Steel–concrete–steel (SCS) structural systems have economic and structural advantages over traditional reinforced concrete; thus, they have been widely used. The performance of concrete made from recycled rubber aggregate from scrap tires has been evaluated since the early 1990s. The use of rubberized concrete in structural construction remains necessary because of its high impact resistance, increases ductility, and produces a lightweight concrete; therefore, it adds such important properties to SCS members. In this research, the use of different concrete core materials in SCS was examined. Twelve SCS specimens were subjected to push-out monotonic loading for inspecting their mechanical performance. One specimen was constructed from co

Fiber Reinforced Polymer (FRP) bars are anisotropic in nature and have high tensile strength in the fiber direction. The use of High-Strength Concrete (HSC) allows for better use of the high-strength properties of FRP bars. The mechanical properties of FRP bars can yield to large crack widths and deflections. As a result, the design of concrete elements reinforced with FRP materials is often governed by the Serviceability Limit States (SLS). This study investigates the short-term serviceability behavior of FRP RC I-beams. Eight RC I-beams reinforced with carbon-FRP (CFRP) and four steel RC I-beams, for comparison purposes, were tested under two-point loading.
Deformations on the concrete and crack widths and spacing are measured and

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

The consumption of fossil fuels has caused many challenges, including environmental and climate damage, global warming, and rising energy costs, which has prompted seeking to substitute other alternative sources. The current study explored the microwave pyrolysis of Albizia branches to assess its potential to produce all forms of fuel (solid, liquid, gas), time savings, and effective thermal heat transfer. The impact of the critical parameters on the quantity and quality of the biofuel generation, including time, power levels, biomass weight, and particle size, were investigated. The results revealed that the best bio-oil production was 76% at a power level of 450 W and 20 g of biomass. Additionally, low power levels led to enhanced

Doxorubicin (DOX) is an efficient antineoplastic agent with a broad antitumor spectrum; however, doxorubicin-associated cardiotoxic adverse effect through oxidative damage and apoptosis limits its clinical application. Cafestol (Caf) is a naturally occurring diterpene in unfiltered coffee with unique antioxidant, antimutagenic, and anti-inflammatory activities by activating the Nrf2 pathway. The present study aimed to investigate the potential chemoprotective effect of cafestol on DOX-induced cardiotoxicity in rats. Wistar albino rats of both sexes were administered cafestol (5 mg/kg/day) for 14 consecutive days by oral gavage alone or with doxorubicin which was injected as a single dose (15 mg/kg intraperitoneally at day 14) to i

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl