Improved column-based radiochemical processing of the generator produced 68Ga

An improved chemical strategy for processing of the generator produced 68Ga was developed based on processing of the original 68Ge/68Ga generator eluate on a micro-column. Direct pre-concentration and purification of the eluted 68Ga is performed on a cation-exchange resin in hydrochloric acid/acetone media. A supplementary step based on a second micro-column filled with a second resin allows direct re-adsorption of 68Ga eluted from the cation exchanger. 68Ga is finally striped from the second resin with a small volume of pure water. For this purpose a strong anion exchanger and a novel extraction chromatographic resin based on tetraalkyldiglycolamides are characterized. The strategy allows online pre-concentration and purification of 68Ga from the original generator eluate. The supplementary column allows transferring 68Ga with high radionuclide and chemical quality in the aqueous solution with small volume and low acidity useful for direct radiolabeling reactions.

Gasoline emissions dominate over diesel in formation of secondary organic aerosol mass

Although laboratory experiments have shown that organic compounds in both gasoline fuel and diesel engine exhaust can form secondary organic aerosol (SOA), the fractional contribution from gasoline and diesel exhaust emissions to ambient SOA in urban environments is poorly known. Here we use airborne and ground-based measurements of organic aerosol (OA) in the Los Angeles (LA) Basin, California made during May and June 2010 to assess the amount of SOA formed from diesel emissions. Diesel emissions in the LA Basin vary between weekdays and weekends, with 54% lower diesel emissions on weekends. Despite this difference in source contributions, in air masses with similar degrees of photochemical processing, formation of OA is the same on weekends and weekdays, within the measurement uncertainties. This result indicates that the contribution from diesel emissions to SOA formation is zero within our uncertainties. Therefore, substantial reductions of SOA mass on local to global scales will be achieved by reducing gasoline vehicle emissions.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Energy harvesting from the beating heart by a mass imbalance oscillation generator

Energy-harvesting devices attract wide interest as power supplies of today's medical implants. Their long lifetime will spare patients from repeated surgical interventions. They also offer the opportunity to further miniaturize existing implants such as pacemakers, defibrillators or recorders of bio signals. A mass imbalance oscillation generator, which consists of a clockwork from a commercially available automatic wrist watch, was used as energy harvesting device to convert the kinetic energy from the cardiac wall motion to electrical energy. An MRI-based motion analysis of the left ventricle revealed basal regions to be energetically most favorable for the rotating unbalance of our harvester. A mathematical model was developed as a tool for optimizing the device's configuration. The model was validated by an in vitro experiment where an arm robot accelerated the harvesting device by reproducing the cardiac motion. Furthermore, in an in vivo experiment, the device was affixed onto a sheep heart for 1 h. The generated power in both experiments-in vitro (30 μW) and in vivo (16.7 μW)-is sufficient to power modern pacemakers.