'IMPLANT SURFACE COATINGS': PAST, PRESENT, ADVANCED, AND FUTURE TRENDS- A REVIEW.

ABSTRACT Digital Elevation Models (DEMs) form the foundation for hydrological modelling, yet their accuracy is often constrained by terrain complexity and spatially varying hydrological processes. In regions such as Anambra State, Nigeria, where diverse topographic forms and dynamic hydrological conditions prevail, fusing multiple DEM sources can enhance elevation accuracy. However, the influence of key hydrological variables on DEM fusion performance remains insufficiently understood. This study evaluates how surface roughness, topographic wetness, drainage density, and flow accumulation affect the accuracy of fused DEMs compared to original datasets. Shuttle Radar Topography Mission (SRTM) and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) DEMs were fused using weighted averaging, simple averaging, and regression-based techniques, with a high-resolution reference DEM used for validation. The results show that regression-based fusion produced the most hydrologically consistent elevation model. It preserved microtopographic variability while avoiding the excessive flattening observed in weighted and simple averages. The regression-based DEM closely matched reference terrain for surface roughness, maintained balanced wetness gradients, and represented drainage density and flow accumulation more accurately than both single-source DEMs and other fusion methods. In contrast, ALOS PALSAR tended to exaggerate ruggedness, wetness extremes, and drainage complexity, while SRTM moderately overestimated flow accumulation and stream segmentation. Weighted and simple averages reduced noise but oversmoothed hydrological features. These findings demonstrate that regression-based fusion outperforms conventional methods by integrating spatial error modelling and retaining hydrological integrity. Improved DEM fusion has direct implications for flood risk mapping, watershed management, erosion modelling, and infrastructure planning in hydrologically dynamic regions of southeastern Nigeria. The study emphasizes the need for hydrology-aware fusion strategies to enhance DEM reliability for terrain-driven environmental applications. KEY WORDS: Dental implants; Surface coatings; Sandblasted- Large-grit- Acid-etched (SLA); Hydroxyapatite; Nanostructures; Calcium-incorporated implants; Antimicrobial coatings; Smart coatings; Osseointegration.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-02
DOI
https://doi.org/10.5281/zenodo.17253130
Primary Topic
Advanced Battery Materials and Technologies
Type
article
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article

'IMPLANT SURFACE COATINGS': PAST, PRESENT, ADVANCED, AND FUTURE TRENDS- A REVIEW.

Zenodo (CERN European Organization for Nuclear Research)
Advanced Battery Materials and Technologies
article

'IMPLANT SURFACE COATINGS': PAST, PRESENT, ADVANCED, AND FUTURE TRENDS- A REVIEW.

article en

Abstract

ABSTRACT Digital Elevation Models (DEMs) form the foundation for hydrological modelling, yet their accuracy is often constrained by terrain complexity and spatially varying hydrological processes. In regions such as Anambra State, Nigeria, where diverse topographic forms and dynamic hydrological conditions prevail, fusing multiple DEM sources can enhance elevation accuracy. However, the influence of key hydrological variables on DEM fusion performance remains insufficiently understood. This study evaluates how surface roughness, topographic wetness, drainage density, and flow accumulation affect the accuracy of fused DEMs compared to original datasets. Shuttle Radar Topography Mission (SRTM) and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) DEMs were fused using weighted averaging, simple averaging, and regression-based techniques, with a high-resolution reference DEM used for validation. The results show that regression-based fusion produced the most hydrologically consistent elevation model. It preserved microtopographic variability while avoiding the excessive flattening observed in weighted and simple averages. The regression-based DEM closely matched reference terrain for surface roughness, maintained balanced wetness gradients, and represented drainage density and flow accumulation more accurately than both single-source DEMs and other fusion methods. In contrast, ALOS PALSAR tended to exaggerate ruggedness, wetness extremes, and drainage complexity, while SRTM moderately overestimated flow accumulation and stream segmentation. Weighted and simple averages reduced noise but oversmoothed hydrological features. These findings demonstrate that regression-based fusion outperforms conventional methods by integrating spatial error modelling and retaining hydrological integrity. Improved DEM fusion has direct implications for flood risk mapping, watershed management, erosion modelling, and infrastructure planning in hydrologically dynamic regions of southeastern Nigeria. The study emphasizes the need for hydrology-aware fusion strategies to enhance DEM reliability for terrain-driven environmental applications. KEY WORDS: Dental implants; Surface coatings; Sandblasted- Large-grit- Acid-etched (SLA); Hydroxyapatite; Nanostructures; Calcium-incorporated implants; Antimicrobial coatings; Smart coatings; Osseointegration.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 49%
Advanced Battery Materials and Technologies
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'IMPLANT SURFACE COATINGS': PAST, PRESENT, ADVANCED, AND FUTURE TRENDS- A REVIEW. · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS