Zipf`s law strikes again : the case of tourism

This paper examines the applicability of Zipf's law to tourism. It is established that a variation of this law holds in this case - a rank-size rule with concavity. Due to this non-linearity, it is shown that a spline regression provides an extremely convenient tool for predicting tourist arrivals in a country. The concavity is explained by appealing to random growth theory (lognormal distribution; Gibrat's law) and locational fundamentals.

Robust strictly positive real synthesis of polynomial segments for discrete time systems

By using the result of robust strictly positive real synthesis of polynomial segments for continuous time systems, it is proved that, for any two n-th order polynomials a(z) and b(z), the Schur stability of their convex combination is necessary and sufficient for the existence of an n-th order polynomial c(z) such that c(z)/a(z) and c(z)/b(z) are both strictly positive real. We also provide the construction method of c(z). Illustrative examples are provided to show the effectiveness of this method.

Photoaffinity labeling of the N-methyltransferase domains of cyclosporin synthetase

The multifunctional polypeptide cyclosporin synthetase (CySyn) remains one of the most complex nonribosomal peptide synthetase described. In this study we used a highly specific photoaffinity labeling procedure with the natural cofactor S-adenosyl-l-methionine (AdoMet), 14C-isotopically labeled at the Sδ methyl group to probe the concerted AdoMet-binding interaction of the N-methyltransferase (N-MTase) centers of CySyn. The binding stoichiometry for the enzyme–AdoMet complex was determined to be 1:7, which is in agreement with inferences made from analysis of the complementary DNA sequence of the simA gene encoding the CySyn polypeptide. The photolabeling of the AdoMet-binding sites displayed homotropic negative cooperativity, characterized by a curvilinear Scatchard plot with upward concavity. Although, the process of N-methyl transfer is not a critical event for peptide elongation, the destabilizing homotropic interactions between N-MTase centers that were observed may represent a mechanism whereby the enzyme preserves the proficiency of the substrate-channeling process of cyclosporin peptide assembly over a broad range of cofactor concentrations. Furthermore, we demonstrated the utility of the photolabeling procedure for tracking the enzyme during purification.

Relative responsiveness of bargaining solutions to changes in status-quo payoffs

It is a well-known fact that several prominent bargaining solutions are responsive to changes in status-quo (i.e., disagreement or fallback) payoffs. When an agent’s status-quo payoff increases, his solution payoff either stays the same or increases. A fully general result for these solutions’ status-quo point ranking is impossible to establish. In this paper, using an important class of bargaining problems, a ranking of the relative status-quo point responsiveness of prominent bargaining solutions is obtained. Using the Constant Elasticity of Substitution class of bargaining problems, regardless of the concavity of the Pareto frontier and the level of increase in one’s status-quo payoff, we find the equal gains solution is the most responsive with respect to changes in status-quo payoffs, followed by the Nash solution. The equal sacrifice solutions is the least responsive, followed by the Kalai/Smorodinsky solution.

Vehicle detection and classification by measuring and processing magnetic signal

This paper presents novel vehicle detection and classification method by measuring and processing magnetic signal based on single micro-electro- mechanical system (MEMS) magnetic sensor. When a vehicle moves over the ground, it generates a succession of impacts on the earth's magnetic field, which can be detected by single magnetic sensor. The magnetic signal measured by the magnetic sensor is related to the moving direction and the type of the vehicle. Generally, the recognition rate using single sensor detector is not high. In order to improve the recognition rate, a novel feature extraction algorithm and a novel vehicle classification and recognition algorithm are presented. The concavity and convexity areas, and the angles of concave and convex parts of the waveform are extracted. An improved support vector machine (ISVM) classifier is developed to perform vehicle classification and recognition. The effectiveness of the proposed approach is verified by outdoor experiments.