29 research outputs found

    A New Risk Evaluation Model for Safety Management on an Entire Ship Route

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    In this paper, we introduce a new risk evaluation model for evaluating the navigation safety zone for an entire ship route. This model considers a new algorithm to determine the navigational safety zone in real-time, and also takes the navigation officers’ perception while navigating a ship into consideration. The risk quantification has been developed using a questionnaire and incorporated into the new model. A simulation was carried out for the Osaka bay area in order to verify the usefulness of the proposed model. A new approach was employed to monitor the level of navigation safety along a ship route. The entire ship route is divided into small sections as a gridded matrix. The level of navigation safety can be quantified by means of a safety index on the basis of the ship’s navigation data within a specified distance range. The results show that the comparison between risks identified for different sections across the entire ship route is easy, which helps determine the navigational safety zone quickly. This model is expected to be able to serve as a new tool for managing safety throughout an entire ship route area in real-time in order to support the port safety authority or vessel traffic service center

    Formal Safety Assessment (FSA) for Analysis of Ship Collision Using AIS Data

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    Currently, Maritime safety is the best issue in the world. International Maritime organization (IMO) have recommended FSA methodology to enhance maritime safety. In this paper, the research conducted in the Malacca Strait. Malacca Strait is an area that has a high risk for shipping navigation. Many accidents occur in the area are like collision, fire, grounding and so on. Therefore a study on improving safety in this area is very important. it is to produce an output that can be used to provide input to the master and multiple stakeholders to improve safety on board at the time of sailing. In this study, AIS is used as a data source. Sea condition data collected actual traffic through the Automatic Identification System (AIS) equipment installed at Kobe University, Japan, and Universiti Teknologi Malaysia (UTM) in Johor, Malaysia. The data is applied to define a method with the help of Geographic Information Systems (GIS)

    Probability of Ship on Collision Courses Based on the New PAW Using MMG Model and AIS Data

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    This paper proposes an estimation method for ships on collision courses taking crash astern maneuvers based on a new potential area of water (PAW) for maneuvering. A crash astern maneuver is an emergency option a ship can take when exposed to the risk of a collision with other ships that have lost control. However, lateral forces and yaw moments exerted by the reversing propeller, as well as the uncertainty of the initial speed and initial yaw rate, will move the ship out of the intended stopping position landing it in a dangerous area. A new PAW for crash astern maneuvers is thus introduced. The PAW is developed based on a probability density function of the initial yaw rate. Distributions of the yaw rates and speeds are analyzed from automatic identification system (AIS) data in Madura Strait, and estimated paths of the maneuvers are simulated using a mathematical maneuvering group model

    The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

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    「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection

    DOCK2 is involved in the host genetics and biology of severe COVID-19

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    「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target

    RedNavi: Building a 3D Scene of the Current Sea from AIS Data

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    The Automatic Identification System (AIS) is a kind of navigation equipment that exchanges a wealth of essential information among vessels and between ships to shore through Very High Frequency. Currently, identification and other navigational information can be obtained in real time with AIS data integrated into other shipborne systems, such as the Electronic Chart Display and Information System and radar. However, at present, AIS information is represented in a two-dimensional (2D) way, which is not the same as the three-dimensional (3D) world people perceive visually. In this paper, we introduce RedNavi, a sustainable computer 3D scene building system that visualizes the current sea, specifically the environment and traffic conditions around the ownship, using received AIS data. RedNavi has a wide range of application scenarios. Applying to the maritime education and training field, it can serve as a bridge between the 2D and 3D worlds, helping less experienced trainees build up their capabilities. Applying to actual navigation, it can provide the deck officer with another visual aid to their lookout in addition to existing 2D information systems. In addition, given the microservices architecture RedNavi adopts, the development, deployment, and maintenance processes become relatively lighter, faster, and easier, and therefore more sustainable than traditional monolithic systems

    Shipboard Data Compression Method for Sustainable Real-Time Maritime Communication in Remote Voyage Monitoring of Autonomous Ships

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    Due to the ever-increasing amount of data collected and the requirements for the rapid and reliable exchange of information across many interconnected communication devices, landbased communications networks are experiencing continuous progress and improvement of existing infrastructures. However, maritime communications are still characterized by slow communication speeds and limited communication capacity, despite a similar trend of increasing demand for information exchange. These limitations are particularly evident in digital data exchange, which is still limited to relatively slow and expensive narrowband satellite transmission. Furthermore, with the increasing digitalization of ships and introducing the sustainable concept of autonomous ship operation, large amounts of collected data need to be transmitted in real-time to enable remote voyage monitoring and control, putting additional pressure on the already strained means of maritime communications. In this paper, an adaptive shipboard data compression method based on differential binary encoding is proposed for real-time maritime data transmission. The proposed approach is verified on the actual data collected on board a training ship equipped with the latest data acquisition system. The obtained results show that the proposed data encoding method efficiently reduces the transmitted data size to an average of 3.4% of the original shipboard data, thus significantly reducing the required data transmission rate. Moreover, the proposed method outperforms several other tested competing methods for shipboard data encoding by up to 69.6% in terms of compression efficiency. Therefore, this study suggests that the proposed data compression approach can be a viable and efficient solution for transmitting large amounts of digital shipboard data in sustainable maritime real-time communications

    BlueNavi: A Microservices Architecture-Styled Platform Providing Maritime Information

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    Traditional methods of marine navigation are undergoing a revolution brought about by the almost universal adoption of the Automatic Identification System (AIS). AIS exchanges a wealth of navigational information among vessels and between ships to shore through Very High Frequency (VHF). With AIS data integrated into the Electronic Chart Display and Information System (ECDIS), the identification and navigational information of surrounding vessels as well as aids to navigation can be reflected on the electronic charts in real time, despite some problems such as the low AIS carriage rate on small vessels where it is not mandatory and the high cost of ECDIS preventing such vessels from installing it. In this paper, we introduce BlueNavi, a lower cost but sustainable maritime information providing platform built with microservices architecture allowing flexible on-demand scalability and cross-platform adaptability. Applications served by BlueNavi can provide users with data either stored in a remote data center through the internet or received locally by devices connected to the station without the need for the internet. From our land test, we show that users with only an internet connection but without any AIS equipment can also obtain live AIS data collected by other stations. Conversely, with access to the internet, BlueNavi can also send data back to the land stations, enabling other ships to identify non-AIS ships as well. Through the live-ship test, we demonstrate that BlueNavi works well offline in cooperation with shipborne AIS equipment. We also look at some possible application scenarios for BlueNavi with other data sources and means of communication other than AIS and VHF that can be expanded to the platform. BlueNavi will enable inexpensive ship identification for small vessels and provide an extension of functionality to ECDIS for large ships
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