Purose: To calculate theoretical fitting success rates (SR) for a range of typical soft contact lens (SCL) designs using a mathematical model.
Method: A spreadsheet mathematical model was used to calculate fitting SR for various SCL designs. Designs were evaluated using ocular topography data from 163 subjects. The model calculated SR based on acceptable edge strain (within range 0-6%) and horizontal diameter overlap (range 0.2-1.2mm). Where lenses had multiple base curves (BCs), eyes unsuccessful with the steeper BC were tested with the flatter BC and aggregate SR calculated. Calculations were based on typical, current, hydrogel and silicone hydrogel SCLs and allowed for appropriate on-eye shrinkage (1.0-2.3%). Theoretical results were compared with those from actual clinical trials.
Results: Theoretical success rates for one-BC lenses ranged from 60.7% (95% CI 7.2%) to 90.2% (95% CI 3.7%). With two-BC designs, most combinations showed a SR increase with a second BC (84.0%-90.2%). However, one of the two-BC combinations showed only negligible increase with a second BC (72.4%-73.0%). For designs with lower SR, the greatest contributor to failure was inadequate lens diameter. For a given design, differences in shrinkage (i.e. on-eye bulk dehydration) had a significant effect on success rate. In comparison with historical clinical data, there was a positive correlation between small lens fitting prevalence and discomfort reports (r=+0.95, P=<0.001) with a poor correlation between theoretical and actual tight/loose fittings.
Conclusions: Mathematical modelling is a useful method for testing SCL design combinations. The results suggest that judicious choice of additional fittings can expand the range of fitting success.
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http://dx.doi.org/10.1016/j.clae.2017.04.001 | DOI Listing |
J Phys Chem A
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School of Environment and Safety Engineering, North University of China, Taiyuan, Shanxi 030051, China.
DNP (3,4-dinitropyrazole) has attracted much interest due to its promising melting characteristics and high detonation performances, such as low melting point, high density, high detonation velocity, and low sensitivity. In this work, first-principles molecular dynamics (MD) simulations were performed to investigate the anisotropic shock response of DNP in conjunction with the multiscale shock technique (MSST). The initial decomposition mechanism was revealed through the evolution of the chemical reaction and product analysis.
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Chief (retired), Department of Statistics, Radiation Research Effects Foundation, Hiroshima, Japan.
Although leukemia in the Japanese atomic bomb survivor data has long exhibited upward curvature, until recently this appeared not to be the case for solid cancer. It has been suggested that the recently observed upward curvature in the dose response for the Japanese atomic bomb survivor solid cancer mortality data may be accounted for by flattening of the dose response in the moderate dose range (0.3-0.
View Article and Find Full Text PDFPLoS One
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Department of Civil and Environmental Engineering, Nazarbayev University, Nur-Sultan, Kazakhstan.
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Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, BT48 7JL Derry-Londonderry, Northern Ireland, U.K.
Decision formation in perceptual decision making involves sensory evidence accumulation instantiated by the temporal integration of an internal decision variable toward some decision criterion or threshold, as described by sequential sampling theoretical models. The decision variable can be represented in the form of experimentally observable neural activities. Hence, elucidating the appropriate theoretical model becomes crucial to understanding the mechanisms underlying perceptual decision formation.
View Article and Find Full Text PDFPLoS One
January 2025
Institute for Health Systems Science, Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands.
Mathematical modeling plays an important role in our understanding and targeting therapy resistance mechanisms in cancer. The polymorphic Gompertzian model, analyzed theoretically and numerically by Viossat and Noble to demonstrate the benefits of adaptive therapy in metastatic cancer, describes a heterogeneous cancer population consisting of therapy-sensitive and therapy-resistant cells. In this study, we demonstrate that the polymorphic Gompertzian model successfully captures trends in both in vitro and in vivo data on non-small cell lung cancer (NSCLC) dynamics under treatment.
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