This paper analyzes the effect of scaling-up model and acceleration history on seismic response of closed-ended pipe pile using a finite element modeling approach and the findings of 1 g shaking table tests of a pile embedded in dry and saturated soils. A number of scaling laws were used to create the numerical modeling according to the data obtained from 1 g shake table tests performed in the laboratory. The current study found that the behaviors of the scaled models, in general have similar trends. From numerical modeling on both the dry and saturated sands, the normalized lateral displacement, bending moment, and vertical displacement of piles with scale factors of 2 and 35 are less than those of the pile with a scale factor of 1 and the

This study deals with the elimination of methyl orange (MO) from an aqueous solution by utilizing the 3D electroFenton process in a batch reactor with an anode of porous graphite and a cathode of copper foam in the presence of granular activated carbon (GAC) as a third pole, besides, employing response surface methodology (RSM) in combination with Box-Behnk Design (BBD) for studying the effects of operational conditions, such as current density (3–8 mA/cm2), electrolysis time (10–20 min), and the amount of GAC (1–3 g) on the removal efficiency beside to their interaction. The model was veiled since the value of R2 was high (>0.98) and the current density had the greatest influence on the response. The best removal efficiency (MO Re%)

Psoriasis, a chronic inflammatory dermatological condition, exhibits heterogeneous responses to anti-TNF therapies such as etanercept (ETN), underscoring the need for predictive biomarkers. This study investigated the association of interleukin-1 beta (IL-1β) gene promoter polymorphisms (rs1143623 C/G, rs752338864 C/G, and rs1143627 C/T) with ETN efficacy in 80 Iraqi patients with moderate to severe plaque psoriasis. Patients were categorized according to treatment response: responders achieved ≥ 75% reduction in the Psoriasis Area and Severity Index (PASI), whereas non-responders demonstrated ≤ 50% reduction. Post-treatment serum IL-1β levels were significantly higher in non-responders (50.35 ± 15.81 pg/mL) compared to respo

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big