Severity of airflow limitation is associated with severity of airway inflammation in smokers

To investigate the relationship between airflow limitation and airway inflammation in smokers, we examined paraffin-embedded bronchial biopsies obtained from 30 smokers: 10 with severe airflow limitation, eight with mild/moderate airflow limitation, and 12 control smokers with normal lung function. Histochemical and immunohistochemical methods were performed to assess the number of inflammatory cells in the subepithelium and the expression of CC chemokines macrophage inflammatory protein (MIP)-1alpha and -1beta in the bronchial mucosa. Compared with control smokers, smokers with severe airflow limitation had an increased number of neutrophils (p < 0.02), macrophages (p < 0.03), and NK lymphocytes (p < 0.03) in the subepithelium, and an increased number of MIP-1alpha+ epithelial cells (p < 0.02). When all smokers were considered together, the value of FEV1 was inversely correlated with the number of neutrophils (r = -0.59, p < 0.002), macrophages (r = -047, p < 0. 012), NK-lymphocytes (r = -0.51, p < 0.006) in the subepithelium, and with the number of MIP-1alpha+ epithelial cells (r = -0.61, p < 0.003). We conclude that in smokers the severity of airflow limitation is correlated with the severity of airway inflammation and that severe airflow limitation is associated with an increased number of neutrophils, macrophages, NK lymphocytes, and MIP-1alpha+ cells in the bronchial mucosa.     

Self-organized coordinated motion in groups of physically connected robots.

An important goal of collective robotics is the design of control systems that allow groups of robots to accomplish common tasks by coordinating without a centralized control. In this paper, we study how a group of physically assembled robots can display coherent behavior on the basis of a simple neural controller that has access only to local sensory information. This controller is synthesized through artificial evolution in a simulated environment in order to let the robots display coordinated-motion behaviors. The evolved controller proves to be robust enough to allow a smooth transfer from simulated to real robots. Additionally, it generalizes to new experimental conditions, such as different sizes/shapes of the group and/or different connection mechanisms. In all these conditions the performance of the neural controller in real robots is comparable to the one obtained in simulation.     

LEARNING OLIGOPOLISTIC COMPETITION IN ELECTRICITY AUCTIONS

This paper addresses the problem of auction markets efficiency within the context of recently liberalized electricity markets. Two different auction mechanisms, i.e., the uniform and the discriminatory price setting rules, have been employed worldwide in designing electricity markets. In this paper, we study the relative efficiency of the two auction mechanisms in the framework of the learning-in-games approach. The behavior of electricity suppliers are modeled by means of an adaptive learning algorithm and the demand is assumed to be constant and inelastic, according to a common hypothesis in electricity market modeling. Computational experiments results are interpreted according game theoretical solutions, i.e., Nash equilibria and Pareto optima. Different economic scenarios corresponding to a duopoly and a tripoly competition with different level of demand are considered. Results show that in the proposed conditions, sellers learn to play competitive strategies, which correspond to Nash equilibria. Finally, this study establishes that, in the presented computational setting and economic scenarios, the discriminatory auction mechanism results more efficient than the uniform auction one.     

Optimization Strategies for the Entropic Lattice Boltzmann Method

The entropic formulation of the lattice Boltzmann method (LBM) features enhanced numerical stability due to its compliance with the Boltzmann H-theorem. This stability comes at the price of some computational overhead, associated with the need of adjusting the local relaxation time of the standard LBM in such a way as to secure compliance with the H-theorem. In this paper, we discuss a number of possible optimization strategies to reduce the computational overhead of entropic LBMs.     

Deterioration status of asbestos-cement roofing sheets assessed by analyzing hyperspectral data

This paper describes a systematic procedure for recognizing corrugated asbestos-cement roofing sheets and evaluating their deterioration status related to the asbestos fiber air dispersion that can cause lung cancer. To develop this procedure, we made field and laboratory measurements and gathered airborne MIVIS data covering two industrial test areas in Italy.Laboratory analyses of asbestos-cement samples representing various levels of deterioration allowed for: (a) recognizing dominant minerals using XRD and FTIR instruments, (b) identifying their optical characteristics using portable field spectrometers (ASD and μFTIR), (c) assessing the abundance of surfacing asbestos fibers using a high resolution scanner.Based on the spectral analyses, two linear regression lines were identified by relating optical asbestos-cement material characteristics (i.e. band-depth ratio of the continuum removed calculated for the two asbestos diagnostic bands at 2.32 μm and at 9.44 μm) to the relative percentage of surfacing asbestos fibers related to AC deterioration status.Suitable MIVIS spectral regions were used in a spectral classification procedure to map asbestos-cement roofs. The detected roofs were further analyzed using the obtained linear regression lines to estimate surfacing asbestos fiber abundance, using the MIVIS TIR range at 9.44 μm, selected by means of the asbestos-cement detection limit analysis.The results showed that a hyperspectral scanner with suitable operational characteristics allows for good clustering of AC roofs as a function of their deterioration status. Therefore, this technique can furnish government authorities with an efficient, rapid and repeatable environmental mapping procedure that can provide information about the location of hazardous AC roofing sheets.     

The Esperanto Broker: a communication platform for nomadic computing systems

There is an increasing demand for middleware for nomadic computing applications. Owing to the inherent characteristics of such environments, these platforms have to address two fundamental issues: (i) device disconnections and the limitations of wireless networks may force users to experience short periods of service unavailability; and (ii) the complexity to design and develop next‐generation mobile computing applications. This paper proposes the Esperanto Broker (EB), a communication platform that addresses mobility issues via an integrated approach, i.e. at data‐link, network, and middleware levels. Decoupling interactions are achieved via a tuple‐space underlying infrastructure. To support developers with advanced services, the EB enhances the distributed objects computing model providing the abstraction for the communication paradigms standardized by the W3C. Esperanto applications can be modeled as sets of objects that are distributed over mobile devices, which communicate via remote method invocations (RMIs). RMIs natively implement pull and push models, in both one‐to‐one and one‐to‐many multiplicity. The paper focuses on the EB design issues, essential aspects of the implementation, and performance evaluations of the implemented prototype. Copyright © 2006 John Wiley & Sons, Ltd.     

Practical Formulas for the Dimensioning of Air Valves

On the basis of theoretical considerations, the technical note presents two practical formulas for the dimensioning of air valves when filling a pipe with water. One is to be used for designing air valves on the basis of the maximum allowed water hammer overpressures; the other when the maximum in pipe water velocity is set. The reliability of these formulas was tested with a numerical model based on the same hypothesis, which was in turn verified with experimental tests.     

The revolution of counting "tops": two decades of the disector principle in morphological research

Twenty years have passed since the publication of the seminal paper enunciating the disector principle by an author using the pseudonym D.C. Sterio. During this time, methods based on the revolutionary principle of counting "tops" have become progressively better known and have been included in several commercially available systems for quantitative morphology. Analysis of the number of published studies citing Sterio's paper on the ISI Web of Knowledge database showed that its scientific "impact factor" has almost continuously risen since its publication, indicating the growing knowledge about disector-based methods in the various scientific fields where morphological quantification is required. This report briefly reviews the first two decades of disector use, pointing to its advantages as well as to shortcomings that have recently been addressed in critical papers and have given rise to a lively debate on the role of counting tops in quantitative morphology today.     

Reliability of parameter estimation in respirometric models

When modelling a biochemical system, the fact that model parameters cannot be estimated exactly stimulates the definition of tests for checking unreliable estimates and design better experiments. The method applied in this paper is a further development from Marsili-Libelli et al. [2003. Confidence regions of estimated parameters for ecological systems. Ecol. Model. 165, 127-146.] and is based on the confidence regions computed with the Fisher or the Hessian matrix. It detects the influence of the curvature, representing the distortion of the model response due to its nonlinear structure. If the test is passed then the estimation can be considered reliable, in the sense that the optimisation search has reached a point on the error surface where the effect of nonlinearities is negligible. The test is used here for an assessment of respirometric model calibration, i.e. checking the experimental design and estimation reliability, with an application to real-life data in the ASM context. Only dissolved oxygen measurements have been considered, because this is a very popular experimental set-up in wastewater modelling. The estimation of a two-step nitrification model using batch respirometric data is considered, showing that the initial amount of ammonium-N and the number of data play a crucial role in obtaining reliable estimates. From this basic application other results are derived, such as the estimation of the combined yield factor and of the second step parameters, based on a modified kinetics and a specific nitrite experiment. Finally, guidelines for designing reliable experiments are provided.