This research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing i

Background: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast.

Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors¹ and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.¹ As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing wit

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

   The potential application of granules of brick waste (GBW) as a low-cost sorbent for removal of Ni⁺²ions from aqueous solutions has been studied. The properties of GBW were determined through several tests such as X-Ray diffraction (XRD), Energy dispersive X-ray (EDX), Scanning electron microscopy (SEM), and BET surface area. In batch tests, the influence of several operating parameters including contact time, initial concentration, agitation speed, and the dose of GBW was investigated. The best values of these parameters that provided maximum removal efficiency of nickel (39.4%) were 1.5 hr, 50 mg/L, 250 rpm, and 1.8 g/100mL, respectively. The adsorption data obtained by batch experiments subjected to the Three i

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

AbstractThe objective of the present study was measured of several oxidative stresses and liver function parameters in workers occupationally exposed to cement dust in Kufa Cement Factory, in order to test the hypothesis that cement dust exposure may perturb these parameters. Assessment of oxidative stress and liver function parameters were performed in 63 workers occupationally, in different departments of Kufa Cement Factory, exposed to cement dust (range of the exposure time was 5-38 years) and 36 matched unexposed controls. The study results illustrated an increasing in the oxidative stress parameters, moreover; liver function parameters showed abnormal results in the exposed workers compared to the unexposed. An increase in theses para

Background: Saliva is a specific bio-fluid with important biomarkers. Analyzing any alternation in these markers could give valuable information, in relation to oral health status parameters. The aim of this study was to investigate the level of α -amylase in unstimulated whole saliva of healthy, primary school children in relation to some oral health parameters. Materials and Methods: A questionnaires consisted of demography and medical histories of participants were filled by children families. Saliva samples were collected for 5- minutes between 9:00 -11:00 AM from 114 healthy students aged 6-13 years, divided into four age groups. Flow- rate, Plaque and Gingival Index were assessed and dentition status was investigated by DMFT/dmft

One of the key molecules in the conversion of sphingosine to sphingosine-1- phosphate is SPHK-1, also known as Sphingosine Kinase 1 (SPHK-1). Sphingosine-1-phosphate (S1P) is a lipid that acts as a signaling molecule and plays an essential role in inflammatory and immunomodulatory responses. S1P has recently been identified as a mediator and a biomarker in inflammatory bone diseases such as osteoporosis and inflammatory osteolysis based on the biological effects of S1P in osteoclastic and osteoblastic cells and immune cells. According to recent research, S1P may play a role in the pathogenesis of periodontitis, an inflammatory bone-destructive condition. This study assesses the salivary level SPHK-1 in periodontitis and its correlat