Effects of Neutron Spatial Distributions on Atomic Parity Nonconservation in Cesium

We have examined modifications to the nuclear weak charge due to small differences between the spatial distributions of neutrons and protons in the Cs nucleus. We derive approximate formulae to estimate the value and uncertainty of this modification based only on nuclear rms neutron and proton radii. Present uncertainties in neutron distributions in Cs are difficult to quantify, but we conclude that they should not be neglected when using atomic parity nonconservation experiments as a means to test the Standard Model.Comment: 5 pages, RevTeX, slightly revised, one figure adde

Improving the performance of cryogenic calorimeters with nonlinear multivariate noise cancellation algorithms

State-of-the-art physics experiments require high-resolution, low-noise, and low-threshold detectors to achieve competitive scientific results. However, experimental environments invariably introduce sources of noise, such as electrical interference or microphonics. The sources of this environmental noise can often be monitored by adding specially designed “auxiliary devices” (e.g. microphones, accelerometers, seismometers, magnetometers, and antennae). A model can then be constructed to predict the detector noise based on the auxiliary device information, which can then be subtracted from the true detector signal. Here, we present a multivariate noise cancellation algorithm which can be used in a variety of settings to improve the performance of detectors using multiple auxiliary devices. To validate this approach, we apply it to simulated data to remove noise due to electromagnetic interference and microphonic vibrations. We then employ the algorithm to a cryogenic light detector in the laboratory and show an improvement in the detector performance. Finally, we motivate the use of nonlinear terms to better model vibrational contributions to the noise in thermal detectors. We show a further improvement in the performance of a particular channel of the CUORE detector when using the nonlinear algorithm in combination with optimal filtering techniques

CDMSlite: A Search for Low-Mass WIMPs using Voltage-Assisted Calorimetric Ionization Detection in the SuperCDMS Experiment

SuperCDMS is an experiment designed to directly detect Weakly Interacting Massive Particles (WIMPs), a favored candidate for dark matter ubiquitous in the Universe. In this paper, we present WIMP-search results using a calorimetric technique we call CDMSlite, which relies on voltage- assisted Luke-Neganov amplification of the ionization energy deposited by particle interactions. The data were collected with a single 0.6 kg germanium detector running for 10 live days at the Soudan Underground Laboratory. A low energy threshold of 170 eVee (electron equivalent) was obtained, which allows us to constrain new WIMP-nucleon spin-independent parameter space for WIMP masses below 6 GeV/c2.Comment: 7 pages, 4 figure

Results from the Super Cryogenic Dark Matter Search (SuperCDMS) experiment at Soudan

We report the result of a blinded search for Weakly Interacting Massive Particles (WIMPs) using the majority of the SuperCDMS Soudan dataset. With an exposure of 1690 kg days, a single candidate event is observed, consistent with expected backgrounds. This analysis (combined with previous Ge results) sets an upper limit on the spin-independent WIMP--nucleon cross section of $1.4 \times 10^{-44}$ ($1.0 \times 10^{-44}$) cm$^2$ at 46 GeV/$c^2$. These results set the strongest limits for WIMP--germanium-nucleus interactions for masses $>$12 GeV/$c^2$

Acute bronchiolitis in infancy as risk factor for wheezing and reduced pulmonary function by seven years in Akershus County, Norway

BACKGROUND: Acute viral bronchiolitis is one of the most common causes of hospitalisation during infancy in our region with respiratory syncytial virus (RSV) historically being the major causative agent. Many infants with early-life RSV bronchiolitis have sustained bronchial hyperreactivity for many years after hospitalisation and the reasons for this are probably multifactorial. The principal aim of the present study was to investigate if children hospitalised for any acute viral bronchiolitis during infancy in our region, and not only those due to RSV, had more episodes of subsequent wheezing up to age seven years and reduced lung function at that age compared to children not hospitalised for acute bronchiolitis during infancy. A secondary aim was to compare the hospitalised infants with proven RSV bronchiolitis (RS+) to the hospitalised infants with non-RSV bronchiolitis (RS-) according to the same endpoints. METHODS: 57 infants hospitalised at least once with acute viral bronchiolitis during two consecutive winter seasons in 1993–1994 were examined at age seven years. An age-matched control group of 64 children, who had not been hospitalised for acute viral bronchiolitis during infancy, were recruited from a local primary school. Epidemiological and clinical data were collected retrospectively from hospital discharge records and through structured clinical interviews and physical examinations at the follow-up visit. RESULTS: The children hospitalised for bronchiolitis during infancy had decreased lung function, more often wheezing episodes, current medication and follow-up for asthma at age seven years than did the age matched controls. They also had lower average birth weight and more often first order family members with asthma. We did not find significant differences between the RSV+ and RSV- groups. CONCLUSION: Children hospitalised for early-life bronchiolitis are susceptible to recurrent wheezing and reduced pulmonary function by seven years compared to age-matched children not hospitalised for early-life bronchiolitis. We propose that prolonged bronchial hyperreactivity could follow early-life RSV negative as well as RSV positive bronchiolitis

Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables

<p>Abstract</p> <p>Background</p> <p>Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks.</p> <p>Methods</p> <p>Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008.</p> <p>Results</p> <p>NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley.</p> <p>Conclusions</p> <p>We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years.</p

Post-exposure prophylaxis during pandemic outbreaks

<p>Abstract</p> <p>Background</p> <p>With the rise of the second pandemic wave of the novel influenza A (H1N1) virus in the current season in the Northern Hemisphere, pandemic plans are being carefully re-evaluated, particularly for the strategic use of antiviral drugs. The recent emergence of oseltamivir-resistant in treated H1N1 patients has raised concerns about the prudent use of neuraminidase inhibitors for both treatment of ill individuals and post-exposure prophylaxis of close contacts.</p> <p>Methods</p> <p>We extended an established population dynamical model of pandemic influenza with treatment to include post-exposure prophylaxis of close contacts. Using parameter estimates published in the literature, we simulated the model to evaluate the combined effect of treatment and prophylaxis in minimizing morbidity and mortality of pandemic infections in the context of transmissible drug resistance.</p> <p>Results</p> <p>We demonstrated that, when transmissible resistant strains are present, post-exposure prophylaxis can promote the spread of resistance, especially when combined with aggressive treatment. For a given treatment level, there is an optimal coverage of prophylaxis that minimizes the total number of infections (final size) and this coverage decreases as a higher proportion of infected individuals are treated. We found that, when treatment is maintained at intermediate levels, limited post-exposure prophylaxis provides an optimal strategy for reducing the final size of the pandemic while minimizing the total number of deaths. We tested our results by performing a sensitivity analysis over a range of key model parameters and observed that the incidence of infection depends strongly on the transmission fitness of resistant strains.</p> <p>Conclusion</p> <p>Our findings suggest that, in the presence of transmissible drug resistance, strategies that prioritize the treatment of only ill individuals, rather than the prophylaxis of those suspected of being exposed, are most effective in reducing the morbidity and mortality of the pandemic. The impact of post-exposure prophylaxis depends critically on the treatment level and the transmissibility of resistant strains and, therefore, enhanced surveillance and clinical monitoring for resistant mutants constitutes a key component of any comprehensive plan for antiviral drug use during an influenza pandemic.</p