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Environmental radiation assessment in the specified living areas for returnees of Okuma Town, Fukushima prefecture: Field measurements prior to decontamination
To assess environmental radiation exposure in the Specified Living Areas for Returnees of Okuma Town, Fukushima Prefecture, external radiation doses were evaluated using ambient dose equivalent rate measurements performed at residential properties. In addition to surveys covering the entirety of the Specified Living Areas for Returnees, area-specific assessments were conducted to account for differences in the progress of decontamination and demolition among districts. The median ambient dose rate measured by car-borne surveys across all Specified Living Areas for Returnees of Okuma Town decreased significantly from 0.49 µSv/h in November 2024 to 0.34 µSv/h in September 2025 (p < 0.05). In measurements conducted at residential properties prior to decontamination and demolition, the median ambient dose equivalent rate measured at house entrances was 0.96 µSv/h. The results of this study demonstrated that the ambient dose equivalent rates on roads measured by car-borne surveys across all Specified Living Areas for Returnees of Okuma Town decreased over the study period. In contrast, the estimated annual external dose at residential properties satisfied the reference level of 20 mSv set by the Ministry of the Environment as a guideline for lifting evacuation orders in most areas, but did not reach the long-term post-accident target level of 1 mSv. These findings provide evidence to inform ongoing discussions on evacuation order policies and long-term radiation management strategies.
Electronic structure engineering of PVA/ZnO/graphene oxide nanocomposites: a DFT study toward CO₂ and humidity detection
Abstract Due to their adjustable physicochemical properties and easy incorporation with functional nanomaterials, nanocomposites based on polyvinyl alcohol (PVA) have garnered significant interest for gas and humidity sensing applications. This study systematically examined the structural, electronic, adsorption, and sensing-related properties of PVA/ZnO/graphene oxide (GO) nanocomposites using density functional theory (DFT) at the B3LYP/LanL2DZ level. Strong interfacial interactions and hydrogen-bond-assisted stabilization within the nanocomposite structure were revealed by the calculated infrared spectra, molecular electrostatic potential (MESP), quantum theory of atoms in molecules (QTAIM), and non-covalent interaction (NCI) analyses. The electronic properties of PVA were significantly modified by the addition of ZnO and GO, as demonstrated by a reduction in the HOMO -LUMO energy gap from 7.334 eV to 1.075 eV and an increase in the total dipole moment from 7.147 to 12.243 Debye, which suggests that charge transfer and electronic polarization have been enhanced. Adsorption studies on H₂O and CO₂ molecules revealed that interactions are thermodynamically favorable, with adsorption energies of -0.306 eV and − 0.381 eV, respectively. PVA/OZn/GO–CO₂ showed the smallest energy gap (0.539 eV) and the largest dipole moment (14.264 Debye) among all configurations examined, indicating a marked electronic responsiveness and potential applicability in gas sensing. The analysis of the density of states further substantiated the emergence of electronic states that promote charge transport and enhance conductivity upon adsorption. The incorporation of ZnO/GO is offers an effective strategy for designing potential PVA-based nanocomposites for CO₂ gas and humidity sensing applications, as evidenced by the combined electronic modulation, strong adsorption affinity, and favorable charge redistribution.
Resource-efficient data transmission for WiFi-capable bio-loggers based on machine learning
Bio-logging is a popular method for data collection in animal research, especially for hard-to-observe animals. Newer bio-logger generations utilise WiFi technology, enabling researchers to collect high-resolution data at the cost of higher energy expenditure of the devices. In this study, we elaborate on how state-of-the-art loggers can benefit from even the simplest methods to reduce transmission costs. We employ machine learning techniques, specifically small decision trees, to enable a bio-logger to recognise a chosen behaviour based on its sensor readings. Based on the recognised behaviour, the logger filters which data to transmit, reducing transmission time and, thus, the logger’s overall energy consumption. Using a controlled dataset, we exemplify the training and evaluation of such decision trees. Using those, we evaluate the reduction of energy consumption based on a state-of-the-art bio-logger, the WildFi tag. We demonstrate that for WiFi-enabled bio-loggers, decision trees are highly beneficial when used as a data filter. We illustrate that filtering with decision trees yields energy savings of 14.68% in realistic scenarios for transmitting data. We provide a full pipeline from data collection to deployable software to holistically elaborate on how to use off-the-shelf solutions to achieve practical gains for animal behaviour. Our results suggest that decision trees can be an effective tool for enabling bio-loggers to detect specific behaviours. Lastly, we emphasise that our approach highly benefits from the use of gyroscopes, a sensor type that mostly sees use for off-board instead of on-board labour. We contribute an investigation of energy consumption reduction of WiFi-enabled bio-loggers through the utilisation of controlled data transmission using machine learning. We offer a promising pathway for enhancing the longevity of such a state-of-the-art bio-logger, maintaining WiFi benefits. Ultimately, we support more efficient and, thus, more sustainable wildlife monitoring practices on the example of the WildFi tag.
A novel multilateral learning state observation controller for wing-rock nonlinear dynamic systems
Differences of dynamic responses of single-pile and pile-group foundations in Meizoseismal areas
In order to investigate the dynamic response variations between isolated pile and pile-group systems in high-seismicity regions, we performed extensive shaking table experiments. These tests examined the acceleration characteristics, displacement patterns, and bending moment distributions across single-pile, four-pile, and six-pile configurations when exposed to four different seismic waveforms at a design-level intensity of 0.35g. Additionally, the structural integrity and damage conditions of the pile foundations were systematically assessed. The experimental data revealed that the greatest displacement at the pile head and the highest bending moment values were specifically caused by Kobe wave excitation. Conversely, the El-Centro wave produced the highest acceleration amplifications. The six-pile foundation exhibited optimal resistance to displacement and bending moment, particularly under the 5010 wave, and the single-pile foundation consistently showed the least acceleration amplification. Post-test inspections, including white-noise scanning and visual checks, showed no evidence of significant macroscopic damage across all foundation types, indicating an essentially elastic response at this intensity level. Engineering suggestions for the seismic design of bridge pile foundations in strong earthquake areas are proposed.
Added value of integrated satellite precipitation products for event-based flood modeling in semi-arid regions
Fertility desires and utilization of an integrated HIV care and family planning services among young women living with HIV in semi-rural Uganda: A cross sectional study
Background Little is known about the fertility desires among young women living with HIV (YWLHIV) in sub-Saharan African (SSA) settings and its association with their utilization of an integrated HIV care and family planning (FP) services. This study assessed the fertility desires and the utilization of an integrated HIV care and FP services among YWLHIV in Northern Uganda, where limited data exist to inform the integration of contraception, safer conception and prevention of mother to child (PMTCT) of HIV services. Methods In a cross-sectional study design, we collected data from YWLHIV attending antiretroviral therapy (ART) clinics in northern Uganda between November 2022 and April 2023. Using an interviewer-administered questionnaire, participants were asked about their fertility desires and the potential associated factors which included the socio-demographic, HIV, ART, sexual and reproductive health (SRH) and access to the community-based SRH resources. They were also asked whether they ever received FP services from the ART clinic facilities where they usually obtain their HIV care. Descriptive statistics for fertility desires and level of utilization of the integrated HIV and FP services were performed. More so, Chi-square test, Fisher’s Exact test, bivariate and multivariable Poisson regression analyses for the associations between the predictor variables and the fertility desires were performed. The 5% significance level and 95% confidence intervals were considered for the measures of fertility desires and the associations. Results We recruited 423 YWLHIV with a median age of 22 (IQR 20–24) years. The data revealed a high fertility desire (88.9%) among the YWLHIV. Single women exhibited 24% lower fertility desires than their married counterparts (p = 0.013). Women who did not know of the integrated FP services offered from the ART clinic facilities had 18% lower fertility desires than their counterparts who knew (p = 0.045). Conversely, women with a positive history of planned pregnancies showed 17% higher fertility desires than their counterparts with positive history of unintended pregnancies (p = 0.040). Similarly, current modern contraceptive users had 23% lower fertility desires than their counterparts who were non-current users (p = 0.003). The utilization of an integrated HIV care and FP services was significantly lower (30.1%) among the YWLHIV with fertility desires compared to 48.9% among those without fertility desires (X 2 5.991, df 1, p = 0.014). Conclusions The study found a high fertility desires but lower utilization of an integrated HIV care and FP services among the YWLHIV in a Ugandan setting. Whereas the factors responsible for the low utilization of an integrated HIV and FP services remains question for future research, being married, having knowledge and receiving modern contraceptive methods from the ART clinic facility, experiences of planned pregnancy and non-current use of modern contraceptives were associated with the higher odds of fertility desires among the YWLHIV. These findings highlight the need to address the low utilization of an integrated HIV care and FP services, marital expectations and modern contraceptive access within the HIV care for YWLHIV with fertility desires.
Different green synthesis methods of Co3O4 NPs using aloe vera leaves: enhance H2 and O2 production from NaBH4 hydrolysis and H2O2 decomposition
Abstract Green synthesis of cobalt oxide nanoparticles (Co 3 O 4 NPs) was achieved using aloe vera leaves via hydrothermal, microwave irradiation, and co-precipitation methods. XRD analysis confirmed the high purity and crystallinity of the catalysts, as no other phases or impurities were observed in the crystal lattice. Catalysts’ morphology was visualized by FESEM images that showed flower-like morphology for AHT and capsule-like shapes for AMW and AWB. The chemical environment was identified by XPS analysis, which also confirmed the synthesis of Co 3 O 4 NPs by the presence of Co 2+ and Co 3+ ions on the catalysts’ surface. All catalysts exhibited dual functionality: catalyzing NaBH 4 hydrolysis and H 2 O 2 decomposition. During NaBH 4 hydrolysis, AHT demonstrated superior catalytic performance with a hydrogen generation rate (HGR) of 4267 ml.min − 1 .g − 1 at 45 °C. Further study on the efficient catalyst (AHT) was performed to evaluate the effect of catalyst weight, NaBH 4 concentration, alkalinity, and recyclability on catalytic activity. In H 2 O 2 decomposition, AWB displayed higher activity with a lower activation energy (E a ) of 39.66 kJ/mol.
Integrated computational analysis identifies FABP4, PTGS2, and HPGD as Key molecular targets linking PET microplastic exposure to metabolic dysfunction-associated steatotic liver disease
Background Metabolic dysfunction-associated steatotic liver disease (MASLD) affects 25–38% of the global population, yet the contribution of environmental polyethylene terephthalate (PET) microplastics to its pathogenesis remains unclear. PET microplastics accumulate in the liver at approximately 4.6 particles per gram of tissue and have been implicated in metabolic disturbance, oxidative stress, and inflammation, but their molecular targets and mechanisms in MASLD are not well defined. Methods We integrated three GEO microarray cohorts (GSE37031, GSE63067, GSE89632) and performed differential expression analysis, weighted gene co-expression network analysis (WGCNA), and PET target prediction using ChEMBL, PharmMapper, and SwissTargetPrediction. Functional enrichment, protein-protein interaction network analysis, CIBERSORT-based immune deconvolution, molecular docking, and 100 ns molecular dynamics simulations were employed to identify and validate hub genes. Results Integration of MASLD transcriptomes and PET target predictions yielded 19 overlapping genes enriched in pathways related to lipid metabolism, fatty acid degradation, glycolysis/gluconeogenesis, and chemical carcinogenesis. Network topology consistently highlighted FABP4, PTGS2, and HPGD as central hub genes. Immune deconvolution revealed MASLD-associated alterations characterized by increased M2 macrophages and γδ T cells, with decreased monocytes, dendritic cells, and naive B cells. PTGS2 and FABP4 expression showed strong correlations with innate immune cells. Molecular docking demonstrated favorable PET binding to all three proteins (–6.3 to –6.9 kcal/mol), and molecular dynamics simulations confirmed stable complexes over 100 ns, with predominantly hydrophobic interactions. Conclusions Through integrated bioinformatics analysis and molecular simulation, this study identifies FABP4, PTGS2, and HPGD as potential molecular targets through which PET microplastics may influence lipid metabolism, prostaglandin signaling, and innate immune responses in MASLD. Molecular docking and dynamics simulations suggest favorable binding interactions between PET and these proteins.
Solitary wave solutions and fractional effects of the time fractional equal width equation
Long-term care hospitals as end-of-life care settings in South Korea: A nationwide analysis of utilization patterns and clinical trajectories
Objectives This study aimed to investigate the utilization patterns and end-of-life trajectories of older adults in Korean long-term care hospitals (LTCHs) using nationwide population-based data. Methods This retrospective observational study analyzed National Health Insurance Service claims data (2014–2023). We constructed three analytical groups: an annual inpatient group to examine longitudinal trends in volume and mortality; a newly admitted inpatient group to assess the sociodemographic profile at the time of LTCH entry; and a decedent group to reconstruct the clinical trajectory and cumulative resource use from initial admission to death. Results While the volume of older inpatients increased, the annual number of deaths involving LTCH use increased from 68,357 in 2014 to 112,157 in 2023 over the decade. Patients were newly admitted to LTCHs in their early 80s (median age 81 years, IQR 75–86) and were predominantly female (62.1%). In addition, Medical Aid beneficiaries (13.7%) and individuals with registered disabilities (28.0%) were overrepresented, indicating high sociodemographic vulnerability. Decedents spent a median of 79 days (IQR 22–299) as LTCH inpatients. While 30.1% stayed for <30 days, 22.2% remained hospitalized for ≥ 360 days, indicating substantial variation in length of stay. Overall, 68.5% of decedents died during LTCH stay. While admissions were driven by chronic geriatric syndromes, the end-of-life phase was dominated by a surge in acute infectious and systemic conditions (e.g., pneumonia, 10.2% to 22.3%; sepsis, 3.3% to 11.9%). Conclusions LTCHs in Korea have played an increasingly important role as a setting for end-of-life care, managing a distinct trajectory from chronic frailty to acute deterioration. Given that these institutions are functioning as end-of-life care settings, policy reforms should strengthen palliative care integration, advance care planning, workforce training, and end-of-life care capacity within LTCHs.
Effects of promotional and preventive framing strategies in AI generated content on neural responses and trust
Research advances in key genes and regulatory mechanisms of posttranslational modifications in Parkinson’s disease
Background The genesis of Parkinson’s disease (PD), a common central neurodegenerative disorder, involves dysregulation of protein posttranslational modifications (PTM). The primary objective of this study was to screen key PTM-associated genes (PTMGs) serving as diagnostic indicators and potential therapeutic targets in PD. Methods Peripheral blood transcriptomic data for PD cohorts and healthy controls were retrieved from publicly accessible repositories. Candidate genes were identified by overlapping differentially expressed genes (DEGs) with established PTMGs via differential expression profiling. Machine learning-based screening approaches were used for the selection of feature genes. Key genes were validated via receiver operating characteristic curve assessment combined with verification of expression levels. Subsequently, enrichment analysis, immune infiltration assessment, chromosome mapping, prediction of ribonucleic acid (RNA) modification sites, and compound screening were further explored. Results A total of 404 DEGs were identified, 19 of which overalpped with PTMGs and were thus selected as candidate genes. ML-based analysis narrowed these to eight feature genes, among which those coding for beta-1,4-galactosyltransferase 3 ( B4GALT3 ), ring finger and FYVE-like domain-containing E3 ubiquitin protein ligase ( RFFL ), and GABA type A receptor-associated protein ( GABARAP ) were validated as key genes based on their diagnostic performance and consistent downregulation in the PD group ( p < 0.05). Gene set enrichment analysis demonstrated significant enrichment within immune signaling cascades. Analysis of immune cell infiltration revealed diminished populations of activated B lymphocytes, activated CD4-positive T cells, and natural killer T cell subsets in the PD group, which exhibited predominantly positive associations with the identified key genes ( p < 0.05). Chromosome mapping localized B4GALT3 to chromosome 1 and RFFL / GABARAP to chromosome 17. High-confidence m 6 A methylation sites were predicted for B4GALT3 and RFFL . Compound screening identified 34 potential compounds targeting these genes, including valproic acid and phenobarbital. Conclusion This study identified B4GALT3 , RFFL , and GABARAP as key PTMGs in PD, highlighting their roles in PD genesis and potential as diagnostic biomarkers.
Association of the cardiometabolic index and depressive symptoms with cardiovascular disease in cardiovascular-kidney-metabolic syndrome stages 0–3: A prospective cohort study
A data-driven remote sensing approach for VMS mineralization mapping: Integrating Sentinel-2 imagery with geology data in the Asmara Belt, Eritrea
Mineral resources play a critical role in the sustainable economic development of countries. In Eritrea, conventional mineral exploration and geological mapping methods are expensive, time-consuming, and in some inaccessible areas, difficult to implement. Advances in remote sensing and data-driven analytical techniques now provide efficient alternatives for mineral exploration. This research applies a remote sensing and data-driven approach, combining multispectral Sentinel-2 imagery with field geological data, to identify volcanogenic massive sulfide (VMS) deposits and map lithology in the arid Asmara mineralized belt of Eritrea. Image processing techniques, including band ratios and Feature Oriented Principal Components Selection (FPCS), were combined with supervised classification algorithms such as Maximum Likelihood, Minimum Distance, and Spectral Angle Mapper to derive geological classes. Field data, including rock samples and GPS locations of known VMS gossans, were integrated for model training, thin-section validation, and performance assessment. The results demonstrate that hydrothermal alteration zones associated with VMS deposits, expressed as oxidized gossans, were effectively distinguished from widespread but unmineralized hematitic laterites using the Chica-Olma ratio method and supervised classification algorithms. The derived lithological and alteration maps show strong agreement with existing geological maps, and the locations of known VMS deposits, underscoring the potential of combining Sentinel-2 imagery and geological field data for mineral exploration in the Arabian–Nubian Shield.
Exploring the mechanism of 6PPD/6PPD-Q-induced allergic rhinitis based on network toxicology, molecular docking, and molecular dynamic simulation
Abstract N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD) and its ozonated derivative, 6PPD-quinone (6PPD-Q), are tire-derived contaminants with established aquatic toxicity, yet their role in respiratory allergies like Allergic Rhinitis (AR) remains unclear. This study employs an integrative computational approach combining toxicological profiling, network pharmacology, and molecular dynamics (MD) simulations to elucidate their allergenic mechanisms. Potential targets were identified from multiple databases and intersected with AR-associated genes. Toxicological modeling revealed that both compounds pose significant respiratory and cutaneous sensitization risks, with 6PPD-Q exhibiting notable genotoxicity. Network analysis prioritized PTPRC (CD45), CXCL8, CCL2, TNF, and AKT1 as central hub targets. Functional enrichment indicated that these pollutants may disrupt leukocyte chemotaxis and activate key inflammatory pathways, including IL-17, NF-kappa B, and Fc epsilon RI signaling. MD simulations suggested stable binding of both pollutants within the PTPRC active site; notably, 6PPD-Q was associated with more pronounced conformational changes in the receptor, suggesting a potential for stronger immunomodulatory effects that warrants experimental investigation. This study provides mechanistic insight offers computational insights into how 6PPD and 6PPD-Q could contribute to mucosal immune dysregulation and may promote AR pathogenesis through multi-target actions, providing a preliminary foundation for environmental risk assessment and safer tire additive design.
Linguistic realizations of personality and emotional polarity in Tan Twan Eng’s The Garden of Evening Mists: A systemic functional discourse analysis
This study examines how personality and emotion are linguistically realized in Tan Twan Eng’s The Garden of Evening Mists , drawing on the Big Five Model of Personality (BFM) and Systemic Functional Linguistics (SFL) to construct an integrated theoretical-qualitative framework for the analysis of character language in literary narrative. Emotional polarity is understood as the systematic orientation of affective meaning, positive, neutral, or negative, realized through lexicogrammatical choices at the interpersonal, ideational, and textual levels of language. Through close discourse analysis of selected passages, the study traces how patterns of modality, process type, and cohesion correspond to shifts in emotional polarity across three narrative phases: trauma recollection, apprenticeship in Yugiri, and reflective closure. The findings indicate that emotional polarity in the novel can be read as a form of psychological adaptation rather than static sentiment: negative polarity, realized through obligation modals and syntactic compression, reflects a high-Conscientiousness, high-Neuroticism configuration associated with trauma-related self-regulation; neutral polarity, marked by evaluative balance and descriptive cohesion, signals stabilized Conscientiousness and emerging Openness; positive polarity, expressed through relational processes and permissive modality, corresponds to increased Openness and diminished Neuroticism. The interpersonal dimensions of Agreeableness and Extraversion are realized at lower density but trace parallel arcs across the three phases, with Agreeableness providing the linguistic site at which the novel’s central thematic question of inherited hatred is settled. By integrating Big Five personality theory with systemic-functional analysis, the study offers a theoretically grounded and interpretively transparent framework for investigating how emotional language encodes personality transformation in narrative discourse. The findings contribute to ongoing dialogues between personality psychology, functional linguistics, and literary stylistics and illustrate how this framework can be applied to postcolonial narrative fiction.
Study of the densification mechanisms of Al–Fe–Cr–Ti alloys during high-velocity compaction based on 3D MPFEM
Abstract Aluminum alloy materials are widely used in aerospace and related fields, among which Al–Fe–Cr–Ti alloys have attracted increasing attention owing to their low density and excellent comprehensive properties. However, the densification mechanisms of alloy powders during high-velocity compaction (HVC) remain insufficiently understood. In this study, a three-dimensional multi-particle finite element method (3D MPFEM) model was developed to simulate the HVC process of Al–Fe–Cr–Ti alloy powders and to evaluate the effects of friction coefficient μ , impact energy per unit mass E m , hammer mass M , and compaction velocity v on powder densification. The results show that increasing μ from 0.25 to 0.65 reduced kinetic-energy transfer and stress transmission, decreasing the relative density ρ of the green from 0.7076 to 0.6797. In contrast, increasing E m from 55.58 to 144.67 J/g markedly improved densification, with the maximum relative density reaching 0.8881. Displacement-field analysis further revealed that appropriate combinations of M and v promote particle rearrangement and plastic deformation. Experimental validation confirmed that the simulated density evolution agreed well with the measured trend, although the predicted values were slightly lower. These findings indicate that 3D MPFEM can reasonably describe the macroscopic densification trend and provide qualitative particle-scale insights into deformation and energy-transfer behavior during HVC.
Forecasting user engagement and competing cascades in social media diffusion: A Hawkes-Transformer approach
Social media has evolved into a socio-technical infrastructure that shapes public attention, social interaction, and information governance. Understanding how user engagement behaviors, such as retweets, comments, and likes, collectively influence information diffusion is important for forecasting digital dynamics. Using large-scale data from Sina Weibo, this study develops a hybrid Hawkes–Transformer framework that combines the interpretability of self-exciting point processes with the predictive capacity of deep learning. The model captures both interactions within a post and competition across parallel posts within the same trending topic. Empirical results show that retweets strongly amplify diffusion through self-excitation, while comments can suppress diffusion by diverting user attention. In addition, parallel cascades tend to fragment rather than reinforce information flow. By incorporating Hawkes-estimated parameters as structured inputs into a Transformer model, the proposed approach improves predictive performance while retaining interpretability. These findings provide insights into how attention is distributed and competed for in social media environments, with implications for understanding algorithmic visibility and managing information diffusion.