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OALib Journal期刊

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Granger Causality Network Reconstruction of Conductance-Based Integrate-and-Fire Neuronal Systems
Douglas Zhou, Yanyang Xiao, Yaoyu Zhang, Zhiqin Xu, David Cai
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0087636
Abstract: Reconstruction of anatomical connectivity from measured dynamical activities of coupled neurons is one of the fundamental issues in the understanding of structure-function relationship of neuronal circuitry. Many approaches have been developed to address this issue based on either electrical or metabolic data observed in experiment. The Granger causality (GC) analysis remains one of the major approaches to explore the dynamical causal connectivity among individual neurons or neuronal populations. However, it is yet to be clarified how such causal connectivity, i.e., the GC connectivity, can be mapped to the underlying anatomical connectivity in neuronal networks. We perform the GC analysis on the conductance-based integrate-and-fire (IF) neuronal networks to obtain their causal connectivity. Through numerical experiments, we find that the underlying synaptic connectivity amongst individual neurons or subnetworks, can be successfully reconstructed by the GC connectivity constructed from voltage time series. Furthermore, this reconstruction is insensitive to dynamical regimes and can be achieved without perturbing systems and prior knowledge of neuronal model parameters. Surprisingly, the synaptic connectivity can even be reconstructed by merely knowing the raster of systems, i.e., spike timing of neurons. Using spike-triggered correlation techniques, we establish a direct mapping between the causal connectivity and the synaptic connectivity for the conductance-based IF neuronal networks, and show the GC is quadratically related to the coupling strength. The theoretical approach we develop here may provide a framework for examining the validity of the GC analysis in other settings.
Analysis of sampling artifacts on the Granger causality analysis for topology extraction of neuronal dynamics
Douglas Zhou,Yaoyu Zhang,Yanyang Xiao,David Cai
Frontiers in Computational Neuroscience , 2014, DOI: 10.3389/fncom.2014.00075
Abstract: Granger causality (GC) is a powerful method for causal inference for time series. In general, the GC value is computed using discrete time series sampled from continuous-time processes with a certain sampling interval length τ, i.e., the GC value is a function of τ. Using the GC analysis for the topology extraction of the simplest integrate-and-fire neuronal network of two neurons, we discuss behaviors of the GC value as a function of τ, which exhibits (i) oscillations, often vanishing at certain finite sampling interval lengths, (ii) the GC vanishes linearly as one uses finer and finer sampling. We show that these sampling effects can occur in both linear and non-linear dynamics: the GC value may vanish in the presence of true causal influence or become non-zero in the absence of causal influence. Without properly taking this issue into account, GC analysis may produce unreliable conclusions about causal influence when applied to empirical data. These sampling artifacts on the GC value greatly complicate the reliability of causal inference using the GC analysis, in general, and the validity of topology reconstruction for networks, in particular. We use idealized linear models to illustrate possible mechanisms underlying these phenomena and to gain insight into the general spectral structures that give rise to these sampling effects. Finally, we present an approach to circumvent these sampling artifacts to obtain reliable GC values.
Enhancement of fault vibration signature analysis for rotary machines using an improved wavelet
Binqiang Chen,Wangpeng He,Yanyang Zi
- , 2018, DOI: 10.1177/0954406217697354
Abstract: In this paper, a wavelet-based periodic group-sparse signal denoising approach is proposed for detecting faults in rotary machines. The proposed approach exploits group sparsity in the wavelet domain. For this purpose, a periodicity-induced overlapping group shrinkage technique is utilized to threshold the wavelet coefficients. The wavelet coefficients are obtained by using the tunable Q-factor wavelet transform to decompose the measured vibration signals. The proposed approach is constrained to promote sparsity more strongly than convex regularization for estimating periodic group-sparse signals in noise, while avoiding nonconvex optimization. In addition, this maximally sparse convex approach has the advantage of preserving the oscillatory behavior of the useful fault features. A simulated signal is formulated to verify the performance of the proposed approach in periodic feature extraction. The detection performance of the proposed approach is compared with that of the comparative methods via root mean square error values. Finally, the proposed approach is applied to fault diagnosis of both experimental cases and engineering application. The processed results demonstrate that the proposed feature extraction technique can effectively detect the fault features from heavy background noise
A graphic pattern feature
Wen Zhou,Yanyang Zi,Yiqing Li
- , 2019, DOI: 10.1177/0954406218755186
Abstract: Effective condition monitoring of diesel engine can ensure the reliability of large-power machines and prevent catastrophic consequences. Cylinder pressure is capable of reflecting the whole combustion process of diesel engine, and hence can help to identify the malfunctions of the diesel engine during operation. In this paper, a graphic pattern feature-mapping method is proposed for graphic pattern feature recognition in data-driven condition monitoring. The graphic feature extraction and recognition are linked by labeled feature-mapping. It is used for identifying the running condition of the diesel engine via analyzing the cylinder pressure signal of the diesel engine. The different types of the malfunctions which are caused by different parts of the diesel engine such as induction system, valve actuating mechanism, fuel system, fuel injection system, etc. can be identified just by cylinder pressure signal. The bench experiment of a large-power diesel engine is performed to validate this graphic pattern recognition method. The results show that it has good accuracy on multi-malfunction identification and classification when the engine operates at one speed and one load
A Numerical Study for Flow Excitation and Performance of Rampressor Inlet considering Rotor Motion
Weijia Kang,Zhansheng Liu,Jiangbo Lu,Yu Wang,Yanyang Dong
Shock and Vibration , 2014, DOI: 10.1155/2014/963234
Abstract: A unique supersonic compressor rotor with high pressure ratio, termed the Rampressor, is presented by Ramgen Power Systems, Inc. (RPS). In order to obtain the excitation characteristic and performance of Rampressor inlet flow field under external excitation, compression inlet flow of Rampressor is studied with considering Rampressor rotor whirling. Flow excitation characteristics and performance of Rampressor inlet are analyzed under different frequency and amplitude of Rampressor rotor whirling. The results indicate that the rotor whirling has a significant effect for flow excitation characteristics and performance of Rampressor inlet. The effect of rotor whirling on the different inlet location excitation has a definite phase difference. Inlet excitation becomes more complex along with the inlet flow path. More frequency components appear in the excitation spectrum of Rampressor inlet with considering Rampressor rotor whirling. The main frequency component is the fundamental frequency, which is caused by the rotor whirling. Besides the fundamental frequency, the double frequency components are generated due to the coupling between inlet compression flow of Rampressor rotor and rotor whirling, especially in the subsonic diffuser of Rampressor rotor inlet. With the increment of rotor whirling frequency and whirling amplitude, the complexity of Rampressor inlet excitation increases, and the stability of Rampressor inlet performance deteriorates. 1. Introduction Ramgen engine with a proof-of-concept version of a new type of compression system has been proposed by American Ramgen Power Systems, Inc. [1, 2]. The core part of Ramgen engine is Rampressor. Rampressor inlet is formed of the rotor compression ramp and engine casing. Shock wave compression system is employed in the Rampressor inlet. Compared with traditional axial or centrifugal compressor, Ramgen engine has some distinct technical characteristics [3–5] such as a higher stage pressure ratio, greater compression efficiency, higher operational reliability, and smaller volume and compact structure. Ramgen Power Systems, Inc. has developed the related numerical simulation of Rampressor inlet, which provided the advantageous validation for the design of inlet flow-path structure and supersonic shock wave compression system [6]. A two-dimensional model of Rampressor rotor inlet was designed and established by Han et al. [7], and this model was numerically studied by CFD. The effects of rotational speed of Rampressor rotor and exit back pressure on the shock wave structure, flow field distributions, and
The Histone Acetyltransferase p300 Regulates the Expression of Pluripotency Factors and Odontogenic Differentiation of Human Dental Pulp Cells
Tong Wang, Huijuan Liu, Yanyang Ning, Qiong Xu
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0102117
Abstract: p300 is a well-known histone acetyltransferase (HAT) and coactivator that plays vital roles in many physiological processes. Despite extensive research on the involvement of p300 in the regulation of transcription in numerous cell lines, the roles of this protein in regulating pluripotency genes and odontogenic differentiation in human dental pulp cells (HDPCs) are poorly understood. To address this issue, we investigated the expression of OCT4, NANOG and SOX2 and the proliferation and odontogenic differentiation capacity of HDPCs following p300 overexpression. We found that p300 overexpression did not overtly affect the ability of HDPCs to proliferate. The overexpression of p300 upregulated the promoter activity and the mRNA and protein expression of NANOG and SOX2. The HAT activity of p300 appeared to partially mediate the regulation of these factors; indeed, when a mutant form of p300 lacking the HAT domain was overexpressed, the promoter activity and expression of NANOG and SOX2 decreased relative to p300 overexpression but was greater than in the control. Furthermore, we demonstrated that the mRNA levels of the odontogenic marker genes dentine matrix protein-1 (DMP-1), dentin sialophosphoprotein (DSPP), dentin sialoprotein (DSP), osteopontin (OPN) and osteocalcin (OCN) were significantly decreased in HDPCs overexpressing p300 cultured under normal culture conditions and increased in HDPCs inducted to undergo odontogenic differentiation. This finding was further confirmed by measuring levels of alkaline phosphatase (ALP) activity and assessing the formation of mineralized nodules. The HAT activity of p300 had no significant effect on odontogenic differentiation. p300 was recruited to the promoter regions of OCN and DSPP and might be acting as a coactivator to increase the acetylation of lysine 9 of histone H3 of OCN and DSPP. Collectively, our results show that p300 plays an important role in regulating the expression of key pluripotency genes in HDPCs and modifying odontogenic differentiation.
Sparsity-based Algorithm for Detecting Faults in Rotating Machines
Wangpeng He,Yin Ding,Yanyang Zi,Ivan W. Selesnick
Computer Science , 2015,
Abstract: This paper addresses the detection of periodic transients in vibration signals for detecting faults in rotating machines. For this purpose, we present a method to estimate periodic-group-sparse signals in noise. The method is based on the formulation of a convex optimization problem. A fast iterative algorithm is given for its solution. A simulated signal is formulated to verify the performance of the proposed approach for periodic feature extraction. The detection performance of comparative methods is compared with that of the proposed approach via RMSE values and receiver operating characteristic (ROC) curves. Finally, the proposed approach is applied to compound faults diagnosis of motor bearings. The non-stationary vibration data were acquired from a SpectraQuest's machinery fault simulator. The processed results show the proposed approach can effectively detect and extract the useful features of bearing outer race and inner race defect.
Mucoepidermoid Carcinoma of the Lung: Report of 29 Cases
Jingjing HOU, Huijuan WANG, Guowei ZHANG, Yanyang HUANG, Zhiyong MA
- , 2017, DOI: : 10.3779/j.issn.1009-3419.2017.03.05
Abstract: Background and objective Pulmonary mucoepidermoid carcinoma (MEC) is an extremely rare pulmonary malignant tumor, its clinical features and conditions of prognosis is not entirely clear. The aim of this study is to discuss clinical features, diagnostic and therapeutic methods, and prognosis of pulmonary MEC. Methods We retrospectively studied 29 pulmonary MEC patients who diagnosed from January 2006 to December 2015 in Affiliated Hospital of Zhengzhou University. The clinical features, prognosis, diagnostic and therapeutic methods were analyzed. Results There were 20 patients identified as pulmonary MEC, which constitutes 0.18% of all the lung tumor patients. There were 18 males and 11 females, the median age of the patients was 45 years (range 10-79). There were 17 patients identified as high-grade pulmonary MEC and 12 low-grade. Epidermal growth factor receptor (EGFR) mutation detection was performed in six patients, none was positive. 17 cases was underwent surgery based comprehensive treatment, 12 cases non-operatived treatment. The median follow-up time was 35 (5-114) months in this cohort of 29 patients. During the follow up, incidence of death was found in 17 cases. The overall 1-, 3-, 5-year survival rates were 65.5%, 51.2%, 39.4%, respectively. The median survival time was 37 months. Conclusion The incidence of pulmonary MEC is low, lacking specific clinical characterization. The diagnosis mainly depends on postoperative pathology, aided by immunohistochemical. Surgery is the main treatment method. The majority of pathology was high-grade type. The prognosis of pulmonary MEC closely relates to the pathological types and clinical stage. EGFR-tyrosine kinase inhibitor (EGFR-TKI) is expected to improve the prognosis of pulmonary MEC.
PRISMA – Practical meta-analysis of applying local triamcinolone acetonide injection for stenosis after esophageal cancer surgery
Baoxin Du,Wu Wang,Yanyang Pang,Zhen Shen
- , 2018, DOI: 10.2147/CMAR.S173769
Abstract: To explore the practical method of endoscopic triamcinolone acetonide (TA) injection immediately after endoscopic surgery and combined with endoscopic dilation (ED) in the management of stenosis after esophageal cancer surgery based on their efficacy and safety
Does the use of targeted agents in advanced gastroesophageal cancer increase complete response? A meta-analysis of 18 randomized controlled trials
Jiancheng Sun,Wu Wang,Yanyang Pang,Zhen Shen
- , 2018, DOI: 10.2147/CMAR.S174063
Abstract: We aimed to investigate whether the use of targeted agents (TAs) in advanced gastroesophageal cancer (GEC) increased the complete response (CR) and to assess the surrogate endpoints for survival in the targeted treatment of GEC by using a meta-analysis of randomized controlled trials (RCTs)
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