B3LYP density functional is utilized for probing the effect of decorating Al, Ga, and In on the sensing performance of a boron phosphide nanotube (BPNT) in detecting the 2-chloroethanol (CHE) molecule. We predict that the interaction of pure BPNT with CHE is physisorption, and the sensing response (SR) of BPNT is approximately 6.3. The adsorption energy of CHE is about − 26.3 to − 91.1, − 96.6, and − 100.3 kJ/mol, when the Al, Ga, and In metals are decorated on the BPNT surface, respectively. This indicates that the decorated metals significantly strength the interaction. Also, the corresponding SR meaningfully rises to 19.4, 41.0, and 93.4, indicating that by increasing the atomic number of metals, the sensitivity i

Physiological status and litter size can indeed have a significant impact on ewes' ‎hematological parameters, which are essential indicators of their health. Therefore, this study ‎examined the hematological profiles of ewes during pregnancy with single and twins in the ‎Awassi ewes. The present study involved 232 ewes in good health and at sexual maturity. ‎Among them, 123 ewes had single pregnancies, while 109 ewes had twin pregnancies. The age ‎range of the ewes included in the study was between 3.5 and 4.5 years. Hematological tests ‎were conducted on the sheep's blood samples promptly following collection. The findings ‎demonstrated variations in hematological parameters among pregnant

    The environmental contamination by the polycyclic aromatic hydrocarbons (PAHs) and heavy metals (Pb, Cu, Ni, Cr, and Cd) concentrations in the leaves of plant Eucalyptus camaldulensis were determined at the city of Kirkuk in 15 selected locations using GPS. The pickings up of samples were carried out in two periods October 2010 and March 2011. Compared with results of other studies, the concentration levels of determined heavy metals show values within these studies results. The average total concentration of polycyclic aromatic hydrocarbons (PAHs) in the leaves of Plant Eucalyptus camaldulensis indicated 37.1 ppb in October, while in March 165.2 ppb.

    The mode

Roller compacted concrete (RCC) is a special type of concrete with zero or even negative slump consistency. In this work, it had aimed to produce an RCC mix suitable for roads paving with minimum cost and better engineering properties so, different RCC mixes had prepared i.e. (M1, M2, M3, and M4) using specified percentages of micro natural silica sand powder (SSP) as partial replacement of (0%, 5%, 10%, and 20%) by weight of sulfate resistant Portland cement. Additionally, M-sand, crushed stone, filler, and water had been used. The results had obtained after 28 days of water curing. The control mix (M1) had satisfied the required f ‘c with accepted results for the other tests. M2 mix with SSP of 5% had

The corrosion protection of low carbon steel in 2.5 M HCl solution by kiwi juice was studied at different temperatures and immersion times by weight loss technique. To study the determination of the optimum conditions from statistical design in evaluation of a corrosion inhibitor, three variables, were considered as the most dominant variables. These variables are: temperature, inhibitor concentration (extracted kiwi juice) and immersion time at static conditions.

These three variables are manipulated through the experimental work using central composite rotatable Box – Wilson Experimental Design (BWED) where second order polynomial model was proposed to correlate the studied variables with the corrosion rate o

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

The photocatalyst process is considered the most promising method for the removal of water contamination. For excellent chemical and structural properties of Co3O4 nanoparticles, various Co3O4-based nanostructures can be applied as a photocatalyst. In this work, carbon quantum dots is prepared via an eco-friendly process and linked to Co3O4 effectively. X-ray diffraction pattern (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-visible absorption spectroscopy and Fourier transform infrared spectroscopy (FT-IR). The photocatalyst process reveals that prepared nanocomposites can be degraded methylene blue under solar irradiation strongly. Results showed that methylene blue and methyl orange are degraded via