In this study, cloud point extraction combined with molecular spectrometry as an eco-friendly method is used for extraction, enrichment and determination of bendiocarb (BC) insecticide in different complex matrices. The method involved an alkaline hydrolysis of BC followed Emerson reaction in which the resultant phenol is reacted with 4-aminoantipyrene(4-AAP) in the presence of an alkaline oxidant of potassium ferric cyanide to form red colored product which then extracted into micelles of Triton X-114 as a mediated extractant at room temperature. The extracted product in cloud point layer is separated from the aqueous layer by centrifugation for 20 min and dissolved in a minimum amount of a mixture ethanol: water (1:1) followed

    X-ray emission contains some of the gaseous properties is produced when the particles of the solar wind strike the atmosphere of comet ISON and PanSTARRS Comets. The data collected with NASA Chandra X-ray Observatory of the two comets, C/2012 S1 (also known as Comet ISON) and C/2011 S4 (Comet PanSTARRS) are used in this study.

   The real abundance of the observed X-ray spectrum elements has been extracted by a new simple mathematic model. The study found some physical properties of these elements in the comet’s gas such as a relationship between the abundance with emitted energy. The elements that have emission energy (2500-6800) eV, have abundance (0.1-0.15) %, while the elements

The conservation of natural resources such as water is one of the areas that sustainable agriculture seeks to preserve, rationalize its use and protect it from pollution, because water is a specific factor for agriculture. Despite Iraq's possession of two international rivers, the Tigris and the Euphrates, which pour into the Shatt Al-Arab, it suffers from water shortages in recent times, As a result of several reasons combined, including water policies initiated by the riparian countries to reduce the quantities of water coming from the two rivers to Iraq, led by neighbor Turkey through the construction of dams and reservoirs and the establishment of irrigation projects, as well as climate changes from rising temperatures and lo

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

The location of fire brigade stations and equipment has a significant impact on the efficacy and efficiency of fire brigade department services. The challenge addressed by this study was that the fire brigade department required a consistent and repeatable technique to assess the response capabilities and safeguarding levels offered as the city of Samawah/Iraq grew and changed. Evaluating the locations of the current fire brigade stations in the city of Samawah is the aspect addressed by the research to determine the accuracy and validity of the locations of these stations by the competent authorities and their suitability to the area of the city’s neighborhoods and its residents. The Iraqi Ministry of Housing, Construction, Municipalitie

Back ground: Diabetic nephropathy is rapidly becoming the leading cause of end-stage renal disease (ESRD). The onset and course of DN can be ameliorated to a very significant degree if intervention institutes at a point very early in the course of the development of this complication.
Objective: The aim of this study was to characterize risk factors associated with nephropathy in type I diabetes and construct a module for early prediction of diabetic nephropathy (DN) by analyzing their risk factors.
Methods: Case control design of 400 patients with type I diabetes mellitus (IDDM), aged 19-45 years. The cases were 200 diabetic patients with overt protein urea while the controls were 200 diabetic patients with no protein urea or micr

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve