An improved algorithm for optimum structural design with multiple frequency constraints

An optimality criterion (OC) method for minimum-weight design of structures having multiple constraints on natural frequencies is presented. In this work a new resizing strategy is developed based on relaxation techniques. A computationally adaptive control parameter is used in conjunction with existing OC recursive formulae to promote convergence of optimum structural designs. Some considerations regarding the coupling of the modified Aitken accelerator with the OC method are discussed. Improved and rapidly converged minimum-weight designs are obtained when using an under-relaxed recursive scheme combined with the modified Aitken accelerator

System/observer/controller identification toolbox

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data

The transformation of asymmetry: the evolution of Philippine and Vietnamese South China Sea policies and the asymmetry of attention

Most relations among states are asymmetric due to a disparity of capacities. This does not mean the strong can crush the weak at will, as the cost could outweigh the gain. If the weaker side sees an issue as more important than the stronger side, the former is likely to invest more attention into building a more robust will and tougher stance against the pressure at hand. However, China’s South China Sea (SCS) policy and neighbouring states’ responses to it demonstrate another scenario: small states may lose the advantages of heightened attention if the great power shifts its focus onto the same issue, dedicating more political resources to it. This represents a missing piece in the established theory of asymmetric politics. The present article examines pertinent policy adjustments by the Philippines and Vietnam before and after Chinese diplomacy gravitated towards prioritising the SCS from 2014 to 2016, especially after the 2016 Arbitration. I argue that, with the US increasingly presence in the region, China’s attention shift to the SCS reflects Beijing’s decision to put more diplomatic resources and time into forming a consistent strategy to replace its uncoordinated policies out of the inattention, which previously motivated small states to make significant policy adjustments in response. In analysing Philippine and the Vietnamese stances on the South China Sea, I gauge the reasons for the two countries’ policy changes from a proactive stance in internationalising the issue to a low-profile posture as an attempt to mend fences with China after the attention shift. Hence, this study aims to reveal the motives behind small states’ policy adjustments, as well as to expand the explanatory scope of the theory of asymmetric attention

Linear response within the projection-based renormalization method: Many-body corrections beyond the random phase approximation

The explicit evaluation of linear response coefficients for interacting many-particle systems still poses a considerable challenge to theoreticians. In this work we use a novel many-particle renormalization technique, the so-called projector-based renormalization method, to show how such coefficients can systematically be evaluated. To demonstrate the prospects and power of our approach we consider the dynamical wave-vector dependent spin susceptibility of the two-dimensional Hubbard model and also determine the subsequent magnetic phase diagram close to half-filling. We show that the superior treatment of (Coulomb) correlation and fluctuation effects within the projector-based renormalization method significantly improves the standard random phase approximation results.Comment: 17 pages, 7 figures, revised versio

Immune complex relay by subcapsular sinus macrophages and noncognate B cells drives antibody affinity maturation.

Subcapsular sinus (SCS) macrophages capture antigens from lymph and present them intact for B cell encounter and follicular delivery. However, the properties of SCS macrophages are poorly defined. Here we show SCS macrophage development depended on lymphotoxin-alpha1beta2, and the cells had low lysosomal enzyme expression and retained opsonized antigens on their surface. Intravital imaging revealed immune complexes moving along macrophage processes into the follicle. Moreover, noncognate B cells relayed antigen opsonized by newly produced antibodies from the subcapsular region to the germinal center, and affinity maturation was impaired when this transport process was disrupted. Thus, we characterize SCS macrophages as specialized antigen-presenting cells functioning at the apex of an antigen transport chain that promotes humoral immunity

System identification from closed-loop data with known output feedback dynamics

This paper presents a procedure to identify the open loop systems when it is operating under closed loop conditions. First, closed loop excitation data are used to compute the system open loop and closed loop Markov parameters. The Markov parameters, which are the pulse response samples, are then used to compute a state space representation of the open loop system. Two closed loop configurations are considered in this paper. The closed loop system can have either a linear output feedback controller or a dynamic output feedback controller. Numerical examples are provided to illustrate the proposed closed loop identification method

Identification of linear systems by an asymptotically stable observer

A formulation is presented for the identification of a linear multivariable system from single or multiple sets of input-output data. The system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded eigenvalue assignment procedure. The prescribed eigenvalues for the observer may be real, complex, mixed real and complex, or zero. In this formulation, the Markov parameters of the observer are identified from input-output data. The Markov parameters of the actual system are then recovered from those of the observer and used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and extensive numerical examples using simulated noise-free data are presented to illustrate the proposed method