Transportability refers to the ease with which people, goods, or services may be transferred. When transportability is high, distance becomes less of a limitation for activities. Transportation networks are frequently represented by a set of locations and a set of links that indicate the connections between those places which is usually called network topology. Hence, each transmission network has a unique topology that distinguishes its structure. The most essential components of such a framework are the network architecture and the connection level. This research aims to demonstrate the efficiency of the road network in the Al-Karrada area which is located in the Baghdad city. The analysis based on a quantitative evaluation using graph th

The current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.

The mucilage from the seeds of Lallemantia royleana family Labiatae was extracted and subjected to preformulation study for evaluation of its suitability for use as suspending agent. Furosemide suspensions were prepared using (1.5% w/v) of the extracted Lallemantia royleana mucilage, (1.5% w/v) chitosan and (0.35% w/v) xanthan gum. The mucilage was white in color and the average yield of dried mucilage obtained from L.royleana nutlets was 14 % w/w of the seeds used. It is sparingly soluble in water but swells in contact with it, giving a highly viscous solution. It is slightly acidic to neutral. It was found that the extracted natural mucilage of Lallemantia royleana exhibited a higher viscosity profil

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

In Production and Operations Management the specialists  have  tried to develop a strategy to counter the risks arising from the activities of the organization and of waste of various types and therefore the risk management in the contemporary framework represents a phenomenon of new quality, and can not be this phenomenon to take practical dimensions, but the development of culture of the organization towards the risks and deal with all aspects and paint ways to address them within an integrated program, and requires new skills and systems provide accurate information capable of coordination between the various parties within the organization.

     The research aims to develop a blu

A series of benzohydrazide derivatives attached to coumarin moiety at position 6 and 7 have been synthesized. The reaction of coumarin derivatives (coumarin I and II) with p-nitrophenyl hydrazine yield Schiff bases (compound1a and IIa_).These Schiff bases were refluxed with benzoyl chloride to give benzohydrazide derivatives of coumarin substituted at its 6 or 7 nucleus position (Ia₁ and IIa₁).The reaction and the purity of the products were checked by thin layer chromatography (TLC). The structures of the final compounds  and  their intermediates were confirmed by their melting points, infra red spectroscopy, and elemental microanalysis(CHN).

Compounds (Ia1 and IIa1) were evaluated for&n

In this work, novel compounds of hydrazones derived from (2,4-dinitrophenyl) hydrazine were synthesized. Benzamides derivatives and sulfonamides derivatives were prepared from p-amino benzaldehyde. Then these compounds were condensed with (2,4-dinitrophenyl) hydrazine through Imine bond formation to give hydrazones compounds. The compounds were characterized using FT-IR (IR Affinity-1) spectrometer, and 1HNMR analyses. The majority of the compounds have a moderate antimicrobial activity against “Gram-positive bacteria staphylococcus Aureus, and staphylococcus epidermidis, Gram-negative bacteria Escherichia coli, and Klebsiella pneumoniae, and fungi species Candida albicans” using concentrations of 250 µg\ml.

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med