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The 13th Symposium on Polar Science/Interdisciplinary sessions [IA] Arctic research, Thu. 17 Nov.

The 13th Symposium on Polar Science/Interdisciplinary sessions [IA] Arctic research, Thu. 17 Nov.

In summer 2018, thick sea ice blocked the mouth of the Amundsen Gulf (AG), Canada, obstructing shipping through the North-west Passage. This study analysed multi-year ice motion to investigate the source of this thick ice and the reasons for its unusual movement. For this purpose, a daily multi-year ice distribution product was generated by ice tracking using gridded daily sea-ice velocities (2003–2018) derived from the AMSR-E and AMSR-2 data. From autumn 2017 to summer 2018, the area of multi-year ice extended westward to the Beaufort Sea and then migrated towards the AG mouth. The primary cause of the unusual ice cover was anomalous AG-ward wind in September 2018. It is known that multi-year ice has become increasingly moveable over the past decades, as indicated by the increasing wind factor (i.e., ratio of ice-drift speed and wind speed), but the unusual ice motion in the summer of 2018 cannot be explainable by the wind factor alone. Accurately, predicting monthly wind and monitoring old thick ice will reduce the risk posed by thick Arctic sea ice to shipping.

The Japanese research vessel MIRAI sailed into the Arctic Ocean through the Bering Strait from 4 to 25 November 2018 to study the atmosphere, ocean, and sea ice of the Chukchi Sea. Early winter dyn...

With the reduction in extent of Arctic Ocean sea ice in recent years, commercial use of Arctic Sea shipping routes has attracted increasing attention. An urgent task for promoting the use of safe and cost-efficient routes in the Arctic Sea is the construction of a navigation support system. Such a system is essential not only for monitoring and forecasting the extent of sea ice but also for integrating such information in determination of the optimal route. This research developed an Arctic Sea Route Search System that has been published as a web application on the Arctic Data archive System website. Ship speed is calculated based on an approximate expression of actual Automatic Identification System data and an Ice Index, which is an index that reflects the ease of navigation based on ice type and the ship’s ice class. The A* algorithm searches for the optimal route using a search graph that places nodes at the grid positions of input data. Comparison of several test calculations using different parameters confirmed that the route search system provides reasonable results.

Recently, cyclones are quite active and dramatically influence the sea ice distribution in the Arctic region. Therefore, precise prediction of sea ice distribution during the cyclones is crucial for safe and efficient navigation in the Arctic Ocean. A high-resolution (about 2.5 km) ice–ocean coupled model is developed for forecasting the short-term sea ice distribution along the Arctic sea routes. Since a commercial ship navigates to avoid the sea ice as much as possible, a factor to score the forecast skill is considered to be ice edge error which is an averaged distance between forecasted and observed ice edges. First, we discuss the influence of horizontal grid resolution on short-term sea ice predictions during May to November 2015. The model grid resolution is varied from 2.5 km, 5 km, 10 km and 15 km. This grid dependency study suggests that the 2.5 km resolution model predicts the ice edge accurately compared to the satellite observations. Second, the primary experiment was run from 2 August 2016 to 7 August 2016 under the extreme cyclone in the Laptev Sea using ensemble predictions. The ensembles are constructed by using forecasted atmospheric forcing data sets from THORPEX Interactive Grand Global Ensemble (TIGGE) project and European Center for Medium-Range Weather Forecast Interim (ERA-Interim) reanalysis data. The ensemble ice edge errors are computed from 2 August 2016 to 7 August 2016. The maximum forecast skill of ensemble average ice edge error in the ice–ocean coupled model is 11.74 ± 0.54 km with the threshold of 15% ice concentration for the AMSR2 and model predicted ice edges. It can be said that the present model of 2.5 km grids satisfies the ship crew requirement of around 10 km ice edge error for 5-day forecast.

The purpose of this basic experiment was to examine the effects of soft touching on an experiment participant&rsquo, s back on tidal volume (TV), as an increase in TV was considered an indication of enhanced relaxation. Healthy experiment participants were divided into an intervention group, where soft touching was administered for two minutes on their back, and a control group, where they were asked to rest. Then the change in TV was measured using a spiro-meter two factor analysis of variance (ANOVA, mixture design) was conducted. As a result of two factor ANOVA, the intervention group&rsquo, s TV changed with statistical significance, while no statistically significant change was observed in the control group. There was a possibility that soft touching on the back had a positive effect on the increase of TV and relaxation. As a result of soft touching on the back, TV was increased. Subjective indicators suggested that the relaxation was enhanced by soft touching on the back.

The 11th Symposium on Polar Science/Special session: [S] Accelerating Arctic research: Recent progress and future prospect of Arctic research, Tue. 1 Dec.

The 11th Symposium on Polar Science/Special session: [S] Accelerating Arctic research: Recent progress and future prospect of Arctic research, Tue. 1 Dec.

This paper examines the temporal and spatial change in the characteristics of sea-ice motion in the Arctic. Ice motion is generally expressed by a motion at a constant ratio (wind factor) of wind speed, with a certain angle (turning angle) from the wind direction, and ocean currents. This study aimed to reveal the recent changes of the wind factor and turning angle using satellite observation data. We first prepared a daily ice-velocity data set from data for 2003–2017 collected by the satellite microwave sensor Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and its successor, AMSR2. Monthly values of the wind factor and turning angle were calculated by a least squares technique, based on the linear relationship between sea-ice velocity and geostrophic wind velocity. The daily variation of sea-ice motion was strongly correlated with that of the wind. The wind factor and turning angle changed regionally, seasonally and interannually. With regard to long-term trends, the wind factor has increased in almost all areas of the Arctic. However, the trend of increase stopped around 2010, especially around the central Arctic.

The 11th Symposium on Polar Science/Ordinary sessions: [OM] Polar Meteorology and Glaciology, Poster presentations, Mon. 16 Nov. - Fri. 18 Dec.

This study aims to investigate the feasibility of using convolutional neural networks to predict an accurate and high resolution dose distribution from an approximated and low resolution input dose.Sixty-six patients were treated for prostate cancer with VMAT. We created the treatment plans using the Acuros XB algorithm with 2 mm grid size, followed by the dose calculated using the anisotropic analytical algorithm with 5 mm grid with the same plan parameters. U-net model was used to predict 2 mm grid dose from 5 mm grid dose. We investigated the two models differing for the training data used as input, one used just the low resolution dose (D model) and the other combined the low resolution dose with CT data (DC model). Dice similarity coefficient (DSC) was calculated to ascertain how well the shape of the dose-volume is matched. We conducted gamma analysis for the following: DVH from the two models and the reference DVH for all prostate structures.The DSC values in the DC model were significantly higher than those in the D model (p 0.01). For the CTV, PTV, and bladder, the gamma passing rates in the DC model were significantly higher than those in the D model (p 0.002-0.02). The mean doses in the CTV and PTV for the DC model were significantly better matched to those in the reference dose (p 0.0001).The proposed U-net model with dose and CT image used as input predicted more accurate dose.

The Tenth Symposium on Polar Science/Ordinary sessions: [OM] Polar Meteorology and Glaciology, Thu. 5 Dec. / 2F Auditorium , National Institute of Polar Research

The Tenth Symposium on Polar Science/Ordinary sessions: [OM] Polar Meteorology and Glaciology, Wed. 4 Dec. / Entrance Hall (1st floor) , National Institute of Polar Research

The ubiquitous presence of microplastics in the environment has raised serious concern, and several studies have been carried out in this regard. This study aimed to develop a method for producing microplastics in the micrometre range for various biological tests, where the morphology and constituents of the microplastics were guaranteed. The proposed production system was a pin-on-disc abrasive machine, where a pin made of polyethylene terephthalate (PET), polypropylene (PP), or polyvinyl chloride (PVC) was pressed onto a quartz glass disc under saline solution lubrication. Four types of micro-abrasive glass surfaces were prepared with the objective of generating particles with various morphologies. Flake-shaped, spherical or strap-shaped, and both spherical and flake-shaped microplastics were obtained using PET, PP, and PVC pins, respectively. PET, PP, and PVC had modal diameter ranges of 38.8 – 100.6 μm, 0.050 – 532.3 μm, and 62.5 – 675.3 μm, respectively. With the use of a higher abrasive-glass surface, the modal diameter of PET, PP, and PVC microplastics gradually decreased, increased, and increased, respectively. These production mechanisms were discussed in terms of the characteristics of each material (PET, PP, and PVC) and the roles of adhesive and abrasive wear, which were influenced by the pattern of the abrasive-glass surface.

A live center is an important mechanical component of a lathe. Water-based cutting fluids are used when high-speed machining or cooling properties are required. We performed an implementation experiment of the hydrophilic seal into an actual live center for preventing ingress of water-based liquids, which can protect bearings in the live center. The sealing structure was similar to that of an oil seal, where the seal lip is closely attached to the counter-face. Polyvinyl formaldehyde (PVF) with hydrophilic characteristics and a micro-level three-dimensional porous structure was selected as the seal lip material. The water-based cutting fluid was injected to the hydrophilic live center, which was rotated by servo motor. It was confirmed that the PVF seal could prevent the ingress of cutting fluids because the grease in bearings remained, and a stable frictional torque was achieved. The PVF seal color changed to that of the cutting fluid after the experiment, suggesting that the porous hydrophilic layer adsorbed the cutting fluid appropriately. On the superficial PVF layer, microscopic damage of the PVF was observed, however, the continuous porous structure was retained. It was supposed that the adsorbed cutting fluid acted as a boundary lubrication film for separating the dynamic seal surfaces.

The purpose of this study was to correlate the modulation complexity score (MCS) with organ location and to predict potential dose errors for organs before beam delivery for intensity-modulated radiation therapy (IMRT) dosimetry. Sixteen head and neck cancer patients treated with IMRT were selected. Distribution of the relative dose error on each beam was performed using forward projection to the planned dose to compute the predicted dose after doing per-beam quality assurance. Original organ-specific modulation complexity score (oMCS) was created based on a modified MLC, which depended on organ location. First, MCS was calculated based on the change in leaf position between adjacent MLC leaves. Second, the segment edge map (SEM) calculated from the intensity map for each beam was applied to the calculation volume. The oMCS with segment edge (oMCSedge) was derived from the product of oMCS and SEM. The correlation between the dose errors (planned and predicted) and oMCSedge values was evaluated for the target and organs at risk. We have also expanded the original MCS concept to oMCSedge including the organ location. We observed a moderate correlation between the dose errors and oMCSedge for all organs and volumes of interest except the gross tumor volume, brain stem, and spinal cord. In other organs, a moderate improvement in sensitivity was observed on the SEM, which was correlated with dose errors. Although the implementation of oMCSedge would be impractical for normal clinical settings, it is expected that oMCSedge would help a treatment planner to judge whether or not the treatment plan would be acceptably delivered.

With the recent changes in the Arctic climate, increased transportation can be observed in the Arctic Ocean. For safe navigation along the Arctic Sea routes, it is important to accurately predict the ice conditions. In this study the ice-ocean coupled Ice-POM model is improved by a Kalman filter based data assimilation system. This system incorporates sea ice observation data such as sea ice concentration, sea ice thickness and sea ice velocity to improve the numerical predictions. Ocean part of the model is based on the Princeton Ocean Model while the Ice model considers the discrete characteristics of ice along the ice edge. In an ice-ocean coupled model, atmospheric forcing directly affects the accuracy of predictions. However, different atmospheric data sets produced by different weather agencies show large differences in the Arctic region. Model errors largely depend upon the inaccuracies in forcing data. This study uses an ensemble of multiple atmospheric data sets collected from different weather agencies and the spread of the ensemble is taken as an indicator of the model error covariance. The Observation errors were varied according to the location and the season. Assimilation has improved the predictions of sea ice variables. It has also indirectly improved the ocean conditions. This Atmospheric forcing based Kalman filter (AFKF) method outperforms other assimilation methods such as direct assimilation and nudging methods.

In this paper, we applied an artificial neural network (ANN) to the short-term prediction of the Arctic sea ice concentration (SIC). The prediction was performed using encoding and decoding processes, in which a gated recurrent unit encodes sequential sea ice data, and a feed-forward neural network model decodes the encoded input data. Because of the large volume of Arctic sea ice data, the ANN predicts the future SIC of each cell individually. The limitation of these singular predictions is that they do not use information from other cells. This results in low accuracy, particularly when there are drastic changes during melting and freezing seasons. To address this issue, we present a new data scheme including global and local SIC information, where the global information is represented by sea ice statistics. We trained ANNs using different data schemes and network architectures, and then compared their performances quantitatively and visually. The results show that, compared with a data scheme that uses only local sea ice information, the newly proposed scheme leads to a significant improvement in prediction accuracy.

This study aims to produce non-contrast computed tomography (CT) images using a deep convolutional neural network (CNN) for imaging. Twenty-nine patients were selected. CT images were acquired without and with a contrast enhancement medium. The transverse images were divided into 64 × 64 pixels. This resulted in 14 723 patches in total for both non-contrast and contrast-enhanced CT image pairs. The proposed CNN model comprises five two-dimensional (2D) convolution layers with one shortcut path. For comparison, the U-net model, which comprises five 2D convolution layers interleaved with pooling and unpooling layers, was used. Training was performed in 24 patients and, for testing of trained models, another 5 patients were used. For quantitative evaluation, 50 regions of interest (ROIs) were selected on the reference contrast-enhanced image of the test data, and the mean pixel value of the ROIs was calculated. The mean pixel values of the ROIs at the same location on the reference non-contrast image and the predicted non-contrast image were calculated and those values were compared. Regarding the quantitative analysis, the difference in mean pixel value between the reference contrast-enhanced image and the predicted non-contrast image was significant (P < 0.0001) for both models. Significant differences in pixels (P < 0.0001) were found using the U-net model; in contrast, there was no significant difference using the proposed CNN model when comparing the reference non-contrast images and the predicted non-contrast images. Using the proposed CNN model, the contrast-enhanced region was satisfactorily reduced.

The Ninth Symposium on Polar Science/Interdisciplinary sessions: [IA] Open session for the interdisciplinary Arctic Science, Thu. 6 Dec. / 2F Auditorium, National Institute of Polar Research

The Ninth Symposium on Polar Science/Ordinary sessions: [OM] Polar meteorology and glaciology, Wed. 5 Dec. / Entrance Hall (1st floor), National Institute of Polar Research

The Ninth Symposium on Polar Science/Ordinary sessions: [OM] Polar meteorology and glaciology, Wed. 5 Dec. / Entrance Hall (1st floor), National Institute of Polar Research

The Ninth Symposium on Polar Science/Ordinary sessions: [OM] Polar meteorology and glaciology, Wed. 5 Dec. / Entrance Hall (1st floor), National Institute of Polar Research

Flicker and image persistence are major issues for low frequency driving. The photo leakage current in an outdoor light environment causes further image quality deterioration. We developed 7.0-inch WUXGA (1200×RGBW×1920) reflective full-color LCD, equipped with light-shielding metal layer which suppress photo leakage current, driven by LTPS TFT at 1Hz.

To investigate the impact of radiosonde data on the sea-ice forecast in the Northern Sea Route during an extremely developed cyclone on 6 August 2012, a series of numerical experiments were conducted using an ice-ocean coupled model with fine horizontal resolution (approximately 2.5 km). The atmospheric forcing data used for the model were forecast data with (CTL) and without (OSE) initialization by radiosonde data over the Fram Strait, obtained by the German R/V Polarstern, and the European Centre for Medium-Range Weather Forecasts Interim reanalysis data. All numerical experiments were run from 06:00 UTC on 3 August 2012 to 00:00 UTC on 8 August 2012 with an initial sea-ice concentration and thickness derived from the Advanced Microwave Scanning Radiometer 2 satellite data. The root-mean-square error and correlation coefficient for the sea-ice distribution showed that the CTL simulation predicted better the sea-ice distribution in the Northern Sea Route than the OSE simulation. This occurred in particular from 6 to 7 August when the cyclone became strong. The thermodynamic processes resulted in the difference in the sea-ice thickness due to changes in the vertical energy fluxes. However, the differences in the sea-ice concentration and velocity were caused mainly by the dynamics, particularly the difference in wind fields, rather than the thermodynamics. These results suggest that radiosonde data are effective in improving the forecast accuracy of the sea-ice distribution. Therefore, errors in the weather forecast data would have a substantial impact on the safety of ship navigation and the sea-ice distribution.