Two active-source, high-resolution seismic profiles were acquired in the Solfatara tuff cone in May and November 2014, with dense, wide-aperture arrays. Common Receiver Surface processing was crucial in improving signal-to-noise ratio and reflector continuity. These surveys provide, for the first time, high-resolution seismic images of the Solfatara crater, depicting a ~400 m deep asymmetrical crater filled by volcanoclastic sediments and rocks and carved within an overall non-reflective pre-eruptive basement showing features consistent with the emplacement of shallow intrusive bodies. Seismic reflection data were interpreted using the trace complex attributes and clearly display several steep and segmented collapse faults, generally having normal kinematics and dipping toward the crater centre. Fault/fracture planes are imaged as sudden amplitude drops that generate narrow low-similarity and high-dip attributes. Uprising fluids degassed by a magmatic source are the most probable cause of the small-scale amplitude reduction. Seismic data also support the interpretation of the shallow structure of the Solfatara crater as a maar. Our results provides a solid framework to constrain the near-surface geological interpretation of such a complex area, which improves our understanding of the temporal changes of the structure in relation with other geophysical and geochemical measurements.
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http://dx.doi.org/10.1038/s41598-017-17589-3 | DOI Listing |
J Acoust Soc Am
January 2025
School of Integrated Circuits, Tsinghua University, Beijing 100084, China.
In shallow water, reverberation complicates the detection of low-intensity, variable-echo moving targets, such as divers. Traditional methods often fail to distinguish these targets from reverberation, and data-driven methods are constrained by the limited data on intruding targets. This paper introduces the online robust principal component analysis and multimodal anomaly detection (ORMAD) method to address these challenges.
View Article and Find Full Text PDFJ Membr Biol
January 2025
Crystallography and Molecular Biology Division, Saha Institute of Nuclear Physics, Kolkata, India.
Inward rectifying potassium (Kir) channels play a critical role in maintaining the resting membrane potential and cellular homeostasis. The high-resolution crystal structure of homotetrameric KirBac1.1 in detergent micelles provides a snapshot of the closed state.
View Article and Find Full Text PDFMicrob Ecol
January 2025
Department of Biology, University of Rome Tor Vergata, 00133, Rome, Italy.
Posidonia oceanica retains a large amount of carbon within its belowground recalcitrant structure, the 'matte,' which is characterized by low oxygen availability and biodegradation. Fungi may play a pivotal role in carbon sequestration within the matte, even if little/no information is available. To fill this gap, we profiled fungal communities from the upper and lower layers of alive and dead matte, by using an ITS2-5.
View Article and Find Full Text PDFFood Chem
January 2025
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu 214122, China; International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, Jiangsu 214122, China.
The effect of pores distribution on the multi-scale structure, enzyme accessibility, and pasting properties of the waxy maize starch granules with the same degree of hydrolysis were examined. Increased maltogenic α-amylase (MA) dosage obviously increased the shallow pores number and the roughness, whereas extended time increased the holes depth. Despite achieving the same hydrolysis degree and specific surface area, samples with numerous shallow holes exhibited a higher mass fractal dimension, a lower, peak viscosity, final viscosity and setback.
View Article and Find Full Text PDFNeural Netw
January 2025
National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi'an, 710054, China; Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, 710054, China.
The presence of substantial similarities and redundant information within video data limits the performance of video object recognition models. To address this issue, a Global-Local Storage Enhanced video object recognition model (GSE) is proposed in this paper. Firstly, the model incorporates a two-stage dynamic multi-frame aggregation module to aggregate shallow frame features.
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