The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

Metal oxide nanoparticles demonstrate uniqueness in various technical applications due to their suitable physiochemical properties. In particular, yttrium oxide nanoparticle(Y₂O₃NPs) is familiar for technical applications because of its higher dielectric constant and thermal stability. It is widely used as a host material for a variety of rare-earth dopants, biological imaging, and photodynamic therapies. In this investigation, yttrium oxide nanoparticles (Y₂O₃NPs) was used as an ecofriendly corrosion inhibitor through the use of scanning electron microscopy (SEM), Fourier transforms infrared spectroscopy (FT-IR), UV-Visible spectroscopy, X-ray diffraction (XRD), and energy dispersive X-ray spe

This paper proposes a novel finite-time generalized proportional integral observer (FTGPIO) based a sliding mode control (SMC) scheme for the tracking control problem of high order uncertain systems subject to fast time-varying disturbances. For this purpose, the construction of the controller consists of two consecutive steps. First, the novel FTGPIO is designed to observe unmeasurable plant dynamics states and disturbance with its higher time derivatives in finite time rather than infinite time as in the standard GPIO. In the FTGPO estimator, the finite time convergence rate of estimations is well achieved, whereas the convergence rate of estimations by classical GPIO is asymptotic and slow. Secondly, on the basis of the finite and fast e

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

Melanoides tuberculata (O. F. Müller, 1774), a freshwater snail native to eastern Mediterranean, eastern Africa, southeast Asia, southern Asia, India, and Malaysia, it is an effective invader and is now nearly globally distributed. This snail has been studied with interest because of its rapidly distributed, and because of being can serve as compatible intermediate host for many of trematodes in the world. We have summarized information from many articles in order to highlight the most important aspects of this invader snail life.

Concrete pavements are essential to modern infrastructure, but their low tensile and flexural strengths can cause cracking and shrinkage. This study evaluates fiber reinforcement with steel and carbon fibers in various combinations to improve rigid pavement performance. Six concrete mixes were tested: a control mix with no fiber, a mix with 1% steel fiber (SF1%), a mix with 1% carbon fiber (CF1%), and three hybrid mixes with 1% fiber content: 0.75% steel /0.25% carbon fiber (SF0.75CF0.25), 0.25% steel /0.75% carbon fiber (SF0.25CF0.75), and 0.5% steel /0.5% carbon fiber ((SF0.5CF0.5). Laboratory experiments including compressive, flexural, and splitting tensile strength tests were conducted at 7, 28, and 90 days, while Finite Element Analys

This study synthesized nanocomposite photocatalyst materials from a mixture of Cu₂O nanoparticles, ZnO nanoparticles, and graphene oxide (GO) through coprecipitation and hydrothermal methods. This study aims to determine the optimum composition of Cu₂O/ZnO/GO nanocomposites in degrading methylene blue. The nanocomposite was synthesized in two steps:  1  the synthesis of Cu₂O and ZnO nanoparticles through the coprecipitation method and the preparation of GO through the modified Hummer method.  2  The preparation of Cu₂O and ZnO nanoparticles mixtures with GO through the hydrothermal method to form Cu₂O/ZnO/GO nanocomposites. The adsorption-photocatalysis process of methylene blue

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of