症例の予後改善のための,電子ビームCT,4列～320列CTを用いた循環器領域の新しい臨床診断学の開発への貢献

I went to the Stanford University Department of Radiology\u27s three-dimensional (3D) imaging laboratory from 1996 to 1999 to study a novel 3D image processing technique using electron beam computed tomography (CT). When I returned to Japan, I found that multi-slice CT had been available in daily practice since 1998. We have published a total of 152 peer-reviewed papers on diagnostic images in the field of cardiovascular disease. In 2003, when 16-slice CT was available for use in general hospitals, we successfully developed a prototype 256-slice cone-beam CT at the National Institute of Radiological Sciences. We produced several papers discussing the utilities of this prototype CT in both animal and phantom experiments, the concepts and ideas that were currently used for cardiac perfusion and myocardium characteristic study. In 2010, our paper was used as a reference in the American College of Cardiology Foundation Expert Consensus Guideline. The our current topics presented include coronary artery stenosis, coronary arterial plaques, the characteristics of the myocardium, the anatomy of structural and congenital heart disease, and the cardiac function, all using 16-320 slice CT with reduced radiation exposure in CT acquisition. Furthermore, we are now performing novel clinical CT studies combined magnetic resonance imaging (MRI), positron emission tomography, and echocardiography. Using previous image data, we analyzed an epidemiology study using CT findings to predict the occurrence of major cardiovascular adverse events over long-term follow-up periods of more than 100 months (median), one of the longest follow-up periods documented in the literature. We also need to obtain accurate diagnoses for subjects with cardiac failure or fatal arrhythmia of unknown origin, allowing them to receive specific effective therapy for their possible cardiac amyloidosis, cardiac sarcoidosis, or Fabry\u27s disease. Of course, in all CT imaging techniques used for evaluation and monitoring of cardiovascular risk

NPP pattern (g C m² yr⁻¹) (upper panel) in the long term and its anomalies (%) (lower panel) with baseline over China modeled through climate change projections for SRES A2, B2, and A1B scenarios.

<p>NPP pattern (g C m² yr⁻¹) (upper panel) in the long term and its anomalies (%) (lower panel) with baseline over China modeled through climate change projections for SRES A2, B2, and A1B scenarios.</p

NPP spatial pattern (g C m² yr⁻¹) (upper panel) in the near term and its anomalies (%) (lower panel) with baseline over China modeled through climate change projections for SRES A2, B2, and A1B scenarios.

<p>NPP spatial pattern (g C m² yr⁻¹) (upper panel) in the near term and its anomalies (%) (lower panel) with baseline over China modeled through climate change projections for SRES A2, B2, and A1B scenarios.</p

PFTs Bioclimatic limiting factors used by LPJ-CN.

<p>Note: The parameter values in round brackets given by Sitch et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060849#pone.0060849-Sitch1" target="_blank">[19]</a> are replaced by italic values in this study. Shrub and cold grass are newly added PFTs in LPJ. <i>T_c</i> min the minimum coldest monthly mean temperature for survival; <i>T_c</i> max the maximum coldest monthly mean temperature; GDD min the minimum growing degree days of over 5°C; <i>T_w</i> max the upper limit of temperature of the warmest month.</p

NPP pattern (g C m² yr⁻¹) (upper panel) in the midterm and its anomalies (%) (lower panel) with baseline over China modeled through climate change projections for SRES A2, B2, and A1B scenarios.

<p>NPP pattern (g C m² yr⁻¹) (upper panel) in the midterm and its anomalies (%) (lower panel) with baseline over China modeled through climate change projections for SRES A2, B2, and A1B scenarios.</p

<b>The fate of deep permafrost carbon in northern high latitudes in the 21st century: a process-based modeling analysis</b>

This dataset composes the results of a process-based model (the terrestrial ecosystem model, TEM) that simulated carbon exchange in the northern high latitudes and focused on the effects of permafrost degradation on ecosystem budget.To investigate the effects of key factors including permafrost degradation, evaluating atmosphere CO2 concentration, changing temperature and precipitation, as well as their interactions on carbon sequestration in the permafrost areas, factorial runs were conducted. For each factor (or each pair of factors), a referenced simulation was carried out, in which the interested factor (or factor pair) was kept at the 2015 value for the entire 2015–2100 period, and the other factors remained unchanged as their original future scenario. Apart from the referenced simulations, a transient simulation was also conducted, in which all the factors were kept as their original future scenario data. The effects of an individual factor (or factor pair) on the simulation results can then be approximated by subtracting the results of the corresponding referenced simulation from the transient simulation. All the transient and referenced simulations were conducted under SSP126 and SSP585 for the 21st century. Therefore, there were 20 simulations in total. The variable names in the dataset, ‘constALT’, ‘constCO2’, ‘constPrec’, and ‘constTair’, denote referenced simulations with constant active layer depth, constant atmosphere CO2 concentration, constant precipitation, and constant air temperature during 2015–2100, respectively. ‘Trans’ denotes the transient simulation. ‘constALTCO2’, ‘constALTPrec’, ‘constCO2Prec’, ‘constCO2Tair’, and ‘constPrecTair’ denote the interactions between factors. ‘Delta’ before variable names means the differences between the transient and referenced simulations.Variable names of ‘ltrc’, ‘npp’, ‘rh’, ‘rh-pf’, ‘soilorgc’, ‘soc-pf’, ‘vegc’, ‘nmin’, ‘son’, ‘vnup’, ‘EcoC’, and ‘SOC_net’ denote litter carbon, net primary production, heterotrophic respiration, heterotrophic respiration from thawed permafrost, soil organic carbon, soil organic carbon from thawed permafrost, vegetation carbon, net nitrogen mineralization, soil organic nitrogen, vegetation nitrogen uptake, ecosystem carbon stock, and the total change of soil organic stock in active layer and permafrost, respectively.The ‘.mat’ files are carbon and nitrogen fluxes along soil depth. Each file is a 3-D matrix, with the first dimension (rows) being years from 2015 to 2100, the second dimension (columns) being soil depth, and the third dimension being simulations from 'trans' to 'constALT', 'constALTCO2', 'cosntALTPrec', 'constCO2', 'cosntCO2Prec', 'constCO2Tair', 'constPrec', 'constPrecTair', and 'constTair', respectively.</p

Mitigating the scintillation effect on GNSS signals using MP and ROTI

Ionospheric scintillation is one of the main error sources of Global Navigation Satellite System (GNSS) positioning. The presence of scintillation may result in cycle slips, measurement errors or even losses of lock on satellites, eventually leading to complete failure of positioning. Typically, scintillation parameters S4 and σϕ are used to characterize amplitude and phase scintillation, respectively. However, the scintillation parameters can only be generated from data with a frequency of at least 1 Hz. Rate of change of total electron content index (ROTI) is often used as a proxy for scintillation parameters, which can be obtained from 1/30 Hz data. However, previous research has shown the inefficiency of ROTI to represent scintillation. Therefore, the multipath parameter (MP) has been proposed as another proxy for scintillation parameters, which can also be obtained from 1/30 Hz data. In this paper, both MP and ROTI (standard parameters) were used to mitigate scintillation effects on precise point positioning (PPP). To evaluate the effectiveness of MP and ROTI in mitigating scintillation effects, S4 and σϕ were also used for comparison and validation. Three strategies are proposed: (1) remove all observations from the satellite that is most affected by scintillation; (2) remove the scintillation-affected observations; (3) weight the measurement noise matrix in the Kalman Filter (KF) process. The results show that the observation removal and weighting strategies are considerably more effective than the satellite removal strategy. The results also show that the improvement of PPP outputs reaches 93.1% and the performance of standard parameters is comparable to that of scintillation parameters in the observation removal and weighting strategies

Spatial-temporal behaviors of large-scale ionospheric perturbations during severe geomagnetic storms on September 7–8 2017 using the GNSS, SWARM and TIE-GCM techniques

Geomagnetic storms on 7–8 September 2017 triggered severe ionospheric disturbances that had a serious effect on satellite navigation and radio communication. Multiple observations derived from Global Navigation Satellite System receivers, Earth's Magnetic Field and Environment Explorers (SWARM) and the Thermosphere-Ionosphere -Electrodynamics General Circulation Model's simulations are utilized to investigate the spatial-temporal ionospheric behaviors under storm conditions. The results indicate that the electron density in the Asia-Australia, Europe-Africa and America sectors suddenly changed with the Bz southward excursion, and the ionosphere over low-middle latitudes under the sunlit hemisphere is easily affected by the disturbed magnetic field. The SWARM observations verified the remarkable double-peak structure of plasma enhancements over the equator and middle latitudes. The physical mechanism of low-middle plasma disturbances can be explained by a combination effect of equatorial electrojets, vertical E × B drifts, meridional wind and thermospheric O/N2 change. Besides, the severe storms triggered strong Polar plasma disturbances on both dayside and nightside hemispheres, and the Polar disturbances had a latitudinal excursion associated with the offset of geomagnetic field. Remarkable plasma enhancements at the altitudes of 100–160 km were also observed in the auroral zone and middle latitudes (>47.5°N/S). The topside polar ionospheric plasma enhancements were dominated by the O+ ions. Furthermore, the TIE-GCM's simulations indicate that the enhanced vertical E × B drifts, cross polar cap potential and Joule heating play an important role in generating the topside plasma perturbations

GNSS carrier-phase multipath modeling and correction: a review and prospect of data processing methods

A multipath error is one of the main sources of GNSS positioning errors. It cannot be eliminated by forming double-difference and other methods, and it has become an issue in GNSS positioning error processing, because it is mainly related to the surrounding environment of the station. To address multipath errors, three main mitigation strategies are employed: site selection, hardware enhancements, and data processing. Among these, data processing methods have been a focal point of research due to their cost-effectiveness, impressive performance, and widespread applicability. This paper focuses on the review of data processing mitigation methods for GNSS carrier-phase multipath errors. The paper begins by elucidating the origins and mitigation strategies of multipath errors. Subsequently, it reviews the current research status pertaining to data processing methods using stochastic and functional models to counter multipath errors. The paper also provides an overview of filtering techniques for extracting multipath error models from coordinate sequences or observations. Additionally, it introduces the evolution and algorithmic workflow of sidereal filtering (SF) and multipath hemispherical mapping (MHM), from both coordinate and observation domain perspectives. Furthermore, the paper emphasizes the practical significance and research relevance of multipath error processing. It concludes by delineating future research directions in the realm of multipath error mitigation.</p

Analysis on the ionospheric scintillation monitoring performance of ROTI extracted from GNSS observations in high-latitude regions

Monitoring ionospheric scintillation on a global scale requires introducing a network of widely distributed geodetic receivers, which call for a special type of scintillation index due to the low sampling rate of such receivers. ROTI, as a scintillation index with great potential being applied in geodetic receivers globally, lacks extensive verification in the high-latitude region. Taking the phase scintillation index (σϕ) provided by ionospheric scintillation monitoring receivers as the reference, this paper analyses data collected at 8 high-latitude GNSS stations to validate the performance of ROTI statistically. The data is evaluated against 4 parameters: 1, the detected daily scintillation occurrence rate; 2, the ability to detect the daily occurrence pattern of ionospheric scintillation; 3, the correlation between the detected scintillation and the space weather parameters, including the 10.7 cm solar flux, Ap, the H component of longitudinally asymmetric and polar cap north indices; 4, the overall distribution of the scintillation magnitude. Results reveal that the scintillation occurrence rates, the occurrence patterns of ionospheric scintillations and the correlations provided by ROTI are generally consistent with those given by σϕ, particularly in the middle-high-latitude region. However, the analysis on the distribution of σϕ for different ranges of ROTI shows ROTI cannot achieve accurate scintillation monitoring at the epoch level in all selected stations. The main outcomes of this paper are of importance in guiding the reasonable application area of ROTI and developing a high-latitude ionospheric scintillation model based on geodetic receivers