Values in the Development of Early Periodic Tables

Julius Lothar Meyer, John Newlands, and Dmitrii Mendeleev were amongst the discoverers of the periodic system of the elements. Although their systems are similar enough to be recognised as the precursors for the modern periodic system, they were also different. Here, I argue that many of their differences can be explained in terms of how the chemists emphasised different values in the process of developing their systems. In particular, Newland highlighted the simplicity of his arrangements; Meyer was more careful about the quality of data that gave rise to his system of elements; and Mendeleev sought to make his system more complete. By shedding light as to how the values of simplicity, completeness and carefulness guided the development of early periodic systems, this paper contributes to a broader understanding of how values influence science.     

Gas phase intramolecular proton transfer in cationized glycine and chlorine substituted derivatives (M-Gly, M = Na+, Mg2+, Cu+, Ni+, and Cu2+): existence of Zwitterionic structures?

The intramolecular proton transfer in cationized glycine and chlorine substituted derivatives with M = Na+, Mg2+, Ni+, Cu+, and Cu2+ has been studied with the three parameter B3LYP density functional method. The coordination of metal cations to the oxygens of the carboxylic group of glycine stabilizes the zwitterionic structure. For all monocations the intramolecular proton transfer occurs readily with small energy barriers (1-2 kcalmol(-1)). For the dication Mg2+ and Cu2+ systems, the zwitterionic structure becomes very stable. However, whereas for Mg2+, the proton transfer process takes place spontaneously, for Cu2+ the reaction occurs with an important energy barrier. The substitution of the hydrogens of the amino group by chlorine atoms decreases the basicity of nitrogen, which destabilizes the zwitterionic structure. For monosubstituted glycine complexed with Na+, the zwitterionic structure still exists as a minimum, but for disubstituted glycine no minimum appears for this structure. In contrast, for Mg2+ complexed to mono- and disubstituted glycine, the zwitterionic structure remains the only minimum, since the enhanced electrostatic interaction with the dication overcomes the destabilizing effect of the chlorine atoms.     

Fuzzy classifier identification using decision tree and multiobjective evolutionary algorithms

This paper presents a hybrid method for identification of Pareto-optimal fuzzy classifiers (FCs). In contrast to many existing methods, the initial population for multiobjective evolutionary algorithms (MOEAs) is neither created randomly nor a priori knowledge is required. Instead, it is created by the proposed two-step initialization method. First, a decision tree (DT) created by C4.5 algorithm is transformed into an FC. Therefore, relevant variables are selected and initial partition of input space is performed. Then, the rest of the population is created by randomly replacing some parameters of the initial FC, such that, the initial population is widely spread. That improves the convergence of MOEAs into the correct Pareto front. The initial population is optimized by NSGA-II algorithm and a set of Pareto-optimal FCs representing the trade-off between accuracy and interpretability is obtained. The method does not require any a priori knowledge of the number of fuzzy sets, distribution of fuzzy sets or the number of relevant variables. They are all determined by it. Performance of the obtained FCs is validated by six benchmark data sets from the literature. The obtained results are compared to a recently published paper [H. Ishibuchi, Y. Nojima, Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning, International Journal of Approximate Reasoning 44 (1) (2007) 4–31] and the benefits of our method are clearly shown.     

Blow‐up profiles of solutions for the exponential reaction‐diffusion equation

We consider the blow‐up of solutions for a semilinear reaction‐diffusion equation with exponential reaction term. It is known that certain solutions that can be continued beyond the blow‐up time possess a non‐constant self‐similar blow‐up profile. Our aim is to find the final time blow‐up profile for such solutions. The proof is based on general ideas using semigroup estimates. The same approach works also for the power nonlinearity. Copyright © 2011 John Wiley & Sons, Ltd.     

A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates

This paper presents a novel method of multi-objective optimization by learning automata (MOLA) to solve complex multi-objective optimization problems. MOLA consists of multiple automata which perform sequential search in the solution domain. Each automaton undertakes dimensional search in the selected dimension of the solution domain, and each dimension is divided into a certain number of cells. Each automaton performs a continuous search action, instead of discrete actions, within cells. The merits of MOLA have been demonstrated, in comparison with a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and non-dominated sorting genetic algorithm II (NSGA-II), on eleven multi-objective benchmark functions and an optimal problem in the midwestern American electric power system which is integrated with wind power, respectively. The simulation results have shown that MOLA can obtain more accurate and evenly distributed Pareto fronts, in comparison with MOEA/D and NSGA-II.     

Molecular dynamics simulations for human CAR inverse agonists

Constitutive androstane receptor (CAR), along with pregnane x receptor (PXR), is an important metabolic sensor in the hepatocytes. Like all other nuclear receptors (NRs), CAR works in concert with coregulator proteins, coactivators, and corepressors which bind to the NRs. The main basis for the receptor to distinguish between coactivators and corepressors is the position of the C-terminal helix 12 (H12), which is determined by the bound NR ligand. CAR, having constitutive activity, can be repressed or further activated by its ligands. Crystal structure of human CAR bound to an agonist and a coactivator peptide is available, but no structural information on an inverse agonist-bound human CAR and a corepressor exists. In our previous molecular dynamics (MD) studies, no corepressor peptide was included. Therefore, probably due to the strong interactions which keep the relatively short H12 of CAR in the active position, the structural changes elicited by inverse agonists were very subtle, and H12 of CAR seemed to more or less retain its active conformation. Here, we have run a series of MD simulations to study the movement of H12 in the presence of both activating and repressing ligands as well as a corepressor peptide. The presence of the corepressor on the coregulator surface of CAR induced a clear shift of H12 of the inverse agonists-bound CAR. In general, H12 moved toward H10 and not away from the ligand binding domain, as seen in some other NRs. However, H12 of CAR is short enough that this movement seems to be adequate to accommodate the binding of the corepressor.     

Phase Transitions on Markovian Bipartite Graphs—an Application of the Zero-range Process

We analyze the existence and the size of the giant component in the stationary state of a Markovian model for bipartite multigraphs, in which the movement of the edge ends on one set of vertices of the bipartite graph is a zero-range process, the degrees being static on the other set. The analysis is based on approximations by independent variables and on the results of Molloy and Reed for graphs with prescribed degree sequences. The possible types of phase diagrams are identified by studying the behavior below the zero-range condensation point. As a specific example, we consider the so-called Evans interaction. In particular, we examine the values of a critical exponent, describing the growth of the giant component as the value of the dilution parameter controlling the connectivity is increased above the critical threshold. Rigorous analysis spans a large portion of the parameter space of the model exactly at the point of zero-range condensation. These results, supplemented with conjectures supported by Monte Carlo simulations, suggest that the phenomenological Landau theory for percolation on graphs is not broken by the fluctuations.     

A general route to 3-unsubstituted 1,5-diaryl-2,4-pentanediones and -4-Methoxy-2-pentanones

2-Isoxazolines are converted to corresponding 3-hydroxyketones which are used as precursors to produce new 3-unsubstituted 1,5-diaryl-2,4-pentanediones and -4-methoxy-2-pentanones.     

A generative model and a generalized trust region Newton method for noise reduction

In practical applications related to, for instance, machine learning, data mining and pattern recognition, one is commonly dealing with noisy data lying near some low-dimensional manifold. A well-established tool for extracting the intrinsically low-dimensional structure from such data is principal component analysis (PCA). Due to the inherent limitations of this linear method, its extensions to extraction of nonlinear structures have attracted increasing research interest in recent years. Assuming a generative model for noisy data, we develop a probabilistic approach for separating the data-generating nonlinear functions from noise. We demonstrate that ridges of the marginal density induced by the model are viable estimators for the generating functions. For projecting a given point onto a ridge of its estimated marginal density, we develop a generalized trust region Newton method and prove its convergence to a ridge point. Accuracy of the model and computational efficiency of the projection method are assessed via numerical experiments where we utilize Gaussian kernels for nonparametric estimation of the underlying densities of the test datasets.