103 research outputs found
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Aviation turbulence: dynamics, forecasting, and response to climate change
Atmospheric turbulence is a major hazard in the aviation industry and can cause injuries to passengers and crew. Understanding the physical and dynamical generation mechanisms of turbulence aids with the development of new forecasting algorithms and, therefore, reduces the impact that it has on the aviation industry. The scope of this paper is to review the dynamics of aviation turbulence, its response to climate change, and current forecasting methods at the cruising altitude of aircraft. Aviation-affecting turbulence comes from three main sources: vertical wind shear instabilities, convection, and mountain waves. Understanding these features helps researchers to develop better turbulence diagnostics. Recent research suggests that turbulence will increase in frequency and strength with climate change, and therefore, turbulence forecasting may become more important in the future. The current methods of forecasting are unable to predict every turbulence event, and research is ongoing to find the best solution to this problem by combining turbulence predictors and using ensemble forecasts to increase skill. The skill of operational turbulence forecasts has increased steadily over recent decades, mirroring improvements in our understanding. However, more work is needed—ideally in collaboration with the aviation industry—to improve observations and increase forecast skill, to help maintain and enhance aviation safety standards in the future
A Novel Diagnostic Target in the Hepatitis C Virus Genome
Christian Drosten and colleagues develop, validate, and make openly available a prototype hepatitis C virus assay based on the conserved 3' X-tail element, with potential for clinical use in developing countries
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A Proposed High-Power UV Industrial Demonstration Laser at CEBAF
The Laser Processing Consortium, a collaboration of industries, universities, and the Continuous Electron Beam Accelerator Facility (CEBAF) in Newport News, Virginia, has proposed building a demonstration industrial processing laser for surface treatment and micro-machining. The laser is a free-electron laser (FEL) with average power output exceeding 1 kW in the ultraviolet (UV). The design calls for a novel driver accelerator that recovers most of the energy of the exhaust electron beam to produce laser light with good wall-plug efficiency. The laser and accelerator design use technologies that are scalable to much higher power. The authors will describe the critical design issues in the laser such as the stability, power handling, and losses of the optical resonator, and the quality, power, and reliability of the electron beam. They will also describe the calculated laser performance. Finally progress to date on accelerator development and resonator modeling will be reported
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Increased light, moderate, and severe clear-air turbulence in response to climate change
Anthropogenic climate change is expected to strengthen the vertical wind shears at aircraft cruising altitudes
within the atmospheric jet streams. Such a strengthening would increase the prevalence of shear instabilities, which generate clear-air turbulence. Climate modelling studies have indicated that the amount of moderate-or-greater clear-air turbulence on transatlantic flight routes in winter will increase significantly in future as the climate changes. However, the individual responses of light, moderate, and severe clear-air turbulence have not previously been studied, despite their importance for aircraft operations.
Here we use climate model simulations to analyse the transatlantic wintertime clear-air turbulence response
to climate change in five aviation-relevant turbulence strength categories. We find that the probability distributions for an ensemble of 21 clear-air turbulence diagnostics generally gain probability in their right-hand tails when the atmospheric carbon dioxide concentration is doubled. By converting the diagnostics into equivalent eddy dissipation rates, we find that the ensemble-average airspace volume containing light clear-air turbulence increases by 59% (with an intra-ensemble range of 43–68%), light-to-moderate by 75% (39–96%), moderate by 94% (37–118%), moderate-to-severe by 127% (30–170%), and severe by 149% (36–188%). These results suggest that the prevalence of transatlantic wintertime clear-air turbulence will increase significantly in all aviation-relevant strength categories as the climate changes
Gay Rights, the Devil and the End Times: Public Religion and the Enchantment of the Homosexuality Debate in Zambia
This article contributes to the understanding of the role of religion in the public and political controversies about homosexuality in Africa. As a case study it investigates the heated public debate in Zambia following a February 2012 visit by United Nations Secretary General Ban Ki-moon, who emphasised the need for the country to recognise the human rights of homosexuals. The focus is on a particular Christian discourse in this debate, in which the international pressure to recognise gay rights is considered a sign of the end times, and Ban Ki-moon, the UN and other international organisations are associated with the Antichrist and the Devil. Here, the debate about homosexuality becomes eschatologically enchanted through millennialist thought. Building on discussions about public religion and religion and politics in Africa, this article avoids popular explanations in terms of fundamentalist religion and African homophobia, but rather highlights the political significance of this discourse in a postcolonial African context
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research
A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes
dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe
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