222 research outputs found

    Experimental Evaluation of High-Level Energy Optimization Based on Thread Partitioning

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    Real-Time Observation of Hydrogen Peroxide Transport through the Oil Phase in a W/O/W Double Emulsion with Chemiluminescence Emission

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    The evaluation of the transport rates of hydrophilic substances is important in agricultural and pharmaceutical chemistry and in the cosmetics and food-processing industries. Although there are some estimation methods focusing on the diffusion of the substances through the oil phase of the W/O/W core-shell double emulsions (oil microcapsules), all of them take several hours or days. This long-time measurement has a risk of rupture of the oil microcapsules, which causes significant errors. If it were possible to measure the transport rate of substances in the oil phase of the oil microcapsules in real time, the risk of rupture could be reduced. Here, we propose a new estimation method for the transport rates of hydrogen peroxide (H2O2) in the oil phase of an oil microcapsule for real-time estimation by means of chemiluminescence (CL) emission of the luminol reaction. We theoretically give the relationship among the CL emission intensity, diffusion coefficient, microcapsule size, and experimental time and successfully estimate the diffusion coefficient of H2O2 in the oil phase of the oil microcapsule from the experimental data. Moreover, we discuss the dependence of the permeation of H2O2 through the oil phase on the concentration of the oil-soluble surfactant; the difference in the permeation rate is likely to be attributed not to the diffusion coefficient but to the partition coefficient of H2O2 in the oil microcapsule.Hiroshi Kouno, Yosuke Iwai, Yoshiaki Uchida et al. Real-Time Observation of Hydrogen Peroxide Transport through the Oil Phase in a W/O/W Double Emulsion with Chemiluminescence Emission. Langmuir, 33 (15), 3802-3808, April 17, © 2017 American Chemical Society. https://doi.org/10.1021/acs.langmuir.7b0010

    Nanosheet Formation in Hyperswollen Lyotropic Lamellar Phases

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    Nanosheets (∼1 nm) are formed using a nonionic hyperswollen lyotropic lamellar phase as a template. The accumulation and reaction of ingredients in the highly separated (several hundred nm) bilayers in the hyperswollen lyotropic lamellar phase should result in very thin nanosheets. This method could be applied to the synthesis of a wide variety of two-dimensional organic and inorganic materials.Yoshiaki Uchida, Takuma Nishizawa, Takeru Omiya et al. Nanosheet Formation in Hyperswollen Lyotropic Lamellar Phases. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 138 (4), 1103-1105, February 16, ©2016 American Chemical Society. https://doi.org/10.1021/jacs.5b1125

    Zero- and Few-shot Sound Event Localization and Detection

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    Sound event localization and detection (SELD) systems estimate direction-of-arrival (DOA) and temporal activation for sets of target classes. Neural network (NN)-based SELD systems have performed well in various sets of target classes, but they only output the DOA and temporal activation of preset classes that are trained before inference. To customize target classes after training, we tackle zero- and few-shot SELD tasks, in which we set new classes with a text sample or a few audio samples. While zero-shot sound classification tasks are achievable by embedding from contrastive language-audio pretraining (CLAP), zero-shot SELD tasks require assigning an activity and a DOA to each embedding, especially in overlapping cases. To tackle the assignment problem in overlapping cases, we propose an embed-ACCDOA model, which is trained to output track-wise CLAP embedding and corresponding activity-coupled Cartesian direction-of-arrival (ACCDOA). In our experimental evaluations on zero- and few-shot SELD tasks, the embed-ACCDOA model showed a better location-dependent scores than a straightforward combination of the CLAP audio encoder and a DOA estimation model. Moreover, the proposed combination of the embed-ACCDOA model and CLAP audio encoder with zero- or few-shot samples performed comparably to an official baseline system trained with complete train data in an evaluation dataset.Comment: 5 pages, 4 figure

    A Processor Core Synthesis System in IP-based SoC Design

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    A subcentimeter duodenal neuroendocrine neoplasm with a liver metastasis upgraded to G3: a case report

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    BACKGROUND: Although duodenal neuroendocrine neoplasms (DuNENs) usually have indolent phenotypes, some DuNENs exhibit aggressive clinical manifestations. Tumor size > 1 cm, lymph node metastasis, and high grade have been associated with poor prognosis. However, preoperative risk evaluation is often difficult, because Ki-67 index on biopsy is frequently underestimated due to the intratumor heterogeneity. Here, we present a case of a subcentimeter DuNEN with a low Ki-67 index on endoscopic biopsy, who developed lymph node metastasis and high-grade liver metastasis. CASE PRESENTATION: The patient was a 52-year-old female who presented an epigastric pain. Esophagogastroduodenoscopy revealed a duodenal submucosal lesion with a size of 8 mm. The endoscopic biopsy showed DuNEN with a Ki-67 index of 3.3% (G2 categorized by the World Health Organization 2019 classification). We performed an open partial duodenectomy with adjacent lymph node dissection. Pathological examination of the resected specimens revealed a Ki-67 index of 13.5% (G2) in the "hot spot" and lymph node metastasis. A hepatic low-density area detected on preoperative contrast-enhanced computed tomography appeared to be a liver metastasis on postoperative gadoxetic acid-enhanced magnetic resonance imaging. Subsequently, we performed a laparoscopic partial hepatectomy. Pathological examination of the liver specimen showed a metastatic neuroendocrine tumor with a Ki-67 index of 27.5% (NET-G3). The patient has been alive for 14 months since the hepatectomy. CONCLUSIONS: This case shows the possibility of high malignant potential of DuNEN even if the primary lesion is < 1 cm and has a low Ki-67 index on biopsy
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