Optimal errors-in-variables filtering

This paper deals with optimal (minimal variance) filtering in an errors-in-variables framework. Differently from many other contexts, errors-in-variables models treat all variables in a symmetric way (no partition of the variables into inputs and outputs is required) and assume additive noise on all the variables. The filtering technique described in this paper can be easily implemented in a recursive way and does not require the use of a Riccati equation at every update. The results of Monte Carlo simulations have shown the effectiveness and consistency of the approach.     

Design and Calibration of an Opto-mechanical Appliance for 3D Non-contact Orthopedic Measurements Part II: Calibration Methodology and Experimental Results

A multistep iterative calibration methodology for the opto-mechanical system introduced in Part I is proposed. The methodology makes use of a monoview coplanar set of control points, whose number has been determined on the basis of both geometrical considerations and the results of a statistical analysis aiming at assessing the procedure stability in the case of noisy image data. The calibration procedure is carried out comparing the theoretical and observed images of the calibration pattern. Both synthetic and real data have been employed to test the calibration procedure, which proved to be accurate and efficient. The experimental results achieved by the calibrated system are satisfactory in terms of measurement precision.     

Finite-tree analysis for constraint logic-based languages

Logic languages based on the theory of rational, possibly infinite, trees have much appeal in that rational trees allow for faster unification (due to the safe omission of the occurs-check) and increased expressivity (cyclic terms can provide very efficient representations of grammars and other useful objects). Unfortunately, the use of infinite rational trees has problems. For instance, many of the built-in and library predicates are ill-defined for such trees and need to be supplemented by run-time checks whose cost may be significant. Moreover, some widely used program analysis and manipulation techniques are correct only for those parts of programs working over finite trees. It is thus important to obtain, automatically, a knowledge of the program variables (the finite variables) that, at the program points of interest, will always be bound to finite terms. For these reasons, we propose here a new data-flow analysis, based on abstract interpretation, that captures such information. We present a parametric domain where a simple component for recording finite variables is coupled, in the style of the open product construction of Cortesi et al., with a generic domain (the parameter of the construction) providing sharing information. The sharing domain is abstractly specified so as to guarantee the correctness of the combined domain and the generality of the approach. This finite-tree analysis domain is further enhanced by coupling it with a domain of Boolean functions, called finite-tree dependencies, that precisely captures how the finiteness of some variables influences the finiteness of other variables. We also summarize our experimental results showing how finite-tree analysis, enhanced with finite-tree dependencies, is a practical means of obtaining precise finiteness information.     

Experimental and Numerical Analysis of Soil–Pipe Interaction

Cases of pipeline damage caused by landslides are common in coastal or mountainous regions, where a continuous monitoring/repair activity is planned in order to maintain their serviceability. The analysis of the soil–structure interaction phenomenon can be invoked to improve the planning and design of buried pipelines, to guide monitoring, and to reduce the risk of damage or failure. Two different approaches are considered in this paper: small scale laboratory tests and numerical simulations using the distinct element method (DEM). The experimental setup consists of a box filled with sand and water. Several experiments were performed, in which the diameter and the depth of the tube varied. The numerical simulations are divided in two separate series: in the first, the numerical model is calibrated and its reliability in reproducing the experimental tests is checked; in the second series, the direction of the relative displacement between the tube and the surrounding “numerical soil” varies over the range ±90° with respect to the horizontal. In the latter, both vertical and horizontal components of the drag force are measured and the corresponding interaction diagrams are constructed. The DEM simulations provide useful information about the shape of the failure mechanisms and the force transfer within the soil.     

Flow,Thermal and Microstructural Analysis during Cast Rolling of Steel in In‐line Strip Production Process

A mathematical model was developed to describe the in‐line hot rolling deformation and recrystallization behaviour of austenite after the solidification on a thin slab casting plant. The most significant features of the cast rolling process were taken into consideration: through‐thickness thermal gradients, inhomogeneous stress and strain, temperature discontinuity between the strip and the rolls. A HSLA (High Strength Low Alloy) steel has been chosen to perform the experiments of cast rolling. The characteristic constants ruling the microstructural evolution of that steel were computed and integrated into the computational module which manages the structural stress‐strain and strain rate computation. The developed approach is based on the Navier‐Stokes’ equations which were used to compute the speed field in the strip during the deformation. Then a model providing a proper constitutive equation was structured on the basis of the Yada's model based on evolution of the dislocation populations. The use of the Navier‐Stokes’ formalism allows to reach the resolution of the structural problem from the data measured easily during the industrial practice (i.e. speed of the rolled product at the entry and at the exit of a stand, the temperature of the rolled material). The validation of this computational approach was obtained by a comparison between the prior austenite grain size of the strip in different positions of the hot rolling process, as well as by a comparison between the computed deformation power and the measured one provided by the engines moving the rolls.     

Mass spectrometry for detection of 4-hydroxy-trans-2-nonenal (HNE) adducts with peptides and proteins

Despite the great technical advancement of mass spectrometry, this technique has contributed in a limited way to the discovery and quantitation of specific/precocious markers linked to free radical-mediated diseases. Unsaturated aldehydes generated by free radical-induced lipid peroxidation of polyunsaturated fatty acids, and in particular 4-hydroxy-trans-2 nonenal (HNE), are involved in the onset and progression of many pathologies such as cardiovascular (atherosclerosis, long-term complications of diabetes) and neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, and cerebral ischemia). Most of the biological effects of HNE are attributed to the capacity of HNE to react with the nucleophilic sites of proteins and peptides (other than nucleic acids), to form covalently modified biomolecules that can disrupt important cellular functions and induce mutations. By considering the emerging role of HNE in several human diseases, an unequivocal analytical approach as mass spectrometry to detect/elucidate the structure of protein-HNE adducts in biological matrices is strictly needed not only to understand the reaction mechanism of HNE, but also to gain a deeper insight into the pathological role of HNE. This with the aim to provide intermediate diagnostic biomarkers for human diseases. This review sheds focus on the "state-of-the-art" of mass spectrometric applications in the field of HNE-protein adducts characterization, starting from the fundamental early studies and discussing the different MS-based approaches that can provide detailed information on the mechanistic aspects of HNE-protein interaction. In the last decade, the increases in the accessible mass ranges of modern instruments and advances in ionization methods have made possible a fundamental improvement in the analysis of protein-HNE adducts by mass spectrometry, and in particular by matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) tandem mass spectrometry. The recent developments and uses of combined analytical approaches to detect and characterize the type/site of interaction have been highlighted, and several other aspects, including sample preparation methodologies, structure elucidation, and data analysis have also been considered.     

Magnetoelastic Stability of Magnetic Axial Bearings

Permanent magnet bearings offer no wear and no mechanical friction. Recently, Rare Earth (RE) permanent magnets have been used, which give rise to force fields 20 times greater than those of common magnets. RE also allows to build magnets suitable for bearings of every shape. RE bearings are then profitable. On the other hand, permanent magnet bearings are unstable. For example, the levitated ring of the axial bearing with opposite magnetic fields of Fig. 1 is stable axially, but unstable radially. It has been, however, verified that a permanent magnet system may become stable under peculiar conditions. As an example, if the above-mentioned levitated ring is subjected to a parametric axial excitation, its radial instability can be removed. In our opinion, it may also be possible that stability is obtained by exploiting microstructural properties of ferromagnetic materials, especially of RE, like dimensional and magnetic changes if subjected to mechanical stresses. Then, in this paper, the stability of the levitated member of an RE axial ring bearing is investigated by a suitable exploitation of magnetoelastic properties of the ring.

Proteins as biomarkers of oxidative/nitrosative stress in diseases: the contribution of redox proteomics

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) contribute to the pathogenesis and/or progression of several human diseases. Proteins are important molecular signposts of oxidative/nitrosative damage. However, it is generally unresolved whether the presence of oxidatively/nitrosatively modified proteins has a causal role or simply reflects secondary epiphenomena. Only direct identification and characterization of the modified protein(s) in a given pathophysiological condition can decipher the potential roles played by ROS/RNS-induced protein modifications. During the last few years, mass spectrometry (MS)-based technologies have contributed in a significant way to foster a better understanding of disease processes. The study of oxidative/nitrosative modifications, investigated by redox proteomics, is contributing to establish a relationship between pathological hallmarks of disease and protein structural and functional abnormalities. MS-based technologies promise a contribution in a new era of molecular medicine, especially in the discovery of diagnostic biomarkers of oxidative/nitrosative stress, enabling early detection of diseases. Indeed, identification and characterization of oxidatively/nitrosatively modified proteins in human diseases has just begun.     

Simplified seismic analysis of piping or equipment mounted on two points of a multistory structure

A simplified procedure is presented to calculate the maximum earthquake response of light mechanical or electrical equipment supported at two arbitrary points of a building structure. The procedure is derived on the basis of the application of the response spectrum method to a combined structure-equipment system, but, in an effort to avoid the complications of such an approach, it is formulated in terms of the dynamic characteristics of the two independent components. It fully takes into account the interaction between the two subsystems, and avoids the generation of floor response spectra and the need to consider two different support excitations. The formulation is attained by using Hurty's component mode synthesis technique and Rayleigh's principle. Linear systems with classical modes of vibration and small structure to equipment mass ratios are considered. The simplicity of the method is demonstrated by a numerical example, and its accuracy verified by a comparative study. In this comparative study, the suggested procedure estimates correct solutions with an average error of about 2%.     

Efficient simulation of hierarchical stochastic activity network models

Stochastic extensions to Petri nets have gained widespread acceptance as a method for describing the dynamic behavior of discrete-event systems. Both simulation and analytic methods have been proposed to solve such models. This paper describes a set of efficient procedures for simulating models that are represented as stochastic activity networks (SANs, a variant of stochastic Petri nets) and composed SAN-based reward models (SBRMs). Composed SBRMs are a hierarchical representation for SANs, in which individual SAN models can be replicated and joined together with other models, in an iterative fashion. The procedures exploit the hierarchical structure and symmetries introduced by the replicate operation in a composed SBRM to reduce the cost of future event list management. The procedures have been implemented as part of a larger performance-dependability modeling package known asUltraSAN, and have been applied to real, large-scale applications. This work was supported in part by the Digital Equipment Corporation Faculty Program: Incentives for Excellence.