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Sensitizers are used to prepare photosensitive materials for ink-printing and thermal-recording media. Typical sensitizers contain an aromatic ring and exhibit aryl hydrocarbon receptor-mediated activity. They can accumulate in aquatic biota, leading to the disruption of ecosystems. Effluent from paper recycling plants has been identified as a source of contamination, and the presence of sensitizers in toilet paper may represent a new source of contamination in aquatic environments. To examine possible sources of contamination by sensitizers, this study investigated the levels of sensitizers in recycled toilet paper. We also studied the prevalence of sensitizers in rivers receiving effluents from sewage treatment plants in Japan, from 2020 to 2022. We detected eight sensitizers and related compounds in both toilet paper and river water samples; their total concentrations ranged from 0.78 to 34 µg/g (mean: 12 µg/g) in toilet paper and 58–1167 µg/L (median: 77 µg/L) in water. In the water samples, sensitizers were partitioned between liquid and suspended solid phases, and in suspended solids, sensitizers accounted for an average of 42% of the total. Correlation analysis showed a high correlation between sensitizer composition in the water from a river receiving sewage treatment plant effluents and toilet paper. Since these compounds were also detected in the river water analyzed in this study, toilet paper should be considered a novel source of sensitizers contamination in sewage treatment systems. [ABSTRACT FROM AUTHOR]

This paper studies the diffusion of battery electric vehicle (BEV) technology in Japan. The diffusion process in this study refers to both the innovation and adoption of BEV technology. While previous studies on BEV technological diffusion focus on policy selection, especially domestic policy, little is known about the connectedness between international and domestic factors in the BEV technological diffusion process. This paper aims to enrich the discussion of technology diffusion by expanding the argument that technology diffusion is not only a domestic problem but also an international relations problem using a case study of BEV technology diffusion in Japan. The findings indicate that two international factors push Japan to diffuse BEV technology: Japanese commitment to the global environmental regime and global competition in BEV manufacturing. However, the domestic institution factor hinders the BEV technology diffusion. The production structures of automobile industries and political economy relations between the automobile industry and the government further complicate the diffusion process of BEV technology. [ABSTRACT FROM AUTHOR]

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]

Background: Bibliometric analysis is a mature method for quantitative evaluation of academic productivity. In view of the rapid development of research in the field of systemic lupus erythematosus (SLE) in the past decade, we used bibliometric methods to comprehensively analyze the literature in the field of SLE from 2013 to 2022. Methods: The relevant literature in the field of SLE from 2013 to 2022 was screened in the Web of Science Core Collection database. After obtaining and sorting out the data, CiteSpace and VOSviewer software were used to visualize the relevant data, and SPSS software was used for scientific statistics. Results: A total of 18,450 publications were included in this study. The number of articles published over the past 10 years has generally shown an upward trend, while Altmetric attention scores have also shown a clear upward trend in general and in most countries. Citation analysis and Altmetric analysis can mutually prove and supplement the influence of papers. The USA, China, Japan, Italy, and the UK are the most productive countries, but China and Japan are significantly inferior to other countries in terms of research influence. Four of the top ten authors are at the center of the collaboration network. LUPUS is the most contributing journal. The theme of systemic lupus erythematosus research mainly focuses on the pathogenesis, treatment, and management of SLE, and the emerging trend is related research on machine learning and immune cells. Conclusion: This study shows the research status of SLE, clarifies the main contributors in this field, discusses and analyzes the research hotspots and trends in this field, and provides reference for further research in this field to promote the development of SLE research. Key Points • Through bibliometric analysis, Altmetric analysis, and visual analysis, we reveal the global productivity characteristics of SLE-related papers in the past 10 years. • The number of global SLE-related studies has shown a significant increase, indicating that SLE is still a hot topic and deserves further study. • Citation analysis and Altmetric analysis can mutually prove and supplement the influence of papers, and the attention of related literature among non-professional researchers is increasing. • The theme of SLE research mainly focuses on the pathogenesis, treatment, and management of SLE. The emerging trend is machine learning and immune cells, which may provide new strategies for the diagnosis and treatment of SLE in the future. [ABSTRACT FROM AUTHOR]

We studied the earthquake detection capacity of DONET (Dense Oceanfloor Network system for Earthquakes and Tsunamis) operating in the Nankai Trough, a target region monitored for future megathrust earthquakes. The focus of this paper was to evaluate the impact on this capacity from the malfunction of parts of the network. For this purpose, the completeness magnitude, above which all earthquakes are considered to be detected by a seismic network, was used. Then, a catalog that includes events observed by DONET was used. We found spatiotemporal variability of completeness magnitude, ranging from values below 1 in one of the areas where stations are densely deployed to values above 2 at the periphery and outside of the DONET area. We conducted a simulation computation for cases of malfunction of densely distributed stations. The results showed that completeness estimates in the area near the malfunctioning stations were about 1 magnitude larger. This implies that malfunction repair and/or replacement with new stations would be desirable because they pronouncedly affect earthquake monitoring. We then demonstrated an example of how to use the information of completeness magnitude as prior knowledge to compute the b value of the Gutenberg-Richter distribution. The result indicates the b value as a proxy that can help to image stress heterogeneity when there is a magnitude-6 class slow slip event on the Nankai Trough plate boundary. [ABSTRACT FROM AUTHOR]

At present, the National Metrology Institute of Japan provides six national primary pH buffers under the Japan Calibration Service System. Each batch of these buffers is certified by the primary pH method using a Harned cell. On the basis of these primary buffers, the designated laboratories supply the secondary and working pH standards using a high-precision pH meter. This paper provides an estimate of the batch-to-batch reproducibility of the primary pH standard production based on the history of the certification of primary carbonate buffers in NMIJ. This buffer, which was chosen as the subject of the study because of the relative difficulty of its measurements (and thus a greater dispersion of results), is nominally the 0.025 mol kg−1 equimolal solution of disodium carbonate and sodium hydrogen carbonate. As its pH value is significantly affected by the purity of the reagents used, the evaluation of their source materials is made by both pH measurements and acidimetric gravimetric back titrations. Considering the experimentally determined pH reproducibility of ca. 0.010, potential risks to the pH accuracy are discussed when using recipe-based carbonate pH standards. [ABSTRACT FROM AUTHOR]

Though there is now a substantial body of research on the relationship between nonprofits and the state, examples from non-Western countries have been lacking in the nonprofit literature in English. This paper attempts to fill this gap using nonprofit cases in three key districts in Fukushima after the Great East Japan Earthquake. By focusing on these cases, this study captures the complex nature of the relationship between the nonprofit sector and state in Japan during a period of increased activity of both the nonprofit sector and the state. The idea of the nonprofit sector, state, and market as relatively separate and with different interests, influences discussions on themes related to the nonprofit sector (e.g., business-like behavior). The study suggests how the Japanese case can contribute in uncovering assumptions that are embedded in the existing understanding of the nonprofit sector, based primarily on Western examples. [ABSTRACT FROM AUTHOR]

To explore the current status of anesthesia research activity in Japan, we analyzed the number of abstracts presented at the Japanese Society of Anesthesiologists (JSA) annual meetings by several factors including gender, society branches, and subspecialty categories. The number of abstracts at JSA annual meetings has declined sharply since 2016 with no gender gap. A decrease in the neurological field predated the overall decline, but other subspecialty categories showed a similar decline. Although the Tokyo, Tokai-Hokuriku, and Kyushu branches were responsible for more than half of the reduction, the trend was similar among all branches. In a survey regarding academic activities of university hospital residents and faculty, Ph.D. aspirants' rate was only 20–30%. Residents had never presented an abstract at scientific conferences and never published any papers at nearly 40% and 30% of the university hospitals, respectively. Our survey suggests that junior anesthetists are losing interest in research. Senior faculty and mentors must redouble efforts to embed and encourage research in departments and by anesthetists in training. If a revival of anesthesia research in Japan does not occur then a service only specialty awaits. [ABSTRACT FROM AUTHOR]

Some global error bounds with undetermined parameters, which are not always valid, for the extended vertical linear complementarity problems (LCP) of CKV-type matrices and CKV-type B -matrices, are presented by Yan and Wang (Jpn. J. Ind. Appl. Math. 41:129–150, 2024). In this paper, new global error bounds for the extended vertical LCP of CKV-type matrices and CKV-type B -matrices are given, which depend only on the entries of the involved matrices. Numerical examples show that the new bounds are better than those provided in Zhang et al. (Comput. Optim. Appl. 42(3):335–352, 2009) and Wang et al. (Comput. Appl. Math. 40:148, 2021) in some cases. [ABSTRACT FROM AUTHOR]

The devastating consequences of tsunamis on coastal infrastructure have highlighted the urgent need for effective disaster risk reduction strategies. To mitigate tsunami disasters, the insurance industry plays a vital role in implementing risk transfer measures by providing financial protection against asset damage. However, the current research on catastrophe insurance policies for coastal infrastructure lacks consideration of climate change effects. It is essential to take into account the non-stationary effects of sea-level rise to develop long-term tsunami disaster mitigation measures and promote socioeconomic resilience in coastal communities. This paper aims to provide an insurance portfolio optimization framework for coastal residential buildings subjected to tsunamis considering non-stationary sea-level rise effects based on a stochastic simulation approach. A spatiotemporal probabilistic sea-level rise hazard assessment is carried out by utilizing available climate models and considering several emission scenarios. Tsunami propagation analyses under various sea-level rise cases are performed to evaluate the time-variant tsunami hazard curves based on Monte Carlo simulation. A life cycle-based stochastic insurance claim model associated with the cumulative loss of building assets is developed based on a non-stationary compound renewal process. Finally, a sample average approximation method is leveraged to estimate the optimum basic insurance premium rate by maximizing the insurer's profit under a cost-constrained insurance purchase decision of homeowners. As a case study, the proposed framework is applied to multiple municipalities situated in the tsunami-prone region of Kochi Prefecture, Japan. Sea-level rise substantially decreases the maximum profits of tsunami insurers and increases the premium rate and ruin probability. [ABSTRACT FROM AUTHOR]

This work is the extended version of a paper presented at the conference HMM2021, about the history of mechanical engineering. First, the initial cultural and industrial steps in the robotic field in Japan are introduced, to display the beginning of this interlaced path, before WW2; then, in the context of the aftermaths of the war, some famous anime heroes are presented as ancestors of the coming mecha anime series. The rising research in the field of robotics and more generally the developments of contemporary Japanese automation industry are then drawn, as a technological substrate for mecha conception. In particular, Masahiro Mori studies are taken into consideration to identify an actual robot design pattern to apply to the following comparative description and examination of the different mecha; finally, thanks to this analysis, the common breeding ground whence robotics and mecha (and their reciprocal influences) arise, is outlined. [ABSTRACT FROM AUTHOR]

Japan is one of the countries with the most frequent natural disasters in the world and is faced with various threats of natural disasters every year, which significantly impact Japan's social economy and people's lives. A great deal of information about disasters is preserved in Japanese literature. Interpreting and organizing this information help us to analyze the regularity of disasters and understand the preventive measures of ancient people. This paper aims to organize, analyze and save disaster data by collecting various information about disasters. Then a disaster spatiotemporal database system is constructed by using deep learning, image processing, and database technology. The system consists of two parts, namely, the disaster database and disaster website. The disaster database is the core of the whole system, which saves the disaster data after organizing and summarizing. The database collects disaster information from various sources, including key information such as disaster type, time, location, scale, and scope of impact. The Disaster website is the system's user interface, providing an interactive platform for users to access and use disaster data easily. The website has many functions, including search, visual display, disaster information query, etc. We also make a detailed analysis of the collected data, aiming to predict the causes and occurrence rules of disasters so as to achieve the target of disaster prediction. [ABSTRACT FROM AUTHOR]

Electrodynamic coupling between the ionospheric E and F regions is widely recognized as the underlying mechanism for generating medium-scale traveling ionospheric disturbances (MSTIDs) during nighttime at midlatitudes. Recently, the double-thin-shell approach has proven to be a useful tool for studying the E–F coupling. By using total electron content (TEC) measurements, this approach enables the simultaneous reconstruction of electron density perturbations in both the E and F regions with broad and continuous coverage. However, the current reconstruction performance is limited when using only GPS-TEC measurements from GEONET, a dense network of ground-based Global Navigation Satellite System (GNSS) receivers over Japan. The expansion of available data sources and the integration of multi-GNSS observation data are considered important to enhance the double-thin-shell model. Fortunately, SoftBank Corp., a Japanese telecommunications provider, has recently developed a dense independent GNSS observation network to improve positioning services. In this paper, we analyze the potential of the improved double-thin-shell approach and emphasize the importance of incorporating multi-GNSS observation data from both GEONET and SoftBank networks. The solvability analysis, simulation, and observation results collectively indicate a substantial improvement in the spatiotemporal resolution. Specifically, the longitudinal and latitudinal resolution is improved from 0.15° to 0.1° in the E region, and from 0.5° to 0.3° in the F region. The temporal resolution is also improved from 2 to 1 min. In addition, significant improvements have been achieved in the reconstruction performance, particularly for the E region under complex background conditions. Based on these assessments, we conclude that the incorporation of GEONET and SoftBank GNSS observation data holds significant potential for improving the double-thin-shell model and advancing our understanding of MSTIDs. [ABSTRACT FROM AUTHOR]