Measurement of 222Rn dissolved in water at the Sudbury Neutrino Observatory

The technique used at the Sudbury Neutrino Observatory (SNO) to measure the concentration of 222Rn in water is described. Water from the SNO detector is passed through a vacuum degasser (in the light water system) or a membrane contact degasser (in the heavy water system) where dissolved gases, including radon, are liberated. The degasser is connected to a vacuum system which collects the radon on a cold trap and removes most other gases, such as water vapor and nitrogen. After roughly 0.5 tonnes of H2O or 6 tonnes of D2O have been sampled, the accumulated radon is transferred to a Lucas cell. The cell is mounted on a photomultiplier tube which detects the alpha particles from the decay of 222Rn and its daughters. The overall degassing and concentration efficiency is about 38% and the single-alpha counting efficiency is approximately 75%. The sensitivity of the radon assay system for D2O is equivalent to ~3 E(-15) g U/g water. The radon concentration in both the H2O and D2O is sufficiently low that the rate of background events from U-chain elements is a small fraction of the interaction rate of solar neutrinos by the neutral current reaction.Comment: 14 pages, 6 figures; v2 has very minor change

Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohort

Constraints on Nucleon Decay via "Invisible" Modes from the Sudbury Neutrino Observatory

Data from the Sudbury Neutrino Observatory have been used to constrain the lifetime for nucleon decay to ``invisible'' modes, such as n -> 3 nu. The analysis was based on a search for gamma-rays from the de-excitation of the residual nucleus that would result from the disappearance of either a proton or neutron from O16. A limit of tau_inv > 2 x 10^{29} years is obtained at 90% confidence for either neutron or proton decay modes. This is about an order of magnitude more stringent than previous constraints on invisible proton decay modes and 400 times more stringent than similar neutron modes.Comment: Update includes missing efficiency factor (limits change by factor of 2) Submitted to Physical Review Letter

First Neutrino Observations from the Sudbury Neutrino Observatory

The first neutrino observations from the Sudbury Neutrino Observatory are presented from preliminary analyses. Based on energy, direction and location, the data in the region of interest appear to be dominated by 8B solar neutrinos, detected by the charged current reaction on deuterium and elastic scattering from electrons, with very little background. Measurements of radioactive backgrounds indicate that the measurement of all active neutrino types via the neutral current reaction on deuterium will be possible with small systematic uncertainties. Quantitative results for the fluxes observed with these reactions will be provided when further calibrations have been completed.Comment: Latex, 7 pages, 10 figures, Invited paper at Neutrino 2000 Conference, Sudbury, Canada, June 16-21, 2000 to be published in the Proceeding

Particle Swarm Optimization with Reinforcement Learning for the Prediction of CpG Islands in the Human Genome

BACKGROUND: Regions with abundant GC nucleotides, a high CpG number, and a length greater than 200 bp in a genome are often referred to as CpG islands. These islands are usually located in the 5' end of genes. Recently, several algorithms for the prediction of CpG islands have been proposed. METHODOLOGY/PRINCIPAL FINDINGS: We propose here a new method called CPSORL to predict CpG islands, which consists of a complement particle swarm optimization algorithm combined with reinforcement learning to predict CpG islands more reliably. Several CpG island prediction tools equipped with the sliding window technique have been developed previously. However, the quality of the results seems to rely too much on the choices that are made for the window sizes, and thus these methods leave room for improvement. CONCLUSIONS/SIGNIFICANCE: Experimental results indicate that CPSORL provides results of a higher sensitivity and a higher correlation coefficient in all selected experimental contigs than the other methods it was compared to (CpGIS, CpGcluster, CpGProd and CpGPlot). A higher number of CpG islands were identified in chromosomes 21 and 22 of the human genome than with the other methods from the literature. CPSORL also achieved the highest coverage rate (3.4%). CPSORL is an application for identifying promoter and TSS regions associated with CpG islands in entire human genomic. When compared to CpGcluster, the islands predicted by CPSORL covered a larger region in the TSS (12.2%) and promoter (26.1%) region. If Alu sequences are considered, the islands predicted by CPSORL (Alu) covered a larger TSS (40.5%) and promoter (67.8%) region than CpGIS. Furthermore, CPSORL was used to verify that the average methylation density was 5.33% for CpG islands in the entire human genome

Search for a Technicolor omega_T Particle in Events with a Photon and a b-quark Jet at CDF

If the Technicolor omega_T particle exists, a likely decay mode is omega_T -> gamma pi_T, followed by pi_T -> bb-bar, yielding the signature gamma bb-bar. We have searched 85 pb^-1 of data collected by the CDF experiment at the Fermilab Tevatron for events with a photon and two jets, where one of the jets must contain a secondary vertex implying the presence of a b quark. We find no excess of events above standard model expectations. We express the result of an exclusion region in the M_omega_T - M_pi_T mass plane.Comment: 14 pages, 2 figures. Available from the CDF server (PS with figs): http://www-cdf.fnal.gov/physics/pub98/cdf4674_omega_t_prl_4.ps FERMILAB-PUB-98/321-

Potentiating antibacterial activity by predictably enhancing endogenous microbial ROS production

The ever-increasing incidence of antibiotic-resistant infections combined with a weak pipeline of new antibiotics has created a global public health crisis1. Accordingly, novel strategies for enhancing our antibiotic arsenal are needed. As antibiotics kill bacteria in part by inducing reactive oxygen species (ROS)2–4, we reasoned that targeting microbial ROS production might potentiate antibiotic activity. Here we show that ROS production can be predictably enhanced in Escherichia coli, increasing the bacteria’s susceptibility to oxidative attack. We developed an ensemble, genome-scale metabolic modeling approach capable of predicting ROS production in E. coli. The metabolic network was systematically perturbed and its flux distribution analyzed to identify targets predicted to increase ROS production. In silico–predicted targets were experimentally validated and shown to confer increased susceptibility to oxidants. Validated targets also increased susceptibility to killing by antibiotics. This work establishes a systems-based method to tune ROS production in bacteria and demonstrates that increased microbial ROS production can potentiate killing by oxidants and antibiotics

Superconductivity at 44 K in K intercalated FeSe system with excess Fe

We report here that a new superconducting phase with much higher Tc has been found in K intercalated FeSe compound with excess Fe. We successfully grew crystals by precisely controlling the starting amount of Fe. Besides the superconducting (SC) transition at ~30 K, we observed a sharp drop in resistivity and a kink in susceptibility at 44 K. By combining thermodynamic measurements with electron spin resonance (ESR), we demonstrate that this is a new SC transition. Structural analysis unambiguously reveals two phases coexisting in the crystals, which are responsible respectively for the SC transitions at 30 and 44 K. The structural experiments and first-principles calculations consistently indicate that the 44 K SC phase is close to a 122 structure, but with an unexpectedly large c-axis of 18.10 {\AA}. We further find a novel monotonic dependence of the maximum Tc on the separation of neighbouring FeSe layers.Comment: 15 pages, 5 figure