The present work provides a list of all amphibians and reptiles recorded from Iraq up to 2014. It includes 115 species (105 species of reptiles and 10 species of amphibians) dating back to 25 families (20 families of reptiles and 5 families of amphibians). Conservation status of each species was mentioned.

The study aims to detail the chemistry of Sabkha located in Abu-Graib, western Baghdad to know the content of the rare elements distributed. Sabkhas are found in dry areas with significant evaporation rates. The quantity of dissolved salts rises as water evaporates from the shallow basins, eventually causing salt to crystallize. The creation of the distinctive salt pans and crusts on the top is greatly influenced by this process. The trace elements (Ti, V, Cr, Mn, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Y, Zr, Nb, Mo, Sn, Ba, Ta, Tl, Pb, Th, U, I, and Br) beside the major oxides were analyzed using XRF technique. There are no clear significant differences in the distribution of the elements between the two Sabkhas in the village of Kadim Al

A novel analytical method is developed for the determination of azithromycin. The method utilizes continuous flow injection analysis to enhance the chemiluminescence system of luminol, H2O2, and Cr(III). The method demonstrated a linear dynamic range of 0.001–100 mmol L-1 with a high correlation coefficient (r) of 0.9978, and 0.001–150 mmol L-1 with a correlation coefficient (r) of 0.9769 for the chemiluminescence emission versus azithromycin concentration. The limit of detection (L.O.D.) of the method was found to be 18.725 ng.50 µL−1 based on the stepwise dilution method for the lowest concentration within the linear dynamic range of the calibration graph. The relative standard deviation (R.S.D. %) for n = 6 was less than 1.2%

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl