Abstract: We have developed an innovative methodology to overcome the lack of techniques for real-time assessment of degradable biomedical polymers at physiological conditions. The methodology was established by combining polymer characterization techniques with electrochemical sensors. The in vitro hydrolytic degradation of a series of aliphatic polyesters was evaluated by following the molar mass decrease and the mass loss at different incubation times while tracing pH and l-lactate released into the incubation media with customized miniaturized electrochemical sensors. The combination of different analytical approaches provided new insights into the mechanistic and kinetics aspects of the degradation of these biomedical materials. Although molar mass had to reach threshold values for soluble oligomers to be formed and specimens’ resorption to occur, the pH variation and l-lactate concentration were direct evidence of the resorption of the polymers and indicative of the extent of chain scission. Linear models were found for pH and released l-lactate as a function of mass loss for the l-lactide-based copolymers. The methodology should enable the sequential screening of degradable polymers at physiological conditions and has potential to be used for preclinical material’s evaluation aiming at reducing animal tests.

Abstract: In this work self-supporting tin dioxide disks are characterized using FT-IR spectroscopy in the presence of a reducing gas in air, and in different O2/N2 mixtures at temperatures varying from room temperature up to 450°C. Every factor inducing a change in the oxygen content of the gas atmosphere above the tin dioxide, as for instance a temperature change, a surface reaction or adsorption of another species, induces a broad, intense IR absorption band with discrete weak bands superimposed on it. This broad absorption is assigned to the electronic transition from a native donor level, the oxygen vacancy in the bulk of the domain, to the conduction band of the tin dioxide material. For the interpretation of the narrow, superimposed absorptions, two hypotheses remain. The results demonstrate that FT-IR spectroscopy is an extremely suitable technique for the characterization of semiconducting metal oxide sensors, since it allows to follow in situ the processes in the bulk, at the surface and in the surrounding gas atmosphere of the sensor material at working temperature as well as in the presence of reducing gases in air.

Abstract: A spatially distributed model for leaching of Cd from the unsaturated zone was developed for the Belgian-Dutch transnational Kempen region. The model uses as input land-use maps, atmospheric deposition data, and soil data and is part of a larger regional model that simulates transport of Cd in soil, groundwater, and surface water. A new method for deriving deposition from multiple sites was validated using soil data in different wind directions. Leaching was calculated for the period 1890 to 2010 using a reconstruction of metal loads in the region. The model was able to reproduce spatial patterns of concentrations in soil and groundwater and predicted the concentration in shallow groundwater adequately well for the purpose of evaluating management options. For 42% of the data points, measurements and calculations were within the same concentration class. The model was used for forecasting under a reference scenario, an autonomous development scenario including climate change, and a scenario with implementation of remediation measures. The impact of autonomous development (under the most extreme scenario of climatic change) amounted to an increase of 10% in cumulative Cd flux after 100 yr as compared with the reference scenario. The impact of remediation measures was mainly local and is less pronounced (i.e., only 3% change in cumulative flux at the regional scale). The integrated model served as a tool to assist in developing management strategies and prioritization of remediation of the wide-spread heavy metal contamination in the region.

Abstract: This work reports results on the drag and heat transfer from an in-line array of three isothermal spheres falling in a cylindrical confinement filled with Bingham plastic fluids. The effects of dimensionless parameters, such as the Reynolds number (1 ≤ Re ≤ 100), Prandtl number (1 ≤ Pr ≤ 100), Bingham number (0 ≤ Bn ≤ 100), blockage ratio (2 ≤ β ≤ 4) and sphere-to-sphere distance (1.5 ≤ t ≤ 6) have been elucidated. The flow and heat transfer characteristics were analysed in terms of yielded/unyielded regions, streamline and isotherm contours, drag coefficient, pressure coefficient, and local and average Nusselt number. Broadly, the drag coefficient shows a positive dependence on Bn and sphere-to-sphere distance (t) while it exhibits an inverse dependence on Re and β. On the other hand, the Nusselt number shows a positive dependence on Re, Pr, Bn and β; and a complex dependence on t for each sphere. Simple predictive expressions for the average Nusselt number for each sphere are formulated, thereby enabling its prediction in a new application.

Abstract: Spectroscopic techniques combined with chemometrics are a promising tool for analysis of seized drug powders. In this study, the performance of three spectroscopic techniques [Mid-InfraRed (MIR), Raman and Near-InfraRed (NIR)] was compared. In total, 364 seized powders were analyzed and consisted of 276 cocaine powders (with concentrations ranging from 4 to 99 w%) and 88 powders without cocaine. A classification model (using Support Vector Machines [SVM] discriminant analysis) and a quantification model (using SVM regression) were constructed with each spectral dataset in order to discriminate cocaine powders from other powders and quantify cocaine in powders classified as cocaine positive. The performances of the models were compared with gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with flame-ionization detection (GC-FID). Different evaluation criteria were used: number of false negatives (FNs), number of false positives (FPs), accuracy, root mean square error of cross-validation (RMSECV) and determination coefficients (R-2). Ten colored powders were excluded from the classification data set due to fluorescence background observed in Raman spectra. For the classification, the best accuracy (99.7%) was obtained with MIR spectra. With Raman and NIR spectra, the accuracy was 99.5% and 98.9%, respectively. For the quantification, the best results were obtained with NIR spectra. The cocaine content was determined with a RMSECV of 3.79% and a R-2 of 0.97. The performance of MIR and Raman to predict cocaine concentrations was lower than NIR, with RMSECV of 6.76% and 6.79%, respectively and both with a R-2 of 0.90. The three spectroscopic techniques can be applied for both classification and quantification of cocaine, but some differences in performance were detected. The best classification was obtained with MIR spectra. For quantification, however, the RMSECV of MIR and Raman was twice as high in comparison with NIR. Spectroscopic techniques combined with chemometrics can reduce the workload for confirmation analysis (e.g., chromatography based) and therefore save time and resources.