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The Role of Virtual Education Networks on Students’ Mental Health
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Background: The Covid-19 pandemic changed the world; its most important achievement for education was changing the approach from traditional to virtual education. The present study aimed to investigate the role of virtual education networks on mental health of students including personality, beliefs, scientific, and cultural dimensions, in selected countries.Methods: This was an exploratory and applied study. According to the phenomenology strategy, theoretical saturation occurred after 24 semi-structured and targeted qualitative interviews with teachers from Iran, Iraq, Syria and Lebanon, in 2023. Quantitative data was collected through a researcher-made online questionnaire with 423 participants. Teachers with at least a Bachelor’s degree and five years of teaching experience were selected as the study participants. PLS software version 3 was used to analyze the quantitative data.Results: After analyzing the qualitative interviews, 131 open codes were extracted, and grouped into 22 components and 4 concepts. The results of the quantitative data analysis (factor load) showed the effect of virtual education networks on personality (0.590), beliefs (0.819), scientific (0.564), and cultural (0.815) dimensions which indicate a statistically significant effect. Accordingly, students’ belief is mostly affected by virtual education networks. The subcomponents of duality and moral-social confusion in the belief dimension, changing life and nutrition patterns in the cultural dimension, increasing communication and interpersonal problems in the personality dimension, and boredom and frustration in the scientific dimension were highly effective.Conclusions: The study results showed that virtual education acts like a double-edged sword, with both negative and positive effects on the body and mind of students, which necessitates more careful monitoring.

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Dentistry
In-vitro adhesive and interfacial analysis of a phosphorylated resin polyalkenoate cement bonded to dental hard tissues.
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Objectives: To assess the performance of a novel resin-modified glass-ionomer cement (pRMGIC) bonded to various tooth tissues after two-time intervals. Methods: 192 sound human molars were randomly assigned to 3 groups (n = 64): sound enamel, demineralised enamel, sound dentine. Sixty-four teeth with natural carious lesions including caries-affected dentine (CAD) were selected. All substrates were prepared, conditioned and restored with pRMGIC (30% ethylene glycol methacrylate phosphate (EGMP, experimental), Fuji II LC (control), Fuji IX, and Filtek™ Supreme with Scotchbond ™ Universal Adhesive. Shear bond strength (SBS) was determined after 24 h and three months storage in SBF at 37C. The debonded surfaces were examined using stereomi

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Publication Date
Tue May 01 2018
Journal Name
Applied Surface Science
Structural, morphological, and optical characterizations of Mo, CrN and Mo:CrN sputtered coatings for potential solar selective applications
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Publication Date
Tue Oct 24 2023
Journal Name
Environmental Engineering Research
Exploring electromembrane extraction and liquid membrane for efficient removal of heavy metals from aqueous solutions: An overview
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Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant

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Publication Date
Fri Jan 24 2025
Journal Name
International Journal Of Sustainable Development And Planning
Simulating Natural Systems for Urban Intelligence: A Case Study of Dora Municipality, Baghdad, for Sustainable Urban Development
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The rapid sprawl in urban areas caused by excessive production and consumption of goods (as driven by local poor social choices) has inevitably resulted in a major burden due to environmental degradation worldwide. Unfortunately, these traditional models of urban planning fail to properly account for the intricacies that permeate a modern city and are deficient in terms of their approach as they shape themselves within an environment largely divorced from natural systems, resulting in vast mismanagement of resources, guiding cities down trajectories where growth destroys both physical and cultural landscapes. As cities suffer from increasing scarcity, we advocate for regeneration and resilience to be embedded in advanced urban design approa

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Publication Date
Wed Jan 01 2025
Journal Name
مجلة العراقية للبحوث الانسانية والاجتماعية والعلمية
Detection of fimH, mrkD and mrkC genes in biofilm-forming Klebsiella pneumoniae isolated from different clinical cases"
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Publication Date
Mon May 25 2026
Journal Name
Journal Of Composites Science
Sectional and Stress Analysis of Hybrid Reinforced Concrete Beams with Embedded GFRP Profiles Under Monotonic Static Loading
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Glass fiber–reinforced polymer (GFRP) reinforcement provides an effective alternative to conventional steel in concrete structures due to its corrosion resistance. Nevertheless, the lower elastic modulus of GFRP necessitates careful consideration of serviceability behavior in GFRP-reinforced concrete members. This study presents a numerical sectional analysis model for predicting the flexural response and ultimate capacity of hybrid reinforced concrete beams incorporating embedded GFRP profiles in combination with either mild steel or GFRP reinforcement bars under monotonic static loading. The proposed model employs realistic nonlinear stress–strain relationships for concrete and steel, together with secant moduli of elasticity

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Publication Date
Sat May 30 2026
Journal Name
Microbes And Infectious Diseases
Reveal by genotyping and phenotyping methods of some Metallo- Beta Lactamases genes among environmental Klebsiella pneumoniae isolates
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Background: Since carbapenems are currently the preferred treatment for severe infections brought on by multidrug-resistant bacteria which can create Extended-Spectrum β-Lactamases (ESBLs), it is extremely concerning that Gram-negative bacteria are becoming resistant to carbapenem. It has been demonstrated that Klebsiella pneumoniae produces a beta-lactamase that hydrolyses the β-lactam ring in antibiotics, making it one of the few bacteria which are currently exhibiting a high value of resistance because of changing in the organism's core genome. Methods: For the current study, 50 samples were gathered from different water sources, and based on morphological and biochemical testing, 10 isolates were determined to be K. pneumoniae. Accord

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Publication Date
Sun Mar 15 2026
Journal Name
Journal Of Research In Pharmacy
In-vivo examination of nasal-to-brain administration for delivering rhodamine B nanospanlastic for fluorescent vesicle imaging
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This study investigated the efficacy of nasal injection of rhodamine B nanospanlastic (RBN) for magnetic vesicle imaging of specific brain locations. Effective delivery of RBN, which functions as fluorescence agents, to specific brain regions is necessary to achieve fluorescence particle imaging (FPI). There has been interest in nasal administration as a means of administering drugs directly to the brain, thereby circumventing the blood-brain barrier. We offered experimental nasal fluorescence agent administration by in vivo research. Fluorescent tests confirmed that, upon nasal delivery, the intended nanospanlastic migrated into the brain. Furthermore, using fluorescent microscopy, we demonstrated how these nanospanla

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Publication Date
Thu May 01 2025
Journal Name
2025 3rd International Conference On Business Analytics For Technology And Security (icbats)
Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction
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This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

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Publication Date
Wed Jan 01 2020
Journal Name
Research Journal Of Pharmacy And Technology
<i>Insilico</i> and <i>in vitro</i> Approach for Design, Synthesis, and Anti-proliferative Activity of Novel Derivatives of 5-(4-Aminophenyl)-4-Substituted Phenyl-2, 4-Dihydro-3<i>H</i>-1, 2, 4-Triazole-3-Thione
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