Nanoparticles (NPs) have unique capabilities that make them an eye-opener opportunity for the upstream oil industry. Their nano-size allows them to flow within reservoir rocks without the fear of retention between micro-sized pores. Incorporating NPs with drilling and completion fluids has proved to be an effective additive that improves various properties such as mud rheology, filtration, thermal conductivity, and wellbore stability. However, the biodegradability of drilling fluid chemicals is becoming a global issue as the discharged wetted cuttings raise toxicity concerns and environmental hazards. Therefore, it is urged to utilize chemicals that tend to break down and susceptible to biodegradation. This research presents the pra

Background: The accuracy of fitness of any dental casting is imperative for the success of any prosthodontic treatment. From the time that dental casting was first introduced, efforts have been made to produce more accurate and better fitted castings with minimal marginal discrepancy. The aim of this in vitro study was to evaluate the effects of three different investing and burnout techniques on the vertical marginal discrepancies ofceramometalcopings invested with two types of phosphate- bonded investments. Materials and methods: Sixty wax patterns were fabricated on a standardized prepared brass die representing an upper central incisor by the aid of a custom-made split mold. Three different investing and burnout techniques were applied

Background: Ideal root canal obturation depends on many factors; one of them is good sealing of root canal without pores. The aim of this study was to determine the radiographic density of GuttaFlow® 2 with different obturation techniques using spiral computed tomography. Materials and Methods: Forty palatal roots of permanent maxillary first molar were used in this study. Following working length determination, root canal was prepared using rotary PROTAPER universal system. They were randomly divided into four groups of 10 roots each, the groups are Conventional lateral condensation with Apexit Plus sealer, Conventional lateral condensation with GuttaFlow® 2 as a sealer, Soft Core Regular with GuttaFlow® 2 as a sealer and singl

        Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.

The method is utilized to predict