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( Hyeun Bum Kim ),( Yuankai Wang ),( Xingmin Sun ) 한국미생물 · 생명공학회 2016 Journal of microbiology and biotechnology Vol.26 No.3
We investigated the increased risk of Clostridium difficile infection (CDI) caused by the combined use of antibiotics and an immunosuppressive drug in a mouse model. Our data showed that an approximate return to pretreatment conditions of gut microbiota occurred within days after cessation of the antibiotic treatment, whereas the recovery of gut microbiota was delayed with the combined treatment of antibiotics and dexamethasone, leading to an increased severity of CDI. An alteration of gut microbiota is a key player in CDI. Therefore, our data implied that immunosuppressive drugs can increase the risk of CDI through the delayed recovery of altered gut microbiota.
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UDGAN: A new urban design inspiration approach driven by using generative adversarial networks
干薇,Zhao Zichen,Wang Yuankai,Zou Yixuan,Zhou Shiqi,오지강 한국CDE학회 2024 Journal of computational design and engineering Vol.11 No.1
The morphological design of urban space affects the quality of the environment. The traditional experience-based design approach was greatly improved by introducing computational design tools. However, the existing urban design tools are mostly developed on pre-set rules or given targets, which have few contributions to enhance creativity or generate inspiring schemes. Therefore, this paper proposes a new computational urban design approach named UDGAN, integrating generative adversarial networks (GANs) and multi-objective optimization algorithms. This model utilizes urban design scheme plans over the past 20 years from a particular designer as training datasets. Four preference models were trained to autonomously generate stylized urban design schemes. Eight morphological parameters were used to analyze the model performance by comparing generated results with the ground truth. This GAN-based surrogate approach is combined with a morphological indicator alignment process using multi-objective optimization model to obtain better results. The result shows that the R2 predicted by the improved Pix2Pix model reaches 0.798, and the similarity of the generated results can be stably distributed between 0.7 and 0.8, so the design scheme of this preferred style can be effectively learned. At the same time, the pre-trained model greatly reduces the time consumption of the design scheme generation, taking 5 min approximately to complete a generation process. This approach quickly generated the design scheme with preferred features, supporting the designer with creativity and greatly saving the time of design creation, transforming computational design into an inspiration-driven process.
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Power Quality Early Warning Based on Anomaly Detection
Gu, Wei,Bai, Jingjing,Yuan, Xiaodong,Zhang, Shuai,Wang, Yuankai The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.4
Different power quality (PQ) disturbance sources can have major impacts on the power supply grid. This study proposes, for the first time, an early warning approach to identifying PQ problems and providing early warning prompts based on the monitored data of PQ disturbance sources. To establish a steady-state power quality early warning index system, the characteristics of PQ disturbance sources are analyzed and summed up. The higher order statistics anomaly detection (HOSAD) algorithm, based on skewness and kurtosis, and hierarchical power quality early warning flow, were then used to mine limit-exceeding and abnormal data and analyze their severity. Cases studies show that the proposed approach is effective and feasible, and that it is possible to provide timely power quality early warnings for limit-exceeding and abnormal data.
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Power Quality Early Warning Based on Anomaly Detection
Wei Gu,Jingjing Bai,Xiaodong Yuan,Shuai Zhang,Yuankai Wang 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.4
Different power quality (PQ) disturbance sources can have major impacts on the power supply grid. This study proposes, for the first time, an early warning approach to identifying PQ problems and providing early warning prompts based on the monitored data of PQ disturbance sources. To establish a steady-state power quality early warning index system, the characteristics of PQ disturbance sources are analyzed and summed up. The higher order statistics anomaly detection (HOSAD) algorithm, based on skewness and kurtosis, and hierarchical power quality early warning flow, were then used to mine limit-exceeding and abnormal data and analyze their severity. Cases studies show that the proposed approach is effective and feasible, and that it is possible to provide timely power quality early warnings for limit-exceeding and abnormal data.
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Yu Feng,Yutao Liu,Mingming Yuan,Guilan Dong,Hongxia Zhang,Tongmei Zhang,Lianpeng Chang,Xuefeng Xia,Lifeng Li,Haohua Zhu,Puyuan Xing,Hongyu Wang,Yuankai Shi,Zhijie Wang,Xingsheng Hu 대한암학회 2022 Cancer Research and Treatment Vol.54 No.3
Purpose To investigate the feasibility of biomarkers based on dynamic circulating tumor DNA (ctDNA) to classify small cell lung cancer (SCLC) into different subtypes. Materials and Methods Tumor and longitudinal plasma ctDNA samples were analyzed by next-generation sequencing of 1,021 genes. PyClone was used to infer the molecular tumor burden index (mTBI). Pre-treatment tumor tissues [T1] and serial plasma samples were collected (pre-treatment [B1], after two [B2], six [B3] cycles of chemotherapy and at progression [B4]). Results Overall concordance between T1 and B1 sequencing (n=30) was 66.5%, and 89.5% in the gene of <i>RB1</i>. A classification method was designed according to the changes of <i>RB1</i> mutation, named as subtype Ⅰ (both positive at B1 and B2), subtype Ⅱ (positive at B1 but negative at B2), and subtype Ⅲ (both negative at B1 and B2). The median progressive-free survival for subtype Ⅰ patients (4.5 months [95%CI: 2.6-5.8]) was inferior to subtype Ⅱ (not reached, p<0.0001) and subtype Ⅲ (10.8 months [95%CI: 6.0-14.4], p=0.002). The median overall survival for subtype Ⅰ patients (16.3 months [95%CI: 5.3-22.9]) was inferior to subtype Ⅱ (not reached, p=0.01) and subtype Ⅲ (not reached, p=0.02). Patients with a mTBI dropped to zero at B2 had longer median overall survival (not reached vs. 19.5 months, p=0.01). The changes of mTBI from B4 to B1 were sensitive to predict new metastases, with a sensitivity of 100% and a specificity of 85.7%. Conclusion Monitoring ctDNA based <i>RB1</i> mutation and mTBI provided a feasible tool to predict the prognosis of SCLC.
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