Signs of eruption decoded with petrology
Related Articles
Escalation of caldera unrest indicated by increasing emission of isotopically light sulfur
Calderas are depressions formed by some of the largest volcanic eruptions. Their long-lived inter-eruptive periods are occasionally interrupted by phases of unrest, in which escalating seismicity, ground deformation and gas emissions raise concerns of potential volcano reawakening. However, interpretation of such physico-chemical signals is complicated by few examples of monitored unrest that culminated into eruption and by our fragmentary understanding of the drivers and timescales of caldera reactivation. Here we show that multi-decadal gas observations at the restless Campi Flegrei caldera in Italy record an unprecedented increase in isotopically light sulfur release from fumaroles since 2018. We then use hydrothermal gas equilibria and numerical simulations of magmatic degassing to propose that such a change in sulfur emissions results from decompression-driven degassing of mafic magma at ≥6 km depth, along with some extent of sulfur remobilization from hydrothermal minerals. Examination of a global dataset indicates that, despite the diversity in eruptive behaviour and tectonic setting, increasing sulfur output may be a common process during unrest escalation at calderas generally. Hence, our observations and models of sulfur behaviour may inform interpretations of unrest and hazard assessment at reawakening calderas and hydrothermal active volcanoes worldwide.
Constructing future behavior in the hippocampal formation through composition and replay
The hippocampus is critical for memory, imagination and constructive reasoning. Recent models have suggested that its neuronal responses can be well explained by state spaces that model the transitions between experiences. Here we use simulations and hippocampal recordings to reconcile these views. We show that if state spaces are constructed compositionally from existing building blocks, or primitives, hippocampal responses can be interpreted as compositional memories, binding these primitives together. Critically, this enables agents to behave optimally in new environments with no new learning, inferring behavior directly from the composition. We predict a role for hippocampal replay in building and consolidating these compositional memories. We test these predictions in two datasets by showing that replay events from newly discovered landmarks induce and strengthen new remote firing fields. When the landmark is moved, replay builds a new firing field at the same vector to the new location. Together, these findings provide a framework for reasoning about compositional memories and demonstrate that such memories are formed in hippocampal replay.
On-patient medical record and mRNA therapeutics using intradermal microneedles
Medical interventions often require timed series of doses, thus necessitating accurate medical record-keeping. In many global settings, these records are unreliable or unavailable at the point of care, leading to less effective treatments or disease prevention. Here we present an invisible-to-the-naked-eye on-patient medical record-keeping technology that accurately stores medical information in the patient skin as part of microneedles that are used for intradermal therapeutics. We optimize the microneedle design for both a reliable delivery of messenger RNA (mRNA) therapeutics and the near-infrared fluorescent microparticles that encode the on-patient medical record-keeping. Deep learning-based image processing enables encoding and decoding of the information with excellent temporal and spatial robustness. Long-term studies in a swine model demonstrate the safety, efficacy and reliability of this approach for the co-delivery of on-patient medical record-keeping and the mRNA vaccine encoding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This technology could help healthcare workers make informed decisions in circumstances where reliable record-keeping is unavailable, thus contributing to global healthcare equity.
MARBLE: interpretable representations of neural population dynamics using geometric deep learning
The dynamics of neuron populations commonly evolve on low-dimensional manifolds. Thus, we need methods that learn the dynamical processes over neural manifolds to infer interpretable and consistent latent representations. We introduce a representation learning method, MARBLE, which decomposes on-manifold dynamics into local flow fields and maps them into a common latent space using unsupervised geometric deep learning. In simulated nonlinear dynamical systems, recurrent neural networks and experimental single-neuron recordings from primates and rodents, we discover emergent low-dimensional latent representations that parametrize high-dimensional neural dynamics during gain modulation, decision-making and changes in the internal state. These representations are consistent across neural networks and animals, enabling the robust comparison of cognitive computations. Extensive benchmarking demonstrates state-of-the-art within- and across-animal decoding accuracy of MARBLE compared to current representation learning approaches, with minimal user input. Our results suggest that a manifold structure provides a powerful inductive bias to develop decoding algorithms and assimilate data across experiments.
Past hydroclimate extremes in Europe driven by Atlantic jet stream and recurrent weather patterns
The jet stream over the Atlantic–European sector is relevant for weather and climate in Europe. It generates temperature extremes and steers moisture and flood-propelling weather systems to Europe or facilitates the development of atmospheric blocks, which can lead to drought. Ongoing climate change may alter the jet characteristics, affecting weather extremes. However, little is known about the past interannual-to-decadal variability of the jet stream. Here we analyse the strength, tilt and latitude of the Atlantic–European jet from 1421 to 2023 in an ensemble of monthly and daily reconstructions of atmospheric fields. We compare the variability of these jet indices with blocking frequency and cyclonic activity data and with drought and flood reconstructions in Europe. Summer drought is enhanced in Central Europe in periods with a poleward-shifted jet. An equatorward-shifted jet associated with decreased blocking leads to frequent floods in Western Europe and the Alps, particularly in winter. Recurrent weather patterns causing floods often characterize an entire season, such that an association between peak discharge and jet indices is seen on seasonal or even annual scales. Jet strength and tilt are significantly influenced by volcanic eruptions. Our 600-year perspective shows that recent changes in the jet indices are within the past variability and cannot be drivers of increasing flood and drought frequency.
Responses