Resilient polymeric materials such as silicone elastomers are currently used for maxillofacial prostheses construction but the strength of these materials and their clinical performance need to be optimized with the addition of reinforcing fillers. This study investigates the effect of zirconia nanopowder addition on tear strength, tensile strength, elongation at break, Shore A hardness, surface roughness and cytotoxicity of VST-50 maxillofacial silicone. Silicone base was mixed with different amounts (1%, 2% and 3%) of zirconia nanopowder using a vacuum mixer. Silicone without filler was used as control for comparison. Scanning Electron Microscopy and Atomic Force Microscopy were utilized to assess the efficiency of high-shear vacuum mixing as filler dispersion method and the surface topography, respectively. Both SEM and AFM images showed that the zirconia nanopowder were distributed fairly well within the polymer. Statistically, highly significant increase in tear strength, tensile strength and hardness with non-significant decrease in elongation at break and non-significant increase in surface roughness were seen with 1% and 2% groups. Whereas with 3% group, there was significant improvement in tear strength, tensile strength and hardness but there was significant undesirable decrease in elongation and increase in roughness. Cytotoxicity test revealed that the addition of zirconia nanopowder was nontoxic to Rat Embryonic Fibroblast (REF) cells and there was non-significant change in the cell viability of all study groups after 24- and 72-hours incubation periods. In conclusion, the addition of 2% by weight nano zirconia to VST-50 maxillofacial silicone could be beneficial in enhancing its performance.
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
An improved Metal Solar Wall (MSW) with integrated thermal energy storage is presented in this research. The proposed MSW makes use of two, combined, enhanced heat transfer methods. One of the methods is characterized by filling the tested ducts with a commercially available copper Wired Inserts (WI), while the other one uses dimpled or sinusoidal shaped duct walls instead of plane walls. Ducts having square or semi-circular cross sectional areas are tested in this work.
A developed numerical model for simulating the transported thermal energy in MSW is solved by finite difference method. The model is described by system of three governing energy equations. An experimental test rig has been built and six new duct configurations have b
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreA Ligand (ECA) methyl 2-((1-cyano-2-ethoxy-2-oxoethyl)diazenyl)benzoate with metals of (Co2+, Ni2+, Cu2+) were prepared and characterization using H-NMR, atomic absorption spectroscopy, ultra violet (UV) visible, magnetic moments measurements, bioactivity, and Molar conductivity measurements in soluble ethanol. Complexes have been prepared using a general formula which was suggested as [M (ECA)2] Cl2, where M = (Cobalt(II), Nickel(II) and Copper(II), the geometry shape of the complexes is octahedral.
Seawater might serve as a fresh‐water supply for future generations to help meet the growing need for clean drinking water. Desalination and waste management using newer and more energy intensive processes are not viable options in the long term. Thus, an integrated and sustainable strategy is required to accomplish cost‐effective desalination via wastewater treatment. A microbial desalination cell (MDC) is a new technology that can treat wastewater, desalinate saltwater, and produce green energy simultaneously. Bio‐electrochemical oxidation of wastewater organics creates power using this method. Desalination and the creation of value‐added by‐products are expected because of this ionic mov
Immune-mediated hepatitis is a severe impendence to human health, and no effective treatment is currently available. Therefore, new, safe, low-cost therapies are desperately required. Berbamine (BE), a natural substance obtained primarily from
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