Widespread initiation, reactivation, and acceleration of landslides in the northern California Coast Ranges due to extreme rainfall

Episodically to continuously active slow‐moving landslides are driven by precipitation. Climate change, which is altering both the frequency and magnitude of precipitation worldwide, is therefore predicted to have a major impact on landslides. Here we examine the behavior of hundreds of slow‐moving landslides in northern California in response to large changes in annual precipitation that occurred between 2016 and 2018. We quantify the landslide displacement using repeat‐pass radar interferometry and pixel offset tracking techniques on a novel dataset from the airborne NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar. We found that 312 landslides were moving due to extreme rainfall during 2017, compared to 119 during 2016, which was the final year of a historic multi‐year drought. However, with a return to below‐average rainfall in 2018, only 146 landslides remained in motion. The increased number of landslides during 2017 was primarily accommodated by landslides that were smaller than the landslides that remained active between 2016 and 2018. Furthermore, by examining a subset of 51 landslides, we found that 49 had increased velocities during 2017 when compared to 2016. Our results show that slow‐moving landslides are sensitive to large changes in annual precipitation, particularly the smaller and thinner landslides that likely experience larger basal pore‐water pressure changes. Based on climate model predictions for the next century in California, which include increases in average annual precipitation and increases in the frequency of dry‐to‐wet extremes, we hypothesize that there will be an overall increase in landslide activity

A model-based circular binary segmentation algorithm for the analysis of array CGH data

<p>Abstract</p> <p>Background</p> <p>Circular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-<it>t </it>test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent implementation utilizing a hybrid method and early stopping rules (hybrid CBS) to improve the performance in speed was subsequently proposed. However, a time analysis revealed that a major portion of computation time of the hybrid CBS was still spent on permutation. In addition, what the hybrid method provides is an approximation of the significance upper bound or lower bound, not an approximation of the significance of change-points itself.</p> <p>Results</p> <p>We developed a novel model-based algorithm, extreme-value based CBS (eCBS), which limits permutations and provides robust results without loss of accuracy. Thousands of aCGH data under null hypothesis were simulated in advance based on a variety of non-normal assumptions, and the corresponding maximal-<it>t </it>distribution was modeled by the Generalized Extreme Value (GEV) distribution. The modeling results, which associate characteristics of aCGH data to the GEV parameters, constitute lookup tables (eXtreme model). Using the eXtreme model, the significance of change-points could be evaluated in a constant time complexity through a table lookup process.</p> <p>Conclusions</p> <p>A novel algorithm, eCBS, was developed in this study. The current implementation of eCBS consistently outperforms the hybrid CBS 4× to 20× in computation time without loss of accuracy. Source codes, supplementary materials, supplementary figures, and supplementary tables can be found at <url>http://ntumaps.cgm.ntu.edu.tw/eCBSsupplementary</url>.</p

A Mechanistic Model and Therapeutic Interventions for COVID-19 Involving a RAS-Mediated Bradykinin Storm

Neither the disease mechanism nor treatments for COVID-19 are currently known. Here, we present a novel molecular mechanism for COVID-19 that provides therapeutic intervention points that can be addressed with existing FDA-approved pharmaceuticals. The entry point for the virus is ACE2, which is a component of the counteracting hypotensive axis of RAS. Bradykinin is a potent part of the vasopressor system that induces hypotension and vasodilation and is degraded by ACE and enhanced by the angiotensin1-9 produced by ACE2. Here, we perform a new analysis on gene expression data from cells in bronchoalveolar lavage fluid (BALF) from COVID-19 patients that were used to sequence the virus. Comparison with BALF from controls identifies a critical imbalance in RAS represented by decreased expression of ACE in combination with increases in ACE2, renin, angiotensin, key RAS receptors, kinogen and many kallikrein enzymes that activate it, and both bradykinin receptors. This very atypical pattern of the RAS is predicted to elevate bradykinin levels in multiple tissues and systems that will likely cause increases in vascular dilation, vascular permeability and hypotension. These bradykinin-driven outcomes explain many of the symptoms being observed in COVID-19

Crustal Deformation During Co- and Postseismic Phases of the Earthquake Cycle Inferred from Geodetic and Seismic Data

The work presented in my dissertation focuses on the crustal deformation during the co- and postseismic periods in earthquake cycles. I use geodetic and seismic data to constrain and better understand the behavior of the earthquake source during the coseismic period. For the postseismic period, I use geodetic data to observe the surface displacements from centimeter-scale to millimeter-scale from an Mw 7.9 and Mw 6.9 event, respectively. I model different mechanisms to explain the postseismic deformation and to further constrain the crustal and upper mantle rheology.For the coseismic earthquake source study, I explore the source of the 2010 Mw 6.3 Jia-Shian, Taiwan earthquake. I develop finite-source models using a combination of seismic data (strong motion and broadband) and geodetic data (InSAR and GPS) to understand the rupture process and slip distribution of this event. The main shock is a thrust event with a small left-lateral component. Both the main shock and aftershocks are located in a transition zone where the depth of seismicity and an inferred regional basal detachment increases from central to southern Taiwan. The depth of this event and the orientation of its compressional axis suggest that this event involves the reactivation of a deep and weak pre-existing NW-SE geological structure.The 1989 Mw 6.9 Loma Prieta earthquake provides the first opportunity since the 1906 San Francisco (Mw 7.9) earthquake to study postseismic relaxation processes and estimate rheological parameters in the region with modern space geodetic tools. The first five years postseismic displacements can be interpreted to be due to aseismic right-oblique fault slip on or near the coseismic rupture, as well as thrusting up-dip of the rupture within the Foothills thrust belt. However, continuing transient surface displacements (≤ 5 mm/yr) until 2002 revealed by PSInSAR and GPS in the northern Santa Cruz Mountains may indicate a longer-term postseismic deformation. I model the viscoelastic relaxation of the lower crust and upper mantle following the Loma Prieta earthquake to explain the surface displacement. A 14-km-thick lower crust (16 - 30 km depth) viscosity of &gt; 1019 Pa s and an upper mantle viscosity of ~1018 Pa s best explain the geodetic data. The weak upper mantle viscosity in this area is in good agreement with upper mantle rheology in southern California (0.46 - 5 × 1019 Pa s) using a similar approach from studying the postseismic deformation following the 1999 (Mw 7.1) Hector Mine earthquake.Periods of accelerated postseismic deformation following large earthquakes reflect the response of the Earth's lithosphere to sudden coseismic stress changes. I investigate postseismic displacements following the 2008 Wenchuan (Mw 7.9), China earthquake in eastern Tibet and probe the differences in rheological properties across the edge of the Tibetan Plateau. Based on nearly two years of GPS and InSAR measurements, I find that the shallow afterslip on the Beichuan Fault can explain the near-field displacements, and the far-field displacements can be explained by a viscoelastic lower crust beneath Tibet with an initial effective viscosity of 4.4 × 1017 Pa s and a long-term viscosity of 1018 Pa s. On the other hand, the Sichuan Basin block has a high-viscosity upper mantle (&gt; 1020 Pa s) underlying an elastic 35-km-thick crust. The inferred strong contrast in lithospheric rheologies between the Tibetan Plateau and the Sichuan Basin is consistent with models of ductile lower crustal flow that predict maximum topographic gradients across the Plateau margins where viscosity differences are greatest.With additional 6-year-long continuous GPS measurements deployed in the eastern Tibetan Plateau and the Sichuan Basin, viscoelastic relaxation models with the same geometry setups suggests Tibetan lower crust with an initial effective viscosity of 9 × 1017 Pa s and steady-state viscosity of 1019 Pa s. I also use the laboratory experiments derived power law flow model to fit the postseismic deformation. The viscosity estimated from this model varies with material parameters (e.g. grain size, water content, etc.) as well as environmental parameters (temperature, pressure, background strain rate, etc.). The diffusion creep refers to the power law flow mainly controlled by the mineral grain size, and the dislocation creep refers to it mainly controlled by the background stress level.For a diffusion creep type of power law flow, a Tibetan crust composed of wet feldspar (water content = 1000 H/106Si; grain size = 1 - 4 mm) and upper mantle composed of wet olivine (water content = 200 H/106Si; grain size = ~2 mm) can predict the 6-year-long poseismic time series well. This result roughly agrees with rock mechanics laboratory experiments.The channel flow model predicts the plateau margins are steepest where the viscosity of the surrounding blocks are highest. The low viscosity in the Tibetan lower crust and the contrasting rheology across the plateau margin derived from postseismic deformation are consistent with the channel flow model

Revealing Crustal Deformation and Strain Rate in Taiwan Using InSAR and GNSS

Interseismic deformation describes the gradual accumulation of crustal strain within the tectonic plate and along the plate boundaries before the sudden release as earthquakes. In this study, we use 5 years of high spatial and temporal geodetic measurements, including Global Navigation Satellite System and Interferometric Synthetic Aperture Radar to monitor 3-dimension interseismic crustal deformation and horizontal strain rate in Taiwan. We find significant deformation (strain rate >8 urn:x-wiley:00948276:media:grl65006:grl65006-math-0001 10−6 yr−1) along the plate boundary between the Philippine Sea and the Eurasian Plates in east Taiwan. The high strain rate in the southern part of the Western Foothills is distributed along a few major fault systems, which reveals the geometry of the deformation front in west Taiwan. Our results help identify active faults in southwest and north Taiwan that were not identified before. These findings can be insightful in informing future seismic hazard models.https://doi.org/10.1029/2022GL10130