Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the reversibility of NP adsorption onto carbonate surfaces was measured using dynamic light scattering (DLS), scanning electron microscope (SEM) images, energy dispersive X-ray spectroscope (EDS), and atomic force microscope (AFM) measurement. Results show that the initial hydrophilicity of the NP and the carbonate rock surface can influence the NPs adsorption onto the rock surfaces. Typically, oppositely charged NP and rock surface are attracted to each other, forming a mono or multilayers of NPs on the rock. Operation conditions including pressure and temperature have shown minor influence on nano-treatment efficiency. Moreover, DLS measurement proved the impact of hydrophilicity on the stability and adsorption trend of NPs. This was also confirmed by SEM images. Further, AFM results indicated that a wide-ranging adsorption scenario of NPs on the carbonate surface exists. Similar results were obtained from the EDS measurements. This study thus gives the first insight into NPs adsorption onto carbonate surfaces at reservoirs conditions.
Coeliac disease is an immunologically mediated disease of the small intestinal mucosa, characterized by flattening of the small intestinal villi, increased numbers of intra-epithelial lymphocytes and inflammatory cell infiltrates in the lamina propria, resulting in gut damage and nonspecific malabsorption of nutrients. The disease is elicited by ingestion of gluten, a protein found in several cereals, principally wheat, but also barley and to a lesser extent, oats. Successful treatment is avoidance of dietary gluten. Long-standing evidence suggests a T-cell-mediated response to peptides derived from the gliadin fraction of wheat gluten, leading to immunologically mediated intestinal injury in genetically susceptible individuals. The
... Show MoreThis research aims to identify the reality of Sino-Russian relations after 2013, and to study the most important motives and determinants that affected the nature of these relations. The research was based on the criterion of national interest in interpreting and understanding relations between China and Russia, on the basis that national interest is what determines the state of cooperation and dependence, or the state of competition and difference. The research was based on the hypothesis that Sino-Russian relations after 2013 witnessed many factors and variables, some of which represented motives for strengthening relations between the two countries, and others represented obstacles that limit the level of cooperation and interaction betw
... Show MoreThe present study examines the main points of differences in the subject of greetings between the English language and the Arabic language. From the review of the related literature on greetings in both languages, it is found that Arabic greeting formulas are more elaborate than the English greetings, because of the differences in the social customs and the Arabic traditions and the Arabic culture. It is also found that Arabic greetings carry a religious meaning basing on the Islamic principle of “the same or more so”, which might lead to untranslatable loopholes when rendered in English.
Mercury is a heavy metal that is extremely toxic. There are three types of it: inorganic, organic, and elemental. Mercury in all its forms has been shown to have harmful effects on living things. It can multiply its concentration from lower to higher trophic levels and accumulate in the body's various tissues. Aquatic organisms bodies have been exposed to mercury mostly through various human activities. The largest source of mercury pollution in the air is thermal power plants that mostly use coal as fuel. It is carried to a body of water after being deposited on the ground surface from the air. The way it enters the food chain is through aquatic plants and animals. Mercury accumulations in the kidney, liver, gills, or gonadal tissues of sp
... Show MoreThe current study included the collection of 175 samples (blood-urea) of patients suffering from rheumatism, collected from Baghdad Teaching Hospital (Educational Laboratory), Al-Kindy Teaching Hospital, Al-Imamian Al-Kadhimya in Medical City in Baghdad at different duration between 2016/10/1-2017/2/1. The bacterial growth results showed that 80% of urea samples positive for bacterial culture, while the rate of samples did not show any bacterial grow this 20%. The isolation subjugates to morphological, microscopically and biochemical tests, as also diagnosis by Api system. The most frequent bacterial pathogenic is E. coli which appeared highly rate (41.97)% followed by E. cloacae (21.25)%, P. aeruginosa (12.5)%, Salmonella (10)% and the pro
... Show MoreThis paper studies the demonstratives as deictic expressions in Standard Arabic and English by outlining their phonological, syntactic and semantic properties in the two languages. On the basis of the outcome of this outline, a contrastive study of the linguistic properties of this group of deictic expressions in the two languages is conducted next. The aim is to find out what generalizations could be made from the results of this contrastive study.
Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col
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