Abstract Background Deep learning (DL) has attracted increasing attention in orthodontics, with many studies reporting high diagnostic and predictive accuracy. However, despite these promising results, routine clinical adoption remains limited. Objectives This scoping review aimed to explore the main barriers that restrict the translation of DL systems from research environments into everyday orthodontic practice. Methodology The review was conducted in accordance with PRISMA-ScR guidelines. Electronic searches were performed in PubMed, Scopus, Web of Science, and IEEE Xplore for English-language studies published between 2015 and June 2025. Studies reporting quantitative performance of DL-based orthodontic applications were included. Dat

Women infertility is a common reproductive system disorder. Diagnosis and treatment are characterized by limited availability and high costs. This paper intends to evaluate the levels of endogenous antioxidant proteins metallothionein 2 (MT2) and metallothionein 4 (MT4) in the serum of both infertile and fertile women, as well as to assess the association between these proteins and total oxidant capacity (TOC), total antioxidant capacity (TAC), oxidative stress index (OSI), serum anti-Müllerian hormone (AMH), and serum testosterone. This case-control study involved one hundred eighty Iraqi women, categorized into three categories: primary infertile women (P group), secondary infertile women (S group), and healthy fertile women (C group). W

       This paper aims at providing the teaching staff members with the necessary skills so as to become capable of tackling various situations, and treating daily problems that face students learning Spanish as a Second Language.  This is made as an attempt to make teachers of foreign languages in general acquainted with modern trends of teaching with less complicated methods, specifically in teaching e earlier stages of foreign languages.

Abstracto:

      En el presente trabajo pretendemos dotar al docente no nativo de Lenguas extranjeras, con algunos de los métodos necesari

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.