Low-cost and sensitive method for Pb isotope determination using a novel ß-Si3N4 emitter by thermal ionization mass spectrometry.

Thermal ionization mass spectrometry (TIMS) is the workhorse for lead isotopic ratio analysis due to its excellent precision. Silica gel as ionization activator on Re filament is proved to the best emitter that can provide excellent sensitivity even small Pb sample size. However, the price of Re filament is three times that of Ta filament that leads to high experimental cost for TIMS laboratory. Here, we first present a novel silicon nitride (ß-Si3N4) emitter on the Ta filament with good sensitivity for Pb isotopic ratio measurements. Hence, the cost of filament material is cut down ∼70%. The ß-Si3N4 emitter can yield stable and long-life Pb+ signal, about 2-3 V 208Pb and 0.65-0.90 V 208Pb for 20 ng and 5 ng NIST SRM981 sample size that is applicable to the most geological materials for bulk analysis. A suite of silicate reference materials were analyzed to verify the reliability and accuracy of our method. For 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb isotope ratios of geological samples, excellent internal precisions (2 SE) of ±0.005%-0.013% are achieved. Replicate digestions and analyses of the basalt standard BCR-2 and coal fly ash standard GBW08401 demonstrate that good external precision is obtainable that is 0.10-0.18% (n = 6, 2 SD) for 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb ratios.

Blind image blur assessment using singular value similarity and blur comparisons.

The increasing number of demanding consumer image applications has led to increased interest in no-reference objective image quality assessment (IQA) algorithms. In this paper, we propose a new blind blur index for still images based on singular value similarity. The algorithm consists of three steps. First, a re-blurred image is produced by applying a Gaussian blur to the test image. Second, a singular value decomposition is performed on the test image and re-blurred image. Finally, an image blur index is constructed based on singular value similarity. The experimental results obtained on four simulated databases to demonstrate that the proposed algorithm has high correlation with human judgment when assessing blur or noise distortion of images.