Microstructural and textural characterization of a hot-rolled IF steel

The present paper reports the experimental results on the microstructural and textural characterization of a hot-rolled IF steel. The IF steel was hot-rolled in multiple passes in the austenitic field (1,070 °C) followed by air-cooling. SEM, TEM, and LOM were used to image the microstructure of the material. The global texture was determined by X-ray diffraction (XRD) technique. The mesotexture of selected regions was investigated by electron backscatter diffraction (EBSD). Results show the presence of a diffuse (nearly random) and weak texture in the hot-band that consists of recrystallized polygonal grains and subgrains. The fraction of boundaries with misorientations comprised in the interval 2° ≤ ψ < 15° was found to be lower than 5%. It can be concluded that these low angle boundaries and the presence of subgrains can be associated to the existence of a few areas softened by recovery during or after hot rolling in austenitic field.     

Interconnection between the solidification and precipitation hardening processes of an AlSiCu alloy

Horizontal directional solidification and precipitation hardening experiments were performed with the Al5.5Si3Cu alloy. Solidification thermal and microstructural parameters such as growth and cooling rates (V_L and T_R, respectively) and the secondary dendrite arm spacing (λ₂) were determined experimentally. As-solidified samples were selected and submitted to the T6-heat treatment (T6-HT). The T6-HT was carried out considering two solution times: 8 and 5?h at 490?±?2°C, followed by quenching in warm water (60?±?2°C), aging for 5?h at 155?±?2°C and air-cooling. Higher HV values were observed for the solution time of 5 h. As highlights of this work, the influence of the processing parameters (V_L, T_R and λ₂) on the distribution, morphology and size of the eutectic Si particles has been investigated.     

Hydrogen production through anaerobic co-digestion of food waste and crude glycerol at mesophilic conditions

Hydrogen production from mesophilic anaerobic co-digestion of food waste (FW) and crude glycerol (GLC) was investigated in this study. Batch experiments were carried out at 35 °C for 36 h to assess the effect of supplementation of different glycerol concentrations (1%, 3% and 5% (v/v)) on dark fermentation of FW. The maximum hydrogen yield (180 mLH₂/gVS) was obtained at 5% GLC while the maximum specific production rate (around 13 mLH₂/(gVS.h)) was similar for all experiments with glycerol addition. Besides contributing to increase H₂ productivity, the presence of glycerol reduced the microorganisms acclimation time (Lag phase) in comparison to the control tests conducted without this co-substrate. In addition, the increment of glycerol concentration also enhanced volatile fatty acids generation and favoured the production of 1,3-propanediol (1,3-PDO). In the experimental conditions studied (i.e., 1–5% (v/v) of GLC), the results revealed that co-digestion of FW and GLC is promising and can be potentially used to maximize energy production while contributing to the management and treatment of these wastes.     

Multi-Residue Determination of Pesticides in Açai Tropical Fruit (Euterpe oleracea) by Matrix Solid-Phase Dispersion Combined with Liquid Chromatography

An extraction method based on matrix solid phase dispersion was developed to determine bromuconazole, fenbuconazole, parathion-methyl, kresoxim-methyl, and teflubenzuron in açai using liquid chromatography with ultraviolet diode array detector. The best results were obtained using 1.0 g of açai, 3.0 g of neutral alumina as the dispersant sorbent, and cyclohexane/ethyl acetate (1:1, v/v, 20 mL) as an eluting solvent. The method was validated using açai samples fortified with pesticides at three concentration levels (0.25, 0.5, and 1.0 mg kg^?1). Average recoveries (seven replicates) ranged from 66 to 119 %, with relative standard deviations between 1.4 and 20 %. The detection and quantification limits for açai ranged from 0.02 to 0.05 mg kg^?1 and from 0.05 to 0.1 mg kg^?1, respectively.     

Benzodioxoles as alternative coinitiators for radical polymerization in a model‐dental adhesive resin

This study evaluated the effectiveness of benzodioxole derivatives as coinitiators of radical polymerization in a model‐dental adhesive resin. To compose the adhesive resin, a monomer mixture based on 50 wt % of Bis‐GMA, 25 wt % of TEGDMA, and 25 wt % of HEMA was used. Camphorquinone (CQ) 1 mol % was used as a photoinitiator to initiate polymerization. 1,3‐Benzodioxole (BDO) and piperonyl alcohol (PA) were used as coinitiators at 0.25, 0.5, 1, 2, 4, 8, and 16 mol % level. In addition, tertiary amine, ethyl 4‐dimethylamino benzoate (EDAB) was used as coinitiator in the control group. Some physical, chemical, and mechanical properties of the polymer formed in the experimental adhesives were evaluated using the kinetics of polymerization, sorption and solubility, flexural strength, and elastic modulus tests. The results indicated that BDO and PA were effective coinitiators in the photoinitiator system based on CQ. Comparisons between the benzodioxoles derivative coinitiators and EDAB showed similar performance in the kinetics of polymerization and flexural strength. For water sorption and solubility evaluation, BDO and PA demonstrated significantly more sorption of water and less solubility than the EDAB control group. The findings suggest that BDO and PA were feasible alternatives to conventional amine as coinitiator. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Adaptive random forests for evolving data stream classification

Random forests is currently one of the most used machine learning algorithms in the non-streaming (batch) setting. This preference is attributable to its high learning performance and low demands with respect to input preparation and hyper-parameter tuning. However, in the challenging context of evolving data streams, there is no random forests algorithm that can be considered state-of-the-art in comparison to bagging and boosting based algorithms. In this work, we present the adaptive random forest (ARF) algorithm for classification of evolving data streams. In contrast to previous attempts of replicating random forests for data stream learning, ARF includes an effective resampling method and adaptive operators that can cope with different types of concept drifts without complex optimizations for different data sets. We present experiments with a parallel implementation of ARF which has no degradation in terms of classification performance in comparison to a serial implementation, since trees and adaptive operators are independent from one another. Finally, we compare ARF with state-of-the-art algorithms in a traditional test-then-train evaluation and a novel delayed labelling evaluation, and show that ARF is accurate and uses a feasible amount of resources.     

The Use of Active Methodologies for Teaching–Learning Systems in Telecommunications

This article discusses the adoption of the Problem Based Learning (PBL) and Project Based Learning (P2BL) approaches in the teaching/learning process of telecommunications. A computational environment was defined to combine these two approaches which focused on the teaching of courses that cover topics related to telecommunications systems. Newly graduated professionals face difficulties when entering the job market, as they have to deal with situations that are not experienced in the academic world. There is still a tendency to rely on traditional approaches for the teaching of telecommunications systems that have proved to be inefficient, as they are only concerned with content and not the applications that the student will require in the job market. The aim of this research is to investigate whether the adoption of PBL and P2BL in a computational environment can enhance student learning more effectively than the traditional teaching approach. This involved conducting an experiment in 7 undergraduate classes to compare the performance of the students that adopted PBL and P2BL with that of the students who were taught with the traditional approach. Data were collected on the grades obtained by the students in the courses and these were statistically analyzed. The results show that the adoption of PBL and P2BL led to the students achieving a 32% increase in performance. However, it was noted that the infrastructure of the institutions directly influences the way the approaches are adopted and, hence affects, the results.

     

A multivariate normal boundary intersection PCA-based approach to reduce dimensionality in optimization problems for LBM process

Engineering with Computers - Laser beam machining (LBM) is a promising manufacturing process that exhibits several desirable quality characteristics. Given a large number of objective functions,...