Preparation, Characterization and Photocatalytic Properties of Ba-Cd-Sr-Ti Doped Fe3O4 Nanohollow Spheres on Removal of Congo Red Under Visible-Light Irradiation

In this study, Ba-Cd-Sr-Ti doped Fe₃O₄ nanohollow spheres were successfully prepared via a simple solvothermal method. The crystal size, structure, morphology and elemental analysis of the as-prepared sample were investigated in detail by X-ray diffraction (XRD), FT-IR, scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy, respectively. Magnetic hysteresis measurement was carried out on a vibrant sample magnetometer (VSM) showing the soft ferromagnetic property at room temperature. The synthesized nanohollow spheres were employed as a photocatalyst to study the photocatalytic degradation of dye contaminations. The UV-Vis results showed that the specimen could well catalyze the decolorizing of congo red (CR) solution and a removal efficiency of 99.5 % was obtained at pH 6. The optical characteristic of the products was studied by estimating the band-gap energy based on diffuse-reflectance spectroscopy (DRS) which represented the doped magnetite with semiconductor metals to be more prone in the visible region as compared to UV region. Some factors such as initial dye concentration, pH, and contact time influencing the decomposition of CR were evaluated.     

Design equations for prediction of pressuremeter soil deformation moduli utilizing expression programming systems

Providing precise estimations of soil deformation modulus is very difficult due to its dependence on many factors. In this study, gene expression programming (GEP) and multi-expression programming (MEP) systems are presented to derive empirical equations for the prediction of the pressuremeter soil deformation modulus. The employed expression programming (EP) systems formulate the soil deformation modulus in terms of the soil physical properties. Selection of the best models is on the basis of developing and controlling several models with different combinations of the affecting parameters. The proposed EP-based models are established upon 114 pressuremeter tests on different soil types conducted in this study. The generalization capabilities of the models are verified using several statistical criteria. Contributions of the variables influencing the soil modulus are evaluated through a sensitivity analysis. The GEP and MEP approaches accurately characterize the soil deformation modulus resulting in a very good prediction performance. The result indicates that moisture content and soil dry unit weight can efficiently represent the initial state and consolidation history of soil for determining its modulus.     

Effects of ultrahigh speed twin screw extrusion on the thermal and mechanical degradation of polystyrene

This article characterizes a novel twin screw extrusion (TSE) process with the capability of rotating at speeds up to 4500 rpm. The resulting extreme high shear rate is expected to result in molecular weight changes due to thermomechanical degradation of the polymeric materials being extruded, polystyrene (PS) in this case. In order to differentiate between mechanical and thermal factors affecting degradation of PS running at ultrahigh speeds and also to evaluate the relative importance of the two mechanisms, PS has been extruded at different screw speeds and different barrel temperatures with corresponding melt temperatures. Viscosity measurements and size exclusion chromatography measurements show the extent of degradation due to mechanical stress as a result of high screw rotational speeds. Furthermore, through analyzing the kinetics of PS depolymerization, the reaction rate and hypothetical apparent temperatures at each screw speed have been calculated. All results support the idea that the mechanical shear stress can be considered as the controlling factor of polymer degradation in ultrahigh speed TSE. POLYM. ENG. SCI., 56:743–751, 2016. © 2016 Society of Plastics Engineers     

Improving Blood Compatibility of Polyethersulfone Hollow Fiber Membranes via Blending with Sulfonated Polyether Ether Ketone

Appropriate membrane for blood contacting applications requires hemocompatibility and high permeation flux; it should inhibit proteins or platelets adsorption and still possess high permeability. Aiming to improve the polyethersulfone (PES) hollow fiber membrane hemocompatibility, sulfonated polyether ether ketone (SPEEK) is self‐synthesized in the present research and added to PES in different ratios. Scanning electron microscopy images have revealed significant changes in PES membranes structure after addition of SPEEK, which can influence water permeation property of the membranes. Water contact angles of the membranes have reduced from 75° to 50° after addition of 4 wt% SPEEK. Influence of SPEEK addition on hemocompatibility of the PES membranes is evaluated via protein (bovine serum albumin) adsorption, platelet attachment, and coagulation time (APTT and TT) assays. Obtained results reveal that hemocompatibility of the modified hollow fiber membranes is enhanced as a result of emerging repulsive forces between negative charges on the membranes surface and negatively charge blood components.

     

Performance assessment of decision-making units using an adaptive neural network algorithm: one period case

This study proposes a nonparametric method based on adaptive neural network (ANN) technique for measuring efficiency of decision making units (DMUs) in one period case as a complementary tool for the ANN-based efficiency methods in the previous studies. In previous studies, there are needed to have large volume of data, and so the proposed method in this study is more applicable because it can be used for the cases which have no historical data. In fact, a limitative weakness of the ANN-based efficiency methods about applying them for these cases is removed. So, it can be a competitive method to the other common tools for measuring efficiency. By noting the importance of flexible manufacturing system, this study presents a decision-making model for optimization of operators’ allocation in cellular manufacturing system by computer simulation. The methodology is illustrated through its application on a previously reported dataset. It was found out that ANN provides more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored.     

A hierarchical stochastic modelling approach for reconstructing lung tumour geometry from 2D CT images

ABSTRACT

Lung cancer is one of the deadliest cancers in both men and women. Nowadays, several methods are used to cure this cancer including surgery and radiotherapy. These methods require prior knowledge about the shape of tumours. This type of knowledge may also help physicians to determine the cancer type. In this paper we propose a novel approach for 3D reconstruction of tumour geometry from a sequence of 2D images. The proposed approach consists of two phases: tumour segmentation from computed tomography (CT) images and 3D shape reconstruction. Segmentation is conducted using snake optimisation and Gustafson–Kessel clustering. For 3D reconstruction, first, we propose a new approach to interpolate some intermediate slices between original slices. Then, the well-known marching cubes algorithm is used for surface reconstruction. Eventually, we smoothen the surface using an explicit fairing algorithm. Experiments show that our new approach can highly improve the quality and the accuracy of the reconstructed tumour shape.