Parallel iterative solution-phase synthesis of 5-amino-1-aryl-[1,2,4]triazolo[1,5-a]pyridine-7-carboxylic acid amide derivatives

The parallel iterative solution-phase synthesis of 5-amino-1-aryl-[1,2,4]triazolo[1,5-a]pyridine-7-carboxylic acid amide derivatives is described. The key intermediate 2,6-bis-aminopyridine-4-carboxylic acid methyl ester was synthesised in a two step procedure in 64% overall yield and elaborated to a variety of triazolopyridine-5-carboxylic acid methyl ester by selective pyridine-N-amination, condensation of the adduct with a wide selection of aldehydes and subsequent cyclisation and oxidation. The desired esters were obtained in yields up to 70%. The final transformation to the amide derivatives was accomplished by application of carefully optimised reaction conditions thus giving access to a library of total 500 triazolopyridine amide derivatives. Iterative synthetic cycles (12-48 library members each) allowing for maximal flexibility in chemistry and maximal efficiency in in vitro biological activity optimisation guided by molecular modelling efforts constitute a synergistic procedure for rapid lead optimisation.     

Local Sensitivity Analysis in Estimation Problems

This article deals with the problem of local sensitivity analysis, that is, how sensitive are the results of a statistical analysis to changes in the data? A general methodology of sensitivity analysis is applied to some statistical problems. The proposed methods are applicable to any statistical problem that can be expressed as an optimization problem or that involves solving a system of equations. As some particular examples, the methodology is applied to the maximum likelihood method, the standard and constrained methods of moments and the standard and constrained probability weighted moments methods. Unlike the standard method of moments, the constrained method of moments ensures that the obtained estimates are always consistent with the data. Closed analytical formulas for the calculation of these local sensitivities are derived. The obtained sensitivities include: (a) the objective function sensitivities to data points and (b) the sensitivities of the estimated parameters to data points. The derived formulas for the sensitivities are based on recent results in the area of mathematical programming. Several examples of parameter estimation problems are used to illustrate the methodology.     

Chiral Thirring–Wess model with Faddeevian regularization

Replacing vector type of interaction of the Thirring–Wess model by the chiral type a new model is presented which is termed here as chiral Thirring–Wess model. Ambiguity parameters of regularization are so chosen that the model falls into the Faddeevian class. The resulting Faddeevian class of model in general does not possess Lorentz invariance. However we can exploit the arbitrariness admissible in the ambiguity parameters to relate the quantum mechanically generated ambiguity parameters with the classical parameter involved in the masslike term of the gauge field which helps to maintain physical Lorentz invariance instead of the absence of manifestly Lorentz covariance of the model. The phase space structure and the theoretical spectrum of this class of model have been determined through Dirac’s method of quantization of constraint system.     

New Interfaces and Approaches to Machine Learning When Classifying Gestures within Music

Interactive music uses wearable sensors (i.e., gestural interfaces—GIs) and biometric datasets to reinvent traditional human–computer interaction and enhance music composition. In recent years, machine learning (ML) has been important for the artform. This is because ML helps process complex biometric datasets from GIs when predicting musical actions (termed performance gestures). ML allows musicians to create novel interactions with digital media. Wekinator is a popular ML software amongst artists, allowing users to train models through demonstration. It is built on the Waikato Environment for Knowledge Analysis (WEKA) framework, which is used to build supervised predictive models. Previous research has used biometric data from GIs to train specific ML models. However, previous research does not inform optimum ML model choice, within music, or compare model performance. Wekinator offers several ML models. Thus, we used Wekinator and the Myo armband GI and study three performance gestures for piano practice to solve this problem. Using these, we trained all models in Wekinator and investigated their accuracy, how gesture representation affects model accuracy and if optimisation can arise. Results show that neural networks are the strongest continuous classifiers, mapping behaviour differs amongst continuous models, optimisation can occur and gesture representation disparately affects model mapping behaviour; impacting music practice.     

Penalty functions,Newton's method,and quadratic programming

In this paper, the search directions computed by two versions of the sequential quadratic programming (SQP) algorithm are compared with that computed by attempting to minimize a quadratic penalty function by Newton's method, and it is shown that the differences are attributable to ignoring certain terms in the equation for the Newton correction. Since the effect of ignoring these terms may be to make the resultant direction a poor descent direction for the quadratic penalty function, it is argued that the latter is an inappropriate merit function for use with SQP. A method is then suggested by which these terms may be included without losing the benefits gained from the use of the orthogonal transformations derived from the constraints Jacobian.The authors wish to thank A. R. Conn and N. I. M. Gould for spirited discussions which took place when the second author spent some time at Waterloo, Ontario, Canada; they also thank L. C. W. Dixon for the clarifications that he suggested to the penultimate draft of this paper.     

The coordination of the catalytic zinc ion in alcohol dehydrogenase studied by combined quantum-chemical and molecular mechanics calculations

Summary The coordination number of the catalytic zinc ion in alcohol dehydrogenase has been studied by integrated ab initio quantum-chemical and molecular mechanics geometry optimisations involving the whole enzyme. A four-coordinate active-site zinc ion is 100–200 kJ/mol more stable than a five-coordinate one, depending on the ligands. The only stable binding site for a fifth ligand at the zinc ion is opposite to the normal substrate site, in a small cavity buried behind the zinc ion. The zinc coordination sphere has to be strongly distorted to accommodate a ligand in this site, and the ligand makes awkward contacts with surrounding atoms. Thus, the results do not support proposals attributing an important role to five-coordinate zinc complexes in the catalytic mechanism of alcohol dehydrogenase. The present approach makes it possible also to quantify the strain induced by the enzyme onto the zinc ion and its ligands; it amounts to 42–87 kJ/mol for four-coordinate active-site zinc ion complexes and 131–172 kJ/mol for five-coordinate ones. The four-coordinate structure with a water molecule bound to the zinc ion is about 20 kJ/mol less strained than the corresponding structure with a hydroxide ion, indicating that the enzyme does not speed up the reaction by forcing the zinc coordination sphere into a structure similar to the reaction intermediates.     

Test examples for nonlinear programming codes

The increasing importance of nonlinear programming software requires an enlarged set of test examples. The purpose of this note is to point out how an interested mathematical programmer could obtain computer programs of more than 120 constrained nonlinear programming problems which have been used in the past to test and compare optimization codes.     

Elimination of bounds in optimization problems by transforming variables

The problem of minimizing a nonlinear objective function ofn variables, with continuous first and second partial derivatives, subject to nonnegativity constraints or upper and lower bounds on the variables is studied. The advisability of solving such a constrained optimization problem by making a suitable transformation of its variables in order to change the problem into one of unconstrained minimization is considered. A set of conditions which guarantees that every local minimum of the new unconstrained problem also satisfies the first-order necessary (Kuhn—Tucker) conditions for a local minimum of the original constrained problem is developed. It is shown that there are certain conditions under which the transformed objective function will maintain the convexity of the original objective function in a neighborhood of the solution. A modification of the method of transformations which moves away from extraneous stationary points is introduced and conditions under which the method generates a sequence of points which converges to the solution at a superlinear rate are given.     

Hamel’s paradox and the foundations of analytical dynamics

This paper deals with an explanation of a paradox posed by Hamel in his 1949 book on Theoretical Mechanics. The explanation deals with the foundations of mechanics and points to new insights into analytical dynamics.