The design of robust value-creating supply chain networks: A critical review

This paper discusses Supply Chain Network (SCN) design problem under uncertainty, and presents a critical review of the optimization models proposed in the literature. Some drawbacks and missing aspects in the literature are pointed out, thus motivating the development of a comprehensive SCN design methodology. Through an analysis of supply chains uncertainty sources and risk exposures, the paper reviews key random environmental factors and discusses the nature of major disruptive events threatening SCN. It also discusses relevant strategic SCN design evaluation criteria, and it reviews their use in existing models. We argue for the assessment of SCN robustness as a necessary condition to ensure sustainable value creation. Several definitions of robustness, responsiveness and resilience are reviewed, and the importance of these concepts for SCN design is discussed. This paper contributes to framing the foundations for a robust SCN design methodology.     

Modal exact linearization of a class of second-order switched nonlinear systems

This paper considers the problem of stabilizing single-input affine switched nonlinear systems. The main idea is to transform a switched nonlinear system to an equivalent controllable switched linear system. First, we define the notion of modal state feedback linearization. Then, we develop a set of conditions for modal state feedback linearizability of a certain class of second order switched nonlinear systems. Considering two special structures, easily verifiable conditions are proposed for the existence of suitable state transformations for modal feedback linearization. The results are constructive. Finally, the method is illustrated with two examples, including a Continuous Stirred Tank Reactor (CSTR) to demonstrate the applicability of the proposed approach.     

Localization from Incomplete Noisy Distance Measurements

We consider the problem of positioning a cloud of points in the Euclidean space ? ^d , using noisy measurements of a subset of pairwise distances. This task has applications in various areas, such as sensor network localization and reconstruction of protein conformations from NMR measurements. It is also closely related to dimensionality reduction problems and manifold learning, where the goal is to learn the underlying global geometry of a data set using local (or partial) metric information. Here we propose a reconstruction algorithm based on semidefinite programming. For a random geometric graph model and uniformly bounded noise, we provide a precise characterization of the algorithm’s performance: in the noiseless case, we find a radius r ₀ beyond which the algorithm reconstructs the exact positions (up to rigid transformations). In the presence of noise, we obtain upper and lower bounds on the reconstruction error that match up to a factor that depends only on the dimension d, and the average degree of the nodes in the graph.     

Une formulation hybride du modèle de coque de Naghdi

We present a new version of the Naghdi model for shells with curvature discontinuities. The unknowns – the displacement and the rotation of the normal to the shell midsurface – are described respectively in Cartesian and local covariant or contravariant basis. Our purpose here is to consider a constraint-free formulation instead of the one introduced by Blouza et al. (Two finite element approximation of Naghdi?s shell model in Cartesian coordinates, SIAM J. Numer. Anal. 44 (2) (2006) 636–654), where the tangency character of the rotation is enforced by penalization or by duality. This new version enables us, in particular, to approximate by conforming finite elements the solution with less degrees of freedom compared to the method of Blouza et al.     

A Characterization of Generalized Derivations on Prime Rings

Let R be a noncommutative prime ring, U be the left Utumi quotient ring of R, and k, m, n, r be fixed positive integers. If there exist a generalized derivation G and a derivation g (which is independent of G) of R such that [G(x^m)xⁿ + xⁿg(x^m), x^r]_k = 0, for all x ∈ R, then there exists a ∈ U such that G(x) = ax, for all x ∈ R. As a consequence of the result in the present article, one may obtain Theorem 1 in Demir and Argaç [10 Demir, Ç., Argaç, N. (2010). A result on generalized derivations with Engel conditions on one-sided ideals. J. Korean Math. Soc. 47(3):483–494.[Crossref], [Web of Science ®] , [Google Scholar]].     

On the Simplicity of the Lie Algebra of a Leavitt Path Algebra

For a field F and a row-finite directed graph Γ, let L(Γ) be the associated Leavitt path algebra. We find necessary and sufficient conditions for the Lie algebra [L(Γ), L(Γ)] to be simple.     

Finite difference approach to trigonometry

Two interrelated, finite difference and graph theoretic, approaches to trigonometry are developed by combining a generalization of the finite difference method first employed by Viète, with solution techniques, based on signal flow graphs, for finite difference equations with variable coefficients, and a scaling approach to trigonometry, based on the polygonometric identities.     

Experimental study of V–I characteristics of wire–plate electrostatic precipitators under clean air conditions

In this paper a laboratory-scale model for prediction of the voltage–current characteristics of wire–plate electrostatic precipitators under clean air conditions is presented and experimentally validated. The model investigates the effect of electrode configurations, wire diameter, spacing between wire electrodes, number of discharge wires and distance between collecting plates that on voltage–current characteristic of wire–plate electrostatic precipitators. Also, this paper presents a simulation model, based on the Finite Difference Method (FDM), to simulate electric conditions of wire–plate electrostatic precipitators under clean air conditions. The experimental results of some models are compared with those obtained from the simulation models.     

The generalized Gompertz distribution

This paper deals with a new generalization of the exponential, Gompertz, and generalized exponential distributions. This distribution is called the generalized Gompertz distribution (GGD). The main advantage of this new distribution is that it has increasing or constant or decreasing or bathtub curve failure rate depending upon the shape parameter. This property makes GGD is very useful in survival analysis. Some statistical properties such as moments, mode, and quantiles are derived. The failure rate function is also derived. The maximum likelihood estimators of the parameters are derived using a simulations study. Real data set is used to determine whether the GGD is better than other well-known distributions in modeling lifetime data or not.     

Segregation of tetracarbon units in low-energy tetracarbindane structures: Major differences from their aluminum and gallium analogs

The structures and energetics of the tetracarbindanes C₄In_n−4Me_n (n = 6-14) have been determined by density functional theory. In contrast to their aluminum and gallium analogs, the lowest energy tetracarbindanes typically have all four carbon atoms segregated into a single C₄ unit. Thus, linear C₄ units resembling butadiene are found in the lowest energy C₄In_n−4Me_n structures. In addition, some higher energy tetracarbindane structures have a structural feature not found in any of the corresponding tetracarbalanes and tetracarbagallanes, namely closed trapezoidal C₄ units resembling cyclobutene. Such trapezoidal C₄ units bind to the In_n−4 subcluster with the CC edge bonding to a single indium atoms as an olefin-metal or 3-center 2-electron bond. These differences may be attributed to the larger size of indium atoms (1.42 Å covalent radius) relative to gallium atoms (1.22 Å covalent radius).