Electrochemical methodology to study labile trace metal/natural organic matter complexation at low concentration levels in natural waters

A new electrochemical methodology to study labile trace metal/natural organic matter complexation at low concentration levels in natural waters is presented. This methodology consists of three steps: (i) an estimation of the complex diffusion coefficient (DML), (ii) determination at low pH of the total metal concentration initially present in the sample, (iii) a metal titration at the desired pH. The free and bound metal concentrations are determined for each point of the titration and modeled with the non-ideal competitive adsorption (NICA-Donnan) model in order to obtain the binding parameters. In this methodology, it is recommended to determine the hydrodynamic transport parameter, α, for each set of hydrodynamic conditions used in the voltammetric measurements. The methodology was tested using two fractions of natural organic matter (NOM) isolated from the Loire river, namely the hydrophobic organic matter (HPO) and the transphilic organic matter (TPI), and a well characterized fulvic acid (Laurentian fulvic acid, LFA). The complex diffusion coefficients obtained at pH 5 were 0.4 ± 0.2 for Pb and Cu/HPO, 1.8 ± 0.2 for Pb/TPI and (0.612 ± 0.009) × 10−10 m2 s−1 for Pb/LFA. NICA-Donnan parameters for lead binding were obtained for the HPO and TPI fractions. The new lead/LFA results were successfully predicted using parameters derived in our previous work.

Open source data sensing software for ultrasonic non-invasive temperature estimation

In this paper, an open source solution for measurement of temperature and ultrasonic signals (RF-lines) is proposed. This software is an alternative to the expensive commercial data acquisition software, enabling the user to tune applications to particular acquisition architectures. The collected ultrasonic and temperature signals were used for non-invasive temperature estimation using neural networks. The existence of precise temperature estimators is an essential point aiming at the secure and effective applica tion of thermal therapies in humans. If such estimators exist then effective controllers could be developed for the therapeutic instrumentation. In previous works the time-shift between RF-lines echoes were extracted, and used for creation of neural networks estimators. The obtained estimators successfully represent the temperature in the time-space domain, achieving a maximum absolute error inferior to the threshold value defined for hyperthermia/diathermia applications.

Multifactorial approach to non-viral gene therapy: development of an efficient system for the retina

Tese de Doutoramento, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016