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

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

Coupling reaction of ( 4-amino antipyrene) with the (L- tyrosine ) gave the new azo ligand 2- ( 4- Antipyrene azo ) - tyrosine .Treatment of this ligand with metal ions (Mn(II) ,Co(II), Ni(II), and Cu(II) )in ethanolic medium in (1:2) (M:L) ratio yield a series of a neutral complexes of the general formula [M(L)2] . The prepared complexes were characterized using flame atomic absorption , FT.IR , UV-Vis spectroscopic and elemental microanalysis (C.H.N) as well as magnetic susceptibility and conductivity measurement

Systemic lupus Erythematosus is an autoimmune disease of unknown aetiology affecting multiple organ system. Reactive nitrogen and oxygen species are claimed to play a role in this disease. However, the potential of Nitrosative/Oxidative Stress to elicit an autoimmune, response remain till now largely unexplored in humans. This study was done to investigate the status and contribution of nitrosative/oxidative stress in Iraqi patients for systemic lupus erythematosus. Blood samples from 19 patients with systemic lupus erythematosus and 19 age-and sex- matched apparently healthy controls were evaluated for serum levels of nitrosative/oxidative stress markers including nitric oxide, peroxynitrite and malondialdehyde. Nitric oxide levels were

Photocatalyst composed of core/shell magnetic zincoxysulfide nanocomposite coated with sulfonated polyindole ([email protected]/SPID) has been prepared and used for simultaneous photocatalytic H2 production and Bisphenol A (BPA) degradation. XRD, FE-SEM, EDX, BET surface area, UV-vis DRS and VSM were used to characterize the synthesized nanocomposites. The photocatalytic performance was evaluated using batch reactor under visible light irradiation. The photocatalytic activity of [email protected]/SPID nanocomposite was revealed to exceed that of [email protected] nanocomposite due to the heterojunctions between SPID and [email protected] species. The results exhibited that the effect of BPA initial concentration was found to be effectual on the improvement

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

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class