Keys for 22 species representing 10 genera of Thripidae were provided collection of
samples carried out during 1999-2001 in different localities in the middle of Iraq. Of them
four species are described as new to science, Frankliniella megacephala sp. nov; Retithrips
bagdadensis sp. nov; Chirothrips imperatus sp. nov; Taeniothrips tigridis sp. nov; Another
fourteen species are recorded for the first time in Iraq; Thrips meridionalis (Pri.);
Microcephalothrips abdominils (Crawford Scolothrips sexmaculatus (Pergande),);Scolothrips
pallidus (Beach); Scritothrips mangiferae Pri.; Frankliniella tritici Bagnall; Frankliniella
schultzie Trybom; Frankliniella unicolor Morgan; Retithrips aegypticus Marchal; Retithrips
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Let G be a graph with p vertices and q edges and  be an injective function, where k is a positive integer. If the induced edge labeling   defined by for each is a bijection, then the labeling f is called an odd Fibonacci edge irregular labeling of G. A graph which admits an odd Fibonacci edge irregular labeling is called an odd Fibonacci edge irregular graph. The odd Fibonacci edge irregularity strength ofes(G) is the minimum k for which G admits an odd Fibonacci edge irregular labeling. In this paper, the odd Fibonacci edge irregularity strength for some subdivision graphs and graphs obtained from vertex identification is determined.

Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Background: Obesity is a worldwide challenge and is closely
connected to many metabolic diseases. Two types of
adipose tissue, white adipose tissue (WAT) and brown
adipose tissue (BAT) have been identified. White fat cells
store chemical energy, brown adipocytes defend against
hypothermia, obesity and diabetes.
Objective: To localize and quantify brown adipocytes in
human subcutaneous (S) and visceral (V) adipose tissue by
histology and immunohistochemistry.
Type of the study: A cross –sectional study.
Methods: Adipose tissue was obtained from histopathology
specimens taken from ten patients, of different age, sex and
body mass index (BMI), undergoing surgery for different
pathologies

JM Karhoot, AA Noaimi, WF Ahmad, The Iraqi Postgraduate Medical Journal, 2012 - Cited by 7

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

   Neural stem cells (NSCs) are progenitor cells which have the ability to self‑renewal and potential for differentiating into neurons, oligodendrocytes, and astrocytes. The in vitro isolation, culturing, identification, cryopreservation were investigated to produce neural stem cells in culture as successful sources for further studies before using it for clinical trials. In this study, mouse bone marrow was the source of neural stem cells. The results of morphological study and immunocytochemistry of isolated cells showed that NSCs can be produced successfully and maintaining their self‑renewal and successfully forming neurosphere for multiple passages. The spheres preserved their morphology in culture and cryopreserved t

A simple, rapid and sensitive spectrophotometric method has been developed for the determination of captopril in aqueous solution. The method is based on reaction of captopril with 2,3-dichloro 1,4- naphthoquinon(Dichlone) in neutral medium to form a stable yellow colored product which shows maximum absorption at 347 nm with molar absorptivity of 5.6 ×103 L.mole-1. cm-1. The proposed method is applied successfully for determination of captopril in commercial pharmaceutical tablets.

A sensitive spectrofluorimetric method for the determination of glibenclamide in its tablet formulations has been proposed. The method is based on the dissolving of glibenclamide in absolute ethanol and measuring the native fluorescence at 354 nm after excitation at 302 nm. Beers law is obeyed in the concentration of 1.4 to 10 µg.ml-1 of glibenclamide with a limit of detection (LD) of 0.067 µg.ml-1 and a standard deviation of 0.614. The range percent recoveries (N=3) is 94 - 103.