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Abstract Background Concerns persist regarding the potential reduction in driving performance due to taking second-generation antihistamines or performing hands-free calling. Previous studies have indicated a potential risk to driving performance under an emergency event when these two factors are combined, whereas a non-emergency event was operated effectively. Currently, there is a lack of a discriminative index capable of detecting the potential risks of driving performance impairment. This study aims to investigate the relationship between driving performance and eye movements under combined conditions of taking second-generation antihistamines and a calling task, and to assess the usefulness of eye movement measurements as a discriminative index for detecting potential risks of driving performance impairment. Methods Participants engaged in a simulated driving task, which included a calling task, both under taking or not taking second-generation antihistamines. Driving performance and eye movements were monitored during both emergency and non-emergency events, assessing their correlation between driving performance and eye movements. The study further evaluated the usefulness of eye movement as a discriminative index for potential driving impairment risk through receiver operating characteristic (ROC) analysis. Results In the case of a non-emergency event, no correlation was observed between driving performance and eye movement under the combined conditions. Conversely, a correlation was observed during an emergency event. The ROC analysis, conducted to assess the discriminative index capability of eye movements in detecting the potential risk of driving performance impairment, demonstrated a high discriminative power, with an area under the curve of 0.833. Conclusions The findings of this study show the correlation between driving performance and eye movements under the concurrent influence of second-generation antihistamines and a calling task, suggesting the usefulness of eye movement measurement as a discriminant index for detecting potential risks of driving performance impairment.

Abstract Drought is the primary driver of wildfires in humid regions, and the main drought drivers for wildfire occurrence and spread vary across different humid climatic areas. This study explores the suitability of different drought descriptions for wildfires under various humid temperate climates in Japan. Based on wildfire data from 1995 to 2012, statistical and correlation analyses were conducted to examine the performance of effective humidity (EH) and soil moisture (SM) as indicators of atmospheric and soil drought. EH is used for nationwide wildfire and drought warnings in Japan. The results show that EH is significantly influenced by seasonal and regional factors, with its ability to assess drought for wildfire varying accordingly, whereas SM demonstrates a more consistent ability to assess drought across different seasons and regions. Correlation analysis revealed that atmospheric drought better explains the drought conditions for wildfire ignition in 11 prefectures, mainly concentrated in the northern regions along the Sea of Japan. In contrast, the correlation coefficients for SM were higher in 33 prefectures, particularly along the Pacific coast, indicating that soil drought better explains the drought conditions for burned areas in these prefectures.

The widespread adoption of electric vehicles (EVs) underscores the urgent need for innovative approaches to estimate their lithium-ion batteries’ state of health (SOH), which is crucial for ensuring safety and efficiency. This study introduces SOH-TEC, a transformer encoder-based model that processes raw time-series battery and vehicle-related data from a single EV trip to estimate the SOH. Unlike conventional methods that rely on lab-experimented battery cycle data, SOH-TEC utilizes real-world EV operation data, enhancing practical application. The model is trained and evaluated on a real-world dataset collected over nearly three years from three EVs. This dataset includes reliable SOH labels obtained through periodic constant-current full-discharge tests using a chassis dynamometer. Despite the challenges posed by noisy EV real-world data, the model shows high accuracy, with a mean absolute error of 0.72% and a root mean square error of 1.17%. Moreover, our proposed pre-training strategies with unlabeled data, particularly SOH ordinal comparison, significantly enhance the model’s performance; using only 50% of the labeled data achieves results nearly identical to those obtained with the full dataset. Self-attention map analysis reveals that the model primarily focuses on stationary or consistent driving periods to estimate SOH. While the study is constrained by a dataset featuring repetitive driving patterns, it highlights the significant potential of transformer for SOH estimation in EVs and offers valuable insights for future data collection and model development.

Abstract With the continuous increase in carbon dioxide emissions due to human activities and the resulting severe climate issues, there is global concern about energy conservation and emission reduction. However, detailed data on energy consumption and emissions at a fine-grained scale, particularly regarding spatial dimensions and sector-specific emissions, remains insufficient and in need of refinement and timely updates. In Japan, following the Fukushima nuclear disaster, there has been a significant shift from nuclear power generation to reliance on fossil fuels across various sectors, highlighting disparities in emissions data across different regions and industries. Our work extends the emissions time series for Japan’s 47 prefectures, incorporating their socioeconomic characteristics over a broader time frame and with a more detailed sectoral classification. The emissions inventory, covering the period from 1990 to 2020, is based on the consumption of the three main fossil fuels across 32 sectors, with emissions carefully allocated for regional power generation. This dataset, presented in a unified format, is expanded to include longer time scales and more detailed socioeconomic data. It is anticipated to offer crucial insights for establishing regional emission reduction targets and identifying sectoral priorities for decarbonization.

Given the accelerating global movement towards decarbonization, the importance of promoting renewable energy (RE) adoption and ensuring efficient transactions in energy markets is increasing worldwide. However, renewable energy sources, including photovoltaic (PV) systems, are subject to output fluctuations due to weather conditions, requiring large-scale backup power to balance supply and demand. This makes trading electricity from large-scale PV systems connected to the existing grid challenging. To address this, peer-to-peer (P2P) energy markets where individual prosumers can trade excess power within their local communities have been garnering attention. This study introduces a simulator for P2P energy trading, designed to account for the diverse behaviors and objectives of participants within a market mechanism. The simulator incorporates two risk aversion parameters: one related to transaction timing, expressed through order prices, and another related to forecast errors, managed by adjusting trade volumes. This allows participants to customize their trading strategies, resulting in more realistic analyses of trading outcomes. To explore the effects of these risk aversion settings, we conduct a case study with 120 participants, including both consumers and prosumers, using real data from household smart meters collected on sunny and cloudy days. Our analysis shows that participants with higher aversion to transaction timing tend to settle trades earlier, often resulting in unnecessary transactions due to forecast inaccuracies. Furthermore, trading outcomes are significantly influenced by weather conditions: sunny days typically benefit buyers through lower settlement prices, while cloudy days favor sellers who execute trades closer to their actual needs. These findings demonstrate the trade-off between early execution and forecast error losses, emphasizing the simulator’s ability to analyze trading outcomes while accounting for participant risk aversion preferences.

Abstract Background The effect of laparoscopic surgery on short-term outcomes in colorectal cancer patients over 90 years old has remained unclear. Methods We reviewed 87 colorectal cancer patients aged over 90 years who underwent surgery between 2016 and 2022. Patients were divided into an open surgery group (n = 22) and a laparoscopic surgery group (n = 65). The aim of this study was to investigate the effect of laparoscopic surgery on postoperative outcome in elderly colorectal cancer patients, as compared to open surgery. Results Seventy-eight patients (89.7%) had comorbidities. Frequency of advanced T stage was lower with laparoscopic surgery (p = 0.021). Operation time was longer (open surgery 146 min vs. laparoscopic surgery 203 min; p = 0.002) and blood loss was less (105 mL vs. 20 mL, respectively; p

Accurately quantifying runoff sources and understanding hydrological processes in glaciated mountain basins is essential for effective water resource management in the face of climate change. This study aimed to determine the contributions from various runoff sources in glaciated basins within the inner Tien-Shan mountains of Kyrgyzstan by utilizing integrated land surface, glacier energy-mass balance, and river routing models. To account for local topographic influences on solar radiation and cloud transmissivity processes, gridded meteorological forcing data were downscaled. The integrated models were then evaluated against observed discharge, glacier mass balance, and snow water equivalent, with a focus on the Kara-Batkak glacier reference site. Shortwave radiation correction was particularly important for improving the accuracy of model simulations. The results indicate that the peak glacier melt contribution occurs in July and August, with some basins reaching up to 54%. On an annual basis, the average contribution from glaciers across the basins was found to be 19%, while the ratios of snowmelt and rainfall were 58% and 23%, respectively. This study highlights the utility of integrated modelling approaches in understanding and quantifying runoff components in data-scarce high mountain regions. The incorporation of observed glacier data proved to be crucial for accurately representing hydrological processes under current climatic conditions. These findings underscore the significance of considering glacier dynamics and their influence on water resources to inform effective water management strategies in glaciated mountain basins.

Abstract Household consumption significantly contributes to greenhouse gas emissions as it is the largest component of final demand in the national accounting system. Nevertheless, there is an apparent lack of comprehensive and consistent datasets detailing emissions from household consumption. Here, we expand and update Japan’s multiscale monthly household carbon footprint from January 2011 to September 2022, combining data from government statistics and surveys. We constructed a dataset comprising 37,692 direct and 4,852,845 indirect emission records, covering households at the national, regional, and prefectural city levels. The dataset provides critical spatiotemporal information that allows for revealing carbon emission patterns, pinpointing primary sources of emissions, and discerning regional variances. Moreover, the inclusion of micro-scale carbon footprint data enables the identification of specific consumption habits, thereby regulating individual consumption behavior to achieve a low-carbon society.

Abstract Background Esophageal duplication cyst (EDC) is a type of gastrointestinal duplication cyst that involves congenital malformations of the gastrointestinal tract. EDCs are frequently found in the mediastinum and thoracoabdominal region, but rarely occur in the abdominal cavity. However, intra-abdominal EDCs are frequently found in the upper abdomen near the abdominal esophagus. Here, we report, for the first time, a case of intra-abdominal EDC that occurred in the ileum. Case presentation A 14-year-old female patient presented to our hospital with complaints of epigastric pain and vomiting. Abdominal computed tomography (CT) revealed a cystic tumor in the pelvis, suspected of ovarian origin. She was admitted to our gynecology department and underwent emergency surgery. The laparoscopic examination revealed that both ovaries were intact and that a primary tumor had developed from the ileal mesentery. Since the patient’s condition was not urgent at the time of the gynecological surgery, the procedure was completed by only performing exploratory laparotomy; the patient was admitted to our department after the surgery. Pelvic magnetic resonance imaging performed on the next day revealed a cystic mass measuring 90 × 65 mm with a smooth margin and homogeneous signal intensity, arising posterior to the uterus. The mass was suspected as an intestinal duplication cyst. On another day, after the examinations were completed, we resected the portion of the small intestine containing the tumor by laparoscopy. The patient had a successful postoperative course and was discharged on the 5th postoperative day. Histological examination showed that the cyst was lined by stratified squamous epithelium, contained esophageal glands, and had a two-layer muscularis propria. Therefore, a diagnosis of intra-abdominal EDC was performed. Conclusions An intra-abdominal EDC cyst is relatively rare; this is the first case reported at the distal ileum.

Traditional learning procedures for artificial intelligence rely on digital methods not suitable for physical hardware. Here, Nakajima et al. demonstrate gradient-free physical deep learning by augmenting a biologically inspired algorithm, accelerating the computation speed on optoelectronic hardware.

Summary: The intricate interplay between gut microbes and the onset of experimental autoimmune encephalomyelitis (EAE) remains poorly understood. Here, we uncover remarkable similarities between CD4+ T cells in the spinal cord and their counterparts in the small intestine. Furthermore, we unveil a synergistic relationship between the microbiota, particularly enriched with the tryptophan metabolism gene EC:1.13.11.11, and intestinal cells. This symbiotic collaboration results in the biosynthesis of kynurenic acid (KYNA), which modulates the recruitment and aggregation of GPR35-positive macrophages. Subsequently, a robust T helper 17 (Th17) immune response is activated, ultimately triggering the onset of EAE. Conversely, modulating the KYNA-mediated GPR35 signaling in Cx3cr1+ macrophages leads to a remarkable amelioration of EAE. These findings shed light on the crucial role of microbial-derived tryptophan metabolites in regulating immune responses within extraintestinal tissues.

Here the authors demonstrate chip-scale high-peak-power lasers by vertical integration of semiconductor and solid state laser gain mediums to reach the same maturity level as existing semiconductor lasers, which are suitable for miniaturization and cost-effective mass production.

Abstract The anti-vaccine movement has gained traction in many countries since the COVID-19 pandemic began. However, their aggressive behaviour through replies on Twitter—a form of directed messaging that can be sent beyond follow-follower relationships—is less understood, and even less is known about the language use differences of this behaviour. We conducted a comparative study of anti-vaxxers’ aggressive behaviours by analysing a longitudinal dataset of COVID-19 tweets in English and Japanese. We found two common features across these languages. First, anti-vaxxers most actively transmit targeted messages or replies to users with different beliefs, especially to neutral accounts, with significantly toxic and negative language, and these replies are often directed to posts about vaccine operations. Second, influential users with many followers and verified accounts are more likely to receive the most toxic replies from the anti-vaxxers. However, pro-vaccine accounts with a few followers receive highly toxic replies in English, which is different from the Japanese case. These results provide insights into both language-dependent and independent countermeasures against anti-vaxxers’ aggressive behaviour.

The copolyester of 3-hydroxybutyrate (3HB) and 3-hydoxyhexanoate (3HHx), PHBHHx, is a biodegradable plastic characterized by high flexibility, softness, a wide process window, and marine biodegradability. PHBHHx is usually produced from structurally related carbon sources, such as vegetable oils or fatty acids, but not from inexpensive carbon sources such as sugars. In previous studies, we demonstrated that engineered strains of a hydrogen-oxidizing bacterium, Cupriavidus necator, synthesized PHBHHx with a high cellular content not only from sugars but also from CO2 as the sole carbon source in the flask culture. In this study, the highly efficient production of PHBHHx from CO2 was investigated via pH-stat jar cultivation of recombinant C. necator strains while feeding the substrate gas mixture (H2/O2/CO2 = 80:10:10 v/v%) to a complete mineral medium in a recycled-gas, closed-circuit culture system. As a result, the dry cell mass and PHBHHx concentration with the strain MF01/pBPP-ccrMeJAc-emd reached up to 59.62 ± 3.18 g·L−1 and 49.31 ± 3.14 g·L−1, respectively, after 216 h of jar cultivation with limited addition of ammonia and phosphate solutions. The 3HHx composition was close to 10 mol%, which is suitable for practical applications. It is expected that the autotrophic cultivation of the recombinant C. necator can be feasible for the mass production of PHBHHx from CO2.

Abstract The JAXA’s Martian Moons Exploration (MMX) mission is planned to reveal the origin of Phobos and Deimos. It will remotely observe both moons and return a sample from Phobos. The nominal instruments include the TElescopic Nadir imager for GeOmOrphology (TENGOO) and Optical RadiOmeter composed of CHromatic Imagers (OROCHI). The scientific objective of TENGOO is to obtain the geomorphological features of Phobos and Deimos. The spatial resolution of TENGOO is 0.3 m at an altitude of 25 km in the quasi-satellite orbit. The scientific objective of OROCHI is to obtain material distribution using spectral mapping. OROCHI possesses seven wide-angle bandpass imagers without a filter wheel and one monochromatic imager dedicated to the observation during the landing phase. Using these two instruments, we plan to select landing sites and obtain information that supports the analysis of return samples. Graphical Abstract

Rheumatoid arthritis is an inflammatory autoimmune disease, characterized by autoantibody production, synovial inflammation, and joint destruction. Its pathogenesis is due to environmental factors and genetic backgrounds. Bruton’s tyrosine kinase is a cytoplasmic non-receptor tyrosine kinase, expressed in most hematopoietic cell lineages, except T cells and plasma cells, and regulates various immune-related signaling pathways, thereby playing a crucial role in pathogenesis. Thus, inhibiting Bruton’s tyrosine kinase may prove beneficial in treating autoimmune diseases. In the present study, we characterized Bruton’s tyrosine kinase inhibitor, TAS5315, in vitro and evaluated its therapeutic effects in experimental arthritis models. TAS5315 markedly inhibited Bruton’s tyrosine kinase enzyme activity and suppressed the B-cell receptor signaling pathway in Ramos cells. Moreover, it suppressed the expression of CD69, CD86, and MHC class II in mouse B lymphocytes and the production of TNF-α and MIP-1α in mouse macrophages and decreased bone resorption activity in mouse osteoclasts. Furthermore, it ameliorated the pathological changes in two rodent models of collagen-induced arthritis in vivo. TAS5315 improved bone mineral density and bone intensity. Thus, these results suggest that TAS5315 could be a promising therapeutic option for the treatment of rheumatoid arthritis.

Abstract The explosive 2022 Tonga submarine volcanic eruption produced a globally propagated atmospheric disturbance. A leading Lamb wave pulse was recorded as a pressure pulse worldwide. A weather‐station network in Japan recorded the pressure pulse together with temperature and wind conditions during the passage of the pulse. Individual temperature and wind records indicate little simultaneous change. However, after alignment of records at the time of pressure pulse arrivals and stacking, clear temperature and wind changes synchronized with the pressure change are evident. Assuming Lamb wave propagation, the synthesized temperature and wind changes from the pressure record show a good match with the observed waveforms. The observed wind speed and pressure change of the Lamb pulse yielded a total energy transported by the pulse of 4.2 × 1016 J.

Abstract Background 1,5-anhydroglucitol is a reduction product of 1,5-anhydrofructose. Circulating 1,5-anhydroglucitol is usually excreted by the kidneys and is reabsorbed via sodium-glucose co-transporter 4 in the renal tubules. In patients on hemodialysis, serum levels of 1,5-anhydroglucitol have been reported to be low; however, the underlying mechanism remains unclear. Methods We measured inter-dialysis changes in the levels of serum 1,5-anhydroglucitol and 1,5-anhydrofructose-derived advanced glycation end products (AGEs) in 78 patients on hemodialysis. Serum levels of 1,5-anhydrofructose-derived AGEs were also determined using a polyclonal antibody. Results The serum 1,5-anhydroglucitol level was decreased to as low as 2.0 μg/mL in the regular hemodialysis group; however, we could not verify changes in the serum 1,5-anhydroglucitol level during inter-dialysis days because of undetectable levels in 29 patients. The measured serum level of 1,5-anhydrofructose-derived AGEs was significantly increased in both patient groups. In addition, the 1,5-anhydrofructose-derived AGEs/1,5-anhydroglucitol ratio was higher in patients on hemodialysis than in controls. Conclusions Accelerated glycation of 1,5-anhydrofructose is one possible mechanism by which serum 1,5-anhydroglucitol levels are lowered in patients on HD, and we propose that the 1,5-anhydrofructose-derived AGEs/1,5-anhydroglucitol ratio should be measured in clinical settings in which patients have low serum levels of 1,5-AG.

A diversity of prokaryotes currently exhibit multicellularity with different generation mechanisms in a variety of contexts of ecology on Earth. In the present study, we report a new type of multicellular bacterium, HS-3, isolated from an underground stream. HS-3 self-organizes its filamentous cells into a layer-structured colony with the properties of a nematic liquid crystal. After maturation, the colony starts to form a semi-closed sphere accommodating clusters of coccobacillus daughter cells and selectively releases them upon contact with water. This is the first report that shows that a liquid-crystal status of cells can support the prokaryotic multicellular behavior. Importantly, the observed behavior of HS-3 suggests that the recurrent intermittent exposure of colonies to water flow in the cave might have been the ecological context that cultivated the evolutionary transition from unicellular to multicellular life. This is the new extant model that underpins theories regarding a role of ecological context in the emergence of multicellularity.

This study analyzes how the electricity demand and supply constitutions affect electricity independence and power trading within a community and between a community and a grid through simulation analysis. To that aim, we create a simulation model equipped with a community-building function and trading capability. We first construct a community consisting of various types of residential and industrial consumers, and renewable power plants deployed in the community. Residential and industrial consumers are characterized by a state of family/business and ownership and the use of energy equipment such as rooftop solar PV and stationary battery storage in their homes/offices. Consumers’ electricity demand is estimated from regression analyses using training data. Using the hypothetical community constructed for the analysis, the simulation model performs rule-based electricity trading and provides outputs comprising the total electricity demand in the community, the state of use of battery storage and solar PV, the trading volume, and the electricity independence rate of the community. From the simulation results, we discuss policy implications on the effective use of renewable energy and increasing electricity independence by fully utilizing battery and trading functions in a community.

Air conditioning is a significant consumer of electricity in buildings, accounting for around 40% of the total consumption. While previous studies have focused on planning methods to minimize electricity costs, recent years have seen an increasing need for energy management methods that consider environmental performance, such as CO2 emissions, alongside economic efficiency. This study proposes a mechanism to support stakeholders’ decision-making by calculating Pareto solutions based on the multi-objective optimization of economic and environmental characteristics for entities that own renewable energy generation facilities. Unlike many existing studies that assume a specific equation for COP (Coefficient of Performance) estimation, this study adopts a nonparametric COP estimation method using machine learning, resulting in a more realistic and flexible modeling of the system. The study also presents a model for selecting an operation strategy that balances environmental and economic goals, incorporating a thermal storage facility to improve the renewable energy rate. Specifically, we proposed and compared methods for calculating solutions using only the GA (Genetic Algorithm) and a two-step optimization method combining a GA and gradient-based optimization method, confirming the superiority of the two-step optimization method. The case study unveiled unique operational profiles corresponding to cost-saving, renewable-energy, and balanced orientation points, suggesting the existence of specific strategies tailored to each orientation. The findings of this study can help stakeholders make more informed decisions regarding energy management in air conditioning systems, with benefits for both the environment and the bottom line.