“…Some of the waves are reflected back to the surface as a result of these modifications, and the sensors capture these reflections. Geophysicists can determine the features of subsurface layers and formations by examining the arrival times and amplitudes of these reflected waves [ 68 ]. Seismic profiles or sections are produced by combining data from various geophones or seismometers in seismic imaging.…”
Section: Geophysical Methods In Health Sciencesmentioning
To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth’s subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.
“…Some of the waves are reflected back to the surface as a result of these modifications, and the sensors capture these reflections. Geophysicists can determine the features of subsurface layers and formations by examining the arrival times and amplitudes of these reflected waves [ 68 ]. Seismic profiles or sections are produced by combining data from various geophones or seismometers in seismic imaging.…”
Section: Geophysical Methods In Health Sciencesmentioning
To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth’s subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.
“…By a multi-parametric description of earthquake activity, Kossobokov et al (2022) provide quantitative evidence, and a better understanding of seismic processes, before and after catastrophic phase transitions (earthquakes) in the dynamics of the hierarchically organised system of lithospheric blocks and faults. This study confirms the existence of spatiotemporal patterns and different regimes of regional seismic energy release.…”
Brilliant scientific ideas coupled with quantitative modelling and laboratory experiments have determined progress in seismology and geodynamics for the last several decades. Methods of nonlinear geophysics, inverse problems, mathematical statistics, extreme theory and data analysis have improved knowledge of the structure of the Earth's lithosphere, earthquake generation, predictability, and seismic hazards.This Special Issue of Surveys in Geophysics "Lithosphere Dynamics and Earthquake Hazard Forecasting" is dedicated to the 100th anniversary of the birth of Professor Vladimir (Volodya) Keilis-Borok (1921-2013, a distinguished mathematical geophysicist. For more than 60 years, the topics of seismology, nonlinear dynamics of the lithosphere, and earthquake prediction were central in Keilis-Borok's research. His scientific contributions covered many challenging areas and problems, including
Mainshocks are often followed by increased earthquake activity (aftershocks). According to the Omori-Utsu law, the rate of aftershocks decays as a power law over time. While aftershocks typically occur in the vicinity of the mainshock, previous studies have suggested that mainshocks can also trigger earthquakes in remote locations, beyond the range of aftershocks. Here we analyze the rate of earthquakes that occurred after mega-earthquakes (with a magnitude of 7.5 or higher) and show that there is a significantly higher occurrence of mega-earthquakes that are followed by reduced activity beyond a certain distance from the epicenter compared to the expected frequency; the results are based on statistical tests we developed. However, the remote earthquake rate after the strongest earthquakes (magnitude ≥8) can also be significantly higher than the expected rate. Comparing our findings to the global Epidemic-Type Aftershock Sequence model, we find that the model does not capture the above findings, hinting at a potential missing mechanism. We suggest that the reduced earthquake rate is due to the release of global energy/tension after substantial mainshock events. This conjecture holds the potential to enhance our comprehension of the intricacies governing post-seismic activity.
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