Interferometric synthetic aperture sonar (InSAS), a new high-resolution three-dimensional imaging device, is broadly utilized in underwater exploration. Interferogram noise removal is a necessary stag...
Marine litter has been quantified in several deep-sea environments, including complex habitats such as submarine canyons that host Vulnerable Marine Ecosystems. However, a standardized method for its ...
Quantitative susceptibility mapping (QSM) has been increasingly applied in longitudinal studies of neurodegenerative diseases and aging to assess temporal alterations in brain iron and myelin. The acc...
Effective collaborative data entry and transparency are foundational for building robust databases and high-quality data synthesis. Yet researchers often face inconsistent data entries, inadvertently ...
We propose a score test for dependence predictability in conditional copulas that is robust to temporal instabilities. Our semiparametric procedure accommodates flexible dynamics in the marginal proce...
Bayesian dynamic borrowing (BDB) methods leverage historical data to reduce treatment effect uncertainty, yet existing approaches rely on parametric outcome models susceptible to misspecification. We ...
Deep neural networks often exploit spurious associations in their training data, a failure known as shortcut learning. Concept-based explainability methods screen for shortcuts by testing whether conc...
In this paper, we present three neural network architectures designed for real-time classification of weather conditions (sunny, rain, snow, fog) from images. These models, inspired by recent advances...
Speckle noise is a multiplicative noise commonly encountered in coherent imaging modalities such as synthetic aperture radar, optical coherence tomography, and digital holography. Although deep learni...
Solea aegyptiaca gelatin (GSA) is a promising alternative to conventional gelatin. With a yield of 9.64% after 9 h, it was produced by alkali pretreatment followed by acid extraction. GSA exhibited a ...
Video world models that maintain 3D spatial consistency across generated frames typically rely on explicit point cloud memory constructed in RGB space. This design is both computationally expensive, r...
At the subantarctic islands of South Georgia, albatrosses and petrels occupy a range of trophic niches, from zooplanktivore to top predator. Interspecific variation in mercury (Hg) contamination is th...
Economic analysis of effective policies for managing epidemics requires an integrated economic and epidemiological approach. We develop and estimate a spatial, micro-founded model of the joint evoluti...
Large Language Models (LLMs) still struggle with multi-step logical reasoning. Existing approaches either purely refine the reasoning chain in natural language form or attach a symbolic solver as an e...
Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, idealized settings and is non-estimable from sampl...
As language models are increasingly deployed for complex autonomous tasks, their ability to reason accurately over longer horizons becomes critical. An essential component of this ability is planning ...
Coral reef ecosystems are declining rapidly due to climate change, disease, and anthropogenic stressors, driving the expansion of land-based coral propagation for reef restoration. A major bottleneck ...
"Vibe coding" and "vibe analytics" have been framed as a democratization of technical capability. This paper argues that AI-assisted methodology more broadly, or what I call "vibe methodology," also d...
Multifunctional materials that balance mechanical resilience and fluid dynamic efficiency are critical in engineering applications, yet their synergistic optimization remains challenging due to inhere...
There is a common misconception among ocean scientists and policy makers that mesopelagic (200-1000 m) food webs are an unexploited "final frontier" of living marine resources. It is true that there a...
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