A new Ni(II) nanostructured chelating system (DHN) was introduced for selective optical heavy-metal ion sensing in an aqueous medium. The cooperative chelating system comprising 8-hydroxyquinoline (8-HQ) and dimethylglyoxime (DMG) has been developed for the first time in association with fibre optic sensing for selective optical heavy-metal ion sensing in an aqueous medium. The Ni(II) nanocompound fluoresces upon 578 nm excitation, showing a highly sensitive optical response with a linear calibration curve in the range 0–100 ng/mL. The regression equation of the calibration curve is y = 0.0035x + 0.9990, which indicates very good linearity, implying R2 = 0.999 with high sensitivity (calibration slope of 0.0035) and low baseline noise (bla

The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated

A new azo (LH) ligand was prepared by coupling reaction between, diazonium salt of Sulfamethoxazole, and 8-hydroxyquinoline in a process called diazotization process resulting in azo-ligand [4-((8-hydroxyquinolin-7-yl)- N(4-methylisoxazol-3-yl) benzene sulfonamide]. The azo ligand was identified by using spectroscopic techniques to detect and characterize the formation of ligand and complexes of Ni2+, Pt4+, Pd2+, and Rh3+ metal ions, and to determine the chelating behavior of ligand and also its bind position. All complexes have a [1:1] [M-ligand] ratio and all complexes are nonelectrolytes and most of the complexes have octahedral geometry, while Pd2+complex gave square planer geometry and Ni2+ complex indicate tetrahedral geometry. Therma

Background: Depression is a common mental disorder that presents with depressed mood;it can become chronic or recurrent and affect dental health .Thus this research aimed to assess the prevalence and severity of dental caries among students with different grade of depression in relation to physicochemical characteristics of stimulated whole saliva. Materials and methods: The total sample involved for depression status assessment is composed of 800 students for both gender aged 15 years old that were selected randomly , This was performed using children depression inventory (CDI) index that divided the students into four groups of depression(low or average grade, high average grade, elevated grade and very elevated grade). The diagnosis and

The paper attempts to find out the elements of picaresque novel in selected English and Iraqi novels. It studies these elements in Henry Fielding’s Joseph Andrews and Adil Abduljabbar’s Arzal Hamad Al-Salim. The paper is divided into four sections. The first is an introduction to the picaresque novel. It gives a definition, a historical background, and the elements of the genre. The second section studies Fielding’s novel focusing on the elements of this type of novel and how it affects the story itself. The paper follows the novel from the beginning to the end showing these elements. The third is dedicated to Abduljabbar’s novel and how the elements of picaresque genre appear in the novel and play an important role in its developm

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti