Naturally available products have been used widely for centuries in handling human disease. The present study aimed to determine the effect of aluminum potassium sulfate addition into the soft liner on tensile strength and peel bond strength. The effect of aluminum potassium sulfate evaluated by two methods, first one include incorporation of KAL (SO4)2 into soft liner monomer in concentration (2%,3% by wt.) while the second method include immersion of soft liner specimens in solution of KAL(SO4)2 in concentration(5%,10% percent) during time periods (0,10 minutes). In conclusions, the results of current study encourage use KAL (SO4)2 within soft liner material

The work was carried out in two stages. The first stage concerned
with study of silicon carbide (SiC) ratio (1.5, 2.5, 3.5, and 4.5 wt%)
effect on the Thermal conductivity of polyvinyl chloride (PVC); and
the second stage concerned with the UV – weatherizing (25, 50, and
75 hr), thermal aging (40, 50, and 60 °C), and rain- weatherizing (1,
2.5, and 4 hr) effect on the samples involved. Thermal conductivity
results proved that there was slight increase in thermal conductivity
by (SiC) loading; it increased from 0.17 W/m.K for PVC to 0.19
W/m.K for 4.5% SiC/PVC; where as it was systematically decreased
by UV- weatherizing, thermal aging, and rain- weatherizing. This
property is in a good agreement with gene

Background: The purpose of this study was to evaluate the effect of addition of surface treated silicon dioxide Nano filler (SiO2) on some properties of heat cured acrylic resin denture base material (PMMA). The properties were impact strength, transvers strength, and surface hardness. Materials and methods: In addition to controlled group SiO2 powder was added to PMMA powder by weight in three different percentages 3%, 5% and 7%, mixed by probe ultra-sonication machine.120 specimens were constructed and divided into 3 groups according to the test (each group consist of 40 specimens) and each group was subdivided into 4 sub-groups according to the percentage of added SiO2 (finally each subgroup consist of 10 specimens). The tests conducte

ABSTRACT Background: Improving the properties of heat- cured and self-cured acrylic resin have been studied by many researchers. However, little studies concerned with visible light cured resin (VLCR) improved through addition of nanofiller are available. The purpose of this study was to evaluate some properties of (VLCR) after addition of SiO2 nanofiller. Materials and Methods: SiO2 nanofiller were added to (VLCR) tray material after being dissolved in tetrahydrofuran (THF) solvent. According to the pilot study 2% SiO2 nanofiller addition exhibited better properties than the other percentages (1%, 3%). The main study conducted involved (100) specimens divided into 5 groups according to the test included. (20) Specimens were selecte

This paper demonstrates an experimental and numerical study on the behavior of reinforced concrete (RC) columns with longitudinal steel embedded tubes positioned at the center of the column cross-section. A total of 12 pin-ended square sectional columns of 150 × 150 mm having a total height of 1400 mm were investigated. The considered variables were the steel tube diameters of 29, 58, and 76 mm and the load eccentricity (0, 50, and 150) mm. Accordingly, these columns were divided into three groups (four columns in each group) depending on the load eccentricity (e) to column depth (h) ratio (e/h = 0, 1/3, and 1). For each group, one column was solid (reference), and the other three columns contained steel tubes with hollow rat

Consider a simple graph   on vertices and edges together with a total  labeling . Then ρ is called total edge irregular labeling if there exists a one-to-one correspondence, say  defined by  for all  where  Also, the value  is said to be the edge weight of . The total edge irregularity strength of the graph G is indicated by  and is the least  for which G admits   edge irregular h-labeling.  In this article,   for some common graph families are examined. In addition, an open problem is solved affirmatively.

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur