Search

Projections indicate increasing coastal hazards in the Yellow Sea region owing to relative sea-level rise. Accordingly, regional studies of such change over the Holocene timescale could be helpful in mitigating these threats. Here, we describe the Holocene record of relative sea-level change in the Gochang-Yeonggwang area of South Korea. We compared this record with that of other sites around the coast of the Yellow Sea, including Bohai Bay (China), the Tando Estuary and Gunsan Bay (South Korea), and sites on the east coast of the South Sea and Toyo-oka Basin, Japan. The findings are based on a multi-proxy study, including lithostratigraphy combined with radiocarbon dating and analyses of grain size distribution, magnetic susceptibility, and geochemistry, which facilitated the generation of 89 paleo-sea-level points reconstructed from 28 borehole cores. The early Holocene transgression was found to start later at Gochang-Yeonggwang than at Gunsan Bay, although the distance between them is only 150 km. This result was inferred from substantial differences in sediment delivery owing to Holocene differences in river basin size, topography, and tectonic context. Before ∼7 ka, the slope and highstands from the predicted mean sea-level models at Bohai Bay, Tando Estuary, and Gochang-Yeonggwang were steeper and lower, respectively, from north to south in the Yellow Sea, approaching the slope of the glacio-eustatic sea-level curve. Therefore, the levering effect of transgression in the early Holocene decreased southward in the Yellow Sea. The slight fluctuation in mean sea-level points of the late Holocene resulted from the formation of storm deposit layers in the coastal area, erosion and redeposition in the channel, and geomorphic effects. A partial difference occurred between the relative sea levels at Gochang-Yeonggwang and Toyo-oka. Future relative sea-level research at the southernmost part of the east coast of the Yellow Sea would further improve understanding of the coastal evolution of the region. • The RSL curve slope at ∼8 ka was the steepest among the Yellow Sea east coast sites. • Highstand on RSL is lower than any other east coast site of the Yellow Sea. • Early Holocene transgression levering effect decreased southern of the Yellow Sea east coast. • RSL in the late Holocene was influenced by glacio-eustatic sea-level change. [ABSTRACT FROM AUTHOR]

• First work to investigate solutions for collaborative medical AI model for COVID-19. • A novel federated semi-supervised learning technique is proposed to train a network. • Method fully utilizes available data from different sources, w/ or w/o annotations. • Multinational dataset of 1704 scans from 3 countries (China, Italy, and Japan). • Studies fully evaluate and understand different configurations of the method. [Display omitted] The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using RT-PCR for testing. As a complimentary tool with diagnostic imaging, chest Computed Tomography (CT) has been shown to be able to reveal visual patterns characteristic for COVID-19, which has definite value at several stages during the disease course. To facilitate CT analysis, recent efforts have focused on computer-aided characterization and diagnosis with chest CT scan, which has shown promising results. However, domain shift of data across clinical data centers poses a serious challenge when deploying learning-based models. A common way to alleviate this issue is to fine-tune the model locally with the target domains local data and annotations. Unfortunately, the availability and quality of local annotations usually varies due to heterogeneity in equipment and distribution of medical resources across the globe. This impact may be pronounced in the detection of COVID-19, since the relevant patterns vary in size, shape, and texture. In this work, we attempt to find a solution for this challenge via federated and semi-supervised learning. A multi-national database consisting of 1704 scans from three countries is adopted to study the performance gap, when training a model with one dataset and applying it to another. Expert radiologists manually delineated 945 scans for COVID-19 findings. In handling the variability in both the data and annotations, a novel federated semi-supervised learning technique is proposed to fully utilize all available data (with or without annotations). Federated learning avoids the need for sensitive data-sharing, which makes it favorable for institutions and nations with strict regulatory policy on data privacy. Moreover, semi-supervision potentially reduces the annotation burden under a distributed setting. The proposed framework is shown to be effective compared to fully supervised scenarios with conventional data sharing instead of model weight sharing. [ABSTRACT FROM AUTHOR]

The sustainable management of WEEE (Waste Electrical and Electronic Equipment) can contribute to the defense of the ESBs (Earth System Boundaries) and achievement of the UN SDGs (United Nations Sustainable Development Goals). This work conducted reasonable generation estimation and critical metals quantity assessment of retired mobile phones in Japan with the sales&new method. The generation estimation is based on the statistical data including sales and quantity of the subscribers. The result shows that there are 31.20 million of mobile phones retired in 2021, comparing 32.83 million in 2008. The calculated lifetime have minimum and maximum value in 2008 and 2019, which is 3.36 and 7.58, comparing 6.42 in 2021. 17 metals are selected as critical metals, with which the quantity and dynamic are also calculated. The replacement from feature phones to smart phones demand less of 11 metals, which shows the critical metals savings leading by the technological innovation. [Display omitted] • Conducting the valid generation estimation of retired mobile phones in Japan. • Calculating the critical metals quantity of retired mobile phones in Japan. • Assessing the dynamic of critical metals quantity by technological progress. [ABSTRACT FROM AUTHOR]

Objectives: The early infection dynamics of patients with SARS-CoV-2 are not well understood. We aimed to investigate and characterize associations between clinical, laboratory, and imaging features of asymptomatic and pre-symptomatic patients with SARS-CoV-2. Methods: Seventy-four patients with RT-PCR-proven SARS-CoV-2 infection were asymptomatic at presentation. All were retrospectively identified from 825 patients with chest CT scans and positive RT-PCR following exposure or travel risks in outbreak settings in Japan and China. CTs were obtained for every patient within a day of admission and were reviewed for infiltrate subtypes and percent with assistance from a deep learning tool. Correlations of clinical, laboratory, and imaging features were analyzed and comparisons were performed using univariate and multivariate logistic regression. Results: Forty-eight of 74 (65%) initially asymptomatic patients had CT infiltrates that pre-dated symptom onset by 3.8 days. The most common CT infiltrates were ground glass opacities (45/48; 94%) and consolidation (22/48; 46%). Patient body temperature (p < 0.01), CRP (p < 0.01), and KL-6 (p = 0.02) were associated with the presence of CT infiltrates. Infiltrate volume (p = 0.01), percent lung involvement (p = 0.01), and consolidation (p = 0.043) were associated with subsequent development of symptoms. Conclusions: COVID-19 CT infiltrates pre-dated symptoms in two-thirds of patients. Body temperature elevation and laboratory evaluations may identify asymptomatic patients with SARS-CoV-2 CT infiltrates at presentation, and the characteristics of CT infiltrates could help identify asymptomatic SARS-CoV-2 patients who subsequently develop symptoms. The role of chest CT in COVID-19 may be illuminated by a better understanding of CT infiltrates in patients with early disease or SARS-CoV-2 exposure. Key Points: • Forty-eight of 74 (65%) pre-selected asymptomatic patients with SARS-CoV-2 had abnormal chest CT findings. • CT infiltrates pre-dated symptom onset by 3.8 days (range 1–5). • KL-6, CRP, and elevated body temperature identified patients with CT infiltrates. Higher infiltrate volume, percent lung involvement, and pulmonary consolidation identified patients who developed symptoms. [ABSTRACT FROM AUTHOR]