Investing in renewable energies, including biomass, is an important topic in Iraq. Research indicates that there is great potential for renewable energy in Iraq, including biomass, but achieving this great potential requires clear strategies and significant investments. This research sought to determine the amount of biomass energy that can be produced by the residues of eight Iraqi crops: wheat, barley, oats, corn, rice (straw), rice (husk), cotton, and sugar beets. could produce. Calorific value and accessible residue amount were considered to determine the residue's potential for energy. Estimates for 2021 showed that 1,308,516 tons of agricultural residue would be available overall for the eight crops. The two crops with the highest residue percentages were wheat at 52.31% and rice (straw), at 19.98%. The total calorific value of the residue was also obtained at 20,744,442 GJ. Wheat and rice (straw) also gave the highest calorific value at 52.79% and 18.81%, respectively. Therefore, according to the results obtained in this study, a portion of the country's energy consumption can be saved in this way given the abundance of agricultural resources in Iraq and the appropriate climate. Implementing residue-to-energy projects will help Iraq harness these resources and contribute to sustainable energy development.
It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i
... Show MoreSeven species of semi venomous Opisthoglypha snakes (Reptilia, Ophidia) of Iraq are listed with important characteristics in morphology due to geographical and individual variation of species, as well, the confusion in the scales count of Telescopus tessellatus martini (Schmidt, 1939) of Iraq are discussed.
Seven species of semi venomous Opisthoglypha snakes (Reptilia, Ophidia) of Iraq are listed with important characteristics in morphology due to geographical and individual variation of species, as well, the confusion in the scales count of Telescopus tessellatus martini (Schmidt, 1939) of Iraq are discussed.
Artichoke (Cynara scolymus L.) is a nutritious vegetable that grown all over the world. It is a promising herbal plant, rich in bioactive components. It is considered as medicinal plant due to its nutritional and phytochemical composition, especially high proportion of phenolic compounds. The primary aim of this study was to achieve chemical profile analyses of artichoke for different phytochemcials, especially Scolymoside and Cynaroside. Methanolic crude was extracted from Artichoke leaves by rotary evaporator and separated by column chromatography. The fractions monitored by Thin Layer Chromatography (TLC), and identified in High-Pressure Liquid Chroma
... Show MoreBackground: 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
... Show MoreThe 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
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