Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles

The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking received support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy, Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL Joint Undertaking under grant agreement No. 692455-2

High-yield fabrication of entangled photon emitters for hybrid quantum networking using high-temperature droplet epitaxy

Several semiconductor quantum dot techniques have been investigated for the generation of entangled photon pairs. Among the other techniques, droplet epitaxy enables the control of the shape, size, density, and emission wavelength of the quantum emitters. However, the fraction of the entanglement-ready quantum dots that can be fabricated with this method is still limited to around 5%, and matching the energy of the entangled photons to atomic transitions (a promising route towards quantum networking) remains an outstanding challenge. Here, we overcome these obstacles by introducing a modified approach to droplet epitaxy on a high symmetry (111)A substrate, where the fundamental crystallization step is performed at a significantly higher temperature as compared to previous reports. Our method drastically improves the yield of entanglement-ready photon sources near the emission wavelength of interest, which can be as high as 95% due to the low values of fine structure splitting and radiative lifetime, together with the reduced exciton dephasing offered by the choice of GaAs/AlGaAs materials. The quantum dots are designed to emit in the operating spectral region of Rb-based slow-light media, providing a viable technology for quantum repeater stations.Comment: 14 pages, 3 figure

Innovative approach for the in vitro research on biomedical scaffolds designed and customized with CAD-CAM technology

Studies on biomaterials involve assays aimed to assess the interactions between the biomaterial and the cells seeded on its surface. However, the morphology of biomaterials is heterogeneous and it could be tricky to standardize the results among different biomaterials and the classic plastic plates. In this light, we decided to create, by means of computer-aided design (CAD) technology, a standardized sample model, with equal shape and sizes, able to fit into a classic shape of a 96-wells tissue culture plate (TCP)

Entanglement swapping with photons generated on-demand by a quantum dot

Photonic entanglement swapping, the procedure of entangling photons without any direct interaction, is a fundamental test of quantum mechanics and an essential resource to the realization of quantum networks. Probabilistic sources of non-classical light can be used for entanglement swapping, but quantum communication technologies with device-independent functionalities demand for push-button operation that, in principle, can be implemented using single quantum emitters. This, however, turned out to be an extraordinary challenge due to the stringent requirements on the efficiency and purity of generation of entangled states. Here we tackle this challenge and show that pairs of polarization-entangled photons generated on-demand by a GaAs quantum dot can be used to successfully demonstrate all-photonic entanglement swapping. Moreover, we develop a theoretical model that provides quantitative insight on the critical figures of merit for the performance of the swapping procedure. This work shows that solid-state quantum emitters are mature for quantum networking and indicates a path for scaling up.Comment: The first four authors contributed equally to this work. 17 pages, 3 figure

The Remapping of Peripersonal Space in a Real but Not in a Virtual Environment

One of the most surprising features of our brain is the fact that it is extremely plastic. Among the various plastic processes supported by our brain, there is the neural representation of the space surrounding our body, the peripersonal space (PPS). The effects of real-world tool use on the PPS are well known in cognitive neuroscience, but little is still known whether similar mechanisms also govern virtual tool use. To this purpose, the present study investigated the plasticity of the PPS before and after a real (Experiment 1) or virtual motor training with a tool (Experiment 2). The results show the expansion of the PPS only following real-world tool use but not virtual use, highlighting how the two types of training potentially rely on different processes. This study enriches the current state of the art on the plasticity of PPS in real and virtual environments. We discuss our data with respect to the relevance for the development of effective immersive environment for trainings, learning and rehabilitation

Restriction of dietary protein decreases mTORC1 in tumors and somatic tissues of a tumor-bearing mouse xenograft model

Reduced dietary protein intake and intermittent fasting (IF) are both linked to healthy longevity in rodents, and are effective in inhibiting cancer growth. The molecular mechanisms underlying the beneficial effects of chronic protein restriction (PR) and IF are unclear, but may be mediated in part by a down-regulation of the IGF/mTOR pathway. In this study we compared the effects of PR and IF on tumor growth in a xenograft mouse model of breast cancer. We also investigated the effects of PR and IF on the mechanistic Target Of Rapamycin (mTOR) pathway, inhibition of which extends lifespan in model organisms including mice. The mTOR protein kinase is found in two distinct complexes, of which mTOR complex 1 (mTORC1) is responsive to acute treatment with amino acids in cell culture and in vivo. We found that both PR and IF inhibit tumor growth and mTORC1 phosphorylation in tumor xenografts. In somatic tissues, we found that PR, but not IF, selectively inhibits the activity of the amino acid sensitive mTORC1, while the activity of the second mTOR complex, mTORC2, was relatively unaffected by PR. In contrast, IF resulted in increased S6 phosphorylation in multiple metabolic tissues. Our work represents the first finding that PR may reduce mTORC1 activity in tumors and multiple somatic tissues, and suggest that PR may represent a highly translatable option for the treatment not only of cancer, but also other age-related diseases

Monolithic growth of ultra-thin Ge nanowires on Si(001)

Self-assembled Ge wires with a height of only 3 unit cells and a length of up to 2 micrometers were grown on Si(001) by means of a catalyst-free method based on molecular beam epitaxy. The wires grow horizontally along either the [100] or the [010] direction. On atomically flat surfaces, they exhibit a highly uniform, triangular cross section. A simple thermodynamic model accounts for the existence of a preferential base width for longitudinal expansion, in quantitative agreement with the experimental findings. Despite the absence of intentional doping, first transistor-type devices made from single wires show low-resistive electrical contacts and single hole transport at sub-Kelvin temperatures. In view of their exceptionally small and self-defined cross section, these Ge wires hold promise for the realization of hole systems with exotic properties and provide a new development route for silicon-based nanoelectronics.Comment: 23 pages, 5 figure

The Topological Cigar Observables

We study the topologically twisted cigar, namely the SL(2,R)/U(1) superconformal field theory at arbitrary level, and find the BRST cohomology of the topologically twisted N=2 theory. We find a one to one correspondence between the spectrum of the twisted coset and singular vectors in the Wakimoto modules constructed over the SL(2,R) current algebra. The topological cigar cohomology is the crucial ingredient in calculating the closed string spectrum of topological strings on non-compact Gepner models.Comment: 28 page

Efficacy of Relaxin on functional recovery of post stroke patients

Background. Relaxin is a peptide hormone that exerts specific effects on cardiovascular system and human brain, leading to the hypothesis that this hormone may play a protective role against CVD and integration and modulation of behavioral activation. We aimed to demonstrate the efficacy of Relaxin on functional recovery of post-stroke patients. Methods. Patients admitted within a Rehabilitation Unit suffering from stroke have been evaluated. Patients have been randomized to RLX (40 mcg/d) plus rehabilitation vs a control group that underwent only rehabilitation. A preliminary analysis of 36 patients at 20 and 40 days was made using the mRS for global function, the Functional Independent Measure (FIM) for daily activity and Trail Making Test (TMT) for cognitive function. Results. Eighteen patients (age 72 (64-79), M 56%) randomized to RLX plus rehabilitation were compared to 18 patients (age 68 (64-78), M 50%) that underwent only rehabilitation. There was no difference between the two groups in terms of risk factors, stroke syndromes and etiology. At admission the two groups showed the same characteristics in terms of functional aspects (mRS, FIM; p ns) and cognitive function (TMT; p ns). After 20 days (T1) the treatment group (RLX+rehabilitation) showed no differences between the two groups (FIM 78 vs 69; p ns), while after 40 days (T2) patients treated with RLX+R showed an excellent recovery (FIM 96 vs 75; p0.001). In terms of cognitive function patients RLX+R revealed a better performance at T1 ( TMT 3.5 vs 2; p 0.002) and still better at T2 (TMT 4 vs 2; p 0.001). These results have been confirmed in terms of global function both at T1 (mRS 2.5 vs 3; p0.001) and T2 (mRS 2 vs 3; p <0.001) . Conclusion. Relaxin showed in this analysis a positive effects on stroke patient’s recovery, thus offering the broad therapeutic potential role of RLX as new drug in post-stroke patients