FTMS structure elucidation of natural products: application to muraymycin antibiotics using ESI multi-CHEF SORI-CID FTMS(n), the top-down/bottom-up approach,and HPLC ESI capillary-skimmer CID FTMS

The molecular formulas for the structures and substructures of muraymycin antibiotics A1 (C52H90N14O19, MW 1214) and B1 (C49H83N11O18, MW 1113) were determined using electrospray ionization (ESI) Fourier transform mass spectrometry (FTMS). The muraymycin A1 and B1 structures were elucidated by utilizing capillary-skimmer fragmentation with up to five stages of mass spectrometry (MS5). Multi-CHEF, a multiple ion isolation method, was used at each stage of MS(n) to isolate a parent ion and up to four reference ions, for exact-mass calibration. The parent ions were fragmented by SORI-CID and the product ions internally calibrated with average absolute mass errors less than 1 ppm at each stage in the fragmentation processes. Using the top-down/bottom-up approach, the molecular formulas for the antibiotics were determined by summing the elemental formulas of the neutral losses, obtained by measuring the mass differences (<500 Da) between the genetically related sequential parent ion masses in the MS(n) spectra, with the unique elemental formula of the lowest parent ion mass (<500 Da). The structures of 12 additional compounds in the muraymycin complex were elucidated using HPLC ESI capillary-skimmer CID FTMS by correlating their fragmentation patterns with those of muraymycins A1 and B1. Sequential neutral losses of an aminosugar, a valine, a uridine, and an ester fatty acid from the muraymycin parent ions provided diagnostic fragments for characterization.     

Consumer credit risk: Individual probability estimates using machine learning

Consumer credit scoring is often considered a classification task where clients receive either a good or a bad credit status. Default probabilities provide more detailed information about the creditworthiness of consumers, and they are usually estimated by logistic regression. Here, we present a general framework for estimating individual consumer credit risks by use of machine learning methods. Since a probability is an expected value, all nonparametric regression approaches which are consistent for the mean are consistent for the probability estimation problem. Among others, random forests (RF), k-nearest neighbors (kNN), and bagged k-nearest neighbors (bNN) belong to this class of consistent nonparametric regression approaches. We apply the machine learning methods and an optimized logistic regression to a large dataset of complete payment histories of short-termed installment credits. We demonstrate probability estimation in Random Jungle, an RF package written in C++ with a generalized framework for fast tree growing, probability estimation, and classification. We also describe an algorithm for tuning the terminal node size for probability estimation. We demonstrate that regression RF outperforms the optimized logistic regression model, kNN, and bNN on the test data of the short-term installment credits.     

Monitoring post-tsunami vegetation recovery in Phang-Nga province,Thailand, based on IKONOS imagery and field investigations – a contribution to the analysis of tsunami vulnerability of coastal ecosystems

A major tsunami in December 2004 devastated the coastal ecosystems along the Andaman Sea coast of Thailand. Since intact coastal ecosystems provide many important services for local communities at the Andaman Sea, it is crucial to investigate to what extent (in terms of percentage area and speed) the affected ecosystems were capable of recovering after the tsunami. Field measurements and multi-date IKONOS imagery were used to estimate the recovery and succession patterns of coastal vegetation types in the Phang-Nga province of Thailand, three years after the tsunami. Thus, this study contributes to a holistic understanding of the ecological vulnerability of the coastal area to tsunamis. A zone-based change detection approach is applied by comparing two change detection techniques: the first method involves the calculation of a recovery rate based on multi-temporal TNDVI (transformed normalized difference vegetation index) images (TNDVI approach), whereas the second approach is a combined approach of the change vector analysis (CVA). Although these two methods provide different types of information (quantitative for the TNDVI approach, qualitative for the CVA), they are comparable in terms of results and accuracies. The results reveal that recovery processes vary based on the type of the ecosystem and, furthermore, are strongly influenced by human activities. Grasslands, coconut plantations and the mixed vegetation cover could recover faster than the mangroves and casuarina forests. Among the forest ecosystems, recovery rates of casuarina forests were higher than for mangroves, but the recovery area was smaller. This study also discusses the potential and some limitations and inaccuracies of applying high-resolution optical imagery for assessing vegetation recovery at a local scale.     

Principles of Branching Morphology and Anatomy in Arborescent Monocotyledons and Columnar Cacti as Concept Generators for Branched Fiber‐Reinforced Composites

The branching of arborescent (tree‐like) monocotyledonous plants of the genus Dracaena or of columnar cacti differ considerably from that observed in other dicotyledonous or gymnosperm trees. The investigated ramifications exhibit distinctive morphological and anatomical features. In arborescent monocotyledons the side branches are attached to the main stem by a fiber‐reinforced tissue newly formed during secondary growth, clasping the main stem and finally resulting in a “flange‐mounted” structure. In the case of columnar cacti the most obvious feature is the pronounced constriction at the attachment point of the branches that is also mirrored in the lignified vascular tissue. One might argue that these characteristic morphological and anatomical features in regions exposed to high mechanical stresses represent structural weaknesses. However, the outer shape and the inner structures of the ramifications cause considerable stability and structural integrity of the stem‐branch connection under static and dynamic loading. Our results allow concluding that load‐adaptation in ramified plant structures is a result of a combination of optimization in outer shape and fiber arrangement within the ramifications. Numerical methods simulating the mechanical behavior based on data obtained from the studied plants support this assumption. A deeper understanding of the outer shape of the connection between shoot and branch as well as of the arrangement of the lignified vascular tissues in the branching region, may contribute toward alternative concepts for branched technical light‐weight‐structures. In particular for braided fiber‐reinforced composites this biomimetic approach might help to keep the demand on the available design space as small as possible.     

The statistics of the thermal motion of the atoms during imaging process in transmission electron microscopy and related techniques

The concern of this work is the influence of the thermal motion of the atoms on electron scattering simulations, used for quantitative interpretation of results in high-resolution electron microscopy. We distinguish between the influence of inelastic phonon excitation and the effect of a moving lattice on images generated by elastically scattered electrons. It is shown that, analog to aberrations, the impact of a moving lattice differs substantially with respect to different imaging conditions and cannot be described by the Debye–Waller damping applicable in XRD. We derive a new formalism, based on the frozen lattice and multislice approach, to incorporate the statistics of the thermal motion into elastic TEM imaging simulations, taking into account different imaging conditions. The averaging over different atom positions is generally performed within a density matrix framework, which can be linearized in the special case of off-axis electron holography. All findings are supported by explicit numerical simulations: molecular dynamics simulations are performed to get a realistic thermal motion and the electron scattering simulations are performed within the new multislice algorithm.     

The sources of normativity: Young children's awareness of the normative structure of games.

In two studies, the authors investigated 2- and 3-year-old children's awareness of the normative structure of conventional games. In the target conditions, an experimenter showed a child how to play a simple rule game. After the child and the experimenter had played for a while, a puppet came (controlled by a 2nd experimenter), asked to join in, and then performed an action that constituted a mistake in the game. In control conditions, the puppet performed the exact same action as in the experimental conditions, but the context was different such that this act did not constitute a mistake. Children's normative responses to the puppet's acts (e.g., protest, critique, or teaching) were scored. Both age groups performed more normative responses in the target than in the control conditions, but the 3-year-olds did so on a more explicit level. These studies demonstrate in a particularly strong way that even very young children have some grasp of the normative structure of conventional activities. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Chemical and Structural Properties of Nickel Hydroxide Xerogels Obtained by the Sol-Gel Procedure in the Presence of Acetic Acid

The sol-gel route to glasses and ceramics has attracted an increasing amount of scientific and technological interest recently. In this process, sols with different concentrations are used as precursors for xerogels and to produce materials that consist of fine oxide particles. In the present work, nickel hydroxide gels have been obtained via the hydrolysis of a molecular precursor in the presence of acetic acid. The chemical aspects of the material transformation have been studied by using Fourier transform infrared (FTIR) spectroscopy and differential scanning calorimetry (DSC) for different acetic acid contents and several heat-treatment temperatures. The carboxylic acid acts as a ligand at a molecular level in the precursor, therefore modifying the entire hydrolysis and condensation process. Small-angle X-ray scattering (SAXS) studies and density measurements have been performed for the structural characterization of the xerogels. A denser, final oxide material is obtained when a higher acetic acid concentration is used. The porosity of the dry gels coarsens when they are heat-treated up to a temperature of ∼400°C and its density decreases. The material that has been heat-treated up to a temperature of 800°C densifies and exhibits a finer porosity. The chemical properties at a molecular level satisfactorily explain and are well correlated with the structural characteristics of the studied material.