Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the infection. Smart technologies have provided the medical field with health predictions for early detection, and digital diagnosis is one of the most important sources on which research has relied on. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
The Ligand 6,6--(1,2-benzenediazo) bis (3-aminobenzoicacid) derived from o-phenylenediamine and 3-aminobenzoicacid was synthesized. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the ligand with the following metal ions (CoII, NiII, CuII and ZnII ) in aqueous ethanol with a 1:1 M:L ratio and at optimum pH. Characterization of these compounds has been done on the basis of elemental analysis, electronic data, FT-IR and UV-Vis, as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). H
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ABSTRACT
The researcher seeks to shed light on the relationship analysis and the impact between organizational values in all its dimensions (Administration Management, Mission, relationship management, environmental management) and strategic performance (financial perspective, customer perspective, the perspective of internal processes, learning and development) in the presidency of Two Universities of Baghdad & Al-Nahrain, it has been formulating three hypotheses for this purpose.
The main research problem has been the following question: Is there a relationship and the impact of bet
... Show MoreAPDBN Rashid, Review of International Geographical Education Online (RIGEO), 2021
In the current study, a direct method was used to create a new series of charge-transfer complexes of chemicals. In a good yield, new charge-transfer complexes were produced when different quinones reacted with acetonitrile as solvent in a 1:1 mole ratio with N-phenyl-3,4-selenadiazo benzophenone imine. By using analysis techniques like UV, IR, and 1H, 13C-NMR, every substance was recognized. The analysis's results matched the chemical structures proposed for the synthesized substances. Functional theory of density (DFT)
has been used to analyze the molecular structure of the produced Charge-Transfer Complexes, and the energy gap, HOMO surfaces, and LUMO surfaces have all been created throughout the geometry optimization process ut
Background: The bond strength of root canal sealers to dentin was important for maintaining the integrity of the seal in root canal filling in both static and dynamic situations. In a static situation, it should eliminate any space that allowed the percolation of fluids between the filling and the wall while in a dynamic situation; it was needed to resist dislodgement of the filling during subsequent manipulation. Materials and Methods: Forty mandibular premolars were selected for this study. All canals were instrumented using ProTaper rotary instruments. Instrumentation was done with copious irrigation of 5.25% sodium hypochlorite. Roots were randomly divided into four groups according to the type of cleaning and method of root canal irrig
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MorePhytochemical Screening and Antibacterial Effect of Stevia Rebaudiana (Bertoni) Alcoholic Leaves Extract on Streptococcus Oralis (Dental Plaques Primary Colonizer), Manar Ibrahim