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Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales. Theoretically grounded bottom-up models are appealing due to their thermodynamic consistency with the underlying all-atom models. In this direction, machine learning approaches hold great promise to fitting complex many-body data. However, training models may require collection of large amounts of expensive data. Moreover, quantifying trained model accuracy is challenging, especially in cases of non-trivial free energy configurations, where training data may be sparse. We demonstrate a path towards uncertainty-aware models of coarse grained free energy surfaces. Specifically, we show that principled Bayesian model uncertainty allows for efficient data collection through an on-the-fly active learning framework and opens the possibility of adaptive transfer of models across different chemical systems. Uncertainties also characterize models’ accuracy of free energy predictions, even when training is performed only on forces. This work helps pave the way towards efficient autonomous training of reliable and uncertainty aware many-body machine learned coarse grain models.

Flat hydrodynamic shells likely represent an evolutionary trade-off between adaptation to an aquatic lifestyle and the instability of more rounded shells, thought beneficial for self-righting. Trade-offs often result in compromises, this is particularly true when freshwater turtles, with flatter shells, must self-right to avoid the negative effects of inverting. These turtles, theoretically, invest more biomechanical effort to achieve successful and timely self-righting when compared to turtles with rounded carapaces. This increase in effort places these hatchlings in a precarious position; prone to inversion and predation and with shells seemingly maladapted to the act of self-righting. Here, we examine hatchling self-righting performance in three morphologically distinct freshwater turtle species (Apalone spinifera,Chelydra serpentinaandTrachemys scripta scripta) that inhabit similar environmental niches. We demonstrate that these hatchlings were capable of rapid self-righting and used considerably less biomechanical effort relative to adult turtles. Despite differences in shell morphology the energetic efficiency of self-righting remained remarkably low and uniform between the three species. Our results confound theoretical predictions of self-righting ability based on shell shape metrics and indicate that other morphological characteristics like neck or tail morphology and shell material properties must be considered to better understand the biomechanical nuances of Testudine self-righting.

National parks and other protected areas are important for preserving landscapes and biodiversity worldwide. An essential component of the mission of the United States (U.S.) National Park Service (NPS) requires understanding and maintaining accurate inventories of species on protected lands. We describe a new, national-scale synthesis of amphibian species occurrence in the NPS system. Many park units have a list of amphibian species observed within their borders compiled from various sources and available publicly through the NPSpecies platform. However, many of the observations in NPSpecies remain unverified and the lists are often outdated. We updated the amphibian dataset for each park unit by collating old and new park-level records and had them verified by regional experts. The new dataset contains occurrence records for 292 of the 424 NPS units and includes updated taxonomy, international and state conservation rankings, hyperlinks to a supporting reference for each record, specific notes, and related fields which can be used to better understand and manage amphibian biodiversity within a single park or group of parks.

Snow and ice topography impact and are impacted by fluxes of mass, energy, and momentum in Arctic sea ice. We measured the topography on approximately a 0.5 km²drifting parcel of Arctic sea ice on 42 separate days from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS). These data are aligned into an ice-fixed, lagrangian reference frame such that topographic changes (e.g., snow accumulation) can be observed for time periods of up to six months. Usingin-situmeasurements, we have validated the vertical accuracy of the alignment to ± 0.011 m. This data collection and processing workflow is the culmination of several prior measurement campaigns and may be generally applied for repeat TLS measurements on drifting sea ice. We present a description of the data, a software package written to process and align these data, and the philosophy of the data processing. These data can be used to investigate snow accumulation and redistribution, ice dynamics, surface roughness, and they can provide valuable context for co-located measurements.

A highly NIR-absorptive organic dye forms monomers when kinetically trapped in a polymer matrix, but upon thermal annealing, aggregation causes changes in excited-state processes, which are assayed via in situ transient absorption.

Subwavelength diffractive optics known as meta-optics have demonstrated the potential to significantly miniaturize imaging systems. However, despite impressive demonstrations, most meta-optical imaging systems suffer from strong chromatic aberrations, limiting their utilities. Here, we employ inverse-design to create broadband meta-optics operating in the long-wave infrared (LWIR) regime (8-12μm). Via a deep-learning assisted multi-scale differentiable framework that links meta-atoms to the phase, we maximize the wavelength-averaged volume under the modulation transfer function (MTF) surface of the meta-optics. Our design framework merges local phase-engineering via meta-atoms and global engineering of the scatterer within a single pipeline. We corroborate our design by fabricating and experimentally characterizing all-silicon LWIR meta-optics. Our engineered meta-optic is complemented by a simple computational backend that dramatically improves the quality of the captured image. We experimentally demonstrate a six-fold improvement of the wavelength-averaged Strehl ratio over the traditional hyperboloid metalens for broadband imaging.

Plant diversity effects on community productivity often increase over time. Whether the strengthening of diversity effects is caused by temporal shifts in species-level overyielding (i.e., higher species-level productivity in diverse communities compared with monocultures) remains unclear. Here, using data from 65 grassland and forest biodiversity experiments, we show that the temporal strength of diversity effects at the community scale is underpinned by temporal changes in the species that yield. These temporal trends of species-level overyielding are shaped by plant ecological strategies, which can be quantitatively delimited by functional traits. In grasslands, the temporal strengthening of biodiversity effects on community productivity was associated with increasing biomass overyielding of resource-conservative species increasing over time, and with overyielding of species characterized by fast resource acquisition either decreasing or increasing. In forests, temporal trends in species overyielding differ when considering above- versus belowground resource acquisition strategies. Overyielding in stem growth decreased for species with high light capture capacity but increased for those with high soil resource acquisition capacity. Our results imply that a diversity of species with different, and potentially complementary, ecological strategies is beneficial for maintaining community productivity over time in both grassland and forest ecosystems.

The science of volcanology advances disproportionately during exceptionally large or well-observed eruptions. The 2018 eruption of Kīlauea Volcano (Hawai‘i) was its most impactful in centuries, involving an outpouring of more than one cubic kilometer of basalt, a magnitude 7 flank earthquake, and the volcano's largest summit collapse since at least the nineteenth century. Eruptive activity was documented in detail, yielding new insights into large caldera-rift eruptions; the geometry of a shallow magma storage-transport system and its interaction with rift zone tectonics; mechanisms of basaltic tephra-producing explosions; caldera collapse mechanics; and the dynamics of fissure eruptions and high-volume lava flows. Insights are broadly applicable to a range of volcanic systems and should reduce risk from future eruptions. Multidisciplinary collaboration will be required to fully leverage the diversity of monitoring data to address many of the most important outstanding questions. ▪ Unprecedented observations of a caldera collapse and coupled rift zone eruption yield new opportunities for advancing volcano science. ▪ Magma flow to a low-elevation rift zone vent triggered quasi-periodic step-like collapse of a summit caldera, which pressurized the magma system and sustained the eruption. ▪ Kīlauea's magmatic-tectonic system is tightly interconnected over tens of kilometers, with complex feedback mechanisms and interrelated hazards over widely varying time scales. ▪ The eruption revealed magma stored in diverse locations, volumes, and compositions, not only beneath the summit but also within the volcano's most active rift zone.

Expected final online publication date for the Annual Review of Earth and Planetary Sciences, Volume 52 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.