The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

Background: For decades, the use of naturally accessible materials in treating human disease has been widespread. The goal of this study was to determine the anti-fungal effectiveness /of the lemongrass essential oil (LGEO) versus Candida albicans (C. albicans) adhesion to polymethylmethacrylate (PMMA) materials. Material and methods: LGEO's anti-fungal activity was tested against C. albicans adhesion using the following concentration of LGEO in PMMA monomer (2.5 vol. %, 5 vol. % LGEO) selected from the pilot study as the best two effective concentrations. A total of 40 specimens were fabricated for the candida adherence test and were subdivided into four equal groups: negative control 0 vol. % addition, experimental with 2.5 vol. % and

This research examines the scientific impact of Al-Hafiz Sharaf al-Din al-Damiati, who descended from a famous scholarly family known as (Al-Damiati) in reference to the city of Damietta in Egypt. This family was distinguished by producing scholars and writers during the Ayyubid and Mamluk eras, the most prominent of whom was Sharaf al-Din. He was preceded by a scholar of no lesser scientific stature, Shams al-Din al-Damiati (d. 693 AH), who was famous for his knowledge of the science of readings. Sharaf al-Din al-Damiati was famous for his mastery of the science of hadith and genealogy. The political situation that prevailed during his era was represented by the occupation of the city of Baghdad in 656 AH/1258 AD, the end of the Abbasid Ca

Samarium(III) ions react with (l-2(2-benzoinidazolyl-azo)-2-hydroxy-3-naphthoic acid in basic medium (pH = 8.0) forms a red-orange complex at A.max (550nm). The complex was found to be stable for at least 48 hrs. at the given pH. The apparent molar absorptivity is 7776.77 L.mol-1.Cm-1 and a linear calibration curve is obtained in the range (0.639x 10-5M - 6.350x 10 -5M). The stoichiometry of complex was confirmed by using mole ratio method which indicated that ratio of reagent to metal is 3:1. The effects of the presence of different cations and anions as interferences in the determination of samarium(III) under the given conditions were investigated

Background: Bone density is a major factor that affect mini implant primarily stability; no Iraqi studies have evaluated bone density related to mini-implant placement for orthodontic anchorage at age 13 -15 years. The present research aims to evaluate gender, side and site differences in the bone density at various orthodontic implant sites for the maxillary alveolar bone. Materials and methods: Twenty nine individuals (16 males and 13 females) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 21 points (9 points for each side and 3 points between the right and left central incisors) . Results: The results obtained showed that there ar

The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival