Microplastic pollution, stemming from plastic degradation or direct release, presents a persistent threat to marine environments. While global concern grows, data from the Indian Ocean, especially on ...
Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to repository-level software engineering. In emerging agent...
The increase in pharmaceutical residues and environmental contaminants, including heavy metals and biotoxins, in coastal ecosystems represents a critical threat to global health. Mussels (Mytilus spp....
Coral reefs are vital ecosystems that support marine biodiversity and provide essential services to coastal economies. However, they are increasingly threatened by different contaminants, such as poly...
Although Quintero-Puchuncaví Bay, Chile, is a coastal area historically known to be subject to multiple industrial pressures, few studies have focused on the associated risks to marine ecosystems and,...
The development of sustainable, bioderived, conductive ionic gels for low-temperature applications remains a critical challenge, particularly in eliminating reliance on ethylene glycol-based antifreez...
The increasing accumulation of low-density polyethylene (LDPE) waste in the environment poses a growing threat to natural ecosystems due to its resistance to degradation. In this study, bacterial isol...
This review examines the growing concern over persistent, non-biodegradable micro- and nanopollutants in marine environments, driven largely by industrial activities, particularly manufacturing proces...
The poles represent Earth's most climate-sensitive biomes, where microbial communities and viruses drive fundamental ecological processes. Within these extreme environments, giant viruses of the phylu...
As immunotherapies become standard cancer treatments, it is increasingly important to identify a patient's immune profile, which encompasses the activity of immune cells within the tumor microenvironm...
This paper introduces \emph{biased mean regression}, estimating the \emph{biased mean}, i.e., $\mathbb{E}[Y] + x$, where $x \in \mathbb{R}$. The approach addresses a fundamental statistical problem th...
Accurate 3D understanding of human hands and objects during manipulation remains a significant challenge for egocentric computer vision. Existing hand-object interaction datasets are predominantly cap...
Chain-of-Thought (CoT) monitoring, in which automated systems monitor the CoT of an LLM, is a promising approach for effectively overseeing AI systems. However, the extent to which a model's CoT helps...
YouTube Shorts have become central to news consumption on the platform, yet research on how geopolitical events are represented in this format remains limited. To address this gap, we present a multim...
Environmental contamination by current-use pesticides (CUPs) has become a global concern due to their widespread use. However, very few studies have examined the spatiotemporal dynamics and multiclass...
We propose a cross-fitted debiasing device for policy learning from offline data. A key consequence of the resulting learning principle is $\sqrt N$ regret even for policy classes with complexity grea...
Current autonomous AI agents, driven primarily by Large Language Models (LLMs), operate in a state of cognitive weightlessness: they process information without an intrinsic sense of network topology,...
This paper introduces a new hybrid framework that combines Reinforcement Learning (RL) and Large Language Models (LLMs) to improve robotic manipulation tasks. By utilizing RL for accurate low-level co...
Robotic mapping systems typically approach building metric-semantic scene representations from the robot's own sensors and cameras. However, these "first person" maps inherit the robot's own limitatio...
🌊
