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We are conducting a research project to develop algorithms to derive information on maritime issues based on images from Geostationary Ocean Color Imager (GOCI), GOCI-II and many others satellite sensors. We are aiming for several practical application areas which are to detect floating macroalgae, marine fog, harmful algal blooms, fine aerosol particles, low sea surface salinity water, to detect and forecast abnormal sea surface temperature, and to derive ocean water quality parameters and primary production. We are also focusing on candidates to discover new practical techniques using machine learning. These practical techniques are integrated into a maritime issue service system which consists of a data collection and processing system and a web-based data display and analysis system. A scheduler was configured for the automation of the data collection and processing system, and a detailed design was carried out. A system prototype based on open-source GIS service was developed. We will verify the performance of the techniques by comparing the results with high-resolution satellite data or reliable in-situ data.

Purpose This study compared the quality of treatment plans for early‐stage, left‐sided breast cancer, as planned for and delivered by the HalcyonTM and VitalBeam®. Materials and methods Fifteen patients diagnosed with early‐stage left‐sided breast cancer, who had received VMAT with hypofractionated SIB, were recruited. All cases were planned using HalcyonTM comprising a dual‐layer MLC (DL‐MLC) and VitalBeam® with a Millennium 120 MLC (VB‐MLC). For the PTVs, the quality of coverage (QC), conformity index (CI), and homogeneity index (HI) were calculated for each plan. The dosimetric differences between the two treatment plans were statistically compared using the Wilcoxon signed‐rank test (p

The chlorophyll and total suspended materials concentrations and remote sensing reflectance data were observed for red tides occurring every summer in waters around the Korean Peninsula. In observation area and date, the field survey were performed (1) in the Jinhae and Geoje coasts during August 1998, August 1999, August 2001, and August 2003, (2) in East Sea coast during August 2013. The remote sensing reflectance data were obtained from portable spectroradiometer. The chlorophyll concentration data were obtained from spectrophotometric method and the total suspended materials concentration data were obtained from filter-weight difference method. The remote sensing reflectance data were validated using Moon et al.(2012). The chlorophyll concentration data were validated using baseline correction and subtraction of 750 nm value, and the total suspended materials concentration data were validated using variation of humidity.

The interaction between the perfluorosulfonic acid (PFSA) ionomer and platinum group metal (PGM) catalyst in polymer electrolyte fuel cell (PEFC) inks is a critical issue for designing high-performance PEFC electrodes. During the ink fabrication, the complex interparticle interaction of the ink components determines the agglomerate morphology and size distribution. Among the ink components, the ionomer, which has amphiphilic in nature due to its hydrophobic backbone and the hydrophilic ionic group, mostly effective parameter for interparticle interaction. Therefore, understanding the interaction and molecular structure of ionomer is required for a high-performance catalyst layer. The backbone length of the ionomer which controls the spacing between ionic pendant groups is the main parameter of the ionomer character. In this study, the three different ionic spacing ionomers, made in the Solvay industry: Aquivion D72-25BS, Aquivion D83-24BS, and D98-25BS, were used for investigating the adsorption behavior of the catalyst ink and PEFC catalyst layer morphology. During the fabrication of PEFC ink and catalyst layer, all samples have same sulfonic acid molality to avoid the ionic clustering effect in the side chain. Ex-situ measurements were carried out to quantify the interparticle interaction and agglomerate size distribution in the PEFC ink. The dynamic lights scattering (DLS) carry out to determine the aggregation size distribution. The rheological behavior was conducted to understand the interparticle interactions and the agglomeration behavior of the inks by steady-shear and dynamic-oscillatory-shear measurements. It is noted that increasing the ionomer backbone length, which favors interaction via hydrophobic interaction on a carbon support, suppresses the agglomeration of ink components and decreases ink viscosity. The in situ electrochemical tests were carried out to figure out the relationship between ink formulation and catalyst layer morphology. It was found that the long ionomer backbone length helps to suppress the O2 transport resistance and ORR kinetic loss by uniform distribution from ionomer backbone-carbon supports interaction.

To address the global climate change issues, polymer electrolyte fuel cells (PEFCs) are receiving attention as electrochemical energy conversion devices employing green hydrogen. Notably, the PEFC fuel cell is because the electrochemical reaction occurs on the Catalyst Layer (CL), the CL is the core of the Membrane Electrode Assembly (MEA). The conventional CL is usually prepared from catalyst ink comprising the various catalyst, ionomer, and solvents and deposited via blade coating to the decal substrate. Therefore, it is necessary to confirm the optimal decal transfer conditions based on analyzing the characteristics of the catalyst ink and the decal substrate. In the study, the characterize the internal microstructure of the catalyst ink was confirmed through rheology, and the coating velocity was tunable based on catalyst property. In addition, the characteristics of the various decal substrate were confirmed through Atomic Force Microscopy (AFM) and Contact Angle, and differences including variations in loading amount were confirmed despite the same slurry. The structure of CL on the decal sheet was confirmed through a scanning electron microscope (SEM) surface image and cross-section image, and the distribution of Pt and ionomer was confirmed through Energy Dispersive X-Ray Spectrometer (EDS) mapping. The definition of electrochemical performance between catalyst ink characterizes and decal substrates property was investigated through polarization curves and electrochemical impedance spectroscopy (EIS). Also, cyclic voltammetry (CV) techniques are used to characterize electrochemical surface areas (ECSA) areas of the CL. As a result, the property between the catalyst ink and the decal substrate, based on the difference that occurs in the rheology characterized in the catalyst ink, leads to a variation in the CL structure. Therefore, it is very important to determine the decal process conditions by understanding the characteristics of various catalyst ink on rheology and decal sheet.

Short-term biological responses to sea surface wind field over mesoscale eddies were investigated using hourly ocean color chlorophyll-a (chl-a) concentration data from the Geostationary Ocean Color Imager (GOCI), scatterometer wind data, and satellite sea surface temperature (SST) data. Four warm eddies were identified from SST fronts, by subjectively fitting ellipses to selected points, and anticyclonically rotating current vectors were estimated from sequential chl-a images. Scatterometer data confirmed wind speed strengthening by approximately 30% over anticyclonic eddies, regardless of wind direction, caused by stability changes in the marine atmospheric boundary layer. The modified wind speed field produced a characteristic pattern of wind stress curl and Ekman pumping (EKP) over the eddies, showing positive and negative values on the left and right sides of the upwind direction, respectively. The EKP field was divided into three components: eddy current-induced, relative vorticity gradient-induced, and crosswind SST-induced terms. Short-term changes in the chl-a concentration showed a positive relation with EKP variations over most eddies. SST-induced EKP played a significant role in the eddies for 76% of the total variations, which is much higher than that in other oceans. This study emphasizes the significant effect of SST distribution and the biological responses to changes in an EKP field in relation to air–sea interactions and feedback processes in the East Sea (Sea of Japan).

Radiation toxicity grades must be reviewed based on existing knowledge-based clinical evidence or be assessed by referencing the clinical research literature to minimize radiation toxicity associated with radiotherapy. The aim of this study was to develop a radiation toxicity prediction system using metarule-guided mining of the clinical research literature to predict radiation pneumonitis and esophagitis in lung cancer patients. A semantic pattern database was built using 100 clinical research articles. Semantic patterns of prognostic factors and toxicity grades were extracted by metarule-guided mining. Feature analysis and correlation investigation of prognostic factors and toxicity grades were performed by using dendrogram and heatmap. A web-based user interface for the prediction system was designed. Patient prognostic factors were used in this prediction system to predict toxicity grade results. Radiation toxicity grades for patients with radiation pneumonitis and esophagitis were calculated through our prediction system. Age and chemotherapy were prognostic factors as were toxicity grades 1–3 and 5 based on the metarule-guided mining system. The odds ratios had similar trends to those in the existing meta-analysis literature. The radiation toxicity prediction system that we developed can potentially be used as a clinical decision support system for patient-specific radiation treatment after weighting of prognostic factors, performing a correlation analysis, and performing a validity evaluation.

Reviewing six years of Geostationary Ocean Color Imager (GOCI) suspended particulate matter (SPM) concentration images from 2011 to 2016 revealed unexpected and some enormously high or low values. ...

Red tide, which occurs off the southern coast of the Korean Peninsula, is a maritime phenomenon that usually occurs between June and September every year, mostly by Cochlodinium polykrikoides single species. There are very few studies using the analytical methods of the inherent and apparent optical properties for these red tide. Ahn et al.(2009) analyzed the inherent optical properties of 26 species of red tide organisms occurring off the southern coast of the Korean Peninsula. Kim et al.(2016) distinguished the optical characteristics for Cochlodinium polykrikoides using field data and Hydrolight simulator. Using these analytical methods, we will understand the ocean optical properties of red tide and use the remote sensing reflectance simulator in the future to produce the input data necessary for developing the red tide analysis technology based on machine learning. Therefore, in this study, as an initial analysis, we will compare the in-situ data of red tide and non-red tide waters off the southern coast of the Korean Peninsula in September 2014 and August 2017 to identify differences in the spectral form and compare the ability of the remote sensing reflectance spectrum with the field data using a remote sensing reflectance simulator.

Sargassum horneri is one of the major components of the floating sargassum that is distributed widely along the coast, including Korea, China and Japan. Sargassum horneri has an air pocket called an ‘air sec’ on its body which leads to a floating life, and drifts by ocean currents and winds. Due to these characteristics, blooms of Sargassum horneri have occurred April-June in the East China Sea. If these blooms flow into Jeju Island in South Korea, the blooms can cause enormous damage to fishing activities and the marine tourism industry. In order to minimize the damage caused by these blooms, we have been studied using remote sensing and field measurements. This study investigates environmental factors associated to the inflow of Sargassum horneri into Korean Peninsula. We used floating algae detection algorithm developed by a Geostationary Ocean Color Imager (GOCI). Since GOCI provides data of the seas surrounding the Korea eight times a day (00 to 07 UTC), it is suitable to monitor the blooms. The algorithm was made using the Red-edge effect which has a sharply rising reflectivity at around 700 nm but a low reflectivity in the red area (660-680 nm). And it was considered that the reflectivity of background seawater which varies from place to place is eliminated. Based on the results of the algorithm for detecting floating algae, Sargassum horneri’s inflow into the Korean Peninsula was analyzed January to June for six years (2014 to 2019). Also, the environment factors affecting to the inflow path were investigated each months and years.

As the succeeder of the Geostationay Ocean Color Imager (GOCI), the world first geostationary ocean monitoring satellite, the second GOCI (GOCI-II) will be launched in 2020. GOCI-II has 12 narrow bands of 380~865nm center wavelength for earth observation and an broadband band for star observation. The main goals of this GOCI series are to monitor ocena short-term/long-term phenomena like red-tide blooming, floating algae movements, tidal movements, low sea surface salinity variation, sea surface currents, primary productivity, etc. GOCI-II is able to obtain 10 images for the area around Korean peninsula and an image for the full-disk area in everyday during its 10 years lifetime. To handle this huge GOCI-II data, we have to develop the dedicated GOCI-II Ground Segment (G2GS) system with data acquisition antenna and GOCI-II operating infrastructure. G2GS have good performance like the data distribution output delay within 60 minutes, the 99% system operability with redundancy, etc. G2GS also generates 26 level-2 data products and provides all data with dedicated software program like GOCI-II plug-in of SNAP framework.

Sea surface salinity (SSS) is an important tracer for monitoring the Changjiang Diluted Water (CDW) extension into Korean coastal regions; however, observing the SSS distribution in near real time is a difficult task. In this study, SSS detection algorithm was developed based on the ocean color measurements by Geostationary Ocean Color Imager (GOCI) in high spatial and temporal resolution using multilayer perceptron neural network (MPNN). Among the various combinations of input parameters, combinations with three to six bands of GOCI remote sensing reflectance (Rrs), sea surface temperature (SST), longitude, and latitude were most appropriate for estimating the SSS. According to model validations with the Soil Moisture Active Passive (SMAP) and Ieodo Ocean Research Station (I-ORS) SSS measurements, the coefficient of determination (R2) were 0.81 and 0.92 and the root mean square errors (RMSEs) were 1.30 psu and 0.30 psu, respectively. In addition, a sensitivity analysis revealed the importance of SST and the red-wavelength spectral signal for estimating the SSS. Finally, hourly estimated SSS images were used to illustrate the hourly CDW distribution. With the model developed in this study, the near real-time SSS distribution in the East China Sea (ECS) can be monitored using GOCI and SST data.

Geostationary Ocean Color Imager (GOCI) observations are applied to marine fog (MF) detection in combination with Himawari-8 data based on the decision tree (DT) approach. Training and validation of the DT algorithm were conducted using match-ups between satellite observations and in situ visibility data for three Korean islands. Training using different sets of two satellite variables for fog and nonfog in 2016 finally results in an optimal algorithm that primarily uses the GOCI 412-nm Rayleigh-corrected reflectance (Rrc) and its spatial variability index. The algorithm suitably reflects the optical properties of fog by adopting lower Rrc and spatial variability levels, which results in a clear distinction from clouds. Then, cloud removal and fog edge detection in combination with Himawari-8 data enhance the performance of the algorithm, increasing the hit rate (HR) of 0.66 to 1.00 and slightly decreasing the false alarm rate (FAR) of 0.33 to 0.31 for the cloudless samples among the 2017 validation cases. Further evaluation of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data reveals the reliability of the GOCI MF algorithm under optically complex atmospheric conditions for classifying marine fog. Currently, the high-resolution (500 m) GOCI MF product is provided to decision-makers in governments and the public sector, which is beneficial to marine traffic management.

Objective Boost radiation using brachytherapy (BT) is a standard treatment for local disease control in concomitant chemoradiation therapy (CCRT) for advanced cervical cancer. However, it is associated with gastrointestinal and genitourinary complications. Hence, this study investigates the feasibility of helical tomotherapy (HT) as an alternative to BT. Methods Medical records of patients who underwent CCRT between 2000 and 2017 at a single institution were retrospectively reviewed. Patients with stage IIB-IVA cancers were selected based on the 2009 criteria of The International Federation of Gynaecology and Obstetrics. External beam radiation combined with chemotherapy was followed by either BT or HT. The propensity score matching of both groups was calculated using logistic regression analysis. Disease outcomes and treatment-related adverse events were compared between the 2 groups. Results The matched population included 70 BT patients and 35 HT patients. The 5-year progression-free survival rates for BT and HT were 72.6% and 72.5%, respectively (p=0.721). There was no difference in the overall survival rate between the two groups (p=0.203). The presence of acute and chronic gastrointestinal complications was also similar between the groups (p=0.460 and p=0.563, respectively). The chronic genitourinary toxicities were also comparable (p=0.105). Conclusions HT boost treatment showed comparable disease outcomes with those observed with conventional BT in patients with advanced cervical cancer. HT could be a complementary boost protocol as a single modality or hybrid with BT in selected patients. Further studies with longer follow-up periods are warranted to confirm long-term outcomes.

Although radiotherapy can be administered with a relatively low therapeutic burden, many elderly patients do not complete radiotherapy. In order to predict intolerance during radiotherapy, this study retrospectively analyzed the frequency of and risk factors for radiotherapy interruption among geriatric patients. From September 2009 to December 2016, 353 patients aged ≥70 years received definitive radiotherapy with a conventionally fractionated schedule. “Total interruption” included completion of ≤90% of a planned radiotherapy, temporary discontinuation, and treatment-related mortality within 2 months. “Early-phase incompletion” and “mid-phase incompletion” represented completion of ≤50 and ≤80% of a planned radiotherapy, respectively. The median age of patients was 74 years. Early- and mid-phase incompletions and total interruption occurred in 4.2, 9.3, and 19.3% of patients, respectively. Total interruption occurred frequently in cancers involving the thorax (27.4%), head and neck (23.1%), abdomen (20.0%), pelvis (17.4%), and breast/extremity (8.1%). The Eastern Cooperative Oncology Group (ECOG) performance score (P = 0.004 and 0.002), serum albumin level (P = 0.016 and 0.002), and the expected 5‑year survival (P = 0.033 and 0.034) were significant factors for mid-phase incompletion and total interruption. Age ≥ 75 years (P = 0.008), concurrent chemotherapy (P = 0.017), and the extent of radiation field (P = 0.027) were factors associated with total interruption. Overall, 19.3% of the elderly patients showed treatment intolerance during conventional radiotherapy. Serum albumin level and ECOG performance score should be considered as surrogate markers for radiotherapy interruption prior to the decision regarding definite conventional radiotherapy.

Min, S.-H.; Park, M.-O.; Kim, S.-W.; Han, I-S.; Kim, W., and Park, Y-J., 2018. Using GOCI Data for Detection of Coastal Upwelling at East/Japan Sea. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1471–1475. Coconut Creek (Florida), ISSN 0749-0208.Recently emergence of cold water from coastal upwelling has caused frequent damages to the coastal aquaculture along the southeast coast of Korea. So, the necessity of early forecasting of cold water using satellite data has emerged. Coastal upwelling generally detected by meteorological satellites of sea surface temperature (SST) data. However, this study tries to seek a possibility of use of ocean color satellite data to find the cold water, by Chromophoric dissolved organic matter (CDOM) concentration of upwelled cold water. The concentration of CDOM will change if coastal upwelling occurs. That could be observed through the ocean color sensor. 2017 summer, SST and CDOM concentrations in the in-situ and satellite data were matched up, when coastal upwelling occurred. As a result, SST and CDOM were correlated positively in coastal area, meanwhile negative correlation was found in off shore. When upwelling occurs, it is considered that high concentration of CDOM on the coast and subsurface flow to the off shore along with cold middle water, and then relatively low CDOM is supplied.

Accurate and timely quantification of widespread harmful algal bloom (HAB) distribution is crucial to respond to the natural disaster, minimize the damage, and assess the environmental impact of the event. Although various remote sensing-based quantification approaches have been proposed for HAB since the advent of the ocean color satellite sensor, there have been no algorithms that were validated with in-situ quantitative measurements for the red tide occurring in the Korean seas. Furthermore, since the geostationary ocean color imager (GOCI) became available in June 2010, an algorithm that exploits its unprecedented observation frequency (every hour during the daytime) has been highly demanded to better track the changes in spatial distribution of red tide. This study developed a novel red tide quantification algorithm for GOCI that can estimate hourly chlorophyll-a ( Chl a) concentration of Cochlodinium (Margalefidinium) polykrikoides , one of the major red tide species around Korean seas. The developed algorithm has been validated using in-situ Chl a measurements collected from a cruise campaign conducted in August 2013, when a massive C. polykrikoides bloom devastated Korean coasts. The proposed algorithm produced a high correlation (R 2 = 0.92) with in-situ Chl a measurements with robust performance also for high Chl a concentration (300 mg/m 3 ) in East Sea areas that typically have a relatively low total suspended particle concentration ( 3 ).

Surface currents in Korean coastal regions were obtained using the maximum cross-correlation method applied to hourly suspended particulate matter images from the Geostationary Ocean Color Imager. ...

The aim of this study was to derive a new plan-scoring index using normal tissue complication probabilities to verify different plans in the selection of personalized treatment. Plans for 12 patients treated with tomotherapy were used to compare scoring for ranking. Dosimetric and biological indexes were analyzed for the plans for a clearly distinguishable group (n = 7) and a similar group (n = 12), using treatment plan verification software that we developed. The quality factor (QF) of our support software for treatment decisions was consistent with the final treatment plan for the clearly distinguishable group (average QF = 1.202, 100% match rate, n = 7) and the similar group (average QF = 1.058, 33% match rate, n = 12). Therefore, we propose a normal tissue complication probability (NTCP) based on the plan scoring index for verification of different plans for personalized treatment-plan selection. Scoring using the new QF showed a 100% match rate (average NTCP QF = 1.0420). The NTCP-based new QF scoring method was adequate for obtaining biological verification quality and organ risk saving using the treatment-planning decision-support software we developed for prostate cancer.

We present a direct and proxy-based approach to qualitatively and semi-quantitatively observe floating plastic litter in the Great Pacific Garbage Patch (GPGP) based on a survey in 2018 using very high geo-spatial resolution 8-waveband WorldView-3 imagery. A proxy for the plastics was defined as a waveband difference for anomalies in the top-of-the-atmosphere spectra. The anomalies were computed by subtracting spatially varying reflectance of the surrounding ocean water as background from the top-of-the-atmosphere reflectance. Spectral shapes and magnitude were also evaluated using a reference target of known plastics, The Ocean Cleanup System 001 Wilson. Presence of ‘suspected plastics’ was confirmed by the similarity in derived anomalies and spectral shapes with respect to the known plastics in the image as well as direct observations in the true color composites. The proposed proxy-based approach is a step towards future mapping techniques of suspected floating plastics with potential operational monitoring applications from the Sentinel-2 that recently started regular imaging over the GPGP that will be supported or validated by numerical solutions and net trawling survey.

Continuous wound infusion usually provides postoperative analgesia as a multimodal analgesia with systemic opioid use. When continuous wound infusion of local anesthetics (LA) supports successful postoperative analgesia without systemic opioid use, the side effects of opioid can be reduced. Nevertheless, continuous wound infusion after mastectomy with immediate autologous breast reconstruction leads to concerns about wound healing. This study evaluated analgesic effects and wound healing conditions of continuous wound infusion of LA compared with opioid-based, intravenous patient-controlled analgesia (IV PCA) in mastectomy with immediate autologous breast reconstruction. This retrospective observational study included females, aged between 33 and 67 years, who underwent mastectomy with immediate autologous breast reconstruction. Sixty-five patients were enrolled. The eligible patients were placed into 2 groups for managing postoperative pain, one used continuous wound infusion with 0.5% ropivacaine (ON-Q, n = 32) and the other used a fentanyl-based IV PCA (IV PCA, n = 33). Using the electronic medical record system, the postoperative recovery profiles were examined over 5 days using a visual analogue scale (VAS), incidence of postoperative nausea and vomiting (PONV), incidence of sleep disturbance, frequency of rescue analgesic use, analgesia-related adverse events, length of hospital stay, and degree of patient satisfaction. The condition of the surgical wound was observed for 1 year after surgery. The primary endpoint was the intensity of pain at 6 hours after surgery. The VAS was comparable between the groups (P > .05). Although recovery profiles and the degree of patient satisfaction were similar between the groups, the incidence of PONV was significantly lower in the ON-Q group than in the IV PCA group on the day of surgery and postoperative day 1. No patients had severe wound complications. The satisfaction score of analgesia in the ON-Q group was comparable with that of the patients in the IV PCA group. This study demonstrates that single use of continuous wound infusion showed comparable analgesia with fentanyl-based IV PCA in patients who underwent mastectomy with immediate autologous breast reconstruction. Furthermore, the continuous infusion of LA directly on the surgical site did not significantly affect wound healing.

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

PurposeThe aim of this study is to develop predictive models to predict organ at risk (OAR) complication level, classification of OAR dose-volume and combination of this function with our in-house developed treatment decision support system.Materials and methodsWe analysed the support vector machine and decision tree algorithm for predicting OAR complication level and toxicity in order to integrate this function into our in-house radiation treatment planning decision support system. A total of 12 TomoTherapyTM treatment plans for prostate cancer were established, and a hundred modelled plans were generated to analyse the toxicity prediction for bladder and rectum.ResultsThe toxicity prediction algorithm analysis showed 91·0% accuracy in the training process. A scatter plot for bladder and rectum was obtained by 100 modelled plans and classification result derived. OAR complication level was analysed and risk factor for 25% bladder and 50% rectum was detected by decision tree. Therefore, it was shown that complication prediction of patients using big data-based clinical information is possible.ConclusionWe verified the accuracy of the tested algorithm using prostate cancer cases. Side effects can be minimised by applying this predictive modelling algorithm with the planning decision support system for patient-specific radiotherapy planning.

We used a spectrophotometer to compare the dosimetric properties of two non-scattering (radiochromic) gel dosimeters: a non-scattering gel dosimeter developed in-house and a PRESAGE™ gel dosimeter. We evaluated the dosimetric characteristics, including spectral absorption, dose linearity, reproducibility, and dose rate dependency of the two gel dosimeters. The non-scattering gel and the PRESAGE™ gel dosimeters showed peak sensitivity at wavelengths of 600 nm and 630 nm, respectively. Over a range of doses the best dose linearities of the non-scattering and the PRESAGE™ gel dosimeters resulted in R2 values of 0.99 at wavelengths of 600 nm and 630 nm, respectively. The reproducibility and dose-rate dependence of each of the two gel dosimeters were within the range of ±3 %. Our results revealed that the peak sensitivities of the two radiochromic gel dosimeters were significantly different; the in-house non-scattering gel dosimeter demonstrated peak sensitivity at a wavelength of 600 nm while the PRESAGE™ gel dosimeter had peak sensitivity at a wavelength of 630 nm. We confirmed that for 3D gel dosimetry, the in-house non-scattering gel dosimeter had a more stable dose response compared with a commercial non-scattering gel dosimeter.

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed to retrieve hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD had accuracy comparable to ground-based and other satellite-based observations but still had errors because of uncertainties in surface reflectance and simple cloud masking. In addition, near-real-time (NRT) processing was not possible because a monthly database for each year encompassing the day of retrieval was required for the determination of surface reflectance. This study describes the improved GOCI YAER algorithm version 2 (V2) for NRT processing with improved accuracy based on updates to the cloud-masking and surface-reflectance calculations using a multi-year Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2 τG has a lower median bias and higher ratio within the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol Robotic Network (AERONET) AOD τA from 2011 to 2016. A validation using the Sun-Sky Radiometer Observation Network (SONET) over China shows similar results. The bias of error (τG−τA) is within −0.1 and 0.1, and it is a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and homogeneity of retrieved AOD, and observation time, month, and year. In addition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is well correlated with the actual error over East Asia, and the GOCI V2 AOD over South Korea has a higher ratio within PEE than that over China and Japan.

This paper reanalyzes the aerosol reflectance correction schemes employed by major ocean color missions. The utilization of two near-infrared (NIR) bands to estimate aerosol reflectance in visible wavelengths has been widely adopted, for example by SeaWiFS/MODIS/VIIRS (GW1994), OCTS/GLI/SGLI (F1998), MERIS/OLCI (AM1999), and GOCI/GOCI-II (A2016). The F1998, AM1999, and A2016 schemes were developed based on GW1994; however, they are implemented differently in terms of aerosol model selection and weighting factor computation. The F1998 scheme determines the contribution of the most appropriate aerosol models in the aerosol optical thickness domain, whereas the GW1994 scheme focuses on single-scattering reflectance. The AM1999 and A2016 schemes both directly resolve the multiple scattering domain contribution. However, A2016 also considers the spectrally dependent weighting factor, whereas AM1999 calculates the spectrally invariant weighting factor. Additionally, ocean color measurements on a geostationary platform, such as GOCI, require more accurate aerosol correction schemes because the measurements are made over a large range of solar zenith angles which causes diurnal instabilities in the atmospheric correction. Herein, the four correction schemes were tested with simulated top-of-atmosphere radiances generated by radiative transfer simulations for three aerosol models. For comparison, look-up tables and test data were generated using the same radiative transfer simulation code. All schemes showed acceptable accuracy, with less than 10% median error in water reflectance retrieval at 443 nm. Notably, the accuracy of the A2016 scheme was similar among different aerosol models, whereas the other schemes tended to provide better accuracy with coarse aerosol models than the fine aerosol models.

Exploration towards the lightweight bipolar plate, composed of cheap and abundant materials, is of great importance to accelerate the commercialization of polymer electrolyte fuel cells (PEFCs). Herein, new bipolar plate is fabricated by carbon fiber plate reinforced with polymeric resin, to alternate the conventional graphite composite (GBP) and metallic ones (MBP). Unlike the previous studies, the woven-type carbon fiber bipolar plates (CFBPs), with an initial thickness of 300 μm, have physically been grinded to 270, 220 and 170 μm, then followed by the deposition of conductive carbon layer, in order to reduce both bulk and interfacial contact resistances. Remarkably, the resultant CFBP even with metallic mesh flow fields exhibited less than 14.6% and 23.6% weight of the GBP and MBP, respectively, which doubles the gravimetric cell power density. Three key properties, i.e., electrical conductivity, mechanical strength and gas permeability, fully satisfied the US DOE's 2020 targets. Furthermore, the PEFC employing the proposed CFBP with metallic mesh flow field showed notable improvements in the ohmic and mass-transport performance, confirmed by both cell polarization and electrochemical impedance spectroscopy. Given the excellent gravimetric power density, this work may draw the first step toward a newly-structured PEFC for an automotive, marinomotive and, particularly, aeromotive powertrain applications.

The surface current field of a mesoscale eddy in the East Sea (Sea of Japan) was derived from consecutive Geostationary Ocean Color Imager chlorophyll-a (chl-a) concentration images using the normalized maximum cross-correlation method. The estimated current field of the eddy exhibited anticyclonic structure demonstrated by the objective dynamic thresholds of correlation coefficients. The eddy periphery was defined by fitting an ellipse to subjectively selected points from the frontal map of chl-a concentration data. Radial distribution and hourly variation of the current speed around the eddy were presented. In terms of the magnitude and direction, the estimated current field was in good agreement with altimeter-based current field and current vectors from surface drifters. Diurnal variations in the current speeds of the mesoscale eddies showed a quadratic relation to the wind speed.

In this study, the geometric and dosimetric accuracy of an in-house-developed couch-based tracking system (CBTS) was investigated using both film and in-house-developed polymer gel dosimeters. We evaluated the 1D and the 2D motion accuracies of our couch system by using Gafchromic EBT film. For the 1D test, the couch system was moved 5, 10, and 20 mm in the X, Y, and Z directions, respectively. Meanwhile, for the 2D test, it was moved along the XY, YZ, and ZX directions. We compared the profiles, full widths at half maximum (FWHMs), and penumbras between the static and the tracking fields. For the 3D test, we quantitatively compared the dose distribution between the static and the tracking fields by using the polymer gel dosimeter when it was simultaneously moved in the XYZ directions. We confirmed that the film was moved according to motion amplitudes of 5, 10, and 20 mm in the X, Y, and Z directions, respectively, in the 1D and 2D motion tests. The value of the FWHM of the static field and the three tracking fields were 51.88, 53.28, 57.67, and 64.43 mm, respectively. Two types of penumbras became wider with increasing amplitudes compared to the static field. For the 3D test, the dose distribution of the XYZ tracking field was qualitatively larger than that of the static field. We conclude that this CBTS has the potential for pre-clinical applications in adaptive radiation therapy.

We attempted for the first time to extract fronts from ocean colour data acquired at a geostationary orbit derived from the Geostationary Ocean Color Imager (GOCI), the world’s first geostationary ocean colour satellite sensor. We extracted fronts from hourly observed GOCI images and then attempted to investigate subtle changes in ocean condition. Suspended sediment (SS)-derived fronts were used to analyse tidal movements in a coastal region having semi-diurnal tides and highly turbid water. We were able to trace fast movements of tidal flows and discovered that the SS-derived ocean fronts are quite relevant to the submarine topography along shallow coasts. In relatively clear waters using chlorophyll concentration (chl)-derived fronts, we were able to discover dynamic variations on sea areas where two independent water masses mixed. We also found that GOCI-derived fronts can provide more detailed information than can SST-derived fronts. We expect that such results can be utilized to search for pr...

Recently, harmful algae (e.g., red tide) has damaged human and marine ecosystems. To address this, a response system should be developed to quickly cope with these ocean disasters. However, it is difficult to simultaneously monitor the vast ocean areas. Here, a marine disaster detection system can be developed through a convergence between the satellite-based ocean color remote sensing and the marine sensor network. The system architecture is divided into two steps: first, the system detects ocean anomalies in realtime using the satellite-based techniques, and secondly, the detected disaster information is transferred to the ships via the marine sensor networks. In this paper, we only focused on the first step and the second step is reserved for future work. Although the polar orbit satellite-based ocean color sensor platforms (e.g., MODIS, MERIS, and SeaWifs) can be used to simultaneously monitor the vast ocean areas, they are unsuitable for capturing subtle changes on a geographically equivalent area. On the other hand, the Geostationary Ocean Color Imager (GOCI), the world’s first ocean color remote sensor platform operated on a geostationary orbit, receives ocean color data around the Northeast Asia region every hour, eight times a day. Therefore, GOCI can be more effectively utilized to observe subtle changes and to detect anomalies in ocean environments in real-time. In this paper, we attempted to build a system to monitor marine disasters by detecting ocean anomalies using the ocean color data derived from GOCI. This system directly compares the test spectrum vectors (i.e. anomaly candidates) to a predefined reference spectrum vector (i.e. a target anomaly) through the cosine similarity. The experimental result showed that the proposed system could efficiently detect the disasters (e.g., the red tide) on the ocean environments.

The data presented herein support “Generation of an induced pluripotent stem cell line KUMCi001-A from CD34+ bone marrow cells of a patient with acute lymphoblastic leukemia using human placenta-derived cell conditioned medium.” The supplementary data were as follows. (1) Comparison of reprogramming efficiency of human placenta-derived cell conditioned medium with defined medium (mTeSR™1) and the generation of induced pluripotent stem cells (iPSCs) from a patient with acute lymphoblastic leukemia (ALL) with significantly higher reprogramming efficiency than that of the defined medium (P ≤ 0.05). (2) Evaluation of differentiation capability of the generated ALL_iPSCs into hematopoietic stem cells (HSCs) and comparison with normal iPSCs using the colony-forming unit (CFU) assay. ALL_iPSCs manifested all lineages for hematopoiesis in their colonies similar to normal iPSCs. (3) ALL_iPSCs showed a considerably higher number of burst-forming unit-erythroid colonies indicating the presence of more erythroid progenitors than normal iPSCs; this tendency was confirmed in the CFU assay of ALL_CD34+ cells. This has been previously reported as a feature of ALL. Thus, the hematopoietic characteristics of the donor patient with ALL appear to be maintained in our ALL_hiPSC line although the karyotype was normalized during reprogramming.

Many patients with acute lymphoblastic leukemia (ALL) show relapse post-chemotherapy. Therefore, it is important to develop a human induced pluripotent stem cell (hiPSC) line from ALL cells to verify the pathophysiology. However, the low efficiency of the established reprogramming protocol has hampered the development of ALL hiPSC lines. Our recently reported novel reprogramming method, using human placenta-derived cell conditioned medium (hPCCM), offers a relatively higher efficiency in humanized conditions. Here, we generated an hiPSC line from ALL-derived CD34+ bone marrow cells, using hPCCM for reprogramming. This hiPSC line might be a useful model for studies on ALL.