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Our research activities would be better served if they were communicated in a manner that is openly accessible to the public and all researchers. The research we share is often limited to representative data included in research papers—science would be much more efficient if all reproducible research data were shared alongside detailed methods and protocols, in the paradigm called Open Science. On the other hand, one primary function of research journals is to select manuscripts of good quality, verify the authenticity of the data and its impact, and deliver to the appropriate audience for critical evaluation and verification. In the current paradigm, where publication in a subset of journals is intimately linked to research evaluation, a hypercompetitive "market" has emerged where authors compete to access a limited number of top‐tier journals, leading to high rejection rates. Competition among publishers and scientific journals for market dominance resulted in an increase in both the number of journals and the cost of publishing and accessing scientific papers. Here we summarize the current problems and potential solutions from the development of AI technology discussed in the seminar at the 46th Annual Meeting of the Molecular Biology Society of Japan. [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]

Aim: To clarify whether the Whitney Comorbidity Index (WCI) is useful in Asian adults with cerebral palsy (CP) and whether aspiration pneumonia and pressure ulcers improved the prognostic significance of the WCI. Method: This cohort study evaluated individuals aged at least 18 years with CP in Japan. We used Cox proportional hazards regression to analyse 2‐year mortality rates. The predictive performance of the Charlson Comorbidity Index, Elixhauser Comorbidity Index, and WCI were compared as comorbidity assessment criteria. Aspiration pneumonia and pressure ulcers were added to the Cox models, and their impact on hazard ratios was determined. Results: Of the 2232 adults with CP, 72 died during the 2 years. The model with a previously reported weighted WCI with aspiration pneumonia and pressure ulcers produced the best fit. Additionally, the hazard risk of 2‐year mortality for an unweighted WCI score of at least 4 was 2.56; when CP‐specific comorbidities were added, it increased to 8.94. Interpretation: This study showed that the WCI can be used in Asian adults with CP. Furthermore, assessing patient age, aspiration pneumonia, and pressure ulcers in addition to the WCI increased the predictive value for mortality. Our findings indicate that the WCI can promote valid comparisons between international populations. What this paper adds: The Whitney Comorbidity Index (WCI) is useful among adults with cerebral palsy, irrespective of ethnic differences.Assessment of aspiration pneumonia and pressure ulcers increased the WCI predictive value.The WCI helps identify adults with cerebral palsy at risk of adverse outcomes. What this paper adds: The Whitney Comorbidity Index (WCI) is useful among adults with cerebral palsy, irrespective of ethnic differences.Assessment of aspiration pneumonia and pressure ulcers increased the WCI predictive value.The WCI helps identify adults with cerebral palsy at risk of adverse outcomes. This article's abstract has been translated into Japanese. Follow the links from the abstract to view the translations. [ABSTRACT FROM AUTHOR]

Accurate traffic volume prediction plays a crucial role in urban traffic control by relieving congestion through improved regulation of traffic volume. Network‐level traffic volume prediction and detector failure have rarely been considered in the literature. This paper proposes a framework based on long short‐term memory and the multilayer perceptron that can predict network‐level traffic volumes even with detector failure. A profile model learns the profile of the detector's signature (traffic pattern). Detectors with similar profiles are considered to have similar traffic patterns and are grouped into a cluster. Failed detectors can obtain reference information from similar detectors in the same cluster without additional information. A predictive model is developed for each cluster. The proposed method is validated using Japan Road Traffic Information Center data for three cities. The computational results indicate that the proposed method performs well both on typical days and atypical days (the COVID‐19 lockdown period and the 2021 Tokyo Olympics). Further, it considers detector reliability: the increase in mean absolute error is less than 1 veh/5 min when the probability of detector failure increases to 20%. [ABSTRACT FROM AUTHOR]