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Evaluation of Youth's Health Risk Behaviors in Baghdad City
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Objective(s): To evaluate youth's health risk behaviors in Baghdad City and to determine the relationship between such behaviors and the youth's demographic characteristics of age, gender and grade. Methodology: A descriptive study, using the evaluation approach, is carried out to evaluate youth's health risk behaviors in Baghdad City for the period of January 26th 2016 to May 20th 2016. A non-probability "purposive" sample of (160) University students is selected for the purpose of the study from four groups of colleges (medical, engineering, sciences, and education) and it is equally distributed of (40) student from group of colleges. The sample is consisted of (50%) males and (50%) females. A questionnaire is constructed for the purpose of the study. It is comprised of eight parts which deal with youth's health risk behaviors of unintentional injuries, tobacco use, drinking alcohol, drug use, sexual behavior, unhealthy dietary behavior, inadequate physical activity, and health related behavior. Internal consistency reliability and content validity are determined for the study instrument through pilot study. Data are collected through the utilization of the questionnaire and the application of the structured interview technique as means of data collection. Data are analyzed through the application of the descriptive statistical data analysis approach which includes frequency, percent, total score and Cronbach alpha correlation coefficient. Results: The study depicts that most of the students have experienced health risk behaviors of unhealthy dietary behavior, inadequate physical activity and health related behavior regardless of their colleges' classification. Male students have been exposed to health risk behaviors of unintentional injuries, tobacco use, drinking alcohol, drug use and sexual behavior more than female students. Recommendations: The study recommends that Youth Health Risk Behaviors Program should be designed and implemented to present these students with all the information for the prevention and control of such behaviors. Further research is needed to determine whether low grades lead to health risk behaviors or health risk behaviors lead to low grades, or some other factors lead to both of these problems.

 
 

 

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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
Removal of Malachite Green from Aqueous Solution using Ficus Benjamina Activated Carbon-Nonmetal Oxide synthesized by pyro Carbonic Acid Microwave
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Activated carbon derived from Ficus Binjamina agro-waste synthesized by pyro carbonic acid microwave method and treated with silicon oxide (SiO2) was used to enhance the adsorption capability of the malachite green (MG) dye. Three factors of concentration of dye, time of mixing, and the amount of activated carbon with four levels were used to investigate their effect on the MG removal efficiency. The results show that 0.4 g/L dosage, 80 mg/L dye concentration, and 40 min adsorption duration were found as an optimum conditions for 99.13% removal efficiency. The results also reveal that Freundlich isotherm and the pseudo-second-order kinetic models were the best models to describe the equilibrium adsorption data.

 

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Publication Date
Fri Jul 14 2023
Journal Name
International Journal Of Information Technology & Decision Making
A Decision Modeling Approach for Data Acquisition Systems of the Vehicle Industry Based on Interval-Valued Linear Diophantine Fuzzy Set
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Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

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Thu Nov 07 2024
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Journal Of Thermal Analysis And Calorimetry
Performance improvement of phase change material (PCM)-based shell-and-tube-type latent heat energy storage system utilizing curved fins
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Sun Jan 01 2023
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Optimization of chemical oxygen demand removal from petroleum refinery wastewater by electrocoagulation using tubular electrochemical reactor with a novel design
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Fri Feb 28 2025
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Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Thu Dec 01 2011
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Engineering Analysis With Boundary Elements
Numerical solution of two-dimensional mixed problems with variable coefficients by the boundary-domain integral and integro-differential equation methods
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Publication Date
Tue May 12 2026
Journal Name
Canadian Metallurgical Quarterly
Investigation of Te <sub>50</sub> Se <sub>50-x</sub> Sn <sub>x</sub> alloys’ structural and electrical characteristics
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Publication Date
Tue Jun 24 2025
Journal Name
Food And Bioprocess Technology
Classification of Apple Slices Treated by Atmospheric Plasma Jet for Post-harvest Processes Using Image Processing and Convolutional Neural Networks
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Abstract<p>Apple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices usin</p> ... Show More
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Theoretical Investigation of Innovative Charge-transfer Complexes Derived from the N-phenyl 3, 4-selenadiazo Benzophenone Imine
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In the current study, a direct method was used to create a new series of charge-transfer complexes of chemicals. In a good yield, new charge-transfer complexes were produced when different quinones reacted with acetonitrile as solvent in a 1:1 mole ratio with N-phenyl-3,4-selenadiazo benzophenone imine. By using analysis techniques like UV, IR, and 1H, 13C-NMR, every substance was recognized. The analysis's results matched the chemical structures proposed for the synthesized substances. Functional theory of density (DFT)
has been used to analyze the molecular structure of the produced Charge-Transfer Complexes, and the energy gap, HOMO surfaces, and LUMO surfaces have all been created throughout the geometry optimization process ut

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Publication Date
Sun Jan 01 2023
Journal Name
Phyton
Toxic and Antifeedant Effects of Different Pesticidal Plant Extracts against Beet Armyworm (&lt;i&gt;Spodoptera exigua&lt;/i&gt;)
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The beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum ,

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