Objectives: The research aims to demonstrate the integration between Quantum Computing (QC) and Predictive Analysis (PA) and their role in reducing costs while achieving Sustainable Development Goals (SDGs). The study addresses the inefficiencies in calculating and measuring product costs under traditional systems and examines how QC and PA can enhance cost reduction and product quality to better meet customer needs. Additionally, the research seeks to strengthen the theoretical framework with practical applications, illustrating how this integration improves a company’s competitive position while promoting social, environmental, and economic sustainability.   Methods: The study employs a descriptive analytical approach, focusi

The increase the rates of natural growth, urbanization and continuous migration, this has generated constant pressure and, as a result, the capital city of Baghdad faces a number of challenges related to its urban environment, including the challenge of acquiring real estate.

 and this research examines the impact of these holdings, representing the main base from which the various projects originate Urban in all areas (economic, social, and recreational).

this leads us to the research problem of the obstacles that arise during the process of acquiring real estate to carry out development projects, and to achieve the objectives of research, namely (work to create a regulatory methodology

6. coli K12 and B. subtilis 168 were investigated for their cadmium and mercury tolerance abilities. They were developed by UV mutagenesis technique to increase their tolerances either to cadmium or mercury, and their names then were designated depend on the name and concentration of metals. E. coli K12 Cd3^R exhibited bioremediation amount of 6.5 mg Cd/g dry biomass cell. At the same time, its wild-type (E. coli K12 Cd3) was able to remove 5.2 mg Cd/g dry biomass cell in treatment of 17 mg Cd /L within 72 hours of incubation at 37 °C (pH=7) in vitro assays. The results show that E.coli K12 Hg 20 was able to remove 0.050 µg Hg/g dry biomass cell

Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

Glycyrrhiza glabra is a herbal plant used for treatment of many infertility diseases. Its roots, a common herbal source, are described to soothe fetuses in pregnant mice, but there isn't enough research to know if it's safe to take during pregnancy and its effects on implantation factors. This study examines the impact of the growth factors betacellulin (BTC), heparin-binding epidermal growth factor, and activin A hormone on embryonic development after oral administration of Glycyrrhiza glabra aqueous extract to mice. In line with clinical use, an aqueous extract of Glycyrrhiza glabra roots was prepared. Pregnant mice were randomly assigned to one of four groups: Two mice groups 8 and 28 weeks old treated with water as a negative co

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay