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The Golgi apparatus, a crucial organelle involved in protein processing, including glycosylation, exhibits complex sub-structures, i.e., cis-, medial, and trans-cisternae. This study investigated the distribution of glycosyltransferases within the Golgi apparatus of mammalian cells via 3D super-resolution imaging. Focusing on human glycosyltransferases involved in N-glycan modification, we found that even enzymes presumed to coexist in the same Golgi compartment exhibit nuanced variations in localization. By artificially making their N-terminal regions [composed of a cytoplasmic, transmembrane, and stem segment (CTS)] identical, it was possible to enhance the degree of their colocalization, suggesting the decisive role of this region in determining the sub-Golgi localization of enzymes. Ultimately, this study reveals the molecular codes within CTS regions as key determinants of glycosyltransferase localization, providing insights into precise control over the positioning of glycosyltransferases, and consequently, the interactions between glycosyltransferases and substrate glycoproteins as cargoes in the secretory pathway. This study advances our understanding of Golgi organization and opens avenues for programming the glycosylation of proteins for clinical applications. Key words: Golgi apparatus, glycosyltransferase, 3D super-resolution imaging, N-glycosylation

Abstract Interseismic strain around southwest Japan can be attributed to slip phenomena on the plate interface and processes inside the continental plate, such as block motions and inland fault slips. Although many crustal deformation analyses have been carried out, the simultaneous estimation of these phenomena and comprehensive discussion regarding the effect on the total strain budget remain topics to be investigated. In this study, we conducted numerical experiment to evaluate the possibility of simultaneously monitoring the spatiotemporal evolution of interseismic fault slips and block motions based on state-space modeling. We aimed to estimate fault slips and block motions using the time series of dense continuous Global Navigation Satellite System sites covering southwest Japan, encompassing 25 years from 1996 onward. We calculated synthetic block motions of the forearc region, monotonically increasing back slips on block boundary faults, and long-term slow slip events in the Tokai region, Kii Channel, and Bungo Channel. Subsequently, we generated the expected synthetic displacement time-series at GNSS stations. Applying Kalman filtering, we successfully estimated the spatiotemporal evolution of block motions, cumulative back slips, multiple slow slip events occurring in different regions. Although the contributions of fault slips and block motions showed slight trade-off, main characteristics of the slip distributions and the direction of block motions were well-recovered. We recovered slow slip events with slips of 5–10 cm or larger. We investigated the estimation uncertainty and separation precision of the unknown parameters using the covariance matrix estimated by Kalman filtering. Focusing on the structure of the non-diagonal component of the covariance matrix, we evaluated the complex effects of site and subfault locations on the estimated slip spatial distribution bias. For instance, the extent of the correlation between subfaults suggested that the three slow slip regions have different tendency of the uncertainties of slip areas, extending toward landside, seaward, or both of them. Our framework enables the comprehensive evaluation of the contributions and uncertainties of various deformation sources covering the entire subduction zone. Graphical abstract

Abstract The 2024 Mw 7.5 Noto Peninsula, Japan, earthquake was initiated within the source region of intense swarm activity. To reveal the mainshock early process, we relocated the earthquake hypocenters and found that many key phenomena, including the mainshock initiation, foreshocks, swarm earthquakes, and deep aseismic slip, occurred at parts of a previously unrecognized fault in intricate fault network. This fault is subparallel (several kilometers deeper) to a known active fault, and the mainshock initiation and foreshocks occurred at the front of a 2‐year westward swarm migration. The initiation location coincides with the destination of the upward migration of a deeper earthquake cluster via several smaller faults. Fluid supply, small earthquakes, and aseismic slip on the fault likely triggered the mainshock, leading to the first major rupture at the western region, propagating further to the west and east sides, resulting in an Mw7.5 event, exceeding 100 km in length.

Abstract Ocean bottom pressure-gauge (OBP) records play an essential role in seafloor geodesy. Oceanographic fluctuations in OBP data, however, pose as a significant noise source in seafloor transient crustal deformation observations, including slow slip events (SSEs), making it crucial to evaluate them quantitatively. To extract the significant fluctuation phenomena common to multiple observation networks, including oceanographic fluctuations and tectonic signals, we applied principal component analysis (PCA) to the 3-year Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) OBP time series for 40 stations during 2016–2019. PCA could separate several oceanographic signals based on the characteristics of their spatial distributions, although evident transient tectonic signals could not be confirmed from the observed pressure records during this observed period. The spatial distribution of the first four principal components (PCs) reflected the common component, inclined component along sea depth, longitude component, and parabola-like pattern, respectively. By subtracting each PC (in particular, PC-2 and PC-4) from the time series, we could significantly reduce the sea depth dependence of OBP records, which has been highlighted in several previous studies and is also evident in this region. We interpreted PCs 2–4 as the reflection of the strength and meandering of ocean geostrophic currents based on a comparison with the PC spatial distribution of the numerical oceanographic models. In addition, to evaluate the ability of PCA to separate transient tectonic signal from OBP time series, including oceanographic fluctuations, we conducted a synthetic ramp assuming an SSE by rectangular fault and then applied PCA. The assumed synthetic tectonic signal could be separated from the oceanographic signals and included in the principal component independently depending on its amplitude, suggesting that the spatial distribution of each PC would change if the amplitude of the synthetic signal were sufficiently large. We propose a transient event-detection method based on the spatial distribution difference of a specific PC with or without a tectonic signal. We used the normalized inner product (NIP) between these PCs as the indicator of their similarities. This method can detect transient tectonic signals more significantly than the moment-magnitude scale of 5.9 from OBP records. Graphical Abstract

Abstract Since November 30, 2020, an intense seismic swarm and transient deformation have been continuously observed in the Noto Peninsula, central Japan, which is a non-volcanic/geothermal area far from major plate boundaries. We modeled transient deformation based on a combined analysis of multiple Global Navigation Satellite System (GNSS) observation networks, including one operated by a private sector company (SoftBank Corp.), relocated earthquake hypocenters, and tectonic settings. Our analysis showed a total displacement pattern over 2 years shows horizontal inflation and uplift of up to ~ 70 mm around the source of the earthquake swarm. In the first 3 months, the opening of the shallow-dipping tensile crack had an estimated volumetric increase of ~ 1.4 × 107 m3 at a depth of ~ 16 km. Over the next 15 months, the observed deformation was well reproduced by shear-tensile sources, which represent an aseismic reverse-type slip and the opening of a southeast-dipping fault zone at a depth of 14–16 km. We suggest that the upwelling fluid spread at a depth of ~ 16 km through an existing shallow-dipping permeable fault zone and then diffused into the fault zone, triggering a long-lasting sub-meter aseismic slip below the seismogenic depth. The aseismic slip further triggered intense earthquake swarms at the updip.

Abstract The 2011 Tohoku-oki earthquake produced the most well-recorded postseismic deformation of any megathrust earthquake in the world. Over the last decade, researchers have used a dense and widespread geodetic network of more than 1300 Global Navigation Satellite System (GNSS) stations inland, as well as the about 50 stations on the seafloor, to investigate the various deformation sources responsible for the observed crustal deformation. One of the contributing mechanisms to this crustal deformation is the stress relaxation of the viscoelastic mantle beneath the Japanese arc. As evident in experimental rock physics and geophysical observations, ambient mantle conditions and related rheology are expected to be heterogeneous in space. However, the contribution of such rheological heterogeneities to the postseismic deformation is still poorly understood. Here, we piece together several rheological heterogeneities inferred from the decade-long postseismic deformation of the 2011 Tohoku-oki earthquake. We reviewed more than twenty postseismic models to understand how viscoelastic earth can influence the postseismic surface deformation observed after the Tohoku-oki earthquake. Besides, we employed several synthetic models to tease out the contribution of individual rheological heterogeneities such as depth-dependent rheology of mantle wedge, oceanic asthenosphere, and low-viscosity zone beneath the volcanic front. We demonstrate that the vertical postseismic observation is the key to unravel rheological complexity beneath northeastern Japan. The broader vertical deformation pattern reveals the major viscosity contrast between backarc and forearc, and small-scale subsidence detects the presence of low-viscosity bodies related to arc magmatism. In short, this review paper provides a vista of three-dimensional heterogeneous rheology of viscoelastic earth. These rheological heterogeneities may play a crucial role in bridging the gap between our understanding of different phase of subduction zone earthquake cycle.

Abstract Long-term continuous observation of seafloor pressure is effective for detecting seafloor vertical deformations that are associated with transient tectonic phenomena such as slow slip events. Since the aseismic slip event prior to the 2011 Tohoku earthquake, several discoveries have been made on spontaneous slow slip events and various other types of slow earthquake along the Japan and Kuril Trenches. Seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net) is expected to provide invaluable information on slow slip activities via geodetic signals that are detected by pressure observation. This study inspects the quality of the S-net pressure data in view of seafloor geodesy by comparison with records obtained by more than 100 autonomous ocean bottom pressure recorders (OBPRs) deployed along the Japan Trench. OBPRs have long been standard tools in seafloor geodesy, and the data collected are considered a benchmark in terms of quality. Most of the S-net stations showed noise levels that are considerably higher than those of the OBPRs over periods of more than 2 d. We speculate that a strong correlation between pressure and temperature accounts for much of the long-term noise. In this study, the temperature-dependent fluctuation component was estimated by prediction filtering and removed from the original data, leading to a significant reduction in the noise level at 51 stations, which reached levels almost equivalent to those of OBPRs. Although no significant pressure changes have been identified as associated with the 2018 Boso SSE or repeated tremor bursts in the northern Japan Trench thus far, our findings indicate that these stations are sufficiently sensitive to detect slow slip events occurring nearby.

Abstract Temporal seismic observations from pop-up type ocean-bottom seismometers were used to detect tectonic tremors immediately following the 2011 Tohoku-Oki earthquake in the northern periphery of the aftershock area. Near-field observations clearly distinguished tremors from regular earthquakes based on their spectral shape in the frequency band of 1–4 Hz. In addition to tremors accompanied by very low-frequency earthquakes (VLFEs), we detected 130 tremors without known VLFE activity during April–October 2011. The newly detected tremors were in the vicinity of a sequence of small repeating earthquakes, indicating a mixed distribution of tremors and regular interplate earthquakes in the region. Tremor activity was high immediately after the deployment of seismometers and gradually decreased. In addition, the tremor activity fluctuated with two activations with an interval of approximately 90 days, similar to the intervals between tremor bursts after 2016. The results of the study suggest that the observed tremors occurred under the influence of aseismic slip caused by the decaying afterslip of the preceding Tohoku-Oki and Mw 7.4 interplate earthquakes and episodic accelerations with a quasi-periodicity unique to the area.

Abstract The transition process from coseismic to early postseismic phenomena within a half-day remains a significant topic for understanding the slip budget and friction properties of the fault. However, the investigation of this phase has undergone limited advancement. This is mainly due to the lack of precision pertaining to the Global Navigation Satellite System (GNSS) analysis caused by difficulty of separation between fault slip and other unknown parameters such as tropospheric delay. Therefore, we propose an alternative approach (phase-to-slip; PTS) that detects fault slip directly from GNSS carrier phase variation without conventional positioning. Since the PTS simultaneously estimates fault slip and other unknowns, we can quantitatively evaluate their separation accuracy and contribution in the estimation. This study attempts to continuously estimate the coseismic and early postseismic slip of the 2011 Tohoku-Oki sequence using the PTS method. We analyzed 1-Hz carrier phase data for approximately 2 h before and after the mainshock origin (2011/03/11/05:46UTC). As a result, we successfully obtained the coseismic slip of the Mw9.0 mainshock and two major aftershocks in the off-Ibaraki (Mw7.8) and off Iwate (Mw7.4) regions. For all three events, the estimated slip distribution, equivalent moment magnitude, and calculated displacement field well agreed with those from the conventional positioning. Additionally, our results suggest postseismic slip mainly in the downdip area adjacent to the mainshock rupture. We obtained three major slip areas around the downdip region near Aomori, Iwate, and Miyagi. The estimated slip amount reaches approximately 0.1–0.2 m in 34 min immediately after the mainshock. The equivalent seismic moment of the slip areas near Iwate and Miyagi were approximately Mw7.4. This amount is similar or slightly greater than the estimations based on conventional positioning. Significant overlap is observed in the locations of the slip areas. In this manner, PTS continuously detected a series of coseismic and early postseismic slips with timescale ranging from a few minutes to an hour. Our results demonstrate the capability of the PTS method for broadband fault slip monitoring and its potential contribution to the investigation of early postseismic phenomena.

Abstract In Southeast Alaska (SE-AK), rapid ground uplift of up to 3 cm/yr has been observed associated with post-Little Ice Age glacial isostatic adjustment (GIA). Geodetic techniques such as global navigation satellite system (GNSS) and absolute gravimetry have been applied to monitor GIA since the last 1990s. Rheological parameters for SE-AK were determined from dense GNSS array data in earlier studies. However, the absolute gravity rate of change observed in SE-AK was inconsistent with the ground uplift rate, mainly because few gravity measurements from 2006 to 2008 resulted in imprecise gravity variation rates. Therefore, we collected absolute gravity data at six gravity points in SE-AK every June in 2012, 2013, and 2015, and updated the gravity variation rate by reprocessing the absolute gravity data collected from 2006 to 2015. We found that the updated gravity variation rate at the six gravity points ranged from −2.05 to −4.40 $$\upmu$$ μ Gal/yr, and its standard deviation was smaller than that reported in the earlier study by up to 88 %. We also estimated the rheological parameters under the assumption of the incompressible Earth to explain the updated gravity variation rate, and their optimal values were determined to be 55 km and $$1.2 \times 10^{19}$$ 1.2 × 10 19 Pa s for lithospheric thickness and upper mantle viscosity, respectively. These optimal values are consistent with those independently obtained from GNSS observations, and this fact indicates that absolute gravimetry can be one of the most effective methods in determining sub-surface structural parameters associated with GIA accurately. Moreover, we utilized the gravity variation rates for estimating the ratio of gravity variation to vertical ground deformation at the six gravity points in SE-AK. The viscous ratio values were obtained as −0.168 and −0.171 $$\upmu$$ μ Gal/mm from the observed data and the calculated result, respectively. These ratios are greater (in absolute) than those for other GIA regions (−0.15 to −0.16 $$\upmu$$ μ Gal/mm in Antarctica and Fennoscandia), because glaciers in SE-AK have melted more recently than in other regions. Graphical Abstract

Abstract A rapid source fault estimation and quantitative assessment of the uncertainty of the estimated model can elucidate the occurrence mechanism of earthquakes and inform disaster damage mitigation. The Bayesian statistical method that addresses the posterior distribution of unknowns using the Markov chain Monte Carlo (MCMC) method is significant for uncertainty assessment. The Metropolis–Hastings method, especially the Random walk Metropolis–Hastings (RWMH), has many applications, including coseismic fault estimation. However, RWMH exhibits a trade-off between the transition distance and the acceptance ratio of parameter transition candidates and requires a long mixing time, particularly in solving high-dimensional problems. This necessitates a more efficient Bayesian method. In this study, we developed a fault estimation algorithm using the Hamiltonian Monte Carlo (HMC) method, which is considered more efficient than the other MCMC method, but its applicability has not been sufficiently validated to estimate the coseismic fault for the first time. HMC can conduct sampling more intelligently with the gradient information of the posterior distribution. We applied our algorithm to the 2016 Kumamoto earthquake (MJMA 7.3), and its sampling converged in 2 × 104 samples, including 1 × 103 burn-in samples. The estimated models satisfactorily accounted for the input data; the variance reduction was approximately 88%, and the estimated fault parameters and event magnitude were consistent with those reported in previous studies. HMC could acquire similar results using only 2% of the RWMH chains. Moreover, the power spectral density (PSD) of each model parameter's Markov chain showed this method exhibited a low correlation with the subsequent sample and a long transition distance between samples. These results indicate HMC has advantages in terms of chain length than RWMH, expecting a more efficient estimation for a high-dimensional problem that requires a long mixing time or a problem using nonlinear Green’s function, which has a large computational cost. Graphical Abstract

Since huge earthquakes are expected along plate subduction zones such as the Japan Trench and Nankai Trough, the estimation of coseismic slip and interseismic slip deficit is essential for immediate response and preliminary measures to reduce damage. Recently, analysis considering the complex topography and underground structure of the plate subduction zone has been performed for improving the estimation performance. However, the three-dimensional (3D) crustal structural model needs to be improved continuously. In this paper, we obtained Green’s functions for 3D crustal structural models with ambiguity by 3D crustal deformation analysis, and the coseismic slip and interseismic slip deficit were estimated. Here we enabled the calculation of many Green’s functions with different physical properties of the 3D crustal structure by utilizing a GPU-based 3D crustal deformation analysis method that significantly reduces the analysis cost. The physical properties on the upper plate’s side, which are located above the plate boundary fault, were changed. We found no significant difference in the estimation performance, except for the upper crust, which most of the fault slip area is in contact with, in the case of coseismic slip estimation. In contrast, the coseismic slip estimation when the properties of the upper crust was changed had a significant error, and a negative slip was estimated at the deep part of the plate boundary where no slip was originally given.

Abstract This study proposes a new method for the uncertainty estimation of coseismic slip distribution on the plate interface deduced from real-time global navigation satellite system (GNSS) data and explores its application for tsunami inundation prediction. Jointly developed by the Geospatial Information Authority of Japan and Tohoku University, REGARD (REal-time GEONET Analysis system for Rapid Deformation monitoring) estimates coseismic fault models (a single rectangular fault model and slip distribution model) in real time to support tsunami prediction. The estimated results are adopted as part of the Disaster Information System, which is used by the Cabinet Office of the Government of Japan to assess tsunami inundation and damage. However, the REGARD system currently struggles to estimate the quantitative uncertainty of the estimated result, although the obtained result should contain both observation and modeling errors caused by the model settings. Understanding such quantitative uncertainties based on the input data is essential for utilizing this resource for disaster response. We developed an algorithm that estimates the coseismic slip distribution and its uncertainties using Markov chain Monte Carlo methods. We focused on the Nankai Trough of southwest Japan, where megathrust earthquakes have repeatedly occurred, and used simulation data to assume a Hoei-type earthquake. We divided the 2951 rectangular subfaults on the plate interface and designed a multistage sampling flow with stepwise perturbation groups. As a result, we successfully estimated the slip distribution and its uncertainty at the 95% confidence interval of the posterior probability density function. Furthermore, we developed a new visualization procedure that shows the risk of tsunami inundation and the probability on a map. Under the algorithm, we regarded the Markov chain Monte Carlo samples as individual fault models and clustered them using the k-means approach to obtain different tsunami source scenarios. We then calculated the parallel tsunami inundations and integrated the results on the map. This map, which expresses the uncertainties of tsunami inundation caused by uncertainties in the coseismic fault estimation, offers quantitative and real time insights into possible worst-case scenarios. Graphical Abstract

Abstract Monitoring of crustal deformation provides essential information for seismology and volcanology. For such earth science fields and other purposes, various Global Navigation Satellite System (GNSS) networks have been constructed at the national and regional levels. In Japan, the continuous nationwide GNSS network, the GNSS Earth Observation Network System (GEONET), is operated by the Geospatial Information Authority of Japan. Although GEONET has made a substantial contribution to earth science research, the large spacing of GEONET sites makes it difficult to accurately understand crustal deformation phenomena in some cases. However, cell phone carriers in Japan have constructed independent GNSS networks to improve their positioning services in recent years. In this study, we examine the performance of a GNSS network operated by SoftBank Corp. for crustal deformation monitoring. The network has more than 3300 sites throughout Japan, which is approximately 2.5 times the number of the GEONET sites. To assess the quality of SoftBank's GNSS data, we first analyzed data from Miyagi Prefecture and evaluated the stability of the coordinate time series for nine consecutive days during a quiet (interseismic) period. The calculated standard deviations were approximately the same for both networks. Furthermore, we calculated the displacement between September 2020 and March 2021. The results reveal that almost all SoftBank sites showed a consistent displacement with their surrounding GEONET sites. Next, we analyzed the coseismic deformation associated with the off-Fukushima earthquake (MJMA 7.3) on February 13, 2021, in both static and kinematic modes. We obtained a westward coherent displacement along the coastline in both networks, although several outliers were observed for the SoftBank sites. Based on these initial assessments, we conclude that these private sector GNSS sites are useful for crustal deformation monitoring with appropriate data quality control. Graphical Abstract

Abstract Rapid estimation of the coseismic fault model for medium-to-large-sized earthquakes is key for disaster response. To estimate the coseismic fault model for large earthquakes, the Geospatial Information Authority of Japan and Tohoku University have jointly developed a real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD can estimate the single rectangular fault model and slip distribution along the assumed plate interface. The single rectangular fault model is useful as a first-order approximation of a medium-to-large earthquake. However, in its estimation, it is difficult to obtain accurate results for model parameters due to the strong effect of initial values. To solve this problem, this study proposes a new method to estimate the coseismic fault model and model uncertainties in real time based on the Bayesian inversion approach using the Markov Chain Monte Carlo (MCMC) method. The MCMC approach is computationally expensive and hyperparameters should be defined in advance via trial and error. The sampling efficiency was improved using a parallel tempering method, and an automatic definition method for hyperparameters was developed for real-time use. The calculation time was within 30 s for 1 × 106 samples using a typical single LINUX server, which can implement real-time analysis, similar to REGARD. The reliability of the developed method was evaluated using data from recent earthquakes (2016 Kumamoto and 2019 Yamagata-Oki earthquakes). Simulations of the earthquakes in the Sea of Japan were also conducted exhaustively. The results showed an advantage over the maximum likelihood approach with a priori information, which has initial value dependence in nonlinear problems. In terms of application to data with a small signal-to-noise ratio, the results suggest the possibility of using several conjugate fault models. There is a tradeoff between the fault area and slip amount, especially for offshore earthquakes, which means that quantification of the uncertainty enables us to evaluate the reliability of the fault model estimation results in real time.

Abstract Obvious crustal deformation is observed during a postseismic period as well as a coseismic period associated with a large earthquake. Major mechanisms of transient postseismic deformation are known as afterslip and viscoelastic relaxation. Since the viscoelastic relaxation occurs as a response to a coseismic slip, postseismic deformation provides information on coseismic deformation through the viscoelastic response. However, most previous studies have not thoroughly utilized postseismic geodetic observational data for revealing coseismic slip behaviors. In this study, we developed a slip inversion method that simultaneously estimates coseismic slip and postseismic slip distributions from coseismic and postseismic geodetic observational data using viscoelastic Green’s function (viscoelastic inversion method). We investigated the performance of the viscoelastic inversion method via two synthetic tests: one assumed a strike–slip event along an inland fault, while the other assumed a dip–slip event along a plate interface in a subduction zone. Both synthetic tests demonstrated that when extensive postseismic observational data were given, the viscoelastic inversion method provided a superior spatial resolution of coseismic slip distributions compared to conventional elastic inversion distributions. We also applied the viscoelastic inversion method to co- and post-seismic deformations associated with the 2011 Tohoku-oki earthquake. The seafloor geodetic observational network of the off-Tohoku region has been widely extended after the occurrence of the mainshock. Using this extended seafloor geodetic observational data, we successfully improved the spatial resolution of the coseismic slip distribution through the viscoelastic inversion method. Furthermore, using the seafloor observational data during the postseismic period, our inversion method enables us to obtain high spatial resolution of the coseismic slip in the offshore area and a reasonable coseismic slip distribution even if seafloor observational data during the coseismic period are unavailable. These results clarify the importance of deploying a geodetic observational network even after large coseismic events to assess past coseismic slip behaviors by considering the viscoelasticity of the Earth.

The secretion of blood coagulation factor V and factor VIII (FV and FVIII) are driven by secretion factors ERGIC-53 and MCDF2. Here, the authors report a 10 amino acid motif from FVIII that can enhance secretion of another glycoprotein erythropoietin (EPO).

Abstract We assessed the positioning accuracy of GNSS-Acoustic (GNSS-A) measurement using a slackly moored buoy. A key feature of real-time buoy-based GNSS-A measurement is that positioning must be performed via single ranging from an arbitrary observation position and encompassing the drifting range of the buoy. In this study, slack-line mooring was employed to resist strong Kuroshio current of up to 5.5 knots in the Nankai Trough. During a year-long sea trial, the buoy drifted within a circle of ~ 4000 m radius, which is much larger than the dimension of a seafloor transponder array. In the sea trial, more than 500 successful regular and on-demand ranging measurements were obtained at various observation positions. The results show that the horizontal positioning accuracy (2σ) of the array for single ranging was 46 cm when the buoy was inside the array and 97 cm when it was outside the array. These accuracies are comparable to those achieved through single ranging in traditional ship-based surveys at the same site. In addition to the distance dependency, we observed directivity in the accuracy, depending on the geometry between an observation point and seafloor transponders. To interpret the accuracy degradation and directivity as a function of observation position, we calculated error ellipses using a dilution-of-precision (DOP) analysis procedure for GNSS-A positioning. The error ellipses clearly illustrate that the variance in array positions is large in the line-of-sight direction from an observation point to the array center. We translated the error ellipses to positioning accuracies using the standard deviation of travel time residuals when an array position is estimated using all pings. The positioning accuracy resulting from the translation corresponded to that obtained using array positions in a buoy observation. The DOP analysis results and their translation into positioning accuracies enabled a detailed assessment of the directional accuracy of GNSS-A positioning at an arbitrary observation position, which is important for real-time measurement of seafloor movement in the event of a huge earthquake.

Estimating the coseismic slip distribution and interseismic slip-deficit distribution play an important role in understanding the mechanism of massive earthquakes and predicting the resulting damage. It is useful to observe the crustal deformation not only in the land area, but also directly above the seismogenic zone. Therefore, improvements in terms of measurement precision and increase in the number of observation points have been proposed in various forms of seafloor observation. However, there is lack of research on the quantitative evaluation of the estimation accuracy in cases where new crustal deformation observation points are available or when the precision of the observation methods have been improved. On the other hand, the crustal structure models are improving and finite element analysis using these highly detailed crustal structure models is becoming possible. As such, there is the real possibility of performing an inverted slip estimation with high accuracy via numerical experiments. In view of this, in this study, we proposed a method for quantitatively evaluating the improvement in the estimation accuracy of the coseismic slip distribution and the interseismic slip-deficit distribution in cases where new crustal deformation observation points are available or where the precision of the observation methods have been improved. As a demonstration, a quantitative evaluation was performed using an actual crustal structure model and observation point arrangement. For the target area, we selected the Kuril Trench off Tokachi and Nemuro, where M9-class earthquakes have been known to occur in the past and where the next imminent earthquake is anticipated. To appropriately handle the effects of the topography and plate boundary geometry, a highly detailed three-dimensional finite element model was constructed and Green’s functions of crustal deformation were calculated with high accuracy. By performing many inversions via optimization using Green’s functions, we statistically evaluated the effect of increase in the number of observation points of the seafloor crustal deformation measurement and the influence of measurement error, taking into consideration the diversity of measurement errors. As a result, it was demonstrated that the observation of seafloor crustal deformation near the trench axis plays an extremely important role in the estimation performance.

Crustal deformation of the seafloor is difficult to observe solely using global navigation satellite system (GNSS). The GNSS-acoustic (GNSS-A) technique was developed to observe seafloor crustal deformation, and it has produced a steady series of successful observations with remarkable results related to crustal deformation associated with huge earthquakes around the Japanese Islands. However, utilizing GNSS-A incurs very large financial and human costs as it requires the use of a research vessel as a surface platform and has a limited observation frequency, which is less than once a year at seafloor stations along the Japan Trench. To conduct frequent observations, an automatic GNSS-A data acquisition system was developed that operates via an unmanned surface vehicle (wave glider). The first observations using this system were performed at a seafloor station off Aomori Prefecture in July 2019. The wave glider was equipped with two GNSS antennas, an acoustic transducer, a microelectromechanical system gyroscope, and associated control and logging units. Data acquisition and autonomous activation of the seafloor stations were successfully executed by controlling the power supply to the payload via satellite communication with the wave glider. The glider rarely strayed off the configured course and the solar panels generated sufficient power to perform the observations although the weather was mostly cloudy. The GNSS-A data processing results show that the position of the station was determined with the same accuracy and precision as in previous observations performed using a research vessel.

Abstract Horizontal crustal strain in the Tohoku area during the twentieth century based on triangulation showed N–S extension and E–W contraction was not significant. This feature was one of the reasons why the 2011 Tohoku-oki earthquake was unexpected for many scientists. The first triangulation conducted in the late nineteenth century used a length scale defined by baseline surveys, direct measurements of short (2–10 km) baselines with steel rods. The Shionohara baseline in the Yamagata prefecture was measured in May–July 1894 and the 1894 Shonai (M7.0) earthquake occurred in its western neighbor 3 months after the measurement. The earthquake possibly elongated the baseline by as large as 5 cm or 10 ppm. However, the original length measured before the earthquake was used for the network adjustment of the entire triangulation network, causing extensive underestimation of the length scale of the network as large as 5–10 ppm in northeast Japan. The scale error effect was comparable to tectonic deformation signal over 100 years. The baseline length was re-surveyed in 2012, 1 year after the Tohoku-oki earthquake, and the result is consistent with the hypothesis of scale bias considering interseismic deformation.

Platelet-derived growth factor (PDGF) signaling controls various physiological functions via two receptor subtypes: PDGF receptor (PDGFR) α and PDGFRβ. Nevertheless, our understanding of their roles is limited because of a lack of pharmacological tools to discriminate subtype-specific signaling. We developed a chimeric receptor by combining ligand-binding-domain truncated PDGFRβ with anti-fluorescein single chain antibody, expecting the control of PDGFRβ-specific signaling by oligomerized fluorescein as an artificial agonist. Results show that calcium mobilization, Cdc42 activation, and cell migration were elicited specifically by the artificial ligand in cells expressing the chimeric receptor. Our method is expected to be useful to understand the subtype-specific roles of PDGFRs in various cellular functions. Keywords:: platelet-derived growth factor receptor, chimeric receptor