An innovative two-step noncatalytic esterifcation technique was proposed to synthesize alkyl esters from free fatty acids simulated in waste cooking oil, as a pretreatment process for biodiesel production, without adding any catalyst under normal conditions of pressure and temperature. The efect of methanol:oil molar ratio, reaction time, mixing rate, and reaction temperature were investigated. The results confrmed that the conversion of the reaction was increased when increasing the methanol molar ratio and decreased in prolonged reaction temperature. High conversion (94.545%) was successfully achieved at optimized conditions of 115:1, 65:1 methanol:oil molar ratio in the frst step and second step, respectively, other conditions i

Background: Hyperfunction of the muscles of the upper lip is considered as the most common cause of excessive gingival display (EGD). The aim of this study was to demonstrate the effectiveness of botulinum toxin (BT) injection as a conservative treatment for EGD due to muscular hyperfunction and to compare the outcome of 2 injection methods. Material and methods: This study included 40 participants who were randomly assigned into 2 groups of 20 each, The first group received 2.5IU BT injection at 1 point per side (2-points group), while the second group received a total of 5 IU of BT at 2 points per side (4-points group). The outcome variables were the reduction in the central and lateral gingival display expressed as the difference between

Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

This work aimed to investigate the effect of Diode laser 805 nm on plasmid DNA and RNA
contents of some Gram negative bacteria represented by Escherichia coli and Proteus mirabilis isolates
.Plasmid extraction was done using two methods (Salting out and CTAB method).Different powers and
pulse repetition rates for 805 nm Diode Laser were used to study this effect. Results revealed that the
plasmid profile of the two species were highly affected using (2, 3) W at different frequencies including
5and 10 kHz as compared with 1 kHz while plasmids were gradually disappeared at 1W, 10 kHz. In the
same time the shining of RNA was also decreased gradually then disappeared with increasing powers
especially at 2W and 10 kHz cau

Objective: This research was carried out in rats in a special place of the laboratory of histopathological diseases in the period 6/9/2018 until 23/11/2018, this study to detect effect of the addition of the alcohol extract of ginger in the reduction of fat in liver tissue of rats. Method: Eight groups and replicates for each group. The groups were homogenous in weights and were placed in 13 cages. Each group consisted of 10 rat and at 5 fares each. In the first treatment, rat were fed on regular feeding without adding and feeding rats in the second treatment sessions add to it the alcoholic extract of ginger in Turkey 150 mg/kg. The third group is the same as the normal food after adding the alcohol extract of ginger at a concentration of

Orange peel was used as a plant-derived medium to prepare a ZnO–calcite mixed-phase nanostructured material, which was physicochemically characterized and evaluated for DPPH radical-scavenging, α-glucosidase inhibitory, and in vitro cytotoxic activities. XRD confirmed the coexistence of hexagonal wurtzite ZnO and crystalline calcite, with ZnO apparent crystallite sizes ranging from 9.2 to 28.3 nm (mean 16.4 ± 7.3 nm). FTIR identified Zn–O vibrations, carbonate-related bands, surface hydroxyl groups, and residual organic functionalities, while FESEM revealed irregular agglomerates composed of nanoscale grains. EDX showed Zn, O, C, and Ca as the principal elements, and the material exhibited a zeta potential of -14.86 ± 0.52 mV

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Penetrating Neck Injuries (PNI) management represents a challenge to most surgeons in civilian trauma, in weighing selective versus mandatory exploration of all cases in different circumstances. Data are encouraging surgeons to adopt the former approach.Objectives: The study aims to assess the selective approach in our war and terror time events in Al-Yarmouk teaching hospital.Type of the study:A retrospective study. Methods: Data of patients presented to the Thoracic and Vascular ward in Al-Yarmouk teaching hospital with PNI were assessed retrospectively, from March 2013 to March 2015, and analyzed for epidemiology, mechanism of trauma, management methods, associated organ injuries, complications and mortality. Results: Amon