In this paper, the problem of resource allocation at Al-Raji Company for soft drinks and juices was studied. The company produces several types of tasks to produce juices and soft drinks, which need machines to accomplish these tasks, as it has 6 machines that want to allocate to 4 different tasks to accomplish these tasks. The machines assigned to each task are subject to failure, as these machines are repaired to participate again in the production process. From past records of the company, the probability of failure machines at each task was calculated depending on company data information. Also, the time required for each machine to complete each task was recorded. The aim of this paper is to determine the minimum expected ti

4 Blood Res 2018;53:314-319. Received on August 11, 2018 Revised on August 30, 2018 Accepted on August 30, 2018 Background Iron overload is a risk factor affecting all patients with thalassemia intermedia (TI). We aimed to determine whether there is a relationship of serum ferritin (SF) and alanine ami- notransferase (ALT) with liver iron concentration (LIC) determined by R2 magnetic reso- nance imaging (R2-MRI), to estimate the most relevant degree of iron overload and best time to chelate in patients with TI. Methods In this cross-sectional study, 119 patients with TI (mean age years) were randomly se- lected and compared with 120 patients who had a diagnosis of thalassemia major (TM). Correlations of LIC, as determined by R2-MRI, with SF

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

Panax ginseng (PG), one of the most widely used herbal medicines, has demonstrated various beneficial effects such as anti-inflammatory, antioxidant, and anticancer impacts. Naturally occurring ginsenosides in the ginseng plant inhibit cell proliferation and significantly reduce liver damage induced by certain chemicals. Aflatoxin B1 (AFB1) is a primary mycotoxin due to its hepatotoxic, immunotoxic, and oncogenic effects in animal models and humans. In this study, we examined the effects of assorted doses of PG aqueous crude extract on the expression of matrix metalloproteinase 1 and 7 (MMP-1 and MMP-7) in the kidney, spleen, and liver of experimental AFB1-exposed mice, using immunohistochemistry (IHC). Mice were orally administered

A numerical study of the two-dimensional steady free convection flow in an inclined annulus between two concentric square cavities filled with a porous medium is presented in this paper for the case when the side outer walls are kept with differentially heated temperature while the horizontal outer walls and the inner walls are insulated. The heated wall is assumed to have spatial sinusoidal temperature variation about a constant mean value. The Darcy model is used and the fluid is assumed to be a standard Boussinesq fluid. For the Cartesian coordinate system, the governing equations which were used in stream function form are discretized by using the finite difference method with successive under – relaxation method (SUR) and are solv

This research aims to test the ability of glass waste powder to adsorb cadmium from aqueous solutions. The glass wastes were collected from the Glass Manufacturing Factory in Ramadi. The effect of concentration and reaction time on sorption was tested through a series of laboratory experiments. Four Cd concentrations (20, 40, 60, and 80) as each concentration was tested ten times for 5, 10, 15, 20, 25, 30, 35, 40, 45, and 50 min. Solid (glass wastes) to liquid was 2g to 30ml was fixed in each experiment where the total volume of the solution was 30ml. The pH, total dissolved salts and electrical conductivity were measured at 30ºC. The equilibrium concentration was determined at 25 minutes, thereafter it was noted that the sorption

This article publishes seven cuneiform tablets in the collection of the Iraq Museum Baghdad. Six of the tablets have an Irisagrig/Al Sarraki provenance, the seventh is of uncertain origin. They are dated to the reigns of Amar-Suen (AS) and Ibbi-Suen (IS) of the Ur III Dynasty. The texts represent administrative texts of the governing institutions and account for economic activities including the assignment of female workers for wool plucking, the remuneration of canal work with barley and the selection of wool for textiles. Three tablets record offerings in respect of cultic observances, two of which describe the disbursement of foodstuffs for the king's monthly 83-63 offerings to the new moon.

Background: Metal ions can be released from metallic orthodontic appliances due to corrosion in the oral cavity; prophylactic mouthwashes may have an effect on ion release from orthodontic wires. Materials and Methods: Thirty six orthodontic sets of half maxillary fixed appliance with 2 types of arch wires SS and NiTi(Morelli) were constructed and immersed in 2 types of mouthwashes; Claradone (non-fluoridated) and Silver Care (fluoridated) for 28 days at 37°C, then the released Ni and Cr ionswere measured using atomic absorption spectrophotometer and compared statistically. Results: Ni ion release was higher from NiTi wire group than SS wire group for both mouthwashes and also was higher for Silver Care group than for Claradone group.

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.