This study investigates the potential of biogas recovery from used engine oil (UEO) by co-digestion with animals’ manure, including cow dung (CD), poultry manure (PM), and cattle manure (CM). The experimental work was carried out in anaerobic biodigesters at mesophilic conditions (37°C). Two groups of biodigesters were prepared. Each group consisted of 4 digesters. UEO was the main component in the first group of biodigesters with and without inoculum, whereby a mix of UEO and petroleum refinery oily sludge (ROS) was the component in the second group of biodigesters. The results revealed that for UEO-based biodigesters, maximum biogas production was 0.98, 1.23, 1.93, and 0 ml/g VS from UEO±CD, UEO±CM, UEO±PM, and U

This research aims to show the most important approaches applicable in forming the accounting standards , the  importance approaches used to formulate local accounting standards & the  need to cancel or develop the unified accounting system in Iraq besides activate the local auditing & accounting standards council to issue accounting standards able to save the relevance & Reliable accounting information that serve the decisions of stockholders and others of stakeholders in the incorporate companies , especially the companies listed in the Iraq securities exchange , So this study based partially on analyzing the questionnaire form which has been designed to inquiry the specialists and experts opinion about the accoun

Integrating Renewable Energy (RE) into Distribution Power Networks (DPNs) is a choice for efficient and sustainable electricity. Controlling the power factor of these sources is one of the techniques employed to manage the power loss of the grid. Capacitor banks have been employed to control phantom power, improving voltage and reducing power losses for several decades. The voltage sag and the significant power losses in the Iraqi DPN make it good evidence to be a case study proving the efficiency enhancement by adjusting the RE power factor. Therefore, this paper studies a part of the Iraqi network in a windy and sunny region, the Badra-Zurbatya-11 kV feeder, in the Wasit governorate. A substation of hybrid RE sources is connected to this

Objective: The purpose of this study was to assess the effectiveness of Vibriophage Universiti Sains Malaysia 8 (VPUSM 8), a bacteriophage that destroys bacteria, in managing the proliferation of Vibrio cholerae, specifically the El Tor serotype, as an alternate therapeutic strategy. Methods: The study entailed subjecting water samples from Kelantan, Malaysia, to reproduce the natural circumstances that promote the growth of V. cholerae. Subsequently, the samples were contaminated with the V. cholerae O1 El Tor Inaba strain and treated using VPUSM 8. The study employed a controlled experimental design, wherein the samples were divided into three groups, each experiencing different treatment methods. Quantifying the number of colony-

Due to the great evolution in digital commercial cameras, several studies have addressed the using of such cameras in different civil and close-range applications such as 3D models generation. However, previous studies have not discussed a precise relationship between a camera resolution and the accuracy of the models generated based on images of this camera. Therefore the current study aims to evaluate the accuracy of the derived 3D buildings models captured by different resolution cameras. The digital photogrammetric methods were devoted to derive 3D models using the data of various resolution cameras and analyze their accuracies. This investigation involves selecting three different resolution cameras (low, medium and

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

The structure, optical, and electrical properties of SnSe and its application as photovoltaic device has been reported widely. The reasons for interest in SnSe due to the magnificent optoelectronic properties with other encouraging properties. The most applications that in this area are PV devices and batteries. In this study tin selenide structure, optical properties and surface morphology were investigated and studies. Thin-film of SnSe were deposit on p-Si substrates to establish a junction as solar cells. Different annealing temperatures (as prepared, 125,200, 275) °C effects on SnSe thin films were investigated. The structure properties of SnSe was studied through X-ray diffraction, and the results appears the increasing of the peaks

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

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