In this work, varying compositions of SiO₂ micro filler were added
with the Polyvinyl Chloride (PVC) and samples have been prepared
using film casting technique. The results have been analyzed and
compared for PVC samples with (1 wt%, 3 wt%, 5 wt% and 10 wt%)
SiO2 micro filler. Mechanical characteristics such as tensile strength,
elongation at break and Young`s modulus were measured for all the
samples, where the tensile strength was increased from 8.39 Mpa for
purified PVC to 16 Mpa for 3% SiO₂/PVC composite. Also, thermal
conductivity measurement values illustrated that composite materials
have a good thermal insulation at 10 wt. %, thermal conductivity was
decreased from 0.1684 W/m.

The one-dimensional, spherical coordinate, non-linear partial differential equation of transient heat conduction through a hollow spherical thermal insulation material of a thermal conductivity temperature dependent property proposed by an available empirical function is solved analytically using Kirchhoff’s transformation. It is assumed that this insulating material is initially at a uniform temperature. Then, it is suddenly subjected at its inner radius with a step change in temperature. Four thermal insulation materials were selected. An identical analytical solution was achieved when comparing the results of temperature distribution with available analytical solution for the same four case studies that assume a constant thermal con

Incremental sheet forming (ISF) process offers a high degree of flexibility in the manufacturing of different sheet parts, which makes it an ideal candidate for prototype parts as well as efficient at fabricating various customized products at low production costs compared to traditionally used processes. However, parts produced in this process exhibit notable geometrical inaccuracy and considerable thickness reduction. In this paper, the single point incremental sheet forming variant of the process has been implemented to manufacture a highly customized cranial implant starting from the computed tomography (CT) scan data of the patient's anatomy. A methodology, from the modeling to the realization of the implant, is presented and discus

The one-dimensional, cylindrical coordinate, non-linear partial differential equation of transient heat conduction through a hollow cylindrical thermal insulation material of a thermal conductivity temperature dependent property proposed by an available empirical
function is solved analytically using Kirchhoff’s transformation. It is assumed that this insulating material is initially at a uniform temperature. Then, it is suddenly subjected at its inner radius with a step change in temperature. Four thermal insulation materials were selected. An identical analytical solution was achieved when comparing the results of temperature distribution with available analytical solution for the same four case studies that assume a constant the

Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy

This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin