Deep-Learning Based DOA Estimation in the Presence of Multiplicative Noise

Wireless Personal Communications - The paper addresses the narrowband direction of arrival estimation problem in the presence of multiplicative noise, namely, the local scatterers affect the...     

Novel Fault Management Framework Using Markov Chain in Wireless Sensor Networks: FMMC

Wireless Personal Communications - Due to using wireless sensor nodes (WSNs) in inaccessible areas and applying limitations in making nodes to reduce costs, these networks are prone to faults. The...     

Sustainability assessment of Iranian petrochemical companies in stock exchange: A data envelopment analysis-based approach

The assessment of efficiency is always of particular importance according to different indicators from different perspectives. There are various techniques for evaluating petrochemical companies, among which the data envelopment analysis technique is one of the best techniques that can be used to calculate the relative efficiency of a set of decision-making units with network structures. In the present paper, seven petrochemical companies listed in the Iranian stock exchange were analysed. These companies were evaluated in terms of financial performance and sustainable development, and their relative efficiency was calculated during 2015–2016. According to the obtained results, only Marun Petrochemical Co. was found to be efficient in all areas and years. The results also showed that four companies were efficient in financial terms over the period under study. In the general conclusion regarding the companies' performance, Marun was ranked first, Jam was ranked second, and Zagros was ranked third.     

Surface modification of multiwalled carbon nanotubes via surface RAFT copolymerization method and capecitabine-loaded anticancer hydrogel for controlled drug delivery in stomach

ABSTRACT

In our work, reversible addition-fragmentation chain transfer (RAFT)/carbon nanotube (CNT)/acrylic acid (AA)/acrylamide (AAm) nanocomposite was synthesized by living radical polymerization. The structure and surface morphology of the synthesized RAFT-CNT-Hydrogel nanocomposites were analyzed by FTIR, ¹HNMR, SEM, TEM, XRD, and TGA/DTG techniques. The results indicated that PAA/AAm chains grafted with CNT by RAFT polymerization. RAFT-CNT-Hydrogel nanocomposites for drug release investigated in different buffers resulted in a strong pH-sensitive behavior. In total, the obtained hydrogel drug-delivery systems are presented a proper effect versus stomach cancer in vitro and in vivo, and it can be used as candidates for controlled release of anticancer drugs in stomach with exalted remedial agents.     

Multilayer perceptron with different training algorithms for streamflow forecasting

Streamflow forecasting has always been a challenging task for water resources engineers and managers. This study applies Multilayer Perceptron (MLP) networks optimized with three training algorithms, including resilient back-propagation (MLP_RP), variable learning rate (MLP_GDX), and Levenberg–Marquardt (MLP_LM), to forecast streamflow in Aspas Watershed, located in Fars province in southwestern Iran. The algorithms were trained and tested using 3 years of data. Antecedent streamflow with 1 day time lag constituted the first input vector, and MLP with this vector, labeled as MLP1 was the first model. Inclusion of streamflow with two, three, and four time lags led to input vectors 2, 3, and 4 which when combined with MLP resulted in MLP2, MLP3, and MLP4, respectively. It was found that the Levenberg–Marquardt algorithm performed best among three types of training algorithms employed for training the MLP models. Generally, the MLP4_LM model yields the best result with a determination coefficient and a root mean square error of 0.93 and 2.6 (m³/s).     

Effects of Raw Material Molar Ratio and Addition of Mg on Titanium Aluminide–Alumina Composite Formation Mechanism

Powder Metallurgy and Metal Ceramics - In this study, the effects of molar ratio of the raw materials (TiO2 and Al) and the addition of Mg on the titanium aluminide–alumina composite...     

Preparation of electrospun nanofibers based on wheat gluten containing azathioprine for biomedical application

In this study, wheat gluten fibers loaded by the azathioprine were fabricated and their physicochemical properties were studied. The nanofibers were characterized by using the scanning electron microscopy (SEM), Fourier transformed-infrared spectroscopy, X-ray diffractometry, thermogravimetric, and differential thermal analysis. The SEM images showed that the addition of polyvinyl alcohol decreased the fibers’ diameters. The diameters of 77.14?±?14.11?nm were obtained for the wheat gluten–polyvinyl alcohol loaded drug fibers. In addition, the cell viability evaluation conducted by the MTT assay proved no cytotoxicity of the prepared nonofibers at concentrations up to 4?mg/mL to human umbilical vein endothelial cell.