Self-consistent kinetic theory with nonlinear wave-particle resonances

We have developed, based on the oscillating-center transformation, a general theoretical approach for self-consistent plasma dynamics including, explicitly, effects of nonlinear(higherorder) wave-particle resonances. A specific example is then given for low-frequency responses of trapped particles in axisymmetric tokamaks. Possible applications to transport as well as nonlinear wave growth/damping are also briefly discussed.     

Integration of InGaP/GaAs/Ge triple‐junction solar cells on deeply patterned silicon substrates

We report preliminary results on InGaP/InGaAs/Ge photovoltaic cells for concentrated terrestrial applications, monolithically integrated on engineered Si(001) substrates. Cells deposited on planar Ge/Si(001) epilayers, grown by plasma‐enhanced chemical vapor deposition, provide good efficiency and spectral response, despite the small thickness of the Ge epilayers and a threading dislocation density as large as 10⁷/cm². The presence of microcracks generated by the thermal misfit is compensated by a dense collection grid that avoids insulated areas. In order to avoid the excessive shadowing introduced by the use of a dense grid, the crack density needs to be lowered. Here, we show that deep patterning of the Si substrate in blocks can be an option, provided that a continuous Ge layer is formed at the top, and it is suitably planarized before the metalorganic chemical vapor deposition. The crack density is effectively decreased, despite that the efficiency is also lowered with respect to unpatterned devices. The reasons of this efficiency reduction are discussed, and a strategy for improvement is proposed and explored. Full morphological analysis of the coalesced Ge blocks is reported, and the final devices are tested under concentrated AM1.5D spectrum. Copyright © 2016 John Wiley & Sons, Ltd.     

Detection,localisation and tracking of pallets using machine learning techniques and 2D range data

The problem of autonomous transportation in industrial scenarios is receiving a renewed interest due to the way it can revolutionise internal logistics, especially in unstructured environments. This paper presents a novel architecture allowing a robot to detect, localise, and track (possibly multiple) pallets using machine learning techniques based on an on-board 2D laser rangefinder only. The architecture is composed of two main components: the first stage is a pallet detector employing a Faster Region-Based Convolutional Neural Network (Faster R-CNN) detector cascaded with a CNN-based classifier; the second stage is a Kalman filter for localising and tracking detected pallets, which we also use to defer commitment to a pallet detected in the first stage until sufficient confidence has been acquired via a sequential data acquisition process. For fine-tuning the CNNs, the architecture has been systematically evaluated using a real-world dataset containing 340 labelled 2D scans, which have been made freely available in an online repository. Detection performance has been assessed on the basis of the average accuracy over k-fold cross-validation, and it scored 99.58% in our tests. Concerning pallet localisation and tracking, experiments have been performed in a scenario where the robot is approaching the pallet to fork. Although data have been originally acquired by considering only one pallet as per specification of the use case we consider, artificial data have been generated as well to mimic the presence of multiple pallets in the robot workspace. Our experimental results confirm that the system is capable of identifying, localising and tracking pallets with a high success rate while being robust to false positives.

     

Coupling Interrupted Fischer and Multicomponent Joullié-Ugi to Chase Chemical Diversity: from Batch to Sustainable Flow Synthesis of Peptidomimetics

The generation of peptidomimetic substructures for medicinal chemistry purposes requires effective and divergent synthetic methods. We present in this work an efficient flow process that allows quick modulation of reagents for Joullié-Ugi multicomponent reaction, using spiroindolenines as core motifs. This sterically hindered imine equivalent could successfully be diversified using various isocyanides and amino acids in generally good space-time yields. A telescoped flow process combining interrupted Fischer reaction for spiroindolenine synthesis and subsequent Joullié-Ugi-type modification resulted in product formation in very good overall yield in less than 2 hours compared to 48 hours required in batch mode. The developed protocol can be seen as a general tool for rapid and facile generation of peptidomimetic compounds. We also showcase preliminary biological assessments for the prepared compounds.     

Triennial 1951: Post-War Reconstruction and “Divine Proportion”

This research centres on the conference dedicated to the theme “Divina Proporzione” organised on the occasion of the 1951 Milano Triennale. Participating in the meeting were some of the most important art historians, architects, engineers, mathematicians and artists of the day: from a very young James Ackerman to Pier Luigi Nervi, from Le Corbusier to Carlo Mollino, from Lucio Fontana to Ernesto Rogers. That historic moment, even given the plurality of voices and approaches, represented the synthesis of a reflection that was as urgent as it was rich in implications, since it brought the concept of “proportion” into the very heart of post-war reconstruction.     

Numerical and experimental characterization of antenna positioning in a dual-radio mesh router

This paper investigates the influence of the position of the antennas in a dual-radio mesh router by characterizing the router components from an electromagnetic point of view. Since the behavior of a wireless router equipped with multiple devices and antennas can be affected by mutual coupling among several close conducting bodies, numerical and experimental tests are carried out to provide some suggestions for an accurate positioning of the antennas. A reference configuration is implemented in an electromagnetic Computer-Aided Design (CAD) simulator. The most significant numerical results are validated by performing a campaign of measurements in anechoic chamber and deploying a testbed for the derivation of the experimental values of throughput, return loss, power density, and directivity.     

Heuristic approaches for the optimal wiring in large scale robotic skin design

This paper faces the problem of optimizing the wiring and the connections in a tactile skin for robots. The robotic skin is a device composed of a network of tactile sensors, whose wiring can be very complex: the control of this complexity is a key problem. In the considered robotic skin, skin elements are grouped into skin patches, which output tactile data that have to be read by a micro-controller. The logical connections between the sensors must be defined in order to route signals through the network. A finite set of micro-controllers is given and a set of constraints is imposed on the given assignment and routing. The considered problem has a combinatorial nature and it can be formulated as a Minimum Constrained Spanning Forest problem with costs on arcs that cannot be a priori defined as they are solution-dependent. The problem is NP-hard. The paper introduces a mathematical formulation and then proposes a Multi-Start Heuristic algorithm and an Ant Colony Optimization approach whose effectiveness is evaluated through experimental tests performed on both real and synthetically generated instances.     

Enabling machine understandable exchange of energy consumption information in intelligent domotic environments

In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontology.     

Constitutive modelling of tuff masonry in direct shear

Shear behaviour of masonry has been deeply investigated for a lot of masonry types. Nevertheless, there is still a lack of knowledge on the shear response of tuff masonry, which is widely spread in the existing building inventory in seismic areas like as Italy, Turkey, and Japan. To characterize the non-linear behaviour of the unit–mortar interface within tuff masonry, a series of direct shear tests were carried out.In this paper, both experimental results and empirical formulae are presented. Classical shear strength and deformation parameters along with shearing fracture energy and dilatancy were characterized. A shear response surface including both stress–strain diagrams and the frictional strength model is proposed.