Existing one-dimensional (1D) models of aerosol dosimetry often ignore mixing mechanisms of inhaled aerosols during their transport in the lung. This mixing or aerosol dispersion results from different physical mechanisms in different regions of the lung. It is a higher order effect, which cannot be directly captured in 1D modeling approaches, and thus is sometimes modeled as a diffusive process. In this study, we improved our recently developed alveolar mixing module incorporated in the multiple path particle dosimetry model (MPPD) to account for flow irreversibility and particle trapping in the alveolar spaces, as well as mixing occurring in the tracheobronchial region. This new version of MPPD was coupled with CFPD-based predictions of aerosol bolus dispersion in the oral airway. The model was used to predict the deposition, dispersion, and mode shift of aerosol bolus inhaled at different penetration depths within the lung for breathing patterns and particle size matching those used in a previous experimental study (Darquenne et al., 2016). Even though a quite simplified approach was used, the computations appear to describe subject-specific and test-specific experimental data reasonably well. The proposed combined dispersion-deposition model can be a useful tool for targeted drug delivery and also for exposure health risk assessment.
Background and purpose: ASPECTS is a long-standing and well-documented selection criterion for acute ischemic stroke treatment; however, the interpretation of ASPECTS is a challenging and time-consuming task for physicians with notable interobserver variabilities. We conducted a multireader, multicase study in which readers assessed ASPECTS without and with the support of a deep learning (DL)-based algorithm to analyze the impact of the software on clinicians' performance and interpretation time. Materials and methods: A total of 200 NCCT scans from 5 clinical sites (27 scanner models, 4 different vendors) were retrospectively collected. The reference standard was established through the consensus of 3 expert neuroradiologists who had access to baseline CTA and CTP data. Subsequently, 8 additional clinicians (4 typical ASPECTS readers and 4 senior neuroradiologists) analyzed the NCCT scans without and with the assistance of CINA-ASPECTS (Avicenna.AI), a DL-based, FDA-cleared, and CE-marked algorithm designed to compute ASPECTS automatically. Differences were evaluated in both performance and interpretation time between the assisted and unassisted assessments. Results: With software aid, readers demonstrated increased region-based accuracy from 72.4% to 76.5% (P < .05) and increased receiver operating characteristic area under the curve (ROC AUC) from 0.749 to 0.788 (P < .05). Notably, all readers exhibited an improved ROC AUC when utilizing the software. Moreover, the use of the algorithm improved the score-based interobserver reliability and correlation coefficient of ASPECTS evaluation by 0.222 and 0.087 (P < .0001), respectively. Additionally, the readers' mean time spent analyzing a case was significantly reduced by 6% (P < .05) when aided by the algorithm. Conclusions: With the assistance of the algorithm, readers' analyses were not only more accurate but also faster. Additionally, the overall ASPECTS evaluation exhibited greater consistency, fewer variabilities, and higher precision compared with the reference standard. This novel tool has the potential to enhance patient selection for appropriate treatment by enabling physicians to deliver accurate and timely diagnoses of acute ischemic stroke.
This report pursues assessment and analysis of earlier experimental shock wave studies of HMX based PBX-9501 explosive material, a mixture of HMX molecular crystal and polymer binder. The effort also undertakes exploring underlying physics of the dynamic compaction and deformation of granular mixtures, and in pursuing compaction model improvements relevant to the shock wave equation-of-state. The model development is applied to experimental unreacting shock strength and Hugoniot data on modestly porous PBX-9501 material tested at Los Alamos National Laboratory (LANL) in the 1980's and again in the 1990's. Time-resolved shock wave experiments lend insights into the energy dissipation dynamics. Complementary detailed material microstructure studies constrain dissipation mechanisms on the microscale. Pore compaction is modelled and the potential for heterogeneous hot-spot formation is assessed. Results of the effort uncover details of the unreacting shock compaction response of this mixture material. Specifics of shock wave structure and the dependence of structure on shock amplitude are explored that lend insights into microstructure dissipation mechanisms responsible for onset of reaction. The report closes with a perspective on dissipation dynamics within the unreacting structured shock wave response of PBX 9501 explosive.
This article examines how screw design and fiber type, diameter, and compatibility impact specific mechanical energy (SME) development in co-rotating twin-screw extruder compounding of glass and carbon-fiber reinforced nylon and HDPE. A data driven experimental approach to correlate process parameters and fundamental physics was developed, then run on the twin-screw extruder at industrial compounding conditions. Operating parameter comparisons include two twin-screw extruder screw configurations, specifically, one based on ZME (Zahnmischelement) tooth-based geometry and the other on kneading blocks (KB). Additional parameter comparisons are two base polymers (polar, non-polar), multiple high aspect ratio glass-fiber grades and carbon-fiber, as well as rpm, rate, and percent fiber. SME comparisons between ZME and KB based mixing sections, and among the various fiber types, diameters, and compatibilization agents are discussed and analyzed in detail. For example, processing 30% 10-mu m nylon sized glass-filled nylon consumed almost 10% more downstream mixing SME than processing 13-mu m nylon sized fiber. The wide range of compounded formulations produced by these runs will be used to verify a preliminary first principles fiber unbundling model based on Hamaker analysis. As this is a process study, analysis of fiber dispersion, attrition, as well as model verification review will be presented in subsequent publications.
Electronic nicotine delivery systems (ENDS) use is prevalent among adolescents and young adults. While there have been several efforts to estimate the exposure and dose of ENDS puff constituents in adults, no study to date has focused on younger ENDS users. Given the non-uniformity of lung growth with age, the lungs of young people cannot be considered miniature versions of those of adults; in addition, breathing profiles and flow rates may substantially differ with age. Thus, inhalation dosimetry models developed for adults cannot be directly applied to youth without proper modifications. We extended a previously developed ENDS aerosol deposition model for adults to younger ages (10-21 years) by developing age-specific lung geometries based on available data on lung morphometry and using relationships such as the volume of the oral cavity of adults based on the relevant trachea dimensions, using relationships for volume of the oral cavity for inhaled puff volume, and functional residual capacity (FRC) at different ages. We then used the age-specific deposition model to predict the fate of an ENDS puff with selected constituents (nicotine, propylene glycol, vegetable glycerin, benzaldehyde, and vanillin). Model predictions showed similar patterns of deposition to those of adults in terms of droplet deposition versus vapor uptake. Total deposition and deposition per surface area of individual constituents in the lung decreased with age. The age-specific deposition model is a useful tool to predict lung deposition of ENDS aerosol constituents and compare results across different age groups.
