Retained soft tissue foreign bodies following injuries are frequently seen in the Emergency and Plastic Surgery practice. The patients with such presentations require a watchful and detailed clinical as- sessment to overcome the anticipant possibility of missing them. However, the diagnosis based on the clinical evaluation is usually challenging and needs to be supported by imaging modalities that are suboptimal and may fail in identifying some types of foreign bodies. Owing to that, serious complications such as chronic pain, infection, and delayed wound healing can be faced that necessitate a prompt intervention to halt those detrimental consequences. The classical method of removal is a surgical exploration which is not free of risks.

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

            Liquid – liquid equilibria data were measured at 293.15 K for the pseudo ternary system (sulfolane + alkanol) + octane + toluene. It is observed that the selectivity of pure sulfolane increases with cosolvent methanol but decreases with increasing the chain length of hydrocarbon in 1-alkanol. The nonrandom two liquid (NRTL) model, UNIQUAC model and UNIFAC model were used to correlate the experimental data and to predict the phase composition of the systems studied. The calculation based on NRTL model gave a good representation of the experimental tie-line data for all systems studied. The agreement between the correlated and the experimental results was very good

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 study Microwave and conventional methods have been used to extract and estimate pectin and its degree of esterification from dried grapefruit and orange peels. Acidified solution water with nitric acid in pH (1.5) was used. In conventional method, different temperature degrees for extraction pectin from grape fruit and orange(85 ,90 , 95 and 100?C) for 1 h were used The results showed grapefruit peels contained 12.82, 17.05, 18.47, 15.89% respectively, while the corresponding values were 5.96, 6.74, 7.41 and 8.00 %, respectively in orange peels. In microwave method, times were 90, 100, 110 and 120 seconds. Grapefruit peels contain 13.86, 16.57, 18.69, and 17.87%, respectively, while the corresponding values were of 6.53, 6.68, 7.2

In current article an easy and selective method is proposed for spectrophotometric estimation of metoclopramide (MCP) in pharmaceutical preparations using cloud point extraction (CPE) procedure. The method involved reaction between MCP with 1-Naphthol in alkali conditions using Triton X-114 to form a stable dark purple dye. The Beer’s law limit in the range 0.34-9 μg mL^-1 of MCP with r =0.9959 (n=3) after optimization. The relative standard deviation (RSD) and percentage recoveries were 0.89 %, and (96.99–104.11%) respectively. As well, using surfactant cloud point extraction as a method to extract MCP was reinforced the extinction coefficient(ε) to 1.7333×105L/mol.cm in surfactant-rich phase. The small volume of organi

The objective of the present work is to measuring the concentration of heavy elements (Pb, Cd, Zn, As) in Baghdad's soil city and indication to the probable sources of pollution as well as comparing the concentration of heavy elements with local and international ranges. The Sampling and analyzing conducted in the present work included ( 15 ) Samples from Baghdad city ( three samples for each location ).The rates of heavy elements in soil samples were as following:. Pb ( 67.5 ) ppm, Cd ( 4.11 ) ppm , Zn ( 77.9 ) ppm , As ( 4.64 ) ppm. According to the results, we find increasing in the concentrations of the heavy elements ( Pb, Cd, Zn ) in soils and decreasing in ( As ).We conclude that the main reason behind the in

ABSTRACT Background: Piezosurgery device is a system developed recently to overcome the limitation of the traditional surgical technique in implant site preparation, which use the principle of ultrasonic microvibrations to create precise & selective cut in bone in harmony with the surrounding tissues. The aim of this study was to evaluate the outcomes of implants inserted by ultrasonic implant site preparation protocol (UISP) using piezosurgery device, regarding the survival rate, stability and other related factors, at 16 weeks postoperative follow up period. Materials and Methods: A total of (24) patients, (6) males and (18) females, aged between (19-51) years old, contributed in this study receiving a total of (42) implants, all of these

The bacterial isolates were obtained from Al-Kindi Hospital were diagnosed by the Vitek-2 system and re confirm by 16srRNA gene as S. aurous, the results were shown 20 isolates (66.7%) out of 30 isolates were positive to protease production. All bacterial isolates (100%) were sensitive to Gentamicin and Levofloxacin. but resistant (100%) to aztreonam. The best temperature for enzyme production from bacteria was 37 °C, and the best pH for enzyme production was 7. Partial purification of the bacterial enzyme (protease) was carried out using short steps included ammonium sulfate 65% saturation, ion exchange using DEAE- cellulose column and then applied on gel filtration chromatography using Sephadex G-200 column. The enzymatic activit

Two different oxidative desulfurization strategies based on oxidation/adsorption or oxidation/extraction were evaluated for the desulfurization of AL-Ahdab (AHD) sour crude oil (3.9wt% sulfur content). In the oxidation process, a homogenous oxidizing agent comprising of hydrogen peroxide and formic acid was used. Activated carbons were used as sorbent/catalyst in the oxidation/adsorption process while acetonitrile was used as an extraction solvent in the oxidation/extraction process. For the oxidation/adsorption scheme, the experimental results indicated that the oxidation desulfurization efficiency was enhanced on using activated carbon as catalyst/sorbent. The effects of the operating conditions (contact time, temperat