Comparative study of the experimentally observed and GAN-generated 3D microstructures in dual-phase steels.

In a deep-learning-based algorithm, generative adversarial networks can generate images similar to an input. Using this algorithm, an artificial three-dimensional (3D) microstructure can be reproduced from two-dimensional images. Although the generated 3D microstructure has a similar appearance, its reproducibility should be examined for practical applications. This study used an automated serial sectioning technique to compare the 3D microstructures of two dual-phase steels generated from three orthogonal surface images with their corresponding observed 3D microstructures. The mechanical behaviors were examined using the finite element analysis method for the representative volume element, in which finite element models of microstructures were directly constructed from the 3D voxel data using a voxel coarsening approach. The macroscopic material responses of the generated microstructures captured the anisotropy caused by the microscopic morphology. However, these responses did not quantitatively align with those of the observed microstructures owing to inaccuracies in reproducing the volume fraction of the ferrite/martensite phase. Additionally, the generation algorithm struggled to replicate the microscopic morphology, particularly in cases with a low volume fraction of the martensite phase where the martensite connectivity was not discernible from the input images. The results demonstrate the limitations of the generation algorithm and the necessity for 3D observations.

This study provided the comparison between experimentally observed and computationally generated 3D microstructures of dual-phase steels in the macro- and microscopic material behaviors with finite element analysis method for periodic microstructure.

Spacer Length Modification Facilitates Discrimination between Normal and Neoplastic Cells and Provides Clinically Relevant CD37 CAR T Cells.

Despite the remarkable initial efficacy of CD19 chimeric Ag receptor T (CAR-T) cell therapy, a high incidence of relapse has been observed. To further increase treatment efficacy and reduce the rate of escape of Ag-negative cells, we need to develop CAR-T cells that target other Ags. Given its restricted expression pattern, CD37 was considered a preferred novel target for immunotherapy in hematopoietic malignancies. Therefore, we designed a CD37-targeting CAR-T (CD37CAR-T) using the single-chain variable fragment of a humanized anti-CD37 Ab, transmembrane and intracellular domains of CD28, and CD3ζ signaling domains. High levels of CD37 expression were confirmed in B cells from human peripheral blood and bone marrow B cell precursors at late developmental stages; by contrast, more limited expression of CD37 was observed in early precursor B cells. Furthermore, we found that human CD37CAR-T cells with longer spacer lengths exhibited high gene transduction efficacy but reduced capacity to proliferate; this may be due to overactivation and fratricide. Spacer length optimization resulted in a modest transduction efficiency together with robust capacity to proliferate. CD37CAR-T cells with optimized spacer length efficiently targeted various CD37+ human tumor cell lines but had no impact on normal leukocytes both in vitro and in vivo. CD37CAR-T cells effectively eradicated Raji cells in xenograft model. Collectively, these results suggested that spacer-optimized CD37CAR-T cells could target CD37-high neoplastic B cells both in vitro and in vivo, with only limited interactions with their normal leukocyte lineages, thereby providing an additional promising therapeutic intervention for patients with B cell malignancies.

Composite CD79A/CD40 co-stimulatory endodomain enhances CD19CAR-T cell proliferation and survival.

Adoptively transferred CD19 chimeric antigen receptor (CAR) T cells have led to impressive clinical outcomes in B cell malignancies. Beyond induction of remission, the persistence of CAR-T cells is required to prevent relapse and provide long-term disease control. To improve CAR-T cell function and persistence, we developed a composite co-stimulatory domain of a B cell signaling moiety, CD79A/CD40, to induce a nuclear translocating signal, NF-κB, to synergize with other T cell signals and improve CAR-T cell function. CD79A/CD40 incorporating CD19CAR-T cells (CD19.79a.40z) exhibited higher NF-κB and p38 activity upon CD19 antigen exposure compared with the CD28 or 4-1BB incorporating CD19CAR-T cells (CD19.28z and CD19.BBz). Notably, we found that CD19.79a.40z CAR-T cells continued to suppress CD19+ target cells throughout the co-culture assay, whereas a tendency for tumor growth was observed with CD19.28z CAR-T cells. Moreover, CD19.79a.40z CAR-T cells exhibited robust T cell proliferation after culturing with CD19+ target cells, regardless of exogenous interleukin-2. In terms of in vivo efficiency, CD19.79a.40z demonstrated superior anti-tumor activity and in vivo CAR-T cell proliferation compared with CD19.28z and CD19.BBz CD19CAR-T cells in Raji-inoculated mice. Our data demonstrate that the CD79A/CD40 co-stimulatory domain endows CAR-T cells with enhanced proliferative capacity and improved anti-tumor efficacy in a murine model.

Permanent Impairment-Free, Relapse-Free Survival: A Novel Composite Endpoint to Evaluate Long-Term Success in Allogeneic Transplantation.

Permanent impairment (PI) of vital organs is one of the transplantation-related health problems affecting the quality of life and morbidity even in patients who do not develop graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplantation (allo-HCT), but no data are available on PI of multiple organs. This retrospective study aimed to estimate a novel composite endpoint of PI-free, relapse-free survival (PIRFS) in 164 allo-HCT recipients. We defined PI as >26% to 30% impairment of the whole person in 6 vital organs using the whole person impairment rating. Conventional GVHD-free/relapse-free survival (GRFS) and PIRFS at 5 years were 33.8% (95% confidence interval [CI], 26.5% to 41.3%) and 40.6% (95% CI, 32.6% to 48.4%), respectively. In the whole cohort, PIRFS was higher than GRFS at any time after allo-HCT. However, PIRFS was lower than GRFS after day 397 post-transplantation in patients who underwent umbilical cord blood transplantation (UCBT). In UCBT recipients, 5-year GRFS and PIRFS were 47.6% (95% CI, 34.3% to 59.7%) and 39.2% (95% CI, 26.6% to 51.5%), respectively. The cumulative incidence of PI after 5 years was 20.9% (95% CI, 13.7% to 29.0%) in patients surviving for ≥6 months without relapse. The multivariate analysis revealed that high disease risk (hazard ratio [HR], 1.91; 95% CI, 1.26 to 2.88; P < .01) and Karnofsky Performance Status score ≤90% at transplantation (HR, 1.73; 95% CI, 1.14 to 2.63; P = .01) were correlated with the lower PIRFS, whereas UCBT (HR, 2.35; 95% CI, 1.11 to 4.99; P = .03), grade III-IV acute GVHD by day 180 (HR, 3.59; 95% CI, 1.04 to 12.4; P = .04), and thrombotic microangiopathy by day 180 (HR, 2.74; 95% CI, 1.10 to 6.87; P = .03) were significantly correlated with a higher incidence of PI. More than 20% of long-term survivors had PI. Our data suggest that PIRFS is a useful endpoint for assessing long-term transplantation success from a different perspective than has been established previously.

Impact of a Nutritional Risk Index on Clinical Outcomes after Allogeneic Hematopoietic Cell Transplantation.

Nutritional status is an important component of cancer care, and malnutrition itself can cause death in 10% to 20% of cancer patients. A nutritional risk index (NRI) is a useful tool for nutritional assessment of cancer patients. This study aimed to evaluate the impact of pretransplant NRI values on outcomes of allogeneic hematopoietic cell transplantation (allo-HSCT). One hundred sixty patients who underwent allo-HSCT between January 2008 and July 2017 at Konan Kosei Hospital were included in this single-center, retrospective analysis. NRI was calculated at the beginning of the conditioning regimen. The patients were divided into high NRI (NRI ≥ 97.5) and low NRI (NRI < 97.5) groups, and overall survival (OS), nonrelapse mortality (NRM), and cumulative incidences of acute and chronic graft-versus-host disease (GVHD) were evaluated. Two-year OS rates were 76% (95% confidence interval [CI], 63% to 83%) and 50.4% (95% CI, 38% to 62%) in the high NRI and low NRI groups, respectively (P < .001). One-year cumulative incidences of NRM were 7.9% (95% CI, 3.5% to 15%) and 23% (95% CI, 14% to 33%; P = .014) and 2-year cumulative relapse rates were 17% (95% CI, 10% to 26%) and 32% (95% CI, 21% to 43%; P = .10) in the high NRI and low NRI groups, respectively. The multivariate analysis indicated low NRI was a significant risk factor for OS and NRM. Conversely, high NRI was associated with increased incidences of grades II to IV acute GVHD and chronic GVHD. Additionally, the subgroup analysis according to stem cell source revealed a significant benefit of higher NRI on survival only in umbilical cord blood recipients. Overall, these results suggest that pretransplant NRI might predict OS and NRM after allo-HSCT.

Promising Outcome of Umbilical Cord Blood Transplantation in Patients with Multiple Comorbidities.

The hematopoietic cell transplantation-specific comorbidity index (HCT-CI) has been recently proposed to predict the probability of nonrelapse mortality (NRM) and overall survival (OS) in allogeneic hematopoietic stem cell transplantation (HSCT). However, the usefulness of the HCT-CI in single-unit umbilical cord blood transplantation (UCBT) remains unclear. We investigated the impact of the HCT-CI on the clinical outcomes of allogeneic HSCT in a single-center retrospective study including 53 recipients of UCBT (UCBT group) and 90 recipients of other HSCT (non-UCBT group). In the non-UCBT group 2-year OS rates for HCT-CI score < 3 and ≥3 were 67% (n = 74; 95% confidence interval [CI], 54% to 78%) and 26% (n = 16; 95% CI, 7% to 51%), respectively (P = .001). In the UCBT group these rates were 66% (n = 39; 95% CI, 48% to 79%) and 69% (n = 14; 95% CI, 36% to 87%), respectively (P = .73). In the non-UCBT group 1-year NRM rates for HCT-CI score < 3 and ≥3 were 14% (95% CI, 6.4% to 22%) and 37% (95% CI, 14% to 61%), respectively (P = .02). In the UCBT group these rates were 6.1% (95% CI, 3.4% to 24%) and 7.7% (95% CI, .4% to 29%), respectively (P = .78). Using multivariate analysis we showed that HCT-CI score ≥ 3 was significantly associated with lower OS (hazard ratio, 3.06; 95% CI, 1.47 to 6.38; P = .003) and higher NRM (hazard ratio, 2.87; 95% CI, 1.18 to 6.96; P = .02) for the non-UCBT group. UCBT showed good OS with low incidence of NRM, even in patients with high HCT-CI scores. Altogether, we propose single-unit UCB to be a promising stem cell source for improving survival in patients with multiple comorbidities.

Delineating the Ultra-Low Misorientation between the Dislocation Cellular Structures in Additively Manufactured 316L Stainless Steel.

Sub-micro dislocation cellular structures formed during rapid solidification break the strength-ductility trade-off in laser powder bed fusion (LPBF)-processed 316L stainless steel through high-density dislocations and segregated elements or precipitates at the cellular boundaries. The high-density dislocation entangled at the cellular boundary accommodates solidification strains among the cellular structures and cooling stresses through elastoplastic deformation. Columnar grains with cellular structures typically form along the direction of thermal flux. However, the ultra-low misorientations between the adjacent cellular structures and their interactions with the cellular boundary formation remain unclear. In this study, we revealed the ultra-low misorientations between the cellular structures in LPBF-processed 316L stainless steel using conventional electron backscatter diffraction (EBSD), transmission Kikuchi diffraction (TKD), and transmission electron microscopy (TEM). The conventional EBSD and TKD analysis results could provide misorientation angles smaller than 2°, while the resolution mainly depends on the specimen quality and scanning step size, and so on. A TEM technique with higher spatial resolution provides accurate information between adjacent dislocation cells with misorientation angles smaller than 1°. This study presents evidence that the TEM method is the better and more precise analytical method for the misorientation measurement of the cellular structures and provides insights into measuring the small misorientation angles between adjacent dislocation cells and nanograins in nanostructured metals and alloys with ultrafine-grained microstructures.

Machine Learning-Aided Analysis of the Rolling and Recrystallization Textures of Pure Iron with Different Cold Reduction Ratios and Cold-Rolling Directions.

We performed a machine learning-aided analysis of the rolling and recrystallization textures in pure iron with different cold reduction ratios and cold-rolling directions. Five types of specimens with different cold reduction ratios and cold-rolling directions were prepared. The effect of two-way cold-rolling on the rolling texture was small at cold reduction ratios different from 60%. The cold reduction ratio in each stage hardly affected the texture evolution during cold-rolling and subsequent short-term annealing. In the case of long-term annealing, although abnormal grain growth occurred, the crystal orientation of the grains varied. Moreover, the direction of cold-rolling in each stage also hardly affected the texture evolution during cold-rolling and subsequent short-term annealing. During long-term annealing, sheets with the same cold-rolling direction in the as-received state and in the first stage showed the texture evolution of conventional one-way cold-rolled pure iron. Additionally, we conducted a machine learning-aided analysis of rolling and recrystallization textures. Using cold-rolling and annealing conditions as the input data and the degree of Goss orientation development as the output data, we constructed high-accuracy regression models using artificial neural networks and XGBoost. We also revealed that the annealing temperature is the dominant factor in the nucleation of Goss grains.

Dual CAR-T Cells Targeting CD19 and CD37 Are Effective in Target Antigen Loss B-cell Tumor Models.

Chimeric antigen receptor T (CAR-T) cells targeting multiple antigens (Ag), may reduce the risk of immune escape following the loss of the target Ag and further increase the efficacy of treatment. We developed dual-targeting CAR-T cells that target CD19 and CD37 Ags and evaluated their antitumor effects. CD19/CD37 dual CAR-T cells were generated using cotransduction and simultaneous gene transfer of two types of lentiviral vectors transferring CD19CAR or CD37CAR genes, including the intracellular domains of CD28 and CD3ζ signaling domains. These dual CAR-T cells contained three fractions: CD19/CD37 bispecific CAR-T cells, single CD19CAR-T cells, and single CD37CAR-T cells. In the functional evaluation of CAR-T cells in vitro, CD19/CD37 dual CAR-T cells showed adequate proliferation and cytokine production in response to CD19 and CD37 antigen stimulation alone or in combination. Evaluation of intracellular signaling revealed that dual CAR-T cell-mediated signals were comparable with single CAR-T cells in response to CD19- and CD37-positive B-cell tumors. Although the cytotoxicity of CD19/CD37 dual CAR-T cells in both CD19- and CD37-positive B-cell tumors was similar to that of single CD19 and CD37CAR-T cells, against CD19 and CD37 Ag-heterogeneous tumor, dual CAR-T cells demonstrated significantly superior tumor lysis compared with single CAR-T cells. Furthermore, CD19/CD37 dual CAR-T cells effectively suppressed Ag-heterogeneous Raji cells in a xenograft mouse model. Collectively, these results suggest that CD19/CD37 dual CAR-T cells may be effective target-Ag-loss B-cell tumor models in vitro and in vivo, which represents a promising treatment for patients with relapsed/refractory B-cell malignancies.

Simulation of Abnormal Grain Growth Using the Cellular Automaton Method.

The abnormal grain growth of steel, which is occurs during carburization, adversely affects properties such as heat treatment deformation and fatigue strength. This study aimed to control abnormal grain growth by controlling the materials and processes. Thus, it was necessary to investigate the effects of microstructure, precipitation, and heat treatment conditions on abnormal grain growth. We simulated abnormal grain growth using the cellular automaton (CA) method. The simulations focused on the grain boundary anisotropy and dispersion of precipitates. We considered the effect of grain boundary misorientation on boundary energy and mobility. The dispersion state of the precipitates and its pinning effect were considered, and grain growth simulations were performed. The results showed that the CA simulation reproduced abnormal grain growth by emphasizing the grain boundary mobility and the influence of the dispersion state of the precipitate on the occurrence of abnormal grain growth. The study findings show that the CA method is a potential technique for the prediction of abnormal grain growth.

Two- and Three-Dimensional Modeling and Simulations of Grain Growth Behavior in Dual-Phase Steel Using Monte Carlo and Machine Learning.

Dual-phase (DP) steel has been widely used in automotive steel plates with a balance of excellent strength and ductility. Grain refinement in DP steel is important to improve the properties further; however, the factors affecting grain growth need to be well understood. The remaining problem is that acquiring data through experiments is still time-consuming and difficult to evaluate quantitatively. With the development of materials informatics in recent years, material development time and costs are expected to be significantly reduced through experimentation, simulation, and machine learning. In this study, grain growth behavior in DP steel was studied using two-dimensional (2D) and three-dimensional (3D) Monte Carlo modeling and simulation to estimate the effect of some key parameters. Grain growth can be suppressed when the grain boundary energy is greater than the phase boundary energy. When the volume fractions of the matrix and the second phase were equal, the suppression of grain growth became obvious. The long-distance diffuse frequency can promote grain growth significantly. The simulation results allow us to better understand the factors affecting grain growth behavior in DP steel. Machine learning was performed to conduct a sensitivity analysis of the affecting parameters and estimate the magnitude of each parameter's effects on grain growth in the model. Combining MC simulation and machine learning will provide one promising research strategy to gain deeper insights into grain growth behaviors in metallic materials and accelerate the research process.

Evaluation of Austenite-Ferrite Phase Transformation in Carbon Steel Using Bayesian Optimized Cellular Automaton Simulation.

Austenite-ferrite phase transformation is a crucial metallurgical tool to tailor the properties of steels required for particular applications. Extensive simulation and modeling studies have been conducted to evaluate the phase transformation behaviors; however, some fundamental physical parameters still need to be optimized for better understanding. In this study, the austenite-ferrite phase transformation was evaluated in carbon steels with three carbon concentrations during isothermal annealing at various temperatures using a developed cellular automaton simulation model combined with Bayesian optimization. The simulation results show that the incubation period for nucleation is an essential factor that needs to be considered during austenite-ferrite phase transformation simulation. The incubation period constant is mainly affected by carbon concentration and the optimized values have been obtained as 10-24, 10-19, and 10-21 corresponding to carbon concentrations of 0.2 wt%, 0.35 wt%, and 0.5 wt%, respectively. The average ferrite grain size after phase transformation completion could decrease with the decreasing initial austenite grain size. Some other parameters were also analyzed in detail. The developed cellular automaton simulation model combined with Bayesian optimization in this study could conduct an in-depth exploration of critical and optimal parameters and provide deeper insights into understanding the fundamental physical characteristics during austenite-ferrite phase transformation.

Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel.

A modified SliceGAN architecture was proposed to generate a high-quality synthetic three-dimensional (3D) microstructure image of TYPE 316L material manufactured through additive methods. The quality of the resulting 3D image was evaluated using an auto-correlation function, and it was discovered that maintaining a high resolution while doubling the training image size was crucial in creating a more realistic synthetic 3D image. To meet this requirement, modified 3D image generator and critic architecture was developed within the SliceGAN framework.

Autologous peripheral blood stem cell transplantation for Philadelphia chromosome-positive acute lymphoblastic leukemia is safe but poses challenges for long-term maintenance of molecular remission: Results of the Auto-Ph17 study.

Autologous hematopoietic stem cell transplantation (SCT) is not a standard treatment option for Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ALL); however, its position has been reassessed since the introduction of tyrosine kinase inhibitors (TKIs). We prospectively analyzed the efficacy and safety of autologous peripheral blood SCT (auto-PBSCT) for Ph+ALL patients aged between 55 and 70 years who had achieved complete molecular remission. Melphalan, cyclophosphamide, etoposide, and dexamethasone were used for conditioning. A total of 12 courses of maintenance therapy, including dasatinib, were performed. The required number of CD34+ cells was harvested in all five patients. No patient died within 100 days after auto-PBSCT, and no unexpected serious adverse events were observed. Although 1-year event-free survival was 100%, hematological relapse was observed in three patients at a median of 801 days (range, 389-1088 days) after auto-PBSCT. Molecular progressive disease was observed in the other two patients, although they maintained their first hematological remission at the last visit. Auto-PBSCT can be safely performed for Ph+ALL with TKIs. A limitation of auto-PBSCT was suggested, despite the increase in the intensity of a single treatment. The development of long-term therapeutic strategies by including new molecular targeted drugs is warranted to maintain long-term molecular remission.

Effect of Cold-Rolling Directions on Recrystallization Texture Evolution of Pure Iron.

The influence of cold-rolling directions on the recrystallization texture evolution of pure iron was examined. As-received pure iron sheets were cold-rolled under two different conditions (specimens A and B). Specimen A was cold-rolled in the vertical direction against the cold-rolling direction of the as-received sheet. Specimen B was cold-rolled in the vertical direction against the cold-rolling direction of the as-received sheet, and then in the cold-rolling direction of the as-received sheet. Cold-rolled specimens were heated to each desired temperature before being quenched in water to room temperature (298 ± 2 K). Both cold-rolled specimens showed the development of γ-fiber and {100}<011> orientation. Additionally, γ-fiber formed comparatively more in cold-rolled specimen A, while α-fiber developed comparatively more in cold-rolled specimen B. Strain distribution in cold-rolled specimen A was presumably inhomogeneous, whereas that in cold-rolled specimen B was rather uniform at the macro-scale. The formation of γ-fiber was confirmed in annealed specimen A. In annealed specimen B, however, the recrystallization texture tended to be random, and the formation of α-fiber was observed. Furthermore, the formation of Goss orientation in both annealed specimens was established. Recrystallized ferrite grains with Goss orientation nucleated in high strain regions of cold-rolled specimen. These findings show that by devising the cold-rolling direction, it is possible to discover new types of recrystallization textures.

Development of gamma-ray-induced positron age-momentum correlation measurement.

In conventional positron annihilation spectroscopy using radioisotopes, source contributions are unavoidable since positrons annihilate in the material covering the radioisotopes. Part of the positrons annihilate within the radioisotopes even when radioisotopes are deposited directly on a sample. Gamma-ray-induced positron annihilation spectroscopy makes it possible to measure only the spectra of a sample without source contributions since positrons are directly generated inside the sample from the gamma rays by pair production and annihilate inside the same sample. In this study, a new positron age-momentum correlation measurement system using ultrashort pulsed gamma rays is developed. The gamma rays with an energy of 6.6 MeV are generated by the inverse Thomson scattering of laser photons by high-energy electrons and are irradiated to the sample. The laser pulse can fully control the timing of gamma-ray generation. This characteristic and the use of a digital oscilloscope with a 12-bit vertical resolution enable us to develop a simple measurement system. Time-resolved momentum distributions for stainless steel with no defects and deformed interstitial free steel show the explicit differences reflecting the type of defect; for BaF2 single crystals, the results have been interpreted by considering the formation of positronium.

Downregulation of HLA class II is associated with relapse after allogeneic stem cell transplantation and alters recognition by antigen-specific T cells.

Genomic deletion of donor-patient-mismatched HLA alleles in leukemic cells is a major cause of relapse after allogeneic hematopoietic stem cell transplantation (HSCT). Mismatched HLA is frequently lost as an individual allele or a whole region in HLA-class I, however, it is downregulated in HLA-class II. We hypothesized that there might be a difference in T cell recognition capacity against epitopes associated with HLA-class I and HLA-class II and consequently such allogeneic immune pressure induced HLA alterations in leukemic cells. To investigate this, we conducted in vitro experiments with T cell receptor-transduced T (TCR-T) cells. The cytotoxic activity of NY-ESO-1-specific TCR-T cells exhibited similarly against K562 cells with low HLA-A*02:01 expression. However, we demonstrated that the cytokine production against low HLA-DPB1*05:01 expression line decreased gradually from the HLA expression level approximately 2-log lower than normal expressors. Using sort-purified leukemia cells before and after HSCT, we applied the next-generation sequencing, and revealed that there were several marked downregulations of HLA-class II alleles which demonstrated consistently low expression from pre-transplantation. The marked downregulation of HLA-class II may lead to decreased antigen recognition ability of antigen-specific T cells and may be one of immune evasion mechanism associated with HLA-class II downregulation.

Three-Dimensional Analysis of Ferrite Grains Recrystallized in Low-Carbon Steel during Annealing.

We performed a three-dimensional (3D) analysis of ferrite grains recrystallized in low-carbon steel during annealing. Cold-rolled specimens were heated to 723 K and held for various periods. The 3D morphology of ferrite grains recrystallized during the annealing process was investigated. The progress of recovery in low-carbon steel was more inhibited than that in pure iron. However, ferrite recrystallization in low-carbon steel was more rapid than that in pure iron. The Avrami exponent was inconsistent with the 3D morphology of the recrystallized ferrite grains in pure iron but consistent with that of the grains in low-carbon steel. Thus, the Avrami exponent depends on the recovery and recrystallization behaviors. Furthermore, the recrystallized ferrite grain growth was virtually 2D. Three types of recrystallized ferrite grains were observed: recrystallized ferrite grains elongated along the transverse or rolling direction; plate-shaped recrystallized ferrite grains grown in the transverse and rolling directions; fine and equiaxed recrystallized ferrite grains. These results suggest that the recrystallized ferrite grains did not grow in the normal direction. Thus, we concluded that the 3D morphology of recrystallized ferrite grains depends on the kinetics of recrystallization and the initial microstructure before recrystallization.

Quantitative Analysis of the Recovery Process in Pure Iron Using X-ray Diffraction Line Profile Analysis.

We conducted quantitative analysis of the recovery process during pure iron annealing using the modified Williamson-Hall and Warren-Averbach methods. We prepared four types of specimens with different dislocation substructures. By increasing the annealing temperature, we confirmed a decrease in dislocation density. In particular, screw-dislocation density substantially decreased in the early stage of the recovery process, while edge-dislocation density gradually decreased as annealing temperature increased. Moreover, changes in hardness during the recovery process mainly depended on edge-dislocation density. Increases in annealing temperature weakly affected the dislocation arrangement parameter and crystallite size. Recovery-process modeling demonstrated that the decrease in screw-dislocation density during the recovery process was mainly dominated by glide and/or cross-slip with dislocation core diffusion. In contrast, the decrease in edge-dislocation density during the recovery process was governed by a climbing motion with both dislocation core diffusion and lattice self-diffusion. From the above results, we succeeded in quantitatively distinguishing between edge- and screw-dislocation density during the recovery process, which are difficult to distinguish using transmission electron microscope and electron backscatter diffraction.

Domain knowledge integration into deep learning for typhoon intensity classification.

In this report, we propose a deep learning technique for high-accuracy estimation of the intensity class of a typhoon from a single satellite image, by incorporating meteorological domain knowledge. By using the Visual Geometric Group's model, VGG-16, with images preprocessed with fisheye distortion, which enhances a typhoon's eye, eyewall, and cloud distribution, we achieved much higher classification accuracy than that of a previous study, even with sequential-split validation. Through comparison of t-distributed stochastic neighbor embedding (t-SNE) plots for the feature maps of VGG with the original satellite images, we also verified that the fisheye preprocessing facilitated cluster formation, suggesting that our model could successfully extract image features related to the typhoon intensity class. Moreover, gradient-weighted class activation mapping (Grad-CAM) was applied to highlight the eye and the cloud distributions surrounding the eye, which are important regions for intensity classification; the results suggest that our model qualitatively gained a viewpoint similar to that of domain experts. A series of analyses revealed that the data-driven approach using only deep learning has limitations, and the integration of domain knowledge could bring new breakthroughs.