Protein encapsulated in electrospun nanofibrous scaffolds for tissue engineering applications

The main purpose of tissue engineering is the preparation of fibrous scaffolds with similar structural and biochemical cues to the extracellular matrix in order to provide a substrate to support the cells. Controlled release of bioactive agents such as growth factors from the fibrous scaffolds improves cell behavior on the scaffolds and accelerates tissue regeneration. In this study, nanofibrous scaffolds were fabricated from biocompatible and biodegradable poly(lactic‐co‐glycolic acid) through the electrospinning technique. Nanofibers with a core–sheath structure encapsulating bovine serum albumin (BSA) as a model protein for hydrophilic bioactive agents were prepared through emulsion electrospinning. The morphology of the nanofibers was evaluated by field‐emission scanning electron microscopy and the core–sheath structure of the emulsion electrospun nanofibers was observed by transmission electron microscopy. The results of the mechanical properties and X‐ray diffraction are reported. The scaffolds demonstrated a sustained release profile of BSA. Biocompatibility of the scaffolds was evaluated using the MTT (3(4,5‐ dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide) assay for NIH‐3T3 fibroblast cells. The results indicated desirable biocompatibility of the scaffolds with the capability of encapsulation and controlled release of the protein, which can serve as tissue engineering scaffolds. © 2013 Society of Chemical Industry     

Analytical investigation of viscoelastic creeping flow and heat transfer inside a curved rectangular duct

An exact solution for creeping viscoelastic flow and heat transfer in a curved rectangular duct is presented based on the order of magnitude technique. Here, the Criminale-Eriksen-Filbey model is used as constitutive equation. The closed form of axial velocity, flow rate, flow resistance ratio, pressure distribution, stress field, temperature and Nusselt number are presented, and the effect of aspect ratio, curvature ratio and both of the first and the second normal stress differences on the flow and heat transfer are investigated. One of the noticeable results of current research is confirming the independency of flow resistance and Nusselt number of creeping flow inside the curved duct to curvature ratio at aspect ratio 0.89077.     

3D Printing-Assisted Self-Assembly to Bio-Inspired Bouligand Nanostructures

Architected materials with nano/microscale orders can provide superior mechanical properties; however, reproducing such levels of ordering in complex structures has remained challenging. Inspired by Bouligand structures in nature, here, 3D printing of complex geometries with guided long-order radially twisted chiral hierarchy, using cellulose nanocrystals (CNC)-based inks is presented. Detailed rheological measurements, in situ flow analysis, polarized optical microscopy (POM), and director field analysis are employed to evaluate the chiral assembly over the printing process. It is demonstrated that shear flow forces inside the 3D printer's nozzle orient individual CNC particles forming a pseudo-nematic phase that relaxes to uniformly aligned concentric chiral nematic structures after the flow cessation. Acrylamide, a photo-curable monomer, is incorporated to arrest the concentric chiral arrangements within the printed filaments. The time series POM snapshots show that adding the photo-curable monomer at the optimized concentrations does not interfere with chiral self-assemblies and instead increases the chiral relaxation rate. Due to the liquid-like nature of the as-printed inks, optimized Carbopol microgels are used to support printed filaments before photo-polymerization. By paving the path towards developing bio-inspired materials with nanoscale hierarchies in larger-scale printed constructs, this biomimetic approach expands 3D printing materials beyond what has been realized so far.     

Taguchi Optimization of Solvent-Antisolvent Crystallization to Prepare Ammonium Perchlorate Particles

The sphericity and size of ammonium perchlorate (AP) particles significantly influence the properties of composite propellants. As the AP particles become more spherical, the accumulation coefficient increases, the viscosity during casting decreases, and the particle loading and burning rate increase. Hence, the production of micronized AP particles with an average size between 1 and 20 μm is important to increase the loading percentage of AP in the composite propellant. Here, the Taguchi experimental design was used to optimize the solvent-antisolvent crystallization (SAC) process for the preparation of micronized AP particles with higher sphericity. SAC parameters such as the type of antisolvent, the solvent-to-antisolvent ratio, the antisolvent temperature, the stirring speed, and the retention time were investigated at four levels. The type of antisolvent and the solvent-to-antisolvent ratio were found to mainly contribute to improving the sphericity and size of the AP particles, respectively.     

PWR fuel management optimization using continuous particle swarm intelligence

The objective of nuclear fuel management is to minimize the cost of electrical energy generation subject to operational and safety constraints. In the present work, a core reload optimization package using continuous version of particle swarm optimization, CRCPSO, which is a combinatorial and discrete one has been developed and mapped on nuclear fuel loading pattern problems. This code is applicable to all types of PWR cores to optimize loading patterns. To evaluate the system, flattening of power inside a WWER-1000 core is considered as an objective function although other variables such as K_eff along power peaking factor, burn up and cycle length can be included. Optimization solutions, which improve the safety aspects of a nuclear reactor, may not lead to economical designs. The system performed well in comparison to the developed loading pattern optimizer using Hopfield along SA and GA.     

Selective recognition of Pr3 + based on fluorescence enhancement sensor

(E)-2-(1-(4-hydroxy-2-oxo-2H-chromen-3-yl)ethylidene)hydrazinecarbothioamide (L) has been used to detect trace amounts of praseodymium ion in acetonitrile–water solution (MeCN/H₂O) by fluorescence spectroscopy. The fluorescent probe undergoes fluorescent emission intensity enhancement upon binding to Pr^3 + ions in MeCN/H₂O (9/1:v/v) solution. The fluorescence enhancement of L is attributed to a 1:1 complex formation between L and Pr^3 +, which has been utilized as the basis for selective detection of Pr^3 +. The sensor can be applied to the quantification of praseodymium ion with a linear range of 1.6 × 10^? 7 to 1.0 × 10^? 5 M. The limit of detection was 8.3 × 10^? 8 M. The sensor exhibits high selectivity toward praseodymium ions in comparison with common metal ions. The proposed fluorescent sensor was successfully used for determination of Pr^3 + in water samples.     

Strength modeling and optimizing ultrasonic welded parts of ABS-PMMA using artificial intelligence methods

This study analyzes variations in metal removal rate (MRR) and quality performance of roughness average (R _a) and corner deviation (CD) depending on parameters of wire electrical discharge machining (WEDM) process in relation to the cutting of pure tungsten profiles. A hybrid method including response surface methodology (RSM) and back-propagation neural network (BPNN) integrated simulated annealing algorithm (SAA) were proposed to determine an optimal parameter setting. The results of 18 experimental runs via a Taguchi orthogonal table were utilized to train the BPNN to predict the MRR, R _a, and CD properties. Simultaneously, RSM and SAA approaches were individually applied to search for an optimal setting. In addition, analysis of variance was implemented to identify significant factors for the processing parameters. Furthermore, the field-emission scanning electron microscope images show that a lot of built-edge layers were presented on the finishing surface after the WEDM process. Finally, the optimized result of BPNN with integrated SAA was compared with that obtained by an RSM approach. Comparisons of the results of the algorithms and confirmation experiments show that both RSM and BPNN/SAA methods are effective tools for the optimization of parameters in WEDM process.     

Assay of Total Mercury in Commercial Food Supplements of Marine Origin by Means of DLLME/ICP-AES

In this work, we have developed a sensitive and cost-effective preconcentration and quantification methodology for total mercury (Hg) at trace levels in food supplements of marine origin. Dispersive liquid–liquid microextraction was successfully employed for the preconcentration of mercury at trace levels prior to inductively coupled plasma atomic emission spectrometry. The mercury was extracted as mercury-1, 5-diphenyl-3-formazathiol complex, at pH 1.0 mediated by multidroplet formation of microextraction solvent assisted by disperser solvent. The lower limit of detection obtained under the optimal conditions was 0.24 μg L⁻¹. The calibration graphs were linear up to 500 μg L⁻¹. The precision of the method in terms of relative standard deviation was 4.8% for the concentration of 100 μg L⁻¹. In order to validate the proposed method, a certified reference material RTC-QCI-049 was analyzed with the proposed procedure. Moreover, potential interference by 20 species was also evaluated.     

Neutral N,N′-bis(2-pyridinecarboxamide)-1,2-ethane as sensing material for determination of lutetium(III) ions in biological and environmental samples

The biological properties of the lutetium as well as other lanthanide ions, primarily based on their similarity to calcium, have been the bases for research into potential therapeutic applications of lanthanide series since the early part of the twentieth century. In this research, a Lu(III) potentiometric membrane sensor based on N,N′-bis(2-pyridinecarboxamide)-1,2-ethane (PCAE) is described. The sensor exhibits a Nernstian response over a concentration range of 1.0 × 10^? 6 mol L^? 1–1.0 × 10^? 1 mol L^? 1, with a detection limit of 6.0 × 10^? 7 mol L^? 1. The best performance was achieved with a membrane composition, consisting of 30% PVC, 63% o-nitrophenyl octyl ether (NPOE), 5% PCAE and 2% sodium tetraphenylborate (NaTPB). It was found that at the pH range of 4.0–9.0, the potential response of the sensor was not affected by the pH. Furthermore, the electrode presents satisfactory reproducibility, very fast response time (5 s) and relatively good discriminating ability for Lu(III) ions with respect to many common cations and other lanthanide ions. The sensor has been applied to the determination of Lu(III) in human serum and in some soil samples where domestic devices were stored.     

Experience classification for transfer learning in traffic signal control

In recent years, due to the drastic rise in the number of vehicles and the lack of sufficient infrastructure, traffic jams, air pollution, and fuel consumption have increased in cities. The optimization of timing for traffic lights is one of the solutions for the mentioned problems. Many methods have been introduced to deal with these problems, including reinforcement learning. Although a great number of learning-based methods have been used in traffic signal control, they suffer from poor performance and slow learning convergence. In this paper, a transfer learning-based method for traffic signal control has been proposed. Multi-agent system has also been used for modelling the traffic network and transfer learning has been used to make reinforcement learning agents transfer their experience to each other. Furthermore, a classifier has been utilized to classify the transferred experiences. The results show that using the proposed method leads to a significant improvement on average delay time and convergence time of the learning process.