Under-reamed piles defined by having one or more bulbs have the potential for sizeable major sides over conventional straight-sided piles, most of the studies on under-reamed piles have been conducted on the experimental side, while theoretical studies, such as the finite element method, have been mainly confined to conventional straight-sided piles. On the other hand, although several laboratory and experimental studies have been conducted to study the behavior of under-reamed piles, few numerical studies have been carried out to simulate the piles' performance. In addition, there is no research to compare and evaluate the behavior of these piles under dynamic loading. Therefore, this study aimed to numerically investigate bearing capacity and settlement of under-reamed piles compared with uniform pile sections by sinusoidal excitation machines foundation. Different geometrical under-reamed piles single and double bulbs compared with uniform pile using finite element method, PLAXIS 3D software. The result showed that uniform pile fizzles out to support the total load and the final settlement was 4.97 cm. Single under-reamed pile S.U.P and double under-reamed pile D.U.P can be reduced final settlement 76% and 81 % respectively.
Pathogenic microorganisms from hospitals, communities, and the environment remain great threats to human health. The increasing concern about antibiotic resistance has also necessitated the search for robust alternatives. Therefore, this study aims to isolate, screen and evaluate the antibiotic susceptibility of Pseudomonas aeruginosa isolated from a soil sample taken from northern, western and eastern parts of Kelana Jaya Lake against four antibiotics (gentamycin, tetracycline, ampicillin, and penicillin) on a Mueller-Hinton Agar media plate. Pseudomonas identification was done by using API 20 kit. Disc diffusion was employed as well as the oxidase test. From the positive oxidase result, the isolated bacteria were identified as Burkhold
... Show MoreThe raw material soil of Al-Sowera factory quarry (quarry soil and mixture) used for building brick industry was tested mineralogically, geochemically and geotechnically. Mineral components of soil are characterized by Clay minerals (Palygoriskite and chlorite) and nonclay minerals like calcite, quratz, feldspar, gypsum and halite. The raw material is deficient in SiO2, Al2O3, K2O, Fe2O3 and MgO, while enriched in CaO. Loss on ignition and Na2O are in suitable level and appear to be concordant with the standard. Grain size analyses show that the decreasing sand and clay, and increasing silt ratio in both quarry soil and mixture caused decreasing in strength of brick during molding and after firing. The quarry soil is characterized by high p
... Show MoreThe Umm Al-Naaj Marsh was chosen in Maysan province, and it is one of the sections of Mar Al-Hawza, which is one of the most prominent Iraqi marshes in the south. The marshes are located between latitudes 30 35 and 32 45 latitudes and longitudes 13 46 and 48 00. The area of the study area is 76479.432142 hectares to evaluate soil quality and health index and their spatial distribution based on measuring physical, chemical, biological and fertility traits and calculating the total quality index for those characteristics. Using an auger drilling machine, we collected 50 randomly selected surface samples, evenly distributed across the study region, from Al-Aq 0.0–0.30 m, noting their precise locations along the way. Soil health and quality w
... Show MoreThere are many animal models for polycystic ovary (PCO); using exogenous testosterone enanthate is one of the methods of induction of these models. However, induction of insulin resistance should also be studied in the modeling technics. Therefore, the present study aims to investigate the expression of insulin receptor substrate (Irs)-2 mRNA in the liver tissue of rat PCO model. Nineteen Wistar rats were divided into three groups; (1) PCO modeling group (N =7) received daily 1.0 mg/100g testosterone enanthate solved in olive oil along with free access dextrose water 5%, (2) vehicle group (N =6), which handled like the PCO group, but did not receive testosterone enanthate, (3) control group (N =6) with standard care. Al
... Show MoreIn this work, corrosion parameters were evaluated using potentiodynamic polarization curves. In order to determine corrosion parameters of potential and current density of the interesting metal, carbon steel, environmental conditions of external corrosion of buried carbon steel pipeline in Iraqi soil were prepared in the laboratory using simulated prepared conditions. Solutions of sodium chloride at different concentrations (300, 1100, 1900, 2700, and 3500 ppm) were used. pH of solution were acidic at pH =5, and alkaline at pH = 9. Laboratory conditions were similar to those of Iraqi soil where the pipelines were buried. Temperature was constant at 20 °C. Potentiodynamic polarization curves, of potential vs. log current density, were ob
... Show MoreAbstract: The world witnessed the speed of a dangereuse virus now as Corona or Covid 19, which left many deaths in light of the inability of local and international Heath agencies to find a suitable vaccine to eliminate it and limit its spread, which negatively affected humain life in its various fields, and remains adopting healthy behaviors and habits A healthy Heath is the best solution to face the spread of the epidemic until realistic solutions that eliminate the virus are found.
Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec
... Show More