High-energy string-brane scattering: leading eikonal and beyond

We extend previous techniques for calculations of transplanckian-energy string-string collisions to the high-energy scattering of massless closed strings from a stack of N Dp-branes in Minkowski spacetime. We show that an effective non-trivial metric emerges from the string scattering amplitudes by comparing them against the semiclassical dynamics of high-energy strings in the extremal p-brane background. By changing the energy, impact parameter and effective open string coupling, we are able to explore various interesting regimes and to reproduce classical expectations, including tidal-force excitations, even beyond the leading-eikonal approximation.Comment: 40 pages, 5 figures, v2: minor corrections, new appendix with a discussion of the Feynman diagrams contributing to the scattering amplitude in the field theory limi

Deep models optimization on embedded devices to improve the orientation estimation task at sea

The environmental monitoring task has greatly benefited from the improvements achieved in the robotics field. The enhancement of navigation and control algorithms, together with the use of performing, small and low-cost sensors, allows in fact to reduce the implementation costs while improving the system reliability. This is strongly supported by the developments of embedded hardware, smart computing devices able to collect and process data in real-time and in low-resource settings. Following the results obtained by DOES, this work aims at putting another step towards its deployment in live scenarios: we propose a study on the performances of DOES tested on embedded systems, using lighter backbone architectures and model optimization techniques

Congenital rhabdomyosarcoma: a different clinical presentation in two cases

Background: Rhabdomyosarcoma (RMS), one of the most common soft tissue sarcomas of childhood, is very rare in the neonatal period (0.4-2% of cases). In order to gain a deeper understanding of this disease at such age, patient and tumor features, as well as treatment modality and outcome need to be reported. Case presentation: We describe two cases with congenital RMS treated at Bambino Gesù Children's Hospital between 2000 and 2016. They represent only 2.24% of all RMS patients diagnosed during that period in our Institution; this data is in agreement with the incidence reported in the literature. They reflect the two different clinical forms in which the disease may manifest itself. One patient, with the alveolar subtype (positive for specific PAX3-FOXO1 fusion transcript) and disseminated disease, had a fatal outcome with central nervous system (CNS) progression despite conventional and high dose chemotherapy. The other child, with the localized embryonal subtype, was treated successfully with conservative surgery and conventional chemotherapy, including prolonged maintenance therapy. He is disease free at 7 years of follow-up. Conclusions: RMS can also be diagnosed during the neonatal period. Given the young age, disease management is often challenging, and especially for the alveolar subtype, the outcome is dismal despite intensified multimodality therapy. In fact, it characteristically manifests with multiple subcutaneous nodules and progression most commonly occurs in the CNS (Rodriguez-Galindo et al., Cancer 92(6):1613-20, 2001). In this context, CNS prophylaxis could play a role in preventing leptomeningeal dissemination, and molecular studies can allow a deeper tumor characterization, treatment stratification and identification of new potential therapeutic targets

DANAE: A denoising autoencoder for underwater attitude estimation

One of the main issues for underwater robots navigation is their accurate positioning, which heavily depends on the orientation estimation phase. The systems employed to this scope are affected by different noise typologies, mainly related to the sensors and to the irregular noise of the underwater environment. Filtering algorithms can reduce their effect if opportunely configured, but this process usually requires fine techniques and time. In this paper we propose DANAE, a deep Denoising AutoeNcoder for Attitude Estimation which works on Kalman filter IMU/AHRS data integration with the aim of reducing any kind of noise, independently of its nature. This deep learningbased architecture showed to be robust and reliable, significantly improving the Kalman filter results. Further tests could make this method suitable for real-time applications on navigation tasks

The gravitational eikonal: from particle, string and brane collisions to black-hole encounters

Motivated by conceptual problems in quantum theories of gravity, the gravitational eikonal approach, inspired by its electromagnetic predecessor, has been successfully applied to the transplanckian energy collisions of elementary particles and strings since the late eighties, and to string-brane collisions in the past decade. After the direct detection of gravitational waves from black-hole mergers, most of the attention has shifted towards adapting these methods to the physics of black-hole encounters. For such systems, the eikonal exponentiation provides an amplitude-based approach to calculate classical gravitational observables, thus complementing more traditional analytic methods such as the Post-Newtonian expansion, the worldline formalism, or the Effective-One-Body approach. In this review we summarize the main ideas and techniques behind the gravitational eikonal formalism. We discuss how it can be applied in various different physical setups involving particles, strings and branes and then we mainly concentrate on the most recent developments, focusing on massive scalars minimally coupled to gravity, for which we aim at being as self-contained and comprehensive as possible.Comment: 208 pages, 19 figure

The eikonal operator at arbitrary velocities I: the soft-radiation limit

Observables related to the real part of the gravitational eikonal, such as the deflection angle and time delay, have been found so far to have a smooth post-Minkowskian (PM) expansion whose validity extends from the non-relativistic to the most extreme ultra-relativistic (UR) regime, which smoothly connects with massless particle collisions. To describe gravitational radiation, the eikonal phase has to be promoted to a unitary operator for which we motivate a proposal and start discussing properties in the soft-radiation limit. A convergent PM expansion is found to only hold below an UR bound (discussed in the GR literature in the seventies) above which a different expansion is instead needed implying, in general, some non-analyticity in Newton's constant. In this extreme UR regime soft radiative observables receive contributions only from gravitons and are therefore universal. This generalises the pattern discussed in \cite{DiVecchia:2020ymx} beyond the elastic case.Comment: 28 pages+reference

Two-loop scalar diagrams from string theory

We show how to obtain correctly normalized expressions for the Feynman diagrams of $\Phi^3$ theory with an internal $U(N)$ symmetry group, starting from tachyon amplitudes of the open bosonic string, and suitably performing the zero--slope limit by giving an arbitrary mass $m$ to the tachyon. In particular we present explicit results for the two--loop amplitudes of $\Phi^3$ theory, in preparation for the more interesting case of the multiloop amplitudes of non--abelian gauge theories.Comment: 15 pages, plain Latex, 5 figures include

String-derived renormalization of Yang-Mills theory

We review the application of bosonic string techniques to the calculation of renormalization constants and effective actions in Yang-Mills theory. We display the multiloop string formulas needed to compute Yang-Mills amplitudes, and we discuss how the renormalizations of proper vertices can be extracted in the field theory limit. We show how string techniques lead to the background field method in field theory, and indicate how the gauge invariance of the multiloop effective action can be inferred form the string formalism. (Proceedings of the 29th International Symposium on the Theory of Elementary Particles, Buckow (Germany), Aug.-Sept. 1995. Preprint DFTT 04/96)Comment: 11 pages. Latex, uses espcrc2.sty. Proceedings Buckow '9

A Smart Battery Management System for Photovoltaic Plants in Households Based on Raw Production Forecast

A basic battery management system (BMS) permits the safe charge/discharge of the batteries and the supply of loads. Batteries are protected to avoid fast degradation: the minimum and maximum state-of-charge (SOC) limits are not exceeded and fast charge/discharge cycles are not permitted. A more sophisticated BMS connected to a photovoltaic (PV) generator could also work with the double purpose of protecting storage and reducing peak demand. Peak reduction by storage generally requires the forecast of consumption and PV generation profiles to perform a provisional energy balance. To do it, it is required to have accurate information about production profiles, that is, to have at disposal accurate weather forecasts, which are not easily available. In the present work, an efficient BMS in grid-connected PV plants for residential users is described. Starting from raw 1-day ahead weather forecast and prediction of consumption, the proposed BMS preserves battery charge when it is expected high load and low PV production and performs peak shaving with a negligible reduction in self-sufficiency