Background: The surface properties of the titanium alloy plays a significant role in the bond of the dental implant with living bone and modification of the implant surface could enhance osseointegration. This study was aimed to investigate the effect of different durations of heat treatment on the surface properties of titanium alloy for dental implants. Materials and methods: Twenty disks of (Ti-6Al-4V) alloy were prepared. The sample was divided into four test groups to study the effect of different duration of heat treatment to the surface topography; surface chemistry, titanium oxide layer thickness, blood contact angle, & blood drop diameter of titanium alloy samples were investigated to evaluate the effect of different durations of

The assessment of data quality from different sources can be considered as a key challenge in supporting effective geospatial data integration and promoting collaboration in mapping projects. This paper presents a methodology for assessing positional and shape quality for authoritative large-scale data, such as Ordnance Survey (OS) UK data and General Directorate for Survey (GDS) Iraq data, and Volunteered Geographic Information (VGI), such as OpenStreetMap (OSM) data, with the intention of assessing possible integration. It is based on the measurement of discrepancies among the datasets, addressing positional accuracy and shape fidelity, using standard procedures and also directional statistics. Line feature comparison has been und

Objective:Fluorid-containing dental alginate impression materials can exert a considerable reduction in
enamel solubility. The objective was to evaluate the effect of fluoride addition on the setting time and
compressive strength of alginate impression materials.
Methodology: 60 samples were constructed from alginate impression material (30 samples for setting
time test and 30 samples for compressive strength test).Specimens of each test divided into three
subgroup. Group A: 10 specimens of alginate were mixed with distilled water [control], Group B: 10
specimens of alginate were mixed with100-ppm fluoride and Group C:10 specimens of alginate were
mixed with 2%Naf.
Results: the result of setting time test showed t

   This study aimed to evaluate the reservoir petrophysical properties (porosity, water saturation, and permeability) for optimal flow unit assessment within the Sadi Formation. Utilizing open hole logging data from five wells, the Sadi formation was divided into two rock units. The upper unit (A) is 45-50 meters thick, mainly consisting of limestone, mainly consisting of shaly limestone at the lower part. The lower unit (B) has a thickness of approximately 75-80 meters and is primarily composed of limestone, further subdivided into three subunits (B1, B2, B3). The average water resistivity is 0.04 ohm-m, and the average mud filtrate resistivity is 0.06 ohm-m. The Pickett plot was utilized to determine Archie parameters (tortuosit

Unsaturated soil can raise many geotechnical problems upon wetting and drying resulting in swelling upon wetting and collapsing (shrinkage) in drying and changing in the soil shear strength. The classical principles of saturated soil are often not suitable in explaining these phenomena. In this study, expansive  soil (bentonite and sand) were tested in different water contents and dry unit weight chosen from the compaction curve to examine the effect of water content change on soil properties (swelling pressure, expansion index, shear strength (soil cohesion) and soil suction by the filter paper method). The physical properties of these soils were studied by conducting series of tests in laboratory. Fitting methods

The main purpose of this paper, is to characterize new admissible classes of linear operator in terms of seven-parameter Mittag-Leffler function, and discuss sufficient conditions in order to achieve certain third-order differential subordination and superordination results. In addition, some linked sandwich theorems involving these classes had been obtained.  

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati