Simultaneous shape and topology optimization of shell structures

In this research, Method of Moving Asymptotes (MMA) is utilized for simultaneous shape and topology optimization of shell structures. It is shown that this approach is well matched with the large number of topology and shape design variables. The currently practiced technology for optimization is to find the topology first and then to refine the shape of structure. In this paper, the design parameters of shape and topology are optimized simultaneously in one go. In order to model and control the shape of free form shells, the NURBS (Non Uniform Rational B-Spline) technology is used. The optimization problem is considered as the minimization of mean compliance with the total material volume as active constraint and taking the shape and topology parameters as design variables. The material model employed for topology optimization is assumed to be the Solid Isotropic Material with Penalization (SIMP). Since the MMA optimization method requires derivatives of the objective function and the volume constraint with respect to the design variables, a sensitivity analysis is performed. Also, for alleviation of the instabilities such as mesh dependency and checkerboarding the convolution noise cleaning technique is employed. Finally, few examples taken from literature are presented to demonstrate the performance of the method and to study the effect of the proposed concurrent approach on the optimal design in comparison to the sequential topology and shape optimization methods.     

The effect of particle size distribution on barite reduction

The present study is a follow-up of investigation on barite reduction to barium sulfide as a function of starting particle size distribution and temperature of reaction. In this work we study the high temperature reduction process of barite from the view point of particle size distribution. Conversion-time data have been obtained using iodometry method in each isothermal condition. A modified kinetic model used to express the carbothermic reduction process. To obtain the values of activation energy and frequency factor, the same expression was selected for each sample at all temperatures. The rate of reaction is found to be related to the particle size distribution and the gasification reaction of coke which has influence on reduction process. The kinetic parameters calculated from standard analysis of isothermal kinetic data indicated that the particle size of barite controlled the reaction when it was coarser than 400 mesh both in presence and absence of catalyst.     

Electrospun nanofibrous alginate sulfate scaffolds promote mesenchymal stem cells differentiation to chondrocytes

Cartilage tissue engineering is one of the interesting approaches used for repairing cartilage injuries. This study reports the fabrication of polyvinyl alcohol/alginate sulfate (PVA/ALG-S) nanofibrous mats as a functional support for chondrogenic differentiation of human bone marrow mesenchymal stem cells (hBM-MSCs). The PVA/ALG-S nanofibers were obtained through electrospinning of PVA solutions containing 10, 20, and 30 wt% of ALG-S. The appearance of a band at 833 cm⁻¹ assigned to the symmetrical C O S vibration associated to a C O SO₃ group confirmed the presence of ALG-S in nanofibrous mat. The SEM images illustrated the bead-free and smooth morphology of PVA/ALG-S nanofibers with a mean diameter of 185 ± 0.06 nm. The MTT assay of the hBM-MSCs seeded on scaffolds indicated the appropriate cytocompatibility of nanofibrous PVA/ALG-S scaffolds. Furthermore, the appropriate attachment and spreading of the hBM-MSCs based on SEM images, and their differentiation to the chondrocyte-like cells accompanied by a decrease in cell growth on MTT analysis and more color absorption in alician blue staining indicated the effective role of alginate sulfate on cell differentiation. Finally, the expression of Type II collagen by RT-PCR and immunocytochemistry analyses revealed the chondrogenic differentiation of hBM-MSCs on alginate sulfate nanofibers.     

The impacts of tomato residuum extract with Arabic gum and dill essential oil on the shelf life improvement of trout fillets stored at chilly condition

The objective of this study was to evaluate the effects of tomato residuum extract (TRE) dipping and Arabic gum (AG) coating enriched with dill essential oil (DEO) on the shelf life extension of refrigerated trout fillets. Gas chromatography/mass spectrometry analysis revealed that the main constituents of DEO were alpha-phellandrene (30.17%), limonene (28.31%), and carvone (21.31%). Antioxidant activities of acetone, ethanol, methanol, cold, and hot water extracts of tomato residuum were examined using reducing power and 2,2-azinobis-3-ethylbenzothiazoline-6-sulphonic acid assays in maceration, ultrasound, and combined ultrasound and maceration extraction methods. The strongest antioxidant activities were found in the ultrasound-assisted extraction with ethanol 50%. Thiobarbituric acid, total volatile basic nitrogen, and peroxide values indicated that TRE 3%–AG–DEO 2% and TRE 6%–AG–DEO 2% treatments could significantly (p ≤ .05) extend the shelf life of the fillets. Also, sensory evaluation showed that TRE along with DEO had significant (p ≤ .05) pleasant effects on the sensory characteristics of the fillets. It was concluded that TRE dipping along with AG coating containing DEO could be a suitable alternative for the synthetic preservative in the refrigerated trout fillets.     

Synthesis of novel dithiocarbamyl-containing organosilicon compounds

Aldehydes-bearing dithiocarbamate moieties were generated via highly efficient and simple method based on the one-pot reaction of amines, CS₂, and 4-(bromoalkoxy)benzaldehydes with the use of K₂CO₃ as a catalyst under solvent-free conditions. The mild reaction conditions, high yields, and broad scope of the reaction, illustrate the good synthetic utility of this method. The newly synthesized aldehydes were converted to 1,1-bis(trimethylsilyl)-1-alkenes via the Peterson olefination reaction and produced dithiocarbamate-based organosilane compounds.     

Progress in stability of organic solar cells exposed to air

In this paper, the stability of small-molecule organic solar cells based on copper phthalocyanine (CuPc) and fullerene (C₆₀) is investigated. The use of silver instead of aluminum as the metal electrode in these solar cells, with smaller grain size and grain boundaries as well as with more uniform grain size distribution in the film, results in significant improvement in the lifetime of the devices. The substantial role of silver in the protection of the cells against permeation of oxygen and/or water molecules into the organic thin films is confirmed. Substitution of a thin buffer layer (70 Å) of bathophenanthroline (Bphen) for bathocuproine (BCP), sandwiched between C₆₀ and the cathode, makes considerable progress in the lifetime of the device.     

Sacrificial‐Post Templating Method for Block Copolymer Self‐Assembly

A sacrificial‐post templating method is presented for directing block copolymer self‐assembly to form nanostructures consisting of monolayers and bilayers of microdomains. In this approach, the topographical post template is removed after self‐assembly and therefore is not incorporated into the final microdomain pattern. Arrays of nanoscale holes of different shapes and symmetries, including mesh structures and perforated lamellae with a bimodal pore size distribution, are produced. The ratio of the pore sizes in the bimodal distributions can be varied via the template pitch, and agrees with predictions of self consistent field theory.     

ECG arrhythmia recognition via a neuro-SVM-KNN hybrid classifier with virtual QRS image-based geometrical features

In this study, a new supervised noise-artifact-robust heart arrhythmia fusion classification solution, is introduced. Proposed method consists of structurally diverse classifiers with a new QRS complex geometrical feature extraction technique.Toward this objective, first, the events of the electrocardiogram (ECG) signal are detected and delineated using a robust wavelet-based algorithm. Then, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Next, the curve length of each excerpted segment is calculated and is used as the element of the feature space. Discrimination power of proposed classifier in isolation of different Gold standard beats was assessed with accuracy 98.20%. Also, proposed learning machine was applied to 7 arrhythmias belonging to 15 different records and accuracy 98.06% was achieved. Comparisons with peer-reviewed studies prove a marginal progress in computerized heart arrhythmia recognition technologies.