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Abstract—Problems of image smoothing and segmentation are among the most important directions of processing and analysis of video information, which have much in common in their formulation, final goals, and solution methods. The similarities and differences of the problems are shown on the base of the image model using the analysis and comparison of known smoothing and segmentation algorithms.

SummaryWe present a new seismic shear wave velocity model of the upper mantle of the Antarctic Plate region, AP2024. It includes the lithosphere and underlying mantle down to 660 km depth beneath both the continental and oceanic portions of the plate. To augment the limited seismic station coverage of Antarctica, we assemble very large regional and global data sets, comprising all publicly available broadband seismic data. The model is built using 785 thousand seismograms from over 27 thousand events and 8.7 thousand stations. It is constrained by both body and Rayleigh surface waves, ensuring the dense data sampling of the entire upper mantle depth range. The tomographic inversion is global but focused on the Antarctic Plate, with the data sampling maximised in the Southern Hemisphere, with elaborate automated and manual outlier analysis and removal performed on the regional data, and with the regularisation tuned for the region. The upper mantle of the Antarctic continent exhibits a bimodal nature. The sharp boundary along the Transantarctic Mountains separates the cratonic eastern from tectonic western Antarctica and shows a shear-velocity contrast of up to 17% at ∼100 km depth. The bimodal pattern is also seen in the oceanic part of the plate, with the older oceanic lithosphere beneath the Indian sector of the Southern Ocean showing higher shear velocities. The continental lithosphere in East Antarctica shows high velocity anomalies similar to those beneath stable cratons elsewhere around the world. It is laterally heterogeneous and exhibits significant thinning in the near-coastal parts of Dronning Maud Land and Wilkes Land. A low velocity channel is observed along the southern front of the West Antarctic Rift System and is probably related to Cenozoic rifting. High seismic velocity anomalies are detected beneath the Antarctic Peninsula and are likely to indicate fragments of the recently subducted Phoenix Plate Slab. Low velocity anomalies beneath Marie Byrd Land extend into the deep upper mantle and are consistent with a deep mantle upwelling feeding West Antarctica intraplate magmatism.

SummaryThis study investigates the effectiveness of inversion methods using tsunami waveforms to analyse volcanic tsunami sources, which are a type of non-seismic tsunami source. We focused on the 2018 Anak Krakatau tsunami triggered by a volcanic eruption. This study developed a static initial sea surface displacement model based on tsunami waveform inversion with data recorded at tide gauge stations using a Gaussian-shaped sea surface displacement for the unit source. A key characteristic of our model is that all initial velocity components of the tsunami were zero. We tested 12 scenarios for accuracy to determine the most plausible sea surface displacement. The optimal displacement model reasonably reproduced the observed tsunami waveforms. The calculated water volume at the initial sea surface displacement was reasonably consistent with the total collapse volume of the Anak Krakatau eruption by magnitude. These findings suggest that our approach to developing a static source model can effectively apply to non-seismic tsunami events. Although this approach offers simplified tsunami source modeling for tsunami estimation during volcanic eruptions with complex source dynamics, further validation is required for its application to other non-seismic tsunami events.

Abstract

A comprehensive approach to the analysis of electroencephalographic (EEG) signals obtained from human brain and artificially synthesized using machine learning methods is presented. The main focus is on data preprocessing, including signal normalization and filtering, as well as application of various feature extraction methods, in particular, Fast Fourier Transform and Mel-Frequency Cepstral Coefficients. A comparative analysis of classification accuracy using logistic regression, random forest, gradient boosting, and recurrent neural network LSTM is performed. Special attention is given to the effect of filtering parameters on classification accuracy. The results show that filtering and proper tuning of model parameters significantly improve the accuracy of EEG signal classification, ensuring separation of real and synthetic EEG pools. The results and discussion may serve as a basis for further research in the field of biomedical signal analysis and processing.

Abstract

The real-time ionospheric data streams are continuously being provided by a number of International GNSS service analysis centers such as Centre National d’Etudes Spatiales (CNES), Chinese Academy of Sciences (CAS), Universitat Politècnica de Catalunya (UPC), and Wuhan University, however, the performance evaluation of these Real-Time Global Ionosphere Map (RT-GIM) products is essential. We assess the quality and consistency of these RT-GIM products from the declining phase of solar cycle 24 (year 2017) to the maximum of solar cycle 25 (year 2024) by comparing with Final GIMs provided by Center for Orbit Determination in Europe (CODE) and Jason-3 altimetry satellite. The results suggest that during the low solar activity periods (2017–2022), all the RT-GIMs perform almost similar. However, the performance of the CNES and CAS RT-GIMs strongly deteriorates as the solar cycle proceeds towards the maximum (2022–2024) with annual RMS values remains between 9 and 7.5 TECU. The external validation vs Jason-3 during this maximum period suggested that the accuracy of the UPC RTGIMs is nearly identical to the final CODE GIMs at typically 4–10 TECU in standard deviation over oceans, while performance degradations are recorded for rest of the RTGIMs exhibiting high standard deviations. Results suggest that the high RMS errors in GIMs from CNES and CAS might be related to the geomagnetic inclination misalignments followed by the map projections as both maps form single peak along geomagnetic equator during high solar activities. In addition, under the presence of a severe G4-class geomagnetic storm, CNES RT-GIMs undergoes severe accuracy degradation across all continents recording a − 20 to − 40 TECU bias offset. Meanwhile, UPC RT-GIM remain the most consistent and stable performer (both, globally and over oceans) that provides accurate global ionospheric information which is promising for their applications in real-time precise GNSS positioning.

Abstract

The Surface Dust Analyser (SUDA) is a mass spectrometer onboard the Europa Clipper mission for investigating the surface composition of the Galilean moon Europa. Atmosphereless planetary moons such as the Galilean satellites are wrapped into a ballistic dust exosphere populated by tiny samples from the moon’s surface produced by impacts of fast micrometeoroids. SUDA will measure the composition of such surface ejecta during close flybys of Europa to obtain key chemical signatures for revealing the satellite’s composition such as organic molecules and salts, history, and geological evolution. Because of their ballistic orbits, detected ejecta can be traced back to the surface with a spatial resolution roughly equal to the instantaneous altitude of the spacecraft. SUDA is a Time-Of-Flight (TOF), reflectron-type impact mass spectrometer, optimized for a high mass resolution which only weakly depends on the impact location. The instrument will measure the mass, speed, charge, elemental, molecular, and isotopic composition of impacting grains. The instrument’s small size of \(268 ~\mathrm {mm} \times 250 ~\mathrm {mm} \times 171\) \(~\mathrm {mm}\) , radiation-hard design, and rather large sensitive area of 220 cm2 matches well the challenging demands of the Clipper mission.

Abstract

The risk of earthquakes and their effects on both nature and infrastructure in seismically active regions of India require adaptable and scalable earthquake early warning (EEW) systems. Developing a robust EEW system is crucial to mitigate earthquake risks in the region, but it is a challenging task. Various institutes have attempted to develop EEW systems using different methods. Still, there is no common consensus, and issues remain with response time and reliability of disseminated information to the public. Efforts by institutions like the Indian Institute of Technology, Roorkee, have advanced EEW technologies, focusing on dense seismic sensor networks, real-time data processing algorithms, and effective dissemination mechanisms. Recent initiatives aim to improve sensor sensitivity and accuracy through fast communication systems for quicker earthquake detection. However, challenges persist in making EEW accessible and affordable, particularly in remote areas, due to the lack of a nationwide system. The National Centre for Seismology (NCS), under the Ministry of Earth Sciences (MoES), is piloting an EEW system in the NW Himalayas, which could lead to a nationwide implementation. Developing region-specific algorithms for rapid data analysis and nurturing collaboration between academic institutions, government agencies, and international partners are crucial steps. Public awareness campaigns and educational programs are essential for community resilience and timely response to earthquake alerts. Establishing a robust EEW system in India could significantly enhance earthquake risk mitigation efforts in earthquake-prone zones of the country and should be viewed within the context of a holistic risk reduction framework. EEW systems can enhance mitigation efforts, but they must be complemented by other essential measures, such as improving building resilience and promoting public awareness.

New Cornell University led-research challenges the long-standing belief that active volcanoes have large magma bodies that are expelled during eruptions and then dissipate over time as the volcanoes become dormant.

The state of Maine was hit by a rare 3.8 magnitude earthquake Monday morning, a tremor that could be felt across the New England region.

As we burn fossil fuels, the amount of carbon dioxide in Earth's atmosphere is gradually rising, and with it, the planet's average temperature. How fast the level of atmospheric carbon dioxide—and with it, the temperature—goes up matters for the ability of humans and ecosystems to adjust. A slower increase gives humans time to move away from low-lying areas and animals time to move to new habitats.

The rate of ocean warming has more than quadrupled over the past four decades, a new study has shown. Ocean temperatures were rising at about 0.06 degrees Celsius per decade in the late 1980s, but are now increasing at 0.27 degrees Celsius per decade.

SummaryDespite significant progress in paleomagnetic research over the last century, the origin, evolution, and long-term behavior of the geomagnetic field remains poorly understood. One significant open question is when and how the inner core nucleated. Since geomagnetic field behavior is intrinsically linked to the thermal evolution of the core, scientists have turned to the global paleointensity record to search for proxies for inner core nucleation. From this record, two signals have been identified as possible indicators of inner core nucleation: (1) A spike in magnetic field strength between 1.5–1.0 Ga, and (2) an initially strong, but gradually decreasing field strength that resulted in a weak dynamo in the Ediacaran. Although both these hypotheses are vastly different, they do have one common challenge hindering rigorous testing: A paucity of paleointensity data. This is especially true for the Precambrian time period for which well-preserved outcrops are scarce and weathering/alteration is nearly inescapable. Despite making up almost 90% of Earth's history, data from this super eon comprises <10% of the global paleointensity database. This lack of data for most of Earth's history represents a considerable gap in our knowledge and greatly impedes our ability to understand the origin and evolution of our planet and its magnetic field. In an effort to fill in this gap, we performed paleointensity experiments on Precambrian-aged mafic dikes from India (Malani Igneous Suite and Bastar, Dharwar, and Bundelkhand cratons) with ages ranging from ∼740 Ma to ∼2.36 Ga. To monitor thermal alteration and minimize the effects of non-ideal grain sizes, the Thellier method following the IZZI protocol was used. Successful results were obtained for samples from the Bundelkhand (∼740 Ma) and Bastar (∼1.89 Ga) cratons. The Bastar results fall in a ∼40 Myr gap in the database and corroborate field trends predicted by the Monte Carlo axial dipole moment model (MCADAM), which suggests that intensity values were moderately low (2–4 × 1022 Am2) in the middle Paleoproterozoic. The Bundelkhand result suggests that the field may have been rapidly decaying in the late Tonian to early Cryogenian.

The Arctic's "Last Ice Area" (LIA)—a vital habitat for ice-dependent species—might disappear within a decade after the central Arctic Ocean becomes ice-free in summer, which is expected to occur sometime around mid-century, a new study by McGill University researchers using a high-resolution model has found.

An interdisciplinary team of researchers from NTU Singapore, and Delft University of Technology (TU Delft), The Netherlands, has projected that if the rate of global CO2 emissions continues to increase and reaches a high emission scenario, sea levels would as a result very likely rise between 0.5 and 1.9 meters by 2100. The high end of this projection's range is 90 centimeters higher than the latest United Nations' global projection of 0.6 to 1.0 meters.

Publication date: Available online 22 January 2025

Source: Advances in Space Research

Author(s): Dieter Bilitza, Yong Ha Kim

Publication date: Available online 22 January 2025

Source: Advances in Space Research

Author(s): Marco Pietrella, Michael Pezzopane, Alessio Pignalberi, Carlo Marcocci, Massimo Viola, Emanuele Pica

Clouds, composed of tiny water droplets or ice crystals, play a vital role in regulating Earth's climate by influencing the amount of solar radiation that reaches the surface. The cloud phase significantly impacts the surface energy balance as liquid water clouds reflect more radiation than ice clouds.

Using a nearly 200-year record of lava chemistry from Kīlauea and Maunaloa, Earth scientists from the University of Hawai'i at Mānoa and colleagues revealed that Hawai'i's two most active volcanoes share a source of magma within the Hawaiian plume. Their discovery was published recently in the Journal of Petrology.

A study reveals that fire emissions in the Amazon and Cerrado are largely driven by the smoldering combustion of woody debris. This crucial discovery highlights the significant influence of fuel characteristics on fire emissions, with wide-ranging implications for global carbon cycles, air quality and biodiversity.

There's often little warning when a tsunami strikes, but a research team at USF aims to improve the forecasting of these hazardous events for communities that are most at risk.