Two compounds,[2-amino-4-(4-nitro phenyl) 1,3-thiazole],(4) and [2-amino-4-(4-bromo phenyl) 1,3-thiazole],(5), were synthesized by refluxing thiourea (1) with each of  para-ntiro and para-bomophanacyl bromides(2) and (3) respectively, in absolute methanol. Then, by reaction of [5] with 3,5-dinitrobenzoyl chloride in dimethylformamide (DMF) yielded  (6) .On the other hand, reaction of (4) with chloroacetyl chloride in dry benzene afforded (7), which is  upon treatment with thiourea in absolute methanol, af

Otitis media with effusion (OME) is a common disease especially among young children (before school age) and it is one of the common causes of acquired hearing loss in childhood. Pediatric patients with OME are usually undernourished. The purpose of this study is to determine whether the serum levels of trace elements (zinc, copper, magnesium, iron) have a role in the development of OME in children. This study carried out on 55 children and subdivided them into two groups. Group 1 (patient group) consist of 30 children suffering from OME and group 2 (control group) included 25 apparently healthy children. Serum levels of zinc, copper, magnesium and iron were measured for both groups. Comparison the results between the two groups showed t

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Some new complexes of 4-(5-(1,5-dimethyl-3-oxo-2-phenyl pyrazolidin-4- ylimino)-3,3-dimethyl cyclohexylideneamino) -1,5- dimethyl-2- phenyl -1H- pyrazol -3(2H) –one (L) with Mn(II), Fe(III), Co(II), Ni(II), Cu(II), Pd(II), Re(V) and Pt(IV) were prepared. The ligand and its metal complexes were characterized by phisco- chemical spectroscopic techniques. The spectral data were suggested that the (L) as a neutral tetradentate ligand is coordinated with the metal ions through two nitrogen and two oxygen atoms. These studies revealed Octahedral geometries for all metal complexes, except square planar for Pd(II) complex. Moreover, the thermodynamic activation parameters, such as ?E*, ?H, ?S, ?G and K are calculated from the TGA curves using Coa

Pathogenic microorganisms are becoming more and more resistant to antimicrobial agents. So the synthesis of new antimicrobial agents is very important. In this work, new 5-fluoroisatin-chalcone conjugates 5(a–g) were synthesized based on previous research that showed the modifications of the isatin moiety led to the synthesis of many derivatives that have antimicrobial activity. 4-aminoacetophenone reacts with 5-fluoroisatin to form Schiff base (3), which in turn reacts with two different groups of aromatic (carbocyclic and heterocyclic) aldehydes 4(a–g) separately to form the final compounds 5(a–g). Proton-nuclear magnetic resonance (¹H-NMR) and Fourier-transform infrared (FT-IR) spectroscopy were used to confirm the chemic

The survey was carried out From January to April of 2018 on macrofungi samples collected from different places in Halabja province located in north eastern parts of Iraq-Kurdistan region. This region is rich in forest trees and pasture lands with diversity of shrubs and herbs and is expected to support the growth of several macro fungal species. However, this part of Kurdistan in Iraq is still unexplored from macrofungal point of view. In this paper three species from Pezizaceae and Pyronemataceae families that belonging to (Pezizales, Ascomycota), were reported from Iraqi Kurdistan. These macrofungal species are recorded for the first time from Iraq. Also the species were identified and showing their locations distributed on a map prepared

Abstract Aim: Autism is a neurodevelopmental disorder which affects communication and social interaction of children. It is a heterogeneous disease with various clinical presentations. Some genes are involved in its pathogenesis. It has been suggested that environmental exposure to lead can increase the risk of autism. The aim of our study was to compare blood lead levels among autistic and non-autistic children. Material and Method: This retrospective study included 107 children (60 with autism and 47 without autism) referred from the different Iraqi provinces, in the years 2015, 2016 and 2017, to the poisoning consultation center in Baghdad. Data collection including age, gender, residence, referral source, family history and blood lead l