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.     

Dependency solving: A separate concern in component evolution management

Maintenance of component-based software platforms often has to face rapid evolution of software components. Component dependencies, conflicts, and package managers with dependency solving capabilities are the key ingredients of prevalent software maintenance technologies that have been proposed to keep software installations synchronized with evolving component repositories. We review state-of-the-art package managers and their ability to keep up with evolution at the current growth rate of popular component-based platforms, and conclude that their dependency solving abilities are not up to the task.We show that the complexity of the underlying upgrade planning problem is NP-complete even for seemingly simple component models, and argue that the principal source of complexity lies in multiple available versions of components. We then discuss the need of expressive languages for user preferences, which makes the problem even more challenging.We propose to establish dependency solving as a separate concern from other upgrade aspects, and present CUDF as a formalism to describe upgrade scenarios. By analyzing the result of an international dependency solving competition, we provide evidence that the proposed approach is viable.     

Advanced Modeling of Food Convective Drying: A Comparison Between Artificial Neural Networks and Hybrid Approaches

In the present paper, three different approaches are proposed to model the convective drying of food. The performance of thin-layer, pure neural network and hybrid neural model is compared in a wide range of operating conditions, with two different vegetables, available either as cylinders or as slabs with different characteristic dimensions. It was found that the thin-layer model was adequate to describe food drying behavior, but it could be applied only as a fitting procedure. Pure neural models gave accurate predictions in some situations, but exhibited poor performance when tested outside the range of operating conditions exploited during their development. Finally, it was shown that hybrid neural models, formulated as a combination of both theoretical and neural network models, are capable of offering the most accurate predictions of system behavior with average relative errors never exceeding 10%, even in operating conditions unexploited during the definition of the neural part of the model. The results obtained proved that the hybrid neural paradigm is a novel and efficient modeling technique that could be used successfully in food processing, thus allowing drying process optimization to be achieved, and efficient and fast on-line controllers to be implemented.     

Controlled suppression of the photoluminescence superlinear dependence on excitation density in quantum dots

We have shown that it is possible to tune, up to complete suppression, the photoluminescence superlinear dependence on the excitation density in quantum dot samples at high temperatures by annealing treatments. The effect has been attributed to the reduction of the defectivity of the material induced by annealing.     

Core Cross-Linked Amphiphilic Star-Block Copolymers with (Meth)acrylic Acid Shells Prepared by Atom Transfer Radical Polymerization

Core cross-linked amphiphilic star-block copolymers were prepared by hydrolysis of the outer shell of star-block copolymers prepared using copper mediated atom transfer radical polymerization (ATRP). In an arm-first approach, linear poly(tert-butyl methacrylate) macroinitiators (PtBMA-Cl) were extended with styrene to yield PtBMA-b-PS-Cl and then cross-linked with divinylbenzene (DVB) in order to yield (PtBMA-b-PS)_arms-PDVB_core star-block copolymers. Then, PMAA-b-PS block and (PMAA-PS)_arms-PDVB_core star-block copolymers were obtained by hydrolysis of the PtBMA blocks in both linear and cross-linked copolymers, as confirmed by ¹H NMR analyses. The amphiphilic character of these copolymers was confirmed by solubilisation in water. Several factors affecting the polymer aggregation and solubility such as the length, the composition of the arms and the catalyst used were studied. An acrylate analogue, that is, (PAA-b-PS)_arms-PDVB_core, was also prepared for comparison purposes. Atomic force microscopy (AFM) and differential scanning calorimetry (DSC) were used to elucidate the morphology and the thermal behaviour of the star-block copolymers.     

A smartphone-based fall detection system

Falls are a major cause of injuries and hospital admissions among elderly people. Thus, the caregiving process and the quality of life of older adults can be improved by adopting systems for the automatic detection of falls. This paper presents a smartphone-based fall detection system that monitors the movements of patients, recognizes a fall, and automatically sends a request for help to the caregivers. To reduce the problem of false alarms, the system includes novel techniques for the recognition of those activities of daily living that could be erroneously mis-detected as falls (such as sitting on a sofa or lying on a bed). To limit the intrusiveness of the system, a small external sensing unit can also be used for the acquisition of movement data.     

Cooperative caging and transport using autonomous aquatic surface vehicles

We present a study on the cooperative control of two autonomous surface vehicles performing a caging and transport mission on the water surface. The two vehicles, connected to each other by means of a floating flexible rope, are required to capture a floating target from a given location, and transport it to a designated position. We focus on the coordination and control strategy to meet these requirements, and on its implementation on two under-actuated vehicles. We describe a multi-layered control architecture which achieves the goal, followed by simulation studies and field experiments with the two vehicles caging and transporting a floating target on the surface of a lake.