|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Molecule simulation for the secondary reactions of fluid catalytic crocking gasoline by the method of structure oriented lumpirg combined with monte carlo 显示文摘 | Yang Bolun Zhou Xiaowei Chen Chun | 2008 | Industrial & Engineering Chemistry Research2008，47，14： | 1 |
| 2 | Modeling and optimization for the secondary reaction of FCC gasoline based on the fuzzy neural network and genetic algorithm显示文摘 | WANG ZHIWEN YANG BOLUN CHEN CHUN | 2007 | Chemical Engineering and Processing2007，46，3： | 1 |
| 3 | Molecule simulation for the secondary reactions of fluid catalytic cracking gasoline by the method of structure oriented lumping combined with Monte Carlo显示文摘 | YANG Bolun ZHOU Xiaowei CHEN Chun | 2008 | Industrial & Engineering Chemistry Research2008，47，14： | 1 |
| 4 | Structure elucidation and NMR assignments for two new quinones from fructus rhodomyrti of Rhodomyrtus tomentosa显示文摘 | Tao Chen Chuguo Yu Bolun Yang | 2011 | Chemistry of Natural Compounds2011，47，4： | 1 |
| 5 | Establishment and solution of eight-lump kinetic model for FCC gasoline secondary reaction using particle swarm optimization 显示文摘 | Chen Chun Yang Bolun Yuan Jun | 2007 | Fuel2007，86，15： | 1 |
| 6 | Kinetic model considering reactant oriented selective deactivation for secondary reactions of fluid catalytic cracking gasoline显示文摘 | Zhou Xiaowei Chen Tao Yang Bolun | 2011 | Energy & Fuel2011，25，6： | 1 |
| 7 | Molecule simu- lation for the secondary reactions of fluid catalytic cracking gasoline by the method of structure oriented lumping com- bined with Monte Carlo显示文摘 | Yang Bolun Zhou Xiaowei Chen Chun | 2008 | Ind Eng Chem Res2008，47，14： | 1 |
| 8 | An Influence Maximization Algorithm Based on the Mixed Importance of Nodes显示文摘The influence maximization is the problem of finding k seed nodes that maximize the scope of influence in a social network.Therefore,the comprehensive influence of node needs to be considered,when we choose the most influential node set consisted of k seed nodes.On account of the traditional methods used to measure the influence of nodes,such as degree centrality,betweenness centrality and closeness centrality,consider only a single aspect of the influence of node,so the influence measured by traditional methods mentioned above of node is not accurate.In this paper,we obtain the following result through experimental analysis:the influence of a node is relevant not only to its degree and coreness,but also to the degree and coreness of the n-order neighbor nodes.Hence,we propose a algorithm based on the mixed importance of nodes to measure the comprehensive influence of node,and the algorithm we proposed is simple and efficient.In addition,the performance of the algorithm we proposed is better than that of traditional influence maximization algorithms. | Yong Hua Bolun Chen Yan Yuan Guochang Zhu Jialin Ma | 2019 | Computers, Materials & Continua2019，，5： | 1 |
| 9 | Molecule simulation for the secondary reactions of fluid catalytic cracking gasoline by the method of structure oriented lumping combined with Monte Carlo显示文摘 | YANG Bolun ZHOU Xiaowei CHEN Chun | 2008 | Ind Eng Chem Res2008，47，14： | 1 |
| 10 | Molecule simulation for the secondary reactions of fluid catalytic cracking gasoline by the method of structure oriented lumping combined with monte carlo 显示文摘 | Yang Bolun Zhou Xiaowei Chen Chun | 2008 | Industrial & Engineering Chemistry Research2008，47，14： | 1 |
| 11 | Gefitinib and fostamatinib target EGFR and SYK to attenuate silicosis:a multi-omics study with drug exploration显示文摘Silicosis is the most prevalent and fatal occupational disease with no effective therapeutics,and currently used drugs cannot reverse the disease progress.Worse still,there are still challenges to be addressed to fully decipher the intricated pathogenesis.Thus,specifying the essential mechanisms and targets in silicosis progression then exploring anti-silicosis pharmacuticals are desperately needed.In this work,multi-omics atlas was constructed to depict the pivotal abnormalities of silicosis and develop targeted agents.By utilizing an unbiased and time-resolved analysis of the transcriptome,proteome and phosphoproteome of a silicosis mouse model,we have verified the significant differences in transcript,protein,kinase activity and signaling pathway level during silicosis progression,in which the importance of essential biological processes such as macrophage activation,chemotaxis,immune cell recruitment and chronic inflammation were emphasized.Notably,the phosphorylation of EGFR(p-EGFR)and SYK(pSYK)were identified as potential therapeutic targets in the progression of silicosis.To inhibit and validate these targets,we tested fostamatinib(targeting SYK)and Gefitinib(targeting EGFR),and both drugs effectively ameliorated pulmonary dysfunction and inhibited the progression of inflammation and fibrosis.Overall,our drug discovery with multi-omics approach provides novel and viable therapeutic strategies for the treatment of silicosis. | Mingyao Wang Zhe Zhang Jiangfeng Liu Meiyue Song Tiantian Zhang Yiling Chen Huiyuan Hu Peiran Yang Bolun Li Xiaomin Song Junling Pang Yanjiang Xing Zhujie Cao Wenjun Guo Hao Yang Jing Wang Juntao Yang Chen Wang | 2022 | Signal Transduction and Targeted Therapy2022，7，6： | 1 |
| 12 | Versatile memristor implemented in van der Waals CuInP_(2)S_(6)显示文摘Memristors are playing an increasingly important role in developing in-memory computing.Versatile memristors which offer both volatile and non-volatile performances can be employed as both memories and selectors,displaying unique advantages for developing novel electronic circuits.Herein,the remarkable multifunctional memristor with switchable operating modes between volatile and non-volatile by regulating compliance currents is implemented in Ag/CIPS/Au(CIPS:CuInP_(2)S_(6))device.Diode-like volatile memristor performances with the rectification ratio of 10^(3) and an endurance of 500 switching cycles were obtained.Meanwhile,significant non-volatile memory performances with on/off ratio of 10^(3)and retention up to 10^(4)s were also developed,which enables it to be utilized as selectors and memories simultaneously.Moreover,such versatile memristor can emulate the short-term plasticity(STP)and long-term plasticity(LTP)of artificial synapse,demonstrating its advantages in neuromorphic computing applications. | Yiqun Liu Yonghuang Wu Bolun Wang Hetian Chen Di Yi Kai Liu Ce-Wen Nan Jing Ma | 2023 | Nano Research2023，16，7： | 0 |
| 13 | Confining carbon dots in amino-functionalized mesoporous silica:n→π^(*) interaction triggered deep-red solid-state fluorescence显示文摘Deep-red and near-infrared emissive carbon dots(CDs)are highly desired for bioimaging,especially in deep tissue imaging,but they are extremely rare and the known ones usually suffer from low-efficient fluorescence in water and aggregation-induced fluorescence quenching in solid state.In this work,CDs with intriguing solvent-dependent and two-photon fluorescence emissions have been prepared by a facile solvothermal method.Detailed characterizations reveal that there is an n→π*interaction between the carboxyl functional groups on CDs and the electron donor groups in solvent,which leads to the increase of energy density of CDs and the decrease of energy level,resulting in the red shift of luminescence with enhanced electron donating ability of solvent.Inspired by this finding,mesoporous silica nanoparticles(MSNs)with suitable pore size and low biological toxicity are modified by amino groups to confine CDs,thus the deep-red fluorescence emission is achieved both in solid state and in water facilitated by the n→π*interaction of host-guest.The as-prepared CDs@EDA-MSN composite exhibits high-efficient fluorescence with 650 nm wavelength,low toxicity,and good biocompatibility,which endow them a promising application in bio-imaging. | Hongyue Zhang Qingyi Li Shuo Wang Xiaowei Yu Bolun Wang Guangrui Chen Li Ren Jiyang Li Mingxing Jin Jihong Yu | 2023 | Nano Research2023，16，3： | 0 |
| 14 | Integrated genetic linkage map of cultivated peanut by three RIL populations显示文摘High-density and precise genetic linkage map is fundamental to detect quantitative trait locus (QTL) of agronomic and quality related traits in cultivated peanut (Arachis hypogaea L.). In this study, three linkage maps from three RIL (recombinant inbred line)populations were used to construct an integrated map. A total of 2,069 SSR and transposon markers were anchored on the high-density integrated map which covered 2,231.53 cM with 20 linkage groups. Totally, 92 QTLs correlating with pod length (PL), pod width (PW), hundred pods weight (HPW) and plant height (PH) from above RIL populations were mapped on it. Seven intervals were found to harbor QTLs controlling the same traits in different populations,including one for PL, three for PW, two for HPW, and one for PH. Besides, QTLs controlling different traits in different populations were found to be overlapped in four intervals.Interval on A05 contains 17 QTLs for different traits from two RIL populations. New markers were added to these intervals to detect QTLs with narrow confidential intervals.Results obtained in this study may facilitate future genomic researches such as QTL study, fine mapping, positional cloning and marker-assisted selection (MAS) in peanut. | Yanbin Song Huaiyong Luo Li Huang Yuning Chen Weigang Chen Nian Liu Xiaoping Ren Bolun Yu Jianbin Guo Huifang Jiang | 2017 | Oil Crop Science2017，2，3： | 0 |
| 15 | Mining Syndrome Differentiating Principles from Traditional Chinese Medicine Clinical Data显示文摘Syndrome differentiation-based treatment is one of the key characteristics of Traditional Chinese Medicine(TCM).The process of syndrome differentiation is difficult and challenging due to its complexity,diversity and vagueness.Analyzing syndrome principles from historical records of TCM using data mining(DM)technology has been of high interest in recent years.Nevertheless,in most relevant studies,existing DM algorithms have been simply developed for TCM mining,while the combination of TCM theories or its characteristics with DM algorithms has rarely been reported.This paper presents a novel Symptom-Syndrome Topic Model(SSTM),which is a supervised probabilistic topic model with three-tier Bayesian structure.In the SSTM,syndromes are considered as observed topic labels to distinguish certain symptoms from possible symptoms according to their different positions.The generation of our model is in full compliance with the syndrome differentiation theory of TCM.Experimental results show that the SSTM is more effective than other models for syndrome differentiating. | Jialin Ma Zhaojun Wang Hai Guo Qian Xie Tao Wang Bolun Chen | 2022 | Computer Systems Science & Engineering2022，40，3： | 0 |
| 16 | A Polyp Detection Method Based on FBnet显示文摘The incidence of colorectal cancer(CRC)in China has increased in recent years.The mortality rate of CRC has become one of the highest among all cancers;CRC increasingly affects the health and quality of people’s lives.However,due to the insufficiency of medical resources in China,the workload on medical doctors has further increased.In the past few decades,the adult CRC mortality and morbidity rate dropped sharply,mainly because of CRC screening and removal of adenomatous polyps.However,due to the differences in polyp itself and the skills of endoscopists,the detection rate of polyps varies greatly.In this paper,we adopt an anchor-free mechanism and introduce a better method to factorize the process of bounding box regression.Firstly,we regress the shape of object by the variant of Faster RCNN.Secondly,we re-define the target function of the location of object.The experimental result shows that our method achieves a mAP of 55.8%,which outperforms other state-of-the-art methods by at least 11.9%.This will greatly help to reduce the missed diagnosis of clinicians during endoscopy and treatment,and provide effective help for early diagnosis,early treatment and prevention of CRC. | Jingjing Wan Taiyue Chen Bolun Chen Yongtao Yu Yiyun Sheng Xinggang Ma | 2020 | Computers, Materials & Continua2020，，6： | 0 |
| 17 | An Influence Maximization Algorithm Based on the Influence Propagation Range of Nodes显示文摘The problem of influence maximization in the social network G is to find k seed nodes with the maximum influence.The seed set S has a wider range of influence in the social network G than other same-size node sets.The influence of a node is usually established by using the IC model(Independent Cascade model)with a considerable amount of Monte Carlo simulations used to approximate the influence of the node.In addition,an approximate effect(1��1=e)is obtained,when the number of Monte Carlo simulations is 10000 and the probability of propagation is very small.In this paper,we analyze that the propagative range of influence of node set is limited in the IC model,and we find that the influence of node only spread to the t0-th neighbor.Therefore,we propose a greedy algorithm based on the improved IC model that we only consider the influence in the t0-th neighbor of node.Finally,we perform experiments on 10 real social network and achieve favorable results. | Yong Hua Bolun Chen Yan Yuan Guochang Zhu Fenfen Li | 2019 | Journal on Internet of Things2019，1，2： | 0 |
| 18 | A Phrase Topic Model Based on Distributed Representation显示文摘Traditional topic models have been widely used for analyzing semantic topics from electronic documents.However,the obvious defects of topic words acquired by them are poor in readability and consistency.Only the domain experts are possible to guess their meaning.In fact,phrases are the main unit for people to express semantics.This paper presents a Distributed Representation-Phrase Latent Dirichlet Allocation(DR-Phrase LDA)which is a phrase topic model.Specifically,we reasonably enhance the semantic information of phrases via distributed representation in this model.The experimental results show the topics quality acquired by our model is more readable and consistent than other similar topic models. | Jialin Ma Jieyi Cheng Lin Zhang Lei Zhou Bolun Chen | 2020 | Computers, Materials & Continua2020，，7： | 0 |
| 19 | Urine biomarkers discovery by metabolomics and machine learning for Parkinson’s disease diagnoses显示文摘Parkinson’s disease(PD)is a complex neurological disorder that typically worsens with age.A wide range of pathologies makes PD a very heterogeneous condition,and there are currently no reliable diagnostic tests for this disease.The application of metabolomics to the study of PD has the potential to identify disease biomarkers through the systematic evaluation of metabolites.In this study,urine metabolic profiles of 215 urine samples from 104 PD patients and 111 healthy individuals were assessed based on liquid chromatography-mass spectrometry.The urine metabolic profile was first evaluated with partial leastsquares discriminant analysis,and then we integrated the metabolomic data with ensemble machine learning techniques using the voting strategy to achieve better predictive performance.A combination of 8-metabolite predictive panel performed well with an accuracy of over 90.7%.Compared to control subjects,PD patients had higher levels of 3-methoxytyramine,N-acetyl-l-tyrosine,orotic acid,uric acid,vanillic acid,and xanthine,and lower levels of 3,3-dimethylglutaric acid and imidazolelactic acid in their urine.The multi-metabolite prediction model developed in this study can serve as an initial point for future clinical studies. | Xiaoxiao Wang Xinran Hao Jie Yan Ji Xu Dandan Hu Fenfen Ji Ting Zeng Fuyue Wang Bolun Wang Jiacheng Fang Jing Ji Hemi Luan Yanjun Hong Yanhao Zhang Jinyao Chen Min Li Zhu Yang Doudou Zhang Wenlan Liu Xiaodong Cai Zongwei Cai | 2023 | Chinese Chemical Letters2023，34，10： | 0 |
| 20 | The power of comments: fostering social interactions in microblog networks显示文摘 | Tianyi WANG Yang CHEN Yi WANG Bolun WANG Gang WANG Xing LI Haitao ZHENG Ben Y. ZHAO | 2016 | Frontiers of Computer Science2016，10，5： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员