The effect of using grinded rocks of (quartzite and porcelanite) as powder of (10 and 20) % replacement by weight of cement for self-compacting concrete slabs was investigated in this study. Five slabs with 15 concrete cubes were tested experimentally at 28 days to study the compressive strength, ultimate load, ultimate deflection, ductility, crack load and steel strain. The test results show that, the compressive strength improvement when replacement of local rock powder reached to (7.3, 4.22) % for (10 and 20) % quartzite powder and (11.3, 16.1) % for (10 and 20) % porcelanite powder, respectively compared to the reference specimen. The ultimate load percentage increase for slabs with (10 and 20) % rep

We propose an intraguild predation ecological system consisting of a tri-trophic food web with a fear response for the basal prey and a Lotka–Volterra functional response for predation by both a specialist predator (intraguild prey) and a generalist predator (intraguild predator), which we call the superpredator. We prove the positivity, existence, uniqueness, and boundedness of solutions, determine all equilibrium points, prove global stability, determine local bifurcations, and illustrate our results with numerical simulations. An unexpected outcome of the prey's fear of its specialist predator is the potential eradication of the superpredator.

Near surface mounted (NSM) carbon fibers reinforced polymer (CFRP) reinforcement is one of the techniques for reinforcing masonry structures and is considered to provide significant advantages. This paper is composed of two parts. The first part presents the experimental study of brick masonry walls reinforced with NSM CFRP strips under combined shear-compression loads. Masonry walls have been tested under vertical compression, with different bed joint orientations 90° and 45° relative to the loading direction. Different reinforcement orientations were used including vertical, horizontal, and a combination of both sides of the wall. The second part of this paper comprises a numerical analysis of unreinforced brick masonry (URM) wa

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

Presentation of urinary calculus ranges from painful urination to acute retention. Diagnosed by x-ray pelvis and non-contrast CT and removal of stone by various methods is the management. Variety in symptoms, sometimes make clinical diagnosis difficult until radiological investigations confirm it. In this case presentation, initial diagnosis was made of Urethrocutaneous fistula may be due to distal stricture, but on investigating, he was diagnosed as urethral calculus in urethral diverticulum , as the reason for his symptoms

We report on the experimental and theoretical characterization of elliptically shaped Fabry–Perot microcavities fabricated through a controlled thin-film buckling process. Due to the highly astigmatic nature of the buckled mirrors, the cavity modes are well described as elliptical Hermite–Gaussian beams. In addition to lifting the typical degeneracy of higher-order transverse spatial modes, the cavities exhibit large polarization-mode splitting greater than 25 GHz in the 1550 nm wavelength range. This large, controllable, and highly predictable birefringence makes these cavities of interest for emerging applications in cavity quantum optics that rely on non-degenerate polarization modes.

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip