The present work is to investigate semiotically the similarities and differences in the textual memes generated by human and AI-ChatGPT-5 and to answer the research question “what are the points of similarity and difference between human and AI-ChatGPT-generated textual memes following Barthes’ framework”. Such a study contributes to the growing field of digital semiotics by examining the process of meaning-making constructed by humans and AI-ChatGPT-5 using one visual stimulus. To meet this objective, a unified image macro “Le Défenseur” by Honoré Daumier has been submitted to a sample of (15) first-year students from the Department of English, College of Education for Women, University of Baghdad, purposively selected

The study explains how translation participates in shaping the responses of different communities to global awareness campaigns, and the extent to which language and translated terminology from English to Arabic influence the audience’s understanding and interaction with the awareness messages delivered by these campaigns. The research aims to explore the problems in translating these campaign titles, which may lead to vague meaning, as the process is considered a major challenge due to the need to navigate linguistic nuances, cultural differences, and contextual variations. In this study, some awareness phrases were randomly chosen from many types of organizations’ campaigns, like the WHO, UN, mental health, and Empowerment, a

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

This work is aiming to study and compare the removal of lead (II) from simulated wastewater by activated carbon and bentonite as adsorbents with particle size of 0.32-0.5 mm. A mathematical model was applied to describe the mass transfer kinetic.

The batch experiments were carried out to determine the adsorption isotherm constants for each adsorbent, and five isotherm models were tested to choose the best fit model for the experimental data. The pore, surface diffusion coefficients and mass transfer coefficient were found by fitting the experimental data to a theoretical model. Partial differential equations were used to describe the adsorption in the bulk and solid phases. These equations were simplified and the

     A new Schiff base ligand was prepared via a condensation reaction. The synthesis involved combining N-(4-aminophenylsulfonyl) benzamide (also known as sulfabenzamide) with indoline-2,3-dione. To facilitate the reaction, three drops of glacial acetic acid were added. This process yielded the ligand N-(4-(2-oxoindoline-3-ylideneamino) phenylsulfonyl) benzamide, designated as (L). Mixed ligand complexes were prepared in a molar ratio (1:1:1) (M:1,10-phen, L) at concentrations of 10-4M by interacting L and 1,10-phenanthroline, with the following metal ions (Cr+3, Mn+2, Zn+2, Pd+2, Cd+2, Pt+4). These complexes exhibited different geometric shapes, including (octahedral for both Cr+3, Mn+2, Pt+4, tetrahedral for Zn+2 and Cd+2, an

Background:Periodontal diseases and dental caries are the most common oral diseases, but they can be adequately prevented by adopting a specific health behavior and plaque control.The study was carried out to determine and compare oral health status; it included both caries experience, gingival health and oral hygiene behavior betweenfirst and fifth yearsof Al-Mustansiriyahdental students. Materials and methods: Total sample of the study consisted of 50 students at first year (25 males, 25 females)and 60 students at fifth year (30 males, 30 females). Plaque andgingival indices,dental caries indices (DMFS and DMFT) wererecorded to evaluateoral health status for each student. Further questionnaires were given to evaluate different oral hyg