The Viscosity and Thermal Conductivity Coefficients of Dilute Neon, Krypton, and Xenon

Viscosity and thermoconductivity coefficients of dilute neon, krypton, and xeno

A Heteroscedastic Bayesian Generalized Logistic Regression Model with Application to Scaling Problems

Power law scaling models have been used to understand the complexity of systems as diverse as cities, neurological activity, and rainfall and lightning. In the scaling framework, power laws and standard linear regression methods are widely used to estimate model parameters with assumed normality and fixed variance. Generalized linear models (GLM) can accommodate a wider range of distributions where the chosen distribution must meet the assumptions of the data to prevent model bias. We present a widely applicable Bayesian generalized logistic regression (BGLR) framework to more flexibly model a continuous real response addressing skew and heteroscedasticity. The Generalized Logistic Distribution (GLD) was selected to flexibly model skewed continuous data. This resulted in a nonlinear posterior distribution which may not have an analytical solution which can be solved numerically with Markov Chain Monte Carlo (MCMC) methods. We compared the BGLR model to standard and Bayesian normal models having fixed and varying variance when fitting power laws to 759 days of COVID-19 data. The BGLR yielded information beyond existing methods about the evolution of skew and skedasticity while revealing parameter bias of widely used methods. The BGLR flexibly modelled the complex characteristics necessary for an improved understanding of the propagation and dynamics of this infectious disease. The model is generally applicable and can be used as a template for modeling complexity with other distributions

Accelerating exhaustive pairwise metagenomic comparisons

In this manuscript, we present an optimized and parallel version of our previous work IMSAME, an exhaustive gapped aligner for the pairwise and accurate comparison of metagenomes. Parallelization strategies are applied to take advantage of modern multiprocessor architectures. In addition, sequential optimizations in CPU time and memory consumption are provided. These algorithmic and computational enhancements enable IMSAME to calculate near optimal alignments which are used to directly assess similarity between metagenomes without requiring reference databases. We show that the overall efficiency of the parallel implementation is superior to 80% while retaining scalability as the number of parallel cores used increases. Moreover, we also show thats equential optimizations yield up to 8x speedup for scenarios with larger data.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

System data communication structures for active-control transport aircraft, volume 2

The application of communication structures to advanced transport aircraft are addressed. First, a set of avionic functional requirements is established, and a baseline set of avionics equipment is defined that will meet the requirements. Three alternative configurations for this equipment are then identified that represent the evolution toward more dispersed systems. Candidate communication structures are proposed for each system configuration, and these are compared using trade off analyses; these analyses emphasize reliability but also address complexity. Multiplex buses are recognized as the likely near term choice with mesh networks being desirable for advanced, highly dispersed systems

System data communication structures for active-control transport aircraft, volume 1

Candidate data communication techniques are identified, including dedicated links, local buses, broadcast buses, multiplex buses, and mesh networks. The design methodology for mesh networks is then discussed, including network topology and node architecture. Several concepts of power distribution are reviewed, including current limiting and mesh networks for power. The technology issues of packaging, transmission media, and lightning are addressed, and, finally, the analysis tools developed to aid in the communication design process are described. There are special tools to analyze the reliability and connectivity of networks and more general reliability analysis tools for all types of systems

Assessing Australian women's knowledge and knowledge preferences about long-term health after hypertensive disorders of pregnancy: a survey study.

OBJECTIVES: To (1) assess women's current knowledge regarding long-term cardiovascular health after hypertensive disorders of pregnancy (2) elicit women's preferred educational content and format regarding health after hypertensive disorders of pregnancy. DESIGN AND SETTING: A custom-created online survey exploring Australian women's knowledge about long-term health after hypertensive disorders of pregnancy, distributed through consumer groups and social media. PARTICIPANTS: 266 women with (n=174) or without (n=92) a history of hypertensive disorders of pregnancy. PRIMARY AND SECONDARY OUTCOME MEASURES: (1) Proportion of women identifying long-term health risks after hypertensive disorder of pregnancy using a 10-point risk knowledge score with 0-4 'low', 4.1-7.0 'moderate' and 7.1-10 'high'. (2) Exploration of preferred content, format and distribution of educational material post hypertensive disorder of pregnancy. RESULTS: Knowledge scores about health after hypertensive disorder of pregnancy were moderate in groups with and without a history of the disorder. Knowledge was highest regarding risk of recurrent hypertensive disorders in a subsequent pregnancy, 'moderate' for chronic hypertension and heart attack, 'moderate' and 'low' regarding risk of heart disease and 'low' for diabetes and renal disease. Only 36% of all participants were aware that risks start within 10 years after the affected pregnancy. The majority of respondents with a history of hypertensive disorder of pregnancy (76%) preferred receiving information about long-term health 0-6 months post partum from a healthcare provider (80%), key organisations (60%), social media (47%) and brochures/flyers (43%). CONCLUSIONS: Women's knowledge regarding health risks after hypertensive disorder of pregnancy was 'moderate', although with important disease-specific gaps such as increased risk of diabetes. Most women wanted to be informed about their long-term health from a healthcare provider

Cognitive demands of face monitoring: Evidence for visuospatial overload

Young children perform difficult communication tasks better face to face than when they cannot see one another (e.g., Doherty-Sneddon & Kent, 1996). However, in recent studies, it was found that children aged 6 and 10 years, describing abstract shapes, showed evidence of face-to-face interference rather than facilitation. For some communication tasks, access to visual signals (such as facial expression and eye gaze) may hinder rather than help children’s communication. In new research we have pursued this interference effect. Five studies are described with adults and 10- and 6-year-old participants. It was found that looking at a face interfered with children’s abilities to listen to descriptions of abstract shapes. Children also performed visuospatial memory tasks worse when they looked at someone’s face prior to responding than when they looked at a visuospatial pattern or at the floor. It was concluded that performance on certain tasks was hindered by monitoring another person’s face. It is suggested that processing of visual communication signals shares certain processing resources with the processing of other visuospatial information

The effect of discrete vs. continuous-valued ratings on reputation and ranking systems

When users rate objects, a sophisticated algorithm that takes into account ability or reputation may produce a fairer or more accurate aggregation of ratings than the straightforward arithmetic average. Recently a number of authors have proposed different co-determination algorithms where estimates of user and object reputation are refined iteratively together, permitting accurate measures of both to be derived directly from the rating data. However, simulations demonstrating these methods' efficacy assumed a continuum of rating values, consistent with typical physical modelling practice, whereas in most actual rating systems only a limited range of discrete values (such as a 5-star system) is employed. We perform a comparative test of several co-determination algorithms with different scales of discrete ratings and show that this seemingly minor modification in fact has a significant impact on algorithms' performance. Paradoxically, where rating resolution is low, increased noise in users' ratings may even improve the overall performance of the system.Comment: 6 pages, 2 figure