Meteorological drivers of European power system stress

A rapid decarbonisation of power systems is underway in order to limit greenhouse gas emissions and meet carbon reduction targets. Renewable energy is a key ingredient to meet these targets, however, it is important that national power systems still maintain energy security with increasing levels of renewable penetration. The operating potential of renewable generation at times of peak demand (a critical time for power system stress) is not well understood. This study therefore uses a multi-decadal dataset of national demand, wind power and solar power generation to identify the meteorological conditions when peak demand occurs, and the contribution of renewables during these events. Wintertime European peak power demand events are associated with high atmospheric pressure over Russia and Scandinavia and are accompanied by lower than average air temperatures and average wind speeds across Europe. When considering power demand extremes net of renewable power production, the associated meteorological conditions are shown to change. There is considerable spatial variability in the dates of national peak demand events, and amount of renewable generation present. Growth in renewable generation has the potential to reduce peak demands. However these impacts are also not uniform with much larger reductions in peak demand seen in Spain than in central Europe. The re-analysis derived energy models have allowed for recent peak demand events to be put into a longer-term context

Herding, contrarianism and delay in financial market trading

Herding and contrarian behaviour are often-cited features of real-world financial markets. Theoretical models of continuous trading that study herding and contrarianism, however, usually do not allow traders to choose when to trade or to trade more than once. We present a large-scale experiment to explore these features within a tightly controlled laboratory environment. Herding and contrarianism are more pronounced than in comparable studies that do not allow traders to time their decisions. Traders with extreme information tend to trade earliest, followed by those with information conducive to contrarianism, while those with the theoretical potential to herd delay the most. A sizeable fraction of trades is clustered in time

Crash dieting: The effects of eating and drinking on driving performance

Previous research suggests that compared to mobile phone use, eating and drinking while driving is more common and is seen as lower risk by drivers. Nevertheless, snacking at the wheel can affect vehicle control to a similar extent as using a hands-free phone, and is actually a causal factor in more crashes. So far, though, there has not been a controlled empirical study of this problem. In an effort to fill this gap in the literature, we used the Brunel University Driving Simulator to test participants on a typical urban scenario. At designated points on the drive, which coincided with instructions to eat or drink, a critical incident was simulated by programming a pedestrian to walk in front of the car. Whilst the driving performance variables measured were relatively unaffected by eating and drinking, perceived driver workload was significantly higher and there were more crashes in the critical incident when compared to driving normally. Despite some methodological limitations of the study, when taken together with previous research, the evidence suggests that the physical demands of eating and drinking while driving can increase the risk of a crash

Rolofylline, an adenosine A1−receptor antagonist, in acute heart failure

Background: Worsening renal function, which is associated with adverse outcomes, often develops in patients with acute heart failure. Experimental and clinical studies suggest that counterregulatory responses mediated by adenosine may be involved. We tested the hypothesis that the use of rolofylline, an adenosine A1−receptor antagonist, would improve dyspnea, reduce the risk of worsening renal function, and lead to a more favorable clinical course in patients with acute heart failure. Methods: We conducted a multicenter, double-blind, placebo-controlled trial involving patients hospitalized for acute heart failure with impaired renal function. Within 24 hours after presentation, 2033 patients were randomly assigned, in a 2:1 ratio, to receive daily intravenous rolofylline (30 mg) or placebo for up to 3 days. The primary end point was treatment success, treatment failure, or no change in the patient’s clinical condition; this end point was defined according to survival, heart-failure status, and changes in renal function. Secondary end points were the post-treatment development of persistent renal impairment and the 60-day rate of death or readmission for cardiovascular or renal causes. Results: Rolofylline, as compared with placebo, did not provide a benefit with respect to the primary end point (odds ratio, 0.92; 95% confidence interval, 0.78 to 1.09; P=0.35). Persistent renal impairment developed in 15.0% of patients in the rolofylline group and in 13.7% of patients in the placebo group (P=0.44). By 60 days, death or readmission for cardiovascular or renal causes had occurred in similar proportions of patients assigned to rolofylline and placebo (30.7% and 31.9%, respectively; P=0.86). Adverse-event rates were similar overall; however, only patients in the rolofylline group had seizures, a known potential adverse effect of A1-receptor antagonists. Conclusions: Rolofylline did not have a favorable effect with respect to the primary clinical composite end point, nor did it improve renal function or 60-day outcomes. It does not show promise in the treatment of acute heart failure with renal dysfunction. (Funded by NovaCardia, a subsidiary of Merck; ClinicalTrials.gov numbers, NCT00328692 and NCT00354458.

A combined clinical and biomarker approach to predict diuretic response in acute heart failure

Background: Poor diuretic response in acute heart failure is related to poor clinical outcome. The underlying mechanisms and pathophysiology behind diuretic resistance are incompletely understood. We evaluated a combined approach using clinical characteristics and biomarkers to predict diuretic response in acute heart failure (AHF). Methods and results: We investigated explanatory and predictive models for diuretic response—weight loss at day 4 per 40 mg of furosemide—in 974 patients with AHF included in the PROTECT trial. Biomarkers, addressing multiple pathophysiological pathways, were determined at baseline and after 24 h. An explanatory baseline biomarker model of a poor diuretic response included low potassium, chloride, hemoglobin, myeloperoxidase, and high blood urea nitrogen, albumin, triglycerides, ST2 and neutrophil gelatinase-associated lipocalin (r2 = 0.086). Diuretic response after 24 h (early diuretic response) was a strong predictor of diuretic response (β = 0.467, P < 0.001; r2 = 0.523). Addition of diuretic response after 24 h to biomarkers and clinical characteristics significantly improved the predictive model (r2 = 0.586, P < 0.001). Conclusions: Biomarkers indicate that diuretic unresponsiveness is associated with an atherosclerotic profile with abnormal renal function and electrolytes. However, predicting diuretic response is difficult and biomarkers have limited additive value. Patients at risk of poor diuretic response can be identified by measuring early diuretic response after 24 h

Drivers of extreme wind events in Mexico for wind power applications

In this study, we use a k-mean clustering approach to investigate the weather patterns responsible for extreme wind speed events throughout Mexico using 40 years of the ERA-5 atmospheric reanalysis. Generally, we find a large geographical split between the weather patterns that generate the strongest winds across the country. The highest wind power production periods therefore occur at different times in different regions across the country. In the South, these are associated with cold surge events, where an anticyclone is present in the Gulf of Mexico resulting in a strong Northerly flow across the Isthmus of Tehuantepec. In the North-East, Easterly trade winds are responsible for the strongest wind events, whereas in the North-West, it is the proximity of the North Pacific High. However, the weakest winds and lowest power production periods occur at the same times for all stations with the exception of Baja California Sur, meaning that low wind power production may be unavoidable at these times. The El Niño Southern Oscillation is found to influence wind speeds at some locations across Mexico at sub-seasonal time-scales. We report that statistically stronger wind speeds are observed during the Summer during El Niño months than during La Niña months for both sites in Chiapas and Oaxaca

The SWAP Filter: A Simple Azimuthally Varying Radial Filter for Wide-Field EUV Solar Images

We present the SWAP Filter: an azimuthally varying, radial normalizing filter specifically developed for EUV images of the solar corona, named for the Sun Watcher with Active Pixels and Image Processing (SWAP) instrument on the Project for On-Board Autonomy 2 spacecraft. We discuss the origins of our technique, its implementation and key user-configurable parameters, and highlight its effects on data via a series of examples. We discuss the filter's strengths in a data environment in which wide field-of-view observations that specifically target the low signal-to-noise middle corona are newly available and expected to grow in the coming years.Comment: Contact D. B. Seaton for animations referenced in figure caption

A network analysis to compare biomarker profiles in patients with and without diabetes mellitus in acute heart failure

Aims: It is unclear whether distinct pathophysiological processes are present among patients with acute heart failure (AHF), with and without diabetes. Network analysis of biomarkers may identify correlative associations that reflect different pathophysiological pathways. Methods and results: We analysed a panel of 48 circulating biomarkers measured within 24 h of admission for AHF in a subset of patients enrolled in the PROTECT trial. In patients with and without diabetes, we performed a network analysis to identify correlations between measured biomarkers. Compared with patients without diabetes (n = 1111), those with diabetes (n = 922) had a higher prevalence of ischaemic heart disease and traditional coronary risk factors. After multivariable adjustment, patients with and without diabetes had significantly different levels of biomarkers across a spectrum of pathophysiological domains, including inflammation (TNFR-1a, periostin), cardiomyocyte stretch (BNP), angiogenesis (VEGFR, angiogenin), and renal function (NGAL, KIM-1) (adjusted P-value <0.05). Among patients with diabetes, network analysis revealed that periostin strongly clustered with C-reactive protein and interleukin-6. Furthermore, renal markers (creatinine and NGAL) closely associated with potassium and glucose. These findings were not seen among patients without diabetes. Conclusion: Patients with AHF and diabetes, compared with those without diabetes, have distinct biomarker profiles. Network analysis suggests that cardiac remodelling, inflammation, and fibrosis are closely associated with each other in patients with diabetes. Furthermore, potassium levels may be sensitive to changes in renal function as reflected by the strong renal–potassium–glucose correlation. These findings were not seen among patients without diabetes and may suggest distinct pathophysiological processes among AHF patients with diabetes