An inductively coupled plasma-time-of-flight mass spectrometer for elemental analysis. Part II: Direct current quadrupole lens system for improved performance

An electrostatic quadrupole lens has been substituted for a cylindrical lens system used in the original inductively coupled plasma-time-of-flight mass spectrometer (ICP-TOFMS). With an improved vacuum system also installed, the cylindrical and quadrupole lenses are compared to each other and to the performance of the prototype ICP-TOFMS. The quadrupole lens requires no tradeoff between ion throughput and resolving power as was encountered with cylindrical lenses. The background noise in both ion-optical systems is within the same order of magnitude. Images of the ion beam formed by each ion-optical system have been obtained on a microchannel plate-phosphor screen. The quadrupole lens shows a higher ion-beam flux and produces a slitlike focus required in the orthogonal ICP-TOFMS instrument. Signal-to-noise ratios in the ICP-TOFMS can be improved by using a technique called pulsed-ion injection that is particularly convenient with the quadrupole lens. In this technique, one quadrupole electrode is pulsed to prevent ions from entering the extraction zone except when an ion packet is to be extracted for mass analysis. This technique significantly reduces the noise over continuous ion injection. In the orthogonal ICP-TOFMS with pulsed-ion injection, 0.5 frnol of analyte could be detected in 1.4 ms with a proper data acquisition system. Overall, the combination of a quadrupole lens and pulsed-ion injection may provide detection limits for the ICP-TOFMS that are competitive with those of quadrupole inductively coupled plasma-mass spectrometry instruments

Submodular Maximization with Matroid and Packing Constraints in Parallel

We consider the problem of maximizing the multilinear extension of a submodular function subject a single matroid constraint or multiple packing constraints with a small number of adaptive rounds of evaluation queries. We obtain the first algorithms with low adaptivity for submodular maximization with a matroid constraint. Our algorithms achieve a $1-1/e-\epsilon$ approximation for monotone functions and a $1/e-\epsilon$ approximation for non-monotone functions, which nearly matches the best guarantees known in the fully adaptive setting. The number of rounds of adaptivity is $O(\log^2{n}/\epsilon^3)$, which is an exponential speedup over the existing algorithms. We obtain the first parallel algorithm for non-monotone submodular maximization subject to packing constraints. Our algorithm achieves a $1/e-\epsilon$ approximation using $O(\log(n/\epsilon) \log(1/\epsilon) \log(n+m)/ \epsilon^2)$ parallel rounds, which is again an exponential speedup in parallel time over the existing algorithms. For monotone functions, we obtain a $1-1/e-\epsilon$ approximation in $O(\log(n/\epsilon)\log(m)/\epsilon^2)$ parallel rounds. The number of parallel rounds of our algorithm matches that of the state of the art algorithm for solving packing LPs with a linear objective. Our results apply more generally to the problem of maximizing a diminishing returns submodular (DR-submodular) function

Predicting substance use behavior among South African adolescents: The role of leisure experiences across time

Using seven waves of data, collected twice a year from the 8th through the 11th grades in a low-resource community in Cape Town, South Africa, we aimed to describe the developmental trends in three specific leisure experiences (leisure boredom, new leisure interests, and healthy leisure) and substance use (cigarettes, alcohol, and marijuana) behaviors and to investigate the ways in which changes in leisure experiences predict changes in substance use behaviors over time. Results indicated that adolescents’ substance use increased significantly across adolescence, but that leisure experiences remained fairly stable over time. We also found that adolescent leisure experiences predicted baseline substance use and that changes in leisure experiences predicted changes in substance use behaviors over time, with leisure boredom emerging as the most consistent and strongest predictor of alcohol, cigarette, and marijuana use. Implications for interventions that target time use and leisure experiences are discussed.Web of Scienc