A method is developed for the determination of iron (III) in pharmaceutical preparations by coupling cloud point extraction (CPE) and UV-Vis spectrophotometry. The method is based on the reaction of Fe(III) with excess drug ciprofloxacin (CIPRO) in dilute H2SO4, forming a hydrophobic Fe(III)- CIPRO complex which can be extracted into a non-ionic surfactant Triton X-114, and iron ions are determined spectrophotometrically at absorption maximum of 437 nm. Several variables which impact on the extraction and determination of Fe (III) are optimized in order to maximize the extraction efficiency and improve the sensitivity of the method. The interferences study is also considered to check the accuracy of the procedure. The results have shown that the preconcentration factor of 71 fold leading to obtain a limit of detection of 2.67 ng mL-1 with linear calibration range of 5-150 ng mL-1 (r=0.9998) and a superb sensitivity in terms of molar absorptivity of 1.13x106 L.mol-1.cm-1 . The mean percent recovery of 99.78±0.53% and the precision (RSD %) ranged from 1.96 to 0.76 are achieved. The developed method is applied to the determination of iron in four selected pharmaceutical drugs. The experimental values agree statistically with the quoted values stated by the manufacturer’ companies.
Metallic nanoparticles are increasingly studied for their biomedical applications due to their unique physicochemical and catalytic properties. Here, a broccoli-mediated gold/platinum nanohybrid (Au@Pt NH) was synthesized using an ultrasound-assisted green method with an aqueous extract of Brassica oleracea var. italica for multifunctional biomedical evaluation. XRD and TEM confirmed a crystalline nanohybrid with an average crystallite size of 7.56 nm and a mean particle diameter of 13.08 ± 7.58 nm. The broccoli extract produced no inhibition zones, whereas Au@Pt NH inhibited Staphylococcus aureus (18 mm), Staphylococcus epidermidis (21 mm), Escherichia coli (18 mm), Klebsiella pneumoniae (20 mm), and Candida albicans (21 mm). In vivo,
... Show MoreAmong the undesirable effects of soil compaction is a measurable reduction in plant growth and crop yield. The prevailing belief is that compacted tillage pans are caused by repetitive farming practices, heavy tractors, tillage tools, and field traffic. This experiment was conducted to determine and map the hardpan layers across an agricultural field through advanced technologies of precision agriculture. These valuable techniques such as data logger, yield map, and data analysis of performance indicators were linked with accurate global positioning systems (GPS) datasets. These important technologies provided the farmers and helped them to identify and manage areas of the fields with higher compacted layers. Three ground speeds 4.3
... Show MoreThe smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreBackground: Knowing the indications for a cesarean section will help to have a better understanding of this common obstetrical procedure and prepare for the high level of care management that it entails. Aims of the study: The goal of this study was to determine the factors that influence caesarean section indications among women who visited AL-Dewaniya Maternity and Pediatric Hospital, as well as the relationship between caesarean section women's indications and socio-demographic data. Methodology: A descriptive cross-sectional study design is conducted for the period of December 26th 2020 to June 1st 2021 at Al Dewaniya Maternity and Pediatric Hospital. The validity of the questionnaire is determined through a panel of experts and reliabi
... Show MoreIn this study, a mathematical model is presented to study the chemisorption of two interacting atoms on solid surface in the presence of laser field. Our mathematical model is based on the occupation numbers formula that depends on the laser field which we derived according to Anderson model for single atom adsorbed on solid surface. Occupation numbers formula and chemisorption energy formula are derived for two interacting atoms (as a diatomic molecule) as they approach to the surface taking into account the correlation effects on each atom and between atoms. This model is characterized by obvious dependence of all relations on the system variables and the laser field characteristics which gives precise description for the molecule –
... Show MoreMixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab
... Show MoreParticulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in
A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.