Biodiesel can be prepared from various types of vegetable oils or animal fats with the aid of a catalyst.
Calcium oxide (CaO) is one of the prospective heterogeneous catalysts for biodiesel synthesis. Modification
of CaO by impregnation on silica (SiO2) can improve the performance of CaO as catalyst. Egg shells and rice
husks as biomass waste can be used as raw materials for the preparation of the silica modified CaO catalyst.
The present study was directed to synthesize and characterize CaO impregnated SiO2 catalyst from biomass
waste and apply it as catalyst in biodiesel synthesis. The catalyst was synthesized by wet impregnation
method and characterized by x-ray diffraction, x-ray fluorescence, nitr

The growing demand for sustainable and high-performance asphalt binders has prompted the exploration of waste-derived modifiers. This study investigates the performance enhancement of Natural Asphalt (NA) using Sugarcane Molasses (SM) and Waste Engine Oil (WEO). The modified blends were prepared by partially replacing 50 % NA with varying proportions of SM and WEO ranging from 10 % to 40 % of the total weight of NA. Comprehensive testing was conducted, including penetration, softening point, ductility, viscosity, Bending Beam Rheometer (BBR), Multiple Stress Creep Recovery (MSCR), Energy Dispersive X-ray Spectroscopy (EDX), Fourier Transform Infrared (FTIR) spectroscopy, and Scanning Electron Microscopy (SEM). The results demonstrated that

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized

The aims of this study are to measure the defect rate and analyze the problems of production of ready concrete mixture plant by using Six Sigma methodology which is a business strategy for operations improvement depending basically on the application of its sub-methodology DMAIC improvement cycle and the basic statistical tools where the process sigma level of concrete production in the case study was 2.41 σ.

        The performance of asphalt concrete pavement has affected by many factors, the temperature is the most important environmental one which has a large effect on the structural behavior of flexible pavement materials. The main cause of premature failure of pavement is the rutting, Due to the viscoelastic nature of the asphalt cement, rutting is more pronounced in hot climate areas because the viscosity of the asphalt binder which is
inversely related to rutting is significantly reduced with the increase in temperature resulting in a more rut susceptible paving mixtures. The objective of this study is to determine the effect of temperatures variations on the permanent deformation parameters (perm

A simple low-cost approach at various exposure times was utilized to generate cold plasma in the aim to fabricate AuNPs. UV-Visible spectra and X-ray diffraction were used to characterize the nanoparticles (XRD). Surface Plasmon resonance was observed in the synthesized AuNPs at 530, 540, and 533 nm. For all samples, the patterns of XRD show very intensive peaks implying the fcc crystalline structure of AuNPs. The average crystallite size of AuNPs is ranging between 20-30 nm. The observation of morphology by FESEM revealed the spherical formation of AuNPs. Doses of 100 and 200 ppm of AuNPs were adapted to investigate their effect on the blood-mixture with and without a 20-second of cold plasma exposure. The WBC components in the blood

Background: Contact between implant material and bones must be strong and fast creation, to fulfill these properties appropriate surface modifications must apply on used implants. In this contribution; double surface modifications are applied on Ti-6Al-4V alloy to accelerate osseointegration. Materials and methods: Anodic process is utilized to create titania nanotubes (TNTs) on the screws made from Ti-6Al-4V alloy. These implants were coated with nano ZrO2 particles. Second modification was annealing anodized screws at 8000C, and implanted in tibiae of nine adult New Zealand white rabbits. Results: Physical and histological consequences of two surface modifications on Ti-6Al-4V alloy screws were studied. Scanning electron microscope (SEM)