This study is included the preparation of two tetradentate amide-thiol proligands of the general structure [H2Ln], [where; (n = (1–2)]. The ligands [H2L1] and [H2L2] have been prepared from the reaction of the cyclic thioester 2-oxo-1, 4-dithiacyclohexane (compound 1) and 3-chloro-2-oxo-1, 4 dithiacyclohexane (compound 2) with 2-aminomethanepyridine in (1:1) ratio respetively. The reaction was carried out in chloroform at room temperature and under N2 atmosphere. Structural formula of these two ligands have been reported.

Objectives: to assess chronic diseases patients’ knowledge toward stroke risk factors and warning signs, besides
determining the relationship between chronic diseases patients’ knowledge and their sociodemographical
characteristics.
Methodology: A descriptive study was carried out at public medical clinics which has started from December
2
nd, 2008 to August 8th, 2009. A purposive "non-probability" sample of (300) chronic diseases individuals who
were clients of Public Medical Clinics who have one or more of the following chronic diseases (hypertension,
diabetes mellitus, heart diseases, and previous stroke), in Baghdad city. The data were collected through the use
of a constructed questionnaire which consists

New compounds of amids [IV]a-e and Schiff bases [V]f-h derived from 2-amino-1,3,4-oxadiazoles [III] were synthesized and characterized by physical and spectraldata.2-Aamino-1,3,4-oxadiazoles was prepared by the action of bromine on acorresponding semicarbazide [II]( which was prepared by reaction of dialdehyde [I]with semicarbazide hydrochloride ) in the presence of sodium acetate , followed byan intramolecular cyclization . (PDF) Synthesis of New Amides and Schiff Bases derived From 2-Amino -1,3,4- Oxadiazole. Available from: https://www.researchgate.net/publication/326679206_Synthesis_of_New_Amides_and_Schiff_Bases_derived_From_2-Amino_-134-_Oxadiazole [accessed Nov 15 2023].

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone

Nowadays, the robotic arm is fast becoming the most popular robotic form used in the industry among others. Therefore, the issues regarding remote monitoring and controlling system are very important, which measures different environmental parameters at a distance away from the room and sets various condition for a desired environment through a wireless communication system operated from a central room. Thus, it is crucial to create a programming system which can control the movement of each part of the industrial robot in order to ensure it functions properly. EDARM ED-7100 is one of the simplest models of the robotic arm, which has a manual controller to control the movement of the robotic arm. In order to improve this control s

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

This paper presents L₁-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L₁-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L₁-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L₁-adaptive controller ensured uniformly bounded