检索结果-南通市图书馆

Combination of AAV-delivered tumor suppressor PTEN with anti-PD-1 loaded depot gel for enhanced antitumor immunity

Acta Pharmaceutica Sinica B 2024年第1期14卷 350-364页

作者： Yongshun zhang Lan Yang yangsen Ou Rui Hu Guangsheng Du Shuang Luo Fuhua Wu Hairui Wang Zhiqiang Xie Yu zhang Chunting He Cheng Ma Tao Gong Ling zhang Zhirong zhang Xun Sun Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial TechnologyWest China School of PharmacySichuan UniversityChengdu 610041China Med-X Center for Materials College of Polymer Science and EngineeringSichuan UniversityChengdu 610065China

Recent clinical studies have shown that mutation of phosphatase and tensin homolog deleted on chromosome 10(PTEN)gene in cancer cells may be associated with immunosuppressive tumor microenvironment(TME)and poor response to immune checkpoint blockade(ICB)therapy.Therefore,efficiently restoring PTEN gene expression in cancer cells is critical to improving the responding rate to ICB therapy.Here,we screened an adeno-associated virus(AAV)capsid for efficient PTEN gene delivery into B16F10 tumor cells.We demonstrated that intratumorally injected AAV6-PTEN successfully restored the tumor cell PTEN gene expression and effectively inhibited tumor progression by inducing tumor cell immunogenic cell death(ICD)and increasing immune cell infiltration.Moreover,we developed an anti-PD-1 loaded phospholipid-based phase separation gel(PPSG),which formed an in situ depot and sustainably release anti-PD-1 drugs within 42 days in vivo.In order to effectively inhibit the recurrence of melanoma,we further applied a triple therapy based on AAV6-PTEN,PPSG^(@anti-PD-1)and CpG,and showed that this triple therapy strategy enhanced the synergistic antitumor immune effect and also induced robust immune memory,which completely rejected tumor recurrence.We anticipate that this triple therapy could be used as a new tumor combination therapy with stronger immune activation capacity and tumor inhibition efficacy.

关键词： Triple therapy Adeno-associated virus PTEN PPSG@anti-PD-1 CpG Immunogenic cell death Antitumor immune response Immune memory

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Knowledge Graph Completion Based on GCN of Multi-Information Fusion and High-Dimensional Structure Analysis Weight

引用

Chinese Journal of Electronics 2022年第2期31卷 387-396页

作者： NIU Haoran HE Haitao FENG Jianzhou NIE Junlan zhang yangsen REN Jiadong Yanshan University Beijing Information Science and Technology University

Knowledge graph completion(KGC) can solve the problem of data sparsity in the knowledge graph. A large number of models for the KGC task have been proposed in recent years. However, the underutilisation of the structure information around nodes is one of the main problems of the previous KGC model, which leads to relatively single encoding information. To this end, a new KGC model that encodes and decodes the feature information is proposed. First, we adopt the subgraph sampling method to extract node structure.Moreover, the graph convolutional network(GCN) introduced the channel attention convolution encode node structure features and represent them in matrix form to fully mine the node feature information. Eventually, the high-dimensional structure analysis weight decodes the encoded matrix embeddings and then constructs the scoring function. The experimental results show that the model performs well on the datasets used.

关键词： Knowledge graph completion Graph convolutional network Channel attention convolution High-dimensional structure analysis weight

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

A Model for Chinese Named Entity Recognition Based on Global Pointer and Adversarial Learning

引用

Chinese Journal of Electronics 2023年第4期32卷 854-867页

作者： zhang yangsen LI Jianlong XIN Yonghui ZHAO Xiquan LIU Yang Institute of Intelligent Information Processing Beijing Information Science and Technology University Computer Network Emergency Response Technical Team Coordination Center of China

To solve the problem that the Chinese named entity recognition(NER) models have poor antiinterference ability and inaccurate entity boundary recognition, this paper proposes the RGP-with-FGM model which is based on global pointer and adversarial learning.Firstly, the RoBERTa-WWM model is used to optimize the semantic representation of the text, and fast gradient method is used to add perturbation to the word embedding layer to enhance the robustness of the model. Then,BiG RU is used to focus on the timing information of Chinese characters to enhance the semantic connection.Finally, the global pointer is constructed in the decoding layer to obtain more accurate entity boundary recognition results. In order to verify the effectiveness of the model proposed in this paper, we construct Uyghur names dataset(UHND) to train the Chinese NER model, and perform extensive experiments with public Chinese NER data sets. Experimental results show that for UHND, the F1 value is 95.12%, which is 3.09% higher than that of the RoB ERTa-WWM-BiG RU-CRF model. For the Resume data set, the Precision and F1 value are 96.28% and 96.10%respectively.

关键词： Chinese named entity recognition (NER) Global pointer RoBERTa-WWM model Fast gradient method (FGM) BiGRU

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Vision-Based Human Body Posture Correction System

引用

Mechanical Engineering Science 2024年第1期6卷 1-7页

作者： yangsen QIU Yukun WANG Yuchen WU Xinyi QIANG Yunzuo zhang School of Information science and Technology Shijiazhuang Tiedao UniversityShijiazhuangHebei050043China

With the development of technology and the progress of life,more and more people,regardless of entertainment,learning,or work,cannot do without computer desks and cannot put down their mobile phones.Due to prolonged sitting and often neglecting the importance of posture,incorrect posture can often lead to health problems such as hunchback,lumbar muscle strain,and shoulder and neck pain over time.To address this issue,we designed a computer vision-based human body posture detection system.The system utilizes YOLOv8 technology to accurately locate key points of the human body skeleton,and then analyzes the coordinate positions and depth information of these key points to establish a criterion for distinguishing different postures.With the assistance of an SVM classifier,the system achieves an average recognition rate of 95%.Finally,we successfully deployed the posture detection system on Raspberry Pi hardware and conducted extensive testing.The test results demonstrate that the system can effectively detect various postures and provide real-time reminders to users to correct poor posture,demonstrating good practicality and stability.

关键词： computer vision human posture deep learning image processing

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Study of Sentiment Classification for Chinese Microblog Based on Recurrent Neural Network

引用

Chinese Journal of Electronics 2016年第4期25卷 601-607页

作者： zhang yangsen JIANG Yuru TONG Yixuan Institute of Intelligent Information Processing Beijing Information Science and Technology University

The sentiment classification of Chinese Microblog is a meaningful topic.Many studies has been done based on the methods of rule and word-bag,and to understand the structure information of a sentence will be the next target.We proposed a sentiment classification method based on Recurrent neural network(RNN).We adopted the technology of distributed word representation to construct a vector for each word in a sentence;then train sentence vectors with fixed dimension for different length sentences with RNN,so that the sentence vectors contain both word semantic features and word sequence features;at last use softmax regression classifier in the output layer to predict each sentence’s sentiment orientation.Experiment results revealed that our method can understand the structure information of negative sentence and double negative sentence and achieve better accuracy.The way of calculating sentence vector can help to learn the deep structure of sentence and will be valuable for different research area.

关键词： Recurrent neural network(RNN) Distributed representation Sentiment classification Sentence vector

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Multi-feature-Based Subjective-Sentence Classification Method for Chinese Micro-blogs

引用

Chinese Journal of Electronics 2017年第6期26卷 1111-1117页

作者： zhang yangsen zhang Yaorong JIANG Yuru HUANG Gaijuan Beijing Information and Technology University

The accurate classification of subjective and objective sentences is important in the preparation for micro-blog sentiment analysis. Since a single feature type cannot provide enough subjective information for classification, we propose a Support vector machine(SVM)-based classification model for Chinese micro-blogs using multiple features. We extracted the subjective features from the Part of speech(POS) and the dependency relationship between words, and constructed a 3-POS subjective pattern set and a dependency template set. We fused these two types of features and used an SVM-based model to classify Chinese micro-blog text. The experimental results showed that the performance of the classification model improved remarkably when using multiple features.

关键词： Micro-blog sentiment analysis Subjective and objective classification Support vector machine(SVM) 3-POS subjective pattern set Dependency template set

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

基于工业大数据的重叠社区发现算法

引用

计算机集成制造系统 2024年第6期30卷 2130-2138页

作者：康海燕景悟张仰森北京信息科技大学信息管理学院北京100192

为了深入挖掘和分析工业大数据隐藏的关系、趋势和模式,从而为企业提供更好的决策依据,结合随机游走和标签传播思想,提出一种基于工业大数据的重叠社区发现算法。设计了种子节点选取算法,通过随机游走计算各节点的重要性,选出不相关和... 详细信息

为了深入挖掘和分析工业大数据隐藏的关系、趋势和模式,从而为企业提供更好的决策依据,结合随机游走和标签传播思想,提出一种基于工业大数据的重叠社区发现算法。设计了种子节点选取算法,通过随机游走计算各节点的重要性,选出不相关和重要性高的种子节点;提出重叠社区发现算法,对种子节点赋予唯一标签,迭代进行标签传播直到节点标签不再改变,根据节点标签得到最终的重叠社区划分结果。通过在真实数据集和人工数据集上进行对比实验表明,该算法可以在网络上有效发现高质量的重叠社区,并进一步解决工业大数据的数据分析、信息挖掘等核心问题。

关键词：工业大数据社区发现重叠社区随机游走标签传播

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A Text Sentiment Classification Modeling Method Based on Coordinated CNN-LSTM-Attention Model

引用

Chinese Journal of Electronics 2019年第1期28卷 120-126页

作者： zhang yangsen ZHENG Jia JIANG Yuru HUANG Gaijuan CHEN Ruoyu Institute of Intelligent Information Processing Beijing Information Science and Technology University Beijing Laboratory of National Economic Security Early-Warning Engineering

The major challenge that text sentiment classification modeling faces is how to capture the intrinsic semantic, emotional dependence information and the key part of the emotional expression of text. To solve this problem, we proposed a Coordinated CNNLSTM-Attention(CCLA) model. We learned the vector representations of sentence with CCLA unit. Semantic and emotional information of sentences and their relations are adaptively encoded to vector representations of document.We used softmax regression classifier to identify the sentiment tendencies in the text. Compared with other methods, the CCLA model can well capture the local and long distance semantic and emotional information.Experimental results demonstrated the effectiveness of CCLA model. It shows superior performances over several state-of-the-art baseline methods.

关键词： Coordinated CNN-LSTM-Attention Sentiment analysis Text modeling Semantic information

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

OSFPMiner: An Optimal Weighted Traversal Software Patterns Miner Based on Complex Network

引用

Chinese Journal of Electronics 2020年第2期29卷 255-264页

作者： HE Haitao SHAN Chun HE Hongdou ZHAO Guyu zhang yangsen TIAN Xiangmin College of Information Science and Engineering Yanshan University Beijing Key Laboratory of Software Security Engineering Technique Beijing Institute of Technology School of Information Management Beijing Information Science & Technology University

The weighted traversal pattern is important in software system for a better understanding of the internal structure and behavior of software. To mine important patterns of software, a complex network-based Optimal Software Fault Patterns Miner is presented. By analyzing the multiple execution traces of software and the relations among functions, we establish the Weighted Software Execution Dependency Graph model ultimately.The traversal database is generated through depth-first search strategy and the extraction of software path traversals. According to the downward-closure property,a pruning strategy is adopted by Weighted Frequent Candidate Pattern Tree to cut off more unpromising patterns in advance. A set of important patterns is derived without repeated calculation. The experimental results show that the proposed approach has good performance in the number of weighted frequent candidate patterns and time efficiency.

关键词： Complex network Weighted traversal pattern Upper-bound Pruning

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

融合多粒度语言知识与层级信息的中文命名实体识别模型

引用

计算机应用 2024年第6期44卷 1706-1712页

作者：于右任张仰森蒋玉茹黄改娟北京信息科技大学智能信息处理研究所北京100101

针对当前大多数命名实体识别(NER)模型只使用字符级信息编码且缺乏对文本层次信息提取的问题,提出一种融合多粒度语言知识与层级信息的中文NER(CNER)模型(CMH)。首先,使用经过多粒度语言知识预训练的模型编码文本,使模型能够同时捕获文... 详细信息

针对当前大多数命名实体识别(NER)模型只使用字符级信息编码且缺乏对文本层次信息提取的问题,提出一种融合多粒度语言知识与层级信息的中文NER(CNER)模型(CMH)。首先,使用经过多粒度语言知识预训练的模型编码文本,使模型能够同时捕获文本的细粒度和粗粒度语言信息,从而更好地表征语料;其次,使用ON-LSTM(Ordered Neurons Long Short-Term Memory network)模型提取层级信息,利用文本本身的层级结构信息增强编码间的时序关系;最后,在模型的解码端结合文本的分词信息,并将实体识别问题转化为表格填充问题,以更好地解决实体重叠问题并获得更准确的实体识别结果。同时,为解决当前模型在不同领域中的迁移能力较差的问题,提出通用实体识别的理念,通过筛选多领域的通用实体类型,构建一套提升模型在多领域中的泛化能力的通用NER数据集MDNER(Multi-Domain NER dataset)。为验证所提模型的效果,在数据集Resume、Weibo、MSRA上进行实验,与MECT(Multi-metadata Embedding based Cross-Transformer)模型相比,F1值分别提高了0.94、4.95和1.58个百分点。为了验证所提模型在多领域中的实体识别效果,在MDNER上进行实验,F1值达到了95.29%。实验结果表明,多粒度语言知识预训练、文本层级结构信息提取和高效指针解码器对模型的性能提升至关重要。

关键词：命名实体识别自然语言处理知识图谱构建高效指针通用实体

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：