Active Magnetic Bearings (AMBs) are progressively being implemented in a wide variety of applications. Their exclusive appealing features make them suitable for solving traditional rotor-bearing problems using novel design approaches for rotating machinery.  In this paper, a linearized uncertain model of AMBs is utilized to develop a nonlinear sliding mode controller based on Lyapunov function for the electromechanical system. The controller requires measurements of the rotor displacements and their derivatives. Since the control law is discontinuous, the proposed controller can achieve a finite time regulation but with the drawback of the chattering problem. To reduce the effect of this problem, the gain of the uni

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

This quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific efficacy, prov

Background: This study was conducted to assess the effect of sonic activation and bulk placement of resin composite in comparison to horizontal incremental placement on the fracture resistance of weakened premolar teeth. Materials and method: Sixty sound human single-rooted maxillary premolars extracted for orthodontic purposes were used in this study. Teeth were divided into six groups of ten teeth each: Group 1 (sound unprepared teeth as a control group), Group 2 (teeth prepared with MOD cavity and left unrestored), Group 3 (restored with SonicFill™ composite), Group 4 (restored with Quixfil™ composite), Group 5 (restored with Tertic EvoCeram® Bulk Fill composite) and Group 6 (restored with Universal Tetric EvoCeram® co

Adhesion (type 1 fimbriae) and host defense avoidance mechanisms (capsule or lipopolysaccharide) have been shown to be prevalent in Escherichia coli isolates associated with urinary tract infections. In this work, 50 uropathogenic Escherichia coli (UPEC) isolated from children with urinary tract infections were genotypically characterized by polymerase chain reaction (PCR) assay. We used two genes; fimH and kpsMTII, both of them previously identified in uropathogenic E.coli (UPEC) isolates. The PCR assay results identified fimH (90.0)% and kpsMTII (72.0)% isolates. In the present study, was also demonstrated that these genes may be included in both or one of them within a single isolate.