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Dr. Abubakar’s study seeks to further improve idea of tumor biology and its effect on remedy reaction and medical outcomes by adopting an ecosystem strategy that experiments both of those the tumor and TME as dynamically interconnected parts in the tumor-associated ecosystem. By leveraging AI, at the side of many laboratory staining methods, He's doing deep phenotypic profiling of tumor tissues to uncover novel functions that can be connected with epidemiological and scientific information to tell prognosis and/or remedy decision-generating for screening-detectable cancers.
Progress of reference recent calculation plan for grid-facet converter through unbalanced faults
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Improved present-day managed doubly fed induction generator model with grid integration under sub and Tremendous synchronous problems
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He provides a eager yet aiding Mind-set to other experts. I am quite self-confident that He'll improve perfectly in his field. I wish him best of luck all through his foreseeable future pursuits.”
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Together with the escalating uptake of population-dependent cancer screening courses throughout the world, the mabubakermaken incidences of benign and precursor lesions on tissue biopsies done for suspected breast, colorectal, prostate, or lung cancers are probably to carry on to rise, underscoring the necessity for normal background experiments into screening-detectable cancers. Accordingly, Dr. Abubakar’s integrative research method in computational pathoepidemiology is focused on advancing scientific knowledge in to the job of tissue ecosystem disruption while in the etiology, all-natural heritage, tumor heterogeneity, and clinical outcomes of screening-detectable cancers.
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SC currents minimization in distributed generation embedded distribution networks with optimal software of FCLs
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