Novel Methodology to Recover Road Surface Height Maps from Illuminated Scene through Convolutional Neural Networks.

Road surface properties have a major impact on pavement's life service conditions. Nowadays, contactless techniques are widely used to monitor road surfaces due to their portability and high precision. Among the different possibilities, laser profilometers are widely used, even though they have two major drawbacks: spatial information is missed and the cost of the equipment is considerable. The scope of this work is to show the methodology used to develop a fast and low-cost system using images taken with a commercial camera to recover the height information of the road surface using Convolutional Neural Networks. Hence, the dataset was created ad hoc. Based on photometric theory, a closed black-box with four light sources positioned around the surface sample was built. The surface was provided with markers in order to link the ground truth measurements carried out with a laser profilometer and their corresponding intensity values. The proposed network was trained, validated and tested on the created dataset. Three loss functions where studied. The results showed the Binary Cross Entropy loss to be the most performing and the best overall on the reconstruction task. The methodology described in this study shows the feasibility of a low-cost system using commercial cameras based on Artificial Intelligence.

Generation of Organozinc Reagents by Nickel Diazadiene Complex Catalyzed Zinc Insertion into Aryl Sulfonates.

The generation of arylzinc reagents (ArZnX) by direct insertion of zinc into the C-X bond of ArX electrophiles has typically been restricted to iodides and bromides. The insertions of zinc dust into the C-O bonds of various aryl sulfonates (tosylates, mesylates, triflates, sulfamates), or into the C-X bonds of other moderate electrophiles (X=Cl, SMe) are catalyzed by a simple NiCl2 -1,4-diazadiene catalyst system, in which 1,4-diazadiene (DAD) stands for diacetyl diimines, phenanthroline, bipyridine and related ligands. Catalytic zincation in DMF or NMP solution at room temperature now provides arylzinc sulfonates, which undergo typical catalytic cross-coupling or electrophilic substitution reactions.

Selection of a human anti-RhD monoclonal antibody for therapeutic use: impact of IgG glycosylation on activating and inhibitory Fc gamma R functions.

The substitution of plasmatic anti-RhD polyclonal antibodies by a monoclonal antibody (mAb) for preventing the hemolytic disease of the newborn (HDN) is an important issue due to supply and safety concerns. Since it has been suggested that FcgammaR are involved in the prevention of HDN, the in vitro functional properties of two anti-RhD mAbs differing through their glycosylation profiles were compared using FcgammaR-based assays to select a candidate mAb. T125(YB2/0), a low fucosylated antibody, bound strongly to both activating FcgammaRIII and inhibitory FcgammaRII, as opposed to its highly fucosylated counterpart. It also exerted a strong ADCC against RhD+ RBCs and a potent FcgammaRIIB-mediated inhibition of cytokine release. Moreover, an in vivo RhD+ red blood cells (RBCs) clearance assay showed that this antibody exhibits a RhD+ RBCs clearance as potent as polyclonal anti-RhD antibodies in NOD-SCID mice. Thus, T125(YB2/O) has been selected to be tested for the prevention of anti-RhD allo-immunization.