Volcanic ash cloud detection is a crucial component of volcano monitoring and a valuable tool for investigating ash cloud dispersion, which is paramount for enhancing the safety of human settlements ...and air traffic. The latest generation of high-resolution satellite sensors (e.g., EUMETSAT MSG Spinning Enhanced Visible and InfraRed Imager, SEVIRI) provides radiometric estimates for monitoring volcanic clouds on a global scale efficiently and timely. However, these radiometric intensities are not always discriminative enough to detect volcanic ash clouds due to the spectral limitations of these instruments and the complex nature of some volcanic clouds, such as low concentration resulting in an averaged detected radiometric estimate comparable to the background. Here, we evaluate the ability of a Convolutional Neural Network (CNN) to detect and track the dispersion of volcanic ash clouds into the atmosphere, exploiting a variety of spatial and spectral intensity information mainly coming from SEVIRI Ash RGB images. We train a deep CNN model through transfer learning, and demonstrate that the trained models overcome the limitations of algorithms based solely on pixel intensity, whether traditional or machine learning, resulting in increased performance compared to other methods. We illustrate the operation of this model using the paroxysmal explosive events that occurred at Mt. Etna between 2020 and 2022.
•Combined use of machine learning and satellite data to monitor volcanic clouds.•A new Deep Convolutional Neural Network model (hybrid of U-Net and VGG16 with transfer learning) to detect volcanic clouds.•Estimated accuracy of 0.90.
Evolution on islands, together with the often extreme phenotypic changes associated with it, has attracted much interest from evolutionary biologists. However, measuring the rate of change of ...phenotypic traits of extinct animals can be challenging, in part due to the incompleteness of the fossil record. Here, we use combined molecular and fossil evidence to define the minimum and maximum rate of dwarfing in an extinct Mediterranean dwarf elephant from Puntali Cave (Sicily).1 Despite the challenges associated with recovering ancient DNA from warm climates,2 we successfully retrieved a mitogenome from a sample with an estimated age between 175,500 and 50,000 years. Our results suggest that this specific Sicilian elephant lineage evolved from one of the largest terrestrial mammals that ever lived3 to an island species weighing less than 20% of its original mass with an estimated mass reduction between 0.74 and 200.95 kg and height reduction between 0.15 and 41.49 mm per generation. We show that combining ancient DNA with paleontological and geochronological evidence can constrain the timing of phenotypic changes with greater accuracy than could be achieved using any source of evidence in isolation.
•We present mitochondrial genome data from an extinct Mediterranean dwarf elephant•Dwarf elephant DNA diverged ∼0.4 million years ago from the large-bodied ancestor•Multidisciplinary evidence places a minimum and maximum boundary on dwarfing rate•We find a size reduction between 0.74 and 200.95 kg and 0.15 and 41.49 mm per generation
Baleka et al. present mitochondrial genome data from an extinct Sicilian dwarf elephant, a small-bodied island lineage that evolved from one of the largest land mammals that ever lived. Combining the genetic data with geochronological and paleontological evidence, Baleka et al. provide an upper and lower estimate of the rate of island dwarfing.
Acromegaly is a rare disease characterized by a diagnostic delay ranging from 5 to 10 years from the symptoms' onset. The aim of this study was to develop and internally validate machine-learning ...algorithms to identify a combination of variables for the early diagnosis of acromegaly. This retrospective population-based study was conducted between 2011 and 2018 using data from the claims databases of Sicily Region, in Southern Italy. To identify combinations of potential predictors of acromegaly diagnosis, conditional and unconditional penalized multivariable logistic regression models and three machine learning algorithms (i.e., the Recursive Partitioning and Regression Tree, the Random Forest and the Support Vector Machine) were used, and their performance was evaluated. The random forest (RF) algorithm achieved the highest Area under the ROC Curve value of 0.83 (95% CI 0.79-0.87). The sensitivity in the test set, computed at the optimal threshold of predicted probabilities, ranged from 28% for the unconditional logistic regression model to 69% for the RF. Overall, the only diagnosis predictor selected by all five models and algorithms was the number of immunosuppressants-related pharmacy claims. The other predictors selected by at least two models were eventually combined in an unconditional logistic regression to develop a meta-score that achieved an acceptable discrimination accuracy (AUC = 0.71, 95% CI 0.66-0.75). Findings of this study showed that data-driven machine learning algorithms may play a role in supporting the early diagnosis of rare diseases such as acromegaly.
After 2 years of the COVID-19 pandemic, we continue to face vital challenges stemming from SARS-CoV-2 variation, causing changes in disease transmission and severity, viral adaptation to animal ...hosts, and antibody/vaccine evasion. Since the monitoring, characterization, and cataloging of viral variants are important and the existing information on this was scant for Sicily, this pilot study explored viral variants circulation on this island before and in the growth phase of the second wave of COVID-19 (September and October 2020), and in the downslope of that wave (early December 2020) through sequence analysis of 54 SARS-CoV-2-positive samples. The samples were nasopharyngeal swabs collected from Sicilian residents by a state-run one-health surveillance laboratory in Palermo. Variant characterization was based on RT-PCR amplification and sequencing of four regions of the viral genome. The B.1.177 variant was the most prevalent one, strongly predominating before the second wave and also as the wave downsized, although its relative prevalence decreased as other viral variants, particularly B.1.160, contributed to virus circulation. The occurrence of the B.1.160 variant may have been driven by the spread of that variant in continental Europe and by the relaxation of travel restrictions in the summer of 2020. No novel variants were identified. As sequencing of the entire viral genome in Sicily for the period covered here was restricted to seven deposited viral genome sequences, our results shed some light on SARS-CoV-2 variant circulation during that wave in this insular region of Italy which combines its partial insular isolation with being a major entry point for the African immigration.
Basalt is the most ubiquitous magma on Earth, erupting typically at intensities ranging from quiescently effusive to mildly explosive. The discovery of highly explosive Plinian eruptions of basaltic ...magma has therefore spurred debate about their cause. Silicic eruptions of similar style are a consequence of brittle fragmentation, as magma deformation becomes progressively more viscoelastic. Magma eventually crosses the glass transition and fragments due to a positive feedback between water exsolution, viscosity and decompression rate. In contrast to silicic eruptions, the viscosity of basaltic magmas is thought to be too low to reach conditions for brittle fragmentation. Pyroclasts from several basaltic Plinian eruptions, however, contain abundant micron-size crystals that can increase magma viscosity substantially. We therefore hypothesize that magma crystallization led to brittle fragmentation during these eruptions. Using combined oscillatory and extensional rheometry of concentrated particle-liquid suspensions that are dynamically similar to microcrystalline basaltic magma, we show that high volume fractions of particles and extension rates of about 1 s−1 or greater result in viscoelastic deformation and brittle fracture. We further show that for experimentally observed crystallization rate, basaltic magma can reach the empirical failure conditions when erupting at high discharge rates.
•Crystals not only increase viscosity but also cause a viscoselastic magma rheology.•Basaltic magma fragments brittly in the presence of crystals.•Basaltic magma during Plinian eruptions can reach to empirical failure conditions.
Altitudinal gradients are characterized by steep changes of the physical and biotic environment that present challenges to plant adaptation throughout large parts of the world. Hybrid zones may form ...where related species inhabit different neighbouring altitudes and can facilitate interspecific gene flow and potentially the breakdown of species barriers. Studies of such hybrid zones can reveal much about the genetic basis of adaptation to environmental differences stemming from changes in altitude and the maintenance of species divergence in the face of gene flow. Furthermore, owing to recombination and transgressive effects, such hybrid zones can be sources of evolutionary novelty. We document plant hybrid zones associated with altitudinal gradients and emphasize similarities and differences in their structure. We then focus on recent studies of a hybrid zone between two Senecio species that occur at high and low altitude on Mount Etna, Sicily, showing how adaptation to local environments and intrinsic selection against hybrids act to maintain it. Finally, we consider the potential of altitudinal hybrid zones for generating evolutionary novelty through adaptive introgression and hybrid speciation. Examples of homoploid hybrid species of Senecio and Pinus that originated from altitudinal hybrid zones are discussed.
New data and interpretations of the geodynamics of eastern Sicily point to deep crustal shortening taking place in the area. Reconstructions of the lithospheric system, seismicity distribution, and ...stress state in the crust indicate that deformation is expressed by a large thrust‐ramp cutting through the entire lower plate. The tectonic structure is propagating directly beneath the Mount Etna volcano, one of the few active volcanoes in Europe. Geostructural interpretation of tomographic sections allows for interpretations of the compressional structure as originating in response to trench‐parallel breakoff of the Ionian slab. Following the simple assumption that if a slab retreats, it must either be compensated or alternatively pushed by the fore‐arc mantle, we argue that the opening of a gateway in the slab has encouraged the fore‐arc mantle to flow toward the Mount Etna region. Mantle mobilization has had a twofold influence on both magmatic source mixing and the inception of underplating processes beneath the Mount Etna. A shortening prevailing over extension in the crust below the volcano seems to have a significant impact on the dynamics of the Mount Etna volcanic system, which manifested through anomalous signals over the last thousands of years. Since a tectonic inversion of previous dilatational magma pathways is expected in such a converging setting, the documented variations are believed to be consistent with a volcano experiencing a declining phase. Comparison with other extinct volcanic systems in the southern Tyrrhenian margin, lying atop a detached slab and involved in contraction, provides insights into the evolution of Mount Etna.
Key Points
The crust below the volcano is currently involved in deep‐seated contraction as result of subduction cessation and collision onset
Increasing in explosiveness, lateral eruptions and changes in lava composition are interpreted as controlled by deep‐seated crustal shortening beneath the volcano
According to the reconstructed geodynamics, anomalies in the late evolution of Mount Etna could indicate a declining stage for the volcano
Summary
This paper introduces a novel seismic isolation system based on metamaterial concepts for the reduction of ground motion‐induced vibrations in fuel storage tanks. In recent years, the advance ...of seismic metamaterials has led to various new concepts for the attenuation of seismic waves. Of particular interest for the present work is the concept of locally resonant materials, which are able to attenuate seismic waves at wavelengths much greater than the dimensions of their unit cells. Based on this concept, we propose a finite locally resonant Metafoundation, the so‐called Metafoundation, which is able to shield fuel storage tanks from earthquakes. To crystallize the ideas, the Metafoundation is designed according to the Italian standards with conservatism and optimized under the consideration of its interaction with both superstructure and ground. To accomplish this, we developed two optimization procedures that are able to compute the response of the coupled foundation‐tank system subjected to site‐specific ground motion spectra. They are carried out in the frequency domain, and both the optimal damping and the frequency parameters of the Metafoundation‐embedded resonators are evaluated. As case studies for the superstructure, we consider one slender and one broad tank characterized by different geometries and eigenproperties. Furthermore, the expected site‐specific ground motion is taken into account with filtered Gaussian white noise processes modeled with a modified Kanai‐Tajimi filter. Both the effectiveness of the optimization procedures and the resulting systems are evaluated through time history analyses with two sets of natural accelerograms corresponding to operating basis and safe shutdown earthquakes, respectively.
Volcano seismology, while its value for surveillance of an active volcano is undebatable, is a very demanding field when it comes to station deployment, maintenance, and finally interpreting the ...measurements. Most valuable in the past was the deployment of arrays of sensors to evaluate the properties of the entire wavefield in order to classify, locate, and estimate the dominant mechanism of the corresponding sources. While very beneficial, an array of seismographs is very hard to maintain in a permanent installation at an active volcano. With the advent of new instrumentation based on fiber optic technology such as Distributed Acoustic Sensing (DAS) with fiber optic cables as well as Fiber-Optic Gyroscopes (FOG) the measurement of deformation and rotation, i.e., the gradient of the wavefield is feasible. The advantage of the FOG instrumentation with respect to DAS lies in the portability and ease of deployment, which is very similar to standard deployments of traditional seismometers. During a field campaign in summer 2018 we were able to install three FOGs together with classical broadband seismometers in close proximity to the active vents of Stromboli volcano (Italy). We show that with this new six-degrees-of-freedom (6DOF) measurement we are able to analyze the wavefield composition, a property normally reserved for array(s) of seismic sensors. As a first result, we can support earlier array-derived findings that a large portion of the wavefield at Stromboli volcano is formed by SV- and SH- type waves. We also present first locations of these signals facilitating the polarization properties of the combined measurement of gyroscopes and seismometers. They emphasize the benefit of recording wavefield gradients. In addition to these array-like results, the 6DOF recordings show a clear separation of at least three distinct groups of volcanic events of which two are already known and one represents a jetting event that appears nearly invisible for classical seismometers. However, rotational motions - or more general - gradients of the wavefield experience severe distortions by local velocity fluctuations and topography significantly complicating the application of 6DOF techniques at activate volcanoes.
•First six-degree-of-freedom measurements with a network of rotational motion sensors at an active volcano.•Identification of three visually different types of explosion quakes at Stromboli.•Localization of volcanic sources using the concepts of six-component polarization analysis.•Synthetics and real data reveal complex wave field in the near field of a volcanic source.
Fault creep along the lower eastern flank of Mt. Etna volcano has been documented since the end of the 19th century and significantly contributes to the surface faulting hazard in the area. On 29 ...October 2002, during a seismic swarm related to dyke intrusions, two earthquakes caused extensive damage and surface faulting in an area between the Santa Venerina and Santa Tecla villages. On the same day after the two earthquakes, an episodic aseismic creep occurred along the Scalo Pennisi Fault close to the Santa Tecla coastline. On 8 February 2022, during another aseismic creep event along the Scalo Pennisi Fault, we observed the reopening of the pre-existing 2002 ground ruptures mostly as pure dilational fractures. We mapped the 2002 and 2022 surface ruptures, and collected data on displacement, length, and pattern of ground breaks. Ground ruptures affected structures located along the activated fault segments, including roads, walls and buildings. The 2002 surface faulting propagation can be ascribed to a sliding of the Mt. Etna eastern flank toward the SE, as also suggested by the related shallow seismicity, and InSAR and geodetic data between 2002 and 2005. For the 2022 event, differential InSAR data, acquired in both descending and ascending views, allowed us to decompose Line of Sight (LOS) displacement into horizontal and vertical components. We detect a ∼ 700 m long and ∼ 500 m wide deformation zone with a downward and eastward motion (max displacement ∼1,5 cm) consistent with a normal fault. We inverted the InSAR–detected surface deformation using a uniform-slip fault model and obtained a shallow detachment for the causative fault, located at ∼300 m depth, within the volcanic pile. This is the first in-depth study along the Scalo Pennisi Fault to suggest a shallow faulting that accommodates Mt. Etna E flank gravitational sliding.
•We mapped the 2002 and 2022 Mt. Etna E flank surface ruptures.•The hypocentres of the strongest earthquakes occurred in 2002 were within the volcanic pile.•2002 surface faulting propagation and instrumental data suggest a sliding of the E flank toward the SE.•InSAR surface deformation and inversion for the 2022 Santa Tecla aseismic creep show a rupture inside the volcanic pile.We suggest shallow faulting for the Scalo Pennisi Fault accommodating the Etna E flank gravitational sliding.
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