The rheological behavior among factors that are present in Stokes law can be used to control the stability of the colloidal dispersion system. The felodipine lipid polymer hybrid nanocarriers  (LPHNs) is an interesting colloidal dispersion system that is used for rheological characteristic analysis. The LPHNs compose of polymeric components and lipids. This research aims to prepare oral felodipine LPHNs to investigate the effect of independent variables on the rheological behavior of the nanosystem. The microwave-based technique was used to prepare felodipine LPHNs (H1-H9) successfully. All the formulations enter the characterization process for particle size and PDI to ascertain the colloidal properties of the prepared nanosystem t

Poly vinyl alcohol has been studied for its ability to form crystallites by using annealing method. Semicrystalline films of poly vinyl alcohol (PVA) were prepared by casting 11.5 wt. % and 13 wt. % PVA aqueous solution onto glass slides at annealing temperature range 90 -120°C and duration time 15- 60 minute. This allowed the macromolecules to form crystallites, small regions of folded and compacted chains separated by amorphous regions where single PVA chain may pass through several of these crystallites. Degree of crystallinity of PVA films (hydrogels) was determined by method of density; on the other hand the swelling behavior was conducted by the determination of water uptake, wet degree of crystallinity, gel fraction and solubilit

The buildup factor was measured after irradiating Iraq carbon black powder using each of and sources respectively, using mixing ratios 40% & 50% for thickness range . The results showed that the buildup factor depends on energy and has limited dependence on the mixing ratio. The QIFT program succeeded accenting for the experimental results even for expected values more than 4 m.f.p outside the thickness range.

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

Background: Metabolic syndrome (MetS) is a collection of connected cardiovascular risk factors that characterizes the complicated illness. The waist circumference cutoff point fluctuation has so far defined Mets. Objective: This study aimed to determine the cutoff point for WC in healthy Iraqi adults. Methods: This cross-sectional survey establishes the standard value for WC among 300 healthy university students in Wasit city, Iraq. They are aged between 18-25 years. The receiver operator characteristic (ROC) curve was used WC to predict the presence of two or more risk factors for MetS, as defined by IDF. Results: The cutoff level yielding maximum sensitivity and specificity for predicting the presence of multiple risk factors was

Background: This study evaluated the influence of different fiber formulations incorporation in resin composite on cuspal deflection (CD) of endodontically-treated teeth with mesio-occluso-distal (MOD) cavities. Materials and Methods: Thirty-two freshly extracted maxillary premolar teeth received MOD cavity preparation followed by endodontic treatment using single cone obturation technique, and divided into: Group I: direct composite resin only using a centripetal technique, Group II: direct composite resin with short fiber-reinforced composite (everX Flow), Group III: direct composite resin with leno wave ultra-high molecular weight polyethylene (LWUHMWPE) fibers placed on the cavity floor, and Group IV: direct composite resin with LWUHMWP

In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H