A liquid membrane process of Alkaloids extraction from Datura Innoxia solution was studied applying pertraction process in rotating discs contactor (RDC). Decane as a liquid membrane and dilute sulphuric acid as stripping solution were used. The effect of the fundamental parameters influencing the transport process, e.g. type of solvent used, effect of disks speed, amount of liquid membrane and effect of pH for feed and strip solution. The transport of alkaloids was analysed on the basis of kinetic laws of two consecutive irreversible first order reactions. Thus, the kinetic parameters (k1, k1, , tmax, and ) for the transport of alkaloids were determined. The effect of organic membrane type on percentage of Alkaloids transport was found

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.

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

A liquid membrane process of Alkaloids extraction from Datura Innoxia solution was studied applying pertraction process in rotating discs contactor (RDC). Decane as a liquid membrane and dilute sulphuric acid as stripping solution were used. The effect of the fundamental parameters influencing the transport process, eg type of solvent used, effect of disks speed, amount of liquid membrane and effect of pH for feed and strip solution. The transport of alkaloids was analysed on the basis of kinetic laws of two consecutive irreversible first order reactions. Thus, the kinetic parameters (k1, k1,, tmax, and) for the transport of alkaloids were determined. The effect of organic membrane type on percentage of Alkaloids transport was found to be i

The extraction of Eucalyptus oil from Iraqi Eucalyptus Camadulensis leaves was studded using water distillation methods. The amount of Eucalyptus oil has been determined in a variety of extraction temperature and agitation speed. The effect of water to Eucalyptus leaves (solvent to solid) ratio and particle size of Eucalyptus leaves has been studied in order to evaluate the amount of Eucalyptus oil. The optimum experimental condition for the Eucalyptus oil extraction was established as follows: 100 C extraction temperature, 200 rpm agitation speed; 0.5 cm leave particle size and 6: 1 ml: g amount of water to eucalyptus leaves Ratio.

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

This work describes the development of new spectrophotometric techniques for 3-aminophenol assessment. The first technique involves using benzidine in an alkaline solution to convert 3-aminophenol into a colored complex. The produced complex has a red color with an absorbance of 462 nm. Between the concentration range 5–14 μg mL−1, Beer's law is obeyed with a correlation coefficient (R2) of 0.99781, a limit of detection (LOD) of 0.0423 μg mL−1, and a limit of quantification (LOQ) of 0.1411 μg mL−1. The recovery was between 87.2–95.43%, the relative standard deviation (%RSD) was 2.40–3.31% and the molar absorptivity was 3.545 × 103 L mol−1 cm−1. Secondly, cloud point extraction (CPE) was used to determ

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

Tooth restoration one of the most common procedures in dental practice. The replacement of the entire restoration leads to loss of tooth structure and increase risk of pulp injury; replacement is also time consuming and costly. According to the minimally invasive approach when minimal defects, repair is the better choice than the total replacement of the restoration. This study aims to evaluate repair rating versus replacement treatment procedure for defective composite fillings among Iraqi dentists. Material and methodology: A questionnaire survey were designed and distributed to 184 post-graduate dentists in Iraq. The inquiry pertained general information; including their clinical experience in years, their preference in terms of direct c