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Sample records for vector system based

  1. Biosensor method and system based on feature vector extraction

    Science.gov (United States)

    Greenbaum, Elias [Knoxville, TN; Rodriguez, Jr., Miguel; Qi, Hairong [Knoxville, TN; Wang, Xiaoling [San Jose, CA

    2012-04-17

    A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

  2. A Versatile System for USER Cloning-Based Assembly of Expression Vectors for Mammalian Cell Engineering

    DEFF Research Database (Denmark)

    Lund, Anne Mathilde; Kildegaard, Helene Faustrup; Petersen, Maja Borup Kjær

    2014-01-01

    A new versatile mammalian vector system for protein production, cell biology analyses, and cell factory engineering was developed. The vector system applies the ligation-free uracil-excision based technique – USER cloning – to rapidly construct mammalian expression vectors of multiple DNA fragments...... efficiency above 90%. The functionality of basic vectors for FAST assembly was tested and validated by transient expression of fluorescent model proteins in CHO, U-2-OS and HEK293 cell lines. In this test, we included many of the most common vector elements for heterologous gene expression in mammalian cells......, in addition the system is fully extendable by other users. The vector system is designed to facilitate high-throughput genome-scale studies of mammalian cells, such as the newly sequenced CHO cell lines, through the ability to rapidly generate high-fidelity assembly of customizable gene expression vectors....

  3. HSV-1-Based Vectors for Gene Therapy of Neurological Diseases and Brain Tumors: Part II. Vector Systems and Applications

    Directory of Open Access Journals (Sweden)

    Andreas Jacobs

    1999-11-01

    Full Text Available Many properties of HSV-1 are especially suitable for using this virus as a vector to treat diseases affecting the central nervous system (CNS, such as Parkinson's disease or malignant gliomas. These advantageous properties include natural neurotropism, high transduction efficiency, large transgene capacity, and the ability of entering a latent state in neurons. Selective oncolysis in combination with modulation of the immune response mediated by replication-conditional HSV-1 vectors appears to be a highly promising approach in the battle against malignant glioma. Helper virus-free HSV/AAV hybrid amplicon vectors have great promise in mediating long-term gene expression in the PNS and CNS for the treatment of various neurodegenerative disorders or chronic pain. Current research focuses on the design of HSV-1-derived vectors which are targeted to certain cell types and support transcriptionally regulatable transgene expression. Here, we review the recent developments on HSV-1-based vector systems and their applications in experimental and clinical gene therapy protocols.

  4. Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia

    Directory of Open Access Journals (Sweden)

    Emmanuel Chanda

    2012-01-01

    Full Text Available Geographic information systems (GISs with emerging technologies are being harnessed for studying spatial patterns in vector-borne diseases to reduce transmission. To implement effective vector control, increased knowledge on interactions of epidemiological and entomological malaria transmission determinants in the assessment of impact of interventions is critical. This requires availability of relevant spatial and attribute data to support malaria surveillance, monitoring, and evaluation. Monitoring the impact of vector control through a GIS-based decision support (DSS has revealed spatial relative change in prevalence of infection and vector susceptibility to insecticides and has enabled measurement of spatial heterogeneity of trend or impact. The revealed trends and interrelationships have allowed the identification of areas with reduced parasitaemia and increased insecticide resistance thus demonstrating the impact of resistance on vector control. The GIS-based DSS provides opportunity for rational policy formulation and cost-effective utilization of limited resources for enhanced malaria vector control.

  5. VectorBase

    Data.gov (United States)

    U.S. Department of Health & Human Services — VectorBase is a Bioinformatics Resource Center for invertebrate vectors. It is one of four Bioinformatics Resource Centers funded by NIAID to provide web-based...

  6. Development of cup-shaped micro-electromechanical systems-based vector hydrophone

    Science.gov (United States)

    Xu, Wei; Liu, Yuan; Zhang, Guojun; Wang, Renxin; Xue, Chenyang; Zhang, Wendong; Liu, Jun

    2016-09-01

    Similar to the vital performance factors, the receiving sensitivity and the bandwidth exist interactively in the micro-electromechanical systems (MEMS)-based vector hydrophones. Some existing methods can improve the sensitivity of the hydrophone, but these improvements are usually gained at a cost of the bandwidth. However, the cup-shaped MEMS vector hydrophone that is presented in this paper can improve its sensitivity while retaining a sufficient bandwidth. The cup-shaped structure acts as a new sensing unit in the MEMS vector hydrophone, replacing the bionic columnar hair that was previously used for sensing. The relationships between the parameters of the cup-shaped structure and the sensitivity of the vector hydrophone were determined by a theoretical deduction. In addition, simulation analyses were performed, and optimized structural parameters were obtained in this work. ANSYS 15.0 simulation was used to derive the optimum characteristics for the cup-shaped structure. The results of the calibration experiments showed that the sensitivity reached up to -188.5 dB (gain of 40 dB, 1 kHz, 0 dB@1 V/μPa), and the bandwidth was in the 20 Hz-1 kHz range, which is sufficient for an underwater acoustic detection at low frequencies. This work has, thus, proved that the cup-shaped vector hydrophone has superior properties for the engineering applications.

  7. Deformation vector measurement by means of ground based interferometric radar system

    Science.gov (United States)

    Michelini, Alberto; Coppi, Francesco

    2017-10-01

    Ground Based Interferometric Radar (GBInRad) is a class of terrestrial remote sensing imaging system, based on microwave interferometric techniques. The principal application of GBInRad system is deformation monitoring, since respect to other techniques they can provide remote sensing, high sensitivity to small deformations, long range of measurements, imaging capability and fast scan time. The main limitation of standard GBInRad system is their capability of detecting movements only along the Line of Sight (LoS) of the sensor, although actual targets may show deformations in any direction of space; this represents an important limitation with respect to other techniques able to estimate the full 3D deformation vector. If the displacement direction is not known a priori, combining together LoS displacement measured from different spatial positions, it is possible to reconstruct the actual 3D displacement vector of monitored targets. In this paper are introduced and analysed the various aspect of the displacement vector measurement with multiple GBInRad system that work both in a monostatic and in a bistatic configuration. In the monostatic configuration every system transmits and receives the signal independently from the others; this approach requires multiple GBInRad system deployed to monitoring the same scenario and therefore its main limitations lie in the costs, power consumption and maintenance. A possible cost-effective evolution of the monostatic configuration is to exploit GBInRad system in a multiple bistatic configuration; a multiple bistatic Radar is a system in which a transmitter operates together with multiple receivers located in different positions in space. In this paper, the deformation vector measurement by means of bistatic GBInRad is proposed.

  8. Hadoop-Based Distributed System for Online Prediction of Air Pollution Based on Support Vector Machine

    Science.gov (United States)

    Ghaemi, Z.; Farnaghi, M.; Alimohammadi, A.

    2015-12-01

    The critical impact of air pollution on human health and environment in one hand and the complexity of pollutant concentration behavior in the other hand lead the scientists to look for advance techniques for monitoring and predicting the urban air quality. Additionally, recent developments in data measurement techniques have led to collection of various types of data about air quality. Such data is extremely voluminous and to be useful it must be processed at high velocity. Due to the complexity of big data analysis especially for dynamic applications, online forecasting of pollutant concentration trends within a reasonable processing time is still an open problem. The purpose of this paper is to present an online forecasting approach based on Support Vector Machine (SVM) to predict the air quality one day in advance. In order to overcome the computational requirements for large-scale data analysis, distributed computing based on the Hadoop platform has been employed to leverage the processing power of multiple processing units. The MapReduce programming model is adopted for massive parallel processing in this study. Based on the online algorithm and Hadoop framework, an online forecasting system is designed to predict the air pollution of Tehran for the next 24 hours. The results have been assessed on the basis of Processing Time and Efficiency. Quite accurate predictions of air pollutant indicator levels within an acceptable processing time prove that the presented approach is very suitable to tackle large scale air pollution prediction problems.

  9. Modelling and Simulation of SVPWM Based Vector Controlled HVDC Light Systems

    Directory of Open Access Journals (Sweden)

    Ajay Kumar MOODADLA

    2012-11-01

    Full Text Available Recent upgrades in power electronics technology have lead to the improvements of insulated gate bipolar transistor (IGBT based Voltage source converter High voltage direct current (VSC HVDC transmission systems. These are also commercially known as HVDC Light systems, which are popular in renewable, micro grid, and electric power systems. Out of different pulse width modulation (PWM schemes, Space vector PWM (SVPWM control scheme finds growing importance in power system applications because of its better dc bus utilization. In this paper, modelling of the converter is described, and SVPWM scheme is utilized to control the HVDC Light system in order to achieve better DC bus utilization, harmonic reduction, and for reduced power fluctuations. The simulations are carried out in the MATLAB/SIMULINK environment and the results are provided for steady state and dynamic conditions. Finally, the performance of SVPWM based vector controlled HVDC Light transmission system is compared with sinusoidal pulse width modulation (SPWM based HVDC Light system in terms of output voltage and total harmonic distortion (THD.

  10. Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Lara del Val

    2015-06-01

    Full Text Available Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM. The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

  11. Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

    Energy Technology Data Exchange (ETDEWEB)

    Miltiadis Alamaniotis; Vivek Agarwal

    2014-10-01

    This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are then inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.

  12. Implementation of algorithms based on support vector machine (SVM for electric systems: topic review

    Directory of Open Access Journals (Sweden)

    Jefferson Jara Estupiñan

    2016-06-01

    Full Text Available Objective: To perform a review of implementation of algorithms based on support vectore machine applied to electric systems. Method: A paper search is done mainly on Biblio­graphic Indexes (BI and Bibliographic Bases with Selection Committee (BBSC about support vector machine. This work shows a qualitative and/or quan­titative description about advances and applications in the electrical environment, approaching topics such as: electrical market prediction, demand predic­tion, non-technical losses (theft, alternative energy source and transformers, among others, in each work the respective citation is done in order to guarantee the copy right and allow to the reader a dynamic mo­vement between the reading and the cited works. Results: A detailed review is done, focused on the searching of implemented algorithms in electric sys­tems and innovating application areas. Conclusion: Support vector machines have a lot of applications due to their multiple benefits, however in the electric energy area; they have not been tota­lly applied, this allow to identify a promising area of researching.

  13. Software-based microwave CT system consisting of antennas and vector network analyzer.

    Science.gov (United States)

    Ogawa, Takahiro; Miyakawa, Michio

    2011-01-01

    We have developed a software-based microwave CT (SMCT) that consists of antennas and a vector network analyzer. Regardless of the scanner type, SMCT collects the S-parameters at each measurement position in the frequency range of interest. After collecting all the S-parameters, it calculates the shortest path to obtain the projection data for CPMCT. Because of the redundant data in SMCT, the calculation of the projection is easily optimized. Therefore, the system can improve the accuracy and stability of the measurement. Furthermore, the experimental system is constructed at a reasonable cost. Hence, SMCT is useful for imaging experiments for CP-MCT and particularly for basic studies. This paper describes the software-based microwave imaging system, and experimental results show the usefulness of the system.

  14. Bio-signal analysis system design with support vector machines based on cloud computing service architecture.

    Science.gov (United States)

    Shen, Chia-Ping; Chen, Wei-Hsin; Chen, Jia-Ming; Hsu, Kai-Ping; Lin, Jeng-Wei; Chiu, Ming-Jang; Chen, Chi-Huang; Lai, Feipei

    2010-01-01

    Today, many bio-signals such as Electroencephalography (EEG) are recorded in digital format. It is an emerging research area of analyzing these digital bio-signals to extract useful health information in biomedical engineering. In this paper, a bio-signal analyzing cloud computing architecture, called BACCA, is proposed. The system has been designed with the purpose of seamless integration into the National Taiwan University Health Information System. Based on the concept of. NET Service Oriented Architecture, the system integrates heterogeneous platforms, protocols, as well as applications. In this system, we add modern analytic functions such as approximated entropy and adaptive support vector machine (SVM). It is shown that the overall accuracy of EEG bio-signal analysis has increased to nearly 98% for different data sets, including open-source and clinical data sets.

  15. Nanotechnologies in delivery of mRNA therapeutics using nonviral vector-based delivery systems.

    Science.gov (United States)

    Guan, S; Rosenecker, J

    2017-03-01

    Because of its safe and effective protein expression profile, in vitro transcribed messenger RNA (IVT-mRNA) represents a promising candidate in the development of novel therapeutics for genetic diseases, vaccines or gene editing strategies, especially when its inherent shortcomings (for example, instability and immunogenicity) have been partially addressed via structural modifications. However, numerous unsolved technical difficulties in successful in vivo delivery of IVT-mRNA have greatly hindered the applications of IVT-mRNA in clinical development. Recent advances in nanotechnology and material science have yielded many promising nonviral delivery systems, some of which were able to efficiently facilitate targeted in vivo delivery of IVT-mRNA in safe and noninvasive manners. The diversity and flexibility of these delivery systems highlight the recent progress of IVT-mRNA-based therapy using nonviral vectors. In this review, we summarize recent advances of existing and emerging nonviral vector-based nanotechnologies for IVT-mRNA delivery and briefly summarize the interesting but rarely discussed applications on simultaneous delivery of IVT-mRNA with DNA.

  16. Relevance Vector Machines for Enhanced BER Probability in DMT-Based Systems

    Directory of Open Access Journals (Sweden)

    Ashraf A. Tahat

    2010-01-01

    Full Text Available A new channel estimation method for discrete multitone (DMT communication system based on sparse Bayesian learning relevance vector machine (RVM method is presented. The Bayesian frame work is used to obtain sparse solutions for regression tasks with linear models. By exploiting a probabilistic Bayesian learning framework, sparse Bayesian learning provides accurate models for estimation and consequently equalization. We consider frequency domain equalization (FEQ using the proposed channel estimate at both the transmitter (preequalization and receiver (postequalization and compare the resulting bit error rate (BER performance curves for both approaches and various channel estimation techniques. Simulation results show that the proposed RVM-based method is superior to the traditional least squares technique.

  17. A Personalized Electronic Movie Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization.

    Science.gov (United States)

    Wang, Xibin; Luo, Fengji; Qian, Ying; Ranzi, Gianluca

    2016-01-01

    With the rapid development of ICT and Web technologies, a large an amount of information is becoming available and this is producing, in some instances, a condition of information overload. Under these conditions, it is difficult for a person to locate and access useful information for making decisions. To address this problem, there are information filtering systems, such as the personalized recommendation system (PRS) considered in this paper, that assist a person in identifying possible products or services of interest based on his/her preferences. Among available approaches, collaborative Filtering (CF) is one of the most widely used recommendation techniques. However, CF has some limitations, e.g., the relatively simple similarity calculation, cold start problem, etc. In this context, this paper presents a new regression model based on the support vector machine (SVM) classification and an improved PSO (IPSO) for the development of an electronic movie PRS. In its implementation, a SVM classification model is first established to obtain a preliminary movie recommendation list based on which a SVM regression model is applied to predict movies' ratings. The proposed PRS not only considers the movie's content information but also integrates the users' demographic and behavioral information to better capture the users' interests and preferences. The efficiency of the proposed method is verified by a series of experiments based on the MovieLens benchmark data set.

  18. Analysis of Vector Quantizers Using Transformed Codebooks with Application to Feedback-Based Multiple Antenna Systems

    Directory of Open Access Journals (Sweden)

    Bhaskar D. Rao

    2008-07-01

    Full Text Available Transformed codebooks are obtained by a transformation of a given codebook to best match the statistical environment at hand. The procedure, though suboptimal, has recently been suggested for feedback of channel state information (CSI in multiple antenna systems with correlated channels because of their simplicity and effectiveness. In this paper, we first consider the general distortion analysis of vector quantizers with transformed codebooks. Bounds on the average system distortion of this class of quantizers are provided. It exposes the effects of two kinds of suboptimality introduced by the transformed codebook, namely, the loss caused by suboptimal point density and the loss caused by mismatched Voronoi shape. We then focus our attention on the application of the proposed general framework to providing capacity analysis of a feedback-based MISO system over spatially correlated fading channels. In particular, with capacity loss as an objective function, upper and lower bounds on the average distortion of MISO systems with transformed codebooks are provided and compared to that of the optimal channel quantizers. The expressions are examined to provide interesting insights in the high and low SNR regime. Numerical and simulation results are presented which confirm the tightness of the distortion bounds.

  19. New Host-Vector System for Thermus spp. Based on the Malate Dehydrogenase Gene

    Science.gov (United States)

    Kayser, Kevin J.; Kilbane, John J.

    2001-01-01

    A Thermus thermophilus HB27 strain was constructed in which the malate dehydrogenase (mdh) gene was deleted. The Δmdh colonies are recognized by a small-colony phenotype. Wild-type phenotype is restored by transformation with Thermus plasmids or integration vector containing an intact mdh gene. The wild-type phenotype provides a positive selection tool for the introduction of plasmid DNA into Thermus spp., and because mdh levels can be readily quantified, this host-vector system is a convenient tool for monitoring gene expression. PMID:11160114

  20. Support Vector Machine based diagnostic system for thyroid cancer using statistical texture features.

    Science.gov (United States)

    Gopinath, B; Shanthi, N

    2013-01-01

    The aim of this study was to develop an automated computer-aided diagnostic system for diagnosis of thyroid cancer pattern in fine needle aspiration cytology (FNAC) microscopic images with high degree of sensitivity and specificity using statistical texture features and a Support Vector Machine classifier (SVM). A training set of 40 benign and 40 malignant FNAC images and a testing set of 10 benign and 20 malignant FNAC images were used to perform the diagnosis of thyroid cancer. Initially, segmentation of region of interest (ROI) was performed by region-based morphology segmentation. The developed diagnostic system utilized statistical texture features derived from the segmented images using a Gabor filter bank at various wavelengths and angles. Finally, the SVM was used as a machine learning algorithm to identify benign and malignant states of thyroid nodules. The SVMachieved a diagnostic accuracy of 96.7% with sensitivity and specificity of 95% and 100%, respectively, at a wavelength of 4 and an angle of 45. The results show that the diagnosis of thyroid cancer in FNAC images can be effectively performed using statistical texture information derived with Gabor filters in association with an SVM.

  1. Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

    Science.gov (United States)

    Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

    2018-01-01

    Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

  2. On the KDD’99 Dataset: Support Vector Machine Based Intrusion Detection System (IDS) with Different Kernels

    OpenAIRE

    Md. Al MehediHasan; Mohammed Nasser; Biprodip Pal

    2013-01-01

    The success of any Intrusion Detection System (IDS) is a complicated problem due to its nonlinearity and the quantitative or qualitative network traffic data stream with many features. To get rid of this problem, several types of intrusion detection methods have been proposed and shown different levels of accuracy. This is why, the choice of the effective and robust method for IDS is very important topic in information security. Support vector machine (SVM) has been employed to provide potent...

  3. Diagnosing tuberculosis with a novel support vector machine-based artificial immune recognition system.

    Science.gov (United States)

    Saybani, Mahmoud Reza; Shamshirband, Shahaboddin; Golzari Hormozi, Shahram; Wah, Teh Ying; Aghabozorgi, Saeed; Pourhoseingholi, Mohamad Amin; Olariu, Teodora

    2015-04-01

    Tuberculosis (TB) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. Diagnosis based on cultured specimens is the reference standard, however results take weeks to process. Scientists are looking for early detection strategies, which remain the cornerstone of tuberculosis control. Consequently there is a need to develop an expert system that helps medical professionals to accurately and quickly diagnose the disease. Artificial Immune Recognition System (AIRS) has been used successfully for diagnosing various diseases. However, little effort has been undertaken to improve its classification accuracy. In order to increase the classification accuracy of AIRS, this study introduces a new hybrid system that incorporates a support vector machine into AIRS for diagnosing tuberculosis. Patient epacris reports obtained from the Pasteur laboratory of Iran were used as the benchmark data set, with the sample size of 175 (114 positive samples for TB and 60 samples in the negative group). The strategy of this study was to ensure representativeness, thus it was important to have an adequate number of instances for both TB and non-TB cases. The classification performance was measured through 10-fold cross-validation, Root Mean Squared Error (RMSE), sensitivity and specificity, Youden's Index, and Area Under the Curve (AUC). Statistical analysis was done using the Waikato Environment for Knowledge Analysis (WEKA), a machine learning program for windows. With an accuracy of 100%, sensitivity of 100%, specificity of 100%, Youden's Index of 1, Area Under the Curve of 1, and RMSE of 0, the proposed method was able to successfully classify tuberculosis patients. There have been many researches that aimed at diagnosing tuberculosis faster and more accurately. Our results described a model for diagnosing tuberculosis with 100% sensitivity and 100% specificity. This model can be used as an additional tool for

  4. Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System

    Directory of Open Access Journals (Sweden)

    Hong-Chan Chang

    2014-01-01

    Full Text Available This study endeavors to develop a cloud monitoring system for solar plants. This system incorporates numerous subsystems, such as a geographic information system, an instantaneous power-consumption information system, a reporting system, and a failure diagnosis system. Visual C# was integrated with ASP.NET and SQL technologies for the proposed monitoring system. A user interface for database management system was developed to enable users to access solar power information and management systems. In addition, by using peer-to-peer (P2P streaming technology and audio/video encoding/decoding technology, real-time video data can be transmitted to the client end, providing instantaneous and direct information. Regarding smart failure diagnosis, the proposed system employs the support vector machine (SVM theory to train failure mathematical models. The solar power data are provided to the SVM for analysis in order to determine the failure types and subsequently eliminate failures at an early stage. The cloud energy-management platform developed in this study not only enhances the management and maintenance efficiency of solar power plants but also increases the market competitiveness of solar power generation and renewable energy.

  5. Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines

    Directory of Open Access Journals (Sweden)

    M. T. Mushtaq

    2015-04-01

    Full Text Available Cognitive radio based network enables opportunistic dynamic spectrum access by sensing, adopting and utilizing the unused portion of licensed spectrum bands. Cognitive radio is intelligent enough to adapt the communication parameters of the unused licensed spectrum. Spectrum sensing is one of the most important tasks of the cognitive radio cycle. In this paper, the auto-correlation function kernel based Support Vector Machine (SVM classifier along with Welch's Periodogram detector is successfully implemented for the detection of four QPSK (Quadrature Phase Shift Keying based signals propagating through an AWGN (Additive White Gaussian Noise channel. It is shown that the combination of statistical signal processing and machine learning concepts improve the spectrum sensing process and spectrum sensing is possible even at low Signal to Noise Ratio (SNR values up to -50 dB.

  6. Dual delivery systems based on polyamine analog BENSpm as prodrug and gene delivery vectors

    Science.gov (United States)

    Zhu, Yu

    Combination drug and gene therapy shows promise in cancer treatment. However, the success of such strategy requires careful selection of the therapeutic agents, as well as development of efficient delivery vectors. BENSpm (N 1, N11-bisethylnorspermine), a polyamine analogue targeting the intracellular polyamine pathway, draws our special attention because of the following reasons: (1) polyamine pathway is frequently dysregulated in cancer; (2) BENSpm exhibits multiple functions to interfere with the polyamine pathway, such as to up-regulate polyamine metabolism enzymes and down-regulate polyamine biosynthesis enzymes. Therefore BENSpm depletes all natural polyamines and leads to apoptosis and cell growth inhibition in a wide range of cancers; (3) preclinical studies proved that BENSpm can act synergistically with various chemotherapy agents, making it a promising candidate in combination therapy; (4) multiple positive charges in BENSpm enable it as a suitable building block for cationic polymers, which can be further applied to gene delivery. In this dissertation, our goal was to design dual-function delivery vector based on BENSpm that can function as a gene delivery vector and, after intracellular degradation, as an active anticancer agent targeting dysregulated polyamine metabolism. We first demonstrated strong synergism between BENSpm and a potential therapeutic gene product TRAIL. Strong synergism was obtained in both estrogen-dependent MCF-7 breast cancer cells and triple-negative MDA-MB-231 breast cancer cells. Significant dose reduction of TRAIL in combination with BENSpm in MDA-MB-231 cells, together with the fact that BENSpm rendered MCF-7 cells more sensitive to TRAIL treatment verified our rationale of designing BENSpm-based delivery platform. This was expected to be beneficial for overcoming drug resistance in chemotherapy, as well as boosting the therapeutic effect of therapeutic genes. We first designed a lipid-based BENSpm dual vector (Lipo

  7. CW-THz vector spectroscopy and imaging system based on 1.55-µm fiber-optics.

    Science.gov (United States)

    Kim, Jae-Young; Song, Ho-Jin; Yaita, Makoto; Hirata, Akihiko; Ajito, Katsuhiro

    2014-01-27

    We present a continuous-wave terahertz (THz) vector spectroscopy and imaging system based on a 1.5-µm fiber optic uni-traveling-carrier photodiode and InGaAs photo-conductive receiver. Using electro-optic (EO) phase modulators for THz phase control with shortened optical paths, the system achieves fast vector measurement with effective phase stabilization. Dynamic ranges of 100 dB · Hz and 75 dB · Hz at 300 GHz and 1 THz, and phase stability of 1.5° per minute are obtained. With the simultaneous measurement of absorbance and relative permittivity, we demonstrate non-destructive analyses of pharmaceutical cocrystals inside tablets within a few minutes.

  8. Support-Vector-Machine-Based Reduced-Order Model for Limit Cycle Oscillation Prediction of Nonlinear Aeroelastic System

    Directory of Open Access Journals (Sweden)

    Gang Chen

    2012-01-01

    Full Text Available It is not easy for the system identification-based reduced-order model (ROM and even eigenmode based reduced-order model to predict the limit cycle oscillation generated by the nonlinear unsteady aerodynamics. Most of these traditional ROMs are sensitive to the flow parameter variation. In order to deal with this problem, a support vector machine- (SVM- based ROM was investigated and the general construction framework was proposed. The two-DOF aeroelastic system for the NACA 64A010 airfoil in transonic flow was then demonstrated for the new SVM-based ROM. The simulation results show that the new ROM can capture the LCO behavior of the nonlinear aeroelastic system with good accuracy and high efficiency. The robustness and computational efficiency of the SVM-based ROM would provide a promising tool for real-time flight simulation including nonlinear aeroelastic effects.

  9. A validated system for ligation-free USER™ -based assembly of expression vectors for mammalian cell engineering

    DEFF Research Database (Denmark)

    Lund, Anne Mathilde; Kildegaard, Helene Faustrup; Hansen, Bjarne Gram

    The development in the field of mammalian cell factories require fast and high-throughput methods, this means a high need for simpler and more efficient cloning techniques. For optimization of protein expression by genetic engineering and for allowing metabolic engineering in mammalian cells, a new...... versatile expression vector system was developed. This vector system applies the ligation-free uracilexcision cloning technique to construct mammalian expression vectors of multiple parts and with maximum flexibility....

  10. Chitosan-based gene delivery vectors targeted to the peripheral nervous system.

    Science.gov (United States)

    Oliveira, Hugo; Pires, Liliana R; Fernandez, Ramon; Martins, M Cristina L; Simões, Sérgio; Pêgo, Ana P

    2010-12-01

    A non-toxic, targeted, simple and efficient system that can specifically transfect peripheral sensorial neurons can pave the way towards the development of new therapeutics for the treatment of peripheral neuropathies. In this study chitosan (CH), a biodegradable polymer, was used as the starting material in the design of a multicomponent vector targeted to the peripheral nervous system (PNS). Polycation-DNA complexes were optimized using imidazole- and thiol-grafted CH (CHimiSH), in order to increase transfection efficiency and allow the formation of ligand conjugated nanocomplexes, respectively. The 50 kDa non-toxic fragment from the tetanus toxin (HC), shown to interact specifically with peripheral neurons and undergo retrograde transport, was grafted to the binary complex via a bi-functional poly(ethylene glycol) (HC-PEG) reactive for the thiol moieties present in the complex surface. The targeting of the developed nanocomplexes was assessed by means of internalization and transfection studies in the ND7/23 (neuronal) vs. NIH 3T3 (fibroblast) cell lines. Targeted transfection was further confirmed in dorsal root ganglion dissociated primary cultures. A versatile, multi-component nanoparticle system that successfully targets and transfects neuronal cell lines, as well as dorsal root ganglia (DRG) primary neuron cultures was obtained for the 1.0 (w/w) HC-PEG/DNA formulation. © 2010 Wiley Periodicals, Inc. J Biomed Mater Res Part A, 2010.

  11. An Emotion Detection System Based on Multi Least Squares Twin Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Divya Tomar

    2014-01-01

    Full Text Available Posttraumatic stress disorder (PTSD, bipolar manic disorder (BMD, obsessive compulsive disorder (OCD, depression, and suicide are some major problems existing in civilian and military life. The change in emotion is responsible for such type of diseases. So, it is essential to develop a robust and reliable emotion detection system which is suitable for real world applications. Apart from healthcare, importance of automatically recognizing emotions from human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications. Detection of emotion in speech can be applied in a variety of situations to allocate limited human resources to clients with the highest levels of distress or need, such as in automated call centers or in a nursing home. In this paper, we used a novel multi least squares twin support vector machine classifier in order to detect seven different emotions such as anger, happiness, sadness, anxiety, disgust, panic, and neutral emotions. The experimental result indicates better performance of the proposed technique over other existing approaches. The result suggests that the proposed emotion detection system may be used for screening of mental status.

  12. Potato virus X and Tobacco mosaic virus-based vectors compatible with the Gateway-TM cloning system

    NARCIS (Netherlands)

    Lacorte, C.C.; Ribeiro, S.G.; Lohuis, H.; Goldbach, R.W.; Prins, M.W.

    2010-01-01

    Virus-based expression vectors are important tools for high-level production of foreign proteins and for gene function analysis through virus induced gene silencing. To exploit further their advantages as fast, high yield replicons, a set of vectors was produced by converting and adapting Potato

  13. A least square support vector machine-based approach for contingency classification and ranking in a large power system

    Directory of Open Access Journals (Sweden)

    Bhanu Pratap Soni

    2016-12-01

    Full Text Available This paper proposes an effective supervised learning approach for static security assessment of a large power system. Supervised learning approach employs least square support vector machine (LS-SVM to rank the contingencies and predict the system severity level. The severity of the contingency is measured by two scalar performance indices (PIs: line MVA performance index (PIMVA and Voltage-reactive power performance index (PIVQ. SVM works in two steps. Step I is the estimation of both standard indices (PIMVA and PIVQ that is carried out under different operating scenarios and Step II contingency ranking is carried out based on the values of PIs. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus (New England system. The approach can be beneficial tool which is less time consuming and accurate security assessment and contingency analysis at energy management center.

  14. Rational design and engineering of a modified adeno-associated virus (AAV1)-based vector system for enhanced retrograde gene delivery.

    Science.gov (United States)

    Davis, Adam S; Federici, Thais; Ray, William C; Boulis, Nicholas M; OʼConnor, Deirdre; Clark, K Reed; Bartlett, Jeffrey S

    2015-02-01

    After injection into muscle and peripheral nerves, a variety of viral vectors undergo retrograde transport to lower motor neurons. However, because of its attractive safety profile and durable gene expression, adeno-associated virus (AAV) remains the only vector to have been applied to the human nervous system for the treatment of neurodegenerative disease. Nonetheless, only a very small fraction of intramuscularly injected AAV vector arrives at the spinal cord. To engineer a novel AAV vector by inserting a neuronal targeting peptide (Tet1), with binding properties similar to those of tetanus toxin, into the AAV1 capsid. Integral to this approach was the use of structure-based design to increase the effectiveness of functional capsid engineering. This approach allowed the optimization of scaffolding regions for effective display of the foreign epitope while minimizing disruption of the native capsid structure. We also validated an approach by which low-titer tropism-modified AAV vectors can be rescued by particle mosaicism with unmodified capsid proteins. Importantly, our rationally engineered AAV1-based vectors exhibited markedly enhanced transduction of cultured motor neurons, diminished transduction of nontarget cells, and markedly superior retrograde delivery compared with unmodified AAV1 vector. This approach promises a significant advancement in the rational engineering of AAV vectors for diseases of the nervous system and other organs.

  15. High performance computing on vector systems

    CERN Document Server

    Roller, Sabine

    2008-01-01

    Presents the developments in high-performance computing and simulation on modern supercomputer architectures. This book covers trends in hardware and software development in general and specifically the vector-based systems and heterogeneous architectures. It presents innovative fields like coupled multi-physics or multi-scale simulations.

  16. Quantitative Assessment of Pap Smear Cells by PC-Based Cytopathologic Image Analysis System and Support Vector Machine

    Science.gov (United States)

    Huang, Po-Chi; Chan, Yung-Kuan; Chan, Po-Chou; Chen, Yung-Fu; Chen, Rung-Ching; Huang, Yu-Ruei

    Cytologic screening has been widely used for controlling the prevalence of cervical cancer. Errors from sampling, screening and interpretation, still concealed some unpleasant results. This study aims at designing a cellular image analysis system based on feasible and available software and hardware for a routine cytologic laboratory. Totally 1814 cellular images from the liquid-based cervical smears with Papanicolaou stain in 100x, 200x, and 400x magnification were captured by a digital camera. Cell images were reviewed by pathologic experts with peer agreement and only 503 images were selected for further study. The images were divided into 4 diagnostic categories. A PC-based cellular image analysis system (PCCIA) was developed for computing morphometric parameters. Then support vector machine (SVM) was used to classify signature patterns. The results show that the selected 13 morphometric parameters can be used to correctly differentiate the dysplastic cells from the normal cells (p<0.001). Additionally, SVM classifier has been demonstrated to be able to achieve a high accuracy for cellular classification. In conclusion, the proposed system provides a feasible and effective tool for the evaluation of gynecologic cytologic specimens.

  17. Independent Component Analysis-Support Vector Machine-Based Computer-Aided Diagnosis System for Alzheimer's with Visual Support.

    Science.gov (United States)

    Khedher, Laila; Illán, Ignacio A; Górriz, Juan M; Ramírez, Javier; Brahim, Abdelbasset; Meyer-Baese, Anke

    2017-05-01

    Computer-aided diagnosis (CAD) systems constitute a powerful tool for early diagnosis of Alzheimer's disease (AD), but limitations on interpretability and performance exist. In this work, a fully automatic CAD system based on supervised learning methods is proposed to be applied on segmented brain magnetic resonance imaging (MRI) from Alzheimer's disease neuroimaging initiative (ADNI) participants for automatic classification. The proposed CAD system possesses two relevant characteristics: optimal performance and visual support for decision making. The CAD is built in two stages: a first feature extraction based on independent component analysis (ICA) on class mean images and, secondly, a support vector machine (SVM) training and classification. The obtained features for classification offer a full graphical representation of the images, giving an understandable logic in the CAD output, that can increase confidence in the CAD support. The proposed method yields classification results up to 89% of accuracy (with 92% of sensitivity and 86% of specificity) for normal controls (NC) and AD patients, 79% of accuracy (with 82% of sensitivity and 76% of specificity) for NC and mild cognitive impairment (MCI), and 85% of accuracy (with 85% of sensitivity and 86% of specificity) for MCI and AD patients.

  18. 3D Modelling of a Vectored Water Jet-Based Multi-Propeller Propulsion System for a Spherical Underwater Robot

    Directory of Open Access Journals (Sweden)

    Xichuan Lin

    2013-01-01

    Full Text Available This paper presents an improved modelling method for a water jet-based multi-propeller propulsion system. In our previous work, the modelling experiments were only carried out in 2D planes, whose experimental results had poor agreement when we wanted to control the propulsive forces in 3D space directly. This research extends the 2D modelling described in the authors' previous work into 3D space. By doing this, the model could include 3D space information, which is more useful than that of 2D space. The effective propulsive forces and moments in 3D space can be obtained directly by synthesizing the propulsive vectors of propellers. For this purpose, a novel experimental mechanism was developed to achieve the proposed 3D modelling. This mechanism was designed with the mass distribution centred for the robot. By installing a six-axis load-cell sensor at the equivalent mass centre, we obtained the direct propulsive effect of the system for the robot. Also, in this paper, the orientation surface and propulsive surfaces are developed to provide the 3D information of the propulsive system. Experiments for each propeller were first carried out to establish the models. Then, further experiments were carried out with all of the propellers working together to validate the models. Finally, we compared the various experimental results with the simulation data. The utility of this modelling method is discussed at length.

  19. Efficient transformation system for Propionibacterium freudenreichii based on a novel vector

    NARCIS (Netherlands)

    Jore, J.P.M.; Luijk, N. van; Luiten, R.G.M.; Werf, M.J. van der; Pouwels, P.H.

    2001-01-01

    A 3.6-kb endogenous plasmid was isolated from a Propionibacterium freudenreichii strain and sequenced completely. Based on homologies with plasmids from other bacteria, notably a plasmid from Mycobacterium, a region harboring putative replicative functions was defined. Outside this region two

  20. VectorBase: a home for invertebrate vectors of human pathogens

    Science.gov (United States)

    Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Emmert, David; Hammond, Martin; Hill, Catherine A.; Kennedy, Ryan C.; Lobo, Neil F.; MacCallum, M. Robert; Madey, Greg; Megy, Karine; Redmond, Seth; Russo, Susan; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Zdobnov, Evgeny M.; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.

    2007-01-01

    VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever. PMID:17145709

  1. Novel Cytotoxic Vectors Based on Adeno-Associated Virus

    Directory of Open Access Journals (Sweden)

    Johannes Kohlschütter

    2010-12-01

    Full Text Available Vectors based on adeno-associated virus (AAV are promising tools for gene therapy. The production of strongly toxic vectors, for example for cancer-directed gene transfer, is often unfeasible due to uncontrolled expression of toxic genes in vector-producing cells. Using an approach based on transcriptional repression, we have created novel AAV vectors carrying the genes coding for diphtheria toxin A (DTA and the pro-apoptotic PUMA protein. The DTA vector had a significant toxic effect on a panel of tumor cell lines, and abrogation of protein synthesis could be shown. The PUMA vector had a toxic effect on HeLa and RPMI 8226 cells, and sensitized transduced cells to doxorubicin. To permit targeted gene transfer, we incorporated the DTA gene into a genetically modified AAV-2 capsid previously developed by our group that mediates enhanced transduction of murine breast cancer cells in vitro. This vector had a stronger cytotoxic effect on breast cancer cells than DTA vectors with wildtype AAV capsid or vectors with a random capsid modification. The vector production and application system presented here allows for easy exchange of promotors, transgenes and capsid specificity for certain target cells. It will therefore be of great possible value in a broad range of applications in cytotoxic gene therapy and significantly broadens the spectrum of available tools for AAV-based gene therapy.

  2. Assessing the tobacco-rattle-virus-based vectors system as an efficient gene silencing technique in Datura stramonium (Solanaceae).

    Science.gov (United States)

    Eftekhariyan Ghamsari, Mohammad Reza; Karimi, Farah; Mousavi Gargari, Seyed Latif; Hosseini Tafreshi, Seyed Ali; Salami, Seyed Alireza

    2014-12-01

    Datura stramonium is a well-known medicinal plant, which is important for its alkaloids. There are intrinsic limitations for the natural production of alkaloids in plants; metabolic engineering methods can be effectively used to conquer these limitations. In order for this the genes involved in corresponding pathways need to be studied. Virus-Induced Gene Silencing is known as a functional genomics technique to knock-down expression of endogenous genes. In this study, we silenced phytoene desaturase as a marker gene in D. stramonium in a heterologous and homologous manner by tobacco-rattle-virus-based VIGS vectors. Recombinant TRV vector containing pds gene from D. stramonium (pTRV2-Dspds) was constructed and injected into seedlings. The plants injected with pTRV2-Dspds showed photobleaching 2 weeks after infiltration. Spectrophotometric analysis demonstrated that the amount of chlorophylls and carotenoids in leaves of the bleached plants decreased considerably compared to that of the control plants. Semi-Quantitative RT-PCR results also confirmed that the expression of pds gene in the silenced plants was significantly reduced in comparison with the control plants. The results showed that the viral vector was able to influence the levels of total alkaloid content in D. stramonium. Our results illustrated that TRV-based VIGS vectors are able to induce effective and reliable functional gene silencing in D. stramonium as an alternative tool for studying the genes of interest in this plant, such as the targeted genes in tropane alkaloid biosynthetic pathway. The present work is the first report of establishing VIGS as an efficient method for transient silencing of any gene of interest in D. stramonium.

  3. The Automation System Censor Speech for the Indonesian Rude Swear Words Based on Support Vector Machine and Pitch Analysis

    Science.gov (United States)

    Endah, S. N.; Nugraheni, D. M. K.; Adhy, S.; Sutikno

    2017-04-01

    According to Law No. 32 of 2002 and the Indonesian Broadcasting Commission Regulation No. 02/P/KPI/12/2009 & No. 03/P/KPI/12/2009, stated that broadcast programs should not scold with harsh words, not harass, insult or demean minorities and marginalized groups. However, there are no suitable tools to censor those words automatically. Therefore, researches to develop a system of intelligent software to censor the words automatically are needed. To conduct censor, the system must be able to recognize the words in question. This research proposes the classification of speech divide into two classes using Support Vector Machine (SVM), first class is set of rude words and the second class is set of properly words. The speech pitch values as an input in SVM, it used for the development of the system for the Indonesian rude swear word. The results of the experiment show that SVM is good for this system.

  4. A Modified Recession Vector Method Based on the Optimization-Simulation Approach to Design Problems of Information Security Systems

    Directory of Open Access Journals (Sweden)

    A. Yu. Bykov

    2015-01-01

    Full Text Available Modern practical task-solving techniques for designing information security systems in different purpose automated systems assume the solution of optimization tasks when choosing different elements of a security system. Formulations of mathematical programming tasks are rather often used, but in practical tasks it is not always analytically possible to set target function and (or restrictions in an explicit form. Sometimes, calculation of the target function value or checking of restrictions for the possible decision can be reduced to carrying out experiments on a simulation model of system. Similar tasks are considered within optimization-simulation approach and require the ad hoc methods of optimization considering the possible high computational effort of simulation.The article offers a modified recession vector method, which is used in tasks of discrete optimization to solve the similar problems. The method is applied when the task to be solved is to minimize the cost of selected information security tools in case of restriction on the maximum possible damage. The cost index is the linear function of the Boolean variables, which specify the selected security tools, with the restriction set as an "example simulator". Restrictions can be actually set implicitly. A validity of the possible solution is checked using a simulation model of the system.The offered algorithm of a method considers features of an objective. The main advantage of algorithm is that it requires a maximum of m+1 of steps where m is a dimensionality of the required vector of Boolean variables. The algorithm provides finding a local minimum by using the Hamming metrics in the discrete space; the radius of neighborhood is equal to 1. These statements are proved.The paper presents solution results of choosing security tools with the specified basic data.

  5. Genetic engineering in Actinoplanes sp. SE50/110 - development of an intergeneric conjugation system for the introduction of actinophage-based integrative vectors.

    Science.gov (United States)

    Gren, Tetiana; Ortseifen, Vera; Wibberg, Daniel; Schneiker-Bekel, Susanne; Bednarz, Hanna; Niehaus, Karsten; Zemke, Till; Persicke, Marcus; Pühler, Alfred; Kalinowski, Jörn

    2016-08-20

    The α-glucosidase inhibitor acarbose is used for treatment of diabetes mellitus type II, and is manufactured industrially with overproducing derivatives of Actinoplanes sp. SE50/110, reportedly obtained by conventional mutagenesis. Despite of high industrial significance, only limited information exists regarding acarbose metabolism, function and regulation of these processes, due to the absence of proper genetic engineering methods and tools developed for this strain. Here, a basic toolkit for genetic engineering of Actinoplanes sp. SE50/110 was developed, comprising a standardized protocol for a DNA transfer through Escherichia coli-Actinoplanes intergeneric conjugation and applied for the transfer of ϕC31, ϕBT1 and VWB actinophage-based integrative vectors. Integration sites, occurring once per genome for all vectors, were sequenced and characterized for the first time in Actinoplanes sp. SE50/110. Notably, in case of ϕC31 based vector pSET152, the integration site is highly conserved, while for ϕBT1 and the VWB based vectors pRT801 and pSOK804, respectively, no sequence similarities to those in other bacteria were detected. The studied plasmids were proven to be stable and neutral with respect to strain morphology and acarbose production, enabling future use for genetic manipulations of Actinoplanes sp. SE50/110. To further broaden the spectrum of available tools, a GUS reporter system, based on the pSET152 derived vector, was also established in Actinoplanes sp. SE50/110. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. A geographical information system-based multicriteria evaluation to map areas at risk for Rift Valley fever vector-borne transmission in Italy.

    Science.gov (United States)

    Tran, A; Ippoliti, C; Balenghien, T; Conte, A; Gely, M; Calistri, P; Goffredo, M; Baldet, T; Chevalier, V

    2013-11-01

    Rift Valley fever (RVF) is a severe mosquito-borne disease that is caused by a Phlebovirus (Bunyaviridae) and affects domestic ruminants and humans. Recently, its distribution widened, threatening Europe. The probability of the introduction and large-scale spread of Rift Valley fever virus (RVFV) in Europe is low, but localized RVF outbreaks may occur in areas where populations of ruminants and potential vectors are present. In this study, we assumed the introduction of the virus into Italy and focused on the risk of vector-borne transmission of RVFV to three main European potential hosts (cattle, sheep and goats). Five main potential mosquito vectors belonging to the Culex and Aedes genera that are present in Italy were identified in a literature review. We first modelled the geographical distribution of these five species based on expert knowledge and using land cover as a proxy of mosquito presence. The mosquito distribution maps were compared with field mosquito collections from Italy to validate the model. Next, the risk of RVFV transmission was modelled using a multicriteria evaluation (MCE) approach, integrating expert knowledge and the results of a literature review on host sensitivity and vector competence, feeding behaviour and abundance. A sensitivity analysis was performed to assess the robustness of the results with respect to expert choices. The resulting maps include (i) five maps of the vector distribution, (ii) a map of suitable areas for vector-borne transmission of RVFV and (iii) a map of the risk of RVFV vector-borne transmission to sensitive hosts given a viral introduction. Good agreement was found between the modelled presence probability and the observed presence or absence of each vector species. The resulting RVF risk map highlighted strong spatial heterogeneity and could be used to target surveillance. In conclusion, the geographical information system (GIS)-based MCE served as a valuable framework and a flexible tool for mapping the

  7. Performance improvement of 64-QAM coherent optical communication system by optimizing symbol decision boundary based on support vector machine

    Science.gov (United States)

    Chen, Wei; Zhang, Junfeng; Gao, Mingyi; Shen, Gangxiang

    2018-03-01

    High-order modulation signals are suited for high-capacity communication systems because of their high spectral efficiency, but they are more vulnerable to various impairments. For the signals that experience degradation, when symbol points overlap on the constellation diagram, the original linear decision boundary cannot be used to distinguish the classification of symbol. Therefore, it is advantageous to create an optimum symbol decision boundary for the degraded signals. In this work, we experimentally demonstrated the 64-quadrature-amplitude modulation (64-QAM) coherent optical communication system using support-vector machine (SVM) decision boundary algorithm to create the optimum symbol decision boundary for improving the system performance. We investigated the influence of various impairments on the 64-QAM coherent optical communication systems, such as the impairments caused by modulator nonlinearity, phase skew between in-phase (I) arm and quadrature-phase (Q) arm of the modulator, fiber Kerr nonlinearity and amplified spontaneous emission (ASE) noise. We measured the bit-error-ratio (BER) performance of 75-Gb/s 64-QAM signals in the back-to-back and 50-km transmission. By using SVM to optimize symbol decision boundary, the impairments caused by I/Q phase skew of the modulator, fiber Kerr nonlinearity and ASE noise are greatly mitigated.

  8. Viral vector-based influenza vaccines

    Science.gov (United States)

    de Vries, Rory D.; Rimmelzwaan, Guus F.

    2016-01-01

    ABSTRACT Antigenic drift of seasonal influenza viruses and the occasional introduction of influenza viruses of novel subtypes into the human population complicate the timely production of effective vaccines that antigenically match the virus strains that cause epidemic or pandemic outbreaks. The development of game-changing vaccines that induce broadly protective immunity against a wide variety of influenza viruses is an unmet need, in which recombinant viral vectors may provide. Use of viral vectors allows the delivery of any influenza virus antigen, or derivative thereof, to the immune system, resulting in the optimal induction of virus-specific B- and T-cell responses against this antigen of choice. This systematic review discusses results obtained with vectored influenza virus vaccines and advantages and disadvantages of the currently available viral vectors. PMID:27455345

  9. Design of Online Monitoring and Fault Diagnosis System for Belt Conveyors Based on Wavelet Packet Decomposition and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Wei Li

    2013-01-01

    Full Text Available Belt conveyors are the equipment widely used in coal mines and other manufacturing factories, whose main components are a number of idlers. The faults of belt conveyors can directly influence the daily production. In this paper, a fault diagnosis method combining wavelet packet decomposition (WPD and support vector machine (SVM is proposed for monitoring belt conveyors with the focus on the detection of idler faults. Since the number of the idlers could be large, one acceleration sensor is applied to gather the vibration signals of several idlers in order to reduce the number of sensors. The vibration signals are decomposed with WPD, and the energy of each frequency band is extracted as the feature. Then, the features are employed to train an SVM to realize the detection of idler faults. The proposed fault diagnosis method is firstly tested on a testbed, and then an online monitoring and fault diagnosis system is designed for belt conveyors. An experiment is also carried out on a belt conveyor in service, and it is verified that the proposed system can locate the position of the faulty idlers with a limited number of sensors, which is important for operating belt conveyors in practices.

  10. Generalized Derivative Based Kernelized Learning Vector Quantization

    NARCIS (Netherlands)

    Schleif, Frank-Michael; Villmann, Thomas; Hammer, Barbara; Schneider, Petra; Biehl, Michael; Fyfe, Colin; Tino, Peter; Charles, Darryl; Garcia-Osoro, Cesar; Yin, Hujun

    2010-01-01

    We derive a novel derivative based version of kernelized Generalized Learning Vector Quantization (KGLVQ) as an effective, easy to interpret, prototype based and kernelized classifier. It is called D-KGLVQ and we provide generalization error bounds, experimental results on real world data, showing

  11. Vector coherent states for nanoparticle systems

    Energy Technology Data Exchange (ETDEWEB)

    Aremua, Isiaka [Institut de Mathematiques et de Sciences Physiques (IMSP), University of Abomey-Calavi, 01 BP 613 Porto-Novo (Benin); Hounkonnou, Mahouton Norbert, E-mail: iaremua@imsp-uac.org, E-mail: norbert.hounkonnou@cipma.uac.bj [International Chair of Mathematical Physics and Applications (ICMPA-UNESCO Chair), University of Abomey-Calavi, 072 BP 50 Cotonou (Benin)

    2011-11-18

    The first part of this work deals with a formalism of vector coherent states construction for a system of M Fermi-type modes associated with N bosonic modes. Then follows a generalization to a Hamiltonian describing the translational motion of the center of mass of a nanoparticle. The latter gives rise to a new mechanism for the electronic energy relaxation in nanocrystals, intensively studied today in condensed matter physics. Finite degeneracies of the involved Hamiltonian systems are also investigated. The defined vector coherent states satisfy relevant mathematical properties of continuity, resolution of identity, temporal stability and action identity. (paper)

  12. Evaluation of an AAV2-based rapamycin-regulated glial cell line-derived neurotrophic factor (GDNF expression vector system.

    Directory of Open Access Journals (Sweden)

    Piotr Hadaczek

    Full Text Available Effective regulation of transgene product in anatomically circumscribed brain tissue is dependent on the pharmacokinetics of the regulating agent, the kinetics of transcriptional activation and degradation of the transgene product. We evaluated rapamycin-regulated AAV2-GDNF expression in the rat brain (striatum. Regulated (a dual-component system: AAV2-FBZhGDNF + AAV2-TF1Nc and constitutive (CMV-driven expression vectors were compared. Constitutively active AAV2-GDNF directed stable GDNF expression in a dose-dependent manner and it increased for the first month, thereafter reaching a plateau that was maintained over a further 3 months. For the AAV2-regGDNF, rapamycin was administered in a 3-days on/4-days off cycle. Intraperitoneal, oral, and direct brain delivery (CED of rapamycin were evaluated. Two cycles of rapamycin at an intraperitoneal dose of 10 mg/kg gave the highest GDNF level (2.75±0.01 ng/mg protein. Six cycles at 3 mg/kg resulted in lower GDNF values (1.36±0.3 ng/mg protein. Interestingly, CED of rapamycin into the brain at a very low dose (50 ng induced GDNF levels comparable to a 6-week intraperitoneal rapamycin cycle. This study demonstrates the effectiveness of rapamycin regulation in the CNS. However, the kinetics of the transgene in brain tissue, the regulator dosing amount and schedule are critical parameters that influence the kinetics of accumulation and zenith of the encoded transgene product.

  13. High stability vector-based direct power control for DFIG-based wind turbine

    DEFF Research Database (Denmark)

    Zhu, Rongwu; Chen, Zhe; Wu, Xiaojie

    2015-01-01

    This paper proposes an improved vector-based direct power control (DPC) strategy for the doubly-fed induction generator (DFIG)-based wind energy conversion system. Based on the small signal model, the proposed DPC improves the stability of the DFIG, and avoids the DFIG operating in the marginal...... stable region (the real part of eigenvalue is equal to zero). The vector-based DPC combines with a space vector modulation technique to achieve a constant switching frequency. The simulation and experimental results clearly validate the effectiveness and feasibility of the proposed vector-based DPC...

  14. Kunjin virus replicons: an RNA-based, non-cytopathic viral vector system for protein production, vaccine and gene therapy applications

    NARCIS (Netherlands)

    Pijlman, G.P.; Suhrbier, A.; Khromykh, A.A.

    2006-01-01

    The application of viral vectors for gene expression and delivery is rapidly evolving, with several entering clinical trials. However, a number of issues, including safety, gene expression levels, cell selectivity and antivector immunity, are driving the search for new vector systems. A number of

  15. Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

    DEFF Research Database (Denmark)

    Vlachogiannis, Ioannis (John); Lee, K Y

    2009-01-01

    In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem...

  16. A vector-based system for the differentiation of mouse embryonic stem cells toward germ-line cells

    Directory of Open Access Journals (Sweden)

    Reza Ebrahimzadeh-Vesal

    2014-08-01

    Conclusion: In this study, we demonstrated the in vitro generation of mouse embryonic stem cells to germ cells by using a backbone vector containing the fusion gene Stra8-EGFP. The Stra8 gene is a retinoic acid-responsive protein and is able to regulate meiotic initiation.

  17. An affordable, quality-assured community-based system for high-resolution entomological surveillance of vector mosquitoes that reflects human malaria infection risk patterns

    Directory of Open Access Journals (Sweden)

    Chaki Prosper P

    2012-05-01

    Full Text Available Abstract Background More sensitive and scalable entomological surveillance tools are required to monitor low levels of transmission that are increasingly common across the tropics, particularly where vector control has been successful. A large-scale larviciding programme in urban Dar es Salaam, Tanzania is supported by a community-based (CB system for trapping adult mosquito densities to monitor programme performance. Methodology An intensive and extensive CB system for routine, longitudinal, programmatic surveillance of malaria vectors and other mosquitoes using the Ifakara Tent Trap (ITT-C was developed in Urban Dar es Salaam, Tanzania, and validated by comparison with quality assurance (QA surveys using either ITT-C or human landing catches (HLC, as well as a cross-sectional survey of malaria parasite prevalence in the same housing compounds. Results Community-based ITT-C had much lower sensitivity per person-night of sampling than HLC (Relative Rate (RR [95% Confidence Interval (CI] = 0.079 [0.051, 0.121], P Anopheles gambiae s.l. and 0.153 [0.137, 0.171], P An. gambiae or Culex respectively. Despite the poor sensitivity of the ITT per night of sampling, when CB-ITT was compared with QA-HLC, it proved at least comparably sensitive in absolute terms (171 versus 169 primary vectors caught and cost-effective (153US$ versus 187US$ per An. gambiae caught because it allowed more spatially extensive and temporally intensive sampling (4284 versus 335 trap nights distributed over 615 versus 240 locations with a mean number of samples per year of 143 versus 141. Despite the very low vectors densities (Annual estimate of about 170 An gambiae s.l bites per person per year, CB-ITT was the only entomological predictor of parasite infection risk (Odds Ratio [95% CI] = 4.43[3.027,7. 454] per An. gambiae or Anopheles funestus caught per night, P =0.0373. Discussion and conclusion CB trapping approaches could be improved with more sensitive traps

  18. Vector Addition System Reversible Reachability Problem

    OpenAIRE

    Leroux, Jérôme

    2013-01-01

    International audience; The reachability problem for vector addition systems is a central problem of net theory. This problem is known to be decidable but the complexity is still unknown. Whereas the problem is EXPSPACE-hard, no elementary upper bounds complexity are known. In this paper we consider the reversible reachability problem. This problem consists to decide if two configurations are reachable one from each other, or equivalently if they are in the same strongly connected component o...

  19. Knowledge-Based Green's Kernel for Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Tahir Farooq

    2010-01-01

    Full Text Available This paper presents a novel prior knowledge-based Green's kernel for support vector regression (SVR. After reviewing the correspondence between support vector kernels used in support vector machines (SVMs and regularization operators used in regularization networks and the use of Green's function of their corresponding regularization operators to construct support vector kernels, a mathematical framework is presented to obtain the domain knowledge about magnitude of the Fourier transform of the function to be predicted and design a prior knowledge-based Green's kernel that exhibits optimal regularization properties by using the concept of matched filters. The matched filter behavior of the proposed kernel function makes it suitable for signals corrupted with noise that includes many real world systems. We conduct several experiments mostly using benchmark datasets to compare the performance of our proposed technique with the results already published in literature for other existing support vector kernel over a variety of settings including different noise levels, noise models, loss functions, and SVM variations. Experimental results indicate that knowledge-based Green's kernel could be seen as a good choice among the other candidate kernel functions.

  20. Improving the Drive System of Permanent Magnet Linear Synchronous Motor Based on Direct Thrust Force Control Applying Space Vector Modulation

    Directory of Open Access Journals (Sweden)

    Mehdi Manoochehri

    2012-07-01

    Full Text Available Applying the direct thrust force control (DFC method in permanent magnet linear synchronous motor (PMLSM leads to some important problems. The most important disadvantages of applying this method are electromagnetic force and linkage flux big ripple and variable switching frequency. In this paper space vector modulation (SVM technique is applied for removing the disadvantages of classic DFC method. SVM technique makes the switching frequency constant and provides continues Voltage space compared with discrete space in classic method. Simulation results confirmed the theory. They show that combining the DFC method with SVM technique removes lots of the disadvantages of classic DFC method like big ripples and variable switching and remains the benefits of this method.

  1. Vector Disparity Sensor with Vergence Control for Active Vision Systems

    Directory of Open Access Journals (Sweden)

    Eduardo Ros

    2012-02-01

    Full Text Available This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system.

  2. pAUL: a gateway-based vector system for adaptive expression and flexible tagging of proteins in Arabidopsis.

    Science.gov (United States)

    Lyska, Dagmar; Engelmann, Kerstin; Meierhoff, Karin; Westhoff, Peter

    2013-01-01

    Determination of protein function requires tools that allow its detection and/or purification. As generation of specific antibodies often is laborious and insufficient, protein tagging using epitopes that are recognized by commercially available antibodies and matrices appears more promising. Also, proper spatial and temporal expression of tagged proteins is required to prevent falsification of results. We developed a new series of binary Gateway cloning vectors named pAUL1-20 for C- and N-terminal in-frame fusion of proteins to four different tags: a single (i) HA epitope and (ii) Strep-tagIII, (iii) both epitopes combined to a double tag, and (iv) a triple tag consisting of the double tag extended by a Protein A tag possessing a 3C protease cleavage site. Expression can be driven by either the 35 S CaMV promoter or, for C-terminal fusions, promoters from genes encoding the chloroplast biogenesis factors HCF107, HCF136, or HCF173. Fusions of the four promoters to the GUS gene showed that endogenous promoter sequences are functional and drive expression more moderately and consistently throughout different transgenic lines when compared to the 35 S CaMV promoter. By testing complementation of mutations affected in chloroplast biogenesis factors HCF107 and HCF208, we found that the effect of different promoters and tags on protein function strongly depends on the protein itself. Single-step and tandem affinity purification of HCF208 via different tags confirmed the integrity of the cloned tags.

  3. Production of papillomavirus-based gene transfer vectors.

    Science.gov (United States)

    Buck, Christopher B; Thompson, Cynthia D

    2007-12-01

    Papillomaviruses are a diverse group of pathogens that infect the skin and mucosal tissues of humans and various animal species. The viral genome is a circular, double-stranded DNA molecule approximately 8-kb in length. The non-enveloped papillomavirus capsid is composed of a virally encoded major coat protein, L1, and a minor coat protein, L2. L1 and L2 co-assemble when expressed in mammalian cells, and can promiscuously encapsidate essentially any papillomavirus-based gene transfer vectors (also known as pseudoviruses). This unit outlines the production and propagative amplification of papillomaviral vectors. The system represents a highly tractable method for converting pre-existing mammalian expression plasmids into infectious virus stocks. The resulting vectors have utility for in vitro, as well as in vivo gene delivery applications. (c) 2007 by John Wiley & Sons, Inc.

  4. Retrovirus-based vectors for transient and permanent cell modification.

    Science.gov (United States)

    Schott, Juliane W; Hoffmann, Dirk; Schambach, Axel

    2015-10-01

    Retroviral vectors are commonly employed for long-term transgene expression via integrating vector technology. However, three alternative retrovirus-based platforms are currently available that allow transient cell modification. Gene expression can be mediated from either episomal DNA or RNA templates, or selected proteins can be directly transferred through retroviral nanoparticles. The different technologies are functionally graded with respect to safety, expression magnitude and expression duration. Improvement of the initial technologies, including modification of vector designs, targeted increase in expression strength and duration as well as improved safety characteristics, has allowed maturation of retroviral systems into efficient and promising tools that meet the technological demands of a wide variety of potential application areas. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

    Directory of Open Access Journals (Sweden)

    Xiang-ming Gao

    2017-01-01

    Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  6. pAUL: a gateway-based vector system for adaptive expression and flexible tagging of proteins in Arabidopsis.

    Directory of Open Access Journals (Sweden)

    Dagmar Lyska

    Full Text Available Determination of protein function requires tools that allow its detection and/or purification. As generation of specific antibodies often is laborious and insufficient, protein tagging using epitopes that are recognized by commercially available antibodies and matrices appears more promising. Also, proper spatial and temporal expression of tagged proteins is required to prevent falsification of results. We developed a new series of binary Gateway cloning vectors named pAUL1-20 for C- and N-terminal in-frame fusion of proteins to four different tags: a single (i HA epitope and (ii Strep-tagIII, (iii both epitopes combined to a double tag, and (iv a triple tag consisting of the double tag extended by a Protein A tag possessing a 3C protease cleavage site. Expression can be driven by either the 35 S CaMV promoter or, for C-terminal fusions, promoters from genes encoding the chloroplast biogenesis factors HCF107, HCF136, or HCF173. Fusions of the four promoters to the GUS gene showed that endogenous promoter sequences are functional and drive expression more moderately and consistently throughout different transgenic lines when compared to the 35 S CaMV promoter. By testing complementation of mutations affected in chloroplast biogenesis factors HCF107 and HCF208, we found that the effect of different promoters and tags on protein function strongly depends on the protein itself. Single-step and tandem affinity purification of HCF208 via different tags confirmed the integrity of the cloned tags.

  7. Flip-Flop HSV-BAC: bacterial artificial chromosome based system for rapid generation of recombinant herpes simplex virus vectors using two independent site-specific recombinases

    Directory of Open Access Journals (Sweden)

    Todo Tomoki

    2006-09-01

    Full Text Available Abstract Background Oncolytic herpes simplex virus (HSV vectors that specifically replicate in and kill tumor cells sparing normal cells are a promising cancer therapy. Traditionally, recombinant HSV vectors have been generated through homologous recombination between the HSV genome and a recombination plasmid, which usually requires laborious screening or selection and can take several months. Recent advances in bacterial artificial chromosome (BAC technology have enabled cloning of the whole HSV genome as a BAC plasmid and subsequent manipulation in E. coli. Thus, we sought a method to generate recombinant oncolytic HSV vectors more easily and quickly using BAC technology. Results We have developed an HSV-BAC system, termed the Flip-Flop HSV-BAC system, for the rapid generation of oncolytic HSV vectors. This system has the following features: (i two site-specific recombinases, Cre and FLPe, are used sequentially to integrate desired sequences and to excise the BAC sequences, respectively; and (ii the size of the HSV-BAC-insert genome exceeds the packaging limit of HSV so only correctly recombined virus grows efficiently. We applied this to the construction of an HSV-BAC plasmid that can be used for the generation of transcriptionally-targeted HSV vectors. BAC sequences were recombined into the UL39 gene of HSV ICP4-deletion mutant d120 to generate M24-BAC virus, from which HSV-BAC plasmid pM24-BAC was isolated. An ICP4 expression cassette driven by an exogenous promoter was re-introduced to pM24-BAC by Cre-mediated recombination and nearly pure preparations of recombinant virus were obtained typically in two weeks. Insertion of the ICP4 coding sequence alone did not restore viral replication and was only minimally better than an ICP4-null construct, whereas insertion of a CMVIE promoter-ICP4 transgene (bM24-CMV efficiently drove viral replication. The levels of bM24-CMV replication in tumor cells varied considerably compared to hrR3 (UL39

  8. Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data

    Science.gov (United States)

    Gloger, Oliver; Tönnies, Klaus; Mensel, Birger; Völzke, Henry

    2015-11-01

    In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches.

  9. Vectors

    DEFF Research Database (Denmark)

    Boeriis, Morten; van Leeuwen, Theo

    2017-01-01

    This article revisits the concept of vectors, which, in Kress and van Leeuwen’s Reading Images (2006), plays a crucial role in distinguishing between ‘narrative’, action-oriented processes and ‘conceptual’, state-oriented processes. The use of this concept in image analysis has usually focused...... on the most salient vectors, and this works well, but many images contain a plethora of vectors, which makes their structure quite different from the linguistic transitivity structures with which Kress and van Leeuwen have compared ‘narrative’ images. It can also be asked whether facial expression vectors...... should be taken into account in discussing ‘reactions’, which Kress and van Leeuwen link only to eyeline vectors. Finally, the question can be raised as to whether actions are always realized by vectors. Drawing on a re-reading of Rudolf Arnheim’s account of vectors, these issues are outlined...

  10. Model Checking Vector Addition Systems with one zero-test

    CERN Document Server

    Bonet, Rémi; Leroux, Jérôme; Zeitoun, Marc

    2012-01-01

    We design a variation of the Karp-Miller algorithm to compute, in a forward manner, a finite representation of the cover (i.e., the downward closure of the reachability set) of a vector addition system with one zero-test. This algorithm yields decision procedures for several problems for these systems, open until now, such as place-boundedness or LTL model-checking. The proof techniques to handle the zero-test are based on two new notions of cover: the refined and the filtered cover. The refined cover is a hybrid between the reachability set and the classical cover. It inherits properties of the reachability set: equality of two refined covers is undecidable, even for usual Vector Addition Systems (with no zero-test), but the refined cover of a Vector Addition System is a recursive set. The second notion of cover, called the filtered cover, is the central tool of our algorithms. It inherits properties of the classical cover, and in particular, one can effectively compute a finite representation of this set, e...

  11. Long-Term Suppression of Hepatitis B Virus Replication by Short Hairpin RNA Expression Using the Scaffold/Matrix Attachment Region-Based Replicating Vector System pEPI-1▿

    Science.gov (United States)

    Jenke, Andreas C. W.; Wilhelm, Andreas D.; Orth, Valerie; Lipps, Hans Joachim; Protzer, Ulrike; Wirth, Stefan

    2008-01-01

    Since the emergence of viral resistance of hepatitis B virus (HBV) during treatment is becoming an important issue even with newer drugs, there is a need for alternative treatment options such as, for example, RNA interference (RNAi) technology. While short-term suppression of HBV replication is easily achieved with small interfering RNA oligonucleotides, this is not the case for long-term suppression due to the lack of an optimal vector system. Based on the nonviral scaffold/matrix attachment region (S/MAR)-based vector system pEPI-1, which is free of common side effects and is stably retained as an episome even in the absence of selection, we designed a short hairpin RNA (shRNA) expression vector called pEPI-RNAi for HBV suppression. HBV-replicating HepG2.2.15 cells were transfected with pEPI-RNAi, and the intracellular status of the plasmid was followed by PCR and Southern analysis. HBV replication was measured on the DNA, RNA, and protein level. HBV RNA expression was reduced by almost 85% 3 months posttransfection with pEPI-RNAi. At 8 months posttransfection in the absence of antibiotic selection pressure, the suppression level was still 70% and the vector was retained as an episome. The reduction of total intracellular HBV DNA at this point was 77%, showing a marked suppression of HBV DNA replication. At a comparable level, secretion of viral antigens, as well as progeny HBV virions, was inhibited. The S/MAR-based vector system pEPI-1 allows long-term suppression of HBV replication by the expression of suitable shRNAs. Due to its unique properties compared to commonly used vectors, it provides an interesting option for the treatment of chronically HBV-infected individuals. PMID:18474581

  12. Tombusvirus-based vector systems to permit over-expression of genes or that serve as sensors of antiviral RNA silencing in plants.

    Science.gov (United States)

    Shamekova, Malika; Mendoza, Maria R; Hsieh, Yi-Cheng; Lindbo, John; Omarov, Rustem T; Scholthof, Herman B

    2014-03-01

    A next generation Tomato bushy stunt virus (TBSV) coat protein gene replacement vector system is described that can be applied by either RNA inoculation or through agroinfiltration. A vector expressing GFP rapidly yields high levels of transient gene expression in inoculated leaves of various plant species, as illustrated for Nicotiana benthamiana, cowpea, tomato, pepper, and lettuce. A start-codon mutation to down-regulate the dose of the P19 silencing suppressor reduces GFP accumulation, whereas mutations that result in undetectable levels of P19 trigger rapid silencing of GFP. Compared to existing virus vectors the TBSV system has a unique combination of a very broad host range, rapid and high levels of replication and gene expression, and the ability to regulate its suppressor. These features are attractive for quick transient assays in numerous plant species for over-expression of genes of interest, or as a sensor to monitor the efficacy of antiviral RNA silencing. Copyright © 2014. Published by Elsevier Inc.

  13. Quantum blind signature based on Two-State Vector Formalism

    Science.gov (United States)

    Qi, Su; Zheng, Huang; Qiaoyan, Wen; Wenmin, Li

    2010-11-01

    Two-State Vector Formalism (TSVF) including pre- and postselected states is a complete description of a system between two measurements. Consequently TSVF gives a perfect solution to the Mean King problem. In this paper, utilizing the dramatic correlation in the verification, we propose a quantum blind signature scheme based on TSVF. Compared with Wen's scheme, our scheme has 100% efficiency. Our scheme guarantees the unconditional security. Moreover, the proposed scheme, which is easy to implement, can be applied to E-payment system.

  14. Neural cell image segmentation method based on support vector machine

    Science.gov (United States)

    Niu, Shiwei; Ren, Kan

    2015-10-01

    In the analysis of neural cell images gained by optical microscope, accurate and rapid segmentation is the foundation of nerve cell detection system. In this paper, a modified image segmentation method based on Support Vector Machine (SVM) is proposed to reduce the adverse impact caused by low contrast ratio between objects and background, adherent and clustered cells' interference etc. Firstly, Morphological Filtering and OTSU Method are applied to preprocess images for extracting the neural cells roughly. Secondly, the Stellate Vector, Circularity and Histogram of Oriented Gradient (HOG) features are computed to train SVM model. Finally, the incremental learning SVM classifier is used to classify the preprocessed images, and the initial recognition areas identified by the SVM classifier are added to the library as the positive samples for training SVM model. Experiment results show that the proposed algorithm can achieve much better segmented results than the classic segmentation algorithms.

  15. A novel two-component Tobacco mosaic virus-based vector system for high-level expression of multiple therapeutic proteins including a human monoclonal antibody in plants.

    Science.gov (United States)

    Roy, Gourgopal; Weisburg, Sangeetha; Rabindran, Shailaja; Yusibov, Vidadi

    2010-09-15

    Expression of multiple therapeutic proteins from Tobacco mosaic virus (TMV)-based vectors was not successful when plants were coinoculated with a mixture of two TMV vectors engineered to express two foreign genes individually. Here, we have engineered and developed a defective RNA (dRNA)-based TMV vector (dRT-V) that utilizes two components of the same virus, with the dRNA component depending on the helper virus for replication. Agrobacterium-mediated coinoculation of Nicotiana benthamiana plants with both components of the dRT-V resulted in high-level expression of a human growth hormone and a lichenase-fused lethal factor protein of Bacillus anthracis. Furthermore, both heavy and light chains were expressed and assembled into a monoclonal antibody (mAb) specific to the protective antigen of B. anthracis, and the average yield of the purified antibody obtained was 120 mg/kg of fresh tissue. Our data suggest that dRT-V has a potential for rapid, cost-effective, large-scale manufacturing of multiple therapeutic proteins including mAbs in response to any biological emergencies. Copyright 2010 Elsevier Inc. All rights reserved.

  16. Support vector machines optimization based theory, algorithms, and extensions

    CERN Document Server

    Deng, Naiyang; Zhang, Chunhua

    2013-01-01

    Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized twi

  17. Risk based surveillance for vector borne diseases

    DEFF Research Database (Denmark)

    Bødker, Rene

    an increasing trend in transmission potential over the last 25 years. However the model suggested that the climate in the Baltic See Region has always permitted transmission of these diseases. The model therefore suggests that a presently unknown factor until recently prevented introduction and spread......Increased temperatures and changes in rainfall pattern are likely to facilitate the spread and establishment of new vector borne diseases in the Baltic See Region. There are a large number of potential vector borne threats to the area. Existing endemic vector borne diseases are likely to increase...... and new exotic diseases like Usutu and West Nile Virus may lead to outbreaks in the region. In the worst case the combined effect of climate change and globalization may potentially lead to European outbreaks of important zoonotic mosquito borne infections like Rift Valley Fever in cattle and Japanese...

  18. Research of DOA Estimation Based on Single MEMS Vector Hydrophone.

    Science.gov (United States)

    Zhang, Wen Dong; Guan, Ling Gang; Zhang, Guo Jun; Xue, Chen Yang; Zhang, Kai Rui; Wang, Jian Ping

    2009-01-01

    The MEMS vector hydrophone is a novel acoustic sensor with a "four-beam-cilia" structure. Based on the MEMS vector hydrophone with this structure, the paper studies the method of estimated direction of arrival (DOA). According to various research papers, many algorithms can be applied to vector hydrophones. The beam-forming approach and bar graph approach are described in detail. Laboratory tests by means of the a standing-wave tube are performed to validate the theoretical results. Both the theoretical analysis and the results of tests prove that the proposed MEMS vector hydrophone possesses the desired directional function.

  19. Neuro-vector-based electrical machine driver combining a neural plant identifier and a conventional vector controller

    Science.gov (United States)

    Madani, Kurosh; Mercier, Gilles; Dinarvand, Mohammad; Depecker, Jean-Charles

    1999-03-01

    One of the most important problems, for a machine control process is the system identification. To identify varying parameters which are dependent from other system's parameters (speed, voltage and currents, etc.), one must have an adaptive control system. Synchronous machines conventional vector control's implementation using PID controllers have been recently proposed presenting the best actual solution. It supposes an appropriated model of the plant. But real plant's parameters vary and the P.I.D. controller is not suitable because of the parameters variation and non-linearity introduced by the machine's physical structure. In this paper, we present an on-line dynamic adaptive neural based vector control system identifying the motor's parameters of a synchronous machine. We present and discuss a DSP based real- time implementation of our adaptive neuro-controller. Simulation and experimental results validating our approach have been reported.

  20. Distinguishing Parkinson’s disease from atypical parkinsonian syndromes using PET data and a computer system based on support vector machines and Bayesian networks

    Directory of Open Access Journals (Sweden)

    Fermín eSegovia

    2015-11-01

    Full Text Available Differentiating between Parkinson's disease (PD and atypical parkinsonian syndromes (APS is still a challenge, specially at early stages when the patients show similar symptoms. During last years, several computer systems have been proposed in order to improve the diagnosis of PD, but their accuracy is still limited. In this work we demonstrate a full automatic computer system to assist the diagnosis of PD using 18F-DMFP PET data. First, a few regions of interest are selected by means of a two-sample t-test. The accuracy of the selected regions to separate PD from APS patients is then computed using a support vector machine classifier. The accuracy values are finally used to train a Bayesian network that can be used to predict the class of new unseen data. This methodology was evaluated using a database with 87 neuroimages, achieving accuracy rates over 78%. A fair comparison with other similar approaches is also provided.

  1. Distinguishing Parkinson's disease from atypical parkinsonian syndromes using PET data and a computer system based on support vector machines and Bayesian networks.

    Science.gov (United States)

    Segovia, Fermín; Illán, Ignacio A; Górriz, Juan M; Ramírez, Javier; Rominger, Axel; Levin, Johannes

    2015-01-01

    Differentiating between Parkinson's disease (PD) and atypical parkinsonian syndromes (APS) is still a challenge, specially at early stages when the patients show similar symptoms. During last years, several computer systems have been proposed in order to improve the diagnosis of PD, but their accuracy is still limited. In this work we demonstrate a full automatic computer system to assist the diagnosis of PD using (18)F-DMFP PET data. First, a few regions of interest are selected by means of a two-sample t-test. The accuracy of the selected regions to separate PD from APS patients is then computed using a support vector machine classifier. The accuracy values are finally used to train a Bayesian network that can be used to predict the class of new unseen data. This methodology was evaluated using a database with 87 neuroimages, achieving accuracy rates over 78%. A fair comparison with other similar approaches is also provided.

  2. Simulation-Based Optimization of a Vector Showerhead System for the Control of Flow Field Profile in a Vertical Reactor Chamber

    Directory of Open Access Journals (Sweden)

    Huanxiong Xia

    2014-03-01

    Full Text Available Optimization of a vector showerhead in a vertical reactor involves thousands of holes on the showerhead face plate and the spatial distribution of physical fields, so parameterizing the geometry configuration of the holes in high resolution is very difficult, which makes the conventional optimization methods hard to deal with. To solve this problem, a profile error feedback (PEF optimization solution was proposed to optimize a vector showerhead gas delivery system for the control of mass transport. The gas velocity profile in the reactor and the continuous-feature impedance distribution profile on the showerhead face plate are defined as design objective and variables, respectively. A cyclic iterative approximation idea was implemented in this solution. The algorithm was started from a guessed initial design model and then cyclically adjusted the design variables by the constructed PEF iterative formula to generate a better model and to make the gas velocity profile in the critical domain of the new model continually approximate to the expected profile, until it could be accepted. Finally, the optimized impedance profile was mapped to the holes geometry configuration through the established equivalent impedance model for the showerhead face plate.

  3. Nitrous Oxide Liquid Injection Thrust Vector Control System Testing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A Nitrous Oxide-fed Liquid Thrust Vector Control system is proposed as an efficient method for vehicle attitude control during powered flight. Pulled from a N2O main...

  4. Comparative Study of Liver Gene Transfer With AAV Vectors Based on Natural and Engineered AAV Capsids.

    Science.gov (United States)

    Wang, Lili; Bell, Peter; Somanathan, Suryanarayan; Wang, Qiang; He, Zhenning; Yu, Hongwei; McMenamin, Deirdre; Goode, Tamara; Calcedo, Roberto; Wilson, James M

    2015-12-01

    Vectors based on the clade E family member adeno-associated virus (AAV) serotype 8 have shown promise in patients with hemophilia B and have emerged as best in class for human liver gene therapies. We conducted a thorough evaluation of liver-directed gene therapy using vectors based on several natural and engineered capsids including the clade E AAVrh10 and the largely uncharacterized and phylogenically distinct AAV3B. Included in this study was a putatively superior hepatotropic capsid, AAVLK03, which is very similar to AAV3B. Vectors based on these capsids were benchmarked against AAV8 and AAV2 in a number of in vitro and in vivo model systems including C57BL/6 mice, immune-deficient mice that are partially repopulated with human hepatocytes, and nonhuman primates. Our studies in nonhuman primates and human hepatocytes demonstrated high level transduction of the clade E-derived vectors and equally high transduction with vectors based on AAV3B. In contrast to previous reports, AAVLK03 vectors are not superior to either AAV3B or AAV8. Vectors based on AAV3B should be considered for liver-directed gene therapy when administered following, or before, treatment with the serologically distinct clade E vectors.

  5. LandSat-Based Land Use-Land Cover (Vector)

    Data.gov (United States)

    Minnesota Department of Natural Resources — Vector-based land cover data set derived from classified 30 meter resolution Thematic Mapper satellite imagery. Classification is divided into 16 classes with source...

  6. Improved NYVAC-based vaccine vectors.

    Directory of Open Access Journals (Sweden)

    Karen V Kibler

    Full Text Available While as yet there is no vaccine against HIV/AIDS, the results of the phase III Thai trial (RV144 have been encouraging and suggest that further improvements of the prime/boost vaccine combination of a poxvirus and protein are needed. With this aim, in this investigation we have generated derivatives of the candidate vaccinia virus vaccine vector NYVAC with potentially improved functions. This has been achieved by the re-incorporation into the virus genome of two host range genes, K1L and C7L, in conjunction with the removal of the immunomodulatory viral molecule B19, an antagonist of type I interferon action. These novel virus vectors, referred to as NYVAC-C-KC and NYVAC-C-KC-ΔB19R, have acquired relevant biological characteristics, giving higher levels of antigen expression in infected cells, replication-competency in human keratinocytes and dermal fibroblasts, activation of selective host cell signal transduction pathways, and limited virus spread in tissues. Importantly, these replication-competent viruses have been demonstrated to maintain a highly attenuated phenotype.

  7. A NEW RECOMBINANT ADENO-ASSOCIATED VIRUS (AAV)-BASED RANDOM PEPTIDE DISPLAY LIBRARY SYSTEM: INFECTION-DEFECTIVE AAV1.9-3 AS A NOVEL DETARGETED PLATFORM FOR VECTOR EVOLUTION*

    OpenAIRE

    Adachi, Kei; Nakai, Hiroyuki

    2010-01-01

    Directed evolution through genetic engineering of viral capsids followed by selection has emerged as a powerful means to create novel recombinant adeno-associated virus (rAAV) vectors with desired tropism and enhanced properties. One of the most effective approaches uses rAAV-based random peptide display libraries. Here we report a novel system based on an infection-defective rAAV1.9-3 as a platform for random peptide display, and show that biopanning of the libraries in vitro effectively ide...

  8. Space vector-based analysis of overmodulation in triangle ...

    Indian Academy of Sciences (India)

    The equivalence of triangle-comparison-based pulse width modulation (TCPWM) and space vector based PWM (SVPWM) during linear modulation is well-known. This paper analyses triangle-comparison based PWM techniques (TCPWM) such as sine-triangle PWM (SPWM) and common-mode voltage injection PWM ...

  9. Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

    Directory of Open Access Journals (Sweden)

    Hailun Wang

    2017-01-01

    Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

  10. Web-based public health geographic information systems for resources-constrained environment using scalable vector graphics technology: a proof of concept applied to the expanded program on immunization data

    Directory of Open Access Journals (Sweden)

    Kamadjeu Raoul

    2006-06-01

    Full Text Available Abstract Background Geographic Information Systems (GIS are powerful communication tools for public health. However, using GIS requires considerable skill and, for this reason, is sometimes limited to experts. Web-based GIS has emerged as a solution to allow a wider audience to have access to geospatial information. Unfortunately the cost of implementing proprietary solutions may be a limiting factor in the adoption of a public health GIS in a resource-constrained environment. Scalable Vector Graphics (SVG is used to define vector-based graphics for the internet using XML (eXtensible Markup Language; it is an open, platform-independent standard maintained by the World Wide Web Consortium (W3C since 2003. In this paper, we summarize our methodology and demonstrate the potential of this free and open standard to contribute to the dissemination of Expanded Program on Immunization (EPI information by providing interactive maps to a wider audience through the Internet. Results We used SVG to develop a database driven web-based GIS applied to EPI data from three countries of WHO AFRO (World Health Organization – African Region. The system generates interactive district-level country immunization coverage maps and graphs. The approach we describe can be expanded to cover other public health GIS demanding activities, including the design of disease atlases in a resources-constrained environment. Conclusion Our system contributes to accumulating evidence demonstrating the potential of SVG technology to develop web-based public health GIS in resources-constrained settings.

  11. A new system for parallel drug screening against multiple-resistant HIV mutants based on lentiviral self-inactivating (SIN vectors and multi-colour analyses

    Directory of Open Access Journals (Sweden)

    Prokofjeva Maria M

    2013-01-01

    Full Text Available Abstract Background Despite progress in the development of combined antiretroviral therapies (cART, HIV infection remains a significant challenge for human health. Current problems of cART include multi-drug-resistant virus variants, long-term toxicity and enormous treatment costs. Therefore, the identification of novel effective drugs is urgently needed. Methods We developed a straightforward screening approach for simultaneously evaluating the sensitivity of multiple HIV gag-pol mutants to antiviral drugs in one assay. Our technique is based on multi-colour lentiviral self-inactivating (SIN LeGO vector technology. Results We demonstrated the successful use of this approach for screening compounds against up to four HIV gag-pol variants (wild-type and three mutants simultaneously. Importantly, the technique was adapted to Biosafety Level 1 conditions by utilising ecotropic pseudotypes. This allowed upscaling to a large-scale screening protocol exploited by pharmaceutical companies in a successful proof-of-concept experiment. Conclusions The technology developed here facilitates fast screening for anti-HIV activity of individual agents from large compound libraries. Although drugs targeting gag-pol variants were used here, our approach permits screening compounds that target several different, key cellular and viral functions of the HIV life-cycle. The modular principle of the method also allows the easy exchange of various mutations in HIV sequences. In conclusion, the methodology presented here provides a valuable new approach for the identification of novel anti-HIV drugs.

  12. Vector Lyapunov Functions for Stochastic Interconnected Systems

    Science.gov (United States)

    Boussalis, D.

    1985-01-01

    Theoretical paper presents set of sufficient conditions for asymptotic and exponential stability with probability 1 for class of stochastic interconnected systems. Theory applicable to complicated, large-scale mechanical or electrical systems, and, for several design problems, it reduces computational difficulty by relating stability criteria to fundamental structural features of system.

  13. Versatile Supramolecular Gene Vector Based on Host-Guest Interaction

    NARCIS (Netherlands)

    Liu, Jia; Hennink, Wim E.; Van Steenbergen, Mies J.; Zhuo, Renxi; Jiang, Xulin

    2016-01-01

    It is a great challenge to arrange multiple functional components into one gene vector system to overcome the extra- and intracellular obstacles for gene therapy. In this study, we developed a supramolecular approach for constructing a versatile gene delivery system composed of adamantyl-terminated

  14. Online Order Priority Evaluation Based on Hybrid Harmony Search Algorithm of Optimized Support Vector Machines

    OpenAIRE

    Yuanyuan Zhao; Qian Chen

    2014-01-01

    To make production plan, online order priority evaluation is the current priority weakness of online order evaluation model. This thesis proposes an online order priority evaluation model based on hybrid harmony search algorithm of optimized support vector machine (HHS-SVM). Firstly, an online order priority evaluation index system is build, and then support vector machine is adopted to build an online order priority evaluation model; secondly, harmony search algorithm is used to optimize the...

  15. Environmental noise forecasting based on support vector machine

    Science.gov (United States)

    Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

    2018-01-01

    As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

  16. VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics.

    Science.gov (United States)

    Megy, Karine; Emrich, Scott J; Lawson, Daniel; Campbell, David; Dialynas, Emmanuel; Hughes, Daniel S T; Koscielny, Gautier; Louis, Christos; Maccallum, Robert M; Redmond, Seth N; Sheehan, Andrew; Topalis, Pantelis; Wilson, Derek

    2012-01-01

    VectorBase (http://www.vectorbase.org) is a NIAID-supported bioinformatics resource for invertebrate vectors of human pathogens. It hosts data for nine genomes: mosquitoes (three Anopheles gambiae genomes, Aedes aegypti and Culex quinquefasciatus), tick (Ixodes scapularis), body louse (Pediculus humanus), kissing bug (Rhodnius prolixus) and tsetse fly (Glossina morsitans). Hosted data range from genomic features and expression data to population genetics and ontologies. We describe improvements and integration of new data that expand our taxonomic coverage. Releases are bi-monthly and include the delivery of preliminary data for emerging genomes. Frequent updates of the genome browser provide VectorBase users with increasing options for visualizing their own high-throughput data. One major development is a new population biology resource for storing genomic variations, insecticide resistance data and their associated metadata. It takes advantage of improved ontologies and controlled vocabularies. Combined, these new features ensure timely release of multiple types of data in the public domain while helping overcome the bottlenecks of bioinformatics and annotation by engaging with our user community.

  17. Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR) tool.

    Science.gov (United States)

    Huang, Zhuojie; Das, Anirrudha; Qiu, Youliang; Tatem, Andrew J

    2012-08-14

    Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible

  18. Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR tool

    Directory of Open Access Journals (Sweden)

    Huang Zhuojie

    2012-08-01

    Full Text Available Abstract Background Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR, to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Methods Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. Results The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. Conclusions VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements

  19. Direct power control of DFIG based on discrete space vector modulation

    Energy Technology Data Exchange (ETDEWEB)

    Verij Kazemi, Mohammad; Sadeghi Yazdankhah, Ahmad; Madadi Kojabadi, Hossein [Electrical Engineering Department, Sahand University of Technology, Tabriz (Iran)

    2010-05-15

    This paper presents a new direct power control (DPC) strategy for a double fed induction generator (DFIG) based wind energy generation system. Switching vectors for rotor side converter were selected from the optimal switching table using the estimated stator flux position and the errors of the active and reactive power. A few number of voltage vectors may cause undesired power and stator current ripple. In this paper the increased number of voltage vectors with application of the Discrete Space Vector Modulation (DSVM) will be presented. Then a new switching table in supersynchronous and subsynchronous frames will be proposed. Simulation results of a 2 MW DFIG system demonstrate the effectiveness and robustness of the proposed control strategy during variations of active and reactive power, machine parameters, and wind speed. (author)

  20. [Ecology of vector systems: a tangle of complexity].

    Science.gov (United States)

    Rodhain, F

    2008-06-01

    The long co-evolutionary process between arthropods and microorganisms has resulted in a wide variety of relationships. One such relationship involves a wide range of infectious agents (virus, bacteria, protozoa, helminthes) that use blood-feeding arthropods (insects and mites) as vectors for transmission from one vertebrate to another. Transmission involves three components, i.e., microorganism, vector(s), and vertebrate host(s). Study under natural conditions has shown that the underlying mechanisms are extremely complex with circulation of the infectious agents depending on numerous conditions linked not only to bioecology but also to genetic factors in all three component populations. The role of arthropods sometimes goes beyond that of a transmitter of disease. In some cases they also serve as reservoirs or disseminators. In addition changes in the environment whether due to natural causes or human activities (e.g. pollution, agropastoralism, urbanization, transportation network development, and climate change) can have profound and rapid effects on the mechanisms underlying these vector systems. In short the ecology of vector systems closely reflects the extreme complexity of epidemiological studies on diseases caused by infectious agents depending on this type of transmission. As a result prediction of infectious risks and planning of preventive action are difficult. It appears obvious that a good understanding of vector systems in their natural context will require a truly ecological approach to the diseases that must be the focus of extremely close epidemiologic surveillance. Achieving this goal will necessitate more than the skills of physicians and veterinarians. It will require the contribution of specialists from a variety of fields such as microbiology, entomology, systematics, climatology, ecology, urbanism, social sciences, economic development, and many others.

  1. Baculovirus expression vector system: An efficient tool for the ...

    African Journals Online (AJOL)

    ... protein in numerous prokaryotic and eukaryotic organisms. Baculovirus expression vector system is considered one of the most successful and widely acceptable means for the production of recombinant proteins in extremely large quantities. Proper posttranslational modifications of the expressed proteins in insect cells, ...

  2. A novel stepwise support vector machine (SVM) method based on ...

    African Journals Online (AJOL)

    ajl yemi

    2011-11-23

    Nov 23, 2011 ... began to use computational approaches, particularly machine learning methods to identify pre-miRNAs (Xue et al., 2005; Huang et al., 2007; Jiang et al., 2007). Xue et al. (2005) presented a support vector machine (SVM)- based classifier called triplet-SVM, which classifies human pre-miRNAs from pseudo ...

  3. The Mathematics of Divergence Based Online Learning in Vector Quantization

    NARCIS (Netherlands)

    Villmann, Thomas; Haase, Sven; Schleif, Frank-Michael; Hammer, Barbara; Biehl, Michael

    2010-01-01

    We propose the utilization of divergences in gradient descent learning of supervised and unsupervised vector quantization as an alternative for the squared Euclidean distance. The approach is based on the determination of the Fréchet-derivatives for the divergences, wich can be immediately plugged

  4. Will integrated surveillance systems for vectors and vector-borne diseases be the future of controlling vector-borne diseases? A practical example from China.

    Science.gov (United States)

    Wu, Y; Ling, F; Hou, J; Guo, S; Wang, J; Gong, Z

    2016-07-01

    Vector-borne diseases are one of the world's major public health threats and annually responsible for 30-50% of deaths reported to the national notifiable disease system in China. To control vector-borne diseases, a unified, effective and economic surveillance system is urgently needed; all of the current surveillance systems in China waste resources and/or information. Here, we review some current surveillance systems and present a concept for an integrated surveillance system combining existing vector and vector-borne disease monitoring systems. The integrated surveillance system has been tested in pilot programmes in China and led to a 21·6% cost saving in rodent-borne disease surveillance. We share some experiences gained from these programmes.

  5. Engineered AAV vectors for improved central nervous system gene delivery.

    Science.gov (United States)

    A Kotterman, Melissa; Schaffer, David V

    2015-01-01

    Adeno-associated viruses (AAV) are non-pathogenic members of the Parvoviridae family that are being harnessed as delivery vehicles for both basic research and increasingly successful clinical gene therapy. To address a number of delivery shortcomings with natural AAV variants, we have developed and implemented directed evolution-a high-throughput molecular engineering approach to generate novel biomolecules with enhanced function-to create novel AAV vectors that are designed to preferentially transduce specific cell types in the central nervous system (CNS), including astrocytes, neural stem cells, and cells within the retina. These novel AAV vectors-which have enhanced infectivity in vitro and enhanced infectivity and selectivity in vivo-can enable more efficient studies to further our understanding of neurogenesis, development, aging, and disease. Furthermore, such engineered vectors may aid gene or cell replacement therapies to treat neurodegenerative disease or injury.

  6. Viking Orbiter 1975 thrust vector control system accuracy

    Science.gov (United States)

    Mcglinchey, L. F.

    1974-01-01

    The thrust vector control (TVC) system of the Viking Orbiter 1975 is discussed. The purpose of the TVC system is to point the engine thrust at the vehicle center of mass and to maintain attitude stability during propulsive maneuvers. This is accomplished by mounting the engine in a two-axis gimbal system. The TVC system then controls the pointing of the engine by closed loop control of two linear actuators which extend or retract and rotate the engine in its gimbal system. The effect of the TVC on the velocity vector pointing error incurred during a propulsive maneuver is analyzed. Models for predicting the magnitude of the error for various propulsive maneuvers are developed.

  7. Efficient Vector-Based Forwarding for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Peng Xie

    2010-01-01

    Full Text Available Underwater Sensor Networks (UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF, a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.

  8. Properties and use of novel replication-competent vectors based on Semliki Forest virus.

    Science.gov (United States)

    Rausalu, Kai; Iofik, Anna; Ulper, Liane; Karo-Astover, Liis; Lulla, Valeria; Merits, Andres

    2009-03-24

    Semliki Forest virus (SFV) has a positive strand RNA genome and infects different cells of vertebrates and invertebrates. The 5' two-thirds of the genome encodes non-structural proteins that are required for virus replication and synthesis of subgenomic (SG) mRNA for structural proteins. SG-mRNA is generated by internal initiation at the SG-promoter that is located at the complementary minus-strand template. Different types of expression systems including replication-competent vectors, which represent alphavirus genomes with inserted expression units, have been developed. The replication-competent vectors represent useful tools for studying alphaviruses and have potential therapeutic applications. In both cases, the properties of the vector, such as its genetic stability and expression level of the protein of interest, are important. We analysed 14 candidates of replication-competent vectors based on the genome of an SFV4 isolate that contained a duplicated SG promoter or an internal ribosomal entry site (IRES)-element controlled marker gene. It was found that the IRES elements and the minimal -21 to +5 SG promoter were non-functional in the context of these vectors. The efficient SG promoters contained at least 26 residues upstream of the start site of SG mRNA. The insertion site of the SG promoter and its length affected the genetic stability of the vectors, which was always higher when the SG promoter was inserted downstream of the coding region for structural proteins. The stability also depended on the conditions used for vector propagation. A procedure based on the in vitro transcription of ligation products was used for generation of replication-competent vector-based expression libraries that contained hundreds of thousands of different genomes, and maintained genetic diversity and the ability to express inserted genes over five passages in cell culture. The properties of replication-competent vectors of alphaviruses depend on the details of their

  9. Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2017-03-01

    Full Text Available The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs. Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable.

  10. Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

    Science.gov (United States)

    Wang, Jianzhou; Niu, Tong; Wang, Rui

    2017-01-01

    The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable. PMID:28257122

  11. TMV-Gate vectors: Gateway compatible tobacco mosaic virus based expression vectors for functional analysis of proteins

    Science.gov (United States)

    Kagale, Sateesh; Uzuhashi, Shihomi; Wigness, Merek; Bender, Tricia; Yang, Wen; Borhan, M. Hossein; Rozwadowski, Kevin

    2012-01-01

    Plant viral expression vectors are advantageous for high-throughput functional characterization studies of genes due to their capability for rapid, high-level transient expression of proteins. We have constructed a series of tobacco mosaic virus (TMV) based vectors that are compatible with Gateway technology to enable rapid assembly of expression constructs and exploitation of ORFeome collections. In addition to the potential of producing recombinant protein at grams per kilogram FW of leaf tissue, these vectors facilitate either N- or C-terminal fusions to a broad series of epitope tag(s) and fluorescent proteins. We demonstrate the utility of these vectors in affinity purification, immunodetection and subcellular localisation studies. We also apply the vectors to characterize protein-protein interactions and demonstrate their utility in screening plant pathogen effectors. Given its broad utility in defining protein properties, this vector series will serve as a useful resource to expedite gene characterization efforts. PMID:23166857

  12. Diagnosis of nutrient imbalances with vector analysis in agroforestry systems.

    Science.gov (United States)

    Isaac, Marney E; Kimaro, Anthony A

    2011-01-01

    Agricultural intensification has had unintended environmental consequences, including increased nutrient leaching and surface runoff and other agrarian-derived pollutants. Improved diagnosis of on-farm nutrient dynamics will have the advantage of increasing yields and will diminish financial and environmental costs. To achieve this, a management support system that allows for site-specific rapid evaluation of nutrient production imbalances and subsequent management prescriptions is needed for agroecological design. Vector diagnosis, a bivariate model to depict changes in yield and nutritional response simultaneously in a single graph, facilitates identification of nutritional status such as growth dilution, deficiency, sufficiency, luxury uptake, and toxicity. Quantitative data from cocoa agroforestry systems and pigeonpea intercropping trials in Ghana and Tanzania, respectively, were re-evaluated with vector analysis. Relative to monoculture, biomass increase in cocoa ( L.) under shade (35-80%) was accompanied by a 17 to 25% decline in P concentration, the most limiting nutrient on this site. Similarly, increasing biomass with declining P concentrations was noted for pigeonpea [ (L). Millsp.] in response to soil moisture availability under intercropping. Although vector analysis depicted nutrient responses, the current vector model does not consider non-nutrient resource effects on growth, such as ameliorated light and soil moisture, which were particularly active in these systems. We revisit and develop vector analysis into a framework for diagnosing nutrient and non-nutrient interactions in agroforestry systems. Such a diagnostic technique advances management decision-making by increasing nutrient precision and reducing environmental issues associated with agrarian-derived soil contamination. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

  13. An Efficient Audio Classification Approach Based on Support Vector Machines

    OpenAIRE

    Lhoucine Bahatti; Omar Bouattane; My Elhoussine Echhibat; Mohamed Hicham Zaggaf

    2016-01-01

    In order to achieve an audio classification aimed to identify the composer, the use of adequate and relevant features is important to improve performance especially when the classification algorithm is based on support vector machines. As opposed to conventional approaches that often use timbral features based on a time-frequency representation of the musical signal using constant window, this paper deals with a new audio classification method which improves the features extraction according ...

  14. Versatile rogue waves in scalar, vector, and multidimensional nonlinear systems

    Science.gov (United States)

    Chen, Shihua; Baronio, Fabio; Soto-Crespo, Jose M.; Grelu, Philippe; Mihalache, Dumitru

    2017-11-01

    This review is dedicated to recent progress in the active field of rogue waves, with an emphasis on the analytical prediction of versatile rogue wave structures in scalar, vector, and multidimensional integrable nonlinear systems. We first give a brief outline of the historical background of the rogue wave research, including referring to relevant up-to-date experimental results. Then we present an in-depth discussion of the scalar rogue waves within two different integrable frameworks—the infinite nonlinear Schrödinger (NLS) hierarchy and the general cubic-quintic NLS equation, considering both the self-focusing and self-defocusing Kerr nonlinearities. We highlight the concept of chirped Peregrine solitons, the baseband modulation instability as an origin of rogue waves, and the relation between integrable turbulence and rogue waves, each with illuminating examples confirmed by numerical simulations. Later, we recur to the vector rogue waves in diverse coupled multicomponent systems such as the long-wave short-wave equations, the three-wave resonant interaction equations, and the vector NLS equations (alias Manakov system). In addition to their intriguing bright–dark dynamics, a series of other peculiar structures, such as coexisting rogue waves, watch-hand-like rogue waves, complementary rogue waves, and vector dark three sisters, are reviewed. Finally, for practical considerations, we also remark on higher-dimensional rogue waves occurring in three closely-related (2  +  1)D nonlinear systems, namely, the Davey–Stewartson equation, the composite (2  +  1)D NLS equation, and the Kadomtsev–Petviashvili I equation. As an interesting contrast to the peculiar X-shaped light bullets, a concept of rogue wave bullets intended for high-dimensional systems is particularly put forward by combining contexts in nonlinear optics.

  15. Dynamic Model Based Vector Control of Linear Induction Motor

    Science.gov (United States)

    2012-05-01

    sensorless control is critical for LIM control in some special case. Reference [13] introduces a direct torque and flux control based on space...Industry Applications, IEEE Transactions on, vol. 28, no. 5, pp. 1054–1061, 1992. [4] J. Nash, “ Direct torque control , induction motor vector ...13] C. Lascu, I. Boldea, and F. Blaabjerg, “A modified direct torque control for induction motor sensorless drive,” Industry Applications,

  16. Chikungunya Virus Vaccines: Viral Vector-Based Approaches.

    Science.gov (United States)

    Ramsauer, Katrin; Tangy, Frédéric

    2016-12-15

    In 2013, a major chikungunya virus (CHIKV) epidemic reached the Americas. In the past 2 years, >1.7 million people have been infected. In light of the current epidemic, with millions of people in North and South America at risk, efforts to rapidly develop effective vaccines have increased. Here, we focus on CHIKV vaccines that use viral-vector technologies. This group of vaccine candidates shares an ability to potently induce humoral and cellular immune responses by use of highly attenuated and safe vaccine backbones. So far, well-described vectors such as modified vaccinia virus Ankara, complex adenovirus, vesicular stomatitis virus, alphavirus-based chimeras, and measles vaccine Schwarz strain (MV/Schw) have been described as potential vaccines. We summarize here the recent data on these experimental vaccines, with a focus on the preclinical and clinical activities on the MV/Schw-based candidate, which is the first CHIKV-vectored vaccine that has completed a clinical trial. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

  17. Engineered AAV vectors for improved central nervous system gene delivery

    Science.gov (United States)

    A Kotterman, Melissa; Schaffer, David V

    2015-01-01

    Adeno-associated viruses (AAV) are non-pathogenic members of the Parvoviridae family that are being harnessed as delivery vehicles for both basic research and increasingly successful clinical gene therapy. To address a number of delivery shortcomings with natural AAV variants, we have developed and implemented directed evolution—a high-throughput molecular engineering approach to generate novel biomolecules with enhanced function—to create novel AAV vectors that are designed to preferentially transduce specific cell types in the central nervous system (CNS), including astrocytes, neural stem cells, and cells within the retina. These novel AAV vectors—which have enhanced infectivity in vitro and enhanced infectivity and selectivity in vivo—can enable more efficient studies to further our understanding of neurogenesis, development, aging, and disease. Furthermore, such engineered vectors may aid gene or cell replacement therapies to treat neurodegenerative disease or injury. PMID:27606332

  18. Fault Isolation for Nonlinear Systems Using Flexible Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Yufang Liu

    2014-01-01

    Full Text Available While support vector regression is widely used as both a function approximating tool and a residual generator for nonlinear system fault isolation, a drawback for this method is the freedom in selecting model parameters. Moreover, for samples with discordant distributing complexities, the selection of reasonable parameters is even impossible. To alleviate this problem we introduce the method of flexible support vector regression (F-SVR, which is especially suited for modelling complicated sample distributions, as it is free from parameters selection. Reasonable parameters for F-SVR are automatically generated given a sample distribution. Lastly, we apply this method in the analysis of the fault isolation of high frequency power supplies, where satisfactory results have been obtained.

  19. A Narcissus mosaic viral vector system for protein expression and flavonoid production

    Science.gov (United States)

    2013-01-01

    Background With the explosive numbers of sequences generated by next generation sequencing, the demand for high throughput screening to understand gene function has grown. Plant viral vectors have been widely used as tools in down-regulating plant gene expression. However, plant viral vectors can also express proteins in a very efficient manner and, therefore, can also serve as a valuable tool for characterizing proteins and their functions in metabolic pathways in planta. Results In this study, we have developed a Gateway®-based high throughput viral vector cloning system from Narcissus Mosaic Virus (NMV). Using the reporter genes of GFP and GUS, and the plant genes PAP1 (an R2R3 MYB which activates the anthocyanin pathway) and selenium-binding protein 1 (SeBP), we show that NMV vectors and the model plant Nicotiana benthamiana can be used for efficient protein expression, protein subcellular localization and secondary metabolite production. Conclusions Our results suggest that not only can the plant viral vector system be employed for protein work but also can potentially be amenable to producing valuable secondary metabolites on a large scale, as the system does not require plant regeneration from seed or calli, which are stages where certain secondary metabolites can interfere with development. PMID:23849589

  20. Virus-based transient expression vectors for woody crops: a new frontier for vector design and use.

    Science.gov (United States)

    Dawson, William O; Folimonova, Svetlana Y

    2013-01-01

    Virus-based expression vectors are commonplace tools for the production of proteins or the induction of RNA silencing in herbaceous plants. This review considers a completely different set of uses for viral vectors in perennial fruit and nut crops, which can be productive for periods of up to 100 years. Viral vectors could be used in the field to modify existing plants. Furthermore, with continually emerging pathogens and pests, viral vectors could express genes to protect the plants or even to treat plants after they become infected. As technologies develop during the life span of these crops, viral vectors can be used for adding new genes as an alternative to pushing up the crop and replanting with transgenic plants. Another value of virus-based vectors is that they add nothing permanently to the environment. This requires that effective and stable viral vectors be developed for specific crops from endemic viruses. Studies using viruses from perennial hosts suggest that these objectives could be accomplished.

  1. Virtual-vector-based space vector pulse width modulation of the DC-AC multilevel-clamped multilevel converter (MLC2)

    DEFF Research Database (Denmark)

    Rodriguez, Pedro; Busquets-Monge, Sergio; Blaabjerg, Frede

    2011-01-01

    This work presents the development of the space vector pulse width modulation (SVPWM) of a new multi-level converter topology. First, the proposed converter and its natural space vector diagram are presented. Secondly, a modified space vector diagram based on the virtual-vectors technique is shown...

  2. Novel gene transfer systems: intelligent gene transfer vectors for gene medicines.

    Science.gov (United States)

    Nakajima, Toshihiro

    2012-01-01

    Drug delivery systems for gene transfer are called 'vectors'. These systems were originally invented as a delivery system for the transfection in vitro or in vivo. Several vectors are then developed for clinical use of gene medicines and currently some of them are approved as animal drugs. Conventional drug delivery system generally consists of approved (existing) materials to avoid additional pre-clinical or clinical studies. However, current vectors contain novel materials to improve an efficacy of gene medicines. Thus, these vectors have functions more than a mere delivery of active ingredients. For example some vectors have immunological functions such as adjuvants in vaccines. These new types of vectors are called 'intelligent' or 'innovative' vector system', since the concept or strategy for the development is completely different from conventional drug delivery systems. In this article, we described a current status of 'intelligent gene transfer vectors and discussed on the potentials of them.

  3. Modeling Analysis of Power Transformer Fault Diagnosis Based on Improved Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Lutao Liu

    2013-01-01

    Full Text Available A new method of transformer fault diagnosis based on relevance vector machine (RVM is proposed. Bayesian estimation is applied to support vector machine (SVM in the novel algorithm, which made fault diagnosis system work more effectively. In the paper, the analysis model is presented that the solutions of RVM have the feature of sparsity and RVM can obtain global solutions under finite samples. The process of transformer fault diagnosis for four working statuses is given in experiments and simulations. The results validated that this method has obvious advantages of diagnosis time and accuracy compared with backpropagation (BP neural networks and general SVM methods.

  4. Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller

    Science.gov (United States)

    Engel, E.; Kovalev, I. V.; Karandeev, D.

    2015-10-01

    The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.

  5. 2D Vector Field Simplification Based on Robustness

    KAUST Repository

    Skraba, Primoz

    2014-03-01

    Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. These geometric metrics do not consider the flow magnitude, an important physical property of the flow. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness, which provides a complementary view on flow structure compared to the traditional topological-skeleton-based approaches. Robustness enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory, has fewer boundary restrictions, and so can handle more general cases. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. © 2014 IEEE.

  6. Stability and Control of Large-Scale Dynamical Systems A Vector Dissipative Systems Approach

    CERN Document Server

    Haddad, Wassim M

    2011-01-01

    Modern complex large-scale dynamical systems exist in virtually every aspect of science and engineering, and are associated with a wide variety of physical, technological, environmental, and social phenomena, including aerospace, power, communications, and network systems, to name just a few. This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, and presents the most complete treatment on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. Large-scale dynami

  7. Cardiovascular Response Identification Based on Nonlinear Support Vector Regression

    Science.gov (United States)

    Wang, Lu; Su, Steven W.; Chan, Gregory S. H.; Celler, Branko G.; Cheng, Teddy M.; Savkin, Andrey V.

    This study experimentally investigates the relationships between central cardiovascular variables and oxygen uptake based on nonlinear analysis and modeling. Ten healthy subjects were studied using cycle-ergometry exercise tests with constant workloads ranging from 25 Watt to 125 Watt. Breath by breath gas exchange, heart rate, cardiac output, stroke volume and blood pressure were measured at each stage. The modeling results proved that the nonlinear modeling method (Support Vector Regression) outperforms traditional regression method (reducing Estimation Error between 59% and 80%, reducing Testing Error between 53% and 72%) and is the ideal approach in the modeling of physiological data, especially with small training data set.

  8. Slope Deformation Prediction Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Lei JIA

    2013-07-01

    Full Text Available This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM. In the prediction process,explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that this model is of high fitting accuracy and generalization, and provides reference for deformation prediction in slope engineering.

  9. Production and Characterization of Vectors Based on the Cardiotropic AAV Serotype 9.

    Science.gov (United States)

    Kohlbrenner, Erik; Weber, Thomas

    2017-01-01

    Vectors based on adeno-associated virus serotype 9 (AAV9) efficiently transduce cardiomyocytes in both rodents and large animal models upon either systemic or regional vector delivery. In this chapter, we describe the most widely used production and purification method of AAV9. This production approach does not depend on the use of a helpervirus but instead on transient transfection of HEK293T cells with a plasmid containing the recombinant AAV genome and a second plasmid encoding the AAV9 capsid proteins, the AAV Rep proteins and the adenoviral helper functions. The recombinant AAV is then purified by iodixanol density gradient centrifugation. This chapter also describes in detail the characterization and quality control methods required for assuring high quality vector preparations, which is of particular importance for experiments in large animal models.

  10. A NEW RECOMBINANT ADENO-ASSOCIATED VIRUS (AAV)-BASED RANDOM PEPTIDE DISPLAY LIBRARY SYSTEM: INFECTION-DEFECTIVE AAV1.9-3 AS A NOVEL DETARGETED PLATFORM FOR VECTOR EVOLUTION.

    Science.gov (United States)

    Adachi, Kei; Nakai, Hiroyuki

    2010-10-01

    Directed evolution through genetic engineering of viral capsids followed by selection has emerged as a powerful means to create novel recombinant adeno-associated virus (rAAV) vectors with desired tropism and enhanced properties. One of the most effective approaches uses rAAV-based random peptide display libraries. Here we report a novel system based on an infection-defective rAAV1.9-3 as a platform for random peptide display, and show that biopanning of the libraries in vitro effectively identifies the peptides that restore and enhance rAAV transduction. rAAV1.9-3 has a genetically engineered AAV1 capsid with amino acids 445-568 being replaced with those of AAV9, and has been identified as a variant exhibiting significantly impaired infectivity and delayed blood clearance when infused into mice. In this study, we generated rAAV1.9-3 variant libraries in which 7- or 12-mer random peptides were expressed at the capsid amino acid position 590. Three rounds of positive selection for primary human dermal fibroblasts successfully identified new rAAV-peptide variants that transduce them more efficiently than the prototype rAAV2. Thus our study demonstrates that an infection-defective rAAV variant serves as a novel detargeted platform for random peptide display libraries. We also describe a brief review of recent progress in rAAV-based random peptide display library approaches.

  11. A NEW RECOMBINANT ADENO-ASSOCIATED VIRUS (AAV)-BASED RANDOM PEPTIDE DISPLAY LIBRARY SYSTEM: INFECTION-DEFECTIVE AAV1.9-3 AS A NOVEL DETARGETED PLATFORM FOR VECTOR EVOLUTION*

    Science.gov (United States)

    Adachi, Kei; Nakai, Hiroyuki

    2011-01-01

    Directed evolution through genetic engineering of viral capsids followed by selection has emerged as a powerful means to create novel recombinant adeno-associated virus (rAAV) vectors with desired tropism and enhanced properties. One of the most effective approaches uses rAAV-based random peptide display libraries. Here we report a novel system based on an infection-defective rAAV1.9-3 as a platform for random peptide display, and show that biopanning of the libraries in vitro effectively identifies the peptides that restore and enhance rAAV transduction. rAAV1.9-3 has a genetically engineered AAV1 capsid with amino acids 445–568 being replaced with those of AAV9, and has been identified as a variant exhibiting significantly impaired infectivity and delayed blood clearance when infused into mice. In this study, we generated rAAV1.9-3 variant libraries in which 7- or 12-mer random peptides were expressed at the capsid amino acid position 590. Three rounds of positive selection for primary human dermal fibroblasts successfully identified new rAAV-peptide variants that transduce them more efficiently than the prototype rAAV2. Thus our study demonstrates that an infection-defective rAAV variant serves as a novel detargeted platform for random peptide display libraries. We also describe a brief review of recent progress in rAAV-based random peptide display library approaches. PMID:21603583

  12. Improvement of RF Vector Modulator Performance by Feed-forward Based Calibration

    CERN Document Server

    Tosovsky, Petr

    2010-01-01

    RF Vector Modulator enables independent control of a narrowband RF signal amplitude and phase. Unfortunately practical realization of an analog vector modulator suffers from misbalances and imperfections in the I and Q signal paths. Use of a feed-forward based calibration can compensate for them and significantly improve RF performance and control accuracy of a real vector modulator. Achieved improvements and results on a small series of vector modulator based phase shifters using feed-forward calibration are presented.

  13. A Kalman Filter for SINS Self-Alignment Based on Vector Observation

    Science.gov (United States)

    Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Tong, Jinwu

    2017-01-01

    In this paper, a self-alignment method for strapdown inertial navigation systems based on the q-method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate. PMID:28146059

  14. Energy Based Clutter Filtering for Vector Flow Imaging

    DEFF Research Database (Denmark)

    Villagómez Hoyos, Carlos Armando; Jensen, Jonas; Ewertsen, Caroline

    2017-01-01

    To obtain accurate blood flow velocity estimates it is important to remove the clutter signal originating from tissue. Conventionally, the clutter signal has been separated from the blood signal based on the difference of their spectral frequencies. However, this approach is not enough for obtain......To obtain accurate blood flow velocity estimates it is important to remove the clutter signal originating from tissue. Conventionally, the clutter signal has been separated from the blood signal based on the difference of their spectral frequencies. However, this approach is not enough...... for obtaining vector flow measurements, since the spectra overlaps at high beam-to-flow angles. In this work a distinct approach is proposed, where the energy of the velocity spectrum is used to differentiate among the two signals. The energy based method is applied by limiting the amplitude of the velocity...

  15. Ultrasound Vector Flow Imaging: Part I: Sequential Systems

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt; Nikolov, Svetoslav Ivanov; Yu, Alfred C. H.

    2016-01-01

    The paper gives a review of the most important methods for blood velocity vector flow imaging (VFI) for conventional, sequential data acquisition. This includes multibeam methods, speckle tracking, transverse oscillation, color flow mapping derived vector flow imaging, directional beamforming, an...

  16. Matrix-Vector Based Fast Fourier Transformations on SDR Architectures

    Directory of Open Access Journals (Sweden)

    Y. He

    2008-05-01

    Full Text Available Today Discrete Fourier Transforms (DFTs are applied in various radio standards based on OFDM (Orthogonal Frequency Division Multiplex. It is important to gain a fast computational speed for the DFT, which is usually achieved by using specialized Fast Fourier Transform (FFT engines. However, in face of the Software Defined Radio (SDR development, more general (parallel processor architectures are often desirable, which are not tailored to FFT computations. Therefore, alternative approaches are required to reduce the complexity of the DFT. Starting from a matrix-vector based description of the FFT idea, we will present different factorizations of the DFT matrix, which allow a reduction of the complexity that lies between the original DFT and the minimum FFT complexity. The computational complexities of these factorizations and their suitability for implementation on different processor architectures are investigated.

  17. Disturbance observer based current controller for vector controlled IM drives

    DEFF Research Database (Denmark)

    Teodorescu, Remus; Dal, Mehmet

    2008-01-01

    In order to increase the accuracy of the current control loop, usually, well known parameter compensation and/or cross decoupling techniques are employed for advanced ac drives. In this paper, instead of using these techniques an observer-based current controller is proposed for vector controlled...... induction motor (IM) drives. The control design, based on synchronously rotating d-q frame model of the machine, has a simple structure that combines the proportional portion of a conventional PI control and output of the observer. The observer is predicted to estimate the disturbances caused by parameters...... change in current control loop and, also to remove undesired cross coupling existing between components of the stator current. The observer uses the measured stator currents and estimated PWM voltages, and produces a disturbance signal with a low pass filter. The proposed control scheme reduces cross...

  18. Vector-based excitation amplitude imaging condition for elastic RTM

    Science.gov (United States)

    Zhou, Jinju; Wang, Deli

    2017-12-01

    In recent years, many studies have focused on elastic reverse time migration (RTM). In response to the problems associated with elastic RTM, we propose a new procedure for 2D elastic multicomponent RTM. In this new method, decomposed P- and S-wave components are obtained from the decoupled propagation of the source and receiver wavefields, which allows the expedient calculation of the Poynting vectors and the incident and reflection angles of the P- and S-waves. In addition, we deduce the vector-based excitation amplitude imaging condition. This process automatically accounts for the particle vibration directions when determining the angle-dependent signed reflection coefficients, and does not require the sign to be determined apart from the value of the reflection coefficients. This concept was further extended to the source-normalized crosscorrelation imaging condition. The reflection coefficient of the layered model test was in agreement with the Zoeppritz theory, the PP and PS wave images of the Marmousi II model were clear, and the PS wave images had higher resolution and richer details. In addition, since the calculated reflection coefficients are angle-dependent, they can be easily used for the extraction of angle-domain common-image gathers. Moreover, the imaging condition avoids the polarization reversal in PS wave images and does not require all of the source wavefield data. Consequently, the computation and storage requirements are significantly reduced, which will facilitate the use of the elastic RTM in practice.

  19. Vectorization, parallelization and porting of nuclear codes on the VPP500 system (vectorization). Progress report fiscal 1996

    Energy Technology Data Exchange (ETDEWEB)

    Nemoto, Toshiyuki; Kawai, Wataru [Fujitsu Ltd., Tokyo (Japan); Kawasaki, Nobuo [and others

    1997-12-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. These results are reported in 3 parts, i.e., the vectorization part, the parallelization part and the porting part. In this report, we describe the vectorization. In this vectorization part, the vectorization of two and three dimensional discrete ordinates simulation code DORT-TORT, gas dynamics analysis code FLOWGR and relativistic Boltzmann-Uehling-Uhlenbeck simulation code RBUU are described. In the parallelization part, the parallelization of 2-Dimensional relativistic electromagnetic particle code EM2D, Cylindrical Direct Numerical Simulation code CYLDNS and molecular dynamics code for simulating radiation damages in diamond crystals DGR are described. And then, in the porting part, the porting of reactor safety analysis code RELAP5/MOD3.2 and RELAP5/MOD3.2.1.2, nuclear data processing system NJOY and 2-D multigroup discrete ordinate transport code TWOTRAN-II are described. And also, a survey for the porting of command-driven interactive data analysis plotting program IPLOT are described. (author)

  20. The Vector Population Monitoring Tool (VPMT: High-Throughput DNA-Based Diagnostics for the Monitoring of Mosquito Vector Populations

    Directory of Open Access Journals (Sweden)

    Chris Bass

    2010-01-01

    Full Text Available Regular monitoring of mosquito vector populations is an integral component of most vector control programmes. Contemporary data on mosquito species composition, infection status, and resistance to insecticides are a prerequisite for effective intervention. For this purpose we, with funding from the Innovative Vector Control Consortium (IVCC, have developed a suite of high-throughput assays based on a single “closed-tube” platform that collectively comprise the “Vector Population Monitoring Tool” (VPMT. The VPMT can be used to screen mosquito disease vector populations for a number of traits including Anopheles gambiae s.l. and Anopheles funestus species identification, detection of infection with Plasmodium parasites, and identification of insecticide resistance mechanisms. In this paper we focus on the Anopheles-specific assays that comprise the VPMT and include details of a new assay for resistance todieldrin Rdl detection. The application of these tools, general and specific guidelines on their use based on field testing in Africa, and plans for further development are discussed.

  1. A concurrent vector-based steering framework for particle transport

    CERN Document Server

    Apostolakis, John; Carminati, Federico; Gheata, Andrei; Wenzel, Sandro

    2014-01-01

    High Energy Physics has traditionally been a technology - limited science that has pushed the boundaries of both the detectors collecting the information about the particles and the computing infrastructure processing this information. However, since a few years the increase in computing power comes in the form of increased parallelism at all levels, and High Energy Physics has now to optimise its code to take advantage of the new architectures, including GPUs and hybrid systems. One of the primary targets for optimisation is the particle transport code used to simulate the detector response, as it is largely experiment independent and one of the most demanding applications in terms of CPU resources . The Geant Vector Prototype project aims to explore innovative designs in particle transport aimed at obtaining maximal performance on the new architectures. This paper describes the current status of the project and its future perspectives. In particular we describe how the present design tries to expose the par...

  2. Adaptive vector quantization in SVD MIMO system backward link with limited number of active sub channels

    Directory of Open Access Journals (Sweden)

    Ivaniš Predrag

    2004-01-01

    Full Text Available This paper presents combination of Channel Optimized Vector Quantization based on LBG algorithm and sub channel power allocation for MIMO systems with Singular Value Decomposition and limited number of active sub channels. Proposed algorithm is designed to enable maximal throughput with bit error rate bellow some tar- get level in case of backward channel capacity limitation. Presence of errors effect in backward channel is also considered.

  3. BEHAVIOR BASED CREDIT CARD FRAUD DETECTION USING SUPPORT VECTOR MACHINES

    Directory of Open Access Journals (Sweden)

    V. Dheepa

    2012-07-01

    Full Text Available Along with the great increase of internet and e-commerce, the use of credit card is an unavoidable one. Due to the increase of credit card usage, the frauds associated with this have also increased. There are a lot of approaches used to detect the frauds. In this paper, behavior based classification approach using Support Vector Machines are employed and efficient feature extraction method also adopted. If any discrepancies occur in the behaviors transaction pattern then it is predicted as suspicious and taken for further consideration to find the frauds. Generally credit card fraud detection problem suffers from a large amount of data, which is rectified by the proposed method. Achieving finest accuracy, high fraud catching rate and low false alarms are the main tasks of this approach.

  4. Vector optical field generation based on birefringent phase plate.

    Science.gov (United States)

    Wang, Jiazhou; Cao, Axiu; Pang, Hui; Zhang, Man; Wang, Guangyi; Chen, Jian; Shi, Lifang; Deng, Qiling; Hu, Song

    2017-05-29

    Vector optical field has recently gained interest in a variety of application fields due to its novel characteristics. Conventional approaches of generating vector optical fields have difficulties in forming highly continuous polarization and suffer from the issue of high energy utilization rates. In order to address these issues, in this study a single optical path was proposed to generate vector optical fields where the birefringent phase plate modulated a linear polarized light into a vector optical field, which was then demodulated to a non-uniform linear polarization distribution of the vector optical field by the polarization demodulation module. Both a theoretical model and numerical simulations of the vector optical field generator were developed, illustrating the relationship between the polarization distribution of the target vector optical field and the depth distribution of the birefringent phase plate. Furthermore, the birefringent phase plate with predefined surface distributions was fabricated by grayscale exposure and ion etching. The generated vector optical field was experimentally characterized, capable of producing continuous polarization with high light energy utilization ratio, consistent with simulations. This new approach may have the potential of being widely used in future studies of generating well-controlled vector optical fields.

  5. A Fiber-Optic Borehole Seismic Vector Sensor System for Geothermal Site Characterization and Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Paulsson, Bjorn N.P. [Paulsson, Inc., Van Nuys, CA (United States); Thornburg, Jon A. [Paulsson, Inc., Van Nuys, CA (United States); He, Ruiqing [Paulsson, Inc., Van Nuys, CA (United States)

    2015-04-21

    Seismic techniques are the dominant geophysical techniques for the characterization of subsurface structures and stratigraphy. The seismic techniques also dominate the monitoring and mapping of reservoir injection and production processes. Borehole seismology, of all the seismic techniques, despite its current shortcomings, has been shown to provide the highest resolution characterization and most precise monitoring results because it generates higher signal to noise ratio and higher frequency data than surface seismic techniques. The operational environments for borehole seismic instruments are however much more demanding than for surface seismic instruments making both the instruments and the installation much more expensive. The current state-of-the-art borehole seismic instruments have not been robust enough for long term monitoring compounding the problems with expensive instruments and installations. Furthermore, they have also not been able to record the large bandwidth data available in boreholes or having the sensitivity allowing them to record small high frequency micro seismic events with high vector fidelity. To reliably achieve high resolution characterization and long term monitoring of Enhanced Geothermal Systems (EGS) sites a new generation of borehole seismic instruments must therefore be developed and deployed. To address the critical site characterization and monitoring needs for EGS programs, US Department of Energy (DOE) funded Paulsson, Inc. in 2010 to develop a fiber optic based ultra-large bandwidth clamped borehole seismic vector array capable of deploying up to one thousand 3C sensor pods suitable for deployment into ultra-high temperature and high pressure boreholes. Tests of the fiber optic seismic vector sensors developed on the DOE funding have shown that the new borehole seismic sensor technology is capable of generating outstanding high vector fidelity data with extremely large bandwidth: 0.01 – 6,000 Hz. Field tests have shown

  6. Viral vector-based reversible neuronal inactivation and behavioral manipulation in the macaque monkey.

    Science.gov (United States)

    Nielsen, Kristina J; Callaway, Edward M; Krauzlis, Richard J

    2012-01-01

    Viral vectors are promising tools for the dissection of neural circuits. In principle, they can manipulate neurons at a level of specificity not otherwise achievable. While many studies have used viral vector-based approaches in the rodent brain, only a few have employed this technique in the non-human primate, despite the importance of this animal model for neuroscience research. Here, we report evidence that a viral vector-based approach can be used to manipulate a monkey's behavior in a task. For this purpose, we used the allatostatin receptor/allatostatin (AlstR/AL) system, which has previously been shown to allow inactivation of neurons in vivo. The AlstR was expressed in neurons in monkey V1 by injection of an adeno-associated virus 1 (AAV1) vector. Two monkeys were trained in a detection task, in which they had to make a saccade to a faint peripheral target. Injection of AL caused a retinotopic deficit in the detection task in one monkey. Specifically, the monkey showed marked impairment for detection targets placed at the visual field location represented at the virus injection site, but not for targets shown elsewhere. We confirmed that these deficits indeed were due to the interaction of AlstR and AL by injecting saline, or AL at a V1 location without AlstR expression. Post-mortem histology confirmed AlstR expression in this monkey. We failed to replicate the behavioral results in a second monkey, as AL injection did not impair the second monkey's performance in the detection task. However, post-mortem histology revealed a very low level of AlstR expression in this monkey. Our results demonstrate that viral vector-based approaches can produce effects strong enough to influence a monkey's performance in a behavioral task, supporting the further development of this approach for studying how neuronal circuits control complex behaviors in non-human primates.

  7. Viral vector-based reversible neuronal inactivation and behavioral manipulation in the macaque monkey

    Directory of Open Access Journals (Sweden)

    Kristina Juliane Nielsen

    2012-06-01

    Full Text Available Viral vectors are promising tools for the dissection of neural circuits. In principle, they can manipulate neurons at a level of specificity not otherwise achievable. While many studies have used viral vector-based approaches in the rodent brain, only a few have employed this technique in the non-human primate, despite the importance of this animal model for neuroscience research. Here, we report for the first time that a viral vector-based approach can be used to manipulate a monkey’s behavior in a task. For this purpose, we used the allatostatin receptor/allatostatin (AlstR/AL system, which has previously been shown to allow inactivation of neurons in vivo. The AlstR was expressed in neurons in monkey V1 by injection of an AAV1 vector. Two monkeys were trained in a detection task, in which they had to make a saccade to a faint peripheral target. Injection of AL caused a retinotopic deficit in the detection task in one monkey. Specifically, the monkey showed marked impairment for detection targets placed at the visual field location represented at the virus injection site, but not for targets shown elsewhere. We confirmed that these deficits indeed were due to the interaction of AlstR and AL by injecting saline, or AL at a V1 location without AlstR expression. Post-mortem histology confirmed AlstR expression in this monkey. We failed to replicate the behavioral results in a second monkey, as AL injection did not impair the second monkey’s performance in the detection task. However, post-mortem histology revealed a very low level of AlstR expression in this monkey. Our results demonstrate that viral vector-based approaches can produce effects strong enough to influence a monkey’s performance in a behavioral task, supporting the further development of this approach for studying how neuronal circuits control complex behaviors in non-human primates.

  8. A direct torque control scheme for permanent magnet synchronous motors based on space vector modulation

    Science.gov (United States)

    Su, Xiao-hui; Xu, Shu-Ping

    2013-03-01

    In order to solve the problem of direct torque control (DTC) for permanent magnet synchronous motor (PMSM) related to the flux and the torque ripple and the uncertainty of switching frequency, A novel direct torque control system based on space vector modulation(SVM-DTC) for permanent magnet synchronous motor was proposed. In this method flux and torque are controlled through stator voltage components in stator flux linkage coordinate axes and space vector modulation is used to control inverters. Therefore, the errors of torque and flux linkage could be compensated accurately. The whole system has only one easily adjustable PI adjuster and needs no high for hardware and easy for realize. The simulation results verify the feasibility of this method, reduction of the flux and the torque ripple, and the good performance of DTC.

  9. Segmentation of Clinical Endoscopic Images Based on the Classification of Topological Vector Features

    Directory of Open Access Journals (Sweden)

    O. A. Dunaeva

    2013-01-01

    Full Text Available In this work, we describe a prototype of an automatic segmentation system and annotation of endoscopy images. The used algorithm is based on the classification of vectors of the topological features of the original image. We use the image processing scheme which includes image preprocessing, calculation of vector descriptors defined for every point of the source image and the subsequent classification of descriptors. Image preprocessing includes finding and selecting artifacts and equalizating the image brightness. In this work, we give the detailed algorithm of the construction of topological descriptors and the classifier creating procedure based on mutual sharing the AdaBoost scheme and a naive Bayes classifier. In the final section, we show the results of the classification of real endoscopic images.

  10. Vector Analysis of Ionic Collision on CaCO3 Precipitation Based on Vibration Time History

    Science.gov (United States)

    Mangestiyono, W.; Muryanto, S.; Jamari, J.; Bayuseno, A. P.

    2017-05-01

    Vibration effects on the piping system can result from the internal factor of fluid or the external factor of the mechanical equipment operation. As the pipe vibrated, the precipitation process of CaCO3 on the inner pipe could be affected. In the previous research, the effect of vibration on CaCO3 precipitation in piping system was clearly verified. This increased the deposition rate and decreased the induction time. However, the mechanism of vibration control in CaCO3 precipitation process as the presence of vibration has not been recognized yet. In the present research, the mechanism of vibration affecting the CaCO3 precipitation was investigated through vector analysis of ionic collision. The ionic vector force was calculated based on the amount of the activation energy and the vibration force was calculated based on the vibration sensor data. The vector resultant of ionic collision based on the vibration time history was analyzed to prove that vibration brings ionic collision randomly to the planar horizontal direction and its collision model was suspected as the cause of the increasing deposition rate.

  11. Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system

    Science.gov (United States)

    Wu, Qi

    2010-03-01

    Demand forecasts play a crucial role in supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Aiming at demand series with small samples, seasonal character, nonlinearity, randomicity and fuzziness, the existing support vector kernel does not approach the random curve of the sales time series in the space (quadratic continuous integral space). In this paper, we present a hybrid intelligent system combining the wavelet kernel support vector machine and particle swarm optimization for demand forecasting. The results of application in car sale series forecasting show that the forecasting approach based on the hybrid PSOWv-SVM model is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves that this method is, for the discussed example, better than hybrid PSOv-SVM and other traditional methods.

  12. Construction of an expression vector for Lactococcus lactis based on ...

    African Journals Online (AJOL)

    PRECIOUS

    2009-11-02

    Nov 2, 2009 ... To construct an expression vector for Lactococcus lactis, the EmPMT fragment which contained the erythromycin resistance gene, P32 promoter, multiple cloning site (MCS) and terminator (T) was subcloned into the small cryptic plasmid pAR141. The resulting vector, designated as pAR1411, was found to ...

  13. Perinatal systemic gene delivery using adeno-associated viral vectors

    Directory of Open Access Journals (Sweden)

    Rajvinder eKarda

    2014-11-01

    Full Text Available Neurodegenerative monogenic diseases can also affect a broad range of tissues and organs throughout the body. An effective treatment would require a systemic approach. The intravenous administration of novel therapies is ideal but is hampered by the inability of such drugs to cross the blood-brain barrier and precludes efficacy in the central nervous system. A number of these early lethal intractable diseases also present devastating irreversible pathology at birth or soon after. Therefore, any therapy would ideally be administered during the perinatal period to prevent, stop or ameliorate disease progression. The concept of perinatal gene therapy has moved a step further towards being a feasible approach to treating such disorders. This has primarily been driven by the recent discoveries that particular serotypes of adeno-associated virus (AAV gene delivery vectors have the ability to cross the blood-brain barrier following intravenous administration. Furthermore, this has been safely demonstrated in perinatal mice and non-human primates. This review focuses on the progress made in using AAV to achieve systemic transduction and what this means for developing perinatal gene therapy for early lethal neurodegenerative diseases.

  14. Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

    Science.gov (United States)

    Fachrurrozi, Muhammad; Saparudin; Erwin

    2017-04-01

    Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

  15. Protocol: Streamline cloning of genes into binary vectors in Agrobacterium via the Gateway® TOPO vector system

    Directory of Open Access Journals (Sweden)

    Xu Ruqiang

    2008-01-01

    Full Text Available Abstract Background In plant functional genomic studies, gene cloning into binary vectors for plant transformation is a routine procedure. Traditionally, gene cloning has relied on restriction enzyme digestion and ligation. In recent years, however, Gateway® cloning technology (Invitrogen Co. has developed a fast and reliable alternative cloning methodology which uses a phage recombination strategy. While many Gateway- compatible vectors are available, we frequently encounter problems in which antibiotic resistance genes for bacterial selection are the same between recombinant vectors. Under these conditions, it is difficult, if not sometimes impossible, to use antibiotic resistance in selecting the desired transformants. We have, therefore, developed a practical procedure to solve this problem. Results An integrated protocol for cloning genes of interest from PCR to Agrobacterium transformants via the Gateway® System was developed. The protocol takes advantage of unique characteristics of the replication origins of plasmids used and eliminates the necessity for restriction enzyme digestion in plasmid selections. Conclusion The protocol presented here is a streamlined procedure for fast and reliable cloning of genes of interest from PCR to Agrobacterium via the Gateway® System. This protocol overcomes a key problem in which two recombinant vectors carry the same antibiotic selection marker. In addition, the protocol could be adapted for high-throughput applications.

  16. A Semisupervised Support Vector Machines Algorithm for BCI Systems

    Directory of Open Access Journals (Sweden)

    Jianzhao Qin

    2007-07-01

    Full Text Available As an emerging technology, brain-computer interfaces (BCIs bring us new communication interfaces which translate brain activities into control signals for devices like computers, robots, and so forth. In this study, we propose a semisupervised support vector machine (SVM algorithm for brain-computer interface (BCI systems, aiming at reducing the time-consuming training process. In this algorithm, we apply a semisupervised SVM for translating the features extracted from the electrical recordings of brain into control signals. This SVM classifier is built from a small labeled data set and a large unlabeled data set. Meanwhile, to reduce the time for training semisupervised SVM, we propose a batch-mode incremental learning method, which can also be easily applied to the online BCI systems. Additionally, it is suggested in many studies that common spatial pattern (CSP is very effective in discriminating two different brain states. However, CSP needs a sufficient labeled data set. In order to overcome the drawback of CSP, we suggest a two-stage feature extraction method for the semisupervised learning algorithm. We apply our algorithm to two BCI experimental data sets. The offline data analysis results demonstrate the effectiveness of our algorithm.

  17. A Semi-automated Vector Migration Tool Based on Road Feature Extraction from High Resolution Imagery

    Science.gov (United States)

    Haithcoat, T. L.; Song, W.

    2001-05-01

    A major stumbling block to the integration of remotely sensed data into existing GIS data base structures is the issue of positional accuracy of the existing line-work within the vector database. This inaccuracy manifests itself when overlain to more positional consistent imagery data. In the example case presented within this paper, the parcel map had a variable accuracy of up to 40 ft plus or minus once the various parcel map tiles were combined. This is the result of data being built by hand historically and remaining un-edgematched between tiles within a mylar mapping system. The investment to convert this (the only base map widely used) was made and the sheets were scanned and vectorized by the private sector, which very accurately reproduced the inherent errors of this mapping approach. With the incorporation of GPS and the associated problems of edgematching the tiles into a seamless database the local government consortium was stymied. This lead to the development of an image based reference for these data layers from the existing DOQQs (1995 vintage) and 1m Pan IKONOS imagery. A process was developed that uses road feature extraction from these imagery sources as well as road intersections derived from within the parcel map layer to create a continuum of linearized adjustments. The parcel linework is then degenerated into points and topological relatinships and the positional locations altered based on the adjustment surface. Once adjusted, the linework is re-built and topology re-established on the adjusted layer. This is a tool that can assist counties and cities in migrating their vector data to the image base while maintaining the integrity and the relative-positional accuracy of the vector data.

  18. Spatial patterns and eco-epidemiological systems – part II: characterising spatial patterns of the occurrence of the insect vectors of Chagas disease based on remote sensing and field data

    Directory of Open Access Journals (Sweden)

    Emmanuel Roux

    2011-11-01

    Full Text Available While the former part of this back-to-back paper dealt with the identification of multi-scale spatial patterns associated with the presence, abundance and dispersion of the insect vectors (Triatominae of Chagas disease, this latter part examines the need for pattern characterisation by means of detailed data on environmental, residential, peri-domiciliary and human behaviour. The study site was, in both cases, a single village situated in Bahia, Brazil, wherefrom the data were collected through field observation and a standardised questionnaire, while the environmental characteristics were derived from satellite images and landscape characterisation. Following this, factorial analysis of mixed group (FAMG, an exploratory data analysis method, was applied to “mine” the huge dataset in a hierarchical way and to evaluate the relative impact of different factors such as the surrounding environment, the domiciliary/peri-domiciliary space properties and the presence of domestic animals. In the study village, five principal “districts” associated with different possible causes of infestation were identified. The results favour the role of depressions of the ground surface due to collapse of karstic subsoil (dolines and open rock faces as infestation sources, vector attraction by outdoor lighting, risk of insect domiciliation in dwellings constructed without finishing materials and associated with apparent disorder. Ultimately, this study not only provides the basic information needed for decision-making and specification of vector control in the study village, but offers also a knowledge-base for more general control strategies in the region.

  19. Expanding the repertoire of Modified Vaccinia Ankara-based vaccine vectors via genetic complementation strategies.

    Directory of Open Access Journals (Sweden)

    David A Garber

    Full Text Available Modified Vaccinia virus Ankara (MVA is a safe, highly attenuated orthopoxvirus that is being developed as a recombinant vaccine vector for immunization against a number of infectious diseases and cancers. However, the expression by MVA vectors of large numbers of poxvirus antigens, which display immunodominance over vectored antigens-of-interest for the priming of T cell responses, and the induction of vector-neutralizing antibodies, which curtail the efficacy of subsequent booster immunizations, remain as significant impediments to the overall utility of such vaccines. Thus, genetic approaches that enable the derivation of MVA vectors that are antigenically less complex may allow for rational improvement of MVA-based vaccines.We have developed a genetic complementation system that enables the deletion of essential viral genes from the MVA genome, thereby allowing us to generate MVA vaccine vectors that are antigenically less complex. Using this system, we deleted the essential uracil-DNA-glycosylase (udg gene from MVA and propagated this otherwise replication-defective variant on a complementing cell line that constitutively expresses the poxvirus udg gene and that was derived from a newly identified continuous cell line that is permissive for growth of wild type MVA. The resulting virus, MVADeltaudg, does not replicate its DNA genome or express late viral gene products during infection of non-complementing cells in culture. As proof-of-concept for immunological 'focusing', we demonstrate that immunization of mice with MVADeltaudg elicits CD8+ T cell responses that are directed against a restricted repertoire of vector antigens, as compared to immunization with parental MVA. Immunization of rhesus macaques with MVADeltaudg-gag, a udg(- recombinant virus that expresses an HIV subtype-B consensus gag transgene, elicited significantly higher frequencies of Gag-specific CD8 and CD4 T cells following both primary (2-4-fold and booster (2-fold

  20. Improvement of Carrier Phase Tracking Based on a Joint Vector Architecture

    Directory of Open Access Journals (Sweden)

    Shaohua Chen

    2017-01-01

    Full Text Available Carrier phase measurements are essential to high precision positioning. Usually, the carrier phase measurements are generated from the phase lock loop in a conventional Global Navigation Satellite System (GNSS receiver. However there is a dilemma problem to the design of the loop parameters in a conventional tracking loop. To address this problem and improve the carrier phase tracking sensitivity, a carrier phase tracking method based on a joint vector architecture is proposed. The joint vector architecture contains a common loop based on extended Kalman filter to track the common dynamics of the different channels and the individual loops for each channel to track the satellite specific dynamics. The transfer function model of the proposed architecture is derived. The proposed method and the conventional scalar carrier phase tracking are tested with a high quality simulator. The test results indicate that carrier phase measurements of satellites start to show cycle slips using the proposed method when carrier noise ratio is equal to and below 15 dB-Hz instead of 21 dB-Hz with using the conventional phase tracking loop. Since the joint vector based tracking loops jointly process the signals of all available satellites, the potential interchannel influence between different satellites is also investigated.

  1. A Wavelet Kernel-Based Primal Twin Support Vector Machine for Economic Development Prediction

    Directory of Open Access Journals (Sweden)

    Fang Su

    2013-01-01

    Full Text Available Economic development forecasting allows planners to choose the right strategies for the future. This study is to propose economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. As gross domestic product (GDP is an important indicator to measure economic development, economic development prediction means GDP prediction in this study. The wavelet kernel-based primal twin support vector machine algorithm can solve two smaller sized quadratic programming problems instead of solving a large one as in the traditional support vector machine algorithm. Economic development data of Anhui province from 1992 to 2009 are used to study the prediction performance of the wavelet kernel-based primal twin support vector machine algorithm. The comparison of mean error of economic development prediction between wavelet kernel-based primal twin support vector machine and traditional support vector machine models trained by the training samples with the 3–5 dimensional input vectors, respectively, is given in this paper. The testing results show that the economic development prediction accuracy of the wavelet kernel-based primal twin support vector machine model is better than that of traditional support vector machine.

  2. Defeasible Deontic Robot Control Based on Extended Vector Annotated Logic Programming

    Science.gov (United States)

    Nakamatsu, Kazumi; Abe, Jair Minoro; Suzuki, Atsuyuki

    2002-09-01

    We have already proposed an annotated logic program called an EVALPSN (Extended Vector Annotated Logic Program with Strong Negation) to deal with defeasible deontic reasoning. In this paper, we propose a defeasible deontic action control system for a virtual robot based on EVALPSN. We suppose a beetle robot who is traveling a maze with three kinds of obstacles and has some different kinds of sensors to detect the obstacles. If some sensor values are input to the robot control, the next action that the robot should do is computed by the EVALPSN programming system.

  3. Inelastic Vector Soliton Collisions: A Lattice-Based Quantum Representation

    National Research Council Canada - National Science Library

    Vahala, George; Vahala, Linda; Yepez, Jeffrey

    2004-01-01

    .... Under appropriate conditions the exact 2-soliton vector solutions yield in elastic soliton collisions, in agreement with the theoretical predictions of Radhakrishnan et al. (1997 Phys. Rev. E56, 2213...

  4. Privacy Preserving Fall Detection Based on Simple Human Silhouette Extraction and a Linear Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Velislava Spasova

    2016-06-01

    Full Text Available The paper presents a novel fast, real-time and privacy protecting algorithm for fall detection based on geometric properties of the human silhouette and a linear support vector machine. The algorithm uses infrared and visible light imagery in order to detect the human. A simple real-time human silhouette extraction algorithm has been developed and used to extract features for training of the support vector machine. The achieved sensitivity and specificity of the proposed approach are over 97% which match state of the art research in the area of fall detection. The developed solution uses low-cost hardware components and open source software library and is suitable for usage in assistive systems for the home or nursing homes.

  5. Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine

    Science.gov (United States)

    Fu, Yumei; Xiang, Shihan; Chen, Tianyi; Zhou, Ping; Huang, Weiyan

    2015-10-01

    The fetal electrocardiogram (FECG) signal has important clinical value for diagnosing the fetal heart diseases and choosing suitable therapeutics schemes to doctors. So, the noninvasive extraction of FECG from electrocardiogram (ECG) signals becomes a hot research point. A new method, the Support Vector Machine (SVM) is utilized for the extraction of FECG with limited size of data. Firstly, the theory of the SVM and the principle of the extraction based on the SVM are studied. Secondly, the transformation of maternal electrocardiogram (MECG) component in abdominal composite signal is verified to be nonlinear and fitted with the SVM. Then, the SVM is trained, and the training results are compared with the real data to ensure the effect of the training. Meanwhile, the parameters of the SVM are optimized to achieve the best performance so that the learning machine can be utilized to fit the unknown samples. Finally, the FECG is extracted by removing the optimal estimation of MECG component from the abdominal composite signal. In order to evaluate the performance of FECG extraction based on the SVM, the Signal-to-Noise Ratio (SNR) and the visual test are used. The experimental results show that the FECG with good quality can be extracted, its SNR ratio is significantly increased as high as 9.2349 dB and the time cost is significantly decreased as short as 0.802 seconds. Compared with the traditional method, the noninvasive extraction method based on the SVM has a simple realization, the shorter treatment time and the better extraction quality under the same conditions.

  6. The HVJ-envelope as an innovative vector system for cardiovascular disease.

    Science.gov (United States)

    Kotani, Hitoshi; Nakajima, Toshihiro; Lai, Shoupeng; Morishita, Ryuichi; Kaneda, Yasufumi

    2004-06-01

    Recently promising results of gene therapy clinical trials have been reported for treatment of peripheral vascular and cardiovascular diseases using various angiogenic growth factors and other therapeutic genes. Viral vector and non-viral vector systems were employed in preclinical studies and clinical trials. Adenoviral vector and naked plasmid have been used most in the clinical studies. HVJ (hemagglutinating virus of Japan or Sendai virus)-liposome vector, a hybrid non-viral vector system with fusion of inactivated HVJ virus particle and liposome, has developed and demonstrated high transfection efficiency in preclinical studies of many different disease models, including a wide range of cardiovascular disease models. However, some limitations exist in the HVJ-liposome technology, especially in the scalability of its production. Recently an innovative vector technology, HVJ envelope (HVJ-E) has been developed as a non-viral vector, consisting of HVJ envelope without its viral genome, which is eliminated by a combination of inactivation and purification steps. HVJ-E is able to enclose various molecule entities, including DNA, oligonucleotides, proteins, as single or multiple therapeutic remedies. The therapeutic molecule-included HVJ-E vector can transfect various cell types in animals and humans with high efficiency. In this review, vector technology for cardiovascular disease and the biology of HVJ-E vector technology is discussed.

  7. Evolving lessons on nanomaterial-coated viral vectors for local and systemic gene therapy.

    Science.gov (United States)

    Kasala, Dayananda; Yoon, A-Rum; Hong, Jinwoo; Kim, Sung Wan; Yun, Chae-Ok

    2016-07-01

    Viral vectors are promising gene carriers for cancer therapy. However, virus-mediated gene therapies have demonstrated insufficient therapeutic efficacy in clinical trials due to rapid dissemination to nontarget tissues and to the immunogenicity of viral vectors, resulting in poor retention at the disease locus and induction of adverse inflammatory responses in patients. Further, the limited tropism of viral vectors prevents efficient gene delivery to target tissues. In this regard, modification of the viral surface with nanomaterials is a promising strategy to augment vector accumulation at the target tissue, circumvent the host immune response, and avoid nonspecific interactions with the reticuloendothelial system or serum complement. In the present review, we discuss various chemical modification strategies to enhance the therapeutic efficacy of viral vectors delivered either locally or systemically. We conclude by highlighting the salient features of various nanomaterial-coated viral vectors and their prospects and directions for future research.

  8. Explaining Support Vector Machines: A Color Based Nomogram.

    Directory of Open Access Journals (Sweden)

    Vanya Van Belle

    Full Text Available Support vector machines (SVMs are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models.In this work, we investigate whether SVMs using linear, polynomial and RBF kernels can be explained such that interpretations for model-based decisions can be provided. We further indicate when SVMs can be explained and in which situations interpretation of SVMs is (hitherto not possible. Here, explainability is defined as the ability to produce the final decision based on a sum of contributions which depend on one single or at most two input variables.Our experiments on simulated and real-life data show that explainability of an SVM depends on the chosen parameter values (degree of polynomial kernel, width of RBF kernel and regularization constant. When several combinations of parameter values yield the same cross-validation performance, combinations with a lower polynomial degree or a larger kernel width have a higher chance of being explainable.This work summarizes SVM classifiers obtained with linear, polynomial and RBF kernels in a single plot. Linear and polynomial kernels up to the second degree are represented exactly. For other kernels an indication of the reliability of the approximation is presented. The complete methodology is available as an R package and two apps and a movie are provided to illustrate the possibilities offered by the method.

  9. Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

    Science.gov (United States)

    Oliker, Leonid; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; VanderWijngaart, Rob

    2003-01-01

    The growing gap between sustained and peak performance for scientific applications has become a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to bridge this gap for a significant number of computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines a full spectrum of low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks using some simple optimizations. Finally, we evaluate the perfor- mance of several numerical codes from key scientific computing domains. Overall results demonstrate that the SX6 achieves high performance on a large fraction of our application suite and in many cases significantly outperforms the RISC-based architectures. However, certain classes of applications are not easily amenable to vectorization and would likely require extensive reengineering of both algorithm and implementation to utilize the SX6 effectively.

  10. Conservative rigid body dynamics by convected base vectors with implicit constraints

    DEFF Research Database (Denmark)

    Krenk, Steen; Nielsen, Martin Bjerre

    2014-01-01

    A conservative time integration formulation is developed for rigid bodies based on a convected set of orthonormal base vectors. The base vectors are represented in terms of their absolute coordinates, and thus the formulation makes use of three translation components, plus nine components...... of the base vectors. Orthogonality and unit length of the base vectors are imposed by constraining the equivalent Green strain components, and the kinetic energy is represented corresponding to rigid body motion. The equations of motion are obtained via Hamilton’s equations including the zero......-strain conditions as well as external constraints via Lagrange multipliers. Subsequently, the Lagrange multipliers associated with the internal zero-strain constraints are eliminated by use of a set of orthogonality conditions between the generalized displacements and the momentum vector, leaving a set...

  11. Energy Systems in the Era of Energy Vectors A Key to Define, Analyze and Design Energy Systems Beyond Fossil Fuels

    CERN Document Server

    Orecchini, Fabio

    2012-01-01

    What lies beyond the era of fossil fuels? While most answers focus on different primary energy resources, Energy Systems in the Era of Energy Vectors provides a completely new approach. Instead of providing a traditional consumption analysis of classical primary energy resources such as oil, coal, nuclear power and gas, Energy Systems in the Era of Energy Vectors describes and assesses energy technologies, markets and future strategies, focusing on their capacity to produce, exchange, and use energy vectors. Special attention is given to the renewable energy resources available in different areas of the world and made exploitable by the integration of energy vectors in the global energy system. Clear definitions of energy vectors and energy systems are used as the basis for a complete explanation and assessment of up-to-date, available technologies for energy resources, transport and storage systems, conversion and use. The energy vectors scheme allows the potential realisation of a worldwide sustainable ener...

  12. Intraventricular vector flow mapping—a Doppler-based regularized problem with automatic model selection

    Science.gov (United States)

    Assi, Kondo Claude; Gay, Etienne; Chnafa, Christophe; Mendez, Simon; Nicoud, Franck; Abascal, Juan F. P. J.; Lantelme, Pierre; Tournoux, François; Garcia, Damien

    2017-09-01

    We propose a regularized least-squares method for reconstructing 2D velocity vector fields within the left ventricular cavity from single-view color Doppler echocardiographic images. Vector flow mapping is formulated as a quadratic optimization problem based on an {{\\ell }2} -norm minimization of a cost function composed of a Doppler data-fidelity term and a regularizer. The latter contains three physically interpretable expressions related to 2D mass conservation, Dirichlet boundary conditions, and smoothness. A finite difference discretization of the continuous problem was adopted in a polar coordinate system, leading to a sparse symmetric positive-definite system. The three regularization parameters were determined automatically by analyzing the L-hypersurface, a generalization of the L-curve. The performance of the proposed method was numerically evaluated using (1) a synthetic flow composed of a mixture of divergence-free and curl-free flow fields and (2) simulated flow data from a patient-specific CFD (computational fluid dynamics) model of a human left heart. The numerical evaluations showed that the vector flow fields reconstructed from the Doppler components were in good agreement with the original velocities, with a relative error less than 20%. It was also demonstrated that a perturbation of the domain contour has little effect on the rebuilt velocity fields. The capability of our intraventricular vector flow mapping (iVFM) algorithm was finally illustrated on in vivo echocardiographic color Doppler data acquired in patients. The vortex that forms during the rapid filling was clearly deciphered. This improved iVFM algorithm is expected to have a significant clinical impact in the assessment of diastolic function.

  13. Misalignment calibration of geomagnetic vector measurement system using parallelepiped frame rotation method

    Energy Technology Data Exchange (ETDEWEB)

    Pang, Hongfeng [Academy of Equipment, Beijing 101416 (China); College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073 (China); Zhu, XueJun, E-mail: zhuxuejun1990@126.com [College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073 (China); Pan, Mengchun; Zhang, Qi; Wan, Chengbiao; Luo, Shitu; Chen, Dixiang; Chen, Jinfei; Li, Ji; Lv, Yunxiao [College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073 (China)

    2016-12-01

    Misalignment error is one key factor influencing the measurement accuracy of geomagnetic vector measurement system, which should be calibrated with the difficulties that sensors measure different physical information and coordinates are invisible. A new misalignment calibration method by rotating a parallelepiped frame is proposed. Simulation and experiment result show the effectiveness of calibration method. The experimental system mainly contains DM-050 three-axis fluxgate magnetometer, INS (inertia navigation system), aluminium parallelepiped frame, aluminium plane base. Misalignment angles are calculated by measured data of magnetometer and INS after rotating the aluminium parallelepiped frame on aluminium plane base. After calibration, RMS error of geomagnetic north, vertical and east are reduced from 349.441 nT, 392.530 nT and 562.316 nT to 40.130 nT, 91.586 nT and 141.989 nT respectively. - Highlights: • A new misalignment calibration method by rotating a parallelepiped frame is proposed. • It does not need to know sensor attitude information or local dip angle. • The calibration system attitude change angle is not strictly required. • It can be widely used when sensors measure different physical information. • Geomagnetic vector measurement error is reduced evidently.

  14. Linear Matrix Inequalities for Analysis and Control of Linear Vector Second-Order Systems

    DEFF Research Database (Denmark)

    Adegas, Fabiano Daher; Stoustrup, Jakob

    2015-01-01

    the Lyapunov matrix and the system matrices by introducing matrix multipliers, which potentially reduce conservativeness in hard control problems. Multipliers facilitate the usage of parameter-dependent Lyapunov functions as certificates of stability of uncertain and time-varying vector second-order systems......SUMMARY Many dynamical systems are modeled as vector second-order differential equations. This paper presents analysis and synthesis conditions in terms of LMI with explicit dependence in the coefficient matrices of vector second-order systems. These conditions benefit from the separation between...

  15. Robust Vision-Based Pose Estimation Algorithm for AN Uav with Known Gravity Vector

    Science.gov (United States)

    Kniaz, V. V.

    2016-06-01

    Accurate estimation of camera external orientation with respect to a known object is one of the central problems in photogrammetry and computer vision. In recent years this problem is gaining an increasing attention in the field of UAV autonomous flight. Such application requires a real-time performance and robustness of the external orientation estimation algorithm. The accuracy of the solution is strongly dependent on the number of reference points visible on the given image. The problem only has an analytical solution if 3 or more reference points are visible. However, in limited visibility conditions it is often needed to perform external orientation with only 2 visible reference points. In such case the solution could be found if the gravity vector direction in the camera coordinate system is known. A number of algorithms for external orientation estimation for the case of 2 known reference points and a gravity vector were developed to date. Most of these algorithms provide analytical solution in the form of polynomial equation that is subject to large errors in the case of complex reference points configurations. This paper is focused on the development of a new computationally effective and robust algorithm for external orientation based on positions of 2 known reference points and a gravity vector. The algorithm implementation for guidance of a Parrot AR.Drone 2.0 micro-UAV is discussed. The experimental evaluation of the algorithm proved its computational efficiency and robustness against errors in reference points positions and complex configurations.

  16. Study on Immune Relevant Vector Machine Based Intelligent Fault Detection and Diagnosis Algorithm

    Directory of Open Access Journals (Sweden)

    Zhong-hua Miao

    2013-01-01

    Full Text Available An immune relevant vector machine (IRVM based intelligent classification method is proposed by combining the random real-valued negative selection (RRNS algorithm and the relevant vector machine (RVM algorithm. The method proposed is aimed to handle the training problem of missing or incomplete fault sampling data and is inspired by the “self/nonself” recognition principle in the artificial immune systems. The detectors, generated by the RRNS, are treated as the “nonself” training samples and used to train the RVM model together with the “self” training samples. After the training succeeds, the “nonself” detection model, which requires only the “self” training samples, is obtained for the fault detection and diagnosis. It provides a general way solving the problems of this type and can be applied for both fault detection and fault diagnosis. The standard Fisher's Iris flower dataset is used to experimentally testify the proposed method, and the results are compared with those from the support vector data description (SVDD method. Experimental results have shown the validity and practicability of the proposed method.

  17. Determinants of Health Service Responsiveness in Community-Based Vector Surveillance for Chagas Disease in Guatemala, El Salvador, and Honduras.

    Science.gov (United States)

    Hashimoto, Ken; Zúniga, Concepción; Romero, Eduardo; Morales, Zoraida; Maguire, James H

    2015-01-01

    Central American countries face a major challenge in the control of Triatoma dimidiata, a widespread vector of Chagas disease that cannot be eliminated. The key to maintaining the risk of transmission of Trypanosoma cruzi at lowest levels is to sustain surveillance throughout endemic areas. Guatemala, El Salvador, and Honduras integrated community-based vector surveillance into local health systems. Community participation was effective in detection of the vector, but some health services had difficulty sustaining their response to reports of vectors from the population. To date, no research has investigated how best to maintain and reinforce health service responsiveness, especially in resource-limited settings. We reviewed surveillance and response records of 12 health centers in Guatemala, El Salvador, and Honduras from 2008 to 2012 and analyzed the data in relation to the volume of reports of vector infestation, local geography, demography, human resources, managerial approach, and results of interviews with health workers. Health service responsiveness was defined as the percentage of households that reported vector infestation for which the local health service provided indoor residual spraying of insecticide or educational advice. Eight potential determinants of responsiveness were evaluated by linear and mixed-effects multi-linear regression. Health service responsiveness (overall 77.4%) was significantly associated with quarterly monitoring by departmental health offices. Other potential determinants of responsiveness were not found to be significant, partly because of short- and long-term strategies, such as temporary adjustments in manpower and redistribution of tasks among local participants in the effort. Consistent monitoring within the local health system contributes to sustainability of health service responsiveness in community-based vector surveillance of Chagas disease. Even with limited resources, countries can improve health service

  18. Determinants of Health Service Responsiveness in Community-Based Vector Surveillance for Chagas Disease in Guatemala, El Salvador, and Honduras

    Science.gov (United States)

    Hashimoto, Ken; Zúniga, Concepción; Romero, Eduardo; Morales, Zoraida; Maguire, James H.

    2015-01-01

    Background Central American countries face a major challenge in the control of Triatoma dimidiata, a widespread vector of Chagas disease that cannot be eliminated. The key to maintaining the risk of transmission of Trypanosoma cruzi at lowest levels is to sustain surveillance throughout endemic areas. Guatemala, El Salvador, and Honduras integrated community-based vector surveillance into local health systems. Community participation was effective in detection of the vector, but some health services had difficulty sustaining their response to reports of vectors from the population. To date, no research has investigated how best to maintain and reinforce health service responsiveness, especially in resource-limited settings. Methodology/Principal Findings We reviewed surveillance and response records of 12 health centers in Guatemala, El Salvador, and Honduras from 2008 to 2012 and analyzed the data in relation to the volume of reports of vector infestation, local geography, demography, human resources, managerial approach, and results of interviews with health workers. Health service responsiveness was defined as the percentage of households that reported vector infestation for which the local health service provided indoor residual spraying of insecticide or educational advice. Eight potential determinants of responsiveness were evaluated by linear and mixed-effects multi-linear regression. Health service responsiveness (overall 77.4%) was significantly associated with quarterly monitoring by departmental health offices. Other potential determinants of responsiveness were not found to be significant, partly because of short- and long-term strategies, such as temporary adjustments in manpower and redistribution of tasks among local participants in the effort. Conclusions/Significance Consistent monitoring within the local health system contributes to sustainability of health service responsiveness in community-based vector surveillance of Chagas disease. Even with

  19. A comparative study on change vector analysis based change ...

    Indian Academy of Sciences (India)

    From this viewpoint, different change detection algorithms have been developed for land-use land-cover (LULC) region. Among the different change detection algorithms, change vector analysis (CVA) has level headed capability of extracting maximuminformation in terms of overall magnitude of change and the direction of ...

  20. Development and Applications of VSV Vectors Based on Cell Tropism.

    Science.gov (United States)

    Tani, Hideki; Morikawa, Shigeru; Matsuura, Yoshiharu

    2011-01-01

    Viral vectors have been available in various fields such as medical and biological research or gene therapy applications. Targeting vectors pseudotyped with distinct viral envelope proteins that influence cell tropism and transfection efficiency are useful tools not only for examining entry mechanisms or cell tropisms but also for vaccine vector development. Vesicular stomatitis virus (VSV) is an excellent candidate for development as a pseudotype vector. A recombinant VSV lacking its own envelope (G) gene has been used to produce a pseudotype or recombinant VSV possessing the envelope proteins of heterologous viruses. These viruses possess a reporter gene instead of a VSV G gene in their genome, and therefore it is easy to evaluate their infectivity in the study of viral entry, including identification of viral receptors. Furthermore, advantage can be taken of a property of the pseudotype VSV, which is competence for single-round infection, in handling many different viruses that are either difficult to amplify in cultured cells or animals or that require specialized containment facilities. Here we describe procedures for producing pseudotype or recombinant VSVs and a few of the more prominent examples from envelope viruses, such as hepatitis C virus, Japanese encephalitis virus, baculovirus, and hemorrhagic fever viruses.

  1. Vector control of three-phase AC machines system development in the practice

    CERN Document Server

    Quang, Nguyen Phung; Dittrich, J

    2015-01-01

    This book addresses the vector control of three-phase AC machines, in particular induction motors with squirrel-cage rotors (IM), permanent magnet synchronous motors (PMSM) and doubly-fed induction machines (DFIM), from a practical design and development perspective. The main focus is on the application of IM and PMSM in electrical drive systems, where field-orientated control has been successfully established in practice. It also discusses the use of grid-voltage oriented control of DFIMs in wind power plants. This second, enlarged edition includes new insights into flatness-based  nonlinear

  2. Skin injury model classification based on shape vector analysis.

    Science.gov (United States)

    Röhrich, Emil; Thali, Michael; Schweitzer, Wolf

    2012-11-06

    Skin injuries can be crucial in judicial decision making. Forensic experts base their classification on subjective opinions. This study investigates whether known classes of simulated skin injuries are correctly classified statistically based on 3D surface models and derived numerical shape descriptors. Skin injury surface characteristics are simulated with plasticine. Six injury classes - abrasions, incised wounds, gunshot entry wounds, smooth and textured strangulation marks as well as patterned injuries - with 18 instances each are used for a k-fold cross validation with six partitions. Deformed plasticine models are captured with a 3D surface scanner. Mean curvature is estimated for each polygon surface vertex. Subsequently, distance distributions and derived aspect ratios, convex hulls, concentric spheres, hyperbolic points and Fourier transforms are used to generate 1284-dimensional shape vectors. Subsequent descriptor reduction maximizing SNR (signal-to-noise ratio) result in an average of 41 descriptors (varying across k-folds). With non-normal multivariate distribution of heteroskedastic data, requirements for LDA (linear discriminant analysis) are not met. Thus, shrinkage parameters of RDA (regularized discriminant analysis) are optimized yielding a best performance with λ = 0.99 and γ = 0.001. Receiver Operating Characteristic of a descriptive RDA yields an ideal Area Under the Curve of 1.0 for all six categories. Predictive RDA results in an average CRR (correct recognition rate) of 97,22% under a 6 partition k-fold. Adding uniform noise within the range of one standard deviation degrades the average CRR to 71,3%. Digitized 3D surface shape data can be used to automatically classify idealized shape models of simulated skin injuries. Deriving some well established descriptors such as histograms, saddle shape of hyperbolic points or convex hulls with subsequent reduction of dimensionality while maximizing SNR seem to work well for the data at hand, as

  3. Space vector modulation strategy for neutral-point voltage balancing in three-level inverter systems

    DEFF Research Database (Denmark)

    Choi, Uimin; Lee, Kyo Beum

    2013-01-01

    This study proposes a space vector modulation (SVM) strategy to balance the neutral-point voltage of three-level inverter systems. The proposed method is implemented by combining conventional symmetric SVM with nearest three-vector (NTV) modulation. The conventional SVM is converted to NTV modula...

  4. Third-Order Newton-Type Methods Combined with Vector Extrapolation for Solving Nonlinear Systems

    Directory of Open Access Journals (Sweden)

    Wen Zhou

    2014-01-01

    Full Text Available We present a third-order method for solving the systems of nonlinear equations. This method is a Newton-type scheme with the vector extrapolation. We establish the local and semilocal convergence of this method. Numerical results show that the composite method is more robust and efficient than a number of Newton-type methods with the other vector extrapolations.

  5. Iterative linear system solvers with approximate matrix-vector products

    NARCIS (Netherlands)

    Eshof, J. van den; Sleijpen, G.L.G.; Gijzen, M.B. van

    2003-01-01

    There are classes of linear problems for which a matrix-vector product is a time consuming operation because an expensive approximation method is required to compute it to a given accuracy. One important example is simulations in lattice QCD with Neuberger fermions where a matrix multiply

  6. Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort.

    Science.gov (United States)

    Casas, Jérôme; Lazzari, Claudio; Insausti, Teresita; Launois, Pascal; Fouque, Florence

    2016-11-01

    Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC) powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR).

  7. Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort

    Directory of Open Access Journals (Sweden)

    Jérôme Casas

    Full Text Available Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR.

  8. Inadvertent gene silencing of argininosuccinate synthase (bcass1) in Botrytis cinerea by the pLOB1 vector system

    NARCIS (Netherlands)

    Patel, R.M.; Kan, van J.A.L.; Bailey, A.M.; Foster, G.D.

    2010-01-01

    For several years, researchers working on the plant pathogen Botrytis cinerea and a number of other related fungi have routinely used the pLOB1 vector system, based on hygromycin resistance, under the control of the Aspergillus nidulans oliC promoter and what was reported to be the ß-tubulin (tubA)

  9. The pOT and pLOB vector systems: Improving ease of transgene expression in Botrytis cinerea

    NARCIS (Netherlands)

    Patel, R.M.; Heneghan, M.N.; Kan, van J.A.L.; Bailey, A.M.; Foster, G.D.

    2008-01-01

    This paper outlines the construction of a novel vector system comprising interchangeable terminators, as well as a multiple cloning site (MCS), to facilitate the transformation of the fungal plant pathogen Botrytis cinerea. Previous molecular studies on B. cinerea have relied upon the pLOB1 based

  10. Development of expression vectors for Escherichia coli based on the pCR2 replicon

    Directory of Open Access Journals (Sweden)

    Deb J K

    2007-05-01

    Full Text Available Abstract Background Recent developments in metabolic engineering and the need for expanded compatibility required for co-expression studies, underscore the importance of developing new plasmid vectors with properties such as stability and compatibility. Results We utilized the pCR2 replicon of Corynebacterium renale, which harbours multiple plasmids, for constructing a range of expression vectors. Different antibiotic-resistance markers were introduced and the vectors were found to be 100% stable over a large number of generations in the absence of selection pressure. Compatibility of this plasmid was studied with different Escherichia coli plasmid replicons viz. pMB1 and p15A. It was observed that pCR2 was able to coexist with these E.coli plasmids for 60 generations in the absence of selection pressure. Soluble intracellular production was checked by expressing GFP under the lac promoter in an expression plasmid pCR2GFP. Also high level production of human IFNγ was obtained by cloning the h-IFNγ under a T7 promoter in the expression plasmid pCR2-IFNγ and using a dual plasmid heat shock system for expression. Repeated sub-culturing in the absence of selection pressure for six days did not lead to any fall in the production levels post induction, for both GFP and h-IFNγ, demonstrating that pCR2 is a useful plasmid in terms of stability and compatibility. Conclusion We have constructed a series of expression vectors based on the pCR2 replicon and demonstrated its high stability and sustained expression capacity, in the absence of selection pressure which will make it an efficient tool for metabolic engineering and co-expression studies, as well as for scale up of expression.

  11. Expression of Separate Proteins in the Same Plant Leaves and Cells Using Two Independent Virus-Based Gene Vectors

    Directory of Open Access Journals (Sweden)

    Maria R. Mendoza

    2017-11-01

    Full Text Available Plant viral vectors enable the expression of proteins at high levels in a relatively short time. For many purposes (e.g., cell biological interaction studies it may be desirable to express more than one protein in a single cell but that is often not feasible when using a single virus vector. Such a co-expression strategy requires the simultaneous delivery by two compatible and non-competitive viruses that can co-exist to each express a separate protein. Here, we report on the use of two agro-launchable coat-protein gene substitution GFP-expressing virus vector systems based on Tomato bushy stunt virus (TBSV referred to as TG, and Tobacco mosaic virus (TMV annotated as TRBO-G. TG expressed GFP in Nicotiana benthamiana, tomato, lettuce and cowpea, whereas expression from TRBO-G was detected only in the first two species. Upon co-infiltration of the two vectors co-expression was monitored by: molecular detection of the two slightly differently sized GFPs, suppressor-complementation assays, and using TG in combination with TRBO-RFP. All the results revealed that in N. benthamiana and tomato the TBSV and TMV vectors accumulated and expressed proteins in the same plants, the same leaves, and in the same cells. Therefore, co-expression by these two vectors provides a platform for fast and high level expression of proteins to study their cell biology or other properties.

  12. Expression of Separate Proteins in the Same Plant Leaves and Cells Using Two Independent Virus-Based Gene Vectors.

    Science.gov (United States)

    Mendoza, Maria R; Payne, Alexandria N; Castillo, Sean; Crocker, Megan; Shaw, Brian D; Scholthof, Herman B

    2017-01-01

    Plant viral vectors enable the expression of proteins at high levels in a relatively short time. For many purposes (e.g., cell biological interaction studies) it may be desirable to express more than one protein in a single cell but that is often not feasible when using a single virus vector. Such a co-expression strategy requires the simultaneous delivery by two compatible and non-competitive viruses that can co-exist to each express a separate protein. Here, we report on the use of two agro-launchable coat-protein gene substitution GFP-expressing virus vector systems based on Tomato bushy stunt virus (TBSV) referred to as TG, and Tobacco mosaic virus (TMV) annotated as TRBO-G. TG expressed GFP in Nicotiana benthamiana, tomato, lettuce and cowpea, whereas expression from TRBO-G was detected only in the first two species. Upon co-infiltration of the two vectors co-expression was monitored by: molecular detection of the two slightly differently sized GFPs, suppressor-complementation assays, and using TG in combination with TRBO-RFP. All the results revealed that in N. benthamiana and tomato the TBSV and TMV vectors accumulated and expressed proteins in the same plants, the same leaves, and in the same cells. Therefore, co-expression by these two vectors provides a platform for fast and high level expression of proteins to study their cell biology or other properties.

  13. Prolonged transgene expression in glomeruli using an EBV replicon vector system combined with HVJ liposomes.

    Science.gov (United States)

    Tsujie, M; Isaka, Y; Nakamura, H; Kaneda, Y; Imai, E; Hori, M

    2001-04-01

    Various gene transfer vectors as well as delivery systems have been developed; however, many problems remain to be solved. We already achieved a technique to introduce genes into glomerular mesangial cells by hemagglutinating virus of Japan (HVJ) liposome-mediated gene transfer via renal artery. The main limitation of this method is the transient transgene expression. For long-term gene expression in glomeruli, Epstein-Barr virus (EBV) replicon-based plasmid was employed, containing the latent viral DNA replication origin (oriP) and EBV nuclear antigen-1 (EBNA-1), which are the minimum EBV component of transgene-nuclear retention. To examine the effect of EBV replicon apparatus on the duration of transgene expression in glomeruli in vivo, the EBV replicon vector pEBActLuc, and the control plasmid vector pActLuc were adopted. These plasmid vectors were transferred into the kidney via renal artery by using artificial viral envelope (AVE)-type HVJ liposome method, and glomerular luciferase activities were analyzed at various time points after transfection. On day 4, pEBActLuc and pActLuc transfer resulted in equal glomerular luciferase activity, and the luciferase gene expression was sustained for at least 56 days in glomeruli transfected with pEBActLuc, whereas it was reduced on seven days in glomeruli transfected with pActLuc. The combination of EBV replicon apparatus and HVJ liposomes appears to be a powerful tool for long-term gene expression in vivo, and furthermore, it may be a promising new therapeutic method for the progression of renal disease.

  14. A comparative study on the immunotherapeutic efficacy of recombinant Semliki Forest virus and adenovirus vector systems in a murine model for cervical cancer

    NARCIS (Netherlands)

    Riezebos-Brilman, A.; Walczak, M.; Regts, J.; Rots, Mg; Kamps, G.; Dontje, B.; Haisma, Hy; Wilschut, J.; Daemen, T.

    2007-01-01

    Currently, various therapeutic strategies are being explored as a potential means to immunize against metastatic malignant cells or even primary tumours. Using recombinant viral vectors systems or protein-based immunization approaches, we are developing immunotherapeutic strategies against cervical

  15. Modelling a Voice Activated Speaker Identification System using MFCC-Pitch-Formant Vector

    Science.gov (United States)

    Sengupta, Avik; Ghosh, Rabindranath

    2012-03-01

    The paper presents the model of an automatic speaker identification system which will recognize users based on their voice. The system will be relatively independent of spoken words but will rely on the voice quality of a user i.e. use speech independent voice recognition. The basic approach was to create a front end system which will identify speech parameters of particular users and create speech feature vectors which will later be used to train a back-propagation neural network for the recognition phase. Mel-frequency cepstrum coefficients and linear predictive coding coefficients have been used, along with Pitch and Formants, for feature extraction. The main area of focus of the paper is to outline the optimum set of speech features which form the most reliable model for an automatic speaker identification system.

  16. Face Recognition Performance Improvement using a Similarity Score of Feature Vectors based on Probabilistic Histograms

    Directory of Open Access Journals (Sweden)

    SRIKOTE, G.

    2016-08-01

    Full Text Available This paper proposes an improved performance algorithm of face recognition to identify two face mismatch pairs in cases of incorrect decisions. The primary feature of this method is to deploy the similarity score with respect to Gaussian components between two previously unseen faces. Unlike the conventional classical vector distance measurement, our algorithms also consider the plot of summation of the similarity index versus face feature vector distance. A mixture of Gaussian models of labeled faces is also widely applicable to different biometric system parameters. By comparative evaluations, it has been shown that the efficiency of the proposed algorithm is superior to that of the conventional algorithm by an average accuracy of up to 1.15% and 16.87% when compared with 3x3 Multi-Region Histogram (MRH direct-bag-of-features and Principal Component Analysis (PCA-based face recognition systems, respectively. The experimental results show that similarity score consideration is more discriminative for face recognition compared to feature distance. Experimental results of Labeled Face in the Wild (LFW data set demonstrate that our algorithms are suitable for real applications probe-to-gallery identification of face recognition systems. Moreover, this proposed method can also be applied to other recognition systems and therefore additionally improves recognition scores.

  17. DSP Based Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) using Space Vector Modulation (DTC-SVM)

    DEFF Research Database (Denmark)

    Swierczynski, Dariusz; Kazmierkowski, Marian P.; Blaabjerg, Frede

    2002-01-01

    DSP Based Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) using Space Vector Modulation (DTC-SVM)......DSP Based Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) using Space Vector Modulation (DTC-SVM)...

  18. Chord Recognition Based on Temporal Correlation Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhongyang Rao

    2016-05-01

    Full Text Available In this paper, we propose a method called temporal correlation support vector machine (TCSVM for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and the sparse component to contain the vocal signals. Then, we extract a new logarithmic pitch class profile (LPCP feature called enhanced LPCP from the low-rank part. To exploit the temporal correlation among the LPCP features of chords, we propose an improved support vector machine algorithm called TCSVM. We perform this study using the MIREX’09 (Music Information Retrieval Evaluation eXchange Audio Chord Estimation dataset. Furthermore, we conduct comprehensive experiments using different pitch class profile feature vectors to examine the performance of TCSVM. The results of our method are comparable to the state-of-the-art methods that entered the MIREX in 2013 and 2014 for the MIREX’09 Audio Chord Estimation task dataset.

  19. Re-engineering an alphoidtetO-HAC-based vector to enable high-throughput analyses of gene function

    Science.gov (United States)

    Kononenko, Artem V.; Lee, Nicholas C. O.; Earnshaw, William C.; Kouprina, Natalay; Larionov, Vladimir

    2013-01-01

    Human artificial chromosome (HAC)-based vectors represent an alternative technology for gene delivery and expression with a potential to overcome the problems caused by the use of viral-based vectors. The recently developed alphoidtetO-HAC has an advantage over other HAC vectors because it can be easily eliminated from cells by inactivation of the HAC kinetochore via binding of tTS chromatin modifiers to its centromeric tetO sequences. This provides unique control for phenotypes induced by genes loaded into the alphoidtetO-HAC. However, inactivation of the HAC kinetochore requires transfection of cells by a retrovirus vector, a step that is potentially mutagenic. Here, we describe an approach to re-engineering the alphoidtetO-HAC that allows verification of phenotypic changes attributed to expression of genes from the HAC without a transfection step. In the new HAC vector, a tTS-EYFP cassette is inserted into a gene-loading site along with a gene of interest. Expression of the tTS generates a self-regulating fluctuating heterochromatin on the alphoidtetO-HAC that induces fast silencing of the genes on the HAC without significant effects on HAC segregation. This silencing of the HAC-encoded genes can be readily recovered by adding doxycycline. The newly modified alphoidtetO-HAC-based system has multiple applications in gene function studies. PMID:23558748

  20. Re-engineering an alphoid(tetO)-HAC-based vector to enable high-throughput analyses of gene function.

    Science.gov (United States)

    Kononenko, Artem V; Lee, Nicholas C O; Earnshaw, William C; Kouprina, Natalay; Larionov, Vladimir

    2013-05-01

    Human artificial chromosome (HAC)-based vectors represent an alternative technology for gene delivery and expression with a potential to overcome the problems caused by the use of viral-based vectors. The recently developed alphoid(tetO)-HAC has an advantage over other HAC vectors because it can be easily eliminated from cells by inactivation of the HAC kinetochore via binding of tTS chromatin modifiers to its centromeric tetO sequences. This provides unique control for phenotypes induced by genes loaded into the alphoid(tetO)-HAC. However, inactivation of the HAC kinetochore requires transfection of cells by a retrovirus vector, a step that is potentially mutagenic. Here, we describe an approach to re-engineering the alphoid(tetO)-HAC that allows verification of phenotypic changes attributed to expression of genes from the HAC without a transfection step. In the new HAC vector, a tTS-EYFP cassette is inserted into a gene-loading site along with a gene of interest. Expression of the tTS generates a self-regulating fluctuating heterochromatin on the alphoid(tetO)-HAC that induces fast silencing of the genes on the HAC without significant effects on HAC segregation. This silencing of the HAC-encoded genes can be readily recovered by adding doxycycline. The newly modified alphoid(tetO)-HAC-based system has multiple applications in gene function studies.

  1. Chilli leaf curl virus-based vector for phloem-specific silencing of endogenous genes and overexpression of foreign genes.

    Science.gov (United States)

    Kushwaha, Nirbhay Kumar; Chakraborty, Supriya

    2017-03-01

    Geminiviruses are the largest and most devastating group of plant viruses which contain ssDNA as a genetic material. Geminivirus-derived virus-induced gene silencing (VIGS) vectors have emerged as an efficient and simple tool to study functional genomics in various plants. However, previously developed VIGS vectors have certain limitations, owing to their inability to be used in tissue-specific functional study. In the present study, we developed a Chilli leaf curl virus (ChiLCV)-based VIGS vector for its tissue-specific utilization by replacing the coat protein gene (open reading frame (ORF) AV1) with the gene of interest for phytoene desaturase (PDS) of Nicotiana benthamiana. Functional validation of ChiLCV-based VIGS in N. benthamiana resulted in systemic silencing of PDS exclusively in the phloem region of inoculated plants. Furthermore, expression of enhanced green fluorescence protein (EGFP) using the same ChiLCV vector was verified in the phloem region of the inoculated plants. Our results also suggested that, during the early phase of infection, ChiLCV was associated with the phloem region, but at later stage of pathogenesis, it can spread into the adjoining non-vascular tissues. Taken together, the newly developed ChiLCV-based vector provides an efficient and versatile tool, which can be exploited to unveil the unknown functions of several phloem-specific genes.

  2. Flagellin Encoded in Gene-Based Vector Vaccines Is a Route-Dependent Immune Adjuvant.

    Directory of Open Access Journals (Sweden)

    Hamada F Rady

    Full Text Available Flagellin has been tested as a protein-based vaccine adjuvant, with the majority of studies focused on antibody responses. Here, we evaluated the adjuvant activity of flagellin for both cellular and humoral immune responses in BALB/c mice in the setting of gene-based immunization, and have made several novel observations. DNA vaccines and adenovirus (Ad vectors were engineered to encode mycobacterial protein Ag85B, with or without flagellin of Salmonella typhimurium (FliC. DNA-encoded flagellin given IM enhanced splenic CD4+ and CD8+ T cell responses to co-expressed vaccine antigen, including memory responses. Boosting either IM or intranasally with Ad vectors expressing Ag85B without flagellin led to durable enhancement of Ag85B-specific antibody and CD4+ and CD8+ T cell responses in both spleen and pulmonary tissues, correlating with significantly improved protection against challenge with pathogenic aerosolized M. tuberculosis. However, inclusion of flagellin in both DNA prime and Ad booster vaccines induced localized pulmonary inflammation and transient weight loss, with route-dependent effects on vaccine-induced T cell immunity. The latter included marked reductions in levels of mucosal CD4+ and CD8+ T cell responses following IM DNA/IN Ad mucosal prime-boosting, although antibody responses were not diminished. These findings indicate that flagellin has differential and route-dependent adjuvant activity when included as a component of systemic or mucosally-delivered gene-based prime-boost immunization. Clear adjuvant activity for both T and B cell responses was observed when flagellin was included in the DNA priming vaccine, but side effects occurred when given in an Ad boosting vector, particularly via the pulmonary route.

  3. Support Vector Regression-Based Adaptive Divided Difference Filter for Nonlinear State Estimation Problems

    Directory of Open Access Journals (Sweden)

    Hongjian Wang

    2014-01-01

    Full Text Available We present a support vector regression-based adaptive divided difference filter (SVRADDF algorithm for improving the low state estimation accuracy of nonlinear systems, which are typically affected by large initial estimation errors and imprecise prior knowledge of process and measurement noises. The derivative-free SVRADDF algorithm is significantly simpler to compute than other methods and is implemented using only functional evaluations. The SVRADDF algorithm involves the use of the theoretical and actual covariance of the innovation sequence. Support vector regression (SVR is employed to generate the adaptive factor to tune the noise covariance at each sampling instant when the measurement update step executes, which improves the algorithm’s robustness. The performance of the proposed algorithm is evaluated by estimating states for (i an underwater nonmaneuvering target bearing-only tracking system and (ii maneuvering target bearing-only tracking in an air-traffic control system. The simulation results show that the proposed SVRADDF algorithm exhibits better performance when compared with a traditional DDF algorithm.

  4. Pain perception in children during caries removal with the Vector system: a pilot study.

    Science.gov (United States)

    Chomyszyn-Gajewska, M; Kwapinska, H; Zarzecka, J

    2006-03-01

    A pilot study to compare pain perception during caries treatment in children by means of: the Vector system versus a mechanical method. A population of 31 children, aged 7-11 years, with a positive attitude towards dental treatment was recruited. Every child had two permanent molar teeth treated, one using the Vector system (piezo-driven ultrasonic device) and the other using conventional method (dental bur). Corah, Hochman and the visual scale (Facial Expression Scale) were applied to evaluate anxiety and pain perception. Treatment with the Vector system required significantly longer time 31.1 versus 4.7 mins for the conventional method. With the Vector system 54.8% of children and with conventional method 29.0% felt no pain. Girls admitted to feeling more pain than boys (verbal scale p caries in children, because it minimizes the negative attitudes to pain but takes significantly longer to use.

  5. Vector mode conversion based on tilted fiber Bragg grating in ring-core fibers

    Science.gov (United States)

    Mi, Yuean; Ren, Guobin; Gao, Yixiao; Li, Haisu; Zhu, Bofeng; Liu, Yu

    2018-03-01

    We propose a vector mode conversion approach based on tilted fiber Bragg grating (TFBG) written in ring-core fiber with effective separation of eigenmodes. The mode coupling properties of TFBG are numerically investigated. It is shown that under the constraint of phase matching, the conversion of high-order vector modes could be achieved at specific wavelengths. Moreover, the polarization of incident light and tilt angle of TFBG play critical roles in mode coupling process. The proposed TFBG provides an efficient method to realize high-order vector mode conversion, and it shows great potential for fibers based OAM beam generation and fiber lasers with vortex beams output.

  6. Automatic SIMD vectorization of SSA-based control flow graphs

    CERN Document Server

    Karrenberg, Ralf

    2015-01-01

    Ralf Karrenberg presents Whole-Function Vectorization (WFV), an approach that allows a compiler to automatically create code that exploits data-parallelism using SIMD instructions. Data-parallel applications such as particle simulations, stock option price estimation or video decoding require the same computations to be performed on huge amounts of data. Without WFV, one processor core executes a single instance of a data-parallel function. WFV transforms the function to execute multiple instances at once using SIMD instructions. The author describes an advanced WFV algorithm that includes a v

  7. Sagnac Interferometer Based Generation of Controllable Cylindrical Vector Beams

    Directory of Open Access Journals (Sweden)

    Cristian Acevedo

    2016-01-01

    Full Text Available We report on a novel experimental geometry to generate cylindrical vector beams in a very robust manner. Continuous control of beams’ properties is obtained using an optically addressable spatial light modulator incorporated into a Sagnac interferometer. Forked computer-generated holograms allow introducing different topological charges while orthogonally polarized beams within the interferometer permit encoding the spatial distribution of polarization. We also demonstrate the generation of complex waveforms obtained by combining two orthogonal beams having both radial modulations and azimuthal dislocations.

  8. A vector system for genomic FLAG epitope-tagging in Schizosaccharomyces pombe.

    Science.gov (United States)

    Noguchi, Chiaki; Garabedian, Mikael V; Malik, Marriam; Noguchi, Eishi

    2008-10-01

    The fission yeast Schizosaccharomyces pombe is a popular model organism to study various cellular processes, although research tools available for S. pombe are relatively inadequate. To facilitate genetic and biochemical investigation in S. pombe, we report here a system of vectors for genomic FLAG epitope-tagging. These vectors enable us to amplify gene-targeting fragments for integration into specific loci of the S. pombe genome. All vectors in this report were designed to express FLAG epitope-tagged proteins from their endogenous genomic loci. Vectors for N-terminal FLAG epitope-tagging allow us to control protein expression levels using the wild-type nmt1 promoter, its weaker derivatives, and the urg1 promoter. These vectors are available with various antibiotic markers including kanMX6, hphMX6, natMX6 and bleMX6, and the his3(+) marker. Vectors for C-terminal FLAG epitope-tagging were designed to express FLAG-fusion proteins under the control of their native promoters at their own genomic loci, allowing us to characterize protein functions under physiological conditions. These vectors are available with kanMX6, hphMX6, nat-MX6 and bleMX6 markers. The series of vectors described in this report should prove useful for protein studies in fission yeast.

  9. Vector-Borne Pathogen and Host Evolution in a Structured Immuno-Epidemiological System.

    Science.gov (United States)

    Gulbudak, Hayriye; Cannataro, Vincent L; Tuncer, Necibe; Martcheva, Maia

    2017-02-01

    Vector-borne disease transmission is a common dissemination mode used by many pathogens to spread in a host population. Similar to directly transmitted diseases, the within-host interaction of a vector-borne pathogen and a host's immune system influences the pathogen's transmission potential between hosts via vectors. Yet there are few theoretical studies on virulence-transmission trade-offs and evolution in vector-borne pathogen-host systems. Here, we consider an immuno-epidemiological model that links the within-host dynamics to between-host circulation of a vector-borne disease. On the immunological scale, the model mimics antibody-pathogen dynamics for arbovirus diseases, such as Rift Valley fever and West Nile virus. The within-host dynamics govern transmission and host mortality and recovery in an age-since-infection structured host-vector-borne pathogen epidemic model. By considering multiple pathogen strains and multiple competing host populations differing in their within-host replication rate and immune response parameters, respectively, we derive evolutionary optimization principles for both pathogen and host. Invasion analysis shows that the [Formula: see text] maximization principle holds for the vector-borne pathogen. For the host, we prove that evolution favors minimizing case fatality ratio (CFR). These results are utilized to compute host and pathogen evolutionary trajectories and to determine how model parameters affect evolution outcomes. We find that increasing the vector inoculum size increases the pathogen [Formula: see text], but can either increase or decrease the pathogen virulence (the host CFR), suggesting that vector inoculum size can contribute to virulence of vector-borne diseases in distinct ways.

  10. Transduction of striatum and cortex tissues by adeno-associated viral vectors produced by herpes simplex virus- and baculovirus-based methods.

    Science.gov (United States)

    Zhang, H Steve; Kim, Eunmi; Lee, Slgirim; Ahn, Ik-Sung; Jang, Jae-Hyung

    2012-01-01

    Recombinant adeno-associated virus (AAV) vectors can be engineered to carry genetic material encoding therapeutic gene products that have demonstrated significant clinical promise. These viral vectors are typically produced in mammalian cells by the transient transfection of two or three plasmids encoding the AAV rep and cap genes, the adenovirus helper gene, and a gene of interest. Although this method can produce high-quality AAV vectors when used with multiple purification protocols, one critical limitation is the difficulty in scaling-up manufacturing, which poses a significant hurdle to the broad clinical utilization of AAV vectors. To address this challenge, recombinant herpes simplex virus type I (rHSV-1)- and recombinant baculovirus (rBac)-based methods have been established recently. These methods are more amenable to large-scale production of AAV vectors than methods using the transient transfection of mammalian cells. To investigate potential applications of AAV vectors produced by rHSV-1- or rBac-based platforms, the in vivo transduction of rHSV-1- or rBac-produced AAV serotype 2 (AAV2) vectors within the rat brain were examined by comparing them with vectors generated by the conventional transfection method. Injection of rHSV-1- or rBac-produced AAV vectors into rat striatum and cortex tissues revealed no differences in cellular tropism (i.e., predominantly neuronal targeting) or anteroposterior spread compared with AAV2 vectors produced by transient transfection. This report represents a step towards validating AAV vectors produced by the rHSV-1- and the rBac-based systems as promising tools, especially for delivering therapeutic molecules to the central nervous system. Copyright © 2011 Elsevier B.V. All rights reserved.

  11. Dynamic Vectorization in the E2 Dynamic Multicore System

    OpenAIRE

    Putnam, Andrew; Smith, Aaron; Burger, Doug

    2010-01-01

    Previous research has shown that Explicit Data Graph Execution (EDGE) instruction set architectures (ISA) allow for power efficient performance scaling. In this paper we describe the preliminary design of a new dynamic multicore processor called E2 that utilizes an EDGE ISA to allow for the dynamic composition of physical cores into logical processors. We provide details of E2’s support for dynamic reconfigurability and show how the EDGE ISA facilities out-of-order vector execution.

  12. HVJ envelope vector, a versatile delivery system: its development, application, and perspectives.

    Science.gov (United States)

    Zhang, Qingxian; Li, Ying; Shi, Yonghong; Zhang, Yanling

    2008-08-29

    An efficient and minimally invasive vector system is the "bottle neck" of both gene transfer and drug delivery. Numerous viral and non-viral (synthetic) delivery systems have been developed and improved. Hemagglutinating virus of Japan (HVJ, Sendai virus) envelope vector is a novel and unique system which combined the advantages of viral and non-viral vectors with the following features and advantages: (1) safe and easy as a "non-viral" transfection reagent; (2) delivery of various molecules including plasmid DNA, siRNA, protein, antisense oligonucleotide; (3) wide usability from in vitro to in vivo. In this review, the development, application, and perspectives of the HVJ envelope vector will be discussed.

  13. Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems.

    Science.gov (United States)

    Cheng, Ching-An; Huang, Han-Pang

    2016-12-01

    We study the modeling of Lagrangian systems with multiple degrees of freedom. Based on system dynamics, canonical parametric models require ad hoc derivations and sometimes simplification for a computable solution; on the other hand, due to the lack of prior knowledge in the system's structure, modern nonparametric models in machine learning face the curse of dimensionality, especially in learning large systems. In this paper, we bridge this gap by unifying the theories of Lagrangian systems and vector-valued reproducing kernel Hilbert space. We reformulate Lagrangian systems with kernels that embed the governing Euler-Lagrange equation-the Lagrangian kernels-and show that these kernels span a subspace capturing the Lagrangian's projection as inverse dynamics. By such property, our model uses only inputs and outputs as in machine learning and inherits the structured form as in system dynamics, thereby removing the need for the mundane derivations for new systems as well as the generalization problem in learning from scratches. In effect, it learns the system's Lagrangian, a simpler task than directly learning the dynamics. To demonstrate, we applied the proposed kernel to identify the robot inverse dynamics in simulations and experiments. Our results present a competitive novel approach to identifying Lagrangian systems, despite using only inputs and outputs.

  14. Modeling a ground-coupled heat pump system by a support vector machine

    Energy Technology Data Exchange (ETDEWEB)

    Esen, Hikmet; Esen, Mehmet [Department of Mechanical Education, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey); Inalli, Mustafa [Department of Mechanical Engineering, Faculty of Engineering, Firat University, 23279 Elazig (Turkey); Sengur, Abdulkadir [Department of Electronic and Computer Science, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey)

    2008-08-15

    This paper reports on a modeling study of ground coupled heat pump (GCHP) system performance (COP) by using a support vector machine (SVM) method. A GCHP system is a multi-variable system that is hard to model by conventional methods. As regards the SVM, it has a superior capability for generalization, and this capability is independent of the dimensionality of the input data. In this study, a SVM based method was intended to adopt GCHP system for efficient modeling. The Lin-kernel SVM method was quite efficient in modeling purposes and did not require a pre-knowledge about the system. The performance of the proposed methodology was evaluated by using several statistical validation parameters. It is found that the root-mean squared (RMS) value is 0.002722, the coefficient of multiple determinations (R{sup 2}) value is 0.999999, coefficient of variation (cov) value is 0.077295, and mean error function (MEF) value is 0.507437 for the proposed Lin-kernel SVM method. The optimum parameters of the SVM method were determined by using a greedy search algorithm. This search algorithm was effective for obtaining the optimum parameters. The simulation results show that the SVM is a good method for prediction of the COP of the GCHP system. The computation of SVM model is faster compared with other machine learning techniques (artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS)); because there are fewer free parameters and only support vectors (only a fraction of all data) are used in the generalization process. (author)

  15. Efficient Transient Expression of Recombinant Proteins in Plants by the Novel pEff Vector Based on the Genome of Potato Virus X.

    Science.gov (United States)

    Mardanova, Eugenia S; Blokhina, Elena A; Tsybalova, Liudmila M; Peyret, Hadrien; Lomonossoff, George P; Ravin, Nikolai V

    2017-01-01

    Agroinfiltration of plant leaves with binary vectors carrying a gene of interest within a plant viral vector is a rapid and efficient method for protein production in plants. Previously, we constructed a self-replicating vector, pA7248AMV, based on the genetic elements of potato virus X (PVX), and have shown that this vector can be used for the expression of recombinant proteins in Nicotiana benthamiana. However, this vector is almost 18 kb long and therefore not convenient for genetic manipulation. Furthermore, for efficient expression of the target protein it should be co-agroinfiltrated with an additional binary vector expressing a suppressor of post-transcriptional gene silencing. Here, we improved this expression system by creating the novel pEff vector. Its backbone is about 5 kb shorter than the original vector and it contains an expression cassette for the silencing suppressor, P24, from grapevine leafroll-associated virus-2 alongside PVX genetic elements, thus eliminating the need of co-agroinfiltration. The pEff vector provides green fluorescent protein expression levels of up to 30% of total soluble protein. The novel vector was used for expression of the influenza vaccine candidate, M2eHBc, consisting of an extracellular domain of influenza virus M2 protein (M2e) fused to hepatitis B core antigen. Using the pEff system, M2eHBc was expressed to 5-10% of total soluble protein, several times higher than with original pA7248AMV vector. Plant-produced M2eHBc formed virus-like particles in vivo, as required for its use as a vaccine. The new self-replicating pEff vector could be used for fast and efficient production of various recombinant proteins in plants.

  16. Fault Diagnosis of a Reconfigurable Crawling–Rolling Robot Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Karthikeyan Elangovan

    2017-10-01

    Full Text Available As robots begin to perform jobs autonomously, with minimal or no human intervention, a new challenge arises: robots also need to autonomously detect errors and recover from faults. In this paper, we present a Support Vector Machine (SVM-based fault diagnosis system for a bio-inspired reconfigurable robot named Scorpio. The diagnosis system needs to detect and classify faults while Scorpio uses its crawling and rolling locomotion modes. Specifically, we classify between faulty and non-faulty conditions by analyzing onboard Inertial Measurement Unit (IMU sensor data. The data capture nine different locomotion gaits, which include rolling and crawling modes, at three different speeds. Statistical methods are applied to extract features and to reduce the dimensionality of original IMU sensor data features. These statistical features were given as inputs for training and testing. Additionally, the c-Support Vector Classification (c-SVC and nu-SVC models of SVM, and their fault classification accuracies, were compared. The results show that the proposed SVM approach can be used to autonomously diagnose locomotion gait faults while the reconfigurable robot is in operation.

  17. Arthropod Innate Immune Systems and Vector-Borne Diseases.

    Science.gov (United States)

    Baxter, Richard H G; Contet, Alicia; Krueger, Kathryn

    2017-02-21

    Arthropods, especially ticks and mosquitoes, are the vectors for a number of parasitic and viral human diseases, including malaria, sleeping sickness, Dengue, and Zika, yet arthropods show tremendous individual variation in their capacity to transmit disease. A key factor in this capacity is the group of genetically encoded immune factors that counteract infection by the pathogen. Arthropod-specific pattern recognition receptors and protease cascades detect and respond to infection. Proteins such as antimicrobial peptides, thioester-containing proteins, and transglutaminases effect responses such as lysis, phagocytosis, melanization, and agglutination. Effector responses are initiated by damage signals such as reactive oxygen species signaling from epithelial cells and recognized by cell surface receptors on hemocytes. Antiviral immunity is primarily mediated by siRNA pathways but coupled with interferon-like signaling, antimicrobial peptides, and thioester-containing proteins. Molecular mechanisms of immunity are closely linked to related traits of longevity and fertility, and arthropods have the capacity for innate immunological memory. Advances in understanding vector immunity can be leveraged to develop novel control strategies for reducing the rate of transmission of both ancient and emerging threats to global health.

  18. A Systematic Approach for Solving the Great Circle Track Problems based on Vector Algebra

    Directory of Open Access Journals (Sweden)

    Chen Chih-Li

    2016-04-01

    Full Text Available A systematic approach, based on multiple products of the vector algebra (S-VA, is proposed to derive the spherical triangle formulae for solving the great circle track (GCT problems. Because the mathematical properties of the geometry and algebra are both embedded in the S-VA approach, derivations of the spherical triangle formulae become more understandable and more straightforward as compared with those approaches which use the complex linear combination of a vector basis. In addition, the S-VA approach can handle all given initial conditions for solving the GCT problems simpler, clearer and avoid redundant formulae existing in the conventional approaches. With the technique of transforming the Earth coordinates system of latitudes and longitudes into the Cartesian one and adopting the relative longitude concept, the concise governing equations of the S-VA approach can be easily and directly derived. Owing to the advantage of the S-VA approach, it makes the practical navigator quickly adjust to solve the GCT problems. Based on the S-VA approach, a program namely GCTPro_VA is developed for friendly use of the navigator. Several validation examples are provided to show the S-VA approach is simple and versatile to solve the GCT problems.

  19. Genetic manipulation of specific neural circuits by use of a viral vector system.

    Science.gov (United States)

    Kobayashi, Kenta; Kato, Shigeki; Kobayashi, Kazuto

    2017-01-05

    To understand the mechanisms underlying higher brain functions, we need to analyze the roles of specific neuronal pathways or cell types forming the complex neural networks. In the neuroscience field, the transgenic approach has provided a useful gene engineering tool for experimental studies of neural functions. The conventional transgenic technique requires the appropriate promoter regions that drive a neuronal type-specific gene expression, but the promoter sequences specifically functioning in each neuronal type are limited. Previously, we developed novel types of lentiviral vectors showing high efficiency of retrograde gene transfer in the central nervous system, termed highly efficient retrograde gene transfer (HiRet) vector and neuron-specific retrograde gene transfer (NeuRet) vector. The HiRet and NeuRet vectors enable genetical manipulation of specific neural pathways in diverse model animals in combination with conditional cell targeting, synaptic transmission silencing, and gene expression systems. These newly developed vectors provide powerful experimental strategies to investigate, more precisely, the machineries exerting various neural functions. In this review, we give an outline of the HiRet and NeuRet vectors and describe recent representative applications of these viral vectors for studies on neural circuits.

  20. Towards human behavior recognition based on spatio temporal features and support vector machines

    Science.gov (United States)

    Ghabri, Sawsen; Ouarda, Wael; Alimi, Adel M.

    2017-03-01

    Security and surveillance are vital issues in today's world. The recent acts of terrorism have highlighted the urgent need for efficient surveillance. There is indeed a need for an automated system for video surveillance which can detect identity and activity of person. In this article, we propose a new paradigm to recognize an aggressive human behavior such as boxing action. Our proposed system for human activity detection includes the use of a fusion between Spatio Temporal Interest Point (STIP) and Histogram of Oriented Gradient (HoG) features. The novel feature called Spatio Temporal Histogram Oriented Gradient (STHOG). To evaluate the robustness of our proposed paradigm with a local application of HoG technique on STIP points, we made experiments on KTH human action dataset based on Multi Class Support Vector Machines classification. The proposed scheme outperforms basic descriptors like HoG and STIP to achieve 82.26% us an accuracy value of classification rate.

  1. Blind multiuser detector for chaos-based CDMA using support vector machine.

    Science.gov (United States)

    Kao, Johnny Wei-Hsun; Berber, Stevan Mirko; Kecman, Vojislav

    2010-08-01

    The algorithm and the results of a blind multiuser detector using a machine learning technique called support vector machine (SVM) on a chaos-based code division multiple access system is presented in this paper. Simulation results showed that the performance achieved by using SVM is comparable to existing minimum mean square error (MMSE) detector under both additive white Gaussian noise (AWGN) and Rayleigh fading conditions. However, unlike the MMSE detector, the SVM detector does not require the knowledge of spreading codes of other users in the system or the estimate of the channel noise variance. The optimization of this algorithm is considered in this paper and its complexity is compared with the MMSE detector. This detector is much more suitable to work in the forward link than MMSE. In addition, original theoretical bit-error rate expressions for the SVM detector under both AWGN and Rayleigh fading are derived to verify the simulation results.

  2. Development of novel AAV serotype 6 based vectors with selective tropism for human cancer cells.

    Science.gov (United States)

    Sayroo, R; Nolasco, D; Yin, Z; Colon-Cortes, Y; Pandya, M; Ling, C; Aslanidi, G

    2016-01-01

    Viral vectors-based gene therapy is an attractive alternative to common anti-cancer treatments. In the present studies, AAV serotype 6 vectors were identified to be particularly effective in the transduction of human prostate (PC3), breast (T47D) and liver (Huh7) cancer cells. Next, we developed chimeric AAV vectors with Arg-Gly-Asp (RGD) peptide incorporated into the viral capsid to enable specific targeting of integrin-overexpressing malignant cells. These AAV6-RGD vectors improved transduction efficiency approximately 3-fold compared with wild-type AAV6 vectors by enhancing the viral entry into the cells. We also observed that transduction efficiency significantly improved, up to approximately 5-fold, by the mutagenesis of surface-exposed tyrosine and threonine residues involved in the intracellular trafficking of AAV vectors. Therefore, in our study, the AAV6-Y705-731F+T492V vector was identified as the most efficient. The combination of RGD peptide, tyrosine and threonine mutations on the same AAV6 capsid further increased the transduction efficiency, approximately 8-fold in vitro. In addition, we mutated lysine (K531E) to impair the affinity of AAV6 vectors to heparan sulfate proteoglycan. Finally, we showed a significant increase in both specificity and efficiency of AAV6-RGD-Y705-731F+T492V+K531E vectors in a xenograft animal model in vivo. In summary, the approach described here can lead to the development of AAV vectors with selective tropism to human cancer cells.

  3. Towards artificial intelligence based diesel engine performance control under varying operating conditions using support vector regression

    Directory of Open Access Journals (Sweden)

    Naradasu Kumar Ravi

    2013-01-01

    Full Text Available Diesel engine designers are constantly on the look-out for performance enhancement through efficient control of operating parameters. In this paper, the concept of an intelligent engine control system is proposed that seeks to ensure optimized performance under varying operating conditions. The concept is based on arriving at the optimum engine operating parameters to ensure the desired output in terms of efficiency. In addition, a Support Vector Machines based prediction model has been developed to predict the engine performance under varying operating conditions. Experiments were carried out at varying loads, compression ratios and amounts of exhaust gas recirculation using a variable compression ratio diesel engine for data acquisition. It was observed that the SVM model was able to predict the engine performance accurately.

  4. A new rotavirus VP6-based foreign epitope presenting vector and immunoreactivity of VP4 epitope chimeric proteins.

    Science.gov (United States)

    Teng, Yumei; Zhao, Bingxin; Pan, Xiaoxia; Wen, Yuling; Chen, Yuanding

    2014-04-01

    The VP6, the group antigenic rotavirus (RV), is highly conserved and the most abundant, constituting about 39% of the viral structure proteins by weight. The high degree of identity (>87%-99%) in the primary amino acid sequences suggests VP6-based vaccines could potentially provide heterotypic protection. Although some efforts have been made toward producing recombinant rotavirus VP6 vaccines, the native VP6 is still unsatisfactory as an optimal vaccine. The major neutralizing antigenic epitopes that exist on VP4 or VP7 are not on the native VP6, and as a vector the native VP6 lacks insertion sites that can be used for insertion of foreign epitopes. In this study, a new foreign epitope presenting system using VP6 as a vector (VP6F) was constructed on the outer surface of the vector six sites that could be used for insertion of the foreign epitopes created. Using this system, three VP6-based VP4 epitope chimeric proteins were constructed. Results showed that these chimeric proteins reacted with anti-VP6 and -VP4 antibodies, and elicited antibodies against VP6 and VP4 in guinea pigs. Antibodies against VP6F or antibodies against the chimeric proteins neutralized RV Wa and SA11 infection in vitro. It is optimistic that the limitation for using the native VP6 as a vaccine candidate or vector will be solved with our proposed approach. It is expected that this VP6-based epitope presenting system and the VP6-based VP4 epitope chimeric proteins will be valuable for and contribute to the development of novel RV vaccines and vaccine vectors.

  5. An Adenoviral Vector Based Vaccine for Rhodococcus equi.

    Directory of Open Access Journals (Sweden)

    Carla Giles

    Full Text Available Rhodococcus equi is a respiratory pathogen which primarily infects foals and is endemic on farms around the world with 50% mortality and 80% morbidity in affected foals. Unless detected early and treated appropriately the disease can be fatal. Currently, there is no vaccine available to prevent this disease. For decades researchers have endeavoured to develop an effective vaccine to no avail. In this study a novel human adenoviral vector vaccine for R. equi was developed and tested in the mouse model. This vaccine generated a strong antibody and cytokine response and clearance of R. equi was demonstrated following challenge. These results show that this vaccine could potentially be developed further for use as a vaccine to prevent R. equi disease in foals.

  6. BioBrick™ compatible vector system for protein expression in Rhodobacter sphaeroides.

    Science.gov (United States)

    Tikh, Ilya B; Held, Mark; Schmidt-Dannert, Claudia

    2014-04-01

    We report here the creation of a modular, plasmid-based protein expression system utilizing elements of the native Rhodobacter puf promoter in a BioBrick(TM)-based vector system with DsRed encoding a red fluorescent reporter protein. A suite of truncations of the puf promoter were made to assess the influence of different portions of this promoter on expression of heterologous proteins. The 3' end of puf was found to be particularly important for increasing expression, with transformants accumulating significant quantities of DsRed under both aerobic and anaerobic growth conditions. Expression levels of this reporter protein in Rhodobacter sphaeroides were comparable to those achieved in Escherichia coli using the strong, constitutive P lac promoter, thus demonstrating the robustness of the engineered system. Furthermore, we demonstrate the ability to tune the designed expression system by modulating cellular DsRed levels based upon the promoter segment utilized and oxygenation conditions. Last, we show that the new expression system is able to drive expression of a membrane protein, proteorhodopsin, and that membrane purifications from R. sphaeroides yielded significant quantities of proteorhodopsin. This toolset lays the groundwork for the engineering of multi-step pathways, including recalcitrant membrane proteins, in R. sphaeroides.

  7. Classification of e-government documents based on cooperative expression of word vectors

    Science.gov (United States)

    Fu, Qianqian; Liu, Hao; Wei, Zhiqiang

    2017-03-01

    The effective document classification is a powerful technique to deal with the huge amount of e-government documents automatically instead of accomplishing them manually. The word-to-vector (word2vec) model, which converts semantic word into low-dimensional vectors, could be successfully employed to classify the e-government documents. In this paper, we propose the cooperative expressions of word vector (Co-word-vector), whose multi-granularity of integration explores the possibility of modeling documents in the semantic space. Meanwhile, we also aim to improve the weighted continuous bag of words model based on word2vec model and distributed representation of topic-words based on LDA model. Furthermore, combining the two levels of word representation, performance result shows that our proposed method on the e-government document classification outperform than the traditional method.

  8. Frequency and 2D Angle Estimation Based on a Sparse Uniform Array of Electromagnetic Vector Sensors

    Directory of Open Access Journals (Sweden)

    Kwong Sam

    2006-01-01

    Full Text Available We present an ESPRIT-based algorithm that yields extended-aperture two-dimensional (2D arrival angle and carrier frequency estimates with a sparse uniform array of electromagnetic vector sensors. The ESPRIT-based frequency estimates are first achieved by using the temporal invariance structure out of the two time-delayed sets of data collected from vector sensor array. Each incident source's coarse direction of arrival (DOA estimation is then obtained through the Poynting vector estimates (using a vector cross-product estimator. The frequency and coarse angle estimate results are used jointly to disambiguate the cyclic phase ambiguities in ESPRIT's eigenvalues when the intervector sensor spacing exceeds a half wavelength. Monte Carlo simulation results verified the effectiveness of the proposed method.

  9. Gene delivery systems: Bridging the gap between recombinant viruses and artificial vectors.

    Science.gov (United States)

    Navarro; Oudrhiri; Fabrega; Lehn

    1998-03-02

    Although most research in the field of somatic gene therapy has investigated the use of recombinant viruses for transferring genes into somatic target cells, various methods for nonviral gene delivery have also been proposed. Both types of gene delivery systems have advantages and drawbacks. Schematically, viral vectors are particularly efficient for gene delivery, whereas nonviral systems are free of the difficulties associated with the use of recombinant viruses but need to be further optimized to reach their full potential. In order to bridge the gap between viral vectors and synthetic reagents, we discuss here some specific features of the viral vector systems of today that could advantageously be taken into account for the design of improved nonviral gene delivery systems. Indeed, although nonviral systems differ fundamentally from viral systems, one possible approach towards enhanced artificial reagents aims at developing 'artificial viruses' that mimic the highly efficient processes of viral infection.

  10. Plasmid Vectors for Xylella fastidiosa Utilizing a Toxin-Antitoxin System for Stability in the Absence of Antibiotic Selection.

    Science.gov (United States)

    Burbank, Lindsey P; Stenger, Drake C

    2016-08-01

    The phytopathogen Xylella fastidiosa causes disease in a variety of important crop and landscape plants. Functional genetic studies have led to a broader understanding of virulence mechanisms used by this pathogen in the grapevine host. Plasmid shuttle vectors are important tools in studies of bacterial genetics but there are only a limited number of plasmid vectors available that replicate in X. fastidiosa, and even fewer that are retained without antibiotic selection. Two plasmids are described here that show stable replication in X. fastidiosa and are effective for gene complementation both in vitro and in planta. Plasmid maintenance is facilitated by incorporation of the PemI/PemK plasmid addiction system, consisting of PemK, an endoribonuclease toxin, and its cognate antitoxin, PemI. Vector pXf20pemIK utilizes a native X. fastidiosa replication origin as well as a high-copy-number pUC origin for propagation in Escherichia coli cloning strains. Broad-host-range vector pBBR5pemIK is a medium- to low-copy-number plasmid based on the pBBR1 backbone. Both plasmids are maintained for extended periods of time in the absence of antibiotic selection, as well as up to 14 weeks in grapevine, without affecting bacterial fitness. These plasmids present an alternative to traditional complementation and expression vectors which rely on antibiotic selection for plasmid retention.

  11. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Mohammed Hasan Abdulameer

    2014-01-01

    Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  12. Support vector machine based on adaptive acceleration particle swarm optimization.

    Science.gov (United States)

    Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  13. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

    Science.gov (United States)

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-07-07

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

  14. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

    Science.gov (United States)

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-01-01

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

  15. Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

    Science.gov (United States)

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2014-05-01

    Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

  16. Nondestructive detection of pork comprehensive quality based on spectroscopy and support vector machine

    Science.gov (United States)

    Liu, Yuanyuan; Peng, Yankun; Zhang, Leilei; Dhakal, Sagar; Wang, Caiping

    2014-05-01

    Pork is one of the highly consumed meat item in the world. With growing improvement of living standard, concerned stakeholders including consumers and regulatory body pay more attention to comprehensive quality of fresh pork. Different analytical-laboratory based technologies exist to determine quality attributes of pork. However, none of the technologies are able to meet industrial desire of rapid and non-destructive technological development. Current study used optical instrument as a rapid and non-destructive tool to classify 24 h-aged pork longissimus dorsi samples into three kinds of meat (PSE, Normal and DFD), on the basis of color L* and pH24. Total of 66 samples were used in the experiment. Optical system based on Vis/NIR spectral acquisition system (300-1100 nm) was self- developed in laboratory to acquire spectral signal of pork samples. Median smoothing filter (M-filter) and multiplication scatter correction (MSC) was used to remove spectral noise and signal drift. Support vector machine (SVM) prediction model was developed to classify the samples based on their comprehensive qualities. The results showed that the classification model is highly correlated with the actual quality parameters with classification accuracy more than 85%. The system developed in this study being simple and easy to use, results being promising, the system can be used in meat processing industry for real time, non-destructive and rapid detection of pork qualities in future.

  17. Predicting the host of influenza viruses based on the word vector

    Directory of Open Access Journals (Sweden)

    Beibei Xu

    2017-07-01

    Full Text Available Newly emerging influenza viruses continue to threaten public health. A rapid determination of the host range of newly discovered influenza viruses would assist in early assessment of their risk. Here, we attempted to predict the host of influenza viruses using the Support Vector Machine (SVM classifier based on the word vector, a new representation and feature extraction method for biological sequences. The results show that the length of the word within the word vector, the sequence type (DNA or protein and the species from which the sequences were derived for generating the word vector all influence the performance of models in predicting the host of influenza viruses. In nearly all cases, the models built on the surface proteins hemagglutinin (HA and neuraminidase (NA (or their genes produced better results than internal influenza proteins (or their genes. The best performance was achieved when the model was built on the HA gene based on word vectors (words of three-letters long generated from DNA sequences of the influenza virus. This results in accuracies of 99.7% for avian, 96.9% for human and 90.6% for swine influenza viruses. Compared to the method of sequence homology best-hit searches using the Basic Local Alignment Search Tool (BLAST, the word vector-based models still need further improvements in predicting the host of influenza A viruses.

  18. Cellular automata for simulating land use changes based on support vector machines

    Science.gov (United States)

    Yang, Qingsheng; Li, Xia; Shi, Xun

    2008-06-01

    Cellular automata (CA) have been increasingly used to simulate urban sprawl and land use dynamics. A major issue in CA is defining appropriate transition rules based on training data. Linear boundaries have been widely used to define the rules. However, urban land use dynamics and many other geographical phenomena are highly complex and require nonlinear boundaries for the rules. In this study, we tested the support vector machines (SVM) as a method for constructing nonlinear transition rules for CA. SVM is good at dealing with nonlinear complex relationships. Its basic idea is to project input vectors to a higher dimensional Hilbert feature space, in which an optimal classifying hyperplane can be constructed through structural risk minimization and margin maximization. The optimal hyperplane is unique and its optimality is global. The proposed SVM-CA model was implemented using Visual Basic, ArcObjects®, and OSU-SVM. A case study simulating the urban development in the Shenzhen City, China demonstrates that the proposed model can achieve high accuracy and overcome some limitations of existing CA models in simulating complex urban systems.

  19. A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

    Science.gov (United States)

    Khawaja, Taimoor Saleem

    A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior

  20. Segmentation Based Video Steganalysis to Detect Motion Vector Modification

    Directory of Open Access Journals (Sweden)

    Peipei Wang

    2017-01-01

    Full Text Available This paper presents a steganalytic approach against video steganography which modifies motion vector (MV in content adaptive manner. Current video steganalytic schemes extract features from fixed-length frames of the whole video and do not take advantage of the content diversity. Consequently, the effectiveness of the steganalytic feature is influenced by video content and the problem of cover source mismatch also affects the steganalytic performance. The goal of this paper is to propose a steganalytic method which can suppress the differences of statistical characteristics caused by video content. The given video is segmented to subsequences according to block’s motion in every frame. The steganalytic features extracted from each category of subsequences with close motion intensity are used to build one classifier. The final steganalytic result can be obtained by fusing the results of weighted classifiers. The experimental results have demonstrated that our method can effectively improve the performance of video steganalysis, especially for videos of low bitrate and low embedding ratio.

  1. Direct Time-Domain-Based Approach for Study of Space-Vector Pulsewidth Modulation

    DEFF Research Database (Denmark)

    Oleschuk, V.; Blaabjerg, Frede; Stankovic, A.M.

    2005-01-01

    Direct time-do main-based approach, which is characterized by the simplicity and clarity, is proposed for the study and design of space-vector based methods of pulsewidth modulation (PWM) for standard voltage source inverters for adjustable speed motor drives. This approach is based on the detailed...

  2. HVJ-envelope vector for gene transfer into central nervous system.

    Science.gov (United States)

    Shimamura, Munehisa; Morishita, Ryuichi; Endoh, Masayuki; Oshima, Kazuo; Aoki, Motokuni; Waguri, Satoshi; Uchiyama, Yasuo; Kaneda, Yasufumi

    2003-01-10

    To overcome some problems of virus vectors, we developed a novel non-viral vector system, the HVJ-envelope vector (HVJ-E). In this study, we investigated the feasibility of gene transfer into the CNS using the HVJ-E both in vitro and in vivo. Using the Venus reporter gene, fluorescence could be detected in cultured rat cerebral cortex neurons and glial cells. In vivo, the reporter gene (Venus) was successfully transfected into the rat brain by direct injection into the thalamus, intraventricular injection, or intrathecal injection, without inducing immunological change. When the vector was injected after transient occlusion of the middle cerebral artery, fluorescence due to EGFP gene or luciferase activity could be detected only in the injured hemisphere. Finally, luciferase activity was markedly enhanced by the addition of 50 U/ml heparin (PHVJ-E for gene transfer into the CNS will be useful for research and clinical gene therapy.

  3. Promoters and serotypes: targeting of adeno-associated virus vectors for gene transfer in the rat central nervous system in vitro and in vivo.

    Science.gov (United States)

    Shevtsova, Z; Malik, J M I; Michel, U; Bähr, M; Kügler, S

    2005-01-01

    The brain parenchyma consists of several different cell types, such as neurones, astrocytes, microglia, oligodendroglia and epithelial cells, which are morphologically and functionally intermingled in highly complex three-dimensional structures. These different cell types are also present in cultures of brain cells prepared to serve as model systems of CNS physiology. Gene transfer, either in a therapeutic attempt or in basic research, is a fascinating and promising tool to manipulate both the complex physiology of the brain and that of isolated neuronal cells. Viral vectors based on the parvovirus, adeno-associated virus (AAV), have emerged as powerful transgene delivery vehicles. Here we describe highly efficient targeting of AAV vectors to either neurones or astrocytes in cultured primary brain cell cultures. We also show that transcriptional targeting can be achieved by the use of small promoters, significantly boosting the transgene capacity of the recombinant viral genome. However, we also demonstrate that successful targeting of a vector in vitro does not necessarily imply that the same targeting works in the adult brain. Cross-packaging the AAV-2 genome in capsids of other serotypes adds additional benefits to this vector system. In the brain, the serotype-5 capsid allows for drastically increased spread of the recombinant vector as compared to the serotype-2 capsid. Finally, we emphasize the optimal targeting approach, in which the natural tropism of a vector for a specific cell type is employed. Taken together, these data demonstrate the flexibility which AAV-based vector systems offer in physiological research.

  4. Casing Vibration Fault Diagnosis Based on Variational Mode Decomposition, Local Linear Embedding, and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Yizhou Yang

    2017-01-01

    Full Text Available To diagnose mechanical faults of rotor-bearing-casing system by analyzing its casing vibration signal, this paper proposes a training procedure of a fault classifier based on variational mode decomposition (VMD, local linear embedding (LLE, and support vector machine (SVM. VMD is used first to decompose the casing signal into several modes, which are subsignals usually modulated by fault frequencies. Vibrational features are extracted from both VMD subsignals and the original one. LLE is employed here to reduce the dimensionality of these extracted features and make the samples more separable. Then low-dimensional data sets are used to train the multiclass SVM whose accuracy is tested by classifying the test samples. When the parameters of LLE and SVM are well optimized, this proposed method performs well on experimental data, showing its capacity of diagnosing casing vibration faults.

  5. A Relevance Vector Machine-Based Approach with Application to Oil Sand Pump Prognostics

    Directory of Open Access Journals (Sweden)

    Peter W. Tse

    2013-09-01

    Full Text Available Oil sand pumps are widely used in the mining industry for the delivery of mixtures of abrasive solids and liquids. Because they operate under highly adverse conditions, these pumps usually experience significant wear. Consequently, equipment owners are quite often forced to invest substantially in system maintenance to avoid unscheduled downtime. In this study, an approach combining relevance vector machines (RVMs with a sum of two exponential functions was developed to predict the remaining useful life (RUL of field pump impellers. To handle field vibration data, a novel feature extracting process was proposed to arrive at a feature varying with the development of damage in the pump impellers. A case study involving two field datasets demonstrated the effectiveness of the developed method. Compared with standalone exponential fitting, the proposed RVM-based model was much better able to predict the remaining useful life of pump impellers.

  6. A relevance vector machine-based approach with application to oil sand pump prognostics.

    Science.gov (United States)

    Hu, Jinfei; Tse, Peter W

    2013-09-18

    Oil sand pumps are widely used in the mining industry for the delivery of mixtures of abrasive solids and liquids. Because they operate under highly adverse conditions, these pumps usually experience significant wear. Consequently, equipment owners are quite often forced to invest substantially in system maintenance to avoid unscheduled downtime. In this study, an approach combining relevance vector machines (RVMs) with a sum of two exponential functions was developed to predict the remaining useful life (RUL) of field pump impellers. To handle field vibration data, a novel feature extracting process was proposed to arrive at a feature varying with the development of damage in the pump impellers. A case study involving two field datasets demonstrated the effectiveness of the developed method. Compared with standalone exponential fitting, the proposed RVM-based model was much better able to predict the remaining useful life of pump impellers.

  7. An introduction to vectors, vector operators and vector analysis

    CERN Document Server

    Joag, Pramod S

    2016-01-01

    Ideal for undergraduate and graduate students of science and engineering, this book covers fundamental concepts of vectors and their applications in a single volume. The first unit deals with basic formulation, both conceptual and theoretical. It discusses applications of algebraic operations, Levi-Civita notation, and curvilinear coordinate systems like spherical polar and parabolic systems and structures, and analytical geometry of curves and surfaces. The second unit delves into the algebra of operators and their types and also explains the equivalence between the algebra of vector operators and the algebra of matrices. Formulation of eigen vectors and eigen values of a linear vector operator are elaborated using vector algebra. The third unit deals with vector analysis, discussing vector valued functions of a scalar variable and functions of vector argument (both scalar valued and vector valued), thus covering both the scalar vector fields and vector integration.

  8. The Evaluation of the Vector System in Removal of Carious Tissue

    Directory of Open Access Journals (Sweden)

    Mine Yildirim

    2010-01-01

    Full Text Available The aim of this study was to evaluate the Vector system in comparison to the conventional technique in cavity preparation. Four extracted primary teeth with no restorations and similar fissure carious lesions and four permanent teeth extracted for orthodontic reasons were used. Class I preparations were made provided that the caries depth remained within the dentin limits. Two teeth were treated with an aerator, the other two had carious tissue removed with the Vector system. Prepared cavities were evaluated with scanning electron microscopy for the surface roughness of the dentine and enamel and for the carious tissue removal efficiency. This pilot study determined that it is possible to remove carious tissue and perform cavity preparation with the Vector system. According to this preliminary evaluation of surface quality, a cavity prepared with the Vector treatment system, allows for a slicker floor, and a more regular enamel-dentine line than that prepared with an aerator. However, the Vector system requires a longer treatment time which we believe may be a negative point, especially for young patients.

  9. Role of T cell competition in the induction of cytotoxic T lymphocyte activity during viral vector-based immunization regimens.

    NARCIS (Netherlands)

    Lambeck, A.J.A.; Nijman, H.W.; Hoogeboom, B.N.; Regts, J.; Mare, A. de; Wilschut, J.; Daemen, T.

    2010-01-01

    T cell competition between antigen- and vector-specific T cells may determine the outcome of viral vector-based immunization regimens, as we previously proposed. Here, we unravelled the interplay between antigen- and vector-specific immunity, using recombinant Semliki Forest virus (rSFV). Priming of

  10. Support vector machine based fault detection approach for RFT-30 cyclotron

    Energy Technology Data Exchange (ETDEWEB)

    Kong, Young Bae, E-mail: ybkong@kaeri.re.kr; Lee, Eun Je; Hur, Min Goo; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-10-21

    An RFT-30 is a 30 MeV cyclotron used for radioisotope applications and radiopharmaceutical researches. The RFT-30 cyclotron is highly complex and includes many signals for control and monitoring of the system. It is quite difficult to detect and monitor the system failure in real time. Moreover, continuous monitoring of the system is hard and time-consuming work for human operators. In this paper, we propose a support vector machine (SVM) based fault detection approach for the RFT-30 cyclotron. The proposed approach performs SVM learning with training samples to construct the classification model. To compensate the system complexity due to the large-scale accelerator, we utilize the principal component analysis (PCA) for transformation of the original data. After training procedure, the proposed approach detects the system faults in real time. We analyzed the performance of the proposed approach utilizing the experimental data of the RFT-30 cyclotron. The performance results show that the proposed SVM approach can provide an efficient way to control the cyclotron system.

  11. Canonicalization of Feature Parameters for Robust Speech Recognition Based on Distinctive Phonetic Feature (DPF) Vectors

    Science.gov (United States)

    Huda, Mohammad Nurul; Ghulam, Muhammad; Fukuda, Takashi; Katsurada, Kouichi; Nitta, Tsuneo

    This paper describes a robust automatic speech recognition (ASR) system with less computation. Acoustic models of a hidden Markov model (HMM)-based classifier include various types of hidden factors such as speaker-specific characteristics, coarticulation, and an acoustic environment, etc. If there exists a canonicalization process that can recover the degraded margin of acoustic likelihoods between correct phonemes and other ones caused by hidden factors, the robustness of ASR systems can be improved. In this paper, we introduce a canonicalization method that is composed of multiple distinctive phonetic feature (DPF) extractors corresponding to each hidden factor canonicalization, and a DPF selector which selects an optimum DPF vector as an input of the HMM-based classifier. The proposed method resolves gender factors and speaker variability, and eliminates noise factors by applying the canonicalzation based on the DPF extractors and two-stage Wiener filtering. In the experiment on AURORA-2J, the proposed method provides higher word accuracy under clean training and significant improvement of word accuracy in low signal-to-noise ratio (SNR) under multi-condition training compared to a standard ASR system with mel frequency ceptral coeffient (MFCC) parameters. Moreover, the proposed method requires a reduced, two-fifth, Gaussian mixture components and less memory to achieve accurate ASR.

  12. Rigid Body Time Integration by Convected Base Vectors with Implicit Constraints

    DEFF Research Database (Denmark)

    Krenk, Steen; Nielsen, Martin Bjerre

    2013-01-01

    A conservative time integration algorithm based on a convected set of orthonormal base vectors is presented. The equations of motion are derived from an extended Hamiltonian formulation, combining the components of the three base vectors with a set of orthonormality constraints. The particular form...... of the kinetic energy used in the present formulation is deliberately chosen to correspond to a rigid body rotation, and the orthonormality constraints are introduced via the equivalent Green strain components of the base vectors. The particular form of the extended inertia tensor used here implies a set....... The differential equations of motion are recast into discrete form using a suitable combination of mean values and increments, which is identified by considering a finite increment of the Hamiltonian. Examples illustrate the accuracy and conservation properties of the algorithm....

  13. Multiplex CRISPR/Cas9-based genome engineering from a single lentiviral vector.

    Science.gov (United States)

    Kabadi, Ami M; Ousterout, David G; Hilton, Isaac B; Gersbach, Charles A

    2014-10-29

    Engineered DNA-binding proteins that manipulate the human genome and transcriptome have enabled rapid advances in biomedical research. In particular, the RNA-guided CRISPR/Cas9 system has recently been engineered to create site-specific double-strand breaks for genome editing or to direct targeted transcriptional regulation. A unique capability of the CRISPR/Cas9 system is multiplex genome engineering by delivering a single Cas9 enzyme and two or more single guide RNAs (sgRNAs) targeted to distinct genomic sites. This approach can be used to simultaneously create multiple DNA breaks or to target multiple transcriptional activators to a single promoter for synergistic enhancement of gene induction. To address the need for uniform and sustained delivery of multiplex CRISPR/Cas9-based genome engineering tools, we developed a single lentiviral system to express a Cas9 variant, a reporter gene and up to four sgRNAs from independent RNA polymerase III promoters that are incorporated into the vector by a convenient Golden Gate cloning method. Each sgRNA is efficiently expressed and can mediate multiplex gene editing and sustained transcriptional activation in immortalized and primary human cells. This delivery system will be significant to enabling the potential of CRISPR/Cas9-based multiplex genome engineering in diverse cell types. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Speed Sensorless Direct Torque Control of a PMSM Drive using Space Vector Modulation Based MRAS and Stator Resistance Estimator

    OpenAIRE

    A. Ameur; B. Mokhtari; N. Essounbouli; L. Mokrani

    2012-01-01

    This paper presents a speed sensorless direct torque control scheme using space vector modulation (DTC-SVM) for permanent magnet synchronous motor (PMSM) drive based a Model Reference Adaptive System (MRAS) algorithm and stator resistance estimator. The MRAS is utilized to estimate speed and stator resistance and compensate the effects of parameter variation on stator resistance, which makes flux and torque estimation more accurate and insensitive to parameter variation. ...

  15. Application of damage locating vectors approach on monitoring shock isolation system

    Directory of Open Access Journals (Sweden)

    Le Quang Tuyen

    2016-01-01

    Full Text Available Structural damage detection based on the changes of dynamic properties is a major topic for structural health monitoring. In this paper, efforts are made to extend the flexibility-based damage localization methods, especially the damage locating vectors (DLVs method, to the case of earthquake vibration, where the finite element model and mass matrices are not available. First, a new method using continuous Cauchy wavelet transform (CCWT and ARX (autoregressive with exogenous input model is applied to identify the modal parameters of a five-storey steel frame with seismic base isolation system LRB from its simulated acceleration responses under 10% and 100% of Chi-Chi Earthquake excitation (Taiwan, 1999. The DLVs, which determined from the change of flexibility matrix between two cases, are then used to monitor the shock isolation device in the structure through a weighted relative displacement index (WRDI. The proposed scheme is also proved to be superior to mode shape based methods (MAC, COMAC in monitoring shock isolation system.

  16. Strategic vectors of transformational shifts in the national tourism system of Ukraine

    Directory of Open Access Journals (Sweden)

    Alla OKHRIMENKO

    2017-10-01

    Full Text Available The article determines transformational factors, which influence a national tourism system (NTS of Ukraine and proposes strategical vectors of its development. Research of the NTS as an economic system is a pre-condition for formation of strategic vectors of development. Transformational driving forces principally change scales, components, and proportions between external and internal factors of development of the NTS. Correspondingly, the mentioned processes objectively encourage modernization of the national tourism system and application of innovative managerial methods. The following Strategical vectors of transformational shifts in the NTS were grounded: 1 Safety of tourists and investors; 2 The normative and legislative framework of the NTS development; 3 Development of infrastructure of the NTS component; 4 Human resources development; 5 A marketing policy of the NTS promotion; 6 Ecological and cultural policies. Their implementation will improve efficiency and competitiveness of the NTS and the national economy.

  17. Fusion of Deep Features and Weighted VLAD Vectors based on Multiple Features for Image Retrieval

    Directory of Open Access Journals (Sweden)

    Wang Yanhong.

    2017-01-01

    Full Text Available In traditional vector of locally aggregated descriptors (VLAD method, the final VLAD vector is reshaped by summing up the residuals between each descriptor and its corresponding visual word. The norm of the residuals varies significantly, and it can make “visual burst”. This is caused by a fact that the contribution of each descriptor to VLAD vector is not the same. To address this problem, we add a different weight to each residual such that the contribution of each descriptor to the VLAD vector becomes even to a certain degree. Also, traditional VLAD method only uses the local gradient features of images. Thus it has a low discrimination. In this paper, local color features are extracted and used to the VLAD method. Moreover, we fuse deep features and the multiple VLAD vectors based on local gradient and color information. Also, in order to reduce running time and improve retrieval accuracy, PCA and whitening operations are used for VLAD vectors. Our proposed method is evaluated on three benchmark datasets, i.e., Holidays, Ukbench and Oxford5k. Experimental results show that our proposed method achieves good performance.

  18. Gene Therapy Vectors with Enhanced Transfection Based on Hydrogels Modified with Affinity Peptides

    Science.gov (United States)

    Shepard, Jaclyn A.; Wesson, Paul J.; Wang, Christine E.; Stevans, Alyson C.; Holland, Samantha J.; Shikanov, Ariella; Grzybowski, Bartosz A.; Shea, Lonnie D.

    2011-01-01

    Regenerative strategies for damaged tissue aim to present biochemical cues that recruit and direct progenitor cell migration and differentiation. Hydrogels capable of localized gene delivery are being developed to provide a support for tissue growth, and as a versatile method to induce the expression of inductive proteins; however, the duration, level, and localization of expression isoften insufficient for regeneration. We thus investigated the modification of hydrogels with affinity peptides to enhance vector retention and increase transfection within the matrix. PEG hydrogels were modified with lysine-based repeats (K4, K8), which retained approximately 25% more vector than control peptides. Transfection increased 5- to 15-fold with K8 and K4 respectively, over the RDG control peptide. K8- and K4-modified hydrogels bound similar quantities of vector, yet the vector dissociation rate was reduced for K8, suggesting excessive binding that limited transfection. These hydrogels were subsequently applied to an in vitro co-culture model to induce NGF expression and promote neurite outgrowth. K4-modified hydrogels promoted maximal neurite outgrowth, likely due to retention of both the vector and the NGF. Thus, hydrogels modified with affinity peptides enhanced vector retention and increased gene delivery, and these hydrogels may provide a versatile scaffold for numerous regenerative medicine applications. PMID:21514659

  19. Cluster-Based Vector-Attribute Filtering for CT and MRI Enhancement

    NARCIS (Netherlands)

    Kiwanuka, Fred N.; Wilkinson, Michael H.F.

    2012-01-01

    Morphological attribute filters modify images based on properties or attributes of connected components. Usually, attribute filtering is based on a scalar property which has relatively little discriminating power. Vector-attribute filtering allow better description of characteristic features for 2D

  20. Recombinant adeno-associated virus type 2, 4, and 5 vectors: Transduction of variant cell types and regions in the mammalian central nervous system

    OpenAIRE

    Davidson, Beverly L.; Stein, Colleen S.; Heth, Jason A.; Martins, Inês; Kotin, Robert M; Derksen, Todd A.; Zabner, Joseph; Ghodsi, Abdi; Chiorini, John A.

    2000-01-01

    Recombinant adeno-associated virus vectors based on serotype 2 (rAAV2) can direct transgene expression in the central nervous system (CNS), but it is not known how other rAAV serotypes perform as CNS gene transfer vectors. Serotypes 4 and 5 are distinct from rAAV2 and from each other in their capsid regions, suggesting that they may direct binding and entry into different cell types. In this study, we examined the tropisms and transduction efficiencies of β-galactosidase-encoding vectors made...

  1. Identification of unique reciprocal and non reciprocal cross packaging relationships between HIV-1, HIV-2 and SIV reveals an efficient SIV/HIV-2 lentiviral vector system with highly favourable features for in vivo testing and clinical usage

    Directory of Open Access Journals (Sweden)

    Caldwell Maeve

    2005-09-01

    Full Text Available Abstract Background Lentiviral vectors have shown immense promise as vehicles for gene delivery to non-dividing cells particularly to cells of the central nervous system (CNS. Improvements in the biosafety of viral vectors are paramount as lentiviral vectors move into human clinical trials. This study investigates the packaging relationship between gene transfer (vector and Gag-Pol expression constructs of HIV-1, HIV-2 and SIV. Cross-packaged vectors expressing GFP were assessed for RNA packaging, viral vector titre and their ability to transduce rat primary glial cell cultures and human neural stem cells. Results HIV-1 Gag-Pol demonstrated the ability to cross package both HIV-2 and SIV gene transfer vectors. However both HIV-2 and SIV Gag-Pol showed a reduced ability to package HIV-1 vector RNA with no significant gene transfer to target cells. An unexpected packaging relationship was found to exist between HIV-2 and SIV with SIV Gag-Pol able to package HIV-2 vector RNA and transduce dividing SV2T cells and CNS cell cultures with an efficiency equivalent to the homologous HIV-1 vector however HIV-2 was unable to deliver SIV based vectors. Conclusion This new non-reciprocal cross packaging relationship between SIV and HIV-2 provides a novel way of significantly increasing bio-safety with a reduced sequence homology between the HIV-2 gene transfer vector and the SIV Gag-Pol construct thus ensuring that vector RNA packaging is unidirectional.

  2. An Enhanced MEMS Error Modeling Approach Based on Nu-Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Deepak Bhatt

    2012-07-01

    Full Text Available Micro Electro Mechanical System (MEMS-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design of low-cost navigation systems. These sensors exhibit significant errors like biases, drift, noises; which are negligible for higher grade units. Different conventional techniques utilizing the Gauss Markov model and neural network method have been previously utilized to model the errors. However, Gauss Markov model works unsatisfactorily in the case of MEMS units due to the presence of high inherent sensor errors. On the other hand, modeling the random drift utilizing Neural Network (NN is time consuming, thereby affecting its real-time implementation. We overcome these existing drawbacks by developing an enhanced Support Vector Machine (SVM based error model. Unlike NN, SVMs do not suffer from local minimisation or over-fitting problems and delivers a reliable global solution. Experimental results proved that the proposed SVM approach reduced the noise standard deviation by 10–35% for gyroscopes and 61–76% for accelerometers. Further, positional error drifts under static conditions improved by 41% and 80% in comparison to NN and GM approaches.

  3. An enhanced MEMS error modeling approach based on Nu-Support Vector Regression.

    Science.gov (United States)

    Bhatt, Deepak; Aggarwal, Priyanka; Bhattacharya, Prabir; Devabhaktuni, Vijay

    2012-01-01

    Micro Electro Mechanical System (MEMS)-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design of low-cost navigation systems. These sensors exhibit significant errors like biases, drift, noises; which are negligible for higher grade units. Different conventional techniques utilizing the Gauss Markov model and neural network method have been previously utilized to model the errors. However, Gauss Markov model works unsatisfactorily in the case of MEMS units due to the presence of high inherent sensor errors. On the other hand, modeling the random drift utilizing Neural Network (NN) is time consuming, thereby affecting its real-time implementation. We overcome these existing drawbacks by developing an enhanced Support Vector Machine (SVM) based error model. Unlike NN, SVMs do not suffer from local minimisation or over-fitting problems and delivers a reliable global solution. Experimental results proved that the proposed SVM approach reduced the noise standard deviation by 10-35% for gyroscopes and 61-76% for accelerometers. Further, positional error drifts under static conditions improved by 41% and 80% in comparison to NN and GM approaches.

  4. Rule-based fuzzy vector median filters for 3D phase contrast MRI segmentation

    Science.gov (United States)

    Sundareswaran, Kartik S.; Frakes, David H.; Yoganathan, Ajit P.

    2008-02-01

    Recent technological advances have contributed to the advent of phase contrast magnetic resonance imaging (PCMRI) as standard practice in clinical environments. In particular, decreased scan times have made using the modality more feasible. PCMRI is now a common tool for flow quantification, and for more complex vector field analyses that target the early detection of problematic flow conditions. Segmentation is one component of this type of application that can impact the accuracy of the final product dramatically. Vascular segmentation, in general, is a long-standing problem that has received significant attention. Segmentation in the context of PCMRI data, however, has been explored less and can benefit from object-based image processing techniques that incorporate fluids specific information. Here we present a fuzzy rule-based adaptive vector median filtering (FAVMF) algorithm that in combination with active contour modeling facilitates high-quality PCMRI segmentation while mitigating the effects of noise. The FAVMF technique was tested on 111 synthetically generated PC MRI slices and on 15 patients with congenital heart disease. The results were compared to other multi-dimensional filters namely the adaptive vector median filter, the adaptive vector directional filter, and the scalar low pass filter commonly used in PC MRI applications. FAVMF significantly outperformed the standard filtering methods (p < 0.0001). Two conclusions can be drawn from these results: a) Filtering should be performed after vessel segmentation of PC MRI; b) Vector based filtering methods should be used instead of scalar techniques.

  5. Developmental Testing of Electric Thrust Vector Control Systems for Manned Launch Vehicle Applications

    Science.gov (United States)

    Bates, Lisa B.; Young, David T.

    2012-01-01

    This paper describes recent developmental testing to verify the integration of a developmental electromechanical actuator (EMA) with high rate lithium ion batteries and a cross platform extensible controller. Testing was performed at the Thrust Vector Control Research, Development and Qualification Laboratory at the NASA George C. Marshall Space Flight Center. Electric Thrust Vector Control (ETVC) systems like the EMA may significantly reduce recurring launch costs and complexity compared to heritage systems. Electric actuator mechanisms and control requirements across dissimilar platforms are also discussed with a focus on the similarities leveraged and differences overcome by the cross platform extensible common controller architecture.

  6. Track Circuit Fault Diagnosis Method based on Least Squares Support Vector

    Science.gov (United States)

    Cao, Yan; Sun, Fengru

    2018-01-01

    In order to improve the troubleshooting efficiency and accuracy of the track circuit, track circuit fault diagnosis method was researched. Firstly, the least squares support vector machine was applied to design the multi-fault classifier of the track circuit, and then the measured track data as training samples was used to verify the feasibility of the methods. Finally, the results based on BP neural network fault diagnosis methods and the methods used in this paper were compared. Results shows that the track fault classifier based on least squares support vector machine can effectively achieve the five track circuit fault diagnosis with less computing time.

  7. Genetically modifying the insect gut microbiota to control Chagas disease vectors through systemic RNAi.

    Science.gov (United States)

    Taracena, Mabel L; Oliveira, Pedro L; Almendares, Olivia; Umaña, Claudia; Lowenberger, Carl; Dotson, Ellen M; Paiva-Silva, Gabriela O; Pennington, Pamela M

    2015-02-01

    Technologies based on RNA interference may be used for insect control. Sustainable strategies are needed to control vectors of Chagas disease such as Rhodnius prolixus. The insect microbiota can be modified to deliver molecules to the gut. Here, Escherichia coli HT115(DE3) expressing dsRNA for the Rhodnius heme-binding protein (RHBP) and for catalase (CAT) were fed to nymphs and adult triatomine stages. RHBP is an egg protein and CAT is an antioxidant enzyme expressed in all tissues by all developmental stages. The RNA interference effect was systemic and temporal. Concentrations of E. coli HT115(DE3) above 3.35 × 10(7) CFU/mL produced a significant RHBP and CAT gene knockdown in nymphs and adults. RHBP expression in the fat body was reduced by 99% three days after feeding, returning to normal levels 10 days after feeding. CAT expression was reduced by 99% and 96% in the ovary and the posterior midgut, respectively, five days after ingestion. Mortality rates increased by 24-30% in first instars fed RHBP and CAT bacteria. Molting rates were reduced by 100% in first instars and 80% in third instars fed bacteria producing RHBP or CAT dsRNA. Oviposition was reduced by 43% (RHBP) and 84% (CAT). Embryogenesis was arrested in 16% (RHBP) and 20% (CAT) of laid eggs. Feeding females 105 CFU/mL of the natural symbiont, Rhodococcus rhodnii, transformed to express RHBP-specific hairpin RNA reduced RHBP expression by 89% and reduced oviposition. Modifying the insect microbiota to induce systemic RNAi in R. prolixus may result in a paratransgenic strategy for sustainable vector control.

  8. Genetically modifying the insect gut microbiota to control Chagas disease vectors through systemic RNAi.

    Directory of Open Access Journals (Sweden)

    Mabel L Taracena

    2015-02-01

    Full Text Available Technologies based on RNA interference may be used for insect control. Sustainable strategies are needed to control vectors of Chagas disease such as Rhodnius prolixus. The insect microbiota can be modified to deliver molecules to the gut. Here, Escherichia coli HT115(DE3 expressing dsRNA for the Rhodnius heme-binding protein (RHBP and for catalase (CAT were fed to nymphs and adult triatomine stages. RHBP is an egg protein and CAT is an antioxidant enzyme expressed in all tissues by all developmental stages. The RNA interference effect was systemic and temporal. Concentrations of E. coli HT115(DE3 above 3.35 × 10(7 CFU/mL produced a significant RHBP and CAT gene knockdown in nymphs and adults. RHBP expression in the fat body was reduced by 99% three days after feeding, returning to normal levels 10 days after feeding. CAT expression was reduced by 99% and 96% in the ovary and the posterior midgut, respectively, five days after ingestion. Mortality rates increased by 24-30% in first instars fed RHBP and CAT bacteria. Molting rates were reduced by 100% in first instars and 80% in third instars fed bacteria producing RHBP or CAT dsRNA. Oviposition was reduced by 43% (RHBP and 84% (CAT. Embryogenesis was arrested in 16% (RHBP and 20% (CAT of laid eggs. Feeding females 105 CFU/mL of the natural symbiont, Rhodococcus rhodnii, transformed to express RHBP-specific hairpin RNA reduced RHBP expression by 89% and reduced oviposition. Modifying the insect microbiota to induce systemic RNAi in R. prolixus may result in a paratransgenic strategy for sustainable vector control.

  9. Object Recognition System-on-Chip Using the Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Houzet Dominique

    2005-01-01

    Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

  10. Lentiviral vectors encoding short hairpin RNAs efficiently transduce and knockdown LINGO-1 but induce an interferon response and cytotoxicity in central nervous system neurones.

    Science.gov (United States)

    Hutson, Thomas H; Foster, Edmund; Dawes, John M; Hindges, Robert; Yáñez-Muñoz, Rafael J; Moon, Lawrence D F

    2012-05-01

    Knocking down neuronal LINGO-1 using short hairpin RNAs (shRNAs) might enhance axon regeneration in the central nervous system (CNS). Integration-deficient lentiviral vectors have great potential as a therapeutic delivery system for CNS injuries. However, recent studies have revealed that shRNAs can induce an interferon response resulting in off-target effects and cytotoxicity. CNS neurones were transduced with integration-deficient lentiviral vectors in vitro. The transcriptional effect of shRNA expression was analysed using quantitative real time-polymerase chain reaction and northern blots were used to assess shRNA production. Integration-deficient lentiviral vectors efficiently transduced CNS neurones and knocked down LINGO-1 mRNA in vitro. However, an increase in cell death was observed when lentiviral vectors encoding an shRNA were applied or when high vector concentrations were used. We demonstrate that high doses of vector or the use of vectors encoding shRNAs can induce an up-regulation of interferon-stimulated genes (2',5'-oligoadenylate synthase 1 and protein kinase R although not myxovirus resistance 1) and a down-regulation of off-target genes (including p75(NTR) and Nogo receptor 1). Furthermore, the northern blot demonstrated that these negative consequences occur even when lentiviral vectors express low levels of shRNAs. Taken together, these results may explain why neurite outgrowth was not enhanced on an inhibitory substrate following transduction with lentiviral vectors encoding an shRNA targeting LINGO-1. These findings highlight the importance of including appropriate controls to verify silencing specificity and the requirement to check for an interferon response when conducting RNA interference experiments. However, the potential benefits that RNA interference and viral vectors offer to gene-based therapies to CNS injuries cannot be overlooked and demand further investigation. Copyright © 2012 John Wiley & Sons, Ltd.

  11. Q-Axis Flux-Based Sensorless Vector Control of Induction Motor Taking into Account Iron Loss

    Science.gov (United States)

    Tsuji, Mineo; Chen, Shuo; Kai, Toshihiro; Hamasaki, Shin-Ichi

    This paper presents a sensorless vector control system for induction motors by taking into account iron loss, in which a flux-observer-based method is applied. Since the flux observer is constructed in a synchronously rotating reference frame with respect to the rotor flux of a current model and the iron loss resistance of parallel exiting circuit is used, the proposed system is very simple and the compensation of iron loss related to the operating frequency is directly realized while calculating rotor fluxes and slip frequency. The accuracies of estimated torque and speed are improved. The effectiveness of the proposed system has been verified by digital simulation and experimentation.

  12. A Compact 600 GHz Electronically Tunable Vector Measurement System for Submillimeter Wave Imaging

    Science.gov (United States)

    Dengler, Robert; Maiwald, Frank; Siegel, Peter H.

    2006-01-01

    The design of a complete vector measurement system being tested over 560-635 GHz is presented. The topics include: 1) Current State-of-the-Art in Vector Measurements; 2) Submillimeter Active Imaging Requirements; 3) 600 GHz Vector Measurement System; 4) 450 MHz IF Signal; 5) 450 MHz IF signal @ 1 kHz Res. BW; 6) 450 MHz IF Signal Mixed with Shifted 450 MHz Reference Signal; 7) Reference Signal Offset Generator; 8) Cavity Bandpass Filter; 9) Miniature Multistage Helical Filter; 10) X36 450 MHz Multiplier; 11) 600 GHz Test Setup; 12) 600 GHz Transmit Module; 13) 600 GHz Receive Module; 14) Performance Tests: Amplitude Stability & Dynamic Range; 15) Performance Tests: Phase Stability; 16) Stability at Imaging Bandwidths; 17) Phase Measurement Verification; and 18) The Next Step: Imaging.

  13. Multiplexed Targeted Genome Engineering Using a Universal Nuclease-Assisted Vector Integration System.

    Science.gov (United States)

    Brown, Alexander; Woods, Wendy S; Perez-Pinera, Pablo

    2016-07-15

    Engineered nucleases are capable of efficiently modifying complex genomes through introduction of targeted double-strand breaks. However, mammalian genome engineering remains limited by low efficiency of heterologous DNA integration at target sites, which is typically performed through homologous recombination, a complex, ineffective and costly process. In this study, we developed a multiplexable and universal nuclease-assisted vector integration system for rapid generation of gene knock outs using selection that does not require customized targeting vectors, thereby minimizing the cost and time frame needed for gene editing. Importantly, this system is capable of remodeling native mammalian genomes through integration of DNA, up to 50 kb, enabling rapid generation and screening of multigene knockouts from a single transfection. These results support that nuclease assisted vector integration is a robust tool for genome-scale gene editing that will facilitate diverse applications in synthetic biology and gene therapy.

  14. Influence of stimuli colour in SSVEP-based BCI wheelchair control using support vector machines.

    Science.gov (United States)

    Singla, Rajesh; Khosla, Arun; Jha, Rameshwar

    2014-04-01

    This study aims to develop a Steady State Visual Evoked Potential (SSVEP)-based Brain Computer Interface (BCI) system to control a wheelchair, with improving accuracy as the major goal. The developed wheelchair can move in forward, backward, left, right and stop positions. Four different flickering frequencies in the low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using LabVIEW. Four colours (green, red, blue and violet) were included in the study to investigate the colour influence in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital region were first segmented into 1 s windows and features were extracted by using Fast Fourier Transform (FFT). Three different classifiers, two based on Artificial Neural Network (ANN) and one based on Support Vector Machine (SVM), were compared to yield better accuracy. Twenty subjects participated in the experiment and the accuracy was calculated by considering the number of correct detections produced while performing a pre-defined movement sequence. SSVEP with violet colour showed higher performance than green and red. The One-Against-All (OAA) based multi-class SVM classifier showed better accuracy than the ANN classifiers. The classification accuracy over 20 subjects varies between 75-100%, while information transfer rates (ITR) varies from 12.13-27 bpm for BCI wheelchair control with SSVEPs elicited by violet colour stimuli and classified using OAA-SVM.

  15. Addressing vulnerability, building resilience: community-based adaptation to vector-borne diseases in the context of global change.

    Science.gov (United States)

    Bardosh, Kevin Louis; Ryan, Sadie J; Ebi, Kris; Welburn, Susan; Singer, Burton

    2017-12-11

    The threat of a rapidly changing planet - of coupled social, environmental and climatic change - pose new conceptual and practical challenges in responding to vector-borne diseases. These include non-linear and uncertain spatial-temporal change dynamics associated with climate, animals, land, water, food, settlement, conflict, ecology and human socio-cultural, economic and political-institutional systems. To date, research efforts have been dominated by disease modeling, which has provided limited practical advice to policymakers and practitioners in developing policies and programmes on the ground. In this paper, we provide an alternative biosocial perspective grounded in social science insights, drawing upon concepts of vulnerability, resilience, participation and community-based adaptation. Our analysis was informed by a realist review (provided in the Additional file 2) focused on seven major climate-sensitive vector-borne diseases: malaria, schistosomiasis, dengue, leishmaniasis, sleeping sickness, chagas disease, and rift valley fever. Here, we situate our analysis of existing community-based interventions within the context of global change processes and the wider social science literature. We identify and discuss best practices and conceptual principles that should guide future community-based efforts to mitigate human vulnerability to vector-borne diseases. We argue that more focused attention and investments are needed in meaningful public participation, appropriate technologies, the strengthening of health systems, sustainable development, wider institutional changes and attention to the social determinants of health, including the drivers of co-infection. In order to respond effectively to uncertain future scenarios for vector-borne disease in a changing world, more attention needs to be given to building resilient and equitable systems in the present.

  16. Fuzzy support vector machine: an efficient rule-based classification technique for microarrays

    Science.gov (United States)

    2013-01-01

    Background The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Results Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Conclusions Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification. PMID:24266942

  17. Wearable Vector Electrical Bioimpedance System to Assess Knee Joint Health.

    Science.gov (United States)

    Hersek, Sinan; Toreyin, Hakan; Teague, Caitlin N; Millard-Stafford, Mindy L; Jeong, Hyeon-Ki; Bavare, Miheer M; Wolkoff, Paul; Sawka, Michael N; Inan, Omer T

    2017-10-01

    We designed and validated a portable electrical bioimpedance (EBI) system to quantify knee joint health. Five separate experiments were performed to demonstrate the: 1) ability of the EBI system to assess knee injury and recovery; 2) interday variability of knee EBI measurements; 3) sensitivity of the system to small changes in interstitial fluid volume; 4) reducing the error of EBI measurements using acceleration signals; and 5) use of the system with dry electrodes integrated to a wearable knee wrap. 1) The absolute difference in resistance ( R) and reactance (X) from the left to the right knee was able to distinguish injured and healthy knees (p knee R was 2.5 Ω and for X was 1.2 Ω. 3) Local heating/cooling resulted in a significant decrease/increase in knee R (p knee R and X measured using the wet electrodes and the designed wearable knee wrap were highly correlated ( R 2 = 0.8 and 0.9, respectively). This study demonstrates the use of wearable EBI measurements in monitoring knee joint health. The proposed wearable system has the potential for assessing knee joint health outside the clinic/lab and help guide rehabilitation.

  18. Wearable Vector Electrical Bioimpedance System to Assess Knee Joint Health

    Science.gov (United States)

    Hersek, Sinan; Töreyin, Hakan; Teague, Caitlin N.; Millard-Stafford, Mindy L.; Jeong, Hyeon-Ki; Bavare, Miheer M.; Wolkoff, Paul; Sawka, Michael N.; Inan, Omer T.

    2017-01-01

    Objective We designed and validated a portable electrical bioimpedance (EBI) system to quantify knee joint health. Methods Five separate experiments were performed to demonstrate the: (1) ability of the EBI system to assess knee injury and recovery; (2) inter-day variability of knee EBI measurements; (3) sensitivity of the system to small changes in interstitial fluid volume; (4) reducing the error of EBI measurements using acceleration signals; (5) use of the system with dry electrodes integrated to a wearable knee wrap. Results (1) The absolute difference in resistance (R) and reactance (X) from the left to the right knee was able to distinguish injured and healthy knees (pmeasurements. (5) Linear regression between the knee R and X measured using the wet electrodes and the designed wearable knee wrap were highly correlated (r2 = 0.8 and 0.9, respectively). Conclusion This work demonstrates the use of wearable EBI measurements in monitoring knee joint health. Significance The proposed wearable system has the potential for assessing knee joint health outside the clinic/lab and help guide rehabilitation. PMID:28026745

  19. Space vector-based analysis of overmodulation in triangle ...

    Indian Academy of Sciences (India)

    1. Introduction. Three-phase voltage source inverters (VSI) are widely employed for DC to AC conversion. The VSI is a three-phase ..... In fact, this equivalence is exploited to produce PWM wave- forms corresponding to CSVPWM by ...... International Journal of Electrical Power and Energy. System 20(6): 375–381. Singh B ...

  20. Ultrasound Vector Flow Imaging: Part II: Parallel Systems

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt; Nikolov, Svetoslav Ivanov; Yu, Alfred C. H.

    2016-01-01

    The paper gives a review of the current state-of-theart in ultrasound parallel acquisition systems for flow imaging using spherical and plane waves emissions. The imaging methods are explained along with the advantages of using these very fast and sensitive velocity estimators. These experimental...... ultrasound imaging for studying brain function in animals. The paper explains the underlying acquisition and estimation methods for fast 2-D and 3-D velocity imaging and gives a number of examples. Future challenges and the potentials of parallel acquisition systems for flow imaging are also discussed....

  1. Improved image retrieval based on fuzzy colour feature vector

    Science.gov (United States)

    Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

    2013-03-01

    One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

  2. Combinatorial Vector Fields for Piecewise Affine Control Systems

    DEFF Research Database (Denmark)

    Wisniewski, Rafal; Larsen, Jesper Abildgaard

    2008-01-01

    This paper is intended to be a continuation of Habets and van Schuppen (2004) and Habets, Collins and van Schuppen (2006), which address the control problem for piecewise-affine systems on an arbitrary polytope or a family of these. Our work deals with the underlying combinatorics of the underlyi...

  3. Development of CRTEIL and CETRIZ, Cre-loxP-Based Systems, Which Allow Change of Expression of Red to Green or Green to Red Fluorescence upon Transfection with a Cre-Expression Vector

    OpenAIRE

    Masato Ohtsuka; Takayuki Warita; Takayuki Sakurai; Satoshi Watanabe; Hidetoshi Inoko; Masahiro Sato

    2009-01-01

    We developed Cre-loxP-based systems, termed CRTEIL and CETRIZ, which allow gene switching in a noninvasive manner. Single transfection with pCRTEIL resulted in predominant expression of red fluorescence. Cotransfection with pCRTEIL and Cre-expression plasmid (pCAG/NCre) caused switching from red to green fluorescence. Similarly, cotransfection with pCETRIZ and pCAG/NCre resulted in change of green to red fluorescence. These noninvasive systems will be useful in cell lineage analysis, since de...

  4. Support vector machine-based facial-expression recognition method combining shape and appearance

    Science.gov (United States)

    Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

    2010-11-01

    Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

  5. Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes

    Directory of Open Access Journals (Sweden)

    Utku Kose

    2016-03-01

    Full Text Available The definition, diagnosis and classification of Diabetes Mellitus and its complications are very important. First of all, the World Health Organization (WHO and other societies, as well as scientists have done lots of studies regarding this subject. One of the most important research interests of this subject is the computer supported decision systems for diagnosing diabetes. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics to streamline the diagnostic process in daily routine and avoid misdiagnosis. In this study, a diabetes diagnosis system, which is formed via both Support Vector Machines (SVM and Cognitive Development Optimization Algorithm (CoDOA has been proposed. Along the training of SVM, CoDOA was used for determining the sigma parameter of the Gauss (RBF kernel function, and eventually, a classification process was made over the diabetes data set, which is related to Pima Indians. The proposed approach offers an alternative solution to the field of Artificial Intelligence-based diabetes diagnosis, and contributes to the related literature on diagnosis processes.

  6. Recombinant alphaviruses as vectors for anti-tumour and anti-microbial immunotherapy

    NARCIS (Netherlands)

    Riezebos-Brilman, A; de Mare, A; Bungener, L; Huckriede, A; Wischut, J; Daemen, T

    Background: Vectors derived from alphaviruses are gaining interest for their high transfection potency and strong immunogenicity. Objectives: After a brief introduction on alphaviruses and their vectors, an overview is given on current preclinical immunotherapy studies using vector systems based on

  7. Evaluation of systemic insecticides mixed in rodenticide baits for plague vector control

    DEFF Research Database (Denmark)

    Larsen, Kim Søholt; Lodal, Jens

    1997-01-01

    Rodenticide baits containing systemic insecticides were evaluated in the laboratory for their palatability to the house rat Rattus rattus and for their toxicity against the oriental rat flea Xenopsylla cheopis - both animals are important Vectors of plague in Africa. The test bait and a non...

  8. Artificial neural networks and support vector machine in banking computer systems

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2013-12-01

    Full Text Available In this paper, some artificial neural networks as well as a support vector machines have been studied due to bank computer system development. These approaches with the contact-less microprocessor technologies can upsurge the bank competitiveness by adding new functionalities. Moreover, some financial crisis influences can be declines.

  9. Usability Evaluation of an Augmented Reality System for Teaching Euclidean Vectors

    Science.gov (United States)

    Martin-Gonzalez, Anabel; Chi-Poot, Angel; Uc-Cetina, Victor

    2016-01-01

    Augmented reality (AR) is one of the emerging technologies that has demonstrated to be an efficient technological tool to enhance learning techniques. In this paper, we describe the development and evaluation of an AR system for teaching Euclidean vectors in physics and mathematics. The goal of this pedagogical tool is to facilitate user's…

  10. Human artificial chromosome-based gene delivery vectors for biomedicine and biotechnology.

    Science.gov (United States)

    Kouprina, Natalay; Tomilin, Alexey N; Masumoto, Hiroshi; Earnshaw, William C; Larionov, Vladimir

    2014-04-01

    Human artificial chromosomes (HACs) have several advantages over viruses as gene delivery vectors, including stable episomal maintenance in a single copy and the ability to carry large gene inserts. In this review, we summarise recent work on gene transfer into mammalian cells using the HACs. HACs allow therapeutic transgenes to be expressed in target cells under conditions that recapitulate the physiological regulation of endogenous loci. Based on the published data, the HAC vectors have a great potential for gene therapy, regenerative medicine, screening of anticancer drugs and biotechnology.

  11. Fatigue crack monitoring of aerospace structure based on binary tree support vector machines

    Science.gov (United States)

    Lu, Shenbo; Zhou, Li

    2017-04-01

    This paper presents a novel method to monitor crack length which based on binary tree support vector machines (BTSVM). In this method, matching pursuit method with Chirplet atom is applied to extract the matching parameters as feature vectors to train and test in the BT-SVM algorithm. Then one simulation of lug joint is carried out for studying the effect of crack extension on Lamb wave signals propagation. Fatigue loading experiments on lug joints are carried out at last. The results show that this new method can monitor the length of fatigue crack effectively.

  12. Enhanced transduction of mouse salivary glands with AAV5-based vectors

    NARCIS (Netherlands)

    Katano, H.; Kok, M. R.; Cotrim, A. P.; Yamano, S.; Schmidt, M.; Afione, S.; Baum, B. J.; Chiorini, J. A.

    2006-01-01

    We previously demonstrated that recombinant adeno-associated virus vectors based on serotype 2 (rAAV2) can direct transgene expression in salivary gland cells in vitro and in vivo. However, it is not known how other rAAV serotypes perform when infused into salivary glands. The capsids of serotypes 4

  13. Vector-based plane-wave spectrum method for the propagation of cylindrical electromagnetic fields.

    Science.gov (United States)

    Shi, S; Prather, D W

    1999-11-01

    We present a vector-based plane-wave spectrum (VPWS) method for efficient propagation of cylindrical electromagnetic fields. In comparison with electromagnetic propagation integrals, the VPWS method significantly reduces time of propagation. Numerical results that illustrate the utility of this method are presented.

  14. Support-Vector-based Least Squares for learning non-linear dynamics

    NARCIS (Netherlands)

    de Kruif, B.J.; de Vries, Theodorus J.A.

    2002-01-01

    A function approximator is introduced that is based on least squares support vector machines (LSSVM) and on least squares (LS). The potential indicators for the LS method are chosen as the kernel functions of all the training samples similar to LSSVM. By selecting these as indicator functions the

  15. Factors Affecting Learning of Vector Math from Computer-Based Practice: Feedback Complexity and Prior Knowledge

    Science.gov (United States)

    Heckler, Andrew F.; Mikula, Brendon D.

    2016-01-01

    In experiments including over 450 university-level students, we studied the effectiveness and time efficiency of several levels of feedback complexity in simple, computer-based training utilizing static question sequences. The learning domain was simple vector math, an essential skill in introductory physics. In a unique full factorial design, we…

  16. The Impact of Satellite Atmospheric Motion Vectors in the GMAO GEOS-5 Global Data Assimilation System

    Science.gov (United States)

    Gelaro, R. D.; Merkova, D.; Tai, King-Sheng; McCarty, W.

    2012-01-01

    The impact of satellite-derived atmospheric motion vectors (AMVs) on numerical weather forecasts is examined using the GEOS-5 global atmospheric data assimilation system. Cycling data assimilation experiments, including twice-daily 5-day forecasts, are conducted for two 6-week periods during the 2010 Atlantic hurricane season and 2010-2011Northern Hemisphere winter season. Results from a control experiment that includes all AMVs and other data types assimilated operationally in GEOS-5 are compared with those from an experiment in which the GEOS-5 AMVs (only) are replaced by ones produced by the U. S. Navy?s NAVDAS-AR atmospheric data assimilation system. The Navy AMVs are assimilated in their entirety as well as in various subset combinations. The primary objective of these experiments is to determine whether aspects of the NAVDAS-AR data selection and quality control procedure, especially the use of carefully averaged ("super-ob?) wind vectors and large volume of AMVs, explain the typically larger beneficial impact of these data in the Navy system as compared with most other forecast systems. Adjoint-based observation impact calculations are assessed and compared with traditional metrics such as forecast geopotential height anomaly correlations and observation-minus-forecast departures. Results so far indicate that that the greater number of NRL AMVs is primarily responsible for their larger impact, although superobing also appears to be beneficial. Map views show that the impact obtained from assimilation of the NRL AMVs is more uniformly beneficial, perhaps due to the averaging of individual observations in creating the super-obs. While the NRL AMVs have a much larger impact in GEOS-5 than do the control AMVs, their impact is still smaller than in the Navy forecast system, suggesting that the mix of observations may play an important role in modulating the impact of any one data type. At the same time, reducing the number of satellite radiances assimilated in

  17. Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

    Science.gov (United States)

    Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

    2017-07-01

    Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

  18. VGSC: A Web-Based Vector Graph Toolkit of Genome Synteny and Collinearity

    Directory of Open Access Journals (Sweden)

    Yiqing Xu

    2016-01-01

    Full Text Available Background. In order to understand the colocalization of genetic loci amongst species, synteny and collinearity analysis is a frequent task in comparative genomics research. However many analysis software packages are not effective in visualizing results. Problems include lack of graphic visualization, simple representation, or inextensible format of outputs. Moreover, higher throughput sequencing technology requires higher resolution image output. Implementation. To fill this gap, this paper publishes VGSC, the Vector Graph toolkit of genome Synteny and Collinearity, and its online service, to visualize the synteny and collinearity in the common graphical format, including both raster (JPEG, Bitmap, and PNG and vector graphic (SVG, EPS, and PDF. Result. Users can upload sequence alignments from blast and collinearity relationship from the synteny analysis tools. The website can generate the vector or raster graphical results automatically. We also provide a java-based bytecode binary to enable the command-line execution.

  19. Vector mode conversion based on an asymmetric fiber Bragg grating in few-mode fibers.

    Science.gov (United States)

    Mi, Yuean; Li, Haisu; Ren, Guobin

    2017-09-01

    We propose a vector mode conversion approach based on asymmetric fiber Bragg gratings (AFBGs) written in step-index fiber and vortex fiber, respectively. The mode coupling properties of AFBGs are numerically investigated. Compared to step-index fiber, the large mode separation in the vortex fiber is beneficial to extracting the desired vector mode at specific wavelengths. In addition, the polarization of incident light and the attenuation coefficient of index change distribution of the AFBG play critical roles in the mode coupling process. The proposed AFBG provides an efficient method to realize high-order vector mode conversion, and it shows great potential for orbital angular momentum multiplexing and fiber lasers with vortex beam output.

  20. The vector behavior of aberrations in high numerical aperture (0.9 < NA < 3.1) laser focusing systems

    Science.gov (United States)

    Jo, Sseunhyeun

    This dissertation investigates vector behavior of aberrations for high numerical aperture optical systems using a solid immersion lens (SIL). In order to analyze the system, this dissertation introduces the illumination system transfer function (ISTF), which is a map in the space of the exit pupil that shows reflection and transmission properties of individual plane waves that are emitted from corresponding points in the exit pupil. A vector analysis using ISTF presents the role of propagating and evanescent energy in the SIL systems, where the boundary between the them is defined by total internal reflection. The behavior of third-order aberrations such as coma and astigmatism, are dramatically affected by polarization in high NA systems. The irradiance distribution exhibits significantly different characteristics, depending on how coma or astigmatism is aligned with the incident linear polarized light. Vector effects including diffraction, polarization, and aberration, are used to analyze tolerances along with a comparison to geometrical optics. Apodization in amplitude and phase of the angular spectrum is generated in high NA focusing systems due to the difference in vector transmission and reflection for each plane wave. The size of the incident gaussian beam is effectively reduced at the exit pupil by the amplitude apodization and causes a spot size increase in image space. The apodization in phase is called gap-induced aberration due to its dependence on the air gap. The gap- induced aberration does not come from lens surface imperfection, and it exhibits multiple orders of spherical aberration and astigmatism. The apodization in amplitude and phase is well characterized by separable supergaussian functions, where each function depends on the refractive index of the SIL n SIL and the air gap height h. The best defocus, based on characteristics of gap-induced aberration, is suggested to be a good compensator only for low nSIL and h. The system performance, as

  1. Transcriptional Silencing of Retroviral Vectors

    DEFF Research Database (Denmark)

    Lund, Anders Henrik; Duch, M.; Pedersen, F.S.

    1996-01-01

    Although retroviral vector systems have been found to efficiently transduce a variety of cell types in vitro, the use of vectors based on murine leukemia virus in preclinical models of somatic gene therapy has led to the identification of transcriptional silencing in vivo as an important problem...

  2. Rapid, scalable, and low-cost purification of recombinant adeno-associated virus produced by baculovirus expression vector system

    Directory of Open Access Journals (Sweden)

    Pierre-Olivier Buclez

    2016-01-01

    Full Text Available Recombinant adeno-associated viruses (rAAV are largely used for gene transfer in research, preclinical developments, and clinical trials. Their broad in vivo biodistribution and long-term efficacy in postmitotic tissues make them good candidates for numerous gene transfer applications. Upstream processes able to produce large amounts of rAAV were developed, particularly those using baculovirus expression vector system. In parallel, downstream processes present a large panel of purification methods, often including multiple and time consuming steps. Here, we show that simple tangential flow filtration, coupled with an optimized iodixanol-based isopycnic density gradient, is sufficient to purify several liters of crude lysate produced by baculovirus expression vector system in only one working day, leading to high titers and good purity of rAAV products. Moreover, we show that the viral vectors retain their in vitro and in vivo functionalities. Our results demonstrate that simple, rapid, and relatively low-cost methods can easily be implemented for obtaining a high-quality grade of gene therapy products based on rAAV technology.

  3. Tractional Electric Drive with Non-Sensing Element Vector Control System

    Directory of Open Access Journals (Sweden)

    O. F. Opeyko

    2010-01-01

    Full Text Available The purpose of the paper is a structure formation and an analysis of non-sensing element vector control system developed for tractional electric drive with the help of mathematical simulation method. The paper presents a functional diagram of the electric drive with non-sensing element vector control system  operated by an asynchronous short-circuited electric motor.  Main expressions used for evaluation of variables of system conditions and parameters are cited in the paper. The paper provides results of mathematical simulation method for electric drive system taking into consideration various parameter values which confirm serviceability of the developed control system within the whole range of possible parameter chnges.

  4. Role of regulatory T-cells in immunization strategies involving a recombinant alphavirus vector system

    NARCIS (Netherlands)

    Walczak, Mateusz; Regts, Joke; van Oosterhout, Antoon J. M.; Boon, Louis; Wilschut, Jan; Nijman, Hans W.; Daemen, Toos

    2011-01-01

    Background: Regulatory T-cells (Treg) hamper immune responses elicited by cancer vaccines. Therefore, depletion of Treg is being used to improve the outcome of vaccinations. Methods: We studied whether an alphavirus vector-based immunotherapeutic vaccine changes the number and/or activity of Treg

  5. Measles virus glycoprotein-based lentiviral targeting vectors that avoid neutralizing antibodies.

    Directory of Open Access Journals (Sweden)

    Sabrina Kneissl

    Full Text Available Lentiviral vectors (LVs are potent gene transfer vehicles frequently applied in research and recently also in clinical trials. Retargeting LV entry to cell types of interest is a key issue to improve gene transfer safety and efficacy. Recently, we have developed a targeting method for LVs by incorporating engineered measles virus (MV glycoproteins, the hemagglutinin (H, responsible for receptor recognition, and the fusion protein into their envelope. The H protein displays a single-chain antibody (scFv specific for the target receptor and is ablated for recognition of the MV receptors CD46 and SLAM by point mutations in its ectodomain. A potential hindrance to systemic administration in humans is pre-existing MV-specific immunity due to vaccination or natural infection. We compared transduction of targeting vectors and non-targeting vectors pseudotyped with MV glycoproteins unmodified in their ectodomains (MV-LV in presence of α-MV antibody-positive human plasma. At plasma dilution 1:160 MV-LV was almost completely neutralized, whereas targeting vectors showed relative transduction efficiencies from 60% to 90%. Furthermore, at plasma dilution 1:80 an at least 4-times higher multiplicity of infection (MOI of MV-LV had to be applied to obtain similar transduction efficiencies as with targeting vectors. Also when the vectors were normalized to their p24 values, targeting vectors showed partial protection against α-MV antibodies in human plasma. Furthermore, the monoclonal neutralizing antibody K71 with a putative epitope close to the receptor binding sites of H, did not neutralize the targeting vectors, but did neutralize MV-LV. The observed escape from neutralization may be due to the point mutations in the H ectodomain that might have destroyed antibody binding sites. Furthermore, scFv mediated cell entry via the target receptor may proceed in presence of α-MV antibodies interfering with entry via the natural MV receptors. These results are

  6. Fault Identification in an Unbalanced Distribution System Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Sophi Shilpa Gururajapathy

    2016-12-01

    Full Text Available Fast and effective fault location in distribution system is important to improve the power system reliability. Most of the researches rarely mention about effective fault location consisting of faulted phase, fault type, faulty section and fault distance identification. This work presents a method using support vector machine to identify the faulted phase, fault type, faulty section and distance at the same time. Support vector classification and regression analysis are performed to locate fault. The method uses the voltage sag data during fault condition measured at the primary substation. The faulted phase and the fault type are identified using three-dimensional support vector classification. The possible faulty sections are identified by matching voltage sag at fault condition to the voltage sag in database and the possible sections are ranked using shortest distance principle. The fault distance for the possible faulty sections isthen identified using support vector regression analysis. The performance of the proposed method was tested on an unbalanced distribution system from SaskPower, Canada. The results show that the accuracy of the proposed method is satisfactory.

  7. Scalar and Vector 4Q Systems in Anisotropic Lattice QCD

    CERN Document Server

    Loan, Mushtaq; Lam, Yu Yiu

    2009-01-01

    We present a detailed study of some $4q$ hadrons in quenched improved anisotropic lattice QCD. Using the $\\pi\\pi$ and diquark-antidiquark local and smeared operators, we attempt to isolate the signal for $I(J^{P})=0(0^{+}), 2(0^{+})$ and $1(1^{+})$ states in two flavour QCD. In the chiral limit of light-quark mass region, the lowest scalar $4q$ state is found to have a mass, $m^{I=0}_{4q}=927(12)$ MeV, which is slightly lower than the experimentally observed $f_{0}(980)$. The results from our variational analysis do not indicate a signature of a tetraquark resonance in I=1 and I=2 channels. After the chiral extrapolation the lowest $1(1^{+})$ state is found to have a mass, $m^{I=1}_{4q}=1358(28)$ MeV. We analysed the static $4q$ potential extracted form a tetraquark Wilson loop and illustrated the behaviour of the $4q$ state as a bound state, unbinding at some critical diquark separation. From our analysis we conclude that scalar $4q$ system appears as a two-pion scattering state and that there is no spatiall...

  8. A Novel CSR-Based Sparse Matrix-Vector Multiplication on GPUs

    Directory of Open Access Journals (Sweden)

    Guixia He

    2016-01-01

    Full Text Available Sparse matrix-vector multiplication (SpMV is an important operation in scientific computations. Compressed sparse row (CSR is the most frequently used format to store sparse matrices. However, CSR-based SpMVs on graphic processing units (GPUs, for example, CSR-scalar and CSR-vector, usually have poor performance due to irregular memory access patterns. This motivates us to propose a perfect CSR-based SpMV on the GPU that is called PCSR. PCSR involves two kernels and accesses CSR arrays in a fully coalesced manner by introducing a middle array, which greatly alleviates the deficiencies of CSR-scalar (rare coalescing and CSR-vector (partial coalescing. Test results on a single C2050 GPU show that PCSR fully outperforms CSR-scalar, CSR-vector, and CSRMV and HYBMV in the vendor-tuned CUSPARSE library and is comparable with a most recently proposed CSR-based algorithm, CSR-Adaptive. Furthermore, we extend PCSR on a single GPU to multiple GPUs. Experimental results on four C2050 GPUs show that no matter whether the communication between GPUs is considered or not PCSR on multiple GPUs achieves good performance and has high parallel efficiency.

  9. Reference Function Based Spatiotemporal Fuzzy Logic Control Design Using Support Vector Regression Learning

    Directory of Open Access Journals (Sweden)

    Xian-Xia Zhang

    2013-01-01

    Full Text Available This paper presents a reference function based 3D FLC design methodology using support vector regression (SVR learning. The concept of reference function is introduced to 3D FLC for the generation of 3D membership functions (MF, which enhance the capability of the 3D FLC to cope with more kinds of MFs. The nonlinear mathematical expression of the reference function based 3D FLC is derived, and spatial fuzzy basis functions are defined. Via relating spatial fuzzy basis functions of a 3D FLC to kernel functions of an SVR, an equivalence relationship between a 3D FLC and an SVR is established. Therefore, a 3D FLC can be constructed using the learned results of an SVR. Furthermore, the universal approximation capability of the proposed 3D fuzzy system is proven in terms of the finite covering theorem. Finally, the proposed method is applied to a catalytic packed-bed reactor and simulation results have verified its effectiveness.

  10. Support vector machine-based open crop model (SBOCM): Case of rice production in China.

    Science.gov (United States)

    Su, Ying-Xue; Xu, Huan; Yan, Li-Jiao

    2017-03-01

    Existing crop models produce unsatisfactory simulation results and are operationally complicated. The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation. Using rice as the research crop, a support vector machine-based open crop model (SBOCM) was developed by integrating developmental stage and yield prediction models. Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used. Based on the principle of scale compatibility of modeling data, an open reading frame was designed for the dynamic daily input of meteorological data and output of rice development and yield records. This was used to generate rice developmental stage and yield prediction models, which were integrated into the SBOCM system. The parameters, methods, error resources, and other factors were analyzed. Although not a crop physiology simulation model, the proposed SBOCM can be used for perennial simulation and one-year rice predictions within certain scale ranges. It is convenient for data acquisition, regionally applicable, parametrically simple, and effective for multi-scale factor integration. It has the potential for future integration with extensive social and economic factors to improve the prediction accuracy and practicability.

  11. Predictive based monitoring of nuclear plant component degradation using support vector regression

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Vivek [Idaho National Lab. (INL), Idaho Falls, ID (United States). Dept. of Human Factors, Controls, Statistics; Alamaniotis, Miltiadis [Purdue Univ., West Lafayette, IN (United States). School of Nuclear Engineering; Tsoukalas, Lefteri H. [Purdue Univ., West Lafayette, IN (United States). School of Nuclear Engineering

    2015-02-01

    Nuclear power plants (NPPs) are large installations comprised of many active and passive assets. Degradation monitoring of all these assets is expensive (labor cost) and highly demanding task. In this paper a framework based on Support Vector Regression (SVR) for online surveillance of critical parameter degradation of NPP components is proposed. In this case, on time replacement or maintenance of components will prevent potential plant malfunctions, and reduce the overall operational cost. In the current work, we apply SVR equipped with a Gaussian kernel function to monitor components. Monitoring includes the one-step-ahead prediction of the component’s respective operational quantity using the SVR model, while the SVR model is trained using a set of previous recorded degradation histories of similar components. Predictive capability of the model is evaluated upon arrival of a sensor measurement, which is compared to the component failure threshold. A maintenance decision is based on a fuzzy inference system that utilizes three parameters: (i) prediction evaluation in the previous steps, (ii) predicted value of the current step, (iii) and difference of current predicted value with components failure thresholds. The proposed framework will be tested on turbine blade degradation data.

  12. Support vector machine-based open crop model (SBOCM: Case of rice production in China

    Directory of Open Access Journals (Sweden)

    Ying-xue Su

    2017-03-01

    Full Text Available Existing crop models produce unsatisfactory simulation results and are operationally complicated. The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation. Using rice as the research crop, a support vector machine-based open crop model (SBOCM was developed by integrating developmental stage and yield prediction models. Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used. Based on the principle of scale compatibility of modeling data, an open reading frame was designed for the dynamic daily input of meteorological data and output of rice development and yield records. This was used to generate rice developmental stage and yield prediction models, which were integrated into the SBOCM system. The parameters, methods, error resources, and other factors were analyzed. Although not a crop physiology simulation model, the proposed SBOCM can be used for perennial simulation and one-year rice predictions within certain scale ranges. It is convenient for data acquisition, regionally applicable, parametrically simple, and effective for multi-scale factor integration. It has the potential for future integration with extensive social and economic factors to improve the prediction accuracy and practicability.

  13. Lentiviral vector-based insertional mutagenesis identifies genes associated with liver cancer

    Science.gov (United States)

    Ranzani, Marco; Cesana, Daniela; Bartholomae, Cynthia C.; Sanvito, Francesca; Pala, Mauro; Benedicenti, Fabrizio; Gallina, Pierangela; Sergi, Lucia Sergi; Merella, Stefania; Bulfone, Alessandro; Doglioni, Claudio; von Kalle, Christof; Kim, Yoon Jun; Schmidt, Manfred; Tonon, Giovanni; Naldini, Luigi; Montini, Eugenio

    2013-01-01

    Transposons and γ-retroviruses have been efficiently used as insertional mutagens in different tissues to identify molecular culprits of cancer. However, these systems are characterized by recurring integrations that accumulate in tumor cells, hampering the identification of early cancer-driving events amongst bystander and progression-related events. We developed an insertional mutagenesis platform based on lentiviral vectors (LVV) by which we could efficiently induce hepatocellular carcinoma (HCC) in 3 different mouse models. By virtue of LVV’s replication-deficient nature and broad genome-wide integration pattern, LVV-based insertional mutagenesis allowed identification of 4 new liver cancer genes from a limited number of integrations. We validated the oncogenic potential of all the identified genes in vivo, with different levels of penetrance. Our newly identified cancer genes are likely to play a role in human disease, since they are upregulated and/or amplified/deleted in human HCCs and can predict clinical outcome of patients. PMID:23314173

  14. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

    KAUST Repository

    Smaili, Fatima Zohra

    2018-01-31

    We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

  15. Short term prediction of the horizontal wind vector within a wake vortex warning system

    Energy Technology Data Exchange (ETDEWEB)

    Frech, M.; Holzaepfel, F.; Gerz, T. [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Wessling (Germany). Inst. fuer Physik der Atmosphaere; Konopka, J. [Deutsche Flugsicherung (DFS) GmbH, Langen (Germany)

    2000-07-14

    A wake vortex warning system (WVWS) has been developed for Frankfurt airport. This airport has two parallel runways which are separated by 518 m, a distance too short to operate them independently because wake vortices may be advected to the adjacent runway. The objective of the WVWS is to enable operation with reduced separation between two aircraft approaching the parallel runways at appropriate wind conditions. The WVWS applies a statistical persistence model to predict the crosswind within a 20 minute period. One of the main problems identified in the old WVWS are discontinuities between successive forecasts. These forecast breakdowns were not acceptable to airtraffic controllers. At least part of the problem was related to the fact that the forecast was solely based on the prediction of crosswind. A new method is developed on the basis of 523 days of sonic anemometer measurements at Frankfurt airport. It is demonstrated that the prediction of the horizontal wind vector avoids these difficulties and significantly improves the system's performance. (orig.)

  16. Widespread Central Nervous System Gene Transfer and Silencing After Systemic Delivery of Novel AAV-AS Vector.

    Science.gov (United States)

    Choudhury, Sourav R; Harris, Anne F; Cabral, Damien J; Keeler, Allison M; Sapp, Ellen; Ferreira, Jennifer S; Gray-Edwards, Heather L; Johnson, Jacob A; Johnson, Aime K; Su, Qin; Stoica, Lorelei; DiFiglia, Marian; Aronin, Neil; Martin, Douglas R; Gao, Guangping; Sena-Esteves, Miguel

    2016-04-01

    Effective gene delivery to the central nervous system (CNS) is vital for development of novel gene therapies for neurological diseases. Adeno-associated virus (AAV) vectors have emerged as an effective platform for in vivo gene transfer, but overall neuronal transduction efficiency of vectors derived from naturally occurring AAV capsids after systemic administration is relatively low. Here, we investigated the possibility of improving CNS transduction of existing AAV capsids by genetically fusing peptides to the N-terminus of VP2 capsid protein. A novel vector AAV-AS, generated by the insertion of a poly-alanine peptide, is capable of extensive gene transfer throughout the CNS after systemic administration in adult mice. AAV-AS is 6- and 15-fold more efficient than AAV9 in spinal cord and cerebrum, respectively. The neuronal transduction profile varies across brain regions but is particularly high in the striatum where AAV-AS transduces 36% of striatal neurons. Widespread neuronal gene transfer was also documented in cat brain and spinal cord. A single intravenous injection of an AAV-AS vector encoding an artificial microRNA targeting huntingtin (Htt) resulted in 33-50% knockdown of Htt across multiple CNS structures in adult mice. This novel AAV-AS vector is a promising platform to develop new gene therapies for neurodegenerative disorders.

  17. Bluetongue Disease Risk Assessment Based on Observed and Projected Culicoides obsoletus spp. Vector Densities

    Science.gov (United States)

    Brugger, Katharina; Rubel, Franz

    2013-01-01

    Bluetongue is an arboviral disease of ruminants causing significant economic losses. Our risk assessment is based on the epidemiological key parameter, the basic reproduction number. It is defined as the number of secondary cases caused by one primary case in a fully susceptible host population, in which values greater than one indicate the possibility, i.e., the risk, for a major disease outbreak. In the course of the Bluetongue virus serotype 8 (BTV-8) outbreak in Europe in 2006 we developed such a risk assessment for the University of Veterinary Medicine Vienna, Austria. Basic reproduction numbers were calculated using a well-known formula for vector-borne diseases considering the population densities of hosts (cattle and small ruminants) and vectors (biting midges of the Culicoides obsoletus spp.) as well as temperature dependent rates. The latter comprise the biting and mortality rate of midges as well as the reciprocal of the extrinsic incubation period. Most important, but generally unknown, is the spatio-temporal distribution of the vector density. Therefore, we established a continuously operating daily monitoring to quantify the seasonal cycle of the vector population by a statistical model. We used cross-correlation maps and Poisson regression to describe vector densities by environmental temperature and precipitation. Our results comprise time series of observed and simulated Culicoides obsoletus spp. counts as well as basic reproduction numbers for the period 2009–2011. For a spatio-temporal risk assessment we projected our results from the location of Vienna to the entire region of Austria. We compiled both daily maps of vector densities and the basic reproduction numbers, respectively. Basic reproduction numbers above one were generally found between June and August except in the mountainous regions of the Alps. The highest values coincide with the locations of confirmed BTV cases. PMID:23560090

  18. Bluetongue disease risk assessment based on observed and projected Culicoides obsoletus spp. vector densities.

    Directory of Open Access Journals (Sweden)

    Katharina Brugger

    Full Text Available Bluetongue is an arboviral disease of ruminants causing significant economic losses. Our risk assessment is based on the epidemiological key parameter, the basic reproduction number. It is defined as the number of secondary cases caused by one primary case in a fully susceptible host population, in which values greater than one indicate the possibility, i.e., the risk, for a major disease outbreak. In the course of the Bluetongue virus serotype 8 (BTV-8 outbreak in Europe in 2006 we developed such a risk assessment for the University of Veterinary Medicine Vienna, Austria. Basic reproduction numbers were calculated using a well-known formula for vector-borne diseases considering the population densities of hosts (cattle and small ruminants and vectors (biting midges of the Culicoides obsoletus spp. as well as temperature dependent rates. The latter comprise the biting and mortality rate of midges as well as the reciprocal of the extrinsic incubation period. Most important, but generally unknown, is the spatio-temporal distribution of the vector density. Therefore, we established a continuously operating daily monitoring to quantify the seasonal cycle of the vector population by a statistical model. We used cross-correlation maps and Poisson regression to describe vector densities by environmental temperature and precipitation. Our results comprise time series of observed and simulated Culicoides obsoletus spp. counts as well as basic reproduction numbers for the period 2009-2011. For a spatio-temporal risk assessment we projected our results from the location of Vienna to the entire region of Austria. We compiled both daily maps of vector densities and the basic reproduction numbers, respectively. Basic reproduction numbers above one were generally found between June and August except in the mountainous regions of the Alps. The highest values coincide with the locations of confirmed BTV cases.

  19. Solution of two nucleon systems using vector variables in momentum space - an innovative approach

    Science.gov (United States)

    Veerasamy, Saravanan

    An alternate formalism that uses vector variables to treat the two-body Lippmann-Schwinger equation for realistic nucleon-nucleon potentials in momentum space is discussed in this thesis. The formalism uses the symmetry properties of the nucleon-nucleon potential and expands the nucleon-nucleon potential in terms of six linearly independent spin operators. The alternate formalism discussed in this thesis brings to light the role of time-odd spin operators. The vector variable formalism's treatment of spin degrees of freedom heavily depends on the analytical computation of hundreds of algebraic expression. A mathematical framework and computer algorithms for an automated symbolic reduction of algebraic expressions into scalar functions of vector variables are explained in this thesis. The vector variable formalism requires nucleon-nucleon potentials that are in operator form as input. The configuration space nucleon-nucleon potential Argonne V18 is one such potential that can be used for relativistic energies if it can be computed efficiently in momentum space. This thesis develops an efficient numerical technique using Chebyshev approximation to compute the Argonne V18 potential in momentum-space. The tools discussed in this thesis, the algebraic system and the efficient computation of the Argonne V18 potential in momentum space are tested by computing the binding energy and bound state wavefunctions of the deuteron using the vector variable approach. The results were successful and the first step towards a higher goal of using vector formalism of the three-body Faddeev equations for intermediate and high energies has been made.

  20. An Effective NoSQL-Based Vector Map Tile Management Approach

    Directory of Open Access Journals (Sweden)

    Lin Wan

    2016-11-01

    Full Text Available Within a digital map service environment, the rapid growth of Spatial Big-Data is driving new requirements for effective mechanisms for massive online vector map tile processing. The emergence of Not Only SQL (NoSQL databases has resulted in a new data storage and management model for scalable spatial data deployments and fast tracking. They better suit the scenario of high-volume, low-latency network map services than traditional standalone high-performance computer (HPC or relational databases. In this paper, we propose a flexible storage framework that provides feasible methods for tiled map data parallel clipping and retrieval operations within a distributed NoSQL database environment. We illustrate the parallel vector tile generation and querying algorithms with the MapReduce programming model. Three different processing approaches, including local caching, distributed file storage, and the NoSQL-based method, are compared by analyzing the concurrent load and calculation time. An online geological vector tile map service prototype was developed to embed our processing framework in the China Geological Survey Information Grid. Experimental results show that our NoSQL-based parallel tile management framework can support applications that process huge volumes of vector tile data and improve performance of the tiled map service.

  1. Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market

    OpenAIRE

    Gao, C.(Central China Normal University, Wuhan, China); Bompard, E.; Napoli, R.; Wan, Q.

    2007-01-01

    The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecast accuracy, with which the being rejected risk is defined. The other takes into account the impact of the producer's own bid. The risks associat...

  2. New Evaluation Vector through the Stanford Mobile Inquiry-Based Learning Environment (SMILE) for Participatory Action Research.

    Science.gov (United States)

    Kim, Paul; An, Ji-Young

    2016-07-01

    This article reviews an evaluation vector model driven from a participatory action research leveraging a collective inquiry system named SMILE (Stanford Mobile Inquiry-based Learning Environment). SMILE has been implemented in a diverse set of collective inquiry generation and analysis scenarios including community health care-specific professional development sessions and community-based participatory action research projects. In each scenario, participants are given opportunities to construct inquiries around physical and emotional health-related phenomena in their own community. Participants formulated inquiries as well as potential clinical treatments and hypothetical scenarios to address health concerns or clarify misunderstandings or misdiagnoses often found in their community practices. From medical universities to rural village health promotion organizations, all participatory inquiries and potential solutions can be collected and analyzed. The inquiry and solution sets represent an evaluation vector which helps educators better understand community health issues at a much deeper level. SMILE helps collect problems that are most important and central to their community health concerns. The evaluation vector, consisting participatory and collective inquiries and potential solutions, helps the researchers assess the participants' level of understanding on issues around health concerns and practices while helping the community adequately formulate follow-up action plans. The method used in SMILE requires much further enhancement with machine learning and advanced data visualization.

  3. In vitro pharmacodynamic evaluation of antiviral medicinal plants using a vector-based assay technique.

    Science.gov (United States)

    Esimone, C O; Grunwald, T; Wildner, O; Nchinda, G; Tippler, B; Proksch, P; Uberla, K

    2005-01-01

    Medicinal plants are increasingly being projected as suitable alternative sources of antiviral agents. The development of a suitable in vitro pharmacodynamic screening technique could contribute to rapid identification of potential bioactive plants and also to the standardization and/or pharmacokinetic-pharmacodynamic profiling of the bioactive components. Recombinant viral vectors (lentiviral, retroviral and adenoviral) transferring the firefly luciferase gene were constructed and the inhibition of viral vector infectivity by various concentrations of plant extracts was evaluated in HeLa or Hep2 cells by measuring the changes in luciferase activity. Cytotoxicity of the extracts was evaluated in parallel on HeLa or Hep2 cells stably expressing luciferase. Amongst the 15 extracts screened, only the methanol (ME) and the ethyl acetate (ET) fractions of the lichen, Ramalina farinacea specifically reduced lentiviral and adenoviral infectivity in a dose-dependent manner. Further, chromatographic fractionation of ET into four fractions (ET1-ET4) revealed only ET4 to be selectively antiviral with an IC50 in the 20 microg ml(-1) range. Preliminary mechanistic studies based on the addition of the extracts at different time points in the viral infection cycle (kinetic studies) revealed that the inhibitory activity was highest if extract and vectors were preincubated prior to infection, suggesting that early steps in the lentiviral or adenoviral replication cycle could be the major target of ET4. Inhibition of wild-type HIV-1 was also observed at a 10-fold lower concentration of the extract. The vector-based assay is a suitable in vitro pharmacodynamic evaluation technique for antiviral medicinal plants. The technique has successfully demonstrated the presence of antiviral principles in R. farinacea. Potential anti-HIV medicinal plants could rapidly be evaluated with the reported vector-based technique. The lichen, R. farinacea could represent a lead source of antiviral

  4. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

    Directory of Open Access Journals (Sweden)

    Liao Li

    2010-10-01

    Full Text Available Abstract Background Protein-protein interaction (PPI plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs, based on domains represented as interaction profile hidden Markov models (ipHMM where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB. Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD. Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure, an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on

  5. pHUSH: a single vector system for conditional gene expression

    Directory of Open Access Journals (Sweden)

    Eby Mike

    2007-09-01

    Full Text Available Abstract Background Conditional expression vectors have become a valuable research tool to avoid artefacts that may result from traditional gene expression studies. However, most systems require multiple plasmids that must be independently engineered into the target system, resulting in experimental delay and an increased potential for selection of a cell subpopulation that differs significantly from the parental line. We have therefore developed pHUSH, an inducible expression system that allows regulated expression of shRNA, miRNA or cDNA cassettes on a single viral vector. Results Both Pol II and Pol III promoters have been successfully combined with a second expression cassette containing a codon-optimized tetracycline repressor and selectable marker. We provide examples of how pHUSH has been successfully employed to study the function of target genes in a number of cell types within in vitro and in vivo assays, including conditional gene knockdown in a murine model of brain cancer. Conclusion We have successfully developed and employed a single vector system that enables Doxycycline regulated RNAi or transgene expression in a variety of in vitro and in vivo model systems. These studies demonstrate the broad application potential of pHUSH for conditional genetic engineering in mammalian cells.

  6. A marker-free system for highly efficient construction of vaccinia virus vectors using CRISPR Cas9

    Directory of Open Access Journals (Sweden)

    Ming Yuan

    Full Text Available The current method for creation of vaccinia virus (VACV vectors involves using a selection and purification marker, however inclusion of a gene without therapeutic value in the resulting vector is not desirable for clinical use. The Cre-LoxP system has been used to make marker-free Poxviruses, but the efficiency was very low. To obtain a marker-free VACV vector, we developed marker gene excision systems to modify the thymidine kinase (TK region and N1L regions using Cre-Loxp and Flp-FRET systems respectively. CRISPR-Cas9 system significantly resulted in a high efficiency (∼90% in generation of marker gene-positive TK-mutant VACV vector. The marker gene (RFP could be excised from the recombinant virus using Cre recombinase. To make a marker-free VV vector with double gene deletions targeting the TK and N1L gene, we constructed a donor repair vector targeting the N1L gene, which can carry a therapeutic gene and the marker (RFP that could be excised from the recombinant virus using Flp recombinase. The marker-free system developed here can be used to efficiently construct VACV vectors armed with any therapeutic genes in the TK region or N1L region without marker genes. Our marker-free system platform has significant potential for development of new marker-free VACV vectors for clinical application.

  7. VIP Barcoding: composition vector-based software for rapid species identification based on DNA barcoding.

    Science.gov (United States)

    Fan, Long; Hui, Jerome H L; Yu, Zu Guo; Chu, Ka Hou

    2014-07-01

    Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time-consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user-friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two-stage algorithm. First, an alignment-free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment-based K2P distance nearest-neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment-free methods and (ii) higher scalability than alignment-based distance methods and character-based methods. These results suggest that this platform is able to deal with both large-scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/. © 2014 John Wiley & Sons Ltd.

  8. A terrestrial lidar-based workflow for determining three-dimensional slip vectors and associated uncertainties

    Science.gov (United States)

    Gold, Peter O.; Cowgill, Eric; Kreylos, Oliver; Gold, Ryan D.

    2012-01-01

    Three-dimensional (3D) slip vectors recorded by displaced landforms are difficult to constrain across complex fault zones, and the uncertainties associated with such measurements become increasingly challenging to assess as landforms degrade over time. We approach this problem from a remote sensing perspective by using terrestrial laser scanning (TLS) and 3D structural analysis. We have developed an integrated TLS data collection and point-based analysis workflow that incorporates accurate assessments of aleatoric and epistemic uncertainties using experimental surveys, Monte Carlo simulations, and iterative site reconstructions. Our scanning workflow and equipment requirements are optimized for single-operator surveying, and our data analysis process is largely completed using new point-based computing tools in an immersive 3D virtual reality environment. In a case study, we measured slip vector orientations at two sites along the rupture trace of the 1954 Dixie Valley earthquake (central Nevada, United States), yielding measurements that are the first direct constraints on the 3D slip vector for this event. These observations are consistent with a previous approximation of net extension direction for this event. We find that errors introduced by variables in our survey method result in <2.5 cm of variability in components of displacement, and are eclipsed by the 10–60 cm epistemic errors introduced by reconstructing the field sites to their pre-erosion geometries. Although the higher resolution TLS data sets enabled visualization and data interactivity critical for reconstructing the 3D slip vector and for assessing uncertainties, dense topographic constraints alone were not sufficient to significantly narrow the wide (<26°) range of allowable slip vector orientations that resulted from accounting for epistemic uncertainties.

  9. On-screen vector-based ultrasound assessment of vesical neck movement.

    Science.gov (United States)

    Reddy, A P; DeLancey, J O; Zwica, L M; Ashton-Miller, J A

    2001-07-01

    We sought to develop a vector-based assessment to determine the magnitude and direction of bladder neck movements, as well as to assess whether probe movement relative to the pubis needs to be taken into account. Ten nulliparous continent, 10 primiparous continent, and 10 primiparous stress-incontinent women were recruited. Perineal ultrasound scanning was performed in standing women while they were resting, performing the Valsalva maneuver, coughing, and performing Kegel exercises. A direct on-screen assessment of bladder neck displacement from rest to the peak of dynamic activity relative to the pubic axis was made. Transducer movement was assessed by measuring the displacement of the pubic bone. The method was feasible because measurements were possible in all 30 subjects. Vesical neck and pubic point movement in millimeters (+/- SD) and the percentage error if pubic point movement is not accounted for are as follow: strain, vesical neck 16.9 +/- 6.1 and pubic point 4.8 +/- 3.9, 28%; cough, vesical neck 10.2 +/- 5.4, pubic point 2.9 +/- 3.4, 33%; Kegel exercise, vesical neck 7.0 +/- 3.6 and pubic point 0.7 +/- 1.4, 37%. Similar discrepancies in angle were found and are presented. Uncorrected direction of vesical neck and pubic point movement in degrees and the percentage error if pubic point movement is not accounted for are as follow: strain, vesical neck 169.4 +/- 18.5 and pubic point 214.0 +/- 56.7, 18%; cough, vesical neck 162.0 +/- 12.8, pubic point 238.4 +/- 27.4, 22%; Kegel exercise, vesical neck -0.9 +/- 12.7 and pubic point -4.8 +/- 20.6, 87%. Test-retest reliability correlations were more than an r value of 0.7 in all measures and 86% of the measurements greater than 0.8. The vector-based system provides a simple method for quantifying distance and direction of vesical neck motion, as well as localizing the resting vesical neck position.

  10. Herpes simplex virus type 1-based amplicon vectors for fundamental research in neurosciences and gene therapy of neurological diseases.

    Science.gov (United States)

    Jerusalinsky, Diana; Baez, María Verónica; Epstein, Alberto Luis

    2012-01-01

    Somatic manipulation of the nervous system without the involvement of the germinal line appears as a powerful counterpart of the transgenic strategy. The use of viral vectors to produce specific, transient and localized knockout, knockdown, ectopic expression or overexpression of a gene, leads to the possibility of analyzing both in vitro and in vivo molecular basis of neural function. In this approach, viral particles engineered to carry transgenic sequences are delivered into discrete brain regions, to transduce cells that will express the transgenic products. Amplicons are replication-incompetent helper-dependent vectors derived from herpes simplex virus type 1 (HSV-1), with several advantages that potentiate their use in neurosciences: (1) minimal toxicity: amplicons do not encode any virus proteins, are neither toxic for the infected cells nor pathogenic for the inoculated animals and elicit low levels of adaptive immune responses; (2) extensive transgene capacity to carry up to 150-kb of foreign DNA; i.e., entire genes with regulatory sequences could be delivered; (3) widespread cellular tropism: amplicons can experimentally infect several cell types including glial cells, though naturally the virus infects mainly neurons and epithelial cells; (4) since the viral genome does not integrate into cellular chromosomes there is low probability to induce insertional mutagenesis. Recent investigations on gene transfer into the brain using these vectors, have focused on gene therapy of inherited genetic diseases affecting the nervous system, such as ataxias, or on neurodegenerative disorders using experimental models of Parkinson's or Alzheimer's disease. Another group of studies used amplicons to investigate complex neural functions such as neuroplasticity, anxiety, learning and memory. In this short review, we summarize recent data supporting the potential of HSV-1 based amplicon vector model for gene delivery and modulation of gene expression in primary cultures

  11. Frequency-agile vector signal generation based on optical frequency comb and pre-coding

    Science.gov (United States)

    Qu, Kun; Zhao, ShangHong; Tan, QingGui; Liang, DanYa

    2017-06-01

    In this paper, we experimentally demonstrate the generation of frequency-agile vector signals based on an optical frequency comb (OFC) and unbalanced pre-coding technology by employing a dual-driven Mach-Zehnder Modulator (DD-MZM) and an intensity modulator (IM). The OFC is generated by the DD-MZM and sent to the IM as a carrier. The IM is driven by a 5 GHz 2 Gbaud quadrature phase-shift keying (QPSK) vector signal with unbalanced pre-coding. The -1st order sideband of one OFC line and the +1st order sideband of another OFC line are selected by a programmable pulse shaper (PPS), after square-low photodiode detection, the frequency-agile vector signal can be obtained. The results show that the 2 Gbaud QPSK vector signals at 30 GHz, 50 GHz, 70 GHz and 90 GHz can be generated by only pre-coding once. It is possible to achieve a bit-error-rate (BER) below 1e-3 for wireless transmissions over 0.5 m using this method.

  12. Assembly of pseudorabies virus genome-based transfer vehicle carrying major antigen sites of S gene of transmissible gastroenteritis virus: potential perspective for developing live vector vaccines.

    Science.gov (United States)

    Yin, Jiechao; Ren, Xiaofeng; Tian, Zhijun; Li, Yijing

    2007-03-01

    Two severe porcine infectious diseases, pseudorabies (PR) and transmissible gastroenteritis (TGE) caused by pseudorabies virus (PRV) and transmissible gastroenteritis virus (TGEV) respectively often result in serious economic loss in animal husbandry worldwide. Vaccination is the important prevention means against both infections. To achieve a PRV genome-based virus live vector, aiming at further TGEV/PRV bivalent vaccine development, a recombinant plasmid pUG was constructed via inserting partial PK and full-length gG genes of PRV strain Bartha K-61 amplified into pUC119 vector. In parallel, another recombinant pHS was generated by introducing a fragment designated S1 encoding the major antigen sites of S gene from TGEV strain TH-98 into a prokaryotic expression vector pP(RO)EX HTc. The SV40 polyA sequence was then inserted into the downstream of S1 fragment of pHS. The continuous region containing S1fragment, SV40 polyA and four single restriction enzyme sites digested from pHS was subcloned into the downstream of gG promoter of pUG. In addition, a LacZ reporter gene was introduced into the universal transfer vector named pUGS-LacZ. Subsequently, a PRV genome-based virus live vector was generated via homologous recombination. The functionally effective vector was purified and partially characterized. Moreover, the potential advantages of this system are discussed.

  13. Lentiviral vectors as tools to understand central nervous system biology in mammalian model organisms.

    Science.gov (United States)

    Parr-Brownlie, Louise C; Bosch-Bouju, Clémentine; Schoderboeck, Lucia; Sizemore, Rachel J; Abraham, Wickliffe C; Hughes, Stephanie M

    2015-01-01

    Lentiviruses have been extensively used as gene delivery vectors since the mid-1990s. Usually derived from the human immunodeficiency virus genome, they mediate efficient gene transfer to non-dividing cells, including neurons and glia in the adult mammalian brain. In addition, integration of the recombinant lentiviral construct into the host genome provides permanent expression, including the progeny of dividing neural precursors. In this review, we describe targeted vectors with modified envelope glycoproteins and expression of transgenes under the regulation of cell-selective and inducible promoters. This technology has broad utility to address fundamental questions in neuroscience and we outline how this has been used in rodents and primates. Combining viral tract tracing with immunohistochemistry and confocal or electron microscopy, lentiviral vectors provide a tool to selectively label and trace specific neuronal populations at gross or ultrastructural levels. Additionally, new generation optogenetic technologies can be readily utilized to analyze neuronal circuit and gene functions in the mature mammalian brain. Examples of these applications, limitations of current systems and prospects for future developments to enhance neuroscience knowledge will be reviewed. Finally, we will discuss how these vectors may be translated from gene therapy trials into the clinical setting.

  14. Transformer fault diagnosis based on chemical reaction optimization algorithm and relevance vector machine

    Directory of Open Access Journals (Sweden)

    Luo Wei

    2017-01-01

    Full Text Available Power transformer is one of the most important equipment in power system. In order to predict the potential fault of power transformer and identify the fault types correctly, we proposed a transformer fault intelligent diagnosis model based on chemical reaction optimization (CRO algorithm and relevance vector machine(RVM. RVM is a powerful machine learning method, which can solve nonlinear, high-dimensional classification problems with a limited number of samples. CRO algorithm has well global optimization and simple calculation, so it is suitable to solve parameter optimization problems. In this paper, firstly, a multi-layer RVM classification model was built by binary tree recognition strategy. Secondly, CRO algorithm was adopted to optimize the kernel function parameters which could enhance the performance of RVM classifiers. Compared with IEC three-ratio method and the RVM model, the CRO-RVM model not only overcomes the coding defect problem of IEC three-ratio method, but also has higher classification accuracy than the RVM model. Finally, the new method was applied to analyze a transformer fault case, Its predicted result accord well with the real situation. The research provides a practical method for transformer fault intelligent diagnosis and prediction.

  15. Very low speed performance of active flux based sensorless control: interior permanent magnet synchronous motor vector control versus direct torque and flux control

    DEFF Research Database (Denmark)

    Paicu, M. C.; Boldea, I.; Andreescu, G. D.

    2009-01-01

    This study is focused on very low speed performance comparison between two sensorless control systems based on the novel ‘active flux' concept, that is, the current/voltage vector control versus direct torque and flux control (DTFC) for interior permanent magnet synchronous motor (IPMSM) drives...... with space vector modulation (SVM), without signal injection. The active flux, defined as the flux that multiplies iq current in the dq-model torque expression of all ac machines, is easily obtained from the stator-flux vector and has the rotor position orientation. Therefore notable simplification...... in the rotor position and speed estimation is obtained. For IPMSM, a stator-flux observer is employed based on combined current and voltage models, with speed-dependent smooth transition between them using a PI compensator of flux error. Comparative experimental results using both sensorless control systems...

  16. Dorsolateral Striatal Lesions Impair Navigation Based on Landmark-Goal Vectors but Facilitate Spatial Learning Based on a "Cognitive Map"

    Science.gov (United States)

    Kosaki, Yutaka; Poulter, Steven L.; Austen, Joe M.; McGregor, Anthony

    2015-01-01

    In three experiments, the nature of the interaction between multiple memory systems in rats solving a variation of a spatial task in the water maze was investigated. Throughout training rats were able to find a submerged platform at a fixed distance and direction from an intramaze landmark by learning a landmark-goal vector. Extramaze cues were…

  17. Development of a plant viral-vector-based gene expression assay for the screening of yeast cytochrome p450 monooxygenases.

    Science.gov (United States)

    Hanley, Kathleen; Nguyen, Long V; Khan, Faizah; Pogue, Gregory P; Vojdani, Fakhrieh; Panda, Sanjay; Pinot, Franck; Oriedo, Vincent B; Rasochova, Lada; Subramanian, Mani; Miller, Barbara; White, Earl L

    2003-02-01

    Development of a gene discovery tool for heterologously expressed cytochrome P450 monooxygenases has been inherently difficult. The activity assays are labor-intensive and not amenable to parallel screening. Additionally, biochemical confirmation requires coexpression of a homologous P450 reductase or complementary heterologous activity. Plant virus gene expression systems have been utilized for a diverse group of organisms. In this study we describe a method using an RNA vector expression system to phenotypically screen for cytochrome P450-dependent fatty acid omega-hydroxylase activity. Yarrowia lipolytica CYP52 gene family members involved in n-alkane assimilation were amplified from genomic DNA, cloned into a plant virus gene expression vector, and used as a model system for determining heterologous expression. Plants infected with virus vectors expressing the yeast CYP52 genes (YlALK1-YlALK7) showed a distinct necrotic lesion phenotype on inoculated plant leaves. No phenotype was detected on negative control constructs. YlALK3-, YlALK5-, and YlALK7-inoculated plants all catalyzed the terminal hydroxylation of lauric acid as confirmed using thin-layer and gas chromatography/mass spectrometry methods. The plant-based cytochrome P450 phenotypic screen was tested on an n-alkane-induced Yarrowia lipolytica plant virus expression library. A subset of 1,025 random library clones, including YlALK1-YlALK7 constructs, were tested on plants. All YlALK gene constructs scored positive in the randomized screen. Following nucleotide sequencing of the clones that scored positive using a phenotypic screen, approximately 5% were deemed appropriate for further biochemical analysis. This report illustrates the utility of a plant-based system for expression of heterologous cytochrome P450 monooxygenases and for the assignment of gene function.

  18. Multimodal biometric authentication based on score level fusion using support vector machine

    Science.gov (United States)

    Wang, F.; Han, J.

    2009-03-01

    Fusion of multiple biometrics for human authentication performance improvement has received considerable attention. This paper presents a novel multimodal biometric authentication method integrating face and iris based on score level fusion. For score level fusion, support vector machine (SVM) based fusion rule is applied to combine two matching scores, respectively from Laplacianface based face verifier and phase information based iris verifier, to generate a single scalar score which is used to make the final decision. Experimental results show that the performance of the proposed method can bring obvious improvement comparing to the unimodal biometric identification methods and the previous fused face-iris methods.

  19. Differential Inequalities for One Component of Solution Vector for Systems of Linear Functional Differential Equations

    Directory of Open Access Journals (Sweden)

    Domoshnitsky Alexander

    2010-01-01

    Full Text Available The method to compare only one component of the solution vector of linear functional differential systems, which does not require heavy sign restrictions on their coefficients, is proposed in this paper. Necessary and sufficient conditions of the positivity of elements in a corresponding row of Green's matrix are obtained in the form of theorems about differential inequalities. The main idea of our approach is to construct a first order functional differential equation for the th component of the solution vector and then to use assertions about positivity of its Green's functions. This demonstrates the importance to study scalar equations written in a general operator form, where only properties of the operators and not their forms are assumed. It should be also noted that the sufficient conditions, obtained in this paper, cannot be improved in a corresponding sense and does not require any smallness of the interval , where the system is considered.

  20. PREPARATION OF PLANT TRANSFORMATION VECTOR CONTAINING “SELF-EXCISION” CRE/LOXP SYSTEM

    Directory of Open Access Journals (Sweden)

    Jana Moravčíková

    2012-02-01

    Full Text Available This work is focused on preparation of the plant transformation vector pZP6 containing “self-excision” Cre/loxP system. The T-DNA of binary vector consists of the cre recombinase gene driven by the Arabidopsis DLL promoter and the nptII expression unit flanked by two loxP sites in direct orientation. The gus reporter gene controlled by the double CaMV 35S promoter was placed out of the loxP embedded DNA. To confirm functionality of the Cre/loxP system, the pZP6 was analyzed for correct removal of the loxP embedded sequence in E. coli. The pZP6 was transformed into two bacterial strains A. tumefaciens AGLO and LBA 4404. Its stability in agrobacteria was evaluated by restriction analyses.

  1. HSV-1-Based Vectors for Gene Therapy of Neurological Diseases and Brain Tumors: Part I. HSV-1 Structure, Replication and Pathogenesis

    Directory of Open Access Journals (Sweden)

    Andreas Jacobs

    1999-11-01

    Full Text Available The design of effective gene therapy strategies for brain tumors and other neurological disorders relies on the understanding of genetic and pathophysiological alterations associated with the disease, on the biological characteristics of the target tissue, and on the development of safe vectors and expression systems to achieve efficient, targeted and regulated, therapeutic gene expression. The herpes simplex virus type 1 (HSV-1 virion is one of the most efficient of all current gene transfer vehicles with regard to nuclear gene delivery in central nervous system-derived cells including brain tumors. HSV-1-related research over the past decades has provided excellent insight into the structure and function of this virus, which, in turn, facilitated the design of innovative vector systems. Here, we review aspects of HSV-1 structure, replication and pathogenesis, which are relevant for the engineering of HSV-1-based vectors.

  2. Comparative Visualization of Vector Field Ensembles Based on Longest Common Subsequence

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Richen; Guo, Hanqi; Zhang, Jiang; Yuan, Xiaoru

    2016-04-19

    We propose a longest common subsequence (LCS) based approach to compute the distance among vector field ensembles. By measuring how many common blocks the ensemble pathlines passing through, the LCS distance defines the similarity among vector field ensembles by counting the number of sharing domain data blocks. Compared to the traditional methods (e.g. point-wise Euclidean distance or dynamic time warping distance), the proposed approach is robust to outlier, data missing, and sampling rate of pathline timestep. Taking the advantages of smaller and reusable intermediate output, visualization based on the proposed LCS approach revealing temporal trends in the data at low storage cost, and avoiding tracing pathlines repeatedly. Finally, we evaluate our method on both synthetic data and simulation data, which demonstrate the robustness of the proposed approach.

  3. Biosafety aspects of modified vaccinia virus Ankara (MVA)-based vectors used for gene therapy or vaccination.

    Science.gov (United States)

    Verheust, Céline; Goossens, Martine; Pauwels, Katia; Breyer, Didier

    2012-03-30

    The modified vaccinia virus Ankara (MVA) strain is a highly attenuated strain of vaccinia virus that has been demonstrated to be safe for humans. MVA is widely considered as the vaccinia virus strain of choice for clinical investigation because of its high safety profile. It also represents an excellent candidate for use as vector system in recombinant vaccine development for gene delivery or vaccination against infectious diseases or tumours, even in immunocompromised individuals. The use of MVA and recombinant MVA vectors must comply with various regulatory requirements, particularly relating to the assessment of potential risks for human health and the environment. The purpose of the present paper is to highlight some biological characteristics of MVA and MVA-based recombinant vectors and to discuss these from a biosafety point of view in the context of the European regulatory framework for genetically modified organisms with emphasis on the assessment of potential risks associated with environmental release. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. An MR Brain Images Classifier System via Particle Swarm Optimization and Kernel Support Vector Machine

    OpenAIRE

    Yudong Zhang; Shuihua Wang; Genlin Ji; Zhengchao Dong

    2013-01-01

    Automated abnormal brain detection is extremely of importance for clinical diagnosis. Over last decades numerous methods had been presented. In this paper, we proposed a novel hybrid system to classify a given MR brain image as either normal or abnormal. The proposed method first employed digital wavelet transform to extract features then used principal component analysis (PCA) to reduce the feature space. Afterwards, we constructed a kernel support vector machine (KSVM) with RBF kernel, usin...

  5. Space vector-based modeling and control of a modular multilevel converter in HVDC applications

    DEFF Research Database (Denmark)

    Bonavoglia, M.; Casadei, G.; Zarri, L.

    2013-01-01

    Modular multilevel converter (MMC) is an emerging multilevel topology for high-voltage applications that has been developed in recent years. In this paper, the modeling and the control of MMCs are restated in terms of space vectors, which may allow a deeper understanding of the converter behavior....... As a result, a control scheme for three-phase MMCs based on the previous theoretical analysis is presented. Numerical simulations are used to test its feasibility....

  6. An Open-Loop Vector Receiver Architecture for GNSS-Based Scintillation Monitoring

    OpenAIRE

    CURRAN JAMES THOMAS; BAVARO MICHELE; FORTUNY GUASCH Joaquim

    2014-01-01

    GNSS-based studies of the ionosphere are typically conducted using navigation receivers which track both the carrier and code phase either on a satellite-by-satellite basis, or collectively via a vector structure [3]. Information relating to phase and amplitude scintillation is gathered from the receiver’s estimate of the carrier phase and the receiver correlators values, respectively. The quality of these parameters, however, is directly influenced by how well the receiver can track the GNSS...

  7. A DSP-based discrete space vector modulation direct torque control of sensorless induction machines

    Energy Technology Data Exchange (ETDEWEB)

    Khoucha, F.; Marouani, K.; Kheloui, A.; Aliouane, K.

    2004-07-01

    In this paper, we present a Direct Torque Control scheme of an induction motor operating without speed sensor. The estimation of the stator flux and the rotor speed is performed by an adaptive observer. In order to reduce the torque, flux, current and speed ripple a Discrete Space Vector Modulation (DSVM-DTC) strategy is implemented using a DSP-based hardware. To illustrate the performances of this control scheme, experimental results are presented. (author)

  8. Quantifying Similarity and Distance Measures for Vector-Based Datasets: Histograms, Signals, and Probability Distribution Functions

    Science.gov (United States)

    2017-02-01

    documents. Citation of manufacturer’s or trade names does not constitute an official endorse- ment or approval of the use thereof. Destroy this report when it...note, a number of different measures implemented in both MATLAB and Python as functions are used to quantify similarity/distance between 2 vector-based...datasets. The scripts are attached as appendixes as is a description of their execution. Python , MATLAB, similarity, distance, X-ray diffraction 40

  9. Capsid Engineering of Adenovirus Vectors: Overcoming Early Vector-Host Interactions for Therapy.

    Science.gov (United States)

    Hagedorn, Claudia; Kreppel, Florian

    2017-10-01

    Adenovirus-based vectors comprise the most frequently used vector type in clinical studies to date. Both intense lab research and insights from the clinical trials reveal the importance of a comprehensive understanding of vector-host interactions. Especially for systemic intravenous adenovirus vector delivery, it is paramount to develop safe and efficacious vectors. Very early vector-host interactions that take place in blood long before the first cell is being transduced are phenomena triggered by the surface, shape, and size of the adenovirus vector particles. Not surprisingly, a multitude of different technologies ranging from genetics to chemistry has been developed to alter the adenovirus vector surface. In this review, we discuss the most important technologies and evaluate them for their suitability to overcome hurdles imposed by early vector-host interactions.

  10. A Matrix-Based Structure for Vario-Scale Vector Representation over a Wide Range of Map Scales : The Case of River Network Data

    NARCIS (Netherlands)

    Huang, L.; Ai, Tinghua; van Oosterom, P.J.M.; Yan, Xiongfeng; Yang, Min

    2017-01-01

    The representation of vector data at variable scales has been widely applied in geographic information systems and map-based services. When the scale changes across a wide range, a complex generalization that involves multiple operations is required to transform the data. To present such complex

  11. A vector-based, 5-electrode, 12-lead monitoring ECG (EASI) is equivalent to conventional 12-lead ECG for diagnosis of acute coronary syndromes

    NARCIS (Netherlands)

    Wehr, Gabriele; Peters, Ron J.; Khalifé, Khalifé; Banning, Adrian P.; Kuehlkamp, Volker; Rickards, Anthony F.; Sechtem, Udo

    2006-01-01

    AIMS: The conventional 12-lead electrocardiogram (cECG) derived from 10 electrodes using a cardiograph is the gold standard for diagnosing myocardial ischemia. This study tested the hypothesis that a new 5-electrode 12-lead vector-based ECG (EASI; Philips Medical Systems, formerly Hewlett Packard

  12. Network-based support vector machine for classification of microarray samples.

    Science.gov (United States)

    Zhu, Yanni; Shen, Xiaotong; Pan, Wei

    2009-01-30

    The importance of network-based approach to identifying biological markers for diagnostic classification and prognostic assessment in the context of microarray data has been increasingly recognized. To our knowledge, there have been few, if any, statistical tools that explicitly incorporate the prior information of gene networks into classifier building. The main idea of this paper is to take full advantage of the biological observation that neighboring genes in a network tend to function together in biological processes and to embed this information into a formal statistical framework. We propose a network-based support vector machine for binary classification problems by constructing a penalty term from the Finfinity-norm being applied to pairwise gene neighbors with the hope to improve predictive performance and gene selection. Simulation studies in both low- and high-dimensional data settings as well as two real microarray applications indicate that the proposed method is able to identify more clinically relevant genes while maintaining a sparse model with either similar or higher prediction accuracy compared with the standard and the L1 penalized support vector machines. The proposed network-based support vector machine has the potential to be a practically useful classification tool for microarrays and other high-dimensional data.

  13. Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields

    KAUST Repository

    Skraba, Primoz

    2015-08-01

    © 2015 IEEE. Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness which enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory and has minimal boundary restrictions. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. We show local and complete hierarchical simplifications for steady as well as unsteady vector fields.

  14. Inductance and Active Phase Vector Based Torque Control for Switched Reluctance Motor Drives.

    Science.gov (United States)

    Kalpathi, Ramani Raman

    The Switched Reluctance Motor (SRM) drive technology has developed significantly over the last few years. The simplicity in both motor design and power converter requirement along with the availability of high frequency, high power semiconductor switches have made SRMs compete with conventional adjustable speed drive technologies. The subject of winding current control in switched reluctance machines has always been associated with the shaft position information. The use of inductance for direct commutation control is the central subject of this dissertation. In contrast to the conventional methods based on position commutation, new methods of control based on inductance commutation are presented. The object of a commutation algorithm is to switch the currents in the phase coils, in order to provide continuous energy conversion with maximum torque output for a given unit of input current. Since torque production in a SRM is based on the concept of variable reluctance, it makes more sense to observe the instantaneous phase inductance or reluctance instead of estimating the rotor position. The inductance sensors observe the machine parameters and provide sufficient information on the electrical characteristics of the coils. This control strategy avoids the inductance to position transformation blocks conventionally used in SRM control systems. In a typical SRM, the phase coils have a nonlinear behavior of inductance due to effects of current saturation. Also the parameters of one phase coil differ from those of the other due to manufacturing tolerances or due to bearing wear. In such cases, the algorithms written during the stage of manufacturing may not be valid after parameter changes. Optimizing torque production in the event of phase asymmetry and saturation is developed in this research. Indirect sensors connected to the active phase coil of the SRM are based on sensing the flux level in the active coil. New commutation algorithms based on flux sensing concepts

  15. A Novel Rotor and Stator Magnetic Fields Direct-Orthogonalized Vector Control Scheme for the PMSM Servo System

    Directory of Open Access Journals (Sweden)

    Shi-Xiong Zhang

    2014-02-01

    Full Text Available Permanent Magnet Synchronous motor (PMSM has received widespread acceptance in recent years. In this paper, a new rotor and stator Magnetic Fields Direct-Orthogonalized Vector Control (MFDOVC scheme is proposed for PMSM servo system. This method simplified the complex calculation of traditional vector control, a part of the system resource is economized. At the same time, through the simulation illustration validation, the performance of PMSM servo system with the proposed MFDOVC scheme can achieve the same with the complex traditional vector control method, but much simpler calculation is implemented using the proposed method.

  16. An Improved Endmember Selection Method Based on Vector Length for MODIS Reflectance Channels

    Directory of Open Access Journals (Sweden)

    Yuanliu Xu

    2015-05-01

    Full Text Available Endmember selection is the basis for sub-pixel land cover classifications using multiple endmember spectral mixture analysis (MESMA that adopts variant endmember matrices for each pixel to mitigate errors caused by endmember variability in SMA. A spectral library covering a large number of endmembers can account for endmember variability, but it also lowers the computational efficiency. Therefore, an efficient endmember selection scheme to optimize the library is crucial to implement MESMA. In this study, we present an endmember selection method based on vector length. The spectra of a land cover class were divided into subsets using vector length intervals of the spectra, and the representative endmembers were derived from these subsets. Compared with the available endmember average RMSE (EAR method, our approach improved the computational efficiency in endmember selection. The method accuracy was further evaluated using spectral libraries derived from the ground reference polygon and Moderate Resolution Imaging Spectroradiometer (MODIS imagery respectively. Results using the different spectral libraries indicated that MESMA combined with the new approach performed slightly better than EAR method, with Kappa coefficient improved from 0.75 to 0.78. A MODIS image was used to test the mapping fraction, and the representative spectra based on vector length successfully modeled more than 90% spectra of the MODIS pixels by 2-endmember models.

  17. [Automatic classification method of star spectra data based on manifold fuzzy twin support vector machine].

    Science.gov (United States)

    Liu, Zhong-bao; Gao, Yan-yun; Wang, Jian-zhen

    2015-01-01

    Support vector machine (SVM) with good leaning ability and generalization is widely used in the star spectra data classification. But when the scale of data becomes larger, the shortages of SVM appear: the calculation amount is quite large and the classification speed is too slow. In order to solve the above problems, twin support vector machine (TWSVM) was proposed by Jayadeva. The advantage of TSVM is that the time cost is reduced to 1/4 of that of SVM. While all the methods mentioned above only focus on the global characteristics and neglect the local characteristics. In view of this, an automatic classification method of star spectra data based on manifold fuzzy twin support vector machine (MF-TSVM) is proposed in this paper. In MF-TSVM, manifold-based discriminant analysis (MDA) is used to obtain the global and local characteristics of the input data and the fuzzy membership is introduced to reduce the influences of noise and singular data on the classification results. Comparative experiments with current classification methods, such as C-SVM and KNN, on the SDSS star spectra datasets verify the effectiveness of the proposed method.

  18. Analysis of Distribution of Vector-Borne Diseases Using Geographic Information Systems.

    Science.gov (United States)

    Nihei, Naoko

    2017-01-01

    The distribution of vector-borne diseases is changing on a global scale owing to issues involving natural environments, socioeconomic conditions and border disputes among others. Geographic information systems (GIS) provide an important method of establishing a prompt and precise understanding of local data on disease outbreaks, from which disease eradication programs can be established. Having first defined GIS as a combination of GPS, RS and GIS, we showed the processes through which these technologies were being introduced into our research. GIS-derived geographical information attributes were interpreted in terms of point, area, line, spatial epidemiology, risk and development for generating the vector dynamic models associated with the spread of the disease. The need for interdisciplinary scientific and administrative collaboration in the use of GIS to control infectious diseases is highly warranted.

  19. Spatial aliasing for efficient direction-of-arrival estimation based on steering vector reconstruction

    Science.gov (United States)

    Yan, Feng-Gang; Cao, Bin; Rong, Jia-Jia; Shen, Yi; Jin, Ming

    2016-12-01

    A new technique is proposed to reduce the computational complexity of the multiple signal classification (MUSIC) algorithm for direction-of-arrival (DOA) estimate using a uniform linear array (ULA). The steering vector of the ULA is reconstructed as the Kronecker product of two other steering vectors, and a new cost function with spatial aliasing at hand is derived. Thanks to the estimation ambiguity of this spatial aliasing, mirror angles mathematically relating to the true DOAs are generated, based on which the full spectral search involved in the MUSIC algorithm is highly compressed into a limited angular sector accordingly. Further complexity analysis and performance studies are conducted by computer simulations, which demonstrate that the proposed estimator requires an extremely reduced computational burden while it shows a similar accuracy to the standard MUSIC.

  20. Compensation method for temperature error of fiber optical gyroscope based on relevance vector machine.

    Science.gov (United States)

    Wang, Guochen; Wang, Qiuying; Zhao, Bo; Wang, Zhenpeng

    2016-02-10

    Aiming to improve the bias stability of the fiber optical gyroscope (FOG) in an ambient temperature-change environment, a temperature-compensation method based on the relevance vector machine (RVM) under Bayesian framework is proposed and applied. Compared with other temperature models such as quadratic polynomial regression, neural network, and the support vector machine, the proposed RVM method possesses higher accuracy to explain the temperature dependence of the FOG gyro bias. Experimental results indicate that, with the proposed RVM method, the bias stability of an FOG can be apparently reduced in the whole temperature ranging from -40°C to 60°C. Therefore, the proposed method can effectively improve the adaptability of the FOG in a changing temperature environment.

  1. Multiwavelength mode-locked cylindrical vector beam fiber laser based on mode selective coupler

    Science.gov (United States)

    Huang, Ping; Cai, Yu; Wang, Jie; Wan, Hongdan; Zhang, Zuxing; Zhang, Lin

    2017-10-01

    We propose and demonstrate a multiwavelength mode-locked fiber laser with cylindrical vector beam generation for the first time, to the best of our knowledge. The mode-locking mechanism is based on a nonlinear polarization rotation effect in fiber, and the multiwavelength operation is contributed to by an in-line birefringence fiber filter with periodic multiple passbands, formed by incorporating a section of polarization maintaining fiber into the laser cavity with a fiber polarizer. Furthermore, by using a home-made mode selective coupler, which acts as both a mode converter from fundamental mode to higher-order mode and an output coupler, multiwavelength mode-locked cylindrical vector beams have been obtained. This may have potential applications in mode-division multiplexing optical fiber communication and material processing.

  2. Gateway-compatible vectors for high-throughput protein expression in pro- and eukaryotic cell-free systems.

    Science.gov (United States)

    Gagoski, Dejan; Mureev, Sergey; Giles, Nichole; Johnston, Wayne; Dahmer-Heath, Mareike; Škalamera, Dubravka; Gonda, Thomas J; Alexandrov, Kirill

    2015-02-10

    Although numerous techniques for protein expression and production are available the pace of genome sequencing outstrips our ability to analyze the encoded proteins. To address this bottleneck, we have established a system for parallelized cloning, DNA production and cell-free expression of large numbers of proteins. This system is based on a suite of pCellFree Gateway destination vectors that utilize a Species Independent Translation Initiation Sequence (SITS) that mediates recombinant protein expression in any in vitro translation system. These vectors introduce C or N terminal EGFP and mCherry fluorescent and affinity tags, enabling direct analysis and purification of the expressed proteins. To maximize throughput and minimize the cost of protein production we combined Gateway cloning with Rolling Circle DNA Amplification. We demonstrate that as little as 0.1 ng of plasmid DNA is sufficient for template amplification and production of recombinant human protein in Leishmania tarentolae and Escherichia coli cell-free expression systems. Our experiments indicate that this approach can be applied to large gene libraries as it can be reliably performed in multi-well plates. The resulting protein expression pipeline provides a valuable new tool for applications of the post genomic era. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. A Wireless Electronic Nose System Using a Fe2O3 Gas Sensing Array and Least Squares Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Yingguo Cheng

    2011-01-01

    Full Text Available This paper describes the design and implementation of a wireless electronic nose (WEN system which can online detect the combustible gases methane and hydrogen (CH4/H2 and estimate their concentrations, either singly or in mixtures. The system is composed of two wireless sensor nodes—a slave node and a master node. The former comprises a Fe2O3 gas sensing array for the combustible gas detection, a digital signal processor (DSP system for real-time sampling and processing the sensor array data and a wireless transceiver unit (WTU by which the detection results can be transmitted to the master node connected with a computer. A type of Fe2O3 gas sensor insensitive to humidity is developed for resistance to environmental influences. A threshold-based least square support vector regression (LS-SVR estimator is implemented on a DSP for classification and concentration measurements. Experimental results confirm that LS-SVR produces higher accuracy compared with artificial neural networks (ANNs and a faster convergence rate than the standard support vector regression (SVR. The designed WEN system effectively achieves gas mixture analysis in a real-time process.

  4. A wireless electronic nose system using a Fe2O3 gas sensing array and least squares support vector regression.

    Science.gov (United States)

    Song, Kai; Wang, Qi; Liu, Qi; Zhang, Hongquan; Cheng, Yingguo

    2011-01-01

    This paper describes the design and implementation of a wireless electronic nose (WEN) system which can online detect the combustible gases methane and hydrogen (CH(4)/H(2)) and estimate their concentrations, either singly or in mixtures. The system is composed of two wireless sensor nodes--a slave node and a master node. The former comprises a Fe(2)O(3) gas sensing array for the combustible gas detection, a digital signal processor (DSP) system for real-time sampling and processing the sensor array data and a wireless transceiver unit (WTU) by which the detection results can be transmitted to the master node connected with a computer. A type of Fe(2)O(3) gas sensor insensitive to humidity is developed for resistance to environmental influences. A threshold-based least square support vector regression (LS-SVR)estimator is implemented on a DSP for classification and concentration measurements. Experimental results confirm that LS-SVR produces higher accuracy compared with artificial neural networks (ANNs) and a faster convergence rate than the standard support vector regression (SVR). The designed WEN system effectively achieves gas mixture analysis in a real-time process.

  5. Hierarchical Modulation with Vector Rotation for E-MBMS Transmission in LTE Systems

    Directory of Open Access Journals (Sweden)

    Hui Zhao

    2010-01-01

    Full Text Available Enhanced Multimedia Broadcast and Multicast Service (E-MBMS is considered of key importance for the proliferation of Long-Term Evolution (LTE network in mobile market. Hierarchical modulation (HM, which involves a “base-layer” (BL and an “enhancement-layer” (EL bit streams, is a simple technique for achieving tradeoff between service quality and radio coverage. Therefore, it is appealing for MBMS. Generally, HM suffers from the severe performance degradation of the less protected EL stream. In this paper, HM with vector rotation operation introduced to EL stream is proposed, in order to improve EL's performance. With the proper interleaving in frequency domain, this operation can exploit the inherent diversity gain from the multipath channel. In this way, HM with vector rotation can effectively enhance multimedia broadcasting on quality video and coverage. The simulation results with scalable video coding (SVC as source show the significant benefits in comparison with the conventional HM and alternative schemes.

  6. Power Sharing and Voltage Vector Distribution Model of a Dual Inverter Open-End Winding Motor Drive System for Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Yi-Fan Jia

    2018-02-01

    Full Text Available A drive system with an open-end winding permanent magnet synchronous motor (OW-PMSM fed by a dual inverter and powered by two independent power sources is suitable for electric vehicles. By using an energy conversion device as primary power source and an energy storage element as secondary power source, this configuration can not only lower the DC-bus voltage and extend the driving range, but also handle the power sharing between two power sources without a DC/DC (direct current to direct current converter. Based on a drive system model with voltage vector distribution, this paper proposes a desired power sharing calculation method and three different voltage vector distribution methods. By their selection strategy the optimal voltage vector distribution method can be selected according to the operating conditions. On the basis of the integral synthesizing of the desired voltage vector, the proposed voltage vector distribution method can reduce the inverter switching frequency while making the primary power source follow its desired output power. Simulation results confirm the validity of the proposed methods, which improve the primary power source’s energy efficiency by regulating its output power and lessen inverter switching loss by reducing the switching frequency. This system also provides an approach to the energy management function of electric vehicles.

  7. Forced recombination of psi-modified murine leukaemia virus-based vectors with murine leukaemia-like and VL30 murine endogenous retroviruses

    DEFF Research Database (Denmark)

    Mikkelsen, J G; Lund, Anders Henrik; Duch, M

    1999-01-01

    -impaired Akv-MLV-derived vectors, we here examine putative genetic interactions between vector RNAs and copackaged endogenous retroviral RNAs of the murine leukaemia virus (MLV) and VL30 retroelement families. We show (i) that MLV recombination is not blocked by nonhomology within the 5' untranslated region....... We note that recombination-based rescue of primer binding site knock-out retroviral vectors may constitute a sensitive assay to register putative genetic interactions involving endogenous retroviral RNAs present in cells of various species.......Co-encapsidation of retroviral RNAs into virus particles allows for the generation of recombinant proviruses through events of template switching during reverse transcription. By use of a forced recombination system based on recombinational rescue of replication- defective primer binding site...

  8. Design development of the Apollo command and service module thrust vector attitude control systems

    Science.gov (United States)

    Peters, W. H.

    1978-01-01

    Development of the Apollo thrust vector control digital autopilot (TVC DAP) was summarized. This is the control system that provided pitch and yaw attitude control during velocity change maneuvers using the main rocket engine on the Apollo service module. A list of ten primary functional requirements for this control system are presented, each being subordinate to a more general requirement appearing earlier on the list. Development process functions were then identified and the essential information flow paths were explored. This provided some visibility into the particular NASA/contractor interface, as well as relationships between the many individual activities.

  9. A simplified vector system for visualization of localized RNAs in Schizosaccharomyces pombe.

    Science.gov (United States)

    Takeuchi-Andoh, Tomoko; Ohba, Sayaka; Shinoda, Yu; Fuchita, Ayako; Hayashi, Sachiko; Nishiyoshi, Emi; Terouchi, Nobuyuki; Tani, Tokio

    2016-07-01

    RNA localization is an important event that is essential for the polarization and differentiation of a cell. Although several methods are currently used to detect localized RNAs, a simplified detection system has not yet been developed for Schizosaccharomyces pombe. In the present study, we describe a new vector system for the visualization of localized RNAs in S. pombe using a U1A-tag-GFP system. A pREP1-U1A-tag vector plasmid to express U1A-tagged RNA and a pREP2-U1AGFP plasmid to produce a U1A-GFP fusion protein were constructed for this system. Since the U1A-GFP protein binds U1A-tagged RNA, fluorescence is observed at the location of U1A-tagged RNA in cells expressing both of these. The nucleolar localization of U3 snoRNA was successfully detected using this system, and a novel RNA localized at the DNA region of the nucleus was found by screening localized RNAs. This system will accelerate the study of localized RNAs in S. pombe.

  10. Multigenic lentiviral vectors for combined and tissue-specific expression of miRNA- and protein-based antiangiogenic factors

    Directory of Open Access Journals (Sweden)

    Anne Louise Askou

    Full Text Available Lentivirus-based gene delivery vectors carrying multiple gene cassettes are powerful tools in gene transfer studies and gene therapy, allowing coexpression of multiple therapeutic factors and, if desired, fluorescent reporters. Current strategies to express transgenes and microRNA (miRNA clusters from a single vector have certain limitations that affect transgene expression levels and/or vector titers. In this study, we describe a novel vector design that facilitates combined expression of therapeutic RNA- and protein-based antiangiogenic factors as well as a fluorescent reporter from back-to-back RNApolII-driven expression cassettes. This configuration allows effective production of intron-embedded miRNAs that are released upon transduction of target cells. Exploiting such multigenic lentiviral vectors, we demonstrate robust miRNA-directed downregulation of vascular endothelial growth factor (VEGF expression, leading to reduced angiogenesis, and parallel impairment of angiogenic pathways by codelivering the gene encoding pigment epithelium-derived factor (PEDF. Notably, subretinal injections of lentiviral vectors reveal efficient retinal pigment epithelium-specific gene expression driven by the VMD2 promoter, verifying that multigenic lentiviral vectors can be produced with high titers sufficient for in vivo applications. Altogether, our results suggest the potential applicability of combined miRNA- and protein-encoding lentiviral vectors in antiangiogenic gene therapy, including new combination therapies for amelioration of age-related macular degeneration.

  11. Bidding strategy with forecast technology based on support vector machine in the electricity market

    Science.gov (United States)

    Gao, Ciwei; Bompard, Ettore; Napoli, Roberto; Wan, Qiulan; Zhou, Jian

    2008-06-01

    The participants in the electricity market are concerned very much with the market price evolution. Various technologies have been developed for price forecasting. The SVM (Support Vector Machine) has shown its good performance in market price forecasting. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecasting accuracy, with which the rejection risk is defined. The other takes into account the impact of the producer’s own bid. The risks associated with the bidding are controlled by the parameter settings. The proposed approaches have been tested on a numerical example.

  12. A Parallel Genetic Algorithm Based Feature Selection and Parameter Optimization for Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhi Chen

    2016-01-01

    Full Text Available The extensive applications of support vector machines (SVMs require efficient method of constructing a SVM classifier with high classification ability. The performance of SVM crucially depends on whether optimal feature subset and parameter of SVM can be efficiently obtained. In this paper, a coarse-grained parallel genetic algorithm (CGPGA is used to simultaneously optimize the feature subset and parameters for SVM. The distributed topology and migration policy of CGPGA can help find optimal feature subset and parameters for SVM in significantly shorter time, so as to increase the quality of solution found. In addition, a new fitness function, which combines the classification accuracy obtained from bootstrap method, the number of chosen features, and the number of support vectors, is proposed to lead the search of CGPGA to the direction of optimal generalization error. Experiment results on 12 benchmark datasets show that our proposed approach outperforms genetic algorithm (GA based method and grid search method in terms of classification accuracy, number of chosen features, number of support vectors, and running time.

  13. DEVELOPMENT OF VACCINES BASED ON ADENOVIRAL VECTORS: A REVIEW OF FOREIGN CLINICAL STUDIES (PART 2

    Directory of Open Access Journals (Sweden)

    L. V. Cherenova

    2017-01-01

    Full Text Available Currently, many human infectious diseases do not developed effective methods of treatment and prevention. One of the latest successes of biotechnology is the use of adenoviral vectors carrying immunodominant antigens  of various pathogens as genetically engineered vaccines  both  preventive and therapeutic. The use of genetic  engineering technologies allows not  to use in the  manufacture of vaccines  live viruses and  bacteria, reduces  the  time  needed for vaccine  creation and  production of new vaccines.  Adenoviral vectors  naturally penetrate into human cells, causing a rather  long and significant  both humoral and cellular immune response. In the second  part of review, we provide  information about  the ongoing  worldwide  clinical  trials of adenoviral vector-based vaccines against various infectious diseases such as influenza, malaria, Ebola haemorrhagic fever, tuberculosis, hepatitis and  several others, like as to consider selection parameters of volunteers, vaccination schedule, doses of drug administration, results of completed experiments, and preliminary data  on currently ongoing  research.

  14. Immunogenicity of ORFV-based vectors expressing the rabies virus glycoprotein in livestock species.

    Science.gov (United States)

    Martins, Mathias; Joshi, Lok R; Rodrigues, Fernando S; Anziliero, Deniz; Frandoloso, Rafael; Kutish, Gerald F; Rock, Daniel L; Weiblen, Rudi; Flores, Eduardo F; Diel, Diego G

    2017-11-01

    The parapoxvirus Orf virus (ORFV) encodes several immunomodulatory proteins (IMPs) that modulate host-innate and pro-inflammatory responses and has been proposed as a vaccine delivery vector for use in animal species. Here we describe the construction and characterization of two recombinant ORFV vectors expressing the rabies virus (RABV) glycoprotein (G). The RABV-G gene was inserted in the ORFV024 or ORFV121 gene loci, which encode for IMPs that are unique to parapoxviruses and inhibit activation of the NF-κB signaling pathway. The immunogenicity of the resultant recombinant viruses (ORFV∆024RABV-G or ORFV∆121RABV-G, respectively) was evaluated in pigs and cattle. Immunization of the target species with ORFV∆024RABV-G and ORFV∆121RABV-G elicited robust neutralizing antibody responses against RABV. Notably, neutralizing antibody titers induced in ORFV∆121RABV-G-immunized pigs and cattle were significantly higher than those detected in ORFV∆024RABV-G-immunized animals, indicating a higher immunogenicity of ORFVΔ121-based vectors in these animal species. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Support vector machine based fault classification and location of a long transmission line

    Directory of Open Access Journals (Sweden)

    Papia Ray

    2016-09-01

    Full Text Available This paper investigates support vector machine based fault type and distance estimation scheme in a long transmission line. The planned technique uses post fault single cycle current waveform and pre-processing of the samples is done by wavelet packet transform. Energy and entropy are obtained from the decomposed coefficients and feature matrix is prepared. Then the redundant features from the matrix are taken out by the forward feature selection method and normalized. Test and train data are developed by taking into consideration variables of a simulation situation like fault type, resistance path, inception angle, and distance. In this paper 10 different types of short circuit fault are analyzed. The test data are examined by support vector machine whose parameters are optimized by particle swarm optimization method. The anticipated method is checked on a 400 kV, 300 km long transmission line with voltage source at both the ends. Two cases were examined with the proposed method. The first one is fault very near to both the source end (front and rear and the second one is support vector machine with and without optimized parameter. Simulation result indicates that the anticipated method for fault classification gives high accuracy (99.21% and least fault distance estimation error (0.29%.

  16. An Adaptive Support Vector Regression Machine for the State Prognosis of Mechanical Systems

    Directory of Open Access Journals (Sweden)

    Qing Zhang

    2015-01-01

    Full Text Available Due to the unsteady state evolution of mechanical systems, the time series of state indicators exhibits volatile behavior and staged characteristics. To model hidden trends and predict deterioration failure utilizing volatile state indicators, an adaptive support vector regression (ASVR machine is proposed. In ASVR, the width of an error-insensitive tube, which is a constant in the traditional support vector regression, is set as a variable determined by the transient distribution boundary of local regions in the training time series. Thus, the localized regions are obtained using a sliding time window, and their boundaries are defined by a robust measure known as the truncated range. Utilizing an adaptive error-insensitive tube, a stabilized tolerance level for noise is achieved, whether the time series occurs in low-volatility regions or in high-volatility regions. The proposed method is evaluated by vibrational data measured on descaling pumps. The results show that ASVR is capable of capturing the local trends of the volatile time series of state indicators and is superior to the standard support vector regression for state prediction.

  17. Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks.

    Science.gov (United States)

    Hartemink, Nienke; Vanwambeke, Sophie O; Purse, Bethan V; Gilbert, Marius; Van Dyck, Hans

    2015-11-01

    Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical-statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially explicit; both methods ignore the way animals use the landscape (i.e. movement ecology). We argue that applying a functional concept for habitat, i.e. the resource-based habitat concept (RBHC), can solve these issues. The RBHC offers a framework to identify systematically the different ecological resources that are necessary for the completion of the transmission cycle and to relate these resources to (combinations of) landscape features and other environmental factors. The potential of the RBHC as a framework for identifying suitable habitats for vector-borne pathogens is explored and illustrated with the case of bluetongue virus, a midge-transmitted virus affecting ruminants. The concept facilitates the study of functional habitats of the interacting species (vectors as well as hosts) and provides new insight into spatial and temporal variation in transmission opportunities and exposure that ultimately determine disease risks. It may help to identify knowledge gaps and control options arising from changes in the spatial configuration of key resources across the landscape. The RBHC framework may act as a bridge between existing mechanistic and statistical modelling approaches. © 2014 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

  18. Mining protein function from text using term-based support vector machines

    Science.gov (United States)

    Rice, Simon B; Nenadic, Goran; Stapley, Benjamin J

    2005-01-01

    Background Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents. Results The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent. Conclusion A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2. PMID:15960835

  19. Optimization of a one-step heat-inducible in vivo mini DNA vector production system.

    Directory of Open Access Journals (Sweden)

    Nafiseh Nafissi

    Full Text Available While safer than their viral counterparts, conventional circular covalently closed (CCC plasmid DNA vectors offer a limited safety profile. They often result in the transfer of unwanted prokaryotic sequences, antibiotic resistance genes, and bacterial origins of replication that may lead to unwanted immunostimulatory responses. Furthermore, such vectors may impart the potential for chromosomal integration, thus potentiating oncogenesis. Linear covalently closed (LCC, bacterial sequence free DNA vectors have shown promising clinical improvements in vitro and in vivo. However, the generation of such minivectors has been limited by in vitro enzymatic reactions hindering their downstream application in clinical trials. We previously characterized an in vivo temperature-inducible expression system, governed by the phage λ pL promoter and regulated by the thermolabile λ CI[Ts]857 repressor to produce recombinant protelomerase enzymes in E. coli. In this expression system, induction of recombinant protelomerase was achieved by increasing culture temperature above the 37°C threshold temperature. Overexpression of protelomerase led to enzymatic reactions, acting on genetically engineered multi-target sites called "Super Sequences" that serve to convert conventional CCC plasmid DNA into LCC DNA minivectors. Temperature up-shift, however, can result in intracellular stress responses and may alter plasmid replication rates; both of which may be detrimental to LCC minivector production. We sought to optimize our one-step in vivo DNA minivector production system under various induction schedules in combination with genetic modifications influencing plasmid replication, processing rates, and cellular heat stress responses. We assessed different culture growth techniques, growth media compositions, heat induction scheduling and temperature, induction duration, post-induction temperature, and E. coli genetic background to improve the productivity and

  20. Asymptotic stability and instability of large-scale systems. [using vector Liapunov functions

    Science.gov (United States)

    Grujic, L. T.; Siljak, D. D.

    1973-01-01

    The purpose of this paper is to develop new methods for constructing vector Lyapunov functions and broaden the application of Lyapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. By redefining interconnection functions among the subsystems according to interconnection matrices, the same mathematical machinery can be used to determine connective asymptotic stability of large-scale systems under arbitrary structural perturbations.

  1. A graph kernel based on context vectors for extracting drug-drug interactions.

    Science.gov (United States)

    Zheng, Wei; Lin, Hongfei; Zhao, Zhehuan; Xu, Bo; Zhang, Yijia; Yang, Zhihao; Wang, Jian

    2016-06-01

    The clinical recognition of drug-drug interactions (DDIs) is a crucial issue for both patient safety and health care cost control. Thus there is an urgent need that DDIs be extracted automatically from biomedical literature by text-mining techniques. Although the top-ranking DDIs systems explore various features of texts, these features can't yet adequately express long and complicated sentences. In this paper, we present an effective graph kernel which makes full use of different types of contexts to identify DDIs from biomedical literature. In our approach, the relations among long-range words, in addition to close-range words, are obtained by the graph representation of a parsed sentence. Context vectors of a vertex, an iterative vectorial representation of all labeled nodes adjacent and nonadjacent to it, adequately capture the direct and indirect substructures' information. Furthermore, the graph kernel considering the distance between context vectors is used to detect DDIs. Experimental results on the DDIExtraction 2013 corpus show that our system achieves the best detection and classification performance (F-score) of DDIs (81.8 and 68.4, respectively). Especially for the Medline-2013 dataset, our system outperforms the top-ranking DDIs systems by F-scores of 10.7 and 12.2 in detection and classification, respectively. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Novel mobilizable prokaryotic two-hybrid system vectors for high-throughput protein interaction mapping in Escherichia coli by bacterial conjugation.

    Science.gov (United States)

    Clarke, Paul; Cuív, Páraic O; O'Connell, Michael

    2005-02-01

    Since its initial description, the yeast two-hybrid (Y2H) system has been widely used for the detection and analysis of protein-protein interactions. Mating-based strategies have been developed permitting its application for automated proteomic interaction mapping projects using both exhaustive and high-throughput strategies. More recently, a number of prokaryotic two-hybrid (P2H) systems have been developed but, despite the many advantages such Escherichia coli-based systems have over the Y2H system, they have not yet been widely implemented for proteomic interaction mapping. This may be largely due to the fact that high-throughput strategies employing bacterial transformation are not as amenable to automation as Y2H mating-based strategies. Here, we describe the construction of novel conjugative P2H system vectors. These vectors carry a mobilization element of the IncPalpha group plasmid RP4 and can therefore be mobilized with high efficiency from an E.coli donor strain encoding all of the required transport functions in trans. We demonstrate how these vectors permit the exploitation of bacterial conjugation for technically simplified and automated proteomic interaction mapping strategies in E.coli, analogous to the mating-based strategies developed for the Y2H system.

  3. Vision-Based Perception and Classification of Mosquitoes Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Masataka Fuchida

    2017-01-01

    Full Text Available The need for a novel automated mosquito perception and classification method is becoming increasingly essential in recent years, with steeply increasing number of mosquito-borne diseases and associated casualties. There exist remote sensing and GIS-based methods for mapping potential mosquito inhabitants and locations that are prone to mosquito-borne diseases, but these methods generally do not account for species-wise identification of mosquitoes in closed-perimeter regions. Traditional methods for mosquito classification involve highly manual processes requiring tedious sample collection and supervised laboratory analysis. In this research work, we present the design and experimental validation of an automated vision-based mosquito classification module that can deploy in closed-perimeter mosquito inhabitants. The module is capable of identifying mosquitoes from other bugs such as bees and flies by extracting the morphological features, followed by support vector machine-based classification. In addition, this paper presents the results of three variants of support vector machine classifier in the context of mosquito classification problem. This vision-based approach to the mosquito classification problem presents an efficient alternative to the conventional methods for mosquito surveillance, mapping and sample image collection. Experimental results involving classification between mosquitoes and a predefined set of other bugs using multiple classification strategies demonstrate the efficacy and validity of the proposed approach with a maximum recall of 98%.

  4. PMSVM: An Optimized Support Vector Machine Classification Algorithm Based on PCA and Multilevel Grid Search Methods

    Directory of Open Access Journals (Sweden)

    Yukai Yao

    2015-01-01

    Full Text Available We propose an optimized Support Vector Machine classifier, named PMSVM, in which System Normalization, PCA, and Multilevel Grid Search methods are comprehensively considered for data preprocessing and parameters optimization, respectively. The main goals of this study are to improve the classification efficiency and accuracy of SVM. Sensitivity, Specificity, Precision, and ROC curve, and so forth, are adopted to appraise the performances of PMSVM. Experimental results show that PMSVM has relatively better accuracy and remarkable higher efficiency compared with traditional SVM algorithms.

  5. A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

    Science.gov (United States)

    Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung

    2017-03-01

    The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.

  6. An accurate algorithm for estimation of coal reserves based on support vector machine

    Energy Technology Data Exchange (ETDEWEB)

    Deng, X.; Liu, W.; Wang, R. [Wuhan University, Wuhan (China). School of Geology and Geomatics

    2008-09-15

    In an effort to improve the limitations of the present methods of estimating coal reserves an accurate algorithm is presented based on the support vector machine model. By building a thick coal and bulk density model from knowledge of drilling data and eliminating the outer points according to the relation between points and polygons, coal reserves were accurately calculated by summing up all the reserves of a small grid. Two examples for different types of coal mine are given and three-dimensional mineral distribution maps are plotted. The examples validate the reliability and advantages of the method proposed. 9 refs., 1 fig., 1 tab.

  7. A Shellcode Detection Method Based on Full Native API Sequence and Support Vector Machine

    Science.gov (United States)

    Cheng, Yixuan; Fan, Wenqing; Huang, Wei; An, Jing

    2017-09-01

    Dynamic monitoring the behavior of a program is widely used to discriminate between benign program and malware. It is usually based on the dynamic characteristics of a program, such as API call sequence or API call frequency to judge. The key innovation of this paper is to consider the full Native API sequence and use the support vector machine to detect the shellcode. We also use the Markov chain to extract and digitize Native API sequence features. Our experimental results show that the method proposed in this paper has high accuracy and low detection rate.

  8. Near-field and high-resolution cylindrical noise source location method based on vector sound pressure array

    Directory of Open Access Journals (Sweden)

    ZUO Xiang

    2017-08-01

    Full Text Available The existing underwater noise source near-field location method usually assumes that the measurement plane is flat, which increases the difficulty of applying the underwater noise target test for cylindrical distribution. Simultaneously, the conventional near-field focused beam has a lower spatial resolution when used to locate an underwater noise source with cylindrical distribution. Moreover, the near-field underwater noise source location method based on the sound pressure array has a left and right side fuzzy problem. In order to solve these problems, by establishing the near-field measurement model of the noise source with cylindrical distribution as the measurement surface, and combining the unilateral directivity of the vector hydrophone and the high resolution characteristics of the MUSIC algorithm, a near-field and high resolution location method is proposed for cylindrical distribution based on vector sound pressure, and a computer simulation is carried out. The results show that the method can use a smaller array aperture to locate the underwater noise source, enabling it to be used to locate and recognize the noise sources of complex and large-scale cylindrical systems.

  9. Phase regeneration for polarization-division multiplexed signals based on vector dual-pump nondegenerate phase sensitive amplification.

    Science.gov (United States)

    Yang, Weili; Yu, Yu; Ye, Mengyuan; Chen, Guanyu; Zhang, Chi; Zhang, Xinliang

    2015-02-09

    The polarization-division multiplexing (PDM) technology is a practical method to double the transmission capacity, and the corresponding phase regeneration (PR) for PDM signals is meaningful and necessary to extend the transmission distance and increase the transparency for the phase-encoded PDM system. Those reported PDM PR schemes either utilized polarization-diversity technique or required special PDM format. In order to overcome these issues, the PR for the PDM phase-modulated signals is proposed and theoretically demonstrated in this paper, based on the vector dual-pump nondegenerate phase sensitive amplification (PSA). The theoretical model is established and the detailed characteristics are investigated to optimize the PR performance. Results show an obvious phase squeezing for the degraded 80 Gbit/s PDM differential phase-shift keying (DPSK) signals, and the error vector magnitude (EVM) of the regenerated signals on dual polarization states can be improved from 22.58% and 21.39% to 4.57% and 4.63%, respectively. Furthermore, the applicability of the proposed scheme for PDM quaternary-phase shift keying (QPSK) signals is investigated. The proposed scheme can be useful and promising in current PDM based coherent fiber-optic communication.

  10. A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method.

    Science.gov (United States)

    Li, Wutao; Huang, Zhigang; Lang, Rongling; Qin, Honglei; Zhou, Kai; Cao, Yongbin

    2016-03-04

    Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS) receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM) is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM) algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms) level and the monitoring time is on microsecond (μs) level, which make the proposed approach usable in practical interference monitoring applications.

  11. Genetically Modifying the Insect Gut Microbiota to Control Chagas Disease Vectors through Systemic RNAi

    OpenAIRE

    Taracena, Mabel L.; Oliveira, Pedro L.; Almendares, Olivia; Uma?a, Claudia; Lowenberger, Carl; Dotson, Ellen M.; Paiva-Silva, Gabriela O.; Pennington, Pamela M.

    2015-01-01

    Technologies based on RNA interference may be used for insect control. Sustainable strategies are needed to control vectors of Chagas disease such as Rhodnius prolixus. The insect microbiota can be modified to deliver molecules to the gut. Here, Escherichia coli HT115(DE3) expressing dsRNA for the Rhodnius heme-binding protein (RHBP) and for catalase (CAT) were fed to nymphs and adult triatomine stages. RHBP is an egg protein and CAT is an antioxidant enzyme expressed in all tissues by all de...

  12. A vector system for efficient and economical switching of a ura4(+) module to three commonly used antibiotic marker cassettes in Schizosaccharomyces pombe.

    Science.gov (United States)

    Chen, Yinghui; Chen, Lihua; An, Ke; Wang, Yamei; Jin, Quanwen

    2015-11-01

    We describe here the development of a set of plasmid vectors that allow simple, efficient and economical switching of a ura4(+) module in existing Schizosaccharomyces pombe strains to any of the three routinely used antibiotic marker cassettes, kanMX6, hphMX6 and natMX6. In principle, the applications of this system can also be extended to switching ura4(+) for additional MX6 module-based cassettes, such as bleMX6, as long as the antibiotic marker has been cloned into an ura4(+) module-switching vector. We illustrate the application of this set of vectors in exchange of the ura4(+) marker in existing strains with three antibiotic marker cassettes with high efficiency. Copyright © 2015 John Wiley & Sons, Ltd.

  13. Evolutionary analysis of human immunodeficiency virus type 1 therapies based on conditionally replicating vectors.

    Directory of Open Access Journals (Sweden)

    Ruian Ke

    Full Text Available Efforts to reduce the viral load of human immunodeficiency virus type 1 (HIV-1 during long-term treatment are challenged by the evolution of anti-viral resistance mutants. Recent studies have shown that gene therapy approaches based on conditionally replicating vectors (CRVs could have many advantages over anti-viral drugs and other approaches to therapy, potentially including the ability to circumvent the problem of evolved resistance. However, research to date has not explored the evolutionary consequences of long-term treatment of HIV-1 infections with conditionally replicating vectors. In this study, we analyze a computational model of the within-host co-evolutionary dynamics of HIV-1 and conditionally replicating vectors, using the recently proposed 'therapeutic interfering particle' as an example. The model keeps track of the stochastic process of viral mutation, and the deterministic population dynamics of T cells as well as different strains of CRV and HIV-1 particles. We show that early in the co-infection, mutant HIV-1 genotypes that escape suppression by CRV therapy appear; this is similar to the dynamics observed in drug treatments and other gene therapies. In contrast to other treatments, however, the CRV population is able to evolve and catch up with the dominant HIV-1 escape mutant and persist long-term in most cases. On evolutionary grounds, gene therapies based on CRVs appear to be a promising tool for long-term treatment of HIV-1. Our model allows us to propose design principles to optimize the efficacy of this class of gene therapies. In addition, because of the analogy between CRVs and naturally-occurring defective interfering particles, our results also shed light on the co-evolutionary dynamics of wild-type viruses and their defective interfering particles during natural infections.

  14. Factors affecting learning of vector math from computer-based practice: Feedback complexity and prior knowledge

    Directory of Open Access Journals (Sweden)

    Andrew F. Heckler

    2016-06-01

    Full Text Available In experiments including over 450 university-level students, we studied the effectiveness and time efficiency of several levels of feedback complexity in simple, computer-based training utilizing static question sequences. The learning domain was simple vector math, an essential skill in introductory physics. In a unique full factorial design, we studied the relative effects of “knowledge of correct response” feedback and “elaborated feedback” (i.e., a general explanation both separately and together. A number of other factors were analyzed, including training time, physics course grade, prior knowledge of vector math, and student beliefs about both their proficiency in and the importance of vector math. We hypothesize a simple model predicting how the effectiveness of feedback depends on prior knowledge, and the results confirm this knowledge-by-treatment interaction. Most notably, elaborated feedback is the most effective feedback, especially for students with low prior knowledge and low course grade. In contrast, knowledge of correct response feedback was less effective for low-performing students, and including both kinds of feedback did not significantly improve performance compared to elaborated feedback alone. Further, while elaborated feedback resulted in higher scores, the learning rate was at best only marginally higher because the training time was slightly longer. Training time data revealed that students spent significantly more time on the elaborated feedback after answering a training question incorrectly. Finally, we found that training improved student self-reported proficiency and that belief in the importance of the learned domain improved the effectiveness of training. Overall, we found that computer based training with static question sequences and immediate elaborated feedback in the form of simple and general explanations can be an effective way to improve student performance on a physics essential skill

  15. Experimental and simulation testing of thermal loading in the jet tabs of a thrust vector control system

    Directory of Open Access Journals (Sweden)

    Živković Saša Ž.

    2016-01-01

    Full Text Available The paper discusses the temperature changes in mechanical jet tabs in a system of rocket motor thrust vector control, estimated by the simulation and experimental tests methodology. The heat transfer calculation is based on complex computational fluid dynamics simulations of both the nozzle and external tab flows, as the comprehensive integral flow zones with high flow parameters gradients. Due to a complexity of the model for flow calculations, the experimental estimation of the calculated results is carried out. The temperature is measured by jet tabs embedded thermocouples, and conducted through the rocket motor static tests. A good agreement of the calculated and measured results is achieved. The main aim of the developed method is to establish an approved calculation tool for designing new TVC systems in order to avoid disadvantages due to overheating.

  16. A hybrid stability-control system: combining direct-yaw-moment control and G-Vectoring Control

    Science.gov (United States)

    Takahashi, Junya; Yamakado, Makoto; Saito, Shinjiro; Yokoyama, Atsushi

    2012-06-01

    In this study, a 'hybrid stability-control' system based on two concepts - G-Vectoring Control (GVC) and direct-yaw-moment control (DYC) - was developed. This system controls deceleration according to the information on vehicle lateral jerk and yaw moment according to the information on vehicle sideslip. It reduces the tendency to understeer by applying deceleration via GVC and reduces the tendency to oversteer by adding yaw moment via DYC. The tests with a vehicle fitted with this new GVC/DYC hybrid control confirmed that understeer can be reduced significantly more than that possible with conventional DYC only. It is concluded that this greater understeer reduction is a result of GVC preventing understeer prior to the skidding of the vehicle.

  17. Support-vector-machines-based multidimensional signal classification for fetal activity characterization

    Science.gov (United States)

    Ribes, S.; Voicu, I.; Girault, J. M.; Fournier, M.; Perrotin, F.; Tranquart, F.; Kouamé, D.

    2011-03-01

    Electronic fetal monitoring may be required during the whole pregnancy to closely monitor specific fetal and maternal disorders. Currently used methods suffer from many limitations and are not sufficient to evaluate fetal asphyxia. Fetal activity parameters such as movements, heart rate and associated parameters are essential indicators of the fetus well being, and no current device gives a simultaneous and sufficient estimation of all these parameters to evaluate the fetus well-being. We built for this purpose, a multi-transducer-multi-gate Doppler system and developed dedicated signal processing techniques for fetal activity parameter extraction in order to investigate fetus's asphyxia or well-being through fetal activity parameters. To reach this goal, this paper shows preliminary feasibility of separating normal and compromised fetuses using our system. To do so, data set consisting of two groups of fetal signals (normal and compromised) has been established and provided by physicians. From estimated parameters an instantaneous Manning-like score, referred to as ultrasonic score was introduced and was used together with movements, heart rate and associated parameters in a classification process using Support Vector Machines (SVM) method. The influence of the fetal activity parameters and the performance of the SVM were evaluated using the computation of sensibility, specificity, percentage of support vectors and total classification accuracy. We showed our ability to separate the data into two sets : normal fetuses and compromised fetuses and obtained an excellent matching with the clinical classification performed by physician.

  18. Reliability analysis on resonance for low-pressure compressor rotor blade based on least squares support vector machine with leave-one-out cross-validation

    Directory of Open Access Journals (Sweden)

    Haifeng Gao

    2015-04-01

    Full Text Available This research article analyzes the resonant reliability at the rotating speed of 6150.0 r/min for low-pressure compressor rotor blade. The aim is to improve the computational efficiency of reliability analysis. This study applies least squares support vector machine to predict the natural frequencies of the low-pressure compressor rotor blade considered. To build a more stable and reliable least squares support vector machine model, leave-one-out cross-validation is introduced to search for the optimal parameters of least squares support vector machine. Least squares support vector machine with leave-one-out cross-validation is presented to analyze the resonant reliability. Additionally, the modal analysis at the rotating speed of 6150.0 r/min for the rotor blade is considered as a tandem system to simplify the analysis and design process, and the randomness of influence factors on frequencies, such as material properties, structural dimension, and operating condition, is taken into consideration. Back-propagation neural network is compared to verify the proposed approach based on the same training and testing sets as least squares support vector machine with leave-one-out cross-validation. Finally, the statistical results prove that the proposed approach is considered to be effective and feasible and can be applied to structural reliability analysis.

  19. The Quality Prediction in Small-batch Producing Based on Weighted Least Squares Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Zhang Sheng Bo

    2016-01-01

    Full Text Available A novel quality prediction method with mobile time window is proposed for small-batch producing process based on weighted least squares support vector regression (LS-SVR. The design steps and learning algorithm are also addressed. In the method, weighted LS-SVR is taken as the intelligent kernel, with which the small-batch learning is solved well and the nearer sample is set a larger weight, while the farther is set the smaller weight in the history data. A typical machining process of cutting bearing outer race is carried out and the real measured data are used to contrast experiment. The experimental results demonstrate that the prediction accuracy of the weighted LSSVR based model is only 20%-30% that of the standard LS-SVR based one in the same condition. It provides a better candidate for quality prediction of small-batch producing process.

  20. Experimental Study on MUSIC-Based DOA Estimation by Using Universal Steering Vector

    Science.gov (United States)

    Yuan, Qiaowei; Chen, Qiang; Sawaya, Kunio

    MUSIC-based estimation of direction of arrival (DOA) using universal steering vector (USV) is experimentally studied. A four-element array antenna and a four-channel receiver are employed for the experiment. In order to improve the accuracy of DOA estimation, USV which has already included the effect of mutual coupling between array elements and effect of array elements themselves is compensated to further include the electric delay and loss of four channels in the receiver. The compensated USV (C-USV) approach proposed in this paper does not need the time-consuming measurement of array element pattern because the compensating matrix for USV is obtained by measuring the S parameters between RF input ports of the feeding cables and IF output ports of the receiver. The experimental results of MUSIC-based DOA estimation show that C-USV approach is an accurate, effective and practical method for the MUSIC-based DOA estimation.

  1. Settlement Prediction of Road Soft Foundation Using a Support Vector Machine (SVM Based on Measured Data

    Directory of Open Access Journals (Sweden)

    Yu Huiling

    2016-01-01

    Full Text Available The suppor1t vector machine (SVM is a relatively new artificial intelligence technique which is increasingly being applied to geotechnical problems and is yielding encouraging results. SVM is a new machine learning method based on the statistical learning theory. A case study based on road foundation engineering project shows that the forecast results are in good agreement with the measured data. The SVM model is also compared with BP artificial neural network model and traditional hyperbola method. The prediction results indicate that the SVM model has a better prediction ability than BP neural network model and hyperbola method. Therefore, settlement prediction based on SVM model can reflect actual settlement process more correctly. The results indicate that it is effective and feasible to use this method and the nonlinear mapping relation between foundation settlement and its influence factor can be expressed well. It will provide a new method to predict foundation settlement.

  2. EFFECTIVENESS OF HUANGLONGBING VECTOR (DIAPHORINA CITRI KUWAYAMA CONTROL IN CITRUS GROWER GROUP BASED IN SAMBAS REGENCY OF WEST KALIMANTAN, INDONESIA

    Directory of Open Access Journals (Sweden)

    Supriyanto A.

    2017-12-01

    Full Text Available The purpose of this study was to determine the effectiveness of Huanglongbing vector control based on Citrus Grower Group recommendation. Studies have been carried out in 2010 in Tebas Sungai village, Sambas district, with 11 tangerine groves owned by growers in the Citrus grower Association of Sambas district. The tangerine grove that been used are, one grower's orchard as a demonstration plot in a particular citrus grower group (orchard I; five other citrus orchards with different ownership at the same citrus grower Group (orchard II, as well as five other citrus orchard with different ownership which each of them spreads over five different citrus grower groups outside the farm demonstration plots (orchard III. The recommendation technology for controlling Huanglongbing vector which applied in this experiment, included bark painting by systemic insecticide of imidacloprid for two each 1.5-month and spray using contact insecticide with dimethoate to the plant crown which application time been alternated after bark painting application. The effectiveness of technology implementation is measured by a decrease psyllid populations found in citrus samples in adult stage, nymphs and eggs that were observed at regular intervals every two weeks during the flushing to the 14th week after the first treatment. The results showed that recommended treatment technology were absolutely proven to reduce Huanglongbing vector population in significant, namely in the orchard I, II, and III respectively at 95.3%, 84.7%, and 72% for stage adult; 97.3 %, 80%, and 100% for stage nymphs; and 98.5%, 100% and 100% for the egg stage.

  3. Prototype early warning systems for vector-borne diseases in Europe.

    Science.gov (United States)

    Semenza, Jan C

    2015-06-02

    Globalization and environmental change, social and demographic determinants and health system capacity are significant drivers of infectious diseases which can also act as epidemic precursors. Thus, monitoring changes in these drivers can help anticipate, or even forecast, an upsurge of infectious diseases. The European Environment and Epidemiology (E3) Network has been built for this purpose and applied to three early warning case studies: (1) The environmental suitability of malaria transmission in Greece was mapped in order to target epidemiological and entomological surveillance and vector control activities. Malaria transmission in these areas was interrupted in 2013 through such integrated preparedness and response activities. (2) Since 2010, recurrent West Nile fever outbreaks have ensued in South/eastern Europe. Temperature deviations from a thirty year average proved to be associated with the 2010 outbreak. Drivers of subsequent outbreaks were computed through multivariate logistic regression models and included monthly temperature anomalies for July and a normalized water index. (3) Dengue is a tropical disease but sustained transmission has recently emerged in Madeira. Autochthonous transmission has also occurred repeatedly in France and in Croatia mainly due to travel importation. The risk of dengue importation into Europe in 2010 was computed with the volume of international travelers from dengue affected areas worldwide.These prototype early warning systems indicate that monitoring drivers of infectious diseases can help predict vector-borne disease threats.

  4. Prototype Early Warning Systems for Vector-Borne Diseases in Europe

    Directory of Open Access Journals (Sweden)

    Jan C. Semenza

    2015-06-01

    Full Text Available Globalization and environmental change, social and demographic determinants and health system capacity are significant drivers of infectious diseases which can also act as epidemic precursors. Thus, monitoring changes in these drivers can help anticipate, or even forecast, an upsurge of infectious diseases. The European Environment and Epidemiology (E3 Network has been built for this purpose and applied to three early warning case studies: (1 The environmental suitability of malaria transmission in Greece was mapped in order to target epidemiological and entomological surveillance and vector control activities. Malaria transmission in these areas was interrupted in 2013 through such integrated preparedness and response activities. (2 Since 2010, recurrent West Nile fever outbreaks have ensued in South/eastern Europe. Temperature deviations from a thirty year average proved to be associated with the 2010 outbreak. Drivers of subsequent outbreaks were computed through multivariate logistic regression models and included monthly temperature anomalies for July and a normalized water index. (3 Dengue is a tropical disease but sustained transmission has recently emerged in Madeira. Autochthonous transmission has also occurred repeatedly in France and in Croatia mainly due to travel importation. The risk of dengue importation into Europe in 2010 was computed with the volume of international travelers from dengue affected areas worldwide.These prototype early warning systems indicate that monitoring drivers of infectious diseases can help predict vector-borne disease threats.

  5. Generalized correlation integral vectors: A distance concept for chaotic dynamical systems

    Energy Technology Data Exchange (ETDEWEB)

    Haario, Heikki, E-mail: heikki.haario@lut.fi [School of Engineering Science, Lappeenranta University of Technology, Lappeenranta (Finland); Kalachev, Leonid, E-mail: KalachevL@mso.umt.edu [Department of Mathematical Sciences, University of Montana, Missoula, Montana 59812-0864 (United States); Hakkarainen, Janne [Earth Observation Unit, Finnish Meteorological Institute, Helsinki (Finland)

    2015-06-15

    Several concepts of fractal dimension have been developed to characterise properties of attractors of chaotic dynamical systems. Numerical approximations of them must be calculated by finite samples of simulated trajectories. In principle, the quantities should not depend on the choice of the trajectory, as long as it provides properly distributed samples of the underlying attractor. In practice, however, the trajectories are sensitive with respect to varying initial values, small changes of the model parameters, to the choice of a solver, numeric tolerances, etc. The purpose of this paper is to present a statistically sound approach to quantify this variability. We modify the concept of correlation integral to produce a vector that summarises the variability at all selected scales. The distribution of this stochastic vector can be estimated, and it provides a statistical distance concept between trajectories. Here, we demonstrate the use of the distance for the purpose of estimating model parameters of a chaotic dynamic model. The methodology is illustrated using computational examples for the Lorenz 63 and Lorenz 95 systems, together with a framework for Markov chain Monte Carlo sampling to produce posterior distributions of model parameters.

  6. Development of a single vector system that enhances trans-splicing of SMN2 transcripts.

    Directory of Open Access Journals (Sweden)

    Tristan H Coady

    Full Text Available RNA modalities are developing as a powerful means to re-direct pathogenic pre-mRNA splicing events. Improving the efficiency of these molecules in vivo is critical as they move towards clinical applications. Spinal muscular atrophy (SMA is caused by loss of SMN1. A nearly identical copy gene called SMN2 produces low levels of functional protein due to alternative splicing. We previously reported a trans-splicing RNA (tsRNA that re-directed SMN2 splicing. Now we show that reducing the competition between endogenous splices sites enhanced the efficiency of trans-splicing. A single vector system was developed that expressed the SMN tsRNA and a splice-site blocking antisense (ASO-tsRNA. The ASO-tsRNA vector significantly elevated SMN levels in primary SMA patient fibroblasts, within the central nervous system of SMA mice and increased SMN-dependent in vitro snRNP assembly. These results demonstrate that the ASO-tsRNA strategy provides insight into the trans-splicing mechanism and a means of significantly enhancing trans-splicing activity in vivo.

  7. Framework and implementation for improving physics essential skills via computer-based practice: Vector math

    Science.gov (United States)

    Mikula, Brendon D.; Heckler, Andrew F.

    2017-06-01

    We propose a framework for improving accuracy, fluency, and retention of basic skills essential for solving problems relevant to STEM introductory courses, and implement the framework for the case of basic vector math skills over several semesters in an introductory physics course. Using an iterative development process, the framework begins with a careful identification of target skills and the study of specific student difficulties with these skills. It then employs computer-based instruction, immediate feedback, mastery grading, and well-researched principles from cognitive psychology such as interleaved training sequences and distributed practice. We implemented this with more than 1500 students over 2 semesters. Students completed the mastery practice for an average of about 13 min /week , for a total of about 2-3 h for the whole semester. Results reveal large (>1 SD ) pretest to post-test gains in accuracy in vector skills, even compared to a control group, and these gains were retained at least 2 months after practice. We also find evidence of improved fluency, student satisfaction, and that awarding regular course credit results in higher participation and higher learning gains than awarding extra credit. In all, we find that simple computer-based mastery practice is an effective and efficient way to improve a set of basic and essential skills for introductory physics.

  8. Physiological levels of HBB transgene expression from S/MAR element-based replicating episomal vectors.

    Science.gov (United States)

    Sgourou, Argyro; Routledge, Samantha; Spathas, Dionysios; Athanassiadou, Aglaia; Antoniou, Michael N

    2009-08-20

    Replicating episomal vectors (REV) are in principle able to provide long-term transgene expression in the absence of integration into the target cell genome. The scaffold/matrix attachment region (S/MAR) located 5' of the human beta-interferon gene (IFNB1) has been shown to confer a stable episomal replication and retention function within plasmid vectors when stably transfected and selected in mammalian cells. The minimal requirement for the IFNB1 S/MAR to function in DNA replication and episomal retention is transcription through this element. We used the erythroid beta-globin locus control region-beta-globin gene (betaLCR-HBB) microlocus cassette as a model to assess tissue-specific expression from within an IFNB1 S/MAR-based plasmid REV. The betaLCR-HBB plus S/MAR combination constructs provided either high or low levels of transcription through the S/MAR element. Our results show that the betaLCR-HBB microlocus is able to reproducibly and stably express at full physiological levels on an episome copy number basis. In addition, our data show that even low levels of transcription from betaLCR-HBB through the S/MAR element are sufficient to allow efficient episomal replication and retention. These data provide the principles upon which generic and flexible expression cassette-S/MAR-based REVs can be designed for a wide range of applications.

  9. Double-stranded RNA transcribed from vector-based oligodeoxynucleotide acts as transcription factor decoy

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Xiao [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Gang, Yi [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Department of Infectious Diseases, Tangdu Hospital, Fourth Military Medical University, Xi’an 710038, Shaanxi Province (China); Wang, Honghong [No. 518 Hospital of Chinese People’s Liberation Army, Xi’an 710043, Shaanxi Province (China); Wang, Jiayin [The Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 (United States); Zhao, Lina [Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Xu, Li, E-mail: lxuhelen@163.com [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Liu, Zhiguo, E-mail: liuzhiguo@fmmu.edu.cn [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China)

    2015-02-06

    Highlights: • A shRNA vector based transcription factor decoy, VB-ODN, was designed. • VB-ODN for NF-κB inhibited cell viability in HEK293 cells. • VB-ODN inhibited expression of downstream genes of target transcription factors. • VB-ODN may enhance nuclear entry ratio for its feasibility of virus production. - Abstract: In this study, we designed a short hairpin RNA vector-based oligodeoxynucleotide (VB-ODN) carrying transcription factor (TF) consensus sequence which could function as a decoy to block TF activity. Specifically, VB-ODN for Nuclear factor-κB (NF-κB) could inhibit cell viability and decrease downstream gene expression in HEK293 cells without affecting expression of NF-κB itself. The specific binding between VB-ODN produced double-stranded RNA and NF-κB was evidenced by electrophoretic mobility shift assay. Moreover, similar VB-ODNs designed for three other TFs also inhibit their downstream gene expression but not that of themselves. Our study provides a new design of decoy for blocking TF activity.

  10. Opportunities for Improved Chagas Disease Vector Control Based on Knowledge, Attitudes and Practices of Communities in the Yucatan Peninsula, Mexico

    Science.gov (United States)

    Rosecrans, Kathryn; Cruz-Martin, Gabriela; King, Ashley; Dumonteil, Eric

    2014-01-01

    Background Chagas disease is a vector-borne parasitic disease of major public health importance. Current prevention efforts are based on triatomine vector control to reduce transmission to humans. Success of vector control interventions depends on their acceptability and value to affected communities. We aimed to identify opportunities for and barriers to improved vector control strategies in the Yucatan peninsula, Mexico. Methodology/principal findings We employed a sequence of qualitative and quantitative research methods to investigate knowledge, attitudes and practices surrounding Chagas disease, triatomines and vector control in three rural communities. Our combined data show that community members are well aware of triatomines and are knowledgeable about their habits. However, most have a limited understanding of the transmission dynamics and clinical manifestations of Chagas disease. While triatomine control is not a priority for community members, they frequently use domestic insecticide products including insecticide spray, mosquito coils and plug-in repellents. Families spend about $32 US per year on these products. Alternative methods such as yard cleaning and window screens are perceived as desirable and potentially more effective. Screens are nonetheless described as unaffordable, in spite of a cost comparable to the average annual spending on insecticide products. Conclusion/Significance Further education campaigns and possibly financing schemes may lead families to redirect their current vector control spending from insecticide products to window screens. Also, synergism with mosquito control efforts should be further explored to motivate community involvement and ensure sustainability of Chagas disease vector control. PMID:24676038

  11. Multiple insecticide resistance: an impediment to insecticide-based malaria vector control program.

    Science.gov (United States)

    Yewhalaw, Delenasaw; Wassie, Fantahun; Steurbaut, Walter; Spanoghe, Pieter; Van Bortel, Wim; Denis, Leen; Tessema, Dejene A; Getachew, Yehenew; Coosemans, Marc; Duchateau, Luc; Speybroeck, Niko

    2011-01-12

    Indoor Residual Spraying (IRS), insecticide-treated nets (ITNs) and long-lasting insecticidal nets (LLINs) are key components in malaria prevention and control strategy. However, the development of resistance by mosquitoes to insecticides recommended for IRS and/or ITNs/LLINs would affect insecticide-based malaria vector control. We assessed the susceptibility levels of Anopheles arabiensis to insecticides used in malaria control, characterized basic mechanisms underlying resistance, and evaluated the role of public health use of insecticides in resistance selection. Susceptibility status of An. arabiensis was assessed using WHO bioassay tests to DDT, permethrin, deltamethrin, malathion and propoxur in Ethiopia from August to September 2009. Mosquito specimens were screened for knockdown resistance (kdr) and insensitive acetylcholinesterase (ace-1(R)) mutations using AS-PCR and PCR-RFLP, respectively. DDT residues level in soil from human dwellings and the surrounding environment were determined by Gas Chromatography with Electron Capture Detector. An. arabiensis was resistant to DDT, permethrin, deltamethrin and malathion, but susceptible to propoxur. The West African kdr allele was found in 280 specimens out of 284 with a frequency ranged from 95% to 100%. Ace-1(R) mutation was not detected in all specimens scored for the allele. Moreover, DDT residues were found in soil samples from human dwellings but not in the surrounding environment. The observed multiple-resistance coupled with the occurrence of high kdr frequency in populations of An. arabiensis could profoundly affect the malaria vector control programme in Ethiopia. This needs an urgent call for implementing rational resistance management strategies and integrated vector control intervention.

  12. Multiple insecticide resistance: an impediment to insecticide-based malaria vector control program.

    Directory of Open Access Journals (Sweden)

    Delenasaw Yewhalaw

    Full Text Available BACKGROUND: Indoor Residual Spraying (IRS, insecticide-treated nets (ITNs and long-lasting insecticidal nets (LLINs are key components in malaria prevention and control strategy. However, the development of resistance by mosquitoes to insecticides recommended for IRS and/or ITNs/LLINs would affect insecticide-based malaria vector control. We assessed the susceptibility levels of Anopheles arabiensis to insecticides used in malaria control, characterized basic mechanisms underlying resistance, and evaluated the role of public health use of insecticides in resistance selection. METHODOLOGY/PRINCIPAL FINDINGS: Susceptibility status of An. arabiensis was assessed using WHO bioassay tests to DDT, permethrin, deltamethrin, malathion and propoxur in Ethiopia from August to September 2009. Mosquito specimens were screened for knockdown resistance (kdr and insensitive acetylcholinesterase (ace-1(R mutations using AS-PCR and PCR-RFLP, respectively. DDT residues level in soil from human dwellings and the surrounding environment were determined by Gas Chromatography with Electron Capture Detector. An. arabiensis was resistant to DDT, permethrin, deltamethrin and malathion, but susceptible to propoxur. The West African kdr allele was found in 280 specimens out of 284 with a frequency ranged from 95% to 100%. Ace-1(R mutation was not detected in all specimens scored for the allele. Moreover, DDT residues were found in soil samples from human dwellings but not in the surrounding environment. CONCLUSION: The observed multiple-resistance coupled with the occurrence of high kdr frequency in populations of An. arabiensis could profoundly affect the malaria vector control programme in Ethiopia. This needs an urgent call for implementing rational resistance management strategies and integrated vector control intervention.

  13. In vivo image analysis of BoHV-4-based vector in mice.

    Directory of Open Access Journals (Sweden)

    Valentina Franceschi

    Full Text Available Due to its biological characteristics bovine herpesvirus 4 (BoHV-4 has been considered as an appropriate gene delivery vector. Its genomic clone, modified as a bacterial artificial chromosome (BAC, is better genetically manipulable and can be used as an efficient gene delivery and vaccine vector. Although a large amount of data have been accumulated in vitro on this specific aspect, the same cannot be asserted for the in vivo condition. Therefore, here we investigated the fate of a recombinant BoHV-4 strain expressing luciferase (BoHV-4-A-CMVlucΔTK after intraperitoneal or intravenous inoculation in mice, by generating a novel recombinant BoHV-4 expressing luciferase (BoHV-4-A-CMVlucΔTK and by following the virus replication through in vivo imaging analysis. BoHV-4-A-CMVlucΔTK was first characterized in vitro where it was shown, on one hand that its replication properties are identical to those of the parental virus, and on the other that the transduced/infected cells strongly express luciferase. When BoHV-4-A-CMVlucΔTK was inoculated in mice, either intraperitoneally or intravenously, BoHV-4-A-CMVlucΔTK infection/transduction was exclusively localized to the liver, as detected by in vivo image analysis, and in particular almost exclusively in the hepatocytes, as determined by immuno-histochemistry. These data, that add a new insight on the biology of BoHV-4 in vivo, provide the first indication for the potential use of a BoHV-4-based vector in gene-transfer in the liver.

  14. Efficient control of gene expression in the hematopoietic system using a single Tet-on inducible lentiviral vector.

    Science.gov (United States)

    Barde, Isabelle; Zanta-Boussif, Maria Antonietta; Paisant, Sylvain; Leboeuf, Marylene; Rameau, Philippe; Delenda, Christophe; Danos, Olivier

    2006-02-01

    This work addresses the problem of efficient control of gene expression in the context of viral vectors, which still represents a difficult challenge. A number of lentiviral vectors incorporating the different elements of regulatable transcriptional systems have been described, but they fail to perform satisfactorily either because of a poor dynamic range of transcription levels or because they display high background activities in the uninduced state and mediocre inducer response. We report here on the systematic comparison of vector designs containing the elements of the doxycycline-inducible Tet-on system in their most advanced versions (rtTA2S-M2 transactivator and tTS(Kid) repressor). We show that a simple "all-in-one" vector can be obtained and used for efficient control of transgene expression in long-term tissue culture and in the hematopoietic system of mice following bone marrow transplantation. Using this vector, the uninduced state can be kept at background levels and induction factors of 100-fold are repeatedly obtained over months both in tissue culture and in vivo. Interestingly, the low background activity of the all-in-one vector renders the use of the tTS repressor dispensable, avoiding the problem of progressive loss of inducibility over time associated with irreversible modifications of the chromatin surrounding proviral sequences.

  15. Emotion recognition from single-trial EEG based on kernel Fisher's emotion pattern and imbalanced quasiconformal kernel support vector machine.

    Science.gov (United States)

    Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

    2014-07-24

    Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods.

  16. Prediction of Military Vehicle's Drawbar Pull Based on an Improved Relevance Vector Machine and Real Vehicle Tests.

    Science.gov (United States)

    Yang, Fan; Sun, Wei; Lin, Guoyu; Zhang, Weigong

    2016-03-10

    The scientific and effective prediction of drawbar pull is of great importance in the evaluation of military vehicle trafficability. Nevertheless, the existing prediction models have demonstrated lots of inherent limitations. In this framework, a multiple-kernel relevance vector machine model (MkRVM) including Gaussian kernel and polynomial kernel is proposed to predict drawbar pull. Nonlinear decreasing inertia weight particle swarm optimization (NDIWPSO) is employed for parameter optimization. As the relations between drawbar pull and its influencing factors have not been tested on real vehicles, a series of experimental analyses based on real vehicle test data are done to confirm the effective influencing factors. A dynamic testing system is applied to conduct field tests and gain required test data. Gaussian kernel RVM, polynomial kernel RVM, support vector machine (SVM) and generalized regression neural network (GRNN) are also used to compare with the MkRVM model. The results indicate that the MkRVM model is a preferable model in this case. Finally, the proposed novel model is compared to the traditional prediction model of drawbar pull. The results show that the MkRVM model significantly improves the prediction accuracy. A great potential of improved RVM is indicated in further research of wheel-soil interactions.

  17. Prediction of Military Vehicle’s Drawbar Pull Based on an Improved Relevance Vector Machine and Real Vehicle Tests

    Directory of Open Access Journals (Sweden)

    Fan Yang

    2016-03-01

    Full Text Available The scientific and effective prediction of drawbar pull is of great importance in the evaluation of military vehicle trafficability. Nevertheless, the existing prediction models have demonstrated lots of inherent limitations. In this framework, a multiple-kernel relevance vector machine model (MkRVM including Gaussian kernel and polynomial kernel is proposed to predict drawbar pull. Nonlinear decreasing inertia weight particle swarm optimization (NDIWPSO is employed for parameter optimization. As the relations between drawbar pull and its influencing factors have not been tested on real vehicles, a series of experimental analyses based on real vehicle test data are done to confirm the effective influencing factors. A dynamic testing system is applied to conduct field tests and gain required test data. Gaussian kernel RVM, polynomial kernel RVM, support vector machine (SVM and generalized regression neural network (GRNN are also used to compare with the MkRVM model. The results indicate that the MkRVM model is a preferable model in this case. Finally, the proposed novel model is compared to the traditional prediction model of drawbar pull. The results show that the MkRVM model significantly improves the prediction accuracy. A great potential of improved RVM is indicated in further research of wheel-soil interactions.

  18. Prediction of Military Vehicle’s Drawbar Pull Based on an Improved Relevance Vector Machine and Real Vehicle Tests

    Science.gov (United States)

    Yang, Fan; Sun, Wei; Lin, Guoyu; Zhang, Weigong

    2016-01-01

    The scientific and effective prediction of drawbar pull is of great importance in the evaluation of military vehicle trafficability. Nevertheless, the existing prediction models have demonstrated lots of inherent limitations. In this framework, a multiple-kernel relevance vector machine model (MkRVM) including Gaussian kernel and polynomial kernel is proposed to predict drawbar pull. Nonlinear decreasing inertia weight particle swarm optimization (NDIWPSO) is employed for parameter optimization. As the relations between drawbar pull and its influencing factors have not been tested on real vehicles, a series of experimental analyses based on real vehicle test data are done to confirm the effective influencing factors. A dynamic testing system is applied to conduct field tests and gain required test data. Gaussian kernel RVM, polynomial kernel RVM, support vector machine (SVM) and generalized regression neural network (GRNN) are also used to compare with the MkRVM model. The results indicate that the MkRVM model is a preferable model in this case. Finally, the proposed novel model is compared to the traditional prediction model of drawbar pull. The results show that the MkRVM model significantly improves the prediction accuracy. A great potential of improved RVM is indicated in further research of wheel-soil interactions. PMID:26978359

  19. Single Cell-Based Vector Tracing in Patients with ADA-SCID Treated with Stem Cell Gene Therapy

    Directory of Open Access Journals (Sweden)

    Yuka Igarashi

    2017-09-01

    Full Text Available Clinical improvement in stem cell gene therapy (SCGT for primary immunodeficiencies depends on the engraftment levels of genetically corrected cells, and tracing the transgene in each hematopoietic lineage is therefore extremely important in evaluating the efficacy of SCGT. We established a single cell-based droplet digital PCR (sc-ddPCR method consisting of the encapsulation of a single cell into each droplet, followed by emulsion PCR with primers and probes specific for the transgene. A fluorescent signal in a droplet indicates the presence of a single cell carrying the target gene in its genome, and this system can clearly determine the ratio of transgene-positive cells in the entire population at the genomic level. Using sc-ddPCR, we analyzed the engraftment of vector-transduced cells in two patients with severe combined immunodeficiency (SCID who were treated with SCGT. Sufficient engraftment of the transduced cells was limited to the T cell lineage in peripheral blood (PB, and a small percentage of CD34+ cells exhibited vector integration in bone marrow, indicating that the transgene-positive cells in PB might have differentiated from a small population of stem cells or lineage-restricted precursor cells. sc-ddPCR is a simplified and powerful tool for the detailed assessment of transgene-positive cell distribution in patients treated with SCGT.

  20. X-ray standing wave simulations based on Fourier vector analysis as a method to retrieve complex molecular adsorption geometries

    Directory of Open Access Journals (Sweden)

    Giuseppe eMercurio

    2014-01-01

    Full Text Available We present an analysis method of normal incidence x-ray standing wave (NIXSW data that allows detailed adsorption geometries of complex molecules to be retrieved. This method (Fourier vector analysis is based on the comparison of both the coherence and phase of NIXSW data to NIXSW simulations of different molecular geometries as the relevant internal degrees of freedom are tuned. We introduce this analysis method using the prototypical molecular switch azobenzene (AB adsorbed on the Ag(111 surface as a model system. The application of the Fourier vector analysis to AB/Ag(111 provides, on the one hand, detailed adsorption geometries including dihedral angles, and on the other hand, insights into the dynamics of molecules and their bonding to the metal substrate. This analysis scheme is generally applicable to any adsorbate, it is necessary for molecules with potentially large distortions, and will be particularly valuable for molecules whose distortion on adsorption can be mapped on a limited number of internal degrees of freedom.

  1. Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs

    KAUST Repository

    Abdelfattah, Ahmad

    2016-05-23

    Simulations of many multi-component PDE-based applications, such as petroleum reservoirs or reacting flows, are dominated by the solution, on each time step and within each Newton step, of large sparse linear systems. The standard solver is a preconditioned Krylov method. Along with application of the preconditioner, memory-bound Sparse Matrix-Vector Multiplication (SpMV) is the most time-consuming operation in such solvers. Multi-species models produce Jacobians with a dense block structure, where the block size can be as large as a few dozen. Failing to exploit this dense block structure vastly underutilizes hardware capable of delivering high performance on dense BLAS operations. This paper presents a GPU-accelerated SpMV kernel for block-sparse matrices. Dense matrix-vector multiplications within the sparse-block structure leverage optimization techniques from the KBLAS library, a high performance library for dense BLAS kernels. The design ideas of KBLAS can be applied to block-sparse matrices. Furthermore, a technique is proposed to balance the workload among thread blocks when there are large variations in the lengths of nonzero rows. Multi-GPU performance is highlighted. The proposed SpMV kernel outperforms existing state-of-the-art implementations using matrices with real structures from different applications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  2. Novel Strategy to Control Transgene Expression Mediated by a Sendai Virus-Based Vector Using a Nonstructural C Protein and Endogenous MicroRNAs.

    Directory of Open Access Journals (Sweden)

    Masayuki Sano

    Full Text Available Tissue-specific control of gene expression is an invaluable tool for studying various biological processes and medical applications. Efficient regulatory systems have been utilized to control transgene expression in various types of DNA viral or integrating viral vectors. However, existing regulatory systems are difficult to transfer into negative-strand RNA virus vector platforms because of significant differences in their transcriptional machineries. In this study, we developed a novel strategy for regulating transgene expression mediated by a cytoplasmic RNA vector based on a replication-defective and persistent Sendai virus (SeVdp. Because of the capacity of Sendai virus (SeV nonstructural C proteins to specifically inhibit viral RNA synthesis, overexpression of C protein significantly reduced transgene expression mediated by SeVdp vectors. We found that SeV C overexpression concomitantly reduced SeVdp mRNA levels and genomic RNA synthesis. To control C expression, target sequences for an endogenous microRNA were incorporated into the 3' untranslated region of the C genes. Incorporation of target sequences for miR-21 into the SeVdp vector restored transgene expression in HeLa cells by decreasing C expression. Furthermore, the SeVdp vector containing target sequences for let-7a enabled cell-specific control of transgene expression in human fibroblasts and induced pluripotent stem cells. Our findings demonstrate that SeV C can be used as an effective regulator for controlling transgene expression. This strategy will contribute to efficient and less toxic SeVdp-mediated gene transfer in various biological applications.

  3. Quantization of Hamiltonian systems with a position dependent mass: Killing vector fields and Noether momenta approach

    Science.gov (United States)

    Cariñena, José F.; Rañada, Manuel F.; Santander, Mariano

    2017-11-01

    The quantization of systems with a position dependent mass (PDM) is studied. We present a method that starts with the study of the existence of Killing vector fields for the PDM geodesic motion (Lagrangian with a PDM kinetic term but without any potential) and the construction of the associated Noether momenta. Then the method considers, as the appropriate Hilbert space, the space of functions that are square integrable with respect to a measure related with the PDM and, after that, it establishes the quantization, not of the canonical momenta p, but of the Noether momenta P instead. The quantum Hamiltonian, that depends on the Noether momenta, is obtained as an Hermitian operator defined on the PDM Hilbert space. In the second part several systems with position-dependent mass, most of them related with nonlinear oscillators, are quantized by making use of the method proposed in the first part.

  4. Novel Discrete Compactness-Based Training for Vector Quantization Networks: Enhancing Automatic Brain Tissue Classification

    Directory of Open Access Journals (Sweden)

    Ricardo Pérez-Aguila

    2013-01-01

    Full Text Available An approach for nonsupervised segmentation of Computed Tomography (CT brain slices which is based on the use of Vector Quantization Networks (VQNs is described. Images are segmented via a VQN in such way that tissue is characterized according to its geometrical and topological neighborhood. The main contribution rises from the proposal of a similarity metric which is based on the application of Discrete Compactness (DC which is a factor that provides information about the shape of an object. One of its main strengths lies in the sense of its low sensitivity to variations, due to noise or capture defects, in the shape of an object. We will present, compare, and discuss some examples of segmentation networks trained under Kohonen’s original algorithm and also under our similarity metric. Some experiments are established in order to measure the effectiveness and robustness, under our application of interest, of the proposed networks and similarity metric.

  5. Graphic Design Of “Green Mission” Education Game Using Software Based On Vector

    Directory of Open Access Journals (Sweden)

    Nur Yanti

    2018-01-01

    Full Text Available Educational game is a digital game in its design using the elements of education and in it support teaching and learning by using technology that is interactive media. Generally an educational game has a fun look, an easy-to-use menu, as well as color combinations that are used that are GUI-based (Graphic User Interface so as to create appeal to users. Because it is undeniable that the human brain tends to more quickly capture learning through visual images rather than writings. Therefore, graphic design of an educational game becomes one of the important points. Software applications become one of the solutions in making game design, one of which is a vector-based software applications. There are various software that can be used in accordance with the function and usefulness of each. But in general the way the software works almost same.

  6. Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model

    Directory of Open Access Journals (Sweden)

    Shaojiang Dong

    2014-01-01

    Full Text Available Predicting the degradation process of bearings before they reach the failure threshold is extremely important in industry. This paper proposed a novel method based on the support vector machine (SVM and the Markov model to achieve this goal. Firstly, the features are extracted by time and time-frequency domain methods. However, the extracted original features are still with high dimensional and include superfluous information, and the nonlinear multifeatures fusion technique LTSA is used to merge the features and reduces the dimension. Then, based on the extracted features, the SVM model is used to predict the bearings degradation process, and the CAO method is used to determine the embedding dimension of the SVM model. After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. The proposed method was validated by two bearing run-to-failure experiments, and the results proved the effectiveness of the methodology.

  7. Support-vector-based emergent self-organising approach for emotional understanding

    Science.gov (United States)

    Nguwi, Yok-Yen; Cho, Siu-Yeung

    2010-12-01

    This study discusses the computational analysis of general emotion understanding from questionnaires methodology. The questionnaires method approaches the subject by investigating the real experience that accompanied the emotions, whereas the other laboratory approaches are generally associated with exaggerated elements. We adopted a connectionist model called support-vector-based emergent self-organising map (SVESOM) to analyse the emotion profiling from the questionnaires method. The SVESOM first identifies the important variables by giving discriminative features with high ranking. The classifier then performs the classification based on the selected features. Experimental results show that the top rank features are in line with the work of Scherer and Wallbott [(1994), 'Evidence for Universality and Cultural Variation of Differential Emotion Response Patterning', Journal of Personality and Social Psychology, 66, 310-328], which approached the emotions physiologically. While the performance measures show that using the full features for classifications can degrade the performance, the selected features provide superior results in terms of accuracy and generalisation.

  8. Vector rectangular-shape laser based on reduced graphene oxide interacting with long fiber taper

    CERN Document Server

    Gao, Lei; Zeng, Jing; Huang, Wei; Liu, Min

    2014-01-01

    A vector dual-wavelength rectangular-shape laser (RSL) based on a long fiber taper deposited with reduced graphene oxide is proposed, where the nonlinearity is enhanced due to large evanescent-field-interacting length and strong field confinement of a 8 mm fiber taper with a waist diameter of 4 micronmeters. Graphene flakes are deposited uniformly on the taper waist with light pressure effect, so this structure guarantees both excellent saturable absorption and high nonlinearity. The RSL with a repetition rate of 7.9 MHz exhibits fast polarization switching in two orthogonal polarization directions, and the temporal and spectral characteristics are investigated. The results suggest that the long taper-based graphene structure is an efficient choice for nonlinear devices.

  9. Tag and Neighbor based Recommender systems for Medical events

    DEFF Research Database (Denmark)

    Bayyapu, Karunakar Reddy; Dolog, Peter

    2010-01-01

    This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag...... in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach....

  10. Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion.

    Science.gov (United States)

    Li, Gang; Liu, Tianming; Nie, Jingxin; Guo, Lei; Malicki, Jarema; Mara, Andrew; Holley, Scott A; Xia, Weiming; Wong, Stephen T C

    2007-10-01

    The zebrafish has become an important vertebrate animal model for the study of developmental biology, functional genomics, and disease mechanisms. It is also being used for drug discovery. Computerized detection of blob objects has been one of the important tasks in quantitative phenotyping of zebrafish. We present a new automated method that is able to detect blob objects, such as nuclei or cells in microscopic zebrafish images. This method is composed of three key steps. The first step is to produce a diffused gradient vector field by a physical elastic deformable model. In the second step, the flux image is computed on the diffused gradient vector field. The third step performs thresholding and nonmaximum suppression based on the flux image. We report the validation and experimental results of this method using zebrafish image datasets from three independent research labs. Both sensitivity and specificity of this method are over 90%. This method is able to differentiate closely juxtaposed or connected blob objects, with high sensitivity and specificity in different situations. It is characterized by a good, consistent performance in blob object detection.

  11. The development of vector based 2.5D print methods for a painting machine

    Science.gov (United States)

    Parraman, Carinna

    2013-02-01

    Through recent trends in the application of digitally printed decorative finishes to products, CAD, 3D additive layer manufacturing and research in material perception, [1, 2] there is a growing interest in the accurate rendering of materials and tangible displays. Although current advances in colour management and inkjet printing has meant that users can take for granted high-quality colour and resolution in their printed images, digital methods for transferring a photographic coloured image from screen to paper is constrained by pixel count, file size, colorimetric conversion between colour spaces and the gamut limits of input and output devices. This paper considers new approaches to applying alternative colour palettes by using a vector-based approach through the application of paint mixtures, towards what could be described as a 2.5D printing method. The objective is to not apply an image to a textured surface, but where texture and colour are integral to the mark, that like a brush, delineates the contours in the image. The paper describes the difference between the way inks and paints are mixed and applied. When transcribing the fluid appearance of a brush stroke, there is a difference between a halftone printed mark and a painted mark. The issue of surface quality is significant to subjective qualities when studying the appearance of ink or paint on paper. The paper provides examples of a range of vector marks that are then transcribed into brush stokes by the painting machine.

  12. Twin Support Vector Machine for Multiple Instance Learning Based on Bag Dissimilarities

    Directory of Open Access Journals (Sweden)

    Divya Tomar

    2016-01-01

    Full Text Available In multiple instance learning (MIL framework, an object is represented by a set of instances referred to as bag. A positive class label is assigned to a bag if it contains at least one positive instance; otherwise a bag is labeled with negative class label. Therefore, the task of MIL is to learn a classifier at bag level rather than at instance level. Traditional supervised learning approaches cannot be applied directly in such kind of situation. In this study, we represent each bag by a vector of its dissimilarities to the other existing bags in the training dataset and propose a multiple instance learning based Twin Support Vector Machine (MIL-TWSVM classifier. We have used different ways to represent the dissimilarity between two bags and performed a comparative analysis of them. The experimental results on ten benchmark MIL datasets demonstrate that the proposed MIL-TWSVM classifier is computationally inexpensive and competitive with state-of-the-art approaches. The significance of the experimental results has been tested by using Friedman statistic and Nemenyi post hoc tests.

  13. Acoustical contribution calculation and analysis of compressor shell based on acoustic transfer vector method

    Science.gov (United States)

    Chen, Xiaol; Guo, Bei; Tuo, Jinliang; Zhou, Ruixin; Lu, Yang

    2017-08-01

    Nowadays, people are paying more and more attention to the noise reduction of household refrigerator compressor. This paper established a sound field bounded by compressor shell and ISO3744 standard field points. The Acoustic Transfer Vector (ATV) in the sound field radiated by a refrigerator compressor shell were calculated which fits the test result preferably. Then the compressor shell surface is divided into several parts. Based on Acoustic Transfer Vector approach, the sound pressure contribution to the field points and the sound power contribution to the sound field of each part were calculated. To obtain the noise radiation in the sound field, the sound pressure cloud charts were analyzed, and the contribution curves in different frequency of each part were acquired. Meanwhile, the sound power contribution of each part in different frequency was analyzed, to ensure those parts where contributes larger sound power. Through the analysis of acoustic contribution, those parts where radiate larger noise on the compressor shell were determined. This paper provides a credible and effective approach on the structure optimal design of refrigerator compressor shell, which is meaningful in the noise and vibration reduction.

  14. Dynamic analysis of suspension cable based on vector form intrinsic finite element method

    Science.gov (United States)

    Qin, Jian; Qiao, Liang; Wan, Jiancheng; Jiang, Ming; Xia, Yongjun

    2017-10-01

    A vector finite element method is presented for the dynamic analysis of cable structures based on the vector form intrinsic finite element (VFIFE) and mechanical properties of suspension cable. Firstly, the suspension cable is discretized into different elements by space points, the mass and external forces of suspension cable are transformed into space points. The structural form of cable is described by the space points at different time. The equations of motion for the space points are established according to the Newton’s second law. Then, the element internal forces between the space points are derived from the flexible truss structure. Finally, the motion equations of space points are solved by the central difference method with reasonable time integration step. The tangential tension of the bearing rope in a test ropeway with the moving concentrated loads is calculated and compared with the experimental data. The results show that the tangential tension of suspension cable with moving loads is consistent with the experimental data. This method has high calculated precision and meets the requirements of engineering application.

  15. Support Vector Machine Based Mobility Prediction Scheme in Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Jiamei Chen

    2015-01-01

    Full Text Available To improve the intelligence of the mobile-aware applications in the heterogeneous wireless networks (HetNets, it is essential to establish an advanced mechanism to anticipate the change of the user location in every subnet for HetNets. This paper proposes a multiclass support vector machine based mobility prediction (Multi-SVMMP scheme to estimate the future location of mobile users according to the movement history information of each user in HetNets. In the location prediction process, the regular and random user movement patterns are treated differently, which can reflect the user movements more realistically than the existing movement models in HetNets. And different forms of multiclass support vector machines are embedded in the two mobility patterns according to the different characteristics of the two mobility patterns. Moreover, the introduction of target region (TR cuts down the energy consumption efficiently without impacting the prediction accuracy. As reported in the simulations, our Multi-SVMMP can overcome the difficulties found in the traditional methods and obtain a higher prediction accuracy and user adaptability while reducing the cost of prediction resources.

  16. Carbohydrate-Based Ice Recrystallization Inhibitors Increase Infectivity and Thermostability of Viral Vectors

    Science.gov (United States)

    Ghobadloo, Shahrokh M.; Balcerzak, Anna K.; Gargaun, Ana; Muharemagic, Darija; Mironov, Gleb G.; Capicciotti, Chantelle J.; Briard, Jennie G.; Ben, Robert N.; Berezovski, Maxim V.

    2014-07-01

    The inability of vaccines to retain sufficient thermostability has been an obstacle to global vaccination programs. To address this major limitation, we utilized carbohydrate-based ice recrystallization inhibitors (IRIs) to eliminate the cold chain and stabilize the potency of Vaccinia virus (VV), Vesicular Stomatitis virus (VSV) and Herpes virus-1 (HSV-1). The impact of these IRIs was tested on the potency of the viral vectors using a plaque forming unit assay following room temperature storage, cryopreservation with successive freeze-thaw cycles and lyophilization. Viral potency after storage with all three conditions demonstrated that N-octyl-gluconamide (NOGlc) recovered the infectivity of shelf stored VV, 5.6 Log10 PFU mL-1 during 40 days, and HSV-1, 2.7 Log10 PFU mL-1 during 9 days. Carbon-linked antifreeze glycoprotein analogue ornithine-glycine-glycine-galactose (OGG-Gal) increases the recovery of VV and VSV more than 1 Log10 PFU mL-1 after 10 freeze-thaw cycles. In VSV, cryostorage with OGG-Gal maintains high infectivity and reduces temperature-induced aggregation of viral particles by 2 times that of the control. In total, OGG-Gal and NOGlc preserve virus potency during cryostorage. Remarkably, NOGlc has potential to eliminate the cold chain and permit room temperature storage of viral vectors.

  17. Modulational instability in a PT-symmetric vector nonlinear Schrödinger system

    Science.gov (United States)

    Cole, J. T.; Makris, K. G.; Musslimani, Z. H.; Christodoulides, D. N.; Rotter, S.

    2016-12-01

    A class of exact multi-component constant intensity solutions to a vector nonlinear Schrödinger (NLS) system in the presence of an external PT-symmetric complex potential is constructed. This type of uniform wave pattern displays a non-trivial phase whose spatial dependence is induced by the lattice structure. In this regard, light can propagate without scattering while retaining its original form despite the presence of inhomogeneous gain and loss. These constant-intensity continuous waves are then used to perform a modulational instability analysis in the presence of both non-hermitian media and cubic nonlinearity. A linear stability eigenvalue problem is formulated that governs the dynamical evolution of the periodic perturbation and its spectrum is numerically determined using Fourier-Floquet-Bloch theory. In the self-focusing case, we identify an intensity threshold above which the constant-intensity modes are modulationally unstable for any Floquet-Bloch momentum belonging to the first Brillouin zone. The picture in the self-defocusing case is different. Contrary to the bulk vector case, where instability develops only when the waves are strongly coupled, here an instability occurs in the strong and weak coupling regimes. The linear stability results are supplemented with direct (nonlinear) numerical simulations.

  18. Antagonistic plant defense system regulated by phytohormones assists interactions among vector insect, thrips and a tospovirus.

    Science.gov (United States)

    Abe, Hiroshi; Tomitaka, Yasuhiro; Shimoda, Takeshi; Seo, Shigemi; Sakurai, Tamito; Kugimiya, Soichi; Tsuda, Shinya; Kobayashi, Masatomo

    2012-01-01

    The western flower thrips (Frankliniella occidentalis) is a polyphagous herbivore that causes serious damage to many agricultural plants. In addition to causing feeding damage, it is also a vector insect that transmits tospoviruses such as Tomato spotted wilt virus (TSWV). We previously reported that thrips feeding on plants induces a jasmonate (JA)-regulated plant defense, which negatively affects both the performance and preference (i.e. host plant attractiveness) of the thrips. The antagonistic interaction between a JA-regulated plant defense and a salicylic acid (SA)-regulated plant defense is well known. Here we report that TSWV infection allows thrips to feed heavily and multiply on Arabidopsis plants. TSWV infection elevated SA contents and induced SA-regulated gene expression in the plants. On the other hand, TSWV infection decreased the level of JA-regulated gene expression induced by thrips feeding. Importantly, we also demonstrated that thrips significantly preferred TSWV-infected plants to uninfected plants. In JA-insensitive coi1-1 mutants, however, thrips did not show a preference for TSWV-infected plants. In addition, SA application to wild-type plants increased their attractiveness to thrips. Our results suggest the following mechanism: TSWV infection suppresses the anti-herbivore response in plants and attracts its vector, thrips, to virus-infected plants by exploiting the antagonistic SA-JA plant defense systems.

  19. An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

    Science.gov (United States)

    Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

    2016-01-01

    For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

  20. Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform.

    Science.gov (United States)

    Ben Salem, Samira; Bacha, Khmais; Chaari, Abdelkader

    2012-09-01

    In this work we suggest an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can create two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two fault signatures are subsequently analysed using the classical fast Fourier transform (FFT). The effects of mechanical faults on the HMCSV and HPCSV spectrums are described, and the related frequencies are determined. The magnitudes of spectral components, relative to the studied faults (air-gap eccentricity and outer raceway ball bearing defect), are extracted in order to develop the input vector necessary for learning and testing the support vector machine with an aim of classifying automatically the various states of the induction motor. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Ulrike Dackermann

    2017-12-01

    Full Text Available This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced, and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%.

  2. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

    Science.gov (United States)

    Barnes, Kayla G; Weedall, Gareth D; Ndula, Miranda; Irving, Helen; Mzihalowa, Themba; Hemingway, Janet; Wondji, Charles S

    2017-02-01

    Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

  3. Data-Based Control for Humanoid Robots Using Support Vector Regression, Fuzzy Logic, and Cubature Kalman Filter

    Directory of Open Access Journals (Sweden)

    Liyang Wang

    2016-01-01

    Full Text Available Time-varying external disturbances cause instability of humanoid robots or even tip robots over. In this work, a trapezoidal fuzzy least squares support vector regression- (TF-LSSVR- based control system is proposed to learn the external disturbances and increase the zero-moment-point (ZMP stability margin of humanoid robots. First, the humanoid states and the corresponding control torques of the joints for training the controller are collected by implementing simulation experiments. Secondly, a TF-LSSVR with a time-related trapezoidal fuzzy membership function (TFMF is proposed to train the controller using the simulated data. Thirdly, the parameters of the proposed TF-LSSVR are updated using a cubature Kalman filter (CKF. Simulation results are provided. The proposed method is shown to be effective in learning and adapting occasional external disturbances and ensuring the stability margin of the robot.

  4. Eco-bio-social research on community-based approaches for Chagas disease vector control in Latin America

    Science.gov (United States)

    Gürtler, Ricardo E.; Yadon, Zaida E.

    2015-01-01

    This article provides an overview of three research projects which designed and implemented innovative interventions for Chagas disease vector control in Bolivia, Guatemala and Mexico. The research initiative was based on sound principles of community-based ecosystem management (ecohealth), integrated vector management, and interdisciplinary analysis. The initial situational analysis achieved a better understanding of ecological, biological and social determinants of domestic infestation. The key factors identified included: housing quality; type of peridomestic habitats; presence and abundance of domestic dogs, chickens and synanthropic rodents; proximity to public lights; location in the periphery of the village. In Bolivia, plastering of mud walls with appropriate local materials and regular cleaning of beds and of clothes next to the walls, substantially decreased domestic infestation and abundance of the insect vector Triatoma infestans. The Guatemalan project revealed close links between house infestation by rodents and Triatoma dimidiata, and vector infection with Trypanosoma cruzi. A novel community-operated rodent control program significantly reduced rodent infestation and bug infection. In Mexico, large-scale implementation of window screens translated into promising reductions in domestic infestation. A multi-pronged approach including community mobilisation and empowerment, intersectoral cooperation and adhesion to integrated vector management principles may be the key to sustainable vector and disease control in the affected regions. PMID:25604759

  5. Engineering web maps with gradual content zoom based on streaming vector data

    Science.gov (United States)

    Huang, Lina; Meijers, Martijn; Šuba, Radan; van Oosterom, Peter

    2016-04-01

    Vario-scale data structures have been designed to support gradual content zoom and the progressive transfer of vector data, for use with arbitrary map scales. The focus to date has been on the server side, especially on how to convert geographic data into the proposed vario-scale structures by means of automated generalisation. This paper contributes to the ongoing vario-scale research by focusing on the client side and communication, particularly on how this works in a web-services setting. It is claimed that these functionalities are urgently needed, as many web-based applications, both desktop and mobile, require gradual content zoom, progressive transfer and a high performance level. The web-client prototypes developed in this paper make it possible to assess the behaviour of vario-scale data and to determine how users will actually see the interactions. Several different options of web-services communication architectures are possible in a vario-scale setting. These options are analysed and tested with various web-client prototypes, with respect to functionality, ease of implementation and performance (amount of transmitted data and response times). We show that the vario-scale data structure can fit in with current web-based architectures and efforts to standardise map distribution on the internet. However, to maximise the benefits of vario-scale data, a client needs to be aware of this structure. When a client needs a map to be refined (by means of a gradual content zoom operation), only the 'missing' data will be requested. This data will be sent incrementally to the client from a server. In this way, the amount of data transferred at one time is reduced, shortening the transmission time. In addition to these conceptual architecture aspects, there are many implementation and tooling design decisions at play. These will also be elaborated on in this paper. Based on the experiments conducted, we conclude that the vario-scale approach indeed supports gradual

  6. Singular vector based targeted observations of chemical constituents: description and first application of the EURAD-IM-SVA

    Science.gov (United States)

    Goris, N.; Elbern, H.

    2015-08-01

    Measurements of the large dimensional chemical state of the atmosphere provide only sparse snapshots of the state of the system due to their typically insufficient temporal and spatial density. In order to optimize the measurement configurations despite those limitations, the present work describes the identification of sensitive states of the chemical system as optimal target areas for adaptive observations. For this purpose, the technique of singular vector analysis (SVA), which has been proved effective for targeted observations in numerical weather predication, is implemented into the chemical transport model EURAD-IM (EURopean Air pollution and Dispersion - Inverse Model) yielding the EURAD-IM-SVA. Besides initial values, emissions are investigated as critical simulation controlling targeting variables. For both variants, singular vectors are applied to determine the optimal placement for observations and moreover to quantify which chemical compounds have to be observed with preference. Based on measurements of the airship based ZEPTER-2 campaign, the EURAD-IM-SVA has been evaluated by conducting a comprehensive set of model runs involving different initial states and simulation lengths. Since the considered cases are restricted in terms of considered chemical compounds and selected areas, they allow for a retracing of the results and a confirmation of their correctness. Our analysis shows that the optimal placement for observations of chemical species is not entirely determined by mere transport and mixing processes. Rather, a combination of initial chemical concentrations, chemical conversions, and meteorological processes determine the influence of chemical compounds and regions. We furthermore demonstrate that the optimal placement of observations of emission strengths is highly dependent on the location of emission sources and that the benefit of including emissions as target variables outperforms the value of initial value optimisation with growing

  7. SVMQA: support-vector-machine-based protein single-model quality assessment.

    Science.gov (United States)

    Manavalan, Balachandran; Lee, Jooyoung

    2017-08-15

    The accurate ranking of predicted structural models and selecting the best model from a given candidate pool remain as open problems in the field of structural bioinformatics. The quality assessment (QA) methods used to address these problems can be grouped into two categories: consensus methods and single-model methods. Consensus methods in general perform better and attain higher correlation between predicted and true quality measures. However, these methods frequently fail to generate proper quality scores for native-like structures which are distinct from the rest of the pool. Conversely, single-model methods do not suffer from this drawback and are better suited for real-life applications where many models from various sources may not be readily available. In this study, we developed a support-vector-machine-based single-model global quality assessment (SVMQA) method. For a given protein model, the SVMQA method predicts TM-score and GDT_TS score based on a feature vector containing statistical potential energy terms and consistency-based terms between the actual structural features (extracted from the three-dimensional coordinates) and predicted values (from primary sequence). We trained SVMQA using CASP8, CASP9 and CASP10 targets and determined the machine parameters by 10-fold cross-validation. We evaluated the performance of our SVMQA method on various benchmarking datasets. Results show that SVMQA outperformed the existing best single-model QA methods both in ranking provided protein models and in selecting the best model from the pool. According to the CASP12 assessment, SVMQA was the best method in selecting good-quality models from decoys in terms of GDTloss. SVMQA method can be freely downloaded from http://lee.kias.re.kr/SVMQA/SVMQA_eval.tar.gz. jlee@kias.re.kr. Supplementary data are available at Bioinformatics online.

  8. Hydrogel based occlusion systems

    NARCIS (Netherlands)

    Stam, F.A.; Jackson, N.; Dubruel, P.; Adesanya, K.; Embrechts, A.; Mendes, E.; Neves, H.P.; Herijgers, P.; Verbrugghe, Y.; Shacham, Y.; Engel, L.; Krylov, V.

    2013-01-01

    A hydrogel based occlusion system, a method for occluding vessels, appendages or aneurysms, and a method for hydrogel synthesis are disclosed. The hydrogel based occlusion system includes a hydrogel having a shrunken and a swollen state and a delivery tool configured to deliver the hydrogel to a

  9. Electrocardiogram Pattern Recognition and Analysis Based on Artificial Neural Networks and Support Vector Machines: A Review

    Directory of Open Access Journals (Sweden)

    Mario Sansone

    2013-01-01

    Full Text Available Computer systems for Electrocardiogram (ECG analysis support the clinician in tedious tasks (e.g., Holter ECG monitored in Intensive Care Units or in prompt detection of dangerous events (e.g., ventricular fibrillation. Together with clinical applications (arrhythmia detection and heart rate variability analysis, ECG is currently being investigated in biometrics (human identification, an emerging area receiving increasing attention. Methodologies for clinical applications can have both differences and similarities with respect to biometrics. This paper reviews methods of ECG processing from a pattern recognition perspective. In particular, we focus on features commonly used for heartbeat classification. Considering the vast literature in the field and the limited space of this review, we dedicated a detailed discussion only to a few classifiers (Artificial Neural Networks and Support Vector Machines because of their popularity; however, other techniques such as Hidden Markov Models and Kalman Filtering will be also mentioned.

  10. Form factor for a two-particle system within a relativistic quasipotential approach: Case of arbitrary masses and of a vector current

    Energy Technology Data Exchange (ETDEWEB)

    Chernichenko, Yu. D., E-mail: chern@gstu.by, E-mail: chyud@mail.ru [Pavel Sukhoi State Technical University of Gomel (Belarus)

    2015-03-15

    A new relativistic form factor for a bound two-particle system was obtained for the case of a vector current. The present consideration was performed within the relativistic quasipotential approach based on the covariant Hamiltonian formulation of quantum field theory by going over to the three-dimensional relativistic configuration representation for the case of interaction between two relativistic spinless particles of arbitrary mass.

  11. Object Based Systems Engineering

    Science.gov (United States)

    2011-10-17

    Based Systems Engineering ( MBSE ) has shifted the emphasis of the Systems Engineering community away from documents towards view-based artifacts. These...Engineering lies primarily in these objects, not the containers that deliver them. FIGURE 1: Evolution of Systems Engineering Practice MBSE ...capture minority viewpoints and discussion threads associated with each object of interest. If the majority view doesn’t lead to success, this data may

  12. Oral Delivery of a Novel Recombinant Streptococcus mitis Vector Elicits Robust Vaccine Antigen-Specific Oral Mucosal and Systemic Antibody Responses and T Cell Tolerance.

    Directory of Open Access Journals (Sweden)

    Emily Xie

    Full Text Available The pioneer human oral commensal bacterium Streptococcus mitis has unique biologic features that make it an attractive mucosal vaccine or therapeutic delivery vector. S. mitis is safe as a natural persistent colonizer of the mouth, throat and nasopharynx and the oral commensal bacterium is capable of inducing mucosal antibody responses. A recombinant S. mitis (rS. mitis that stably expresses HIV envelope protein was generated and tested in the germ-free mouse model to evaluate the potential usefulness of this vector as a mucosal vaccine against HIV. Oral vaccination led to the efficient and persistent bacterial colonization of the mouth and the induction of both salivary and systemic antibody responses. Interestingly, persistently colonized animals developed antigen-specific systemic T cell tolerance. Based on these findings we propose the use of rS. mitis vaccine vector for the induction of mucosal antibodies that will prevent the penetration of the mucosa by pathogens such as HIV. Moreover, the first demonstration of rS. mitis having the ability to elicit T cell tolerance suggest the potential use of rS. mitis as an immunotherapeutic vector to treat inflammatory, allergic and autoimmune diseases.

  13. Oral Delivery of a Novel Recombinant Streptococcus mitis Vector Elicits Robust Vaccine Antigen-Specific Oral Mucosal and Systemic Antibody Responses and T Cell Tolerance

    Science.gov (United States)

    Xie, Emily; Kotha, Abhiroop; Biaco, Tracy; Sedani, Nikita; Zou, Jonathan; Stashenko, Phillip; Duncan, Margaret J.; Campos-Neto, Antonio; Cayabyab, Mark J.

    2015-01-01

    The pioneer human oral commensal bacterium Streptococcus mitis has unique biologic features that make it an attractive mucosal vaccine or therapeutic delivery vector. S. mitis is safe as a natural persistent colonizer of the mouth, throat and nasopharynx and the oral commensal bacterium is capable of inducing mucosal antibody responses. A recombinant S. mitis (rS. mitis) that stably expresses HIV envelope protein was generated and tested in the germ-free mouse model to evaluate the potential usefulness of this vector as a mucosal vaccine against HIV. Oral vaccination led to the efficient and persistent bacterial colonization of the mouth and the induction of both salivary and systemic antibody responses. Interestingly, persistently colonized animals developed antigen-specific systemic T cell tolerance. Based on these findings we propose the use of rS. mitis vaccine vector for the induction of mucosal antibodies that will prevent the penetration of the mucosa by pathogens such as HIV. Moreover, the first demonstration of rS. mitis having the ability to elicit T cell tolerance suggest the potential use of rS. mitis as an immunotherapeutic vector to treat inflammatory, allergic and autoimmune diseases. PMID:26618634

  14. Towards PLDA-RBM based speaker recognition in mobile environment: Designing stacked/deep PLDA-RBM systems

    DEFF Research Database (Denmark)

    Nautsch, Andreas; Hao, Hong; Stafylakis, Themos

    2016-01-01

    The vast majority of text-independent speaker recognition systems rely on intermediate-sized vectors (i-vectors), which are compared by probabilistic linear discriminant analysis (PLDA). This paper proposes a PLDA-alike approach with restricted Boltzmann machines for i-vector based speaker...

  15. Unmarked gene deletion and host-vector system for the hyperthermophilic crenarchaeon Sulfolobus islandicus

    DEFF Research Database (Denmark)

    Deng, Ling; Zhu, Haojun; Chen, Zhengjun

    2009-01-01

    , and unmarked lacS mutants were obtained by each method. A new alternative recombination mechanism, i.e., marker circularization and integration, was shown to operate in the latter method, which did not yield the designed deletion mutation. Subsequently, Sulfolobus-E. coli plasmid shuttle vectors were...... constructed, which genetically complemented DeltapyrEFDeltalacS mutation after transformation. Thus, a complete set of genetic tools was established for S. islandicus with pyrEF and lacS as genetic markers.......Sulfolobus islandicus is being used as a model for studying archaeal biology, geo-biology and evolution. However, no genetic system is available for this organism. To produce an S. islandicus mutant suitable for genetic analyses, we screened for colonies with a spontaneous pyrEF mutation. One...

  16. Biology of Adeno-Associated Viral Vectors in the Central Nervous System

    Directory of Open Access Journals (Sweden)

    Giridhar eMurlidharan

    2014-09-01

    Full Text Available Gene therapy is a promising approach for treating a spectrum of neurological and neurodegenerative disorders by delivering corrective genes to the central nervous system (CNS. In particular, Adeno-Associated Viruses (AAV have emerged as promising tools for clinical gene transfer in a broad range of genetic disorders with neurological manifestations. In the current review, we have attempted to bridge our understanding of the biology of different AAV strains with their transduction profiles, cellular tropisms and transport mechanisms within the CNS. Continued efforts to dissect AAV-host interactions within the brain are likely to aid in the development of improved vectors for CNS-directed gene transfer applications in the clinic.

  17. Optimization of novel vector systems for functional genomics in cancer research

    DEFF Research Database (Denmark)

    Schmidt, Steffen

    Optimization of novel vector systems for functional genomics in cancer research Steffen Schmidt1*, Stephanie Blaich2, Rainer Wittig3, Stefan Lyer4, Caroline End2, Melanie Hudler2, Lukasz Kacprzyk2, Angela Riedel1,2, Helle Christiansen1, Jan Mollenhauer1,2 1 Molekylær Onkologi, Medicinsk...... for Lokal Tumor Terapi, Universitet Hospital, Waldstraße1, 91054 Erlangen, Tyskland * Præsenterende forfatter Large datasets about differentially expressed genes in cancer tissue have been recovered by expression profiling using microarray technologies. To study the effects of these genes in cancer cells...... will lead to an improved understanding of the molecular mechanisms underlying cancer and may result in the identification of novel druggable targets for cancer treatment. We established a novel rapid technique to generate stable cell lines with inducible overexpression of genes. This enables for functional...

  18. Parameters sensitivity analysis of underground excavation impacting on slope stability based on Vector Sum Method

    Science.gov (United States)

    Chen, Quan

    2018-01-01

    The impact of underground excavation on slope stability is controlled by many parameters, including the shape of slope, the mechanical property of soil and rock, the relative position of excavation zone and slip surface, and so on. The factor of safety (FOS) base on limit equilibrium method (LEM) and strength reduction method (SRM) is not suitable to evaluate the impact. Vector sum method (VSM) and orthogonal experiment are used to evaluate the impact by doing parameters sensitivity analysis. The result shows that the VSM could be used to in this research field, and the gradient of a slope, the relative position between a excavation area and a slope, the cohesion are the top three factors which impact the stability significantly.

  19. Optical image encoding based on digital holographic recording on polarization state of vector wave.

    Science.gov (United States)

    Lin, Chao; Shen, Xueju; Xu, Qinzu

    2013-10-01

    We propose and analyze a compact optical image encoder based on the principle of digital holographic recording on the polarization state of a vector wave. The optical architecture is a Mach-Zehnder interferometer with in-line digital holographic recording mechanism. The original image is represented by distinct polarization states of elliptically polarized light. This state of polarization distribution is scrambled and then recorded by a two-step digital polarization holography method with random phase distributed reference wave. Introduction of a rotation key in the object arm and phase keys in the reference arm can achieve the randomization of plaintext. Statistical property of cyphertext is analyzed from confusion and diffusion point of view. Fault tolerance and key sensitivity of the proposed approach are also investigated. A chosen plaintext attack on the proposed algorithm exhibits its high security level. Simulation results that support the theoretical analysis are presented.

  20. Prediction of mitochondrial proteins based on genetic algorithm - partial least squares and support vector machine.

    Science.gov (United States)

    Tan, F; Feng, X; Fang, Z; Li, M; Guo, Y; Jiang, L

    2007-11-01

    Mitochondria are essential cell organelles of eukaryotes. Hence, it is vitally important to develop an automated and reliable method for timely identification of novel mitochondrial proteins. In this study, mitochondrial proteins were encoded by dipeptide composition technology; then, the genetic algorithm-partial least square (GA-PLS) method was used to evaluate the dipeptide composition elements which are more important in recognizing mitochondrial proteins; further, these selected dipeptide composition elements were applied to support vector machine (SVM)-based classifiers to predict the mitochondrial proteins. All the models were trained and validated by the jackknife cross-validation test. The prediction accuracy is 85%, suggesting that it performs reasonably well in predicting the mitochondrial proteins. Our results strongly imply that not all the dipeptide compositions are informative and indispensable for predicting proteins. The source code of MATLAB and the dataset are available on request under liml@scu.edu.cn.

  1. Vector Extrapolation-Based Acceleration of Regularized Richardson Lucy Image Deblurring

    Science.gov (United States)

    Remmele, Steffen; Hesser, Jürgen

    Confocal fluorescence microscopy has become an important tool in biological and medical sciences for imaging thin specimen, even living ones. Due to out-of-focus blurring and noise the acquired images are degraded and thus it is necessary to restore them. One of the most popular methods is an iterative Richardson-Lucy algorithm with total variation regularization. This algorithm while improving the image quality is converging slowly whereas with a constantly increasing amount of image data fast methods are required. In this paper, we present an accelerated version of the algorithm and investigate the achieved speed up. The acceleration method is based on a vector extrapolation technique and avoids a computational intensive evaluation of the underlying cost function. To evaluate the acceleration two synthetic test images are used. The accelerated algorithm reaches an acceptable result within 30% to 40% less computational time.

  2. Fast Fourier transform-based support vector machine for subcellular localization prediction using different substitution models.

    Science.gov (United States)

    Wang, Zhimeng; Jiang, Lin; Li, Menglong; Sun, Lina; Lin, Rongying

    2007-09-01

    There are approximately 10(9) proteins in a cell. A hotspot in bioinformatics is how to identify a protein subcellular localization, if its sequence is known. In this paper, a method using fast Fourier transform-based support vector machine is developed to predict the subcellular localization of proteins from their physicochemical properties and structural parameters. The prediction accuracies reached 83% in prokaryotic organisms and 84% in eukaryotic organisms with the substitution model of the c-p-v matrix (c, composition; p, polarity; and v, molecular volume). The overall prediction accuracy was also evaluated using the "leave-one-out" jackknife procedure. The influence of the substitution model on prediction accuracy has also been discussed in the work. The source code of the new program is available on request from the authors.

  3. A scatter-based prototype framework and multi-class extension of support vector machines.

    Directory of Open Access Journals (Sweden)

    Robert Jenssen

    Full Text Available We provide a novel interpretation of the dual of support vector machines (SVMs in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. This enables us to implement computationally efficient solvers based on sequential minimal and chunking optimization. As a further contribution, the primal problem formulation is developed in terms of regularized risk minimization and the hinge loss, revealing the score function to be used in the actual classification of test patterns. We investigate Scatter SVM properties related to generalization ability, computational efficiency, sparsity and sensitivity maps, and report promising results.

  4. FINGERPRINT CLASSIFICATION BASED ON RECURSIVE NEURAL NETWORK WITH SUPPORT VECTOR MACHINE

    Directory of Open Access Journals (Sweden)

    T. Chakravarthy

    2011-01-01

    Full Text Available Fingerprint classification based on statistical and structural (RNN and SVM approach. RNNs are trained on a structured representation of the fingerprint image. They are also used to extract a set of distributed features of the fingerprint which can be integrated in this support vector machine. SVMs are combined with a new error correcting codes scheme. This approach has two main advantages. (a It can tolerate the presence of ambiguous fingerprint images in the training set and (b It can effectively identify the most difficult fingerprint images in the test set. In this experiment on the fingerprint database NIST-4 (National Institute of Science and Technology, our best classification accuracy of 94.7% is obtained by training SVM on both fingerCode and RNN –extracted futures of segmentation algorithm which has used very sophisticated “region growing process”.

  5. Ambient Air Quality Classification by Grey Wolf Optimizer Based Support Vector Machine

    Science.gov (United States)

    Shekhawat, Shalini

    2017-01-01

    With the development of society along with an escalating population, the concerns regarding public health have cropped up. The quality of air becomes primary concern regarding constant increase in the number of vehicles and industrial development. With this concern, several indices have been proposed to indicate the pollutant concentrations. In this paper, we present a mathematical framework to formulate a Cumulative Index (CI) on the basis of an individual concentration of four major pollutants (SO2, NO2, PM2.5, and PM10). Further, a supervised learning algorithm based classifier is proposed. This classifier employs support vector machine (SVM) to classify air quality into two types, that is, good or harmful. The potential inputs for this classifier are the calculated values of CIs. The efficacy of the classifier is tested on the real data of three locations: Kolkata, Delhi, and Bhopal. It is observed that the classifier performs well to classify the quality of air. PMID:28890728

  6. Content-Based Discovery for Web Map Service using Support Vector Machine and User Relevance Feedback.

    Science.gov (United States)

    Hu, Kai; Gui, Zhipeng; Cheng, Xiaoqiang; Qi, Kunlun; Zheng, Jie; You, Lan; Wu, Huayi

    2016-01-01

    Many discovery methods for geographic information services have been proposed. There are approaches for finding and matching geographic information services, methods for constructing geographic information service classification schemes, and automatic geographic information discovery. Overall, the efficiency of the geographic information discovery keeps improving., There are however, still two problems in Web Map Service (WMS) discovery that must be solved. Mismatches between the graphic contents of a WMS and the semantic descriptions in the metadata make discovery difficult for human users. End-users and computers comprehend WMSs differently creating semantic gaps in human-computer interactions. To address these problems, we propose an improved query process for WMSs based on the graphic contents of WMS layers, combining Support Vector Machine (SVM) and user relevance feedback. Our experiments demonstrate that the proposed method can improve the accuracy and efficiency of WMS discovery.

  7. High efficiency mode-locked, cylindrical vector beam fiber laser based on a mode selective coupler.

    Science.gov (United States)

    Wan, Hongdan; Wang, Jie; Zhang, Zuxing; Cai, Yu; Sun, Bin; Zhang, Lin

    2017-05-15

    We propose and demonstrate an all-fiber passively mode-locked laser with a figure-8 cavity, which generates pulsed cylindrical vector beam output based on a mode selective coupler (MSC). The MSC made of a two mode fiber and a standard single mode fiber is used as both the intracavity transverse mode converter and mode splitter with a low insertion loss of about 0.65 dB. The slope efficiency of the fiber laser is > 3%. Through adjusting the polarization state in the laser cavity, both radially and azimuthally polarized beams have been obtained with high mode purity which are measured to be > 94%. The laser operates at 1556.3 nm with a spectral bandwidth of 3.2 nm. The mode-locked pulses have duration of 17 ns and a repetition rate of 0.66 MHz.

  8. Identification algorithm of the right part of a dynamic system described with non-linear vector stochastic equation

    OpenAIRE

    Sokolov, Sergey V.; Shcherban', I. V.; Shcherban', O. G.

    2007-01-01

    Identification algorithm of the right part of a dynamic system described with non-linear vector stochastic equation is considered. The main benefit of the suggested approach is the possibility of forming in real time and in explicit form the searched function’s right part approximate estimation of the object’s differential equations system.

  9. Simple downstream process based on detergent treatment improves yield and in vivo transduction efficacy of adeno-associated virus vectors

    Directory of Open Access Journals (Sweden)

    Gabriella Dias Florencio

    2015-01-01

    Full Text Available Recombinant adeno-associated viruses (rAAV are promising candidates for gene therapy approaches. The last two decades were particularly fruitful in terms of processes applied in the production and purification of this type of gene transfer vectors. This rapid technological evolution led to better yields and higher levels of vector purity. Recently, some reports showed that rAAV produced by transient tri-transfection method in adherent human embryonic kidney 293 cells can be harvested directly from supernatant, leading to easier and faster purification compared to classical virus extraction from cell pellets. Here, we compare these approaches with new vector recovery method using small quantity of detergent at the initial clarification step to treat the whole transfected cell culture. Coupled with tangential flow filtration and iodixanol-based isopycnic density gradient, this new method significantly increases rAAV yields and conserves high vector purity. Moreover, this approach leads to the reduction of the total process duration. Finally, the vectors maintain their functionality, showing unexpected higher in vitro and in vivo transduction efficacies. This new development in rAAV downstream process once more demonstrates the great capacity of these vectors to easily accommodate to large panel of methods, able to furthermore ameliorate their safety, functionality, and scalability.

  10. Simplified production and concentration of HIV-1-based lentiviral vectors using HYPERFlask vessels and anion exchange membrane chromatography

    Science.gov (United States)

    Kutner, Robert H; Puthli, Sharon; Marino, Michael P; Reiser, Jakob

    2009-01-01

    Background During the past twelve years, lentiviral (LV) vectors have emerged as valuable tools for transgene delivery because of their ability to transduce nondividing cells and their capacity to sustain long-term transgene expression in target cells in vitro and in vivo. However, despite significant progress, the production and concentration of high-titer, high-quality LV vector stocks is still cumbersome and costly. Methods Here we present a simplified protocol for LV vector production on a laboratory scale using HYPERFlask vessels. HYPERFlask vessels are high-yield, high-performance flasks that utilize a multilayered gas permeable growth surface for efficient gas exchange, allowing convenient production of high-titer LV vectors. For subsequent concentration of LV vector stocks produced in this way, we describe a facile protocol involving Mustang Q anion exchange membrane chromatography. Results Our results show that unconcentrated LV vector stocks with titers in excess of 108 transduction units (TU) per ml were obtained using HYPERFlasks and that these titers were higher than those produced in parallel using regular 150-cm2 tissue culture dishes. We also show that up to 500 ml of an unconcentrated LV vector stock prepared using a HYPERFlask vessel could be concentrated using a single Mustang Q Acrodisc with a membrane volume of 0.18 ml. Up to 5.3 × 1010 TU were recovered from a single HYPERFlask vessel. Conclusion The protocol described here is easy to implement and should facilitate high-titer LV vector production for preclinical studies in animal models without the need for multiple tissue culture dishes and ultracentrifugation-based concentration protocols. PMID:19220915

  11. Improved Reliability-Based Optimization with Support Vector Machines and Its Application in Aircraft Wing Design

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2015-01-01

    Full Text Available A new reliability-based design optimization (RBDO method based on support vector machines (SVM and the Most Probable Point (MPP is proposed in this work. SVM is used to create a surrogate model of the limit-state function at the MPP with the gradient information in the reliability analysis. This guarantees that the surrogate model not only passes through the MPP but also is tangent to the limit-state function at the MPP. Then, importance sampling (IS is used to calculate the probability of failure based on the surrogate model. This treatment significantly improves the accuracy of reliability analysis. For RBDO, the Sequential Optimization and Reliability Assessment (SORA is employed as well, which decouples deterministic optimization from the reliability analysis. The improved SVM-based reliability analysis is used to amend the error from linear approximation for limit-state function in SORA. A mathematical example and a simplified aircraft wing design demonstrate that the improved SVM-based reliability analysis is more accurate than FORM and needs less training points than the Monte Carlo simulation and that the proposed optimization strategy is efficient.

  12. Development of marine magnetic vector measurement system using AUV and deep-towed vehicle

    Science.gov (United States)

    Sayanagi, K.; Isezaki, N.; Matsuo, J.; Harada, M.; Kasaya, T.; Nishimura, K.; Baba, H.

    2012-04-01

    Marine magnetic survey is one of useful methods in order to investigate the nature of the oceanic crust. Most of the data are, however, intensity of the geomagnetic field without its direction. Therefore we cannot properly apply a physical formula describing the relation between magnetic field and magnetization to analyses of the data. With this problem, Isezaki (1986) developed a shipboard three-component magnetometer which measures the geomagnetic vector at the sea. On the other hand, geophysical surveys near the seafloor have been more and more necessary in order to show the details of the oceanic crust. For instance, development of seabed resources like hydrothermal deposits needs higher resolution surveys compared with conventional surveys at the sea for accurate estimation of abundance of the resources. From these viewpoints, we have been developing a measurement system of the deep-sea geomagnetic vector using AUV and deep-towed vehicle. The measurement system consists of two 3-axis flux-gate magnetometers, an Overhauser magnetometer, an optical fiber gyro, a main unit (control, communication, recording), and an onboard unit. These devices except for the onboard unit are installed in pressure cases (depth limit: 6000m). Thus this measurement system can measure three components and intensity of the geomagnetic field in the deep-sea. In 2009, the first test of the measurement system was carried out in the Kumano Basin using AUV Urashima and towing vehicle Yokosuka Deep-Tow during the R/V Yokosuka YK09-09 cruise. In this test, we sank a small magnetic target to the seafloor, and examined how the system worked. As a result, we successfully detected magnetic anomaly of the target to confirm the expected performance of that in the sea. In 2010, the measurement system was tested in the Bayonnaise Knoll area both using a titanium towing frame during the R/V Bosei-maru cruise and using AUV Urashima during the R/V Yokosuka YK10-17 cruise. The purpose of these tests was

  13. Novel Approach for Automatic Detection of Atrial Fibrillation Based on Inter Beat Intervals and Support Vector Machine

    DEFF Research Database (Denmark)

    Andersen, Rasmus S.; Poulsen, Erik S.; Puthusserypady, Sadasivan

    2017-01-01

    for AF detection based on Inter Beat Intervals (IBI) extracted from long term electrocardiogram (ECG) recordings. Five time-domain features are extracted from the IBIs and a Support Vector Machine (SVM) is used for classification. The results are compared to a state of the art algorithm based on raw ECG...

  14. Insulated Foamy Viral Vectors

    Science.gov (United States)

    Browning, Diana L.; Collins, Casey P.; Hocum, Jonah D.; Leap, David J.; Rae, Dustin T.; Trobridge, Grant D.

    2016-01-01

    Retroviral vector-mediated gene therapy is promising, but genotoxicity has limited its use in the clinic. Genotoxicity is highly dependent on the retroviral vector used, and foamy viral (FV) vectors appear relatively safe. However, internal promoters may still potentially activate nearby genes. We developed insulated FV vectors, using four previously described insulators: a version of the well-studied chicken hypersensitivity site 4 insulator (650cHS4), two synthetic CCCTC-binding factor (CTCF)-based insulators, and an insulator based on the CCAAT box-binding transcription factor/nuclear factor I (7xCTF/NF1). We directly compared these insulators for enhancer-blocking activity, effect on FV vector titer, and fidelity of transfer to both proviral long terminal repeats. The synthetic CTCF-based insulators had the strongest insulating activity, but reduced titers significantly. The 7xCTF/NF1 insulator did not reduce titers but had weak insulating activity. The 650cHS4-insulated FV vector was identified as the overall most promising vector. Uninsulated and 650cHS4-insulated FV vectors were both significantly less genotoxic than gammaretroviral vectors. Integration sites were evaluated in cord blood CD34+ cells and the 650cHS4-insulated FV vector had fewer hotspots compared with an uninsulated FV vector. These data suggest that insulated FV vectors are promising for hematopoietic stem cell gene therapy. PMID:26715244

  15. Application of a wide-range yeast vector (CoMed™ system to recombinant protein production in dimorphic Arxula adeninivorans, methylotrophic Hansenula polymorpha and other yeasts

    Directory of Open Access Journals (Sweden)

    Kunze Gotthard

    2006-11-01

    Full Text Available Abstract Background Yeasts provide attractive expression platforms in combining ease of genetic manipulation and fermentation of a microbial organism with the capability to secrete and to modify proteins according to a general eukaryotic scheme. However, early restriction to a single yeast platform can result in costly and time-consuming failures. It is therefore advisable to assess several selected systems in parallel for the capability to produce a particular protein in desired amounts and quality. A suitable vector must contain a targeting sequence, a promoter element and a selection marker that function in all selected organisms. These criteria are fulfilled by a wide-range integrative yeast expression vector (CoMed™ system based on A. adeninivorans- and H. polymorpha-derived elements that can be introduced in a modular way. Results The vector system and a selection of modular elements for vector design are presented. Individual single vector constructs were used to transform a range of yeast species. Various successful examples are described. A vector with a combination of an rDNA sequence for genomic targeting, the E. coli-derived hph gene for selection and the A. adeninivorans-derived TEF1 promoter for expression control of a GFP (green fluorescent protein gene was employed in a first example to transform eight different species including Hansenula polymorpha, Arxula adeninivorans and others. In a second example, a vector for the secretion of IL-6 was constructed, now using an A. adeninivorans-derived LEU2 gene for selection of recombinants in a range of auxotrophic hosts. In this example, differences in precursor processing were observed: only in A. adeninivorans processing of a MFα1/IL-6 fusion was performed in a faithful way. Conclusion rDNA targeting provides a tool to co-integrate up to 3 different expression plasmids by a single transformation step. Thus, a versatile system is at hand that allows a comparative assessment of newly

  16. A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-25

    This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

  17. Development and Validation of Remote Sensing-Based Surface Inundation Products for Vector-Borne Disease Risk in East Africa

    Science.gov (United States)

    Jensen, K.; McDonald, K. C.; Ceccato, P.; Schroeder, R.; Podest, E.

    2014-12-01

    The potential impact of climate variability and change on the spread of infectious disease is of increasingly critical concern to public health. Newly-available remote sensing datasets may be combined with predictive modeling to develop new capabilities to mitigate risks of vector-borne diseases such as malaria, leishmaniasis, and rift valley fever. We have developed improved remote sensing-based products for monitoring water bodies and inundation dynamics that have potential utility for improving risk forecasts of vector-borne disease epidemics. These products include daily and seasonal surface inundation based on the global mappings of inundated area fraction derived at the 25-km scale from active and passive microwave instruments ERS, QuikSCAT, ASCAT, and SSM/I data - the Satellite Water Microwave Product Series (SWAMPS). Focusing on the East African region, we present validation of this product using multi-temporal classification of inundated areas in this region derived from high resolution PALSAR (100m) and Landsat (30m) observations. We assess historical occurrence of malaria in the east African country of Eritrea with respect to the time series SWAMPS datasets, and we aim to construct a framework for use of these new datasets to improve prediction of future malaria risk in this region. This work is supported through funding from the NASA Applied Sciences Program, the NASA Terrestrial Ecology Program, and the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program. This study is also supported and monitored by National Oceanic and Atmospheric Administration (NOAA) under Grant - CREST Grant # NA11SEC4810004. The statements contained within the manuscript/research article are not the opinions of the funding agency or the U.S. government, but reflect the authors' opinions. This work was conducted in part under the framework of the ALOS Kyoto and Carbon Initiative. ALOS PALSAR data were provided by JAXA EORC.

  18. Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

    Science.gov (United States)

    Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S

    2018-01-01

    The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

  19. Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

    Directory of Open Access Journals (Sweden)

    A H Sabry

    Full Text Available The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

  20. Chromosomal manipulation by site-specific recombinases and fluorescent protein-based vectors.

    Directory of Open Access Journals (Sweden)

    Munehiro Uemura

    Full Text Available Feasibility of chromosomal manipulation in mammalian cells was first reported 15 years ago. Although this technique is useful for precise understanding of gene regulation in the chromosomal context, a limited number of laboratories have used it in actual practice because of associated technical difficulties. To overcome the practical hurdles, we developed a Cre-mediated chromosomal recombination system using fluorescent proteins and various site-specific recombinases. These techniques enabled quick construction of targeting vectors, easy identification of chromosome-rearranged cells, and rearrangement leaving minimum artificial elements at junctions. Applying this system to a human cell line, we successfully recapitulated two types of pathogenic chromosomal translocations in human diseases: MYC/IgH and BCR/ABL1. By inducing recombination between two loxP sites targeted into the same chromosome, we could mark cells harboring deletion or duplication of the inter-loxP segments with different colors of fluorescence. In addition, we demonstrated that the intrachromosomal recombination frequency is inversely proportional to the distance between two recombination sites, implicating a future application of this frequency as a proximity sensor. Our method of chromosomal manipulation can be employed for particular cell types in which gene targeting is possible (e.g. embryonic stem cells. Experimental use of this system would open up new horizons in genome biology, including the establishment of cellular and animal models of diseases caused by translocations and copy-number variations.

  1. Vector velocimeter

    DEFF Research Database (Denmark)

    2012-01-01

    for generation of a reference beam, a detector system comprising a first detector arrangement arranged in such a way that the signal beam and the reference beam are incident upon the first detector arrangement with the reference beam propagating at an angle relative to a signal beam, and wherein the first......The present invention relates to a compact, reliable and low-cost vector velocimeter for example for determining velocities of particles suspended in a gas or fluid flow, or for determining velocity, displacement, rotation, or vibration of a solid surface, the vector velocimeter comprising a laser...... assembly for emission of a measurement beam for illumination of an object in a measurement volume with coherent light whereby a signal beam emanating from the object in the measurement volume is formed in response to illumination of the object by the measurement beam, a reference beam generator...

  2. Hydrogel based occlusion systems

    OpenAIRE

    Stam, F.A.; Jackson, N.; Dubruel, P.; Adesanya, K.; Embrechts, A.; Mendes, E.; Neves, H.P.; Herijgers, P.; Verbrugghe, Y.; Shacham, Y.; Engel, L; Krylov, V.

    2013-01-01

    A hydrogel based occlusion system, a method for occluding vessels, appendages or aneurysms, and a method for hydrogel synthesis are disclosed. The hydrogel based occlusion system includes a hydrogel having a shrunken and a swollen state and a delivery tool configured to deliver the hydrogel to a target occlusion location. The hydrogel is configured to permanently occlude the target occlusion location in the swollen state. The hydrogel may be an electro-activated hydrogel (EAH) which could be ...

  3. Engineered XcmI cassette-containing vector for PCR-based ...

    Indian Academy of Sciences (India)

    Unknown

    vectors, such as pGEM-T (Promega) and pT7Blue (Novagen), are expensive and cannot be re- generated in the laboratory for further use. We describe here the development of a simple and general method for constructing T-vectors bearing an ...

  4. Application of Support Vector Machine-Based Semiactive Control for Seismic Protection of Structures with Magnetorheological Dampers

    Directory of Open Access Journals (Sweden)

    Chunxiang Li

    2012-01-01

    Full Text Available Based on recent research by Li and Liu in 2011, this paper proposes the application of support vector machine- (SVM- based semiactive control methodology for seismic protection of structures with magnetorheological (MR dampers. An important and challenging task of designing the MR dampers is to develop an effective semiactive control strategy that can fully exploit the capabilities of MR dampers. However, amplification of the local acceleration response of structures exists in the widely used semiactive control strategies, namely “Switch” control strategies. Then the SVM-based semiactive control strategy has been employed to design MR dampers. Firstly, the LQR controller for the numerical model of a multistory structure formulated using the dynamic dense method is constructed by using the classic LQR control theory. Secondly, an SVM model which comprises the observers and controllers in the control system is designed and trained to emulate the performance of the LQR controller. Finally, an online autofeedback semiactive control strategy is developed by resorting to SVM and then used for designing MR dampers. Simulation results show that the MR dampers utilizing the SVM-based semiactive control algorithm, which eliminates the local acceleration amplification phenomenon, can remarkably reduce the displacement, velocity, and acceleration responses of the structure.

  5. Molecular Characterization of Heterologous HIV-1gp120 Gene Expression Disruption in Mycobacterium bovis BCG Host Strain: A Critical Issue for Engineering Mycobacterial Based-Vaccine Vectors

    Directory of Open Access Journals (Sweden)

    Joan Joseph

    2010-01-01

    Full Text Available Mycobacterium bovis Bacillus Calmette-Guérin (BCG as a live vector of recombinant bacterial vaccine is a promising system to be used. In this study, we evaluate the disrupted expression of heterologous HIV-1gp120 gene in BCG Pasteur host strain using replicative vectors pMV261 and pJH222. pJH222 carries a lysine complementing gene in BCG lysine auxotrophs. The HIV-1 gp120 gene expression was regulated by BCG hsp60 promoter (in plasmid pMV261 and Mycobacteria spp. α-antigen promoter (in plasmid pJH222. Among 14 rBCG:HIV-1gp120 (pMV261 colonies screened, 12 showed a partial deletion and two showed a complete deletion. However, deletion was not observed in all 10 rBCG:HIV-1gp120 (pJH222 colonies screened. In this study, we demonstrated that E. coli/Mycobacterial expression vectors bearing a weak promoter and lysine complementing gene in a recombinant lysine auxotroph of BCG could prevent genetic rearrangements and disruption of HIV 1gp120 gene expression, a key issue for engineering Mycobacterial based vaccine vectors.

  6. Infra-Through Ultrasonic Piezoelectric Acoustic Vector Sensor Particle Rejection System

    Directory of Open Access Journals (Sweden)

    Scott E. Cravens

    2012-01-01

    Full Text Available Sensor elements which employ fine filaments are often vulnerable to particulate fouling when used in certain operational field conditions. Depending on the size, attraction level, thermal and electrical conduction, and charge accumulation properties of the particles, erroneous readings can be easily generated in such “dirty” environments. This paper describes the design, development, and testing of an ultrasonic system which dynamically rejects highly tenacious electrostatically charged particles of a wide variety of sizes and even water. The paper starts with a brief introduction to the field of acoustic vector sensing, outlining its outstanding characteristics and history. Operational challenges including a statistical analysis of typical Middle-Eastern wind-blown desert sand and charge density are laid out. Several representative subscale hot-wire filaments were fouled with calibrated dust representing desert sand. The fouled elements were then exposed to airflows of 13 ft/s (4 m/s and showed highly erratic shifted conduction levels with respect to baseline (clean levels. An ultrasonic cleaning system was designed specifically resonate the filament and cantilever so as to mechanically reject foulants. When operated at resonance, the ultrasonic cleaning system showed 98.6% particulate rejection levels and associated restoration of uncorrupted filament resistance levels to within 2% of baseline resistance measurements.

  7. Large-System Analysis of Joint User Selection and Vector Precoding for Multiuser MIMO Downlink

    CERN Document Server

    Takeuchi, Keigo; Kawabata, Tsutomu

    2012-01-01

    Joint user selection (US) and vector precoding (US-VP) is proposed for multiuser multiple-input multiple-output (MU-MIMO) downlink. The main difference between joint US-VP and conventional US is that US depends on data symbols for joint US-VP, whereas conventional US is independent of data symbols. The replica method is used to analyze the performance of joint US-VP in the large-system limit, where the numbers of transmit antennas, users, and selected users tend to infinity while their ratios are kept constant. The analysis under the assumptions of replica symmetry (RS) and 1-step replica symmetry breaking (1RSB) implies that optimal data-independent US provides nothing but the same performance as random US in the large-system limit, whereas data-independent US is capacity-achieving as only the number of users tends to infinity. It is shown that joint US-VP can provide a substantial reduction of the energy penalty in the large-system limit. Consequently, joint US-VP outperforms separate US-VP in terms of the ...

  8. MAPPING LOCAL CLIMATE ZONES WITH A VECTOR-BASED GIS METHOD

    Directory of Open Access Journals (Sweden)

    E. Lelovics

    2013-03-01

    Full Text Available In this study we determined Local Climate Zones in a South-Hungarian city, using vector-based and raster-based databases. We calculated seven of the originally proposed ten physical (geometric, surface cover and radiative properties for areas which are based on the mobile temperature measurement campaigns earlier carried out in this city.As input data we applied 3D building database (earlier created with photogrammetric methods, 2D road database, topographic map, aerial photographs, remotely sensed reflectance information from RapidEye satellite image and our local knowledge about the area. The values of the properties were calculated by GIS methods developed for this purpose.We derived for the examined areas and applied for classification sky view factor, mean building height, terrain roughness class, building surface fraction, pervious surface fraction, impervious surface fraction and albedo.Six built and one land cover LCZ classes could be detected with this method on our study area. From each class one circle area was selected, which is representative for that class. Their thermal reactions were examined with the application of mobile temperature measurement dataset. The comparison was made in cases, when the weather was clear and calm and the surface was dry. We found that compact built-in types have more temperature surplus than open ones, and midrise types also have more than lowrise ones. According to our primary results, these categories provide a useful opportunity for intra- and inter-urban comparisons.

  9. Development and evaluation of a biomedical search engine using a predicate-based vector space model.

    Science.gov (United States)

    Kwak, Myungjae; Leroy, Gondy; Martinez, Jesse D; Harwell, Jeffrey

    2013-10-01

    Although biomedical information available in articles and patents is increasing exponentially, we continue to rely on the same information retrieval methods and use very few keywords to search millions of documents. We are developing a fundamentally different approach for finding much more precise and complete information with a single query using predicates instead of keywords for both query and document representation. Predicates are triples that are more complex datastructures than keywords and contain more structured information. To make optimal use of them, we developed a new predicate-based vector space model and query-document similarity function with adjusted tf-idf and boost function. Using a test bed of 107,367 PubMed abstracts, we evaluated the first essential function: retrieving information. Cancer researchers provided 20 realistic queries, for which the top 15 abstracts were retrieved using a predicate-based (new) and keyword-based (baseline) approach. Each abstract was evaluated, double-blind, by cancer researchers on a 0-5 point scale to calculate precision (0 versus higher) and relevance (0-5 score). Precision was significantly higher (psearching than keywords, laying the foundation for rich and sophisticated information search. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Solvability and Regularity for an Elliptic System Prescribing the Curl, Divergence, and Partial Trace of a Vector Field on Sobolev-Class Domains

    Science.gov (United States)

    Cheng, C. H. Arthur; Shkoller, Steve

    2017-09-01

    We provide a self-contained proof of the solvability and regularity of a Hodge-type elliptic system, wherein the divergence and curl of a vector field u are prescribed in an open, bounded, Sobolev-class domain {Ω \\subseteq R^n}, and either the normal component {{u} \\cdot {N}} or the tangential components of the vector field {{u} × {N}} are prescribed on the boundary {partial Ω}. For {k > n/2}, we prove that u is in the Sobolev space {H^k+1(Ω)} if {Ω} is an {H^k+1}-domain, and the divergence, curl, and either the normal or tangential trace of u has sufficient regularity. The proof is based on a regularity theory for vector elliptic equations set on Sobolev-class domains and with Sobolev-class coefficients, and with a rather general set of Dirichlet and Neumann boundary conditions. The resulting regularity theory for the vector u is fundamental in the analysis of free-boundary and moving interface problems in fluid dynamics.

  11. Is outdoor vector control needed for malaria elimination? An individual-based modelling study.

    Science.gov (United States)

    Zhu, Lin; Müller, Günter C; Marshall, John M; Arheart, Kristopher L; Qualls, Whitney A; Hlaing, WayWay M; Schlein, Yosef; Traore, Sekou F; Doumbia, Seydou; Beier, John C

    2017-07-03

    Residual malaria transmission has been reported in many areas even with adequate indoor vector control coverage, such as long-lasting insecticidal nets (LLINs). The increased insecticide resistance in Anopheles mosquitoes has resulted in reduced efficacy of the widely used indoor tools and has been linked with an increase in outdoor malaria transmission. There are considerations of incorporating outdoor interventions into integrated vector management (IVM) to achieve malaria elimination; however, more information on the combination of tools for effective control is needed to determine their utilization. A spatial individual-based model was modified to simulate the environment and malaria transmission activities in a hypothetical, isolated African village setting. LLINs and outdoor attractive toxic sugar bait (ATSB) stations were used as examples of indoor and outdoor interventions, respectively. Different interventions and lengths of efficacy periods were tested. Simulations continued for 420 days, and each simulation scenario was repeated 50 times. Mosquito populations, entomologic inoculation rates (EIRs), probabilities of local mosquito extinction, and proportion of time when the annual EIR was reduced below one were compared between different intervention types and efficacy periods. In the village setting with clustered houses, the combinational intervention of 50% LLINs plus outdoor ATSBs significantly reduced mosquito population and EIR in short term, increased the probability of local mosquito extinction, and increased the time when annual EIR is less than one per person compared to 50% LLINs alone; outdoor ATSBs alone significantly reduced mosquito population in short term, increased the probability of mosquito extinction, and increased the time when annual EIR is less than one compared to 50% LLINs alone, but there was no significant difference in EIR in short term between 50% LLINs and outdoor ATSBs. In the village setting with dispersed houses, the

  12. A set of GFP-based organelle marker lines combined with DsRed-based gateway vectors for subcellular localization study in rice (Oryza sativa L.).

    Science.gov (United States)

    Wu, Tsung-Meng; Lin, Ke-Chun; Liau, Wei-Shiang; Chao, Yun-Yang; Yang, Ling-Hung; Chen, Szu-Yun; Lu, Chung-An; Hong, Chwan-Yang

    2016-01-01

    In the post-genomic era, many useful tools have been developed to accelerate the investigation of gene functions. Fluorescent proteins have been widely used as protein tags for studying the subcellular localization of proteins in plants. Several fluorescent organelle marker lines have been generated in dicot plants; however, useful and reliable fluorescent organelle marker lines are lacking in the monocot model rice. Here, we developed eight different GFP-based organelle markers in transgenic rice and created a set of DsRed-based gateway vectors for combining with the marker lines. Two mitochondrial-localized rice ascorbate peroxidase genes fused to DsRed and successfully co-localized with mitochondrial-targeted marker lines verified the practical use of this system. The co-localization of GFP-fusion marker lines and DsRed-fusion proteins provide a convenient platform for in vivo or in vitro analysis of subcellular localization of rice proteins.

  13. Vero cells as a model to study the effects of adenoviral gene delivery vectors on the RNAi system in context of viral infection.

    Science.gov (United States)

    Matskevich, Alexey A; Jung, Jiun-Shan; Schümann, Michael; Cascallo, Manel; Moelling, Karin

    2009-01-01

    Technology based on RNA interference (RNAi) is a promising source for new antiviral therapies. Although the application of RNAi has been studied extensively, significant problems with using RNAi remain. Very few studies have specifically assessed model systems for testing the effects of viruses or gene delivery vectors on the RNAi system. Since viruses have developed efficient strategies to circumvent the interferon (IFN) response, an IFN-deficient model system should be considered. Here we show that in Vero cells, which lack IFN-alpha and IFN-beta genes, knockdown of Dicer, a key RNAi component, led to accelerated death of cells infected with other evolutionary distinct viruses: influenza A virus, vesicular stomatitis virus and poliovirus. We also demonstrate that transduction of Vero cells with adenoviral vector with subsequent infection with influenza A virus also resulted in increased mortality of infected cells. These effects were much weaker in IFN-producing A549 and Hela cell lines. Thus, the Vero cell line could serve as an interesting model for studying the effects of gene delivery vectors on the RNAi system in the context of virus-related disorders. Copyright 2009 S. Karger AG, Basel.

  14. Applying Support Vector Machines for Gene ontology based gene function prediction

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2004-08-01

    Full Text Available Abstract Background The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on a large scale. However, these methods can either only be applied for specific subsets, or their results are not formalised, or they do not provide precise confidence estimates for their predictions. Results We have developed a large-scale annotation system that tackles all of these shortcomings. In our approach, annotation was provided through Gene Ontology terms by applying multiple Support Vector Machines (SVM for the classification of correct and false predictions. The general performance of the system was benchmarked with a large dataset. An organism-wise cross-validation was performed to define confidence estimates, resulting in an average precision of 80% for 74% of all test sequences. The validation results show that the prediction performance was organism-independent and could reproduce the annotation of other automated systems as well as high-quality manual annotations. We applied our trained classification system to Xenopus laevis sequences, yielding functional annotation for more than half of the known expressed genome. Compared to the currently available annotation, we provided more than twice the number of contigs with good quality annotation, and additionally we assigned a confidence value to each predicted GO term. Conclusions We present a complete automated annotation system that overcomes many of the usual problems by applying a controlled vocabulary of Gene Ontology and an established classification method on large and well-described sequence data sets. In a case study, the function for Xenopus laevis contig sequences was predicted and the results are publicly available at ftp://genome.dkfz-heidelberg.de/pub/agd/gene_association.agd_Xenopus.

  15. Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine

    Science.gov (United States)

    Abbasion, S.; Rafsanjani, A.; Farshidianfar, A.; Irani, N.

    2007-10-01

    Due to the importance of rolling bearings as one of the most widely used industrial machinery elements, development of proper monitoring and fault diagnosis procedure to prevent malfunctioning and failure of these elements during operation is necessary. For rolling bearing fault detection, it is expected that a desired time-frequency analysis method has good computational efficiency, and has good resolution in both, time and frequency domains. The point of interest of this investigation is the presence of an effective method for multi-fault diagnosis in such systems with optimizing signal decomposition levels by using wavelet analysis and support vector machine (SVM). The system that is under study is an electric motor which has two rolling bearings, one of them is next to the output shaft and the other one is next to the fan and for each of them there is one normal form and three false forms, which make 8 forms for study. The results that we achieved from wavelet analysis and SVM are fully in agreement with empirical result.

  16. Hardware Implementation of Vector Control of Induction Motor Drive without Speed Encoder Using an Adaptive Luenberger Based MRAS Observer

    Directory of Open Access Journals (Sweden)

    Karim NEGADI

    2012-08-01

    Full Text Available Vector control of induction motor drives without mechanical speed sensors has the attraction of low cost and high reliability. An adaptive Luenberger style stator flux observers is presented. Therefore, this paper presents a theory of adaptive Luenberger observers and his capability to compensate for stator voltage errors and usefully in electrical drivers systems without sensorless.

  17. Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

    Science.gov (United States)

    W. Hasan, W. Z.

    2018-01-01

    The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554

  18. Control strategy for Single-phase Transformerless Three-leg Unified Power Quality Conditioner Based on Space Vector Modulation

    DEFF Research Database (Denmark)

    Lu, Yong; Xiao, Guochun; Wang, Xiongfei

    2016-01-01

    The unified power quality conditioner (UPQC) is known as an effective compensation device to improve PQ for sensitive end-users. This paper investigates the operation and control of a single-phase three-leg UPQC (TL-UPQC), where a novel space vector modulation method is proposed for naturally...... solving the coupling problem introduced by the common switching leg. The modulation method is similar to the well-known space vector modulation widely used with three-phase voltage source converters, which thus brings extra flexibility to the TL-UPQC system. Two optimized modulation modes with either...

  19. Characterization of Recombinant Thermococcus kodakaraensis (KOD) DNA Polymerases Produced Using Silkworm-Baculovirus Expression Vector System

    KAUST Repository

    Yamashita, Mami

    2017-05-08

    The KOD DNA polymerase from Thermococcus kodakarensis (Tkod-Pol) has been preferred for PCR due to its rapid elongation rate, extreme thermostability and outstanding fidelity. Here in this study, we utilized silkworm-baculovirus expression vector system (silkworm-BEVS) to express the recombinant Tkod-Pol (rKOD) with N-terminal (rKOD-N) or C-terminal (rKOD-C) tandem fusion tags. By using BEVS, we produced functional rKODs with satisfactory yields, about 1.1 mg/larva for rKOD-N and 0.25 mg/larva for rKOD-C, respectively. Interestingly, we found that rKOD-C shows higher thermostability at 95 °C than that of rKOD-N, while that rKOD-N is significantly unstable after exposing to long period of heat-shock. We also assessed the polymerase activity as well as the fidelity of purified rKODs under various conditions. Compared with commercially available rKOD, which is expressed in E. coli expression system, rKOD-C exhibited almost the same PCR performance as the commercial rKOD did, while rKOD-N did lower performance. Taken together, our results suggested that silkworm-BEVS can be used to express and purify efficient rKOD in a commercial way.

  20. Geographic Distribution of Chagas Disease Vectors in Brazil Based on Ecological Niche Modeling

    Directory of Open Access Journals (Sweden)

    Rodrigo Gurgel-Gonçalves

    2012-01-01

    Full Text Available Although Brazil was declared free from Chagas disease transmission by the domestic vector Triatoma infestans, human acute cases are still being registered based on transmission by native triatomine species. For a better understanding of transmission risk, the geographic distribution of Brazilian triatomines was analyzed. Sixteen out of 62 Brazilian species that both occur in >20 municipalities and present synanthropic tendencies were modeled based on their ecological niches. Panstrongylus geniculatus and P. megistus showed broad ecological ranges, but most of the species sort out by the biome in which they are distributed: Rhodnius pictipes and R. robustus in the Amazon; R. neglectus, Triatoma sordida, and T. costalimai in the Cerrado; R. nasutus, P. lutzi, T. brasiliensis, T. pseudomaculata, T. melanocephala, and T. petrocchiae in the Caatinga; T. rubrovaria in the southern pampas; T. tibiamaculata and T. vitticeps in the Atlantic Forest. Although most occurrences were recorded in open areas (Cerrado and Caatinga, our results show that all environmental conditions in the country are favorable to one or more of the species analyzed, such that almost nowhere is Chagas transmission risk negligible.