The Shale revolution: Global gas and oil markets under transformation

The shale gas and oil revolution has unexpectedly and forcefully begun to change the energy landscape in the USA. It is expected to spread beyond the USA, with far reaching implications for the global energy map, but also for the macro economy and politics of many countries. The purpose of this paper is to bring a better understanding to what prompted the revolution, to assess the production methods and associated environmental concerns, to speculate what can reasonably be expected in coming decades, and to sketch the full impact of a ripening shale revolution on the emerging economic and political policy choices for energy exporting and importing countries. We find that a large scale expansion can be expected in US shale gas and oil activities in the coming two decades. Globally, the shale leaders are likely to be countries that are already significant gas and oil producers. Setting up a policy framework to allow and promote shale development in a safe manner is a necessity for the launch of shale exploitation. The most important implication of a successful shale revolution would arguably be a downward pressure on gas and coal prices in regional markets and on the global oil price

Influenza activity in Europe during eight seasons (1999–2007): an evaluation of the indicators used to measure activity and an assessment of the timing, length and course of peak activity (spread) across Europe

<p>Abstract</p> <p>Background</p> <p>The European Influenza Surveillance Scheme (EISS) has collected clinical and virological data on influenza since 1996 in an increasing number of countries. The EISS dataset was used to characterise important epidemiological features of influenza activity in Europe during eight winters (1999–2007). The following questions were addressed: 1) are the sentinel clinical reports a good measure of influenza activity? 2) how long is a typical influenza season in Europe? 3) is there a west-east and/or south-north course of peak activity ('spread') of influenza in Europe?</p> <p>Methods</p> <p>Influenza activity was measured by collecting data from sentinel general practitioners (GPs) and reports by national reference laboratories. The sentinel reports were first evaluated by comparing them to the laboratory reports and were then used to assess the timing and spread of influenza activity across Europe during eight seasons.</p> <p>Results</p> <p>We found a good match between the clinical sentinel data and laboratory reports of influenza collected by sentinel physicians (overall match of 72% for +/- 1 week difference). We also found a moderate to good match between the clinical sentinel data and laboratory reports of influenza from non-sentinel sources (overall match of 60% for +/- 1 week). There were no statistically significant differences between countries using ILI (influenza-like illness) or ARI (acute respiratory disease) as case definition. When looking at the peak-weeks of clinical activity, the average length of an influenza season in Europe was 15.6 weeks (median 15 weeks; range 12–19 weeks). Plotting the peak weeks of clinical influenza activity reported by sentinel GPs against the longitude or latitude of each country indicated that there was a west-east spread of peak activity (spread) of influenza across Europe in four winters (2001–2002, 2002–2003, 2003–2004 and 2004–2005) and a south-north spread in three winters (2001–2002, 2004–2005 and 2006–2007).</p> <p>Conclusion</p> <p>We found that: 1) the clinical data reported by sentinel physicians is a valid indicator of influenza activity; 2) the length of influenza activity across the whole of Europe was surprisingly long, ranging from 12–19 weeks; 3) in 4 out of the 8 seasons, there was a west-east spread of influenza, in 3 seasons a south-north spread; not associated with type of dominant virus in those seasons.</p

Strongly magnetized pulsars: explosive events and evolution

Well before the radio discovery of pulsars offered the first observational confirmation for their existence (Hewish et al., 1968), it had been suggested that neutron stars might be endowed with very strong magnetic fields of $10^{10}$-$10^{14}$G (Hoyle et al., 1964; Pacini, 1967). It is because of their magnetic fields that these otherwise small ed inert, cooling dead stars emit radio pulses and shine in various part of the electromagnetic spectrum. But the presence of a strong magnetic field has more subtle and sometimes dramatic consequences: In the last decades of observations indeed, evidence mounted that it is likely the magnetic field that makes of an isolated neutron star what it is among the different observational manifestations in which they come. The contribution of the magnetic field to the energy budget of the neutron star can be comparable or even exceed the available kinetic energy. The most magnetised neutron stars in particular, the magnetars, exhibit an amazing assortment of explosive events, underlining the importance of their magnetic field in their lives. In this chapter we review the recent observational and theoretical achievements, which not only confirmed the importance of the magnetic field in the evolution of neutron stars, but also provide a promising unification scheme for the different observational manifestations in which they appear. We focus on the role of their magnetic field as an energy source behind their persistent emission, but also its critical role in explosive events.Comment: Review commissioned for publication in the White Book of "NewCompStar" European COST Action MP1304, 43 pages, 8 figure

Association of MC1R Variants and host phenotypes with melanoma risk in CDKN2A mutation carriers: a GenoMEL study

&lt;p&gt;&lt;b&gt;Background&lt;/b&gt; Carrying the cyclin-dependent kinase inhibitor 2A (CDKN2A) germline mutations is associated with a high risk for melanoma. Penetrance of CDKN2A mutations is modified by pigmentation characteristics, nevus phenotypes, and some variants of the melanocortin-1 receptor gene (MC1R), which is known to have a role in the pigmentation process. However, investigation of the associations of both MC1R variants and host phenotypes with melanoma risk has been limited.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Methods&lt;/b&gt; We included 815 CDKN2A mutation carriers (473 affected, and 342 unaffected, with melanoma) from 186 families from 15 centers in Europe, North America, and Australia who participated in the Melanoma Genetics Consortium. In this family-based study, we assessed the associations of the four most frequent MC1R variants (V60L, V92M, R151C, and R160W) and the number of variants (1, &#8805;2 variants), alone or jointly with the host phenotypes (hair color, propensity to sunburn, and number of nevi), with melanoma risk in CDKN2A mutation carriers. These associations were estimated and tested using generalized estimating equations. All statistical tests were two-sided.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Results&lt;/b&gt; Carrying any one of the four most frequent MC1R variants (V60L, V92M, R151C, R160W) in CDKN2A mutation carriers was associated with a statistically significantly increased risk for melanoma across all continents (1.24 × 10−6 &#8804; P &#8804; .0007). A consistent pattern of increase in melanoma risk was also associated with increase in number of MC1R variants. The risk of melanoma associated with at least two MC1R variants was 2.6-fold higher than the risk associated with only one variant (odds ratio = 5.83 [95% confidence interval = 3.60 to 9.46] vs 2.25 [95% confidence interval = 1.44 to 3.52]; Ptrend = 1.86 × 10−8). The joint analysis of MC1R variants and host phenotypes showed statistically significant associations of melanoma risk, together with MC1R variants (.0001 &#8804; P &#8804; .04), hair color (.006 &#8804; P &#8804; .06), and number of nevi (6.9 × 10−6 &#8804; P &#8804; .02).&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusion&lt;/b&gt; Results show that MC1R variants, hair color, and number of nevi were jointly associated with melanoma risk in CDKN2A mutation carriers. This joint association may have important consequences for risk assessments in familial settings.&lt;/p&gt

Reaction rates and transport in neutron stars

Understanding signals from neutron stars requires knowledge about the transport inside the star. We review the transport properties and the underlying reaction rates of dense hadronic and quark matter in the crust and the core of neutron stars and point out open problems and future directions.Comment: 74 pages; commissioned for the book "Physics and Astrophysics of Neutron Stars", NewCompStar COST Action MP1304; version 3: minor changes, references updated, overview graphic added in the introduction, improvements in Sec IV.A.

The life cycle impact for platinum group metals and lithium to 2070 via surplus cost potential

© 2017 The Author(s)Purpose: A surplus cost potential (SCP) indicator has been developed as a measure of resource scarcity in the life cycle impact assessment (LCIA) context. To date, quality SCP estimates for other minerals than fossils are either not yet available or suffer methodological and data limitations. This paper overcomes these limitations and demonstrate how SCP estimates for metals can be calculated without the utilisation of ore grade function and by collecting primary economic and geological data. Methods: Data were collected in line with the geographical distribution, mine type, deposit type and production volumes and total production costs in order to construct cost-cumulative availability curves for platinum group metals (PGMs) and lithium. These curves capture the total amount of known mineral resources that can be recovered profitably at various prices from different types of mineral deposits under current conditions (this is, current technology, prevailing labour and other input prices). They served as a basis for modelling the marginal cost increase, a necessary parameter for estimating the SCP indicator. Surplus costs were calculated for different scenario projections for future mineral production considering future market dynamics, recyclability rates, demand-side technological developments and economic growth and by applying declining social discount rate. Results and discussion: Surplus costs were calculated for three mineral production scenarios, ranging from (US$2014/kg) 6545–8354 for platinum, 3583–4573 for palladium, 8281–10,569 for rhodium, 513–655 for ruthenium, 3201–4086 for iridium and 1.70–5.80 for lithium. Compared with the current production costs, the results indicate that problematic price increases of lithium are unlikely if the latest technological trends in the automotive sector will continue up to 2070. Surplus costs for PGMs are approximately one-third of the current production costs in all scenarios; hence, a threat of their price increases by 2070 will largely depend on the discovery of new deposits and the ability of new technologies to push these costs down over time. This also applies to lithium if the increasing electrification of road transport will continue up to 2070. Conclusions: This study provides useful insight into the availability of PGMs and lithium up to 2070. It proves that if time and resources permit, reliable surplus cost estimates can be calculated, at least in the short-run, based on the construction of one’s own curves with the level of quality comparable to expert-driven consulting services. Modelling and incorporating unknown deposits and potential future mineral production costs into these curves is the subject of future work

Real-time numerical forecast of global epidemic spreading: Case study of 2009 A/H1N1pdm

Background Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches. Methods We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability. Results Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model. Conclusions Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models

Genetic and Non-Genetic Influences during Pregnancy on Infant Global and Site Specific DNA Methylation: Role for Folate Gene Variants and Vitamin B12

Inter-individual variation in patterns of DNA methylation at birth can be explained by the influence of environmental, genetic and stochastic factors. This study investigates the genetic and non-genetic determinants of variation in DNA methylation in human infants. Given its central role in provision of methyl groups for DNA methylation, this study focuses on aspects of folate metabolism. Global (LUMA) and gene specific (IGF2, ZNT5, IGFBP3) DNA methylation were quantified in 430 infants by Pyrosequencing®. Seven polymorphisms in 6 genes (MTHFR, MTRR, FOLH1, CβS, RFC1, SHMT) involved in folate absorption and metabolism were analysed in DNA from both infants and mothers. Red blood cell folate and serum vitamin B12 concentrations were measured as indices of vitamin status. Relationships between DNA methylation patterns and several covariates viz. sex, gestation length, maternal and infant red cell folate, maternal and infant serum vitamin B12, maternal age, smoking and genotype were tested. Length of gestation correlated positively with IGF2 methylation (rho = 0.11, p = 0.032) and inversely with ZNT5 methylation (rho = −0.13, p = 0.017). Methylation of the IGFBP3 locus correlated inversely with infant vitamin B12 concentration (rho = −0.16, p = 0.007), whilst global DNA methylation correlated inversely with maternal vitamin B12 concentrations (rho = 0.18, p = 0.044). Analysis of common genetic variants in folate pathway genes highlighted several associations including infant MTRR 66G>A genotype with DNA methylation (χ2 = 8.82, p = 0.003) and maternal MTHFR 677C>T genotype with IGF2 methylation (χ2 = 2.77, p = 0.006). These data support the hypothesis that both environmental and genetic factors involved in one-carbon metabolism influence DNA methylation in infants. Specifically, the findings highlight the importance of vitamin B12 status, infant MTRR genotype and maternal MTHFR genotype, all of which may influence the supply of methyl groups for DNA methylation. In addition, gestational length appears to be an important determinant of infant DNA methylation patterns