This study aims to remove Cd(II) ions from simulated wastewater by using Chlorophyceae algae (CA). Different parameters were studied to show their effects on the biosorption efficiency of CA. These parameters are: the effect of pH 3-7, initial metal ion concentration 20-200 mg/L, sorbent dos-age 0.05-2 g/L, contact time 5-180 min, and agitation speed 100-300 rpm. We found that both the Langmuir and Freundlich models appropriate for characterizing the metal removal process. The biosorption data fit best with the results of the pseudo-second-order kinetic model, demonstrating that the chemisorption process is the dominant mechanism controlling the removal. CA was char-acterized using the scanning electron microscopy test, prior to and post bi

Off-nucleus isotropic magnetic shielding (σiso(r)) and multi-points nucleus independent chemical shift (NICS(0-2 Å)) index were utilized to find the impacts of the isomerization of gas-phase furfuraldehyde (FD) on bonding and aromaticity of FD. Multidimensional (1D to 3D) grids of ghost atoms (bqs) were used as local magnetic probes to evaluate σiso(r) through gauge-including atomic orbitals (GIAO) at density functional theory (DFT) and B3LYP functional/6-311+G(d,p) basis set level of theory. 1D σiso(r) responses along each bond of FD were examined. Also, a σiso(r) 2D-scan was performed to obtain σiso(r) behavior at vertical heights of 0–1 Å above the FD plane in its cis, transition state (TS) and trans forms. New techniques fo

The present work involved preparation of new substituted and unsubstituted and poly imides (1-17) using reaction of acryloyl chloride with different amides (aliphatic ,aromatic) in the presence of a suitable solvent and amount tri ethyl amine (Et3N) with heating – the structure confirmation of all polymers were proved using FT-IR,1H-NMR,C13NMR and UV spectroscopy ,thermal analysis (TG) for some polymers confirmed their thermal stabilities . Other physical properties including softening and melting points, PH and solubility of the polymers were also measured

Abstract

Objective(s): A descriptive study aimed to determine nurses' knowledge about chest physiotherapy techniques for patients with Corona virus disease and observe the relationship between nurses' knowledge and their socio-demographic characteristics.

Methodology: The study was directed in isolation units of Al- Hussein teaching hospitals in Thi-Qar, Iraq for the period from June 1st,  2022 to November 27th, 2022. Non- probability (purposively) sample comprised 41 nurses. A questionnaire was used for data collection and it consists of two parts: the first part comprises socio demographic features, the second part includes self- administered questionnaire sheet wa

Objective: To assess the clinical learning environment and clinical training for students' in maternal and child
health nursing.
Methodology: A descriptive study was conducted on non probability sample (purposive) of (175) students' in
Nursing College/ University of Baghdad for the period of June 19th to July 18th 2013. A questionnaire was used as a
tool of data collection to fulfill with objective of the study and consisted of three parts, including demographic,
clinical learning environment and clinical training for students' in maternal and child health nursing. Descriptive
statistical analyses were used to analyze the data.
Results: The results of the study revealed that the 65.1% of student at age which ranged b

Introduction: Melanin is a high-molecular weight pigment produced through the oxidative polymerization of phenolic or indolic compounds and plays a perfect role in UV-light shielding, as well as in photoprotection. Among biopolymers, melanin is unique in many aspects. This study is designed to screen Production, extraction and characterizes of an extracellular melanin pigment from clinically isolated P. aeruginosa. Objective: The aim of the current study is isolation and diagnosis of P.aeruginosa using vitek-2 compact system and screening the ability to produce melanin and characterization of extracted melanin by UV-vis, FTIR, XRD and SEM. Materials and methods: the samples swab inoculated on cetrimide agar as selective media and incubated

The provision of openings in serviceable reinforced concrete beams may result in a substantial decline in the beam's capacity and integrity, indicating the necessity of opening strengthening. The present study investigates the experimental response of reinforced concrete T-beams with multiple web-strengthened openings disposed in shear span to static and impact loads. Fourteen RC T-beams were tested in two groups, each of seven beams. The first group was tested under static loading up to failure, while the second group was tested under repeated impact loading until the width of shear cracks reached 0.3 mm. The residual static strengths of the beams subjected to impact loading were then determined. The test variables considered were

The provision of openings in serviceable reinforced concrete beams may result in a substantial decline in the beam's capacity and integrity, indicating the necessity of opening strengthening. The present study investigates the experimental response of reinforced concrete T-beams with multiple web-strengthened openings disposed in shear span to static and impact loads. Fourteen RC T-beams were tested in two groups, each of seven beams. The first group was tested under static loading up to failure, while the second group was tested under repeated impact loading until the width of shear cracks reached 0.3 mm. The residual static strengths of the beams subjected to impact loading were then determined. The test variables considered were

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p