Ibuprofen is one of the most important members of NSAIDs, named aryl propionic acid derivative. Isatin (1H-indole-2,3-dione) is an important molecule of heterocyclic compounds that have many biological activities. This work illustrates the synthesis of new ibuprofen-isatin derivatives by connecting ibuprofen hydrazide with different isatin derivatives by a condensation reaction, followed by characterization by fourier-transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1H-NMR) spectroscopy. The anti-inflammatory activity was evaluated by using the egg-white induce edema method for all the synthesized compounds (5-8), the compounds 5 and 6 showed better anti-inflammatory activity than ibuprofen as a standard

Ibuprofen is one of the most important members of NSAIDs, named aryl propionic acid derivative. Isatin (1H-indole-2,3-dione) is an important molecule of heterocyclic compounds that have many biological activities. This work illustrates the synthesis of new ibuprofen-isatin derivatives by connecting ibuprofen hydrazide with different isatin derivatives by a condensation reaction, followed by characterization by fourier-transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1H-NMR) spectroscopy. The anti-inflammatory activity was evaluated by using the egg-white induce edema method for all the synthesized compounds (5-8), the compounds 5 and 6 showed better anti-inflammatory activity than ibuprofen as a standard compoun

ABSTRACT Background: One of the challenges to use chlorhexidine is its effect on the amount of microleakage after restoration; however, use of the materials with antibacterial properties after tooth preparation and before restoration has been widespread. The objective of this, in-vitro, study was to evaluate the influence of consepsis (chlorhexidine gloconate disinfectant) application on microleakage in class II cavities restored with light cured composite using universal adhesive system; etch and rinse technique –self etch technique. Materials and Methods: Forty class II cavities were prepared on mesial and distal surfaces of 20 non-carious mandibular third molars. The cavities were divided into four groups; (n =10 for each group).

We study in this paper the composition operator that is induced by ?(z) = sz + t. We give a characterization of the adjoint of composiotion operators generated by self-maps of the unit ball of form ?(z) = sz + t for which |s|?1, |t|<1 and |s|+|t|?1. In fact we prove that the adjoint is a product of toeplitz operators and composition operator. Also, we have studied the compactness of C? and give some other partial results.

The main objective of this paper is to designed algorithms and implemented in the construction of the main program designated for the determination the tenser product of representation for the special linear group.

Oscillation criteria are obtained for all solutions of the first-order linear delay differential equations with positive and negative coefficients where we established some sufficient conditions so that every solution of (1.1) oscillate. This paper generalized the results in [11]. Some examples are considered to illustrate our main results.

The process of selection assure the objective of receiving for chosen ones to high levels more than other ways , and the problem of this research came by these inquires (what is the variables of limits we must considered when first preliminaries selections for mini basket ? and what is the proper test that suits this category ? and is there any standards references it can be depend on it ?) also the aims of this research that knowing the limits variables to basketball mini and their tests as a indicators for preliminaries for mini basketball category in ages (9-12) years and specifies standards (modified standards degrees in following method) to tests results to some limits variables for research sample. Also the researchers depends on (16)

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).