On the Stability Analysis of a Geometrically Complex Leaning Historic Structure

In this paper, a simple approach for the stability analysis of the southwest leaning ruined tower of the Caerphilly castle (Wales, UK) is discussed. To account for the actual complex geometry of the tower, a mesh generation procedure recently proposed by the authors is used to automatically transform the 3D point cloud surveyed from the tower into a 3D solid finite element model. A simple approach based on nonlinear static analyses is pursued to evaluate the stability condition of the tower. Geometric nonlinearity and nonlinear plastic-damaging behavior of masonry are supposed. Results show that the proposed approach could serve as a simplified method to evaluate the stability of leaning historic structures considering their actual geometry

Statistical Optimization of Process Variables for Antibiotic Activity of Xenorhabdus bovienii

The production of secondary metabolites with antibiotic properties is a common characteristic to entomopathogenic bacteria Xenorhabdus spp. These metabolites not only have diverse chemical structures but also have a wide range of bioactivities of medicinal and agricultural interests. Culture variables are critical to the production of secondary metabolites of microorganisms. Manipulating culture process variables can promote secondary metabolite biosynthesis and thus facilitate the discovery of novel natural products. This work was conducted to evaluate the effects of five process variables (initial pH, medium volume, rotary speed, temperature, and inoculation volume) on the antibiotic production of Xenorhabdus bovienii YL002 using response surface methodology. A 25–1 factorial central composite design was chosen to determine the combined effects of the five variables, and to design a minimum number of experiments. The experimental and predicted antibiotic activity of X. bovienii YL002 was in close agreement. Statistical analysis of the results showed that initial pH, medium volume, rotary speed and temperature had a significant effect (P<0.05) on the antibiotic production of X. bovienii YL002 at their individual level; medium volume and rotary speed showed a significant effect at a combined level and was most significant at an individual level. The maximum antibiotic activity (287.5 U/mL) was achieved at the initial pH of 8.24, medium volume of 54 mL in 250 mL flask, rotary speed of 208 rpm, temperature of 32.0°C and inoculation volume of 13.8%. After optimization, the antibiotic activity was improved by 23.02% as compared with that of unoptimized conditions

Masonry compressive strength prediction using artificial neural networks

The masonry is not only included among the oldest building materials, but it is also the most widely used material due to its simple construction and low cost compared to the other modern building materials. Nevertheless, there is not yet a robust quantitative method, available in the literature, which can reliably predict its strength, based on the geometrical and mechanical characteristics of its components. This limitation is due to the highly nonlinear relation between the compressive strength of masonry and the geometrical and mechanical properties of the components of the masonry. In this paper, the application of artificial neural networks for predicting the compressive strength of masonry has been investigated. Specifically, back-propagation neural network models have been used for predicting the compressive strength of masonry prism based on experimental data available in the literature. The comparison of the derived results with the experimental findings demonstrates the ability of artificial neural networks to approximate the compressive strength of masonry walls in a reliable and robust manner.- (undefined

High-performance liquid chromatography–tandem mass spectrometry in the identification and determination of phase I and phase II drug metabolites

Applications of tandem mass spectrometry (MS/MS) techniques coupled with high-performance liquid chromatography (HPLC) in the identification and determination of phase I and phase II drug metabolites are reviewed with an emphasis on recent papers published predominantly within the last 6 years (2002–2007) reporting the employment of atmospheric pressure ionization techniques as the most promising approach for a sensitive detection, positive identification and quantitation of metabolites in complex biological matrices. This review is devoted to in vitro and in vivo drug biotransformation in humans and animals. The first step preceding an HPLC-MS bioanalysis consists in the choice of suitable sample preparation procedures (biomatrix sampling, homogenization, internal standard addition, deproteination, centrifugation, extraction). The subsequent step is the right optimization of chromatographic conditions providing the required separation selectivity, analysis time and also good compatibility with the MS detection. This is usually not accessible without the employment of the parent drug and synthesized or isolated chemical standards of expected phase I and sometimes also phase II metabolites. The incorporation of additional detectors (photodiode-array UV, fluorescence, polarimetric and others) between the HPLC and MS instruments can result in valuable analytical information supplementing MS results. The relation among the structural changes caused by metabolic reactions and corresponding shifts in the retention behavior in reversed-phase systems is discussed as supporting information for identification of the metabolite. The first and basic step in the interpretation of mass spectra is always the molecular weight (MW) determination based on the presence of protonated molecules [M+H]+ and sometimes adducts with ammonium or alkali-metal ions, observed in the positive-ion full-scan mass spectra. The MW determination can be confirmed by the [M-H]- ion for metabolites providing a signal in negative-ion mass spectra. MS/MS is a worthy tool for further structural characterization because of the occurrence of characteristic fragment ions, either MSn analysis for studying the fragmentation patterns using trap-based analyzers or high mass accuracy measurements for elemental composition determination using time of flight based or Fourier transform mass analyzers. The correlation between typical functional groups found in phase I and phase II drug metabolites and corresponding neutral losses is generalized and illustrated for selected examples. The choice of a suitable ionization technique and polarity mode in relation to the metabolite structure is discussed as well