Corncob is an agricultural biomass waste that was widely investigated as an adsorbent of contaminants after transforming it into activated carbon. In this research carbonization and chemical activation processes were achieved to synthesize corncob-activated carbon (CAC). Many pretreatment steps including crushing, grinding, and drying to obtain corncob powder were performed before the carbonization step. The carbonization of corncob powder has occurred in the absence of air at a temperature of 500 °C. The chemical activation was accomplished by using HCl as an acidic activation agent. Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) facilitate

New schiff bases series (VIII) a-e and 1,3-thiazolidin-4-one derivatives (IX) a-e containing the 1,2,4-triazole and 1,3,4-thiazazole rings were synthesized and screening their biological activities. These compounds were identified via Fourier transform infrared (FT-IR) spectra, some via Proton nuclear magnetic resonance (1H-NMR) and mass spectra. The biological results indicated that all of these compounds did not reveal antibacterial effectiveness against (Escherichia coli and Klebsiella species) (G-). Some of these compounds showed moderate antibacterial activity against (Staphylococcus aureus, and Staphylococcus epidermidis) (G+), and all compounds exhibited moderate activity against Candida albicans.

This study was conducted to isolate and identify killer yeast Hanseniaspora uvarum from dates vinegar and measurement the ability of this yeast to produce killer toxin. The antimicrobial activity of the concentrated supernatant containing partially purified concentrated killer toxin was also detected against several pathogenic bacteria and yeast species, which includes two types of yeast Rhodotorula mucilaginosa and Candida tropicalis and four human pathogenic bacteria Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeurginosa. In addition, the antagonistic activity of examined yeast have been studied toward four types of fungi, where two are pathogenic

In this study, an analysis of the synoptic characteristics, causes and mechanisms of Kahlaa tornado event was carried out. This tornado occurred on 10:30 UTC (1:30 pm Iraq Local Time) on 14 April 2016 to the north of Kahlaa town in Maysan governorate. We analyzed surface and upper charts, weather conditions, the damage indices, the dynamical features and the instability of the tornado. The analysis showed that there was a low pressure system which was an extension of the Monsoon low in addition to a supercell thunderstorm and a jet stream aloft. The cold trough and high relative vorticity at 500 hPa level, the humid warm wind blowing from the south and the dry cold wind from the north contributed to the initiation of the tornado. Accordi

Background: The incidence of oral cancers is increasing all over the world. Early detection ofthis important public health matter makes them more amenable to treatment and allows the greatest chance of cure.The aim of this study was to investigate the awareness and knowledge on oral cancer among final -year dental students in Iraq. Materials and methods: Questionnaires were delivered to 160 final–year dental students in the College of Dentistry in Baghdad. The questionnaire focused on the awareness/knowledge of oral cancer, earlyand common clinical signs and symptoms andassociated risk factors. Results: It was found that 87% of students were aware of oral cancer. The followings were recognized as signs and symptoms of oral cancer: persis

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals