ALBERT

Description: A massive landslide often causes long-lasting instability dynamics that need to be analyzed in detail for risk management and mitigation. Multiple satellite remote sensing observations, in-situ measurements, and geophysical approaches have been jointly implemented to monitor and interpret the life cycle of landslides and their failure mechanisms from various perspectives. In this work, we propose a framework where satellite optical and synthetic aperture radar (SAR) remote sensing techniques are combined with feature extractions using independent component analysis (ICA) and a mathematical relaxation model to assess the complete four-dimensional (4D) spatiotemporal patterns of post-failure slope evolution. The large, deep-seated Aniangzhai landslide in Southwest China that occurred on 17 June 2020 is comprehensively analyzed and characterized for its post-failure mechanism. Time series of Planet high-resolution optical images are first explored to derive the large horizontal motions for the first six months after the failure. Spatiotemporal dynamics of line-of-sight (LOS) displacement in the landslide body are then derived between November 2020 and February 2022 by combining 40 TerraSAR-X (TSX) High-resolution Spotlight (HS) images and 76 medium-resolution Sentinel-1 (S1) SAR datasets using Multi-temporal InSAR (MTI) method. The InSAR-derived results are subsequently analyzed with ICA to find common deformation components of points between optical and MTI results, indicating the same temporal evolution in the deformation pattern. Finally, the complete 4D deformation field for the whole post-failure period is modeled using a decaying exponential model representing stress relaxation after the failure by integrating multiple remote sensing datasets. Cross-correlation analysis of Planet imagery shows a decaying exponential pattern of post-failure displacements with an approximately 94% reduction in the deformation rate after six months with respect to the co-failure event. MTI analysis suggests a maximum LOS displacement rate of approximately 30 cm/year over the main failure body from November 2020 to February 2022; while the high-resolution TSX datasets show irreplaceable advantages in choosing the number of measurement points in MTI analysis with the number of measurement points being five times larger than those obtained by S1 datasets. The ICA analysis reveals three main types of kinematic patterns in the temporal evolution of post-failure deformation in MTI results, the dominant one being an exponential declining pattern similar to the results from Planet observations. Integrated 4D deformation modeling suggests that the most significant post-failure displacement mainly occurred toward the west, amounting to 28 m during the entire post-failure acquisitions from June 2020 until February 2022. Additionally, maximum displacements of 17 m and 19 m occurred in this period toward the north and downward, respectively.

Description: Interferometric Synthetic Aperture Radar (InSAR) is a highly effective and widely used approach for monitoring large-scale ground deformation. The precise and timely prediction of deformation holds significant importance in mitigating and preventing geological hazards, particularly considering the long revisit cycle of satellites and the considerable time required for data processing. In this study, we propose a strategy that predicts spatiotemporal InSAR time series based on Independent Component Analysis (ICA) and the Long Short-Term Memory (LSTM) machine learning model. Unlike traditional methods that rely on physical or statistical models, the proposed strategy leverages the power of ICA and LSTM to achieve accurate predictions without such dependencies. ICA is employed to decompose and capture the InSAR displacement signals of interest caused by various natural or anthropogenic processes and to characterize each individual signal. The spatiotemporal unsupervised K-mean cluster method is then applied to partition large-scale deformation fields into homogeneous subregions, considering the spatial variations and temporal nonlinearities of time series. This process facilitates the refinement of the model, thereby enhancing the accuracy of large-scale predictions. The neural network models are then individually constructed for each cluster, and the optimal parameters are determined through a grid search strategy. Subsequently, the proposed framework is implemented and assessed using two datasets featuring distinct deformation patterns: Case I involves land subsidence in Willcox Basin, USA, while Case II focuses on post-seismic deformation following the 12 November 2017 Mw 7.3 Sarpol-e Zahab earthquake. The results demonstrate that our proposed ICA-assisted LSTM outperforms the original LSTM model on large-scale deformation prediction, with the average prediction accuracy for one-step prediction (12 days in our case) being improved by 34% and 17% for cases I and II, respectively. Furthermore, we perform iterative predictions on the spatiotemporal InSAR measurements with varying temporal characteristics for the subsequent five steps using Sentinel-1 data and evaluate its performance and limitations. The successful prediction of land subsidence and post-seismic deformation provides further evidence that the proposed prediction strategy can be effectively employed in monitoring other large-scale geohazards characterized by prolonged and gradual deformation. This capability enables expedited decision-making and timely implementation of risk mitigation measures.

Description: Multi-temporal interferometric synthetic aperture radar (MT-InSAR) is a widely used technique for monitoring subtle ground instabilities, with a precision ranging from centimeters to millimeters. Traditional MT-InSAR analysis often employs low-pass temporal filtering to suppress stochastic noise and extract deformation features from measurements. However, these approaches may hinder the detection and estimation of transient slope instabilities triggered by external factors. In this study, we propose a methodology for characterizing transient deformation of reservoir bank slopes under the coupling effects of rainfall and reservoir water level (RWL) changes. Following MT-InSAR analysis, slope kinematics is analyzed using time series decomposition and independent component analysis (ICA) to separate trends from seasonality. Although triggers of slope instability exhibit similar periods of increase and decrease, they are not entirely synchronized. Therefore, the seasonal components of surface deformation along with environmental triggers are analyzed using a wavelet transform to determine the time-lag between them. This helps define an effective priori search windows for constraining transient behaviors in landslide kinematics. A constrained least-squares optimization is finally applied to extract step-like kinematics features. Our methodology’s effectiveness is evaluated using a dataset comprising 102 TerraSAR-X (TSX) images in High-resolution Spotlight (HS) mode, 197 Sentinel-1 images, 10 ALOS-1 and 12 ALOS-2 Stripmap images, collected from 2006 to 2022 across Badong County, located along the Yangtze River. After the successful validation against in-situ measurements and comparison with conventional post-processing strategies, we apply our method to generate a map of hazardous sliding areas and evaluate the regional-scale slope instability of slow-moving landslides across Badong County in the Three Gorges Area (TGA).

Description: Author(s): Y. Y. Peng, M. Hashimoto, M. Moretti Sala, A. Amorese, N. B. Brookes, G. Dellea, W.-S. Lee, M. Minola, T. Schmitt, Y. Yoshida, K.-J. Zhou, H. Eisaki, T. P. Devereaux, Z.-X. Shen, L. Braicovich, and G. Ghiringhelli Magnetic excitations in the optimally doped high- T c superconductor Bi 1.5 Pb 0.55 Sr 1.6 La 0.4 CuO 6 + δ (OP-Bi2201, T c ≃ 34 K) are investigated by Cu L 3 edge resonant inelastic x-ray scattering (RIXS), below and above the pseudogap opening temperature. At both temperatures the broad spectral distribution dispe… [Phys. Rev. B 92, 064517] Published Mon Aug 24, 2015

Description: A recent study by Shannon et al. (1) proposes a Central Asian domestication origin of dogs, based upon the finding that Central Asia had the lowest short-range linkage disequilibrium (LD) among village dogs across the globe. A reanalysis of their data, however, suggests that these conclusions may require revision. First,...

Description: Author(s): T. Zou, H. B. Cao, G. Q. Liu, J. Peng, M. Gottschalk, M. Zhu, Y. Zhao, J. B. Leão, W. Tian, Z. Q. Mao, and X. Ke We report the hydrostatic pressure-induced electronic and magnetic phase transitions in a Mott insulator, a bilayer ruthenate C a 3 ( R u 0.97 T i 0.03 ) 2 O 7 , via electronic transport and single crystal neutron diffraction measurements. The system undergoes an insulator-metal transition at a very small hydrost… [Phys. Rev. B 94, 041115(R)] Published Wed Jul 27, 2016

Description: Many large paleo-lakes in North China were formed after the Triassic Era. Seawater incursion events (SWIEs) in these lakes have been extensively discussed in the literature, yet lack reliable methodology and solid evidence, which are essential for reconstructing and confirming SWIEs. The present study employs specific marine biological markers (24-n-propyl and 24-isopropyl cholestanes) to trace SWIEs in a dated core taken from the Songliao Basin (SLB). Two SWIEs were identified. The first SWIE from 91.37 to 89.00 Ma, was continuous and variable but not strong, while the second SWIE from 84.72 to 83.72 Ma was episodic and strong. SWIEs caused high total organic carbon (TOC) and negative δ13Corg values in the sediments, which were interpreted as an indication of high productivity in the lake, due to the enhancement of nutrient supplies as well as high levels of aqueous CO2, due to the mixing of alkaline seawater and acidic lake water. The SWIEs in SLB were controlled by regional tectonic activity and eustatic variation. Movement direction changes of the Izanagi/Kula Plate in 90 Ma and 84 Ma created faults and triggered SWIEs. A high sea level, from 90 to 84 Ma, also facilitated the occurrence of SWIEs in SLB. Scientific Reports 5 doi: 10.1038/srep09508

Description: Mitochondrial respiratory chain (RC) disease therapies directed at intra-mitochondrial pathology are largely ineffective. Recognizing that RC dysfunction invokes pronounced extra-mitochondrial transcriptional adaptations, particularly involving dysregulated translation, we hypothesized that translational dysregulation is itself contributing to the pathophysiology of RC disease. Here, we investigated the activities, and effects from direct inhibition, of a central translational regulator (mTORC1) and its downstream biological processes in diverse genetic and pharmacological models of RC disease. Our data identify novel mechanisms underlying the cellular pathogenesis of RC dysfunction, including the combined induction of proteotoxic stress, the ER stress response and autophagy. mTORC1 inhibition with rapamycin partially ameliorated renal disease in B6. Pdss2 kd/kd mice with complexes I–III/II–III deficiencies, improved viability and mitochondrial physiology in gas-1(fc21) nematodes with complex I deficiency, and rescued viability across a variety of RC-inhibited human cells. Even more effective was probucol, a PPAR-activating anti-lipid drug that we show also inhibits mTORC1. However, directly inhibiting mTORC1-regulated downstream activities yielded the most pronounced and sustained benefit. Partial inhibition of translation by cycloheximide, or of autophagy by lithium chloride, rescued viability, preserved cellular respiratory capacity and induced mitochondrial translation and biogenesis. Cycloheximide also ameliorated proteotoxic stress via a uniquely selective reduction of cytosolic protein translation. RNAseq-based transcriptome profiling of treatment effects in gas-1(fc21) mutants provide further evidence that these therapies effectively restored altered translation and autophagy pathways toward that of wild-type animals. Overall, partially inhibiting cytosolic translation and autophagy offer novel treatment strategies to improve health across the diverse array of human diseases whose pathogenesis involves RC dysfunction.

Description: PAX7 is a required target for microRNA-206-induced differentiation of fusion-negative rhabdomyosarcoma Cell Death and Disease 7, e2256 (June 2016). doi:10.1038/cddis.2016.159 Authors: J A Hanna, M R Garcia, J C Go, D Finkelstein, K Kodali, V Pagala, X Wang, J Peng & M E Hatley

Description: In a recent study, Xiang et al. (1) analyze ancient chicken mtDNA from northern China, together with published modern chicken data, and they proposed that the chicken was domesticated in northern China as early as 10,000 y ago. However, a reanalysis of their data suggested that the data are overinterpreted....