1 Experiments were designed to investigate whether or not oxygen-derived free radicals mediate endothelium-dependent contractions to acetylcholine in the aorta of spontaneously hypertensive rat (SHR). 2 Isometric tension was measured in aortic rings taken from adult male SHR and Wistar-Kyoto rat (WKY) in the presence of N G -nitro-L-arginine. 3 Endothelium-dependent contractions to acetylcholine were signi®cantly greater in rings from SHR compared to WKY. Oxygen-derived free radicals, generated from xanthine plus xanthine oxidase, induced contractions that were larger in aortas from SHR than from WKY. Contractions to acetylcholine and free radicals were abolished by a selective TP-receptor antagonist, S 18886, and a preferential inhibitor of cyclo-oxygenase-1, valeryl salicylate, but not by a preferential inhibitor of cyclo-oxygenase-2, NS-398. 4 Allopurinol, deferoxamine and the combination of superoxide dismutase plus catalase inhibited the contractions to oxygen-derived free radicals but did not signi®cantly aect those to acetylcholine. In contrast, diethyldithiocarbamic acid, an inhibitor of superoxide dismutase, or Tiron, a scavenger of superoxide anion, reduced endothelium-dependent contractions to acetylcholine in aortas from SHR. The eect of these two drugs was additive. 5 In SHR chronically treated with dimethylthiourea endothelium-dependent contractions to acetylcholine were decreased, and reduced further by acute in vitro exposure to deferoxamine or the combination of superoxide dismutase plus catalase. 6 These results suggest that in the SHR aorta acetylcholine-induced endothelium-dependent contractions involve endothelial superoxide anion production and the subsequent dismutation into hydroxyl radicals and/or hydrogen peroxide. The free radicals activate cyclo-oxygenase-1, most likely to produce endoperoxides. Activation of TP-receptors is required to observe endotheliumdependent contractions to acetylcholine or endothelium-independent contractions in response to free radical generation.

Text mining is an emerging topic that advances the review of academic literature. This paper presents a preliminary study on how to review solar irradiance and photovoltaic (PV) power forecasting (both topics combined as "solar forecasting" for short) using text mining, which serves as the first part of a forthcoming series of text mining applications in solar forecasting. This study contains three main contributions: (1) establishing the technological infrastructure (authors, journals & conferences, publications, and organizations) of solar forecasting via the top 1000 papers returned by a Google Scholar search; (2) consolidating the frequently-used abbreviations in solar forecasting by mining the full texts of 249 ScienceDirect publications; and (3) identifying key innovations in recent advances in solar forecasting (e.g., shadow camera, forecast reconciliation). As most of the steps involved in the above analysis are automated via an application programming interface, the presented method can be transferred to other solar engineering topics, or any other scientific domain, by means of changing the search word. The authors acknowledge that text mining, at its present stage, serves as a complement to, but not a replacement of, conventional review papers.

Forecasting has been an essential part of the power and energy industry. Researchers and practitioners have contributed thousands of papers on forecasting electricity demand and prices, and renewable generation (e.g., wind and solar power). This paper offers a brief review of influential energy forecasting papers; summarizes research trends; discusses importance of reproducible research and points out six valuable open data sources; makes recommendations about publishing highquality research papers; and offers an outlook into the future of energy forecasting.