In this study, iron oxide nanoparticles (α-Fe₂O₃ NPs) were prepared using a readily available chili pepper plant extract from local markets. This study aims to evaluate the magnetic properties of α-Fe₂O₃ prepared in green chemistry from Capsicum plant extract. After several simple preparatory steps, such as washing and cutting, they were treated with an inorganic complex (potassium hexacyanoferrate) (K3[Fe(CN)₆]). In the first analytical step, the in vitro detection of the plant extract solution after reaction with the potassium hexacyanoferrate (III) complex revealed characteristic adsorption bands of the cyanide group, which disappeared upon complexation. The iron oxide NPs were characterized using various methods, including X

Objectives: Maxillofacial silicone is used to restore abnormalities due to congenital or acquired causes. However, the quality of silicone is far from ideal. This study was aimed at assessing the influence of the addition of cellulose nanofibers (CNFs; several nanometers wide and 2-5 micro m long) on the physical and mechanical characteristics of maxillofacial silicone elastomers. Methods: Two CNF weight percentages (0.5% and 1%) were tested, and 180 specimens were divided into one control and two experimental groups. Each group was subdivided into six subgroups. In each subgroup, ten specimens subjected to each of the following tests: tearing strength, Shore-A hardness, tensile strength, elongation percentage, surface roughness, and color

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

Abstract:

     Due to the importance of technology and the accompanying changes of the environment affecting companies that use the technology mainly in their work, especially as most companies live in an unstable dynamic environment, which motivated the researchers to choose the International Company for smart card (Keycard) as a field of research and find ways to them to face Those changes.

     The problem of the study was "limited attention to the components of technological change", which included research and development, innovation and information technology, which had an impact on the design decisions of the process (process selection, cust

Wastewater treatment plants operators prefer to make adjustments because they are more cost effective, to use the existing tank instead of building new ones. In this case an imported materials would be  used as bio-loads to increase biomass and thus maintain efficiency as the next organic loading increases.In the present study, a local substance "pumice stone" was used as a biological carrier in the aeration tank, and the experiments were carried out in five stages: without biological carriers, filling ratio of 4%,10%,20%, and25% with pumice stone, the maximum organic loading at each stage (1.1884, 1.2144, 1.9432, 2.7768, 3.3141)g BOD /l.d respectively.Other experiments were carried out to determine the best filling ratio, the SS remova

Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic performance that was optimized by r

Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H₂O₂) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO₄ concentration, current density, and electrolysis time) on the catalytic perform

Electrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µs), and pulse off time (4, 12 and 25 µs) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A