Renewed spectroscopic and theoretical research of hydrogen bonding in ascorbic acid.

The studies of two isomers of ascorbic acid and their deuteroanalogues, presented in the paper, have been accomplished by vibrational spectroscopy methods and quantum-chemical simulations. The spectroscopic research of L-ascorbic and D-isoascorbic acids have been carried out by the infrared (IR) and Raman (R) techniques. On the basis of the obtained results the spectral interpretation of the hydrogen bonded groups of ascorbic acids has been performed. Car-Parrinello Molecular Dynamics (CPMD) and Density Functional Theory (DFT) have been employed to support spectroscopic experimental findings and shed light onto the bridged proton dynamics in the L- and D- isomers of ascorbic acids. The accurate assignments of the hydrogen bond modes have been accomplished with the application of deuterosubstitution, CPMD-solid state simulations and Potential Energy Distribution (PED) analysis. The spectral and structural results have shown that dependency ν(OH) = f(γ(OH)) is the most common for the OHO hydrogen bond, whereas dependency d(OO) = f(γ(OH)) differs as for the ionic and resonance assisted hydrogen bonds.

Attribution Markers and Data Mining in Art Authentication.

Today's global art market is a billion-dollar business, attracting not only investors but also forgers. The high number of forged works requires reliable authentication procedures to mitigate the risk of investments. However, with the developments in the methodology, continuous time pressure and the threat of litigation, authenticating artwork is becoming increasingly complex. In this paper, we examined whether the decision process involved in the authenticity examination may be supported by machine learning algorithms. The idea is motivated by existing clinical decision support systems. We used a set of 55 artworks (including 12 forged ones) with determined attribution markers to train a decision tree model. From our preliminary results, it follows that it is a very promising technique able to support art experts. Decision trees are able to summarize the existing knowledge about all investigations and may also be used as a classifier for new paintings with known markers. However, larger datasets with artworks of known provenance are needed to build robust classification models. The method can also utilize the most important markers and, consequently, reduce the costs of investigations.