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A model of calcium signaling and degranulation dynamics induced by laser irradiation in mast cells

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Chinese Science Bulletin 2008年第15期53卷 2315-2325页

作者： SHI XiaoMin ZHENG YuFan LIU ZengRong yang wenzhong Institute of Systems Science Shanghai University Shanghai 200444 China Institute of Systems Biology Shanghai University Shanghai 200444 China Department of Physics Fudan University Shanghai 200433 China

Recent experiments show that calcium signaling and degranulation dynamics induced by low power laser irradiation in mast cells must rely on extracellular Ca2+ influx. An analytical expression of Ca2+ flux through TRPV4 cation channel in response to interaction of laser photon energy and extracellular Ca2+ is deduced, and a model characterizing dynamics of calcium signaling and degranulation activated by laser irradiation in mast cells is established. The model indicates that the characteristics of calcium signaling and degranulation dynamics are determined by interaction between laser photon energy and Ca2+ influx. Extracellular Ca2+ concentration is so high that even small photon energy can activate mast cells, thus avoiding the possible injury caused by laser irradiation with shorter wavelengths. The model predicts that there exists a narrow parameter domain of photon energy and extracellular Ca2+ concen-tration of which results in cytosolic Ca2+ limit cycle oscillations, and shows that PKC activity is in direct proportion to the frequency of Ca2+ oscillations. With the model it is found that sustained and stable maximum plateau of cytosolic Ca2+ concentration can get optimal degranulation rate. Furthermore, the idea of introducing the realistic physical energy into model is applicable to modeling other physical signal transduction systems.

关键词：激光钙肥大细胞 TRPV4渠道动态模式

DFE-GCN: Dual Feature Enhanced Graph Convolutional Network for Controversy Detection

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Computers, Materials & Continua 2023年第10期77卷 893-909页

作者： Chengfei Hua wenzhong yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Software Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur Autonomous Region Xinjiang UniversityUrumqi830000China Key Laboratory of Multilingual Information Technology in Xinjiang Uygur Autonomous Region Xinjiang UniversityUrumqi830000China

With the development of social media and the prevalence of mobile devices,an increasing number of people tend to use social media platforms to express their opinions and attitudes,leading to many online *** online controversies can severely threaten social stability,making automatic detection of controversies particularly *** controversy detection methods currently focus on mining features from text semantics and propagation ***,these methods have two drawbacks:1)limited ability to capture structural features and failure to learn deeper structural features,and 2)neglecting the influence of topic information and ineffective utilization of topic *** light of these phenomena,this paper proposes a social media controversy detection method called Dual Feature Enhanced Graph Convolutional Network(DFE-GCN).This method explores structural information at different scales from global and local perspectives to capture deeper structural features,enhancing the expressive power of structural ***,to strengthen the influence of topic information,this paper utilizes attention mechanisms to enhance topic features after each graph convolutional layer,effectively using topic *** validated our method on two different public datasets,and the experimental results demonstrate that our method achieves state-of-the-art performance compared to baseline *** the Weibo and Reddit datasets,the accuracy is improved by 5.92%and 3.32%,respectively,and the F1 score is improved by 1.99%and 2.17%,demonstrating the positive impact of enhanced structural features and topic features on controversy detection.

关键词： Controversy detection graph convolutional network feature enhancement social media

GRATDet:Smart Contract Vulnerability Detector Based on Graph Representation and Transformer

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Computers, Materials & Continua 2023年第8期76卷 1439-1462页

作者： Peng Gong wenzhong yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Information Science and Engineering Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur Autonomous Region Xinjiang UniversityUrumqi830000China Key Laboratory of Multilingual Information Technology in Xinjiang Uygur Autonomous Region Xinjiang UniversityUrumqi830000China

Smart contracts have led to more efficient development in finance and healthcare,but vulnerabilities in contracts pose high risks to their future *** current vulnerability detection methods for contracts are either based on fixed expert rules,which are inefficient,or rely on simplistic deep learning techniques that do not fully leverage contract semantic ***,there is ample room for improvement in terms of detection *** solve these problems,this paper proposes a vulnerability detector based on deep learning techniques,graph representation,and Transformer,called *** method first performs swapping,insertion,and symbolization operations for contract functions,increasing the amount of small sample *** line of code is then treated as a basic semantic element,and information such as control and data relationships is extracted to construct a new representation in the form of a Line Graph(LG),which shows more structural features that differ from the serialized presentation of the ***,the node information and edge information of the graph are jointly learned using an improved Transformer-GP model to extract information globally and locally,and the fused features are used for vulnerability *** effectiveness of the method in reentrancy vulnerability detection is verified in experiments,where the F1 score reaches 95.16%,exceeding stateof-the-art methods.

关键词： Vulnerability detection smart contract graph representation deep learning source code

The Detection of Fraudulent Smart Contracts Based on ECA-EfficientNet and Data Enhancement

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Computers, Materials & Continua 2023年第12期77卷 4073-4087页

作者： Xuanchen Zhou wenzhong yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Software Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur Autonomous Region Urumqi830000China Key Laboratory of Multilingual Information Technology in Xinjiang Uygur Autonomous Region Urumqi830000China

With the increasing popularity of Ethereum,smart contracts have become a prime target for fraudulent activities such as Ponzi,honeypot,gambling,and phishing *** some researchers have studied intelligent fraud detection,most research has focused on identifying Ponzi contracts,with little attention given to detecting and preventing gambling or phishing *** are three main issues with current ***,there exists a severe data imbalance between fraudulent and non-fraudulent ***,the existing detection methods rely on diverse raw features that may not generalize well in identifying various classes of fraudulent ***,most prior studies have used contract source code as raw features,but many smart contracts only exist in *** address these issues,we propose a fraud detection method that utilizes Efficient Channel Attention EfficientNet(ECA-EfficientNet)and data *** method begins by converting bytecode into Red Green Blue(RGB)three-channel images and then applying channel exchange data *** then use the enhanced ECA-EfficientNet approach to classify fraudulent smart contract RGB *** proposed method achieves high F1-score and Recall on both publicly available Ponzi datasets and self-built multi-classification datasets that include Ponzi,honeypot,gambling,and phishing smart *** results of the experiments demonstrate that our model outperforms current methods and their variants in Ponzi contract *** research addresses a significant problem in smart contract security and offers an effective and efficient solution for detecting fraudulent contracts.

关键词： Fraud detection smart contract ECA-EfficientNet Ethereum

Clinical Manifestation and Laboratory Characteristics of SARS-CoV-2Infection in Pregnant Women

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Virologica Sinica 2020年第3期35卷 305-310页

作者： Chunchen Wu wenzhong yang Xiaoxue Wu Tianzhu Zhang Yaoyao Zhao Wei Ren Jianbo Xia Department of Laboratory Medicine Maternal and Child Health Hospital of Hubei ProvinceWuhan 430070China Department of Radiology Maternal and Child Health Hospital of Hubei ProvinceWuhan 430070China Department of Obstetrics Maternal and Child Health Hospital of Hubei ProvinceWuhan 430070China

The severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) epidemic has become a major challenge to public health in China and other countries, considering its pathogenicity across all age groups. Pregnancy is a unique physiological condition, and is characterized by altered immunity and elevated hormone levels to actively tolerate the semiallogeneic fetus, which undergoes a sudden and substantial fluctuation during the immediate postpartum period. Changes in clinical features, laboratory characteristics, and imaging features of pregnant women during the pre-partum and postpartum periods require further elucidation. Here, we retrospectively analyzed the clinical features, laboratory characteristics, and imaging features of eight pregnant cases of SARS-CoV-2 infection during the pre-partum and post-partum periods. Our results showed that four of the eight pregnant women were asymptomatic before delivery but became symptomatic post-partum. Correspondingly, white blood cell(WBC) counts increased and lymphocyte(LYMPH) counts decreased. C-reactive protein(CRP) levels in the serum also increased to a higher level than those in general ***, it is imperative to closely monitor laboratory parameters including the WBC count, LYMPH count, and CRP,along with other imaging features in chest CT scans, to promptly prevent, diagnose, and treat a SARS-CoV-2 infection during pregnancy.

关键词： SARS-CoV-2 Pregnant women Clinical manifestation Laboratory characteristics Immunity

Study on nitrile-degrading microorganisms

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Journal of Environmental Sciences 1991年第3期3卷 91-97页

作者： Li wenzhong, Zhang Hongyi and yang HuifangInstitute of Microbiology,Academia Sinica,Beijing 100080,China

Two strains of bacteria were isolated from nitrile polluted soils, and identified as Corynebacterium boffmanii and Arthrobacter flavescens. Acetonitrile, propionitrile, butyronitrile and acrylonitrile were degraded by these bacteria to yield corresponding amides, carboxylic acids and ammonia. The nitrile-degrading abilities of these strains were investigated. The removal rates for the nitrile were nearly 100%, after these bacteria were grown in medium containing 10000 ppm of aceto-, propio-, or butyronitrile at 28 ℃ for 24h. When the reaction mkture consisting of 5000 ppm of above mentioned nitriles or acrylonitrile and 20g (dry cell) /L resting cells of the two strains in 0.06mol/L phosphate buffer (pH7.5) was incubated separately at 25 ℃ with moderate shaking for 15 or 45 min, the nitrile could be degraded completely. The optimum growth conditions for *** and *** were studied as well.

关键词： nitrile microbial degradation microorganisms.

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在唐山地震中生命线系统的破坏及其恢复

地震工程与工程振动 2006年第3期26卷 184-185页

作者：杨文忠唐山学院河北唐山063000

1976年的大地震,使唐山的生命线系统遭到极其严重的破坏。震后,生命线系统迅速恢复,特别是通讯、供水、电力、铁路、公路的恢复。这些对救灾工作的开展至关重要。

关键词：地震灾害生命线应急救灾

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沪宁线轨道不平顺谱的分析

同济大学学报（自然科学版） 2007年第10期35卷 1342-1346页

作者：练松良刘扬杨文忠同济大学道路与交通工程教育部重点实验室上海200092

对国外不平顺标准谱和我国轨道不平顺统计谱进行对比,根据沪宁线的线路不平顺检测数据进行谱分析,得出沪宁线的轨道不平顺谱与美国5级铁路的不平顺谱相接近,但方向不平顺谱值较大.利用相干函数分析轨道不平顺与车体垂向和水平振动之间... 详细信息

对国外不平顺标准谱和我国轨道不平顺统计谱进行对比,根据沪宁线的线路不平顺检测数据进行谱分析,得出沪宁线的轨道不平顺谱与美国5级铁路的不平顺谱相接近,但方向不平顺谱值较大.利用相干函数分析轨道不平顺与车体垂向和水平振动之间的关系,得出垂向振动有两个主要振动频率,其中一个频率的振动与轨道不平顺相干度较高,车体水平振动加速度有一个振动主频,也与轨道的水平不平顺具有较高的相干性.最后,建议将轨道不平顺谱作为控制轨道质量的指标之一.

关键词：铁路轨道不平顺谱分析

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轨道不平顺功率谱拟合分析方法

同济大学学报（自然科学版） 2006年第3期34卷 363-367页

作者：杨文忠练松良刘扬同济大学道路与交通工程教育部重点实验室上海200092

对国内外轨道不平顺谱作了简要的对比,并对实测轨道不平顺谱及其拟合谱的分析方法作了较为详细的介绍.首先说明了功率谱分析的必要性;然后就国内外不同的标准谱进行比较,再次,介绍了数据处理软件对功率谱的基本算法,并重点介绍了拟合谱... 详细信息

对国内外轨道不平顺谱作了简要的对比,并对实测轨道不平顺谱及其拟合谱的分析方法作了较为详细的介绍.首先说明了功率谱分析的必要性;然后就国内外不同的标准谱进行比较,再次,介绍了数据处理软件对功率谱的基本算法,并重点介绍了拟合谱的计算方法;最后,结合沪杭线的实例,利用该软件将实测数据拟合成功率谱,并与国内外现有的功率谱进行对比分析.

关键词：铁路轨道不平顺功率谱分析