ZnO nanostructures were synthesized by hydrothermal method at different temperatures and growth times. The effect of increasing the temperature on structural and optical properties of ZnO were analyzed and discussed. The prepared ZnO nanostructures were characterized by X-ray diffraction (XRD), UV–Vis. absorption spectroscopy (UV–Vis.), Photoluminescence (PL), and scanning electron microscopy (SEM). In this work, hexagonal crystal structure prepared ZnO nanostructures was observed using X-ray diffraction (XRD) and the average crystallite size equal 14.7 and 23.8 nm for samples synthesized at growth time 7 and 8 hours respectively. A nanotubes-shaped surface morphology was found using scanning electron microscopy (SEM). The optic

The extraction of Cupressus sempervirens L. or cypress essential oil was studied in this paper. This cypress oil was extracted by using the hydro-distillation method, using a clevenger apparatus. Cupressus sempervirens L. leaves were collected from Hit city in Al-Anbar province – Iraq. The influences of three important parameters on the process of oil extraction; water which used as a solvent to the solid ratio (5:1 and 14:1 (ml solvent/g plant), temperature (30 to 100 °C) and processing time, were examined to obtain the best processing conditions to achieve the maximum yield of the essential oil. Also, the mathematical model was described to calculate the mass transfer coefficient. Therefore, the best conditions, that were obtained in

Zinc oxide (ZnO) nanoparticles were synthesized using a modified hydrothermal approach at different reaction temperatures and growth times. Moreover, a thorough morphological, structural and optical investigation was demonstrated using scanning electron microscopy (SEM), x-ray diffraction (XRD), ultra-violate visible light spectroscopy (UV-Vis.), and photoluminescence (PL) techniques. Notably, SEM analysis revealed the occurrence of nanorods-shaped surface morphology with a wide range of length and diameter. Meanwhile, a hexagonal crystal structure of the ZnO nanoparticles was perceived using XRD analysis and crystallite size ranging from 14.7 to 23.8 nm at 7 and 8 ℎ𝑟𝑠., respectively. The prepared ZnO samples showed good abso

     In the present investigation two different types of fiber reinforced polymer composites were prepared by hand lay-up method using three different parameters (curing temperature, pressing load and fiber volume fraction). These composites were prepared from the polyester resin as the matrix material reinforced with glass fibers as first group of samples and mat Kevlar fibers as the second group, both with different volume fractions (4%, 8%, and 12%) of fibers. They were then tested by tensile strength and impact strength. The main objective in this study is to use Taguchi method for predicting the better parameters that give the better tensile and impact strength to the composites, and then preparing composites at

   Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr

In recent years, observed focus greatly on gold nanoparticles synthesis due to its unique properties and tremendous applicability. In most of these researches, the citrate reduction method has been adopted. The aim of this study was to prepare and optimize monodisperse ultrafine particles by addition of reducing agent to gold salt, as a result of seed mediated growth mechanism. In this research, gold nanoparticles suspension (G) was prepared by traditional standard Turkevich method and optimized by studying different variables such as reactants concentrations, preparation temperature and stirring rate on controlling size and uniformity of nanoparticles through preparing twenty formulas (G1-G20). Subsequently, the selected formula that pr

Hemogloin (Hb) and serum ferritin levels are used to assess anemia in pregnancy. Some studies referred to the influence of maternal age, body mass index (BMI) and parity on Hb and serum ferritin levels. The study aimed to examine the possible association of maternal Hb and serum ferritin with maternal age, parity, and BMI in a sample of pregnant women in Baghdad.

 Ninety healthy pregnant women, grouped in three equal groups according to the pregnancy trimester, and thirty apparently healthy non-pregnant women from Baghdad were enrolled in this observational study.  Blood and serum samples were obtained for the estimation of Hb and serum ferritin levels.

The pooled data of participants showed a n

The relationship between the elements of the climate and the productivity of citrus (kg
/ tree) in the province of Karbala has been determined through the use of simple correlation
coefficient of Pearson (rp) and (t) test. The result for each of oranges, limes and tangerine had
all shown moral and relevant statistical indications; except for relative humidity, which were
not linked to a moral relationship with productivity of tangerine, oranges and limes.As for the
relationship between climatic factors and yield of bitter orange were all not significant
statistically and very weak.
In order to determine the strength of the correlation between fluctuations in the
climatic elements and fluctuations in the productivi

 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo