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.

Background: Diabetes mellitus is a metabolic disorder affecting people worldwide, which require constant monitoring of their glucose levels. Commonly employed procedures include collection of blood or urine samples causing discomfort to the patients. Necessity arises to find alternative non invasive technique is required to monitor glucose levels. Saliva is one of most abundant secretions in the human body and its collection is easy, noninvasive and painless technique. Objective: The aim of this study was to determine the efficacy of saliva as a diagnostic tool by study the correlation between blood and salivary glucose levels and glycosylated hemoglobin (HbA1c%) in diabetes and non diabetes, and the comparison of salivary glucose level

This study included estimation of glutathione (GSH) and Malondialdehyde (MDA) levels in the serum of diabetic patients type II who are treated with a polyherbs mixture (Nigella sativa, Trigonella foenum-graeum, Cyperus rotundus and Teucrium polium) for three months of treatments. Seventy samples of diabetic patients Type II male and females with age about (35-60) years were taken including 44 samples for group one (24 male, 20 female) who used herbs accompanied with chemical treatment (drugs) and 26 samples for the second group (13male and 13 female) who used herbs only. These groups were compared with 60 samples obtained from healthy persons (29 male, 31 female) at the same age of patients as a control group. Effect of age and treatment fo

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

Objective (s): To determine factors associated with the pregnancy complications (Maternal age, education,
obstetrical history, gravidity, birth space interval, and smoking).
Methodology: A cross-sectional study conducted at Al- washash & Bab-almoadham primary health care
centers. The sample was (non probability convenient sample) which included (550) pregnant women. The
study started from 1st April 2014 to 1
st of April 2015. The data was collected by direct interview using
special questionnaire to obtain socio-demographic information.
Results: the result shows that mean age of the subjects was 26.5± 4.39 years, 57.8% were housewives, the
sample included 103 premature uterine contractions, 98 pregnancy induce

Transactions on Engineering and Sciences

. 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

It must be emphasized that media is amongst human studies fusing older and more recent sciences together, and that its disclosures are the physics of the new communication. Michio Kaku, a theoretical physicist, in his book “ Visions”, confirms this fact when he says :” As a research physicist, I believe that physicists have been particularly successful at predicting the broad outlines of the future .Professionally, I work in one of the most fundamental areas of physics, the quest to complete Einstein's dream of a "theory of everything." As a result, I am constantly reminded of the ways in which quantum physics touches many of the key discoveries that shaped the twentieth century. “ He then got to the fact that the physical disclo

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