Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression

The probabilistic forecasting of electricity loads is crucial for effective scheduling and decision-making in volatile and competitive energy markets with ever-growing uncertainties. We propose a novel approach to construct the probabilistic predictors for curves (PPC) of electricity loads, which leads to properly defined predictive bands and quantiles in the context of curve-to-curve regression. The proposed predictive model provides not only accurate hourly load point forecasts, but also generates well-defined probabilistic bands and day-long trajectories of the loads at any probability level, pre-specified by managers. We also define the predictive quantile curves that exhibit future loads in extreme scenarios and provide insights for hedging risks in the supply management of electricity. When applied to the day-ahead forecasting for French half-hourly electricity loads, the PPC outperform several state-of-the-art time series and machine learning predictive methods with more accurate point forecasts (mean absolute percentage error of 1.10%, compared to 1.36%–4.88% for the alternatives), a higher coverage rate of the day-long trajectory of loads (coverage rate of 95.5%, against 31.9%–90.7% for the alternatives) and a narrower average length of the predictive bands. In a series of numerical experiments, the PPC further demonstrate robust performance and general applicability, achieving accurate coverage probabilities under a variety of data-generating mechanisms

4-Meth­oxy-3-nitro­biphen­yl

In the title compound, C13H11NO3, the dihedral angle between the two benzene rings is 36.69 (2)° and the nitro and methy­oxy groups are oriented at 29.12 (14) and 2.14 (12)° with respect to the benzene ring to which they are bonded

Effect of coal mining on soil nitrogen distribution in semi-arid mining area of western China

Soil nitrogen is a key indicator of soil quality and plays a significant role for plant growth. Therefore, it is very important to study soil nitrogen distribution, especially in semi-arid area of western China. Fewer scholars paid attention to the effect on soil nitrogen due to coal mining in semi-arid mining areas of western China. In this paper, soil samples of different locations were tested in both the loess region and the aeolian sand region in the Daliuta mining area in Shaanxi Province. The impacts of mining subsidence on soil nitrogen were investigated. The soil nitrogen distributions between the loess region and the aeolian sand region were compared, and used the principal component analysis method to evaluate soil quality in semi-arid mining area. The results showed that the comprehensive score of soil quality in the loess region was as follows: the internal pulling stress zone (NLS) > the external pulling stress zone (WLS) > the compressive stress zone (YS) > the neutral zone (ZX). The content of soil total nitrogen in YS-zone was the lowest in the loess region. The loss of nitrogen increased with time in the mining area, in which the total nitrogen loss at the depth of 0−15 cm was 0.27 g/kg, and the alkaline nitrogen loss at the depth of 0−15 cm was 1.08 mg/kg. In the aeolian sand region, the comprehensive score of soil quality was as follows: WLS > FC (the non-mining zone) > ZX > NLS > YS. The amount of soil nitrogen content in the loess region was larger than that in the aeolian sand region. It was found that for the loess region, the relationship between total nitrogen and nitrate nitrogen showed a significant positive correlation. It was also a significant positive correlation between ammonium nitrogen and alkaline nitrogen. In the aeolian sand region, there was a significant positive correlation between total nitrogen and alkaline nitrogen. There was no significant correlation among other nitrogen forms

The analysis of candidate genes and loci involved with carotenoid metabolism in cassava (Manihot esculenta Crantz) using SLAF-seq

Carotenoids in cassava storage roots play important roles in benefiting people’s health in the tropics because they provide essential nutrients and antioxidants. Although the related genes and loci associated with carotenoid metabolism in many species are well reported, in cassava they are poorly understood. In the present study, GWAS base on SLAF-seq was used in detecting the related genes and loci correlated to carotenoid contents in 98 accessions from a cassava F1 mapping population. The 98 accessions were divided into four subgroups. On the basis of general linear and compressed linear models, 144 genes were detected by selective sweep analysis, and 84 SNPs and 694 genes were detected by association mapping, in which Manes.04G164700 (XanDH) and Manes.11G105300 (AAO) were probably involved in the downstream pathway of carotenoid metabolism, and their expressions in six cassava genotypes were confirmed. Our results will be useful in yellow-root cassava variety improvement and provide the most effective and sustainable approach to maximize the nutritional and health benefits of carotenoid to a large number of populations

3,9-Dimethyl-3,9-bis­(4-nitro­phen­yl)-2,4,8,10-tetra­oxaspiro­[5.5]undeca­ne

In the title compound, C21H22N2O8, both of the nonplanar six-membered heterocycles adopt chair conformations. The dihedral angle between the terminal benzene rings is 58.22 (11)°. Weak inter­molecular C—H⋯O inter­actions are observed in the crystal structure

3,9-Di-1-naphthyl-2,4,8,10-tetra­oxa­spiro­[5.5]undeca­ne

In the title compound, C27H24O4, the 1,3-dioxane rings have chair conformations. The mol­ecule has non-crystallographic twofold rotation symmetry. The dihedral angle between the naphthalene ring systems is 17.96(4)° In the crystal structure, weak inter­molecular C—H⋯π inter­actions contribute to the crystal packing