ways that negatively impact investment returns.

    Systematic Behavior in Real Estate Investment Risk: Performance Persistence in NCREIF Returns

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    Serial dependence of total annual returns in the NCREIF database is shown to be statistically significant in the first and fourth quartiles of disaggregated data between 1978 and 1994. More precisely, superior performance is generally followed by continued superior performance, and inferior performance is generally followed by continued inferior performance. In contrast, there is virtually no evidence to support serial dependence in the second or third quartiles, whether combined or taken separately. The empirical rejection of serial independence among real estate returns calls into question the conclusions of research based upon models that incorporate the assumption of serial independence.

    The Shape of Australian Real Estate Return Distributions and Comparisons to the United States

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    Investment risk models with variance provide a better description of distribution of individual property returns in the Property Council of Australia data base from 1985 to 1996 than normally distributed risk models. The shape of the distribution of Australian property returns is virtually indistinguishable from the shape of United States property returns in the NCREIF Property Index for the years 1980 to 1992. Australian real estate investment risk is heteroscedastic, like its US counterpart, but the characteristic exponent of the investment risk function is constant across time and property type. It follows that portfolio management and asset diversification techniques that rely upon finite-variance statistics are as ineffectual for the Australian real estate market as they have been found to be for the United States.

    Role of Proteome Physical Chemistry in Cell Behavior.

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    We review how major cell behaviors, such as bacterial growth laws, are derived from the physical chemistry of the cell's proteins. On one hand, cell actions depend on the individual biological functionalities of their many genes and proteins. On the other hand, the common physics among proteins can be as important as the unique biology that distinguishes them. For example, bacterial growth rates depend strongly on temperature. This dependence can be explained by the folding stabilities across a cell's proteome. Such modeling explains how thermophilic and mesophilic organisms differ, and how oxidative damage of highly charged proteins can lead to unfolding and aggregation in aging cells. Cells have characteristic time scales. For example, E. coli can duplicate as fast as 2-3 times per hour. These time scales can be explained by protein dynamics (the rates of synthesis and degradation, folding, and diffusional transport). It rationalizes how bacterial growth is slowed down by added salt. In the same way that the behaviors of inanimate materials can be expressed in terms of the statistical distributions of atoms and molecules, some cell behaviors can be expressed in terms of distributions of protein properties, giving insights into the microscopic basis of growth laws in simple cells
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