Green synthesis of silver nanoparticles (AgNPs) using different plant parts has shown a great potential in medicinal and industrial applications. In this study, AgNPs were in vitro green synthesized using A. graecorum, and its antifungal and antitumoractivities were investigated. Scanning electron microscopy (SEM) image result indicated spherical shape of AgNPs with a size range of 22-36 nm indicated by using Image J program. The functional groups indicated by Fourier-transform infrared spectroscopy (FTIR) represented the groups involved in the reduction of silver ion into nanoparticles. Alhagi graecorum AgNPs inhibited MCF-7 breast cancer cell line growth in increased concentration depend manner, significant differences shown at

A theoretical study on corrosion inhibitors was done by quantum calculations includes semi-empirical PM3 and Density Functional Theory (DFT) methods based on B3LYP/6311++G (2d,2P). Benzimidazole derivative (oxo(4- ((phenylcarbamothioyl) carbamoyl)phenyl) ammonio) oxonium (4NBP) and thiourea derivative 2-((4- bromobenzyl)thio) -1H-benzo[d] imidazole (2SB) were used as corrosion inhibitors and an essential quantum chemical parameters correlated with inhibition efficiency, EHOMO (highest occupied molecular orbital energy) and ELUMO (lowest molecular orbital energy). Other parameters are also studied like energy gap [ΔE (HOMO-LUMO)], electron affinity (EA), hardness (Δ), dipole moment (μ), softness (S), ionization potential (IE), absolut

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

In this research, the degradation of Dazomet has been studied by using thermal Fenton process and photo-Fenton processes under UV and lights sun. The optimum values of amounts of the Fenton reagents have been determined (0.07g FeSO4 .7H2O, 3.5µl H2O2) at 25 °C and at pH 7 where the degradation percentages of Dazomet were recorded high. It has been found that solar photo Fenton process was more effective in degradation of Dazomet than photo-Fenton under UV-light and thermal Fenton processes, the percentage of degradation of Dazomet by photo-Fenton under sun light are 88% and 100% at 249 nm and 281 nm respectively, while the percentages of degradation for photo-Fenton under UV-light are 87%, 96% and for thermal Fenton are 70% and 66.8% at 2

The problem of the current paper is embodied in the weakness of the female students
of the department of the Quran sciences in the college of Education for Women in the
University of Baghdad in the subject of reciting and memorizing the Holy Quran. This is what
the professors and the scientific and educational supervisors stress equally through their visits
to the students applicants during the period of their practical application of teaching in the
schools; especially that the subject is thought for four years during their study in the college.
That weakness is so explicit with a quite large number of the students-applicants, who are
supposed to be the future teachers in the subject of the Holy Quran and Islamic Ed