Isomer differentiation via collision‐induced dissociation: The case of protonated α‐, β2‐ and β3‐phenylalanines and their derivatives

A combination of electrospray ionisation (ESI), multistage and high‐resolution mass spectrometry experiments is used to examine the gas‐phase fragmentation reactions of the three isomeric phenylalanine derivatives, α‐phenylalanine, β²‐phenylalanine and β³‐phenylalanine. Under collision‐induced dissociation (CID) conditions, each of the protonated phenylalanine isomers fragmented differently, allowing for differentiation. For example, protonated β³‐phenylalanine fragments almost exclusively via the loss of NH₃, only β²‐phenylalanine via the loss of H₂O, while α‐ and β²‐phenylalanine fragment mainly via the combined losses of H₂O + CO. Density functional theory (DFT) calculations were performed to examine the competition between NH₃ loss and the combined losses of H₂O and CO for each of the protonated phenylalanine isomers. Three potential NH₃ loss pathways were studied: (i) an aryl‐assisted neighbouring group; (ii) 1,2 hydride migration; and (iii) neighbouring group participation by the carboxyl group. Finally, we have shown that isomer differentiation is also possible when CID is performed on the protonated methyl ester and methyl amide derivatives of α‐, β²‐ and β³‐phenylalanines. Copyright © 2010 John Wiley & Sons, Ltd.     

Hartogs Phenomena and Antisyzygies for Systems of Differential Equations

We introduce the notion of antisyzygies, which studies the inverse problem of finding a system of PDEs, given compatibility conditions. The system obtained possesses the property of removability of compact singularities. We write explicit computations in the cases of the Cauchy-Fueter system and Maxwell’s system for electromagnetism, and we conclude with a study of systems of non-maximal rank.      

Measurement and analysis of the dextran partition coefficient in sucrose crystallization

The effect of crystallization conditions on the dextran partition coefficient between impure syrup and sugar crystal has been investigated in a batch crystallizer. The crystallizer is operated isothermally at temperatures of 30, 40, and 50 °C, at constant relative supersaturations of 0.05, 0.07, and 0.09, and with mother liquor dextran concentrations of 1000 and 2000 ppm/Brix. The dextran content has been determined by the CSR method. A 1:1 mass ratio of high-fraction dextran (approximately 250,000 Da) and low-fraction dextran (60,000-90,000 Da) is used to represent a wide range of dextran contamination. It is seen that the dextran partition coefficient in sucrose crystallization increases with both increasing supersaturation and increasing crystallization temperature. However it appears that these are secondary effects, with the partition coefficient strongly correlating with crystal growth rate alone, despite the regressed data having large variations in temperature, mother liquor dextran content, and supersaturation. Dextran incorporation into the sugar crystal results from both dextran adsorption onto the crystal surface and mother liquor inclusions. The explanation for the variation in the dextran content in sugar crystal with respect to the growth rate is due to increased adsorption due to the higher surface roughness of crystals grown at high growth rates. Although the dextran concentration in the solution affects the dextran content in the crystal, it does not strongly affect the dextran partition coefficient.     

Novel light-fluorous TEMPO reagents and their application in oxidation reactions

The synthesis of two light-fluorous TEMPO derivatives is reported, along with their application in oxidation reactions.     

A fast Pareto genetic algorithm approach for solving expensive multiobjective optimization problems

We present a new multiobjective evolutionary algorithm (MOEA), called fast Pareto genetic algorithm (FastPGA), for the simultaneous optimization of multiple objectives where each solution evaluation is computationally- and/or financially-expensive. This is often the case when there are time or resource constraints involved in finding a solution. FastPGA utilizes a new ranking strategy that utilizes more information about Pareto dominance among solutions and niching relations. New genetic operators are employed to enhance the proposed algorithm’s performance in terms of convergence behavior and computational effort as rapid convergence is of utmost concern and highly desired when solving expensive multiobjective optimization problems (MOPs). Computational results for a number of test problems indicate that FastPGA is a promising approach. FastPGA yields similar performance to that of the improved nondominated sorting genetic algorithm (NSGA-II), a widely-accepted benchmark in the MOEA research community. However, FastPGA outperforms NSGA-II when only a small number of solution evaluations are permitted, as would be the case when solving expensive MOPs.