Knudsen gas provides nanobubble stability

We provide a model for the remarkable stability of surface nanobubbles to bulk dissolution. The key to the solution is that the gas in a nanobubble is of Knudsen type. This leads to the generation of a bulk liquid flow which effectively forces the diffusive gas to remain local. Our model predicts the presence of a vertical water jet immediately above a nanobubble, with an estimated speed of $\sim3.3\,\mathrm{m/s}$, in good agreement with our experimental atomic force microscopy measurement of $\sim2.7\,\mathrm{m/s}$. In addition, our model also predicts an upper bound for the size of nanobubbles, which is consistent with the available experimental data

Surface bubble nucleation phase space

Recent research has revealed several different techniques for nanoscopic gas nucleation on submerged surfaces, with findings seemingly in contradiction with each other. In response to this, we have systematically investigated the occurrence of surface nanobubbles on a hydrophobised silicon substrate for various different liquid temperatures and gas concentrations, which we controlled independently. We found that nanobubbles occupy a distinct region of this phase space, occurring for gas concentrations of approximately 100-110%. Below the nanobubble phase we did not detect any gaseous formations on the substrate, whereas micropancakes (micron wide, nanometer high gaseous domains) were found at higher temperatures and gas concentrations. We moreover find that supersaturation of dissolved gases is not a requirement for nucleation of bubbles.Comment: 4 pages, 4 figure

Quantifying quantum speedups: improved classical simulation from tighter magic monotones

Consumption of magic states promotes the stabilizer model of computation to universal quantum computation. Here, we propose three different classical algorithms for simulating such universal quantum circuits, and characterize them by establishing precise connections with a family of magic monotones. Our first simulator introduces a new class of quasiprobability distributions and connects its runtime to a generalized notion of negativity. We prove that this algorithm has significantly improved exponential scaling compared to all prior quasiprobability simulators for qubits. Our second simulator is a new variant of the stabilizer-rank simulation algorithm, extended to work with mixed states and with significantly improved runtime bounds. Our third simulator trades precision for speed by discarding negative quasiprobabilities. We connect each algorithm's performance to a corresponding magic monotone and, by comprehensively characterizing the monotones, we obtain a precise understanding of the simulation runtime and error bounds. Our analysis reveals a deep connection between all three seemingly unrelated simulation techniques and their associated monotones. For tensor products of single-qubit states, we prove that our monotones are all equal to each other, multiplicative and efficiently computable, allowing us to make clear-cut comparisons of the simulators' performance scaling. Furthermore, our monotones establish several asymptotic and non-asymptotic bounds on state interconversion and distillation rates. Beyond the theory of magic states, our classical simulators can be adapted to other resource theories under certain axioms, which we demonstrate through an explicit application to the theory of quantum coherence.Comment: 24+13 pages, 8 figures; final author copy. Since v1: restructured with additional discussion, proof sketches and examples. Since v3: minor revisions to improve clarity, additional acknowledgment

Surface nanobubbles as a function of gas type

We experimentally investigate the nucleation of surface nanobubbles on PFDTS-coated silicon as a function of the specific gas dissolved in the water. In each case we restrict ourselves to equilibrium conditions ($c=100$, $T_{liquid} = T_{substrate}$). Not only is nanobubble nucleation a strong function of gas type, but there also exists an optimal system temperature of $\sim 35-40\mathrm{^oC}$ where nucleation is maximized, which is weakly dependent on gas type. We also find that contact angle is a function of nanobubble radius of curvature for all gas types investigated. Fitting this data allows us to describe a line tension which is dependent on the type of gas, indicating that the nanobubbles are sat on top of adsorbed gas molecules. The average line tension was $\tau \sim -0.8 \mathrm{nN}$

A systematic review of current knowledge of HIV epidemiology and of sexual behaviour in Nepal

OBJECTIVE: To systematically review information on HIV epidemiology and on sexual behaviour in Nepal with a view to identifying gaps in current knowledge. METHODS: Systematic review covering electronic databases, web-based information, personal contact with experts and hand searching of key journals. RESULTS: HIV-1 seroprevalence has been rising rapidly in association with high-risk behaviours, with current levels of 40% amongst the nation's injecting drug users and approaching 20% amongst Kathmandu's female commercial sex workers (FCSWs). HIV seroprevalence remains low in the general population (0.29% of 15–49 year olds). There are significant methodological limitations in many of the seroprevalence studies identified, and these estimates need to be treated with caution. There are extensive migration patterns both within the country and internationally which provide the potential for considerable sexual networking. However, studies of sexual behaviour have focused on FCSWs and the extent of sexual networks within the general population is largely unknown. CONCLUSIONS: Whilst some of the ingredients are present for an explosive HIV epidemic in Nepal, crucial knowledge on sexual behaviour in the general population is missing. Research on sexual networking is urgently required to guide HIV control in Nepal. There is also a need for further good-quality epidemiological studies of HIV seroprevalence

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator