New series of metal ions complexes have been prepared from the new ligand [4-Amino-N-(5- methyl-isaxazol-3-yl)-benzenesulfonamide] derived from Sulfamethoxazole and 3-aminophenol. Accordingly, mono-nuclear Mn(II), Fe(III), Co (II), and Rh(III) complexes were prepared by the reaction of previous ligand with MnCl2.4H2O, CoCl2.6H2O, FeCl3.6H2O and RhCl3H2O, respectively. The compounds have been characterized by Fourier-transform infrared (FTIR), ultraviolet–visible (UV–vis), mass, 1H-, and 13C-nuclear magnetic resonance (NMR) spectra and thermo gravimetric analysis (TGA& DSC) curve, Bohr magnetic (B.M.), elemental microanalyses, metal ions, chloride containing, and molar conductance.These reviews uncovered octahedral geometries for complex

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads

Ensuring reliable data transmission in Network on Chip (NoC) is one of the most challenging tasks, especially in noisy environments. As crosstalk, interference, and radiation were increased with manufacturers' increasing tendency to reduce the area, increase the frequencies, and reduce the voltages.  So many Error Control Codes (ECC) were proposed with different error detection and correction capacities and various degrees of complexity. Code with Crosstalk Avoidance and Error Correction (CCAEC) for network-on-chip interconnects uses simple parity check bits as the main technique to get high error correction capacity. Per this work, this coding scheme corrects up to 12 random errors, representing a high correction capac

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

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