Advanced thermoplastic resins, phase 2

High temperature structural resins are required for use on advanced aerospace vehicles as adhesives and composite matrices. NASA-Langley developed polyimide resins were evaluated as high temperature structural adhesives for metal to metal bonding and as composite matrices. Adhesive tapes were prepared on glass scrim fabric from solutions of polyamide acids of the semicrystalline polyimide LARC-CPI, developed at the NASA-Langley Research Center. Using 6Al-4V titanium adherends, high lap shear bond strengths were obtained at ambient temperature (45.2 MPa, 6550 psi) and acceptable strengths were obtained at elevated temperature (14.0 MPa, 2030 psi) using the Pasa-Jell 107 conversion coating on the titanium and a bonding pressure of 1.38 MPa (200 psi). Average zero degree composite tensile and compressive strengths of 1290 MPa (187 ksi) and 883 MPa (128 ksi) respectively were obtained at ambient temperature with unsized AS-4 carbon fiber reinforcement

Leptogenesis and Low-energy Observables

We relate leptogenesis in a class of theories to low-energy experimental observables: quark and lepton masses and mixings. With reasonable assumptions motivated by grand unification, one can show that the CP-asymmetry parameter takes a universal form. Furthermore the dilution mass is related to the light neutrino masses. Overall, these models offer a natural explanation for a lepton asymmetry in the early universe.Comment: 10 pages, revised discussion on light neutrino masse

Photogrammetric processes and augmented reality applications using mobile devices

This contribution shows the first results of a research "in fieri", which aims to introduce low-cost instruments for the continuous monitoring of architectures. The use of these devices in the architectural field is of great interest to the scientific community and therefore, with the aim of researching rapid mapping methodologies, the integrated camera on the new iPhone 12PRO is analyzed and then compared with the NikonD5000 reflex camera, whose use is more consolidated. In the era of digitalization and industry 4.0, smartphones have made significant progress and these devices are establishing as ideal solutions, thanks to their technical characteristics, costs and portability, compared to other acquisition techniques. The study is aimed at experimenting with image-based methodologies with the use of low-cost sensors where the three-dimensional models will constitute the basic element on which, through augmented reality applications, it will be possible to implement strategies aimed at documentation, conservation and monitoring. The experiment, reported therein, was conducted on the facade of the Quadriportico of the Cathedral of San Matteo in Salerno, Italy

Near-infrared spectroscopy study of tourniquet-induced forearm ischaemia in patients with coronary artery disease

Near-Infrared Spectroscopy (NIR) can be employed to monitor local changes in haemodynamics and oxygenation of human tissues. A preliminary study has been performed in order to evaluate the NIRS transmittance response to induced forearm ischaemia in patients with coronary artery disease (CAD). The population consists in 40 patients with cardiovascular risk factors and angiographically documented CAD, compared to a group of 13 normal subjects. By inflating and subsequently deflating a cuff placed around the patient arm, an ischaemia has been induced and released, and the patients have been observed until recovery of the basal conditions. A custom LAIRS spectrometer (IRIS) has been used to collect the backscattered light intensities from the patient forearm throughout the ischaemic and the recovery phase. The time dependence of the near-infrared transmittance on the control group is consistent with the available literature. On the contrary, the magnitude and dynamics of the NIRS signal on the CAD patients show deviations from the documented normal behavior, which can be tentatively attributed to abnormal vessel stiffness. These preliminary results, while validating the performance of the IRIS spectrometer, are strongly conducive towards the applicability of the NIRS technique to ischaemia analysis and to endothelial dysfunction characterization in CAD patients with cardiovascular risk factors.Publisher PD

An efficient policy iteration algorithm for dynamic programming equations

We present an accelerated algorithm for the solution of static Hamilton–Jacobi–Bellman equations related to optimal control problems. Our scheme is based on a classic policy iteration procedure, which is known to have superlinear convergence in many relevant cases provided the initial guess is sufficiently close to the solution. This limitation often degenerates into a behavior similar to a value iteration method, with an increased computation time. The new scheme circumvents this problem by combining the advantages of both algorithms with an efficient coupling. The method starts with a coarse-mesh value iteration phase and then switches to a fine-mesh policy iteration procedure when a certain error threshold is reached. A delicate point is to determine this threshold in order to avoid cumbersome computations with the value iteration and at the same time to ensure the convergence of the policy iteration method to the optimal solution. We analyze the methods and efficient coupling in a number of examples in different dimensions, illustrating their properties

Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL Catalog using Machine Learning Techniques

We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope (LAT) Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or Active Galactic Nuclei (AGN). Using 1904 3FGL sources that have been identified/associated with AGN (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a sub-sample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (~90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providing predictions on the likely nature of {\it unassociated} sources, including the likely type of pulsar (YNG or MSP). We also use our predictions to shed light on the possible nature of some gamma-ray sources with known associations (e.g. binaries, SNR/PWN). Finally, we provide a list of plausible X-ray counterparts for some pulsar candidates, obtained using Swift, Chandra, and XMM. The results of our study will be of interest for both in-depth follow-up searches (e.g. pulsar) at various wavelengths, as well as for broader population studies.Comment: Accepted by Ap

A tree structure algorithm for optimal control problems with state constraints

We present a tree structure algorithm for optimal control problems with state constraints. We prove a convergence result for a discrete time approximation of the value function based on a novel formulation in the case of convex constraints. Then the Dynamic Programming approach is developed by a discretization in time leading to a tree structure in space derived by the controlled dynamics, taking into account the state constraints to cut several branches of the tree. Moreover, an additional pruning allows for the reduction of the tree complexity as for the case without state constraints. Since the method does not use an a priori space grid, no interpolation is needed for the reconstruction of the value function and the accuracy essentially relies on the time step h. These features permit a reduction in CPU time and in memory allocations. The synthesis of optimal feedback controls is based on the values on the tree and an interpolation on the values obtained on the tree will be necessary if a different discretization in the control space is adopted, e.g. to improve the accuracy of the method in the reconstruction of the optimal trajectories. Several examples show how this algorithm can be applied to problems in low dimension and compare it to a classical DP method on a grid

Optimal scheduling and control for constrained multi-agent networked control systems

In this paper, we study optimal control and communication schedule co-design for multi-agent networked control systems, with assuming shared parallel communication channels and uncertain constrained linear time-invariant discrete-time systems. To that end, we specify the communication demand for each system using an associated robust control invariant set and reachability analysis. We use these communication demands and invariant sets to formulate tube-based model predictive control and offline/online communication schedule co-design problems. Since the scheduling part includes an infinite dimension integer problem, we propose heuristics to find suboptimal solutions that guarantee robust constraints satisfaction and recursive feasibility. The effectiveness of our approach is illustrated through numerical simulations