Komazawa University

Murakami Y., Magome T., Matsumoto K., Sato T., Yoshioka Y., Oguchi M.

Purpose Although dose prediction for intensity modulated radiation therapy (IMRT) has been accomplished by a deep learning approach, delineation of some structures is needed for the prediction. We sought to develop a fully automated dose-generation framework for IMRT of prostate cancer by entering the patient CT datasets without the contour information into a generative adversarial network (GAN) and to compare its prediction performance to a conventional prediction model trained from patient contours. Methods We propose a synthetic approach to translate patient CT datasets into a dose distribution for IMRT. The framework requires only paired-images, i.e., patient CT images and corresponding RT-doses. The model was trained from 81 IMRT plans of prostate cancer patients, and then produced the dose distribution for 9 test cases. To compare its prediction performance to that of another trained model, we created a model trained from structure images. Dosimetric parameters for the planning target volume (PTV) and organs at risk (OARs) were calculated from the generated and original dose distributions, and mean differences of dosimetric parameters were compared between the CT-based model and the structure-based model. Results The mean differences of all dosimetric parameters except for D98% and D95% for PTV were within approximately 2% and 3% of the prescription dose for OARs in the CT-based model, while the differences in the structure-based model were within approximately 1% for PTV and approximately 2% for OARs, with a mean prediction time of 5 seconds per patient. Conclusions Accurate and rapid dose prediction was achieved by the learning of patient CT datasets by a GAN-based framework. The CT-based dose prediction could reduce the time required for both the iterative optimization process and the structure contouring, allowing physicians and dosimetrists to focus their expertise on more challenging cases.

Cui Y., Hada K., Kawashima T., Kino M., Lin W., Mizuno Y., Ro H., Honma M., Yi K., Yu J., Park J., Jiang W., Shen Z., Kravchenko E., Algaba J., et. al.

The nearby radio galaxy M87 offers a unique opportunity to explore the connections between the central supermassive black hole and relativistic jets. Previous studies of the inner region of M87 revealed a wide opening angle for the jet originating near the black hole1–4. The Event Horizon Telescope resolved the central radio source and found an asymmetric ring structure consistent with expectations from general relativity5. With a baseline of 17 years of observations, there was a shift in the jet’s transverse position, possibly arising from an 8- to 10-year quasi-periodicity3. However, the origin of this sideways shift remains unclear. Here we report an analysis of radio observations over 22 years that suggests a period of about 11 years for the variation in the position angle of the jet. We infer that we are seeing a spinning black hole that induces the Lense–Thirring precession of a misaligned accretion disk. Similar jet precession may commonly occur in other active galactic nuclei but has been challenging to detect owing to the small magnitude and long period of the variation. This study analyses radio observations of the jet in galaxy M87, from which the existence of a spinning black hole that induces Lense–Thirring precession of a misaligned accretion disk is inferred.

Knoll M., Götz M., Adriasola E., Al‐Atwi A.A., Arenas A., Atitsogbe K.A., Barrett S., Bhattacharjee A., Blanco N.D., Bogilović S., Bollmann G., Bosak J., Bulut C., Carter M., Černe M., et. al.

Suzuki S., Kanno S.

• Co-branding as a strategy for luxury brands to achieve masstige. • Luxury brands should ally with “mass cool” brands for masstige co-branding. • Brand coolness creates perceived fit between luxury and mass brands. • Self-brand connection moderates the brand coolness and perceived fit relationship. Masstige marketing could be attractive to luxury brands to reach a wider market, though success is difficult. This study proposes co-branding as an alternative strategy for luxury brands to achieve masstige. Luxury brands can ally with mass brands to leverage their strength in mass marketing. Because luxury and mass are conceptually opposing ideas, co-branding between the two can be difficult. However, this study identifies brand coolness as a key attribute to create perceived fit between luxury and mass brands. The results show that brand coolness of mass brand affects perceived fit, which impacts attitude toward the co-branded product and its purchase intention. Additionally, self-brand connection with the luxury brand moderates this effect, and product category involvement negatively impacts perceived fit. The results have implications for brand managers who wish to select partners for masstige co-branding. The article concludes by proposing methods to create congruence among opposing brand concepts.

Andica C., Kamagata K., Kirino E., Uchida W., Irie R., Murata S., Aoki S.

Evidences suggesting the association between behavioral anomalies in autism and white matter (WM) microstructural alterations are increasing. Diffusion tensor imaging (DTI) is widely used to infer tissue microstructure. However, due to its lack of specificity, the underlying pathology of reported differences in DTI measures in autism remains poorly understood. Herein, we applied neurite orientation dispersion and density imaging (NODDI) to quantify and define more specific causes of WM microstructural changes associated with autism in adults. NODDI (neurite density index [NDI], orientation dispersion index, and isotropic volume fraction [ISOVF]) and DTI (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity, and radial diffusivity [RD]) measures were compared between autism (N = 26; 19 males and 7 females; 32.93 ± 9.24 years old) and age- and sex-matched typically developing (TD; N = 25; 17 males and 8 females; 34.43 ± 9.02 years old) groups using tract-based spatial statistics and region-of-interest analyses. Linear discriminant analysis using leave-one-out cross-validation (LDA-LOOCV) was also performed to assess the discriminative power of diffusion measures in autism and TD. Significantly lower NDI and higher ISOVF, suggestive of decreased neurite density and increased extracellular free-water, respectively, were demonstrated in the autism group compared with the TD group, mainly in commissural and long-range association tracts, but with distinct predominant sides. Consistent with previous reports, the autism group showed lower FA and higher MD and RD when compared with TD group. Notably, LDA-LOOCV suggests that NDI and ISOVF have relatively higher accuracy (82%) and specificity (NDI, 84%; ISOVF, 88%) compared with that of FA, MD, and RD (accuracy, 67–73%; specificity, 68–80%). The absence of histopathological confirmation limit the interpretation of our findings. Our results suggest that NODDI measures might be useful as imaging biomarkers to diagnose autism in adults and assess its behavioral characteristics. Furthermore, NODDI allows interpretation of previous findings on changes in WM diffusion tensor metrics in individuals with autism.

Matsumoto J., Takiwaki T., Kotake K., Asahina Y., Takahashi H.R.

ABSTRACT We study the effects of the magnetic field on the dynamics of non-rotating stellar cores by performing 2D, magnetohydrodynamic (MHD) simulations. To this end, we have updated our neutrino-radiation-hydrodynamics supernova code to include MHD employing a divergence cleaning method with both careful treatments of finite volume and area reconstructions. By changing the initial strength of the magnetic field, the evolution of 15.0, 18.4, and $27.0\,\rm M_\odot$ pre-supernova progenitors is investigated. An intriguing finding in our study is that the neutrino-driven explosion occurs regardless of the strength of the initial magnetic field. For the 2D models presented in this work, the neutrino heating is the main driver for the explosion, whereas the magnetic field secondary contributes to the pre-explosion dynamics. Our results show that the strong magnetic field weakens the growth of the neutrino-driven turbulence in the small scale compared to the weak magnetic field. This results in the slower increase of the turbulent kinetic energy in the post-shock region, leading to the slightly delayed onset of the shock revival for models with the stronger initial magnetic field.

Sumida I., Magome T., Das I.J., Yamaguchi H., Kizaki H., Aboshi K., Yamaguchi H., Seo Y., Isohashi F., Ogawa K.

Purpose 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. Methods 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. Results The DSC values in the DC model were significantly higher than those in the D model (p  Conclusions The proposed U-net model with dose and CT image used as input predicted more accurate dose.

Matsumoto J., Asahina Y., Takiwaki T., Kotake K., Takahashi H.R.

ABSTRACT The impact of the magnetic field on post-bounce supernova dynamics of non-rotating stellar cores is studied by performing 3D magnetohydrodynamics simulations with spectral neutrino transport. The explodability of strongly and weakly magnetized models of 20 and 27 M⊙ pre-supernova progenitors are compared. We find that although the efficiency for the conversion of the neutrino heating into turbulent energy including magnetic fields in the gain region is not significantly different between the strong and weak field models, the amplified magnetic field due to the neutrino-driven convection on large hot bubbles just behind stalled shock results in a faster and more energetic explosion in the strongly magnetized models. In addition, by comparing the difference between the 2nd- and 5th-order spatial accuracy of the simulation in the strong field model for 27 M⊙ progenitor, we also find that the higher order accuracy in space is beneficial to the explosion because it enhances the growth of neutrino-driven convection in the gain region. Based on our results of core-collapse supernova simulations for the non-rotating model, a new possibility for the origin of the magnetic field of the protoneutron star (PNS) is proposed. The magnetic field is accumulated and amplified to magnetar level, that is, $\mathcal {O}(10^{14})$ G, in the convectively stable shell near the PNS surface.

Goldfinch S., Yamamoto K., Aoyagi S.

Trust in government and its antecedents and development remain leading policy and research concerns. Drawing on a broadly representative online survey of 3100 respondents in Japan, we examine measures of trust in three local government actors. We find political participation is not associated with trust in local government, contrary to our expectations. Civic participation is associated with trust in the mayor, but not councillors or administrators. Satisfaction with services provided by local government, and positive perceptions of policy process, are associated with trust, with interactions suggesting process is the stronger antecedent. To develop greater trust in local government, it is important that public sector actors exhibit respect for rights and follow procedure, laws, and regulations, as well as deliver positive outcomes. Points for practitioners Building trust in government remains a key concern for policy makers, as it is related to successful adoption of policies. Trust in local government in Japan is related to perceived performance and citizen satisfaction. Civic participation is also related to some forms of trust in government. However, possibly more important are citizen perceptions that policy processes respect rights, procedures, and laws. To increase trust in government, practitioners need to practice, and show that they practice, good processes in developing and delivering policy, and show that policy leads to better perceived outcomes.

Hojo M.

Too long work hours of Japanese school teachers, along with an increasing number of teachers taking leave due to mental illness, are well known and recognized as a serious social problem. In order to prevent the spread of COVID-19 by reducing the density in the classroom, the Japanese government has decided to reduce the upper-limit of class size in primary schools after 2021, which is expected to result in lowering the student-teacher ratio. The aim of this study was to examine the association between student-teacher ratio, teacher work hours and teacher stress. Data on student-teacher ratio, teacher work hours, and teacher stress were obtained from a large-scale international survey conducted by OECD. The number of teachers participated in the survey was 3308 (primary school) and 3555 (lower-secondary school). After excluding teachers with missing observations, the analytic sample consisted of 2761 (primary school) and 3006 (lower-secondary school) teachers. Multivariate regression analysis was performed. Regression results revealed that student-teacher ratio was positively correlated with total work hours and workload stress of teachers. In particular, teachers working in schools with high student-teacher ratio spent more time on time-consuming tasks such as marking/correcting student work and communication with parents or guardians. The coefficient estimates suggested that, on average, lowering the student-teacher ratio by five in lower-secondary school was associated with 2.8 hours shorter working hours per week (p<0.001). Our empirical results suggested that the class-size reduction policy starting in 2021 could reduce teacher stress and long work hours through the consequent decrease in student-teacher ratios.