Introduction and Aim: Klebsiella pneumoniae is a Gram-negative bacterium responsible for a wide range of infections, including respiratory tract infections (RTIs). This research was aimed to study the antibacterial and antibiofilm effect of AgNPs produced by Gram positive and negative bacteria on RTIs associated with K. pneumoniae. Materials and Methods: The biofilm formation of K. pneumoniae was determined by tube method qualitatively from select bacterial species characterized by UV-Visible spectroscopy. The antibacterial susceptibility of the bacteria AgNPs was tested for their antibacterial and antibiofilm activity on a clinical isolate of K. pneumoniae. Results: K. pneumoniae isolated from RTIs were strong biofilm producers. The ant

Introduction and Aim: Klebsiella pneumoniae is a Gram-negative bacterium responsible for a wide range of infections, including respiratory tract infections (RTIs). This research was aimed to study the antibacterial and anti-biofilm effect of AgNPs produced by Gram positive and negative bacteria on RTIs associated with K. pneumoniae.   Materials and Methods: The biofilm formation of K.  pneumoniae was determined by tube method qualitatively from select bacterial species characterized by UV-Visible spectroscopy. The antibacterial susceptibility of the bacteria AgNPs was tested for their antibacterial and antibiofilm activity on a clinical isolate of K. pneumoniae.   Results: K. pneumoniae isolated from RTIs were strong biofilm prod

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

DNA, as the basis of every living cell, is one of the most important and influential scientific discoveries. This research aims to identify and compare the organizational DNA to the leadership practices of school principals in the Sultanate of Oman and to reveal the similarity between principals’ leadership practices and the structure of DNA. In addition, it intends to identify any statistically significant differences between the responses of the participants due to the study variables: gender, job title and experience. A questionnaire was designed and data were collected from a randomly selected sample composed of (100) teachers in the Sultanate of Oman. The study found limitless diversity in the characteristics of DNA of leadership

Klebsiella pneumoniae is a severe opportunistic strain of enteric bacteria that is a major cause of urinary tract infection and pneumonia. This study was conducted in Baghdad City during September 2020-November 2020 on 50 clinical samples of urine, vaginal, sputum, wound swabs, ear swabs, and burn swabs. strains were identified using the VITEK-2 compact system and tested in K. pneumoniae terms of susceptibility to various antimicrobial drugs by Kirby-Bauer test. The isolates were more predominant in the females (56%) compared to males (44%). The antibiotic resistance rate of varied among different isolated clinical sample sources. K. pneumoniae K. pneumoniae isolated from different clinical specimens differed with respect

The study the problem emerged in the inability of local companies to enter the field of active competition with other companies operating in the same economic sector due to the high cost of their products, hence, the companies that want to apply this technique can effectively compete in order to achieve those objectives.

  So this study focused on the goal of reducing the cost of products by reducing the cost product to a minimum , as the study was based in its hypothesis on the ability of companies to application this technique which in turn leads to increased profits under conditions of normal working and the power available and their potential in improving the quality of its products, as well as the need for full coordina

This research aimed to develop a simulation traffic model for an urban street with heterogeneous traffic capable of analyzing different types of vehicles of static and dynamic characteristics based on trajectory analysis that demonstrated psychophysical driver behavior. The base developed model for urban traffic was performed based on the collected field data for the major urban street in Baghdad city. The parameter; CC1 minimum headway (represented the speed-dependent of the safety distance from stop line that the driver desired) justified in the range from (2.86sec) to (2.17 sec) indicated a good match to reflect the actual traffic behavior for urban traffic streets. A good indication of the convergence between simulat

The adult worms of the Microphallidae family are mainly found as intestinal parasites of birds and mammals, while metacercariae is most commonly found in decapodal crustaceans. The Microphallidaeare family is spread throughout the world. It includes approximately 47 genera. Mature worms usually enter the digestive system of vertebrates, especially birds and mammals. Microphallidae contain eight subfamilies: Androcotylinae - Basantisiinae - Endocotylinae - Gynaecotylinae - Levinseniellinae - MaritrematinaeMicrophallinae - Sphairiotrematinae. Therefore, due to the lack of studies on the Microphallidae family in Iraq, we began to develop a database on this important family.

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.