Improvement of corrosion protection of steel by incorporation of a new phosphonated fatty acid in a phosphorus-containing polymer coating obtained by UV curing

Six formulations containing diacrylate monomers (from 89 to 92.5% (w/w)) as well as a phosphonated methacrylate monomer (from 1 to 10% (w/w)) were prepared. All formulations were UV-cured and the corrosion performance of the resulting coatings applied onto a steel substrate was assessed by electrochemical impedance spectroscopy (EIS). It was first shown that the coatings containing phosphonic acid methacrylate (MAPC1(OH)₂) instead of methacrylate phosphonic dimethyl ester (MAPC1) presented higher corrosion protection related to the strong adhesive properties of phosphonic acid on the metal substrate. A minimum MAPC1(OH)₂ content of 2.5% was determined to provide the highest impedance values (best efficiency). Then, a new bio-based compound, i.e. phosphonic acid-bearing oleic acid (phosphonated fatty acid), was synthesized and added as an inhibitor to the formulations. In the presence of this compound, the corrosion protection was notably improved. The beneficial effect of phosphonated fatty acid was explained by its inhibitive action at the steel/coating interface and by the improvement of the barrier properties.     

A middleware‐transparent approach to developing distributed applications

An innovative middleware‐transparent approach to developing distributed applications is presented. The approach uses an aspect‐oriented software development technique to separate an application's middleware‐independent functionality from its middleware‐specific functionality. Application elements that are specific to the middleware are localized in aspects that can be seamlessly integrated into middleware‐independent application designs. The middleware‐transparent approach is used to decouple business functionality from middleware‐specific functionality. The decoupling allows developers to change middleware application elements without significantly modifying business functionality. Middleware technologies such as Java Remote Method Invocation (RMI), Jini, Simple Object Access Protocol (SOAP) remote procedure call (RPC) and .Net are used as examples to illustrate the approach. Copyright © 2005 John Wiley & Sons, Ltd.     

Surfactant-aided, matrix-assisted laser desorption/ionization mass spectrometry of hydrophobic and hydrophilic peptides

The analysis of hydrophobic and hydrophilic peptides in an aqueous medium using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is reported. The key development allowing for simultaneous analysis of both hydrophobic and hydrophilic components of the sample mixture is the use of surfactants to solubilize the hydrophobic components in the MALDI matrix solution. A wide variety of anionic, cationic, zwitterionic, and nonionic surfactants were evaluated for their ability to assist in the generation of an abundant pseudomolecular ion from a model hydrophobic peptide ([tert-butoxycarbonyl]Glu[gamma-O-benzyl]-Ala-Leu-Ala[O-phenacyl ester]). The results indicate that the most successful surfactant among those studied for analyzing the model hydrophobic peptide is sodium dodecyl sulfate (SDS). SDS exhibited no interfering surfactant background ions, little to no loss of the acid-labile protecting groups from the model hydrophobic peptide, and an abundant pseudomolecular ion of the analyte. In addition, the use of surfactants is shown to be compatible with hydrophilic peptides as well. Mixtures of hydrophobic and hydrophilic peptides were characterized using surfactant-aided (SA) MALDI-MS, and it is demonstrated that all components are detectable once the surfactant is included in the sample solution. We conclude that the key benefit of using SA-MALDI-MS is its ability to simultaneously analyze hydrophobic and hydrophilic peptides from a single sample mixture, including synthetic peptides containing acid- and base-labile protecting groups.     

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (kl), 3) growth (kg), and the efficiency of utilization of body stores for milk production (kt). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate kg and kt. Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for kg and kt using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for kg and 0.82 to 0.84 for kt. Using the estimated values of kg and kt, the data were corrected to allow for body tissue changes. Based on the definition of kl as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and kl were determined. Meta-analysis of the pooled data showed that the average kl ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.     

Generating compact classifier systems using a simple artificial immune system.

Current artificial immune system (AIS) classifiers have two major problems: 1) their populations of B-cells can grow to huge proportions, and 2) optimizing one B-cell (part of the classifier) at a time does not necessarily guarantee that the B-cell pool (the whole classifier) will be optimized. In this paper, the design of a new AIS algorithm and classifier system called simple AIS is described. It is different from traditional AIS classifiers in that it takes only one B-cell, instead of a B-cell pool, to represent the classifier. This approach ensures global optimization of the whole system, and in addition, no population control mechanism is needed. The classifier was tested on seven benchmark data sets using different classification techniques and was found to be very competitive when compared to other classifiers.     

ADSORPTION AT CRYSTAL-SOLUTION INTERFACES

The present work is a continuation of the study of adsorption processes at solution-crystal interfaces. It consists of an investigation of the adsorption of dyes and gelatin by the various faces of potassium alum. The growth ratios of this alum were measured both in the presence and absence of the dyes and gelatin. It was found that Bismarck Brown and Diamine Sky Blue greatly affected the growth rates of the cube faces and also modified the crystal habit. This effect is explained on the basis of the ionic structure of the faces and the presence of polar groups in the dyes. The growth ratio V₁₀₀/V₁₁₁ for pure potassium alum was found to be 1.61.