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408 results on '"Xu, Xiaona"'

159. Identification of a TOR signaling pathway gene as a candidate target for reproductive management of Adelphocoris suturalis

Author

Zheng, Wanying, Jiao, Panyang, Xu, Xiaona, Ma, Weihua, Hull, J. Joe, Hua, Hongxia, and Chen, Lizhen

Abstract

Adelphocoris suturalisis a polyphagous pest that is increasingly causing severe economic damage due to more frequent outbreaks. The development of non-target resistance to commercial Bacillus thuringiensis(Bt) cotton has further exacerbated its pest status and amplified the need for more sustainable methods of control. RNA interference (RNAi)-based pest management strategies, such as root soaking and transgenic plants that express dsRNAs, have proven to be reliable, eco-friendly pest control strategies. To identify new RNAi targets for potential A. suturalispopulation control, we investigated the target of rapamycin (TOR) signaling pathway. A critical role for this pathway in A. suturalisreproductive regulation was suggested by pharmacological analyses. Subsequent RNAi-mediated knockdown of the A. suturalisTOR pathway genes TOR, Ras homolog enriched in the brain(Rheb), and ribosomal S6 kinase(S6K) reduced fertility. Moreover, a spray-induced and nanocarrier-delivered gene silencing (SI-NDGS) system targeting TORsuccessfully suppressed ovarian development, which demonstrates its effectiveness as a pest control target. These results provide a critical foundation for understanding reproductive regulation in A. suturalisand introduce new candidates for RNAi-based A. suturalismanagement.

Published
2024
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164. Study on Curve Phenomenon between English and Chinese and its Solution

Author

Xu Xiaona, Li Li, and Gao Qingshi

Subjects
Grammar, Computer science, business.industry, media_common.quotation_subject, Lexicology, Context (language use), computer.software_genre, Semantics, Rule-based machine translation, Phenomenon, Artificial intelligence, Language translation, business, computer, Natural language, Natural language processing, media_common
Abstract

Differences between natural languages in lexicology, grammar, semantics and pragmatics usually lead to mistakes in machine translation. These differences between languages are called curve phenomenon. This paper summarized fourteen kinds of curve phenomena between English and Chinese, and proposed a new method to solve curve phenomenon based on Semantic Element, especially importing context variable and type-curve SE to solve curve phenomenon problems radically.

Published
2010

167. Research on Kernel-Based Feature Fusion Algorithm in Multimodal Recognition

Author

Xu Xiaona, Pan Xiuqin, Zhao Yue, and Pu Qiumei

Subjects
Image fusion, Biometrics, InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.,HCI), Computer science, business.industry, Feature vector, Speech recognition, Feature extraction, Pattern recognition, Facial recognition system, GeneralLiterature_MISCELLANEOUS, Statistical classification, ComputingMethodologies_PATTERNRECOGNITION, Kernel method, otorhinolaryngologic diseases, Three-dimensional face recognition, sense organs, Artificial intelligence, business, Algorithm
Abstract

Ear and face based multimodal recognition could fully utilize their connection relationship, and implement recognizing people without their cooperation because of ear’s special physiological location and structure. In this paper akernel-based feature fusion algorithm is presented and applied to multimodal recognition based on fusing ear and face. With the algorithm, the associated feature vectors of ear and profile face are established for the following classification. The experimental results show that the method is efficient for feature fusion, and the multimodal recognition based on ear and profile face performs better than ear or profile face unimodal biometric recognition.

Published
2009

168. Multimodal recognition fusing ear and profile face based on KPCA

Author

Xu Xiaona, Zhao Yue, and Pan Xiuqin

Subjects
Biometrics, Contextual image classification, InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.,HCI), Computer science, business.industry, Feature vector, Speech recognition, Feature extraction, Pattern recognition, Sensor fusion, Facial recognition system, GeneralLiterature_MISCELLANEOUS, ComputingMethodologies_PATTERNRECOGNITION, Face (geometry), otorhinolaryngologic diseases, Three-dimensional face recognition, sense organs, Artificial intelligence, business
Abstract

Ear recognition has been proved to be a promising subject in biometrics authentication. The fusion of ear and face biometrics could fully utilize their connection relationship, and possess the merit of recognizing persons without their cooperation because of earpsilas special physiological structure and location. In this paper a feature fusion method based on KPCA is proposed and applied to multimodal recognition fusing ear and profile face. With the method, the associated feature vectors of ear and profile face are established for the following classification. The experimental results show that the method is efficient for feature fusion, and the multimodal recognition based on ear and profile face performs better than ear or profile face unimodal biometric recognition.

Published
2008

169. Found on Artificial Neural Network and Genetic Algorithm Design the ASSEL Roll Profile

Author

Chen Xi, Zhong Xidi, Wang Yu-feng, and Xu Xiaona

Subjects
Artificial neural network, business.industry, Computer science, Genetic algorithm, Mill, Artificial intelligence, Gauge (firearms), business, Machine learning, computer.software_genre, Toe, computer, Algorithm
Abstract

This article introduces a method of optimizing design of ASSEL roller profile. It obtains the feed angle and toe angle for all rolling gauges with genetic artificial neural network (GANN), and to optimize weight coefficient and network structure by training of weight value of genetic neural network. The model was tested on the imported ASSEL mill. The results indicate that the inaccuracy of feed angle and toe angle obtained based on the model were both less than plusmn2%. With obtained feed angle and toe angle, ASSEL roller characteristic parameters of each gauge can be calculated via roller profile design formulas provided by MEER of Germany. The ASSEL roll profile characteristic parameter values are determined by searching all common characteristics and approximate attribute in the possible gauges with parallel optimization method, one of the generic algorithms (GA).

Published
2008

170. Experimental study of anti-tumor effect of electrochemical therapy alone or in combination with radiotherapy

Author

Xiao Weiqun and Xu Xiaona

Subjects
Oncology, Antitumor activity, Cancer Research, medicine.medical_specialty, medicine.diagnostic_test, business.industry, medicine.medical_treatment, Cancer, medicine.disease, behavioral disciplines and activities, Flow cytometry, Radiation therapy, Apoptosis, Untreated control, Internal medicine, mental disorders, medicine, Tumor growth, business, Nuclear medicine, After treatment
Abstract

Experimental study was perfumed to explore the potential benefits of electrochemical therapy (ECT) in tumor-bearing mice. The mice were divided into four groups: Group A, received ECT alone; Group B, radiotherapy alone; Group C, ECT plus radiotherapy; and group D untreated control. We find that it causes tumor growth delayed when ECT of 10 coulombs and radiotherapy 10 GY have the similar action of resisted cancer. We also find G2-phase arrest and increase apoptosis by cell flow cytometry after treatment when ECT and/or radiation. ECT plus radiotherapy have cooperative antitumor effects.

Published
1995

176. Determination of salvianolic acid C in rat plasma using liquid chromatography-mass spectrometry and its application to pharmacokinetic study.

Author

Song, Junke, Zhang, Wen, Sun, Jialin, Zhang, Xue, Xu, Xiaona, Zhang, Li, Feng, Zhangying, and Du, Guanhua

Abstract

A sensitive and reliable LC-ESI-MS method for the determination of salvianolic acid C in rat plasma has been developed and validated. Plasma samples were prepared by liquid-liquid extraction with ethyl acetate and separated on a Zorbax SB-C18 column (3.5 µm, 2.1 × 100 mm) at a flow rate of 0.3 mL/min using acetonitrile-water as mobile phase. The detection was carried out by a single quadrupole mass spectrometer with electrospray ionization source and selected ion monitoring mode. Linearity was obtained for salvianolic acid C ranging from 5 to 1000 ng/mL. The intra- and inter-day precisions (RSD, %) didn't exceed 9.96%, and the accuracy (RE, %) were all within ±3.64%. The average recoveries of the analyte and internal standard were >89.13%. Salvianolic acid C was proved to be stable during all sample storage, preparation and analytic procedures. The validated method was successfully applied to pharmacokinetic study after oral and intravenous administration of salvianolic acid C to rats. The absolute oral bioavailability of salvianolic acid C was 0.29 ± 0.05%. This method was further applied to simultaneous determination of salvianolic acid A, salvianolic acid B and salvianolic acid C in rat plasma and showed good practicability. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Published
2016
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177. Addition of graphene oxide into graphite toward effective positive electrode for advanced zinc-cerium redox flow battery.

Author

Xie, Zhipeng, Yang, Bin, Yang, Liang, Xu, Xiaona, Cai, Dingjian, Chen, Jianchai, Chen, Yujuan, He, Yanhua, Li, Ying, and Zhou, Xiaochun

Subjects
GRAPHENE oxide, ELECTRODES, ELECTROCHEMICAL analysis, X-ray diffraction, SCANNING electron microscopy
Abstract

The paper first reports the use of a kind of positive electrode material (graphite/graphene-oxide composite) in zinc-cerium redox flow battery (RFB). It exhibits excellent electrochemical performance toward Ce/Ce redox couple in zinc-cerium RFB. The material was characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The electrochemical activity of this kind of material to Ce/Ce redox reaction was studied with cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The results showed that the electrochemical performance of the electrode was improved significantly when 2.5 wt% graphene oxide (GO) was added into graphite electrode. The redox peak current of Ce/Ce couple on the composite electrode was significantly larger than that on the graphite electrode, and the charge transfer resistance on the composite electrode is also obviously reduced. The enhanced electrochemical activity could be attributed to the presence of plentiful oxygen-containing functional groups on the basal planes and sheet edges of the GO and large specific areas introduced by the GO. The energy efficiency of zinc-cerium RFB using graphite/GO composite as positive electrode is around 76.3 %, which is larger than that using graphite (65.9 %). The excellent results demonstrate that the graphite/GO composite holds great promise in the application of zinc-cerium RFB. [ABSTRACT FROM AUTHOR]

Published
2015
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195. Polyanthraquinone-based nanostructured electrode material capable of high-performance pseudocapacitive energy storage in aprotic electrolyte.

Author

Zhou, Yu, Wang, Bin, Liu, Changhai, Han, Na, Xu, Xiaona, Zhao, Feipeng, Fan, Jian, and Li, Yanguang

Abstract

Currently very few non-aqueous pseudocapacitor electrode materials are available. Organic matter based electrodes hold a great promise but remain largely unexplored. In this work, Ketjenblack carbon supported polyanthraquinone with different carbon to polymer ratios was prepared and evaluated as the pseudocapacitor electrode material in acetronitrile. These composite electrodes exhibit large specific capacitance up to 650 F/g and specific capacity up to 270 mAh/g when normalized to the polymer mass, which is much greater than other non-aqueous supercapacitor materials. They also have improved cycling stability with more than 85% capacitance retention after 1000 cycles as a result of the diminished quinone solubility in the electrolyte. When paired with a graphene-based positive electrode in asymmetric supercapacitors, composite electrodes demonstrate significant energy density up to 45.5 Wh/kg and power density up to 21.4 kW/kg. Their great supercapacitive performance, together with their low costs as well as structural and property diversities, makes them highly appealing for future energy storage applications. [ABSTRACT FROM AUTHOR]

Published
2015
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196. Unsupervised Tibetan speech features Learning based on Dynamic Bayesian Networks.

Author

Zhao, Yue, Xu, Xiaona, and Yang, Guosheng

Abstract

This paper proposed an unsupervised learning method to learn speech features based on Dynamic Bayesian Networks (DBNs) that accounts for the spatiotemporal dependences in speech signal. Although deep networks have been successfully applied to unsupervised learning features, the structures of the deep networks are often fixed before learning and they fail to capture temporal representation. In this paper, we propose to construct DBNs for unsupervised learning spatial-temporal features from speech data. The experiment results on Tibetan speech data showed the features learned using proposed DBNs outperforms the state-of-art methods in word recognition accuracy. [ABSTRACT FROM PUBLISHER]

Published
2012

197. A near-optimal non-myopic active learning method.

Author

Zhao, Yue, Yang, Guosheng, Xu, Xiaona, and Ji, Qiang

Abstract

Non-myopic active learning allows the learner to select multiple unlabeled samples at a time. It avoids tedious retraining with each selected sample, and is effective to utilize multiple labelers. But current non-myopic active learning methods are typically greedy by selecting top N unlabeled samples with maximum score. While efficient, such a greedy active learning approach cannot guarantee the learner's performance. In this paper, we introduce a near-optimal non-myopic active learning algorithm that is efficient and simultaneously has a performance guarantee. Our experimental results on UCI data sets and a real-world application show that the proposed algorithm outperforms the myopic active learning method and the existing non-myopic active learning methods in both efficiency and accuracy. [ABSTRACT FROM PUBLISHER]

Published
2012

199. Emerging markers for antimicrobial resistance monitoring

Author

Yi, Zineng, Xu, Xiaona, Meng, Xiaohan, Liu, Congyu, Zhou, Qianpeng, Gong, Deyan, and Zha, Zhengbao

Abstract

The appearance and spread of antibiotic-resistant pathogens known as antimicrobial resistance (AMR) is one of the major worldwide health crises that humanity have to deal with over the next decades. One of the main methods for addressing AMR is the effective screening for antimicrobial insensitivity in clinical and environmental monitoring. Current clinical laboratory procedures use traditional culture-based antibiotic susceptibility testing (AST) methods, which can take up to 24 h to identify which drug is suitable for the infection inhibition. Therefore, it is vital to develop novel strategies that offer quick, simple, affordable, reliable, sensitive, and accurate AMR monitoring. Sensors for AMR markers detection could possess the essential qualities for quickly identifying resistant microorganisms and could give vital data for the selection of antibacterial drugs administration. This review offers a summary of the innovative application of these AMR markers detection strategies focusing on healthcare and environmental surveillance for the AMR genotypic or phenotypic assessment.

Published
2023
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