Mitsubishi Research Institute (Japan)

<strong class="journal-contentHeaderColor">Abstract.</strong> Assessing future changes in typhoon-related hazards is essential for climate adaptation. We develop an event-based storyline framework coupling high-resolution meteorological simulations with river discharge and storm-surge models to quantify future risks under specified warming levels. Using Super Typhoon Hagibis (2019) as a case study, we conduct multi-model, multi-initial-condition ensemble experiments to account for structural model uncertainty and internal variability. Three meteorological models are run with 27-member initial-condition ensembles to drive three river models and two storm-surge models. Experiments cover the present climate and two warming scenarios (+2 K, +4 K). Across ensembles, Hagibis intensifies under warming: precipitation and near-surface winds strengthen, along with lower central pressure relative to present-climate runs. Consistent with these changes, many river basins in eastern Japan exhibit increased discharge, amplifying flood risk, and coastal models indicate larger storm surges. For Typhoon Hagibis, we quantify uncertainties in peak discharge and maximum storm-surge level. The multi-model combination widens uncertainties by sampling structural model differences, thereby spanning a wider range of plausible outcomes. Thus, our multi-model, multi-initial-condition framework provides a more comprehensive assessment of future typhoon-related risks than single-model experiments.

Abstract. Assessing future changes in typhoon-related hazards is essential for climate adaptation. We develop an event-based storyline framework coupling high-resolution meteorological simulations with river discharge and storm-surge models to quantify future risks under specified warming levels. Using Super Typhoon Hagibis (2019) as a case study, we conduct multi-model, multi-initial-condition ensemble experiments to account for structural model uncertainty and internal variability. Three meteorological models are run with 27-member initial-condition ensembles to drive three river models and two storm-surge models. Experiments cover the present climate and two warming scenarios (+2 K, +4 K). Across ensembles, Hagibis intensifies under warming: precipitation and near-surface winds strengthen, along with lower central pressure relative to present-climate runs. Consistent with these changes, many river basins in eastern Japan exhibit increased discharge, amplifying flood risk, and coastal models indicate larger storm surges. For Typhoon Hagibis, we quantify uncertainties in peak discharge and maximum storm-surge level. The multi-model combination widens uncertainties by sampling structural model differences, thereby spanning a wider range of plausible outcomes. Thus, our multi-model, multi-initial-condition framework provides a more comprehensive assessment of future typhoon-related risks than single-model experiments.

BackgroundNovel protein-coding genes were considered to be born by re-organization of pre-existing genes, such as gene duplication and gene fusion. However, recent progress of genome research revealed that more protein-coding genes than expected were born de novo, that is, gene origination by accumulating mutations in non-genic DNA sequences. Nonetheless, the in-depth process (scenario) for de novo origination is not well understood.ResultsWe have conceived bioinformatic analysis for sketching a scenario for de novo origination of protein-coding genes. For each de novo protein-coding gene, we firstly identified an edge of a given phylogenetic tree where the gene was born based on parsimony. Then, from a multiple sequence alignment of the de novo gene and its orthologous regions, we constructed ancestral DNA sequences of the gene corresponding to both end nodes of the edge. We finally revealed statistical features observed in evolution between the two ancestral sequences. In the analysis of the Saccharomyces cerevisiae lineage, we have successfully sketched a putative scenario for de novo origination of protein-coding genes. (1) In the beginning was GC-rich genome regions. (2) Neutral mutations were accumulated in the regions. (3) ORFs were extended/combined, and then (4) translation signature (Kozak consensus sequence) was recruited. Interestingly, as the scenario progresses from (2) to (4), the specificity of mutations increases.ConclusionTo the best of our knowledge, this is the first report outlining a scenario of de novo origination of protein-coding genes. Our bioinformatic analysis can capture events that occur during a short evolutionary time by directly observing the evolution of the ancestral sequences from non-genic to genic. This property is suitable for the analysis of fast evolving de novo genes.

In this study, it was evaluated the long-term catalytic effect and catalyst poisoning effect of gamma-ray irradiation on zirconium molybdate hydrate in the presence of three-way catalysts. The results indicated that the three-way catalyst was effective in suppressing the increase in hydrogen concentration due to radiolysis without being affected by poisoning. In addition, hydrogen diffusion analysis of the compressed hull and endpiece waste shows that hydrogen flows well through the waste and is suppressed by a three-way catalyst located in the center of the waste headspace.

Analyzing the SARS-CoV-2 pandemic outbreak based on actual data while reflecting the characteristics of the real city provides beneficial information for taking reasonable infection control measures in the future. We demonstrate agent-based modeling for Tokyo based on GPS information and official national statistics and perform a spatiotemporal analysis of the infection situation in Tokyo. As a result of the simulation during the first wave of SARS-CoV-2 in Tokyo using real GPS data, the infection occurred in the service industry, such as restaurants, in the city center, and then the infected people brought back the virus to the residential area; the infection spread in each area in Tokyo. This phenomenon clarifies that the spread of infection can be curbed by suppressing going out or strengthening infection prevention measures in service facilities. It was shown that pandemic measures in Tokyo could be achieved not only by strong control, such as the lockdown of cities, but also by thorough infection prevention measures in service facilities, which explains the curb phenomena in real Tokyo.

This paper investigated the dynamic response characteristic with focus on damped slit configuration of damped braced tube systems with oil dampers. According to the results, 1) damped braced tube system has over 10% 1st to 3rd damping ratio, 2) while the displacement and acceleration responses are simultaneously reduced up to maximized 1st mode damping ratio, the acceleration reduction effect may be getting worse after the peak, 3) while uniform damper distribution contributes to better damping performance, centralized damper distribution contributes to better period reduction.

Efforts to counter COVID-19 reaffirmed the importance of rich medical, behavioral, and sociological data. To make data available to many researchers who can conduct statistical analyses and machine learning, personally identifiable information must be excluded to protect individual privacy. It is essential to remove explicit identifiers, sample population data, and apply differential privacy, the de facto standard privacy metric. Despite the general belief that the risk of re-identification is insignificant when these techniques are applied, this study shows that even after applying these techniques, the risk of being re-identified is highly significant for some data. This study proposes in detail an algorithm for estimating the number of people in a population who have certain attribute values based on incomplete, differentially private databases. If the estimated number is one, the probability that only one person with that attribute value is present in the population is high, which means that there is a high probability of re-identification. Therefore, this study concludes that the re-identification risk must be evaluated even after applying state-of-the-art techniques to protect privacy.

BackgroundThe survival rate of chronic dialysis patients in Japan remains the highest worldwide, so there is value in presenting Japan’s situation internationally. We examined whether aggregate figures on dialysis patients in the National Database of Health Insurance Claims and Special Health Checkups of Japan (NDB), which contains data on insured procedures of approximately 100 million Japanese residents, complement corresponding figures in the Japanese Society for Dialysis Therapy Renal Data Registry (JRDR).MethodsSubjects were patients with medical fee points for dialysis recorded in the NDB during 2014–2018. We analyzed annual numbers of dialysis cases, newly initiated dialysis cases– and deaths.ResultsCompared with the JRDR, the NDB had about 6–7% fewer dialysis cases but a similar number of newly initiated dialysis cases. In the NDB, the number of deaths was about 6–10% lower, and the number of hemodialysis cases was lower, while that of peritoneal dialysis cases was higher. The cumulative survival rate at dialysis initiation was approximately 6 percentage points lower in the NDB than in the JRDR, indicating that some patients die at dialysis initiation. Cumulative survival rate by age group was roughly the same between the NDB and JRDR in both sexes.ConclusionThe use of the NDB enabled us to aggregate data of dialysis patients. With the definition of dialysis patients used in this study, analyses of concomitant medications, comorbidities, surgeries, and therapies will become possible, which will be useful in many future studies.

Die Beiträge in diesem Open-Access-Sammelband analysieren die Bewältigungsstrategien von Alterung und Pflege in japanischen und deutschen Gemeinden.