Performance of SSEBop model for estimating wheat actual evapotranspiration in the Brazilian Savannah region

In a scenario where supplying the increasing demand for food depends highly on irrigation, understanding the temporal and spatial variation of actual evapotranspiration (ETa) is essential for water resources management. In the last decades, several models for mapping and monitoring ETa using remote sensing data were developed and studied. In this work, the Simplified Surface Energy Balance for Operational Application (SSEBop) model was applied to estimate actual evapotranspiration of irrigated wheat in the Cerrado (Brazilian Savannahs) region, using ETM+/Landsat 7 and OLI-TIRS/Landsat 8 images. The results were compared with evapotranspiration calculated by the Bowen ratio method. Considering the data referring to satellites overpasses days, SSEBop overestimated ETa by an average of 13.6%, with a coefficient of determination (R²) equal to 0.82 and root mean square error (RMSE) equal to 0.89 mm d^?1. Considering the daily data for the entire period, including the extrapolation for the days between the satellites overpasses, SSEBop overestimated ETa by an average of 5.5%, with R² equal to 0.66 and RMSE equal to 0.95 mm d^?1. The results obtained demonstrated a reliable performance of the SSEBop for estimating actual evapotranspiration of irrigated wheat in the Cerrado, which can contribute to improve the irrigation efficiency and reduce water use conflicts. Considering the simplicity of the modeling concept and operational implementation, it can also be beneficial for water agencies on water resources planning, management and regulation in the region.     

Optimizing earthquake design of reinforced concrete bridge infrastructures based on evolutionary computation techniques

This paper presents a methodology for the earthquake design of reinforced concrete (RC) bridge infrastructures based on the application of multi-objective     

Characterization of Extra Virgin Olive Oil from Southern Brazil

Six olive oils extracted from the cultivars Arbequina, Arbosana, Coratina, Frantoio, Koroneiki, and Picual from 2017 and 2018 harvests, cultivated in Pinheiro Machado, Rio Grande do Sul, Brazil, are evaluated for standard oil composition parameters and bioactive constituents (pigments, tocopherols, and phenolic compounds). Multivariate principal component analysis (PCA) and univariate ANOVA and Fisher's LSD test are used to verify the effect of cultivar and harvest year on oil composition. Olive oil composition met extra virgin olive oil (EVOO) standard parameters and is influenced by both cultivar and harvest year. EVOO produced in 2018 has greater chlorophyll, caffeic acid, ligstroside aglycone, hydroxyoleuropein aglycone, syringic acid, and hydroxytyrosol acetate contents than the EVOOs from 2017. Linoleic acid, ferulic acid, ligstroside aglycone, and hydroxytyrosol acetate are the variables whose contents most contributed to the differentiation of oils by cultivar in both harvest years. Chemical characterization analyses allow for the differentiation of oil composition based on harvest year and cultivar. Metabolic quality data obtained here support the establishment of a local EVOO profile and the compounds that most contributed to treatment differentiation may serve as markers that can be utilized in determining origin, cultivar, and harvest year. Practical Applications: Olive production in Brazil is recent and is based on European cultivars which have not been bred for the local environmental conditions. Therefore, the measurement of olive oil metabolic quality will determine cultivar adaptability to local edaphoclimatic conditions as well as assist in the establishment of a standard of identity for the product and promote the development of its market. Olive oil produced in Southern Brazil shows high quality, and is especially rich in phenolic compounds. Although harvest year influences oil composition, oil from both harvests meet EVOO standards and cultivar specific metabolic markers are observed. This study provides the foundation for olive producers in Southern Brazil to seek authentication of the geographical origin of olive oil.     

Frequency domain analysis of the mirror-modified filtered-x least mean squares algorithm with low ambient noise

The mirror-modified filtered-x least mean squares (MMFxLMS ) algorithm is a variation of the FxLMS algorithm with online secondary path modeling that cannot diverge due to secondary path modeling errors. However, problems may occur when the ambient noise is not limited due to insufficient modeling power. This work shows that under a frequency domain analysis without ambient noise, the MMFxLMS algorithm is always stable, and expressions for the maximum residual noise level at any given time are obtained. It is also shown that, under the same context, convergence to the minimum residual noise is guaranteed. Still, convergence can be much slower for high secondary path modeling errors than that of the LMS or MFxLMS algorithms. Simulations confirm these results.     

Application of nanotechnology in removal of NAPLs from contaminated aquifers: a source clean-up experimental study

Clean Technologies and Environmental Policy - This work investigates the removal of non-aqueous phase liquids (NAPLs) from groundwater resources using nanotechnology. We present results of a series...     

On generic G-prevalent properties and a quantitative K-S theorem for Cr diffeomorphisms of the circle

We will consider a convex subset of a metric linear space and a certain group of actions G on this set, that allow us to define the notion of Haar zero measure on sets that have zero Haar measure for the translation (by adding) invariant HSY prevalence theory. In this way, we will be able to define the meaning of G-prevalent set according to the pioneering work of Christensen. Our setting considers problems which take into account the convex structure and this is quite different from the previous results on prevalence which consider basically the linear additive structure. In this setting, we will show a kind of quantitative Kupka–Smale theorem, and also we generalize a result about rotation numbers which was first considered by J.-C. Yoccoz (and, also by M. Tsujii). Among other things we present an estimation of the amount of hyperbolicity in a setting that we believe was not considered before.     

A self‐scalable load injection service

Load testing of applications is an important and costly activity for software provider companies. Classical solutions are very difficult to set up statically, and their cost is prohibitive in terms of both human and hardware resources. Virtualized cloud computing platforms provide new opportunities for stressing an application's scalability, by providing a large range of flexible and less expensive (pay‐per‐use model) computation units. On the basis of these advantages, load testing solutions could be provided on demand in the cloud. This paper describes a Benchmark‐as‐a‐Service solution that automatically scales the load injection platform and facilitates its setup according to load profiles. Our approach is based on: (i) virtualization of the benchmarking platform to create self‐scaling injectors; (ii) online calibration to characterize the injector's capacity and impact on the benched application; and (iii) a provisioning solution to appropriately scale the load injection platform ahead of time. We also report experiments on a benchmark illustrating the benefits of this system in terms of cost and resource reductions. Copyright © 2013 John Wiley & Sons, Ltd.     

Kinetics of Soybean Oil Hydrolysis on Niobium Catalysts

The catalytic hydrolysis of soybean oil was used as an alternative for the production of monoglycerides (MG) and diglycerides (DG). The reactions were conducted in a stainless-steel tubular reactor in the temperature range of 240–290 °C, on niobium phosphate (NBP) and niobium oxide (NBO) as catalysts. In the hydrolysis reactions at 270 °C, the maximum selectivities of the products of interest were obtained at 22 % MG and 48 % DG for the reaction with NBP, and 7 % MG and 33 % DG with NBO, for 59 % and 36 % of triglyceride conversion in 10 min, respectively. The proposed kinetic model presented a good fit of the theoretical model with the experimental data, showing that the previous hypotheses considered for the mechanism development are suitable for describing the kinetics of soybean oil hydrolysis.     

Influence of Alkaline Additives and Buffers on Mineral Trapping of CO2 under Mild Conditions

Carbon dioxide (CO₂) gas is the main contributor to climate change. CO₂ storage in underground brines and oil‐field brines by mineral trapping has been considered as a promising alternative in order to reduce CO₂ emissions. However, permanent storage of CO₂ in stable carbonate minerals is greatly dependent on brine pH, being favored over an alkaline pH. The effect of alkaline additives (NaOH, KOH, CaO) and buffer solutions (NaHCO₃/NaOH, Na₂HPO₄/NaOH, NH₄Cl/NH₄OH) on the mineral trapping of CO₂ under mild conditions using a synthetic brine is investigated. The results indicate that both NaOH+NH₄Cl/NH₄OH and KOH+NH₄Cl/NH₄OH mixtures promote precipitation mainly of calcium carbonate (CaCO₃).