A Laced Reinforced Concrete (LRC) structural element comprises continuously inclined shear reinforcement in the form of lacing that connects the longitudinal reinforcements on both faces of the structural element. This study conducted a theoretical investigation of LRC deep beams to predict their behavior after exposure to fire and high temperatures. Four simply supported reinforced concrete beams of 1500 mm, 200 mm, and 240 mm length, width, and depth, respectively, were considered. The specimens were identical in terms of compressive strength ( 40 MPa) and steel reinforcement details. The same laced steel reinforcement ratio of 0.0035 was used. Three specimens were burned at variable durations and steady-state temperatures (one hour at 500 °C and 600 °C, and two hours at 500 °C). The flexural behavior of the simply supported deep beams, subjected to the two concentric loads in the middle third of the beam, was investigated with ABAQUS software. The results showed that the laced reinforcement with an inclination of 45˚ improved the structural behavior of the deep beams, and the lacing resisted failure and extended the life of the model. The optimal structural response was observed for the specimens. The laced reinforcement improved the failure mode and converted it from shear to flexure-shear failure. The parametric study showed that the lacing bars remarkably improved the strength of the deep beams and they were not affected more by the steady-state temperature and duration. Furthermore, a greater increase in load-carrying capacity was associated with an increase in the flexural diameter of approximately 12 and 16 mm by approximately 24.77% and 87.61%, respectively, compared to the reference LRC deep beams.
Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.
The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreThe electronic properties and Hall effect of thin amorphous Si1-xGex:H films of thickness (350 nm) have been studied such as dc conductivity, activation energy, Hall coefficient under magnetic field (0.257 Tesla) for measuring carrier density of electrons and holes and Hall mobility as a function of germanium content (x = 0–1), deposition temperature (303-503) K and dopant concentration for Al and As in the range (0-3.5)%. The composition of the alloys and films were determined by using energy dispersive spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS).
This study showed that dc conductivity of a-Si1-xGex:H thin films is found to increase with increasing Ge content and dopant concentration, whereas conductivity activati
Abstract:
The aim of the present research is to evaluate the child’s nutritional
method (2-5 years old) which is based on his resistance of the food highly rich
with nutritional elements and his acceptance of the food of a low nutritional
value in addition to his having forbidden food with other mates and making
use of all mates when having food, in establishing the sound social values and
affection since child hood. The required statistical equation have been used
by the researcher namely (Z test).
The sample of the present study consists of (26) children who were selected
intentionally and randomly from the kindergartens of Al-Bayaa region and the
college of Education for women. The questionnaires were d
Women are considered the real power to build societies, as they are half of society, and it is their responsibility to raise generations، as human history testifies to the recording of great names with their giving and achievement in various scientific, social and humanitarian disciplines. Because of the importance of women in our lives, society must give them special care, whether at home or within the community structure to which they belong, so that they contribute to the image that brings about a transformation in the public scene, as well as providing them with support to take charge of bringing about change themselves, and this explains the interest of the press at all levels. Women's issues and topics through various journal
... Show MoreAbstract Diabetic nephropathy (DN) is a prevalent chronic microvascular diabetic complication. As inflammation plays a vital role in the development and progress of DN the macrophages migration inhibitory factor (MIF), a proinflammatory multifunctional cytokine approved to play a critical function in inflammatory responses in various pathologic situations like DN. This study aimed To assess serum levels of MIF in a sample of Iraqi diabetic patients with nephropathy supporting its validity as a marker for predicting nephropathy in T2DM patients. In addition, to evaluate the nephroprotective effect of angiotensin-converting enzyme (ACE) inhibitors in terms of their influence on MIF levels. This is a case-control study involving ninety
... Show MoreMetasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
... Show MoreThis study included estimation of glutathione (GSH) and Malondialdehyde (MDA) levels in the serum of diabetic patients type II who are treated with a polyherbs mixture (Nigella sativa, Trigonella foenum-graeum, Cyperus rotundus and Teucrium polium) for three months of treatments. Seventy samples of diabetic patients Type II male and females with age about (35-60) years were taken including 44 samples for group one (24 male, 20 female) who used herbs accompanied with chemical treatment (drugs) and 26 samples for the second group (13male and 13 female) who used herbs only. These groups were compared with 60 samples obtained from healthy persons (29 male, 31 female) at the same age of patients as a control group. Effect of age and treatment fo
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