Recently, several concepts and expressions have emerged that have often preoccupied the world . around the concept of environment and sustainability. This is due to the negative and irresponsible impact of man and his innovations in various industrial and technological fieldsthat have damaged the natural environment. Architecture and cities at the broader level are some of the man made components that caused these negative impacts and in the same time affected by them. What distinguishes architectural and urban projects is the consumption of large . quantities of natural resources and production larger amounts of waste and pollution, along the life of these projects. At the end of the twentieth century and the beginning of the twenty-fir

This study suggests using the recycled plastic waste to prepare the polymer matrix composite (PMCs) to use in different applications. Composite materials were prepared by mixing the polyester resin (UP) with plastic waste, two types of plastic waste were used in this work included polyethylene-terephthalate (PET) and Polyvinyl chloride (PVC) with varies weight fractions (0, 5, 10, 15, 20 and 25 %) added as a filler in flakes form. Charpy impact test was performed on the prepared samples to calculate the values of impact strength (I.S). Flexural and hardness tests were carried out to calculate the values of flexural strength and hardness. Acoustic insulation and optical microscope tests were carried out. In general, it is found that UP/PV

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Background. “Polyetheretherketone (PEEK)” is a biocompatible, high-strength polymer that is well-suited for use in dental applications due to its unique properties. However, achieving good adhesion between PEEK and hydrophilic materials such as dental adhesives or cement can be challenging. Also, this hydrophobicity may affect the use of PEEK as an implant material. Surface treatment or conditioning is often necessary to improve surface properties. The piranha solution is the treatment of choice to be explored for this purpose. Methods. PEEK disks of 10 mm diameter and 2 mm thickness were used in this study. Those samples were divided into five groups (each group has five samples). The first is the control group, in which no

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The new Hexadentate complexes type [M(H3L3)]K were prepared from the condensation reaction of Diphenylmonoxime and KOH with (Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Hg(II)) in methanol with 3:1 ligand : metal ratio to give a series of new complexes of the general formula [M(H3L3)]K (where: M(II) = Mn ,Co ,N ,Cu ,Zn and Hg).All compounds have been Characterized by spectroscopic methods [I.R, U.v-Vis, atomic absorption and microanalysis (C.H.N) along with conductivity measurements. The stability constant K and Gibbs free energy ∆G were calculated for [Co (H3L3)] K, [Ni (H3L3)] K and [Cu (H3L3)] K and complexes using spectrophotometer method. The obtained values indicate that these complexes stable in their solution. From the above data

The research includes the preparation of several complexes of the internal transition elements lanthanide (Ln = La, Nd, Er, Gd, and Dy) containing the 4f shell, with Schiff bases resulting from condensation reactions between 4-antipyrinecarboxaldehyde and 2-aminobenzothiazoles. Schiff's base was identified using FTIR spectra, UV-vis spectroscopy, elemental microanalysis CHNSO, nuclear magnetic resonance, mass spectrometry, and TGA thermal analysis. The complexes were studied and identified with elemental microanalysis CHNSO, FTIR spectroscopy, UV-vis spectroscopy, TGA thermal analysis, conductivity measurement, and magnetic sensitivity. The result showed that these complexes were classified as homogeneous bidentate complexes with th

The impacts of numerous important factors on the Energy Absorption (EA) of torsional Reinforced Concrete (RC) beams strengthened with external FRP is the main purpose and innovation of the current research. A total of 81 datasets were collected from previous studies, focused on the investigation of EA behaviour. The impact of nine different parameters on the Torsional EA of RC-beams was examined and evaluated, namely the concrete compressive strength (f’c), steel yield strength (fy), FRP thickness (tFRP), width-to-depth of the beam section (b/h), horizontal (ρh) and vertical (ρv) steel ratio, angle of twist (θu), ultimate torque (Tu), and FRP ultimate strength (fy-FRP). For the evaluation of the energy absorption capacity at di