Preparation and physicochemical study of jute and glass composites of epoxy resin of (2E, 6E)-bis(4-hydroxybenzylidene)cyclohexanone

Polymer Bulletin - Jute and glass composites of epoxy resin of (2E, 6E)-bis(4-hydroxybenzylidene)cyclohexanone (EBHBC) were prepared by compressing molding technique using three different hardeners...     

Synthesis and physicochemical study of bisphenol‐C‐formaldehyde‐toluene diisocyanate polyurethane–jute and jute–rice husk/wheat husk composites

Bisphenol‐C‐formaldehyde‐toluene‐2,4‐di isocyanate polyurethane (PU) has been synthesized at room temperature and used for the fabrication of jute and jute–rice husk/wheat husk hybrid composites. PU–jute and PU–jute–RH/WH composites were prepared under pressure of 30.4 MPa at room temperature for 8 h, while PU–jute–RH/WH composites were prepared under same pressure at 110°C for 5 h. PU–jute composite has good tensile strength and flexural strength (50–53 MPa), while PU–jute–RH/WH hybrid composites have moderate tensile strength (9–11 MPa) and a fairly good flexural strength (15–31 MPa). Composites possess 1.1–2.2 kV electric strength and 0.94–1.26 × 10¹² ohm cm volume resistivity. Water absorption in PU–jute composite is different in water (9.75%), 10% HCl (12.14%), and 10% NaCl (6.05%). Equilibrium water uptake time in salt environment is observed 96 h, while in pure water and acidic environments it is 192 h. In boiling water equilibrium water content and equilibrium time are found to be 21.7% and 3 h, respectively. Water absorption increased 2.2 times in boiling water, whereas equilibrium time reduced 64 times. Thus, PU–jute composite has excellent hydrolytic stability against boiling water, 10% HCl, and 10% NaCl solutions. Fairly good mechanical and electrical properties and excellent hydrolytic stability of composites signify their usefulness for low cost housing units and in electrical and marine industries. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2363–2370, 2006     

Enhancing level set brain tumor segmentation using fuzzy shape prior information and deep learning

Magnetic resonance imaging (MRI) brain tumor segmentation is a crucial task for clinical treatment. However, it is challenging owing to variations in type, size, and location of tumors. In addition, anatomical variation in individuals, intensity non-uniformity, and noises adversely affect brain tumor segmentation. To address these challenges, an automatic region-based brain tumor segmentation approach is presented in this paper which combines fuzzy shape prior term and deep learning. We define a new energy function in which an Adaptively Regularized Kernel-Based Fuzzy C-Means (ARKFCM) Clustering algorithm is utilized for inferring the shape of the tumor to be embedded into the level set method. In this way, some shortcomings of traditional level set methods such as contour leakage and shrinkage have been eliminated. Moreover, a fully automated method is achieved by using U-Net to obtain the initial contour, reducing sensitivity to initial contour selection. The proposed method is validated on the BraTS 2017 benchmark dataset for brain tumor segmentation. Average values of Dice, Jaccard, Sensitivity and specificity are 0.93 ± 0.03, 0.86 ± 0.06, 0.95 ± 0.04, and 0.99 ± 0.003, respectively. Experimental results indicate that the proposed method outperforms the other state-of-the-art methods in brain tumor segmentation.     

Isolation and identification of low-density polyethylene (LDPE) biodegrading bacteria from waste landfill in Yazd

Microorganisms used as a biodegradation technique can provide economic benefits and can be compatible with the environment. The aim of this study was to isolate low-density polyethylene (LDPE) degrading bacteria. The waste samples were collected from Yazd landfills. Biochemical and molecular tests based on 16S rDNA sequencing were done to identify the superior isolates. Biodegradation rate was measured using weight loss measurement, spectroscopic analysis with Fourier-transform infrared (FTIR) spectroscopy and an investigation of surface morphology changes using scanning electron microscopy (SEM). Two biodegrading isolates were identified as Pseudomonas aeruginosa strain SKN1 and strain SKN2. The weight loss of LDPE strips was measured at 10.32%. SEM micrographs showed the surface degradation and colony formation on LDPE strips. The FTIR spectrum revealed the structural changes on LDPE strip surfaces. Bio-decomposition was observed to have taken place and the bacterial strains had a special ability to biodegrade LDPE wastes.     

General DG-Methods for Highly Indefinite Helmholtz Problems

We develop a stability and convergence theory for a Discontinuous Galerkin formulation (DG) of a highly indefinite Helmholtz problem in $\mathbb R ^{d}$ , $d\in \{1,2,3\}$ . The theory covers conforming as well as non-conforming generalized finite element methods. In contrast to conventional Galerkin methods where a minimal resolution condition is necessary to guarantee the unique solvability, it is proved that the DG-method admits a unique solution under much weaker conditions. As an application we present the error analysis for the $hp$ -version of the finite element method explicitly in terms of the mesh width $h$ , polynomial degree $p$ and wavenumber $k$ . It is shown that the optimal convergence order estimate is obtained under the conditions that $kh/\sqrt{p}$ is sufficiently small and the polynomial degree $p$ is at least $O(\log k)$ . On regular meshes, the first condition is improved to the requirement that $kh/p$ be sufficiently small.     

Investigating the wicking behavior of micro/nanofibrous core-sheath PET–PAN yarn modified by dimethyl 5-sodium sulfoisophthalate

The present research aims at imparting an improved wicking ability to the recycled multifilament yarns by wrapping composite nanofibers to attain an efficient material for filtration purposes. Therefore, polyacrylonitrile nanofibers containing dimethyl 5-sodium sulfoisophthalate nanoparticles were wrapped around the recycled poly(ethylene terephthalate) yarn by means of a novel electrospinning technique. Several tests were performed to investigate the parameters affecting wicking rise and moisture regain of the samples. Taguchi method was used in two separate designs (with or without nanoparticles). Some factors such as polymer solution concentration, mass ratio of nanoparticles, take-up rate, and number of filaments were considered as the variable factors while yarn wicking rate and moisture regain were the response factors. It was found that the hydrophilic nature of nanoparticles together with the ultrafine structure of nanofibers provide yarns with enhanced wicking properties. Although solution concentration is the predominant factor in wicking rate of the yarns containing nanoparticles, the most effective factor in wicking rise and moisture regain for other cases is the number of filaments. The mechanism of nanoparticle effect on fluidic jet during electrospinning process is explained by theory of nanofluids stability which has never been validated experimentally in previous research studies. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48185.     

Erratum to: Efficient keyword search over graph-structured data based on minimal covered r-cliques

Frontiers of Information Technology & Electronic Engineering - Unfortunately the second author’s name has been misspelt. It should be read: Abbas NIKNAFS.     

Differential scanning calorimetric investigation of polymerisation of epoxy resin based on phenolphthalein with phthalic anhydride

Polymerisation of phenolphthalein-based epoxy resin with phthalic anhydride has been investigated by differential scanning calorimetry. The overall polymerisation kinetics were found to be independent of the concentration of phthalic anhydride and scan rate. The polymerisation was found to follow a simple Arrhenius-type temperature dependence up to about 80% completion.     

ZnO Nanoparticles as Ethanol Gas Sensors and the Effective Parameters on Their Performance

<正>ZnO nanoparticles are synthesized and applied as ethanol gas sensors.In some cases,the sensitivity and response time of these particles are shown to be higher than that has been reported in the literature.It has been investigated that the most possible reason for this higher gas sensing performance can be attributed to the quantity of the activity coefficient of its initial components.However,other effects such as pH and thermal decomposition are of importance as well.Specific ion interaction(SIT) model is applied to derive the mean activity coefficient values of the additives used in synthesis of ZnO nanoparticles.