Among a collection of leafhoppers from Erbil Province in Kurdistan/Iraq, a new species of the genus Arboridia Zakhvatkin, 1946 was designated and described here as a new species  to  the science. The erection of this species was mainly built on the external characters included the male genitalia. Sites and dates of collections so as the host-plants were verified.

This study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su

Aim of the study: Using surface roughness and tensile bond strength tests, the objective of this investigation was to ascertain the impact of laser surface modification on the binding strength of injectable thermoplastic acrylic denture base material to acrylic-based soft-liner material. Materials and methods: Acrylic base soft liner material was bonded to injectable thermoplastic acrylic resin (Deflex). Forty specimens were created (20 disc, 20 dumbbells) 10 of each specimen type as control specimens, and 10 were treated with nano pulse Nd: YAG laser. The data were analyzed using the Kruskal-Wallis test and unpaired t-test (a=.05) and the roughness test was performed utilizing a double column universal test machine. Results: Compar

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

In this work, enhancement to the fluorescence characteristics of laser dye solutions hosting highly-pure titanium dioxide nanoparticles as random gain media. This was achieved by coating two opposite sides of the cells containing these media with nanostructured thin films of highly-pure titanium dioxide. Two laser dyes; Rhodamine B and Coumarin 102, were used to prepare solutions in hexanol and methanol, respectively, as hosts for the nanoparticles. The nanoparticles and thin films were prepared by dc reactive magnetron sputtering technique. The enhancement was observed by the narrowing of fluorescence linewidth as well as by increasing the fluorescence intensity. These parameters were compared to those of the dye only and the dye solution

In this study, the potential of adsorption of amoxicillin antibiotic (AMOX) from aqueous solutions using prepared activated carbon (AC) was studied. The used AC was prepared from an inexpensive and available precursor (sunflower seed hulls (SSH)) and activated by potassium hydroxide (KOH). The prepared AC was examined for its ability to remove AMOX from aqueous contaminated solutions and characterized with the aid of N2 -adsorption/desorption isotherm Brunauer–Emmett– Teller, scanning electron microscopy, energy-dispersive X-ray spectroscopy and Fourier-transform infrared. Zeta potential of the prepared activated carbon from sunflower seed hulls (SSHAC) were studied in relation to AMOX adsorption. The physical and chemical propert

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve