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Evaluation of mechanical properties and cytotoxicity of maxillofacial silicone material after incorporation of zirconia nanopowder
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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.

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>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</p> ... Show More
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Publication Date
Tue Nov 01 2016
Journal Name
Renewable And Sustainable Energy Reviews
Dye-sensitised solar cells: Development, structure, operation principles, electron kinetics, characterisation, synthesis materials and natural photosensitisers
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Compound Heat Transfer Enhancement in Dimpled and Sinusoidal Metal Solar Wall Ducts Fitted with Wired Inserts
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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

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Publication Date
Wed Jun 11 2025
Journal Name
Biomedical Reports
Valproic acid exposure alters histone deacetylase mRNA expression profile in oral cancer and premalignant cell lines
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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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

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Publication Date
Thu Jun 01 2017
Journal Name
Nuclear Physics A
Alpha-cluster preformation factor within cluster-formation model for odd-A and odd–odd heavy nuclei
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Synthesis, characterization and bioactivity Study from azo – ligand derived frommethyl-2-amino benzoatewith some metal ions
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A 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.

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Publication Date
Thu Aug 04 2022
Journal Name
Contemporary Nurse
ICU nurses’ safety performance related to respect for safety and management commitment: A cross-sectional study
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Publication Date
Wed Jul 27 2022
Journal Name
Journal Of Chemical Technology &amp; Biotechnology
Broad‐ranging review: configurations, membrane types, governing equations, and influencing factors on microbial desalination cell technology
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Abstract<p>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</p> ... Show More
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Publication Date
Tue Jul 26 2022
Journal Name
Frontiers In Veterinary Science
Berbamine and thymoquinone exert protective effects against immune-mediated liver injury via NF-κB dependent pathway
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Background

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 Berberis vulgaris L, is a traditional herbal medicine with several bioactivities, such as antimicrobial and anticancer activities. Thymoquinone (TQ), a phytochemical molecule derived from the Nigella sativa plant's black cumin seeds, has attracted interest owing to itsanti-inflammatory, antioxidant, and anticancer properties.

Aim

This c

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