This paper presents a comprehensive numerical analysis of the improvement in bearing capacity and settlement performance of hexagonal shallow footings with inclined skirts. Various numerical analyses were conducted using PLAXIS 3D to investigate the influence of skirt length-to-footing width (L/B) ratios and skirt inclination angles (θ) on hexagonal footings in loose sand. The models showed very good agreement with experimental data reported in previous studies, with an R² value of 0.996 and a maximum error of less than 4.31%. It was concluded that the inclusion of inclined skirts has a positive effect on bearing capacity, increasing it by up to approximately 2.97 times compared to non-inclined configurations, while significantly

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Background: Asymptomatic bacteriuria (ASB) is
defined as isolation of a specified quantitative count
of bacteria in an appropriately collected urine
specimen from an individual without symptoms or
signs of urinary tract infection.
Aim of study: To evaluate the frequency of
bacteriuria according to age, pregnancy, and type II
diabetes mellitus in a sample of Iraqi women.
Patients and Methods: A total of 125 female
individuals were involved. The study participants
were classified into the following groups: nonpregnant
women with type II diabetes mellitus,
pregnant women with type II diabetes mellitus,
pregnant women without type II diabetes mellitus, and
apparently healthy non-pregnant women. Urine

BackgroundThe diagnosis and important aspects in treating acute abdomen during pregnancy tend to be delayed due to the peculiar physiological features of pregnancy and the restrictions imposed on imaging diagnostic techniques such as x-ray and CT.Aim of the studyTo identify the most common causes of acute abdomen during pregnancy and identifying the approaches for early diagnosis and to take a correct decision for surgery and assigning the complications that may occur during and/or after surgery for the mother and the fetus.Patients and Methods This is a prospective study that involves data obtained from 91 pregnant patients admitted in the surgical wards in Baghdad teaching hospital during the period from January 2008 to December 2009 .

The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

In folk medicine there are various medicinal amalgamation possessing hepatoprotective activity. This activity is of significance because several toxins cause liver injury. Hence, many pharmaceutical companies are targeting herbal medicines for the treatment of liver abnormalities and towards evolving a safe and effective formulation with desired route of administration. In current review we have focused on the studies showing hepatoprotective effect using marine compounds and plant derived compounds. Liver disorder, a global health problem, usually include acute or chronic hepatitis, heptoses, and cirrhosis. It may be due to toxic chemicals and certain antibiotics. Uncontrolled consumption of alcohol also affects liver in an unhealthy wa

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

Background The escalating global concern over increased body weight in adolescents, coupled with the rising rates of adolescent pregnancy worldwide, presents a significant challenge to healthcare systems. We plan to identify the maternal and neonatal consequences associated with pre-pregnancy overweight in adolescent women. Methods Throughout five years, all singleton adolescent pregnant women with pre-pregnancy self-reported body mass index (BMI) of 18.5– ≤ 29.9 were involved during the first-trimester visit. Two groups were generated: overweight and appropriate-weight (BMI 25–29.9 and 18.5–24.9, respectively). Obstetric and neonatal outcomes were observed prospectively and statistically adjusted for the confounding factors.

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa