Microstructure and flexural strength of the Y:TZP/BG composite

The addition of bioactive glasses to a Y:TZP matrix represents a feasible alternative to provide bioactivity to this material and optimize osseointegration. This work evaluated the effect of the BG concentration (0 and 10 wt%) and the sintering temperature (1200°C and 1300°C) on the microstructure, relative density, and flexural strength of the composite Y:TZP/BG. The Y:TZP and Y:TZP/BG powders were uniaxially pressed and sintered at 1200°C or 1300°C for 1 h. The microstructure was characterized by X-ray diffraction analysis, scanning electron microscopy, and energy-dispersive X-ray Spectroscopy. Relative density was calculated from density values obtained using the Archimedes’ principle. For the flexural strength, specimens (n = 6) were fractured in a biaxial flexural setup using a piston-on-three-balls fixture in a universal testing machine. Bioactivity test was performed in simulated body fluid solution. The results suggested that BG addition decreased the grain size of the composite, increased porosity and caused a significant decrease in the relative density and flexural strength. Crystalline phases of calcium stabilized cubic zirconia and sodium zirconium silicate were formed after the addition of BG. Finally, it was concluded that composite specimens sintered at 1300°C showed the highest density values and larger grains compared to those sintered at 1200°C.     

Combined application of electrolysed water and ultrasound to improve the sanitation of knives in the meat industry

This study investigated the effect of the combination of basic electrolysed water (BEW) and slightly acid electrolysed water (SAEW) with ultrasound (US) for cleaning and sanitation of the knives used in slaughtering processes. The knives were sonicated in a US bath using two modes of operation (normal and sweep) in two steps: (i) 5 min with BEW and (ii) 10 min with SAEW at 35 °C. The microbiological counts and the possible changes in the physical structure of the knives were evaluated. The association BEW + SAEW + US, in the sweep mode, provided lower mesophilic, enterobacterial, Staphylococcus aureus and yeast counts when compared to the values recommended by the international legislation. In addition, these conditions removed all organic residues from the knife blades and promoted the highest migration rate of the residues to the US water bath (12.35 mg/L·min), without modifications in the knife blades. Thus, cleaning and sanitation of knives was feasible with the association of BEW + SAEW + US, which could be a useful alternative for the meat industry.     

The role of the ratio (PEG:PPG) of a triblock copolymer (PPG‐b‐PEG‐b‐PPG) in the cure kinetics,miscibility and thermal and mechanical properties in an epoxy matrix

The aim of this study was to evaluate the role of different poly(ethylene glycol):poly(propylene glycol) (PEG:PPG) molar ratios in a triblock copolymer in the cure kinetics, miscibility and thermal and mechanical properties in an epoxy matrix. The poly(propylene glycol)‐block‐poly(ethylene glycol)‐block‐poly(propylene glycol) (PPG‐b‐PEG‐b‐PPG) triblock copolymers used had two different molecular masses: 3300 and 2000 g mol^?1. The mass concentration of PEG in the copolymer structure played a key role in the miscibility and cure kinetics of the blend as well as in the thermal–mechanical properties. Phase separation was observed only for blends formed with the 3300 g mol^?1 triblock copolymer at 20 wt%. Concerning thermal properties, the miscibility of the copolymer in the epoxy matrix reduced the T_g value by 13 °C, although a 62% increase in fracture toughness (K_IC) was observed. After the addition of PPG‐b‐PEG‐b‐PPG with 3300 g mol^?1 there was a reduction in the modulus of elasticity by 8% compared to the neat matrix; no significant changes were observed in T_g values for the immiscible system. The use of PPG‐b‐PEG‐b‐PPG with 2000 g mol^?1 reduced the modulus of elasticity by approximately 47% and increased toughness (K_IC) up to 43%. Finally, for the curing kinetics of all materials, the incorporation of the triblock copolymer PPG‐b‐PEG‐b‐PPG delayed the cure reaction of the DGEBA/DDM (DGEBA, diglycidyl ether of bisphenol A; DDM, Q3‐4,4′‐Diaminodiphenylmethane) system when there is miscibility and accelerated the cure reaction when it is immiscible. All experimental curing reactions could be fitted to the Kamal autocatalytic model presenting an excellent agreement with experimental data. This model was able to capture some interesting features of the addition of triblock copolymers in an epoxy resin. © 2018 Society of Chemical Industry     

The “Carbonyl Story” and Beyond; Experiences,Lessons and Implications

The complex [^99mTc(OH₂)₃(CO)₃]⁺ has become a versatile building block in radiopharmaceutical chemistry, applied by many groups worldwide. However, despite widespread efforts, only one compound has made it right the way through clinical trials. Along the way from its discovery to its development into an eventual product, the author experienced issues that he would handle differently in retrospect. In this article, these experiences are turned into “lessons” that might be helpful for young researchers finding themselves in similar situations. Beside issues with patenting and company strategies, the carbonyl story has provided scientific implications beyond its own story, and insights from which any future ^99mTc-based chemistry for radiopharmacy or molecular imaging might benefit.     

Nonlinear adaptive filtering using kernel‐based algorithms with dictionary adaptation

Nonlinear adaptive filtering has been extensively studied in the literature, using, for example, Volterra filters or neural networks. Recently, kernel methods have been offering an interesting alternative because they provide a simple extension of linear algorithms to the nonlinear case. The main drawback of online system identification with kernel methods is that the filter complexity increases with time, a limitation resulting from the representer theorem, which states that all past input vectors are required. To overcome this drawback, a particular subset of these input vectors (called dictionary) must be selected to ensure complexity control and good performance. Up to now, all authors considered that, after being introduced into the dictionary, elements stay unchanged even if, because of nonstationarity, they become useless to predict the system output. The objective of this paper is to present an adaptation scheme of dictionary elements, which are considered here as adjustable model parameters, by deriving a gradient‐based method under collinearity constraints. The main interest is to ensure a better tracking performance. To evaluate our approach, dictionary adaptation is introduced into three well‐known kernel‐based adaptive algorithms: kernel recursive least squares, kernel normalized least mean squares, and kernel affine projection. The performance is evaluated on nonlinear adaptive filtering of simulated and real data sets. As confirmed by experiments, our dictionary adaptation scheme allows either complexity reduction or a decrease of the instantaneous quadratic error, or both simultaneously. Copyright © 2015 John Wiley & Sons, Ltd.