Drag reduction (DR) techniques are used to improve the flow by spare the flow energy. The applications of DR are conduits in oil pipelines, oil well operations and flood water disposal, many techniques for drag reduction are used. One of these techniques is microbubbles.  In this work, reduce of drag percent occurs by using a small bubbles of air pumped in the fluid transported. Gasoil is used as liquid transporting in the pipelines and air pumped as microbubbles. This study shows that the maximum value of drag reduction is 25.11%.

Growth of Penicillium expansum, an ubiquitous mould found in stored fruit globallyt, was significantly restricted by exposure to 48 h cell-free supernatant of two strains of Lactobacillus plantarum (p < 0.001). In addition, the biotransformation of patulin, a toxic secondary metabolite formed by P. expansum, on exposure to L. plantarum cells and cell-free supernatant highlights the potential of this GRAS microbe as a biocontrol agent. Up to 80% of patulin was biotransformed following a 4 h incubation with 1010 cells ml−1 (37 °C) forming E- and Z-ascladiol. The formation of these products was more pronounced at elevated pH and cell density. Exposure to cell free supernatant or sonicated cells resulted in complete patulin biotransformation

QJ Rashid, IH Abdul-Abbas, MR Younus, PalArch's Journal of Archaeology of Egypt/Egyptology, 2021 - Cited by 4

Education is the most powerful and important weapon in fighting poverty and unemployment because it provides students with new skills that appropriate the new market requirements and fair distribution of natural resources. It also transfers knowledge, skills, and ethics over generations. Education aims to create effective leaders who go under training and rehabilitation process, create a new human and instill faith, generate the creativity and innovation, and keep abreast with scientific process, updating curriculum, and finally, applying the technical education

This research aimed to develop a simulation traffic model for an urban street with heterogeneous traffic capable of analyzing different types of vehicles of static and dynamic characteristics based on trajectory analysis that demonstrated psychophysical driver behavior. The base developed model for urban traffic was performed based on the collected field data for the major urban street in Baghdad city. The parameter; CC1 minimum headway (represented the speed-dependent of the safety distance from stop line that the driver desired) justified in the range from (2.86sec) to (2.17 sec) indicated a good match to reflect the actual traffic behavior for urban traffic streets. A good indication of the convergence between simulat

Lifestyle Medicine is the application of evidence-based lifestyle approaches for the prevention, treatment, and even the reversal of lifestyle-related chronic diseases such as diabetes, hypertension, heart disease, obesity, polycystic ovarian diseases, dementia, arthritis, and cancers

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio