Analysis of MWCNT/epoxy composites at microwave frequency: reproducibility investigation

A wide-band microwave characterization of nanocomposites based on commercial multiwalled carbon nanotubes (MWCNTs) and epoxy resin is presented. The sample preparation method is discussed in detail. Field emission scanning electron microscopy is used for morphological sample analysis of nanocomposites and MWCNTs. The complex permittivity is measured in a wide frequency band (3 to 18 GHz) using a commercial dielectric probe (Agilent 85070D) and a network analyzer (E8361A). A statistical analysis based on one-way analysis of variance (ANOVA) technique is performed. The aim of this statistical analysis is to investigate the influence of concentration of nanoparticles inside the polymer matrix on the complex permittivity. This can be significantly different in nanocomposites even if the samples have similar electrical properties.     

A comparative study on the effects of Coriolus versicolor on properties of HDPE/wood flour/paper sludge composites

In this study, the effects of white-rot fungus (Coriolus versicolor) on the properties of high density polyethylene (HDPE)/wood flour/paper sludge composites were examined. In addition, the effectiveness of using coupling agent on the durability of decayed and undecayed WPCs was investigated. Two different types of sludge materials, namely paper making waste water sludge (PS) and ink-eliminated sludge (IES) were used. The mechanical properties, morphology, and water absorption of fabricated composites were investigated. At a similar wood flour loading, except for modulus of elasticity, the fungi treated composites showed lower mechanical properties (such as modulus of rupture and unnotched Izod impact strength), and higher water absorption compared to untreated composites. According to the results, addition of wood flour decreased the resistance of the composites to moisture and fungal environment. The exposure of the composites to a 4-cycle (2, 24, 48 and 72 h) water immersion caused serious damage to the interfacial adhesion between wood flour and polymer matrix due to contraction and swelling stresses developed during the cyclic exposure. The detrimental effect of fungal treatment on the water uptake of the composites could be explained by the degradation of lignin which made the cellulose content more accessible. Further, it makes chains of cavities that accelerate water absorption. However, the weight losses of all cases of treated composites were low (less than 2.5%), while PS filled composites were more susceptible to white-rot fungi. The addition of coupling agent during the compounding of wood flour and HDPE prevented the colonization and proliferation of fungus on the surface of the composites, and had an advantageous effect on the water uptake and mechanical properties of both treated and untreated composites.     

CAD/CAM scaffolds for bone tissue engineering: investigation of biocompatibility of selective laser melted lightweight titanium

The objective of the current in‐vitro study was to evaluate the biocompatibility of a new type of CAD/CAM scaffold for bone tissue engineering by using human cells. Porous lightweight titanium scaffolds and Bio‐Oss® scaffolds as well as their eluates were used for incubation with human osteoblasts, fibroblasts and osteosarcoma cells. The cell viability was assessed by using fluorescein diazo‐acetate propidium iodide staining. Cell proliferation and metabolism was examined by using MTT‐, WST‐Test and BrdU‐ELISA tests. Scanning electron microscope was used for investigation of the cell adhesion behaviour. The number of devitalised cells in all treatment groups did not significantly deviate from the control group. According to MTT and WST results, the number of metabolically active cells was decreased by the eluates of both test groups with a more pronounced impact of the eluate from Bio‐Oss®. The proliferation of the cells was inhibited by the addition of the eluates. Both scaffolds showed a partial surface coverage after 1 week and an extensive to complete coverage after 3 weeks. The CAD/CAM titanium scaffolds showed favourable biocompatibility compared to Bio‐Oss® scaffolds in vitro. The opportunity of a defect‐specific design and rapid prototyping by selective laser melting are relevant advantages in the field of bone tissue engineering and regenerative medicine.Inspec keywords: calcium compounds, scanning electron microscopy, adhesion, titanium, CAD/CAM, tissue engineering, bone, biomedical materials, cellular biophysics, biomechanics, laser materials processing, meltingOther keywords: bone tissue engineering, human cells, porous lightweight titanium scaffolds, human osteoblasts, osteosarcoma cells, cell viability, fluorescein diazo‐acetate propidium iodide staining, cell proliferation, MTT tests, WST‐Test, BrdU‐ELISA tests, cell adhesion, devitalised cells, metabolically active cells, biocompatibility, selective laser melting, CAD‐CAM scaffolds, cell metabolism, scanning electron microscopy, Ti     

Pixel’s Quantum Image Enhancement Using Quantum Calculus

The current study provides a quantum calculus-based medical image enhancement technique that dynamically chooses the spatial distribution of image pixel intensity values. The technique focuses on boosting the edges and texture of an image while leaving the smooth areas alone. The brain Magnetic Resonance Imaging (MRI) scans are used to visualize the tumors that have spread throughout the brain in order to gain a better understanding of the stage of brain cancer. Accurately detecting brain cancer is a complex challenge that the medical system faces when diagnosing the disease. To solve this issue, this research offers a quantum calculus-based MRI image enhancement as a pre-processing step for brain cancer diagnosis. The proposed image enhancement approach improves images with low gray level changes by estimating the pixel’s quantum probability. The suggested image enhancement technique is demonstrated to be robust and resistant to major quality changes on a variety of MRI scan datasets of variable quality. For MRI scans, the BRISQUE “blind/referenceless image spatial quality evaluator” and the NIQE “natural image quality evaluator” measures were 39.38 and 3.58, respectively. The proposed image enhancement model, according to the data, produces the best image quality ratings, and it may be able to aid medical experts in the diagnosis process. The experimental results were achieved using a publicly available collection of MRI scans.     

MUC1 aptamer-conjugated mesoporous silica nanoparticles effectively target breast cancer cells

In the present study, we developed aptamer (Apt) conjugated mesoporous silica nanoparticles (MSNs) for specific delivery of epirubicin (EPI) to breast cancer cells. MSNs were synthesized and functionalized with 3-mercaptopropyltrimethoxysilane (3-MPTMS), followed by MUC1 aptamer conjugation through disulfide bonds. The nanoparticles were analyzed by transmission electron microscopy (TEM), particle size analyzer, zeta potential, elemental analysis (CHNS), aptamer conjugation efficiency, drug loading efficiency, and drug release profile. Cell uptake and in vitro cytotoxicity of different formulations were performed. The results of MSNs characterization confirmed spherical nanoparticles with thiol functional groups. Particle size of obtained nanoparticles was 163?nm in deionized water. After conjugation of MUC1 aptamer and EPI loading (MSN-MUC1-EPI), particle size increased to 258?nm. The aptamer conjugation to MSNs with disulfide bonds were confirmed using gel retardation assay. Cellular uptake studies revealed better cell uptake of MSN-MUC1-EPI compared to MSN-EPI. Moreover, cytotoxicity study results in MCF7 cell lines showed improved cytotoxicity of MSN-MUC1-EPI in comparison with MSN-EPI or EPI at the same concentration of drug. These results exhibited that MSN-MUC1-EPI has the potential for targeted drug delivery into MUC1 positive breast cancer cells to improve drug efficacy and alleviate side effects.     

Fused Deposition Modeling for Unmanned Aerial Vehicles (UAVs): A Review

Additive Manufacturing (AM) is a game changing production technology for aerospace applications. Fused deposition modeling is one of the most widely used AM technologies and recently has gained much attention in the advancement of many products. This paper introduces an extensive review of fused deposition modeling and its application in the development of high performance unmanned aerial vehicles. The process methodology, materials, post processing, and properties of its products are discussed in details. Successful examples of using this technology for making functional, lightweight, and high endurance unmanned aerial vehicles are also highlighted. In addition, major opportunities, limitations, and outlook of fused deposition modeling are also explored. The paper shows that the emerge of fused deposition modeling as a robust technique for unmanned aerial vehicles represents a good opportunity to produce compact, strong, lightweight structures, and functional parts with embedded electronic.

     

Hydrogenation of natural rubber using nickel 2-ethylhexanoate catalyst in combination with triisobutylaluminum

Kinetic studies for the homogeneous hydrogenation of natural rubber, in the presence of nickel 2-ethylhexanoate and triisobutylaluminum, have been carried out by monitoring the change in hydrogen pressure in a Parr reactor of fixed volume. ¹H-NMR spectroscopy provides the measurements of the extent of hydrogenation. The reaction kinetics, in the presence of a fixed amount of catalyst, showed an overall second-order kinetic with respect to [H₂] and [CC]. The reaction has a relatively low apparent activation energy of 26.0 kJ mol^-1 and is therefore suitable for the hydrogenation of natural rubber at ambient conditions to minimize side reactions. The impurities in commercial rubbers have a slight effect on the catalyst activity. © 1996 John Wiley & Sons, Inc.     

Improved Slime Mould Algorithm based on Firefly Algorithm for feature selection: A case study on QSAR model

Feature selection (FS) methods are necessary to develop intelligent analysis tools that require data preprocessing and enhancing the performance of the machine learning algorithms. FS aims to maximize the classification accuracy by minimizing the number of selected features. This paper presents a new FS method using a modified Slime mould algorithm (SMA) based on the firefly algorithm (FA). In the developed SMAFA, FA is adopted to improve the exploration of SMA, since it has high ability to discover the feasible regions which have optima solution. This will lead to enhance the convergence by increasing the quality of the final output. SMAFA is evaluated using twenty UCI datasets and also with comprehensive comparisons to a number of the existing MH algorithms. To further assess the applicability of SMAFA, two high-dimensional datasets related to the QSAR modeling are used. Experimental results verified the promising performance of SMAFA using different performance measures.