The reaction of 2-amino benzoic acid with 1,2-dichloroethane under reflux in methanol and KOH as a base to gave the precursor [H₄L]. The precursor under reflux and drops of CH₃COOH which reacted with (2mole) from salicycaldehyde in methanol to gave a new type N₂O₄ ligand [H₂L], this ligand was reacted with (MCl₂) Where [M= Co (II), Ni(II), Cu(II) and Zn(II)] in (1:1) ratio at reflux in methanol using KOH as a base, to give complexes of the general formula [M(L)]. All compounds have been characterized by spectroscopic methods [¹H NMR ( just to the ligand), FTIR, uv-vis, atomic absorption], melting point, conductivity, chloride content, as well as m

This work contains synthesis and characterization of new compounds [I-VIII], starting from compound [I] which was prepared through the reaction of chloroacetyl chloride with hydrazine hydrate and then cyclized the product with chloroacetic acid using phosphorous oxychloride to give 2,5-bis(chloromethyl)-1,3,4-oxadiazole compound [II], then the later compound [II] reacted with 4-hydroxy benzaldehyde to form compound [III]. The compound thiazolidine 2,4-dione [IV] was prepared from the reaction of chloroacetic acid with thiourea. Subsequently compound [III] reacted with compound [IV] to get [V] compound. Then the later compound was reacted with n-alkyl bromide (with several carbon atoms n= 4,5,6,8 ) to give compounds [VI]n. compound

Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential

This article includes designed and synthesized for bent-shaped liquid crystal molecules starting from 5,5-diethylpyrimidine-2,4,6(1H,3H,5H)-trione and two moles of chloroacetylchloride in N, N-dimethyl formamide (DMF) and triethylamine (TEA) to product compound [I] ,then reacted the later compound with two moles of 4-hydroxybenzonitrile to yield nitrile compound [II]. Likewise, reaction 5,5-diethylpyrimidine-2,4,6(1H,3H,5H)-trione and two moles of ethylchloroacetate with fused sodium acetate in ethanol to create an ester compound [III], and then the later compound was reacted with two moles of hydrazine hydrate in ethanol to obtained hydrazide acid compound [IV]. After that, the compound [IV] reacted with two moles of ethyl acetoacetate in

A set newly complexes with the general formula [M(L)Cl2] are resulting from the reaction of a new schiff base ligand [Ethyl (6R,7R)-7-((E)-2-((2-ethoxy-2- oxoethoxy)imino)-2-(2-(((E)-4-nitrobenzylidene) amino) thiazol -4- yl) acetamido) -8- oxo -3- vinyl -5- thia -1-aza bicyclo [4. 2.0] oct -2- ene -2- carboxylate] (L). This ligand was derived from the reaction of the two substances 4-nitrobenzaldehyde and precursor (P). Reaction the ligand with metal ions M= Mn(II), Co(II), Ni(II), Cu(II) and Cd(II) afforded new complexes which are characterized by FT-IR and Electronic Spectra. These measurements indicate that the complexes have a tetrahedral geometry. The Penicillin-Binding Protein 3 (PBP3) of Staphylococcus aureus and the target protein

A multistep synthesis was established for the preparation of a new vanillic acid-1, 2, 4-1triazole-3-thiol conjugate (4). Finally, several aromatized aldehydes reacted with compound (4) to produce Schiff bases derivatives (5–11). The purpose of this research is to prepare new vanillic acid derivatives with 1, 2, 4-triazole-3-thiol heterocyclic ring structures and to evaluate their antimicrobial activity in a preliminary assessment. Fourier-transform infrared (FT-IR) and proton nuclear magnetic resonance spectroscopy (¹H-NMR) were used to verify the structures of the newly synthesized compounds. all the final synthesized compounds (

طريقة سهلة وبسيطة ودقيقة لتقدير السبروفلوكساسين  في وجود السيفاليكسين او العكس بالعكس في خليط منهما. طبقت الطريقة المقترحة بطريقة الاضافة القياسية لنقطة بنجاح في تقدير السبروفلوكساسين بوجود السيفاليكسين كمتداخل عند الاطوال الموجية 240-272.3 نانوميتر وبتراكيز مختلفة من  السبروفلوكساسين 4-18 مايكروغرام . مل-1 وكذلك تقدير السيفاليكسين بوجود السبروفلوكساسين الذي يتداخل باطوال موجية 262-285.7 نانوميتر وبتراكيز مخ

Nowadays, university education stands in front of both students who feel they are weak and teachers who are addicted to using traditional and dependent teaching. This has led to have negative repercussions on the learner from different aspects, including the mental aspect and the academic achievement process. Therefore, the present research is concerned with finding a new teaching method that adopts the motivation by the fear of failure technique. Thus, the study aims to examine the effect of adopting this method on students’ academic achievement. To achieve this aim, an experimental method was used, and an achievement test was built for the curriculum material of level two students. The pretest test was applied on 17 male and female s

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv