Search for: All records

An accurate assessment of seismic hazard requires a combination of earthquake physics and statistical analysis. Because of the limitations in the investigation of the seismogenic sources and of the short temporal intervals covered by earthquake catalogs, laboratory experiments have played a crucial role in improving our understanding of earthquake phenomena. However, differences exist between acoustic emissions in the lab, events in small, regulated systems (e.g., mines) and natural seismicity. One of the most pressing issues concerns the role of mechanical parameters and how they affect seismic activity across boundary conditions and spatial-temporal scales. Here, we focus on fault friction. There is evidence inferred from geodesy, computational simulations and seismological investigations that most large faults are weak and characterized by very low static friction coefficients which are inconsistent with those of smaller faults and laboratory experiments. We support the hypothesis that static friction decreases with fault size due to the presence of fabrics, roughness, structural asperities and network geometry. We also model its scaling behavior as dependent on a few physical properties (e.g., fault fractal dimension). Conversely, dynamic coefficients are not affected by the spatial scale. Mathematical derivations are based on the hypothesis that earthquake onset results from fracture instability controlled by the extremes of fault shear strength. We validate this using a simple model for earthquake occurrence rooted in fracture mechanics, which reproduces key features of major seismicity (i.e., interevent time distribution, clustering and frequency-size relationship). 

We present a frequency/time hybrid integral-equation method for the time-dependent wave equation in two and three-dimensional spatial domains, possibly including closed cavities. 

Abstract. Accurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity. The GSTI database is developed on GitHub (https://github.com/plantphys/gsti, last access: 4 January 2026) and published to ESS-DIVE https://doi.org/10.15485/2530733, Lamour et al., 2025). It includes gas exchange data, derived photosynthetic parameters, and key leaf traits often associated with traditional gas exchange measurements such as leaf mass per area and leaf elemental composition. By providing a standardized repository for data sharing and analysis, we present a critical step towards creating hyperspectral models for predicting photosynthetic traits and associated leaf traits for terrestrial plants. 

Abstract We presentSLIDE, a pipeline that enables transient discovery in data from the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), using archival images from the Dark Energy Camera as templates for difference imaging. We apply this pipeline to the recently released Data Preview 1 (DP1; the first public release of Rubin commissioning data) and search for transients in the resulting difference images. The image subtraction, photometry extraction, and transient detection are all performed on the Rubin Science Platform. We demonstrate thatSLIDEeffectively extracts clean photometry by circumventing poor or missing LSST templates. We identified 29 previously unreported transients, 12 of which would not have been detected based on the DP1DiaObjectcatalog.SLIDEwill be especially useful for transient analysis in the early years of LSST, when template coverage will be largely incomplete or when templates may be contaminated by transients present at the time of acquisition. We present multiband light curves for a sample of known transients, along with new transient candidates identified through our search. Finally, we discuss the prospects of applying this pipeline during the main LSST survey. Our pipeline is broadly applicable and will support studies of all transients with slowly evolving phases.