Fragmentation of Lanthanide (III) Cationized Small Peptides: Generation of Peptide Radical Cations and Dipositive a and b ions.

This research work examines the dissociation chemistry of tripositive complexes formed by trivalent lanthanide ions and small peptides with tandem mass spectrometry under low-energy collision-induced dissociation (CID). By fragmentation of the tripositive lanthanide(III) cationized small peptide, a new route to generate peptide radical cations has been discovered. The dipositive b ions are also observed and the mechanisms by which they fragment are investigated by MSn. Tripositive complexes of lanthanide(III)/peptide have similar fragmentation chemistries in the gas phase when lanthanide = yttrium, lanthanum, cerium, samarium, gadolinium and terbium; [a3+H]2+ ions are formed and there are no peptide radical cations observed. When the lanthanide is europium(III), radical cations of tryptophan-, tyrosine-, phenylalanine-, methionine-containing peptides and of aliphatic peptides have been generated. Fragmentations of tripositive Ce(III)/peptide and Eu(III)/peptide complexes show very different behaviours. Abundant CO loss is only observed for dissociation of Ce(III)/peptide complexes, whereas CO2 loss is the predominant channel for Eu(III)/peptide complexes. Similarly, CO loss and CO2 loss are the predominant channels for the dissociations of [Ce(peptide-H)]2+ and [Eu(peptide-H)]2+, respectively. Peptide radical cations are only generated by the fragmentation of Eu(III)/peptide complexes, while protonated a and b ions are only observed when Ce(III)/peptide complexes dissociate. The dissociations of aliphatic [peptide]+ions generate [b3-H]+/ [b2-H]+ions for most peptides. In the dissociation of [a3+H]+ions, [b2-H]+ions are formed from most peptides. [a3+H]2+ ions usually cleave at the C-terminal amide bonds, creating two singly charged ions, a [b2]+ ion and an iminium ion derived from the C-terminal residue. Some [a3+H]2+ ions also lose small neutral molecules. The composition of the peptides dictates the preferred mode of the fragmentation of [b3+H]2+ ions, either loss of CO to form [a3+H]2+, or loss of CO plus H2O. Fragmentations of [Ce(peptide-H)]2+ ions show CO loss, and CO2 losses are observed for peptides with aromatic side chains or a methionine residue at C-terminus. For [Ce(peptide-H)(peptide)]2+ complexes, neutral losses are also observed but formation of two singly charged ions is dominant. The dissociation behaviour of [Ce(peptide-H)(CH3CN)]2+ and [Eu(peptide-H)(CH3CN)]2+ complexes are quite different. The former loses only CH3CN whereas the latter loses only CO2

Adaptive Generalized Multiscale Model Reduction Techniques for Problems in Perforated Domains

Multiscale modeling of complex physical phenomena in many areas, including hydrogeology, material science, chemistry and biology, consists of solving problems in highly heterogeneous porous media. In many of these applications, differential equations are formulated in perforated domains which can be considered as the region outside of inclusions or connected bodies of various sizes. Due to complicated geometries of these inclusions, solutions to these problems have multiscale features. Taking into account the uncertainties, one needs to solve these problems extensively many times. Model reduction techniques are significant for problems in perforated domains in order to improve the computational efficiency. There are some existing approaches for model reduction in perforated domains including homogenization, heterogeneous multiscale methods and multiscale finite element methods. These techniques typically consider the case when there is a scale separation or the perforation distribution is periodic, and assume that the solution space can be approximated by the solutions of directional cell problems and the effective equations contain a limited number of effective parameters. For more complicated problems where the effective properties may be richer, we are interested in developing systematic local multiscale model reduction techniques to obtain accurate macroscale representations of the underlying fine-scale problem in highly heterogeneous perforated domains. In this dissertation, based on the framework of Generalized Multiscale Finite Element Method, we develop novel methods and algorithms including (1) development of systematic local model reduction techniques for computing multiscale basis in perforated domains, (2) numerical analysis and exhaustive simulation utilizing the proposed basis functions, (3) design of different applicable global coupling frameworks and (4) applications to various problems with challenging engineering backgrounds. Our proposed methods can significantly advance the computational efficiency and accuracy for multiscale problems in perforated media

The LBFGS Quasi-Newtonian Method for Molecular Modeling Prion AGAAAAGA Amyloid Fibrils

Experimental X-ray crystallography, NMR (Nuclear Magnetic Resonance) spectroscopy, dual polarization interferometry, etc are indeed very powerful tools to determine the 3-Dimensional structure of a protein (including the membrane protein); theoretical mathematical and physical computational approaches can also allow us to obtain a description of the protein 3D structure at a submicroscopic level for some unstable, noncrystalline and insoluble proteins. X-ray crystallography finds the X-ray final structure of a protein, which usually need refinements using theoretical protocols in order to produce a better structure. This means theoretical methods are also important in determinations of protein structures. Optimization is always needed in the computer-aided drug design, structure-based drug design, molecular dynamics, and quantum and molecular mechanics. This paper introduces some optimization algorithms used in these research fields and presents a new theoretical computational method - an improved LBFGS Quasi-Newtonian mathematical optimization method - to produce 3D structures of Prion AGAAAAGA amyloid fibrils (which are unstable, noncrystalline and insoluble), from the potential energy minimization point of view. Because the NMR or X-ray structure of the hydrophobic region AGAAAAGA of prion proteins has not yet been determined, the model constructed by this paper can be used as a reference for experimental studies on this region, and may be useful in furthering the goals of medicinal chemistry in this field

Deactivation of Soybean Agglutinin by Enzymatic and Other Physical Treatments

The main objective of this study was to eliminate the hemagglutination activity of an antinutritional factor in soybeans, soybean agglutinin (SBA). A series of experiments was designed to enzymatically modify SBA structure and to use other physical treatments to reduce activity. SBA extract was prepared from soy flour and used as the substrate for all treatments. Deglycosylation by enzyme decreased activity of SBA by 21%, but not to the level of denaturation by heat or by denaturing reagents (47−77% residual activity). Single enzymes, such as trypsin, chymotrypsin, thermolysin, and endoproteinase Glu-C, did not hydrolyze native SBA, but they hydrolyzed heat- or organic solute-denatured SBA. Even after hydrolysis, SBA still had 44−62% residual activity. Combinations of enzymes with thermolysin fully deactivated heat- or guanidine hydrochloride- and urea-treated SBA. Pepsin and pancreatin hydrolysis fully deactivated not only heated but also native SBA. Tea polyphenols, metal ions, and chelating agents were also tested, and they showed no significant effect on SBA activity. N-Acetylgalactosamine−agarose beads specifically but not fully removed SBA from the soy protein mixture. In general, SBA needs to be denatured first for an effective enzymatic hydrolysis, and multiple enzymes are needed to fully deactivate SBA. Pepsin and pancreatin treatment showed great promise in fully reducing SBA activity, and it would be further tested using soy flour as a model system

China Business Perception Index

The Business Perception Index (BPI) has been developed to understand the Kenya-based Chinese companies' characteristics, to understand the business and investment climate faced by Chinese enterprises, and how these conditions affect productivity and growth of Chinese companies in Kenya. The BPI Survey-Kenya is a firm-level descriptive survey of Chinese private and state-owned enterprises in Kenya. The questionnaire includes the following ten major sections: basic firm characteristics, regulation and taxes, crime and safety, informality, gender, finance, infrastructure, trade, workforce, corruption and obstacles analysis. We reached out through email and telephone to 184 Chinese establishments in Kenya, and 75 companies accepted the survey

On a neural network approach for solving potential control problem of the semiclassical Schr\"odinger equation

Robust control design for quantum systems is a challenging and key task for practical technology. In this work, we apply neural networks to learn the control problem for the semiclassical Schr\"odinger equation, where the control variable is the potential given by an external field that may contain uncertainties. Inspired by a relevant work [29], we incorporate the sampling-based learning process into the training of networks, while combining with the fast time-splitting spectral method for the Schr\"odinger equation in the semiclassical regime. The numerical results have shown the efficiency and accuracy of our proposed deep learning approach

Job Performance Modeling: A Holistic Theoretical Analysis

The purpose of this study is to investigate inconsistent findings in extant research on organizational performance prediction. Systematic review is used to (a) evaluate the overall validity of traditional antecedents of organizational performance, (b) examine their underlying casual relationships in determining organizational performance, and (c) investigate the potential existence of mediating and moderating effects of each antecedent. Rather than simply making the customary plea for more elaborate micro theories of behavior or improved research designs, it is contended that greater progress could be made by examining and organizing what is already known about performance and its antecedents. Thus, leveraging on the systematic review analysis, this research develops a holistic theoretical model by blending three job performance antecedents to study their explanatory power and to reveal how these factors may interact with each other. The proposed causal-chain framework may be regarded as representative references for future research in the organizational psychology. Practitioners can also develop a better operational strategies based on the theoretical model