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| 1 | Washed microbiota transplantation vs.manual fecal microbiota transplantation:clinical findings,animal studies and in vitro screening显示文摘Fecal microbiota transplantation(FMT)by manual preparation has been applied to treat diseases for thousands of years.However,this method still endures safety risks and challenges the psychological endurance and acceptance of doctors,patients and donors.Population evidence showed the washed microbiota preparation with microfiltration based on an automatic purification system followed by repeated centrifugation plus suspension for three times significantly reduced FMT-related adverse events.This washing preparation makes delivering a precise dose of the enriched microbiota feasible,instead of using the weight of stool.Intraperitoneal injection in mice with the fecal microbiota supernatant obtained after repeated centrifugation plus suspension for three times induced less toxic reaction than that by the first centrifugation following the microfiltration.The toxic reactions that include death,the change in the level of peripheral white blood cells,and the proliferation of germinal center in secondary lymphoid follicles in spleen were noted.The metagenomic next-generation sequencing(NGS)indicated the increasing types and amount of viruses could be washed out during the washing process.Metabolomics analysis indicated metabolites with pro-inflammatory effects in the fecal microbiota supernatant such as leukotriene B4,corticosterone,and prostaglandin G2 could be removed by repeated washing.Near-infrared absorption spectroscopy could be served as a rapid detection method to control the quality of the washingprocess.In conclusion,this study for the first time provides evidence linking clinical findings and animal experiments to support that washed microbiota transplantation(WMT)is safer,more precise and more quality-controllable than the crude FMT by manual. | Ting Zhang Gaochen Lu Zhe Zhao Yafei Liu Quan Shen Pan Li Yaoyao Chen Haoran Yin Huiquan Wang Cicilia Marcella Bota Cui Lei Cheng Guozhong Ji Faming Zhang | 2020 | Protein & Cell2020，11，4： | 44 |
| 2 | Student Performance Prediction Based on Behavior Process Similarity显示文摘Student performance prediction plays an important role in improving education quality.Noticing that students'exercise-answering processes exhibit different characteristics according to their different performance levels,this paper aims to mine the performance-related information from students'exercising logs and to explore the possibility of predicting students'performance using such process-characteristic information.A formal model of student-shared exercising processes and its discovery method from students'exercising logs are presented.Several similarity measures between students'individual exercising behavior and student-shared exercising processes are presented.A prediction method of students'performance level considering these similarity measures is explored based on classification algorithms.An experiment on real-life exercise-answering event logs shows the effectiveness of the proposed prediction method. | BAO Yunxia LU Faming WANG Yanxiao ZENG Qingtian LIU Cong | 2020 | Chinese Journal of Electronics2020，29，6： | 3 |
| 3 | Modeling and verification for cross-department collaborative business proces- ses using extended Petri nets显示文摘 | ZENG Qingtian LU Faming LIU Cong | 2015 | IEEE Transaction on Sys- tem Man and Cybernetics : Systems2015，45，2： | 1 |
| 4 | Hierarchy modeling and formal verification of emergency treatment processes显示文摘 | LU Faming ZENG Qingtian BAO Yunxia | 2014 | IEEE Transactions on Systems Man and Cyber- netics: Systems2014，44，2： | 1 |
| 5 | Establishment and Characterization of a High Metastatic Potential in the Peritoneum for Human Gastric Cancer by Orthotopic Tumor Cell Implantation显示文摘 | Feihu Bai Xinning Guo Li Yang Jun Wang Yongquan Shi Faming Zhang Huihong Zhai Yuanyuan Lu Huahong Xie Kaichun Wu Daiming Fan | 2007 | Digestive Diseases and Sciences2007，，6： | 1 |
| 6 | Identifying quasi-2D and 1D electrides in yttrium and scandium chlorides via geometrical identification显示文摘Developing and understanding electron-rich electrides offers a promising opportunity for a variety of electronic and catalytic applications.Using a geometrical identification strategy,here we identify a new class of electride material,yttrium/scandium chlorides Y(Sc)_(x)Cl_(y)(yx<2).Anionic electrons are found in the metal octahedral framework topology.The diverse electronic dimensionality of these electrides is quantified explicitly by quasi-two-dimensional(2D)electrides for[YCl]^(+)∙e−and[ScCl]^(+∙)e−and one-dimensional(1D)electrides for[Y_(2)Cl_(3)]^(+)∙e−,[Sc_(7)Cl_(10)]^(+)∙e−,and[Sc5Cl8]2+∙2e−with divalent metal elements(Sc^(2+):3d^(1) and Y^(2+):4d^(1)).The localized anionic electrons were confined within the inner-layer spaces,rather than inter-layer spaces that are observed in A_(2)B-type 2D electrides,e.g.Ca_(2)N.Moreover,when hydrogen atoms are introduced into the host structures to form YClH and Y2Cl3H,the generated phases transform to conventional ionic compounds but exhibited a surprising reduction of work function,arising from the increased Fermi level energy,contrary to the conventional electrides reported so far.Y_(2C)l_(3) was experimentally confirmed to be a semiconductor with a band gap of 1.14 eV.These results may help to promote the rational design and discovery of new electride materials for further technological applications. | Biao Wan Yangfan Lu Zewen Xiao Yoshinori Muraba Junghwan Kim Dajian Huang Lailei Wu Huiyang Gou Jingwu Zhang Faming Gao Ho-kwang Mao Hideo Hosono | 2018 | npj Computational Materials2018，，1： | 0 |
| 7 | Environmental selection and evolutionary process jointly shape genomic and functional profiles of mangrove rhizosphere microbiomes显示文摘Mangrove reforestation with introduced species has been an important strategy to restore mangrove ecosystem functioning.However,how such activities affect microbially driven methane(CH4),nitrogen(N),and sulfur(S)cycling of rhizosphere microbiomes remains unclear.To understand the effect of environmental selection and the evolutionary process on microbially driven biogeochemical cycles in native and introduced mangrove rhizospheres,we analyzed key genomic and functional profiles of rhizosphere microbiomes from native and introduced mangrove species by metagenome sequencing technologies.Compared with the native mangrove(Kandelia obovata,KO),the introduced mangrove(Sonneratia apetala,SA)rhizosphere microbiome had significantly(p<0.05)higher average genome size(AGS)(5.8 vs.5.5 Mb),average 16S ribosomal RNA gene copy number(3.5 vs.3.1),relative abundances of mobile genetic elements,and functional diversity in terms of the Shannon index(7.88 vs.7.84)but lower functional potentials involved in CH4 cycling(e.g.,mcrABCDG and pmoABC),N2 fixation(nifHDK),and inorganic S cycling(dsrAB,dsrC,dsrMKJOP,soxB,sqr,and fccAB).Similar results were also observed from the recovered Proteobacterial metagenome-assembled genomes with a higher AGS and distinct functions in the introduced mangrove rhizosphere.Additionally,salinity and ammonium were identified as the main environmental drivers of functional profiles of mangrove rhizosphere microbiomes through deterministic processes.This study advances our understanding of microbially mediated biogeochemical cycling of CH_(4),N,and S in the mangrove rhizosphere and provides novel insights into the influence of environmental selection and evolutionary processes on ecosystem functions,which has important implications for future mangrove reforestation. | Xiaoli Yu Qichao Tu Jihua Liu Yisheng Peng Cheng Wang Fanshu Xiao Yingli Lian Xueqin Yang Ruiwen Hu Huang Yu Lu Qian Daoming Wu Ziying He Longfei Shu Qiang He Yun Tian Faming Wang Shanquan Wang Bo Wu Zhijian Huang Jianguo He Qingyun Yan Zhili He | 2023 | mLife2023，2，3： | 0 |
| 8 | Washed microbiota transplantation stopped the deterioration of amyotrophic lateral sclerosis:The first case report and narrative review显示文摘Amyotrophic lateral sclerosis(ALS) is known as a progressive paralysis disorder characterized by degeneration of upper and lower motor neurons, and has an average survival time of three to five years. Growing evidence has suggested a bidirectional link between gut microbiota and neurodegeneration. Here we aimed to report one female case with ALS, who benefited from washed microbiota transplantation(WMT), an improved fecal microbiota transplantation(FMT), through a transendoscopic enteral tube during a 12-month follow-up. Notedly, the accidental scalp trauma the patient suffered later was treated with prescribed antibiotics that caused ALS deterioration. The subsequent rescue WMTs successfully stopped the progression of the disease with a quick improvement. The plateaus and reversals occurred during the whole course of WMT. The stool and blood samples from the first WMT to the last were collected for dynamic microbial and metabolomic analysis. We observed the microbial and metabolomic changing trend consistent with the disease status. This case report for the first time shows the direct clinical evidence on using WMT for treating ALS, indicating that WMT may be the novel treatment strategy for controlling this so-called incurable disease. | Gaochen Lu Quan Wen Bota Cui Qianqian Li Faming Zhang | 2023 | The Journal of Biomedical Research2023，37，1： | 0 |
| 9 | A Survey of Detection Methods for Software Use-After-Free Vulnerability显示文摘Due to the absence of validity detection on pointers and automatic memory rubbish reclaim mechanisms in programming languages such as the C/C++language,software developed in these languages may have many memory safety vulnerabilities,such as Use-After-Free(UAF)vulnerability.An UAF vulnerability occurs when a memory object has been freed,but it can still be accessed through a dangling pointer that points to the object before it is reclaimed.Since UAF vulnerabilities are frequently exploited by malware which may lead to memory data leakage or corruption,much research work has been carried out to detect UAF vulnerabilities.This paper investigates existing UAF detection methods.After comparing and categorizing these methods,an outlook on the future development of UAF detection methods is provided.This has an important reference value for subsequent research on UAF detection. | Faming Lu Mengfan Tang Yunxia Bao Xiaoyu Wang | 2022 | 国际计算机前沿大会会议论文集2022，，2： | 0 |
| 10 | A Survey of Malware Classification Methods Based on Data Flow Graph显示文摘Malware is emerging day by day.To evade detection,many malware obfuscation techniques have emerged.Dynamicmalware detectionmethods based on data flow graphs have attracted much attention since they can deal with the obfuscation problem to a certain extent.Many malware classification methods based on data flow graphs have been proposed.Some of them are based on userdefined features or graph similarity of data flow graphs.Graph neural networks have also recently been used to implement malware classification recently.This paper provides an overview of current data flow graph-based malware classification methods.Their respective advantages and disadvantages are summarized as well.In addition,the future trend of the data flow graph-based malware classification method is analyzed,which is of great significance for promoting the development of malware detection technology. | Tingting Jiang Lingling Cui Zedong Lin Faming Lu | 2022 | 国际计算机前沿大会会议论文集2022，，1： | 0 |
| 11 | Survey of Methods for Time Series Symbolic Aggregate Approximation显示文摘Time series analysis is widely used in the fields of finance, medical, and climate monitoring. However, the high dimension characteristic of time series brings a lot of inconvenience to its application. In order to solve the high dimensionality problem of time series, symbolic representation, a method of time series feature representation is proposed, which plays an important role in time series classification and clustering, pattern matching, anomaly detection and others. In this paper, existing symbolization representation methods of time series were reviewed and compared. Firstly, the classical symbolic aggregate approximation (SAX) principle and its deficiencies were analyzed. Then, several SAX improvement methods, including aSAX, SMSAX, ESAX and some others, were introduced and classified;Meanwhile, an experiment evaluation of the existing SAX methods was given. Finally, some unresolved issues of existing SAX methods were summed up for future work. | Lin Wang Faming Lu Minghao Cui Yunxia Bao | 2019 | 国际计算机前沿大会会议论文集2019，，1： | 0 |
| 12 | Explainable Business Process Remaining Time Prediction Using Reachability Graph显示文摘With the recent advances in the field of deep learning,an increasing number of deep neural networks have been applied to business process prediction tasks,remaining time prediction,to obtain more accurate predictive results.However,existing time prediction methods based on deep learning have poor interpretability,an explainable business process remaining time prediction method is proposed using reachability graph,which consists of prediction model construction and visualization.For prediction models,a Petri net is mined and the reachability graph is constructed to obtain the transition occurrence vector.Then,prefixes and corresponding suffixes are generated to cluster into different transition partitions according to transition occurrence vector.Next,the bidirectional recurrent neural network with attention is applied to each transition partition to encode the prefixes,and the deep transfer learning between different transition partitions is performed.For the visualization of prediction models,the evaluation values are added to the sub-processes of a Petri net to realize the visualization of the prediction models.Finally,the proposed method is validated by publicly available event logs. | CAO Rui ZENG Qingtian NI Weijian LU Faming LIU Cong DUAN Hua | 2023 | Chinese Journal of Electronics2023，32，3： | 0 |
| 13 | Remaining Time Prediction for Business Processes with Concurrency Based on Log Representation显示文摘Remaining time prediction of business processes plays an important role in resource scheduling and plan making.The structural features of single process instance and the concurrent running of multiple process instances are the main factors that affect the accuracy of the remaining time prediction.Existing prediction methods does not take full advantage of these two aspects into consideration.To address this issue,a new prediction method based on trace representation is proposed.More specifically,we first associate the prefix set generated by the event log to different states of the transition system,and encode the structural features of the prefixes in the state.Then,an annotation containing the feature representation for the prefix and the corresponding remaining time are added to each state to obtain an extended transition system.Next,states in the extended transition system are partitioned by the different lengths of the states,which considers concurrency among multiple process instances.Finally,the long short-term memory(LSTM)deep recurrent neural networks are applied to each partition for predicting the remaining time of new running instances.By extensive experimental evaluation using synthetic event logs and reallife event logs,we show that the proposed method outperforms existing baseline methods. | Rui Cao Weijian Ni Qingtian Zeng Faming Lu Cong Liu Hua Duan | 2021 | China Communications2021，18，11： | 0 |
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