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.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.     

Optimal Control of the Primary Drying Stage of Freeze Drying of Solutions in Vials Using Variational Calculus

The problem of operating freeze drying of pharmaceutical products in vials placed in trays of a freeze dryer to remove free water (in frozen state) at a minimum time was formulated as an optimal control problem. Two different types of freeze dryer designs were considered. In type I freeze dryer design, upper and lower plate temperatures were controlled together, while in type II freeze dryer design, upper and lower plate temperatures were controlled independently. The heat input to the material being dried and the drying chamber pressure were considered as control variables. Constraints were placed on the system state variables by the melting and scorch temperatures during primary drying stage. Necessary conditions of optimality for the primary drying stage of freeze drying process in vials are derived and presented. Furthermore, an approach for constructing the optimal control policies that would minimize the drying time for the primary drying stage was given. In order to analyze optimal control policy for the primary drying stage of the freeze-drying process in vials, a rigorous multi-dimensional unsteady state mathematical model was used. The theoretical approach presented in this work was applied in the freeze drying of skim milk. Significant reductions in the drying times of primary drying stage of freeze drying process in vials were obtained, as compared to the drying times obtained from conventional operational policies.     

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     

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.     

Biodegradable Microparticles for Simultaneous Detection of Counterfeit and Deteriorated Edible Products

In an era of globalized trade relations where food and pharmaceutical products cross borders effortlessly, consumers face counterfeit and deteriorated products at elevated rates. This paper presents multifunctional, biodegradable hydrogel microparticles that can provide information on the authenticity and the potential deterioration of the tagged food or pharmaceutical formulations. These microparticles integrate spatially patterned authenticity code with two sensors—the first one detects possible presence of pathogenic microbes through monitoring pH while the second one identifies products stored above optimal temperatures via optical monitoring of the microparticle degradation. Particles are synthesized from a biocompatible polymer and a photoinitiator, dextran modified with 2‐hydroxyethylmethacrylate and riboflavin, respectively, using a continuous, high throughput method stop‐flow lithography. The proposed synthesis approach also enables crosslinking with visible light bringing about additional flexibility to flow lithography. Model liquid and solid food and pharmaceutical products are successfully labeled with microparticles and the functionality of the sensors in aqueous solutions is demonstrated.     

Wear behavior of as-deposited and oxidized ternary (Zr,Hf)N coatings

In the present study, the tribological performance of ternary (Zr,Hf)N coatings, whose Hf content was varied between 0 and 21 wt pct, has been systematically examined in the as-deposited and oxidized conditions. Coatings were applied on AISI D2 tool steel plates by arc physical vapor deposition (PVD). Oxidation was conducted at 400 °C for times up to 12 hours in air. Wear tests revealed pronounced improvement in the wear resistance with increasing Hf content in the as-deposited coatings. Oxidation for 12 hours yielded more than a fourfold increase in wear resistance. The beneficial effect of Hf on wear resistance decreased upon oxidation.     

On-line neuro-expert monitoring system for Borssele Nuclear Power Plant

A new method for an on-line monitoring system for the nuclear power plants has been developed utilizing the neural networks and the expert system. The integration of them is expected to enhance a substantial potential of the functionality as operators support.

The recurrent neural network and the feed-forward neural network with adaptive learning are selected for the plant modeling and anomaly detection because of the high capability of modeling for dynamic behavior. The expert system is used as a decision agent, which works on the information space of both the neural networks and the human operators. The information of other sensory signals is also fed to the expert system, together with the outputs that the neural networks generate from the measured plant signals. The expert system can treat almost all known correlation between plant status patterns and operation modes as a priori set of rules.

From the off-line test at Borssele Nuclear Power Plant (PWR 480 MWe) in the Netherlands, it was shown that the neuro-expert system successfully monitored the plant status. The expert system worked satisfactorily in diagnosing the system status by using the outputs of the neural networks and a priori knowledge base from the PWR simulator. The electric power coefficient is simultaneously monitored from the measured reactive and active electric power signals.     

Sliding wear behaviour of ZrN and (Zr, 12 wt% Hf)N coatings

In the present study, the sliding wear resistances of ZrN and (Zr, 12 wt% Hf)N coatings deposited on a hardened AISI D2 tool steel by arc-physical vapor deposition (PVD) technique were examined by a ball-on-disc wear tester. Alloying of ZrN coating with 12 wt% Hf did not change the hardness significantly, but achieved an improvement on adhesion strength and dry sliding wear resistance against steel (AISI 52100-55HRC) and Al₂O₃ balls.