Nanosponges (NS) of etodolac(ETO) was prepared using the emulsion solvent diffusion method ; the effects of drug: polymer ratio, the effect of level concentration of internal phase and stirring time and other variables that effect on the physical characteristics of NS were investigated and characterized, The selected formula was lyophilized then incorporated into hydrogel ; which also evaluated .The results show that the formulation that contain Drug: PVA:EC in ratio 1:3:2 is the best with smallest particle size 40.2±0.098 with polydispersibility0.005 and in vitro release 97.6±0.11%, , ETO NS Carbopol hydrogel produced a significant(p<0.05) improvement of the in vitro release than pure ETO hydrogel.

      Political Discourse Analysis is an important linguistic study approach used by politicians to gain people support. The present paper sheds light on the figures of speech  of emphasis in the televised debate between the two presidential elections candidates, Emmanuel Macron and Marine Le Pen and the distinctive effect they add to the political discourse to win general public support as well as the presidential elections.

       The present paper provides a rudimentary definition and an analysis of the terms “discourse” and “political discourse” and traces the significant role played by politically directed televised Media and internet to support political pa

Systemic lupus erythematosus (SLE) is the prototypic multisystem autoimmune disorder with a broad spectrum of clinical presentations encompassing almost all organs and tissues. Aimes of study determination of integrin- linked kinase 1(ILK-1) and anti-smith antibody(ASAB) levels in serum of Iraqi patients with systemic lupus erythematosus, in addition, that ILK-1 may be as a diagnostic marker of SLE disease, and study the effect of systemic lupus erythematosus on renal function in these patients. This study included 100 females’ patients with systemic lupus erythematosus attending to the Rheumatology Unit in Baghdad Teaching Hospital, Medical City, (Baghdad), in addition to 30 healthy females as controller group were chosen without any chr

Hydrogen sulfide removal catalyst was prepared chemically by precipitation of zinc bicarbonate at a controlled pH. The physical and chemical catalyst characterization properties were investigated. The catalyst was tested for its activity in adsorption of H₂S using a plant that generates the H₂S from naphtha hydrodesulphurization and a unit for the adsorption of H₂S. The results comparison between the prepared and commercial catalysts revealed that the chemical method can be used to prepare the catalyst with a very good activity.

It has observed that the hydrogen sulfide removal over zinc oxide catalyst follows first order reaction kinetics with activation energy of 19.26 kJ/mole and enthalpy and e

&nbsp;The reaction of L-ascorbic acid with the tirchloroacetic acid in the presence of potassium hydroxide gave new product Bis[O,O-2,3;O,O-5,6(chlorocarboxylicmethyliden)]Lascorbic acid (H2L) which was isolated and characterized by 1H,13C-NMR, elemental analysis (C,H,N), UV-Visible and Fourier Transform Infrared (FTIR). The complexes of the ligand (H2L) with metal ions, M+2= (Cu, Co, Ni, Cd and Hg) were synthesized and characterized by FTIR, UV-Visible, molar conductance, atomic absorption, magnetic susceptibility and the molar ratio. The analysis evidence showed the binding of the metal ions with (H2L) through the bicarboxylato group manner resulting in six-coordinated metal ion. The TLC for (H2L) and complexes showed one spot for eac

New two experiments of the three factors, in this study were constructed to investigate the effects, of the fixed variations to the box plot on subjects' judgments of the box lengths. These two experiments were constructed as an extension to the group B experiments, the ratio experiments the experiments with two variables carried out previously by Hussin, M.M. (1989, 2006, 2007). The first experiment box notch experiment, and the second experiment outlier values experiment. Subjects were asked to judge what percentage the shorter represented of the longer length in pairs of box lengths and give an estimate of percentage, one being a standard plot and the other being of a different box lengths and

Colloidal silver nanoparticles were prepared by single step green synthesis using aqueous extracts of the leaves of thyme as a function of different molar concentration of AgNO₃ (1,2,3,4 mM(. The Field Emission Scanning Electron Microscopy (FESEM), UV-Visible and X-ray diffraction (XRD) were used to characterize the resultant AgNPs. The surface Plasmon resonance was observed at wavelength of 444 nm. The four intensive peaks of XRD pattern indicate the crystalline nature and the face centered cubic structure of the AgNPs. The average crystallite size of the AgNPs ranged from 18 to 22 nm. The FESEM image illustrated the well dispersion of the AgNPs and the spherical shape of the nanoparticles with a particle size distribution be

The [2-aminobenzothiazole]was reacted with [2,4,6 triyhydroxy-acetophenon monohydrate] to give a new ligand [2-N-2,4,6-trihydroxyacetophenonyliden benzothiazole] [H3L]. This ligand was reacted with metal ions ( CoII, NiII,CuII and ZnII) in methanol as solvent with ( 1:2 ) metal : ligand ratio to give a series of new complexes with general formula [ M(H2L)2],(where:M= CoII, NiII ,CuIIand, ZnII).All compounds were characterized by spectroscopic methods ( I.R , U.V – vis,HPLC) atomic absorption, along with chloride content and conductivity measurements. According to the data of these measurements we suggested a tetrahedral

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D