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Effects of Artificial Aging on Some Properties of Room-Temperature-Vulcanized Maxillofacial Silicone Elastomer Modified by Yttrium Oxide Nanoparticles
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Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each parameter tested (i.e., tear strength, surface roughness, hardness, tensile strength and elongation percentage). Specimens were artificially aged in a weathering chamber for 150 h and then tested. Data were analyzed by ANOVA and Tukey’s honestly significant difference (HSD). Statistical significance was set to P ≤ 0.05. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were also conducted. Results and Discussion: SEM results showed that Y2O3 NPs were distributed well within the silicon matrix. FTIR results indicated that the NPs were physically dispersed within VST50F silicone without chemical interaction. After 150 h of accelerated artificial aging, adding Y2O3 NPs significantly increased the tear strength, hardness, surface roughness, and elongation percentage. Tensile strength increased non significantly. Conclusion: Adding Y2O3 NPs as fillers improved the mechanical properties of artificially aged maxillofacial silicone elastomer. Keywords: maxillofacial silicone, Y2O3, nanoparticles, fillers, artificial aging.

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Medicinal And Pharmaceutical Chemistry Research
The effect of selenium nanoparticles with fenugreek extract on oxidative stress related to polycystic ovary syndrome
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In recent years, there has been growing interest in using Nanosystems in different biomedical applications. Among all metal nanoparticles, selenium nanoparticles have attracted the attention of many researchers due to its low toxicity and nutritional supplementation value. The purpose of the current study was designed to examine the possible effect of selenium nanoparticles in combination with fenugreek leaves extract (an edible herb with good medicinal properties) in the treatment of oxidative stress status-related to polycystic ovary syndrome in letrozole-induced PCOS (an imbalance of reproductive hormones that causes infertility) in adult female rats. Cold plasma was used in the preparation of selenium nanoparticles subsequently the prod

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Publication Date
Wed Nov 05 2025
Journal Name
Journal Of Oral Biology And Craniofacial Research
The effect of thermocycling on fracture resistance of zirconia crowns cemented with polylysine modified resin cements (Comparative in vitro study)
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ABSTRACT Background: resin cement type and intraoral temperature fluctuations may affect the fracture performance of successful zirconia restorations. To fill this gap, the purpose of this study is to evaluate and compare the influence of thermocycling on fracture resistance and mode of failure of monolithic zirconia crowns luted with Rely X™ U200 and BreezeTMself-adhesive resin cements as well as imply the effect of adding 2 % of polylysine (PLS) to these cements. Materials: 64 maxillary premolars were milled out of zirconia blocks using CAD/CAM milling system. They were divided into four groups (n = 16) according to the cement type. Four different resin cements were used (RelyXTMU200, Breeze™, RelyX™ U200 with 2 % PLS

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
Environmental effects on intestinal parasitic disease transmission in Mosul governorate
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This study, which was conducted in the city of Mosul, through collected 1200 samples from the stool of patients with diarrhea attending hospitals and private clinics for the period from the beginning of January 2019 to the end of December 2019, those whose ages ranged from less than a year-60 year, and for both sexes and by reality 700 samples stool for males and 500 samples stool for females. Samples were collected in clean, sterile, and sealed 40ml plastic bottles. Patient information is noted, name of the parasite, history, sex, age, address. The result showed that climate and temperature have a significant effect on increase the incidence of intestinal parasites through the direct effect on the increase in infection rate. This effect wa

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Publication Date
Fri May 15 2026
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Generative AI Effects on Academic Achievement and Sustainable Professional Development
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This quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific efficacy, prov

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Publication Date
Fri May 15 2026
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Generative AI Effects on Academic Achievement and Sustainable Professional Development
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This quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific effica

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Experimental and Numerical Study on Cavitation Effects in Centrifugal Pumps
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Experimental and numerical investigations of the centrifugal pump performance at non-cavitating and cavitating flow conditions were carried out in the present study. Experiments were performed by applying a vacuum to a closed-loop system to investigate the effects of the net positive suction head available (NPSHa), flow rate, water temperature and pump speed on the centrifugal pump performance. Accordingly, many of the important parameters concerning cavitation phenomenon were calculated. Also, the noise which is accompanied by cavitation was measured. Numerical analysis was implemented for two phase flow (the water and its vapor) using a 2-D simulation by ANSYS FLUENT software to investigate the internal flow of centrifugal pump under c

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Publication Date
Mon Jun 16 2025
Journal Name
مجلة كلية التربية الاساسية
A MINI-REVIEW ON THE FABRICATION OF EXPANDED GRAPHITE AND ITS METAL OXIDE COMPOSITES FOR THE PHOTODEGRADATION OF DYES
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This mini review provides an overview of methods for manufacturing expanded graphite (EGT) and the use of its composites with metal oxides in the field of photodegradation of dyes. Dyes from textile manufacturing represent a significant environmental pollution problem in waterways worldwide, highlighting the need for environmentally friendly and efficient technologies to remove dyes from industrial and local wastewater. Photodegradation technologies offer a low-cost, sustainable solution with minimal secondary pollution. Carbon-based materials, such as expanded graphite, are advantageous in enhancing catalytic activity. Accordingly, this review will explore the different fabrication techniques of expanded graphite and summarize the recent d

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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