The measurements and tests of the samples conducted in the laboratories of the College of Agriculture included isolating bio-fertilizers and testing the efficiency of isolates that fix atmospheric nitrogen and solubilize phosphorous compounds. Bacteria were isolated and identified from the rhizosphere soils of different plants collected from various agricultural areas. A total of 74 bacterial isolates were obtained based on the phenotypic characteristics of the developing colonies, as well as biochemical and microscopic traits. The results of isolation and identification showed that among the 74 bacterial isolates, there were 15 isolates of A. chroococcum, 13 of Az. lipoferum, 13 of B. megaterium, 10 of P. putida, 10 of Actinomycetes, and n

This study examines the removal of ciprofloxacin in an aqueous solution using green tea silver nanoparticles (Ag-NPs). The synthesized Ag-NPs have been classified by the different techniques of SEM, AFM, BET, FTIR, and Zeta potential. Spherical nanoparticles with average sizes of 32 nm and a surface area of 1.2387m2/g are found to be silver nanoparticles. The results showed that the ciprofloxacin removal efficiency depends on the initial pH (2.5-10), CIP (2-15 mg/L), temperature (20-50°C), time (0-180 min), and Ag-NPs dosage (0.1-1g/L). Batch experiments revealed that the removal rate with ratio (1:1) (w/w) were 52%, and 79.8% of the 10 mg/L of CIP at 60, and 180 minutes, respectively with optimal pH=4. Kinetic models for adsorpti

           Titanium dioxide nanoparticles (TiO₂ NPs) are generally used in different types of applications such as the industry of plastics, paper industry, paints, toothpaste, cosmetics, sunscreens, and in various lifestyles, because of the vast range of applications and our daily exposure to these nanoparticles and a lack of information on animal and human health this study was designed to reveal dose and time-dependent effects of TiO₂-NPs on the thyroid gland and kidney functions in male rats.

For this study 54, Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided i

In the present work, nanocomposite of poly (vinyl alcohol) (PVA) incorporated with functionalized graphene oxide (FGO) were fabricated using casting method. PVA was dispersed by varying content of FGO (0.3, 0.5, 0.8, 1 wt %). The PVA- FGO nanocomposite was characterized by FT‐IR, FE-SEM and XRD. Frequency dependence of real permittivity (ε’), imaginary (ε’’) and a.c conductivity of PVA/FGO and PVA/GO nanocomposite were studied in the frequency range 100 Hz- 1 MHz. The experimental results showed that the values of real (ε’) and imaginary permittivity (ε’’) increased dramatically by increasing the FGO content in PVA matrix. PVA/ FGO (1 wt %) nanocomposite revealed higher electrical conductivity of 6.4×10-4 Sm-1 compared to

NiO nanoparticle synthesis by chemical method and characterized by XRD with crystal size 11.72
nm and grain size 13 nm from FESEM image also NiO micro used ,two NiO as an additive to evaluate the
possibility of producing photodegradable polymers, the practical application of solid-phase photocatalytic
degradation of polyvinyl chloride (PVC- NiO composite films) was investigated. PVC has a negative impact
on the environment since its polymer degrades slowly, yet it has a wide range of industrial applications and
the amount used shows no evidence of diminishing use. Thus, a synthesis of modified PVC- NiO micro and
nano has been studied with 0, 50, 100, 150, 200, 250, and 300 (hours) as irradiation time a

This study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts