Sonia Rubio

TL;DR: In this paper, partial least square discriminant analysis was used to classify bone samples based on their burning conditions, providing an efficient and accurate method to discern calcined and carbonized bone, and Partial Least Square regression models were built to predict calcium, magnesium and strontium concentration of bone samples from their NIR spectra.

TL;DR: In this paper, the principal component analysis (PCA) was applied to discriminate the construction phases of the unearthed buildings, and a statistical model was built by employing partial least squares discriminant analysis (PLS-DA) in order to classify the mortars from Roman Imperial period and from Islamic period due to the problematic overlapping between these two phases.

TL;DR: Results obtained evidenced that NIR spectra combined with statistical analysis can help to predict bone mineral profiles suitable to evaluate bone diagenesis.

TL;DR: For the first time, an archaeometric study was carried out on the carbonate rock ashlars of the Sagunto Castle as discussed by the authors, which is one of the most important and best preserved Spanish archaeological and architectural monuments, characterized by different construction phases from the Roman period to Modern Ages.

TL;DR: Gallello et al. as mentioned in this paper used X-ray fluorescence and inductively coupled plasma mass spectrometry to determine major and trace elements of ancient mortars from two archaeological excavations carried out in Sagunto's city centre.