Results 131 to 140 of about 7,541,076 (252)
Exposure to default and loss given default
Two important risk drivers in credit risk are exposure risk (measured by exposure at default (EAD) and loss given default (LGD) or recovery rate (RR)).
RESTI, ANDREA CESARE
core
Lactiplantibacillus plantarum GUANKE remodels the indigenous gut microbiota and is associated with microbiota‐dependent restoration of circulating IAA. IAA treatment attenuates JAK3‐STAT3 and Jag1‐Notch4‐Hey1 signaling and reduces CX3CR1+Ly6C− monocytic precursor generation and pulmonary CD11b+ DC accumulation, together with reduced Th2 inflammation ...
Yujia He +10 more
wiley +1 more source
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Econometric Estimation of Loss Given Default
One of the most mentioned credit risk parameters in banking sector is loss given default (LGD). The regulatory framework allows to use own LGD estimation procedures after approval.
Jacina, Viktor
core
We demonstrate a novel therapy for traumatic brain injury TBI using a LIPUS‐responsive Piezoelectric fibrous membrane. It targets microglial mitochondria via in situ electrical signals, restoring homeostasis and reducing oxidative stress to promote an anti‐inflammatory M2 phenotype.
Wei Li +9 more
wiley +1 more source
Análise do Modelo CreditRisk+ em uma amostra de portfólio de crédito
The paper analyzes CreditRisk+ Model theoretical foundations and fulfillment in a credit portfolio sample. In this analysis, CreditRisk+ Model, one of the risk assessment models created by banks, was applied in an US portfolio sample with default events ...
Rafael Mileo +2 more
doaj
Title from cover.Mode of access: Internet.Merger of: Official cohort default rate guide, and: Draft cohort default rate ...
United States. Dept. of Education. Default Management Division.
core
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi +7 more
wiley +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source

