Flexible poly(styrene-ethylene-butadiene-styrene) hybrid nanofibers for bioengineering and water filtration applications

Among the thermoplastic elastomers that play important roles in the polymer industry due to their superior properties, styrene-based species and polyurethane block copolymers are of great interest. Poly(styrene-ethylene-butadiene-styrene) (SEBS) as a triblock copolymer seems to have the potential to meet many demands in different applications due to various industrial requirements where durability, biocompatibility, breaking elongation, and interfacial adhesion are important. In this study, the SEBS triblock copolymer was functionalized with natural (Satureja hortensis, SH) and synthetic (nanopowder, TiO₂) agents to obtain composite nanofibers by electrospinning and electrospraying methods for use in biomedical and water filtration applications. The results were compared with thermoplastic polyurethane (TPU) composite nanofibers, which are commonly used in these fields. Here, functionalized SEBS nanofibers exhibited antibacterial effect while at the same time improving cell viability. In addition, because of successful water filtration by using the SEBS composite nanofibers, the material may have a good potential to be used comparably to TPU for the application.     

Electro-copolymerisation of indene and styrene

Electroinitiated cationic copolymerisation of indene and styrene was investigated by constant potential electrolysis. Effects of copolymerisation potential and temperature on the copolymer composition and the reactivity ratios are discussed. The reactivity ratios of the monomers were calculated according to the integrated Lewis-Mayo equation.     

Highly resistant dispensing nozzles based on zirconium dioxide for profiled CBCM. Part 1. Structure and physicomechanical properties of materials based on zirconium dioxide for producing CBCM dispensing nozzles

Technology is developed for preparing refractory components made of partially stabilized zirconium dioxide using an isostatic compaction press. Technology is provided for manufacturing dispensing nozzles using combined and separately stabilized zirconium dioxide, and also indices of the refractories obtained and imported materials are compared. __________ Translated from Novye Ogneupory, No. 3, pp. 127–131, March 2008.     

Photoelectrocatalytic humic acid degradation kinetics and effect of pH,applied potential and inorganic ions

This study addresses the removal of humic acid (HA) dissolved in an aqueous medium by a photoelectrocatalytic process. UV₂₅₄ removal and the degradation of color (Vis₄₀₀) followed pseudo‐first order kinetics. Rate constants were 1.1 × 10^?1 min^?1, 8.3 × 10^?2 min^?1 and 2.49 × 10^?2 min^?1 (R² > 0.97) for UV₂₅₄ degradation and 1.7 × 10^?1 min^?1, 6.5 × 10^?2 min^?1 and 2.0 × 10^?2 min^?1 for color removal from 5 mg dm^?3, 10 mg dm^?3 and 25 mg dm^?3 HA respectively. Following a 2 h irradiation time, 96% of the color, 98% of the humic acid and 85% of the total organic carbon (TOC) was removed from an initial 25 mg dm^?3 HA solution in the photoanode cell. Photocatalytic removal on the same photoanode was also studied in order to compare the two methods of degradation. Results showed that the photoelectrocatalytic method was much more effective than the photocatalytic method especially at high pH values and with respect to UV₂₅₄ removal. The effect of other important reaction variables, eg pH, external potential and electrolyte concentration, on the photoelectrocatalytic HA degradation was also studied. Copyright © 2003 Society of Chemical Industry     

Fuzzy rule interpolation for multidimensional input spaces in determining d50c of hydrocyclones

Fuzzy rule-based systems have been very popular in many engineering applications. In mineral engineering, fuzzy rules are normally constructed using some fuzzy rule extraction techniques to establish the determination model in predicting the d50c of hydrocyclones. However, when generating fuzzy rules from the available information, it may result in a sparse fuzzy rule base. The use of more than one input variable is also common in hydrocyclone data analysis. This paper examines the application of fuzzy interpolation to resolve the problems using sparse fuzzy rule bases, and to perform analysis of fuzzy interpolation in multidimensional input spaces.     

A new deep intuitionistic fuzzy time series forecasting method based on long short-term memory

The Journal of Supercomputing - In recent years, deep artificial neural networks can have better forecasting performance than many other artificial neural networks. The long short-term memory...     

Simultaneous afterclearing and decolorisation by ozonation after disperse dyeing of polyester

A set of trials have been conducted to examine the efficiency of ozonation on afterclearing of disperse dyed poly(ethylene terephthalate) fibres. Ozonation was performed in the cooled dyebath after the completion of the dyeing cycle. The ozone concentration used was 12.8 ± 0.3 mg/min at a gas flow rate of 400 ml/min. The results indicate that 3 min ozonation time is appropriate to achieve wash fastness results comparable to conventional reduction clearing. These results were obtained with simultaneous dyebath decolorisation ratios up to 67% and without significant colour yield ( K/S value) losses of the dyed fabric. Ozonation periods exceeding 3 min caused significant colour yield ( K/S value) losses, although dyebath decolorisation ratios increased up to 82% and wash fastness properties further improved. The chemical oxygen demand of the dyeing process decreased up to 62% by the ozonation afterclearing. The advantages of the ozonation afterclearing process are savings in terms of water, energy and time and reduction in environmental load.     

A modified genetic algorithm for forecasting fuzzy time series

Fuzzy time series approaches are used when observations of time series contain uncertainty. Moreover, these approaches do not require the assumptions needed for traditional time series approaches. Generally, fuzzy time series methods consist of three stages, namely, fuzzification, determination of fuzzy relations, and defuzzification. Artificial intelligence algorithms are frequently used in these stages with genetic algorithms being the most popular of these algorithms owing to their rich operators and good performance. However, the mutation operator of a GA may cause some negative results in the solution set. Thus, we propose a modified genetic algorithm to find optimal interval lengths and control the effects of the mutation operator. The results of applying our new approach to real datasets show superior forecasting performance when compared with those obtained by other techniques.     

Using heuristic algorithms for capacity leasing and task allocation issues in telecommunication networks under fuzzy quality of service constraints

Nowadays, every firm uses telecommunication networks in different amounts and ways in order to complete their daily operations. In this article, we investigate an optimisation problem that a firm faces when acquiring network capacity from a market in which there exist several network providers offering different pricing and quality of service (QoS) schemes. The QoS level guaranteed by network providers and the minimum quality level of service, which is needed for accomplishing the operations are denoted as fuzzy numbers in order to handle the non-deterministic nature of the telecommunication network environment. Interestingly, the mathematical formulation of the aforementioned problem leads to the special case of a well-known two-dimensional bin packing problem, which is famous for its computational complexity. We propose two different heuristic solution procedures that have the capability of solving the resulting nonlinear mixed integer programming model with fuzzy constraints. In conclusion, the efficiency of each algorithm is tested in several test instances to demonstrate the applicability of the methodology.     

The Training of Pi-Sigma Artificial Neural Networks with Differential Evolution Algorithm for Forecasting

Computational Economics - Looking at the artificial neural networks’ literature, most of the studies started with feedforward artificial neural networks and the training of many feedforward...