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Outbreaks of infectious diseases can occur after natural disasters as vital services are disrupted and populations move into evacuation centres. National notifiable disease surveillance may be inadequate in these situations because of resource-consuming disease confirmation or system interruptions. Although syndromic surveillance has been used as an alternative in post-disaster situations, no systematic evaluations of it have been published. We evaluated the ad hoc paper-based syndromic surveillance system implemented in evacuation centres in Ibaraki prefecture after the 2011 Great East Japan Earthquake and Tsunami. We assessed the simplicity, acceptability, data quality, timeliness and portability of this system and reviewed its usefulness. We concluded that the system was simple, acceptable, portable and useful. The documentation and monitoring of disease events and trends were useful for developing interventions in evacuation centres and have since been used to improve post-disaster infectious disease and surveillance knowledge in Japan. We believe timeliness was a challenge due to the chain of data transmission and communication passing through an intermediary. Future implementations of this system could consider a more direct chain of data transmission and communication from collectors to analysers. Too few key informant interviewees and the inability to obtain original paper-based data from evacuation centres limited our findings; we conducted this evaluation four years after the response occurred. Future evaluations should be completed closer to when operations cease. The usefulness of the system suggests adopting it in future disasters. A simple, plain-language manual should be developed to improve future employment.

This study aimed to examine whether risk of withdrawal from HTTx was higher in coastal areas that were severely damaged by tsunami than in inland areas. We conducted a cross-sectional study of 9218 participants aged ≥20 years in Miyagi, Japan. The odds ratios (ORs) and confidence interval (CI) for withdrawal from HTTx in coastal and inland groups were compared using multivariate logistic regression analysis, adjusting for potential confounders. In total, 194 of 5860 and 146 of 3358 participants in the inland and coastal groups, respectively, withdrew from HTTx treatment. OR (95%CI) of withdrawal from HTTx in the coastal group was 1.46 (1.14-1.86) compared to the inland group. According to housing damage, ORs (95% CI) in the no damage, partially destroyed, and more than half destroyed coastal groups compared with the no damage inland group were 1.62 (1.04-2.50), 1.69 (1.17-2.45), and 1.08 (0.71-1.65), respectively. In conclusion, the risk of HTTx withdrawal for participants whose homes in coastal areas were relatively less damaged was significantly higher compared with those in inland areas, while the risk of HTTx withdrawal for participants whose homes were more than half destroyed was not. Post-disaster administrative support for disaster victims is considered vital for continuation of their treatment., (© 2023. The Author(s).)

Space is a feature of all disasters, and it is through decisions on how space is developed, used, and reproduced that disasters manifest themselves. Critical urban theory sees urban space-cities-as an arena of contestation expressed through the relationship between people, power, and the built environment. Cities allow for an unpacking of this process of contestation through the interpretation of various temporal, spatial, social, and physical elements that together create complex issues and 'wicked problems'. In these urban spaces in all their complexity, disasters reveal both the worst injustices and inequalities present in a society. By drawing on three well-known cases-Hurricane Katrina in 2010; the Haiti earthquake in 2010; and the Great East Japan Earthquake and Tsunami in 2011-this paper not only explores the opportunities that critical urban theory presents for gaining a deeper understanding of disaster risk creation, but also it encourages disaster scholars to engage with it., (© 2023 The Authors. Disasters published by John Wiley & Sons Ltd on behalf of ODI.)

Aim: The 2011 Great East Japan Earthquake (GEJE) was a disaster leading to radiation exposure and psychological distress, particularly among pregnant women. However, it is not known how this affected the seasonal changes of pregnancy and childbirth. Therefore, this study investigated the impact of the GEJE in the Fukushima Prefecture on spontaneous and induced abortions with regard to seasonal variability., Methods: We used the data of vital statistics of live birth and stillbirth registry and the census survey of the Fukushima Maternity Care Facility. We calculated the spontaneous and induced abortion rate for 2011-2016 using two different methods (cross-sectional and longitudinal). We calculated the quartiles and outliers to determine the impact and duration of the GEJE. Periodicity was investigated using spectral density analysis. The data were analyzed for the entire Fukushima Prefecture and by region., Results: The spontaneous abortion rate did not show specific changes after the GEJE. Contrarily, the monthly analysis in the cross-sectional method, revealed specific increases in induced abortion rate during the year after the GEJE; in the longitudinal method, induced abortions increased among women who became pregnant within 1 year after the GEJE. Spontaneous abortion showed no specific periodicity, while induced abortion showed cycles of 6 and 12 months, with a particular increase in May each year., Conclusions: The spontaneous abortion rate was not affected by the GEJE. The changes in the induced abortion rate after the disaster may have overlapped with the timing of the increased periodicity, and cannot be attributed solely to the GEJE., (© 2023 Japan Society of Obstetrics and Gynecology.)

During the Great East Japan Earthquake, many people experienced the loss of family and friends, among other traumatic events. This study sought to clarify the impact of the loss of significant close others on posttraumatic stress symptoms (PTSS), as well as the factors associated with PTSS, among individuals who experienced the loss of significant close others (i.e., bereaved group). Self-administered questionnaires were mailed to men and women (N = 180,604) aged 16 years and older living in municipalities that included evacuated areas surrounding the Tokyo Electric Power Company's Fukushima Daiichi Nuclear Power Station, which was significantly damaged following an earthquake and tsunami in March 2011, causing subsequent radiation leakage; this mailing yielded a 40.7% response rate, with 57,388 valid responses, in 2012. We used the Posttraumatic Stress Disorder Checklist-Specific (PCL-S) to measure PTSS as the outcome variable. Loss of significant close others in the disaster and respondents' relationship with the deceased constituted the explanatory variables. Basic characteristics and disaster-related factors were the confounding variables. Data were analyzed using chi-square tests and logistic regression analyses. The bereaved group showed more severe PTSS than the nonbereaved group, aOR = 1.58, 95% CI [1.50, 1.67]. The risk of developing PTSS increased if the deceased was a respondent's spouse, aOR = 1.67, 95% CI [1.22, 2.29]; child, 1.51 [1.01, 2.25]; or friend, 1.33 [1.16, 1.53]. Individuals who lose significant close others, including both family and friends, in disasters require close mental health care and, if necessary, should be referred for psychiatric treatment., (© 2022 ReedGroup Ltd. Journal of Traumatic Stress published by Wiley Periodicals LLC on behalf of International Society for Traumatic Stress Studies.)

Earthquakes are insured in high-risk high-income countries only if the public sector is involved. Prototypical examples are the insurance schemes in California (United States), Japan, and New Zealand, but each is structured differently. This paper examines these variations using a concrete case study: the sequence of earthquakes in Christchurch, New Zealand, in 2010-11-the most heavily insured seismic event in history. It assesses what would have been the outcome had the Christchurch insurance system been different, focusing on the California Earthquake Authority (CEA) programme and Japan Earthquake Reinsurance (JER). Overall, the aggregate cost of the earthquake to the New Zealand public insurer (Earthquake Commission) was USD 6.2 billion. If a similar-sized disaster had occurred in Japan and California, homeowners would have received around USD 1.6 billion and USD 0.7 billion, respectively. This paper describes the distributive and spatial patterns of these scenarios and discusses some key policy questions that emerge from this comparison., (© 2019 The Authors Disasters © 2019 Overseas Development Institute.)

This study used the Disablement Process framework to examine how exposure to the great east Japan earthquake and tsunami on 11 March 2011 was related to elders' experiences of disability-that is, 'a gap between personal capability and environmental demand' (Verbrugge and Jette, 1994, p. 1). Data were derived from two waves (2009 and 2013) of the Nihon University Japanese Longitudinal Study of Aging, involving a representative sample of citizens aged 65 or more. Logistic regression was employed to model how the disaster was associated with the prevalence and incidence of disability. A significant relationship was documented between the two. Those impacted by the event exhibited greater odds of reporting a disability in 2013 and developing one between 2009 and 2013. Disasters destroy social infrastructure and disrupt daily life, widening the lacuna between the environment and personal resources. Given the increasing number of disasters, more policy attention should be directed to reducing their adverse consequences for health., (© 2020 The Authors Disasters © 2020 Overseas Development Institute.)

In this paper, a scalable end-to-end tree boosting system called XGBoost has been applied for predicting the magnitude of an earthquake from the early part of earthquake waveform data. This model uses the features extracted from the early P wave phase of the records as an input. The model's effectiveness has been verified by using data on earthquakes occurring in the Eurasian plate of Japan Islands from 1996 to 2021. Feature engineering has given 29 new features identified from the early P wave phase of the record, which show a high correlation with the magnitude of an earthquake. The comparison of predicted and actual magnitude shows that a trained XGboost model, which uses a single input record for magnitude prediction, gives an average prediction error of 0.004 ± 0.57 for earthquakes in the test dataset. In contrast, the average prediction error of –1.1 ± 0.80 and –0.65 ± 0.69 has been obtained for the magnitude estimated from conventional τc and Pd methods using the same test dataset. It is further seen that the average predicted magnitude of a single earthquake of magnitude 4.5 and 6.1 (MJMA) obtained by using multiple nearfield records using XGBoost model is 4.58 ± 0.33 and 6.32 ± 0.29, which is close to the actual magnitude of the earthquake. The results presented in this paper clearly show that the structured data can be effectively used by complex machine learning or deep learning models to predict earthquake magnitude from single or multiple records. [ABSTRACT FROM AUTHOR]

The electron density (Ne), ion density (Ni), and electron temperature (Te) statistics recorded by the DEMETER satellite payload ISL (Instrument Sonde de Langmuir) were used to study the disturbance characteristics of the ionosphere before solid earthquakes of magnitude 6 or higher in Japan during the summer of 2005 – 2009 , to provide more information and methods for the coupling mechanism and short-range earthquake prediction. In this paper, the region of ± 10 ° of the epicenter is divided into 1 ° × 1 ° pixels, and the background field of each parameter is constructed using data without earthquakes and relatively calm space weather. We also define a measure of the perturbation intensity of ionospheric parameters relative to the background field during the occurrence of earthquakes. The analysis results of the four Japanese earthquakes from space and time show an excellent synchronization in the time and area of the anomalies in ionospheric parameters of the four cases. All four instances showed Ne abnormalities, and three showed Ni and Te anomalies, in which N e and Ni increased or decreased abnormally, while Te increased abnormally every time, and the anomalies mainly occurred about 9–12 days before the earthquake. This paper eliminates the influence of solar, geomagnetic, and satellite data defects on the experimental results as much as possible in data screening and method selection. The results partially agree with the conclusions reported in the existing literature, and the obtained anomalies are somewhat related to the ionospheric precursors of earthquakes. [ABSTRACT FROM AUTHOR]

Earthquake swarms are most commonly composed of small‐magnitude earthquakes. However, a recent study by Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) analyzed a swarm beneath the Noto Peninsula in Japan that, after more than two years of moderate‐magnitude seismicity, triggered the moment magnitude (Mw) 6.2 Suzu mainshock in May 2023. Based on high‐precision earthquake locations and a slip inversion of the mainshock, these authors found that the Mw 6.2 Suzu earthquake occurred on the updip extension of a fault that was active during the swarm, likely driven by increased fluid pressure. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby on 1 January 2024. These events underscore the potential for swarms to be precursors to large, damaging earthquakes. Forecasting the eventual evolution of swarms is currently very challenging but could be aided in the future by new observations and models. Plain Language Summary: Although earthquake swarms often only contain small earthquakes, occasionally they can trigger large, damaging earthquakes. Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) examined the triggering of a magnitude 6.2 earthquake in Japan, which caused extensive damage, following two years of smaller earthquakes. This sequence, like many swarms, may have been driven by elevated fluid pressure migrating upwards within the crust. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby. Forecasting the eventual evolution of ongoing swarms is currently very challenging but could be aided in the future by new observations and models. Key Points: Earthquake swarms can be precursors to damaging earthquakes, including the 1 January 2024, Mw 7.5 Noto Peninsula, Japan eventFluid pressure changes often drive swarm activity, and their degree of confinement may influence swarm evolutionDirect observations of fluids in fault zones combined with numerical modeling may aid swarm forecasting in the future [ABSTRACT FROM AUTHOR]

When discussing Buddhism in practice, we should first note that the word practice has a multilayered meaning in Buddhism. For the purposes of this paper, I would like to simplify things considerably, and divide those multiple meanings into two groups. The first involves the training of one's mind and body. By engaging in such training, the practitioner is said to draw closer to Buddhist enlightenment. This practice takes various forms depending on the time and place, such as observing the precepts or engaging in meditation, and is referred to as 'benefiting the self' (jiri 自利). Second, there is the practice that consists of Buddhists' activities vis-à-vis society. Even Buddhists, whose fundamental orientation is towards leaving the secular world (shusseken 出世 間), have engaged in activities in society that have taken a variety of forms. There are records of Śākyamuni having given various pieces of advice to rulers during ancient times. We also find many records of later Buddhists engaging in missionary and charitable activities. This is referred to as 'benefiting others' (rita 利他). In particular, Mahayana Buddhism emphasizes the inseparability of 'benefiting the self' and 'benefiting others'. Although Buddhist practice is traditionally divided into two categories: self-interest and altruism, it would not be true to say, in fact, that 'benefiting others' has always been as much of a primary concern as 'benefiting the self.' Rather, it can be said that concern for others has always been a weakness of Buddhism, overshadowed by concerns with 'benefiting the self.' Thus, Mahayana Buddhism's emphasis on the importance of benefiting others, on the contrary, could be said to imply that this was a weakness of the Buddhism at the time of the Mahayana arose. My paper focuses on recent developments surrounding Buddhism and its practice in contemporary Japan, particularly the element of 'benefiting others.' The question of how Buddhists should contribute to society has continually and repeatedly appeared from the origins of Mahayana Buddhism to the present. Against this backdrop, an event occurred in Japan in recent years that marked a major turning point in the issue of Buddhist contributions to society. That event is the Great East Japan Earthquake of 2011. In this paper, I consider the issue of 'benefiting others' in Buddhism in light of the effects of the tragic earthquake disaster. [ABSTRACT FROM AUTHOR]

The year 2023 marks the 100th commemoration of the disastrous Kanto Earthquake in Japan, which shattered the urban fabric of Tokyo and other southern prefectures. In the years following 1923, much research into disaster risk reduction (especially fire prevention) was undertaken. This study evaluated research trends and the impact of the earthquake on the city using metropolitan population data. The following is reported: (1) This study summarized English and Japanese academic papers and reports on the Great Kanto Earthquake that have been published over the last 100 years. (2) The area of fire spread and number of damaged buildings in Tokyo due to the Great Kanto Earthquake were overwhelmingly larger than those in other areas. (3) The difference in the relative amount of damage caused by natural disasters with more than 1,000 death toll to the annual national budget in Japan became clear. (4) The Great Kanto Earthquake was the only natural disaster that caused a net worth of damage exceeding the Japanese national budget by 3.8 times. (5) The expansion of the Tokyo metropolitan area over the 100 years since the Great Kanto Earthquake was visually clarified based on demographics. (6) Today, many people live densely on soft ground, with an amplification factor of 1.8 or higher, which is 23.0% of the total population. [ABSTRACT FROM AUTHOR]

Recent geodetic measurements have detected recurrent slow slip events (SSEs) in many subduction zones. Numerical simulations suggest that the recurrence intervals and magnitudes of such SSEs decrease in the later stage of the interseismic period. Therefore, activities of SSEs and their temporal variations in recurrence intervals and magnitudes provide important clues for evaluating future large earthquakes. However, our knowledge of recurrent SSEs before the establishment of dense observation networks is limited. Here, we report a possible SSE in 1973 beneath the Kii peninsula along the Nankai subduction zone, southwest Japan, where magnitude 8 class earthquakes such as the 1944 Tonankai and 1946 Nankai earthquakes repeatedly occur. The possible SSE was detected by a horizontal pendulum tiltmeter installed in 1947 at the Kishu observatory. We recovered and converted the original tilt records from 1969 to 1974 drawn on bromide (light sensitive) papers to digital tilt records. In late-November 1973, there was a slow transient signal down to the northeast of about 1.4 μrad, lasting about 1–3 days. Assuming this crustal deformation was due to an SSE, we searched for a possible fault model by adopting the already-known SSE models occurring from 1996 to 2012 as template models. Among the 42 template fault models, five models were able to qualitatively explain the direction of the observed tilt change. The centroids of these fault models were located about 30–60 km to the west of the observatory. In the source region, two magnitude 5 class earthquakes occurred before the initiation of the transient signal, and thus may be related to the occurrence of the possible SSE. In contrast, the magnitude of the calculated tilt change was about 1–2 order smaller than that of the observed tilt change. This discrepancy could be partly explained by a slip amount larger than that in the template models, which suggests that the possible SSE in 1973 was larger than those detected by recent observations. Further investigation of historical data on crustal deformation will reveal more about the temporal change in the recurrence intervals and magnitudes of SSEs during earthquake cycles of large earthquakes. [ABSTRACT FROM AUTHOR]

The Fukushima power station in Japan was affected by a major earthquake and tsunami in March 2011, inspecting the primary containment vessel remains difficult due to high radioactivity. Long-reach robot arms are useful in inspecting such hazardous environments, and a coupled tendon-driven mechanism enables realizing a long, light-weight, and thin manipulator. However, high elastic elongation of tendons due to gravity may lead to unstable joint control. In this paper, we introduce dynamics-based control as a feasible strategy for a long-reach tendon-driven robotic arm. Additionally, a planning method to identify the joint angle path ensuring stability is proposed. Considering stability analysis, the potential due to the tendon elasticity and gravity is evaluated and used as an index of joint stability. The rapidly exploring random tree is used as the planning algorithm. The effectiveness of the proposed method was demonstrated through the successful manipulation of a 5-kg payload by a 10-m long robotic arm. [ABSTRACT FROM AUTHOR]

Disaster resilience is an interdisciplinary area of study. Collaboration between humanities and sciences is important to approach issues in this area. However, science and engineering consider disaster resilience as minimizing the scientifically estimated damage induced by natural hazards. In contrast, disaster resilience studies in the social sciences tend to focus on societal vulnerability. The views between the two disciplines can lead to inconsistency or contradiction. This paper discussed this issue. To do so, the author uses the case study focusing on the effects of predictions on Nankai Trough Earthquake countermeasures in Kochi City, Japan. First, this study revealed that not only the revision of hazard prediction but the historical background of land use development affected the large-scale earthquake damage estimation in Kochi City. Second, the upward revision of hazard prediction resulted in strengthening of community disaster management. However, it also accelerated residential relocation associated with class disparities. As a result, ironically, marginalized social groups were unevenly located in predicted tsunami inundation areas. However, such issues are not considered in the existing disaster resilience scheme and policy. Based on this analysis, it is argued that communicating scientific knowledge on hazards to society alone is not enough. Considering the local context, the perspective of literacy for disaster resilience from downstream' is also important. [ABSTRACT FROM AUTHOR]

A cross-region prediction model named SeisEML (an acronym for Seismological Ensemble Machine Learning) has been developed in this paper to predict the peak ground acceleration (PGA) at a given site during an earthquake. The SeisEML model consists of hybridized models, kernel-based algorithms, tree regression algorithms, and regression algorithms. The model ablation study is conducted to examine the performance and the selection of meta-machine learning models in the SeisEML. The training and testing dataset consists of 20852 and 6256 accelerograms recorded by the Kyoshin Network, Japan. The mean absolute error (MAE) and root mean square error (RMSE) have been utilized to compare the predicted peak ground acceleration (PGA) for the test data. The SeisEML model yields approximately half the MAE and RMSE values obtained with conventional attenuation relations. The SeisEML model has been used to compute Japan's iso acceleration contour map of three earthquakes ( M JMA 7.4, 6.6, and 6.1). The qualitative comparison of iso acceleration contours obtained from actual and predicted PGA using SeisEML clearly shows that the model can reliably predict the PGA distribution during an earthquake compared to the regional ground motion prediction equation (GMPE). The cross-region prediction was performed on the datasets of the Iranian earthquakes using SeisEML. The comparison of predicted and observed peak ground acceleration in terms of MAE and RMSE shows that the machine learning model's performance is superior to the regional attenuation relation. The predictions of PGA from the developed ML model indicate that this trained model has the potential for predicting regional and global scenarios with similar tectonic setups. The ML model developed in this paper can considerably enhance the reliability of PGA prediction for seismic hazard mapping of any region and can serve as a reliable substitute for GMPEs. [ABSTRACT FROM AUTHOR]

Background. The significance of mutual-help in communities for disaster management is a fundamental important concept. However, the current societal state does not reflect this lesson. S&G (Simulation and Gaming) has the potential to overcome the challenges faced in promoting community-based disaster management. No scientific research is currently present that reviews their achievements in Japan. Aim. This paper analyzes the current achievements of S&G in enhancing community resilience against large-scale earthquakes in Japan. Method. The paper clarifies the theoretical advantages of S&G in enhancing community resilience in coping and adaptive capacity plus proposes a conceptual contribution framework of S&G in improving community resilience. Based on this framework, the paper analyzes some major games that tackle community resilience against earthquakes in Japan. Results. The paper demonstrates the achievements through the S&G spectrum that stresses the disastrous experience with specific resilience views on one side, while decision making for critical reflection from other players with more comprehensive resilience views on the other side. Conclusion. The paper showcases the current S&G achievements in enhancing community resilience against large-scale earthquakes in Japan using the proposed framework, which can be utilized by other disaster-prone countries to develop and evaluate applications of S&G for increasing community resilience against earthquakes. [ABSTRACT FROM AUTHOR]

The Great East Japan Earthquake that occurred on March 11, 2011, was one of the largest natural disasters in modern times. Publication in medical journals is important aspects of the academic promotion process, and is thus important for all scientists. However, little is known about whether and how substantial natural disasters affect gender disparities in academic productivity in disaster-affected areas. We hypothesized that the Great East Japan Earthquake widened the existing disparities in scientific publishing between male and female researchers. To test this hypothesis, this retrospective observational study using existing databases was conducted. We extracted from the MEDLINE database all types of biomedical articles published from March 11, 2007, to March 11, 2015, by three medical universities in a disaster-affected area of Japan. Differences in the proportion of female first authorship during the 4 years before and after the Great East Japan Earthquake were compared. A total of 5,873 papers were analyzed. The proportion of female first authors significantly declined after the Great East Japan Earthquake (20.5% vs. 14.1%; odds ratio 0.64; 95% confidence interval 0.56-0.73). A similar trend was identified across all prespecified subgroups, including clinical department; original article; public medical university; and prestigious journal with impact factor >6. Reference data from two medical universities minimally affected by the Great East Japan Earthquake showed the opposite trend. These results collectively suggest that large natural disasters can reinforce existing gender disparities in first authorship in biomedicine.

In this paper, we simulate the economic loss resulting from supply chain disruptions triggered by the Great East Japan Earthquake (GEJE) in 2011, applying data from firm-level supply chains and establishment-level attributes to an agent-based model. To enhance the accuracy of the simulation, we extend data and models in previous studies in four ways. First, we identify the damage to production facilities in the disaster-hit regions more accurately by using establishment-level census and survey data and geographic information system (GIS) data on the damages caused by the GEJE and subsequent tsunami. Second, the use of establishment-level data enables us to capture supply chains between non-headquarter establishments in disaster-hit regions and establishments in other regions. Third, we incorporate the effect of power outages after the GEJE on production reduction, which exacerbated the effect of the supply chain disruption, particularly in the weeks immediately after the GEJE. Finally, our model incorporates sectoral heterogeneity by employing sector-specific parameters. Our findings indicate that the extended method can significantly improve the accuracy of predicting the domestic production after the GEJE, particularly due to the first three improvements utilizing various data sources, not because of the use of more sector-specific parameters. Our method can be applied to predict the economic effect of future disasters, such as the Nankai Trough earthquake, on each region more precisely., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Inoue et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper discusses the relationship between the vertical ground motion and ionospheric disturbances before the Kumamoto earthquake on 16 April 2016, in Kyushu, Japan, using the vertical ground motion measured by slant gauges widely distributed in Kyushu, and the NmF2 observed by ionosondes in Japan and another region. We provide evidence that vertical ground motion excites internal gravity waves (IGWs) that disturb changes in the ionospheric plasma density. From the spectral analysis results of the vertical ground motion data, the summation of various period (frequency) components analyzed from the original data of the slant gauge shows a possible correlation with the change of NmF2 before the earthquake. On the other hand, the influence of the geomagnetic disturbance on vertical ground motion seems to exist. However, we cannot confirm that vertical ground motion is influenced by the geomagnetic disturbance (Kp index) and that the earthquake is triggered by the geomagnetic disturbance. There are two conditions for the vertical ground motion to disturb variations in the ionospheric plasma density: (1) The effective vertical ground motion period should be shorter than 5 h. In addition, (2) vertical ground motion should continue to exist so that wave energy can be continuously injected into the atmosphere. A possible mechanism with which to modify the ionosphere is discussed. The results of this study can provide a basis for the future ionospheric precursors of earthquakes by using the vertical ground motion. [ABSTRACT FROM AUTHOR]

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This paper summarizes the results of 10 years of research on models of the megathrust earthquake cycles and crustal deformation associated with the 2011 Tohoku-oki earthquake. Several earthquake cycle models have been proposed for the northeast Japan subduction zone to elucidate why megathrust earthquakes occur at intervals of approximately 600 years and why large slips occurred in the shallow subduction zone. A model that considers a strong asperity in the shallow plate interface, and a hierarchical asperity model that considers the scale dependence of the critical displacement of the rate- and state-dependent friction law have been proposed. Modeling with dynamic weakening of faults has also been proposed. In the model using the shallow friction characteristics obtained by the Japan Trench Fast Drilling Project, rupture from depth can propagate to the trench, resulting in shallow large slips. Submarine crustal deformation has been observed for the first time in addition to dense observations of the inland crustal deformation. The observation of the seafloor deformation near the trench showed that viscoelastic relaxation played an important role in short-term postseismic deformation near the trench. The effects of the low-viscosity region at the oceanic lithosphere and asthenosphere boundary, and the cold forearc mantle wedge (cold nose) have been discussed. Simulations using the nonlinear flow law of rock in the mantle, where a power–law relationship holds between stress and strain rate, and the fault friction law at the plate boundary, show that the Tohoku-oki earthquake caused large stress fluctuations, resulting in a sudden viscosity decrease and rapid flow in the asthenosphere below the oceanic lithosphere. The simulations of the crustal deformation associated with the Tohoku-oki earthquake cycle also indicate that in the later stage of the earthquake cycle, the Pacific coastal region begins to subside due to the increasing slip deficit rate on the deeper parts of the plate interface. These results explain the subsidence of the Pacific coast of northeast Japan observed for about 100 years prior to the Tohoku-oki earthquake. In the future, a model that explains the long-term crust and mantle deformation during the entire Tohoku-oki earthquake cycle must be constructed. [ABSTRACT FROM AUTHOR]

In Japan, recently there has been an increase in the failure of dry masonry retaining walls located in an urban residential area due to strong earthquakes. However, currently there are no established optimal seismic reinforcement methods for such dry masonry retaining walls due to issues related to workability and construction cost. This paper presents a novel reinforcement method wherein the tilting reinforcement bars were installed from top of the retaining wall whose individual blocks were integrated. A detailed investigation and discussion on the mechanical behavior of a dry masonry retaining wall is made by comparing the results among different experimental cases which had different seismic reinforcement treatment with the help of tilting table experiments conducted in a geotechnical centrifuge. The results highlighted that the proposed method, the application of tilting reinforcement bars together with the integration of individual wall blocks, led to the best seismic resilient performance of the retaining wall with the least measured soil deformations and soil strains at the backfill. Among all the tested cases, the proposed method resulted in the least mobilization of axial force and bending moment at the top of reinforcement bars which may result in the overall reduction of the construction cost (i.e., by reducing the number of reinforcement bars) aiming toward a performance‐based design. Lastly, an analytical evaluation of the factor of safety (FOS) against collapse as per the Mononobe‐Okabe theory was made which was found to be in excellent agreement with the centrifuge experiments revealing the proposed method to perform best among all the cases. [ABSTRACT FROM AUTHOR]

The role of non‐structural elements (NSEs) in the seismic performance of buildings has been highlighted in past years. Research studies following state‐of‐the‐art methodologies generally find that when the structural collapse is not of significant concern, NSEs tend to dominate the repair costs and financial investment required in a building. This paper examines field observations from interviews and data collected from commercial buildings via structural health monitoring (SHM) following the 2018 Osaka earthquake in Japan. It suggests that fragility functions used in current methodologies for estimating NSE damage may not be entirely representative of the in‐situ reality and possibly underestimate actual damage. Additionally, interviews with building owners/managers indicate that the alarm and financial impact of NSEs was not as critical as anticipated, with much of the observed NSE damage not of serious concern and tolerable in many cases. This article provides discussion and insight into possible causes for these differences before discussing how current methodologies can benefit from these observations. It is believed that many of the fragility functions currently used to estimate NSE damage may not be representative because of differences in installation conditions and loading protocols used in experimental testing, possible interaction with other elements, variability in the quality of workmanship during installation and possible wear, tear and degradation during service. On the other hand, it is seen how SHM data recorded during seismic events may provide valuable data for an alternative means to develop fragility functions. Furthermore, it is seen that when building recovery states (RSs) other than the implicitly assumed 'full recovery' state used in guidelines like FEMA P‐58 are explored, the role of NSEs in direct monetary losses significantly reduces. This coincides with the field observations in Japan regarding the impact of NSEs and supports the recent developments in functional recovery on what building owners and occupants are prepared to tolerate post‐earthquake. It indicates that when discussing the relative importance of different building performance groups, it is vital that the expected RS is also stated, as for most decision‐makers following major events, functionality rather than full recovery remains the primary goal; hence, repairs and proactive measures should bear this in mind for more effective use of resources. [ABSTRACT FROM AUTHOR]

Understanding the location of risk to natural hazards, namely the areas of high exposure and vulnerability is a major priority that was identified by the Sendai framework for Disaster Reduction 2015-2030 in order to reach substantial reduction of disaster risk. It is also a necessary decision-making tool for disaster mitigation policy-makers in Japan and around the world. This paper successfully develops a simple methodology using only open data to build the first large-scale (whole country), fine resolution (sub-municipal level) social vulnerability analysis in the context of five different types of natural hazards (earthquake, tsunami, storm surge, flooding and landslide). The result is then compared to an indicator of exposure of population to these hazards in Japan in order to propose a representation of disaster risk. Results show that vulnerability in Japan is highly heterogeneous with urban/rural and north/south fractures. Combining the social vulnerability index with exposure analysis, results show a wide variety of spatial patterns of risk areas in Japan., (© 2023. The Author(s).)

Shikoku island, southwestern Japan lies in the western Nankai Trough and showcases along-strike segmentation of slow earthquake behavior. Whether the spatial variation of tremor behavior reflects the regional differences in structure/source properties and how much such differences can be recognized by the seismic signals themselves are two questions addressed in this paper. Taking advantage of advanced methods in recognizing and classifying signals using machine learning approaches, we attempt to answer them by conducting signal classification experiments in Shikoku. Based on the tremor catalog from 1 June 2014 to 31 March 2015, the tremors recorded in four different areas were treated as different classes and segmented into 60-s-long signals. The number of tremors in four different areas (A to D, from west to east) reached 15,000, 31,000, 10,000, and 16,000, respectively. To efficiently distinguish between tremors from different areas, we applied a k-nearest neighbor (k-NN) classifier with Fisher's class separability criteria to select the optimal feature subset. The resulting classification performance reached more than 90% at all 12 stations. We further designed a triangle test to select the features that can better represent the differences in source properties between areas. We found that the most efficient features were associated with (1) the number of peaks in the temporal evolution of discrete Fourier transforms and (2) the energy distribution in the autocorrelation function (ACF). To match the difference in behavior revealed by the ACF, the size of the tremor zone, which mainly controls how long the seismic energy lasts in a tremor episode, was determined to be largest in Area B and smallest in Area C. The heterogeneity of the asperities in a tremor zone, which may control how spiky the tremor signals developed over time, was determined to be strong in Areas B and C. Together with previously documented variations in slow earthquake behavior in the same area, we finally propose a conceptual model that provides a better understanding of the regional differences in the tremor source properties in Shikoku, Japan. [ABSTRACT FROM AUTHOR]

This paper presents a rapid or real-time estimation method of the economic value of direct stock damages caused by significant earthquakes in Japan. The result will contribute to both the government and private sectors' early decision-making, particularly for provisional budget allocation. First, we developed a simple but evidence-based model for estimating stock losses explained by a representative earthquake hazard factor and an exposure factor, i.e., seismic intensity and existing stock of physical assets. The key characteristic of our estimation model is that the dependent variable is prefectural damage amount. Still, the explanatory variables come from municipal sources: we overcome this data availability problem through our estimation process. Second, we carefully checked the model's specification, estimation, and performance to be soundly applied to a real-time assessment of future earthquake events. We also explain the automated measuring of the prefectural direct loss value and its distribution to every 250 m mesh. Finally, we show two examples of the application of our model; one is the case of the 2018 Northern Osaka Earthquake, and the other is the anticipated Tokyo inland earthquake. [ABSTRACT FROM AUTHOR]

Slow earthquakes are episodic slow fault slips. They form a fundamental component of interplate deformation processes, along with fast, regular earthquakes. Recent seismological and geodetic observations have revealed detailed slow earthquake activity along the Japan Trench—the subduction zone where the March 11, 2011, moment magnitude (Mw) 9.0 Tohoku-Oki earthquake occurred. In this paper, we review observational, experimental, and simulation studies on slow earthquakes along the Japan Trench and their research history. By compiling the observations of slow earthquakes (e.g., tectonic tremors, very-low-frequency earthquakes, and slow slip events) and related fault slip phenomena (e.g., small repeating earthquakes, earthquake swarms, and foreshocks of large interplate earthquakes), we present an integrated slow earthquake distribution along the Japan Trench. Slow and megathrust earthquakes are spatially complementary in distribution, and slow earthquakes sometimes trigger fast earthquakes in their vicinities. An approximately 200-km-long along-strike gap of seismic slow earthquakes (i.e., tectonic tremors and very-low-frequency earthquakes) corresponds with the huge interplate locked zone of the central Japan Trench. The Mw 9.0 Tohoku-Oki earthquake ruptured this locked zone, but the rupture terminated without propagating deep into the slow-earthquake-genic regions in the northern and southern Japan Trench. Slow earthquakes are involved in both the rupture initiation and termination processes of megathrust earthquakes in the Japan Trench. We then compared the integrated slow earthquake distribution with the crustal structure of the Japan Trench (e.g., interplate sedimentary units, subducting seamounts, petit-spot volcanoes, horst and graben structures, residual gravity, seismic velocity structure, and plate boundary reflection intensity) and described the geological environment of the slow-earthquake-genic regions (e.g., water sources, pressure–temperature conditions, and metamorphism). The integrated slow earthquake distribution enabled us to comprehensively discuss the role of slow earthquakes in the occurrence process of the Tohoku-Oki earthquake. The correspondences of the slow earthquake distribution with the crustal structure and geological environment provide insights into the slow-earthquake-genesis in the Japan Trench and imply that highly overpressured fluids are key to understanding the complex slow earthquake distribution. Furthermore, we propose that detailed monitoring of slow earthquake activity can improve the forecasts of interplate seismicity along the Japan Trench. [ABSTRACT FROM AUTHOR]

In Japan, natural disasters have historically caused massive damage, and the importance of emergency temporary housing is increasing. In this paper, the summer thermal environment at the Shirahata temporary housing site in Kousa Town was assessed. The site was constructed following the 2016 Kumamoto Earthquake. The site was improved by applying a design methodology called "Kumamoto Type D," "D" stands for "Default & Design." Field measurements and computational fluid dynamics simulations were conducted to investigate the influence of the building arrangement on the outdoor thermal environment for the Kumamoto Type D layout. The results indicated that the impact of wind was reduced using this layout. However, when the surface temperature in the parking lot and other areas increased, hot air could be transmitted to the site, even under reduced wind conditions. [ABSTRACT FROM AUTHOR]

Real‐time tsunami prediction is necessary for tsunami forecasting. Although tsunami forecasting based on a precomputed tsunami simulation database is fast, it is difficult to respond to earthquakes that are not in the database. As the computation speed increases, various alternatives based on physics‐based models have been proposed. However, physics‐based models still require several minutes to simulate tsunamis and can have numerical stability issues that potentially make them unreliable for use in forecasting—particularly in the case of near‐field tsunamis. This paper presents a data‐driven model called the tsunami runup response function for finite faults (TRRF‐FF) model that can predict alongshore near‐field tsunami runup distribution from heterogeneous earthquake slip distribution in less than a second. Once the TRRF‐FF model is trained and calibrated based on a discrete set of tsunami simulations, the TRRF‐FF model can predict alongshore tsunami runup distribution from any combination of finite fault parameters. The TRRF‐FF model treats the leading‐order contribution and the residual part of the alongshore tsunami runup distribution separately. The interaction between finite faults is modeled based on the leading‐order alongshore tsunami runup distribution. We validated the TRRF‐FF modeling approach with more than 200 synthetic tsunami scenarios in eastern Japan. We further explored the performance of the TRRF‐FF model by applying it to the 2011 Tohoku (Japan) tsunami event. The results show that the TRRF‐FF model is more flexible, occupies much less storage space than a precomputed tsunami simulation database, and is more rapid and reliable than real‐time physics‐based numerical simulation. Plain Language Summary: Timely tsunami warning is important to save lives and property. Existing physics‐based models require a lot of time to predict tsunamis. For this reason, many countries rely on a precomputed tsunami simulation database for tsunami warning. However, such databases do not include all possible tsunami scenarios, because in the real world there is almost an infinite number of possible tsunamigenic‐earthquakes. The present study introduces a new data‐driven model that can rapidly predict the maximum onshore tsunami height along the coast from the earthquake information. Once the model is trained based on physics‐based model simulations, the new model can be applied to any possible tsunami scenario. This new model captures the leading‐order contribution and the residual part of the alongshore tsunami runup distribution separately. This new model can account for complex large earthquakes with different land movements depending on location. We tested this new model using artificial earthquake scenarios as well as the historic Japan earthquake from 2011. The results show that the new model can handle wider variety of scenarios than the traditional database approach, and the new model takes up less storage space. Moreover, the new model is more rapid and reliable than a physics‐based model. Key Points: A rapid data‐driven model is proposed that can predict tsunami runup distribution from heterogeneous earthquake slip distributionThe data‐driven model is validated based on synthetic tsunami scenarios and the 2011 Tohoku tsunamiThis model has potential for supporting real‐time tsunami forecasting [ABSTRACT FROM AUTHOR]

In this paper, we explore the Western Pacific subduction impact on the geodynamics of the Asian continent. The data on migration of slow strain and earthquakes from the Nankai, Japan and Kuril-Kamchatka segments of the Western Pacific subduction zone deep into mainland Asia are analyzed. The calculations performed on five profiles, crossing the Kuril Islands, the Japanese Archipelago and Sakhalin Island toward the Asian continent, have revealed the transverse migration of earthquakes from the Japan–Kuril-Kamchatka subduction zone. The velocities of hypocenter migration of M ≥ 4.5 earthquakes from the Kuril-Kamchatka Trench via northern and central Sakhalin vary from 6 to 17 km/year, on average, at different depths. The profiles crossing the islands of Hokkaido and Sakhalin show the M ≥ 4.earthquake migration from the Kuril and Japan trenches at velocities of 8–27 km/year. [ABSTRACT FROM AUTHOR]

A modified k-nearest-neighbors method is introduced that provides an efficient nonlinear estimate of the intensity of a point process (field) based on locations of events. The method is applied to perform a detailed statistical analysis of the spatial structure of the seismic intensity field (in the context of this paper, the term "intensity" refers to the intensity of the seismic field, and should not be mistaken for the intensity of ground motion caused by an earthquake). The proposed method requires neither a preliminarily delineated area nor a normalization procedure for the estimates. In contrast to many interpolation methods, estimates based on the proposed method are statistically justified. The "uncertainty relation" between the spatial smoothing effect and random errors is established for the method in an explicit form. A procedure for choosing the number of nearest neighbors k* that controls the effective radius of smoothing is suggested. The proposed method is applied to analyze the seismic intensity field in two seismogenic regions surrounding the Kuril Islands and Japan during the period from 1904 to 2011. Spots of increased seismic activity in these regions are localized by the new method, and some quantitative statistical characteristics of these spots are determined and discussed. [ABSTRACT FROM AUTHOR]

In this paper, we explore the use of seismicity data on a single-station basis in site response characterization. We train a supervised deep-learning model, SeismAmp, to recognize and separate seismic site response with reference to seismological bedrock (VS  = 3.45 km s−1) in a broad frequency range (0.2–20 Hz) directly from single-station earthquake recordings (features) in Japan. Ground-truth data are homogeneously created using a classical multistation approach—generalized spectral inversion at a total number of 1725 sites. We demonstrate that site response can be reliably separated from single-station seismograms in an end-to-end approach. When SeismAmp is tested at new sites in both Japan (in-domain) and Europe (cross-domain), it achieves the lowest standard deviation among all tested single-station techniques. We also find that horizontal-to-vertical spectral ratio (HVSR) is not the optimal use of single-station recordings. The individual components of each record carry salient information on site response, especially at high frequencies. However, part of the information is lost in HVSR. SeismAmp could lead to improved site-specific earthquake hazard prediction in cases where recordings are available or can be collected at target sites. It is also a convenient tool to remove repeatable site effects from ground motions, which may benefit other applications, for example, improving the retrieval of seismic source parameters. Finally, SeismAmp is trained on data from Japan, future studies could explore transfer learning for practical applications in other regions. [ABSTRACT FROM AUTHOR]

Japan has an established tradition of museums commemorating its long history of disasters, which memorialize lives lost and convey the scientific mechanisms of natural hazards, disaster history, and people's experiences during and after disasters. The first part of this paper provides an overview of seven modern disaster museums in Japan established before 3.11, starting from the museum of the 1923 Great Kanto Earthquake. These seven museums commemorate disasters of different types, time, and scales of damages. Considering their shared commonalities and individual characteristics, it describes the components and approaches of exhibits that these museums use to convey experiences and stories of disasters, passing on local knowledge toward future disaster risk reduction. The second part of the paper provides an overview of new museums and exhibit facilities established to commemorate the 3.11 Great East Japan Earthquake, tsunami, and nuclear disaster of March 11, 2011. The scale of the devastation of 3.11, as well as an explosion of interest and support for activities of memorialization, documentation, and exhibition, has resulted in a variety and decentralization of new museums and exhibit spaces throughout the area affected by the 3.11 disaster. Spanning various combinations and types of exhibit facilities, this paper concludes by considering emergent trends compared to pre-3.11 disaster museums and potential future developments. [ABSTRACT FROM AUTHOR]

Some previous disaster studies in the field of sociology suggest that it is not sufficient for victims to recover only by rebuilding their houses. Then, what other factors are important for their recovery? This paper aims to address two questions based on the results of a questionnaire survey of the disaster public housing residents in Otsuchi Town, which we have been conducting since 2016: 1) whether many of the victims feel they have made a recovery, and 2) why. We made four observations during our research: 1. Victims' sense of their own recovery was low in 2019, as more than 50% of the respondents considered their recovery level as only half or less than the acceptable level for them. 2. Important factors that may affect victims' sense of their own recovery were found to be stability of budget, degree of health and well-being, and degree of social inclusion. 3. The respondents raised the following issues related to their lives, which need to be resolved--"it's too hot or cold," "undesired noise," "inconvenient transportation system," and "weak human relationships in the housing complex or local neighborhood." 4. It seems there are gaps in perception between the public recovery policies, the victims' lifestyle, and their cognition of the recovery process. In conclusion, this paper suggests the following to reduce the abovementioned gap: 1. Policymakers need to consider the climate of the affected areas to build better disaster public housing. 2. Policymakers must promote not only tangible recovery (e.g., rebuilding houses and infrastructure) but also intangible recovery (e.g., reconstructing the transportation system to enhance residents' health and well-being). 3. When supporters and local community leaders coordinate and promote interactions among neighbors to build new communities, they must bear in mind that diverse people from diverse regions live in disaster public housing, and not everyone likes interacting with people (in fact, problems emerge among residents when they are forced to become close to each other). The right people are needed in the right posts for the success of such interactions. [ABSTRACT FROM AUTHOR]

Coastal regions around the Pacific Ring of Fire share the risk of massive earthquakes and tsunamis. Along with their own political-economic, cultural and biophysical contexts, each region has their own history and experiences of tsunami disasters. Coastal areas of Washington State in the U.S. are currently at risk of experiencing a tsunami following a massive Magnitude 9 (M9) earthquake anticipated in the Cascadia Subduction Zone (CSZ). Looking ahead to consider adaptive planning in advance of a tsunami following this M9 event, this paper explores how lessons from recent megaquake- and tsunami-related experiences of risk-based planning and relocation in coastal areas of Japan and Chile could inform anticipatory action in coastal Washington State. Based on a comparison of earthquake and tsunami hazards, social factors, and the roles of government, this paper outlines a framework to compare policy contexts of tsunami risk-based planning and relocation in three Ring of Fire countries, including factors shaping the possible transfer of approaches between them. Findings suggest some aspects of comparative significance and commonalities shared across coastal communities in the three countries and at the same time highlight numerous differences in governance and policies related to planning and relocation. Although there are limitations to the transferability of lessons in disaster adaptive planning and anticipatory action from one national/regional context to another, we believe there is much more that Washington and the Pacific Northwest can learn from Japanese and Chilean experiences. In any context, risk reduction policies and actions need to garner political support in order to be implemented. Additional case study research and detailed analysis is still needed to understand specific lessons that may be applied to detailed risk-based planning and relocation programs across these different national contexts. [ABSTRACT FROM AUTHOR]

Crustal earthquakes are generally recognized as having recurrence periods of more than 1000 years. However, in northern Ibaraki Prefecture, Japan, two moderate-sized earthquakes occurred on almost the same fault plane in 2011 and 2016. Moreover, it has been reported that the slip distributions derived from crustal deformation data from these two events are almost identical. We performed a near-field waveform inversion analysis to estimate the details of the spatiotemporal distribution of the co-seismic rupture. Our results reveal large slip areas during each earthquake at different locations across the bend of the fault plane. These results indicate that the shear stress of the fault area where the main slip occurred during the 2011 event was not rebuilt in such a short period, a phenomenon that had not previously been discussed for this sequence. Our results also suggest that the fault geometry affected such complex fault ruptures. [ABSTRACT FROM AUTHOR]

In this paper we investigate whether destruction due to natural disasters induces industries to increase their regional production efficiency using the case of pre-war Japan, a setting of frequent disasters and technological upgrading. To this end we compile a regional sectoral dataset of natural disaster destruction and production for machinery and textiles. We then employ a stochastic frontier analysis (SFA) approach to estimate the role of disaster events on changes in production efficiency. Our results show that earthquakes led to increases in efficiency for both machinery and textiles, although they were substantially greater for textiles due to the recovery persisting longer. Overall earthquakes contributed 6.8% of efficiency gains in textiles and 3.1% in machinery. However, allowing events to compound in their impact showed that such gains were dampened when there were damaging earthquakes in subsequent years. In contrast, for climate-related natural disaster events there is only weak, if any, evidence that these played a significant role in determining productive efficiency. [ABSTRACT FROM AUTHOR]

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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 FROM AUTHOR]

In Japan, campaigning over the Internet was once strictly prohibited, but this ruling was finally reversed for the 2013 election as a result of observations of the US presidential campaigns and the effects of the Great East Japan Earthquake of March 11, 2011. The United States has few restrictions on Internet campaigning and a longer history of the use of the Internet in elections. Internet campaigns promote grassroots movements and connect politicians and voters. However, certain side effects have also appeared: (1) they have enhanced nationalism and polarization through selective contact behavior, (2) they are vulnerable to foreign interventions such as hacks, trolling, and micro-targeting, and (3) they increase the emotional use of words, a tendency that has progressed as media formats changed from party papers to penny papers, from radio to television, and from homepages to social networking systems. This paper will analyze election campaigns using the Internet, comparing the present state of the United States and Japan. [ABSTRACT FROM AUTHOR]

Because information and communication technology (ICT), especially Web 2.0 interactivity and ubiquitous connectivity, enhances citizen coproduction, ICT tool deployment in disaster relief has a great potential for improving disaster logistics by, for example, promoting awareness of real-time needs in affected areas and ensuring visibility among actors. This paper describes how ICT tools, especially Web 2.0, can influence the effectiveness and efficiency of disaster logistics. The paper provides a conceptual framework of issues around disaster logistics based on a literature review. It then examines the case of the Great East Japan Earthquake and Tsunami of 2011 to address how ICT tools can support disaster logistics operations. The findings suggest that, although implementation of Web 2.0 was still in its infancy at the time of the earthquake and tsunami, it helped to address some issues of disaster logistics, such as assessing community needs and storing, transporting, and distributing supplies. In addition, this paper argues that combining the use of various ICT tools would be an effective way for a community to manage disaster logistics because each ICT tool has its own value. In addition, because ICT tools widen the range of actors involved in disaster logistics operations, effective coordination between these grassroots agile web-connected activities and traditional hierarchical logistics operations is important. [ABSTRACT FROM AUTHOR]

Rupture size is a fundamental earthquake source parameter that is challenging to infer independently from far‐field seismological observations. Here, we develop a novel observational constraint on source size based on the decay rate of wavefield coherence across a seismic array. For a given earthquake, waveform coherence decays with increasing interstation distance or, more precisely, with increasing projection difference defined as the difference between the takeoff vectors associated to the two stations projected along the rupture direction. We find that coherence generally falls off with projection difference faster for earthquakes of larger magnitudes. The magnitude dependence of the coherence decay rate can be explained by a finite source effect: larger source sizes cause larger differences of phase delays between waves arriving from different parts of the rupture at different stations, hence a stronger spatial variability of the wavefield, resulting in a breakdown of waveform coherence. Assuming a 1‐D Haskell's source model, the rupture size can be estimated from the coherence decay rate. We apply this method to USArray data of earthquakes in three subduction zones, the Sea of Okhotsk, South America and Japan. The source sizes inferred from the coherence decay patterns are consistent with scaling relations intermediate between width‐saturated L‐models and quasi equi‐dimensional rupture models. Our observation captures a unique pattern of array waveform coherence and demonstrates the potential of utilizing waveform coherence to study earthquake source parameters. Plain Language Summary: In this paper, we observe that for a given earthquake, the similarity of the waveform (coherence) recorded by stations in a far‐field array decays with increasing interstation distance. The waveform coherence generally falls off with interstation distance faster for earthquakes of larger magnitudes and therefore, larger rupture sizes. We develop a novel method using array waveform coherence to estimate the earthquake rupture size, and apply this method to USArray data of earthquakes in three geological regions: the Sea of Okhotsk, South America and Japan. The source sizes inferred from the coherence decay patterns are consistent with previous studies using different methods. According to our observation, there is a potential to infer earthquake rupture independently from far‐field observations by waveform coherence. Key Points: Waveform coherence decays as a function of interstation distance faster for large earthquakes (Mw > 7)The waveform coherence pattern is governed by earthquake source sizeRupture sizes inferred from waveform coherence satisfy empirical scaling relations [ABSTRACT FROM AUTHOR]

Since the appearance and evolution of earthquake ionospheric precursors are expected to show a nonlinear and complex behaviour, the use of nonlinear predictor models seems more appropriate. This paper proposes a new approach based on deep learning as a powerful tool for extracting the nonlinear patterns from a time series of ionospheric precursors. A Long Short-Term Memory (LSTM) network as a type of Recurrent Neural Network (RNN) was used to investigate 52 six-month time series, deduced from the three Swarm satellite (Alpha (A), Bravo (B) and Charlie (C)) measurements, including electron density (Ne), electron temperature (Te), magnetic scalar and vector (X, Y, Z) components, Slant and Vertical Total Electron Content (STEC and VTEC), for day and night periods around the time and location of a seismic event. This new approach was tested on a strong Mw = 7.1 earthquake in Japan on 13 February 2021, at 14:07:50 UTC by comparing the results with two implemented methods, i.e., Median and LSTM methods. Furthermore, clear anomalies are seen by a voting classification method 1, 6, 8, 13, 31 and 32 days before the earthquake. A comparison with atmospheric data investigation is further provided, supporting the lithosphere–atmosphere–ionosphere coupling (LAIC) mechanism as a suitable theory to explain the alteration of upper geolayers in the earthquake preparation phase. In other words, using multi-method and multi-precursor analysis applied to 52 time series and also to the orbit-by-orbit investigation, the observed anomalies on the previous day and up to 32 days before the event in normal solar and quiet geomagnetic conditions could be considered as a striking hint of the forthcoming Japan earthquake. [ABSTRACT FROM AUTHOR]

On 11 March 2011, a catastrophic earthquake and subsequent tsunami hit the Pacific coast of northern Japan, devastating many of the towns, villages and coastal ecosystems located along the shoreline. To assess the impacts of the disaster, we investigated temporal dynamics of fish and epibenthic megafaunal community structure in relation to changes in a range of physical, biological and anthropogenic variables between 2007 and 2018 in Onagawa Bay. Commercially important fish such as greenlings, Japanese anchovy, flatfishes, rockfishes were consistently abundant in both larval and adult fish assemblages. While abundance, species richness, and Shannon index H' for adult fish and epibenthic megafaunal assemblages increased significantly soon after the disaster to peak values towards the end of the study period, the same metrics did not change accordingly for larval fish assemblages. Temporal dynamics of larval fish community clearly demonstrated significant seasonal variation along with changes in large-scale environmental conditions such as temperature and nutrients. However, anthropogenic components such as decline in human population, reduction in fishing pressure and the recovery of aquaculture operations significantly explained the observed post-disaster change in adult fish and epibenthic megafaunal communities. The pelagic and benthic components of Onagawa Bay appeared to have responded to the 2011 disaster very differently, and this study suggests the post-disaster recovery and dynamics of the coastal ecosystems may be regulated by how human societies respond to the impacts of a tsunami catastrophe through their influences on benthic habitat of ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The Kumamoto area includes 11 municipalities and a population of about one million. The area represents the largest total use of groundwater in Japan. The main recharging area for this groundwater used to be paddy fields for rice production located along the mid-stream section of the Shirakawa River. In the past few decades, the area of paddy fields has rapidly decreased due to the Japanese government's rice production adjustment policy and urbanization. In consequence, the groundwater recharge decreased from 656.2 million m3 in 1992 to 606.9 million m3 in 2006. Thus, groundwater recharge from paddy fields only might not be sufficient for groundwater demand in the future. For this reason, an artificial recharge system was established to increase groundwater recharge. In this study, we review the history of groundwater management and results of 14 years' operation of a large-scale artificial groundwater recharge project in the Kumamoto area. We visualize the resilience of the groundwater management and recharge project by influence of the 2016 Kumamoto Earthquake. It is shown that through an integrated approach of all societal groundwater stakeholders, a sustainable groundwater management can be achieved. The hydrological methods in this integrated approach quantify recharging groundwater volumes for different types of recharge fields by use of 170 local experimental observations. Results and experiences outlined in this paper can be used by planners and managers of dwindling groundwater resources to build resilient systems for groundwater recharge by involving all societal stakeholders through an integrated approach. [ABSTRACT FROM AUTHOR]

Peak ground acceleration (PGA) is a key parameter used in earthquake early warning systems to measure the ground motion strength and initiate emergency protocols at major projects. The traditional P -wave peak displacement-dependent PGA prediction model (Pd-PGA model) tends to underestimate the PGA for large earthquakes because it cannot make full use of the fault continuity rupture information hidden in the time-varying process of ground motion. In this paper, a continuous PGA prediction long short-term memory (LSTM) neural network model is proposed. The model takes eight sequential features of stations that are proxies of the energy and other physical parameters as input and provides the recorded PGA at the station as the target output. A total of 5961 records from 119 earthquakes recorded by the Japanese Strong-Motion Earthquake Network (K-NET) in Japan are used to train the neural network and 3433 records from 73 earthquakes are used as the test set to verify the model's generalization ability. The results show that within the same data set, the residuals of the predicted PGA for the proposed model are smaller than those of the Pd-PGA model and that the problem of PGA underestimation is resolved. The prediction accuracy also improves with increasing sequence length, which indicates that the LSTM neural network learns the rules hidden in the time series. To further verify the model's generalization ability, the model performance is analyzed for an M 7.3 earthquake that was not included in the training or test data sets. The results show that the residuals of the predicted PGA for the event are consistent with those for the test data set, indicating that the model has good generalization ability. [ABSTRACT FROM AUTHOR]

The motivation of this study stems from a retaining wall made of waste tires. The wall did not suffer any earthquake or tsunami-induced damage during the 2011 Off the Pacific Coast of Tohoku Earthquake, Japan. This paper deals with a case study on this tire retaining wall. Results from a series of field and laboratory investigations are first described. A numerical simulation is also described in which whole tires were used as protective layers in an embankment. The results show that confining effect of each tire, friction between the tires, ductility, and damping inherent in tires contribute towards the excellent performance of the retaining wall during the earthquake loading. The case study also reveals that it is the isolation mechanism due to the vibration absorption capability of rubber particles in tires, which could protect tire retaining structure during the earthquake. [ABSTRACT FROM AUTHOR]

This paper proposes a Bayesian model selection framework to determine optimal, parsimonious models for given building structures under ground motion excitation using stochastic filtering. Structural system identification at a regional scale after an earthquake is nominally a monumental task due to its inherently high computational cost. This challenge is currently addressed in the literature by using simplified structural models that bear analytical solutions, such as Timoshenko or shear beams, and shear building models. However, a low computational effort usually leads to an increased prediction error and consequently, a higher model uncertainty. This poses the dilemma of prediction accuracy versus model complexity when selecting a model class to represent a building structure. The proposed framework selects the model class that strikes the best balance between the two. To this end, the notion of cumulative evidence is introduced here as the integral of local evidence over the ground motion duration, which is then formulated as the difference between the cumulative likelihood of the observed measurements and the cumulative penalty. The likelihood measure promotes models whose predictions better match the observations. This is counteracted by the penalty, which is devised as an "Ockham factor," and penalizes models with higher information gains due to their higher complexities, for example, a larger number of parameters. The proposed approach also yields the best tuning parameters of the stochastic filter for each model class and the best initial values of the identification parameters. The proposed framework is verified using a synthetic example, and validated using recorded data from the Millikan Library building in California and the ANX building in Japan. [ABSTRACT FROM AUTHOR]