Background: Cholera has been recognized as a killer disease since earliest time. The disease is caused by infection of the small intestine by Vibrio cholerae O1 and O1391 which is characterized by severe dehydrating diarrheal condition and is one disease in modern times that is epidemic, endemic and pandemic in nature. Objective: This study was carried out to detect and isolate V. cholerae from patients suffered from watery diarrhea, which may cause severe complications such as dehydration, shock followed by death. Materials and methods: stool specimens were collected from 308 patients with watery diarrhea. These samples were tested with many criteria such as TCBS agar, gram stain, biochemical tests and VITEK-2 system to improve the isolati

 A new series of Sulfamethoxazole derivatives was prepared and examined for antifibrinolytic and antimicrobial activities. Sulfamethoxazole derivatives bear heterocyclic moieties such as 1,3,4-thiadiazine {3},  pyrazolidine-3,5-diol {4} 6-hydroxy-1,3,4-thiadiazinane-2-thione {5} and [(3-methyl-5-oxo-4,5-dihydro-1H-pyrazol-4-yl)diazenyl] {8}. Their structures were elucidated by spectral methods (FT-IR, H¹-NMR). Physical properties are also determined for all compound derivatives.  Recently prepared compounds were tested for their antimicrobial activity in the laboratory. Each screened compound showed good tendency to moderate antimicrobial activity.

The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

Abstract

In this manuscript, a simple new method for the green synthesis of platinum nanoparticles (Pt NPs) utilizing F. carica Fig extract as reducing agent for antimicrobial activities was reported. Simultaneously, the microstructural and morphological features of the synthesized Pt NPs were thoroughly investigated. In particular, the attained Pt NPs exhibited spherical shape with diameter range of 5-30 nm and root mean square of 9.48 nm using Transmission Electron Microscopy (TEM) and Atomic Force Microscopy (AFM), respectively. Additionally, the final product (Pt NPs) was screened as antifungal and antibacterial agent against Candida and Aspergillus species as well as Gram-positive Staphyllococcus aureus and G

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

Objective: To identify causes of maternal death in Mizan Aman and Gebretsadik shawo general hospitals
Methodology: A case control study on 595 charts, 119 cases and 476 controls was conducted in Mizan
Aman & Gebretsadik shawo general hospitals. Data was analyzed by STATA 13.1. Propensity score
matching analysis was used to see causes of maternal death.
Results: Hemorrhage were the main direct causes of maternal death which accounts 47.9% (β =0.58
(95% CI (0.28,0.87)) in hospital but when projected to population based the sample (β =0.26 (95% CI
(0.22,0.31)). Followed by infection 36 (25.21%) (β = 0.50 (95% CI (0.08, 0.92)). when projected to
population based the sample PIH 7.6%) is significant cause (β = 0.16

‎ This research aims to estimate stock returns, according to the ‎Rough Set Theory ‎approach, ‎test ‎its effectiveness and accuracy in predicting stock returns and their potential in the ‎field of ‎financial ‎markets, and rationalize investor decisions. The research sample is totaling (10) ‎companies traded at Iraq Stock Exchange. The results showed a remarkable ‎ ‎Rough Set Theory application in data reduction, contributing to the rationalization of ‎investment ‎decisions. The most prominent conclusions are the capability of rough set theory ‎in ‎dealing with financial data and applying it for forecasting stock ‎returns.‎The ‎research provides those interested in investing stocks in financial

Abstract Sweden is today one of the most active European countries in the regional and international environment despite the adoption of neutrality as a guiding principle in its foreign policy. For more than two centuries, the length of time for Swedish neutrality has made it a global standard, an agreed foreign policy at home and a political culture rooted in institutions and society. Swedish. Although discussions are still underway on Swedish security and foreign policies after the end of the Cold War, especially cooperation with NATO through the Partnership for Peaceprogram, EU accession and its impact on the principle of neutrality in foreign policy. Sweden, however, insists that it still maintains neutrality, but more adequately, in