Suspended sediment and bedload discharges in sand-bed rivers shape semi-arid landscapes and impact sediment delivery from these landscapes, but are still incompletely understood. Suspended sediment and bedload fluxes of the intermittent Exu River, Brazil, were sampled by direct measurements. The highest suspended sediment concentration observed was 4847.4 mg L-1 and this value was possibly associated with the entrainment of sediment that was deposited in the preceding year. The bedload flux was well related to the stream power and the river efficiently transported all available bedload with a mean rate of 0.0047 kg m-1 s-1 , and the percentage of bedload to suspended sediment varied between 4 and 12.72. The bed sediment of Exu River was prone to entrainment and showed a proclivity for transport. Thus, sand-bed and gravel-bed rivers of arid environments seem to exhibit the same mobility in the absence of armour layer.
An increasing number of cases of infection and death by COVID-19 has been observed in several parts of the world, including Brazil. While scientists are looking for a drug / vaccine capable of combating COVID-19, its devastating action is spreading out of control. In this context, statistical studies and preliminary analyzes of the epidemic situation may be important to provide a basis for disease prevention and control. Thus, the objective of this work was to adjust nonlinear regression models to mortality data and confirmed cases of COVID-19 in Brazil, Italy and the world until 03/31/2020. Data from the Ministry of Health of Brazil and the World Health Organization were used. The models were compared using the Akaike information criterion and the Bayesian information criterion, as well as the determination and adjusted determination coefficients, in addition to the square root of the mean square error. All models presented were adequate to model the studied variables. It is not yet possible to make reliable projections of when the numbers of confirmed cases and deaths will decrease. Social detachment in Brazil is being effective in restricting the progression of the disease by reducing the speed of infection and transmissibility.
The Rocas Atoll Biological Reserve is located in the Atlantic Ocean, at 3º 51' S and 33º 49' W. It lies 143 nautical miles from the City of Natal, Rio Grande do Norte (Brazil). The purpose of this study was to analyze the hydrology, water masses, currents and chlorophyll a content to determine the dynamics of phytoplankton biomass around the Rocas Atoll. Samples were collected in July 2010 in the area around the Atoll, using the Research Vessel Cruzeiro do Sul of the Brazilian Navy. Two transects were established according to the surface currents, one of which at the southeast of the Atoll (SE) and the other at norwest (NW). Three collection points were determined on each of these transects. Samples were collected at different depths (surface and DCM - Deep Chlorophyll Maximum) and different times (day and night). According to PCA (Principal Component Analysis), the nutrients analyzed, DIN (dissolved inorganic nitrogen), DIP (dissolved inorganic phosphorus) and silicate, were inversely correlated with temperature and dissolved oxygen. Most environmental variables showed a significant increase due to the turbulence on the Northwest transect. There was an increase in the concentration of chlorophyll a and nutrients when the temperature and oxygen in the mixed layer was reduced due to the influence of the SACW (South Atlantic Central Water). Despite the increase observed in some variables such as nutrient salts and chlorophyll a, the temperature in the mixed layer attained a mean value of 23.23 ºC due to the predominance of Tropical Water. The increase of the phytoplankton biomass on the NW transect was, therefore, caused by the "island effect" and not by upwelling.
This study aims to propose a method to generate growth and degrowth models using differential equations as well as to present a model based on the method proposed, compare it with the classic linear mathematical models Logistic, Von Bertalanffy, Brody, Gompertz, and Richards, and identify the one that best represents the mean growth curve. To that end, data on Undefined Breed (UB) goats and Santa Inês sheep from the works of Cavalcante et al. (2013) and Sarmento et al. (2006a), respectively, were used. Goodness-of-fit was measured using residual mean squares (RMS), Akaike information criterion (AIC), Bayesian information criterion (BIC), mean absolute deviation (MAD), and adjusted coefficient of determination . The models’ parameters (?, weight at adulthood; ?, an integration constant; ?, shape parameter with no biological interpretation; k, maturation rate; and m, inflection point) were estimated by the least squares method using Levenberg-Marquardt algorithm on the software IBM SPSS Statistics 1.0. It was observed that the proposed model was superior to the others to study the growth curves of goats and sheep according to the methodology and conditions under which the present study was carried out.
Mathematical models that describe gas production are widely used to estimate the rumen degradation digestibility and kinetics. The present study presents a method to generate models by combining existing models and to propose the von Bertalanffy-Gompertz two-compartment model based on this method. The proposed model was compared with the logistic two-compartment one to indicate which best describes the kinetic curve of gas production through the semi-automated in vitro technique from different pinto peanut cultivars. The data came from an experiment grown and harvested at the Far South Animal Sciences station (Essul) in Itabela, BA, Brazil and gas production was read at 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 h after the start of the in vitro fermentation process. The parameters were estimated by the least squares method using the iterative Gauss-Newton process in the software R version 3.4.1. The best model to describe gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion, and Bayesian information criterion. The von Bertalanffy-Gompertz two-compartment model had the best fit to describe the cumulative gas production over time according to the methodology and conditions of the present study.
INTRODUÇÃO: o sono é uma função biológica fundamental para a conservação da energia e a restauração do metabolismo energético.OBJETIVO: analisar o efeito de uma sessão do treinamento de força realizada em diferentes horários sobre a qualidade do sono de adolescentes e examinar se a relação entre a melhoria da qualidade do sono e o horário da sessão de treino se altera após o ajuste para idade.MÉTODOS: participaram do estudo seis estudantes do sexo masculino moradores internos do IFPE - Campus Vitória de Santo Antão, PE, Brasil. Foram realizadas três sessões de treinamento de força em diferentes horários manhã, tarde e noite, durante 12 semanas. A escala OMINI-RES foi utilizada para percepção do esforço. A qualidade do sono foi avaliada pelo Índice de Qualidade do Sono de Pittsburgh PSQI. Ainda foram avaliadas variáveis antropométricas massa corporal, estatura, IMC e a composição corporal % gordura, massa gorda e massa magra.RESULTADOS: foram observadas diferenças entre as sessões de treino realizadas em diferentes horários e a diagnose de qualidade do sono manhã: P < 0,001; tarde: P = 0,001; noite: P = 0,047. Houve correlação entre a sessão de treino realizada pela manhã r = 0,95 e à tarde r = 0,92 e a diagnose de qualidade do sono. Utilizando o modelo de regressão linear, as sessões de treinamento de força realizadas pela manhã R2= 0,91 e tarde R2= 0,75 explicaram de forma significativa a melhora da qualidade do sono em adolescentes, mesmo após o controle pela idade.CONCLUSÃO: as sessões de treinamento de força realizadas pela manhã e tarde apresentaram melhor resposta de qualidade do sono de adolescentes.
This study evaluates the insolation calculations and their analysis soon after plotting their respective local historical average graph from 1962 to 2019 for some municipalities in Pernambucana. Monthly and annual insolation data for the study period was obtained from the National Institute of Meteorology.After homogenization, data consistency and failure filling of each series, the spatial and temporal insolation densities were performed for municipalities like Arcoverde, Cabrobó, Garanhuns, Ouricuri, Petrolina, Recife, Surubim and Triunfo. The average and its historical average were calculated and appropriate analysis was performed. The spatial distribution of the monthly insolation data showed great variability for the months studied, ranging from approximately 3 to 4 hours. The median values most likely occured during the months for the eight municipalities under study. The municipality of Garanhuns presented higher insolation values than Petrolina. Comparing the values obtained in this study with the values of the Solarimetric Atlas of Brazil, indicated a good similarity of the recorded data.
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