Computation of drag and diffusion coefficient for coronavirus: I.
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SUBMITTER: White N
PROVIDER: S-EPMC8103743 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Sediment transport calculations are used globally in the numerical models that coastal managers, scientists and engineers use to assess and forecast coastal change. Most of the existing sediment transport equations were defined based on experimental results using siliciclastic sands. Yet these equations are applied to all types of sand, including carbonate sands that have different characteristics and therefore, settling behaviour. A rigorous management of the transport of carbonate sand is essential for the present and future management of sedimentary features in coral reefs such as sandy beaches or reef islands. Here we present a new approach to estimating the drag coefficient of carbonate sands that considers both friction and pressure. Based on our new method, the calculated drag coefficients explain the great variability in settling velocities of carbonate sand observed in nature (from 0.025?m/s to 0.364?m/s in our database). Using our formula, we demonstrate that even small differences in the settling velocity obtained with the new drag coefficient can lead to substantial changes in sediment transport and call for an update of numerical models.
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Project description:PurposeTo characterize the diffusion coefficient of human blood for accurate results in intravoxel incoherent motion imaging.MethodsDiffusion-weighted MRI of blood samples from 10 healthy volunteers was acquired with a single-shot echo-planar-imaging sequence at body temperature. Effects of gradient profile (monopolar or flow-compensated), diffusion time (40-100 ms), and echo time (60-200 ms) were investigated.ResultsAlthough measured apparent diffusion coefficients of blood were larger for flow-compensated than for monopolar gradients, no dependence of the apparent diffusion coefficient on the diffusion time was found. Large differences between individual samples were observed, with results ranging from 1.26 to 1.66 µm2 /ms for flow-compensated and 0.94 to 1.52 µm2 /ms for monopolar gradients. Statistical analysis indicates correlations of the flow-compensated apparent diffusion coefficient with hematocrit (P = 0.007) and hemoglobin (P = 0.017), but not with mean corpuscular volume (P = 0.64). Results of Monte-Carlo simulations support the experimental observations.ConclusionsMeasured blood apparent diffusion coefficient values depend on hematocrit/hemoglobin concentration and applied gradient profile due to non-Gaussian diffusion. Because in vivo measurement is delicate, an estimation based on blood count results could be an alternative. For intravoxel incoherent motion modeling, the use of a blood self-diffusion constant Db = 1.54 ± 0.12 µm2 /ms for flow-compensated and Db = 1.30 ± 0.18 µm2 /ms for monopolar encoding is suggested. Magn Reson Med 79:2752-2758, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Project description:We define a new family of similarity and distance measures on graphs, and explore their theoretical properties in comparison to conventional distance metrics. These measures are defined by the solution(s) to an optimization problem which attempts find a map minimizing the discrepancy between two graph Laplacian exponential matrices, under norm-preserving and sparsity constraints. Variants of the distance metric are introduced to consider such optimized maps under sparsity constraints as well as fixed time-scaling between the two Laplacians. The objective function of this optimization is multimodal and has discontinuous slope, and is hence difficult for univariate optimizers to solve. We demonstrate a novel procedure for efficiently calculating these optima for two of our distance measure variants. We present numerical experiments demonstrating that (a) upper bounds of our distance metrics can be used to distinguish between lineages of related graphs; (b) our procedure is faster at finding the required optima, by as much as a factor of 103; and (c) the upper bounds satisfy the triangle inequality exactly under some assumptions and approximately under others. We also derive an upper bound for the distance between two graph products, in terms of the distance between the two pairs of factors. Additionally, we present several possible applications, including the construction of infinite "graph limits" by means of Cauchy sequences of graphs related to one another by our distance measure.
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Project description:Drag coefficient (Cd) is an essential metric in the calculation of momentum exchange over the air-sea interface and thus has large impacts on the simulation or forecast of the upper ocean state associated with sea surface winds such as storm surges. Generally, Cd is a function of wind speed. However, the exact relationship between Cd and wind speed is still in dispute, and the widely-used formula that is a linear function of wind speed in an ocean model could lead to large bias at high wind speed. Here we establish a parabolic model of Cd based on storm surge observations and simulation in the South China Sea (SCS) through a number of tropical cyclone cases. Simulation of storm surges for independent Tropical cyclones (TCs) cases indicates that the new parabolic model of Cd outperforms traditional linear models.
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Project description:Single-particle tracking is increasingly used to extract quantitative parameters on single molecules and their environment, while advances in spatial and temporal resolution of tracking techniques inspire new questions and avenues of investigation. Correspondingly, sophisticated analytical methods are constantly developed to obtain more refined information from measured trajectories. Here we point out some fundamental limitations of these approaches due to the finite length of trajectories, the presence of localization error, and motion blur, focusing on the simplest motion regime of free diffusion in an isotropic medium (Brownian motion). We show that two recently proposed algorithms approach the theoretical limit of diffusion coefficient uncertainty. We discuss the practical performance of the algorithms as well as some important implications of these results for single-particle tracking.
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Project description:Background and Purpose- In this era of endovascular therapy (EVT) with early, complete recanalization and reperfusion, we have observed an even more rapid apparent diffusion coefficient (ADC) normalization within the acute ischemic lesion compared with the natural history or IV-tPA-treated patient. In this study, we aimed to evaluate the effect of revascularization on ADC evolution within the core lesion in the first 24 hours in acute ischemic stroke patients. Methods- This retrospective study included anterior circulation acute ischemic stroke patients treated with EVT with or without intravenous tPA (IVT) from 2015 to 2017 compared with a consecutive cohort of IVT-only patients treated before 2015. Diffusion-weighted imaging and ADC maps were used to quantify baseline core lesions. Median ADC value change and core reversal were determined at 24 hours. Diffusion-weighted imaging lesion growth was measured at 24 hours and 5 days. Good clinical outcome was defined as modified Rankin Scale score of 0 to 2 at 90 days. Results- Twenty-five patients (50%) received IVT while the other 25 patients received EVT (50%) with or without IVT. Between these patient groups, there were no differences in age, sex, baseline National Institutes of Health Stroke Scale, interhospital transfer, or IVT rates. Thirty-two patients (64%) revascularized with 69% receiving EVT. There was a significant increase in median ADC value of the core lesion at 24 hours in patients who revascularized compared with further ADC reduction in nonrevascularization patients. Revascularization patients had a significantly higher rate of good clinical outcome at 90 days, 63% versus 9% (P=0.003). Core reversal at 24 hours was significantly higher in revascularization patients, 69% versus 22% (P=0.002). Conclusions- ADC evolution in acute ischemic stroke patients with early, complete revascularization, now more commonly seen with EVT, is strikingly different from our historical understanding. The early ADC normalization we have observed in this setting may include a component of secondary injury and serve as a potential imaging biomarker for the development of future adjunctive therapies. Clinical Trial Registration- URL: https://www.clinicaltrials.gov. Unique identifier: NCT00009243.
| S-EPMC6646065 | biostudies-literature
Project description:The air-sea drag coefficient controls the transfer of momentum from wind to water. In modeling storm surge, this coefficient is a crucial parameter for estimating the surge height. This study uses two strong wind events on Lake Erie to calibrate the drag coefficient using the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) modeling system and the the Regional Ocean Modeling System (ROMS). Simulated waves are generated on the lake with Simulating WAves Nearshore (SWAN). Wind setdown provides the opportunity to eliminate wave setup as a contributing factor, since waves are minimal at the upwind shore. The study finds that model results significantly underestimate wind setdown and storm surge when a typical open-ocean formulation without waves is used for the drag coefficient. The contribution of waves to wind setdown and storm surge is 34.7%. Scattered lake ice also increases the effective drag coefficient by a factor of 1.1.
| S-EPMC3747107 | biostudies-literature
Project description:Background and purposeIntramedullary high signal intensity on T2-weighted imaging was frequently observed in patients with CSM, although this finding does not well correlate with severity or prognosis of CSM. Instead of this nonquantitative information, another measure for CSM is desired. The work was focused primarily on assessing the relationships between ADC values and clinical and radiologic severity for the diagnosis of CSM.Materials and methodsThe relationship between ADC values measured in the spinal cord at 322 intervertebral levels of 66 patients and clinical factors were analyzed.ResultsADC values in the spinal cord significantly increased with the degree of spinal cord compression and decreased with time after decompression surgery. Patients with higher ADC values had lower preoperative JOA scores and tended to show poorer clinical recovery.ConclusionsADC values appear to indicate the severity of spinal cord compression and clinical recovery after decompression surgery, so spondylotic myelopathy may partly be predicted preoperatively by using ADC values.
| S-EPMC7964806 | biostudies-literature
Project description:We compare the folding kinetics of a fluorescent phosphoglycerate kinase construct in 30 mammalian cells with that in aqueous buffer. In both environments, the kinetics can be fitted to the functional form exp[-(t/τ)(β)]. A histogram of τ shows that the average folding relaxation time in cells is only twice as long as in aqueous buffer. Consideration of the folding free energy and of β reveals that only some of the variation in τ arises from perturbation of the protein's energy landscape. Thus, the diffusion that controls barrier crossing during protein folding is nearly as fast in cells as in vitro, even though translational diffusion of phosphoglycerate kinase in the cell is slow compared to in vitro.
| S-EPMC2965994 | biostudies-literature
Project description:Purpose To assess the repeatability of apparent diffusion coefficient (ADC) estimates in extracranial soft-tissue diffusion-weighted magnetic resonance imaging across a wide range of imaging protocols and patient populations. Materials and Methods Nine prospective patient studies and one prospective volunteer study, performed between 2006 and 2016 with research ethics committee approval and written informed consent from each subject, were included in this single-institution study. A total of 141 tumors and healthy organs were imaged twice (interval between repeated examinations, 45 minutes to 10 days, depending the on study) to assess the repeatability of median and mean ADC estimates. The Levene test was used to determine whether ADC repeatability differed between studies. The Pearson linear correlation coefficient was used to assess correlation between coefficient of variation (CoV) and the year the study started, study size, and volumes of tumors and healthy organs. The repeatability of ADC estimates from small, medium, and large tumors and healthy organs was assessed irrespective of study, and the Levene test was used to determine whether ADC repeatability differed between these groups. Results CoV aggregated across all studies was 4.1% (range for each study, 1.7%-6.5%). No correlation was observed between CoV and the year the study started or study size. CoV was weakly correlated with volume (r = -0.5, P = .1). Repeatability was significantly different between small, medium, and large tumors (P < .05), with the lowest CoV (2.6%) for large tumors. There was a significant difference in repeatability between studies-a difference that did not persist after the study with the largest tumors was excluded. Conclusion ADC is a robust imaging metric with excellent repeatability in extracranial soft tissues across a wide range of tumor sites, sizes, patient populations, and imaging protocol variations. Online supplemental material is available for this article.
| S-EPMC6063352 | biostudies-literature