In this study, the water treatment plants located on the Tigris River within Baghdad city were subjected to qualitative and quantitative assessments. Based on location, the plants from upstream to downstream are Al-Karkh, East Tigris, Al-Karamah, Al-Wathbah, Al-Wehdah, Al-Kadiseyah, Al-Dora, and Al-Rashid. Data from 2009 to 2020 on the turbidity, total dissolved solids, Alkalinity, hardness, chloride, calcium, and temperature were used in the qualitative assessment while data on the treated water production and population served were used in the quantitative assessment. The above Data was acquired from the Municipality of Baghdad. The turbidity was mainly used as a fair gauge to assess the performance of the water treatment plants in Baghda

One hundred isolates of Pseudomonas aeruginosa were obtained from patients admitted to Baghdad hospitals, Iraq during the period between May 2018 until July 2018. These isolates were distributed as 15 isolates from blood, 25 isolates from urinary tract infections, 10 isolates from sputum, 12 isolates from wounds, 15 isolates from ear infections, 15 isolates from bronchial wash of patients suffering from respiratory tract infections in addition to 8 isolates from cystic fibrosis patients. The isolates were initially identified by culturing on MacConkey agar, blood agar and P. aeruginosa agar then diagnosed by performing some morphological and biochemical tests. The second diagnosis was done by API 20E system followed by Vitek 2 compact syste

  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

In this paper solar radiation was studied over a region of Baghdad (Latitude 33.3o and longitude 44.4o). The two parts of global solar radiation: diffuse and direct solar radiation were estimated depending on the clearance index of measured data (Average Monthly mean global solar radiation). Metrological data of measured (average monthly mean diffuse and direct solar radiation) were used to comparison the results and show the agreement between them. Results are determined by applying Liu and Jordan two models (1960). Excel 2007program is used in calculation, graphics and comparison the results.

To determine the relationship between herpes simplex virus 1, 2 and neurological disorders, sixty samples from patients with neurological diseases were collected (40 patients with Multiple sclerosis and 20 patients with Parkinson’s disease) all of whom attended both the Neurological science Hospital as well as the Neuropathology consultation Department in Baghdad Hospital In Iraq. The samples were collected in the time frame between November 2017 and April 2018. The ages of the patients that were investigated were between (17-76) years and compared to a control group consisting of 25 samples collected from apparently healthy individuals. All the studied groups were subjected to the measurement of anti-HSV 1, 2 IgG antibodies by the means

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

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami