Background: 37% phosphoric acid (PA) is the traditional enamel etching technique prior to bracket ‎adhesion, yet it has been implicated in numerous enamel injuries. The purpose of the current study was to create a calcium phosphate (CaP) etching paste in a ‎‎simplified capsule ‎formula that can underpin clinically ‎adequate bracket bond strength ‎without jeopardizing the ‎integrity of enamel upon ‎the debracketing procedure. Materials and Methods: micro-sized hydroxyapatite (HA) powder was mixed with 40% PA solution to prepare ‎experimental acidic CaP paste. Sixty human premolars were ‎assigned into two groups of 30 each. ‎Enamel conditioning was accomplished using 37% PA-gel‎ for control group and CaP paste for e

This study applies a discourse analysis framework to explore the portrayal of women in Maysloon Hadi’s novel (The Black Eyes) (2011), using Critical Discourse Analysis (CDA) and Norman Fairclough’s tri-dimensional model (1989) as the analytical foundation. It investigates the roles and challenges women face in the novel. While there is growing interest in the portrayal of women in literature, Iraqi literature—especially from the perspective of Iraqi women writers remains underexplored. Hadi’s *The Black Eyes* provides a unique case to examine this intersection. Despite the novel’s rich narrative, which offers insight into Iraqi women’s lives, there is a lack of comprehensive CDA to understand how its language constructs

This study aims at describing the identity crisis of Diaspora people (Arab -American) in "Laila Halaby's" novel "Once in A promise Land". Halaby tackles the issues of racism, exclusion, and instability of identity that affect the Arab American community after the terrorist event of eleventh of September. She sheds light on the experiences of her significant characters Salwa and Jassim in America, clarifying how this event weakened their social position and turns their presence in America questionable. "Halaby" describes the bitterness of her characters who are induced into a dream of belonging to a land that transcends their original culture and religious values as well as their language. "Halaby" explains the subsistence in America involvi

Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad

The aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D