In this work the strain energy of tetrahedrane and its nitrogen substituted molecules were calculated by isodesmic reaction method according to DFT quantum chemical fashion, the used basis set was 6-31G/B3-LYP, in addition all structures were optimized by RM1 semi-empirical method. From the obtained data we estimate an empirical equation connect between strain energy of the molecule with charge functions represented by dipole moment of the molecule plus accumulated charge density involved within the tetrahedron frame plus the number of nitrogen atoms. The results indicate the charge spreading factors by polarization and processes are the most important factors in decreasing the strain energy.

   In this paper, we investigate the basic characteristics of "magnetron sputtering plasma" using the target V₂O₅. The "magnetron sputtering plasma" is produced using "radio frequency (RF)" power supply and Argon gas. The intensity of the light emission from atoms and radicals in the plasma measured by using "optical emission spectrophotometer", and the appeared peaks in all patterns match the standard lines from NIST database and employed are to estimate the plasma parameters, of computes electron temperature and the electrons density. The characteristics of V₂O₅ sputtering plasma at multiple discharge provisos are studied at the "radio frequency" (RF) power ranging from 75 - 150 Wat

2-amino-4-(4-chloro phenyl)-1,3-thiazole (1) was synthesized by refluxing thiourea with para-chloro phenacyl bromide in absolute methanol. The condensation of amine compound (1)  with phenylisothiocyanate in the presence of pyridine will  produce 1-(4-(4-chlorophenyl)thiazol-2-yl)-3-phenylthiourea(2), which is  upon treatment with 2,4 dinitrophenyl hydrazine by conventional method, afforded 1- ( 4 - ( 4 – chlorophenyl ) thiazol – 2 – yl ) – 3 - phenylhydrazonamide,N' - ( 2 , 4 -dinitrophenyl) ,(3).The characterization of the titled compounds were performed utilizing FTIR spectroscopy, ¹HNMR and CHNS elemental analysis, and by me

Objective(s): Ramadan is the Holy month of the Muslims, where they are required to abstain from food and drinks
from dawn till the beginning of night. This study was conducted in Ramadan to investigate the effect of fasting on
hematological incidences, lipid profile, renal and liver function tests among healthy adult males.
Methodology: The present study was carried out in Ramadan – 1431 of Higira (August-September 2010). The study
sample was 56 healthy adult males. Five samples of blood were taken at five intervals (Before, at day 1, 15, 28 and
after Ramadan). Estimation was done for hematological markers, (hemoglobin, white blood cells count, platelet
count); renal function tests (blood urea, serum uric acid, serum

Abstract

          The research aims to determine the nature of the Iraqi market in terms of banking financial stability and the extent impact of the operational efficiency on it, Accordingly, chosen 15 relational banks were chosen as an intentional sample that could represent the Iraqi banking system for the period 2010-2020. The operational efficiency variable was measured according to the data envelope model, and banking financial stability used  CAMELS model which includes five indicators (capital adequacy, asset quality, management quality, profitability, and liquidity), so for testing the research hypotheses used the random regression model by adopting the S

In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

He mentioned in this article the main types of corruption, which are political, moral, financial and administrative. Others may add other types of corruption, such as religious, scientific, media, informational and statistical corruption. At the global level, the focus is largely on financial corruption, although other types of corruption are no less bad than it. Financial corruption can be defined as all financial deviations in violation of general laws or the provisions of regulations, legislation, and procedures regulating the work of the state, private institutions and individuals and applied in state institutions and the private sector in general and inconsistent with the controls and instructions of financial control.

In th

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

In this paper we reported the microfabrication of three-dimensional structures using two-photon polymerization (2PP) in a mixture of MEH-PPV and an acrylic resin. Femtosecond laser operating at 800nm was employed for the two-photon polymerization processes. As a first step in this project we obtained the better composition in order to fabricate microstructers of MEH-PPV in the resin via two-photon polymerzation. Acknowledgement:This research is support by Mazur Group, Harvrad Universirt.