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OPTIMIZATION OF PLASMA-ASSISTED DESORPTION/IONIZATIONMASS SPECTROMETRY FOR ANALYSIS OF IBUPROFEN
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In medical practice, nonsteroidal anti-inflammatory drugs (NSAIDs) are often used to treat osteoarthritis and rheumatoid arthritis. Ibuprofen is a well-known NSAID, analgesic, and antipyretic medication. This chemical is an active ingredient of several oral medications that are offered in tablet, gel pellet, and syrup forms and has higher efficacy, tolerance, and side effect rates than other compounds, including pyrazolone derivatives. We present a unique plasma-assisted desorption/ionization mass spectrometry (PADI-MS) approach for improving pharmaceutically important solids using an ibuprofen tablet as a model solid sample. The goal of the study is to create an innovative mass spectrometric method that could be used for quick and accurate analysis in the development of pharmaceutically relevant compounds. Sniffer tubes were used to route sample ions into a single quadrupole MS, with each acquisition lasting for 1 minute. Without any prior preparation, samples of ibuprofen tablets were directly exposed to PADI plasma for one minute at an atmosphere pressure. The approach is rapid, easy to use, and needs little to no sample preparation. In this study, the settings were improved by optimization of several parameters, such as plasma power, plasma-to-sample distance, and inner/outer flows of helium carrier gas, which were found to be 8 W, 2 mm, and 284 mL/min, respectively. The PADI-MS method provides a real-time information about structural features on the compounds. Ibuprofen tablets were used as a paradigm for pharmaceutically significant materials and direct PADI-MS analysis without a preliminary sample -treatment appeared to be successful: according to PADI-MS data a medication can be examined after one minute of plasma exposure.

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Experimental Analysis for the Influence of Ignition Time on Combustion Characteristics of a Free Piston Engine Linear Generator
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Abstract<p>Free Piston Engine Linear Generator (FPELG) is a modern engine and promising power generation engine. It has many advantages compared to conventional engines such as less friction, few numbers of parts, and high thermal efficiency. The cycle-to-cycle variation one of the big challenges of the FPELG because it is influence on the stability and output power of the engine. Therefore, in this study, the effect of ignition time on combustion characteristics is investigated. The single-cylinder FPELG with spark ignition (SI) combustion type by using compressed natural gas (CNG) fuel type was set to run. LabVIEW is used to run the engine and control of input parameters. All experimental data</p> ... Show More
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Publication Date
Sat Oct 09 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education
An Analysis of the Mathematics Book for the First Intermediate Grade According to the Dimensions of Mathematical Power
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The current research aims to analyze the mathematics book for the first intermediate grade according to the dimensions of mathematical power by answering the following question: What is the percentage of the availability of the dimensions of mathematical power included in the content of the mathematics textbook for first-grade students, average, in its first, and second parts for the academic year 2020-2021, approved by the Iraqi Ministry of Education / General Directorate of Curricula? The research community was determined by middle school mathematics books, and middle school students for middle ,and high school day schools affiliated to the Directorate of Education in Dhi Qar, and by the intentional test, the research sample was s

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Use of Principal Components Analysis in the Formation of a Sustainable Human Development Index for Arab Countries
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This study aims to derive a sustainable human development index for the Arab countries by using the principal components analysis, which can help in reducing the number of data in the case of multiple variables.  This can be relied upon in the interpretation and tracking sustainable human development in the Arab countries in the view of the multiplicity of sustainable human development indicators and its huge data, beside the heterogeneity of countries in a range of characteristics associated with indicators of sustainable human development such as area, population, and economic activity. The study attempted to use the available data to the selected Arab countries for the recent years. This study concluded that a single inde

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Oxidative Coupling Reaction for Micro Trace Analysis of Mebendazol Residual with p-bromoaniline in Presence of n- bromosuccinimide
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Rapid, reproducible and accurate method has been developed for the assay for of mebendazol (MBZ) residual assay. The method is based on alkaline hydrolysis of MBZ with sodium hydroxide then oxidation with N-bromosuccinimide (NBS) followed by coupling with 4-Bromoaniline (4-BA) to yield a highly colored product absorbed at maximum 434 nm. Regression analysis of linearity range was found (0.6-2.8) µg.ml-1.  The optimum conditions that affect the oxidation were studied. The developed method was found to be precise with mean value of relative standard deviation (1.153- 1.303) and accurate with relative error (-0.5940-1.7821) .The calculated molar absorptivity and sandal sensitivity values of (29825 L.mol-1.cm-1), 0.0099 µg.cm-2 respe

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Oxidative Coupling Reaction for Micro Trace Analysis of Mebendazol Residual with p-bromoaniline in Presence of n- bromosuccinimide
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Rapid, reproducible and accurate method has been developed for the assay for of mebendazol (MBZ) residual assay. The method is based on alkaline hydrolysis of MBZ with sodium hydroxide then oxidation with N-bromosuccinimide (NBS) followed by coupling with 4-Bromoaniline (4-BA) to yield a highly colored product absorbed at maximum 434 nm. Regression analysis of linearity range was found (0.6-2.8) µg.ml-1.  The optimum conditions that affect the oxidation were studied. The developed method was found to be precise with mean value of relative standard deviation (1.153- 1.303) and accurate with relative error (-0.5940-1.7821) .The calculated molar absorptivity and sandal sensitivity values of (29825 L.mol-1.cm

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Publication Date
Sun Apr 22 2018
Journal Name
Al-nahrain Journal For Engineering Sciences
Numerical Analysis of the Effect of Scanning Speed on the Temperature Field Distribution for Laser Heat Treatment Applications
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One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Tue Sep 21 2021
Journal Name
Jmerd
stress and strain analysis for the prosthetic hand design actuated by links
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Prosthetic hands are compensatory devices for the hand amputees as a result of injury, various accidents or birth deformities, types of prosthetic hand vary depending on the mechanism they operate and how they perform. There are common types in use that are characterized by their complex mechanisms, which are difficult for the amputee to use or exclude use because of their high cost, therefore the aim of this research is to design an artificial hand that is suitable in terms of simplicity of use and low cost and similar to a natural hand with regard to dimensions and shape that operated in the mechanism of links. This research involves Stress and strain analysis of the prosthetic hand and its fingers that modelled from (Petg CR)

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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