Several studies have shown that certain microbes, mainly bacteria may have the ability to digest plastic wastes. The goal of this study was to see how well Bacillus subtilis, Staphylococcus lentus, Aeromonas hydrophila, Sphingomonas paucimobilis and Kocuria paedia degrade three kinds of oil-based plastics: low-density polyethylene (LDPE), polystyrene (PS) and polyvinylchloride (PVC) polymer sheets. The experiment was conducted for 30 days under laboratory conditions with occasional shaking at 180 rpm and 32°C. Biodegradation was measured in terms of weight loss.. Accordingto IR Spectroscopy, the C-H stretch band at 2920cm-1 improved as a result of bacterial degradation of polyethyl

The injection of Low Salinity Water (LSWI) as an Enhanced Oil Recovery (EOR) method has recently attracted a lot of attention. Extensive research has been conducted to investigate and identify the positive effects of LSWI on oil recovery. In order to demonstrate the impact of introducing low salinity water into a reservoir, simulations on the ECLIPSE 100 simulator are being done in this work. To simulate an actual reservoir, an easy static model was made. In order to replicate the effects of injecting low salinity water and normal salinity, or seawater, the reservoir is three-phase with oil, gas, and water. It has one injector and one producer. Five cases were suggested to investigate the effect of low salinity water injection with differen

In the present time, radioactive contamination is considered one of the most dangerous types of environmental pollution. It usually takes place because of a leakage of radioactive materials to one of the environment natural components, such as, water, air, and soil. Iraq is considered one of the most contaminated environments in the world; this is closely associated with the wars Iraq had suffered from; especially, in 1991 and 2003. Considering the importance of the radioactive contamination and its different health impacts on the population, the current paper is interested in studying this type of environmental contamination and its impact on the birth defects depending on the data available in the annual reports issued by the Iraqi min

Were studied some bacteria evidence of pollution as well as the total number of live bacteria in the waters of the Diyala river and selected five stations within the 17 km final Diyala River before its mouth in the Tigris River was the first before the new bridge of the Diyala River about 4 km and the second after the mouth of the water purification plant Rustumiya suit inverselywith temperatures

     Due to rapid urbanization and industrialization that occurred in Al- Muthanna province in southeastern Iraq during the last decade, pollutants such as heavy metals were emitted into the environment and became a serious threat to human health. Environmental pollution could be caused by different types of pollutants, which come from different sources.

     This study aims to assess the environmental magnetism efficiency for heavy metal pollution assessment using the magnetic susceptibility technique which became a more rapid and cost-effective compared to conventional methods. Increasing heavy metal contents in soils causes an increase in the magnetic mineral concentration. The study are

A series of batch demulsification runs were carried out to evaluate the final emulsified water content of emulsion samples after the exposure to microwave. An experimental study was conducted to evaluate the effects of a set of operating variables on the demulsification performance. Several microwave irradiation demulsification runs were carried out at different irradiation powers (700, 800, and 900 watt), using water-in-oil emulsion samples containing different water contents (20-80%, 30-70%, and 50-50%) and salt contents (10000, 20000, and 30000 ppm). It was found that the best separation efficiency was obtained at 900watt, 50% water content and 160 s of irradiation time. Experimental results showed that microwave radiation method can

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a