The aim of the research is to investigate the effect of cold plasma on the bacteria grown on texture of sesame paste in its normal particle and nano particle size. Starting by using the image segmentation process depending on the threshold method, it is used to get rid of the reflection of the glass slides on which the sesame samples are placed. The classification process implemented to separate the sesame paste texture from normal and abnormal texture. The abnormal texture appears when the bacteria has been grown on the sesame paste after being left for two days in the air, unsupervised k-mean classification process used to classify the infected region, the normal region and the treated region. The bacteria treated with cold plasma, the time exposure is two minutes. The textural features related to gray level co-occurrence matrix are calculated for the normal, abnormal and the treated texture, it is obvious that the treated texture class has the best features compared with the other classes. The result shows the sesame paste treated with plasma has good result compared with nano sesame paste treated with plasma. This is because the plasma provides the sesame paste with heat and makes the sesame nano particle congregate together.
The cathodic deposition of zinc from simulated chloride wastewater was used to characterize the mass transport properties of a flow-by fixed bed electrochemical reactor composed of vertical stack of stainless steel nets, operated in batch-recycle mode. The electrochemical reactor employed potential value in such a way that the zinc reduction occurred under mass transport control. This potential was determined by hydrodynamic voltammetry using a borate/chloride solution as supporting electrolyte on stainless steel rotating disc electrode. The results indicate that mass transfer coefficient (Km) increases with increasing of flow rate (Q) where .The electrochemical reactor proved to be efficient in removing zinc and was abl
... Show MoreOne of the main environmental problems which affect extensively the areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Landsat satellite (TM & ETM+) images have been analyzed to study soil pollution (Exacerbation of salinity in the soil without the use of abandoned agricultural for a long time) at west of Baghdad city of Iraqi country for the years 1990, 2001 & 2007. All of the th
... Show MoreAsthma is a chronic respiratory disorder of airways characterized by inflammation, hyperresponsiveness, inflammatory cell infiltration, mucous secretion, and remodelling. Ammi majus is medicinal plant belong to family of Apiaceous which has anti-inflammatory and antioxidant activities. This study designed to investigate of anti-asthmatic activity of alcoholic extract of Ammi majus in improvement of asthma. Forty-eight healthy female mice divided to six groups Group I: the negative control group (distal water only), Group II: Positive control group (ovalbumin group), Group III: Ammi majus (64 mg/kg/day) with sensitization, Group IV:Ammi majus (128 mg/kg/day) with sensitization, Group V: Ammi majus (64 mg/kg/day) without sensitiza
... Show MoreThe investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
... Show MoreThe expansion of building blocks at the expense of agricultural land is one of the main problems causing climate change within the urban area of a city. The research came to determine these indicators, as a study was conducted on the expansion of the building blocks in three municipalities in the city of Baghdad for a period of four decades extended in the form of time cycles for the period (1981-2021) and using ArcMap GIS 10.7 technology. Then, the impact of this expansion on temperature rates was evaluated, as they are the most important climatic elements due to their significant effect on the rest of the elements. The results showed a clear, direct relationship between the increase in urban expansion rates and the corresponding r
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