Growth and Characterization of YbBCO Films on Textured Gd2O3 Buffer-Layered Ni Tapes: All Sol–Gel Process

YbBa₂Cu₃O_7?x (YbBCO) thick films were grown on buffered, cube-textured Nickel tapes by sol–gel dip-coating method. Yb-123 films were prepared using solutions of Yb, Ba, and Cu organometallic compounds. A solution-based Gd₂O₃ buffer layer was deposited by dip-coating process with excellent texture and uniformity. The texture development and surface morphology of the buffer-layer films were examined by X-ray diffraction, pole figures, and ESEM analysis. Microstructure and characterization of Yb-123 films were done by ESEM, EDS, and XRD analysis. T _c and J _c were conducted by four-wire measurement method     

Visualizing Extracellular Vesicles and Their Function in 3D Tumor Microenvironment Models

Extracellular vesicles (EVs) are cell-derived nanostructures that mediate intercellular communication by delivering complex signals in normal tissues and cancer. The cellular coordination required for tumor development and maintenance is mediated, in part, through EV transport of molecular cargo to resident and distant cells. Most studies on EV-mediated signaling have been performed in two-dimensional (2D) monolayer cell cultures, largely because of their simplicity and high-throughput screening capacity. Three-dimensional (3D) cell cultures can be used to study cell-to-cell and cell-to-matrix interactions, enabling the study of EV-mediated cellular communication. 3D cultures may best model the role of EVs in formation of the tumor microenvironment (TME) and cancer cell-stromal interactions that sustain tumor growth. In this review, we discuss EV biology in 3D culture correlates of the TME. This includes EV communication between cell types of the TME, differences in EV biogenesis and signaling associated with differing scaffold choices and in scaffold-free 3D cultures and cultivation of the premetastatic niche. An understanding of EV biogenesis and signaling within a 3D TME will improve culture correlates of oncogenesis, enable molecular control of the TME and aid development of drug delivery tools based on EV-mediated signaling.     

Human-Induced Neural and Mesenchymal Stem Cell Therapy Combined with a Curcumin Nanoconjugate as a Spinal Cord Injury Treatment

We currently lack effective treatments for the devastating loss of neural function associated with spinal cord injury (SCI). In this study, we evaluated a combination therapy comprising human neural stem cells derived from induced pluripotent stem cells (iPSC-NSC), human mesenchymal stem cells (MSC), and a pH-responsive polyacetal–curcumin nanoconjugate (PA-C) that allows the sustained release of curcumin. In vitro analysis demonstrated that PA-C treatment protected iPSC-NSC from oxidative damage in vitro, while MSC co-culture prevented lipopolysaccharide-induced activation of nuclear factor-κB (NF-κB) in iPSC-NSC. Then, we evaluated the combination of PA-C delivery into the intrathecal space in a rat model of contusive SCI with stem cell transplantation. While we failed to observe significant improvements in locomotor function (BBB scale) in treated animals, histological analysis revealed that PA-C-treated or PA-C and iPSC-NSC + MSC-treated animals displayed significantly smaller scars, while PA-C and iPSC-NSC + MSC treatment induced the preservation of β-III Tubulin-positive axons. iPSC-NSC + MSC transplantation fostered the preservation of motoneurons and myelinated tracts, while PA-C treatment polarized microglia into an anti-inflammatory phenotype. Overall, the combination of stem cell transplantation and PA-C treatment confers higher neuroprotective effects compared to individual treatments.     

Synthesis and application of core–shell particles as toughening agents for epoxies

Poly(butadiene-co-styrene) [P(B-S)] core-poly(methyl methacrylate) (PMMA) shell particles were prepared using a two-step emulsion polymerization. These core-shell particles were used to toughen an epoxy polymer. The role of particle-epoxy interfaces were studied by systematically varying the shell compositions of the core-shell particles such as PMMA, P[MMA-acrylonitrile (AN)], P[MMA-glycidyl methacrylate (GMA)] and P[MMA-divinyl benzene(DVB)]. Therefore, the nature of the particle-epoxy interfaces is varied in terms of physical interactions and chemical bonding. The fracture toughness values of the toughened epoxies were measured using linear elastic fracture mechanics. Results indicate that the morphology of the dispersed particles in the epoxy matrix plays an important role in the toughening of epoxies. This degree of dispersion can be varied by incorporating AN and GMA comonomers in the PMMA shells or by crosslinking the shell. In summary, nanoscale interactions of the rubber-matrix interface do not directly influence fracture toughness, instead, it was found that the nanoscale interactions could be used to control the blend morphology which has a dramatic effect on toughness. © 1995 John Wiley & Sons, Inc.     

Effects of physical refining on contents of waxes and fatty alcohols of refined olive oil

Changes in the contents of waxes and fatty alcohols during deodorization/physical refining of bleached olive oil were studied. Experiments were carried out with 1.85% acidity oil, which was physically refined in a discontinuous deodorizer of 250-kg maximum capacity using nitrogen as stripping gas instead of steam. The variables studied were load and temperature of oil in the deodorizer as well as N₂ flow. Analyses of waxes and alcohols were carried out at different operation times. The maximum content of wax was always observed when the oil reached the deodorization temperature. The variation in the wax content depended on temperature and N₂ flow. Wax decomposition started and continued during the operating time, and a progressive decrease, which was pronounced between 3 and 4 h, was observed. Small changes in waxes were observed between 4 and 5 h. Total content of fatty alcohols diminished throughout the operating time, and changes did not depend on the variables studied.     

High PVC film‐forming composite latex particles via miniemulsification,part 1: Preparation

Miniemulsification technology was used to encapsulate TiO₂ particles inside a styrene/n‐butyl acrylate copolymer with high loading levels (11 to 70% PVC (pigment volume concentration)). In this approach, a St/BA copolymer dissolved in toluene in the presence of a costabilizer (hexadecane) was mixed with a dispersion of TiO₂ particles in toluene and sonified, and then emulsified in an aqueous surfactant solution by sonification. The effect of sonification time on both the dispersibility of the TiO₂ particles in the presence of the copolymer and hexadecane and on the encapsulated particle size was investigated. Particle size analysis by dynamic light scattering showed that these composite latexes are quite stable. It was also found that as the TiO₂ loading increased from 11 to 43% PVC, the particle size of the TiO₂ dispersion decreased while the polymer‐encapsulated TiO₂ particle size increased. The effect of surfactant concentration (sodium lauryl sulfate, SLS) on the encapsulated particle size was investigated using four different SLS concentrations in the 11% PVC system. The results showed that as the SLS concentration increased the particle size decreased, as expected. Also it was found that the minimum surfactant concentration that gives stable encapsulated TiO₂ particles is above 10 mM SLS. The role of HD in the recipe was studied for an artificial latex containing no TiO₂ and one prepared at 11% PVC, in terms of particle size before and after solvent stripping, and its effect on the T_g. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 4504–4516, 2006     

Short-term prediction of traffic flow using a binary neural network

This paper introduces a binary neural network-based prediction algorithm incorporating both spatial and temporal characteristics into the prediction process. The algorithm is used to predict short-term traffic flow by combining information from multiple traffic sensors (spatial lag) and time series prediction (temporal lag). It extends previously developed Advanced Uncertain Reasoning Architecture (AURA) k-nearest neighbour (k-NN) techniques. Our task was to produce a fast and accurate traffic flow predictor. The AURA k-NN predictor is comparable to other machine learning techniques with respect to recall accuracy but is able to train and predict rapidly. We incorporated consistency evaluations to determine whether the AURA k-NN has an ideal algorithmic configuration or an ideal data configuration or whether the settings needed to be varied for each data set. The results agree with previous research in that settings must be bespoke for each data set. This configuration process requires rapid and scalable learning to allow the predictor to be set-up for new data. The fast processing abilities of the AURA k-NN ensure this combinatorial optimisation will be computationally feasible for real-world applications. We intend to use the predictor to proactively manage traffic by predicting traffic volumes to anticipate traffic network problems.     

Maximization of total surface area of Pt-SnO<Subscript>2</Subscript>/Al<Subscript>2</Subscript>O<Subscript>3</Subscript> catalyst by the Taguchi method

The maximization of the total surface area of Pt-SnO₂/Al₂O₃ catalyst was studied by using the Taguchi method of experimental design. The catalysts were prepared by sol-gel method. The effects of HNO₃, H₂O and aluminum nitrate concentrations and the stirring rate on the total surface area were studied at three levels of each. L₉ orthogonal array leading nine experiments was used in the experimental design. The parameter levels that give maximum total surface area were determined and experimentally verified. In the range of conditions studied it was found that, medium levels of HNO₃ and H₂O concentration and lower levels of aluminum nitrate concentration and stirring rate maximize the total surface area.