The corrosion inhibiting properties of the new furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione in acidic solution (1.0 M HCl) were explored utilizing electrochemical, surface morphology (AFM), and quantum chemical calculations approaches. The novel furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione shows with an inhibitory efficiency value of 99.4 percent at 150 ppm, carbon steel corrosion in acidic medium is effectively inhibited, according to the results. The influence of temperature on corrosion prevention was studied using adsorption parameters and activation thermodynamics. The novel furan derivative creates a protective layer over the metallic surfa

In this work, fluid catalytic cracking of vacuum gas oil to produce gasoline over prepared faujasite type Y zeolite was investigated using experimental laboratory plant scale of fluidized bed reactor.
The catalytic activity of prepared faujasite type NaY, NaNH4Y and NaHY zeolites was investigated. The cracking process was carried out in the temperature range 440 to 500 oC, weight hourly space velocity (WHSV) range 10 to 25 h-1 ,and atmospheric pressure . The catalytic activities of the prepared faujasite type NaY , NaNH4Y and NaHY zeolites were determined in terms of vacuum gas oil (VGO) conversion, and gasoline yield . The conversion at 500oC and WHSV10 hr-1 by using faujasite type NaY, NaNH4Y and NaHY zeolite were 50.2%, 64.1% and 6

One of the important objectives of the varistor is for a sustainable environment and reduce the pollution resulting from the frequent damage of the electrical devices and power station waste. In present work, the influence of Al2O3 additives on the non –linear electrical features of SnO2 varistors, has been investigated, where SnO2 ceramic powder doped with Al2O3 in three rates (0.005, 0.01, and 0.05), the XRD test improved that SnO2 is the primary phase, while CoCr2O4, and Al2O3 represent the secondary phases. The electrical tests of all prepared samples confirmed that the increasing of Al2O3 rates and sintering temperature improves and increase the electrical features, where the best results obtained at Al2O3 (0.05) and 1000℃, the non

Thermal conductivity for epoxy composites filled with Al2O3 and Fe2O3 are
calculated, it found that increasing the weight ratio of Al2O3 and Fe2O3 lead to
increase in the values of thermal conductivity, but the epoxy composite filled with
Fe2O3, have values of thermal conductivity less than for epoxy composite filled with
Al2O3, for the same weight ratio. Also thermal conductivity calculated for epoxy
composites by contact to every two specimens (like sandwich) content same weight
ratio of alumina-oxide and ferrite-oxide, its found that the value of thermal
conductivity lays between the values of epoxy filled Al2O3 and of epoxy filled Fe2O3

In this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibra

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a