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Big Earth Data 2024年第1期8卷 82-114页

作者： Antonia Ivanda LjiljanaŠerić DušanŽagar Krištof Oštir Faculty of Electrical Engineering Mechanical Engineering and Naval ArchitectureUniversity of SplitSplitCroatia Faculty of Civil and Geodetic Engineering University of LjubljanaLjubljanaSlovenia

This paper presents a novel approach for predicting the water quality indicator-Secchi disk depth(Z_(SD)).Z_(SD)indirectly reflects water clarity and serves as a proxy for other quality *** study utilizes Deep Neural Network(DNN)trained on satellite remote sensing and measured data from three sources:two datasets obtained from official agencies in Croatia and Slovenia,and one citizen science data source,all covering the northern coastal region of the Adriatic *** proposed model uses 1D Convolutional Neural Network(CNN)in the spectral dimension to predict Z_(SD).The model’s performance indicates a strong fit to the observed data,proving capability of 1D-CNN to capture changes in water *** the test dataset,the model achieved a high R-squared value of 0.890,a low root mean squared error(RMSE)of 0.023 and mean absolute error(MAE)of *** results demonstrate that employing a 1D-CNN in the spectral dimension of Sentinel-3 OLCI data is an effective approach for predicting water *** findings have significant implications for monitoring Z_(SD)in coastal *** integrating diverse data sources and leveraging advanced machine learning algorithms,a more accurate and comprehensive assessment of water quality can be achieved.

关键词： Secchi Sentinel-3 OLCI 1DCNN Adriatic sea

Performance Comparison of Vision Transformer- and CNN-Based Image Classification Using Cross Entropy: A Preliminary Application to Lung Cancer Discrimination from CT Images

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Journal of Biomedical Science and Engineering 2024年第9期17卷 157-170页

作者： eri Matsuyama Haruyuki Watanabe Noriyuki Takahashi Faculty of Informatics The University of Fukuchiyama Kyoto Japan School of Radiological Technology Gunma Prefectural College of Health Sciences Gunma Japan School of Health Sciences Fukushima Medical University Fukushima Japan

This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categories: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), large cell carcinoma (LULC), and normal. Although CNNs have made significant advancements in medical imaging, their limited capacity to capture long-range dependencies has led to the exploration of ViTs, which leverage self-attention mechanisms for a more comprehensive global understanding of images. The study utilized a dataset of 748 lung CT images to train both models with standardized input sizes, assessing their performance through conventional metrics—accuracy, precision, recall, F1 score, specificity, and AUC—as well as cross entropy, a novel metric for evaluating prediction uncertainty. Both models achieved similar accuracy rates (95%), with ViT demonstrating a slight edge over ResNet50 in precision and F1 scores for specific classes. However, ResNet50 exhibited higher recall for LULC, indicating fewer missed cases. Cross entropy analysis showed that the ViT model had lower average uncertainty, particularly in the LUAD, Normal, and LUSC classes, compared to ResNet50. This finding suggests that ViT predictions are generally more reliable, though ResNet50 performed better for LULC. The study underscores that accuracy alone is insufficient for model comparison, as cross entropy offers deeper insights into the reliability and confidence of model predictions. The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing a nuanced understanding of their performance and reliability. While the ViT outperformed the CNN-based ResNet50 in lung cancer classification based on cross-entropy values, the performance differences were minor and may not hold c

关键词： Lung Cancer Classification Vision Transformers Convolutional Neural Networks Cross Entropy Deep Learning

Thermally activated delayed fluorescence carbazole-triazine dendrimer with bulky substituents

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Aggregate 2024年第1期5卷 236-243页

作者： Hiroki Ikebe Kohei Nakao eri Hisamura Minori Furukori Yasuo Nakayama Takuya Hosokai Minlang Yang Guanting Liu Takuma Yasuda Ken Albrecht Interdisciplinary Graduate School of Engineering Sciences Kyushu UniversityFukuokaJapan Institute for Materials Chemistry and Engineering Kyushu UniversityKasugaJapan Department of Pure and Applied Chemistry Graduate School of Science and TechnologyTokyo University of ScienceNodaChibaJapan National Metrology Institute of Japan(NMIJ) National Institute of Advanced Industrial Science and Technology(AIST)TsukubaIbarakiJapan Institute for Advanced Study Kyushu UniversityNishi-kuFukuokaJapan

Carbazole-triazine dendrimers with a bulky terminal substituent were synthesized,and the thermally activated delayed fluorescence(TADF)property was *** to unsubstituted carbazole dendrimers,dendrimers with bulky terminal substituents showed comparable to better photoluminescence quantum yields(PLQY)in neat ***(PF)-substituted dendrimers showed the highest PLQY of 81%,a smallΔEst of 0.06 eV,and the fastest reverse intersystem crossing(RISC)rate of∼1×10^(5 )s^(−1) compared to other *** measurements of dendrimers and dendrons(fragments)indicate that the close proximity of the triplet energy of phenylfluorene-substituted carbazole dendrons(^(3)LE)to that of phenylfluorene-substituted dendrimers(^(1)CT,^(3)CT)contributes to RISC promotion and improves TADF *** modification fine-tunes the energy level and suppresses intermolecular interactions,and this study provides a guideline for designing efficient solution-processable and non-doped TADF materials.

关键词： dendrimer OLED TADF 1 INTRODUCTION Thermally activated delayed fluorescence(TADF)materials which are inexpensive and highly efficient alternatives to fluorescent

Using Cross Entropy as a Performance Metric for Quantifying Uncertainty in DNN Image Classifiers: An Application to Classification of Lung Cancer on CT Images

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Journal of Biomedical Science and Engineering 2024年第1期17卷 1-12页

作者： eri Matsuyama Masayuki Nishiki Noriyuki Takahashi Haruyuki Watanabe Faculty of Informatics University of Fukuchiyama Kyoto Japan Graduate School of Radiological Sciences International University of Health and Welfare Tochigi Japan School of Health Sciences Fukushima Medical University Fukushima Japan School of Radiological Technology Gunma Prefectural College of Health Sciences Gunma Japan

Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation metric for image classifier models and apply it to the CT image classification of lung cancer. A convolutional neural network is employed as the deep neural network (DNN) image classifier, with the residual network (ResNet) 50 chosen as the DNN archi-tecture. The image data used comprise a lung CT image set. Two classification models are built from datasets with varying amounts of data, and lung cancer is categorized into four classes using 10-fold cross-validation. Furthermore, we employ t-distributed stochastic neighbor embedding to visually explain the data distribution after classification. Experimental results demonstrate that cross en-tropy is a highly useful metric for evaluating the reliability of image classifier models. It is noted that for a more comprehensive evaluation of model perfor-mance, combining with other evaluation metrics is considered essential. .

关键词： Cross Entropy Performance Metrics DNN Image Classifiers Lung Cancer Prediction Uncertainty

The Effect of Umami Stimulation on Salivary Secretion Rate and Duration

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Health 2024年第1期16卷 52-59页

作者： eri Sambuichi Rumi Nishimura Shiho Morishita Shigeru Watanabe Department of Oral Health Sciences School of Health Sciences Meikai University Urayasu Japan Department of Oral Epidemiology Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima Japan

Purpose: Umami reportedly promotes salivation. We aimed to investigate the effects of taste stimuli on slow and fast salivary secretion in humans using umami, sweet, and sour stimuli. Methods: Eight healthy women participated between 14:00 and 15:00, taking the circadian rhythm of salivary secretion into account. The types and concentrations of the taste solutions were glutamic acid (1.7 × 10−3 M), inosinic acid (9.8 × 10−3 M), and guanylic acid (9.8 × 10−3 M) for umami stimulation, citric acid (6.5 × 10−3 M) for acidity stimulation, and sucrose (1.6 × 10−2 M) for sweetness stimulation. First, the unstimulated salivary flow rate was measured. Then, 3 ml of a flavor solution was dropped under the tongue using a syringe. The saliva was expelled into an aluminum cup every minute and weighed. The first minute’s value minus 3 ml flavor solution was the stimulated salivary secretion rate produced by each flavor. The time-to-return to the initial unstimulated salivary flow rate was the duration of the stimulated saliva secretion rate. Results: The mean unstimulated salivary flow rate across participants was 0.64 ± 0.25 ml/min (range: 0.23 - 1.03 ml/min). The highest amount of saliva was induced by citric acid. There were significant differences between citric acid and the other flavor solutions (p < 0.05 for glutamic acid, inosinic acid, and sucrose;p < 0.01 for guanylic acid). There were no significant differences in duration of salivation between the flavor solutions. When the participants were divided into slow (0.45 ± 0.16 ml/min) and fast groups (0.83 ± 0.15 ml/min) based on their median resting salivary secretion rate, there were no significant differences between the two groups in the amount of saliva secreted at 1 minute after stimulation and the duration of the salivary secretion rate. Conclusion: Umami stimulation was effective in slowing salivary secretion and sustaining salivary secretion after stimulation.

关键词： Salivary Secretion Umami Flavor Oral Health Stimulated Salivary Secretion

Usefulness of Newly Devised Clomiphene Citrate Administration Method Compared with the Conventional Method in Ovulation and Pregnancy

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Open Journal of Obstetrics and Gynecology 2024年第4期14卷 637-649页

作者： Makoto Kawamura Misaki Akiyama Remi Nakajima eri Satoi Yoko Ogaki Rieko Kanda Department of Obstetrics and Gynecology Kohseichuo General Hospital Tokyo Japan

Objective: Since not all women wish to conceive a child through aggressive treatment, we investigated the usefulness of modified repeated intracyclic clomiphene citrate (CC) therapy (repeated CC therapy) as a newly devised administration method. Methods: We evaluated the effects of CC administration on menstrual cycle length and retrospectively compared ovulation and pregnancy in 220 women who received CC at our hospital. Patients in the conventional method group received 50 mg per day for five days, starting on the fifth day of menstruation (withdrawal bleeding). Groups with and without menstrual cycle shortening after conventional CC administration were compared. The repeated CC therapy group was also compared with the non-shortened group. Repeated CC therapy was administered for the first five days as in the conventional method, and a second five-day repeat treatment was administered after an interval of five to seven days. Pregnancy rates, including indirect pregnancies, were evaluated by three different methods. Results: Ovulation and pregnancy rates were significantly better in the shortened group than in the non-shortened group (P < 0.001 and P = 0.010, respectively). Even in the non-shortened group, ovulation and pregnancy rates including indirect pregnancies were significantly improved when ovulation was observed with repeated CC therapy (P < 0.001 and P = 0.022, respectively). Conclusions: For patients whose menstrual cycle was not improved or shortened, repeated CC therapy as the newly devised CC administration method is useful as the next step after the conventional CC administration method.

关键词： Clomiphene Citrate Infertility Menstrual Cycle Ovulation Induction

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2023年西藏美术热点现象述评

西藏艺术研究 2024年第1期 4-12页

作者：俄日东主西藏大学艺术学院

本文回顾评述了2023年西藏美术相关的热点现象。西藏近现代美术挖掘整理、后疫情时代艺术的国际交流、美术创作以及展览等热点现象,反映了中华民族的文化自信,呈现了西藏美术多领域的时代新风。2023年的西藏美术重点围绕铸牢中华民族共... 详细信息

本文回顾评述了2023年西藏美术相关的热点现象。西藏近现代美术挖掘整理、后疫情时代艺术的国际交流、美术创作以及展览等热点现象,反映了中华民族的文化自信,呈现了西藏美术多领域的时代新风。2023年的西藏美术重点围绕铸牢中华民族共同体意识,在创作、展览、交流、研究和美术馆建设等方面取得了优异的成绩。

关键词： 2023年西藏美术热点分析年度述评

Current perspectives of viral hepatitis

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World Journal of Gastroenterology 2024年第18期30卷 2402-2417页

作者： Daisuke Usuda Yuki Kaneoka Rikuo Ono Masashi Kato Yuto Sugawara Runa Shimizu Tomotari Inami eri Nakajima Shiho Tsuge Riki Sakurai Kenji Kawai Shun Matsubara Risa Tanaka Makoto Suzuki Shintaro Shimozawa Yuta Hotchi Ippei Osugi Risa Katou Sakurako Ito Kentaro Mishima Akihiko Kondo Keiko Mizuno Hiroki Takami Takayuki Komatsu Tomohisa Nomura Manabu Sugita Department of Emergency and Critical Care Medicine Juntendo University Nerima HospitalNerima 177-8521TokyoJapan Department of Sports Medicine Faculty of MedicineJuntendo UniversityBunkyo 113-8421TokyoJapan

Viral hepatitis represents a major danger to public health,and is a globally leading cause of *** five liver-specific viruses:Hepatitis A virus,hepatitis B virus,hepatitis C virus,hepatitis D virus,and hepatitis E virus,each have their own unique epidemiology,structural biology,transmission,endemic patterns,risk of liver complications,and response to antiviral *** remain few options for treatment,in spite of the increasing prevalence of viral-hepatitiscaused liver ***,chronic viral hepatitis is a leading worldwide cause of both liver-related morbidity and mortality,even though effective treatments are available that could reduce or prevent most patients’*** 2016,the World Health Organization released its plan to eliminate viral hepatitis as a public health threat by the year 2030,along with a discussion of current gaps and prospects for both regional and global eradication of viral ***,treatment is sufficiently able to prevent the disease from reaching advanced ***,future therapies must be extremely safe,and should ideally limit the period of treatment necessary.A better understanding of pathogenesis will prove beneficial in the development of potential treatment strategies targeting infections by viral *** review aims to summarize the current state of knowledge on each type of viral hepatitis,together with major innovations.

关键词： Hepatitis A virus Hepatitis B virus Hepatitis C virus Hepatitis D virus Hepatitis E virus Current perspectives

Transport, signaling, and homeostasis of potassium and sodium in plants

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Journal of Integrative Plant Biology 2014年第3期56卷 231-249页

作者： eri Adams Ryoung Shin RIKEN Center for Sustainable Resource Science

Potassium （K＋） is an essential macronutrient in plants and a lack of K＋ significantly reduces the potential for plant growth and development. By contrast, sodium （Na＋）, while beneficial to some extent, at high concentrations it disturbs and inhibits various physiological processes and plant growth. Due to their chemical similarities, some functions of K＋ can be undertaken by Na＋ but K＋ homeostasis is severely affected by salt stress, on the other hand. Recent advances have highlighted the fascinating regulatory mechanisms of K＋ and Na＋ transport and signaling in plants. This review summarizes three major topics：（i） the transport mechanisms of K＋ and Na＋ from the soil to the shoot and to the cellular - compartments; （ii） the mechanisms through which plants sense and respond to K＋ and Na＋ availability; and （iii） the components involved in maintenance of K＋/Na＋ homeostasis in plants under salt stress.

关键词： Homeostasis potassium signaling sodium transport