Correlated Lightning Mapping Array (LMA) and Radar Observations of the Initial Stages of Florida Triggered Lightning Discharges

We characterize the geometrical and electrical characteristics of the initial stages of nine Florida triggered lightning discharges using a Lightning Mapping Array (LMA), a C-band SMART radar, and measured channel-base currents. We determine initial channel and subsequent branch lengths, average initial channel and branch propagation speeds, and channel-base current at the time of each branch initiation. The channel-base current is found to not change significantly when branching occurs, an unexpected result. The initial stage of Florida triggered lightning typically transitions from vertical to horizontal propagation at altitudes of 3-6 km, near the typical 0 C level of 4-5 km and several kilometers below the expected center of the negative cloud-charge region at 7-8 km. The data presented potentially provide information on thunderstorm electrical and hydrometeor structure and discharge propagation physics. LMA source locations were obtained from VHF sources of positive impulsive currents as small as 10 A, in contrast to expectations found in the literature

Optical one-way quantum computing with a simulated valence-bond solid

One-way quantum computation proceeds by sequentially measuring individual spins (qubits) in an entangled many-spin resource state. It remains a challenge, however, to efficiently produce such resource states. Is it possible to reduce the task of generating these states to simply cooling a quantum many-body system to its ground state? Cluster states, the canonical resource for one-way quantum computing, do not naturally occur as ground states of physical systems. This led to a significant effort to identify alternative resource states that appear as ground states in spin lattices. An appealing candidate is a valence-bond-solid state described by Affleck, Kennedy, Lieb, and Tasaki (AKLT). It is the unique, gapped ground state for a two-body Hamiltonian on a spin-1 chain, and can be used as a resource for one-way quantum computing. Here, we experimentally generate a photonic AKLT state and use it to implement single-qubit quantum logic gates.Comment: 11 pages, 4 figures, 8 tables - added one referenc

Estimating Effect of Antiviral Drug Use during Pandemic (H1N1) 2009 Outbreak, United States

From April 2009 through March 2010, during the pandemic (H1N1) 2009 outbreak, ≈8.2 million prescriptions for influenza neuraminidase-inhibiting antiviral drugs were filled in the United States. We estimated the number of hospitalizations likely averted due to use of these antiviral medications. After adjusting for prescriptions that were used for prophylaxis and personal stockpiles, as well as for patients who did not complete their drug regimen, we estimated the filled prescriptions prevented ≈8,400–12,600 hospitalizations (on the basis of median values). Approximately 60% of these prevented hospitalizations were among adults 18–64 years of age, with the remainder almost equally divided between children 0–17 years of age and adults >65 years of age. Public health officials should consider these estimates an indication of success of treating patients during the 2009 pandemic and a warning of the need for renewed planning to cope with the next pandemic

Effects of Scavenging, Entrainment, and Aqueous Chemistry on Peroxides and Formaldehyde in Deep Convective Outflow over the Central and Southeast U.S.

Deep convective transport of gaseous precursors to ozone (O3) and aerosols to the upper troposphere is affected by liquid- and mixed-phase scavenging, entrainment of free tropospheric air, and aqueous chemistry. The contributions of these processes are examined using aircraft measurements obtained in storm inflow and outflow during the 2012 Deep Convective Clouds and Chemistry (DC3) experiment combined with high resolution (dx <= 3 km) WRF-Chem simulations of a severe storm, an airmass storm, and a mesoscale convective system (MCS). The simulation results for the MCS suggest that formaldehyde (CH2O) is not retained in ice when cloud water freezes, in agreement with previous studies of the severe storm. By analyzing WRF-Chem trajectories, the effects of scavenging, entrainment, and aqueous chemistry on outflow mixing ratios of CH2O, methyl hydroperoxide (CH3OOH), and hydrogen peroxide (H2O2) are quantified. Liquid-phase microphysical scavenging was the dominant process reducing CH2O and H2O2 outflow mixing ratios in all three storms. Aqueous chemistry did not significantly affect outflow mixing ratios of all three species. In the severe storm and MCS, the higher than expected reductions in CH3OOH mixing ratios in the storm cores were primarily due to entrainment of low background CH3OOH. In the airmass storm, lower CH3OOH and H2O2 scavenging efficiencies (SEs) than in the MCS were partly due to entrainment of higher background CH3OOH and H2O2. Overestimated rain and hail production in WRF-Chem reduces the confidence in ice retention fraction values determined for the peroxides and CH2O

The 2015 Plains Elevated Convection at Night Field Project

The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night. To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings

Meta-analysis of binary outcomes via generalized linear mixed models: a simulation study

Background: Systematic reviews and meta-analyses of binary outcomes are widespread in all areas of application. The odds ratio, in particular, is by far the most popular effect measure. However, the standard meta-analysis of odds ratios using a random-effects model has a number of potential problems. An attractive alternative approach for the meta-analysis of binary outcomes uses a class of generalized linear mixed models (GLMMs). GLMMs are believed to overcome the problems of the standard random-effects model because they use a correct binomial-normal likelihood. However, this belief is based on theoretical considerations, and no sufficient simulations have assessed the performance of GLMMs in meta-analysis. This gap may be due to the computational complexity of these models and the resulting considerable time requirements. Methods: The present study is the first to provide extensive simulations on the performance of four GLMM methods (models with fixed and random study effects and two conditional methods) for meta-analysis of odds ratios in comparison to the standard random effects model. Results: In our simulations, the hypergeometric-normal model provided less biased estimation of the heterogeneity variance than the standard random-effects meta-analysis using the restricted maximum likelihood (REML) estimation when the data were sparse, but the REML method performed similarly for the point estimation of the odds ratio, and better for the interval estimation. Conclusions: It is difficult to recommend the use of GLMMs in the practice of meta-analysis. The problem of finding uniformly good methods of the meta-analysis for binary outcomes is still open

Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic. Methods We review 18 IPD meta-analyses of RCTs into treatments for cancer, in order to quantify the amount of heterogeneity present and also to discuss practical methods for explaining heterogeneity. Results Differing results were obtained when the standard Q and I2 statistics were used to test for the presence of heterogeneity. The two meta-analyses with the largest amount of heterogeneity were investigated further, and on inspection the straightforward application of a random effects model was not deemed appropriate. Compared to the standard Q statistic, the generalised Q statistic provided a more accurate platform for estimating the amount of heterogeneity in the 18 meta-analyses. Conclusions Explaining heterogeneity via the pre-specification of trial subgroups, graphical diagnostic tools and sensitivity analyses produced a more desirable outcome than an automatic application of the random effects model. Generalised Q statistic methods for quantifying and adjusting for heterogeneity should be incorporated as standard into statistical software. Software is provided to help achieve this aim.Published versio

Experimental investigation of the uncertainty principle in the presence of quantum memory

Heisenberg's uncertainty principle provides a fundamental limitation on an observer's ability to simultaneously predict the outcome when one of two measurements is performed on a quantum system. However, if the observer has access to a particle (stored in a quantum memory) which is entangled with the system, his uncertainty is generally reduced. This effect has recently been quantified by Berta et al. [Nature Physics 6, 659 (2010)] in a new, more general uncertainty relation, formulated in terms of entropies. Using entangled photon pairs, an optical delay line serving as a quantum memory and fast, active feed-forward we experimentally probe the validity of this new relation. The behaviour we find agrees with the predictions of quantum theory and satisfies the new uncertainty relation. In particular, we find lower uncertainties about the measurement outcomes than would be possible without the entangled particle. This shows not only that the reduction in uncertainty enabled by entanglement can be significant in practice, but also demonstrates the use of the inequality to witness entanglement.Comment: 8 pages, 4 figures, comments welcom