Preparation of superabsorbent composite based on acrylic acid-hydroxypropyl distarch phosphate and clinoptilolite for agricultural applications

Recently, using superabsorbent polymers (SAPs) are considered as a solution for reducing the water consumption particularly in agricultural applications. Presented here is the synthesis of a novel biocompatible SAP, utilizing for reducing the water consumption particularly in agricultural applications via graft copolymerization of hydroxypropyl distarch phosphate (HDP) based on tapioca starch with acrylic acid (AA), loading with clinoptilolite zeolites. A two-level factorial design of experiments, investigating the effect of the SAP composition on the water absorbency exhibited that the optimum SAP has the maximum water absorbencies of 1075 and 67 g g⁻¹ in distilled water and 0.9 wt % NaCl solution, respectively. The chemical structure of the best superabsorbent was characterized using Fourier transform infrared, X-ray diffraction, thermogravimetric analysis, and scanning electron microscopy analyses. The results revealed that AA was successfully grafted onto HDP and surface morphology of the superabsorbent was improved with incorporated clinoptilolite zeolites. In addition, the results of water absorption in different soil textures showed that within a first week after irrigation, the soil texture with 100% sand has the maximum water retention (69.6 g more than its control sample), as well as that with 50% sand, loses the absorbed moisture 49 days later than its control sample. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47365.     

Thermodynamics of the Spin-1/2 Two-Leg Ladder Compound (C_5H_{12}N)_2CuBr_4

The thermodynamic behavior of the spin \(S=1/2\) antiferromagnetic two-leg ladder compound (C \(_5\) H \(_{12}\) N) \(_{2}\) CuBr \(_{4}\) in a uniform magnetic field is studied using numerical and analytical approaches. The entropy \(S(H,T)\) and specific heat \(C(H,T)\) are calculated. The specific heat shows various behaviors in different regions of the magnetic field. The field dependence of the specific heat is almost symmetric about the average of quantum critical fields in complete agreement with experimental results. In addition, it is found that during an adiabatic demagnetization process, temperature drops in the vicinity of the field induced zero-temperature quantum phase transitions.     

MWCNTs/Cu(OH)2 nanoparticles/IL nanocomposite modified glassy carbon electrode as a voltammetric sensor for determination of the non-steroidal anti-inflammatory drug diclofenac

This paper describes the development and utilization of a new nanocomposite consisting of Cu(OH)₂ nanoparticles, hydrophobic ionic liquid 1-ethyl-3-methylimidazolium hexafluorophosphate (EMIMPF₆) and multiwalled carbon nanotubes for glassy carbon electrode modification. The nanocomposite was characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM) along with energy-dispersive X-ray spectroscopy (EDX). The modified electrode was used for electrochemical characterization of diclofenac. Using differential pulse voltammetry, the prepared sensor showed good sensitivity and selectivity with low overpotential for the determination of diclofenac in the range from 0.18 to 119 μM, with a detection limit of 0.04 μM. Electrochemical studies suggested that the MWCNTs/Cu(OH)₂ nanoparticles/IL nanocomposite modified electrode provided a synergistic augmentation on the voltammetric behavior of electrochemical oxidation of diclofenac, which was indicated by the improvement of anodic peak current.     

Improved black hole and multiverse algorithms for discrete sizing optimization of planar structures

This study compares two novel nature-inspired algorithms developed based on cosmology for discrete sizing optimization of structures. The first metaheuristic is the black hole, which is inspired by the black hole phenomenon. The second one is the multiverse, and the main inspiration for this algorithm is based on three concepts in cosmology: white holes, black holes and wormholes. Moreover, an improved version of each algorithm, termed improved black hole (IBH) and improved multiverse (IMV), is proposed to overcome the defects of their original versions in tackling the discrete sizing structural optimization problems. Three types of structure, i.e. steel trusses, steel frames and reinforced concrete frames, are presented to illustrate the efficiency of the proposed IBH and IMV algorithms. The numerical results demonstrate the excellence of the proposed improved algorithms compared with other state-of-the-art metaheuristics in the literature, in terms of their optimum solutions and reliability.     

A Benders decomposition for the location-allocation and scheduling model in a healthcare system regarding robust optimization

The hospital location and service allocation is one of the most important aspects of healthcare systems. Due to lack of studies on covering location-allocation and scheduling problems with respect to the uncertain budget, this paper develops a bi-objective hybrid model to locate hospitals and allocate machines and services scheduled. The costs of establishing facilities are assumed to be uncertain, while a robust counterpart model is employed to overcome the uncertainty. Covering the demand of each service is limited as well. Moreover, hospitals have a limited space to the specialized equipment like CT scan and MRI machines, while there is a cost constraint on hospitals and the specialized equipment. The aim of this paper is to find a near-optimal solution including the number of hospitals and the specialized equipment, the location of hospitals, the assignment of demand of each service and the specialized equipment to hospitals, the determination of allowable number of each service of hospitals, the determination of demand that should be transferred from one hospital to another (patient transfer), and schedule services. As the proposed model, minimizing the total costs and the completion time of demand simultaneously, is an NP-hard problem, it is impossible to solve its large-scale version with exact methods in a reasonable time. Thus, a hybrid algorithm including simulated annealing optimization and the Benders decomposition is employed to solve it. The CPLEX optimizer verifies the presented algorithm to solve the proposed model. The sensitivity analysis is performed to validate the proposed robust model against of uncertain situations while the Monte Carlo simulation is used to analyze the quality and the robustness of solutions under uncertain situations. The results show that the uncertainty used in the proposed model properly formulates real-world situations compared to the deterministic case. Finally, the contributions and the future research are presented.

     

Block preconditioners for saddle point systems arising from liquid crystal directors modeling

We analyze two types of block preconditioners for a class of saddle point problems arising from the modeling of liquid crystal directors using finite elements. Spectral properties of the preconditioned matrices are investigated, and numerical experiments are performed to assess the behavior of preconditioned iterations using both exact and inexact versions of the preconditioners.     

Effect of Magnetized Ethanol on the Shape Evolution of Zinc Oxide from Nanoparticles to Microrods: Experimental and Molecular Dynamic Simulation Study

In the current research, ethanol was exposed to an external magnetic field, called magnetized ethanol, and then, used as a solvent in the solvothermal method to synthesize various ZnO structures. Moreover, the morphologies of the synthesized structures are compared with those obtained using ordinary ethanol. The attained results evidently demonstrated the formation of ZnO nanoparticles and microrods by using ordinary and magnetized ethanol, respectively. Moreover, X-ray diffraction (XRD) and scanning electron microscopy (SEM) were utilized for characterizing the synthesized ZnO structures. The XRD results demonstrated that the synthesized products are in Zincite hexagonal phase. Besides, molecular dynamics simulation suggested that the molecular mobility is diminished upon using the magnetic field. It was found that the interactions among ZnO particles were enhanced by the slight increase in the magnetic field while the number of interactions between ZnO and solvent was reduced revealing the magnetic-field-induced particle growth from the molecular level insight.     

A new model-based framework for lung tissue segmentation in three-dimensional thoracic CT images

A new framework for model-based lung tissue segmentation in three-dimensional thoracic CT images is proposed. In the first stage, a parametric model for lung segmenting surface is created using shape representation based on level sets method. This model is constituted by the sum of a mean distance function and a number of weighted eigenshapes. Consequently, unlike the other model-based segmentation methods, there is no need to specify any marker point in this model. In the second stage, the segmenting surface is varied so as to be matched with the binarized input image. For this purpose, a region-based energy function is minimized with respect to the parameters including the weights of eigenshapes and coefficients of a three-dimensional similarity transform. Finally, the resulted segmenting surface is post-processed in order to improve its fitness with the lung borders of the input image. The experimental results demonstrated the outperformance of the proposed framework over its model-based counterparts in model matching stage. Moreover, it performed slightly better in terms of final segmentation results.