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Dr. Abubakar’s investigation seeks to enhance knowledge of tumor biology and its impact on procedure reaction and medical outcomes by adopting an ecosystem approach that research each the tumor and TME as dynamically interconnected components with the tumor-affiliated ecosystem. By leveraging AI, along with a number of laboratory staining strategies, he is carrying out deep phenotypic profiling of tumor tissues to uncover novel options that could be connected with epidemiological and clinical facts to inform prognosis and/or procedure final decision-building for screening-detectable cancers.
Improvement of reference latest calculation scheme for grid-facet converter for the duration of unbalanced faults
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Enhanced existing controlled doubly fed induction generator product with grid integration underneath sub and super synchronous circumstances
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Improvement of fault journey via functionality of DFIG-centered wind turbine techniques working with superconducting fault current limiter
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While using the raising uptake of populace-based most cancers screening plans around the globe, the incidences of benign and precursor lesions on tissue biopsies performed for suspected breast, colorectal, prostate, or lung cancers are most likely abubakar to carry on to rise, underscoring the necessity for normal background studies into screening-detectable cancers. Accordingly, Dr. Abubakar’s integrative research method in computational pathoepidemiology is focused on advancing scientific being familiar with to the role of tissue ecosystem disruption from the etiology, all-natural record, tumor heterogeneity, and clinical results of screening-detectable cancers.
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SC currents minimization in distributed technology embedded distribution networks with best application of FCLs
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