Reducing the number of miscreant tasks executions in a multi-use cluster.

Exploiting computational resources within an organisation for more than their primary task offers great benefits – making better use of capital expenditure and provides a pool of computational power. This can be achieved through the deployment of a cycle stealing distributed system, where tasks execute during the idle time on computers. However, if a task has not completed when a computer returns to its primary function the task will be preempted, wasting time (and energy), and is often reallocated to a new resource in an attempt to complete. This becomes exacerbated when tasks are incapable of completing due to excessive execution time or faulty hardware / software, leading to a situation where tasks are perpetually reallocated between computers – wasting time and energy. In this work we investigate techniques to increase the chance of ‘good’ tasks completing whilst curtailing the execution of ‘bad’ tasks. We demonstrate, through simulation, that we could have reduce the energy consumption of our cycle stealing system by approximately 50%

Flood modelling for cities using Cloud computing

Urban flood risk modelling is a highly topical example of intensive computational processing. Such processing is increasingly required by a range of organisations including local government, engineering consultancies and the insurance industry to fulfil statutory requirements and provide professional services. As the demands for this type of work become more common, then ownership of high-end computational resources is warranted but if use is more sporadic and with tight deadlines then the use of Cloud computing could provide a cost-effective alternative. However, uptake of the Cloud by such organisations is often thwarted by the perceived technical barriers to entry. In this paper we present an architecture that helps to simplify the process of performing parameter sweep work on an Infrastructure as a Service Cloud. A parameter sweep version of the urban flood modelling, analysis and visualisation software “CityCat” was developed and deployed to estimate spatial and temporal flood risk at a whole city scale – far larger than had previously been possible. Performing this work on the Cloud allowed us access to more computing power than we would have been able to purchase locally for such a short time-frame (∼21 months of processing in a single calendar month). We go further to illustrate the considerations, both functional and non-functional, which need to be addressed if such an endeavour is to be successfully achieved

Reducing the number of miscreant tasks executions in a multi-use cluster

Exploiting computational resources within an organisation for more than their primary task offers great benefits – making better use of capital expenditure and provides a pool of computational power. This can be achieved through the deployment of a cycle stealing distributed system, where tasks execute during the idle time on computers. However, if a task has not completed when a computer returns to its primary function the task will be preempted, wasting time (and energy), and is often reallocated to a new resource in an attempt to complete. This becomes exacerbated when tasks are incapable of completing due to excessive execution time or faulty hardware / software, leading to a situation where tasks are perpetually reallocated between computers – wasting time and energy. In this work we investigate techniques to increase the chance of ‘good’ tasks completing whilst curtailing the execution of ‘bad’ tasks. We demonstrate, through simulation, that we could have reduce the energy consumption of our cycle stealing system by approximately 50%

Severity scoring of manganese health effects for categorical regression

Characterizing the U-shaped exposure response relationship for manganese (Mn) is necessary for estimating the risk of adverse health from Mn toxicity due to excess or deficiency. Categorical regression has emerged as a powerful tool for exposure-response analysis because of its ability to synthesize relevant information across multiple studies and species into a single integrated analysis of all relevant data. This paper documents the development of a database on Mn toxicity designed to support the application of categorical regression techniques. Specifically, we describe (i) the conduct of a systematic search of the literature on Mn toxicity to gather data appropriate for dose-response assessment; (ii) the establishment of inclusion/exclusion criteria for data to be included in the categorical regression modeling database; (iii) the development of a categorical severity scoring matrix for Mn health effects to permit the inclusion of diverse health outcomes in a single categorical regression analysis using the severity score as the outcome variable; and (iv) the convening of an international expert panel to both review the severity scoring matrix and assign severity scores to health outcomes observed in studies (including case reports, epidemiological investigations, and in vivo experimental studies) selected for inclusion in the categorical regression database. Exposure information including route, concentration, duration, health endpoint(s), and characteristics of the exposed population was abstracted from included studies and stored in a computerized manganese database (MnDB), providing a comprehensive repository of exposure-response information with the ability to support categorical regression modeling of oral exposure data

A genomewide scan for Attention-Deficit/Hyperactivity Disorder in an extended sample: Suggestive linkage on 17p11

Attention-deficit/hyperactivity disorder (ADHD [MIM 143465]) is a common, highly heritable neurobehavioral disorder of childhood onset, characterized by hyperactivity, impulsivity, and/or inattention. As part of an ongoing study of the genetic etiology of ADHD, we have performed a genomewide linkage scan in 204 nuclear families comprising 853 individuals and 270 affected sibling pairs (ASPs). Previously, we reported genomewide linkage analysis of a “first wave” of these families composed of 126 ASPs. A follow-up investigation of one region on 16p yielded significant linkage in an extended sample. The current study extends the original sample of 126 ASPs to 270 ASPs and provides linkage analyses of the entire sample, using polymorphic microsatellite markers that define an ∼10-cM map across the genome. Maximum LOD score (MLS) analysis identified suggestive linkage for 17p11 (MLS=2.98) and four nominal regions with MLS values >1.0, including 5p13, 6q14, 11q25, and 20q13. These data, taken together with the fine mapping on 16p13, suggest two regions as highly likely to harbor risk genes for ADHD: 16p13 and 17p11. Interestingly, both regions, as well as 5p13, have been highlighted in genomewide scans for autism

Interstellar Silicate Dust in the z=0.89 Absorber Towards PKS 1830-211: Crystalline Silicates at High Redshift?

We present evidence of a >10-sigma detection of the 10 micron silicate dust absorption feature in the spectrum of the gravitationally lensed quasar PKS 1830-211, produced by a foreground absorption system at redshift 0.886. We have examined more than 100 optical depth templates, derived from both observations of Galactic and extragalactic sources and laboratory measurements, in order to constrain the chemical structure of the silicate dust. We find that the best fit to the observed absorption profile is produced by laboratory crystalline olivine, with a corresponding peak optical depth of tau_10=0.27+/-0.05. The fit is slightly improved upon by including small contributions from additional materials such as silica, enstatite, or serpentine, which suggests that the dust composition may consist of a blend of crystalline silicates. Combining templates for amorphous and crystalline silicates, we find that the fraction of crystalline silicates needs to be at least 95%. Given the rarity of extragalactic sources with such a high degree of silicate crystallinity, we also explore the possibility that the observed spectral features are produced by amorphous silicates in combination with other molecular or atomic transitions, or by foreground source contamination. While we cannot rule out these latter possibilities, they lead to much poorer profile fits than for the crystalline olivine templates. If the presence of crystalline interstellar silicates in this distant galaxy is real, it would be highly unusual, given that the Milky Way interstellar matter contains essentially only amorphous silicates. It is possible that the z=0.886 absorber towards PKS 1830-211, well known for its high molecular content, has a unique star-forming environment that enables crystalline silicates to form and prevail.Comment: 67 pages, 21 figures, accepted for publication in the Astrophysical Journa

Monitoring internet trade to inform species conservation actions

Specimens, parts and products of threatened species are now commonly traded on the internet. This could threaten the survival of some wild populations if inadequately regulated. We outline two methods to monitor internet sales of threatened species in order to assess potential threats and inform conservation actions. Our first method combines systematic monitoring of online offers of plants for sale over the internet with consultation by experts experienced in identifying plants collected from the wild based on images of the specimens, species identity and details of the trade. Our second method utilises a computational model, trained using Bayesian techniques to records that have been classified by an expert as wild collected or artificially propagated, to predict unknown properties of the traded taxa, such as whether a species being sold is collected from the wild or the identity of an unknown wild collected species. We used these methods to monitor internet trade in five genera of succulent plant species endemic to Madagascar, for which some have recently been listed for trade regulation under the Convention on International Trade in Endangered Species (CITES). This revealed potential threats to wild populations: for instance, almost all species recorded were of high conservation concern yet most offers for live plants were of apparently wild collected specimens (85%). Moreover, no records of international trade in the official CITES database were from the countries featured in our survey. Our model predicted with 89% accuracy whether the live plants were classified as propagated or wild collected by an expert, although accuracy dropped for data collected in the following summer due to a change in the patterns of sales. Our results highlight potential threats by internet trade to the survival of some CITES and non-CITES listed plant species from Madagascar. These should be addressed by further conservation actions and policy. More generally, our results reveal how standardised internet surveys can provide information on levels of trade in wild collected threatened species that could impact on natural populations and can provide data that can be incorporated into models to facilitate future monitoring and enforcement

Local Chatter or International Buzz? Language Differences on Posts about Zika Research on Twitter and Facebook

Background When the Zika virus outbreak became a global health emergency in early 2016, the scientific community responded with an increased output of Zika-related research. This upsurge in research naturally made its way into academic journals along with editorials, news, and reports. However, it is not yet known how or whether these scholarly communications were distributed to the populations most affected by Zika. Methodology/Principal findings To understand how scientific outputs about Zika reached global and local audiences, we collected Tweets and Facebook posts that linked to Zika-related research in the first six months of 2016. Using a language detection algorithm, we found that up to 90% of Twitter and 76% of Facebook posts are in English. However, when none of the authors of the scholarly article are from English-speaking countries, posts on both social media are less likely to be in English. The effect is most pronounced on Facebook, where the likelihood of posting in English is between 11 and 16% lower when none of the authors are from English-speaking countries, as compared to when some or all are. Similarly, posts about papers written with a Brazilian author are 13% more likely to be in Portuguese on Facebook than when made on Twitter. Conclusions/Significance Our main conclusion is that scholarly communication on Twitter and Facebook of Zikarelated research is dominated by English, despite Brazil being the epicenter of the Zika epidemic. This result suggests that scholarly findings about the Zika virus are unlikely to be distributed directly to relevant populations through these popular online mediums. Nevertheless, there are differences between platforms. Compared to Twitter, scholarly communication on Facebook is more likely to be in the language of an author’s country. The Zika outbreak provides a useful case-study for understanding how scientific outputs are communicated to relevant populations. Our results suggest that Facebook is a more effective channel than Twitter, if communication is desired to be in the native language of the affected country. Further research should explore how local media—such as governmental websites, newspapers and magazines, as well as television and radio—disseminate scholarly publication

Recommendations to encourage participation of individuals from diverse backgrounds in psychiatric genetic studies

We present innovative research practices in psychiatric genetic studies to ensure representation of individuals from diverse ancestry, sex assigned at birth, gender identity, age, body shape and size, and socioeconomic backgrounds. Due to histories of inappropriate and harmful practices against marginalized groups in both psychiatry and genetics, people of certain identities may be hesitant to participate in research studies. Yet their participation is essential to ensure diverse representation, as it is incorrect to assume that the same genetic and environmental factors influence the risk for various psychiatric disorders across all demographic groups. We present approaches developed as part of the Eating Disorders Genetics Initiative (EDGI), a study that required tailored approaches to recruit diverse populations across many countries. Considerations include research priorities and design, recruitment and study branding, transparency, and community investment and ownership. Ensuring representation in participants is costly and funders need to provide adequate support to achieve diversity in recruitment in prime awards, not just as supplemental afterthoughts. The need for diverse samples in genetic studies is critical to minimize the risk of perpetuating health disparities in psychiatry and other health research. Although the EDGI strategies were designed specifically to attract and enroll individuals with eating disorders, our approach is broadly applicable across psychiatry and other fields