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学者姓名：刘博
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Abstract ：
Background. Currently, predictive models were not developed based on the signaling pathway signatures of immune-related lncRNAs in breast cancer (BRCA) patients. Methods. We selected unsupervised hierarchical clustering algorithm to classify patients with BRCA based on the significant immune-derived lncRNAs from the TCGA dataset. And different methods including ESTIMATE, ImmuneCellAI, and CIBERSORT were performed to evaluate the immune infiltration of tumor microenvironment. Using Lasso regression algorithm, we filtered the significant signaling pathways enriched by GSEA, GSVA, or PPI analysis to develop a prognostic model. And a nomogram integrated with clinical factors and significant pathways was constructed to predict the precise probability of overall survival (OS) of BRCA patients in the TCGA dataset (n =1,098) and another two testing sets (n = 415). Results. BRCA patients were stratified into the PC (n = 571) and GC (n = 527) subgroup with significantly different prognosis with 550 immune-related lncRNAs in the TCGA dataset. Integrated analysis revealed different immune response, oncogenic signaling, and metabolic reprograming pathways between these two subgroups. And a 5-pathway signature could predict the prognosis of BRCA patients between these two subgroups independently in the TCGA dataset, which was confirmed in another two cohorts from the GEO dataset. In the TCGA dataset, 5-year OS rate was 78% (95% CI: 73-84) vs. 82% (95% CI: 77-87) for the PC and GC group (HR = 1.63 (95% CI: 1.17-2.28), p 0.004). The predictive power was similar in another two testing sets (HR > 1.20, p < 0.01). Finally, a nomogram is developed for clinical application, which integrated this signature and age to accurately predict the survival probability in BRCA patients. Conclusion. This 5-pathway signature correlated with immune derived lncRNAs was able to precisely predict the prognosis for patients with BRCA and provided a rich source characterizing immune-related lncRNAs and further informed strategies to target BRCA vulnerabilities.
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| GB/T 7714 | Liu, Bo , Zhu, Nian , Huo, Huixia et al. A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer [J]. | JOURNAL OF ONCOLOGY , 2022 , 2022 . |
| MLA | Liu, Bo et al. "A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer" . | JOURNAL OF ONCOLOGY 2022 (2022) . |
| APA | Liu, Bo , Zhu, Nian , Huo, Huixia , Long, Junqi , Ji, Xinchan , Li, Jinmeng et al. A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer . | JOURNAL OF ONCOLOGY , 2022 , 2022 . |
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Abstract ：
With the continuous development of bioinformatics, traditionally biological sequence analysis methods are insufficient to deal with the increasingly complex and huge biological data. In the face of this situation, deep learning has been gradually applied in biological analysis and made a series of progresses, which has become a hot research topic in biological data analysis with its advantages in processing high-dimensional data. The current research status was reviewed to better understand the new development of deep learning in the field of bioinformatics data analysis. First, the importance of applying deep learning were introduced. Second, representative deep learning models in the current application fields was described. Then, the application research status of deep learning in this field was analyzed. Finally, current limitations of deep learning in the bioinformatics field and the factors that should be considered in future development were illustrated in this paper. © 2022, Editorial Department of Journal of Beijing University of Technology. All right reserved.
Keyword ：
Bioinformatics; Biological sequences analysis; Deep learning; Gene; Nucleic acid; Protein Bioinformatics; Biological sequences analysis; Deep learning; Gene; Nucleic acid; Protein
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| GB/T 7714 | Zhang, J. , Wang, Z. , Liu, B. . Progress in the Applications of Deep Learning in Biological Sequences Analysis [深度学习在生物序列分析领域的应用进展] [J]. | Journal of Beijing University of Technology , 2022 , 48 (8) : 878-887 . |
| MLA | Zhang, J. et al. "Progress in the Applications of Deep Learning in Biological Sequences Analysis [深度学习在生物序列分析领域的应用进展]" . | Journal of Beijing University of Technology 48 . 8 (2022) : 878-887 . |
| APA | Zhang, J. , Wang, Z. , Liu, B. . Progress in the Applications of Deep Learning in Biological Sequences Analysis [深度学习在生物序列分析领域的应用进展] . | Journal of Beijing University of Technology , 2022 , 48 (8) , 878-887 . |
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Abstract ：
Upper limb kinematic analysis that has been employed in the clinical assessment of motion functions or rehabilitation training is traditionally tested manually with a goniometer. Nowadays, it is a trend to deploy different technology and devices including low-cost but accurate RGB cameras in order to save manual efforts. Among these, a new method using deep learning-based cameras has been investigated to provide the same ease and accessibility as a manual handheld goniometer. The key to measuring upper limb Range of Motion (ROM) using a camera is to estimate upper limb joints accurately. Many existing joint estimation algorithms focus on improving the accuracy performance but put the efficiency concerns aside. It is still challenging to apply those algorithms to low-capacity and budget-friendly devices, which is highly demanding in clinical scenarios. We propose a lightweight and fast deep learning model to estimate human pose and then use predicted joints to measure the range of motion for upper limb joints. Unlike other human pose estimation methods that learn and predict all major joints of the human body, the proposed model only focuses on the upper limb, which improves the accuracy and reduces the overhead of prediction. To further reduce model size and latency, our model is based on a compact neural network architecture, and parameters in the network are quantized to 8-bit precision. As a result, our model runs 4.1 times faster and is 15.5 times smaller compared with a full sized state of the art human pose estimation model. The proposed method is further evaluated on different upper limb functional tasks. Results show that our new method achieves a satisfying accuracy in ROM measurement and a high degree of agreement with a goniometer. Compared with the goniometer to measure ROM, our presented method is easier to operate and can be performed remotely, while still retaining good accuracy.
Keyword ：
2D body estimate 2D body estimate low-capacity device low-capacity device range of motion range of motion quantized convolutional neural network quantized convolutional neural network deep learning deep learning
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| GB/T 7714 | Yan, Xuke , Zhang, Linxi , Liu, Bo et al. A Lightweight and Fast Approach for Upper Limb Range of Motion Assessment [J]. | 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA , 2022 : 53-60 . |
| MLA | Yan, Xuke et al. "A Lightweight and Fast Approach for Upper Limb Range of Motion Assessment" . | 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA (2022) : 53-60 . |
| APA | Yan, Xuke , Zhang, Linxi , Liu, Bo , Qu, Guangzhi . A Lightweight and Fast Approach for Upper Limb Range of Motion Assessment . | 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA , 2022 , 53-60 . |
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Abstract ：
针对服务计算、物联网、云计算、服务互联网、工业互联网、数字智慧服务等新兴产业对具有原始创新能力的软件设计人才需求，探讨如何围绕软件设计核心价值体系进行本科软件设计与体系结构课程内容建设及实践环节创新，提出以“知识型工程创新设计(KEID)”为核心价值的课程知识体系结构并介绍以开放式领域建模为基础的创新性实践环节设计。
Keyword ：
软件体系结构 软件体系结构 KIIC实践环节设计 KIIC实践环节设计 知识型工程创新设计(KEID) 知识型工程创新设计(KEID) 开放式领域建模 开放式领域建模
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| GB/T 7714 | 张建 , 刘博 , 朱青 et al. 软件设计与体系结构课程内容建设及创新探索 [J]. | 计算机教育 , 2022 , PageCount-页数: 5 (07) : 62-66 . |
| MLA | 张建 et al. "软件设计与体系结构课程内容建设及创新探索" . | 计算机教育 PageCount-页数: 5 . 07 (2022) : 62-66 . |
| APA | 张建 , 刘博 , 朱青 , 张丽 . 软件设计与体系结构课程内容建设及创新探索 . | 计算机教育 , 2022 , PageCount-页数: 5 (07) , 62-66 . |
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| GB/T 7714 | Liu, Bo , Ji, Xinchan , Li, Jinmeng et al. Integrative analysis identifies three molecular subsets in ovarian cancer [J]. | CLINICAL AND TRANSLATIONAL MEDICINE , 2022 , 12 (9) . |
| MLA | Liu, Bo et al. "Integrative analysis identifies three molecular subsets in ovarian cancer" . | CLINICAL AND TRANSLATIONAL MEDICINE 12 . 9 (2022) . |
| APA | Liu, Bo , Ji, Xinchan , Li, Jinmeng , Zhu, Nian , Long, Junqi , Zhuang, Xujie et al. Integrative analysis identifies three molecular subsets in ovarian cancer . | CLINICAL AND TRANSLATIONAL MEDICINE , 2022 , 12 (9) . |
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Abstract ：
本发明公开了基于节点级嵌入特征三维关系重建的图数据相似度方法，属于深度学习领域，首先通过孪生图卷积层和相似节点交互模块生成节点级嵌入特征三维关系，然后将节点级嵌入特征三维关系经过三维卷积提取特征，将三维特征经过Flatten层展开为一维，获得最终节点级关系向量。这一关系向量输入到由全连接层构成的结果输出模块得到预测输出。这一预测输出与实际的标签值进行比较，通过损失函数和反向传播算法对整体模型参数进行更新以达到学习的目的。完成训练的DeepSIM‑3D模型能高效可靠地计算输入的两个图结构数据的相似度。
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| GB/T 7714 | 刘博 , 武嘉慧 , 王志晗 et al. 基于节点级嵌入特征三维关系重建的图数据相似度方法 : CN202210059012.6[P]. | 2022-01-18 . |
| MLA | 刘博 et al. "基于节点级嵌入特征三维关系重建的图数据相似度方法" : CN202210059012.6. | 2022-01-18 . |
| APA | 刘博 , 武嘉慧 , 王志晗 , 张冀东 . 基于节点级嵌入特征三维关系重建的图数据相似度方法 : CN202210059012.6. | 2022-01-18 . |
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Abstract ：
In this experiment, three replicated SBR reactors were operated using asynchronous acclimation of the phased method (A/O-A/O/A), simultaneous domestication of continuous aeration by A/O/A, and simultaneous domestication of intermittent aeration by A/O/A. Using artificial water distribution as the influent substrate, flocculent sludge was inoculated and granulated by hydraulic selection. The domestication and nitrogen and phosphorus removal characteristics of shortcut nitrification denitrifying phosphorus removal granules under different operation modes were assessed. The results show that simultaneous domestication of intermittent aeration by A/O/A has the most efficient under the combination of short aeration time (140 min) and low aeration strength[3.5 L·(h·L)-1]. The average removal rates of carbon, nitrogen, and phosphorus were 90.74%, 91.15%, and 95.66%, respectively, which could achieve synchronous removal during later stable operation. The particle size was 895 μm, and the particles were small but uniformly dense in microscope observations. The f value (MLVSS/MLSS) was kept stable at 0.8-0.85 and sludge had a high biomass due to the alternate aerobic/anoxic operation with intermittent aeration. This supported anoxic heterotrophic bacteria at the core of the particles, which was conducive to the stability of the granular sludge structure. Batch experiments showed that the specific ammonia-oxidation rate of the simultaneous domestication of intermittent aeration by A/O/A system was 3.38 mg·(g·h)-1, and denitrifying phosphate accumulating organisms (DPAOs) able to utilize nitrite as electron acceptor accounted for 65.46%. This was more conducive to the simultaneous domestication and enrichment of ammonia-oxidizing bacteria (AOB) and NO2--type DPAOs, ensuring a stable treatment effect.
Keyword ：
short-cut nitrification denitrifying phosphorus removal short-cut nitrification denitrifying phosphorus removal aeration time aeration time intermittent aeration intermittent aeration granules sludge granules sludge aeration intensity aeration intensity simultaneous domestication simultaneous domestication
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| GB/T 7714 | Wang Wen-Qi , Li Dong , Gao Xin et al. [Simultaneous Domestication of Short-cut Nitrification Denitrifying Phosphorus Removal Granules]. [J]. | Huanjing kexue , 2021 , 42 (6) : 2946-2956 . |
| MLA | Wang Wen-Qi et al. "[Simultaneous Domestication of Short-cut Nitrification Denitrifying Phosphorus Removal Granules]." . | Huanjing kexue 42 . 6 (2021) : 2946-2956 . |
| APA | Wang Wen-Qi , Li Dong , Gao Xin , Liu Bo , Zhang Jie . [Simultaneous Domestication of Short-cut Nitrification Denitrifying Phosphorus Removal Granules]. . | Huanjing kexue , 2021 , 42 (6) , 2946-2956 . |
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Abstract ：
To overcome the performance bottlenecks (e.g. power consumption and bandwidth) of electrical packet switching based data center networks, Optical Circuit Switching(OCS) technology has been widely studied recently, aiming at constructing the next-generation data center and carrying the ever-increasing network traffic. To achieve this goal, how to effectively handle the emerging application-level communication in nowadays data centers, i.e. how to adapt OCS to various of traffic flows, has turned to one of the crucial topics in this area. In this paper, we summarize the state-of-the-art works that focus on the flow schedule problems in OCS based data center networks and further introduce the future directions. The scope of this paper includes the schedule problems on unicast-flows, multicast-flows, and co-flows, which are denoted as *-flows in this paper, and are the major traffic patterns in the modern data center networks. The purpose of this paper is to present a broad research guideline for the *-flow scheduling of OCS, and motivate researchers to develop more innovative proposals and algorithms.
Keyword ：
Optical network Optical network Optical circuit switching Optical circuit switching Data center network Data center network Flow schedule Flow schedule
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| GB/T 7714 | Tang, Yinan , Yuan, Tongtong , Liu, Bo et al. Effective *-flow schedule for optical circuit switching based data center networks: A comprehensive survey [J]. | COMPUTER NETWORKS , 2021 , 197 . |
| MLA | Tang, Yinan et al. "Effective *-flow schedule for optical circuit switching based data center networks: A comprehensive survey" . | COMPUTER NETWORKS 197 (2021) . |
| APA | Tang, Yinan , Yuan, Tongtong , Liu, Bo , Xiao, Chuangbai . Effective *-flow schedule for optical circuit switching based data center networks: A comprehensive survey . | COMPUTER NETWORKS , 2021 , 197 . |
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Abstract ：
对深度学习模型应用于时空序列预测的最新进展进行总结.首先介绍时空序列数据的属性及类型,并进行相应的实例化与表示.接着针对时空序列数据存在的3个问题分别提出相应的数据预处理方法,对基于传统参数模型、传统机器学习模型以及深度学习模型的时空序列预测方法逐一阐述并对比分析,为研究者选择模型提供指导,之后总结深度学习模型在不同领域内对时空序列预测的应用.最后指出当前研究的不足以及时空序列预测进一步的研究方向.
Keyword ：
循环神经网络 循环神经网络 时空序列数据 时空序列数据 时空序列预测 时空序列预测 深度学习 深度学习 特征选择 特征选择 卷积神经网络 卷积神经网络
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| GB/T 7714 | 刘博 , 王明烁 , 李永 et al. 深度学习在时空序列预测中的应用综述 [J]. | 北京工业大学学报 , 2021 , 47 (8) : 925-941 . |
| MLA | 刘博 et al. "深度学习在时空序列预测中的应用综述" . | 北京工业大学学报 47 . 8 (2021) : 925-941 . |
| APA | 刘博 , 王明烁 , 李永 , 陈洪丽 , 李建强 . 深度学习在时空序列预测中的应用综述 . | 北京工业大学学报 , 2021 , 47 (8) , 925-941 . |
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Abstract ：
In this paper, we studied infrared (IR) maritime salient object detection based on convolutional neural networks (CNNs). There are mainly two contributions. Firstly, we constructed a large extended IR ship image dataset (ExtIRShip) for salient maritime target detection, including 9,123 labelled IR images. Secondly, we proposed a global guided lightweight non-local depth feature (DG-Light-NLDF) model. We introduced Dilated Linear Bottleneck (DLB) to replace the standard convolution and adding a simplified global module to provide the location information of the potential salient object, the proposed method can significantly improve the efficiency of Light-NLDF. Experimental results demonstrate that the proposed DG-Light-NLDF model could detect IR maritime salient objects more accurately with less parameters. In addition, comparison experiments between two datasets validated that the larger dataset is also much more beneficial in improving saliency detection performance. © 2021 Elsevier B.V.
Keyword ：
Large dataset Large dataset Object recognition Object recognition Ships Ships Convolution Convolution Neural networks Neural networks Object detection Object detection Infrared imaging Infrared imaging Feature extraction Feature extraction
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| GB/T 7714 | Liu, Zhaoying , Zhang, Xuesi , Jiang, Tianpeng et al. Infrared salient object detection based on global guided lightweight non-local deep features [J]. | Infrared Physics and Technology , 2021 , 115 . |
| MLA | Liu, Zhaoying et al. "Infrared salient object detection based on global guided lightweight non-local deep features" . | Infrared Physics and Technology 115 (2021) . |
| APA | Liu, Zhaoying , Zhang, Xuesi , Jiang, Tianpeng , Zhang, Ting , Liu, Bo , Waqas, Muhammad et al. Infrared salient object detection based on global guided lightweight non-local deep features . | Infrared Physics and Technology , 2021 , 115 . |
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