Complex formation equilibria between Ag(I) and thioureas in n-propanol

Complex formation equilibria between Ag(I) and thiourea or N-alkyl-substituted thioureas have been investigated in n-propanol by potentiometry at 10 °C intervals from 5 to 50 °C. Stepwise formation of tris-coordinated AgL_n (n = 1-3) complexes has been found for the majority of the ligands. ΔH and ΔS values for the complex formation reactions have been evaluated from the dependence of ln β_n on temperature. The alkyl-substituents affect the ligand affinities in different ways in relation with the coordination level n.The reactions are exothermic with few exceptions. Enthalpy favoured complex formation with negative dependence of ΔG on temperature (ΔS > 0) have been found.The enthalpy and entropy changes for the stepwise complex formation equilibria are correlated by two linear compensative relationships with the same isoequilibrium temperature 50-51 °C.     

Chaos and reproduction in sea level

Prediction of sea-level is an important task for navigation, coastal engineering and geodetic applications, as well as recreational activities. This study presents a comparison of Chaos theory and Auto-Regressive Integrated Moving Average (ARIMA) techniques for sea level modelling for daily, weekly, 10-day and monthly time scale at the Cocos (Keeling) islands from 1992 to 2001. The state space reconstruction of the unknown underlying process is directly employed from time series data, through Takens delay embedding method: optimal embedding dimension and delay time are obtained from false nearest neighbours and average mutual information techniques, respectively. Optimal values are then used for the estimation of the correlation dimension and the largest Lyapunov exponent, for inspecting possible signatures of chaotic dynamics. We find a positive Lyapunov exponent an evident feature of chaos. Indeed, the nonlinear prediction of sea level, in the period ranging from January 2001 to December 2001, is in an excellent agreement with the data for the same period, evidencing the nonlinear nature of the process. ARIMA method is also used for sea level modelling, for the same time scales; the performances of the two models are compared using such statistical indices as the root mean square error (RMSE) and correlation coefficient (CC). The comparative analyses show that the chaos theory model has a slight edge over ARIMA while both models are in principal acceptable.     

Studies on decarboxylation reactions. Part 5 . Micellar catalysis and mixed solvents effects on the decarboxylation of some N-alkyl- or N-aryl-substituted 5-amino-1,3,4-oxadiazole-2-carboxylic acids

The effect of micelles and mixed solvents on the decarboxylation of some N-alkyl- or N-aryl-substituted 5-amino-1,3,4-oxadiazole-2-carboxylic acids has been studied. The data support the unimolecular decarboxylation mechanism proposed by us. Moreover, they show that mixed solvents and micelles have different effects on reactivity of the amino acids under study.     

Evaluation of insurance products with guarantee in incomplete markets

Life insurance products are usually equipped with minimum guarantee and bonus provision options. The pricing of such claims is of vital importance for the insurance industry. Risk management, strategic asset allocation, and product design depend on the correct evaluation of the written options. Also regulators are interested in such issues since they have to be aware of the possible scenarios that the overall industry will face. Pricing techniques based on the Black & Scholes paradigm are often used, however, the hypotheses underneath this model are rarely met.To overcome Black & Scholes limitations, we develop a stochastic programming model to determine the fair price of the minimum guarantee and bonus provision options. We show that such a model covers the most relevant sources of incompleteness accounted in the financial and insurance literature. We provide extensive empirical analyses to highlight the effect of incompleteness on the fair value of the option, and show how the whole framework can be used as a valuable normative tool for insurance companies and regulators.     

Contact Pseudo-Metric Manifolds of Constant Curvature and CR Geometry

In this paper, we show that if an integrable contact pseudo-metric manifold of dimension 2n + 1, n ≥ 2, has constant sectional curvature \({\kappa}\) , then the structure is Sasakian and \({\kappa=\varepsilon=g(\xi,\xi)}\) , where \({\xi}\) is the Reeb vector field. We note that the notion of contact pseudo-metric structure is equivalent to the notion of non-degenerate almost CR manifold, then an equivalent statement of this result holds in terms of CR geometry. Moreover, we study the pseudohermitian torsion \({\tau}\) of a non-degenerate almost CR manifold.     

Robust clustering around regression lines with high density regions

Robust methods are needed to fit regression lines when outliers are present. In a clustering framework, outliers can be extreme observations, high leverage points, but also data points which lie among the groups. Outliers are also of paramount importance in the analysis of international trade data, which motivate our work, because they may provide information about anomalies like fraudulent transactions. In this paper we show that robust techniques can fail when a large proportion of non-contaminated observations fall in a small region, which is a likely occurrence in many international trade data sets. In such instances, the effect of a high-density region is so strong that it can override the benefits of trimming and other robust devices. We propose to solve the problem by sampling a much smaller subset of observations which preserves the cluster structure and retains the main outliers of the original data set. This goal is achieved by defining the retention probability of each point as an inverse function of the estimated density function for the whole data set. We motivate our proposal as a thinning operation on a point pattern generated by different components. We then apply robust clustering methods to the thinned data set for the purposes of classification and outlier detection. We show the advantages of our method both in empirical applications to international trade examples and through a simulation study.