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Dr. Abubakar’s research seeks to further improve idea of tumor biology and its effect on remedy response and scientific outcomes by adopting an ecosystem approach that experiments both equally the tumor and TME as dynamically interconnected parts in the tumor-related ecosystem. By leveraging AI, along with many laboratory staining methods, He's accomplishing deep phenotypic profiling of tumor tissues to uncover novel capabilities which can be linked with epidemiological and scientific knowledge to inform prognosis and/or procedure final decision-generating for screening-detectable cancers.
Enhancement of reference recent calculation plan for grid-aspect converter all through unbalanced faults
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Enhanced present-day Muhammad Abubakar Maken managed doubly fed induction generator model with grid integration under sub and Tremendous synchronous disorders
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Advancement of fault journey as a result of ability of DFIG-centered wind turbine methods employing superconducting fault present-day limiter
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While using the raising uptake of populace-based most cancers screening plans worldwide, the incidences of benign and precursor lesions on tissue biopsies performed for suspected breast, colorectal, prostate, or lung cancers are possible to continue to rise, underscoring the necessity for normal background experiments into screening-detectable cancers. Appropriately, Dr. Abubakar’s integrative analysis program in computational pathoepidemiology is centered on advancing scientific knowing into the job of tissue ecosystem disruption while in the etiology, natural heritage, tumor heterogeneity, and clinical results of screening-detectable cancers.
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SC currents minimization in distributed generation embedded distribution networks with exceptional software of FCLs
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