He and Cr effects on radiation damage formation in ion-irradiated pure iron and Fe–5.40 wt.% Cr: A transmission electron microscopy study

The first walls of future fusion reactors will be exposed to 14 MeV neutron irradiation. In order to gain insight into their radiation resistance, model materials (a high purity iron and a Fe–5.40 wt.% Cr alloy) have been ion-irradiated in the JANNuS facility to high doses with and without helium. The materials were self-ion-irradiated at 500 °C up to ～100 displacements per atom (dpa) with gas implantation rates equal to 0, 2.5 and 25 appm He dpa^?1. He and Cr effects on the radiation damage formation have been studied at the microscopic scale by transmission electron microscopy. In pure Fe, a coarse dislocation network was observed after irradiation, irrespective of helium implantation rate. Concerning the V-containing features (nanobubbles or cavities), few large cavities were observed in pure iron irradiated without helium. The main effect of helium implantation was to increase their density and diminish their size. The main effect of chromium was to reduce the swelling for all the He implantation rates. Furthermore, in both materials, the cavity formation was mainly heterogeneous.     

AGEs-Induced IL-6 Synthesis Precedes RAGE Up-Regulation in HEK 293 Cells: An Alternative Inflammatory Mechanism?

Advanced glycation end products (AGEs) can activate the inflammatory pathways involved in diabetic nephropathy. Understanding these molecular pathways could contribute to therapeutic strategies for diabetes complications. We evaluated the modulation of inflammatory and oxidative markers, as well as the protective mechanisms employed by human embryonic kidney cells (HEK 293) upon exposure to 200 μg/mL bovine serum albumine (BSA) or AGEs–BSA for 12, 24 and 48 h. The mRNA and protein expression levels of AGEs receptor (RAGE) and heat shock proteins (HSPs) 27, 60 and 70, the activity of antioxidant enzymes and the expression levels of eight cytokines were analysed. Cell damage via oxidative mechanisms was evaluated by glutathione and malondialdehyde levels. The data revealed two different time scale responses. First, the up-regulation of interleukin-6 (IL-6), HSP 27 and high catalase activity were detected as early as 12 h after exposure to AGEs–BSA, while the second response, after 24 h, consisted of NF-κB p65, RAGE, HSP 70 and inflammatory cytokine up-regulation, glutathione depletion, malondialdehyde increase and the activation of antioxidant enzymes. IL-6 might be important in the early ignition of inflammatory responses, while the cellular redox imbalance, RAGE activation and NF-κB p65 increased expression further enhance inflammatory signals in HEK 293 cells.     

Kinetics of chitosan coagulation from aqueous solutions

In this study, we investigated the kinetics of chitosan hydrogel formation from aqueous chitosan solutions with sodium hydroxide (NaOH) as the coagulant. Two sets of experiments were performed, one in a parallelepiped cell and the other with cylindrical chitosan solution extrudates. The coagulation occurred by the neutralization of the protonated amino groups (? ) present in the chitosan chains, with the kinetics being controlled by NaOH transport toward the gelification zone. In this study, we confirmed the appropriateness of Fick's second law to describe NaOH transport, considering the instantaneous reaction between the NaOH and ? groups. The experimental data were used to determine the NaOH diffusion coefficient in gels having different chitosan concentrations. The diffusion coefficient values obtained from the cylindrical coagulation data were lower than those determined for linear coagulation because of the influences of transport geometry and gel structure, respectively. Accordingly, in fiber coagulation calculations, it is recommended to use diffusion coefficient values determined from cylindrical coagulation studies. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46062.     

Training an Active Random Field for Real-Time Image Denoising

Many computer vision problems can be formulated in a Bayesian framework based on Markov random fields (MRF) or conditional random fields (CRF). Generally, the MRF/CRF model is learned independently of the inference algorithm that is used to obtain the final result. In this paper, we observe considerable gains in speed and accuracy by training the MRF/CRF model together with a fast and suboptimal inference algorithm. An active random field (ARF) is defined as a combination of a MRF/CRF based model and a fast inference algorithm for the MRF/CRF model. This combination is trained through an optimization of a loss function and a training set consisting of pairs of input images and desired outputs. We apply the ARF concept to image denoising, using the Fields of Experts MRF together with a 1-4 iteration gradient descent algorithm for inference. Experimental validation on unseen data shows that the ARF approach obtains an improved benchmark performance as well as a 1000-3000 times speedup compared to the Fields of Experts MRF. Using the ARF approach, image denoising can be performed in real-time, at 8 fps on a single CPU for a 256times256 image sequence, with close to state-of-the-art accuracy.     

Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features

We propose an automatic four-chamber heart segmentation system for the quantitative functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics are discussed: heart modeling and automatic model fitting to an unseen volume. Heart modeling is a nontrivial task since the heart is a complex nonrigid organ. The model must be anatomically accurate, allow manual editing, and provide sufficient information to guide automatic detection and segmentation. Unlike previous work, we explicitly represent important landmarks (such as the valves and the ventricular septum cusps) among the control points of the model. The control points can be detected reliably to guide the automatic model fitting process. Using this model, we develop an efficient and robust approach for automatic heart chamber segmentation in 3-D CT volumes. We formulate the segmentation as a two-step learning problem: anatomical structure localization and boundary delineation. In both steps, we exploit the recent advances in learning discriminative models. A novel algorithm, marginal space learning (MSL), is introduced to solve the 9-D similarity transformation search problem for localizing the heart chambers. After determining the pose of the heart chambers, we estimate the 3-D shape through learning-based boundary delineation. The proposed method has been extensively tested on the largest dataset (with 323 volumes from 137 patients) ever reported in the literature. To the best of our knowledge, our system is the fastest with a speed of 4.0 s per volume (on a dual-core 3.2-GHz processor) for the automatic segmentation of all four chambers.      

Flat pressed wood plastic composites made of milled foam core particleboard residues

Flat pressed wood plastic composites were produced on a laboratory-scale using residues of lightweight foam core particleboards as raw material. Raw material preparation methods (dry blending and compounding with a twin screw extruder) and the wood flour content (WF) loading, as influencing parameters on the panel properties, were varied, and coupling agents (CA) were added in some variations. The results showed that panels produced with lower WF content (75 %) have better physical and mechanical properties compared to those of higher WF. The CAs only influenced the panel properties when they were added during the compounding of the materials. Due to the assumed higher wood degradation resulting from raw material compounding, the panel properties were inferior to the panels produced with dry blended materials.     

Physical and mechanical properties of oriented strand lumber made from an Asian bamboo (Dendrocalamus asper Backer)

The study was conducted to determine the physical and mechanical properties as follows: modulus of rupture, modulus of elasticity, internal bond, thickness swelling and water absorption of oriented strand lumber (OSL) made from the Asian bamboo Dendrocalamus asper Backer. Thirty-six lab boards were produced from these bamboo strands with two manufacturing parameters varying, i.e., four resin types (MF, MUPF, PF, and pMDI) and three levels of resin content (7, 10, and 13%). The results indicate that OSL made from bamboo strands exhibits superior strength properties compared to the commercial products made from wood for the building sector. The resin type has a?significant effect on board properties. Moreover, all properties of the board improve generally with increasing resin content. With regard to the internal bond, bamboo-based OSL shows less strength than wood-based boards. The best results were obtained by using 13% pMDI content at 750?kg $ / $ m³ density.     

Cluster Dynamics modelling of irradiation growth of zirconium single crystals

This paper aims at modelling irradiation growth of zirconium single crystals as a function of neutron fluence. The Cluster Dynamics approach is used, which makes it possible to describe the variation of irradiation microstructure (dislocation loops) with neutron fluence. From the irradiation microstructure, the strain can be calculated along the axes of the lattice structure. The model is applied to the growth of annealed zirconium single crystals at 553 K measured by Carpenter and Rogerson in 1981 and 1987. The model is found to fit the experimentally measured growth of Zr single crystals very nicely, even at large neutron fluence where the ‘breakaway growth’ occurs. This was made possible by considering in the model the growth of vacancy loops in the basal planes. This growth of vacancy loops in the basal planes could be modelled by taking into account that diffusion of self-interstitial atoms (SIA) is anisotropic and that there exist in the basal planes some nucleation sites for vacancy loops (iron clusters), the density of which is considered constant over time.     

Characterization of neutron-irradiated ferritic model alloys and a RPV steel from combined APT, SANS, TEM and PAS analyses

Understanding the behavior of reactor pressure vessel (RPV) steels under irradiation is a mandatory task that has to be elucidated in order to be able to operate safely a nuclear power plant or to extend its lifetime. To build up predictive tools, a substantial experimental data base is needed at the nanometre scale to extract quantitative information on neutron-irradiated materials and to validate the theoretical models. To reach this experimental goal, ferritic model alloys and French RPV steel were neutron irradiated in a test reactor at an irradiation flux of 9 × 10¹⁷ nm⁻² s, doses from 0.18 to 1.3 × 10²⁴ nm⁻² and 300 °C. The main goal of this paper is to report the characterization of the radiation-induced microstructural change in the materials by using the state-of-the-art of characterization techniques available in Europe at the nanometre scale. Possibilities, limitations and complementarities of the techniques to each other are highlighted.