Since all long-distance trade in the Roman world travelled by water, Roman harbour design and construction have special importance. Harbour excavation must be supplemented by analysis of the components of the hydraulic concrete, structural analysis of the cementing materials, and consideration of the design of the wooden formwork. The authors have begun collecting large cores from concrete blocks at Roman harbours and other maritime structures, analysing the materials used, the method of placement, and the structural characteristics of the resulting concrete. These data have provided new information on the engineering properties of Roman concrete, the process of funding and execution, and the trade in the volcanic ash which was the crucial component of hydraulic concrete.
A quantitative understanding of how proteins interact with hydrophobic charge induction chromatographic resins is provided. Selectivity on this mode of chromatography for monoclonal antibodies as compared to other model proteins is probed by means of a linear retention vs pH plot. The pH-dependent adsorption behavior on this mode of chromatography for a hydrophobic, charged solute is described by taking into account the equilibrium between a hydrophobic, charged solute and an ionizable, heterocyclic ligand. By analogy, an equation that is seen to adequately describe macromolecular retention under linear conditions over a range of pH is developed. A preparative, nonlinear isotherm that can capture both pH and salt concentration dependency for proteins is proposed by using an exponentially modified Langmuir isotherm model. This model is seen to successfully simulate adsorption isotherms for a variety of proteins over a range of pHs and mobile phase salt concentrations. Finally, the widely differing retention characteristics of two monoclonal antibodies are used to derive two different strategies for improving separations on this mode of chromatography. A better understanding of protein binding to this class of resins is seen as an important step to future exploitation of this mode of chromatography for industrial scale purification of proteins.
The elastic properties of earlywood and latewood and their variability were measured in 388 specimens from six loblolly pine trees in a commercial plantation. Properties measured included longitudinal modulus of elasticity, shear modulus, specific gravity, microfibril angle and presence of compression wood. Novel testing procedures were developed to measure properties from specimens of 1 mm=1 mm=30 mm from earlywood or latewood. The elastic properties varied substantially circumferentially around a given ring and this variation was nearly as large as the variation across rings. The elastic properties varied by ring and height, but while the modulus of elasticity increased with height, the shear modulus decreased with height. A strong correlation was found between modulus of elasticity and shear modulus, but only at low heights and inner rings. Specific gravity and microfibril angle were the strongest predictors of elastic properties and explained 75% of the variation in modulus of elasticity for latewood. Despite being the best predictors in this study, these parameters accounted for less than half of the variability of earlywood modulus of elasticity, earlywood shear modulus and latewood shear modulus.
A technique is presented for the high-throughput screening of ion-exchange displacers. Potential displacers were employed to displace proteins in parallel batch ion-exchange experiments. The percentage of protein displaced from a particular stationary phase was then used as a parameter to rank the displacers. By employing this technique, a large number of molecules possessing a range of affinities and properties could be rapidly evaluated. This data was then used together with traditional and electron density-based transferable atom equivalent (TAE) molecular descriptors computed for the displacer molecules to produce quantitative structure-efficacy relationship (QSER) models using a genetic algorithm/partial least squares (GA/PLS) regression approach. The QSER models were generated using a portion of the protein-displacement data, with the remainder serving as a test set. Descriptor selection and model building was accomplished using a genetic algorithm/partial least squares approach. The resulting models were found to have high-correlation coefficients and could be used to accurately predict the behavior of molecules not included in the training set. In addition, the models were employed to examine a virtual library of displacers based on modifications of neomycin to provide further insight into displacer design. The results presented here indicate that it may be possible to design displacers that can dramatically improve the effective selectivity of ion-exchange chromatographic materials.
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