B4C reinforced NiTi-based composites: Microstructure and wear performance

In this study, NiTi–x wt.% B₄C (x = 0, 2, and 4) composites were consolidated with spark plasma sintering method, and the effects of boron carbide reinforcement addition on the microstructure and wear behavior of samples were investigated. Identification of the constituent phases of samples by the X-ray diffraction method plus Rietveld analysis revealed that the stability of the martensite phase increased in the composite samples because of mismatch stresses between the NiTi matrix phase and the reinforcing particles, which increases the density of the dislocations and facilitates the diffusion process that subsequently leads to the formation of stable intermetallics. The results of hardness test indicated that the hardness value increased from 3.67 GPa for pure NiTi to 10.99 GPa for NiTi–4 wt.% B₄C. Results of wear test revealed that boron carbide reinforced composite specimens had higher wear resistance, whereas wear rate of NiTi sample was 3.6 × 10⁻³ mm³/N m, and it reached to .21 × 10⁻³ mm³/N m for NiTi–4 wt.% B₄C. Investigation of microstructure by scanning electron microscopy images and EDS analysis revealed that the wear mechanism in NiTi samples was abrasive and the addition of B₄C to NiTi changed the wear mechanisms from abrasive to a combination of oxidation, adhesive, and delamination mechanisms.     

An intelligent hybrid meta-heuristic for solving a case of no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines

This paper addresses the problem of no-wait two-stage flexible flow shop scheduling problem (NWTSFFSSP) considering unrelated parallel machines, sequence-dependent setup times, probable reworks and different ready times to actualize the problem. The performance measure used in this study is minimizing maximum completion time (makespan). Because of the complexity of addressed problem, we propose a novel intelligent hybrid algorithm [called hybrid algorithm (HA)] based on imperialist competitive algorithm (ICA) which are combined with simulated annealing (SA), variable neighborhood search (VNS) and genetic algorithm (GA) for solving the mentioned problem. The hybridization is carried out to overcome some existing drawbacks of each of these three algorithms and also for increasing the capability of ICA. To achieve reliable results, Taguchi approach is used to define robust parameters' values for our proposed algorithm. A simulation model is developed to study the performance of our proposed algorithm against ICA, SA, VNS, GA and ant colony optimization (ACO). The results of the study reveal the relative superiority of HA studied. In addition, potential areas for further researches are highlighted.     

Application of a modified VIKOR method for decision-making problems in lean tool selection

Group decision making with multiple criteria is the most popular method for ranking a set of alternatives. In this regard, all alternatives are compared based on a common criteria set. Meanwhile, decision makers sometimes encounter special situations, for example, having to select from among a set of alternatives without a set of criteria or with a set of criteria that are grouped/related to various alternatives. Thus, it may be impossible to select from among a set of alternatives using typical methods. Hence, in this study, a new, modified VIKOR method is proposed to address the lean tool selection problems in manufacturing systems. In this study, a model was developed to help practitioners improve their ability to solve problems when the possible solutions have their own individual criteria. In fact the modified VIKOR method can be applied to rank alternatives in threefold: alternatives with common criteria, without common criteria, with integrated common, and uncommon criteria. This paper offers numerical examples of the model, using a case study to illustrate an application of the proposed model and properly assess the validity of this new method. The results demonstrate the usefulness and effectiveness of the modified new method. The model covers the lack existing in the current literature to assess effectiveness of applying lean tools.     

Production and radiochemical separation of no-carrier-added <Superscript>88</Superscript>Y by liquid-liquid extraction

A method was suggested for the cyclotron production of ⁸⁸Y with liquid-liquid extraction. The sedimented ^natSrCO₃ target was irradiated with 18-MeV protons at current of 20 μA for 10 h. The ⁸⁸Y yields of about 1.326 MBq μA⁻¹ h⁻¹ were experimentally obtained. Solvent extraction of no-carrier-added ⁸⁸Y from irradiated strontium carbonate target in the hydrochloric acid solution was studied using di(2-ethylhexyl) hydrogen phosphate (HDEHP). The optimum separation was achieved in the system n-hexane/10% HDEHP-0.1 M HCl. Yttrium radionuclides were recovered from the HDEHP phase by stripping with 60 ml of 9 M HC1. Also, excitation functions of the proton, deuteron, and α-particle induced reactions of ⁸⁹Y, ⁸⁸Sr, ^natSr, and natRb were determined using computer codes and compared to the existing data.     

Effect of copper nanoparticles on permeability, physical, and mechanical properties of particleboard

Effects of a 200 ppm nanocopper suspension, with size range from 10 to 80 nm, on the physical and mechanical properties of particleboard made on an industrial scale at the Iran-Choob Factory were studied. Nanocopper suspension was added to the mat at two levels of 100 and 150 ml/kg dry weight wood particles and compared with control boards. Results showed that hot-pressing time was reduced by 5.7 and 3.4 % when 100 and 150 ml of nanocopper were used, respectively. Also, both levels of nanocopper consumption had improving effects on physical and mechanical properties, although in some cases not significant. Permeability was significantly decreased to its lowest value in 150 ml/kg treatment. It can be concluded that 150 ml of nanocopper/kg may be used to improve the physical and mechanical properties, to reduce press time, and to decrease permeability in particleboards. For industrially accepted outcome, 150 ml/kg of nanocopper is recommended.     

Poly(glycerol sebacate) nanoparticles for ocular delivery of sunitinib: physicochemical,cytotoxic and allergic studies

Poly(glycerol sebacate) (PGS) is a new biodegradable polymer with good biocompatibility used in many fields of biomedicine and drug delivery. Sunitinib‐loaded PGS/gelatine nanoparticles were prepared by the de‐solvation method for retinal delivery and treatment of diabetic retinopathy. The nanoparticles were characterised by Fourier‐transform infrared and differential scanning calorimetry. The effects of different formulation variables including drug‐to‐carrier ratio, gelatine‐to‐PGS ratio, and glycerine‐to‐sebacate ratio were assessed on the encapsulation efficiency (EE%), particle size, release efficiency (RE), and zeta potential of the nanoparticles. The in vitro cytotoxicity of PGS/gelatine nanoparticles was studied on L929 cells. Draize test on rabbit eyes was also done to investigate the possible allergic reactions caused by the polymer. Glycerine/sebacic acid was the most effective parameter on the EE and RE. Gelatine‐to‐PGS ratio had the most considerable effect on the particle size while the RE was more affected by the glycerine/sebacic acid ratio. The optimised formulation (S₁ G_0.7 D_21.2) exhibited a particle size of 282 nm, 34.6% EE, zeta potential of −8.9 mV, and RE% of about 27.3% for drug over 228 h. The 3‐(4,5‐dimethylthuazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay indicated PGS/gelatine nanoparticles were not cytotoxic and sunitinib‐loaded nanoparticles were not toxic at concentrations <36 nM.Inspec keywords: polymers, differential scanning calorimetry, toxicology, drug delivery systems, solvation, eye, encapsulation, particle size, drugs, biodegradable materials, nanofabrication, nanomedicine, nanoparticles, gelatin, Fourier transform infrared spectraOther keywords: gelatine‐to‐PGS ratio, glycerine‐to‐sebacate ratio, particle size, zeta potential, sunitinib‐loaded nanoparticles, biodegradable polymer, retinal delivery, differential scanning calorimetry, drug‐to‐carrier ratio, allergic reactions, physicochemistry, cytotoxicity, poly(glycerol sebacate) nanoparticles, sunitinib ocular delivery, drug delivery, sunitinib‐loaded PGS‐gelatine nanoparticles, Fourier‐transform, in vitro cytotoxicity, biocompatibility, Draize test, rabbit eyes, 3‐(4,5‐dimethylthuazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay     

Document Image Coding for Processing and Retrieval

Document images belong to a unique class of images where the information is embedded in the language represented by a series of symbols on the page rather than in the visual objects themselves. Since these symbols tend to appear repeatedly, a domain-specific image coding strategy can be designed to facilitate enhanced compression and retrieval. In this paper we describe a coding methodology that not only exploits component-level redundancy to reduce code length but also supports efficient data access. The approach identifies and organizes symbol patterns which appear repeatedly. Similar components are represented by a single prototype stored in a library and the location of each component instance is coded along with the residual between it and its prototype. A representation is built which provides a natural information index allowing access to individual components. Compression results are competitive and compressed-domain access is superior to competing methods. Applications to network-related problems have been considered, and show promising results.     

Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization

Over the last decade, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Their broad applicability, ease of use, and global perspective may be considered as the primary reason for their success. The honey-bees mating process may also be considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bees mating. In this paper, the honey-bees mating optimization algorithm (HBMO) is presented and tested with few benchmark examples consisting of highly non-linear constrained and/or unconstrained real-valued mathematical models. The performance of the algorithm is quite comparable with the results of the well-developed genetic algorithm. The HBMO algorithm is also applied to the operation of a single reservoir with 60 periods with the objective of minimizing the total square deviation from target demands. Results obtained are promising and compare well with the results of other well-known heuristic approaches.     

Asphalt colloidal types differentiated by Korcak distribution

Asphalt in a colloidal context can be considered as a sol, sol-gel or gel type where in all three cases the asphaltene particle plays an important role. Usually the three colloidal types can be differentiated by refinery processes or by rheological properties. The aggregation or clustering of the asphaltene particles (or micelles) from sol to sol-gel and finally to the gel state with a fixed lattice can follow the stochastic process of fractal Brownian motion which can fit a hyperbolic (or Korcak) distribution. A test was carried out using the same mass of various asphalts of different colloidal types for floc formation with a series of n-alkanes (dispersion media) of increasing characteristic lengths. Results from floc formation studies indicate that the value of the size distribution for the gel type is small, is higher for the sol-gel type, and is highest for the sol type. On the other hand, the surface irregularities for all three types of asphalt do not have any correlation. These observed facts are consistent with principles based on the fractal approach.