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A Review of the Issues in the Process of Inscribing Japans Modern Industrial Heritage as a World Heritage Site: A Focus on the Meiji Industrial Revolution Heritage and
No full textTMF-GNN: Temporal matrix factorization-based graph neural network for multivariate time series forecasting with missing values
No full textMissing data in multivariate time series (MTS) is a very common issue, often caused by unreliable sensors and data storage or transmission problems. Particularly, such missing data can cause some errors and biases in the MTS forecasting tasks of real-world applications, implying that proper handling of the missing data is essential. Therefore, in this study, we propose anew method for MTS forecasting with missing values, called a temporal matrix factorization-based graph neural network (TMF-GNN), to improve predictive performance outcomes. TMF-GNN basically uses the concept of TMF, which reconstructs partially observed MTS data. We newly present a data-adaptive regularization method for TMF based on graph-based and sequential deep learning algorithms to capture both the variable-wise and time-wise information of MTS data affected by missingness. We demonstrate the feasibility of the proposed method by conducting various experiments on three MTS datasets and show how it outperforms baseline methods. We believe that our study will have an impact on several MTS-related tasks and that it can be a useful alternative for handling missing values in MTS data.Y
Machine Learning-based Photometric Redshifts for Galaxies in the North Ecliptic Pole Wide Field: Catalogs of Spectroscopic and Photometric Redshifts
No full textWe perform an MMT/Hectospec redshift survey of the North Ecliptic Pole Wide (NEPW) field covering 5.4 deg2 and use it to estimate the photometric redshifts for the sources without spectroscopic redshifts. By combining 2572 newly measured redshifts from our survey with existing data from the literature, we create a large sample of 4421 galaxies with spectroscopic redshifts in the NEPW field. Using this sample, we estimate photometric redshifts of 77,755 sources in the band-merged catalog of the NEPW field with a random forest model. The estimated photometric redshifts are generally consistent with the spectroscopic redshifts, with a dispersion of 0.028, an outlier fraction of 7.3%, and a bias of -0.01. We find that the standard deviation of the prediction from each decision tree in the random forest model can be used to infer the fraction of catastrophic outliers and the measurement uncertainties. We test various combinations of input observables, including colors and magnitude uncertainties, and find that the details of these various combinations do not change the prediction accuracy much. As a result, we provide a catalog of 77,755 sources in the NEPW field, which includes both spectroscopic and photometric redshifts up to z similar to 2. This data set has significant legacy value for studies in the NEPW region, especially with upcoming space missions such as JWST, Euclid, and SPHEREx.N
Evaluating the impact of attention shift intervention on human evacuation behavior in virtual environment
No full textTraditional auditory evacuation cues, such as fire alarms, frequently fail to capture individuals' attention, particularly when they are using handheld devices. This study investigates the effectiveness of attention shift interventions delivered via emergency text messages displayed on these devices to improve evacuation responses. Participants in a virtual reality simulation of a metro station were exposed to emergency cues through auditory broadcasts or visual text messages. The findings show that visual attention shift interventions reduce the likelihood of re-engaging in pre-evacuation activities while improving evacuation performance when compared to auditory cues. Continuous visual cues were more effective than auditory cues in keeping attention during evacuation. These results highlight the potential for personalized visual communication to improve emergency response strategies in environments where handheld devices are widely used, providing critical insights into developing more effective emergency communication systems for improved evacuation behavior and overall safety during emergencies.Y
Artificial intelligence system for identification of overlooked lung metastasis in abdominopelvic computed tomography scans of patients with malignancy
No full textPURPOSE This study aimed to evaluate whether an artificial intelligence (AI) system can identify basal lung metastatic nodules examined using abdominopelvic computed tomography (CT) that were initially overlooked by radiologists. METHODS We retrospectively included abdominopelvic CT images with the following inclusion criteria: a) CT images from patients with solid organ malignancies between March 1 and March 31, 2019, in a single institution; and b) abdominal CT images interpreted as negative for basal lung metastases. Reference standards for diagnosis of lung metastases were confirmed by reviewing medical records and subsequent CT images. An AI system that could automatically detect lung nodules on CT images was applied retrospectively. A radiologist reviewed the AI detection results to classify them as lesions with the possibility of metastasis or clearly benign. The performance of the initial AI results and the radiologist's review of the AI results were evaluated using patient-level and lesion-level sensitivities, false-positive rates, and the number of false-positive lesions per patient. RESULTS A total of 878 patients (580 men; mean age, 63 years) were included, with overlooked basal lung metastases confirmed in 13 patients (1.5%). The AI exhibited an area under the receiver operating characteristic curve value of 0.911 for the identification of overlooked basal lung metastases. Patient- and lesion-level sensitivities of the AI system ranged from 69.2% to 92.3% and 46.2% to 92.3%, respectively. After a radiologist reviewed the AI results, the sensitivity remained unchanged. The false-positive rate and number of false-positive lesions per patient ranged from 5.8% to 27.6% and 0.1% to 0.5%, respectively. Radiologist reviews significantly reduced the false-positive rate (2.4%-12.6%; all P values < 0.001) and the number of false-positive lesions detected per patient (0.03-0.20, respectively). CONCLUSION The AI system could accurately identify basal lung metastases detected in abdominopelvic CT images that were overlooked by radiologists, suggesting its potential as a tool for radiologist interpretation. CLINICAL SIGNIFICANCE The AI system can identify missed basal lung lesions in abdominopelvic CT scans in patients with malignancy, providing feedback to radiologists, which can reduce the risk of missing basal lung metastasis.Y
Temporal Trends in Stroke Management and Outcomes Between 2011 and 2020 in South Korea: Results From a Nationwide Multicenter Registry
No full textBackground This study aims to evaluate temporal trends of advanced treatments and related clinical outcomes of ischemic stroke through a decade-long trend analysis, using data from a comprehensive, national, multicenter registry. We also seek to identify areas in need of improvement. Methods and Results This analysis involved patients with ischemic stroke or transient ischemic attack registered prospectively in the CRCS-K-NIH (Clinical Research Center for Stroke in Korea-National Institute of Health) registry between 2011 and 2020. We examined temporal trends in risk factors, pathogenetic subtypes, acute management strategies, and outcomes for up to 1 year following a stroke. Generalized linear mixed models were used to account for center clustering. The average age of 77 662 patients increased 2.2 years in men and 2.4 years in women over the 10-year follow-up. Notably, in-hospital neurological deterioration, 3-month and 1-year mortality rate, and cumulative incidence of recurrent stroke within 1-year decreased over time after adjustments for age, sex, and initial stroke severity (P<0.01). However, functional outcomes at 3 months and 1 year remained unchanged. Endovascular thrombectomy increased from 5.4% in 2011 to 10.6% in 2020. Use of anticoagulants for atrial fibrillation, dual antiplatelet therapy, statins, and stroke unit care also increased. Contrarily, the rate of intravenous thrombolysis showed a slight decline. Conclusions This study points to a reduction in death and risk of recurrent stroke over the past decade, paralleling enhancement in acute and preventive stroke management. Nevertheless, the decline in the use of intravenous thrombolysis and the lack of improvement in functional outcomes following stroke are concerning trends that warrant thorough investigation.Y
Need for and Acceptance of Digital Health Interventions for Self-Management Among Older Adults Living Alone: A Mixed-Methods Approach
No full textPurpose: Although digital solutions could mitigate the challenges faced by older adults living alone (OALA), only a few studies investigated the need for and acceptance of digital health interventions for self-management (DHISMs) among this demographic. Thus, we aim to explore this need and acceptance, along with the contextual factors, among OALA. Methods: A mixed-methods research approach was adopted. We conducted 1) a quantitative survey (n = 191) to investigate the need for and acceptance of DHISMs using a numeric rating scale and 2) a qualitative study (n = 24) based on focus group interviews to explore contextual factors related to the quantitative results. Qualitative data were analyzed using thematic analysis. Results: In the quantitative study, the mean scores for the need for and acceptance of DHISMs were 6.41 and 6.53 out of 10, respectively. Emergency response systems had the highest need and acceptance scores, whereas digital interventions for behavioral change (medication adherence, sleep, stress, and diet management) had relatively lower scores. The qualitative analysis revealed two themes and five subthemes: the need for inclusive support for independent living (environmental safety and diverse self-management challenges with limited support) and multidimensional factors related to DHISM acceptance (personal, technological, and relational barriers and facilitators). Conclusions: In the future, the unique and multidimensional factors influencing the need for and acceptance of DHISMs among OALA should be carefully considered to support their self-management and independent living. Blended care, which involves integrating age-friendly technology with personalized human interaction, is pivotal for increasing DHISM acceptance in this population. (c) 2025 Korean Society of Nursing Science. Published by Elsevier BV. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Y
Efficacy of Zenocutuzumab in NRG1 Fusion-Positive Cancer
No full textBACKGROUND Neuregulin 1 (NRG1) fusions are recurrent oncogenic drivers found in multiple solid tumors. NRG1 binds to human epidermal growth factor receptor 3 (HER3), leading to heterodimerization with HER2 and activation of downstream growth and proliferation pathways. The efficacy and safety of zenocutuzumab, a bispecific antibody against HER2 and HER3, in patients with NRG1 fusion-positive solid tumors are unclear. METHODS In this registrational, phase 2 clinical study, we assigned patients with advanced NRG1 fusion-positive cancer involving any tumor type to receive zenocutuzumab at a dose of 750 mg intravenously every 2 weeks. The primary end point was overall response (complete or partial response) according to investigator assessment. Secondary end points included duration of response, progression-free survival, and safety. RESULTS A total of 204 patients with 12 tumor types were enrolled and treated. Among 158 patients who had measurable disease and were enrolled at least 24 weeks before the data-cutoff date, a response occurred in 30% (95% confidence interval [CI], 23 to 37). The median duration of response was 11.1 months (95% CI, 7.4 to 12.9); 19% of responses were ongoing at the data-cutoff date. Responses were observed in multiple tumor types - including in 27 of 93 patients (29%; 95% CI, 20 to 39) with non-small-cell lung cancer (NSCLC) and 15 of 36 patients (42%; 95% CI, 25 to 59) with pancreatic cancer - and across multiple NRG1 fusion partners. The median progression-free survival was 6.8 months (95% CI, 5.5 to 9.1). Adverse events were primarily grade 1 or 2. The most common adverse events that were considered by the investigator to be related to zenocutuzumab were diarrhea (in 18% of the patients), fatigue (in 12%), and nausea (in 11%). Infusion-related reactions (composite term) were observed in 14% of the patients. One patient discontinued zenocutuzumab owing to a treatment-related adverse event. CONCLUSIONS Zenocutuzumab showed efficacy in patients with advanced NRG1 fusion-positive cancer, notably NSCLC and pancreatic cancer, with mainly low-grade adverse events. (Funded by Merus; eNRGy ClinicalTrials.gov number, NCT02912949.)N
Molecular dynamics-informed material point method for hypervelocity impact analysis
No full textThis paper introduces a framework specifically designed to simulate hypervelocity impact scenarios precisely. The framework utilizes the multiscale shock technique (MSST) from molecular dynamics (MD) to accurately model material states under extreme impact loading conditions, focusing on calculating the equation of state (EOS). A vital aspect of this work is the acquisition and application of the Mie-Gruneisen EOS, which is highly relevant in impact analysis research. The framework employs the material point method (MPM) to conduct analyses of hypervelocity impacts using the derived EOS. This method offers a detailed insight into the dynamic responses of materials subjected to hypervelocity impacts, underscoring the integration of molecular dynamics with the MPM.N
Paradox of Time Pressure: Cognitive and Task Performance during Time-Sensitive and Challenging Teleoperation
No full textA heavy machinery operators' ability to adhere to schedules is crucial for the success of construction projects. However, unforeseen delays often occur during projects, forcing operators to expedite their work. This pressure often presents challenges for teleoperators. Completing tasks remotely typically takes longer than performing the same tasks on-site due to reduced situational awareness and reliance on technology for perception and understanding in remote workplaces. These inherent aspects of teleoperation add complexity to tasks, especially under time-constrained conditions. This study explores operators' cognitive and task performance during teleoperation of challenging tasks under various time pressures. Thirty-one participants operated a virtual excavator under four different levels of time pressure during the experiments. Results show that appropriate time pressure enhances task performance in aspects of safety, productivity, and quality, whereas excessive pressure results in cognitive overload, disengagement, impaired situational awareness, increased errors, and reduced productivity. This research contributes to enhancing the understanding of teleoperation from the operator's perspective, addressing cognitive challenges to improve safety and efficiency during the remote operation of heavy machinery in construction.N