A variety of new phenolic Schiff bases derivatives have been synthesized starting from Terephthaladehyde compound, all proposed structures were supported by FTIR, 1H-NMR, 13C-NMR, Elemental analysis, some derivatives evaluated by Thermal analysis (TGA).

Three Schiff bases from Benzaldehyde and Salicylaldehyde have been synthesized (A, 1and 2) and two of them (1and 2) have been tested for anti-inflammatory activity. The p-aminobenzene sulfonamide has been synthesized from acetanilide through the addition of excess chlorosulfonic acid then concentrated ammonia solution; Schiff base of this derivative (2) exhibited good level of activity against egg-white induced edema in rat hind paw, while the other tested derivative exhibited no activity.

Key words: Schiff bases, sulfonamide derivatives, salicylaldehyde

The pharmacophore 2-aminothiazole has an interesting role in pharmaceutical chemistry as this led to the synthesis of many types of compounds with diverse biological activity. Schiff base derivatives at the same time contribute to drug evolution importantly. In this review, the Schiff base derivatives of 2-aminothiazole formed and some of their metal complexes are being focused on, and the antimicrobial and anticancer activity of them is being illustrated.

            In the present study, ( Schiff's bases 6a - 6e) and  (new amids derivatives 6f - 6j) have been synthesized . The glutaroyl chloride(2) has been prepared by the reacting of glutaric acid and thionyl chloride in presence of (DMF) . The new compound bis(4-formylphenyl) glutarate (3) has been Synthesized from reaction of one mole of glutaroyl chloride and two moles of 4-hydroxybenzaldehyde . Compound 4,4'-(glutaroylbis(oxy))dibenzoic acid (4) was Synthesized from one mole of glutaroyl chloride and two moles of 4-hydroxybenzoic acid, while compound bis(4-(chlorocarbonyl)phenyl) glutarate (5) was prepared from 4,4'-(glutaroylbis(oxy))dibenzoic acid and Thionyl chloride . Then Schiff's bases 6a - 6e that prepared

Embracing digital technological advancements in media and communication has led government entities to adopt communication practices fully aligned with the digital and networked system in government communication. Traditional media practices within the government environment increasingly rely on the ability to utilize digital tools and systems for content creation, communication, evaluation, and the management of the entire communication process within an electronic and intelligent framework for government services. Naturally, this transformation has caught the attention of communication and public relations researchers worldwide, as the digital and networked aspects of government communication now form an intelle

In this research, we present a nonparametric approach for the estimation of a copula density using different kernel density methods. Different functions were used: Gaussian, Gumbel, Clayton, and Frank copula, and through various simulation experiments we generated the standard bivariate normal distribution at samples sizes (50, 100, 250 and 500), in both high and low dependency. Different kernel methods were used to estimate the probability density function of the copula with marginal of this bivariate distribution: Mirror – Reflection (MR), Beta Kernel (BK) and transformation kernel (KD) method, then a comparison was carried out between the three methods with all the experiments using the integrated mean squared error. Furthermore, some

Non uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band at

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