关键词： 牛大力   指纹图谱   主成分分析   聚类分析  

摘要： 目的:建立牛大力药材HPLC指纹图谱,并结合化学模式识别技术对其质量进行评价,为牛大力药材的质量控制提供参考。方法:采用Agilent TC-C18色谱柱(250 mm×4.6 mm,5μm),以乙腈-0.1%乙酸溶液为流动相,梯度洗脱;柱温:30℃,流速:0.8 mL/min,检测波长:290 nm;建立牛大力样品指纹图谱,进行相似度评价;并运用聚类分析和主成分分析法对牛大力指纹图谱进行数据分析。结果:建立了牛大力HPLC指纹图谱,确定了13个共有峰。26批样品相似度为0.847~0.998,表明不同产地牛大力药材质量相对稳定;聚类分析及主成分分析均能将不同产地牛大力样品分为2类。结论:该研究首次建立了牛大力HPLC指纹图谱,结合化学模式识别,系统评价了牛大力药材质量。方法简单、稳定、重现性和分离度好,可为今后牛大力药材的生产和质量评价提供参考。

关键词： 模式识别受体   白色念珠菌   作用机制  

摘要： 模式识别受体(PRRs)是宿主抵抗白色念珠菌入侵的第一道屏障,通过识别并结合白色念珠菌表面的病原体相关分子模式(PAMP),激活机体的固有免疫应答,从而发挥抗菌作用。目前机体主要有两类模式识别受体,其中胞内模式识别受体,在抗白色念珠菌感染发挥了重要作用,越来越受到大家的重视。本文就胞内模式识别受体的类型及它们在抗白色念珠菌感染中作用机制进行综述。

关键词： generalized spectral-analytical method   biomedical data analysis   bioinformatics   genome analysis   search for repeats   magnetic encephalography   recognition and analysis of brain activity pathologies  

摘要： The generalized spectral-analytical method as a new approach to the processing of information arrays is stated. Some theoretical foundations of this method and its applications in different experimental data analysis problems are given. The method is based on the adaptive expansion of initial arrays in the functional bases belonging to the classical algebraic systems of polynomials and functions of continuous and discrete arguments (Jacobi, Chebyshev, Lagrange, Laguerre, Kravchuk, Charlier, and other polynomials). This approach combines analytical and digital data-processing procedures, thus providing a basis for the universal combined technology for the processing of information arrays. An appreciable part of this review is devoted to video data analysis and pattern-recognition problems. In addition, some relevant applications of this method in biomedical and bioinformation data analysis, recognition, classification, and diagnosis problems are described.

关键词： seminal vesicle   vesiculitis   pattern recognition pattern receptor   innate immune response   male infertility  

摘要： The seminal vesicles can be infected by microorganisms, thereby resulting in vesiculitis and impairment in male fertility. Innate immune responses in seminal vesicles cells to microbial infections, which facilitate vesiculitis, have yet to be investigated. The present study aims to elucidate pattern recognition receptor-mediated innate immune responses in seminal vesicles epithelial cells. Various pattern recognition receptors, including Toll-like receptor 3, Toll-like receptor 4, cytosolic ribonucleic acid, and deoxyribonucleic acid sensors, are abundantly expressed in seminal vesicles epithelial cells. These pattern recognition receptors can recognize their respective ligands, thus activating nuclear factor kappa B and interferon regulatory factor 3. The pattern recognition receptor signaling induces expression of pro-inflammatory cytokines, such as tumor necrosis factor alpha (Tnfa) and interleukin 6 (Il6), chemokines monocyte chemoattractant protein-1 (Mcp1) and C-X-C motif chemokine 10 (Cxcl10), and type 1 interferons Ifna and Ifnb. Moreover, pattern recognition receptor-mediated innate immune responses up-regulated the expression of microsomal prostaglandin E synthase and cyclooxygenase 2, but they down-regulated semenogelin-1 expression. These results provide novel insights into the mechanism underlying vesiculitis and its impact on the functions of the seminal vesicles. Summary Sentence Microbe infections induce seminal vesicle innate immune response through pattern recognition receptor, which may lead to male infertility.

关键词： Hybrid electric vehicle   Adaptive control strategy   Driving pattern recognition   Dynamic programming   Multivariable nonlinear regression   Learning vector quantization  

摘要： An appropriate control strategy can play an important role in further improving the fuel economy performance of hybrid electric vehicle (HEV). This research developed a novel adaptive control strategy to achieve optimal power distribution for a series-parallel hybrid electric bus (SPHEB) to adapt driving pattern instantaneously. First, a methodology of extracting mode transition control and power distribution strategy from dynamic programming (DP) solution is proposed for the development of the hierarchical energy management strategy. A SPHEB energy management problem under the Chinese typical bus driving schedule at urban district (CTBDS_UD) is investigated as a case study. Second, an approach of driving pattern recognition (DPR) module is developed. For adaptive learning, four typical driving patterns are selected as the database of driving condition and using the extraction method described above to acquire optimal control strategies for four driving patterns. Third, a framework of adaptive control strategy has been proposed based on the extracted hierarchical energy management strategy from DP and combined with DPR. Finally, the simulation results demonstrate the proposed adaptive strategy can make power distribution proper adjustments in real time and be capable of improving significantly the fuel efficiency of the SPHEB.

关键词： Cutting pattern recognition   Relevance Vector Machine (RVM)   Gravitational Search Algorithm (GSA)   Chaotic mapping  

摘要： The accurate recognition of the shearer cutting pattern is the focus in fully mechanized coal mining. Hence, a new cutting pattern recognition model based on the combination of Relevance Vector Machine (RVM) and Chaotic Gravitational Search Algorithm (CGSA) is proposed. Initially, the motor operation data, including voltage, current and motor speed, are collected as the detection signal and the RVM classifier based on Bayesian framework is chosen for pattern recognition. In order to optimize the parameters in RVM, which has a great influence on the performance of RVM, the optimization algorithm Gravitational Search Algorithm (GSA) is introduced. Finally, the basic GSA is modified into CGSA with the chaotic mapping for increasing the search diversity of the algorithm. The experimental study demonstrates the advantageous performance of the proposed model even without any feature extraction operations. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Criminal events   pattern recognition   ontology population   ontology enrichment   natural language processing   linguistic patterns  

摘要： Thousands of criminal events are reported in newspapers and social networks every day. They describe violent acts that include actors, places, times, causes and any information concerning them. Verbal and nominal phrases are used to characterize and expose criminal events, which employ an important variety of natural language structures in the newspapers. In addition, causes, times and spaces of criminal events, use linguistic phrases to represent them in text. All of them need to be extracted as a pattern recognition process in order to extract criminal events from text and the information that concerns them. The extracted events, as a knowledge base, are very useful for information retrieval tasks. Therefore, this paper presents an approach based on pattern recognition in order to extract criminal events from Spanish text, by populating and enriching an ontology model. Ontology population and enrichment involve the instantiation of criminal events and their cause relationships. An evaluation process is carried out with a set of manually tagged newspapers with categories of specific events, and shows promising results.

关键词： M   bealei   SFC fingerprint   chemical pattern recognition   quality evaluation  

摘要： Mahonia bealei (Fort.) Carr. (M. bealei) plays an important role in the treatment of many diseases. In the present study, a comprehensive method combining supercritical fluid chromatography (SFC) fingerprints and chemical pattern recognition (CPR) for quality evaluation of M. bealei was developed. Similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) were applied to classify and evaluate the samples of wild M. bealei, cultivated M. bealei and its substitutes according to the peak area of 11 components but an accurate classification could not be achieved. PLS-DA was then adopted to select the characteristic variables based on variable importance in projection (VIP) values that responsible for accurate classification. Six characteristics peaks with higher VIP values (>= 1) were selected for building the CPR model. Based on the six variables, three types of samples were accurately classified into three related clusters. The model was further validated by a testing set samples and predication set samples. The results indicated the model was successfully established and predictive ability was also verified satisfactory. The established model demonstrated that the developed SFC coupled with PLS-DA method showed a great potential application for quality assessment of M. bealei.

关键词： Immunodeficiency   Complement   Lectin pathway   Immunological evaluation   Screening  

摘要： Purpose To compare plasma concentrations of all lectin pathway (LP) pattern recognition molecules (PRMs) in patients referred for laboratory evaluation due to recurrent infections with healthy individuals. Methods Patients were divided into categories according to referral: recurrent airway infections (RAI), recurrent abscesses, common variable immunodeficiency (CVID), lung transplantation candidates (LTX), and 'other causes'. LP PRMs (mannose-binding lectin (MBL), collectin liver 1 (CL-L1), H-ficolin, L-ficolin, M-ficolin) and C-reactive protein (CRP) were determined in 332 patients and 150 healthy blood donors using time-resolved immunofluorometric assays. Results None of the LP PRMs was found in lower concentration in the patient categories;however, several PRMs were detected in higher concentrations. M-ficolin was found in higher concentrations in all patient categories. Patients suffering from RAI had higher concentrations of CL-L1 and H-ficolin. Patients suffering from abscesses exhibited higher concentrations of MBL and CL-L1, whereas LTX had higher concentrations of MBL. Patients with other causes of referral had higher concentrations of MBL and CL-L1. Prevalence of combined deficiencies of PRMs in patient categories and controls did not differ. CRP was used as a marker of ongoing inflammation and was significantly higher among all patient categories. Furthermore, CRP was found to correlate with both M-ficolin and L-ficolin. Conclusion The results suggest that neither single nor combined deficiencies of LP PRMs are more frequent among patients referred for an immunological evaluation than in healthy individuals. Future studies are needed and should focus on deficiencies of LP PRMs combined with deficiencies in other parts of the immune system.

关键词： Time series   Load profiles   Machine learning   Pattern recognition   Clustering   Smart grid  

摘要： System analysis and real-time operations in power distribution utilities require an accurate but compact load data model created on the basis of large number of consumers' measurements modeled as high-dimensional time series. This paper proposes an algorithm for grouping time series with similar load patterns and extracting characteristic representatives of loads from the obtained groups, resulting in reduced load data model size. The proposed Time Series Grouping Algorithm combines dimensionality reduction, both partitional and hierarchical clustering and cluster validation to group time series into an optimal number of clusters based on simple parametric settings. The usefulness of the proposed algorithm is proven in a case study implemented in R language. The case study was conducted on real smart meter data from three distribution networks: one North American and the other two European. Results of the case study confirm that the proposed solution achieves high cluster validity and short execution time comparing to related algorithms. Therefore, the article's main contribution is load pattern recognition support convenient for applications in distribution management systems. (C) 2019 Elsevier B.V. All rights reserved.