This study describes the preparation of tetradentate Schiff base derived from the condensation of 2-Hydroxy naphthaldehyde with 2-amine benzhydrazide and the synthesis of new complexes series with a good yield.The prepared ligand was characterized using a microanalysis technique, UV-visible, FT-IR, nuclear magnetic resonance ¹H-NMR, mass spectrometry, thermal gravimetric analysis TGA, and the addition of conductivity measurement and magnetic moment of complexes. The invitro antimicrobial activity of the prepared compounds was tested against  Gram-negative Klebsiella pneumonia, Gram-positive Staphylococcus aureu, and Candida albicans by the agar well diffusion method. The spectroscopy and measurement studies showed that the li

       In this study, light elements 19F ,22Na for  (α,n) and (n,α) reactions as well as α-particle energy  from a threshold energy  to 10 MeV are used according to the available data of reaction cross sections.  The more recent cross sections data of (α,n) and (n,α) reactions are reproduced in fine steps 86.4 KeV for 22Na (n,α) 19F  in the specified energy range, as well as cross section (α,n)  values were derived from the published data of (n,α) as a function of αenergy in the same fine energy steps by using the principle inverse reactions. This calculation involves only the ground state of  19F ,22Na in the reactions 19F (α,n) 22Na ,  2

Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc

Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc

Background: Diarrheal diseases are still a major public health problem especially in developing countries, due to their high morbidity & mortality rates, moreover the lagest
number of deaths with diarrheal diseases are due to persistent diarrheal states.We attemted to evaluate the size of the problem in our infants, and assess risk factors & outcome.
Methods: A retrospective study was performed in Al-Kadhemya teaching hospital, to evaluate diarrheal cases in under 2 years of age children , admitted to hospital during the period (Dec. 1991- Dec. 2001), from a total of 863, chronic diarrheal cases formed 286 (33.14%) that were evaluated for certain variables; epidemiology & risk factors etiology ,

Abstract: The aim of the current research is to identify (the relationship between deep understanding skills and mathematical modeling among fifth grade students) the research sample consisted of (411) male and female students of the fifth grade of biology distributed over the General Directorates of Education in Baghdad / Al-Rusafa / 2 / and Al-Karkh / 1 /, and two research tools were built: 1- A test of deep understanding skills, consisting of (20) test items and a scale for two skills. 2- The second test consists of (24) test items distributed among (18) essay items and (6) objective items. The psychometric properties of validity, stability, discriminatory strength, and effectiveness of alternatives were verified for the two tests fo

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to