Contracaecum rudolphii Hartwich, 1964 is a nematode which causes major concerns to human and wildlife animal’s health. However, the population genetics of C. rudolphii has been poorly studied in Iraq. In order to gain a deeper understanding in the outline of the genetic diversity of the nematode C. rudolphii that were isolated from its host cormorant Phalacrocorax carbo (Linnaeus, 1758), in the middle areas of Iraq, twenty specimens of C. rudolphii adults were isolated from nine individuals of P. carbo. The first (ITS-1) internal transcribed spacers (ITS) of ribosomal DNA (rDNA) of C. rudolphii were amplified using conventional polymerase chain reaction (PCR); then, the amplicons were subjected to sequencing. Concatenation of ITS

Asphalt Hot Mix (HMA) is mainly applied in highway construction in Iraq because of its economic advantage and easy maintenance. Various factors impact the performance of HMA in the field. It is one of the significant impacts on aggregate gradation. The Universal Specification for Roads and Bridges in Iraq (SCRB) limits the different types of asphalt layers and allows for designed tolerance aggregate gradation. It is quite hard for contractors in the present asphalt industries to achieve the required job mix because of sieves' control problems. This study focuses on the effects on the required specification performance of aggregate deviations by using original and modified asphalt binder with AC(40-50) and

Pseudomonas aerogenosa lipopolysaccharidewas extracted by hot phenol method and purified by gel filtration method using the Sephadex G-200 gel and detected by the limulus amebocyt lysate (EU/ml 0.03)(Wako Chemicals USA, Inc.). The inhibitory effect of partially purified LPS on Candida glabrata yeast was studied in a microdilution method. This study found that LPS has an inhibitory effect on Candida glabrata with the lower concentrations. The inhibitory effect of LPS which treated with heating was studied under boiling and wet heat effect. The toxicity of LPS on Candida glabrata was not affected when treated with heating LPS and the results were similar to those found in untreated LPS

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

The aim of this research is to develop qualitative workouts based on certain sensory perceptions for the development of offensive basketball abilities and to determine their impact on female pupils. Several findings, based on the au-thor's extensive expertise instructing basketball materials and our closeness to the sample, revealed deficits in some sensory perceptions “in the game of basketball”, which impair the accuracy of passing the ball to the best team-mate. It also affects the pace of dribbling and the difficulty of selecting the op-timal moment and distance to fire. Therefore, the researcher designs qualita-tive activities based on many sensory experiences, including distance, speed, force, and direction shift. In addition, the

     This article aims to determine the time-dependent heat coefficient together with the temperature solution for a type of semi-linear time-fractional inverse source problem by applying a method based on the finite difference scheme and Tikhonov regularization. An unconditionally stable implicit finite difference scheme is used as a direct (forward) solver. While by the MATLAB routine lsqnonlin from the optimization toolbox, the inverse problem is reformulated as nonlinear least square minimization and solved efficiently. Since the problem is generally incorrect or ill-posed that means any error inclusion in the input data will produce a large error in the output data. Therefore, the Tikhonov regularization technique is applie