Scaling-up experiments of smouldering combustion as a remediation technology for contaminated soil

Self-sustaining Treatment for Active Remediation (STAR) is a novel, patent-pending process that uses smouldering combustion as a remediation technology for land contaminated with hazardous organic liquids. Compounds such as chlorinated solvents, coal tar and petroleum products, called Non-Aqueous Phase Liquids (NAPLs) for their low miscibility with water, have a long history of use in the industrialised world and are among the most ubiquitous of contaminants worldwide. These contaminants are toxic and many are suspected or known carcinogens. Existing remediation technologies are expensive and ineffective at reducing NAPL source zones sufficiently to restore affected water resources to appropriate quality levels. STAR introduces a self-sustaining smouldering reaction within the NAPL pool in the subsurface and allows that reaction to provide all of the post-ignition energy required by the reaction to completely remediate the NAPL source zone in the soil. Results from laboratory and field experiments have been very promising. Laboratory experiments have demonstrated STAR across a wide range of NAPL fuels and focused on coal tar to identify key parameters for successful remediation. Modelling has suggested that STAR efficiency will improve with scale as effects such as heat losses from boundaries become less significant. Observations from field experiments support the modelling theory - significantly lower relative air flow in a smouldering field experiment (330L) led to faster smouldering front propagation than observed in laboratory experiments (1L and 3L). Preliminary emissions monitoring by Fourier Transform Infrared (FTIR) spectroscopy has suggested that STAR emissions might be low enough to meet regulatory requirements, but further study is necessary. As emissions are expected to vary with each contaminant, activated carbon filters are being developed and tested in case emissions filtration is necessary. Experiments at all scales have demonstrated that STAR is controllable and self-terminating. Pilot-scale (2500L) field trials are underway to demonstrate STAR on excavated contaminated soil. The materials that will be studied in these trials are manufactured coal tar in coarse sand (which is the same material as used in the laboratory and field experiments) as well as two soils obtained from coal tar contaminated sites. This poster focuses on the scale-up to these field trials, including small scale characterisation, large scale performance, emissions monitoring and post-treatment soil analysis

Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population

Online genealogy datasets contain extensive information about millions of people and their past and present family connections. This vast amount of data can assist in identifying various patterns in human population. In this study, we present methods and algorithms which can assist in identifying variations in lifespan distributions of human population in the past centuries, in detecting social and genetic features which correlate with human lifespan, and in constructing predictive models of human lifespan based on various features which can easily be extracted from genealogy datasets. We have evaluated the presented methods and algorithms on a large online genealogy dataset with over a million profiles and over 9 million connections, all of which were collected from the WikiTree website. Our findings indicate that significant but small positive correlations exist between the parents' lifespan and their children's lifespan. Additionally, we found slightly higher and significant correlations between the lifespans of spouses. We also discovered a very small positive and significant correlation between longevity and reproductive success in males, and a small and significant negative correlation between longevity and reproductive success in females. Moreover, our machine learning algorithms presented better than random classification results in predicting which people who outlive the age of 50 will also outlive the age of 80. We believe that this study will be the first of many studies which utilize the wealth of data on human populations, existing in online genealogy datasets, to better understand factors which influence human lifespan. Understanding these factors can assist scientists in providing solutions for successful aging

The Core, Periphery, and Beyond: Stock Market Comovements among EU and Non-EU Countries

We thank conference participants at the 2016 Financial Management Association and our discussant Fernando Moreira, and two anonymous referees for immensely helpful comments. We also thank Andrew Patton and James P. LeSage for sharing their MATLAB codes for computing quantile dependence. The authors of this paper are responsible for any errors or omissions. The Securities and Exchange Commission, as a matter of policy, disclaims responsibility for any private publication or statement by any of its employees. The views expressed herein are those of the authors and do not necessarily reflect the views of the Commission or the authors\u27 colleagues on the staff of the Commission

Quantitative Analysis of Genealogy Using Digitised Family Trees

Driven by the popularity of television shows such as Who Do You Think You Are? many millions of users have uploaded their family tree to web projects such as WikiTree. Analysis of this corpus enables us to investigate genealogy computationally. The study of heritage in the social sciences has led to an increased understanding of ancestry and descent but such efforts are hampered by difficult to access data. Genealogical research is typically a tedious process involving trawling through sources such as birth and death certificates, wills, letters and land deeds. Decades of research have developed and examined hypotheses on population sex ratios, marriage trends, fertility, lifespan, and the frequency of twins and triplets. These can now be tested on vast datasets containing many billions of entries using machine learning tools. Here we survey the use of genealogy data mining using family trees dating back centuries and featuring profiles on nearly 7 million individuals based in over 160 countries. These data are not typically created by trained genealogists and so we verify them with reference to third party censuses. We present results on a range of aspects of population dynamics. Our approach extends the boundaries of genealogy inquiry to precise measurement of underlying human phenomena

How Informative Is Floating NAV When Securities Trade Infrequently?

We examine if a floating net asset value (NAV) increases the transparency of risk for investors. Using closed-income fixed income funds we find little evidence that a floating NAV helps investors better understand the value and risk of a fund when a fund\u27s assets trade infrequently. This potentially informs the debate regarding the adoption of a floating NAV in the money market industry. Our results suggest that it is unlikely that the benefits of floating NAV will outweigh the costs

Italian hybrid fire prevention code

Fire safety of residential buildings and activities subjected to fire inspection is a difficult task, especially when the safety targets have to be adopted in built buildings or in activities that are going to be modified into more complex ones. Generally, these circumstances show more constraints and it could be difficult to achieve an acceptable level of fire residual risk by prescriptive based fireregulations. Therefore, the Italian National Fire Rescue and Service in charge for fire safety, in August 2015 issued a new Fire Prevention Code whose design methodology is more oriented to fire performance based design rather than prescriptive fire codes. The flexibility of this new fire design methodology offers a very complex tool to experts in order to design fire safety measures and strategies of buildings and activities subjected to fire inspection. The present paper aims tohighlig hts the contents and the fire safety strategy design methodology of the new Italian Fire Prevention Code