The survival of dried spores of A.flavus, Penicillia Spp., and Cladosporia Spp.inoculated into multivitamins and folic acid tablets were examined at different compression pressures.Survival of fungal spores decreased with increasing compression pressure. The level of survival at particular pressures was shown to depend on the size of the contaminating fungal spores.The lethal effect of tabletting was attributed to shearing forces upon the contaminating spores generated by interparticulate movement. This hypothesis was supported by the dependence of survival upon spore size.

Key words: Fungal spores, microbial contamination.

The effect of considering the third dimension in mass concrete members on its cracking behavior is investigated in this study. The investigation includes thermal and structural analyses of mass concrete structures. From thermal analysis, the actual temperature distribution throughout the mass concrete body was obtained due to the generation of heat as a result of cement hydration in addition to the ambient circumstances. This was performed via solving the differential equations of heat conduction and convection using the finite element method. The finite element method was also implemented in the structural analysis adopting the concept of initial strain problem. Drying shrinkage volume changes were calculated using the procedure suggested

The purpose of this study is designate quenching and tempering heat treatment by using Taguchi technique to determine optimal factors of heat treatment (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time) for increasing hardness, wear rate and impact energy properties of 420 martensitic stainless steel. An (L₁₈) orthogonal array was chosen for the design of experiment. The optimum process parameters were determined by using signal-to-noise ratio (larger is better) criterion for hardness and impact energy while (Smaller is better) criterion was for the wear rate. The importance levels of process parameters that effect on hardness, wear rate and impact energy propertie

This study aims to suggest a technique for soil properties improvement of AL- Kadhimin shrine Minaret and to support the foundation, which has a tilt of roughly 80 cm from the vertical axis. The shrine of the AL- Kadhimin is made up of four minarets with two domes set in a large courtyard. The four minarets have skewed to varying degrees due to uncontrolled dewatering inside the shrine in recent years. However, the northeast minaret was the most inclined due to its proximity to the well placed inside shrine courtyard. When the well near the minaret is operated, the water level drops, increasing the effective stresses of the soil and causing differential settling of the minaret foundation. To maintain the minaret's foundation from potenti

The effect of considering the third dimension in mass concrete members on its cracking behavior is investigated in this study. The investigation includes thermal and structural analyses of mass concrete structures. From thermal analysis, the actual temperature distribution throughout the mass concrete body was obtained due to the generation of heat as a result of cement hydration in
addition to the ambient circumstances. This was performed via solving the differential equations of heat conduction and convection using the finite element method. The finite element method was also implemented in the structural analysis adopting the concept of initial strain problem. Drying shrinkage volume changes were calculated using the procedure sug

In this work, magnesium aluminate spinel (MA) (MgO 28 wt%, Al2O3 72 wt%) stoichiometric compound , were synthesized via solid state reaction (SSR) Single firing stage, and the impact of sintering on the physical properties and thermal properties as well as the fine structure and morphology of the ceramic product were examined. The Spinel samples were pressed at of (14 MPa) and sintering soaking time (2h). The effect of adding oxide titania (TiO2) was studied. The obtained powders were calcined at a temperature range of 1200 and 1400 °C. The calcined samples spinel were characterized by XRD, it showed the presence of developed spinel phase end also showed that the best catalyst is titania. The SEM image showed the high sintering temperat

Background: Complete removal of filling material from the root canal is an essential requirement for endodontic retreatment. The purpose of the present study is to evaluate and compare the dissolving capabilities of various solvents (Xylene, Eugenate Desobturator, Eucalyptol, EDTA and Distilled water (as a control)) on four different types of sealer (Endofill, Apexit Plus, AH Plus and EndoSequence bioceramic sealer). Materials and method: Eighty samples of each sealer were prepared according to the manufacturers' instructions and then divided into ten groups (of 8 samples) for immersion in the respective solvents for 2 and 5 min immersion periods. Each sealer specimen was weighed to obtain its initial mass. The specimens were immersed in

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de