ALBERT

Description: A set of uniaxial compression tests of granite specimens taken from five localities across Japan was conducted to identify the factors controlling the quantity of radon (Rn) emission (sum of 222 Rn and 220 Rn) during compression and failure. An α-scintillation detector and a gas flow unit were installed with a testing machine to enable continuous measurement of Rn emissions. Common to all specimens, Rn emissions remained at or slightly declined from the background level after the start of loading; this is similar to the natural phenomenon of decline in groundwater-dissolved Rn before an earthquake. Closure of original microcracks is the most likely cause of the initial Rn decline. Then, Rn emissions begin to increase at 46–57 per cent stress level to the uniaxial compressive strength, and continue to increase even after the failure of specimen. This commencement stress level is close to the general stress level at outbreak of acoustic emissions caused by the development and connection of microcracks. The Rn increase after failure is similar to a phenomenon observed in aftershocks, which may originate from the enhancement of Rn emanations from grains due to the large increase in total surface area and stress release. In addition to the initial radioelement content in rock, the failure pattern (conjugate shear versus longitudinal tensile type), compressive strength, and grain size are possible control factors of the maximum quantity of Rn emissions induced by failure. This maximum may also be affected by the development velocity of the emanation area, which is related to the Rn emanation fraction, associated with the fragmentation. In addition to the magnitude of an earthquake and its hypocentre distance to Rn detectors, the magnitude of increase in Rn concentration in soil gas and groundwater before, during, and after an earthquake in crystalline rocks depends on the intrinsic radioelement content, the mineral texture, and the mechanical properties of rocks. Rock fracturing and failure do not necessarily induce increase in Rn emission due to these rock properties, which can be used to understand the sensitivity of Rn concentration in soil gas or groundwater in connection with an earthquake.

Description: We present an approach for subspace detection of small seismic events that includes methods for estimating magnitudes and associating detections from multiple stations into unique events. The process is used to identify mining related seismicity from a surface coal mine and an underground coal mining district, both located in the Western U.S. Using a blasting log and a locally derived seismic catalogue as ground truth, we assess detector performance in terms of verified detections, false positives and failed detections. We are able to correctly identify over 95 per cent of the surface coal mine blasts and about 33 per cent of the events from the underground mining district, while keeping the number of potential false positives relatively low by requiring all detections to occur on two stations. We find that most of the potential false detections for the underground coal district are genuine events missed by the local seismic network, demonstrating the usefulness of regional subspace detectors in augmenting local catalogues. We note a trade-off in detection performance between stations at smaller source–receiver distances, which have increased signal-to-noise ratio, and stations at larger distances, which have greater waveform similarity. We also explore the increased detection capabilities of a single higher dimension subspace detector, compared to multiple lower dimension detectors, in identifying events that can be described as linear combinations of training events. We find, in our data set, that such an advantage can be significant, justifying the use of a subspace detection scheme over conventional correlation methods.

Description: We conduct a numerical experiment to investigate potential bias in measurements of S -wave splitting (apparent differences between the arrival times of SH and SV phases) for waves propagating close to the core–mantle boundary (CMB) in the D'' layer. The bias is defined as the discrepancy between shear wave splitting measured from finite frequency synthetic seismograms (‘apparent splitting’) and the splitting predicted by ray theory, which is a high-frequency approximation. For simple isotropic models, we find biases which are typically between 0.5 and 4 s, depending on the model, the Q structure and the dominant period of the synthetics. The bias increases for lower frequencies or lower Q values. The epicentral distance at which the bias starts depends on the frequency and the Q structure. We also compute synthetics for models based on mineral physics (using the elastic constants under lower-mantle pressure and temperature conditions, taking into account the phase transition from Mg-perovskite to Mg-post-perovskite) and geodynamics (the thermal boundary layer) and find that the depth of the positive velocity jump associated with the phase transition and the depth range over which the velocity decreases (due to temperature increases) in the thermal boundary layer significantly influence the wavefield in the lowermost mantle. For example, in cold regions beneath subduction zones, wavefields for SH and SV differ greatly due to the steep velocity decrease close to the CMB. For complex models, apparent splitting can also arise from the possibility that low amplitude direct phases might be overlooked, and larger amplitude later phases might instead incorrectly be picked as the direct arrival. Biases of the type investigated in this study combine with other sources of uncertainty for splitting in D'' (e.g. the correction for upper-mantle anisotropy and the difference between SH and SV ray paths) to make a precise evaluation of the anisotropy in D'' difficult.

Description: A new method of fully nonlinear waveform fitting to measure interstation phase speeds and amplitude ratios is developed and applied to USArray. The Neighbourhood Algorithm is used as a global optimizer, which efficiently searches for model parameters that fit two observed waveforms on a common great-circle path by modulating the phase and amplitude terms of the fundamental-mode surface waves. We introduce the reliability parameter that represents how well the waveforms at two stations can be fitted in a time–frequency domain, which is used as a data selection criterion. The method is applied to observed waveforms of USArray for seismic events in the period from 2007 to 2010 with moment magnitude greater than 6.0. We collect a large number of phase speed data (about 75 000 for Rayleigh and 20 000 for Love) and amplitude ratio data (about 15 000 for Rayleigh waves) in a period range from 30 to 130 s. The majority of the interstation distances of measured dispersion data is less than 1000 km, which is much shorter than the typical average path-length of the conventional single-station measurements for source-receiver pairs. The phase speed models for Rayleigh and Love waves show good correlations on large scales with the recent tomographic maps derived from different approaches for phase speed mapping; for example, significant slow anomalies in volcanic regions in the western Unites States and fast anomalies in the cratonic region. Local-scale phase speed anomalies corresponding to the major tectonic features in the western United States, such as Snake River Plains, Basin and Range, Colorado Plateau and Rio Grande Rift have also been identified clearly in the phase speed models. The short-path information derived from our interstation measurements helps to increase the achievable horizontal resolution. We have also performed joint inversions for phase speed maps using the measured phase and amplitude ratio data of vertical component Rayleigh waves. These maps exhibit better recovery of phase speed perturbations, particularly where the strong lateral velocity gradient exists in which the effects of elastic focussing can be significant; that is, the Yellowstone hotspot, Snake River Plains, and Rio Grande Rift. The enhanced resolution of the phase speed models derived from the interstation phase and amplitude measurements will be of use for the better seismological constraint on the lithospheric structure, in combination with dense broad-band seismic arrays.

Description: Finite-fault earthquake source inversion is an ill-posed inverse problem leading to non-unique solutions. In addition, various fault parametrizations and input data may have been used by different researchers for the same earthquake. Such variability leads to large intra-event variability in the inferred rupture models. One way to understand this problem is to develop robust metrics to quantify model variability. We propose a Multi Dimensional Scaling (MDS) approach to compare rupture models quantitatively. We consider normalized squared and grey-scale metrics that reflect the variability in the location, intensity and geometry of the source parameters. We test the approach on two-dimensional random fields generated using a von Kármán autocorrelation function and varying its spectral parameters. The spread of points in the MDS solution indicates different levels of model variability. We observe that the normalized squared metric is insensitive to variability of spectral parameters, whereas the grey-scale metric is sensitive to small-scale changes in geometry. From this benchmark, we formulate a similarity scale to rank the rupture models. As case studies, we examine inverted models from the Source Inversion Validation (SIV) exercise and published models of the 2011 Mw 9.0 Tohoku earthquake, allowing us to test our approach for a case with a known reference model and one with an unknown true solution. The normalized squared and grey-scale metrics are respectively sensitive to the overall intensity and the extension of the three classes of slip (very large, large, and low). Additionally, we observe that a three-dimensional MDS configuration is preferable for models with large variability. We also find that the models for the Tohoku earthquake derived from tsunami data and their corresponding predictions cluster with a systematic deviation from other models. We demonstrate the stability of the MDS point-cloud using a number of realizations and jackknife tests, for both the random field and the case studies.

Description: We studied the seismicity rate increase in the Kanto region around Tokyo following the 2011 Tohoku-Oki earthquake ( M w 9.0) to examine whether this increase was correlated with the static increases in the Coulomb failure function (CFF) of the Tohoku-Oki earthquake sequence. Because earthquakes in the Kanto region exhibit various focal mechanisms, the receiver faults for the CFF were assumed to be the focal mechanism solutions for nearly 19 000 earthquakes that previously occurred. Our results showed that the number of earthquakes for which the mechanism solutions had a positive CFF (~12 000) is much larger than those that had a negative CFF (~2000). Comparison of the CFF values for earthquakes before and after the Tohoku-Oki earthquake showed that the latter had more positive values; this supports the hypothesis that the coseismic stress change transferred from the Tohoku-Oki earthquake sequence is the major contributing factor to the increased seismicity rate in the Kanto region.

Description: A new method of fully nonlinear waveform fitting to measure interstation phase speeds and amplitude ratios is developed and applied to USArray. The Neighbourhood Algorithm is used as a global optimizer, which efficiently searches for model parameters that fit two observed waveforms on a common great-circle path by modulating the phase and amplitude terms of the fundamental-mode surface waves. We introduce the reliability parameter that represents how well the waveforms at two stations can be fitted in a time–frequency domain, which is used as a data selection criterion. The method is applied to observed waveforms of USArray for seismic events in the period from 2007 to 2010 with moment magnitude greater than 6.0. We collect a large number of phase speed data (about 75 000 for Rayleigh and 20 000 for Love) and amplitude ratio data (about 15 000 for Rayleigh waves) in a period range from 30 to 130 s. The majority of the interstation distances of measured dispersion data is less than 1000 km, which is much shorter than the typical average path-length of the conventional single-station measurements for source-receiver pairs. The phase speed models for Rayleigh and Love waves show good correlations on large scales with the recent tomographic maps derived from different approaches for phase speed mapping; for example, significant slow anomalies in volcanic regions in the western Unites States and fast anomalies in the cratonic region. Local-scale phase speed anomalies corresponding to the major tectonic features in the western United States, such as Snake River Plains, Basin and Range, Colorado Plateau and Rio Grande Rift have also been identified clearly in the phase speed models. The short-path information derived from our interstation measurements helps to increase the achievable horizontal resolution. We have also performed joint inversions for phase speed maps using the measured phase and amplitude ratio data of vertical component Rayleigh waves. These maps exhibit better recovery of phase speed perturbations, particularly where the strong lateral velocity gradient exists in which the effects of elastic focussing can be significant; that is, the Yellowstone hotspot, Snake River Plains, and Rio Grande Rift. The enhanced resolution of the phase speed models derived from the interstation phase and amplitude measurements will be of use for the better seismological constraint on the lithospheric structure, in combination with dense broad-band seismic arrays.

Description: Epigenetic regulation of gene expression involves, besides DNA and histone modifications, the relative positioning of DNA sequences within the nucleus. To trace specific DNA sequences in living cells, we used programmable sequence-specific DNA binding of designer transcription activator-like effectors (dTALEs). We designed a recombinant dTALE (msTALE) with variable repeat domains to specifically bind a 19-bp target sequence of major satellite DNA. The msTALE was fused with green fluorescent protein (GFP) and stably expressed in mouse embryonic stem cells. Hybridization with a major satellite probe (3D-fluorescent in situ hybridization) and co-staining for known cellular structures confirmed in vivo binding of the GFP-msTALE to major satellite DNA present at nuclear chromocenters. Dual tracing of major satellite DNA and the replication machinery throughout S-phase showed co-localization during mid to late S-phase, directly demonstrating the late replication timing of major satellite DNA. Fluorescence bleaching experiments indicated a relatively stable but still dynamic binding, with mean residence times in the range of minutes. Fluorescently labeled dTALEs open new perspectives to target and trace DNA sequences and to monitor dynamic changes in subnuclear positioning as well as interactions with functional nuclear structures during cell cycle progression and cellular differentiation.

Description: We infer 3-D localized shear velocity structure in the lowermost 400 km of the mantle at the western edge of the Pacific large low shear velocity province (LLSVP) by applying waveform inversion to transverse component body-wave waveforms from the F-net seismic array in Japan. Our data set consists of relatively long period (12.5–200 s) broad-band seismic waveforms of Tonga-Fiji deep focus and intermediate deep earthquakes. We conduct several tests to confirm the robustness of the inversion results. We find two low-velocity zones at the bottom of the target region, with a high-velocity zone in the middle, and a low-velocity zone above the high-velocity zone and contiguous with the two deeper low-velocity zones at a depth of 200–300 km above the core-mantle boundary (CMB). This supports the idea that the Pacific LLSVP may be an aggregation of small upwelling plumes rather than a single large thermochemical pile.

Description: Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.