A framework for analytical cost estimation of mechanical components based on manufacturing knowledge representation

This paper presents a novel framework for manufacturing and cost-related knowledge formalization. This artefact allows industries to capitalize the knowled     

Filtering for bimodal systems: the case of unknown switching statistics

This paper considers the problem of state estimation for discrete-time systems whose dynamics randomly switches between two linear stochastic behaviors (bimodal systems). The novelty of this paper is that no statistical information on the switching process is assumed available for the filter design. Two different approaches are here proposed to solve the estimation problem in these conditions. One method is based on a combined use of stochastic singular systems and of the minimax filtering theory, while the other relies on the maximum entropy principle. Based on these approaches two filtering algorithms are derived, whose features are theoretically and numerically compared. Some attention has been devoted to the study of the asymptotic properties of both the filters.     

Linear filtering for bilinear stochastic differential systems with unknown inputs

Investigates the problem of state estimation for bilinear stochastic multivariable differential systems in the presence of an additional disturbance, whose statistics are completely unknown.. A linear filter is proposed, based on a suitable decomposition of the state of the bilinear system into two components. The first one is a computable function of the observations while the second component is estimated via a suitable linear filtering algorithm. No a priori information on the disturbance is required for the filter implementation. The proposed filter is robust with respect to the unknown input, in that the covariance of the estimation error is not affected by such input. Numerical simulations show the effectiveness of the proposed filter.     

Traceability as a means to investigate supply chain sustainability: the real case of a leather shoe supply chain

In recent years, the growing attention to environmental challenges has shown that these issues are becoming of more and more interest to both research and industry. Companies are expected to ensure their products are fully traceable and more sustainable, which requires the involvement of all of the actors in the production network. According to this aim, this study proposes a structured approach that uses the traditional traceability concept as a means to identify the main information needed to assess environmental impacts along the whole supply chain (SC). The proposed approach is composed of four main steps: (i) SC modelling to identify all stakeholders and their inter-relations, (ii) data sharing to collect all relevant data, (iii) data elaboration to calculate performance at different levels of detail and (iv) result interpretation to optimise the SC. The distributed implementation of the approach at different SC steps represents a useful means to practically realise a sustainable SC management. A case study involving a leather shoe SC is used to demonstrate the effectiveness of the approach in identifying criticalities, supporting the selection of the most appropriate suppliers and correctly setting a management strategy towards the optimisation of internal and external traceability and environmental sustainability performances.     

Electro-tactile device for material texture simulation

This paper deals with the simulation of material texture by means of electro-tactile stimuli, which directly derive from real material properties. The research presents a novel tactile display by its hardware and software system architecture and the elaboration procedure to generate the stimulating signals, and validates the adopted simulation strategy by experimental testing. The tactile system elaborates data from scans of real material samples and generates electrical stimuli to reproduce roughness and texture coarseness sensations. It also adds a coherent sound feedback to improve the realism of the simulation. The research defines also an experimental protocol based on the theory of Psychophysics to carry out system calibration and tests with users. The scope is to validate the proposed tactile system as a new tool for material simulation, which can be adopted for material virtual prototyping in several fields (product design, textile and clothing, gaming and entertainment, virtual museum, rehabilitation, etc.). Experimentations have been carried out to measure the users’ response to our different material classes (wood, paper, rubber and textile fabric). Experimental results concern how good the adopted simulation approach is and the analysis of the human tactile perception simulated by the system. Main findings relate to the system performance and the users’ response in terms of signal recognition and material class discrimination.     

Optimization of a water–gas shift reactor over a Pt/ceria/alumina monolith

The water–gas shift (WGS) reaction is an important step in the purification of hydrogen for fuel cells. It lowers the carbon monoxide content and produces extra hydrogen. The constraints of automotive applications render the commercial WGS catalysts unsuitable. Pt/ceria catalysts are cited as promising catalysts for onboard applications as they are highly active and non-pyrophoric. This paper reports on a power law rate expression for a Pt/CeO₂/Al₂O₃ catalyst. This rate equation is used to compare different reactor configurations for an onboard water–gas shift reactor. A one-dimensional heterogeneous model that accounts for the interfacial and intraparticle gradients has been used to optimize a dual stage adiabatic monolith reactor.     

Kalman filter approach to solution of rational expectations models

The solution of forward looking dynamical models for economical systems consists in finding a suitable expression of the forcing term describing the agents expectations on the future behaviour of the involved economical variables. In this paper, such a control function is estimated by a Kalman filtering technique which allows us to exploit just the current informations. The solution obtained is shown to be an asymptotically stationary process with finite steady-state covariance.     

Vav binding to heterogeneous nuclear ribonucleoprotein (hnRNP) C. Evidence for Vav-hnRNP interactions in an RNA-dependent manner

The vav proto-oncogene is exclusively expressed in hematopoietic cells and encodes a 95-kDa protein that contains multiple structural domains. Vav is involved in the expansion of T and B cells, in antigen-mediated proliferative responses, and in the induction of intrathymic T cell maturation. It becomes rapidly and transiently tyrosine-phosphorylated upon triggering of a large number of surface receptors and catalyzes GDP/GTP exchange on Rac-1. We now provide evidence for the specific interaction of Vav with heterogeneous nuclear ribonucleoprotein (hnRNP) C. Vav and hnRNP C interact both in vivo and in vitro mediated through the carboxyl Src homology 3 domain of Vav and the proline-rich motif located in the nuclear retention sequence of hnRNP C. More importantly, Vav-hnRNP C complexes are present in living hematopoietic cells and both proteins localize in the nuclei, mainly on perichromatic fibrils but also on clusters of interchromatin granules. The Vav-hnRNP C interaction is regulated by poly(U) RNA, although a basal association is still detected in the absence of RNA. Furthermore, RNA homopolymers differentially alter the binding affinity of Vav to hnRNP C and hnRNP K. We propose that Vav-hnRNP interactions may be established in an RNA-dependent manner.