The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology – a computational knowledge structure describing functional characteristics of genes; 2) GO annotations – evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) – mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project.

In this paper we propose an optimization scheme for a selling strategy of an electricity producer who in advance decides on the share of electricity sold on the day-ahead market. The remaining part is sold on the complementary (intraday/balancing) market. To this end, we use probabilistic forecasts of the future selling price distribution. Next, we find an optimal share of electricity sold on the day-ahead market using one of the three objectives: maximization of the overall profit, minimization of the sellers risk, or maximization of the median of portfolio values. Using data from the Polish day-ahead and balancing markets, we show that the assumed objective is achieved, as compared to the naive strategy of selling the whole produced electricity only on the day-ahead market. However, an increase of the profit is associated with a significant increase of the risk.

The aim of the study was to assess the contamination of selected heavy metals in cultivated soils of the Odra river floodplain. The heavy metals Mn, Fe, Cu, Zn, Ni, Cd and Pb were determined in soil samples collected in the autumn of 2020 - after the vegetation period of plants from designated measurement points. Concentrations of the analytes were measured using an atomic absorption spectrometer (F-ASA). A comparison was made between concentrations of heavy metals in soil samples collected from areas flooded in 1997 and from areas flooded as a result of rainfall, snowmelt and winter floods. The results of the studies were compared with the data for soils taken from non-flooded areas. The studies confirmed enrichment of soils subjected to precipitation, snowmelt and winter floods in heavy metals. Also samples taken from two measurement points located on floodplains of the Odra river were characterised by high concentrations of Zn, Cd and Pb.