Myofibroblast accumulation induced by transforming growth factor-beta is involved in the pathogenesis of nasal polyps

Myofibroblasts that express alpha-smooth muscle actin (alpha-SMA) are detected in many chronic inflammatory diseases. Transforming growth factor-beta (TGF-beta) is a potent inducer of myofibroblast accumulation in tissues. In this study, scattered myofibroblasts and TGF-beta were quantified and localized in nasal polyps (NPs) and normal nasal mucosa (NM). NPs were sampled in 16 patients during ethmoidectomy and NM was obtained from 10 control subjects during rhinoplasty. alpha-SMA and TGF-beta were detected using immunohistochemistry and the numbers of labeled cells were quantified (alpha-SMA and TGF-beta indices) and compared between NPs and NM. In eight NPs, in which the pedicle was preserved, alpha-SMA and TGF-beta were evaluated and compared in the pedicle, central, and tip areas. Finally, TGF-beta expression was compared between low (zone 1), moderate (zone 2), and high (zone 3) zones of alpha-SMA positivity. alpha-SMA and TGF-beta indices were significantly higher in NPs than in NM. In the eight selected NPs, alpha-SMA-positive cells were significantly more abundant in the pedicle than in the central and tip areas, whereas TGF-beta-positive cells were significantly more numerous in the pedicle than in the tip area. The number of TGF-beta-positive cells was significantly higher in zone 3 than in zone 1 of alpha-SMA positivity. Myofibroblasts, which are abundant in NPs but rare in NM, could be involved in the growth of NPs by inducing extracellular matrix accumulation. The local development of myofibroblasts in NPs could be controlled by TGF-beta, locally produced by inflammatory cells.     

Effect of electron irradiation on alternating current electrical properties of gelatin – cadmium sulfide nano-composite films

Gelatin was doped with 1 %, 3 %, 5 % and 10 % cadmium sulfide nanoparticles in weight concentrations forming the gelatin-cadmium sulfide nanocomposites and irradiated by various electron beam doses equals 50 kGy, 75 kGy, 100 kGy, and 150 kGy using 3 MeV – 3 mA electron accelerator. The applied alternating current electrical field frequency ranging from 70 Hz to 5 MHz is what caused the fluctuation in dielectric properties and alternating current electrical conductivity of these nanocomposites. The results showed that the films of 1 %, 3 %, 5 %, and 10 % for blank (nanocomposite film without electron beam irradiation) nanocomposites had the highest dielectric parameters (έ, ϵ′′, tan δ) at 0.5 kHz with values of (0.696, 0.0233, 0.034), (0.533, 0.0114, 0.0215), (0.402, 0.001196, 0.003), and (0.459, 0.00418, 0.0091), respectively. However, the lowest dielectric parameters were (0.645, 0.00618, 0.0066), (0.523, 0.00165, 0.0215), (0.417, 0.00035, 0.0008), and (0.455, 0.00066, 0.0015) at 5 MHz, respectively. The highest conductivity values for blank nanocomposites of 1 %, 3 %, 5 %, and 10 % were 1.79×10⁻⁴ S/m, 1.45×10⁻⁴ S/m, 1.16×10⁻⁴ S/m, 1.27×10⁻⁴ S/m at 5 MHz, and the lowest values were 1.92×10⁻⁸ S/m, 1.49×10⁻⁸ S/m, 1.13×10⁻⁸ S/m, 1.26×10⁻⁸ S/m at 0.5 kHz, respectively. For irradiated nanocomposites at 5 MHz, the dielectric constant order for 1 % was 100 kGy, 150 kGy, 50 kGy, and 75 kGy with values 0.63, 0.537, 0.532, and 0.523, respectively. For 10 % weight concentration, the order was 50 kGy, 100 kGy, 150 kGy, and 75 kGy with values 0.515, 0.477, 0.47, and 0.437, respectively. Otherwise the dielectric constant order for 3 % and 5 % was 100 kGy, 75 kGy, 150 kGy, and 50 kGy. The highest dielectric properties and conductivity values for blank and irradiated nanocomposites were observed at 100 kGy for 1 %, 3 %, and 5 %.     

A robust optimization approach for imprecise data envelopment analysis

Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the input and output data in real-world problems are often imprecise or ambiguous. Some researchers have proposed interval DEA (IDEA) and fuzzy DEA (FDEA) to deal with imprecise and ambiguous data in DEA. Nevertheless, many real-life problems use linguistic data that cannot be used as interval data and a large number of input variables in fuzzy logic could result in a significant number of rules that are needed to specify a dynamic model. In this paper, we propose an adaptation of the standard DEA under conditions of uncertainty. The proposed approach is based on a robust optimization model in which the input and output parameters are constrained to be within an uncertainty set with additional constraints based on the worst case solution with respect to the uncertainty set. Our robust DEA (RDEA) model seeks to maximize efficiency (similar to standard DEA) but under the assumption of a worst case efficiency defied by the uncertainty set and it’s supporting constraint. A Monte-Carlo simulation is used to compute the conformity of the rankings in the RDEA model. The contribution of this paper is fourfold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA; (2) we address the gap in the imprecise DEA literature for problems not suitable or difficult to model with interval or fuzzy representations; (3) we propose a robust optimization model in which the input and output parameters are constrained to be within an uncertainty set with additional constraints based on the worst case solution with respect to the uncertainty set; and (4) we use Monte-Carlo simulation to specify a range of Gamma in which the rankings of the DMUs occur with high probability.     

Prediction and analysis of flow behavior of a polymer melt through nanochannels using artificial neural network and statistical methods

A new methodology, namely, artificial neural network (ANN) approach was proposed for modeling and predicting flow behavior of the polyethylene melt through nanochannels of nanoporous alumina templates. Wetting length of the nanochannels was determined to be a function of time, temperature, diameter of nanochannels, and surface properties of the inner wall of the nanochannels. An ANN was designed to forecast the relationship between the length of wetting as output parameter and other aforementioned parameters as input variables. It was demonstrated that the ANN method is capable of modeling this phenomenon with high accuracy. The designed ANN was then employed to obtain the wetting length of the nanochannels for those cases, which were not reported by the wetting experiments. The results were then analyzed statistically to identify the effect of each independent variable, namely, time, temperature, diameter of nanochannels, and surface properties of the inner wall of nanochannels as well as their combinations on the wetting length of the nanochannels. Interesting results were attained and discussed.     

A heuristic method for the vehicle routing problem with mixed deliveries and pickups

The vehicle routing problem with deliveries and pickups is a challenging extension to the vehicle routing problem that lately attracted growing attention in the literature. This paper investigates the relationship between two versions of this problem, called “mixed” and “simultaneous”. In particular, we wish to know whether a solution algorithm designed for the simultaneous case can solve the mixed case. To this end, we implement a metaheuristic based on reactive tabu search. The results suggest that this approach can yield good results.     

Determination of dairy wastewater treatability by bio-trickling filter packed with lava rocks - case study PEGAH dairy factory

This paper investigates the effectiveness of a biological trickling filter for the treatment of wastewaters produced by a company manufacturing dairy products. First a bio-trickling column with a height of 150 cm was packed with lava rocks from north mountain of Tehran. It operates with the recirculation of liquid through the packing. In order to startup the pilot scale, steady state condition was gained by pumping activated sludge and dairy wastewater for 23 days. Afterwards, dairy wastewater was added to liquid tank for treatment. Hydraulic retention time (HRT) of treatment decreases from 5 days to 1 day then at HRT of 12, 8, 7, 6 and 4 h. Results show that the average chemical oxygen demand (COD) decreased from 2,750 to 98 mg/L at HRT of 7 h and efficiency of TKN removal was more than 70%. The microorganisms developed in the bio-trickling filter were able to efficiently remove COD levels up to 2,750 mg/L, under aerobic conditions at pH values between 6.8 and 7.2 under low temperature condition between 10 and 13 °C.     

An efficient method for terminal and multiterminal pathset enumeration

The literature is abundant with algorithms for determining separately the paths for the single terminal pair, paths for multiterminal pairs and cuts for a specified terminal pair of any network, from knowledge of the reliability logic diagram (RLD). However, very few methods are available as efficient algorithms for enumerating simultaneously the paths between any single terminal pair, paths for multiterminal pairs and cuts for the specified terminal pair.The present paper provides a conceptually simple and computationally efficient algorithm to obtain simultaneously the paths between any single pair of terminals, paths for multiterminal pairs and the cuts for the specified terminal pair of interest of any complex network. The algorithm is easy and computationally economical and also applicable to graphs having both nodes and branches of finite non-zero failure probability.An illustrative example is provided to demonstrate the effectiveness of the proposed algorithm.