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text, 紀要論文 / Departmental Bulletin Paper

By the continuous development of aerospace, petroleum exploration, and other industrial fields, the fiber-optic acoustic sensor (FOAS) with high reliability is a desideration sensor, which can be used for noise monitoring in the extremely harsh environment. The FOAS based on the all-rigid Fabry–Perot resonator (FPR) relies on the new acoustic sensitive principle, where the change in the air refractive index is induced by sound waves and gets rid of the distortion caused by the mechanical characteristics of the acoustic sensor based on the movable parts. So, the FPR-based FOAS is very suitable for acoustic sensing in the harsh environment. In this paper, the reliability of this kind of FOASs is simulated and analyzed. The modal and anti-vibration simulation results of FPR with different sizes show that the FPR has a high natural frequency, and the external vibration environment does not affect the acoustic sensitivity of the FPR. The micro and small-batch all-rigid FPR can be manufactured by the optical contact. Moreover, the FPR can withstand the high temperature of 500°C that is verified by rapid heat treatment equipment. In order to improve the reliability of the FOAS, the metal packing shell is designed and fabricated. Moreover, the vibration and high-temperature tests of the packaged sensor are carried out. The two groups of tests show that the sensor can work normally under 10 g of acceleration vibration and 200°C high temperature, respectively. Therefore, the FOAS based on the FPR has high reliability and is very suitable for noise monitoring in the extreme harsh environment of various industrial fields. Furthermore, the research results of this paper will enhance the competitiveness and influence of the commercialized FOAS.

The clinical features of EBV-positive diffuse large B cell lymphoma (DLBCL) indicate a poorer prognosis than EBV-negative DLBCL. Currently, there is no efficacious drug for EBV-positive DLBCL. The cytokine interleukin-21 (IL-21) has been reported to be pro-apoptotic in DLBCL cell lines and is being explored as a new therapeutic strategy for this type of lymphomas. However, our previous studies showed that IL-21 stimulation of EBV-positive DLBCL cell lines leads to increased proliferation. Here, analysis of a rare clinical sample of EBV-positive DLBCL, in combination with a NOD/SCID mouse xenograft model, confirmed the effect of IL-21 on the proliferation of EBV-positive DLBCL cells. Using RNA-sequencing, we identified the pattern of differentially-expressed genes following IL-21 treatment and verified the expression of key genes at the protein level using western blotting. We found that IL-21 upregulates expression of the host MYC and AP-1 (composed of related Jun and Fos family proteins) and STAT3 phosphorylation, as well as expression of the viral LMP-1 protein. These proteins are known to promote the G1/S phase transition to accelerate cell cycle progression. Furthermore, in NOD/SCID mouse xenograft model experiments, we found that IL-21 treatment increases glucose uptake and angiogenesis in EBV-positive DLBCL tumours. Although more samples are needed to validate these observations, our study reconfirms the adverse effects of IL-21 on EBV-positive DLBCL, which has implications for the drug development of DLBCL.

Fully-epitaxial magnetoresistance (MR) devices with half-metallic Heusler alloys has attracted considerable attention for years due to their excellent spin-dependent transport properties such as high MR ratio and ultra-low resistance-area product. However, their poor manufacturability due to the necessity of epitaxial growth on a special single crystalline substrate such as MgO(001) hinders their practical applications. To overcome this issue, in this study, we fabricated Heusler-based epitaxial current-perpendicular-to-plane giant magnetoresistance (CPP-GMR) film grown on Si substrate and directly bonded it to poly-crystalline electrode wafer by using three-dimensional (3D) integration processes such as direct wafer bonding and removal of backside Si substrate. First we explored suitable seed/buffer layers for the (001)-oriented epitaxial growth of Heusler CPP-GMR on Si(001) substrate. Si-subs/NiAl/CoFe seed/buffer structure was found to induce (001)-oriented epitaxial growth and to suppress an Al diffusion from NiAl to the Heusler electrode even after annealing at 500 °C, resulting in large MR ratio comparable to that with MgO substrate. After direct wafer bonding process, the microstructure analysis revealed clean damage-free bonded interface between the epitaxial Heusler GMR and poly-crystalline electrode films with Au capping layers. After the 3D integration processes, high MR performance has been successfully reproduced. This unique processing method enables the integration of high performance Heusler-based epitaxial spintronic devices for various practical applications.

B. amyloliquefaciens D2WM, a plant growth-promoting rhizobacteria from the Camellia oleifera rhizosphere, exhibits strong antimicrobial activity and has the capacity to promote plant growth, and this study aimed to determine its antibacterial mechanism against the soft rot disease pathogen D. chrysanthemi HBEU-9. The metabolites from D2WM were also identified and purified. The crude extract (CE) of D2WM effectively inhibited the mycelial growth of five fungal species and the growth of five bacterial species. In particular, CE was well able to inhibit walnut blight caused by Xanthomonas arboricola pv. Juglandis, which is an effect that has rarely been reported. Compared with the control, the addition of 0.2%–0.3% CE to the growth medium notably decreased the cell biomass of HBEU-9 and significantly increased the membrane permeability, soluble proteins and reducing sugars of HBEU-9. SEM and TEM analyses revealed that CE could destroy the cell wall and distort cells and decreased the levels of cell-degrading enzymes (Cx, PG and PMG) by 23.4%, 53.8% and 27.5%, respectively. Importantly, CE retained nearly 80% activity after either storage for 7 months at 4 °C or exposure to 121 °C for 30 min. In addition, the most essential antibacterial compound, macrolactin A, was purified and identified from D2WM cultures through column chromatography, semi-preparative HPLC and HPLC-MS. Taken together, our results highlight the potential of B. amyloliquefaciens D2WM as a biocontrol agent against bacterial diseases and the utility of macrolactin A as an antimicrobial compound.

PII signal transduction proteins are ubiquitous and highly conserved in bacteria, archaea, and plants and play key roles in controlling nitrogen metabolism. However, research on biological functions and regulatory targets of PII proteins remains limited. Here, we illustrated experimentally that the PII protein Corynebacterium glutamicum GlnK (CgGlnK) increased l-arginine yield when glnK was overexpressed in Corynebacterium glutamicum. Data showed that CgGlnK regulated l-arginine biosynthesis by upregulating the expression of genes of the l-arginine metabolic pathway and interacting with N-acetyl-l-glutamate kinase (CgNAGK), the rate-limiting enzyme in l-arginine biosynthesis. Further assays indicated that CgGlnK contributed to alleviation of the feedback inhibition of CgNAGK caused by l-arginine. In silico analysis of the binding interface of CgGlnK-CgNAGK suggested that the B and T loops of CgGlnK mainly interacted with C and N domains of CgNAGK. Moreover, F11, R47, and K85 of CgGlnK were identified as crucial binding sites that interact with CgNAGK via hydrophobic interaction and H bonds, and these interactions probably had a positive effect on maintaining the stability of the complex. Collectively, this study reveals PII-NAGK interaction in nonphotosynthetic microorganisms and further provides insights into the regulatory mechanism of PII on amino acid biosynthesis in corynebacteria. IMPORTANCE Corynebacteria are safe industrial producers of diverse amino acids, including l-glutamic acid and l-arginine. In this study, we showed that PII protein GlnK played an important role in l-glutamic acid and l-arginine biosynthesis in C. glutamicum. Through clarifying the molecular mechanism of CgGlnK in l-arginine biosynthesis, the novel interaction between CgGlnK and CgNAGK was revealed. The alleviation of l-arginine inhibition of CgNAGK reached approximately 48.21% by CgGlnK addition, and the semi-inhibition constant of CgNAGK increased 1.4-fold. Furthermore, overexpression of glnK in a high-yield l-arginine-producing strain and fermentation of the recombinant strain in a 5-liter bioreactor led to a remarkably increased production of l-arginine, 49.978 g/liter, which was about 22.61% higher than that of the initial strain. In conclusion, this study provides a new strategy for modifying amino acid biosynthesis in C. glutamicum.

Accurate load forecasting provides a reference of vital importance for power generation and power dispatching systems. A short-term load forecasting model combining similar day clustering and CatBoost method is proposed in this paper. Similar day clustering is a method for evaluating the similarity between the days to be forecast and historical days. Similar day clustering is based on K-means clustering which can classify samples with similar features into the same category. Then, CatBoost is used to build load forecasting models. CatBoost enables us to directly handle categorical features without pre-processing. This paper utilized the information collected by a substation in Hangzhou as the data set, and compare the proposed model with the existing forecasting model based on Autoregressive Moving Average, Gradient Boosting Decision Tree, CatBoost, Long Short-Term Memory. The experimental results show that the proposed model provides more accurate results compared with other models in terms of MAPE, RMSE.

In this paper, we study the Dispute Generation (DG) problem from the plaintiff allegation (PA) and the defendant argument (DA) in a law document. We are the first to formulate DG as a text-to-text natural language generation (NLG) problem. Since the logical relationships between a PA and a DA are rather difficult to identify, existing models cannot generate accurate disputes, let alone find all disputes. To solve this problem, we propose a novel Seq2Seq model with two dispute detection modules, which captures relationships among the PA and the DA in two ways. First, in the context-level detection module, we employ hierarchical attention mechanism to learn sentence representation and joint attention mechanism to match right disputes. Second, in the topic-level detection module, topic information is taken into account to find indirect disputes. We conduct extensive experiments on the real-world dataset. The results demonstrate the effectiveness of our method. Also the results show that the context-level and the topic-level detection modules can improve the accuracy and coverage of generated disputes.

With the rapid development of the domestic logistics industry, the demand for quick inquiry of express parcel delivery information is becoming more and more urgent. The automatic acquisition of express delivery number is expected to solve this problem. This paper proposes a barcode localization segmentation recognition algorithm for bar code/QR code location segmentation recognition in a single scan image of a parcel in a complex environment. The whole algorithm is fully tested in the actual express single scan image. The results show that the algorithm is fast, accurate and has low bit error rate, and has strong practical value.

Based on the scattering loss difference between the single-mode-fiber-optical-waveguide (SMFW) and multimode-fiber-optical-waveguide (MMFW) structures, a method to estimate the roughness of multimode rectangular optical waveguide (ROW) is proposed. Based on the analysis of the mode coupling characteristics of the SMFW structure and the MMFW structure, the coupling efficiency of higher order mode of the ROW for the MMFW structure is larger than that of the SMFW structure. However, it is reversed for the lower order mode. By further analyzing the mode scattering loss coefficients of ROW induced by roughness, it is found that the total scattering loss for the SMFW structure is less than that for the MMFW structure, which can be used to estimate the roughness. The experimental results show that the roughness is 248.67 nm when the waveguide length is 75 mm and the scattering loss difference is 0.31dB. As the roughness is 275.37 nm by the 3-D optical profiler, this implies that the method is effective. Compared to the conventional methods, the method has many advantages, such as convenience, high efficiency, and ability for large measurement area.

Objectives It is difficult and time-consuming to detect narcotic drugs concealed within human bodies by visual assessment of X-ray images . This study aimed to describe a method for automatic detection of concealed drugs based on abdominal X-ray transmission images. Methods 43 X-ray images from suspects during border inspection are used in this study. Image features were extracted from both the directional fractal dimension and the gray level to form feature vectors. An unbalanced data preprocessing method was implemented before training to minimize the false alarms. A support vector machine model was applied for training and final classification. Results The proposed method yielded a 97.7% classification accuracy and a 96.1% sensitivity in 43 image cases, which were superior to the method without unbalanced data process resulting in a 95.3% classification accuracy and a 92.3% sensitivity. Conclusions This fast, computer-based X-ray transmission image processing method can be used in the field inspection for rapid, automatic detection of body packing.

In this study, a fluorescence biosensor based on the peroxidase mimicking activity of platinum nanoparticles (Pt NPs) was fabricated for rapid detection of hypoxanthine (Hx), which is a sensitive indicator of the freshness of aquatic products. The fluorescence intensity of the sensing system had a linear relationship with the concentration of Hx in the range of 8–2500 μM, and the limit of detection was as low as 2.88 μM (S/N = 3). Moreover, benefiting from the excellent selectivity of the biosensor, Hx content in fish, shrimp and squid samples could be quickly detected with good recovery rates (103.94–109.00%). And the Pt NPs used in the biosensor was reusable, which was proved by the recovery rate was only slightly decreased to 91% after three cycles. In addition to the advantages of facile preparation and low cost, the proposed biosensor will be a promising candidate for rapid and convenient freshness evaluation of aquatic products.

Automatic material classification is very useful for threat detection with X-ray screening technology. In this paper, we propose the use of machine learning methods to the problem of fine-grained classification of organic matters based on multi-energy transmission images, which has been overlooked by existing methods. The method which we propose consists three main steps: spectrum analysis, feature selection and supervised classification. We show detailed analysis of the relationship between feature dimension and material classification accuracy. Our method can also be used to find optimal X-ray configurations for material classification. We compare the performance of several machine learning models for the fine-grained classification task. For the task of classifying three categories of organic matters, we can obtain the classification accuracy higher than 85% with only X-ray measurements with the dimension of four. In conclusion, the results of our paper provide one promising direction for the automatic identification of organic contraband using multi-energy X-ray imaging techniques.

Multi-voltage threshold (MVT) digitizes the scintillation pulse by taking the timing samples when it crosses the predefined thresholds. In our previous work, we have demonstrated an FPGA-only MVT digitizer based on this method and developed several modularized PET detectors. It has become a promised high integration density and low cost digitizer for readout the signal from the SiPM based scintillation detector. In this work, we describe the design and implementation of a photon-counting x-ray detector using FPGA-only MVT digitizer and YSO/SiPM detector. The count-rate of the detector is measured to be as high as 1.3 Mcps/pixel and it’s variation is 11.9 kcps/pixel. We also demonstrated an X-ray security inspection system by using of such detectors. Our preliminary imaging from the system indicated a spatial resolution of 1.0 line pair/mm and a wire resolution of 0.2 mm. Moreover the normalized imaging indicates that the mean value of gray scale varying with the sampling time in one channel is 253 with a standout deviation 4. And the mean gradation between channels is 253 with a standout deviation 3.

Face milling commonly generates surface quality of roughness or variation, especially severe for the milling of large-scale components with complex surface geometry such as cylinder block, engine head, and valve body. Thus surface variation serves as an important indicator both for machining parameter selection and components’ service performance. Conversely the optimization of machining process is a vital objective to improve the surface quality and its service life of machined components. Many researchers have dedicated to the prediction of machined surface variation generated by face milling using numerical or experimental methods. However, the numerical methods based on finite element analysis (FEA) are good at predicting local deformation of workpiece under instantaneous milling force, particularly applied for online compensation in face milling. Whereas experimental methods can only be used to estimate whole surface variation through reverse correlation analysis of measured data and processing variables. Therefore, an efficient and comprehensive numerical model is highly desired for the prediction of surface variation of entire surface. This study proposes a coupled numerical simulation method, updating FE model literarily based on the integration of data from ABAQUS and MATLAB, to predict surface variation induced by the face milling of large-scale components with complex surfaces. Using the coupled model, the 3D variation of large-scale surface can be successfully simulated by considering face milling process including dynamic milling force, spiral curve of milling trajectory, and intermittently rotating contact characteristics. Surface variation is finally represented with point cloud from totally iterative FE analysis and verified by face milling experiment. Result shows that the new prediction method can simulate surface variation of complex components. Based on the verified model, a set of numerical analyses are conducted to evaluate the effects of local stiffness non-homogenization and milling force variation on machined surface variation. It demonstrates that surface variation with surface peaks and concaves is strongly correlated with local stiffness non-homogenization especially in feed direction. Thus the coupled prediction method provides a theoretical and efficient way to study surface variation induced by face milling of large-scale complex components.

Carcinosarcoma of the pancreas is a very rare tumor with distinct malignant epithelial and mesenchymal components. The pathogenesis, however, remains to be further clarified. This is a report on a 44-year old Chinese woman with a solid tumor in the head of pancreas analyzed on immunohistochemistry, K-ras, and p53 sequence. On gross inspection, the tumor was grey-white and poorly circumscribed with a bone-like texture component. In the histology, it was also noteworthy that the heterogeneous features of the tumor were mixed in the same field, which consisted of adenocarcinoma, sarcoma, and osteosarcoma. Immunohistochemical results have confirmed that these are three histological components with different phenotypes. Gene mutation analyses confirmed the heterogeneity, in which the adenocarcinoma component and the sarcoma component did not burden the same K-ras mutation and p53 mutations as that of the osteosarcoma component. It is gratifying that the woman is still alive 48 months after surgery. Based on these findings, this case was the first case reported to date of pancreatic adenocarcinoma combing with sarcoma and osteosarcoma in the same tumor. Furthermore, this case was a unique pancreatic tumor composed of carcinosarcoma and extraskeletal osteosarcomas. The morphological, immunohistochemical, and genetic findings suggested that the pancreatic tumor was of a multiple clonal origins.

text, 紀要論文 / Departmental Bulletin Paper

text, 紀要論文 / Departmental Bulletin Paper

In consideration of the harm to society, hiding narcotics in human bodies should be investigate strictly. While the automatic detection method is absent nowadays, and the inspection rate by human eyes is low. So we introduce a new method based on directional fractal dimension texture feature extraction and support vector machine(SVM) to classify the inspection x-ray images. Using this method, the detection could be totally automatic. It has been compared by cross validation in RBF and linear kernel. In our method, the classification accuracy is 95% and negative predictive value is 100% when 40 images had been tested.

2017, この博士論文は、全文公表に適さないやむを得ない事由があり要約のみを公表していましたが、解消したため、令和3(2021)年9月21日に全文を公表しました。

We perform a systematic study of elliptic flow ($v_2$) in Au+Au collision at $\sqrt{s_{NN}}=5$ GeV by using a microscopic transport model JAM. The centrality, pseudorapidity, transverse momentum and beam energy dependence of $v_2$ for charged as well as identified hadrons are studied. We investigate the effects of both the hadronic mean-field and the softening of equation of state (EoS) on elliptic flow. The softening of EoS is realized by imposing attractive orbits in two body scattering, which can reduce the pressure of the system. We found that the softening of EoS leads to the enhancement of $v_2$, while the hadronic mean-field suppresses $v_2$ relative to the cascade mode. It indicates that elliptic flow at high baryon density regions is highly sensitive to the EoS and the enhancement of $v_2$ may probe the signature of a first-order phase transition in heavy-ion collisions at beam energies of a strong baryon stopping region., Comment: 7 pages, 9 figures, to appear in Chinese Physics C

We investigated the effect of Ag doping on atomic order and spin polarization of Co2FeSi Heusler alloy thin films. The Co2FeSi film doped with 3at.%-Ag showed improved degree of B2- and 〖L2〗_1-ordering after thermal annealing comparing to Co2FeSi film. Negative sign of anisotropic magnetoresistance suggests the half-metallic nature of Ag-doped Co2FeSi film after annealing at a relatively low temperature of 300 °C. The current-perpendicular-to-plane pseudo spin-valves using the Ag-doped Co2FeSi ferromagnetic (FM) electrodes showed about 1.2 times larger MR ratio than that using the Co2FeSi FM electrodes, reflecting an enhanced spin polarization in Ag-doped Co2FeSi film. Micro-structure analysis revealed the doped Ag was rejected out of Co2FeSi layer after annealing. This study suggests Ag doping to Co-based Heusler compound having no/few solubility with Ag is beneficial for realizing spin-valves with high output at moderate annealing conditions.

To fully investigate cellular responses to stimuli and perturbations within tissues, it is essential to replicate the complex molecular interactions within the local microenvironment of cellular niches. Here, the authors introduce Alginate-based tissue engineering (ALTEN), a biomimetic tissue platform that allows ex vivo analysis of explanted tissue biopsies. This method preserves the original characteristics of the source tissue's cellular milieu, allowing multiple and diverse cell types to be maintained over an extended period of time. As a result, ALTEN enables rapid and faithful characterization of perturbations across specific cell types within a tissue. Importantly, using single-cell genomics, this approach provides integrated cellular responses at the resolution of individual cells. ALTEN is a powerful tool for the analysis of cellular responses upon exposure to cytotoxic agents and immunomodulators. Additionally, ALTEN's scalability using automated microfluidic devices for tissue encapsulation and subsequent transport, to enable centralized high-throughput analysis of samples gathered by large-scale multicenter studies, is shown Refereed/Peer-reviewed