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.     

Structural,thermal, and mechanical properties of silanized boron carbide doped epoxy nanocomposites

In the presented study, the structural, thermal, and mechanical properties of the nanocomposites were investigated by doping silanized hexagonal boron carbide (h-B₄C) nanoparticles in varying proportions (0.5%, 1%, 2%, 3%, 4%, and 5%) into the epoxy resin by weight. For this purpose, the surfaces of h-B₄C nanoparticles were silanized by using 3-(glycidyloxypropyl) trimethoxysilane (GPS) to improve adhesion between h-B₄C nanoparticles and epoxy matrix. Then, the silanized nanoparticles were added to the resin by ultrasonication and mechanical stirring techniques to produce nanocomposites. The bond structure differences of silanized B₄C nanoparticles (s-B₄C) and nanoparticle doped composites were investigated by using Fourier transform infrared spectroscopy. Scanning electron microscopy and energy dispersion X-ray spectroscopy (SEM-EDS) technique was used to examine the distribution of nanoparticles in the modified nanocomposites. Differential scanning calorimetry and thermogravimetric analysis techniques were used to determine the thermal properties of the neat and s-B₄C doped nanocomposites. The tensile test and dynamic mechanical analysis were performed to determine the mechanical properties. When the experimental results were examined, changes in the bonding structure of the s-B₄C nanoparticles doped nanocomposites and significant improvements in the mechanical and thermal properties were observed. The optimum doping ratio was determined as 2% by weight. At this doping ratio, the T_g, tensile strength and storage modulus increased approximately 18%, 35%, and 44% compared to the neat composite, respectively.     

Parameter-Dependent Lyapunov Functions for Linear Systems With Constant Uncertainties

Robust stability of linear time-invariant systems with respect to structured uncertainties is considered. The small gain condition is sufficient to prove robust stability and scalings are typically used to reduce the conservatism of this condition. It is known that if the small gain condition is satisfied with constant scalings then there is a single quadratic Lyapunov function which proves robust stability with respect to all allowable time-varying perturbations. In this technical note we show that if the small gain condition is satisfied with frequency-varying scalings then an explicit parameter dependent Lyapunov function can be constructed to prove robust stability with respect to constant uncertainties. This Lyapunov function has a rational quadratic dependence on the uncertainties.     

Analysis of autocatalytic networks in biology

Autocatalytic networks, in particular the glycolytic pathway, constitute an important part of the cell metabolism. Changes in the concentration of metabolites and catalyzing enzymes during the lifetime of the cell can lead to perturbations from its nominal operating condition. We investigate the effects of such perturbations on stability properties, e.g., the extent of regions of attraction, of a particular family of autocatalytic network models. Numerical experiments demonstrate that systems that are robust with respect to perturbations in the parameter space have an easily “verifiable” (in terms of proof complexity) region of attraction properties. Motivated by the computational complexity of optimization-based formulations, we take a compositional approach and exploit a natural decomposition of the system, induced by the underlying biological structure, into a feedback interconnection of two input–output subsystems: a small subsystem with complicating nonlinearities and a large subsystem with simple dynamics. This decomposition simplifies the analysis of large pathways by assembling region of attraction certificates based on the input–output properties of the subsystems. It enables numerical as well as analytical construction of block-diagonal Lyapunov functions for a large family of autocatalytic pathways.     

Edge cracks in a transversely isotropic hollow cylinder

The analytical solution for the linear elastic, axisymmetric problem of inner and outer edge cracks in a transversely isotropic infinitely long hollow cylinder is considered. The z = 0 plane on which the crack lies is a plane of symmetry. The loading is uniform crack surface pressure. The mixed boundary value problem is reduced to a singular integral equation where the unknown is the derivative of the crack surface displacement. An asymptotic analysis is done to derive the generalized Cauchy kernel associated with edge cracks. It is shown that the stress intensity factor is a function of three material parameters. The singular integral equation is solved numerically. Stress intensity factors are presented for various values of material and geometric parameters.     

Carboxymethyl sago pulp/chitosan hydrogel as an immobilization medium for activated sludge for p-nitrophenol biodegradation

In this study, carboxymethyl sago pulp (CMSP) derived from sago waste was successfully crosslinked with ferric ions in the presence of chitosan forming a novel immobilization matrix for p-nitrophenol (PNP)-acclimated activated sludge. On the basis of the shortest biodegradation time of PNP, the optimized operational conditions of immobilization were found to be: 7 w/v% CMSP, 9 g L⁻¹ of activated sludge, 0.1 M ferric ion, and 15 min of crosslinking time. Observable inhibited PNP biodegradation was exhibited by the suspended activated sludge at the initial PNP concentration of 400 mg L⁻¹. In contrast, complete mineralization was achieved by the CMSP/chitosan-immobilized activated sludge (CMSP/Ch-AS) beads. The results revealed the important role of CMSP/Ch hydrogel in protecting activated sludge from the toxicity of PNP. The CMSP/Ch-AS beads could be reused consecutively up to three and two cycles, respectively, for the biodegradation of PNP at 200 and 400 mg L⁻¹, with the attainment of more than 99% of PNP removal at each cycle. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47531.     

Stochastic resonance in binary composite hypothesis-testing problems in the Neyman–Pearson framework

Performance of some suboptimal detectors can be enhanced by adding independent noise to their inputs via the stochastic resonance (SR) effect. In this paper, the effects of SR are studied for binary composite hypothesis-testing problems. A Neyman–Pearson framework is considered, and the maximization of detection performance under a constraint on the maximum probability of false-alarm is studied. The detection performance is quantified in terms of the sum, the minimum, and the maximum of the detection probabilities corresponding to possible parameter values under the alternative hypothesis. Sufficient conditions under which detection performance can or cannot be improved are derived for each case. Also, statistical characterization of optimal additive noise is provided, and the resulting false-alarm probabilities and bounds on detection performance are investigated. In addition, optimization theoretic approaches to obtaining the probability distribution of optimal additive noise are discussed. Finally, a detection example is presented to investigate the theoretical results.