Human urinary Adenosine-3',5'-cyclic monophosphate (cAMP) was studied in 90 normal healthy volunteers (49 males and 41 females) aged between (11 months -55 years), and 86 leukemia patients (48 males and 38 females) of four types (25 ALL, 28 AML, 14 CLL, 19 CML) aged between (11 months - 65 years). The study includes the following:- Extraction and purification of urinary cAMP from the interfering nucleotides, proteins, phosphates and pyrophosphates, by using Zinc sulphate –Barium hydroxide precipitation. The extracted cAMP was purified by using Dowax 50W-H+ hydrogen form column chromatography (1x5 cm). Identification of the purified cAMP, this was achieved by applying the following techniques: a- U.V analysis: -

In this research two series of the new derivatives of Trimethoprim and paracetamol drugs have been prepared which known as a high medicinal effectiveness. Series (A) is including the interaction of diazonium salt of trimethoprim and coupling with some substituted phenol compounds (2-amino phenol, 3-ethyl phenol, 1-naphthol, 2-nitro phenol, Salbutamol). Series (B) is including the interaction coupling alkali solution of paracetamol with diazonium salt of some substituted aniline compounds (Benzedine, 2, 3-di chloro aniline, Trimethoprim, Anilinium chloride, 2-nitro- 4-chloro aniline).Chemical structures of all synthesized compounds were confirmed by UV-visible and FTIR spectroscopy.

     The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca

Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent $\left({}\right)$

This paper presents a numerical solution to the inverse problem consisting of recovering time-dependent thermal conductivity and  heat source coefficients  in the one-dimensional  parabolic heat equation.   This  mathematical  formulation  ensures that the inverse problem  has a unique  solution.   However, the problem  is still  ill-posed since small errors  in the input data lead to a drastic  amount  of errors in the output coefficients.  The  finite  difference method  with  the Crank-Nicolson  scheme is adopted  as a direct  solver of the problem in a fixed domain.   The inverse problem is solved sub

Enterococci are usually encountered and predominate in oral infections, especially those associated with dental root canal infections of necrotic pulp and periodontitis. This study aimed to detect and identify Enterococcus faecium isolated from infected root canals, using polymerase chain reaction ( PCR). Thirty samples were collected from patients with  necrotic pulp, infected root canals, and endodontic treatment failure, attending the Conservative Treatment Department, College of Dentistry, Mosul University, Dental Teaching Hospital. The samples were obtained by inserting sterile paper points into the root canals and transferred in brain heart infusion broth vials to be  inoculated in a selective M-Enterococcus Agar Base . T

Construction is a hazardous industry with a high number of injuries. Prior research found that many industry injuries can be prevented by implementing an effective safety plan if prepared and maintained by qualified safety personnel. However, there are no specific guidelines on how to select qualified construction safety personnel and what criteria should be used to select an individual for a safety position in the United States (US) construction industry. To fill this gap in knowledge, the study goal was to identify the desired qualifications of safety personnel in the US construction industry. To achieve the study goal, the Delphi technique was used as the main methodology for determining the desired qualifications for constructio

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha