Specialized Escherichia coli (E. coli) isolates, called uropathogenic E. coli (UPEC), cause most of urinary tract infections (UITs). Once bacteria reached the urinary tract of the host, they have to adhere to the host cell for the colonization. For this purpose, bacteria have different structures including fimbrial adhesins. Most of the UPECs contain type 1 fimbriae encoded by fim operon (fimB, E, A, I, C, D, F, G, H) which is responsible for the adhesive ability in these isolates. Ninety-four isolates of UPEC were obtained from UTI patients in Baghdad hospitals and their diagnosis were confirmed by the PCR method using 16srDNA as a housekeeping gene. The UPEC isolates were tested for their ability of adherence to the urothelial cells obtai

A nano manganese dioxide (MnO₂) was electrodeposited galvanostatically onto a carbon fiber (CF) surface using the simple method of anodic electrodeposition. The composite electrode was characterized by field emission scanning electron microscopy (FESEM), and X-ray diffraction (XRD). Very few studies investigated the efficiency of this electrode for heavy metals removal, especially chromium. The electrosorption properties of the nano MnO₂/CF electrode were examined by removing Cr(VI) ions from aqueous solutions. NaCl concentration, pH, and cell voltage were studied and optimized using the Box-Behnken design (BDD) to investigate their effects and interactions on the electrosorption process. The results showed that the

  The general trend in Iraqi banks is focused towards the application of international financial reporting standards, especially the international financial reporting standard IFRS 9 “Financial Instruments”, in addition to the directives issued on the Central Bank of Iraq’s instructions for the year 2018 regarding the development of expected credit losses models, and not to adhere to a specific method for calculating these losses and authorizing the banks’ departments to adopt the method of calculating losses that suits the nature of the bank’s activity and to be consistent in its use from time to time. The research problem revolves around the different methodologies for calculatin

Silver selenide telluride Semiconducting (Ag2Se0.8Te0.2) thin films were by thermal evaporation at RT with thickness350 nm at annealing temperatures (300, 348, 398, and 448) °K for 1 hour on glass substrates .using X-ray diffraction, the structural characteristics were calculated as a function of annealing temperatures with no preferential orientation along any plane. Atomic force microscopy (AFM) and X-ray techniques are used to analyze the Ag2SeTe thin films' physical makeup and properties. AFM techniques were used to analyze the surface morphology of the Ag2SeTe films, and the results showed that the values for average diameter, surface roughness, and grain size mutation increased with annealing temperature (116.36-171.02) nm The transm

Silver selenide telluride Semiconducting (Ag2Se0.8Te0.2) thin films were by thermal evaporation at RT with thickness350 nm at annealing temperatures (300, 348, 398, and 448) °K for 1 hour on glass substrates .using X-ray diffraction, the structural characteristics were calculated as a function of annealing temperatures with no preferential orientation along any plane. Atomic force microscopy (AFM) and X-ray techniques are used to analyze the Ag2SeTe thin films' physical makeup and properties. AFM techniques were used to analyze the surface morphology of the Ag2SeTe films, and the results showed that the values for average diameter, surface roughness, and grain size mutation increased with annealing temperature (116.36-171.02) nm The transm

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr