AI weather foundation models now achieve forecast skill comparable to numerical weather prediction at far lower computational cost, yet their predictability for high-impact extremes across dynamical r...
In this paper, we propose a novel frequency-severity joint trip-level risk index that combines the frequency of abnormal driving patterns with a severity component reflecting how extreme such behavior...
Data scarcity is a primary obstacle in developing robust Machine Learning (ML) models for detecting rapidly intensifying tropical cyclones. Traditional data augmentation techniques (rotation, flipping...
Employers in Germany argue that collective agreements restrict their flexibility concerning working hours. Using data from the IAB Establishment Panel for the years 2008 to 2024, we investigate workin...
Climate extremes have become important drivers of mortality, producing sudden spikes that traditional mortality models fail to predict. To address this gap, we propose a two-step modelling framework t...
Marine heatwaves (MHWs) threaten marine ecosystems and significantly impact weather patterns. In the Arabian Sea, summer MHWs are of particular concern due to their potential impacts on the Indian sum...
Understanding the environmental drivers of forest transpiration is critical for improving global predictions of water availability and ecosystem health. Due to many competing controls on plant water s...
Ride-hailing platforms increasingly rely on non-exclusive notifications-broadcasting a single request to multiple drivers simultaneously-to mitigate inefficiencies caused by uncertain driver acceptanc...
The freight industry is undergoing a digital revolution, with an ever-growing volume of transactions being facilitated by digital marketplaces. A core capability of these marketplaces is the fulfillme...
Direct air carbon capture and storage (DACCS) is a promising CO2 removal technology, but its deployment at scale remains speculative. Yet, its technological, economic, and policy-related uncertainties...
In a statistical factor model, principal components (or eigenvectors) of a sample covariance matrix serve as estimates of {\it principal directions}, the true drivers of co-movement of a collection of...
Cross-cutting commenting on social media is often imagined as a path to deliberation, yet exposure to opposing views frequently fuels hostility. To explain this dynamic, we introduce the concept of pa...
As more investors contemplate private markets and contend with limited transparency, sparse disclosures, and infrequent transactions, identifying economically meaningful peer companies for comparison ...
Environmental conditions are major drivers of malaria transmission, but epidemiological analyses are often constrained by temporal misalignment between health outcomes reported at coarse time scales a...
We conduct the first rigorous study of electricity price volatility for the full panel of electricity prices across three European generation zones. By interpreting the observed day-ahead prices as lo...
The accelerating shift toward low and ultra-low fertility has intensified the debate over whether countries now undergoing rapid decline are approaching stabilization or entering a more persistent low...
Human driving behavior is inherently personal, which is shaped by long-term habits and influenced by short-term intentions. Individuals differ in how they accelerate, brake, merge, yield, and overtake...
Large Arctic rivers transport substantial amounts of freshwater, carbon (C), and nutrients from land to the Arctic Ocean and play an important role in continental-ocean biogeochemical coupling. Althou...
The Arctic stratospheric polar vortex (SPV) is known to influence winter surface climate through dynamical coupling. Here, we demonstrate that beyond this established pathway, variations in SPV streng...
The proliferation of antibiotic resistance in marine ecosystems represents a critical One Health challenge, particularly within coastal habitats that receive anthropogenic inputs. This study presents ...
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