As per the projections of conventional credit risk structured model, the risky asset values tend to adhere to the geometric Brownian motion. On the contrary, the risky asset values remain a non-continuous and dynamic ones and jump based on the conditions. Is not possible to measure the real Knight Uncertainty risks in financial markets with the help of a single probability measure. In this background, the current research work analyzes a structural credit risk model that belongs to Levy market under Knight Uncertainty. With the help of Lévy-Laplace exponent, the authors developed a dynamic pricing model in this study and acquired the price intervals for default probability, stock value and the bond value of enterprise. To be specific, the study intended to establish explicit solutions for three value processes, discussed earlier, with an assumption that the jump process follows a log-normal distribution. At the end, the study also conducted numerical analysis to understand the crucial role played by Knight Uncertainty upon the pricing of default probability and the stock value of the enterprise.
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http://dx.doi.org/10.1007/s10479-023-05309-2 | DOI Listing |
JCO Clin Cancer Inform
January 2025
SimBioSys Inc, Chicago, IL.
Purpose: Perfusion modeling presents significant opportunities for imaging biomarker development in breast cancer but has historically been held back by the need for data beyond the clinical standard of care (SoC) and uncertainty in the interpretability of results. We aimed to design a perfusion model applicable to breast cancer SoC dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) series with results stable to low temporal resolution imaging, comparable with published results using full-resolution DCE-MRI, and correlative with orthogonal imaging modalities indicative of biophysical markers.
Methods: Subsampled high-temporal-resolution DCE-MRI series were run through our perfusion model and resulting fits were compared for consistency.
Lancet Psychiatry
December 2024
Background: High-quality estimates of the epidemiology of the autism spectrum and the health needs of autistic people are necessary for service planners and resource allocators. Here we present the global prevalence and health burden of autism spectrum disorder from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 following improvements to the epidemiological data and burden estimation methods.
Methods: For GBD 2021, a systematic literature review involving searches in PubMed, Embase, PsycINFO, the Global Health Data Exchange, and consultation with experts identified data on the epidemiology of autism spectrum disorder.
Lancet Planet Health
December 2024
The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia; Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia; Department of Cardiology, Royal Prince Alfred Hospital, Sydney, NSW, Australia.
Background: The health-care sector is responsible for 5·2% of global emissions, however, little data exist regarding the environmental impact of disease management strategies. SGLT2 inhibitors are now widely used to reduce the risk of hospital admission and kidney failure in people with type 2 diabetes and chronic kidney disease. This study aimed to estimate the impact of SGLT2 inhibitors on greenhouse gas emissions using data from the CREDENCE trial.
View Article and Find Full Text PDFEur Phys J C Part Fields
December 2024
ACS Earth Space Chem
November 2024
Department of Chemistry, University of Oxford, Oxford OX1 3QZ, U.K.
The radiative forcing caused by atmospheric aerosol represents one of the largest uncertainties in climate models. In part, these uncertainties derive from poor characterizations of the optical properties of light-absorbing brown carbon (BrC) containing aerosols. Here, single particle cavity ring-down spectroscopy (SP-CRDS) is used to determine the complex refractive index at the optical wavelength of 405 nm for aqueous particles composed of an abundant BrC species, 4-nitrocatechol.
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