Potential to retrofit existing small-scale gasifiers through steam gasification of biomass residues for hydrogen and biofuels production

This work investigates the opportunity of retrofitting existing small-scale gasifiers shifting from combined heat and power (CHP) to hydrogen and biofuels production, using steam and biomass residues (woodchips, vineyard pruning and bark). The experiments were carried out in a batch reactor at 700 °C and 800 °C and at different steam flow (SF) rates (0.04 g/min and 0.20 g/min). The composition of the producer gas is in the range of 46–70 % H₂, 9–29 % CO, 12–27 % CO₂, and 2–6 % CH₄. A producer gas specific production factor of approx. 10 NL_pg/g_char can be achieved when the lower SFs are used, which allows to provide 80 % of the hydrogen concentration required for biomethanation and MeOH synthesis. As for FT synthesis, an optimal H₂/CO ratio of approx. 2 can be achieved. The results of this work provide further evidence towards the feasibility of hydrogen and biofuels generation from residual biomass through steam gasification.     

Nanoporous microtubes obtained from a Cu-Ni metallic wire

Nanoporous microtubes of a nickel-copper alloy were obtained from a Cu-44Ni-1Mn (wt%) commercial wire (200 μm diameter). A new synthesis method was established through three steps: 1) partial oxidation of the wire at 1173 K in air, 2) removal of the inner unoxidized core by chemical etching, 3) reduction in 10 bar hydrogen atmosphere. During oxidation, the segregation of Cu and Ni occurred because of their different diffusion coefficients in the corresponding oxides. As a consequence, pores were formed by Kirkendall effect and due to selective chemical etching of the different oxides. Additional porosity formed because of volume contraction during reduction with hydrogen. After reduction, the microtube shows a composition gradient from the inner wall (almost pure nickel) to the outer wall (almost pure copper). The process allowed to obtain microtubes with tuneable wall thickness and inner pores around 180 ± 80 nm. The morphological features developed suggest improved capillarity properties for applications in MEMS.     

Circulating Tumor Cells in the Adenocarcinoma of the Esophagus

Circulating tumor cells (CTCs) are elements of indisputable significance as they seem to be responsible for the onset of metastasis. Despite this, research into CTCs and their clinical application have been hindered by their rarity and heterogeneity at the molecular and cellular level, and also by a lack of technical standardization. Esophageal adenocarcinoma (EAC) is a highly aggressive cancer that is often diagnosed at an advanced stage. Its incidence has increased so much in recent years that new diagnostic, prognostic and predictive biomarkers are urgently needed. Preliminary findings suggest that CTCs could represent an effective, non-invasive, real-time assessable biomarker in all stages of EAC. This review provides an overview of EAC and CTC characteristics and reports the main research results obtained on CTCs in this setting. The need to carry out further basic and translational research in this area to confirm the clinical usefulness of CTCs and to provide oncologists with a tool to improve therapeutic strategies for EAC patients was herein highlighted.     

Experimental tests on the limit states of dry-jointed tuff blocks

A proper definition of the yield domains governing the frictional behaviour at contact interfaces is generally required to perform the limit analysis of 3D dry-jointed masonry block structures. However, the modelling of the actual behaviour of frictional contact interfaces under simultaneous normal and shear forces, torsion and bending moments is a topic still poorly studied, especially from the experimental point of view. In this paper the single contact interface of a system composed of two dry-jointed tuff blocks under different loading conditions is experimentally investigated. The programme includes several sets of tests based on different eccentricities of the vertical and horizontal loading implying pure strengths and interactions among shear, torsion and bending moments. The results of each set are then compared with those obtained by a recently proposed numerical model for 3D masonry block assemblages, based on the assumptions of infinite strength in compression, tension and shear for blocks and no-tension and frictional behaviour at their contact. The comparison is useful, on the one hand, as a further validation the efficacy of the previously proposed yield domains in order to be used in 3D limit analysis formulations and, on the other, to highlight which yield domains need to be better represented.     

Reversible Fragmentation and Self‐Assembling of Nematic Liquid Crystal Droplets on Functionalized Pyroelectric Substrates

Investigation on the behavior of nematic liquid crystals on functionalized polar dielectric crystal substrates is accomplished. Very interesting effects can be observed in maneuvering liquid crystal droplets on the substrate surface, driven by electric fields generated by pyroelectric effect. Reversible drops fragmentation and self‐assembling in different configurations can be achieved. The dynamics of the observed phenomena is studied and the repeatability of the process is full assessed.     

An LMI approach for H ∞ analysis and control of discrete-time piecewise affine systems

In this paper we investigate some analysis and control problems for discrete-time hybrid systems in the piece-wise affine form. By using arguments from the dissipativity theory for non-linear systems, we show that H X analysis and synthesis problems can be formulated and solved via linear matrix inequalities by taking into account the switching structure of the considered system. In this paper we address the generalized problem of controlling hybrid systems whose switching structure does not depend only on the state but also on the control input.     

On the detection of card-sharing traffic through wavelet analysis and Support Vector Machines

In the last years, the interest in methods and techniques for circumventing the security of the available digital video broadcasting systems is continuously increasing. Digital TV providers are struggling to restrict access to their video contents only to authorized users, by deploying more and more sophisticated conditional access systems. At the state-of-the-art, the most significant menace is the card-sharing activity which exploits a known weakness allowing an authorized subscriber to provide access to digital contents to a potentially large group of unauthorized ones connected over a communication network. This is usually realized by using ad hoc customized devices. Detecting the presence of these illegal systems on a network, by recognizing their related traffic is an issue of primary importance. Unfortunately, to avoid the identification of such traffic, payload obfuscation strategies based on encryption are often used, hindering packet inspection techniques.This paper presents a strategy for the detection of card-sharing traffic, empowered by machine-learning-driven traffic classification techniques and based on the natural capability of wavelet analysis to decompose a traffic time series into several component series associated with particular time and frequency scales and hence allowing its observation at different frequency component levels and with different resolutions. These ideas have been used for the proof-of-concept implementation of an SVM-based binary classification scheme that relies only on time regularities of the traffic and not on the packet contents and hence is immune to payload obfuscation techniques.     

General Framework for Rotation Invariant Texture Classification Through Co-occurrence of Patterns

The use of co-occurrences of patterns in image analysis has been recently suggested as one of the possible strategies to improve on the bag-of-features model. The intrinsically high number of features of the method, however, is a potential limit to its widespread application. Its extension into rotation invariant versions also requires careful consideration. In this paper we present a general, rotation invariant framework for co-occurrences of patterns and investigate possible solutions to the dimensionality problem. Using local binary patterns as bag-of-features model, we experimentally evaluate the potential advantages that co-occurrences can provide in comparison with bag-of-features. The results show that co-occurrences remarkably improve classification accuracy in some datasets, but in others the gain is negligible, or even negative. We found that this surprising outcome has an interesting explanation in terms of the degree of association between pairs of patterns in an image, and, in particular, that the higher the degree of association, the lower the gain provided by co-occurrences in comparison with bag-of-features.