Inference of distributional parameters from compositional samples containing nondetects

Low concentrations of elements in geochemical analyses have the peculiarity of being compositional data and, for a given level of significance, are likely to be beyond the capabilities of laboratories to distinguish between minute concentrations and complete absence, thus preventing laboratories from reporting extremely low concentrations of the analyte. Instead, what is reported is the detection limit, which is the minimum concentration that conclusively differentiates between presence and absence of the element. A spatially distributed exhaustive sample is employed in this study to generate unbiased sub-samples, which are further censored to observe the effect that different detection limits and sample sizes have on the inference of population distributions starting from geochemical analyses having specimens below detection limit (nondetects). The isometric logratio transformation is used to convert the compositional data in the simplex to samples in real space, thus allowing the practitioner to properly borrow from the large source of statistical techniques valid only in real space. The bootstrap method is used to numerically investigate the reliability of inferring several distributional parameters employing different forms of imputation for the censored data. The case study illustrates that, in general, best results are obtained when imputations are made using the distribution best fitting the readings above detection limit and exposes the problems of other more widely used practices. When the sample is spatially correlated, it is necessary to combine the bootstrap with stochastic simulation

Detection of matchings in a sequence of underwater images through texture analysis

This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability

Internal test sets studies in a group of antimalarials

Topological indices have been applied to build QSAR models for a set of 20 antimalarial cyclic peroxy cetals. In order to evaluate the reliability of the proposed linear models leave-n-out and Internal Test Sets (ITS) approaches have been considered. The proposed procedure resulted in a robust and consensued prediction equation and here it is shown why it is superior to the employed standard cross-validation algorithms involving multilinear regression models

Theoretical studies of systems of biochemical interest containing Fe and Cu transition metals

La presència de la química teòrica i computacional està augmentant en quasi tots els camps de la recerca en química. Els càlculs teòrics poden ajudar a entendre millor l'estructura, les propietats i la reactivitat de compostos metàl·lics d'àrees tan diferents com la química inorgànica, organometàl·lica i bioinorgànica. No obstant això, és imprescindible utilitzar la metodologia adequada per obtenir resultats teòrics fiables. Els estudis d'aquesta tesi es poden dividir en dos grups diferents. El primer grup inclou l'estudi teòric del mecanisme de reacció de diversos sistemes que contenen coure i tenen diferents estructures Cun-O2. Aquests estudies s'han dut a terme amb l'objectiu de profunditzar en la natura dels processos oxidants químics i biològics promoguts per sistemes que contenen coure. En la segona part de la tesi, s'estudia la fiabilitat de diferents tècniques utilitzades per estudiar l'estructura electrònica i la reactivitat de sistemes que contenen coure, ferro i altres metalls de transició.