Abstract

  The objective of this study was to investigate the phytochemical constituents of two different parts of Vigna radiata (seeds and sprouts), and identify their  anti angiogenic activity .the goal was achieved by Preliminary qualitative phytochemical screening for crude ethanolic extract of two parts of plant

 ; rat aorta anti-angiogenesis assay had been conducted for both extracts .   isolation , separation and purification of some phytochemical constituents that belong to important groups (flavonoids) from  n-butanol fraction extract of Vigna radiata plant had been done in pure form by using preparative thin layer chromatography ( PTLC ) and then

The current study was conducted to evaluate the effect a mixture of threespecies of arbuscular mycorrhizal fungi (Glomus etunicatum, G. leptotichum andRhizophagus intraradices) double and triple mixture and organic matter by usingplastic pots in the greenhouse at some mycorrhiza and physiological limitationscharacteristics in tomato plant after four and eight weeks of cultivation. Theresults of the determinants mycorrhiza significant increase the percentage ofmycorrhizal frequency F% dry weight of roots mycorrhiza (g.plant-1) andorganic matter in all mycorrhiza single, double and triple mixture after four andeight weeks cultivation treatments. The highest percentage of mycorrhizalfrequency and increase the dry weight of the root in the trea

The study aimed to prepare a measure of metacognitive thinking commensurate with learning the skill, preparing educational units using the Claus Meyer model for metacognitive thinking, and learning the skill of defending the court in volleyball. To identify the effect of educational units using the model (and Claus Meyer) for metacognitive thinking and learning the skill of defending the court in volleyball. The two researchers used the experimental approach with the design of the experimental and control groups.The research community consisted of students of the second stage / College of Physical Education and Sports Sciences / University of Baghdad for the academic year 2021-2022, whose number is (385) st

The business environment is witnessing great and rapid developments due to the economic and technological development that has caused damage to human beings, which requires the need to reduce this damage and work to protect the environment and participate in supporting the social aspects. This requires economic resources to be realized by the economic units. Economic development in preserving the environment that has caused damage and supporting the social aspects that preserve human rights, enhance their position and satisfy their needs in society. Global professional organizations, the United Nations and stakeholder representatives have been issuing the Global Reporting Initiative (GRI) to find guidelines for the preparation of

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord