Preparation and characterization of β‐cyclodextrin‐linked chitosan microparticles

Hydrophobically modified chitosan containing β‐cyclodextrin (CD) units was synthesized by using tosylated β‐CD. The final product was characterized by Fourier transform infrared (FTIR) spectroscopy, elemental analysis and TGA, and rheometry. The polymer bearing β‐CD moieties was used to obtain crosslinked microparticles by spray‐drying which could then be used in a controlled release system for drugs. FTIR confirmed the formation of an amide linkage between cyclodextrin and chitosan. As fluorescence spectroscopy demonstrated, hydrophobic microenvironments were formed by chitosan bearing cyclodextrin in solution at lower concentrations than for chitosan. Rheometry and FTIR showed the crosslinking of the new polymer using genipin, a molecule of natural origin. Microspheres (MS) obtained by spray‐drying showed narrow size distribution when β‐CD was grafted onto chitosan and ξ‐potential of MS was slightly lower although it remained positive. In conclusion, β‐CD linked chitosan polymer can be considered as a very promising controlled drug delivery system for drugs. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Forecasting of Hydrographs to Simulate Long Term Recharge From Rivers in Numerical Models of Mining Reservoirs; Application to A Coal Mine in NW Spain

Although the natural permeability of rocks in the Asturian Central Coal Basin (NW Spain) is generally low, intensive mining activities over many decades has given rise to fracture flow paths that are far more permeable than those associated with the natural lithology. Abandoned and flooded mining works set up artificial ‘pseudo‐karst’ aquifers, which can act as underground reservoirs, with many potential applications. In particular, a mining reservoir shaped by two connected mining shafts within the River Turón basin has been studied. A runoff model was used to produce accurate simulations of streamflow in three different gauging stations during a monitored period of 2 years. The purpose was to use this model in the forecast situation, in order to predict long‐term situations in a hydrogeological FEFLOW model. It was necessary to develop depletion curves for each gauging station based on the available daily effective rainfall and measured flow data, as well as the knowledge of the basin characteristics. The resulting simulated hydrographs were very similar to the measured hydrographs during the monitored period, so the adequate adjusting allows input of the flow for forecast purposes. The model produced forecast hydrographs that had a r = 0.8 and difference in annual volume ranging from 1.6% to 5%. The defined model was applied to a rainfall data set of 30 years, and the average recharge from the river to the mining reservoir could be adequately estimated. The method developed needs to be refined and tested on additional years, but the approach appears to be applicable to operational runoff forecasting for numerical models input data. Copyright © 2015 John Wiley & Sons, Ltd.     

Exergy analysis of the diesel pre-reforming solid oxide fuel cell system with anode off-gas recycling in the SchIBZ project. Part I: Modeling and validation

Solid oxide fuel cell (SOFC) systems with anode off-gas recirculation (AGR) and diesel pre-reforming are advantageous because they can operate with the current fuel infrastructure. In the SchIBZ-project, the prototype of such a SOFC system for maritime applications has already been commissioned. In this first paper, we model the system devices to conduct an exergy analysis of this real SOFC plant and validate them with experimental values from experiments in laboratory scale. The results of our simulation agree well with the experimental values. The calculations with the validated results may be closer to the real thermodynamic behavior of such system components than previous literature.     

Optimization of MRI Acquisition and Texture Analysis to Predict Physico-chemical Parameters of Loins by Data Mining

The main objective of this study was to configure the acquisition and analysis of low-field magnetic resonance imaging (MRI) to predict physico-chemical characteristics of Iberian loin, evaluating the use of different MRI sequences (spin echo, SE; gradient echo, GE; turbo 3D, T3D), computational texture feature methods (GLCM, NGLDM, GLRLM, GLCM + NGLDM + GLRLM), and data mining techniques (multiple linear regression, MLR; isotonic regression, IR). Moderate to very good correlation coefficients and low mean absolute error were found when applying MLR or IR on any method of computational texture features from MRI acquired with SE or GE. For T3D sequence, accurate results are only obtained by applying IR on GLCM or GLCM + NGLDM + GLRLM methods. Considering not only the accuracy of the methodology but also consumed time and required resources, the use of SE sequences for MRI acquisition, GLCM method for MRI texture analysis, and MLR could be indicated for prediction physico-chemical characteristics of loin.