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Review of the literature laparoscopic surgery for metastatic hepatic leiomyosarcoma associated with smooth muscle tumor of uncertain malignant potential: Case report

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World Journal of Hepatology 2018年第4期10卷 402-408页

作者： Keisuke Fukui Nobuhisa Takase Taiichiro Miyake Koji Hisano eri Maeda Tohru Nishimura Koichiro Abe Akihito Kozuki Tomohiro tanaka Naoki Harada Manabu Takamatsu Kunihiko Kaneda Department of Surgery Kakogawa Central City Hospital

Metastatic hepatic leiomyosarcoma is a rare malignant smooth muscle *** report a case of metastatic hepatic leiomyosarcoma associated with smooth muscle tumor of uncertain malignant potential(STUMP).A 68-year-old female presented with a liver mass(60 mm × 40 mm, Segment 4).She underwent left salpingooophorectomy for an ovary tumor with STUMP in a broad ligament 6 years *** FDG-PET showed obvious metabolically active foci, abnormal metabolically active foci other than the lesion were not detected.A malignant liver tumor was strongly suspected and laparoscopic partial liver resection was performed with vessel-sealing devices using the crush clamping method and Pringle *** findings revealed metastatic liver leiomyosarcoma associated with STUMP in a broad *** case is an extremely rare case of malignant transformation from primary STUMP to metastatic hepatic *** provides important evidence regarding the treatment for metastatic hepatic leiomyosarcoma associated with STUMP.

关键词： Leiomyosarcoma Smooth muscle tumor Hepatic neoplasm Neoplasm metastasis Laparoscopic surgery Liver resection

DETERMINATION OF SOME PARAMETERS OF CRACK BASED ON FRASTA SIMULATION

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Acta Metallurgica Sinica(English Letters) 2005年第5期18卷 594-602页

作者： K. tanaka Department of Mechanical Systems Engineering Toyama Prefectural University Toyama 939-0398 Japan

A new method, using the fracture-surface topography analysis （FRASTA）, of determining the parameters of rotation factor and CTOA is provided. The fracture surfaces are scanned by laser microscope and the height data is recorded to analyze. By comparing the crack extension, plastic rotation factor and COA obtained by the method of double clip gauge and by this new method respectively, the validity of it is verified. It is then used to determine the CTOA. .The critical CTOA is well determined in this paper. Also by the new method, the variation of crack opening deformation （COA and CTOA） through specimen thickness can be obtained which can＇t be obtained by the usual methods. It also can provide much information of crack extension such as direction and ratio.

关键词： FRASTA COA CTOA rotation factor

DEVELOPMENT OF FRASTA SIMULATION SOFTWARE

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Acta Metallurgica Sinica(English Letters) 2006年第3期19卷 165-170页

作者： K. tanaka Department of Mechanical Systems Engineering Toyama Prefectural University Toyama 939-0398 Japan

Fracture-surface topography analysis （FRASTA） was successfully used to simulate the process of crack and calculate parameters of crack such as the crack opening angle （COA） and crack-tip opening angle （CTOA）. But because the amount of calculation is large, errors are often made during the course of calculation. FRASTA simulation software, namely fracture surface analyst （FSA ） is developed and a series of center-cracked tension （CCT） and double edge notched （DEN） specimens of different materials with different sizes are tested, their fracture surfaces are scanned by non-contact 319 scanning system and the elevation data of the fracture surfaces is recorded. FSA used the recorded elevation data of fracture surfaces to simulate the process of crack based on the principle of FRASTA. Results show that FSA can accurately simulate the process and calculate the parameters of crack.

关键词： FRASTA (fracture-surface topography analysis) COA (crack opening angle) CTOA (crack-tip opening angle) CCT (center-cracked tension) DEN (double edge notched)

Solvent extraction equilibrium of dysprosium(Ⅲ) from nitric acid solutions with 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester

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Transactions of Nonferrous Metals Society of China 2010年第4期20卷 707-711页

作者： HUANG Ying tanaka Mikiya Research Institute for Environmental Management Technology National Institute of Advanced Industrial Science and Technology （AIST） 16-10nogawa Tsukuba Ibaraki 305-8569 Japan School of Energy and Environment Southeast University Nanjing 210096 China

In view of the importance of solvent extraction of rare earth metals with the acidic organophosphorous reagent,the development of a chemically based model applicable to high concentration is *** the present study,the equilibrium distribution of dysprosium(Ⅲ)between an aqueous nitric acid solution and 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester (PC88A)was measured in the range of an initial aqueous dysprosium(Ⅲ)concentration from 1.0×10-3to 1.0×10-1kmol/m 3and PC88A concentration from 0.16 to 0.65 kmol/m3in Shellsol D70 as the *** obtained data were analyzed using the chemically based model in order to correlate the equilibrium distribution *** this model,dysprosium(Ⅲ)was assumed to be extracted with the PC88A dimer as a 1:3 complex,the activities were considered for the aqueous species,and the effective concentration of the PC88A dimer was calculated using Alstad's empirical *** a result,the apparent extraction equilibrium constant was determined to be 253(kmol·m- 3)-2with an excellent correlation between the experiment and calculation results in the wide range of the logarithm of the distribution ratio from-2 to *** conclusion,the methodology in this model would be effective for quantitative description of solvent extraction behavior of general rare earth elements as well as dysprosium.

关键词： solvent extraction dysprosium 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester(PC88A) nitric acid equilibrium

Mechanisms of Cup-Shaped Vesicle Formation Using Amphiphilic Diblock Copolymer

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Open Journal of Polymer Chemistry 2022年第2期12卷 43-54页

作者： eri Yoshida Department of Applied Chemistry and Life Science Toyohashi University of Technology Toyohashi Japan

A cup shape is a dynamic morphology of cells and organelles. With the aim of elucidating the formation of the biotic cup-shaped morphology, this study investigated cup-shaped vesicles consisting of an amphiphilic diblock copolymer from the aspect of synthetic polymer chemistry. Cup-shaped vesicles were obtained by the polymerization-induced self-assembly of poly(methacrylic acid)-block-poly(n-butyl methacrylate-random-methacrylic acid), PMAA-b-P(BMA-r-MAA), in an aqueous methanol solution using the photo nitroxide-mediated controlled/living radical polymerization technique. Field emission scanning electron microscopic observations demonstrated that the cup-shaped vesicles were suddenly formed during the late stage of the polymerization due to the extension of the hydrophobic P(BMA-r-MAA) block chain. During the early stage, the polymerization produced spherical vesicles rather than a cup shape. As the hydrophobic block chain was extended by the polymerization progress, the spherical vesicles reduced the size and were accompanied by the generation of small particles that were attached to the vesicles. The vesicles continued to reduce the size due to further extension of the hydrophobic chain;however, they suddenly grew into cup-shaped vesicles. This growth was accounted for by a change in the critical packing shape of the copolymer due to the hydrophobic chain extension. These findings are helpful for a better understanding of the biotic cup-shaped vesicle formation.

关键词： Cup-Shaped Vesicles Polymerization-Induced Self-Assembly Poly(methacrylic acid)-block-poly(n-butyl methacrylate-random-methacrylic acid) Critical Packing Shape

A Novel Method for Automated Lung Region Segmentation in Chest X-Ray Images

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Journal of Biomedical Science and Engineering 2021年第6期14卷 288-299页

作者： eri Matsuyama Faculty of Informatics The University of Fukuchiyama Kyoto Japan

Detecting and segmenting the lung regions in chest X-ray images is an important part in artificial intelligence-based computer-aided diagnosis/detection (AI-CAD) systems for chest radiography. However, if the chest X-ray images themselves are used as training data for the AI-CAD system, the system might learn the irrelevant image-based information resulting in the decrease of system’s performance. In this study, we propose a lung region segmentation method that can automatically remove the shoulder and scapula regions, mediastinum, and diaphragm regions in advance from various chest X-ray images to be used as learning data. The proposed method consists of three main steps. First, employ the simple linear iterative clustering algorithm, the lazy snapping technique and local entropy filter to generate an entropy map. Second, apply morphological operations to the entropy map to obtain a lung mask. Third, perform automated segmentation of the lung field using the obtained mask. A total of 30 images were used for the experiments. In order to verify the effectiveness of the proposed method, two other texture maps, namely, the maps created from the standard deviation filtering and the range filtering, were used for comparison. As a result, the proposed method using the entropy map was able to appropriately remove the unnecessary regions. In addition, this method was able to remove the markers present in the image, but the other two methods could not. The experimental results have revealed that our proposed method is a highly generalizable and useful algorithm. We believe that this method might act an important role to enhance the performance of AI-CAD systems for chest X-ray images.

关键词： Chest X-Ray Image Segmentation Thresholding Simple Linear Iterative Clustering Lazy Snapping Entropy Filtering Masking AI-CAD

Direct measurement of the three-dimensional distribution of leaf area density and light conditions in a mature oak stand by the cube method

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林业研究:英文版 2023年第6期34卷 1817-1827页

作者： Chiharu Migita Yukihiro Chiba tanaka Kenzo Forestry and Forest Products Research Institute TsukubaIbaraki 305-8687Japan Japan International Research Centre for Agricultural Sciences TsukubaIbaraki 305-8686Japan

Although the distributions of foliage and light play major roles in various forest functions,accurate,nondestructive measurement of these distributions is difficult due to the complexity of the canopy *** evaluate the foliage and light distributions directly and nondestructively in a mature oak stand,we used the cube method by dividing the forest canopy into small cubes(50 cm per side)and directly measured leaf area density(LAD,the total one-sided leaf area per unit volume,i.e.,cube)and relative irradiance(RI)within each *** distribution of LAD and of RI was highly heterogeneous,even at the same canopy *** heterogeneity reflected the presence of foliage clusters associated with multiple forking *** relationship between cumulative LAD at the canopy surface and average RI followed the Beer-Lambert *** mean light extinction coefficient(K)was ***,K was overestimated by more than double(0.80)when calculated based on the classical method using RI at the forest *** overestimation was caused by the lower RI due to light absorption by nonleaf plant parts below the *** findings on the complex foliage and light distributions in canopy layers should help improve the accuracy of RI and K measurements and thus more accurate predictions of environmental responses and forest functions.

关键词： Beer-Lambert law Canopy structure Foliage cluster Leaf area density Leaf area index Relative light intensity

Characterization of Organic Aerosol at a Rural Site in the North China Plain Region:Sources,Volatility and Organonitrates

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Advances in Atmospheric Sciences 2021年第7期38卷 1115-1127页

作者： Qiao ZHU Li-Ming CAO Meng-Xue TANG Xiao-Feng HUANG eri SAIKAWA Ling-Yan HE Key Laboratory for Urban Habitat Environmental Science and Technology Peking University Shenzhen Graduate SchoolShenzhen 518055China Department of Environmental Sciences Emory UniversityAtlantaGA 30322USA Rollins School of Public Health Emory UniversityAtlantaGA 30322USA

The North China Plain(NCP)is a region that experiences serious aerosol pollution.A number of studies have focused on aerosol pollution in urban areas in the NCP region;however,research on characterizing aerosols in rural NCP areas is comparatively *** this study,we deployed a TD-HR-AMS(thermodenuder high-resolution aerosol mass spectrometer)system at a rural site in the NCP region in summer 2013 to characterize the chemical compositions and volatility of submicron aerosols(PM_(1)).The average PM_(1)mass concentration was 51.2±48.0μg m^(−3) and organic aerosol(OA)contributed most(35.4%)to PM_(1).Positive matrix factorization(PMF)analysis of OA measurements identified four OA factors,including hydrocarbon-like OA(HOA,accounting for 18.4%),biomass burning OA(BBOA,29.4%),lessoxidized oxygenated OA(LO-OOA,30.8%)and more-oxidized oxygenated OA(MO-OOA,21.4%).The volatility sequence of the OA factors was HOA>BBOA>LO-OOA>MO-OOA,consistent with their oxygen-to-carbon(O:C)***,the mean concentration of organonitrates(ON)was 1.48−3.39μg m−3,contributing 8.1%-19%of OA based on cross validation of two estimation methods with the high-resolution time-of-flight aerosol mass spectrometer(HRToF-AMS)*** analysis shows that ON were more correlated with BBOA and black carbon emitted from biomass burning but poorly correlated with ***,volatility analysis for ON further confirmed that particulate ON formation might be closely associated with primary emissions in rural NCP areas.

关键词： organic aerosols volatility organonitrates biomass burning North China Plain

A Deep Learning Interpretable Model for Novel Coronavirus Disease (COVID-19) Screening with Chest CT Images

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Journal of Biomedical Science and Engineering 2020年第7期13卷 140-152页

作者： eri Matsuyama Faculty of Informatics The University of Fukuchiyama Kyoto Japan

In this article, we propose a convolutional neural network (CNN)-based model, a ResNet-50 based model, for discriminating coronavirus disease 2019 (COVID-19) from Non-COVID-19 using chest CT. We adopted the use of wavelet coefficients of the entire image without cropping any parts of the image as input to the CNN model. One of the main contributions of this study is to implement an algorithm called gradient-weighted class activation mapping to produce a heat map for visually verifying where the CNN model is looking at the image, thereby, ensuring the model is performing correctly. In order to verify the effectiveness and usefulness of the proposed method, we compare the obtained results with that obtained by using pixel values of original images as input to the CNN model. The measures used for performance evaluation include accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and Matthews correlation coefficient (MCC). The overall classification accuracy, F1 score, and MCC for the proposed method (using wavelet coefficients as input) were 92.2%, 0.915%, and 0.839%, and those for the compared method (using pixel values of the original image as input) were 88.3%, 0.876%, and 0.766%, respectively. The experiment results demonstrate the superiority of the proposed method. Moreover, as a comprehensible classification model, the interpretability of classification results was introduced. The region of interest extracted by the proposed model was visualized using heat maps and the probability score was also shown. We believe that our proposed method could provide a promising computerized toolkit to help radiologists and serve as a second eye for them to classify COVID-19 in CT scan screening examination.

关键词： Convolutional Neural Networks Wavelet Transforms Classification Lung Diseases CT Imaging COVID-19