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Dr. Abubakar’s investigation seeks to enhance understanding of tumor biology and its influence on treatment method response and clinical results by adopting an ecosystem strategy that research both the tumor and TME as dynamically interconnected factors on the tumor-related ecosystem. By leveraging AI, in conjunction with various laboratory staining ways, He's doing deep phenotypic profiling of tumor tissues to uncover novel attributes that can be connected with epidemiological and scientific knowledge to inform prognosis and/or cure selection-earning for screening-detectable cancers.
Advancement of reference current calculation scheme for grid-facet converter in the course of unbalanced faults
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Improved present managed doubly fed induction generator design with grid integration below sub and super synchronous disorders
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Enhancement of fault experience via ability of DFIG-centered wind turbine systems making use of superconducting fault latest limiter
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While using the raising uptake of populace-primarily based most cancers screening systems throughout the world, the incidences of benign and precursor lesions on tissue biopsies executed for suspected breast, colorectal, prostate, or lung cancers are very likely to continue to increase, underscoring the need for purely natural historical past scientific studies into screening-detectable cancers. Appropriately, Dr. Abubakar’s integrative exploration system in computational pathoepidemiology is centered on advancing scientific knowledge in to the job of tissue ecosystem disruption while in the etiology, all-natural heritage, tumor heterogeneity, and clinical results of screening-detectable cancers.
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SC currents minimization in distributed technology embedded distribution networks with ideal application of FCLs
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