M
Mohamed Talaat
Researcher at University of Massachusetts Lowell
Publications - 8
Citations - 62
Mohamed Talaat is an academic researcher from University of Massachusetts Lowell. The author has contributed to research in topics: Sniffing & Inhalation. The author has an hindex of 3, co-authored 8 publications receiving 21 citations. Previous affiliations of Mohamed Talaat include University of Massachusetts Amherst.
Papers
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Journal ArticleDOI
SARS COV-2 virus-laden droplets coughed from deep lungs: Numerical quantification in a single-path whole respiratory tract geometry
TL;DR: In this paper, the behavior and fate of respiratory droplets (0.1 − 4 µm) during coughs in a single-path respiratory tract model extending from terminal alveoli to mouth opening was investigated.
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Micrometer aerosol deposition in normal and emphysematous subacinar models
TL;DR: The subacinus-averaged doses increase with progressing septal destructions, suggesting an escalating risk factor to the acinar health at the late stages of emphysema.
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Alveolar size effects on nanoparticle deposition in rhythmically expanding-contracting terminal alveolar models
TL;DR: Results of this study indicate that empirical correlations obtained from one sub-population cannot be directly applied to others, nor can they be simply scaled as a function of the alveolar size or respiration frequency due to the regime-transiting deposition mechanism that is both localized and dynamic.
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The application of statistical shape modeling for lung morphology in aerosol inhalation dosimetry
TL;DR: This is the first study, to the author's knowledge, that SSM was applied in lung models with high complexity to quantify the resultant variances from these geometry remodeling, which showed that even though the airway remodeling can be local, its influences on flow partition and deposition distribution can be global.
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Leveraging statistical shape modeling in computational respiratory dynamics: Nanomedicine delivery in remodeled airways
TL;DR: In this paper, the authors presented a method to simulate the airway remodeling in a mouth-lung geometry extending to G9 using statistical shape modeling and Lagrangian tracking.