Interoperability of Remote Laboratories Systems

There has been growing interest in, and development of, remotely accessible laboratories as a mechanism for improving access and flexibility, and enabling sharing of facilities. Differences in focus, philosophy, approach or domain have led to quite different technical solutions in supporting remote laboratories. Whilst this diversity represents a significant strength in terms of the ability to explore different issues and support diverse applications, it does however potentially hamper the sharing of labs between different institutions. Investigation into interoperability between two remote lab platforms has realized a need for a common application protocol to achieve the goals remote labs aims to provide. We describe our approach to providing a bridge between two current remote laboratory architectures Labshares Sahara and MITs iLabs and report on the issues that arise with regard to the protocol translations

Bayesian Gaussian Copula Factor Models for Mixed Data.

Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models acommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables the latent variables typically influence both the dependence structure and the form of the marginal distributions, complicating interpretation and introducing artifacts. To address this problem we propose a novel class of Bayesian Gaussian copula factor models which decouple the latent factors from the marginal distributions. A semiparametric specification for the marginals based on the extended rank likelihood yields straightforward implementation and substantial computational gains. We provide new theoretical and empirical justifications for using this likelihood in Bayesian inference. We propose new default priors for the factor loadings and develop efficient parameter-expanded Gibbs sampling for posterior computation. The methods are evaluated through simulations and applied to a dataset in political science. The models in this paper are implemented in the R package bfa

Volcanic ash ice-nucleating activity can be enhanced or depressed by ash-gas interaction in the eruption plume

Volcanic ash can trigger ice nucleation when immersed in supercooled water. This will impact several processes (e.g., electrification, aggregation, precipitation) in the eruption plume and cloud and in the wider atmosphere upon ash dispersal. Previous studies show that ash bulk properties, reflecting the chemistry and phase state of the source magma, likely contribute to the ice-nucleating activity (INA) of ash. However, it remains unexplored how interaction with magmatic gases in the hot eruption plume, which inevitably leads to altered ash surface properties, affects the ash INA. Here we demonstrate that the INA of tephra is raised by exposure to H2O(g) mixed with SO2(g) at both 800 and 400 °C, but is substantially reduced by exposure to H2O(g) alone or mixed with HCl(g) at the same temperatures. In contrast, the INA of K-feldspar and quartz is reduced by all three eruption plume processing treatments. The decrease in INA of all silicates after heating with H2O(g) might relate to a loss of ice-active sites by surface dehydroxylation and/or oxidation. In the presence of HCl(g) or SO2(g), respectively, metal chloride or sulphate salts form on the tephra surfaces only. While NaCl and CaCl2 seem to have no effect on the tephra INA, CaSO4 is inferred to create ice-active sites, potentially through a particular combination of surface chemistry and topography. Overall, our findings suggest a complex interplay of bulk mineralogy and surface alteration in influencing ice nucleation by volcanic ash, and highlight the general sensitivity (enhancement or depression) of ash INA to interaction with magmatic gases in the eruption plume

Derivation of Suitability Metrics for Remote Access Mode Experiments

When considering the possible use of an online mode of experimentation it is important to evaluate the suitability of the remote access mode to a particular learning exercise. Within a large and diverse set of possible experiment-oriented learning exercises, it follows that not all laboratory experiments are well-suited for conversion to the remote access mode. In this paper we consider a range of factors that should be considered before the decision is taken to implement a remote laboratory. These factors fit broadly into four categories: learning factors, equipment factors, cohort factors and accreditation factors. Some of the factors may demonstrate a tendency to belong to more than one category, and some may present with a more significant weighting than others, but the categorical organization of the factors adds an ability to apply an objective assessment to remote access mode suitability

Clustering of under-five mortality in Rufiji Health and Demographic Surveillance System in rural Tanzania

BACKGROUND\ud \ud Less than 5 years remain before the 2015 mark when countries will be evaluated on their achievements for the Millennium Development Goals (MDGs). The MDG 4 and 6 call for a reduction of child mortality by two-thirds and combating malaria, HIV/AIDS, TB, and other diseases, respectively. To accelerate the achievement of these goals, focused allocation of resources and high deployment of cost-effective interventions is paramount. The knowledge of spatial and temporal distribution of diseases is important for health authorities to prioritize and allocate resources.\ud \ud METHODS\ud \ud To identify possible significant clusters, we used SatTScan software, and analyzed 2,745 cases of under-five with 134,099 person-years for the period between 1999and 2008. Mortality rates for every year were calculated, likewise a spatial scan statistic was used to test for clusters of total under-five mortalities in both space and time.\ud \ud RESULTS\ud \ud A number of significant clusters from space, time, and space-time analysis were identified in several locations for a period of 10 years in the Rufiji Demographic Surveillance Site (RDSS). These locations show that villages within the clusters have an elevated risk of under-five deaths. The spatial analysis identified three significant clusters. The first cluster had only one village, Kibiti A (p < 0.05, the second cluster involved five villages (Mtawanya, Pagae, Kibiti A, Machepe, and Kibiti B; p < 0.05), the third cluster involved one village, Jaribu Mpakani (p < 0.05). A space-time cluster of 10 villages for the period between 1999 and 2002 with a radius of 14.73 km was discovered with the highest risk (RR 1.6, p < 0.001). The mortality rates were very high for the years 1999-2002 according to the analysis. The death rates were 33.5, 26.4, 24.1, and 24.9, respectively. Total childhood mortality rates calculated for the period of 10 years were 21.0 per 1,000 person-years.\ud \ud CONCLUSION\ud \ud During the 10 years of analysis, mortality seemed to decrease in RDSS. The mortality decline should be taken with caution because the Demographic Surveillance System is not statistically representative of the whole population; therefore, inference should not be made to the general population of Tanzania. The pattern observed could be attributed to demographic and weather characteristics of RDSS. This should provide new insights for further studies and interventions toward reducing under-five mortality

Measuring the Burden of Neglected Tropical Diseases: The Global Burden of Disease Framework

Reliable, comparable information about the main causes of disease and injury in populations, and how these are changing, is a critical input for debates about priorities in the health sector. Traditional sources of information about the descriptive epidemiology of diseases, injuries, and risk factors are generally incomplete, fragmented, and of uncertain reliability and comparability. The Global Burden of Disease (GBD) study has provided a conceptual and methodological framework to quantify and compare the health of populations using a summary measure of both mortality and disability, the disability-adjusted life year (DALY)

World health system performance revisited: the impact of varying the relative importance of health system goals

BACKGROUND: In 2002, the World Health Organization published a health system performance ranking for 191 member countries. The ranking was based on five indicators, with fixed weights common to all countries. METHODS: We investigate the feasibility and desirability of using mathematical programming techniques that allow weights to vary across countries to reflect their varying circumstances and objectives. RESULTS: By global distributional measures, scores and ranks are found to be not very sensitive to changes in weights, although differences can be large for individual countries. CONCLUSIONS: Building the flexibility of variable weights into calculation of the performance index is a useful way to respond to the debates and criticisms appearing since publication of the ranking

Population health metrics: crucial inputs to the development of evidence for health policy

Valid, reliable and comparable measures of the health states of individuals and of the health status of populations are critical components of the evidence base for health policy. We need to develop population health measurement strategies that coherently address the relationships between epidemiological measures (such as risk exposures, incidence, and mortality rates) and multi-domain measures of population health status, while ensuring validity and cross-population comparability. Studies reporting on descriptive epidemiology of major diseases, injuries and risk factors, and on the measurement of health at the population level – either for monitoring trends in health levels or inequalities or for measuring broad outcomes of health systems and social interventions – are not well-represented in traditional epidemiology journals, which tend to concentrate on causal studies and on quasi-experimental design. In particular, key methodological issues relating to the clear conceptualisation of, and the validity and comparability of measures of population health are currently not addressed coherently by any discipline, and cross-disciplinary debate is fragmented and often conducted in mutually incomprehensible language or paradigms. Population health measurement potentially bridges a range of currently disjoint fields of inquiry relating to health: biology, demography, epidemiology, health economics, and broader social science disciplines relevant to assessment of health determinants, health state valuations and health inequalities. This new journal will focus on the importance of a population based approach to measurement as a way to characterize the complexity of people's health, the diseases and risks that affect it, its distribution, and its valuation, and will attempt to provide a forum for innovative work and debate that bridge the many fields of inquiry relevant to population health in order to contribute to the development of valid and comparable methods for the measurement of population health and its determinants

Compressively sampling the optical transmission matrix of a multimode fibre (article)

This is the final version. Available on open access from Springer Nature via the DOI in this recordThe dataset associated with this article is available in ORE at : https://doi.org/10.24378/exe.3204The measurement of the optical transmission matrix (TM) of an opaque material is an advanced form of space-variant aberration correction. Beyond imaging, TM-based methods are emerging in a range of fields, including optical communications, micro-manipulation, and computing. In many cases, the TM is very sensitive to perturbations in the configuration of the scattering medium it represents. Therefore, applications often require an up-to-the-minute characterisation of the fragile TM, typically entailing hundreds to thousands of probe measurements. Here, we explore how these measurement requirements can be relaxed using the framework of compressive sensing, in which the incorporation of prior information enables accurate estimation from fewer measurements than the dimensionality of the TM we aim to reconstruct. Examples of such priors include knowledge of a memory effect linking the input and output fields, an approximate model of the optical system, or a recent but degraded TM measurement. We demonstrate this concept by reconstructing the full-size TM of a multimode fibre supporting 754 modes at compression ratios down to ∼5% with good fidelity. We show that in this case, imaging is still possible using TMs reconstructed at compression ratios down to ∼1% (eight probe measurements). This compressive TM sampling strategy is quite general and may be applied to a variety of other scattering samples, including diffusers, thin layers of tissue, fibre optics of any refractive profile, and reflections from opaque walls. These approaches offer a route towards the measurement of high-dimensional TMs either quickly or with access to limited numbers of measurements.National Natural Science Foundation of ChinaNational Science Foundation (NSF)European Regional Development Fund (ERDF)European Research Council (ERC)Royal Academy of Engineering (RAE