Renewable energy regulation and structural breaks: An empirical analysis of Spanish electricity price volatility

International experience proves that electricity prices have undergone major changes in volatility since the entry of green technologies. The intermittency of renewable sources is one of the reasons for these changes, as it leads to higher volatility in periods of higher participation by renewables. We argue that the development of the regulatory system promoting renewable electricity also plays a crucial role. We raise a question that deserves attention: could an incentive scheme induce higher share of renewables and lower volatility simultaneously? In this paper, we conduct an empirical analysis with Spanish data. We analyze possible ensuing structural changes in Spanish electricity spot price volatility from January 2002 to December 2017. We identify two structural breaks linked to important measures related to renewable electricity: (i) the abolishment of the feed-in tariff scheme; and (ii) the establishment of a more market-oriented regulation based on investment and operating costs. We conclude that stable regulatory policies reduce volatility even though the presence of renewable sources is greater. Furthermore, market-based policy measures achieve lower volatility, encouraging good integration of intermittent renewable electricity. © 2020 Elsevier B.V.Financial support from Ministerio de Economa y Competitividad and Fondo Europeo de Desarrollo Regional under research grant ECO2015-64467-R (MINECO/FEDER) and from Dpto. de Educación, Universidades e Investigación del Gobierno Vasco under research grant IT1336-19 is acknowledged. Cristina Pizarro-Irizar also acknowledges financial support from Ministerio de Economa y Competitividad under research grant ECO2015-68023 , Ministerio de Ciencia, Innovación y Universidades under research grant RTI2018-093352-B-I00 , Gobierno Vasco through the BERC 2018-2021 program and by Ministerio de Economa y Competitividad MINECO through BC3 Maria de Maeztu excellence accreditation MDM-2017-0714 . All the authors are grateful for the valuable comments made by participants in the 41st International Conference of the International Association for Energy Economics and the 14th Conference of the Spanish Association for Energy Economics

Comparación de dos métodos de fraccionamiento físico de la materia orgánica del suelo

115-121Regression analysis was used to compare particulate organic carbon (COP) and light carbon (Cs) concentrations obtained by size (fraction greather than 53 um) and density fractionation (liquor density = 2 g cm-3) methods, respectively. The soil samples were taken from a long-term experiment located at the EEA-INTA Pergamino comparing four cropping sequences and two tillage systems. Both methods were linearly and positively correlated to depths of 0-5 and 5-10 cm and the y-intercept did not differ from zero, indicating that both methods resulted in a similar estimate for labile C. As the slopes did not different from unity, the differences between the two methods remained constant throughout all the labile range measured. There was no correlation for a depth of 10-20 cm, and Cs concentrations were higher and less variable than those of COP. The liquor density used might explain the obtention of similar or greater amounts of Cs than of COP because of the important contribution of the organomineral complex to the light fraction

Framework for collaborative intelligence in forecasting day-ahead electricity price

Electricity price forecasting in wholesale markets is an essential asset for deciding bidding strategies and operational schedules. The decision making process is limited if no understanding is given on how and why such electricity price points have been forecast. The present article proposes a novel framework that promotes human–machine collaboration in forecasting day-ahead electricity price in wholesale markets. The framework is based on a new model architecture that uses a plethora of statistical and machine learning models, a wide range of exogenous features, a combination of several time series decomposition methods and a collection of time series characteristics based on signal processing and time series analysis methods. The model architecture is supported by open-source automated machine learning platforms that provide a baseline reference used for comparison purposes. The objective of the framework is not only to provide forecasts, but to promote a human-in-the-loop approach by providing a data story based on a collection of model-agnostic methods aimed at interpreting the mechanisms and behavior of the new model architecture and its predictions. The framework has been applied to the Spanish wholesale market. The forecasting results show good accuracy on mean absolute error (1.859, 95% HDI [0.575, 3.924] EUR (MWh)−1) and mean absolute scaled error (0.378, 95% HDI [0.091, 0.934]). Moreover, the framework demonstrates its human-centric capabilities by providing graphical and numeric explanations that augments understanding on the model and its electricity price point forecasts

Assessing soil P fractions changes with long-term phosphorus fertilization related to crop yield of soybean and maize

Long-term P Fertiliser application increases soil phosphorus (P) labile fractions, which can be associated with crop P uptake and grain yield and are useful to improve fertilizer recommendations. Research aims were to evaluate in long-term experiments with different P Fertiliser application in a Mollisol and a Vertisol: (a) the changes of soil P fractions and (b) the relationship between soil P fractions with long-term P Fertiliser application, with accumulated apparent P budget, grain P, total P uptake, soybean (Glycine max L.Merr.) and maize (Zea mays L.) grain yield. Soil P fractions were measured after 1 and 9 year since the beginning of the long-term experiments. Experiments included an initial Fertiliser application rate of 200 kg P ha−1 and annual P Fertiliser application rate of 36 kg P ha−1. Bray1-P, total, organic, and inorganic P in fine (53 μm) (CF) soil fractions, and in NaHCO3 extract were measured. Initial P Fertiliser application increased inorganic and total P fractions. However, Bray1-P, total P in NaHCO3 extract and in the CF were the fractions that most increased with continuous long-term P Fertiliser application in both sites. In the Mollisol, maize grain yield was unrelated to long-term P Fertiliser application. In the Vertisol, total P in NaHCO3 extract, and total and organic P in the CF were more closely related to soybean grain yield than Bray1-P. We proposed soil P indices of labile inorganic and organic P that showed close relationships with soybean grain yield and may be useful to improve the diagnosis of P soil fertility.Fil: Appelhans, Stefania Carolina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias. Departamento de Producción Vegetal; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Paraná; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Barbagelata, Pedro Aníbal. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias. Departamento de Producción Vegetal; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Paraná; ArgentinaFil: Melchiori, Ricardo José Miguel. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Paraná; ArgentinaFil: Gutiérrez Boem, Flavio Hernán. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Ingeniería Agrícola y Uso de la Tierra. Cátedra de Fertilidad y Fertilizantes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentin

Adolescent Verbal Memory as a Psychosis Endophenotype: A Genome-Wide Association Study in an Ancestrally Diverse Sample

Verbal memory impairment is one of the most prominent cognitive deficits in psychosis. However, few studies have investigated the genetic basis of verbal memory in a neurodevelopmental context, and most genome-wide association studies (GWASs) have been conducted in European-ancestry populations. We conducted a GWAS on verbal memory in a maximum of 11,017 participants aged 8.9 to 11.1 years in the Adolescent Brain Cognitive Development Study®, recruited from a diverse population in the United States. Verbal memory was assessed by the Rey Auditory Verbal Learning Test, which included three measures of verbal memory: immediate recall, short-delay recall, and long-delay recall. We adopted a mixed-model approach to perform a joint GWAS of all participants, adjusting for ancestral background and familial relatedness. The inclusion of participants from all ancestries increased the power of the GWAS. Two novel genome-wide significant associations were found for short-delay and long-delay recall verbal memory. In particular, one locus (rs9896243) associated with long-delay recall was mapped to the NSF (N-Ethylmaleimide Sensitive Factor, Vesicle Fusing ATPase) gene, indicating the role of membrane fusion in adolescent verbal memory. Based on the GWAS in the European subset, we estimated the SNP-heritability to be 15% to 29% for the three verbal memory traits. We found that verbal memory was genetically correlated with schizophrenia, providing further evidence supporting verbal memory as an endophenotype for psychosis

Small Ultrasound-Based Corrosion Sensor for Intraday Corrosion Rate Estimation

The conventional way of studying corrosion in marine environments is by installing corrosion coupons. Instead, this paper presents an experimental field study using an unattended corrosion sensor developed on the basis of ultrasound (US) technology to assess the thickness loss caused by general atmospheric corrosion on land close to the sea (coastal region). The system described here uses FPGA, low-power microcontroller, analog front-end devices in the sensor node, and a Beaglebone black wireless board for posting data to a server. The overall system is small, operates at low power, and was deployed at Gran Canaria to detect the thickness loss of an S355 steel sample and consequently estimate the corrosion rate. This experiment aims to demonstrate the system's viability in marine environments and its potential to monitor corrosion in offshore wind turbines. In a day, the system takes four sets of measurements in 6 hour intervals, and each set consists of 5 consecutive measurements. Over the course of 5 months, the proposed experiment allowed for us to continuously monitor the corrosion rate in an equivalent corrosion process to an average thickness loss rate of 0.134 mm/year

Associations of common mental disorder with alcohol use in the adult general population: a systematic review and meta-analysis

Background and Aims: Research has shown that alcohol use and common mental disorders (CMDs) co-occur; however, little is known about how the global prevalence of alcohol use compares across different CMDs. We aimed to (i) report global associations of alcohol use (alcohol use disorder (AUD), binge drinking and consumption) comparing those with and without a CMD, (ii) examine how this differed among those with and without specific types of CMDs and (iii) examine how results may differ by study characteristics. Methods: We used a systematic review and meta-analysis. Cross-sectional, cohort, prospective, longitudinal and case–control studies reporting the prevalence of alcohol use among those with and without a CMD in the general population were identified using PsycINFO, MEDLINE, PsyARTICLES, PubMed, Scopus and Web of Science until March 2020. Depression, anxiety and phobia were included as a CMD. Studies were included if they used a standardized measure of alcohol use. A random-effects meta-analysis was conducted to generate pooled prevalence and associations of AUD with CMD with 95% confidence intervals (CI). A narrative review is provided for binge drinking and alcohol consumption. Results: A total of 512 full-texts were reviewed, 51 included in our final review and 17 in our meta-analyses (n = 382 201). Individuals with a CMD had a twofold increase in the odds of reporting an AUD [odds ratio (OR) = 2.02, 95% CI = 1.72–2.36]. The odds of having an AUD were similar when stratified by the type of CMD (mood disorder: OR = 2.00, 95% CI = 1.62–2.47; anxiety/phobic disorder: OR = 1.94, 95% CI = 1.35–2.78). An analysis of study characteristics did not reveal any clear explanations for between-study heterogeneity (I2 > 80%). There were no clear patterns for associations between having a CMD and binge drinking or alcohol consumption, respectively. Conclusions: People with common mental disorders (depression, anxiety, phobia) are twice as likely to report an alcohol use disorder than people without common mental disorders

The effect of CYP2D6 variation on antipsychotic-induced hyperprolactinaemia: a systematic review and meta-analysis

Hyperprolactinemia is a known adverse drug reaction to antipsychotic treatment. Antipsychotic blood levels are influenced by cytochrome P450 enzymes, primarily CYP2D6. Variation in CYP450 genes may affect the risk of antipsychotic-induced hyperprolactinemia. We undertook a systematic review and meta-analysis to assess whether CYP2D6 functional genetic variants are associated with antipsychotic-induced hyperprolactinemia. The systematic review identified 16 relevant papers, seven of which were suitable for the meta-analysis (n = 303 participants including 134 extreme metabolisers). Participants were classified into four phenotype groups as poor, intermediate, extensive, and ultra-rapid metabolisers. A random effects meta-analysis was used and Cohen’s d calculated as the effect size for each primary study. We found no significant differences in prolactin levels between CYP2D6 metabolic groups. Current evidence does not support using CYP2D6 genotyping to reduce risk of antipsychotic-induced hyperprolactinemia. However, statistical power is limited. Future studies with larger samples and including a range of prolactin-elevating drugs are needed