Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries

Electricity systems are becoming increasingly exposed to weather. The need for high-quality meteorological forecasts for managing risk across all timescales has therefore never been greater. This paper seeks to extend the uptake of meteorological data in the power systems modelling community to include probabilistic meteorological forecasts at sub-seasonal lead times. Such forecasts are growing in skill and are receiving considerable attention in power system risk management and energy trading. Despite this interest, these forecasts are rarely evaluated in power system terms, and technical barriers frequently prohibit use by non-meteorological specialists.This paper therefore presents data produced through a new EU climate services programme Subseasonal-to-seasonal forecasting for Energy (S2S4E). The data correspond to a suite of well-documented, easy-to-use, self-consistent daily and nationally aggregated time series for wind power, solar power and electricity demand across 28 European countries. The data are accessible from https://doi.org/10.17864/1947.275 (Gonzalez et al., 2020). The data include a set of daily ensemble reforecasts from two leading forecast systems spanning 20 years (ECMWF, an 11-member ensemble, with twice-weekly starts for 1996–2016, totalling 22 880 forecasts) and 11 years (NCEP, a 12-member lagged-ensemble, constructed to match the start dates from the ECMWF forecast from 1999–2010, totalling 14 976 forecasts). The reforecasts contain multiple plausible realisations of daily weather and power data for up to 6 weeks in the future.To the authors’ knowledge, this is the first time a fully calibrated and post-processed daily power system forecast set has been published, and this is the primary purpose of this paper. A brief review of forecast skill in each of the individual primary power system properties and a composite property is presented, focusing on the winter season. The forecast systems contain additional skill over climatological expectation for weekly-average forecasts at extended lead times, though this skill depends on the nature of the forecast metric considered. This highlights the need for greater collaboration between the energy and meteorological research communities to develop applications, and it is hoped that publishing these data and tools will support this

The nature of weather and climate impacts in the energy sector

The power sector’s meteorological information needs are diverse and cover many different distinct applications and users. Recognising this diversity, it is important to understand the general nature of how weather and climate influence the energy sector and the implications they have for quantitative impact modelling. Using conceptual examples and illustrations from recent research, this chapter argues that the traditional ‘transfer function’ approach that is common to many industrial applications of weather and climate science—whereby weather can be directly mapped to an energy impact—is inadequate for many important power system applications (such as price forecasting and system operations and planning). The chapter concludes by arguing that a deeper understanding of how meteorological impacts in the energy sector are modelled is required

Scaling leaf respiration with nitrogen and phosphorus in tropical forests across two continents

Leaf dark respiration (Rdark) represents an important component controlling the carbon balance in tropical forests. Here, we test how nitrogen (N) and phosphorus (P) affect Rdark and its relationship with photosynthesis using three widely separated tropical forests which differ in soil fertility. Rdark was measured on 431 rainforest canopy trees, from 182 species, in French Guiana, Peru and Australia. The variation in Rdark was examined in relation to leaf N and P content, leaf structure and maximum photosynthetic rates at ambient and saturating atmospheric CO2 concentration. We found that the site with the lowest fertility (French Guiana) exhibited greater rates of Rdark per unit leaf N, P and photosynthesis. The data from Australia, for which there were no phylogenetic overlaps with the samples from the South American sites, yielded the most distinct relationships of Rdark with the measured leaf traits. Our data indicate that no single universal scaling relationship accounts for variation in Rdark across this large biogeographical space. Variability between sites in the absolute rates of Rdark and the Rdark : photosynthesis ratio were driven by variations in N- and P-use efficiency, which were related to both taxonomic and environmental variability

Cannabis dampens the effects of music in brain regions sensitive to reward and emotion

Background: Despite the current shift towards permissive cannabis policies, few studies have investigated the pleasurable effects users seek. Here we investigate the effects of cannabis on listening to music - a rewarding activity that frequently occurs in the context of recreational cannabis use. We additionally tested how these effects are influenced by cannabidiol (CBD), which may offset cannabis-related harms. Methods: Across three sessions, sixteen cannabis users inhaled cannabis with CBD, cannabis without CBD, and placebo. We compared their response to music relative to control excerpts of scrambled sound during functional Magnetic Resonance Imaging (fMRI) within regions identified in a meta-analysis of music-evoked reward and emotion. All results were False Discovery Rate corrected (p<0.05). Results: Compared to placebo, cannabis without CBD dampened response to music in bilateral auditory cortex (right: p=0.005, left: p=0.008), right hippocampus/parahippocampal gyrus (p=0.025), right amygdala (p=0.025) and right ventral striatum (p=0.033). Across all sessions, the effects of music in this ventral striatal region correlated with pleasure ratings (p=0.002) and increased functional connectivity with auditory cortex (right: p=0.000, left: p=0.000), supporting its involvement in music reward. Functional connectivity between right ventral striatum and auditory cortex was increased by CBD (right: p=0.003, left: p=0.030), and cannabis with CBD did not differ from placebo on any fMRI measures. Both types of cannabis increased ratings of wanting to listen to music (p<0.002) and enhanced sound perception (p<0.001). Conclusions: Cannabis dampens the effects of music in brain regions sensitive to reward and emotion. These effects were offset by a key cannabis constituent, cannabidol

The Effects of Acute Δ⁹-Tetrahydrocannabinol on Striatal Glutamatergic Function: A Proton Magnetic Resonance Spectroscopy Study

Background: Cannabis and its main psychoactive component, Δ9-tetrahydrocannabinol (THC), can elicit transient psychotic symptoms. A key candidate biological mechanism of how THC induces psychotic symptoms is the modulation of glutamate in the brain. We sought to investigate the effects of acute THC administration on striatal glutamate levels and its relationship to the induction of psychotic symptoms. Methods: We used proton magnetic resonance spectroscopy to measure glutamate levels in the striatum in 20 healthy participants after THC (15 mg, oral) and matched placebo administration in a randomized, double-blind, placebo-controlled design. Psychotic symptoms were measured using the Psychotomimetic States Inventory. Results: We found that THC administration did not significantly change glutamate (glutamate plus glutamine relative to creatine) concentration in the striatum (p = .58; scaled Jeffreys-Zellner-Siow Bayes factor = 4.29). THC increased psychotic symptoms, but the severity of these symptoms was not correlated with striatal glutamate levels. Conclusions: These findings suggest that oral administration of 15 mg of THC does not result in altered striatal glutamate levels. Further work is needed to clarify the effects of THC on striatal glutamate

Acute and chronic effects of cannabinoids on effort-related decision-making and reward learning: an evaluation of the cannabis 'amotivational' hypotheses

Rationale: Anecdotally, both acute and chronic cannabis use have been associated with apathy, amotivation, and other reward processing deficits. To date, empirical support for these effects is limited, and no previous studies have assessed both acute effects of Δ-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), as well as associations with cannabis dependence. Objectives: The objectives of this study were (1) to examine acute effects of cannabis with CBD (Cann + CBD) and without CBD (Cann-CBD) on effort-related decision-making and (2) to examine associations between cannabis dependence, effort-related decision-making and reward learning. Methods: In study 1, 17 participants each received three acute vaporized treatments, namely Cann-CBD (8 mg THC), Cann + CBD (8 mg THC + 10 mg CBD) and matched placebo, followed by a 50 % dose top-up 1.5 h later, and completed the Effort Expenditure for Rewards Task (EEfRT). In study 2, 20 cannabis-dependent participants were compared with 20 non-dependent, drug-using control participants on the EEfRT and the Probabilistic Reward Task (PRT) in a non-intoxicated state. Results: Cann-CBD reduced the likelihood of high-effort choices relative to placebo (p = 0.042) and increased sensitivity to expected value compared to both placebo (p = 0.014) and Cann + CBD (p = 0.006). The cannabis-dependent and control groups did not differ on the EEfRT. However, the cannabis-dependent group exhibited a weaker response bias than the control group on the PRT (p = 0.007). Conclusions: Cannabis acutely induced a transient amotivational state and CBD influenced the effects of THC on expected value. In contrast, cannabis dependence was associated with preserved motivation alongside impaired reward learning, although confounding factors, including depression, cannot be disregarded. This is the first well powered, fully controlled study to objectively demonstrate the acute amotivational effects of THC

On the probability of cost-effectiveness using data from randomized clinical trials

BACKGROUND: Acceptability curves have been proposed for quantifying the probability that a treatment under investigation in a clinical trial is cost-effective. Various definitions and estimation methods have been proposed. Loosely speaking, all the definitions, Bayesian or otherwise, relate to the probability that the treatment under consideration is cost-effective as a function of the value placed on a unit of effectiveness. These definitions are, in fact, expressions of the certainty with which the current evidence would lead us to believe that the treatment under consideration is cost-effective, and are dependent on the amount of evidence (i.e. sample size). METHODS: An alternative for quantifying the probability that the treatment under consideration is cost-effective, which is independent of sample size, is proposed. RESULTS: Non-parametric methods are given for point and interval estimation. In addition, these methods provide a non-parametric estimator and confidence interval for the incremental cost-effectiveness ratio. An example is provided. CONCLUSIONS: The proposed parameter for quantifying the probability that a new therapy is cost-effective is superior to the acceptability curve because it is not sample size dependent and because it can be interpreted as the proportion of patients who would benefit if given the new therapy. Non-parametric methods are used to estimate the parameter and its variance, providing the appropriate confidence intervals and test of hypothesis

Spatial and topological organization of DNA chains induced by gene co-localization

Transcriptional activity has been shown to relate to the organization of chromosomes in the eukaryotic nucleus and in the bacterial nucleoid. In particular, highly transcribed genes, RNA polymerases and transcription factors gather into discrete spatial foci called transcription factories. However, the mechanisms underlying the formation of these foci and the resulting topological order of the chromosome remain to be elucidated. Here we consider a thermodynamic framework based on a worm-like chain model of chromosomes where sparse designated sites along the DNA are able to interact whenever they are spatially close-by. This is motivated by recurrent evidence that there exists physical interactions between genes that operate together. Three important results come out of this simple framework. First, the resulting formation of transcription foci can be viewed as a micro-phase separation of the interacting sites from the rest of the DNA. In this respect, a thermodynamic analysis suggests transcription factors to be appropriate candidates for mediating the physical interactions between genes. Next, numerical simulations of the polymer reveal a rich variety of phases that are associated with different topological orderings, each providing a way to increase the local concentrations of the interacting sites. Finally, the numerical results show that both one-dimensional clustering and periodic location of the binding sites along the DNA, which have been observed in several organisms, make the spatial co-localization of multiple families of genes particularly efficient.Comment: Figures and Supplementary Material freely available on http://dx.doi.org/10.1371/journal.pcbi.100067

Neural Correlates of Threat Perception: Neural Equivalence of Conspecific and Heterospecific Mobbing Calls Is Learned

Songbird auditory areas (i.e., CMM and NCM) are preferentially activated to playback of conspecific vocalizations relative to heterospecific and arbitrary noise [1]–[2]. Here, we asked if the neural response to auditory stimulation is not simply preferential for conspecific vocalizations but also for the information conveyed by the vocalization. Black-capped chickadees use their chick-a-dee mobbing call to recruit conspecifics and other avian species to mob perched predators [3]. Mobbing calls produced in response to smaller, higher-threat predators contain more “D” notes compared to those produced in response to larger, lower-threat predators and thus convey the degree of threat of predators [4]. We specifically asked whether the neural response varies with the degree of threat conveyed by the mobbing calls of chickadees and whether the neural response is the same for actual predator calls that correspond to the degree of threat of the chickadee mobbing calls. Our results demonstrate that, as degree of threat increases in conspecific chickadee mobbing calls, there is a corresponding increase in immediate early gene (IEG) expression in telencephalic auditory areas. We also demonstrate that as the degree of threat increases for the heterospecific predator, there is a corresponding increase in IEG expression in the auditory areas. Furthermore, there was no significant difference in the amount IEG expression between conspecific mobbing calls or heterospecific predator calls that were the same degree of threat. In a second experiment, using hand-reared chickadees without predator experience, we found more IEG expression in response to mobbing calls than corresponding predator calls, indicating that degree of threat is learned. Our results demonstrate that degree of threat corresponds to neural activity in the auditory areas and that threat can be conveyed by different species signals and that these signals must be learned