Forward and transverse energy distributions in oxygen-induced reactions at 60 A GeV and 200 A GeV

Results are presented from reactions of 60 A GeV and 200 A GeV ¹⁶O projectiles with C, Cu, Ag, and Au nuclei. Energy spectra measured at zero degrees and transverse energy distributions in the pseudorapidity range from 2.4 to 5.5 are shown. The average transverse energy per participant is found to be nearly independent of target mass. Estimates of nuclear stopping and of attained energy densities are made.     

Higgs-boson two-loop contributions to electric dipole moments in the MSSM

The complete set of Higgs-boson two-loop contributions to electric dipole moments of the electron and neutron is calculated in the minimal supersymmetric standard model. The electric dipole moments are induced by CP-violating trilinear couplings of the `CP-odd' and charged Higgs bosons to the scalar top and bottom quarks. Numerical estimates of the individual two-loop contributions to electric dipole moments are given.     

Sharper asset ranking from total drawdown durations

The total duration of drawdowns is shown to provide a moment-free, unbiased, efficient and robust estimator of Sharpe ratios both for Gaussian and heavy-tailed price returns. We then use this quantity to infer an analytic expression of the bias of moment-based Sharpe ratio estimators as a function of the return distribution tail exponent. The heterogeneity of tail exponents at any given time among assets implies that our new method yields significantly different asset rankings than those of moment-based methods, especially in periods large volatility. This is fully confirmed by using 20 years of historical data on 3449 liquid US equities.     

Exciton-polaritons in lattices: A non-linear photonic simulator

Microcavity polaritons are mixed light–matter quasiparticles with extraordinary nonlinear properties, which can be easily accessed in photoluminescence experiments. Thanks to the possibility of designing the potential landscape of polaritons, this system provides a versatile photonic platform to emulate 1D and 2D Hamiltonians. Polaritons allow transposing to the photonic world some of the properties of electrons in solid-state systems, and to engineer Hamiltonians for photons with novel transport properties. Here we review some experimental implementations of polariton Hamiltonians using lattice geometries.     

3DSEM++: Adaptive and intelligent 3D SEM surface reconstruction

Structural analysis of microscopic objects is a longstanding topic in several scientific disciplines, such as biological, mechanical, and materials sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around for decades to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. Whereas SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and facts about their three-dimensional (3D) structures. 3D surface reconstruction from SEM images leads to remarkable understanding of microscopic surfaces, allowing informative and qualitative visualization of the samples being investigated. In this contribution, we integrate several computational technologies including machine learning, contrario methodology, and epipolar geometry to design and develop a novel and efficient method called 3DSEM++ for multi-view 3D SEM surface reconstruction in an adaptive and intelligent fashion. The experiments which have been performed on real and synthetic data assert the approach is able to reach a significant precision to both SEM extrinsic calibration and its 3D surface modeling.     

DNS and LES of spark ignition with an automotive coil

The cycle to cycle combustion variability which is observed in spark-ignition engines is often caused by fluctuations of the early flame development. LES can be exploited for a better understanding and mastering of their origins. For that purpose appropriate models taking into account energy deposition, mixture ignition and transition to propagation are necessary requirements. This paper presents first DNS and LES of spark ignition with a real automotive coil and simplified pin-pin electrodes. The electrical circuit characteristics are provided by ISSIM while the energy deposition is modelled by Lagrangian particles. The ignition model is first evaluated in terms of initial spark radius on a pin-pin ignition experiment in pure air performed at CORIA and EM2C laboratories, showing that it pilots the radius of the torus formed by the initial shock wave. DNS of a quiescent lean propane/air mixture are then performed with this ignition system and a two-step mechanism. The impact of the modelled transferred energy during glow phase as well as the initial arc radius on the minimum ignition energy (MIE) are examined and compared to experimental values. Replacing the two-step chemistry by an analytically reduced mechanism leads to similar MIE but shows a different ignition kernel shape. Finally, LES of turbulent ignition using a Lagrangian arc model show a realistic prediction of the arc shape and its important role on the energy transfer location and thus on the flame kernel shape.     

Routing a mix of conventional,plug-in hybrid,and electric vehicles

We introduce an electric vehicle routing problem combining conventional, plug-in hybrid, and electric vehicles. Electric vehicles are constrained in their service range by their battery capacity, and may require time-consuming recharging operations at some specific locations. Plug-in hybrid vehicles have two engines, an internal combustion engine and an electric engine using a built-in rechargeable battery. These vehicles can avoid visits to recharging stations by switching to fossil fuel. However, this flexibility comes at the price of a generally higher consumption rate and utility cost.To solve this complex problem variant, we design a sophisticated metaheuristic which combines a genetic algorithm with local and large neighborhood search. All route evaluations, within the approach, are based on a layered optimization algorithm which combines labeling techniques and greedy evaluation policies to insert recharging stations visits in a fixed trip and select the fuel types. The metaheuristic is finally hybridized with an integer programming solver, over a set partitioning formulation, so as to recombine high-quality routes from the search history into better solutions. Extensive experimental analyses are conducted, highlighting the good performance of the algorithm and the contribution of each of its main components. Finally, we investigate the impact of fuel and energy cost on fleet composition decisions. Our experiments show that a careful use of a mixed fleet can significantly reduce operational costs in a large variety of price scenarios, in comparison with the use of a fleet composed of a single vehicle class.     

Deciphering the Structure and Chemical Composition of Drug Nanocarriers: From Bulk Approaches to Individual Nanoparticle Characterization

Drug nanocarriers (NCs) with sizes usually below 200 nm are gaining increasing interest in the treatment of severe diseases such as cancer and infections. Characterization methods to investigate the morphology and physicochemical properties of multifunctional NCs are key in their optimization and in the study of their in vitro and in vivo fate. Whereas a variety of methods has been developed to characterize “bulk” NCs in suspension, the scope of this review is to describe the different approaches for the NC characterization on an individual basis, for which fewer techniques are available. The accent is put on methods devoid of labelling, which could lead to artefacts. For each characterization method, the principles and approaches to analyze the data are presented in an accessible manner. Aspects related to sample preparation to avoid artefacts are indicated, and emphasis is put on examples of applications. NC characterization on an individual basis allows gaining invaluable information in terms of quality control, on: i) NC localization and fate in biological samples; ii) NC morphology and crystallinity; iii) distribution of the NC components (drugs, shells), and iv) quantification of NCs’ chemical composition. The individual characterization approaches are expected to gain increasing interest in the near future.