Winston Churchill Foundation

In this study, we conducted a sensitivity analysis to determine the optimal design of a supersonic airfoil. The design includes four independent variables: angle of attack, thickness of the upper surface, and the locations of the upper and lower surfaces' maximum thicknesses. The output is the maximum lift-to-wave drag ratio. First, we used a first-order Taylor approximation to analyze the impact of each design variable on the output. The first three variables have similar effects, while the fourth has less influence. Next, we applied a second-order Taylor approximation to further explore how each variable affects the output and the response function near the optimal design point. The results show that small variations in the design variables lead to minor changes in airfoil performance. We also identified the variable ranges around this point that satisfy the constraints through numerical calculations. Finally, we compared our approach with factorial design, a common sensitivity analysis method, and found that Taylor approximations offer a more detailed theoretical explanation of the results.

Abstract The spiro[3.3]heptane core, with the non‐coplanar exit vectors, was shown to be a saturated benzene bioisostere. This scaffold was incorporated into the anticancer drug sonidegib (instead of the meta‐benzene), the anticancer drug vorinostat (instead of the phenyl ring), and the anesthetic drug benzocaine (instead of the para‐benzene). The patent‐free saturated analogs obtained showed a high potency in the corresponding biological assays.

ABSTRACTBrain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive, and may be unavailable for legacy datasets used for genome-wide association studies (GWAS). Using an integrated feature selection/aggregation model, we developed Image-Mediated Association Study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression Quantitative Trait Loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost-savings for integrated analysis of genetics and imaging.

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