Versatile liquid helium scintillation counter of large volume design

Design and performance of large liquid helium scintillation counter for meson experiment

Calculation Of Electron Capture Cross Sections Of Collisions Of Be ²⁺ On H

Using the perturbed stationary state method, including electron translation factors, the authors have calculated electron capture cross sections for the helium-like ions Be2+ and B3+ incident on ground-state atomic hydrogen. The molecular structure calculation employs pseudo-potentials to represent the inactive K-shell electrons on the incident ions. The calculated cross sections vary rapidly in the 107 cm s-1 velocity range (E approximately 1 keV amu-1). The calculations show preferential transfer to the Be+(2s) and the B2+(2p) product states. The calculations for B3++H are in good agreement with experimental measurements of Cradall et al (1979). In addition, the calculations indicate the importance of including rotational coupling to 2 Pi states when determining state-to-state cross sections

Charge Exchange Processes between Excited Helium and Fully Stripped Ions

We made a classical trajectory Monte Carlo (CTMC) calculation of state selective cross sections for processes between some light ions and excited helium. The results, useful for analysis of spectroscopic data of fusion devices, are in good agreement with theoretical predictions of scaling laws.Comment: LaTex, 8 pages, 4 figures (available on request to the authors), DFPD/94/TH/57, to be published in Phys. Rev.

Dissecting a complex chemical stress: chemogenomic profiling of plant hydrolysates.

The efficient production of biofuels from cellulosic feedstocks will require the efficient fermentation of the sugars in hydrolyzed plant material. Unfortunately, plant hydrolysates also contain many compounds that inhibit microbial growth and fermentation. We used DNA-barcoded mutant libraries to identify genes that are important for hydrolysate tolerance in both Zymomonas mobilis (44 genes) and Saccharomyces cerevisiae (99 genes). Overexpression of a Z. mobilis tolerance gene of unknown function (ZMO1875) improved its specific ethanol productivity 2.4-fold in the presence of miscanthus hydrolysate. However, a mixture of 37 hydrolysate-derived inhibitors was not sufficient to explain the fitness profile of plant hydrolysate. To deconstruct the fitness profile of hydrolysate, we profiled the 37 inhibitors against a library of Z. mobilis mutants and we modeled fitness in hydrolysate as a mixture of fitness in its components. By examining outliers in this model, we identified methylglyoxal as a previously unknown component of hydrolysate. Our work provides a general strategy to dissect how microbes respond to a complex chemical stress and should enable further engineering of hydrolysate tolerance

Fragmentation of High-spin Stretched States in the (p,n) Reaction on 36-Ar and 40-Ca

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Search for a State at E_x = 2.6MeV in 20-Na via the 20-Ne(p,n)20-Na Reaction and Possible Breakout from the Hot CNO Cycle

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Association of polygenic scores with chronic kidney disease phenotypes in a longitudinal study of older adults

Risk of chronic kidney disease (CKD) is influenced by environmental and genetic factors and increases sharply in individuals 70 years and older. Polygenic scores (PGS) for kidney disease-related traits have shown promise but require validation in well-characterized cohorts. Here, we assessed the performance of recently developed PGSs for CKD-related traits in a longitudinal cohort of healthy older individuals enrolled in the Australian ASPREE randomized controlled trial of daily low-dose aspirin with CKD risk at baseline and longitudinally. Among 11,813 genotyped participants aged 70 years or more with baseline eGFR measures, we tested associations between PGSs and measured eGFR at baseline, clinical phenotype of CKD, and longitudinal rate of eGFR decline spanning up to six years of follow-up per participant. A PGS for eGFR was associated with baseline eGFR, with a significant decrease of 3.9 mL/min/1.73m2 (95% confidence interval -4.17 to -3.68) per standard deviation (SD) increase of the PGS. This PGS, as well as a PGS for CKD stage 3 were both associated with higher risk of baseline CKD stage 3 in cross-sectional analysis (Odds Ratio 1.75 per SD, 95% confidence interval 1.66-1.85, and Odds Ratio 1.51 per SD, 95% confidence interval 1.43-1.59, respectively). Longitudinally, two separate PGSs for eGFR slope were associated with significant kidney function decline during follow-up. Thus, our study demonstrates that kidney function has a considerable genetic component in older adults, and that new PGSs for kidney disease-related phenotypes may have potential utility for CKD risk prediction in advanced age

The Kent State "2π" Neutron Polarimeter

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

ROCs in Eyewitness Identification: Instructions vs. Confidence Ratings

From the perspective of signal-detection theory, different lineup instructions may induce different levels of response bias (Clark, 2005). If so, then collecting correct and false identification rates across different instructional conditions will trace out the ROC – the same ROC that, theoretically, could also be traced out from a single instruction condition in which each eyewitness decision is accompanied by a confidence rating. We tested whether the two approaches do in fact yield the same ROC. Participants were assigned to a confidence rating condition or to an instructional biasing condition (liberal, neutral, unbiased, or conservative). After watching a video of a mock crime, participants were presented with instructions followed by a 6-person simultaneous photo lineup. The ROCs from both methods were similar, but they were not exactly the same. These findings have potentially important policy implications for how the legal system should go about controlling eyewitness response bias