Background: The excessive use and abuse of antibiotics contribute to bacterial resistance, raising the risk of complications and treatment failures. This study investigates adherence to antibiotic prescriptions among Iraqi dental patients, highlighting implications for antimicrobial resistance.Objective: To assess adherence levels and identify factors influencing antibiotic therapy compliance among dental patients.Methods: A cross-sectional survey was conducted in which adult dental patients aged 18 and older, who had been prescribed antibiotics within the past year, participated. The modified Morisky Medication Adherence Scale-8 items was used to evaluate adherence, and data were analyzed with IBM SPSS Statistics software V26.Results: Amon

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

Erosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the

In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m³

This study addressed the work stress sources and level of the communicator in public relations in governmental institutions in the United Arab Emirates. The importance of this study is the lack of studies on work stress of the communicator in public relations. The study aimed to investigate the work stress source Physical, individual, groups, organizational and Professional source which effect on the performance of communicator in public relations. The researcher used the descriptive approach and questionnaire as an essential tool for collecting information. Some of the important results of the study are The communicator in public relations facing stress in work by 42% which affect on his performance by average level. The organizational

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models