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Go to Editorial ManagerSoil’s characteristics are essential for the successful design of projects such as airports runway and flexible pavement. CBR (California Bering Ratio) is one of the significant soil characteristics for highways and airports projects. Thus, the CBR property can be used to determine the subgrade reaction of soil through correlations. Many of the soil geotechnical parameters such as compaction characteristics (Maximum Dry Density, MDD; Optimum Moisture Content, OMC), and consistency parameters (Liquid Limit, LL; Plastic Limit, PL; Plasticity Index, PI) can be in charge of changes that happen in soil CBR value. Soaked and/or non-soaked conditions of soils also affect CBR value. Hence, testing soils in a laboratory for CBR calculation is time-consuming that needs notable effort. Therefore, this study aims to generate some useful correlations for soil’s CBR with compaction and consistency parameters for 85 samples of fine-grained soils. The study trials were applied on natural soil samples of various places in Sulaimani Governorate, Northern Iraq. Statistical analysis has been carried out by using SPSS software (Version 28). Soaked CBR is counted, which is important for conditions such as rural roads that remain prone to water for few days. Based on the statistical analysis, there is a significant correlation between LL, PL, PI, MDD, and OMC with CBR as the dependent variable as a single variable equation with R2 of 0.7673, 0.5423, 0.5192, 0.6489, and 0.51, respectively. In addition, the highest value of R2 correlation was obtained between CBR value with consistency and compaction properties as a multiple regression equation with R2 of 0.82. The obtained equations for correlation purposes are successfully achieved and can be used, notably, to estimate CBR value.
This study has been performed to compare the compartmental modeling of two types of extravascular routes, sustained-release (SR) oral dosage forms and intramuscular (IM) injection. Twenty healthy volunteers received a single dose of 100 mg Diclofenac Sodium (DS) sustained-release tablet, then 75 mg DS Intramuscular injection after two weeks washout period. The concentrations of DS in plasma were measured using reverse-phase high-performance liquid chromatography (HPLC). The data analyzed using compartmental modeling, with single time-variant input and output. Primary kinetic parameters for both formulations, ( , , ) and other kinetic parameters were evaluated. The result shows that the IM injection needs a shorter time to reach the maximum concentration with convergent bioavailability to SR oral dosage forms, in another hand the data of IM injection fitted to single-compartment model with a correlation coefficient of 0.93 and the data of SR tablet fitted to two-compartment models with a correlation coefficient of 0.97.
The non-woven materials industry is one of the fastest-growing industries in the world with the ability to produce materials in less time, specifications, and better prices. nonwoven materials are defined as a web of guided or random fibers that are bonded by friction, interlacement or adhesion. In this research, the rotary electrospinning system was used and a prototype was made to study the process and the complete visualization in terms of the correlation of the electrostatic forces to the formation of nanofibers by preparing polymeric solutions and exposing them to the electric field between the positive electrode (the serrated cylinder) and the Grounded electrode (plate) and produced high-precision fibers with a diameter (185nm) at 25 kV, whereas the installation of polyvinyl alcohol (PVA) was with different concentrations and the formed fibers possessed an effective surface and deposited on a collector electrode forming nonwoven webs and high productivity is the most important feature of this system compared with the traditional electrospinning system.
The research aims to improve the quality of the product through improving the quality of production processes by relying on the principle of quality control, the aim of this research is to identify the reality of quality control in the industrial public sector companies in Syria, and explaining the advantages of using the principle of quality control producing information and data that contribute to improve the quality of production, where the research was based on theoretical side to provide an explanation on the quality and its objectives and the principle of quality control and production processes, but on the practical side, the workers were surveyed at the General Company for Wool and Carpets in Hama._x000D_ To achieve the objective of the research and to prove or deny the impact of quality control on the quality of production processes was based on the descriptive analytical method and using the appropriate statistical methods, where statistical analysis was carried out using SPSS 19 program._x000D_ The statistical results have shown that there is a strong correlation between the quality control and improving the quality of production processes._x000D_ The researcher recommended the need to form an administrative structure or forming a team work to improve the quality or using the consultants and researchers in order to supervise on the principle of quality control.
Power outages are a common and persistent problem in Iraq, significantly impacting various aspects of life and business. These interruptions disrupt routine household tasks and hinder more complex technical operations in industries and services. Emphasizing the need for careful management and proactive solutions. This paper introduces a real-world time series dataset for Baghdad city, including historical outages, weather conditions (such as temperature), and power overloads, and analyzes the correlation among these parameters in different seasons. The research uses this dataset to train one-dimensional Convolutional Neural Networks (1D CNN) to find patterns and relationships that can accurately predict when power outages can happen in the long term and short term to improve the management of the Baghdad electricity grid through data-driven networks. This model was evaluated using performance metrics, and the results show that CNN is accurate in predicting outages in the short term with a Mean Absolute Error (MAE) of (0.0077), whereas, in the long term, it has achieved an MAE of (0.0775). These predictive models have the potential to facilitate the development of proactive measures aimed at reducing the impact of power outages by anticipating potential outages in advance. This research focuses on enhancing the reliability and efficiency of Baghdad's electricity supply, ultimately contributing to economic growth and stability.