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Interfacial Bond Strength and Morphology of Sound and Caries-affected Dentin Surfaces Bonded to Two Resin-modified Glass Ionomer Cements
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SUMMARY<sec> <title>Objective

To evaluate the shear bond strength and interfacial morphology of sound and caries-affected dentin (CAD) bonded to two resin-modified glass ionomer cements (RMGICs) after 24 hours and two months of storage in simulated body fluid at 37°C.

Methods and Materials

Sixty-four permanent human mandibular first molars (32 sound and 32 with occlusal caries, following the International Caries Detection and Assessment System) were selected. Each prepared substrate (sound and CAD) was conditioned (10% polyacrylic acid) and bonded to Activa BioACTIVE Restorative (Activa) and Fuji II LC (F2LC) as per the manufacturers’ instructions. Shear bond strength (SBS) was performed after 24 hours and two months of storage. The interfacial surfaces were examined using a digital microscope and scanning electron microscope (SEM). Three-way ANOVA, Bonferroni post-hoc tests (α=0.05), and independent T-tests were used for multifactorial analysis.

Results

Activa exhibited reduced bond strength values to sound and CAD in comparison to F2LC after two time periods (p=0.01). There is a pronounced enhancement in SBS of F2LC when bonded to CAD (p=0.01) after storage, with no statistically significant effect on sound dentin (p=0.309). Activa showed stable SBS to sound and CAD immediately and post-aging (p&gt;0.05). However, the evidence of mineral-like deposits under an SEM attached to the aged, debonded dentin surfaces, thereby obliterating the exposed dentinal tubules, might support the tissue repair potential of Activa.

Conclusions

The SBS of Activa was lower than F2LC when bonded to sound and CAD, but the bonding stability and sealing ability is advantageous in minimally invasive therapy, suggesting use with a resin composite coverage when used in stress-bearing areas.

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Wed Oct 01 2025
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A Modified Fama-MacBeth Model based on the Single-Index Model
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The aim of this essay is to use a single-index model in developing and adjusting Fama-MacBeth.  Penalized smoothing spline regression technique (SIMPLS) foresaw this adjustment.  Two generalized cross-validation techniques, Generalized Cross Validation Grid (GGCV) and Generalized Cross Validation Fast (FGCV), anticipated the regular value of smoothing covered under this technique. Due to the two-steps nature of the Fama-MacBeth model, this estimation generated four estimates: SIMPLS(FGCV) - SIMPLS(FGCV), SIMPLS(FGCV) - SIM PLS(GGCV), SIMPLS(GGCV) - SIMPLS(FGCV), SIM PLS(GGCV) - SIM PLS(GGCV). Three-factor Fama-French model—market risk premium, size factor, value factor, and their implication for excess stock returns and portfolio return

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Publication Date
Wed Jun 16 2021
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Modified Single Mode Optical Fiber Ammonia Sensors Deploying PANI Thin Films
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Thu Apr 01 2021
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Modified ZnO for efficient photo-catalysis by Silver/Graphite oxide nanoparticles
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Wed Jan 01 2014
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LTE Peak Data Rate Estimation Using Modified alpha-Shannon Capacity Formula
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Wed May 01 2024
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Journal Of Physics: Conference Series
A modified ARIMA model for forecasting chemical sales in the USA
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Sat Dec 01 2018
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Applying A* Path Planning Algorithm Based on Modified C-Space Analysis
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Sat Dec 01 2012
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The use of two indicators of market value-added and return on capital invested in measuring the performance of the Iraqi banking sector
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Wed Jan 01 2025
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The Effect of Two Training Approaches with (Hanging–Heavy) Ropes in Developing Some Physical Abilities and Accuracy of Shooting—In Front of Handball
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Sun May 02 2021
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Value at risk simulation in a fixed return stock portfolio using the Monte Carlo simulation model The concept of a bond portfolio
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This research aims to predict the value of the maximum daily loss that the fixed-return securities portfolio may suffer in Qatar National Bank - Syria, and for this purpose data were collected for risk factors that affect the value of the portfolio represented by the time structure of interest rates in the United States of America over the extended period Between 2017 and 2018, in addition to data related to the composition of the bonds portfolio of Qatar National Bank of Syria in 2017, And then employing Monte Carlo simulation models to predict the maximum loss that may be exposed to this portfolio in the future. The results of the Monte Carlo simulation showed the possibility of decreasing the value at risk in the future due to the dec

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