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Rainwater samples are derived from three precipitation collectors installed at different altitudes (monitoring period 2010-2019; n = 57). Surface water samples were collected at three sampling sites located along the Del Azul Creek and six wetlands (monitoring period 2018-2019; n = 12). Groundwater samples were collected from 17 piezometers with depths ranging between 3 and 10 m, and from 12 piezometers of 30 m depth, all located throughout the entire basin (monitoring period 2018-2019; n = 115). Sampling campaigns were performed during the austral dry (summer) and wet (spring) seasons. This dataset provides useful information to understand a) how water moves from recharge to discharge areas, b) how water acquires salinity, and c) how particular solutes of concern, such as arsenic and fluoride, are distributed in space and time across in an extensive plain.Non-invasive foetal electrocardiography (fECG) can be obtained at different gestational ages by means of surface electrodes applied on the maternal abdomen. The signal-to-noise ratio (SNR) of the fECG is usually low, due to the small size of the foetal heart, the foetal-maternal compartment, the maternal physiological interferences and the instrumental noise. Even after powerful fECG extraction algorithms, a post-processing step could be required to improve the SNR of the fECG signal. In order to support the researchers in the field, this work presents an annotated dataset of real and synthetic signals, which was used for the study "Wavelet Denoising as a Post-Processing Enhancement Method for Non-Invasive Foetal Electrocardiography" [1]. selleck compound Specifically, 21 15 s-long fECG, dual-channel signals obtained by multi-reference adaptive filtering from real electrophysiological recordings were included. The annotation of the foetal R peaks by an expert cardiologist was also provided. Recordings were performed on 17 voluntary pregnant women between the 21st and the 27th week of gestation. The raw recordings were also included for the researchers interested in applying a different fECG extraction algorithm. Moreover, 40 10 s-long synthetic non-invasive fECG were provided, simulating the electrode placement of one of the abdominal leads used for the real dataset. The annotation of the foetal R peaks was also provided, as generated by the FECGSYN tool used for the signals' creation. Clean fECG signals were also included for the computation of indexes of signal morphology preservation. All the signals are sampled at 2048 Hz. The data provided in this work can be used as a benchmark for fECG post-processing techniques but can also be used as raw signals for researchers interested in foetal QRS detection algorithms and fECG extraction methods.A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expression analysis. Genes not present in genomes of all three species were filtered out. The resulting dataset included 591,084 chemical-gene interaction. All chemical compounds in the database were annotated for their major uses. For every gene in the database number of chemical-gene interactions was calculated and used as a metric of gene sensitivity to a variety of chemical exposures. The lists of genes with corresponding numbers of chemical-gene interactions were used in gene-set enrichment analysis (GSEA) to identify potential sensitivity to chemical exposures of molecular pathways in Hallmark, KEGG and Reactome collections. Thus, data presented here represent unbiased and searchable datasets of sensitivity of genes and molecular pathways to a broad range of chemical exposures. As such the data can be used for a diverse range of toxicological and regulatory applications. Approach for the identification of molecular mechanisms sensitive to chemical exposures may inform regulatory toxicology about best toxicity testing strategies. Analysis of sensitivity of genes and molecular pathways to chemical exposures based on these datasets was published in Chemosphere (Suvorov et al., 2021) [1].Metal(loid) pollution in aquatic ecosystems has become a cause for concern, particularly in areas where communities depend on services from these systems for their livelihood. This dataset presents the metal(loi) concentrations recorded in the water column, bottom sediment, and tissues of Oreochromis mossambicus and Labeo rosae from Flag Boshielo Dam, an impoundment in one of the most polluted river systems in Southern Africa, the Olifants River. The concentrations of metal(loid)s were measured using inductively coupled plasma-optical emission spectrophotometry (ICP-OES; Perkin Elmer, Optima 2100DV). The data generated attest that in aquatic ecosystems, metal(loid)s do not remain in suspension in the water column, but sink down to the bottom sediment where they accumulate or get taken up by receptor organisms such as fish. It further confirm that there is a clear separation on the extent to which metal(loid)s are accumulating in different tissues and liver mostly accumulate higher concentration followed by gills and muscle, respectively. These data can be useful to guide future studies aiming to understand the dynamics, pathways and fate of metal(loid)s in relation to water, sediment and fish tissues. These data can also be used for decision making in relation to the establishment of freshwater fisheries in dams receiving metal(loid)s from different land use activities.The leaf inclination angle distribution is an important parameter in models useful for understanding forest canopy processes of photosynthesis, evapotranspiration, radiation transmission, and spectral reflectance. Yet, despite the strong sensitivity of many of these models to variability in leaf inclination angle distribution, relatively few measurements have been reported for different tree species in literature and databases such as TRY, and various assumptions about leaf inclination angle distribution are often made by modellers. Here we provide a dataset of leaf inclination angles for 71 different Australia-native Eucalyptus species measured in 13 botanical gardens around the world. Leaf inclination angles were measured using a leveled digital camera approach. The leaf angle measurements were used to estimate corresponding Beta distribution parameters and to assign the appropriate classic type of leaf inclination angle distribution. The data can be used to parameterize leaf angle distributions in e.g., physically-based reflectance models, land surface models, and regional carbon cycle models.