Salmonellosis in poultry is one of the most significant bacterial infections causing mortality, reduced production, and serious economic losses. This study aimed to study the molecular diversity among Salmonella isolates and investigate the epidemiological spread of these bacteria in broiler and layer chicken flocks in five different farms in Karbala, Iraq, using random amplified polymorphic DNA (RAPD) polymerase chain reaction (PCR). In total, 217 cloac a swabs were collected from the farms, out of which 129 and 88 swabs were taken from broiler and layer chickens. The samples were screened by PCR for S. enterica subsp. enterica using primers specific for the invA gene. Afterward, RAPD-PCR with uniplex or multiplex octamer primers was appli

The fingerprinting DNA method which depends on the unique pattern in this study was employed to detect the hydatid cyst of Echinococcus granulosus and to determine the genetic variation among their strains in different intermediate hosts (cows and sheep).  The unique pattern represents the number of amplified bands and their molecular weights with specialized sequences to one sample which different from the other samples.   Five hydatitd cysts samples  from cows and sheep were  collected, genetic analysis for  isolated DNA was done using PCR technique and  Random Amplified Polymorphic DNA reaction(RAPD) depending on (4) random primers, and the results showed:      

   Stick- slip is the continuous stopping& release of the Bit/BHA due to the irregular down-hole rotation prompted by the existing relationship between the friction torque and the torque applied from the surface to free the bit.

   Friction coefficient between BHA and wellbore is the main player of stick slip amount, which can be mitigated by support a good lubricators as additives in drilling mud.

   Mathematical (or empirical) solves should be done through adjusting all parameters which supposed to reduce stick- slip as low as possible using different models, one of the main parameters is drilling mud. As per Nanoparticles drilling fluid is a new technology that offers high performance

The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t