Erosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the

The presence of deposition in the river decreases the river flow capability's efficiency due to the absence of maintenance along the river. In This research, a new formula to evaluate the sediment capacity in the upstream part of Al-Gharraf River will be developed. The current study reach lies in Wasit province with a distance equal to 58 km. The selected reach of the river was divided into thirteen stations. At each station, the suspended load and the bedload were collected from the river during a sampling period extended from February 2019 till July 2019. The samples were examined in the laboratory with a different set of sample tests. The formula was developed using data of ten stations, and the other three s

     A new colorimetric-flow injection method has been developed and validated for the detection of Cefotaxime sodium in pharmaceutical formulations. This method stands out for its rapid and sensitive nature. The formation of a brown-colored complex between Cefotaxime sodium and the Biuret reagent in a highly alkaline environment serves as the basis for the detection. The intensity of this colored complex is measured using a custom-built Continuous Flow Injection Analyzer, enabling accurate quantification of Cefotaxime sodium. Optimization studies of the chemical and physical parameters such as dilution of Biuret reagent, effect of the medium basicity, flow rate, sample loop and others have been investigated. The calibration gra

A fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th

Type 2 diabetes mellitus is a progressive and chronic disease manifested by β-cell dysfunction and improved insulin resistance. Higher levels of urokinase-type plasminogen activator receptors have been found to predict morbidity and mortality among diabetic patients with cardiac disease.

Drones play a vital role in the fundamental aspects of Industry 4.0 by converting conventional warehouses into intelligent ones, particularly in the realm of barcode scanning. Various potential issues frequently arise during barcode scanning by drones, specifically when the drone camera has difficulty obtaining distinct images due to certain factors, such as distance, capturing the image whilst flying, noise in the environment and different barcode dimensions. In addressing these challenges, this study proposes an approach that combines a proportional–integral–derivative (PID) controller with image processing techniques. The PID controller is responsible for continuously monitoring the camera’s input, detecting the difference

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti