Chemical data of contaminants in water and sediments from the Doce River four years after the mining dam collapse disaster.

Chemical datasets describing the occurrence of both inorganic and organic contaminants along the Doce River Basin (DRB) could provide a better understanding of the potential impacts of a major mining dam collapse disaster combined to additional chronic sources of contamination. This data article presents datasets of main contaminants detected in the water and sediments sampled four years after the mining dam collapse in the DRB. A summary table of data obtained in the literature is also provided to allow a comparison of the variation of chemicals before, right after in 2015/2016 and after the event (current data). In addition, there are also provided physical-chemical parameters of water and sediments of different sampling sites, which could support the investigation of chemicals distribution. For this purpose, triplicate samples of water and sediment were obtained in 8 sampling sites along the DRB during wet and dry seasons of 2019, totalizing 48 samples of each environmental matrix. The sampling sites were strategically selected according to their different main sources of pollution along the river. Concentrations of trace elements and organic contaminants (polycyclic aromatic hydrocarbons, and pyrethroids) were determined in samples of water and sediments by inductively coupled plasma mass spectrometry (ICP-MS) and gas chromatography - mass spectrometry GC-MS, respectively. Main data obtained in the literature consisted in published reports from environmental agencies (IGAM) and private companies (RENOVA) as well as journal articles. The datasets provided may be useful to the stakeholders, which include scientific community, authorities and public agencies, and private companies interested to understand the impacts of the contaminants introduced along the River Basin four years after the environmental disaster.

Digital monitoring and compensation of MDL based on higher-order Poincaré spheres.

We present a digital technique able to monitor and compensate for the mode-dependent losses (MDL) in space-division multiplexing (SDM) transmission systems. The working principle of the technique is based on the analysis of the received signal samples in the higher-order Poincaré spheres (HoPs). When an arbitrary pair of tributaries is represented in the respective HoPs, the effect of the MDL can be modeled as a simple shift of the constellation points in a such sphere. Therefore, the MDL can be estimated by computing those shifts over all the HoPs and the induced signal distortions can be compensated by re-centering all the constellations in the respective HoPs. It should be highlighted that the proposed technique is scalable with an arbitrary number of spatial channels, modulation format agonistic and free of training sequences. The HoPs-based MDL monitoring (compensation) technique allows the MDL estimation (compensation) up to values of ≈ 6 dB. The proposed technique can partially compensate the MDL distortion, making a MDL sensitive algorithm in an insensitive one. When the proposed technique assists a HoPs-based space-demultiplexing algorithm, it provides signal-to-noise ratio (SNR) enhancements of 2, 4 and 8 dB for PM-QPSK, PM-16QAM and PM-64QAM signals, respectively, for the particular case of a SDM-based transmission system with a spatial diversity of 2 and 2 dB of MDL.

Economic values and selection index in different Angus-Nellore cross-bred production systems.

Bioeconomic models were developed to calculate economic values (EV) for economically important traits in beef cattle, to evaluate the impact of these traits on production profitability, to assess possible market changes with a payment system and to develop economic selection indexes for Angus cattle for two production systems. Two beef cattle production systems were simulated as follows: a cow-calf cycle (CC) and a complete cycle (CoC). Following selection, positive changes in the EV were observed. In the CC, each 1.0% increment in weaning weight (WW), weaning rate (WR) and pregnancy rate (PR) resulted in increases in US$ 1.30, US$ 3.68 and US$ 3.55 per cow/year in profit, respectively. In the CoC, EV of US$ 1.01, US$ 1.79, US$ 1.19, US$ 1.34, US$ 6.84 and US$ 7.86 per cow/year were obtained for WW, year weight, yearling weight, final weight, WR and PR, respectively. The payment system for carcass quality showed that the scenario considering that 100% of the animals displayed uniform carcasses exhibited the highest EV and was considered optimal. Considering the sensitivity analysis, the price paid per animal was the factor that most affected the EV in both systems. The selection indexes obtained may be used in similar production systems, and the use of EV and selection indexes are important tools for any production system with positive change in profit after selection.

A case-control study of CYP2E1 (PstI) and CYP1A1 (MspI) polymorphisms in colorectal cancer.

Polymorphisms in genes encoding P450 cytochrome enzymes may increase the risk of sporadic colorectal cancer (SCRC). Here we investigated the association between SCRC and CYP2E1 (PstI) and CYP1A1 (MspI) polymorphisms in a case-control study. Moreover, we sought to determine any possible associations between this disease and the sociodemographic factors. We included 273 individuals (74 patients and 199 controls); the gender, age, tobacco usage, and alcohol consumption of the included subjects, and the clinico-histopathological parameters of the tumors, were analyzed. Molecular analyses were performed using PCR-RFLP. The effect of polymorphisms on SCRC development, and the association between this disease and sociodemographic factors were determined by multiple-logistic regression analyses. The combined genotype was also evaluated. Statistically significant differences between the patients and controls regarding the male gender (odds ratio, OR = 0.19, 95% confidence interval, CI = 0.08-0.46; P ≤ 0.05) and age ≥44 years (median = 44; OR = 96.84, 95%CI = 21.78-430.49; P ≤ 0.05) were observed. The evaluated polymorphisms were not associated with SCRC (PstI-CYP2E1: OR = 0.93, 95%CI = 0.30-2.85; P = 0.897; MspI-CYP1A1: OR = 0.75, 95%CI = 0.35-1.61; P = 0.463); the combined genotypes were not associated with the risk of disease. Thus, individuals aged ≥44 years are more sensitive to SCRC, while men are less susceptible. Additionally, polymorphisms in CYP2E1 (PstI) and CYP1A1 (MspI) were not associated with SCRC in the evaluated Brazilian population.