Internal performance of a nonaxisymmetric nozzle with a rotating upper flap and a center-pivoted lower flap

NASA Technical Reports Server (NTRS)

Wing, David J.; Leavitt, Laurence D.; Re, Richard J.

1993-01-01

An investigation was conducted at wind-off conditions in the static-test facility of the Langley 16-Foot Transonic Tunnel to determine the internal performance characteristics of a single expansion-ramp nozzle with thrust-vectoring capability to 105 degrees. Thrust vectoring was accomplished by the downward rotation of an upper flap with adaptive capability for internal contouring and a corresponding rotation of a center-pivoted lower flap. The static internal performance of configurations with pitch thrust-vector angles of 0 degrees, 60 degrees, and 105 degrees each with two throat areas, was investigated. The nozzle pressure ratio was varied from 1.5 to approximately 8.0 (5.0 for the maximum throat area configurations). Results of this study indicated that the nozzle configuration of the present investigation, when vectored, provided excellent flow-turning capability with relatively high levels of internal performance. In all cases, the thrust vector angle was a function of the nozzle pressure ratio. This result is expected because the flow is bounded by a single expansion surface on both vectored- and unvectored-nozzle geometries.

Selected Performance Measurements of the F-15 Active Axisymmetric Thrust-vectoring Nozzle

NASA Technical Reports Server (NTRS)

Orme, John S.; Sims, Robert L.

1998-01-01

Flight tests recently completed at the NASA Dryden Flight Research Center evaluated performance of a hydromechanically vectored axisymmetric nozzle onboard the F-15 ACTIVE. A flight-test technique whereby strain gages installed onto engine mounts provided for the direct measurement of thrust and vector forces has proven to be extremely valuable. Flow turning and thrust efficiency, as well as nozzle static pressure distributions were measured and analyzed. This report presents results from testing at an altitude of 30,000 ft and a speed of Mach 0.9. Flow turning and thrust efficiency were found to be significantly different than predicted, and moreover, varied substantially with power setting and pitch vector angle. Results of an in-flight comparison of the direct thrust measurement technique and an engine simulation fell within the expected uncertainty bands. Overall nozzle performance at this flight condition demonstrated the F100-PW-229 thrust-vectoring nozzles to be highly capable and efficient.

Selected Performance Measurements of the F-15 ACTIVE Axisymmetric Thrust-Vectoring Nozzle

NASA Technical Reports Server (NTRS)

Orme, John S.; Sims, Robert L.

1999-01-01

Flight tests recently completed at the NASA Dryden Flight Research Center evaluated performance of a hydromechanically vectored axisymmetric nozzle onboard the F-15 ACTIVE. A flight-test technique whereby strain gages installed onto engine mounts provided for the direct measurement of thrust and vector forces has proven to be extremely valuable. Flow turning and thrust efficiency, as well as nozzle static pressure distributions were measured and analyzed. This report presents results from testing at an altitude of 30,000 ft and a speed of Mach 0.9. Flow turning and thrust efficiency were found to be significantly different than predicted, and moreover, varied substantially with power setting and pitch vector angle. Results of an in-flight comparison of the direct thrust measurement technique and an engine simulation fell within the expected uncertainty bands. Overall nozzle performance at this flight condition demonstrated the F100-PW-229 thrust-vectoring nozzles to be highly capable and efficient.

Lanczos eigensolution method for high-performance computers

NASA Technical Reports Server (NTRS)

Bostic, Susan W.

1991-01-01

The theory, computational analysis, and applications are presented of a Lanczos algorithm on high performance computers. The computationally intensive steps of the algorithm are identified as: the matrix factorization, the forward/backward equation solution, and the matrix vector multiples. These computational steps are optimized to exploit the vector and parallel capabilities of high performance computers. The savings in computational time from applying optimization techniques such as: variable band and sparse data storage and access, loop unrolling, use of local memory, and compiler directives are presented. Two large scale structural analysis applications are described: the buckling of a composite blade stiffened panel with a cutout, and the vibration analysis of a high speed civil transport. The sequential computational time for the panel problem executed on a CONVEX computer of 181.6 seconds was decreased to 14.1 seconds with the optimized vector algorithm. The best computational time of 23 seconds for the transport problem with 17,000 degs of freedom was on the the Cray-YMP using an average of 3.63 processors.

Parallel-vector solution of large-scale structural analysis problems on supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1989-01-01

A direct linear equation solution method based on the Choleski factorization procedure is presented which exploits both parallel and vector features of supercomputers. The new equation solver is described, and its performance is evaluated by solving structural analysis problems on three high-performance computers. The method has been implemented using Force, a generic parallel FORTRAN language.

Preliminary performance of a vertical-attitude takeoff and landing, supersonic cruise aircraft concept having thrust vectoring integrated into the flight control system

NASA Technical Reports Server (NTRS)

Robins, A. W.; Beissner, F. L., Jr.; Domack, C. S.; Swanson, E. E.

1985-01-01

A performance study was made of a vertical attitude takeoff and landing (VATOL), supersonic cruise aircraft concept having thrust vectoring integrated into the flight control system. Those characteristics considered were aerodynamics, weight, balance, and performance. Preliminary results indicate that high levels of supersonic aerodynamic performance can be achieved. Further, with the assumption of an advanced (1985 technology readiness) low bypass ratio turbofan engine and advanced structures, excellent mission performance capability is indicated.

A static investigation of the thrust vectoring system of the F/A-18 high-alpha research vehicle

NASA Technical Reports Server (NTRS)

Mason, Mary L.; Capone, Francis J.; Asbury, Scott C.

1992-01-01

A static (wind-off) test was conducted in the static test facility of the Langley 16-foot Transonic Tunnel to evaluate the vectoring capability and isolated nozzle performance of the proposed thrust vectoring system of the F/A-18 high alpha research vehicle (HARV). The thrust vectoring system consisted of three asymmetrically spaced vanes installed externally on a single test nozzle. Two nozzle configurations were tested: A maximum afterburner-power nozzle and a military-power nozzle. Vane size and vane actuation geometry were investigated, and an extensive matrix of vane deflection angles was tested. The nozzle pressure ratios ranged from two to six. The results indicate that the three vane system can successfully generate multiaxis (pitch and yaw) thrust vectoring. However, large resultant vector angles incurred large thrust losses. Resultant vector angles were always lower than the vane deflection angles. The maximum thrust vectoring angles achieved for the military-power nozzle were larger than the angles achieved for the maximum afterburner-power nozzle.

Online Sequential Projection Vector Machine with Adaptive Data Mean Update

PubMed Central

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM. PMID:27143958

Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

PubMed

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

Vector-Based Data Services for NASA Earth Science

NASA Astrophysics Data System (ADS)

Rodriguez, J.; Roberts, J. T.; Ruvane, K.; Cechini, M. F.; Thompson, C. K.; Boller, R. A.; Baynes, K.

2016-12-01

Vector data sources offer opportunities for mapping and visualizing science data in a way that allows for more customizable rendering and deeper data analysis than traditional raster images, and popular formats like GeoJSON and Mapbox Vector Tiles allow diverse types of geospatial data to be served in a high-performance and easily consumed-package. Vector data is especially suited to highly dynamic mapping applications and visualization of complex datasets, while growing levels of support for vector formats and features in open-source mapping clients has made utilizing them easier and more powerful than ever. NASA's Global Imagery Browse Services (GIBS) is working to make NASA data more easily and conveniently accessible than ever by serving vector datasets via GeoJSON, Mapbox Vector Tiles, and raster images. This presentation will review these output formats, the services, including WFS, WMS, and WMTS, that can be used to access the data, and some ways in which vector sources can be utilized in popular open-source mapping clients like OpenLayers. Lessons learned from GIBS' recent move towards serving vector will be discussed, as well as how to use GIBS open source software to create, configure, and serve vector data sources using Mapserver and the GIBS OnEarth Apache module.

The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

NASA Astrophysics Data System (ADS)

Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

2015-08-01

The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

Unrestricted Hepatocyte Transduction with Adeno-Associated Virus Serotype 8 Vectors in Mice

PubMed Central

Nakai, Hiroyuki; Fuess, Sally; Storm, Theresa A.; Muramatsu, Shin-ichi; Nara, Yuko; Kay, Mark A.

2005-01-01

Recombinant adeno-associated virus (rAAV) vectors can mediate long-term stable transduction in various target tissues. However, with rAAV serotype 2 (rAAV2) vectors, liver transduction is confined to only a small portion of hepatocytes even after administration of extremely high vector doses. In order to investigate whether rAAV vectors of other serotypes exhibit similar restricted liver transduction, we performed a dose-response study by injecting mice with β-galactosidase-expressing rAAV1 and rAAV8 vectors via the portal vein. The rAAV1 vector showed a blunted dose-response similar to that of rAAV2 at high doses, while the rAAV8 vector dose-response remained unchanged at any dose and ultimately could transduce all the hepatocytes at a dose of 7.2 × 1012 vector genomes/mouse without toxicity. This indicates that all hepatocytes have the ability to process incoming single-stranded vector genomes into duplex DNA. A single tail vein injection of the rAAV8 vector was as efficient as portal vein injection at any dose. In addition, intravascular administration of the rAAV8 vector at a high dose transduced all the skeletal muscles throughout the body, including the diaphragm, the entire cardiac muscle, and substantial numbers of cells in the pancreas, smooth muscles, and brain. Thus, rAAV8 is a robust vector for gene transfer to the liver and provides a promising research tool for delivering genes to various target organs. In addition, the rAAV8 vector may offer a potential therapeutic agent for various diseases affecting nonhepatic tissues, but great caution is required for vector spillover and tight control of tissue-specific gene expression. PMID:15596817

Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

ERIC Educational Resources Information Center

Wolf, Michael Maclean

2009-01-01

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

Nonlinearity analysis of measurement model for vision-based optical navigation system

NASA Astrophysics Data System (ADS)

Li, Jianguo; Cui, Hutao; Tian, Yang

2015-02-01

In the autonomous optical navigation system based on line-of-sight vector observation, nonlinearity of measurement model is highly correlated with the navigation performance. By quantitatively calculating the degree of nonlinearity of the focal plane model and the unit vector model, this paper focuses on determining which optical measurement model performs better. Firstly, measurement equations and measurement noise statistics of these two line-of-sight measurement models are established based on perspective projection co-linearity equation. Then the nonlinear effects of measurement model on the filter performance are analyzed within the framework of the Extended Kalman filter, also the degrees of nonlinearity of two measurement models are compared using the curvature measure theory from differential geometry. Finally, a simulation of star-tracker-based attitude determination is presented to confirm the superiority of the unit vector measurement model. Simulation results show that the magnitude of curvature nonlinearity measurement is consistent with the filter performance, and the unit vector measurement model yields higher estimation precision and faster convergence properties.

Disclosing the Parameters Leading to High Productivity of Retroviral Producer Cells Lines: Evaluating Random Versus Targeted Integration.

PubMed

Bandeira, Vanessa S; Tomás, Hélio A; Alici, Evren; Carrondo, Manuel J T; Coroadinha, Ana S

2017-04-01

Gammaretrovirus and lentivirus are the preferred viral vectors to genetically modify T and natural killer cells to be used in immune cell therapies. The transduction efficiency of hematopoietic and T cells is more efficient using gibbon ape leukemia virus (GaLV) pseudotyping. In this context gammaretroviral vector producer cells offer competitive higher titers than transient lentiviral vectors productions. The main aim of this work was to identify the key parameters governing GaLV-pseudotyped gammaretroviral vector productivity in stable producer cells, using a retroviral vector expression cassette enabling positive (facilitating cell enrichment) and negative cell selection (allowing cell elimination). The retroviral vector contains a thymidine kinase suicide gene fused with a ouabain-resistant Na + ,K + -ATPase gene, a potential safer and faster marker. The establishment of retroviral vector producer cells is traditionally performed by randomly integrating the retroviral vector expression cassette codifying the transgene. More recently, recombinase-mediated cassette exchange methodologies have been introduced to achieve targeted integration. Herein we compared random and targeted integration of the retroviral vector transgene construct. Two retroviral producer cell lines, 293 OuaS and 293 FlexOuaS, were generated by random and targeted integration, respectively, producing high titers (on the order of 10 7 infectious particles·ml -1 ). Results showed that the retroviral vector transgene cassette is the key retroviral vector component determining the viral titers notwithstanding, single-copy integration is sufficient to provide high titers. The expression levels of the three retroviral constructs (gag-pol, GaLV env, and retroviral vector transgene) were analyzed. Although gag-pol and GaLV env gene expression levels should surpass a minimal threshold, we found that relatively modest expression levels of these two expression cassettes are required. Their levels of expression should not be maximized. We concluded, to establish a high producer retroviral vector cell line only the expression level of the genomic retroviral RNA, that is, the retroviral vector transgene cassette, should be maximized, both through (1) the optimization of its design (i.e., genetic elements composition) and (2) the selection of high expressing chromosomal locus for its integration. The use of methodologies identifying and promoting integration into high-expression loci, as targeted integration or high-throughput screening are in this perspective highly valuable.

The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Kepner, J. V.; Janka, R. S.; Lebak, J.; Richards, M. A.

1999-12-01

The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.

Simplified production and concentration of HIV-1-based lentiviral vectors using HYPERFlask vessels and anion exchange membrane chromatography

PubMed Central

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

Standard Free Droplet Digital Polymerase Chain Reaction as a New Tool for the Quality Control of High-Capacity Adenoviral Vectors in Small-Scale Preparations

PubMed Central

Boehme, Philip; Stellberger, Thorsten; Solanki, Manish; Zhang, Wenli; Schulz, Eric; Bergmann, Thorsten; Liu, Jing; Doerner, Johannes; Baiker, Armin E.

2015-01-01

Abstract High-capacity adenoviral vectors (HCAdVs) are promising tools for gene therapy as well as for genetic engineering. However, one limitation of the HCAdV vector system is the complex, time-consuming, and labor-intensive production process and the following quality control procedure. Since HCAdVs are deleted for all viral coding sequences, a helper virus (HV) is needed in the production process to provide the sequences for all viral proteins in trans. For the purification procedure of HCAdV, cesium chloride density gradient centrifugation is usually performed followed by buffer exchange using dialysis or comparable methods. However, performing these steps is technically difficult, potentially error-prone, and not scalable. Here, we establish a new protocol for small-scale production of HCAdV based on commercially available adenovirus purification systems and a standard method for the quality control of final HCAdV preparations. For titration of final vector preparations, we established a droplet digital polymerase chain reaction (ddPCR) that uses a standard free-end-point PCR in small droplets of defined volume. By using different probes, this method is capable of detecting and quantifying HCAdV and HV in one reaction independent of reference material, rendering this method attractive for accurately comparing viral titers between different laboratories. In summary, we demonstrate that it is possible to produce HCAdV in a small scale of sufficient quality and quantity to perform experiments in cell culture, and we established a reliable protocol for vector titration based on ddPCR. Our method significantly reduces time and required equipment to perform HCAdV production. In the future the ddPCR technology could be advantageous for titration of other viral vectors commonly used in gene therapy. PMID:25640117

Research on bearing fault diagnosis of large machinery based on mathematical morphology

NASA Astrophysics Data System (ADS)

Wang, Yu

2018-04-01

To study the automatic diagnosis of large machinery fault based on support vector machine, combining the four common faults of the large machinery, the support vector machine is used to classify and identify the fault. The extracted feature vectors are entered. The feature vector is trained and identified by multi - classification method. The optimal parameters of the support vector machine are searched by trial and error method and cross validation method. Then, the support vector machine is compared with BP neural network. The results show that the support vector machines are short in time and high in classification accuracy. It is more suitable for the research of fault diagnosis in large machinery. Therefore, it can be concluded that the training speed of support vector machines (SVM) is fast and the performance is good.

The Unified Floating Point Vector Coprocessor for Reconfigurable Hardware

NASA Astrophysics Data System (ADS)

Kathiara, Jainik

There has been an increased interest recently in using embedded cores on FPGAs. Many of the applications that make use of these cores have floating point operations. Due to the complexity and expense of floating point hardware, these algorithms are usually converted to fixed point operations or implemented using floating-point emulation in software. As the technology advances, more and more homogeneous computational resources and fixed function embedded blocks are added to FPGAs and hence implementation of floating point hardware becomes a feasible option. In this research we have implemented a high performance, autonomous floating point vector Coprocessor (FPVC) that works independently within an embedded processor system. We have presented a unified approach to vector and scalar computation, using a single register file for both scalar operands and vector elements. The Hybrid vector/SIMD computational model of FPVC results in greater overall performance for most applications along with improved peak performance compared to other approaches. By parameterizing vector length and the number of vector lanes, we can design an application specific FPVC and take optimal advantage of the FPGA fabric. For this research we have also initiated designing a software library for various computational kernels, each of which adapts FPVC's configuration and provide maximal performance. The kernels implemented are from the area of linear algebra and include matrix multiplication and QR and Cholesky decomposition. We have demonstrated the operation of FPVC on a Xilinx Virtex 5 using the embedded PowerPC.

A Performance Evaluation of the Cray X1 for Scientific Applications

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak; Borrill, Julian; Canning, Andrew; Carter, Jonathan; Djomehri, M. Jahed; Shan, Hongzhang; Skinner, David

2004-01-01

The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end capability and cost effectiveness. However, the recent development of massively parallel vector systems is having a significant effect on the supercomputing landscape. In this paper, we compare the performance of the recently released Cray X1 vector system with that of the cacheless NEC SX-6 vector machine, and the superscalar cache-based IBM Power3 and Power4 architectures for scientific applications. Overall results demonstrate that the X1 is quite promising, but performance improvements are expected as the hardware, systems software, and numerical libraries mature. Code reengineering to effectively utilize the complex architecture may also lead to significant efficiency enhancements.

Static investigation of a two-dimensional convergent-divergent exhaust nozzle with multiaxis thrust-vectoring capability

NASA Technical Reports Server (NTRS)

Taylor, John G.

1990-01-01

An investigation was conducted in the Static Test Facility of the NASA Langley 16-Foot Transonic Tunnel to determine the internal performance of two-dimensional convergent-divergent nozzles designed to have simultaneous pitch and yaw thrust vectoring capability. This concept utilized divergent flap rotation of thrust vectoring in the pitch plane and deflection of flat yaw flaps hinged at the end of the sidewalls for yaw thrust vectoring. The hinge location of the yaw flaps was varied at four positions from the nozzle exit plane to the throat plane. The yaw flaps were designed to contain the flow laterally independent of power setting. In order to eliminate any physical interference between the yaw flap deflected into the exhaust stream and the divergent flaps, the downstream corners of both upper and lower divergent flaps were cut off to allow for up to 30 deg of yaw flap deflection. The impact of varying the nozzle pitch vector angle, throat area, yaw flap hinge location, yaw flap length, and yaw flap deflection angle on nozzle internal performance characteristics, was studied. High-pressure air was used to simulate jet exhaust at nozzle pressure ratios up to 7.0. Static results indicate that configurations with the yaw flap hinge located upstream of the exit plane provide relatively high levels of thrust vectoring efficiency without causing large losses in resultant thrust ratio. Therefore, these configurations represent a viable concept for providing simultaneous pitch and yaw thrust vectoring.

Design and test of a high power electromechanical actuator for thrust vector control

NASA Technical Reports Server (NTRS)

Cowan, J. R.; Myers, W. N.

1992-01-01

NASA-Marshall is involved in the development of electromechanical actuators (EMA) for thrust-vector control (TVC) system testing and implementation in spacecraft control/gimballing systems, with a view to the replacement of hydraulic hardware. TVC system control is furnished by solid state controllers and power supplies; a pair of resolvers supply position feedback to the controller for precise positioning. Performance comparisons between EMA and hydraulic TVC systems are performed.

Automatic differentiation for design sensitivity analysis of structural systems using multiple processors

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Storaasli, Olaf O.; Qin, Jiangning; Qamar, Ramzi

1994-01-01

An automatic differentiation tool (ADIFOR) is incorporated into a finite element based structural analysis program for shape and non-shape design sensitivity analysis of structural systems. The entire analysis and sensitivity procedures are parallelized and vectorized for high performance computation. Small scale examples to verify the accuracy of the proposed program and a medium scale example to demonstrate the parallel vector performance on multiple CRAY C90 processors are included.

Design and test of a high power electromechanical actuator for thrust vector control

NASA Astrophysics Data System (ADS)

Cowan, J. R.; Myers, W. N.

1992-07-01

NASA-Marshall is involved in the development of electromechanical actuators (EMA) for thrust-vector control (TVC) system testing and implementation in spacecraft control/gimballing systems, with a view to the replacement of hydraulic hardware. TVC system control is furnished by solid state controllers and power supplies; a pair of resolvers supply position feedback to the controller for precise positioning. Performance comparisons between EMA and hydraulic TVC systems are performed.

Multitasking 3-D forward modeling using high-order finite difference methods on the Cray X-MP/416

DOE Office of Scientific and Technical Information (OSTI.GOV)

Terki-Hassaine, O.; Leiss, E.L.

1988-01-01

The CRAY X-MP/416 was used to multitask 3-D forward modeling by the high-order finite difference method. Flowtrace analysis reveals that the most expensive operation in the unitasked program is a matrix vector multiplication. The in-core and out-of-core versions of a reentrant subroutine can perform any fraction of the matrix vector multiplication independently, a pattern compatible with multitasking. The matrix vector multiplication routine can be distributed over two to four processors. The rest of the program utilizes the microtasking feature that lets the system treat independent iterations of DO-loops as subtasks to be performed by any available processor. The availability ofmore » the Solid-State Storage Device (SSD) meant the I/O wait time was virtually zero. A performance study determined a theoretical speedup, taking into account the multitasking overhead. Multitasking programs utilizing both macrotasking and microtasking features obtained actual speedups that were approximately 80% of the ideal speedup.« less

Mathematical modelling of Bit-Level Architecture using Reciprocal Quantum Logic

NASA Astrophysics Data System (ADS)

Narendran, S.; Selvakumar, J.

2018-04-01

Efficiency of high-performance computing is on high demand with both speed and energy efficiency. Reciprocal Quantum Logic (RQL) is one of the technology which will produce high speed and zero static power dissipation. RQL uses AC power supply as input rather than DC input. RQL has three set of basic gates. Series of reciprocal transmission lines are placed in between each gate to avoid loss of power and to achieve high speed. Analytical model of Bit-Level Architecture are done through RQL. Major drawback of reciprocal Quantum Logic is area, because of lack in proper power supply. To achieve proper power supply we need to use splitters which will occupy large area. Distributed arithmetic uses vector- vector multiplication one is constant and other is signed variable and each word performs as a binary number, they rearranged and mixed to form distributed system. Distributed arithmetic is widely used in convolution and high performance computational devices.

Automated vector selection of SIVQ and parallel computing integration MATLAB™: Innovations supporting large-scale and high-throughput image analysis studies.

PubMed

Cheng, Jerome; Hipp, Jason; Monaco, James; Lucas, David R; Madabhushi, Anant; Balis, Ulysses J

2011-01-01

Spatially invariant vector quantization (SIVQ) is a texture and color-based image matching algorithm that queries the image space through the use of ring vectors. In prior studies, the selection of one or more optimal vectors for a particular feature of interest required a manual process, with the user initially stochastically selecting candidate vectors and subsequently testing them upon other regions of the image to verify the vector's sensitivity and specificity properties (typically by reviewing a resultant heat map). In carrying out the prior efforts, the SIVQ algorithm was noted to exhibit highly scalable computational properties, where each region of analysis can take place independently of others, making a compelling case for the exploration of its deployment on high-throughput computing platforms, with the hypothesis that such an exercise will result in performance gains that scale linearly with increasing processor count. An automated process was developed for the selection of optimal ring vectors to serve as the predicate matching operator in defining histopathological features of interest. Briefly, candidate vectors were generated from every possible coordinate origin within a user-defined vector selection area (VSA) and subsequently compared against user-identified positive and negative "ground truth" regions on the same image. Each vector from the VSA was assessed for its goodness-of-fit to both the positive and negative areas via the use of the receiver operating characteristic (ROC) transfer function, with each assessment resulting in an associated area-under-the-curve (AUC) figure of merit. Use of the above-mentioned automated vector selection process was demonstrated in two cases of use: First, to identify malignant colonic epithelium, and second, to identify soft tissue sarcoma. For both examples, a very satisfactory optimized vector was identified, as defined by the AUC metric. Finally, as an additional effort directed towards attaining high-throughput capability for the SIVQ algorithm, we demonstrated the successful incorporation of it with the MATrix LABoratory (MATLAB™) application interface. The SIVQ algorithm is suitable for automated vector selection settings and high throughput computation.

A Study on Aircraft Engine Control Systems for Integrated Flight and Propulsion Control

NASA Astrophysics Data System (ADS)

Yamane, Hideaki; Matsunaga, Yasushi; Kusakawa, Takeshi; Yasui, Hisako

The Integrated Flight and Propulsion Control (IFPC) for a highly maneuverable aircraft and a fighter-class engine with pitch/yaw thrust vectoring is described. Of the two IFPC functions the aircraft maneuver control utilizes the thrust vectoring based on aerodynamic control surfaces/thrust vectoring control allocation specified by the Integrated Control Unit (ICU) of a FADEC (Full Authority Digital Electronic Control) system. On the other hand in the Performance Seeking Control (PSC) the ICU identifies engine's various characteristic changes, optimizes manipulated variables and finally adjusts engine control parameters in cooperation with the Engine Control Unit (ECU). It is shown by hardware-in-the-loop simulation that the thrust vectoring can enhance aircraft maneuverability/agility and that the PSC can improve engine performance parameters such as SFC (specific fuel consumption), thrust and gas temperature.

A Performance Evaluation of the Cray X1 for Scientific Applications

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak; Borrill, Julian; Canning, Andrew; Carter, Jonathan; Djomehri, M. Jahed; Shan, Hongzhang; Skinner, David

2003-01-01

The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end capability and capacity computers because of their generality, scalability, and cost effectiveness. However, the recent development of massively parallel vector systems is having a significant effect on the supercomputing landscape. In this paper, we compare the performance of the recently-released Cray X1 vector system with that of the cacheless NEC SX-6 vector machine, and the superscalar cache-based IBM Power3 and Power4 architectures for scientific applications. Overall results demonstrate that the X1 is quite promising, but performance improvements are expected as the hardware, systems software, and numerical libraries mature. Code reengineering to effectively utilize the complex architecture may also lead to significant efficiency enhancements.

Insecticide resistance profile of Anopheles gambiae from a phase II field station in Cové, southern Benin: implications for the evaluation of novel vector control products.

PubMed

Ngufor, Corine; N'Guessan, Raphael; Fagbohoun, Josias; Subramaniam, Krishanthi; Odjo, Abibatou; Fongnikin, Augustin; Akogbeto, Martin; Weetman, David; Rowland, Mark

2015-11-18

Novel indoor residual spraying (IRS) and long-lasting insecticidal net (LLIN) products aimed at improving the control of pyrethroid-resistant malaria vectors have to be evaluated in Phase II semi-field experimental studies against highly pyrethroid-resistant mosquitoes. To better understand their performance it is necessary to fully characterize the species composition, resistance status and resistance mechanisms of the vector populations in the experimental hut sites. Bioassays were performed to assess phenotypic insecticide resistance in the malaria vector population at a newly constructed experimental hut site in Cové, a rice growing area in southern Benin, being used for WHOPES Phase II evaluation of newly developed LLIN and IRS products. The efficacy of standard WHOPES-approved pyrethroid LLIN and IRS products was also assessed in the experimental huts. Diagnostic genotyping techniques and microarray studies were performed to investigate the genetic basis of pyrethroid resistance in the Cové Anopheles gambiae population. The vector population at the Cové experimental hut site consisted of a mixture of Anopheles coluzzii and An. gambiae s.s. with the latter occurring at lower frequencies (23 %) and only in samples collected in the dry season. There was a high prevalence of resistance to pyrethroids and DDT (>90 % bioassay survival) with pyrethroid resistance intensity reaching 200-fold compared to the laboratory susceptible An. gambiae Kisumu strain. Standard WHOPES-approved pyrethroid IRS and LLIN products were ineffective in the experimental huts against this vector population (8-29 % mortality). The L1014F allele frequency was 89 %. CYP6P3, a cytochrome P450 validated as an efficient metabolizer of pyrethroids, was over-expressed. Characterizing pyrethroid resistance at Phase II field sites is crucial to the accurate interpretation of the performance of novel vector control products. The strong levels of pyrethroid resistance at the Cové experimental hut station make it a suitable site for Phase II experimental hut evaluations of novel vector control products, which aim for improved efficacy against pyrethroid-resistant malaria vectors to WHOPES standards. The resistance genes identified can be used as markers for further studies investigating the resistance management potential of novel mixture LLIN and IRS products tested at the site.

Vectorization for Molecular Dynamics on Intel Xeon Phi Corpocessors

NASA Astrophysics Data System (ADS)

Yi, Hongsuk

2014-03-01

Many modern processors are capable of exploiting data-level parallelism through the use of single instruction multiple data (SIMD) execution. The new Intel Xeon Phi coprocessor supports 512 bit vector registers for the high performance computing. In this paper, we have developed a hierarchical parallelization scheme for accelerated molecular dynamics simulations with the Terfoff potentials for covalent bond solid crystals on Intel Xeon Phi coprocessor systems. The scheme exploits multi-level parallelism computing. We combine thread-level parallelism using a tightly coupled thread-level and task-level parallelism with 512-bit vector register. The simulation results show that the parallel performance of SIMD implementations on Xeon Phi is apparently superior to their x86 CPU architecture.

New gorilla adenovirus vaccine vectors induce potent immune responses and protection in a mouse malaria model.

PubMed

Limbach, Keith; Stefaniak, Maureen; Chen, Ping; Patterson, Noelle B; Liao, Grant; Weng, Shaojie; Krepkiy, Svetlana; Ekberg, Greg; Torano, Holly; Ettyreddy, Damodar; Gowda, Kalpana; Sonawane, Sharvari; Belmonte, Arnel; Abot, Esteban; Sedegah, Martha; Hollingdale, Michael R; Moormann, Ann; Vulule, John; Villasante, Eileen; Richie, Thomas L; Brough, Douglas E; Bruder, Joseph T

2017-07-03

A DNA-human Ad5 (HuAd5) prime-boost malaria vaccine has been shown to protect volunteers against a controlled human malaria infection. The potency of this vaccine, however, appeared to be affected by the presence of pre-existing immunity against the HuAd5 vector. Since HuAd5 seroprevalence is very high in malaria-endemic areas of the world, HuAd5 may not be the most appropriate malaria vaccine vector. This report describes the evaluation of the seroprevalence, immunogenicity and efficacy of three newly identified gorilla adenoviruses, GC44, GC45 and GC46, as potential malaria vaccine vectors. The seroprevalence of GC44, GC45 and GC46 is very low, and the three vectors are not efficiently neutralized by human sera from Kenya and Ghana, two countries where malaria is endemic. In mice, a single administration of GC44, GC45 and GC46 vectors expressing a murine malaria gene, Plasmodium yoelii circumsporozoite protein (PyCSP), induced robust PyCSP-specific T cell and antibody responses that were at least as high as a comparable HuAd5-PyCSP vector. Efficacy studies in a murine malaria model indicated that a prime-boost regimen with DNA-PyCSP and GC-PyCSP vectors can protect mice against a malaria challenge. Moreover, these studies indicated that a DNA-GC46-PyCSP vaccine regimen was significantly more efficacious than a DNA-HuAd5-PyCSP regimen. These data suggest that these gorilla-based adenovectors have key performance characteristics for an effective malaria vaccine. The superior performance of GC46 over HuAd5 highlights its potential for clinical development.

Investigation of advanced thrust vectoring exhaust systems for high speed propulsive lift

NASA Technical Reports Server (NTRS)

Hutchison, R. A.; Petit, J. E.; Capone, F. J.; Whittaker, R. W.

1980-01-01

The paper presents the results of a wind tunnel investigation conducted at the NASA-Langley research center to determine thrust vectoring/induced lift characteristics of advanced exhaust nozzle concepts installed on a supersonic tactical airplane model. Specific test objectives include: (1) basic aerodynamics of a wing body configuration, (2) investigation of induced lift effects, (3) evaluation of static and forward speed performance, and (4) the effectiveness of a canard surface to trim thrust vectoring/induced lift forces and moments.

Analysis of the clonal repertoire of gene-corrected cells in gene therapy.

PubMed

Paruzynski, Anna; Glimm, Hanno; Schmidt, Manfred; Kalle, Christof von

2012-01-01

Gene therapy-based clinical phase I/II studies using integrating retroviral vectors could successfully treat different monogenetic inherited diseases. However, with increased efficiency of this therapy, severe side effects occurred in various gene therapy trials. In all cases, integration of the vector close to or within a proto-oncogene contributed substantially to the development of the malignancies. Thus, the in-depth analysis of integration site patterns is of high importance to uncover potential clonal outgrowth and to assess the safety of gene transfer vectors and gene therapy protocols. The standard and nonrestrictive linear amplification-mediated PCR (nrLAM-PCR) in combination with high-throughput sequencing exhibits technologies that allow to comprehensively analyze the clonal repertoire of gene-corrected cells and to assess the safety of the used vector system at an early stage on the molecular level. It enables clarifying the biological consequences of the vector system on the fate of the transduced cell. Furthermore, the downstream performance of real-time PCR allows a quantitative estimation of the clonality of individual cells and their clonal progeny. Here, we present a guideline that should allow researchers to perform comprehensive integration site analysis in preclinical and clinical studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Optical Vector Receiver Operating Near the Quantum Limit

NASA Astrophysics Data System (ADS)

Vilnrotter, V. A.; Lau, C.-W.

2005-05-01

An optical receiver concept for binary signals with performance approaching the quantum limit at low average-signal energies is developed and analyzed. A conditionally nulling receiver that reaches the quantum limit in the absence of background photons has been devised by Dolinar. However, this receiver requires ideal optical combining and complicated real-time shaping of the local field; hence, it tends to be difficult to implement at high data rates. A simpler nulling receiver that approaches the quantum limit without complex optical processing, suitable for high-rate operation, had been suggested earlier by Kennedy. Here we formulate a vector receiver concept that incorporates the Kennedy receiver with a physical beamsplitter, but it also utilizes the reflected signal component to improve signal detection. It is found that augmenting the Kennedy receiver with classical coherent detection at the auxiliary beamsplitter output, and optimally processing the vector observations, always improves on the performance of the Kennedy receiver alone, significantly so at low average-photon rates. This is precisely the region of operation where modern codes approach channel capacity. It is also shown that the addition of background radiation has little effect on the performance of the coherent receiver component, suggesting a viable approach for near-quantum-limited performance in high background environments.

High Order Entropy-Constrained Residual VQ for Lossless Compression of Images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Scales, Allen

1995-01-01

High order entropy coding is a powerful technique for exploiting high order statistical dependencies. However, the exponentially high complexity associated with such a method often discourages its use. In this paper, an entropy-constrained residual vector quantization method is proposed for lossless compression of images. The method consists of first quantizing the input image using a high order entropy-constrained residual vector quantizer and then coding the residual image using a first order entropy coder. The distortion measure used in the entropy-constrained optimization is essentially the first order entropy of the residual image. Experimental results show very competitive performance.

An efficient parallel algorithm for matrix-vector multiplication

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hendrickson, B.; Leland, R.; Plimpton, S.

The multiplication of a vector by a matrix is the kernel computation of many algorithms in scientific computation. A fast parallel algorithm for this calculation is therefore necessary if one is to make full use of the new generation of parallel supercomputers. This paper presents a high performance, parallel matrix-vector multiplication algorithm that is particularly well suited to hypercube multiprocessors. For an n x n matrix on p processors, the communication cost of this algorithm is O(n/[radical]p + log(p)), independent of the matrix sparsity pattern. The performance of the algorithm is demonstrated by employing it as the kernel in themore » well-known NAS conjugate gradient benchmark, where a run time of 6.09 seconds was observed. This is the best published performance on this benchmark achieved to date using a massively parallel supercomputer.« less

First Report of Aedes aegypti Transmission of Chikungunya Virus in the Americas

PubMed Central

Díaz-González, Esteban E.; Kautz, Tiffany F.; Dorantes-Delgado, Alicia; Malo-García, Iliana R.; Laguna-Aguilar, Maricela; Langsjoen, Rose M.; Chen, Rubing; Auguste, Dawn I.; Sánchez-Casas, Rosa M.; Danis-Lozano, Rogelio; Weaver, Scott C.; Fernández-Salas, Ildefonso

2015-01-01

During a chikungunya fever outbreak in late 2014 in Chiapas, Mexico, entomovirological surveillance was performed to incriminate the vector(s). In neighborhoods, 75 households with suspected cases were sampled for mosquitoes, of which 80% (60) harbored Aedes aegypti and 2.7% (2) Aedes albopictus. A total of 1,170 Ae. aegypti and three Ae. albopictus was collected and 81 pools were generated. Although none of the Ae. albopictus pools were chikungunya virus (CHIKV)–positive, 18 Ae. aegypti pools (22.8%) contained CHIKV, yielding an infection rate of 32.3/1,000 mosquitoes. A lack of herd immunity in conjunction with high mosquito populations, poor vector control services in this region, and targeted collections in locations of human cases may explain the high infection rate in this vector. Consistent with predictions from experimental studies, Ae. aegypti appears to be the principal vector of CHIKV in southern Mexico, while the role of Ae. albopictus remains unknown. PMID:26416113

Neem cake as a promising larvicide and adulticide against the rural malaria vector Anopheles culicifacies (Diptera: Culicidae): a HPTLC fingerprinting approach.

PubMed

Benelli, Giovanni; Chandramohan, Balamurugan; Murugan, Kadarkarai; Madhiyazhagan, Pari; Kovendan, Kalimuthu; Panneerselvam, Chellasamy; Dinesh, Devakumar; Govindarajan, Marimuthu; Higuchi, Akon; Toniolo, Chiara; Canale, Angelo; Nicoletti, Marcello

2017-05-01

Mosquitoes are insects of huge public health importance, since they act as vectors for important pathogens and parasites. Here, we focused on the possibility of using the neem cake in the fight against mosquito vectors. The neem cake chemical composition significantly changes among producers, as evidenced by our HPTLC (High performance thin layer chromatography) analyses of different marketed products. Neem cake extracts were tested to evaluate the ovicidal, larvicidal and adulticidal activity against the rural malaria vector Anopheles culicifacies. Ovicidal activity of both types of extracts was statistically significant, and 150 ppm completely inhibited egg hatching. LC 50 values were extremely low against fourth instar larvae, ranging from 1.321 (NM1) to 1.818 ppm (NA2). Adulticidal activity was also high, with LC 50 ranging from 3.015 (NM1) to 3.637 ppm (NM2). This study pointed out the utility of neem cake as a source of eco-friendly mosquitocides in Anopheline vector control programmes.

First Report of Aedes aegypti Transmission of Chikungunya Virus in the Americas.

PubMed

Díaz-González, Esteban E; Kautz, Tiffany F; Dorantes-Delgado, Alicia; Malo-García, Iliana R; Laguna-Aguilar, Maricela; Langsjoen, Rose M; Chen, Rubing; Auguste, Dawn I; Sánchez-Casas, Rosa M; Danis-Lozano, Rogelio; Weaver, Scott C; Fernández-Salas, Ildefonso

2015-12-01

During a chikungunya fever outbreak in late 2014 in Chiapas, Mexico, entomovirological surveillance was performed to incriminate the vector(s). In neighborhoods, 75 households with suspected cases were sampled for mosquitoes, of which 80% (60) harbored Aedes aegypti and 2.7% (2) Aedes albopictus. A total of 1,170 Ae. aegypti and three Ae. albopictus was collected and 81 pools were generated. Although none of the Ae. albopictus pools were chikungunya virus (CHIKV)-positive, 18 Ae. aegypti pools (22.8%) contained CHIKV, yielding an infection rate of 32.3/1,000 mosquitoes. A lack of herd immunity in conjunction with high mosquito populations, poor vector control services in this region, and targeted collections in locations of human cases may explain the high infection rate in this vector. Consistent with predictions from experimental studies, Ae. aegypti appears to be the principal vector of CHIKV in southern Mexico, while the role of Ae. albopictus remains unknown. © The American Society of Tropical Medicine and Hygiene.

On the Improvement of Convergence Performance for Integrated Design of Wind Turbine Blade Using a Vector Dominating Multi-objective Evolution Algorithm

NASA Astrophysics Data System (ADS)

Wang, L.; Wang, T. G.; Wu, J. H.; Cheng, G. P.

2016-09-01

A novel multi-objective optimization algorithm incorporating evolution strategies and vector mechanisms, referred as VD-MOEA, is proposed and applied in aerodynamic- structural integrated design of wind turbine blade. In the algorithm, a set of uniformly distributed vectors is constructed to guide population in moving forward to the Pareto front rapidly and maintain population diversity with high efficiency. For example, two- and three- objective designs of 1.5MW wind turbine blade are subsequently carried out for the optimization objectives of maximum annual energy production, minimum blade mass, and minimum extreme root thrust. The results show that the Pareto optimal solutions can be obtained in one single simulation run and uniformly distributed in the objective space, maximally maintaining the population diversity. In comparison to conventional evolution algorithms, VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation for handling complex problems of multi-variables, multi-objectives and multi-constraints. This provides a reliable high-performance optimization approach for the aerodynamic-structural integrated design of wind turbine blade.

Longevity of rAAV vector and plasmid DNA in blood after intramuscular injection in nonhuman primates: implications for gene doping.

PubMed

Ni, W; Le Guiner, C; Gernoux, G; Penaud-Budloo, M; Moullier, P; Snyder, R O

2011-07-01

Legitimate uses of gene transfer technology can benefit from sensitive detection methods to determine vector biodistribution in pre-clinical studies and in human clinical trials, and similar methods can detect illegitimate gene transfer to provide sports-governing bodies with the ability to maintain fairness. Real-time PCR assays were developed to detect a performance-enhancing transgene (erythropoietin, EPO) and backbone sequences in the presence of endogenous cellular sequences. In addition to developing real-time PCR assays, the steps involved in DNA extraction, storage and transport were investigated. By real-time PCR, the vector transgene is distinguishable from the genomic DNA sequence because of the absence of introns, and the vector backbone can be identified by heterologous gene expression control elements. After performance of the assays was optimized, cynomolgus macaques received a single dose by intramuscular (IM) injection of plasmid DNA, a recombinant adeno-associated viral vector serotype 1 (rAAV1) or a rAAV8 vector expressing cynomolgus macaque EPO. Macaques received a high plasmid dose intended to achieve a significant, but not life-threatening, increase in hematocrit. rAAV vectors were used at low doses to achieve a small increase in hematocrit and to determine the limit of sensitivity for detecting rAAV sequences by single-step PCR. DNA extracted from white blood cells (WBCs) was tested to determine whether WBCs can be collaterally transfected by plasmid or transduced by rAAV vectors in this context, and can be used as a surrogate marker for gene doping. We demonstrate that IM injection of a conventional plasmid and rAAV vectors results in the presence of DNA that can be detected at high levels in blood before rapid elimination, and that rAAV genomes can persist for several months in WBCs.

Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

PubMed

Held, Elizabeth; Cape, Joshua; Tintle, Nathan

2016-01-01

Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

Vector 33: A reduce program for vector algebra and calculus in orthogonal curvilinear coordinates

NASA Astrophysics Data System (ADS)

Harper, David

1989-06-01

This paper describes a package with enables REDUCE 3.3 to perform algebra and calculus operations upon vectors. Basic algebraic operations between vectors and between scalars and vectors are provided, including scalar (dot) product and vector (cross) product. The vector differential operators curl, divergence, gradient and Laplacian are also defined, and are valid in any orthogonal curvilinear coordinate system. The package is written in RLISP to allow algebra and calculus to be performed using notation identical to that for operations. Scalars and vectors can be mixed quite freely in the same expression. The package will be of interest to mathematicians, engineers and scientists who need to perform vector calculations in orthogonal curvilinear coordinates.

F-15B ACTIVE - First supersonic yaw vectoring flight

NASA Technical Reports Server (NTRS)

1996-01-01

On Wednesday, April 24, 1996, the F-15 Advanced Control Technology for Integrated Vehicles (ACTIVE) aircraft achieved its first supersonic yaw vectoring flight at Dryden Flight Research Center, Edwards, California. ACTIVE is a joint NASA, U.S. Air Force, McDonnell Douglas Aerospace (MDA) and Pratt & Whitney (P&W) program. The team will assess performance and technology benefits during flight test operations. Current plans call for approximately 60 flights totaling 100 hours. 'Reaching this milestone is very rewarding. We hope to set some more records before we're through,' stated Roger W. Bursey, P&W's pitch-yaw balance beam nozzle (PYBBN) program manager. A pair of P&W PYBBNs vectored (horizontally side-to-side, pitch is up and down) the thrust for the MDA manufactured F-15 research aircraft. Power to reach supersonic speeds was provided by two high-performance F100-PW-229 engines that were modified with the multi-directional thrust vectoring nozzles. The new concept should lead to significant increases in performance of both civil and military aircraft flying at subsonic and supersonic speeds.

Vectorization and parallelization of the finite strip method for dynamic Mindlin plate problems

NASA Technical Reports Server (NTRS)

Chen, Hsin-Chu; He, Ai-Fang

1993-01-01

The finite strip method is a semi-analytical finite element process which allows for a discrete analysis of certain types of physical problems by discretizing the domain of the problem into finite strips. This method decomposes a single large problem into m smaller independent subproblems when m harmonic functions are employed, thus yielding natural parallelism at a very high level. In this paper we address vectorization and parallelization strategies for the dynamic analysis of simply-supported Mindlin plate bending problems and show how to prevent potential conflicts in memory access during the assemblage process. The vector and parallel implementations of this method and the performance results of a test problem under scalar, vector, and vector-concurrent execution modes on the Alliant FX/80 are also presented.

New Research on MEMS Acoustic Vector Sensors Used in Pipeline Ground Markers

PubMed Central

Song, Xiaopeng; Jian, Zeming; Zhang, Guojun; Liu, Mengran; Guo, Nan; Zhang, Wendong

2015-01-01

According to the demands of current pipeline detection systems, the above-ground marker (AGM) system based on sound detection principle has been a major development trend in pipeline technology. A novel MEMS acoustic vector sensor for AGM systems which has advantages of high sensitivity, high signal-to-noise ratio (SNR), and good low frequency performance has been put forward. Firstly, it is presented that the frequency of the detected sound signal is concentrated in a lower frequency range, and the sound attenuation is relatively low in soil. Secondly, the MEMS acoustic vector sensor structure and basic principles are introduced. Finally, experimental tests are conducted and the results show that in the range of 0°∼90°, when r = 5 m, the proposed MEMS acoustic vector sensor can effectively detect sound signals in soil. The measurement errors of all angles are less than 5°. PMID:25609046

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1996-01-01

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.

Emergence and Prevalence of Human Vector-Borne Diseases in Sink Vector Populations

PubMed Central

Rascalou, Guilhem; Pontier, Dominique; Menu, Frédéric; Gourbière, Sébastien

2012-01-01

Vector-borne diseases represent a major public health concern in most tropical and subtropical areas, and an emerging threat for more developed countries. Our understanding of the ecology, evolution and control of these diseases relies predominantly on theory and data on pathogen transmission in large self-sustaining ‘source’ populations of vectors representative of highly endemic areas. However, there are numerous places where environmental conditions are less favourable to vector populations, but where immigration allows them to persist. We built an epidemiological model to investigate the dynamics of six major human vector borne-diseases in such non self-sustaining ‘sink’ vector populations. The model was parameterized through a review of the literature, and we performed extensive sensitivity analysis to look at the emergence and prevalence of the pathogen that could be encountered in these populations. Despite the low vector abundance in typical sink populations, all six human diseases were able to spread in 15–55% of cases after accidental introduction. The rate of spread was much more strongly influenced by vector longevity, immigration and feeding rates, than by transmission and virulence of the pathogen. Prevalence in humans remained lower than 5% for dengue, leishmaniasis and Japanese encephalitis, but substantially higher for diseases with longer duration of infection; malaria and the American and African trypanosomiasis. Vector-related parameters were again the key factors, although their influence was lower than on pathogen emergence. Our results emphasize the need for ecology and evolution to be thought in the context of metapopulations made of a mosaic of sink and source habitats, and to design vector control program not only targeting areas of high vector density, but working at a larger spatial scale. PMID:22629337

An integrated vector system for cellular studies of phage display-derived peptides.

PubMed

Voss, Stephan D; DeGrand, Alec M; Romeo, Giulio R; Cantley, Lewis C; Frangioni, John V

2002-09-15

Peptide phage display is a method by which large numbers of diverse peptides can be screened for binding to a target of interest. Even when successful, the rate-limiting step is usually validation of peptide bioactivity using living cells. In this paper, we describe an integrated system of vectors that expedites both the screening and the characterization processes. Library construction and screening is performed using an optimized type 3 phage display vector, mJ(1), which is shown to accept peptide libraries of at least 23 amino acids in length. Peptide coding sequences are shuttled from mJ(1) into one of three families of mammalian expression vectors for cell physiological studies. The vector pAL(1) expresses phage display-derived peptides as Gal4 DNA binding domain fusion proteins for transcriptional activation studies. The vectors pG(1), pG(1)N, and pG(1)C express phage display-derived peptides as green fluorescent protein fusions targeted to the entire cell, nucleus, or cytoplasm, respectively. The vector pAP(1) expresses phage display-derived peptides as fusions to secreted placental alkaline phosphatase. Such enzyme fusions can be used as highly sensitive affinity reagents for high-throughput assays and for cloning of peptide-binding cell surface receptors. Taken together, this system of vectors should facilitate the development of phage display-derived peptides into useful biomolecules.

MIC-SVM: Designing A Highly Efficient Support Vector Machine For Advanced Modern Multi-Core and Many-Core Architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

You, Yang; Song, Shuaiwen; Fu, Haohuan

2014-08-16

Support Vector Machine (SVM) has been widely used in data-mining and Big Data applications as modern commercial databases start to attach an increasing importance to the analytic capabilities. In recent years, SVM was adapted to the field of High Performance Computing for power/performance prediction, auto-tuning, and runtime scheduling. However, even at the risk of losing prediction accuracy due to insufficient runtime information, researchers can only afford to apply offline model training to avoid significant runtime training overhead. To address the challenges above, we designed and implemented MICSVM, a highly efficient parallel SVM for x86 based multi-core and many core architectures,more » such as the Intel Ivy Bridge CPUs and Intel Xeon Phi coprocessor (MIC).« less

A highly optimized vectorized code for Monte Carlo simulations of SU(3) lattice gauge theories

NASA Technical Reports Server (NTRS)

Barkai, D.; Moriarty, K. J. M.; Rebbi, C.

1984-01-01

New methods are introduced for improving the performance of the vectorized Monte Carlo SU(3) lattice gauge theory algorithm using the CDC CYBER 205. Structure, algorithm and programming considerations are discussed. The performance achieved for a 16(4) lattice on a 2-pipe system may be phrased in terms of the link update time or overall MFLOPS rates. For 32-bit arithmetic, it is 36.3 microsecond/link for 8 hits per iteration (40.9 microsecond for 10 hits) or 101.5 MFLOPS.

High-efficiency Transduction of Rhesus Hematopoietic Repopulating Cells by a Modified HIV1-based Lentiviral Vector

PubMed Central

Uchida, Naoya; Hargrove, Phillip W.; Lap, Coen J.; Evans, Molly E.; Phang, Oswald; Bonifacino, Aylin C.; Krouse, Allen E.; Metzger, Mark E.; Nguyen, Anh-Dao; Hsieh, Matthew M.; Wolfsberg, Tyra G.; Donahue, Robert E.; Persons, Derek A.; Tisdale, John F.

2012-01-01

Human immunodeficiency virus type 1 (HIV1) vectors poorly transduce rhesus hematopoietic cells due to species-specific restriction factors, including the tripartite motif-containing 5 isoformα (TRIM5α) which targets the HIV1 capsid. We previously developed a chimeric HIV1 (χHIV) vector system wherein the vector genome is packaged with the simian immunodeficiency virus (SIV) capsid for efficient transduction of both rhesus and human CD34+ cells. To evaluate whether χHIV vectors could efficiently transduce rhesus hematopoietic repopulating cells, we performed a competitive repopulation assay in rhesus macaques, in which half of the CD34+ cells were transduced with standard SIV vectors and the other half with χHIV vectors. As compared with SIV vectors, χHIV vectors achieved higher vector integration, and the transgene expression rates were two- to threefold higher in granulocytes and red blood cells and equivalent in lymphocytes and platelets for 2 years. A recipient of χHIV vector-only transduced cells reached up to 40% of transgene expression rates in granulocytes and lymphocytes and 20% in red blood cells. Similar to HIV1 and SIV vectors, χHIV vector frequently integrated into gene regions, especially into introns. In summary, our χHIV vector demonstrated efficient transduction for rhesus long-term repopulating cells, comparable with SIV vectors. This χHIV vector should allow preclinical testing of HIV1-based therapeutic vectors in large animal models. PMID:22871664

Matrix multiplication operations using pair-wise load and splat operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eichenberger, Alexandre E.; Gschwind, Michael K.; Gunnels, John A.

Mechanisms for performing a matrix multiplication operation are provided. A vector load operation is performed to load a first vector operand of the matrix multiplication operation to a first target vector register. A pair-wise load and splat operation is performed to load a pair of scalar values of a second vector operand and replicate the pair of scalar values within a second target vector register. An operation is performed on elements of the first target vector register and elements of the second target vector register to generate a partial product of the matrix multiplication operation. The partial product is accumulatedmore » with other partial products and a resulting accumulated partial product is stored. This operation may be repeated for a second pair of scalar values of the second vector operand.« less

Full Wave Analysis of RF Signal Attenuation in a Lossy Cave using a High Order Time Domain Vector Finite Element Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pingenot, J; Rieben, R; White, D

2004-12-06

We present a computational study of signal propagation and attenuation of a 200 MHz dipole antenna in a cave environment. The cave is modeled as a straight and lossy random rough wall. To simulate a broad frequency band, the full wave Maxwell equations are solved directly in the time domain via a high order vector finite element discretization using the massively parallel CEM code EMSolve. The simulation is performed for a series of random meshes in order to generate statistical data for the propagation and attenuation properties of the cave environment. Results for the power spectral density and phase ofmore » the electric field vector components are presented and discussed.« less

A Method for Integrating Thrust-Vectoring and Actuated Forebody Strakes with Conventional Aerodynamic Controls on a High-Performance Fighter Airplane

NASA Technical Reports Server (NTRS)

Lallman, Frederick J.; Davidson, John B.; Murphy, Patrick C.

1998-01-01

A method, called pseudo controls, of integrating several airplane controls to achieve cooperative operation is presented. The method eliminates conflicting control motions, minimizes the number of feedback control gains, and reduces the complication of feedback gain schedules. The method is applied to the lateral/directional controls of a modified high-performance airplane. The airplane has a conventional set of aerodynamic controls, an experimental set of thrust-vectoring controls, and an experimental set of actuated forebody strakes. The experimental controls give the airplane additional control power for enhanced stability and maneuvering capabilities while flying over an expanded envelope, especially at high angles of attack. The flight controls are scheduled to generate independent body-axis control moments. These control moments are coordinated to produce stability-axis angular accelerations. Inertial coupling moments are compensated. Thrust-vectoring controls are engaged according to their effectiveness relative to that of the aerodynamic controls. Vane-relief logic removes steady and slowly varying commands from the thrust-vectoring controls to alleviate heating of the thrust turning devices. The actuated forebody strakes are engaged at high angles of attack. This report presents the forward-loop elements of a flight control system that positions the flight controls according to the desired stability-axis accelerations. This report does not include the generation of the required angular acceleration commands by means of pilot controls or the feedback of sensed airplane motions.

FPGA Implementation of Generalized Hebbian Algorithm for Texture Classification

PubMed Central

Lin, Shiow-Jyu; Hwang, Wen-Jyi; Lee, Wei-Hao

2012-01-01

This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized Hebbian Algorithm (GHA) because of its simplicity and effectiveness. The architecture is separated into three portions: the weight vector updating unit, the principal computation unit and the memory unit. In the weight vector updating unit, the computation of different synaptic weight vectors shares the same circuit for reducing the area costs. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is physically implemented by Field Programmable Gate Array (FPGA). It is embedded in a System-On-Programmable-Chip (SOPC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs. PMID:22778640

Acid-Labile Poly(glycidyl methacrylate)-Based Star Gene Vectors.

PubMed

Yang, Yan-Yu; Hu, Hao; Wang, Xing; Yang, Fei; Shen, Hong; Xu, Fu-Jian; Wu, De-Cheng

2015-06-10

It was recently reported that ethanolamine-functionalized poly(glycidyl methacrylate) (PGEA) possesses great potential applications in gene therapy due to its good biocompatibility and high transfection efficiency. Importing responsivity into PGEA vectors would further improve their performances. Herein, a series of responsive star-shaped vectors, acetaled β-cyclodextrin-PGEAs (A-CD-PGEAs) consisting of a β-CD core and five PGEA arms linked by acid-labile acetal groups, were proposed and characterized as therapeutic pDNA vectors. The A-CD-PGEAs owned abundant hydroxyl groups to shield extra positive charges of A-CD-PGEAs/pDNA complexes, and the star structure could decrease charge density. The incorporation of acetal linkers endowed A-CD-PGEAs with pH responsivity and degradation. In weakly acidic endosome, the broken acetal linkers resulted in decomposition of A-CD-PGEAs and morphological transformation of A-CD-PGEAs/pDNA complexes, lowering cytotoxicity and accelerating release of pDNA. In comparison with control CD-PGEAs without acetal linkers, A-CD-PGEAs exhibited significantly better transfection performances.

VEST: Abstract vector calculus simplification in Mathematica

NASA Astrophysics Data System (ADS)

Squire, J.; Burby, J.; Qin, H.

2014-01-01

We present a new package, VEST (Vector Einstein Summation Tools), that performs abstract vector calculus computations in Mathematica. Through the use of index notation, VEST is able to reduce three-dimensional scalar and vector expressions of a very general type to a well defined standard form. In addition, utilizing properties of the Levi-Civita symbol, the program can derive types of multi-term vector identities that are not recognized by reduction, subsequently applying these to simplify large expressions. In a companion paper Burby et al. (2013) [12], we employ VEST in the automation of the calculation of high-order Lagrangians for the single particle guiding center system in plasma physics, a computation which illustrates its ability to handle very large expressions. VEST has been designed to be simple and intuitive to use, both for basic checking of work and more involved computations.

Vector Adaptive/Predictive Encoding Of Speech

NASA Technical Reports Server (NTRS)

Chen, Juin-Hwey; Gersho, Allen

1989-01-01

Vector adaptive/predictive technique for digital encoding of speech signals yields decoded speech of very good quality after transmission at coding rate of 9.6 kb/s and of reasonably good quality at 4.8 kb/s. Requires 3 to 4 million multiplications and additions per second. Combines advantages of adaptive/predictive coding, and code-excited linear prediction, yielding speech of high quality but requires 600 million multiplications and additions per second at encoding rate of 4.8 kb/s. Vector adaptive/predictive coding technique bridges gaps in performance and complexity between adaptive/predictive coding and code-excited linear prediction.

Design and performance of an ultra-high vacuum spin-polarized scanning tunneling microscope operating at 30 mK and in a vector magnetic field

NASA Astrophysics Data System (ADS)

von Allwörden, Henning; Eich, Andreas; Knol, Elze J.; Hermenau, Jan; Sonntag, Andreas; Gerritsen, Jan W.; Wegner, Daniel; Khajetoorians, Alexander A.

2018-03-01

We describe the design and performance of a scanning tunneling microscope (STM) that operates at a base temperature of 30 mK in a vector magnetic field. The cryogenics is based on an ultra-high vacuum (UHV) top-loading wet dilution refrigerator that contains a vector magnet allowing for fields up to 9 T perpendicular and 4 T parallel to the sample. The STM is placed in a multi-chamber UHV system, which allows in situ preparation and exchange of samples and tips. The entire system rests on a 150-ton concrete block suspended by pneumatic isolators, which is housed in an acoustically isolated and electromagnetically shielded laboratory optimized for extremely low noise scanning probe measurements. We demonstrate the overall performance by illustrating atomic resolution and quasiparticle interference imaging and detail the vibrational noise of both the laboratory and microscope. We also determine the electron temperature via measurement of the superconducting gap of Re(0001) and illustrate magnetic field-dependent measurements of the spin excitations of individual Fe atoms on Pt(111). Finally, we demonstrate spin resolution by imaging the magnetic structure of the Fe double layer on W(110).

Design and performance of an ultra-high vacuum spin-polarized scanning tunneling microscope operating at 30 mK and in a vector magnetic field.

PubMed

von Allwörden, Henning; Eich, Andreas; Knol, Elze J; Hermenau, Jan; Sonntag, Andreas; Gerritsen, Jan W; Wegner, Daniel; Khajetoorians, Alexander A

2018-03-01

We describe the design and performance of a scanning tunneling microscope (STM) that operates at a base temperature of 30 mK in a vector magnetic field. The cryogenics is based on an ultra-high vacuum (UHV) top-loading wet dilution refrigerator that contains a vector magnet allowing for fields up to 9 T perpendicular and 4 T parallel to the sample. The STM is placed in a multi-chamber UHV system, which allows in situ preparation and exchange of samples and tips. The entire system rests on a 150-ton concrete block suspended by pneumatic isolators, which is housed in an acoustically isolated and electromagnetically shielded laboratory optimized for extremely low noise scanning probe measurements. We demonstrate the overall performance by illustrating atomic resolution and quasiparticle interference imaging and detail the vibrational noise of both the laboratory and microscope. We also determine the electron temperature via measurement of the superconducting gap of Re(0001) and illustrate magnetic field-dependent measurements of the spin excitations of individual Fe atoms on Pt(111). Finally, we demonstrate spin resolution by imaging the magnetic structure of the Fe double layer on W(110).

Design and Integration of an Actuated Nose Strake Control System

NASA Technical Reports Server (NTRS)

Flick, Bradley C.; Thomson, Michael P.; Regenie, Victoria A.; Wichman, Keith D.; Pahle, Joseph W.; Earls, Michael R.

1996-01-01

Aircraft flight characteristics at high angles of attack can be improved by controlling vortices shed from the nose. These characteristics have been investigated with the integration of the actuated nose strakes for enhanced rolling (ANSER) control system into the NASA F-18 High Alpha Research Vehicle. Several hardware and software systems were developed to enable performance of the research goals. A strake interface box was developed to perform actuator control and failure detection outside the flight control computer. A three-mode ANSER control law was developed and installed in the Research Flight Control System. The thrust-vectoring mode does not command the strakes. The strakes and thrust-vectoring mode uses a combination of thrust vectoring and strakes for lateral- directional control, and strake mode uses strakes only for lateral-directional control. The system was integrated and tested in the Dryden Flight Research Center (DFRC) simulation for testing before installation in the aircraft. Performance of the ANSER system was monitored in real time during the 89-flight ANSER flight test program in the DFRC Mission Control Center. One discrepancy resulted in a set of research data not being obtained. The experiment was otherwise considered a success with the majority of the research objectives being met.

(Re)engineering Earth System Models to Expose Greater Concurrency for Ultrascale Computing: Practice, Experience, and Musings

NASA Astrophysics Data System (ADS)

Mills, R. T.

2014-12-01

As the high performance computing (HPC) community pushes towards the exascale horizon, the importance and prevalence of fine-grained parallelism in new computer architectures is increasing. This is perhaps most apparent in the proliferation of so-called "accelerators" such as the Intel Xeon Phi or NVIDIA GPGPUs, but the trend also holds for CPUs, where serial performance has grown slowly and effective use of hardware threads and vector units are becoming increasingly important to realizing high performance. This has significant implications for weather, climate, and Earth system modeling codes, many of which display impressive scalability across MPI ranks but take relatively little advantage of threading and vector processing. In addition to increasing parallelism, next generation codes will also need to address increasingly deep hierarchies for data movement: NUMA/cache levels, on node vs. off node, local vs. wide neighborhoods on the interconnect, and even in the I/O system. We will discuss some approaches (grounded in experiences with the Intel Xeon Phi architecture) for restructuring Earth science codes to maximize concurrency across multiple levels (vectors, threads, MPI ranks), and also discuss some novel approaches for minimizing expensive data movement/communication.

Thrust vectoring for lateral-directional stability

NASA Technical Reports Server (NTRS)

Peron, Lee R.; Carpenter, Thomas

1992-01-01

The advantages and disadvantages of using thrust vectoring for lateral-directional control and the effects of reducing the tail size of a single-engine aircraft were investigated. The aerodynamic characteristics of the F-16 aircraft were generated by using the Aerodynamic Preliminary Analysis System II panel code. The resulting lateral-directional linear perturbation analysis of a modified F-16 aircraft with various tail sizes and yaw vectoring was performed at several speeds and altitudes to determine the stability and control trends for the aircraft compared to these trends for a baseline aircraft. A study of the paddle-type turning vane thrust vectoring control system as used on the National Aeronautics and Space Administration F/A-18 High Alpha Research Vehicle is also presented.

Vectors and Rotations in 3-Dimensions: Vector Algebra for the C++ Programmer

DTIC Science & Technology

2016-12-01

Proving Ground, MD 21005-5068 This report describes 2 C++ classes: a Vector class for performing vector algebra in 3-dimensional space ( 3D ) and a Rotation...class for performing rotations of vectors in 3D . Each class is self-contained in a single header file (Vector.h and Rotation.h) so that a C...vector, rotation, 3D , quaternion, C++ tools, rotation sequence, Euler angles, yaw, pitch, roll, orientation 98 Richard Saucier 410-278-6721Unclassified

Implementation of a fast digital optical matrix-vector multiplier using a holographic look-up table and residue arithmetic

NASA Technical Reports Server (NTRS)

Habiby, Sarry F.; Collins, Stuart A., Jr.

1987-01-01

The design and implementation of a digital (numerical) optical matrix-vector multiplier are presented. A Hughes liquid crystal light valve, the residue arithmetic representation, and a holographic optical memory are used to construct position coded optical look-up tables. All operations are performed in effectively one light valve response time with a potential for a high information density.

Implementation of a fast digital optical matrix-vector multiplier using a holographic look-up table and residue arithmetic.

PubMed

Habiby, S F; Collins, S A

1987-11-01

The design and implementation of a digital (numerical) optical matrix-vector multiplier are presented. A Hughes liquid crystal light valve, the residue arithmetic representation, and a holographic optical memory are used to construct position coded optical look-up tables. All operations are performed in effectively one light valve response time with a potential for a high information density.

A fast and high performance multiple data integration algorithm for identifying human disease genes

PubMed Central

2015-01-01

Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620

Infection of an Insect Vector with a Bacterial Plant Pathogen Increases Its Propensity for Dispersal

PubMed Central

Coy, Monique R.; Stelinski, Lukasz L.; Pelz-Stelinski, Kirsten S.

2015-01-01

The spread of vector-transmitted pathogens relies on complex interactions between host, vector and pathogen. In sessile plant pathosystems, the spread of a pathogen highly depends on the movement and mobility of the vector. However, questions remain as to whether and how pathogen-induced vector manipulations may affect the spread of a plant pathogen. Here we report for the first time that infection with a bacterial plant pathogen increases the probability of vector dispersal, and that such movement of vectors is likely manipulated by a bacterial plant pathogen. We investigated how Candidatus Liberibacter asiaticus (CLas) affects dispersal behavior, flight capacity, and the sexual attraction of its vector, the Asian citrus psyllid (Diaphorina citri Kuwayama). CLas is the putative causal agent of huanglongbing (HLB), which is a disease that threatens the viability of commercial citrus production worldwide. When D. citri developed on CLas-infected plants, short distance dispersal of male D. citri was greater compared to counterparts reared on uninfected plants. Flight by CLas-infected D. citri was initiated earlier and long flight events were more common than by uninfected psyllids, as measured by a flight mill apparatus. Additionally, CLas titers were higher among psyllids that performed long flights than psyllid that performed short flights. Finally, attractiveness of female D. citri that developed on infected plants to male conspecifics increased proportionally with increasing CLas bacterial titers measured within female psyllids. Our study indicates that the phytopathogen, CLas, may manipulate movement and mate selection behavior of their vectors, which is a possible evolved mechanism to promote their own spread. These results have global implications for both current HLB models of disease spread and control strategies. PMID:26083763

Comparing the performance of two CBIRS indexing schemes

NASA Astrophysics Data System (ADS)

Mueller, Wolfgang; Robbert, Guenter; Henrich, Andreas

2003-01-01

Content based image retrieval (CBIR) as it is known today has to deal with a number of challenges. Quickly summarized, the main challenges are firstly, to bridge the semantic gap between high-level concepts and low-level features using feedback, secondly to provide performance under adverse conditions. High-dimensional spaces, as well as a demanding machine learning task make the right way of indexing an important issue. When indexing multimedia data, most groups opt for extraction of high-dimensional feature vectors from the data, followed by dimensionality reduction like PCA (Principal Components Analysis) or LSI (Latent Semantic Indexing). The resulting vectors are indexed using spatial indexing structures such as kd-trees or R-trees, for example. Other projects, such as MARS and Viper propose the adaptation of text indexing techniques, notably the inverted file. Here, the Viper system is the most direct adaptation of text retrieval techniques to quantized vectors. However, while the Viper query engine provides decent performance together with impressive user-feedback behavior, as well as the possibility for easy integration of long-term learning algorithms, and support for potentially infinite feature vectors, there has been no comparison of vector-based methods and inverted-file-based methods under similar conditions. In this publication, we compare a CBIR query engine that uses inverted files (Bothrops, a rewrite of the Viper query engine based on a relational database), and a CBIR query engine based on LSD (Local Split Decision) trees for spatial indexing using the same feature sets. The Benchathlon initiative works on providing a set of images and ground truth for simulating image queries by example and corresponding user feedback. When performing the Benchathlon benchmark on a CBIR system (the System Under Test, SUT), a benchmarking harness connects over internet to the SUT, performing a number of queries using an agreed-upon protocol, the multimedia retrieval markup language (MRML). Using this benchmark one can measure the quality of retrieval, as well as the overall (speed) performance of the benchmarked system. Our Benchmarks will draw on the Benchathlon"s work for documenting the retrieval performance of both inverted file-based and LSD tree based techniques. However in addition to these results, we will present statistics, that can be obtained only inside the system under test. These statistics will include the number of complex mathematical operations, as well as the amount of data that has to be read from disk during operation of a query.

Searching for transcription factor binding sites in vector spaces

PubMed Central

2012-01-01

Background Computational approaches to transcription factor binding site identification have been actively researched in the past decade. Learning from known binding sites, new binding sites of a transcription factor in unannotated sequences can be identified. A number of search methods have been introduced over the years. However, one can rarely find one single method that performs the best on all the transcription factors. Instead, to identify the best method for a particular transcription factor, one usually has to compare a handful of methods. Hence, it is highly desirable for a method to perform automatic optimization for individual transcription factors. Results We proposed to search for transcription factor binding sites in vector spaces. This framework allows us to identify the best method for each individual transcription factor. We further introduced two novel methods, the negative-to-positive vector (NPV) and optimal discriminating vector (ODV) methods, to construct query vectors to search for binding sites in vector spaces. Extensive cross-validation experiments showed that the proposed methods significantly outperformed the ungapped likelihood under positional background method, a state-of-the-art method, and the widely-used position-specific scoring matrix method. We further demonstrated that motif subtypes of a TF can be readily identified in this framework and two variants called the k NPV and k ODV methods benefited significantly from motif subtype identification. Finally, independent validation on ChIP-seq data showed that the ODV and NPV methods significantly outperformed the other compared methods. Conclusions We conclude that the proposed framework is highly flexible. It enables the two novel methods to automatically identify a TF-specific subspace to search for binding sites. Implementations are available as source code at: http://biogrid.engr.uconn.edu/tfbs_search/. PMID:23244338

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet.

PubMed

Mariappan, Leo; Hu, Gang; He, Bin

2014-02-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼ 1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction.

Effects of internal yaw-vectoring devices on the static performance of a pitch-vectoring nonaxisymmetric convergent-divergent nozzle

NASA Technical Reports Server (NTRS)

Asbury, Scott C.

1993-01-01

An investigation was conducted in the static test facility of the Langley 16-Foot Transonic Tunnel to evaluate the internal performance of a nonaxisymmetric convergent divergent nozzle designed to have simultaneous pitch and yaw thrust vectoring capability. This concept utilized divergent flap deflection for thrust vectoring in the pitch plane and flow-turning deflectors installed within the divergent flaps for yaw thrust vectoring. Modifications consisting of reducing the sidewall length and deflecting the sidewall outboard were investigated as means to increase yaw-vectoring performance. This investigation studied the effects of multiaxis (pitch and yaw) thrust vectoring on nozzle internal performance characteristics. All tests were conducted with no external flow, and nozzle pressure ratio was varied from 2.0 to approximately 13.0. The results indicate that this nozzle concept can successfully generate multiaxis thrust vectoring. Deflection of the divergent flaps produced resultant pitch vector angles that, although dependent on nozzle pressure ratio, were nearly equal to the geometric pitch vector angle. Losses in resultant thrust due to pitch vectoring were small or negligible. The yaw deflectors produced resultant yaw vector angles up to 21 degrees that were controllable by varying yaw deflector rotation. However, yaw deflector rotation resulted in significant losses in thrust ratios and, in some cases, nozzle discharge coefficient. Either of the sidewall modifications generally reduced these losses and increased maximum resultant yaw vector angle. During multiaxis (simultaneous pitch and yaw) thrust vectoring, little or no cross coupling between the thrust vectoring processes was observed.

Fusion PIC code performance analysis on the Cori KNL system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koskela, Tuomas S.; Deslippe, Jack; Friesen, Brian

We study the attainable performance of Particle-In-Cell codes on the Cori KNL system by analyzing a miniature particle push application based on the fusion PIC code XGC1. We start from the most basic building blocks of a PIC code and build up the complexity to identify the kernels that cost the most in performance and focus optimization efforts there. Particle push kernels operate at high AI and are not likely to be memory bandwidth or even cache bandwidth bound on KNL. Therefore, we see only minor benefits from the high bandwidth memory available on KNL, and achieving good vectorization ismore » shown to be the most beneficial optimization path with theoretical yield of up to 8x speedup on KNL. In practice we are able to obtain up to a 4x gain from vectorization due to limitations set by the data layout and memory latency.« less

High-performance ultra-low power VLSI analog processor for data compression

NASA Technical Reports Server (NTRS)

Tawel, Raoul (Inventor)

1996-01-01

An apparatus for data compression employing a parallel analog processor. The apparatus includes an array of processor cells with N columns and M rows wherein the processor cells have an input device, memory device, and processor device. The input device is used for inputting a series of input vectors. Each input vector is simultaneously input into each column of the array of processor cells in a pre-determined sequential order. An input vector is made up of M components, ones of which are input into ones of M processor cells making up a column of the array. The memory device is used for providing ones of M components of a codebook vector to ones of the processor cells making up a column of the array. A different codebook vector is provided to each of the N columns of the array. The processor device is used for simultaneously comparing the components of each input vector to corresponding components of each codebook vector, and for outputting a signal representative of the closeness between the compared vector components. A combination device is used to combine the signal output from each processor cell in each column of the array and to output a combined signal. A closeness determination device is then used for determining which codebook vector is closest to an input vector from the combined signals, and for outputting a codebook vector index indicating which of the N codebook vectors was the closest to each input vector input into the array.

The Performance of the NAS HSPs in 1st Half of 1994

NASA Technical Reports Server (NTRS)

Bergeron, Robert J.; Walter, Howard (Technical Monitor)

1995-01-01

During the first six months of 1994, the NAS (National Airspace System) 16-CPU Y-MP C90 Von Neumann (VN) delivered an average throughput of 4.045 GFLOPS while the ACSF (Aeronautics Consolidated Supercomputer Facility) 8-CPU Y-MP C90 Eagle averaged 1.658 GFLOPS. The VN rate represents a machine efficiency of 26.3% whereas the Eagle rate corresponds to a machine efficiency of 21.6%. VN displayed a greater efficiency than Eagle primarily because the stronger workload demand for its CPU cycles allowed it to devote more time to user programs and less time to idle. An additional factor increasing VN efficiency was the ability of the UNICOS 8.0 Operating System to deliver a larger fraction of CPU time to user programs. Although measurements indicate increasing vector length for both workloads, insufficient vector lengths continue to hinder HSP (High Speed Processor) performance. To improve HSP performance, NAS should continue to encourage the HSP users to modify their codes to increase program vector length.

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs

PubMed Central

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-01-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network. PMID:28763014

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

PubMed

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-08-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

X-31 high angle of attack control system performance

NASA Technical Reports Server (NTRS)

Huber, Peter; Seamount, Patricia

1994-01-01

The design goals for the X-31 flight control system were: (1) level 1 handling qualities during post-stall maneuvering (30 to 70 degrees angle-of-attack); (2) thrust vectoring to enhance performance across the flight envelope; and (3) adequate pitch-down authority at high angle-of-attack. Additional performance goals are discussed. A description of the flight control system is presented, highlighting flight control system features in the pitch and roll axes and X-31 thrust vectoring characteristics. The high angle-of-attack envelope clearance approach will be described, including a brief explanation of analysis techniques and tools. Also, problems encountered during envelope expansion will be discussed. This presentation emphasizes control system solutions to problems encountered in envelope expansion. An essentially 'care free' envelope was cleared for the close-in-combat demonstrator phase. High angle-of-attack flying qualities maneuvers are currently being flown and evaluated. These results are compared with pilot opinions expressed during the close-in-combat program and with results obtained from the F-18 HARV for identical maneuvers. The status and preliminary results of these tests are discussed.

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

NASA Technical Reports Server (NTRS)

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.

Search for heavy resonances that decay into a vector boson and a Higgs boson in hadronic final states at √{s} = 13 {TeV}

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rabady, D.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Strauss, J.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Gonzalez, J. Suarez; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Zeid, S. Abu; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Velde, C. Vander; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Marono, M. Vidal; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Martins Junior, M. Correa; Hensel, C.; Moraes, A.; Pol, M. E.; Teles, P. Rebello; Chagas, E. Belchior Batista Das; Carvalho, W.; Chinellato, J.; Custódio, A.; Costa, E. M. Da; Silveira, G. G. Da; Damiao, D. De Jesus; De Souza, S. Fonseca; Guativa, L. M. Huertas; Malbouisson, H.; De Almeida, M. Melo; Herrera, C. Mora; Mundim, L.; Nogima, H.; Santoro, A.; Sznajder, A.; Manganote, E. J. Tonelli; De Araujo, F. Torres Da Silva; Pereira, A. Vilela; Ahuja, S.; Bernardes, C. A.; Tomei, T. R. Fernandez Perez; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Abad, D. Romero; Vargas, J. C. Ruiz; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Stoykova, S.; Sultanov, G.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Sierra, L. F. Chaparro; Florez, C.; Hernández, C. F. González; Alvarez, J. D. Ruiz; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Cipriano, P. M. Ribeiro; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Jarrin, E. Carrera; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; de Monchenault, G. Hamel; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; de Cassagnac, R. Granier; Jo, M.; Lisniak, S.; Lobanov, A.; Blanco, J. Martin; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Leiton, A. G. Stahl; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Jansová, M.; Bihan, A.-C. Le; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; Depasse, P.; Mamouni, H. El; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Donckt, M. Vander; Viret, S.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Martin, M. Aldaya; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Martínez, A. Bermúdez; Anuar, A. A. Bin; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Pardos, C. Diez; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garcia, J. Garay; Geiser, A.; Gizhko, A.; Luyando, J. M. Grados; Grohsjean, A.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Bein, S.; Blobel, V.; Vignali, M. Centis; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Freund, B.; Friese, R.; Giffels, M.; Gilbert, A.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Evangelou, I.; Foudas, C.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Csanad, M.; Filipovic, N.; Pasztor, G.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Bhawandeep, U.; Chawla, R.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Chowdhury, S. Roy; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Tadavani, E. Eskandari; Etesami, S. M.; Khakzad, M.; Najafabadi, M. Mohammadi; Naseri, M.; Mehdiabadi, S. Paktinat; Hosseinabadi, F. Rezaei; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Chatterjee, K.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Robutti, E.; Tosi, S.; Brianza, L.; Brivio, F.; Ciriolo, V.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pauwels, K.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; de Fatis, T. Tabarelli; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Khan, W. A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; De Oliveira, A. Carvalho Antunes; Checchia, P.; Manzano, P. De Castro; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Solestizi, L. Alunni; Biasini, M.; Bilei, G. M.; Cecchi, C.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Manoni, E.; Mantovani, G.; Mariani, V.; Menichelli, M.; Rossi, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giannini, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Manca, E.; Mandorli, G.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Angioni, G. L. Pinna; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, J.; Lee, S.; Lee, S. W.; Moon, C. S.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Moon, D. H.; Oh, G.; Cifuentes, J. A. Brochero; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Kim, J. S.; Lee, H.; Lee, K.; Nam, K.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Choi, Y.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Ali, M. A. B. Md; Idris, F. Mohamad; Abdullah, W. A. T. Wan; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; Cruz-Burelo, E. De La; Cruz, I. Heredia-De La; Lopez-Fernandez, R.; Guisao, J. Mejia; Sanchez-Hernandez, A.; Moreno, S. Carrillo; Barrera, C. Oropeza; Valencia, F. Vazquez; Pedraza, I.; Ibarguen, H. A. Salazar; Estrada, C. Uribe; Pineda, A. Morelos; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Silva, C. Beirão Da Cruz E.; Calpas, B.; Di Francesco, A.; Faccioli, P.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Iglesias, L. Lloret; Nemallapudi, M. V.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Afanasiev, S.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Stepennov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chistov, R.; Danilov, M.; Parygin, P.; Philippov, D.; Polikarpov, S.; Tarkovskii, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Blinov, V.; Skovpen, Y.; Shtol, D.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Maestre, J. Alcaraz; Luna, M. Barrio; Cerrada, M.; Colino, N.; Cruz, B. De La; Peris, A. Delgado; Del Valle, A. Escalante; Bedoya, C. Fernandez; Ramos, J. P. Fernández; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Lopez, O. Gonzalez; Lopez, S. Goy; Hernandez, J. M.; Josa, M. I.; Yzquierdo, A. Pérez-Calero; Pelayo, J. Puerta; Olmeda, A. Quintario; Redondo, I.; Romero, L.; Soares, M. S.; Fernández, A. Álvarez; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Erice, C.; Menendez, J. Fernandez; Caballero, I. Gonzalez; Fernández, J. R. González; Cortezon, E. Palencia; Cruz, S. Sanchez; Andrés, I. Suárez; Vischia, P.; Garcia, J. M. Vizan; Cabrillo, I. J.; Calderon, A.; Quero, B. Chazin; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Virto, A. Lopez; Marco, J.; Rivero, C. Martinez; Arbol, P. Martinez Ruiz del; Matorras, F.; Gomez, J. Piedra; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Cortabitarte, R. Vilar; Abbaneo, D.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bianco, M.; Bloch, P.; Bocci, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; Chapon, E.; Chen, Y.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Karacheban, O.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Verweij, M.; Wardle, N.; Zeuner, W. D.; Bertl, W.; Caminada, L.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Bachmair, F.; Bäni, L.; Berger, P.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Klijnsma, T.; Lustermann, W.; Mangano, B.; Marionneau, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Schönenberger, M.; Shchutska, L.; Tavolaro, V. R.; Theofilatos, K.; Olsson, M. L. Vesterbacka; Wallny, R.; Zagozdzinska, A.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Canelli, M. F.; De Cosa, A.; Donato, S.; Galloni, C.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Moya, M. Miñano; Paganis, E.; Psallidas, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Adiguzel, A.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Topaksu, A. Kayis; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Cerci, D. Sunar; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Davignon, O.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Nasr-storey, S. Seif El; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Bainbridge, R.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Elwood, A.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Palladino, V.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Summers, S.; Tapper, A.; Uchida, K.; Acosta, M. Vazquez; Virdee, T.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. 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T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; De Sá, R. Lopes; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Gonzalez, I. D. Sandoval; Tonjes, M. B.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Royon, C.; Sanders, S.; Schmitz, E.; Stringer, R.; Takaki, J. D. Tapia; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Ceballos, G. Gomez; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Suarez, R. Gonzalez; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; De Lima, R. Teixeira; Trocino, D.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Anampa, K. Hurtado; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Benaglia, A.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Espinosa, T. A. Gómez; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Elayavalli, R. Kunnawalkam; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Hernandez, A. Castaneda; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2017-09-01

A search for heavy resonances with masses above 1 {TeV}, decaying to final states containing a vector boson and a Higgs boson, is presented. The search considers hadronic decays of the vector boson, and Higgs boson decays to b quarks. The decay products are highly boosted, and each collimated pair of quarks is reconstructed as a single, massive jet. The analysis is performed using a data sample collected in 2016 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 {TeV}, corresponding to an integrated luminosity of 35.9 {fb}^{-1}. The data are consistent with the background expectation and are used to place limits on the parameters of a theoretical model with a heavy vector triplet. In the benchmark scenario with mass-degenerate W' and Z' bosons decaying predominantly to pairs of standard model bosons, for the first time heavy resonances for masses as high as 3.3 {TeV} are excluded at 95% confidence level, setting the most stringent constraints to date on such states decaying into a vector boson and a Higgs boson.

Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

PubMed Central

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality. PMID:23049544

Medical image compression based on vector quantization with variable block sizes in wavelet domain.

PubMed

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

Computer-aided diagnosis with textural features for breast lesions in sonograms.

PubMed

Chen, Dar-Ren; Huang, Yu-Len; Lin, Sheng-Hsiung

2011-04-01

Computer-aided diagnosis (CAD) systems provided second beneficial support reference and enhance the diagnostic accuracy. This paper was aimed to develop and evaluate a CAD with texture analysis in the classification of breast tumors for ultrasound images. The ultrasound (US) dataset evaluated in this study composed of 1020 sonograms of region of interest (ROI) subimages from 255 patients. Two-view sonogram (longitudinal and transverse views) and four different rectangular regions were utilized to analyze each tumor. Six practical textural features from the US images were performed to classify breast tumors as benign or malignant. However, the textural features always perform as a high dimensional vector; high dimensional vector is unfavorable to differentiate breast tumors in practice. The principal component analysis (PCA) was used to reduce the dimension of textural feature vector and then the image retrieval technique was performed to differentiate between benign and malignant tumors. In the experiments, all the cases were sampled with k-fold cross-validation (k=10) to evaluate the performance with receiver operating characteristic (ROC) curve. The area (A(Z)) under the ROC curve for the proposed CAD system with the specific textural features was 0.925±0.019. The classification ability for breast tumor with textural information is satisfactory. This system differentiates benign from malignant breast tumors with a good result and is therefore clinically useful to provide a second opinion. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Support Vector Machine-Based Gender Identification Using Speech Signal

NASA Astrophysics Data System (ADS)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Community Participation in Chagas Disease Vector Surveillance: Systematic Review

PubMed Central

Abad-Franch, Fernando; Vega, M. Celeste; Rolón, Miriam S.; Santos, Walter S.; Rojas de Arias, Antonieta

2011-01-01

Background Vector control has substantially reduced Chagas disease (ChD) incidence. However, transmission by household-reinfesting triatomines persists, suggesting that entomological surveillance should play a crucial role in the long-term interruption of transmission. Yet, infestation foci become smaller and harder to detect as vector control proceeds, and highly sensitive surveillance methods are needed. Community participation (CP) and vector-detection devices (VDDs) are both thought to enhance surveillance, but this remains to be thoroughly assessed. Methodology/Principal Findings We searched Medline, Web of Knowledge, Scopus, LILACS, SciELO, the bibliographies of retrieved studies, and our own records. Data from studies describing vector control and/or surveillance interventions were extracted by two reviewers. Outcomes of primary interest included changes in infestation rates and the detection of infestation/reinfestation foci. Most results likely depended on study- and site-specific conditions, precluding meta-analysis, but we re-analysed data from studies comparing vector control and detection methods whenever possible. Results confirm that professional, insecticide-based vector control is highly effective, but also show that reinfestation by native triatomines is common and widespread across Latin America. Bug notification by householders (the simplest CP-based strategy) significantly boosts vector detection probabilities; in comparison, both active searches and VDDs perform poorly, although they might in some cases complement each other. Conclusions/Significance CP should become a strategic component of ChD surveillance, but only professional insecticide spraying seems consistently effective at eliminating infestation foci. Involvement of stakeholders at all process stages, from planning to evaluation, would probably enhance such CP-based strategies. PMID:21713022

Matrix-vector multiplication using digital partitioning for more accurate optical computing

NASA Technical Reports Server (NTRS)

Gary, C. K.

1992-01-01

Digital partitioning offers a flexible means of increasing the accuracy of an optical matrix-vector processor. This algorithm can be implemented with the same architecture required for a purely analog processor, which gives optical matrix-vector processors the ability to perform high-accuracy calculations at speeds comparable with or greater than electronic computers as well as the ability to perform analog operations at a much greater speed. Digital partitioning is compared with digital multiplication by analog convolution, residue number systems, and redundant number representation in terms of the size and the speed required for an equivalent throughput as well as in terms of the hardware requirements. Digital partitioning and digital multiplication by analog convolution are found to be the most efficient alogrithms if coding time and hardware are considered, and the architecture for digital partitioning permits the use of analog computations to provide the greatest throughput for a single processor.

Static performance investigation of a skewed-throat multiaxis thrust-vectoring nozzle concept

NASA Technical Reports Server (NTRS)

Wing, David J.

1994-01-01

The static performance of a jet exhaust nozzle which achieves multiaxis thrust vectoring by physically skewing the geometric throat has been characterized in the static test facility of the 16-Foot Transonic Tunnel at NASA Langley Research Center. The nozzle has an asymmetric internal geometry defined by four surfaces: a convergent-divergent upper surface with its ridge perpendicular to the nozzle centerline, a convergent-divergent lower surface with its ridge skewed relative to the nozzle centerline, an outwardly deflected sidewall, and a straight sidewall. The primary goal of the concept is to provide efficient yaw thrust vectoring by forcing the sonic plane (nozzle throat) to form at a yaw angle defined by the skewed ridge of the lower surface contour. A secondary goal is to provide multiaxis thrust vectoring by combining the skewed-throat yaw-vectoring concept with upper and lower pitch flap deflections. The geometric parameters varied in this investigation included lower surface ridge skew angle, nozzle expansion ratio (divergence angle), aspect ratio, pitch flap deflection angle, and sidewall deflection angle. Nozzle pressure ratio was varied from 2 to a high of 11.5 for some configurations. The results of the investigation indicate that efficient, substantial multiaxis thrust vectoring was achieved by the skewed-throat nozzle concept. However, certain control surface deflections destabilized the internal flow field, which resulted in substantial shifts in the position and orientation of the sonic plane and had an adverse effect on thrust-vectoring and weight flow characteristics. By increasing the expansion ratio, the location of the sonic plane was stabilized. The asymmetric design resulted in interdependent pitch and yaw thrust vectoring as well as nonzero thrust-vector angles with undeflected control surfaces. By skewing the ridges of both the upper and lower surface contours, the interdependency between pitch and yaw thrust vectoring may be eliminated and the location of the sonic plane may be further stabilized.

Ambulatory Monitoring of Congestive Heart Failure by Multiple Bioelectric Impedance Vectors

PubMed Central

Khoury, Dirar S.; Naware, Mihir; Siou, Jeff; Blomqvist, Andreas; Mathuria, Nilesh S.; Wang, Jianwen; Shih, Hue-Teh; Nagueh, Sherif F.; Panescu, Dorin

2009-01-01

Objectives To investigate properties of multiple bioelectric impedance signals recorded during congestive heart failure (CHF) by utilizing various electrode configurations of an implanted cardiac resynchronization therapy (CRT) system. Background Monitoring of CHF has relied mainly on right-heart sensors. Methods Fifteen normal dogs underwent implantation of CRT systems using standard leads. An additional left atrial (LA) pressure lead-sensor was implanted in 5 dogs. Continuous rapid right ventricular (RV) pacing was applied over several weeks. Left ventricular (LV) catheterization and echocardiography were performed biweekly. Six steady-state impedance signals, utilizing intrathorcaic and intracardiac vectors, were measured via ring (r), coil (c), and device Can electrodes. Results All animals developed CHF after 2–4 weeks of pacing. Impedance diminished gradually during CHF induction, but at varying rates for different vectors. Impedance during CHF decreased significantly in all measured vectors: LVr-Can, −17%; LVr-RVr, −15%; LVr-RAr, −11%; RVr-Can, −12%; RVc-Can, −7%; RAr-Can, −5%. The LVr-Can vector reflected both the fastest and largest change in impedance in comparison to vectors employing only right-heart electrodes, and was highly reflective of changes in LV end-diastolic volume and LA pressure. Conclusions Impedance, acquired via different lead-electrodes, have variable responses to CHF. Impedance vectors employing a LV lead are highly responsive to physiologic changes during CHF. Measuring multiple impedance signals could be useful for optimizing ambulatory monitoring in heart failure patients. PMID:19298923

A High Performance Block Eigensolver for Nuclear Configuration Interaction Calculations

DOE PAGES

Aktulga, Hasan Metin; Afibuzzaman, Md.; Williams, Samuel; ...

2017-06-01

As on-node parallelism increases and the performance gap between the processor and the memory system widens, achieving high performance in large-scale scientific applications requires an architecture-aware design of algorithms and solvers. We focus on the eigenvalue problem arising in nuclear Configuration Interaction (CI) calculations, where a few extreme eigenpairs of a sparse symmetric matrix are needed. Here, we consider a block iterative eigensolver whose main computational kernels are the multiplication of a sparse matrix with multiple vectors (SpMM), and tall-skinny matrix operations. We then present techniques to significantly improve the SpMM and the transpose operation SpMM T by using themore » compressed sparse blocks (CSB) format. We achieve 3-4× speedup on the requisite operations over good implementations with the commonly used compressed sparse row (CSR) format. We develop a performance model that allows us to correctly estimate the performance of our SpMM kernel implementations, and we identify cache bandwidth as a potential performance bottleneck beyond DRAM. We also analyze and optimize the performance of LOBPCG kernels (inner product and linear combinations on multiple vectors) and show up to 15× speedup over using high performance BLAS libraries for these operations. The resulting high performance LOBPCG solver achieves 1.4× to 1.8× speedup over the existing Lanczos solver on a series of CI computations on high-end multicore architectures (Intel Xeons). We also analyze the performance of our techniques on an Intel Xeon Phi Knights Corner (KNC) processor.« less

A High Performance Block Eigensolver for Nuclear Configuration Interaction Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aktulga, Hasan Metin; Afibuzzaman, Md.; Williams, Samuel

As on-node parallelism increases and the performance gap between the processor and the memory system widens, achieving high performance in large-scale scientific applications requires an architecture-aware design of algorithms and solvers. We focus on the eigenvalue problem arising in nuclear Configuration Interaction (CI) calculations, where a few extreme eigenpairs of a sparse symmetric matrix are needed. Here, we consider a block iterative eigensolver whose main computational kernels are the multiplication of a sparse matrix with multiple vectors (SpMM), and tall-skinny matrix operations. We then present techniques to significantly improve the SpMM and the transpose operation SpMM T by using themore » compressed sparse blocks (CSB) format. We achieve 3-4× speedup on the requisite operations over good implementations with the commonly used compressed sparse row (CSR) format. We develop a performance model that allows us to correctly estimate the performance of our SpMM kernel implementations, and we identify cache bandwidth as a potential performance bottleneck beyond DRAM. We also analyze and optimize the performance of LOBPCG kernels (inner product and linear combinations on multiple vectors) and show up to 15× speedup over using high performance BLAS libraries for these operations. The resulting high performance LOBPCG solver achieves 1.4× to 1.8× speedup over the existing Lanczos solver on a series of CI computations on high-end multicore architectures (Intel Xeons). We also analyze the performance of our techniques on an Intel Xeon Phi Knights Corner (KNC) processor.« less

Implementing a vector surveillance-response system for chagas disease control: a 4-year field trial in Nicaragua.

PubMed

Yoshioka, Kota; Tercero, Doribel; Pérez, Byron; Nakamura, Jiro; Pérez, Lenin

2017-03-06

Chagas disease is one of the neglected tropical diseases (NTDs). International goals for its control involve elimination of vector-borne transmission. Central American countries face challenges in establishing sustainable vector control programmes, since the main vector, Triatoma dimidiata, cannot be eliminated. In 2012, the Ministry of Health in Nicaragua started a field test of a vector surveillance-response system to control domestic vector infestation. This paper reports the main findings from this pilot study. This study was carried out from 2012 to 2015 in the Municipality of Totogalpa. The Japan International Cooperation Agency provided technical cooperation in designing and monitoring the surveillance-response system until 2014. This system involved 1) vector reports by householders to health facilities, 2) data analysis and planning of responses at the municipal health centre and 3) house visits or insecticide spraying by health personnel as a response. We registered all vector reports and responses in a digital database. The collected data were used to describe and analyse the system performance in terms of amount of vector reports as well as rates and timeliness of responses. During the study period, T. dimidiata was reported 396 times. Spatiotemporal analysis identified some high-risk clusters. All houses reported to be infested were visited by health personnel in 2013 and this response rate dropped to 39% in 2015. Rates of insecticide spraying rose above 80% in 2013 but no spraying was carried out in the following 2 years. The timeliness of house visits improved significantly after the responsibility was transferred from a vector control technician to primary health care staff. We argue that the proposed vector surveillance-response system is workable within the resource-constrained health system in Nicaragua. Integration to the primary health care services was a key to improve the system performance. Continual efforts are necessary to keep adapting the surveillance-response system to the dynamic health systems. We also discuss that the goal of eliminating vector-borne transmission remains unachievable. This paper provides lessons not only for Chagas disease control in Central America, but also for control efforts for other NTDs that need a sustainable surveillance-response system to support elimination.

Static vs. dynamic decoding algorithms in a non-invasive body-machine interface

PubMed Central

Seáñez-González, Ismael; Pierella, Camilla; Farshchiansadegh, Ali; Thorp, Elias B.; Abdollahi, Farnaz; Pedersen, Jessica; Mussa-Ivaldi, Ferdinando A.

2017-01-01

In this study, we consider a non-invasive body-machine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a high-dimensional body-signal vector into a lower dimensional control vector on 6 subjects with high-level SCI and 8 controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter. SCI and control participants performed straighter and smoother cursor movements with the Kalman algorithm during center-out reaching, but their movements were faster and more precise when using PCA. All participants were able to use the BMI’s continuous, two-dimensional control to type on a virtual keyboard and play pong, and performance with both algorithms was comparable. However, seven of eight control participants preferred PCA as their method of virtual wheelchair control. The unsupervised PCA algorithm was easier to train and seemed sufficient to achieve a higher degree of learnability and perceived ease of use. PMID:28092564

System for Automated Calibration of Vector Modulators

NASA Technical Reports Server (NTRS)

Lux, James; Boas, Amy; Li, Samuel

2009-01-01

Vector modulators are used to impose baseband modulation on RF signals, but non-ideal behavior limits the overall performance. The non-ideal behavior of the vector modulator is compensated using data collected with the use of an automated test system driven by a LabVIEW program that systematically applies thousands of control-signal values to the device under test and collects RF measurement data. The technology innovation automates several steps in the process. First, an automated test system, using computer controlled digital-to-analog converters (DACs) and a computer-controlled vector network analyzer (VNA) systematically can apply different I and Q signals (which represent the complex number by which the RF signal is multiplied) to the vector modulator under test (VMUT), while measuring the RF performance specifically, gain and phase. The automated test system uses the LabVIEW software to control the test equipment, collect the data, and write it to a file. The input to the Lab - VIEW program is either user-input for systematic variation, or is provided in a file containing specific test values that should be fed to the VMUT. The output file contains both the control signals and the measured data. The second step is to post-process the file to determine the correction functions as needed. The result of the entire process is a tabular representation, which allows translation of a desired I/Q value to the required analog control signals to produce a particular RF behavior. In some applications, corrected performance is needed only for a limited range. If the vector modulator is being used as a phase shifter, there is only a need to correct I and Q values that represent points on a circle, not the entire plane. This innovation has been used to calibrate 2-GHz MMIC (monolithic microwave integrated circuit) vector modulators in the High EIRP Cluster Array project (EIRP is high effective isotropic radiated power). These calibrations were then used to create correction tables to allow the commanding of the phase shift in each of four channels used as a phased array for beam steering of a Ka-band (32-GHz) signal. The system also was the basis of a breadboard electronic beam steering system. In this breadboard, the goal was not to make systematic measurements of the properties of a vector modulator, but to drive the breadboard with a series of test patterns varying in phase and amplitude. This is essentially the same calibration process, but with the difference that the data collection process is oriented toward collecting breadboard performance, rather than the measurement of output from a network analyzer.

Initial Flight Test Evaluation of the F-15 ACTIVE Axisymmetric Vectoring Nozzle Performance

NASA Technical Reports Server (NTRS)

Orme, John S.; Hathaway, Ross; Ferguson, Michael D.

1998-01-01

A full envelope database of a thrust-vectoring axisymmetric nozzle performance for the Pratt & Whitney Pitch/Yaw Balance Beam Nozzle (P/YBBN) is being developed using the F-15 Advanced Control Technology for Integrated Vehicles (ACTIVE) aircraft. At this time, flight research has been completed for steady-state pitch vector angles up to 20' at an altitude of 30,000 ft from low power settings to maximum afterburner power. The nozzle performance database includes vector forces, internal nozzle pressures, and temperatures all of which can be used for regression analysis modeling. The database was used to substantiate a set of nozzle performance data from wind tunnel testing and computational fluid dynamic analyses. Findings from initial flight research at Mach 0.9 and 1.2 are presented in this paper. The results show that vector efficiency is strongly influenced by power setting. A significant discrepancy in nozzle performance has been discovered between predicted and measured results during vectoring.

Distribution of AAV-TK following intracranial convection-enhanced delivery into rats.

PubMed

Cunningham, J; Oiwa, Y; Nagy, D; Podsakoff, G; Colosi, P; Bankiewicz, K S

2000-01-01

Adeno-associated virus (AAV)-based vectors are being tested in animal models as viable treatments for glioma and neurodegenerative disease and could potentially be employed to target a variety of central nervous system disorders. The relationship between dose of injected vector and its resulting distribution in brain tissue has not been previously reported nor has the most efficient method of delivery been determined. Here we report that convection-enhanced delivery (CED) of 2.5 x 10(8), 2.5 x 10(9), or 2.5 x 10(10) particles of AAV-thymidine kinase (AAV-TK) into rat brain revealed a clear dose response. In the high-dose group, a volume of 300 mm3 of brain tissue was partially transduced. Results showed that infusion pump and subcutaneous osmotic pumps were both capable of delivering vector via CED and that total particle number was the most important determining factor in obtaining efficient expression. Results further showed differences in histopathology between the delivery groups. While administration of vector using infusion pump had relatively benign effects, the use of osmotic pumps resulted in notable toxicity to the surrounding brain tissue. To determine tissue distribution of vector following intracranial delivery, PCR analysis was performed on tissues from rats that received high doses of AAV-TK. Three weeks following CED, vector could be detected in both hemispheres of the brain, spinal cord, spleen, and kidney.

A Parallel Framework with Block Matrices of a Discrete Fourier Transform for Vector-Valued Discrete-Time Signals.

PubMed

Soto-Quiros, Pablo

2015-01-01

This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT): the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.

Development of software for the MSFC solar vector magnetograph

NASA Technical Reports Server (NTRS)

Kineke, Jack

1996-01-01

The Marshall Space Flight Center Solar Vector Magnetograph is a special purpose telescope used to measure the vector magnetic field in active areas on the surface of the sun. This instrument measures the linear and circular polarization intensities (the Stokes vectors Q, U and V) produced by the Zeeman effect on a specific spectral line due to the solar magnetic field from which the longitudinal and transverse components of the magnetic field may be determined. Beginning in 1990 as a Summer Faculty Fellow in project JOVE and continuing under NASA Grant NAG8-1042, the author has been developing computer software to perform these computations, first using a DEC MicroVAX system equipped with a high speed array processor, and more recently using a DEC AXP/OSF system. This summer's work is a continuation of this development.

A hybrid LBG/lattice vector quantizer for high quality image coding

NASA Technical Reports Server (NTRS)

Ramamoorthy, V.; Sayood, K.; Arikan, E. (Editor)

1991-01-01

It is well known that a vector quantizer is an efficient coder offering a good trade-off between quantization distortion and bit rate. The performance of a vector quantizer asymptotically approaches the optimum bound with increasing dimensionality. A vector quantized image suffers from the following types of degradations: (1) edge regions in the coded image contain staircase effects, (2) quasi-constant or slowly varying regions suffer from contouring effects, and (3) textured regions lose details and suffer from granular noise. All three of these degradations are due to the finite size of the code book, the distortion measures used in the design, and due to the finite training procedure involved in the construction of the code book. In this paper, we present an adaptive technique which attempts to ameliorate the edge distortion and contouring effects.

The ecological foundations of transmission potential and vector-borne disease in urban landscapes.

PubMed

LaDeau, Shannon L; Allan, Brian F; Leisnham, Paul T; Levy, Michael Z

2015-07-01

Urban transmission of arthropod-vectored disease has increased in recent decades. Understanding and managing transmission potential in urban landscapes requires integration of sociological and ecological processes that regulate vector population dynamics, feeding behavior, and vector-pathogen interactions in these unique ecosystems. Vectorial capacity is a key metric for generating predictive understanding about transmission potential in systems with obligate vector transmission. This review evaluates how urban conditions, specifically habitat suitability and local temperature regimes, and the heterogeneity of urban landscapes can influence the biologically-relevant parameters that define vectorial capacity: vector density, survivorship, biting rate, extrinsic incubation period, and vector competence.Urban landscapes represent unique mosaics of habitat. Incidence of vector-borne disease in urban host populations is rarely, if ever, evenly distributed across an urban area. The persistence and quality of vector habitat can vary significantly across socio-economic boundaries to influence vector species composition and abundance, often generating socio-economically distinct gradients of transmission potential across neighborhoods.Urban regions often experience unique temperature regimes, broadly termed urban heat islands (UHI). Arthropod vectors are ectothermic organisms and their growth, survival, and behavior are highly sensitive to environmental temperatures. Vector response to UHI conditions is dependent on regional temperature profiles relative to the vector's thermal performance range. In temperate climates UHI can facilitate increased vector development rates while having countervailing influence on survival and feeding behavior. Understanding how urban heat island (UHI) conditions alter thermal and moisture constraints across the vector life cycle to influence transmission processes is an important direction for both empirical and modeling research.There remain persistent gaps in understanding of vital rates and drivers in mosquito-vectored disease systems, and vast holes in understanding for other arthropod vectored diseases. Empirical studies are needed to better understand the physiological constraints and socio-ecological processes that generate heterogeneity in critical transmission parameters, including vector survival and fitness. Likewise, laboratory experiments and transmission models must evaluate vector response to realistic field conditions, including variability in sociological and environmental conditions.

An Efficient Wait-Free Vector

DOE PAGES

Feldman, Steven; Valera-Leon, Carlos; Dechev, Damian

2016-03-01

The vector is a fundamental data structure, which provides constant-time access to a dynamically-resizable range of elements. Currently, there exist no wait-free vectors. The only non-blocking version supports only a subset of the sequential vector API and exhibits significant synchronization overhead caused by supporting opposing operations. Since many applications operate in phases of execution, wherein each phase only a subset of operations are used, this overhead is unnecessary for the majority of the application. To address the limitations of the non-blocking version, we present a new design that is wait-free, supports more of the operations provided by the sequential vector,more » and provides alternative implementations of key operations. These alternatives allow the developer to balance the performance and functionality of the vector as requirements change throughout execution. Compared to the known non-blocking version and the concurrent vector found in Intel’s TBB library, our design outperforms or provides comparable performance in the majority of tested scenarios. Over all tested scenarios, the presented design performs an average of 4.97 times more operations per second than the non-blocking vector and 1.54 more than the TBB vector. In a scenario designed to simulate the filling of a vector, performance improvement increases to 13.38 and 1.16 times. This work presents the first ABA-free non-blocking vector. Finally, unlike the other non-blocking approach, all operations are wait-free and bounds-checked and elements are stored contiguously in memory.« less

All-in-One CRISPR-Cas9/FokI-dCas9 Vector-Mediated Multiplex Genome Engineering in Cultured Cells.

PubMed

Sakuma, Tetsushi; Sakamoto, Takuya; Yamamoto, Takashi

2017-01-01

CRISPR-Cas9 enables highly convenient multiplex genome engineering in cultured cells, because it utilizes generic Cas9 nuclease and an easily customizable single-guide RNA (sgRNA) for site-specific DNA double-strand break induction. We previously established a multiplex CRISPR-Cas9 assembly system for constructing an all-in-one vector simultaneously expressing multiple sgRNAs and Cas9 nuclease or other Cas9 variants including FokI-dCas9, which supersedes the wild-type Cas9 with regard to high specificity. In this chapter, we describe a streamlined protocol to design and construct multiplex CRISPR-Cas9 or FokI-dCas9 vectors, to introduce them into cultured cells by lipofection or electroporation, to enrich the genomically edited cells with a transient puromycin selection, to validate the mutation efficiency by Surveyor nuclease assay, and to perform off-target analyses. We show that our protocol enables highly efficient multiplex genome engineering even in hard-to-transfect HepG2 cells.

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

A Discriminant Distance Based Composite Vector Selection Method for Odor Classification

PubMed Central

Choi, Sang-Il; Jeong, Gu-Min

2014-01-01

We present a composite vector selection method for an effective electronic nose system that performs well even in noisy environments. Each composite vector generated from a electronic nose data sample is evaluated by computing the discriminant distance. By quantitatively measuring the amount of discriminative information in each composite vector, composite vectors containing informative variables can be distinguished and the final composite features for odor classification are extracted using the selected composite vectors. Using the only informative composite vectors can be also helpful to extract better composite features instead of using all the generated composite vectors. Experimental results with different volatile organic compound data show that the proposed system has good classification performance even in a noisy environment compared to other methods. PMID:24747735

Support vector machine incremental learning triggered by wrongly predicted samples

NASA Astrophysics Data System (ADS)

Tang, Ting-long; Guan, Qiu; Wu, Yi-rong

2018-05-01

According to the classic Karush-Kuhn-Tucker (KKT) theorem, at every step of incremental support vector machine (SVM) learning, the newly adding sample which violates the KKT conditions will be a new support vector (SV) and migrate the old samples between SV set and non-support vector (NSV) set, and at the same time the learning model should be updated based on the SVs. However, it is not exactly clear at this moment that which of the old samples would change between SVs and NSVs. Additionally, the learning model will be unnecessarily updated, which will not greatly increase its accuracy but decrease the training speed. Therefore, how to choose the new SVs from old sets during the incremental stages and when to process incremental steps will greatly influence the accuracy and efficiency of incremental SVM learning. In this work, a new algorithm is proposed to select candidate SVs and use the wrongly predicted sample to trigger the incremental processing simultaneously. Experimental results show that the proposed algorithm can achieve good performance with high efficiency, high speed and good accuracy.

A diagram for evaluating multiple aspects of model performance in simulating vector fields

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Hou, Zhaolu; Han, Ying; Guo, Weidong

2016-12-01

Vector quantities, e.g., vector winds, play an extremely important role in climate systems. The energy and water exchanges between different regions are strongly dominated by wind, which in turn shapes the regional climate. Thus, how well climate models can simulate vector fields directly affects model performance in reproducing the nature of a regional climate. This paper devises a new diagram, termed the vector field evaluation (VFE) diagram, which is a generalized Taylor diagram and able to provide a concise evaluation of model performance in simulating vector fields. The diagram can measure how well two vector fields match each other in terms of three statistical variables, i.e., the vector similarity coefficient, root mean square length (RMSL), and root mean square vector difference (RMSVD). Similar to the Taylor diagram, the VFE diagram is especially useful for evaluating climate models. The pattern similarity of two vector fields is measured by a vector similarity coefficient (VSC) that is defined by the arithmetic mean of the inner product of normalized vector pairs. Examples are provided, showing that VSC can identify how close one vector field resembles another. Note that VSC can only describe the pattern similarity, and it does not reflect the systematic difference in the mean vector length between two vector fields. To measure the vector length, RMSL is included in the diagram. The third variable, RMSVD, is used to identify the magnitude of the overall difference between two vector fields. Examples show that the VFE diagram can clearly illustrate the extent to which the overall RMSVD is attributed to the systematic difference in RMSL and how much is due to the poor pattern similarity.

Parallel-Vector Algorithm For Rapid Structural Anlysis

NASA Technical Reports Server (NTRS)

Agarwal, Tarun R.; Nguyen, Duc T.; Storaasli, Olaf O.

1993-01-01

New algorithm developed to overcome deficiency of skyline storage scheme by use of variable-band storage scheme. Exploits both parallel and vector capabilities of modern high-performance computers. Gives engineers and designers opportunity to include more design variables and constraints during optimization of structures. Enables use of more refined finite-element meshes to obtain improved understanding of complex behaviors of aerospace structures leading to better, safer designs. Not only attractive for current supercomputers but also for next generation of shared-memory supercomputers.

Preliminary Investigation on Battery Sizing Investigation for Thrust Vector Control on Ares I and Ares V Launch Vehicles

NASA Technical Reports Server (NTRS)

Miller, Thomas B.

2011-01-01

An investigation into the merits of battery powered Electro Hydrostatic Actuation (EHA) for Thrust Vector Control (TVC) of the Ares I and Ares V launch vehicles is described. A top level trade study was conducted to ascertain the technical merits of lithium-ion (Li-ion) and thermal battery performance to determine the preferred choice of an energy storage system chemistry that provides high power discharge capability for a relatively short duration.

Remote sensing and GIS integration: Towards intelligent imagery within a spatial data infrastructure

NASA Astrophysics Data System (ADS)

Abdelrahim, Mohamed Mahmoud Hosny

2001-11-01

In this research, an "Intelligent Imagery System Prototype" (IISP) was developed. IISP is an integration tool that facilitates the environment for active, direct, and on-the-fly usage of high resolution imagery, internally linked to hidden GIS vector layers, to query the real world phenomena and, consequently, to perform exploratory types of spatial analysis based on a clear/undisturbed image scene. The IISP was designed and implemented using the software components approach to verify the hypothesis that a fully rectified, partially rectified, or even unrectified digital image can be internally linked to a variety of different hidden vector databases/layers covering the end user area of interest, and consequently may be reliably used directly as a base for "on-the-fly" querying of real-world phenomena and for performing exploratory types of spatial analysis. Within IISP, differentially rectified, partially rectified (namely, IKONOS GEOCARTERRA(TM)), and unrectified imagery (namely, scanned aerial photographs and captured video frames) were investigated. The system was designed to handle four types of spatial functions, namely, pointing query, polygon/line-based image query, database query, and buffering. The system was developed using ESRI MapObjects 2.0a as the core spatial component within Visual Basic 6.0. When used to perform the pre-defined spatial queries using different combinations of image and vector data, the IISP provided the same results as those obtained by querying pre-processed vector layers even when the image used was not orthorectified and the vector layers had different parameters. In addition, the real-time pixel location orthorectification technique developed and presented within the IKONOS GEOCARTERRA(TM) case provided a horizontal accuracy (RMSE) of +/- 2.75 metres. This accuracy is very close to the accuracy level obtained when purchasing the orthorectified IKONOS PRECISION products (RMSE of +/- 1.9 metre). The latter cost approximately four times as much as the IKONOS GEOCARTERRA(TM) products. The developed IISP is a step closer towards the direct and active involvement of high-resolution remote sensing imagery in querying the real world and performing exploratory types of spatial analysis. (Abstract shortened by UMI.)

Exploring the capabilities of support vector machines in detecting silent data corruptions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Subasi, Omer; Di, Sheng; Bautista-Gomez, Leonardo

As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs), or silent errors, are one of the major sources that corrupt the execution results of HPC applications without being detected. Here in this paper, we explore a set of novel SDC detectors – by leveraging epsilon-insensitive support vector machine regression – to detect SDCs that occur in HPC applications. The key contributions are threefold. (1) Our exploration takes temporal, spatial, and spatiotemporal features into account and analyzes different detectors based onmore » different features. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show that support-vector-machine-based detectors can achieve detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% false positive rate for most cases. Our detectors incur low performance overhead, 5% on average, for all benchmarks studied in this work.« less

Exploring the capabilities of support vector machines in detecting silent data corruptions

DOE PAGES

Subasi, Omer; Di, Sheng; Bautista-Gomez, Leonardo; ...

2018-02-01

As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs), or silent errors, are one of the major sources that corrupt the execution results of HPC applications without being detected. Here in this paper, we explore a set of novel SDC detectors – by leveraging epsilon-insensitive support vector machine regression – to detect SDCs that occur in HPC applications. The key contributions are threefold. (1) Our exploration takes temporal, spatial, and spatiotemporal features into account and analyzes different detectors based onmore » different features. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show that support-vector-machine-based detectors can achieve detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% false positive rate for most cases. Our detectors incur low performance overhead, 5% on average, for all benchmarks studied in this work.« less

Search for heavy resonances that decay into a vector boson and a Higgs boson in hadronic final states at $$\\sqrt{s} = 13$$ TeV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.

A search for heavy resonances with masses above 1 TeV, decaying to final states containing a vector boson and a Higgs boson, is presented. The search considers hadronic decays of the vector boson, and Higgs boson decays to b quarks. The decay products are highly boosted, and each collimated pair of quarks is reconstructed as a single, massive jet. The analysis is performed using a data sample collected in 2016 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 inverse femtobarns. The data are consistentmore » with the background expectation and are used to place limits on the parameters of a theoretical model with a heavy vector triplet. In the benchmark scenario with mass-degenerate W' and Z' bosons decaying predominantly to pairs of standard model bosons, for the first time heavy resonances for masses as high as 3.3 TeV are excluded at 95% confidence level, setting the most stringent limit to date on such states decaying into a vector boson and a Higgs boson.« less

Supercomputer implementation of finite element algorithms for high speed compressible flows

NASA Technical Reports Server (NTRS)

Thornton, E. A.; Ramakrishnan, R.

1986-01-01

Prediction of compressible flow phenomena using the finite element method is of recent origin and considerable interest. Two shock capturing finite element formulations for high speed compressible flows are described. A Taylor-Galerkin formulation uses a Taylor series expansion in time coupled with a Galerkin weighted residual statement. The Taylor-Galerkin algorithms use explicit artificial dissipation, and the performance of three dissipation models are compared. A Petrov-Galerkin algorithm has as its basis the concepts of streamline upwinding. Vectorization strategies are developed to implement the finite element formulations on the NASA Langley VPS-32. The vectorization scheme results in finite element programs that use vectors of length of the order of the number of nodes or elements. The use of the vectorization procedure speeds up processing rates by over two orders of magnitude. The Taylor-Galerkin and Petrov-Galerkin algorithms are evaluated for 2D inviscid flows on criteria such as solution accuracy, shock resolution, computational speed and storage requirements. The convergence rates for both algorithms are enhanced by local time-stepping schemes. Extension of the vectorization procedure for predicting 2D viscous and 3D inviscid flows are demonstrated. Conclusions are drawn regarding the applicability of the finite element procedures for realistic problems that require hundreds of thousands of nodes.

Increasing the computational efficient of digital cross correlation by a vectorization method

NASA Astrophysics Data System (ADS)

Chang, Ching-Yuan; Ma, Chien-Ching

2017-08-01

This study presents a vectorization method for use in MATLAB programming aimed at increasing the computational efficiency of digital cross correlation in sound and images, resulting in a speedup of 6.387 and 36.044 times compared with performance values obtained from looped expression. This work bridges the gap between matrix operations and loop iteration, preserving flexibility and efficiency in program testing. This paper uses numerical simulation to verify the speedup of the proposed vectorization method as well as experiments to measure the quantitative transient displacement response subjected to dynamic impact loading. The experiment involved the use of a high speed camera as well as a fiber optic system to measure the transient displacement in a cantilever beam under impact from a steel ball. Experimental measurement data obtained from the two methods are in excellent agreement in both the time and frequency domain, with discrepancies of only 0.68%. Numerical and experiment results demonstrate the efficacy of the proposed vectorization method with regard to computational speed in signal processing and high precision in the correlation algorithm. We also present the source code with which to build MATLAB-executable functions on Windows as well as Linux platforms, and provide a series of examples to demonstrate the application of the proposed vectorization method.

Search for heavy resonances that decay into a vector boson and a Higgs boson in hadronic final states at $$\\sqrt{s} = 13$$ TeV

DOE PAGES

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

2017-09-22

A search for heavy resonances with masses above 1 TeV, decaying to final states containing a vector boson and a Higgs boson, is presented. The search considers hadronic decays of the vector boson, and Higgs boson decays to b quarks. The decay products are highly boosted, and each collimated pair of quarks is reconstructed as a single, massive jet. The analysis is performed using a data sample collected in 2016 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 inverse femtobarns. The data are consistentmore » with the background expectation and are used to place limits on the parameters of a theoretical model with a heavy vector triplet. In the benchmark scenario with mass-degenerate W' and Z' bosons decaying predominantly to pairs of standard model bosons, for the first time heavy resonances for masses as high as 3.3 TeV are excluded at 95% confidence level, setting the most stringent limit to date on such states decaying into a vector boson and a Higgs boson.« less

A static investigation of several STOVL exhaust system concepts

NASA Technical Reports Server (NTRS)

Romine, B. M., Jr.; Meyer, B. E.; Re, R. J.

1989-01-01

A static cold flow scale model test was performed in order to determine the internal performance characteristics of various STOVL exhaust systems. All of the concepts considered included a vectorable cruise nozzle and a separate vectorable vertical thrust ventral nozzle mounted on the tailpipe. The two ventral nozzle configurations tested featured vectorable constant thickness cascade vanes for area control and improved performance during transition and vertical lift flight. The best transition performance was achieved using a butterfly door type ventral nozzle and a pitch vectoring 2DCD or axisymmetric cruise nozzle. The clamshell blocker type of ventral nozzle had reduced transition performance due to the choking of the tailpipe flow upstream of the cruise nozzle.

A comparison of linear approaches to filter out environmental effects in structural health monitoring

NASA Astrophysics Data System (ADS)

Deraemaeker, A.; Worden, K.

2018-05-01

This paper discusses the possibility of using the Mahalanobis squared-distance to perform robust novelty detection in the presence of important environmental variability in a multivariate feature vector. By performing an eigenvalue decomposition of the covariance matrix used to compute that distance, it is shown that the Mahalanobis squared-distance can be written as the sum of independent terms which result from a transformation from the feature vector space to a space of independent variables. In general, especially when the size of the features vector is large, there are dominant eigenvalues and eigenvectors associated with the covariance matrix, so that a set of principal components can be defined. Because the associated eigenvalues are high, their contribution to the Mahalanobis squared-distance is low, while the contribution of the other components is high due to the low value of the associated eigenvalues. This analysis shows that the Mahalanobis distance naturally filters out the variability in the training data. This property can be used to remove the effect of the environment in damage detection, in much the same way as two other established techniques, principal component analysis and factor analysis. The three techniques are compared here using real experimental data from a wooden bridge for which the feature vector consists in eigenfrequencies and modeshapes collected under changing environmental conditions, as well as damaged conditions simulated with an added mass. The results confirm the similarity between the three techniques and the ability to filter out environmental effects, while keeping a high sensitivity to structural changes. The results also show that even after filtering out the environmental effects, the normality assumption cannot be made for the residual feature vector. An alternative is demonstrated here based on extreme value statistics which results in a much better threshold which avoids false positives in the training data, while allowing detection of all damaged cases.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feldman, Steven; Valera-Leon, Carlos; Dechev, Damian

The vector is a fundamental data structure, which provides constant-time access to a dynamically-resizable range of elements. Currently, there exist no wait-free vectors. The only non-blocking version supports only a subset of the sequential vector API and exhibits significant synchronization overhead caused by supporting opposing operations. Since many applications operate in phases of execution, wherein each phase only a subset of operations are used, this overhead is unnecessary for the majority of the application. To address the limitations of the non-blocking version, we present a new design that is wait-free, supports more of the operations provided by the sequential vector,more » and provides alternative implementations of key operations. These alternatives allow the developer to balance the performance and functionality of the vector as requirements change throughout execution. Compared to the known non-blocking version and the concurrent vector found in Intel’s TBB library, our design outperforms or provides comparable performance in the majority of tested scenarios. Over all tested scenarios, the presented design performs an average of 4.97 times more operations per second than the non-blocking vector and 1.54 more than the TBB vector. In a scenario designed to simulate the filling of a vector, performance improvement increases to 13.38 and 1.16 times. This work presents the first ABA-free non-blocking vector. Finally, unlike the other non-blocking approach, all operations are wait-free and bounds-checked and elements are stored contiguously in memory.« less

Vector Quantization Algorithm Based on Associative Memories

NASA Astrophysics Data System (ADS)

Guzmán, Enrique; Pogrebnyak, Oleksiy; Yáñez, Cornelio; Manrique, Pablo

This paper presents a vector quantization algorithm for image compression based on extended associative memories. The proposed algorithm is divided in two stages. First, an associative network is generated applying the learning phase of the extended associative memories between a codebook generated by the LBG algorithm and a training set. This associative network is named EAM-codebook and represents a new codebook which is used in the next stage. The EAM-codebook establishes a relation between training set and the LBG codebook. Second, the vector quantization process is performed by means of the recalling stage of EAM using as associative memory the EAM-codebook. This process generates a set of the class indices to which each input vector belongs. With respect to the LBG algorithm, the main advantages offered by the proposed algorithm is high processing speed and low demand of resources (system memory); results of image compression and quality are presented.

Lysine acetylation sites prediction using an ensemble of support vector machine classifiers.

PubMed

Xu, Yan; Wang, Xiao-Bo; Ding, Jun; Wu, Ling-Yun; Deng, Nai-Yang

2010-05-07

Lysine acetylation is an essentially reversible and high regulated post-translational modification which regulates diverse protein properties. Experimental identification of acetylation sites is laborious and expensive. Hence, there is significant interest in the development of computational methods for reliable prediction of acetylation sites from amino acid sequences. In this paper we use an ensemble of support vector machine classifiers to perform this work. The experimentally determined acetylation lysine sites are extracted from Swiss-Prot database and scientific literatures. Experiment results show that an ensemble of support vector machine classifiers outperforms single support vector machine classifier and other computational methods such as PAIL and LysAcet on the problem of predicting acetylation lysine sites. The resulting method has been implemented in EnsemblePail, a web server for lysine acetylation sites prediction available at http://www.aporc.org/EnsemblePail/. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Reconstruction of the domain orientation distribution function of polycrystalline PZT ceramics using vector piezoresponse force microscopy.

PubMed

Kratzer, Markus; Lasnik, Michael; Röhrig, Sören; Teichert, Christian; Deluca, Marco

2018-01-11

Lead zirconate titanate (PZT) is one of the prominent materials used in polycrystalline piezoelectric devices. Since the ferroelectric domain orientation is the most important parameter affecting the electromechanical performance, analyzing the domain orientation distribution is of great importance for the development and understanding of improved piezoceramic devices. Here, vector piezoresponse force microscopy (vector-PFM) has been applied in order to reconstruct the ferroelectric domain orientation distribution function of polished sections of device-ready polycrystalline lead zirconate titanate (PZT) material. A measurement procedure and a computer program based on the software Mathematica have been developed to automatically evaluate the vector-PFM data for reconstructing the domain orientation function. The method is tested on differently in-plane and out-of-plane poled PZT samples, and the results reveal the expected domain patterns and allow determination of the polarization orientation distribution function at high accuracy.

Method and system for efficient video compression with low-complexity encoder

NASA Technical Reports Server (NTRS)

Chen, Jun (Inventor); He, Dake (Inventor); Sheinin, Vadim (Inventor); Jagmohan, Ashish (Inventor); Lu, Ligang (Inventor)

2012-01-01

Disclosed are a method and system for video compression, wherein the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a video decoder, wherein the method for encoding includes the steps of converting a source frame into a space-frequency representation; estimating conditional statistics of at least one vector of space-frequency coefficients; estimating encoding rates based on the said conditional statistics; and applying Slepian-Wolf codes with the said computed encoding rates. The preferred method for decoding includes the steps of; generating a side-information vector of frequency coefficients based on previously decoded source data, encoder statistics, and previous reconstructions of the source frequency vector; and performing Slepian-Wolf decoding of at least one source frequency vector based on the generated side-information, the Slepian-Wolf code bits and the encoder statistics.

Current status of genome editing in vector mosquitoes: A review.

PubMed

Reegan, Appadurai Daniel; Ceasar, Stanislaus Antony; Paulraj, Michael Gabriel; Ignacimuthu, Savarimuthu; Al-Dhabi, Naif Abdullah

2017-01-16

Mosquitoes pose a major threat to human health as they spread many deadly diseases like malaria, dengue, chikungunya, filariasis, Japanese encephalitis and Zika. Identification and use of novel molecular tools are essential to combat the spread of vector borne diseases. Genome editing tools have been used for the precise alterations of the gene of interest for producing the desirable trait in mosquitoes. Deletion of functional genes or insertion of toxic genes in vector mosquitoes will produce either knock-out or knock-in mutants that will check the spread of vector-borne diseases. Presently, three types of genome editing tools viz., zinc finger nuclease (ZFN), transcription activator-like effector nucleases (TALEN) and clustered regulatory interspaced short palindromic repeats (CRISPR) and CRISPR associated protein 9 (Cas9) are widely used for the editing of the genomes of diverse organisms. These tools are also applied in vector mosquitoes to control the spread of vector-borne diseases. A few studies have been carried out on genome editing to control the diseases spread by vector mosquitoes and more studies need to be performed with the utilization of more recently invented tools like CRISPR/Cas9 to combat the spread of deadly diseases by vector mosquitoes. The high specificity and flexibility of CRISPR/Cas9 system may offer possibilities for novel genome editing for the control of important diseases spread by vector mosquitoes. In this review, we present the current status of genome editing research on vector mosquitoes and also discuss the future applications of vector mosquito genome editing to control the spread of vectorborne diseases.

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy.

PubMed

Welikala, R A; Fraz, M M; Dehmeshki, J; Hoppe, A; Tah, V; Mann, S; Williamson, T H; Barman, S A

2015-07-01

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Joint Smoothed l₀-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar.

PubMed

Liu, Jing; Zhou, Weidong; Juwono, Filbert H

2017-05-08

Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l 0 -norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l 0 -norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l 1 -norm minimization based methods, such as l 1 -SVD (singular value decomposition), RV (real-valued) l 1 -SVD and RV l 1 -SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance.

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet

PubMed Central

Mariappan, Leo; Hu, Gang; He, Bin

2014-01-01

Purpose: Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. Methods: In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. Results: The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. Conclusions: The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction. PMID:24506649

Wavelet subband coding of computer simulation output using the A++ array class library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J.N.; Brislawn, C.M.; Quinlan, D.J.

1995-07-01

The goal of the project is to produce utility software for off-line compression of existing data and library code that can be called from a simulation program for on-line compression of data dumps as the simulation proceeds. Naturally, we would like the amount of CPU time required by the compression algorithm to be small in comparison to the requirements of typical simulation codes. We also want the algorithm to accomodate a wide variety of smooth, multidimensional data types. For these reasons, the subband vector quantization (VQ) approach employed in has been replaced by a scalar quantization (SQ) strategy using amore » bank of almost-uniform scalar subband quantizers in a scheme similar to that used in the FBI fingerprint image compression standard. This eliminates the considerable computational burdens of training VQ codebooks for each new type of data and performing nearest-vector searches to encode the data. The comparison of subband VQ and SQ algorithms in indicated that, in practice, there is relatively little additional gain from using vector as opposed to scalar quantization on DWT subbands, even when the source imagery is from a very homogeneous population, and our subjective experience with synthetic computer-generated data supports this stance. It appears that a careful study is needed of the tradeoffs involved in selecting scalar vs. vector subband quantization, but such an analysis is beyond the scope of this paper. Our present work is focused on the problem of generating wavelet transform/scalar quantization (WSQ) implementations that can be ported easily between different hardware environments. This is an extremely important consideration given the great profusion of different high-performance computing architectures available, the high cost associated with learning how to map algorithms effectively onto a new architecture, and the rapid rate of evolution in the world of high-performance computing.« less

Video data compression using artificial neural network differential vector quantization

NASA Technical Reports Server (NTRS)

Krishnamurthy, Ashok K.; Bibyk, Steven B.; Ahalt, Stanley C.

1991-01-01

An artificial neural network vector quantizer is developed for use in data compression applications such as Digital Video. Differential Vector Quantization is used to preserve edge features, and a new adaptive algorithm, known as Frequency-Sensitive Competitive Learning, is used to develop the vector quantizer codebook. To develop real time performance, a custom Very Large Scale Integration Application Specific Integrated Circuit (VLSI ASIC) is being developed to realize the associative memory functions needed in the vector quantization algorithm. By using vector quantization, the need for Huffman coding can be eliminated, resulting in superior performance against channel bit errors than methods that use variable length codes.

Internal performance of two nozzles utilizing gimbal concepts for thrust vectoring

NASA Technical Reports Server (NTRS)

Berrier, Bobby L.; Taylor, John G.

1990-01-01

The internal performance of an axisymmetric convergent-divergent nozzle and a nonaxisymmetric convergent-divergent nozzle, both of which utilized a gimbal type mechanism for thrust vectoring was evaluated in the Static Test Facility of the Langley 16-Foot Transonic Tunnel. The nonaxisymmetric nozzle used the gimbal concept for yaw thrust vectoring only; pitch thrust vectoring was accomplished by simultaneous deflection of the upper and lower divergent flaps. The model geometric parameters investigated were pitch vector angle for the axisymmetric nozzle and pitch vector angle, yaw vector angle, nozzle throat aspect ratio, and nozzle expansion ratio for the nonaxisymmetric nozzle. All tests were conducted with no external flow, and nozzle pressure ratio was varied from 2.0 to approximately 12.0.

Computational Study of an Axisymmetric Dual Throat Fluidic Thrust Vectoring Nozzle for a Supersonic Aircraft Application

NASA Technical Reports Server (NTRS)

Deere, Karen A.; Flamm, Jeffrey D.; Berrier, Bobby L.; Johnson, Stuart K.

2007-01-01

A computational investigation of an axisymmetric Dual Throat Nozzle concept has been conducted. This fluidic thrust-vectoring nozzle was designed with a recessed cavity to enhance the throat shifting technique for improved thrust vectoring. The structured-grid, unsteady Reynolds- Averaged Navier-Stokes flow solver PAB3D was used to guide the nozzle design and analyze performance. Nozzle design variables included extent of circumferential injection, cavity divergence angle, cavity length, and cavity convergence angle. Internal nozzle performance (wind-off conditions) and thrust vector angles were computed for several configurations over a range of nozzle pressure ratios from 1.89 to 10, with the fluidic injection flow rate equal to zero and up to 4 percent of the primary flow rate. The effect of a variable expansion ratio on nozzle performance over a range of freestream Mach numbers up to 2 was investigated. Results indicated that a 60 circumferential injection was a good compromise between large thrust vector angles and efficient internal nozzle performance. A cavity divergence angle greater than 10 was detrimental to thrust vector angle. Shortening the cavity length improved internal nozzle performance with a small penalty to thrust vector angle. Contrary to expectations, a variable expansion ratio did not improve thrust efficiency at the flight conditions investigated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Zheming; Yoshii, Kazutomo; Finkel, Hal

Open Computing Language (OpenCL) is a high-level language that enables software programmers to explore Field Programmable Gate Arrays (FPGAs) for application acceleration. The Intel FPGA software development kit (SDK) for OpenCL allows a user to specify applications at a high level and explore the performance of low-level hardware acceleration. In this report, we present the FPGA performance and power consumption results of the single-precision floating-point vector add OpenCL kernel using the Intel FPGA SDK for OpenCL on the Nallatech 385A FPGA board. The board features an Arria 10 FPGA. We evaluate the FPGA implementations using the compute unit duplication andmore » kernel vectorization optimization techniques. On the Nallatech 385A FPGA board, the maximum compute kernel bandwidth we achieve is 25.8 GB/s, approximately 76% of the peak memory bandwidth. The power consumption of the FPGA device when running the kernels ranges from 29W to 42W.« less

Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches.

PubMed

Franke, Jonas; Gebreslasie, Michael; Bauwens, Ides; Deleu, Julie; Siegert, Florian

2015-06-03

Malaria affects about half of the world's population, with the vast majority of cases occuring in Africa. National malaria control programmes aim to reduce the burden of malaria and its negative, socioeconomic effects by using various control strategies (e.g. vector control, environmental management and case tracking). Vector control is the most effective transmission prevention strategy, while environmental factors are the key parameters affecting transmission. Geographic information systems (GIS), earth observation (EO) and spatial modelling are increasingly being recognised as valuable tools for effective management and malaria vector control. Issues previously inhibiting the use of EO in epidemiology and malaria control such as poor satellite sensor performance, high costs and long turnaround times, have since been resolved through modern technology. The core goal of this study was to develop and implement the capabilities of EO data for national malaria control programmes in South Africa, Swaziland and Mozambique. High- and very high resolution (HR and VHR) land cover and wetland maps were generated for the identification of potential vector habitats and human activities, as well as geoinformation on distance to wetlands for malaria risk modelling, population density maps, habitat foci maps and VHR household maps. These products were further used for modelling malaria incidence and the analysis of environmental factors that favour vector breeding. Geoproducts were also transferred to the staff of national malaria control programmes in seven African countries to demonstrate how EO data and GIS can support vector control strategy planning and monitoring. The transferred EO products support better epidemiological understanding of environmental factors related to malaria transmission, and allow for spatio-temporal targeting of malaria control interventions, thereby improving the cost-effectiveness of interventions.

PCR-based detection of gene transfer vectors: application to gene doping surveillance.

PubMed

Perez, Irene C; Le Guiner, Caroline; Ni, Weiyi; Lyles, Jennifer; Moullier, Philippe; Snyder, Richard O

2013-12-01

Athletes who illicitly use drugs to enhance their athletic performance are at risk of being banned from sports competitions. Consequently, some athletes may seek new doping methods that they expect to be capable of circumventing detection. With advances in gene transfer vector design and therapeutic gene transfer, and demonstrations of safety and therapeutic benefit in humans, there is an increased probability of the pursuit of gene doping by athletes. In anticipation of the potential for gene doping, assays have been established to directly detect complementary DNA of genes that are top candidates for use in doping, as well as vector control elements. The development of molecular assays that are capable of exposing gene doping in sports can serve as a deterrent and may also identify athletes who have illicitly used gene transfer for performance enhancement. PCR-based methods to detect foreign DNA with high reliability, sensitivity, and specificity include TaqMan real-time PCR, nested PCR, and internal threshold control PCR.

A Coarse Alignment Method Based on Digital Filters and Reconstructed Observation Vectors

PubMed Central

Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Wang, Zhicheng

2017-01-01

In this paper, a coarse alignment method based on apparent gravitational motion is proposed. Due to the interference of the complex situations, the true observation vectors, which are calculated by the apparent gravity, are contaminated. The sources of the interference are analyzed in detail, and then a low-pass digital filter is designed in this paper for eliminating the high-frequency noise of the measurement observation vectors. To extract the effective observation vectors from the inertial sensors’ outputs, a parameter recognition and vector reconstruction method are designed, where an adaptive Kalman filter is employed to estimate the unknown parameters. Furthermore, a robust filter, which is based on Huber’s M-estimation theory, is developed for addressing the outliers of the measurement observation vectors due to the maneuver of the vehicle. A comprehensive experiment, which contains a simulation test and physical test, is designed to verify the performance of the proposed method, and the results show that the proposed method is equivalent to the popular apparent velocity method in swaying mode, but it is superior to the current methods while in moving mode when the strapdown inertial navigation system (SINS) is under entirely self-contained conditions. PMID:28353682

Experimental Study of an Axisymmetric Dual Throat Fluidic Thrust Vectoring Nozzle for Supersonic Aircraft Application

NASA Technical Reports Server (NTRS)

Flamm, Jeffrey D.; Deere, Karen A.; Mason, Mary L.; Berrier, Bobby L.; Johnson, Stuart K.

2007-01-01

An axisymmetric version of the Dual Throat Nozzle concept with a variable expansion ratio has been studied to determine the impacts on thrust vectoring and nozzle performance. The nozzle design, applicable to a supersonic aircraft, was guided using the unsteady Reynolds-averaged Navier-Stokes computational fluid dynamics code, PAB3D. The axisymmetric Dual Throat Nozzle concept was tested statically in the Jet Exit Test Facility at the NASA Langley Research Center. The nozzle geometric design variables included circumferential span of injection, cavity length, cavity convergence angle, and nozzle expansion ratio for conditions corresponding to take-off and landing, mid climb and cruise. Internal nozzle performance and thrust vectoring performance was determined for nozzle pressure ratios up to 10 with secondary injection rates up to 10 percent of the primary flow rate. The 60 degree span of injection generally performed better than the 90 degree span of injection using an equivalent injection area and number of holes, in agreement with computational results. For injection rates less than 7 percent, thrust vector angle for the 60 degree span of injection was 1.5 to 2 degrees higher than the 90 degree span of injection. Decreasing cavity length improved thrust ratio and discharge coefficient, but decreased thrust vector angle and thrust vectoring efficiency. Increasing cavity convergence angle from 20 to 30 degrees increased thrust vector angle by 1 degree over the range of injection rates tested, but adversely affected system thrust ratio and discharge coefficient. The dual throat nozzle concept generated the best thrust vectoring performance with an expansion ratio of 1.0 (a cavity in between two equal minimum areas). The variable expansion ratio geometry did not provide the expected improvements in discharge coefficient and system thrust ratio throughout the flight envelope of typical a supersonic aircraft. At mid-climb and cruise conditions, the variable geometry design compromised thrust vector angle achieved, but some thrust vector control would be available, potentially for aircraft trim. The fixed area, expansion ratio of 1.0, Dual Throat Nozzle provided the best overall compromise for thrust vectoring and nozzle internal performance over the range of NPR tested compared to the variable geometry Dual Throat Nozzle.

Evaluation of Four Advanced Nozzle Concepts for Short Takeoff and Landing Performance

NASA Technical Reports Server (NTRS)

Quinto, P. Frank; Kemmerly, Guy T.; Paulson, John W., Jr.

1993-01-01

Four advanced nozzle concepts were tested on a canard-wing fighter in the Langley 14- by 22-Foot Subsonic Tunnel. The four vectoring-nozzle concepts were as follows: (1) an axisymmetric nozzle (AXI); (2) an asymmetric, load balanced exhaust nozzle (ALBEN); (3) a low aspect ratio, single expansion ramp nozzle (LASERN); and (4) a high aspect ratio, single expansion ramp nozzle (HASERN). The investigation was conducted to determine the most suitable nozzle concept for short takeoff and landing (STOL) performance. The criterion for the best STOL performance was a takeoff ground roll of less than 1000 ft. At approach, the criteria were high lift and sufficient drag to maintain a glide slope of -3 to -6 deg with enough pitching-moment control from the canards. The test was performed at a dynamic pressure of 45 lb/sq ft and an angle-of-attack range of 0 to 20 deg. The nozzle pressure ratio was varied from 1.0 to 4.3 at both dry power and after burning nozzle configurations with nozzle vectoring to 60 deg. In addition, the model was tested in and out of ground effects. The ALBEN concept was the best of the four nozzle concepts tested for STOL performance.

A static investigation of yaw vectoring concepts on two-dimensional convergent-divergent nozzles

NASA Technical Reports Server (NTRS)

Berrier, B. L.; Mason, M. L.

1983-01-01

The flow-turning capability and nozzle internal performance of yaw-vectoring nozzle geometries were tested in the NASA Langley 16-ft Transonic wind tunnel. The concept was investigated as a means of enhancing fighter jet performance. Five two-dimensional convergent-divergent nozzles were equipped for yaw-vectoring and examined. The configurations included a translating left sidewall, left and right sidewall flaps downstream of the nozzle throat, left sidewall flaps or port located upstream of the nozzle throat, and a powered rudder. Trials were also run with 20 deg of pitch thrust vectoring added. The feasibility of providing yaw-thrust vectoring was demonstrated, with the largest yaw vector angles being obtained with sidewall flaps downstream of the nozzle primary throat. It was concluded that yaw vector designs that scoop or capture internal nozzle flow provide the largest yaw-vector capability, but decrease the thrust the most.

High-speed optical three-axis vector magnetometry based on nonlinear Hanle effect in rubidium vapor

NASA Astrophysics Data System (ADS)

Azizbekyan, Hrayr; Shmavonyan, Svetlana; Khanbekyan, Aleksandr; Movsisyan, Marina; Papoyan, Aram

2017-07-01

The magnetic-field-compensation optical vector magnetometer based on the nonlinear Hanle effect in alkali metal vapor allowing two-axis measurement operation has been further elaborated for three-axis performance, along with significant reduction of measurement time. The upgrade was achieved by implementing a two-beam resonant excitation configuration and a fast maximum searching algorithm. Results of the proof-of-concept experiments, demonstrating 1 μT B-field resolution, are presented. The applied interest and capability of the proposed technique is analyzed.

Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

The transition from linear to highly branched poly(β-amino ester)s: Branching matters for gene delivery

PubMed Central

Zhou, Dezhong; Cutlar, Lara; Gao, Yongsheng; Wang, Wei; O’Keeffe-Ahern, Jonathan; McMahon, Sean; Duarte, Blanca; Larcher, Fernando; Rodriguez, Brian J.; Greiser, Udo; Wang, Wenxin

2016-01-01

Nonviral gene therapy holds great promise but has not delivered treatments for clinical application to date. Lack of safe and efficient gene delivery vectors is the major hurdle. Among nonviral gene delivery vectors, poly(β-amino ester)s are one of the most versatile candidates because of their wide monomer availability, high polymer flexibility, and superior gene transfection performance both in vitro and in vivo. However, to date, all research has been focused on vectors with a linear structure. A well-accepted view is that dendritic or branched polymers have greater potential as gene delivery vectors because of their three-dimensional structure and multiple terminal groups. Nevertheless, to date, the synthesis of dendritic or branched polymers has been proven to be a well-known challenge. We report the design and synthesis of highly branched poly(β-amino ester)s (HPAEs) via a one-pot “A2 + B3 + C2”–type Michael addition approach and evaluate their potential as gene delivery vectors. We find that the branched structure can significantly enhance the transfection efficiency of poly(β-amino ester)s: Up to an 8521-fold enhancement in transfection efficiency was observed across 12 cell types ranging from cell lines, primary cells, to stem cells, over their corresponding linear poly(β-amino ester)s (LPAEs) and the commercial transfection reagents polyethyleneimine, SuperFect, and Lipofectamine 2000. Moreover, we further demonstrate that HPAEs can correct genetic defects in vivo using a recessive dystrophic epidermolysis bullosa graft mouse model. Our findings prove that the A2 + B3 + C2 approach is highly generalizable and flexible for the design and synthesis of HPAEs, which cannot be achieved by the conventional polymerization approach; HPAEs are more efficient vectors in gene transfection than the corresponding LPAEs. This provides valuable insight into the development and applications of nonviral gene delivery and demonstrates great prospect for their translation to a clinical environment. PMID:27386572

Nonlinear feedback control for high alpha flight

NASA Technical Reports Server (NTRS)

Stalford, Harold

1990-01-01

Analytical aerodynamic models are derived from a high alpha 6 DOF wind tunnel model. One detail model requires some interpolation between nonlinear functions of alpha. One analytical model requires no interpolation and as such is a completely continuous model. Flight path optimization is conducted on the basic maneuvers: half-loop, 90 degree pitch-up, and level turn. The optimal control analysis uses the derived analytical model in the equations of motion and is based on both moment and force equations. The maximum principle solution for the half-loop is poststall trajectory performing the half-loop in 13.6 seconds. The agility induced by thrust vectoring capability provided a minimum effect on reducing the maneuver time. By means of thrust vectoring control the 90 degrees pitch-up maneuver can be executed in a small place over a short time interval. The agility capability of thrust vectoring is quite beneficial for pitch-up maneuvers. The level turn results are based currently on only outer layer solutions of singular perturbation. Poststall solutions provide high turn rates but generate higher losses of energy than that of classical sustained solutions.

Experimental and Computational Investigation of Multiple Injection Ports in a Convergent-Divergent Nozzle for Fluidic Thrust Vectoring

NASA Technical Reports Server (NTRS)

Waithe, Kenrick A.; Deere, Karen A.

2003-01-01

A computational and experimental study was conducted to investigate the effects of multiple injection ports in a two-dimensional, convergent-divergent nozzle, for fluidic thrust vectoring. The concept of multiple injection ports was conceived to enhance the thrust vectoring capability of a convergent-divergent nozzle over that of a single injection port without increasing the secondary mass flow rate requirements. The experimental study was conducted at static conditions in the Jet Exit Test Facility of the 16-Foot Transonic Tunnel Complex at NASA Langley Research Center. Internal nozzle performance was obtained at nozzle pressure ratios up to 10 with secondary nozzle pressure ratios up to 1 for five configurations. The computational study was conducted using the Reynolds Averaged Navier-Stokes computational fluid dynamics code PAB3D with two-equation turbulence closure and linear Reynolds stress modeling. Internal nozzle performance was predicted for nozzle pressure ratios up to 10 with a secondary nozzle pressure ratio of 0.7 for two configurations. Results from the experimental study indicate a benefit to multiple injection ports in a convergent-divergent nozzle. In general, increasing the number of injection ports from one to two increased the pitch thrust vectoring capability without any thrust performance penalties at nozzle pressure ratios less than 4 with high secondary pressure ratios. Results from the computational study are in excellent agreement with experimental results and validates PAB3D as a tool for predicting internal nozzle performance of a two dimensional, convergent-divergent nozzle with multiple injection ports.

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme.

PubMed

Espinosa, Manuel O; Polop, Francisco; Rotela, Camilo H; Abril, Marcelo; Scavuzzo, Carlos M

2016-11-21

The main objective of this study was to obtain and analyse the space-time dynamics of Aedes aegypti breeding sites in Clorinda City, Formosa Province, Argentina coupled with landscape analysis using the maximum entropy approach in order to generate a dengue vector niche model. In urban areas, without vector control activities, 12 entomologic (larval) samplings were performed during three years (October 2011 to October 2014). The entomologic surveillance area represented 16,511 houses. Predictive models for Aedes distribution were developed using vector breeding abundance data, density analysis, clustering and geoprocessing techniques coupled with Earth observation satellite data. The spatial analysis showed a vector spatial distribution pattern with clusters of high density in the central region of Clorinda with a well-defined high-risk area in the western part of the city. It also showed a differential temporal behaviour among different areas, which could have implications for risk models and control strategies at the urban scale. The niche model obtained for Ae. aegypti, based on only one year of field data, showed that 85.8% of the distribution of breeding sites is explained by the percentage of water supply (48.2%), urban distribution (33.2%), and the percentage of urban coverage (4.4%). The consequences for the development of control strategies are discussed with reference to the results obtained using distribution maps based on environmental variables.

Three dimensional magnetic fields in extra high speed modified Lundell alternators computed by a combined vector-scalar magnetic potential finite element method

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Wang, R.; Secunde, R.

1992-01-01

A 3D finite element (FE) approach was developed and implemented for computation of global magnetic fields in a 14.3 kVA modified Lundell alternator. The essence of the new method is the combined use of magnetic vector and scalar potential formulations in 3D FEs. This approach makes it practical, using state of the art supercomputer resources, to globally analyze magnetic fields and operating performances of rotating machines which have truly 3D magnetic flux patterns. The 3D FE-computed fields and machine inductances as well as various machine performance simulations of the 14.3 kVA machine are presented in this paper and its two companion papers.

A Subdivision-Based Representation for Vector Image Editing.

PubMed

Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou

2012-11-01

Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.

Recursive feature selection with significant variables of support vectors.

PubMed

Tsai, Chen-An; Huang, Chien-Hsun; Chang, Ching-Wei; Chen, Chun-Houh

2012-01-01

The development of DNA microarray makes researchers screen thousands of genes simultaneously and it also helps determine high- and low-expression level genes in normal and disease tissues. Selecting relevant genes for cancer classification is an important issue. Most of the gene selection methods use univariate ranking criteria and arbitrarily choose a threshold to choose genes. However, the parameter setting may not be compatible to the selected classification algorithms. In this paper, we propose a new gene selection method (SVM-t) based on the use of t-statistics embedded in support vector machine. We compared the performance to two similar SVM-based methods: SVM recursive feature elimination (SVMRFE) and recursive support vector machine (RSVM). The three methods were compared based on extensive simulation experiments and analyses of two published microarray datasets. In the simulation experiments, we found that the proposed method is more robust in selecting informative genes than SVMRFE and RSVM and capable to attain good classification performance when the variations of informative and noninformative genes are different. In the analysis of two microarray datasets, the proposed method yields better performance in identifying fewer genes with good prediction accuracy, compared to SVMRFE and RSVM.

Characteristics of Minimally Oversized Adeno-Associated Virus Vectors Encoding Human Factor VIII Generated Using Producer Cell Lines and Triple Transfection.

PubMed

Nambiar, Bindu; Cornell Sookdeo, Cathleen; Berthelette, Patricia; Jackson, Robert; Piraino, Susan; Burnham, Brenda; Nass, Shelley; Souza, David; O'Riordan, Catherine R; Vincent, Karen A; Cheng, Seng H; Armentano, Donna; Kyostio-Moore, Sirkka

2017-02-01

Several ongoing clinical studies are evaluating recombinant adeno-associated virus (rAAV) vectors as gene delivery vehicles for a variety of diseases. However, the production of vectors with genomes >4.7 kb is challenging, with vector preparations frequently containing truncated genomes. To determine whether the generation of oversized rAAVs can be improved using a producer cell-line (PCL) process, HeLaS3-cell lines harboring either a 5.1 or 5.4 kb rAAV vector genome encoding codon-optimized cDNA for human B-domain deleted Factor VIII (FVIII) were isolated. High-producing "masterwells" (MWs), defined as producing >50,000 vg/cell, were identified for each oversized vector. These MWs provided stable vector production for >20 passages. The quality and potency of the AAVrh8R/FVIII-5.1 and AAVrh8R/FVIII-5.4 vectors generated by the PCL method were then compared to those prepared via transient transfection (TXN). Southern and dot blot analyses demonstrated that both production methods resulted in packaging of heterogeneously sized genomes. However, the PCL-derived rAAV vector preparations contained some genomes >4.7 kb, whereas the majority of genomes generated by the TXN method were ≤4.7 kb. The PCL process reduced packaging of non-vector DNA for both the AAVrh8R/FVIII-5.1 and the AAVrh8R/FVIII-5.4 kb vector preparations. Furthermore, more DNA-containing viral particles were obtained for the AAVrh8R/FVIII-5.1 vector. In a mouse model of hemophilia A, animals administered a PCL-derived rAAV vector exhibited twofold higher plasma FVIII activity and increased levels of vector genomes in the liver than mice treated with vector produced via TXN did. Hence, the quality of oversized vectors prepared using the PCL method is greater than that of vectors generated using the TXN process, and importantly this improvement translates to enhanced performance in vivo.

Real-Time Visual Tracking through Fusion Features

PubMed Central

Ruan, Yang; Wei, Zhenzhong

2016-01-01

Due to their high-speed, correlation filters for object tracking have begun to receive increasing attention. Traditional object trackers based on correlation filters typically use a single type of feature. In this paper, we attempt to integrate multiple feature types to improve the performance, and we propose a new DD-HOG fusion feature that consists of discriminative descriptors (DDs) and histograms of oriented gradients (HOG). However, fusion features as multi-vector descriptors cannot be directly used in prior correlation filters. To overcome this difficulty, we propose a multi-vector correlation filter (MVCF) that can directly convolve with a multi-vector descriptor to obtain a single-channel response that indicates the location of an object. Experiments on the CVPR2013 tracking benchmark with the evaluation of state-of-the-art trackers show the effectiveness and speed of the proposed method. Moreover, we show that our MVCF tracker, which uses the DD-HOG descriptor, outperforms the structure-preserving object tracker (SPOT) in multi-object tracking because of its high-speed and ability to address heavy occlusion. PMID:27347951

SEMIPARAMETRIC QUANTILE REGRESSION WITH HIGH-DIMENSIONAL COVARIATES

PubMed Central

Zhu, Liping; Huang, Mian; Li, Runze

2012-01-01

This paper is concerned with quantile regression for a semiparametric regression model, in which both the conditional mean and conditional variance function of the response given the covariates admit a single-index structure. This semiparametric regression model enables us to reduce the dimension of the covariates and simultaneously retains the flexibility of nonparametric regression. Under mild conditions, we show that the simple linear quantile regression offers a consistent estimate of the index parameter vector. This is a surprising and interesting result because the single-index model is possibly misspecified under the linear quantile regression. With a root-n consistent estimate of the index vector, one may employ a local polynomial regression technique to estimate the conditional quantile function. This procedure is computationally efficient, which is very appealing in high-dimensional data analysis. We show that the resulting estimator of the quantile function performs asymptotically as efficiently as if the true value of the index vector were known. The methodologies are demonstrated through comprehensive simulation studies and an application to a real dataset. PMID:24501536

Static internal performance of a two-dimensional convergent nozzle with thrust-vectoring capability up to 60 deg

NASA Technical Reports Server (NTRS)

Leavitt, L. D.

1985-01-01

An investigation was conducted at wind-off conditions in the static-test facility of the Langley 16-Foot Transonic Tunnel to determine the internal performance characteristics of a two-dimensional convergent nozzle with a thrust-vectoring capability up to 60 deg. Vectoring was accomplished by a downward rotation of a hinged upper convergent flap and a corresponding rotation of a center-pivoted lower convergent flap. The effects of geometric thrust-vector angle and upper-rotating-flap geometry on internal nozzle performance characteristics were investigated. Nozzle pressure ratio was varied from 1.0 (jet off) to approximately 5.0.

Human action classification using procrustes shape theory

NASA Astrophysics Data System (ADS)

Cho, Wanhyun; Kim, Sangkyoon; Park, Soonyoung; Lee, Myungeun

2015-02-01

In this paper, we propose new method that can classify a human action using Procrustes shape theory. First, we extract a pre-shape configuration vector of landmarks from each frame of an image sequence representing an arbitrary human action, and then we have derived the Procrustes fit vector for pre-shape configuration vector. Second, we extract a set of pre-shape vectors from tanning sample stored at database, and we compute a Procrustes mean shape vector for these preshape vectors. Third, we extract a sequence of the pre-shape vectors from input video, and we project this sequence of pre-shape vectors on the tangent space with respect to the pole taking as a sequence of mean shape vectors corresponding with a target video. And we calculate the Procrustes distance between two sequences of the projection pre-shape vectors on the tangent space and the mean shape vectors. Finally, we classify the input video into the human action class with minimum Procrustes distance. We assess a performance of the proposed method using one public dataset, namely Weizmann human action dataset. Experimental results reveal that the proposed method performs very good on this dataset.

Econo-ESA in semantic text similarity.

PubMed

Rahutomo, Faisal; Aritsugi, Masayoshi

2014-01-01

Explicit semantic analysis (ESA) utilizes an immense Wikipedia index matrix in its interpreter part. This part of the analysis multiplies a large matrix by a term vector to produce a high-dimensional concept vector. A similarity measurement between two texts is performed between two concept vectors with numerous dimensions. The cost is expensive in both interpretation and similarity measurement steps. This paper proposes an economic scheme of ESA, named econo-ESA. We investigate two aspects of this proposal: dimensional reduction and experiments with various data. We use eight recycling test collections in semantic text similarity. The experimental results show that both the dimensional reduction and test collection characteristics can influence the results. They also show that an appropriate concept reduction of econo-ESA can decrease the cost with minor differences in the results from the original ESA.

Support Vector Machine-Based Endmember Extraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Filippi, Anthony M; Archibald, Richard K

Introduced in this paper is the utilization of Support Vector Machines (SVMs) to automatically perform endmember extraction from hyperspectral data. The strengths of SVM are exploited to provide a fast and accurate calculated representation of high-dimensional data sets that may consist of multiple distributions. Once this representation is computed, the number of distributions can be determined without prior knowledge. For each distribution, an optimal transform can be determined that preserves informational content while reducing the data dimensionality, and hence, the computational cost. Finally, endmember extraction for the whole data set is accomplished. Results indicate that this Support Vector Machine-Based Endmembermore » Extraction (SVM-BEE) algorithm has the capability of autonomously determining endmembers from multiple clusters with computational speed and accuracy, while maintaining a robust tolerance to noise.« less

Unsupervised segmentation of lung fields in chest radiographs using multiresolution fractal feature vector and deformable models.

PubMed

Lee, Wen-Li; Chang, Koyin; Hsieh, Kai-Sheng

2016-09-01

Segmenting lung fields in a chest radiograph is essential for automatically analyzing an image. We present an unsupervised method based on multiresolution fractal feature vector. The feature vector characterizes the lung field region effectively. A fuzzy c-means clustering algorithm is then applied to obtain a satisfactory initial contour. The final contour is obtained by deformable models. The results show the feasibility and high performance of the proposed method. Furthermore, based on the segmentation of lung fields, the cardiothoracic ratio (CTR) can be measured. The CTR is a simple index for evaluating cardiac hypertrophy. After identifying a suspicious symptom based on the estimated CTR, a physician can suggest that the patient undergoes additional extensive tests before a treatment plan is finalized.

Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.

PubMed

Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Li, Li-Ping; Huang, De-Shuang; Yan, Gui-Ying; Nie, Ru; Huang, Yu-An

2017-04-04

Identification of protein-protein interactions (PPIs) is of critical importance for deciphering the underlying mechanisms of almost all biological processes of cell and providing great insight into the study of human disease. Although much effort has been devoted to identifying PPIs from various organisms, existing high-throughput biological techniques are time-consuming, expensive, and have high false positive and negative results. Thus it is highly urgent to develop in silico methods to predict PPIs efficiently and accurately in this post genomic era. In this article, we report a novel computational model combining our newly developed discriminative vector machine classifier (DVM) and an improved Weber local descriptor (IWLD) for the prediction of PPIs. Two components, differential excitation and orientation, are exploited to build evolutionary features for each protein sequence. The main characteristics of the proposed method lies in introducing an effective feature descriptor IWLD which can capture highly discriminative evolutionary information from position-specific scoring matrixes (PSSM) of protein data, and employing the powerful and robust DVM classifier. When applying the proposed method to Yeast and H. pylori data sets, we obtained excellent prediction accuracies as high as 96.52% and 91.80%, respectively, which are significantly better than the previous methods. Extensive experiments were then performed for predicting cross-species PPIs and the predictive results were also pretty promising. To further validate the performance of the proposed method, we compared it with the state-of-the-art support vector machine (SVM) classifier on Human data set. The experimental results obtained indicate that our method is highly effective for PPIs prediction and can be taken as a supplementary tool for future proteomics research.

A low cost implementation of multi-parameter patient monitor using intersection kernel support vector machine classifier

NASA Astrophysics Data System (ADS)

Mohan, Dhanya; Kumar, C. Santhosh

2016-03-01

Predicting the physiological condition (normal/abnormal) of a patient is highly desirable to enhance the quality of health care. Multi-parameter patient monitors (MPMs) using heart rate, arterial blood pressure, respiration rate and oxygen saturation (S pO2) as input parameters were developed to monitor the condition of patients, with minimum human resource utilization. The Support vector machine (SVM), an advanced machine learning approach popularly used for classification and regression is used for the realization of MPMs. For making MPMs cost effective, we experiment on the hardware implementation of the MPM using support vector machine classifier. The training of the system is done using the matlab environment and the detection of the alarm/noalarm condition is implemented in hardware. We used different kernels for SVM classification and note that the best performance was obtained using intersection kernel SVM (IKSVM). The intersection kernel support vector machine classifier MPM has outperformed the best known MPM using radial basis function kernel by an absoute improvement of 2.74% in accuracy, 1.86% in sensitivity and 3.01% in specificity. The hardware model was developed based on the improved performance system using Verilog Hardware Description Language and was implemented on Altera cyclone-II development board.

Multiprocessing MCNP on an IBM RS/6000 cluster

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKinney, G.W.; West, J.T.

1993-01-01

The advent of high-performance computer systems has brought to maturity programming concepts like vectorization, multiprocessing, and multitasking. While there are many schools of thought as to the most significant factor in obtaining order-of-magnitude increases in performance, such speedup can only be achieved by integrating the computer system and application code. Vectorization leads to faster manipulation of arrays by overlapping instruction CPU cycles. Discrete ordinates codes, which require the solving of large matrices, have proved to be major benefactors of vectorization. Monte Carlo transport, on the other hand, typically contains numerous logic statements and requires extensive redevelopment to benefit from vectorization.more » Multiprocessing and multitasking provide additional CPU cycles via multiple processors. Such systems are generally designed with either common memory access (multitasking) or distributed memory access. In both cases, theoretical speedup, as a function of the number of processors (P) and the fraction of task time that multiprocesses (f), can be formulated using Amdahl's Law S ((f,P) = 1 f + f/P). However, for most applications this theoretical limit cannot be achieved, due to additional terms not included in Amdahl's Law. Monte Carlo transport is a natural candidate for multiprocessing, since the particle tracks are generally independent and the precision of the result increases as the square root of the number of particles tracked.« less

Observation of High-Order Polarization-Locked Vector Solitons in a Fiber Laser

NASA Astrophysics Data System (ADS)

Tang, D. Y.; Zhang, H.; Zhao, L. M.; Wu, X.

2008-10-01

We report on the experimental observation of a new type of polarization-locked vector soliton in a passively mode-locked fiber laser. The vector soliton is characterized by the fact that not only are the two orthogonally polarized soliton components phase-locked, but also one of the components has a double-humped intensity profile. Multiple phase-locked high-order vector solitons with identical soliton parameters and harmonic mode locking of the vector solitons were also obtained in the laser. Numerical simulations confirmed the existence of stable high-order vector solitons in the fiber laser.

Observation of high-order polarization-locked vector solitons in a fiber laser.

PubMed

Tang, D Y; Zhang, H; Zhao, L M; Wu, X

2008-10-10

We report on the experimental observation of a new type of polarization-locked vector soliton in a passively mode-locked fiber laser. The vector soliton is characterized by the fact that not only are the two orthogonally polarized soliton components phase-locked, but also one of the components has a double-humped intensity profile. Multiple phase-locked high-order vector solitons with identical soliton parameters and harmonic mode locking of the vector solitons were also obtained in the laser. Numerical simulations confirmed the existence of stable high-order vector solitons in the fiber laser.

Effects of Cavity on the Performance of Dual Throat Nozzle During the Thrust-Vectoring Starting Transient Process.

PubMed

Gu, Rui; Xu, Jinglei

2014-01-01

The dual throat nozzle (DTN) technique is capable to achieve higher thrust-vectoring efficiencies than other fluidic techniques, without compromising thrust efficiency significantly during vectoring operation. The excellent performance of the DTN is mainly due to the concaved cavity. In this paper, two DTNs of different scales have been investigated by unsteady numerical simulations to compare the parameter variations and study the effects of cavity during the vector starting process. The results remind us that during the vector starting process, dynamic loads may be generated, which is a potentially challenging problem for the aircraft trim and control.

Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding

NASA Astrophysics Data System (ADS)

Kang, Shouqiang; Ma, Danyang; Wang, Yujing; Lan, Chaofeng; Chen, Qingguo; Mikulovich, V. I.

2017-03-01

To effectively assess different fault locations and different degrees of performance degradation of a rolling bearing with a unified assessment index, a novel state assessment method based on the relative compensation distance of multiple-domain features and locally linear embedding is proposed. First, for a single-sample signal, time-domain and frequency-domain indexes can be calculated for the original vibration signal and each sensitive intrinsic mode function obtained by improved ensemble empirical mode decomposition, and the singular values of the sensitive intrinsic mode function matrix can be extracted by singular value decomposition to construct a high-dimensional hybrid-domain feature vector. Second, a feature matrix can be constructed by arranging each feature vector of multiple samples, the dimensions of each row vector of the feature matrix can be reduced by the locally linear embedding algorithm, and the compensation distance of each fault state of the rolling bearing can be calculated using the support vector machine. Finally, the relative distance between different fault locations and different degrees of performance degradation and the normal-state optimal classification surface can be compensated, and on the basis of the proposed relative compensation distance, the assessment model can be constructed and an assessment curve drawn. Experimental results show that the proposed method can effectively assess different fault locations and different degrees of performance degradation of the rolling bearing under certain conditions.

Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

PubMed Central

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm. PMID:23737718

Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.

PubMed

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

Currency crisis indication by using ensembles of support vector machine classifiers

NASA Astrophysics Data System (ADS)

Ramli, Nor Azuana; Ismail, Mohd Tahir; Wooi, Hooy Chee

2014-07-01

There are many methods that had been experimented in the analysis of currency crisis. However, not all methods could provide accurate indications. This paper introduces an ensemble of classifiers by using Support Vector Machine that's never been applied in analyses involving currency crisis before with the aim of increasing the indication accuracy. The proposed ensemble classifiers' performances are measured using percentage of accuracy, root mean squared error (RMSE), area under the Receiver Operating Characteristics (ROC) curve and Type II error. The performances of an ensemble of Support Vector Machine classifiers are compared with the single Support Vector Machine classifier and both of classifiers are tested on the data set from 27 countries with 12 macroeconomic indicators for each country. From our analyses, the results show that the ensemble of Support Vector Machine classifiers outperforms single Support Vector Machine classifier on the problem involving indicating a currency crisis in terms of a range of standard measures for comparing the performance of classifiers.

Effectiveness of Large-Scale Chagas Disease Vector Control Program in Nicaragua by Residual Insecticide Spraying Against Triatoma dimidiata.

PubMed

Yoshioka, Kota; Nakamura, Jiro; Pérez, Byron; Tercero, Doribel; Pérez, Lenin; Tabaru, Yuichiro

2015-12-01

Chagas disease is one of the most serious health problems in Latin America. Because the disease is transmitted mainly by triatomine vectors, a three-phase vector control strategy was used to reduce its vector-borne transmission. In Nicaragua, we implemented an indoor insecticide spraying program in five northern departments to reduce house infestation by Triatoma dimidiata. The spraying program was performed in two rounds. After each round, we conducted entomological evaluation to compare the vector infestation level before and after spraying. A total of 66,200 and 44,683 houses were sprayed in the first and second spraying rounds, respectively. The entomological evaluation showed that the proportion of houses infested by T. dimidiata was reduced from 17.0% to 3.0% after the first spraying, which was statistically significant (P < 0.0001). However, the second spraying round did not demonstrate clear effectiveness. Space-time analysis revealed that reinfestation of T. dimidiata is more likely to occur in clusters where the pre-spray infestation level is high. Here we discuss how large-scale insecticide spraying is neither effective nor affordable when T. dimidiata is widely distributed at low infestation levels. Further challenges involve research on T. dimidiata reinfestation, diversification of vector control strategies, and implementation of sustainable vector surveillance. © The American Society of Tropical Medicine and Hygiene.

Proceedings: Sisal `93

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feo, J.T.

1993-10-01

This report contain papers on: Programmability and performance issues; The case of an iterative partial differential equation solver; Implementing the kernal of the Australian Region Weather Prediction Model in Sisal; Even and quarter-even prime length symmetric FFTs and their Sisal Implementations; Top-down thread generation for Sisal; Overlapping communications and computations on NUMA architechtures; Compiling technique based on dataflow analysis for funtional programming language Valid; Copy elimination for true multidimensional arrays in Sisal 2.0; Increasing parallelism for an optimization that reduces copying in IF2 graphs; Caching in on Sisal; Cache performance of Sisal Vs. FORTRAN; FFT algorithms on a shared-memory multiprocessor;more » A parallel implementation of nonnumeric search problems in Sisal; Computer vision algorithms in Sisal; Compilation of Sisal for a high-performance data driven vector processor; Sisal on distributed memory machines; A virtual shared addressing system for distributed memory Sisal; Developing a high-performance FFT algorithm in Sisal for a vector supercomputer; Implementation issues for IF2 on a static data-flow architechture; and Systematic control of parallelism in array-based data-flow computation. Selected papers have been indexed separately for inclusion in the Energy Science and Technology Database.« less

Effective Vectorization with OpenMP 4.5

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huber, Joseph N.; Hernandez, Oscar R.; Lopez, Matthew Graham

This paper describes how the Single Instruction Multiple Data (SIMD) model and its extensions in OpenMP work, and how these are implemented in different compilers. Modern processors are highly parallel computational machines which often include multiple processors capable of executing several instructions in parallel. Understanding SIMD and executing instructions in parallel allows the processor to achieve higher performance without increasing the power required to run it. SIMD instructions can significantly reduce the runtime of code by executing a single operation on large groups of data. The SIMD model is so integral to the processor s potential performance that, if SIMDmore » is not utilized, less than half of the processor is ever actually used. Unfortunately, using SIMD instructions is a challenge in higher level languages because most programming languages do not have a way to describe them. Most compilers are capable of vectorizing code by using the SIMD instructions, but there are many code features important for SIMD vectorization that the compiler cannot determine at compile time. OpenMP attempts to solve this by extending the C++/C and Fortran programming languages with compiler directives that express SIMD parallelism. OpenMP is used to pass hints to the compiler about the code to be executed in SIMD. This is a key resource for making optimized code, but it does not change whether or not the code can use SIMD operations. However, in many cases critical functions are limited by a poor understanding of how SIMD instructions are actually implemented, as SIMD can be implemented through vector instructions or simultaneous multi-threading (SMT). We have found that it is often the case that code cannot be vectorized, or is vectorized poorly, because the programmer does not have sufficient knowledge of how SIMD instructions work.« less

Efficient solution of parabolic equations by Krylov approximation methods

NASA Technical Reports Server (NTRS)

Gallopoulos, E.; Saad, Y.

1990-01-01

Numerical techniques for solving parabolic equations by the method of lines is addressed. The main motivation for the proposed approach is the possibility of exploiting a high degree of parallelism in a simple manner. The basic idea of the method is to approximate the action of the evolution operator on a given state vector by means of a projection process onto a Krylov subspace. Thus, the resulting approximation consists of applying an evolution operator of a very small dimension to a known vector which is, in turn, computed accurately by exploiting well-known rational approximations to the exponential. Because the rational approximation is only applied to a small matrix, the only operations required with the original large matrix are matrix-by-vector multiplications, and as a result the algorithm can easily be parallelized and vectorized. Some relevant approximation and stability issues are discussed. We present some numerical experiments with the method and compare its performance with a few explicit and implicit algorithms.

The nondeterministic divide

NASA Technical Reports Server (NTRS)

Charlesworth, Arthur

1990-01-01

The nondeterministic divide partitions a vector into two non-empty slices by allowing the point of division to be chosen nondeterministically. Support for high-level divide-and-conquer programming provided by the nondeterministic divide is investigated. A diva algorithm is a recursive divide-and-conquer sequential algorithm on one or more vectors of the same range, whose division point for a new pair of recursive calls is chosen nondeterministically before any computation is performed and whose recursive calls are made immediately after the choice of division point; also, access to vector components is only permitted during activations in which the vector parameters have unit length. The notion of diva algorithm is formulated precisely as a diva call, a restricted call on a sequential procedure. Diva calls are proven to be intimately related to associativity. Numerous applications of diva calls are given and strategies are described for translating a diva call into code for a variety of parallel computers. Thus diva algorithms separate logical correctness concerns from implementation concerns.

GNSS Single Frequency, Single Epoch Reliable Attitude Determination Method with Baseline Vector Constraint.

PubMed

Gong, Ang; Zhao, Xiubin; Pang, Chunlei; Duan, Rong; Wang, Yong

2015-12-02

For Global Navigation Satellite System (GNSS) single frequency, single epoch attitude determination, this paper proposes a new reliable method with baseline vector constraint. First, prior knowledge of baseline length, heading, and pitch obtained from other navigation equipment or sensors are used to reconstruct objective function rigorously. Then, searching strategy is improved. It substitutes gradually Enlarged ellipsoidal search space for non-ellipsoidal search space to ensure correct ambiguity candidates are within it and make the searching process directly be carried out by least squares ambiguity decorrelation algorithm (LAMBDA) method. For all vector candidates, some ones are further eliminated by derived approximate inequality, which accelerates the searching process. Experimental results show that compared to traditional method with only baseline length constraint, this new method can utilize a priori baseline three-dimensional knowledge to fix ambiguity reliably and achieve a high success rate. Experimental tests also verify it is not very sensitive to baseline vector error and can perform robustly when angular error is not great.

Static internal performance of a single expansion ramp nozzle with multiaxis thrust vectoring capability

NASA Technical Reports Server (NTRS)

Capone, Francis J.; Schirmer, Alberto W.

1993-01-01

An investigation was conducted at static conditions in order to determine the internal performance characteristics of a multiaxis thrust vectoring single expansion ramp nozzle. Yaw vectoring was achieved by deflecting yaw flaps in the nozzle sidewall into the nozzle exhaust flow. In order to eliminate any physical interference between the variable angle yaw flap deflected into the exhaust flow and the nozzle upper ramp and lower flap which were deflected for pitch vectoring, the downstream corners of both the nozzle ramp and lower flap were cut off to allow for up to 30 deg of yaw vectoring. The effects of nozzle upper ramp and lower flap cutout, yaw flap hinge line location and hinge inclination angle, sidewall containment, geometric pitch vector angle, and geometric yaw vector angle were studied. This investigation was conducted in the static-test facility of the Langley 16-Foot Transonic Tunnel at nozzle pressure ratios up to 8.0.

Re-engineering adenovirus vector systems to enable high-throughput analyses of gene function.

PubMed

Stanton, Richard J; McSharry, Brian P; Armstrong, Melanie; Tomasec, Peter; Wilkinson, Gavin W G

2008-12-01

With the enhanced capacity of bioinformatics to interrogate extensive banks of sequence data, more efficient technologies are needed to test gene function predictions. Replication-deficient recombinant adenovirus (Ad) vectors are widely used in expression analysis since they provide for extremely efficient expression of transgenes in a wide range of cell types. To facilitate rapid, high-throughput generation of recombinant viruses, we have re-engineered an adenovirus vector (designated AdZ) to allow single-step, directional gene insertion using recombineering technology. Recombineering allows for direct insertion into the Ad vector of PCR products, synthesized sequences, or oligonucleotides encoding shRNAs without requirement for a transfer vector Vectors were optimized for high-throughput applications by making them "self-excising" through incorporating the I-SceI homing endonuclease into the vector removing the need to linearize vectors prior to transfection into packaging cells. AdZ vectors allow genes to be expressed in their native form or with strep, V5, or GFP tags. Insertion of tetracycline operators downstream of the human cytomegalovirus major immediate early (HCMV MIE) promoter permits silencing of transgenes in helper cells expressing the tet repressor thus making the vector compatible with the cloning of toxic gene products. The AdZ vector system is robust, straightforward, and suited to both sporadic and high-throughput applications.

Alterations to the orientation of the ground reaction force vector affect sprint acceleration performance in team sports athletes.

PubMed

Bezodis, Neil E; North, Jamie S; Razavet, Jane L

2017-09-01

A more horizontally oriented ground reaction force vector is related to higher levels of sprint acceleration performance across a range of athletes. However, the effects of acute experimental alterations to the force vector orientation within athletes are unknown. Fifteen male team sports athletes completed maximal effort 10-m accelerations in three conditions following different verbal instructions intended to manipulate the force vector orientation. Ground reaction forces (GRFs) were collected from the step nearest 5-m and stance leg kinematics at touchdown were also analysed to understand specific kinematic features of touchdown technique which may influence the consequent force vector orientation. Magnitude-based inferences were used to compare findings between conditions. There was a likely more horizontally oriented ground reaction force vector and a likely lower peak vertical force in the control condition compared with the experimental conditions. 10-m sprint time was very likely quickest in the control condition which confirmed the importance of force vector orientation for acceleration performance on a within-athlete basis. The stance leg kinematics revealed that a more horizontally oriented force vector during stance was preceded at touchdown by a likely more dorsiflexed ankle, a likely more flexed knee, and a possibly or likely greater hip extension velocity.

Performance characteristics of two multiaxis thrust-vectoring nozzles at Mach numbers up to 1.28

NASA Technical Reports Server (NTRS)

Wing, David J.; Capone, Francis J.

1993-01-01

The thrust-vectoring axisymmetric (VA) nozzle and a spherical convergent flap (SCF) thrust-vectoring nozzle were tested along with a baseline nonvectoring axisymmetric (NVA) nozzle in the Langley 16-Foot Transonic Tunnel at Mach numbers from 0 to 1.28 and nozzle pressure ratios from 1 to 8. Test parameters included geometric yaw vector angle and unvectored divergent flap length. No pitch vectoring was studied. Nozzle drag, thrust minus drag, yaw thrust vector angle, discharge coefficient, and static thrust performance were measured and analyzed, as well as external static pressure distributions. The NVA nozzle and the VA nozzle displayed higher static thrust performance than the SCF nozzle throughout the nozzle pressure ratio (NPR) range tested. The NVA nozzle had higher overall thrust minus drag than the other nozzles throughout the NPR and Mach number ranges tested. The SCF nozzle had the lowest jet-on nozzle drag of the three nozzles throughout the test conditions. The SCF nozzle provided yaw thrust angles that were equal to the geometric angle and constant with NPR. The VA nozzle achieved yaw thrust vector angles that were significantly higher than the geometric angle but not constant with NPR. Nozzle drag generally increased with increases in thrust vectoring for all the nozzles tested.

A new vector radiative transfer model as a part of SCIATRAN 3.0 software package.

NASA Astrophysics Data System (ADS)

Rozanov, Alexei; Rozanov, Vladimir; Burrows, John P.

The SCIATRAN 3.0 package is a result of further development of the SCIATRAN 2.x software family which, similar to previous versions, comprises a radiative transfer model and a retrieval block. A major improvement was achieved in comparison to previous software versions by adding the vector mode to the radiative transfer model. Thus, the well-established Discrete Ordinate solver can now be run in the vector mode to calculate the scattered solar radiation including polarization, i.e., to simulate all four components of the Stockes vector. Similar to the scalar version, the simulations can be performed for any viewing geometry typical for atmospheric observations in the UV-Vis-NIR spectral range (nadir, limb, off-axis, etc.) as well as for any observer position within or outside the Earth's atmosphere. Similar to the precursor version, the new model is freely available for non-commercial use via the web page of the University of Bremen. In this presentation a short description of the software package, especially of the new vector radiative transfer model will be given, including remarks on the availability for the scientific community. Furthermore, comparisons to other vector models will be shown and some example problems will be considered where the polarization of the observed radiation must be accounted for to obtain high quality results.

Locally adaptive vector quantization: Data compression with feature preservation

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Sayano, M.

1992-01-01

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

Interaction and Impact Studies for Distributed Energy Resource, Transactive Energy, and Electric Grid, using High Performance Computing ?based Modeling and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelley, B. M.

The electric utility industry is undergoing significant transformations in its operation model, including a greater emphasis on automation, monitoring technologies, and distributed energy resource management systems (DERMS). With these changes and new technologies, while driving greater efficiencies and reliability, these new models may introduce new vectors of cyber attack. The appropriate cybersecurity controls to address and mitigate these newly introduced attack vectors and potential vulnerabilities are still widely unknown and performance of the control is difficult to vet. This proposal argues that modeling and simulation (M&S) is a necessary tool to address and better understand these problems introduced by emergingmore » technologies for the grid. M&S will provide electric utilities a platform to model its transmission and distribution systems and run various simulations against the model to better understand the operational impact and performance of cybersecurity controls.« less

A high performance linear equation solver on the VPP500 parallel supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakanishi, Makoto; Ina, Hiroshi; Miura, Kenichi

1994-12-31

This paper describes the implementation of two high performance linear equation solvers developed for the Fujitsu VPP500, a distributed memory parallel supercomputer system. The solvers take advantage of the key architectural features of VPP500--(1) scalability for an arbitrary number of processors up to 222 processors, (2) flexible data transfer among processors provided by a crossbar interconnection network, (3) vector processing capability on each processor, and (4) overlapped computation and transfer. The general linear equation solver based on the blocked LU decomposition method achieves 120.0 GFLOPS performance with 100 processors in the LIN-PACK Highly Parallel Computing benchmark.

The F-18 High Alpha Research Vehicle: A High-Angle-of-Attack Testbed Aircraft

NASA Technical Reports Server (NTRS)

Regenie, Victoria; Gatlin, Donald; Kempel, Robert; Matheny, Neil

1992-01-01

The F-18 High Alpha Research Vehicle is the first thrust-vectoring testbed aircraft used to study the aerodynamics and maneuvering available in the poststall flight regime and to provide the data for validating ground prediction techniques. The aircraft includes a flexible research flight control system and full research instrumentation. The capability to control the vehicle at angles of attack up to 70 degrees is also included. This aircraft was modified by adding a pitch and yaw thrust-vectoring system. No significant problems occurred during the envelope expansion phase of the program. This aircraft has demonstrated excellent control in the wing rock region and increased rolling performance at high angles of attack. Initial pilot reports indicate that the increased capability is desirable although some difficulty in judging the size and timing of control inputs was observed. The aircraft, preflight ground testing and envelope expansion flight tests are described.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System.

PubMed

Liu, Ying-Pei; Liang, Hai-Ping; Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System

PubMed Central

Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane. PMID:26098556

A qualitative study of community perception and acceptance of biological larviciding for malaria mosquito control in rural Burkina Faso.

PubMed

Dambach, Peter; Jorge, Margarida Mendes; Traoré, Issouf; Phalkey, Revati; Sawadogo, Hélène; Zabré, Pascal; Kagoné, Moubassira; Sié, Ali; Sauerborn, Rainer; Becker, Norbert; Beiersmann, Claudia

2018-03-23

Vector and malaria parasite's rising resistance against pyrethroid-impregnated bed nets and antimalarial drugs highlight the need for additional control measures. Larviciding against malaria vectors is experiencing a renaissance with the availability of environmentally friendly and target species-specific larvicides. In this study, we analyse the perception and acceptability of spraying surface water collections with the biological larvicide Bacillus thuringiensis israelensis in a single health district in Burkina Faso. A total of 12 focus group discussions and 12 key informant interviews were performed in 10 rural villages provided with coverage of various larvicide treatments (all breeding sites treated, the most productive breeding sites treated, and untreated control). Respondents' knowledge about the major risk factors for malaria transmission was generally good. Most interviewees stated they performed personal protective measures against vector mosquitoes including the use of bed nets and sometimes mosquito coils and traditional repellents. The acceptance of larviciding in and around the villages was high and the majority of respondents reported a relief in mosquito nuisance and malarial episodes. There was high interest in the project and demand for future continuation. This study showed that larviciding interventions received positive resonance from the population. People showed a willingness to be involved and financially support the program. The positive environment with high acceptance for larviciding programs would facilitate routine implementation. An essential factor for the future success of such programs would be inclusion in regional or national malaria control guidelines.

High-dimensional vector semantics

NASA Astrophysics Data System (ADS)

Andrecut, M.

In this paper we explore the “vector semantics” problem from the perspective of “almost orthogonal” property of high-dimensional random vectors. We show that this intriguing property can be used to “memorize” random vectors by simply adding them, and we provide an efficient probabilistic solution to the set membership problem. Also, we discuss several applications to word context vector embeddings, document sentences similarity, and spam filtering.

Parametric study of a simultaneous pitch/yaw thrust vectoring single expansion ramp nozzle

NASA Technical Reports Server (NTRS)

Schirmer, Alberto W.; Capone, Francis J.

1989-01-01

In the course of the last eleven years, the concept of thrust vectoring has emerged as a promising method of enhancing aircraft control capabilities in post-stall flight incursions during combat. In order to study the application of simultaneous pitch and yaw vectoring to single expansion ramp nozzles, a static test was conducted in the NASA-Langley 16 foot transonic tunnel. This investigation was based on internal performance data provided by force, mass flow and internal pressure measurements at nozzle pressure ratios up to 8. The internal performance characteristics of the nozzle were studied for several combinations of six different parameters: yaw vectoring angle, pitch vectoring angle, upper ramp cutout, sidewall hinge location, hinge inclination angle and sidewall containment. Results indicated a 2-to- 3-percent decrease in resultant thrust ratio with vectoring in either pitch or yaw. Losses were mostly associated with the turning of supersonic flow. Resultant thrust ratios were also decreased by sideways expansion of the jet. The effects of cutback corners in the upper ramp and lower flap on performance were small. Maximum resultant yaw vector angles, about half of the flap angle, were achieved for the configuration with the most forward hinge location.

Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), Vector of Leishmania (Leishmania) amazonensis in South America, under Climate Change.

PubMed

Carvalho, Bruno M; Rangel, Elizabeth F; Ready, Paul D; Vale, Mariana M

2015-01-01

Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector's climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: "stabilization" and "high increase". Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.

High-capacity 'gutless' adenoviral vectors.

PubMed

Kochanek, S; Schiedner, G; Volpers, C

2001-10-01

Adenoviral vectors are promising gene transfer vehicles for different gene therapy applications. High-capacity adenoviral (HC-Ad) vectors address some of the problems that have been observed with replication-defective, E1-deleted first-generation adenoviral vectors: toxicity and immunogenicity due to viral gene expression and 7 to 8 kb capacity limit for the transport of therapeutic DNA. This review summarizes HC-Ad vector-related publications from the past 18 months that are mainly concerned with vector design/production and in vivo applications in different murine models.

Field evaluation of picaridin repellents reveals differences in repellent sensitivity between Southeast Asian vectors of malaria and arboviruses.

PubMed

Van Roey, Karel; Sokny, Mao; Denis, Leen; Van den Broeck, Nick; Heng, Somony; Siv, Sovannaroth; Sluydts, Vincent; Sochantha, Tho; Coosemans, Marc; Durnez, Lies

2014-12-01

Scaling up of insecticide treated nets has contributed to a substantial malaria decline. However, some malaria vectors, and most arbovirus vectors, bite outdoors and in the early evening. Therefore, topically applied insect repellents may provide crucial additional protection against mosquito-borne pathogens. Among topical repellents, DEET is the most commonly used, followed by others such as picaridin. The protective efficacy of two formulated picaridin repellents against mosquito bites, including arbovirus and malaria vectors, was evaluated in a field study in Cambodia. Over a period of two years, human landing collections were performed on repellent treated persons, with rotation to account for the effect of collection place, time and individual collector. Based on a total of 4996 mosquitoes collected on negative control persons, the overall five hour protection rate was 97.4% [95%CI: 97.1-97.8%], not decreasing over time. Picaridin 20% performed equally well as DEET 20% and better than picaridin 10%. Repellents performed better against Mansonia and Culex spp. as compared to aedines and anophelines. A lower performance was observed against Aedes albopictus as compared to Aedes aegypti, and against Anopheles barbirostris as compared to several vector species. Parity rates were higher in vectors collected on repellent treated person as compared to control persons. As such, field evaluation shows that repellents can provide additional personal protection against early and outdoor biting malaria and arbovirus vectors, with excellent protection up to five hours after application. The heterogeneity in repellent sensitivity between mosquito genera and vector species could however impact the efficacy of repellents in public health programs. Considering its excellent performance and potential to protect against early and outdoor biting vectors, as well as its higher acceptability as compared to DEET, picaridin is an appropriate product to evaluate the epidemiological impact of large scale use of topical repellents on arthropod borne diseases.

Field Evaluation of Picaridin Repellents Reveals Differences in Repellent Sensitivity between Southeast Asian Vectors of Malaria and Arboviruses

PubMed Central

Denis, Leen; Van den Broeck, Nick; Heng, Somony; Siv, Sovannaroth; Sluydts, Vincent; Sochantha, Tho; Coosemans, Marc; Durnez, Lies

2014-01-01

Scaling up of insecticide treated nets has contributed to a substantial malaria decline. However, some malaria vectors, and most arbovirus vectors, bite outdoors and in the early evening. Therefore, topically applied insect repellents may provide crucial additional protection against mosquito-borne pathogens. Among topical repellents, DEET is the most commonly used, followed by others such as picaridin. The protective efficacy of two formulated picaridin repellents against mosquito bites, including arbovirus and malaria vectors, was evaluated in a field study in Cambodia. Over a period of two years, human landing collections were performed on repellent treated persons, with rotation to account for the effect of collection place, time and individual collector. Based on a total of 4996 mosquitoes collected on negative control persons, the overall five hour protection rate was 97.4% [95%CI: 97.1–97.8%], not decreasing over time. Picaridin 20% performed equally well as DEET 20% and better than picaridin 10%. Repellents performed better against Mansonia and Culex spp. as compared to aedines and anophelines. A lower performance was observed against Aedes albopictus as compared to Aedes aegypti, and against Anopheles barbirostris as compared to several vector species. Parity rates were higher in vectors collected on repellent treated person as compared to control persons. As such, field evaluation shows that repellents can provide additional personal protection against early and outdoor biting malaria and arbovirus vectors, with excellent protection up to five hours after application. The heterogeneity in repellent sensitivity between mosquito genera and vector species could however impact the efficacy of repellents in public health programs. Considering its excellent performance and potential to protect against early and outdoor biting vectors, as well as its higher acceptability as compared to DEET, picaridin is an appropriate product to evaluate the epidemiological impact of large scale use of topical repellents on arthropod borne diseases. PMID:25522134

Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion.

PubMed

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.

Exact analytical modeling of magnetic vector potential in surface inset permanent magnet DC machines considering magnet segmentation

NASA Astrophysics Data System (ADS)

Jabbari, Ali

2018-01-01

Surface inset permanent magnet DC machine can be used as an alternative in automation systems due to their high efficiency and robustness. Magnet segmentation is a common technique in order to mitigate pulsating torque components in permanent magnet machines. An accurate computation of air-gap magnetic field distribution is necessary in order to calculate machine performance. An exact analytical method for magnetic vector potential calculation in surface inset permanent magnet machines considering magnet segmentation has been proposed in this paper. The analytical method is based on the resolution of Laplace and Poisson equations as well as Maxwell equation in polar coordinate by using sub-domain method. One of the main contributions of the paper is to derive an expression for the magnetic vector potential in the segmented PM region by using hyperbolic functions. The developed method is applied on the performance computation of two prototype surface inset magnet segmented motors with open circuit and on load conditions. The results of these models are validated through FEM method.

An adaptive evolutionary multi-objective approach based on simulated annealing.

PubMed

Li, H; Landa-Silva, D

2011-01-01

A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic algorithms. Each subproblem corresponds to one weighted aggregation function. For example, MOEA/D is an evolutionary multi-objective optimization (EMO) algorithm that attempts to optimize multiple subproblems simultaneously by evolving a population of solutions. However, the performance of MOEA/D highly depends on the initial setting and diversity of the weight vectors. In this paper, we present an improved version of MOEA/D, called EMOSA, which incorporates an advanced local search technique (simulated annealing) and adapts the search directions (weight vectors) corresponding to various subproblems. In EMOSA, the weight vector of each subproblem is adaptively modified at the lowest temperature in order to diversify the search toward the unexplored parts of the Pareto-optimal front. Our computational results show that EMOSA outperforms six other well established multi-objective metaheuristic algorithms on both the (constrained) multi-objective knapsack problem and the (unconstrained) multi-objective traveling salesman problem. Moreover, the effects of the main algorithmic components and parameter sensitivities on the search performance of EMOSA are experimentally investigated.

The application of artificial neural networks and support vector regression for simultaneous spectrophotometric determination of commercial eye drop contents

NASA Astrophysics Data System (ADS)

Valizadeh, Maryam; Sohrabi, Mahmoud Reza

2018-03-01

In the present study, artificial neural networks (ANNs) and support vector regression (SVR) as intelligent methods coupled with UV spectroscopy for simultaneous quantitative determination of Dorzolamide (DOR) and Timolol (TIM) in eye drop. Several synthetic mixtures were analyzed for validating the proposed methods. At first, neural network time series, which one type of network from the artificial neural network was employed and its efficiency was evaluated. Afterwards, the radial basis network was applied as another neural network. Results showed that the performance of this method is suitable for predicting. Finally, support vector regression was proposed to construct the Zilomole prediction model. Also, root mean square error (RMSE) and mean recovery (%) were calculated for SVR method. Moreover, the proposed methods were compared to the high-performance liquid chromatography (HPLC) as a reference method. One way analysis of variance (ANOVA) test at the 95% confidence level applied to the comparison results of suggested and reference methods that there were no significant differences between them. Also, the effect of interferences was investigated in spike solutions.

A procedure for accurate calibration of the orientation of the three sensors in a vector magnetometer. [at the Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Mcpherron, R. L.

1977-01-01

Procedures are described for the calibration of a vector magnetometer of high absolute accuracy. It is assumed that the calibration will be performed in the magnetic test facility of Goddard Space Flight Center (GSFC). The first main section of the report describes the test equipment and facility calibrations required. The second presents procedures for calibrating individual sensors. The third discusses the calibration of the sensor assembly. In a final section recommendations are made to GSFC for modification of the test facility required to carry out the calibration procedures.

Flexible body stability analysis of Space Shuttle ascent flight control system by using lambda matrix solution techniques

NASA Technical Reports Server (NTRS)

Bown, R. L.; Christofferson, A.; Lardas, M.; Flanders, H.

1980-01-01

A lambda matrix solution technique is being developed to perform an open loop frequency analysis of a high order dynamic system. The procedure evaluates the right and left latent vectors corresponding to the respective latent roots. The latent vectors are used to evaluate the partial fraction expansion formulation required to compute the flexible body open loop feedback gains for the Space Shuttle Digital Ascent Flight Control System. The algorithm is in the final stages of development and will be used to insure that the feedback gains meet the design specification.

Improved Online Support Vector Machines Spam Filtering Using String Kernels

NASA Astrophysics Data System (ADS)

Amayri, Ola; Bouguila, Nizar

A major bottleneck in electronic communications is the enormous dissemination of spam emails. Developing of suitable filters that can adequately capture those emails and achieve high performance rate become a main concern. Support vector machines (SVMs) have made a large contribution to the development of spam email filtering. Based on SVMs, the crucial problems in email classification are feature mapping of input emails and the choice of the kernels. In this paper, we present thorough investigation of several distance-based kernels and propose the use of string kernels and prove its efficiency in blocking spam emails. We detail a feature mapping variants in text classification (TC) that yield improved performance for the standard SVMs in filtering task. Furthermore, to cope for realtime scenarios we propose an online active framework for spam filtering.

Exploiting MIC architectures for the simulation of channeling of charged particles in crystals

NASA Astrophysics Data System (ADS)

Bagli, Enrico; Karpusenko, Vadim

2016-08-01

Coherent effects of ultra-relativistic particles in crystals is an area of science under development. DYNECHARM + + is a toolkit for the simulation of coherent interactions between high-energy charged particles and complex crystal structures. The particle trajectory in a crystal is computed through numerical integration of the equation of motion. The code was revised and improved in order to exploit parallelization on multi-cores and vectorization of single instructions on multiple data. An Intel Xeon Phi card was adopted for the performance measurements. The computation time was proved to scale linearly as a function of the number of physical and virtual cores. By enabling the auto-vectorization flag of the compiler a three time speedup was obtained. The performances of the card were compared to the Dual Xeon ones.

Opportunities and choice in a new vector era

NASA Astrophysics Data System (ADS)

Nowak, A.

2014-06-01

This work discusses the significant changes in computing landscape related to the progression of Moore's Law, and the implications on scientific computing. Particular attention is devoted to the High Energy Physics domain (HEP), which has always made good use of threading, but levels of parallelism closer to the hardware were often left underutilized. Findings of the CERN openlab Platform Competence Center are reported in the context of expanding "performance dimensions", and especially the resurgence of vectors. These suggest that data oriented designs are feasible in HEP and have considerable potential for performance improvements on multiple levels, but will rarely trump algorithmic enhancements. Finally, an analysis of upcoming hardware and software technologies identifies heterogeneity as a major challenge for software, which will require more emphasis on scalable, efficient design.

A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits.

PubMed

Yan, Kang K; Zhao, Hongyu; Pang, Herbert

2017-12-06

High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order to provide a holistic understanding of human health and diseases, it is necessary to integrate multiple data sources. Several algorithms have been proposed so far, however, a comprehensive comparison of data integration algorithms for classification of binary traits is currently lacking. In this paper, we focus on two common classes of integration algorithms, graph-based that depict relationships with subjects denoted by nodes and relationships denoted by edges, and kernel-based that can generate a classifier in feature space. Our paper provides a comprehensive comparison of their performance in terms of various measurements of classification accuracy and computation time. Seven different integration algorithms, including graph-based semi-supervised learning, graph sharpening integration, composite association network, Bayesian network, semi-definite programming-support vector machine (SDP-SVM), relevance vector machine (RVM) and Ada-boost relevance vector machine are compared and evaluated with hypertension and two cancer data sets in our study. In general, kernel-based algorithms create more complex models and require longer computation time, but they tend to perform better than graph-based algorithms. The performance of graph-based algorithms has the advantage of being faster computationally. The empirical results demonstrate that composite association network, relevance vector machine, and Ada-boost RVM are the better performers. We provide recommendations on how to choose an appropriate algorithm for integrating data from multiple sources.

Time-based self-spacing techniques using cockpit display of traffic information during approach to landing in a terminal area vectoring environment

NASA Technical Reports Server (NTRS)

Williams, D. H.

1983-01-01

A simulation study was undertaken to evaluate two time-based self-spacing techniques for in-trail following during terminal area approach. An electronic traffic display was provided in the weather radarscope location. The displayed self-spacing cues allowed the simulated aircraft to follow and to maintain spacing on another aircraft which was being vectored by air traffic control (ATC) for landing in a high-density terminal area. Separation performance data indicate the information provided on the traffic display was adequate for the test subjects to accurately follow the approach path of another aircraft without the assistance of ATC. The time-based technique with a constant-delay spacing criterion produced the most satisfactory spacing performance. Pilot comments indicate the workload associated with the self-separation task was very high and that additional spacing command information and/or aircraft autopilot functions would be desirable for operational implementational of the self-spacing task.

Improving the Accuracy and Training Speed of Motor Imagery Brain-Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors.

PubMed

Lee, David; Park, Sang-Hoon; Lee, Sang-Goog

2017-10-07

In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configured as follows: first, wavelet transforms are applied to extract the feature vectors for identification of motor imagery electroencephalography (EEG) and principal component analyses are used to reduce the dimensionality of the feature vectors and linearly combine them. Subsequently, the GMM universal background model is trained by the expectation-maximization (EM) algorithm to purify the training data and reduce its size. Finally, a purified and reduced GMM-supervector is used to train the support vector machine classifier. The performance of the proposed method was evaluated for three different motor imagery datasets in terms of accuracy, kappa, mutual information, and computation time, and compared with the state-of-the-art algorithms. The results from the study indicate that the proposed method achieves high accuracy with a small amount of training data compared with the state-of-the-art algorithms in motor imagery EEG classification.

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

High-Efficiency Promoter-Dependent Transduction by Adeno-Associated Virus Type 6 Vectors in Mouse Lung

PubMed Central

HALBERT, CHRISTINE L.; LAM, SIU-LING; MILLER, A. DUSTY

2014-01-01

The transduction efficiency of adeno-associated virus (AAV) vectors in various somatic tissues has been shown to depend heavily on the AAV type from which the vector capsid proteins are derived. Among the AAV types studied, AAV6 efficiently transduces cells of the airway epithelium, making it a good candidate for the treatment of lung diseases such as cystic fibrosis. Here we have evaluated the effects of various promoter sequences on transduction rates and gene expression levels in the lung. Of the strong viral promoters examined, the Rous sarcoma virus (RSV) promoter performed significantly better than a human cytomegalovirus (CMV) promoter in the airway epithelium. However, a hybrid promoter consisting of a CMV enhancer, β-actin promoter and splice donor, and a β-globin splice acceptor (CAG promoter) exhibited even higher expression than either of the strong viral promoters alone, showing a 38-fold increase in protein expression over the RSV promoter. In addition, we show that vectors containing either the RSV or CAG promoter expressed well in the nasal and tracheal epithelium. Transduction rates in the 90% range were achieved in many airways with the CAG promoter, showing that with the proper AAV capsid proteins and promoter sequences, highly efficient transduction can be achieved. PMID:17430088

Critical design criteria for minimal antibiotic-free plasmid vectors necessary to combine robust RNA Pol II and Pol III-mediated eukaryotic expression with high bacterial production yields

PubMed Central

Carnes, Aaron E.; Luke, Jeremy M.; Vincent, Justin M.; Anderson, Sheryl; Schukar, Angela; Hodgson, Clague P.; Williams, James A.

2010-01-01

Background For safety considerations, regulatory agencies recommend elimination of antibiotic resistance markers and nonessential sequences from plasmid DNA-based gene medicines. In the present study we analyzed antibiotic-free (AF) vector design criteria impacting bacterial production and mammalian transgene expression. Methods Both CMV-HTLV-I R RNA Pol II promoter (protein transgene) and murine U6 RNA Pol III promoter (RNA transgene) vector designs were studied. Plasmid production yield was assessed through inducible fed-batch fermentation. RNA Pol II-directed EGFP and RNA Pol III-directed RNA expression were quantified by fluorometry and quantitative real-time polymerase chain reaction (RT-PCR), respectively, after transfection of human HEK293 cells. Results Sucrose-selectable minimalized protein and therapeutic RNA expression vector designs that combined an RNA-based AF selection with highly productive fermentation manufacturing (>1,000 mg/L plasmid DNA) and high level in vivo expression of encoded products were identified. The AF selectable marker was also successfully applied to convert existing kanamycin-resistant DNA vaccine plasmids gWIZ and pVAX1 into AF vectors, demonstrating a general utility for retrofitting existing vectors. A minimum vector size for high yield plasmid fermentation was identified. A strategy for stable fermentation of plasmid dimers with improved vector potency and fermentation yields up to 1,740 mg/L was developed. Conclusions We report the development of potent high yield AF gene medicine expression vectors for protein or RNA (e.g. short hairpin RNA or microRNA) products. These AF expression vectors were optimized to exceed a newly identified size threshold for high copy plasmid replication and direct higher transgene expression levels than alternative vectors. PMID:20806425

Spatial aliasing for efficient direction-of-arrival estimation based on steering vector reconstruction

NASA Astrophysics Data System (ADS)

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.

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine.

PubMed

Wahba, Maram A; Ashour, Amira S; Napoleon, Sameh A; Abd Elnaby, Mustafa M; Guo, Yanhui

2017-12-01

Basal cell carcinoma is one of the most common malignant skin lesions. Automated lesion identification and classification using image processing techniques is highly required to reduce the diagnosis errors. In this study, a novel technique is applied to classify skin lesion images into two classes, namely the malignant Basal cell carcinoma and the benign nevus. A hybrid combination of bi-dimensional empirical mode decomposition and gray-level difference method features is proposed after hair removal. The combined features are further classified using quadratic support vector machine (Q-SVM). The proposed system has achieved outstanding performance of 100% accuracy, sensitivity and specificity compared to other support vector machine procedures as well as with different extracted features. Basal Cell Carcinoma is effectively classified using Q-SVM with the proposed combined features.

Thrust shock vector control of an axisymmetric conical supersonic nozzle via secondary transverse gas injection

NASA Astrophysics Data System (ADS)

Zmijanovic, V.; Lago, V.; Sellam, M.; Chpoun, A.

2014-01-01

Transverse secondary gas injection into the supersonic flow of an axisymmetric convergent-divergent nozzle is investigated to describe the effects of the fluidic thrust vectoring within the framework of a small satellite launcher. Cold-flow dry-air experiments are performed in a supersonic wind tunnel using two identical supersonic conical nozzles with the different transverse injection port positions. The complex three-dimensional flow field generated by the supersonic cross-flows in these test nozzles was examined. Valuable experimental data were confronted and compared with the results obtained from the numerical simulations. Different nozzle models are numerically simulated under experimental conditions and then further investigated to determine which parameters significantly affect thrust vectoring. Effects which characterize the nozzle and thrust vectoring performances are established. The results indicate that with moderate secondary to primary mass flow rate ratios, ranging around 5 %, it is possible to achieve pertinent vector side forces. It is also revealed that injector positioning and geometry have a strong effect on the shock vector control system and nozzle performances.

Deceptive chemical signals induced by a plant virus attract insect vectors to inferior hosts.

PubMed

Mauck, Kerry E; De Moraes, Consuelo M; Mescher, Mark C

2010-02-23

Previous studies have shown that vector-borne pathogens can alter the phenotypes of their hosts and vectors in ways that influence the frequency and nature of interactions between them, with significant implications for the transmission and spread of disease. For insect-borne pathogens, host odors are particularly likely targets for manipulation, because both plant- and animal-feeding insects use volatile compounds derived from their hosts as key foraging cues. Here, we document the effects of a widespread plant pathogen, Cucumber mosaic virus (CMV), on the quality and attractiveness of one of its host plants (Cucurbita pepo cv. Dixie) for two aphid vectors, Myzus persicae and Aphis gossypii. Our results indicate that CMV greatly reduces host-plant quality-aphids performed poorly on infected plants and rapidly emigrated from them-but increases the attractiveness of infected plants to aphids by inducing elevated emissions of a plant volatile blend otherwise similar to that emitted by healthy plants. Thus, CMV appears to attract vectors deceptively to infected plants from which they then disperse rapidly, a pattern highly conducive to the nonpersistent transmission mechanism employed by CMV and very different from the pattern previously reported for persistently transmitted viruses that require sustained aphid feeding for transmission. In addition to providing a documented example of a pathogen inducing a deceptive signal of host-plant quality to vectors, our results suggest that the transmission mechanism is a major factor shaping pathogen-induced changes in host-plant phenotypes. Furthermore, our findings yield a general hypothesis that, when vector-borne plant or animal pathogens reduce host quality for vectors, pathogen-induced changes in host phenotypes that enhance vector attraction frequently will involve the exaggeration of existing host-location cues.

Deceptive chemical signals induced by a plant virus attract insect vectors to inferior hosts

PubMed Central

Mauck, Kerry E.; De Moraes, Consuelo M.; Mescher, Mark C.

2010-01-01

Previous studies have shown that vector-borne pathogens can alter the phenotypes of their hosts and vectors in ways that influence the frequency and nature of interactions between them, with significant implications for the transmission and spread of disease. For insect-borne pathogens, host odors are particularly likely targets for manipulation, because both plant- and animal-feeding insects use volatile compounds derived from their hosts as key foraging cues. Here, we document the effects of a widespread plant pathogen, Cucumber mosaic virus (CMV), on the quality and attractiveness of one of its host plants (Cucurbita pepo cv. Dixie) for two aphid vectors, Myzus persicae and Aphis gossypii. Our results indicate that CMV greatly reduces host-plant quality—aphids performed poorly on infected plants and rapidly emigrated from them—but increases the attractiveness of infected plants to aphids by inducing elevated emissions of a plant volatile blend otherwise similar to that emitted by healthy plants. Thus, CMV appears to attract vectors deceptively to infected plants from which they then disperse rapidly, a pattern highly conducive to the nonpersistent transmission mechanism employed by CMV and very different from the pattern previously reported for persistently transmitted viruses that require sustained aphid feeding for transmission. In addition to providing a documented example of a pathogen inducing a deceptive signal of host-plant quality to vectors, our results suggest that the transmission mechanism is a major factor shaping pathogen-induced changes in host-plant phenotypes. Furthermore, our findings yield a general hypothesis that, when vector-borne plant or animal pathogens reduce host quality for vectors, pathogen-induced changes in host phenotypes that enhance vector attraction frequently will involve the exaggeration of existing host-location cues. PMID:20133719

Purification of adenoviral vectors by combined anion exchange and gel filtration chromatography.

PubMed

Eglon, Marc N; Duffy, Aoife M; O'Brien, Timothy; Strappe, Padraig M

2009-11-01

Adenoviral vectors are used extensively in human gene therapy trials and in vaccine development. Large-scale GMP production requires a downstream purification process, and liquid chromatography is emerging as the most powerful mode of purification, enabling the production of vectors at a clinically relevant scale and quality. The present study describes the development of a two-step high-performance liquid chromatography (HPLC) process combining anion exchange (AIEX) and gel filtration (GF) in comparison with the caesium chloride density gradient method. HEK-293 cells were cultured in ten-layer CellStacks() and infected with 10 pfu/cell of adenoviral vector expressing green fluorescent protein (Ad5-GFP). Cell-bound virus was harvested and benzonase added to digest DNA, crude lysate was clarified by centrifugation and filtration prior to HPLC. Chromatography fractions were added to HEK-293 cells and GFP expression measured using a fluorescent plate reader. Using AIEX then GF resulted in an adenoviral vector with purity comparable to Ad5-GFP purified by CsCl, whereas the reverse process (GF-AIEX) showed a reduced purity by electrophoresis and required further buffer exchange of the product. The optimal process (AIEX-GF) resulted in a vector yield of 2.3 x 10(7) pfu/cm(2) of cell culture harvested compared to 3.3 x 10(7) pfu/cm(2) for CsCl. The process recovery for the HPLC process was 36% compared to 27.5% for CsCl and total virion to infectious particle ratios of 18 and 11, respectively, were measured. We present a simple two-step chromatography process that is capable of producing high-quality adenovirus at a titre suitable for scale-up and clinical translation.

Attacking the mosquito on multiple fronts: Insights from the Vector Control Optimization Model (VCOM) for malaria elimination.

PubMed

Kiware, Samson S; Chitnis, Nakul; Tatarsky, Allison; Wu, Sean; Castellanos, Héctor Manuel Sánchez; Gosling, Roly; Smith, David; Marshall, John M

2017-01-01

Despite great achievements by insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in reducing malaria transmission, it is unlikely these tools will be sufficient to eliminate malaria transmission on their own in many settings today. Fortunately, field experiments indicate that there are many promising vector control interventions that can be used to complement ITNs and/or IRS by targeting a wide range of biological and environmental mosquito resources. The majority of these experiments were performed to test a single vector control intervention in isolation; however, there is growing evidence and consensus that effective vector control with the goal of malaria elimination will require a combination of interventions. We have developed a model of mosquito population dynamic to describe the mosquito life and feeding cycles and to optimize the impact of vector control intervention combinations at suppressing mosquito populations. The model simulations were performed for the main three malaria vectors in sub-Saharan Africa, Anopheles gambiae s.s, An. arabiensis and An. funestus. We considered areas having low, moderate and high malaria transmission, corresponding to entomological inoculation rates of 10, 50 and 100 infective bites per person per year, respectively. In all settings, we considered baseline ITN coverage of 50% or 80% in addition to a range of other vector control tools to interrupt malaria transmission. The model was used to sweep through parameters space to select the best optimal intervention packages. Sample model simulations indicate that, starting with ITNs at a coverage of 50% (An. gambiae s.s. and An. funestus) or 80% (An. arabiensis) and adding interventions that do not require human participation (e.g. larviciding at 80% coverage, endectocide treated cattle at 50% coverage and attractive toxic sugar baits at 50% coverage) may be sufficient to suppress all the three species to an extent required to achieve local malaria elimination. The Vector Control Optimization Model (VCOM) is a computational tool to predict the impact of combined vector control interventions at the mosquito population level in a range of eco-epidemiological settings. The model predicts specific combinations of vector control tools to achieve local malaria elimination in a range of eco-epidemiological settings and can assist researchers and program decision-makers on the design of experimental or operational research to test vector control interventions. A corresponding graphical user interface is available for national malaria control programs and other end users.

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

NASA Astrophysics Data System (ADS)

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.

A comparison of the performance of two types of inertial systems for strapdown airborne gravimetry

NASA Astrophysics Data System (ADS)

Deurloo, R. A.; Martin, J.; Bastos, M. L.; Becker, M. H.

2012-12-01

Over the past two decades so-called strapdown airborne gravimetry systems have proven to have the potential to compete with more traditional measurement systems such as modified spring gravimeters (e.g. LaCoste & Romberg Air-Sea gravimeters). Strapdown gravimetry systems rely on the integration of high-accuracy data from a GNSS (Global Navigation Satellite System) receiver and from a strapdown IMU (Inertial Measurement Unit). These GNSS/IMU integrated systems have the advantage of being less expensive and more compact, while being easier to use and install than spring gravimeters, which tend to be bulky and require specialized human resources for its operation. In the scope of a research project developed through the collaboration of the University of Porto and the Portuguese Air Force (PAF), an airborne survey was recently performed over the middle and southern area of Continental Portugal using a CASA C212 aircraft. The goal of this survey was to acquire data to assess the performance of different GNSS/IMU systems and associated processing approaches to determine the gravity field and evaluate their potential and effectiveness for airborne gravimetry using different types of airborne platforms, including UAVs (Unmanned Airborne Vehicles). Among the systems on board were a medium-quality (tactical grade) IMU with fiber-optic gyros (FOG), a Litton LN-200, and a high-quality (navigation grade) IMU with ring-laser gyros (RLG), an iMAR RHQ-1003, which are the focus of the present comparison. The advantage of using a strapdown airborne gravimetry system with high-quality inertial sensor is that it allows the complete gravity vector to be determined from the triads of accelerometers and gyros in the IMU (vector gravimetry). On the other hand a medium-quality inertial system is limited to determining only the magnitude of the gravity vector (scalar gravimetry). The limited quality of the gyros of the medium-quality inertial systems does not allow the horizontal components of the gravity vector to be determined. In spite of that, this type of system has been shown to still deliver very useful results in the range of a few mGal for resolutions below 10km. In this work we describe the setup used for our airborne test and we present a comparison and analysis of the performance of the medium- and high-quality inertial systems. This includes an analysis of the results of overlapping flight lines obtained with both systems. Considerations about the suitability of each of the systems for different types of applications are also discussed.

The New Self-Inactivating Lentiviral Vector for Thalassemia Gene Therapy Combining Two HPFH Activating Elements Corrects Human Thalassemic Hematopoietic Stem Cells

PubMed Central

Papanikolaou, Eleni; Georgomanoli, Maria; Stamateris, Evangelos; Panetsos, Fottes; Karagiorga, Markisia; Tsaftaridis, Panagiotis; Graphakos, Stelios

2012-01-01

Abstract To address how low titer, variable expression, and gene silencing affect gene therapy vectors for hemoglobinopathies, in a previous study we successfully used the HPFH (hereditary persistence of fetal hemoglobin)-2 enhancer in a series of oncoretroviral vectors. On the basis of these data, we generated a novel insulated self-inactivating (SIN) lentiviral vector, termed GGHI, carrying the Aγ-globin gene with the −117 HPFH point mutation and the HPFH-2 enhancer and exhibiting a pancellular pattern of Aγ-globin gene expression in MEL-585 clones. To assess the eventual clinical feasibility of this vector, GGHI was tested on CD34+ hematopoietic stem cells from nonmobilized peripheral blood or bone marrow from 20 patients with β-thalassemia. Our results show that GGHI increased the production of γ-globin by 32.9% as measured by high-performance liquid chromatography (p=0.001), with a mean vector copy number per cell of 1.1 and a mean transduction efficiency of 40.3%. Transduced populations also exhibited a lower rate of apoptosis and resulted in improvement of erythropoiesis with a higher percentage of orthochromatic erythroblasts. This is the first report of a locus control region (LCR)-free SIN insulated lentiviral vector that can be used to efficiently produce the anticipated therapeutic levels of γ-globin protein in the erythroid progeny of primary human thalassemic hematopoietic stem cells in vitro. PMID:21875313

SOLAR FLARE PREDICTION USING SDO/HMI VECTOR MAGNETIC FIELD DATA WITH A MACHINE-LEARNING ALGORITHM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bobra, M. G.; Couvidat, S., E-mail: couvidat@stanford.edu

2015-01-10

We attempt to forecast M- and X-class solar flares using a machine-learning algorithm, called support vector machine (SVM), and four years of data from the Solar Dynamics Observatory's Helioseismic and Magnetic Imager, the first instrument to continuously map the full-disk photospheric vector magnetic field from space. Most flare forecasting efforts described in the literature use either line-of-sight magnetograms or a relatively small number of ground-based vector magnetograms. This is the first time a large data set of vector magnetograms has been used to forecast solar flares. We build a catalog of flaring and non-flaring active regions sampled from a databasemore » of 2071 active regions, comprised of 1.5 million active region patches of vector magnetic field data, and characterize each active region by 25 parameters. We then train and test the machine-learning algorithm and we estimate its performances using forecast verification metrics with an emphasis on the true skill statistic (TSS). We obtain relatively high TSS scores and overall predictive abilities. We surmise that this is partly due to fine-tuning the SVM for this purpose and also to an advantageous set of features that can only be calculated from vector magnetic field data. We also apply a feature selection algorithm to determine which of our 25 features are useful for discriminating between flaring and non-flaring active regions and conclude that only a handful are needed for good predictive abilities.« less

A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.

PubMed

Chen, Zhenyu; Li, Jianping; Wei, Liwei

2007-10-01

Recently, gene expression profiling using microarray techniques has been shown as a promising tool to improve the diagnosis and treatment of cancer. Gene expression data contain high level of noise and the overwhelming number of genes relative to the number of available samples. It brings out a great challenge for machine learning and statistic techniques. Support vector machine (SVM) has been successfully used to classify gene expression data of cancer tissue. In the medical field, it is crucial to deliver the user a transparent decision process. How to explain the computed solutions and present the extracted knowledge becomes a main obstacle for SVM. A multiple kernel support vector machine (MK-SVM) scheme, consisting of feature selection, rule extraction and prediction modeling is proposed to improve the explanation capacity of SVM. In this scheme, we show that the feature selection problem can be translated into an ordinary multiple parameters learning problem. And a shrinkage approach: 1-norm based linear programming is proposed to obtain the sparse parameters and the corresponding selected features. We propose a novel rule extraction approach using the information provided by the separating hyperplane and support vectors to improve the generalization capacity and comprehensibility of rules and reduce the computational complexity. Two public gene expression datasets: leukemia dataset and colon tumor dataset are used to demonstrate the performance of this approach. Using the small number of selected genes, MK-SVM achieves encouraging classification accuracy: more than 90% for both two datasets. Moreover, very simple rules with linguist labels are extracted. The rule sets have high diagnostic power because of their good classification performance.

Clinical Protection of Goats against CpHV-1 Induced Genital Disease with a BoHV-4-Based Vector Expressing CpHV-1 gD

PubMed Central

Donofrio, Gaetano; Franceschi, Valentina; Lovero, Angela; Capocefalo, Antonio; Camero, Michele; Losurdo, Michele; Cavirani, Sandro; Marinaro, Mariarosaria; Grandolfo, Erika; Buonavoglia, Canio; Tempesta, Maria

2013-01-01

Caprine herpesvirus type 1 (CpHV-1) is an alphaherpesvirus causing genital disease leading to abortion in adult pregnant goats and a systemic disease with high morbility and mortality in kids. Further, Caprine herpesvirus 1 infection represents a valuable large animal model for human herpesvirus induced genital disease, exploitable for pathogenic studies, new vaccines and antiviral molecules testing. Here, the bovine herpesvirus 4 (BoHV-4) based vector derived from an apathogenic isolate of BoHV-4 and expressing the immunodominant CpHV-1 glycoprotein D (BoHV-4-A-gDcpgD106ΔTK) was constructed and its ability to protect goats against CpHV-1 induced genital disease evaluated. The subcutaneous route of recombinant BoHV-4 administration was first tested in vivo/ex vivo by in vivo image analysis and in vitro by goat skin primary cultures preparation and transduction. Next, an exploratory immunization and safety study in goats was performed with two recombinant BoHV4, BoHV-4-A-gDcpgD106ΔTK or BoHV-4-CMV-IgK-gE2gD-TM. In both cases no clinical signs were evident but a good titer of serum neutralizing antibodies was produced in all inoculated animals. When a challenge experiment was performed in a new group of animals using a highly pathogenic dose of CpHV-1, all the vaccinated goats with BoHV-4-A-gDcpgD106ΔTK were protected toward CpHV-1 induced genital disease respect to the unvaccinated control which showed typical vaginal lesions with a high grade of clinical score as well as a long lasting viral shedding. In summary, the data acquired in the present study validate BoHV-4-based vector as a safe and effective viral vector for goat vaccination against CpHV-1 induced genital disease and pave the way for further applications. PMID:23300989

Multiprocessing MCNP on an IBN RS/6000 cluster

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKinney, G.W.; West, J.T.

1993-01-01

The advent of high-performance computer systems has brought to maturity programming concepts like vectorization, multiprocessing, and multitasking. While there are many schools of thought as to the most significant factor in obtaining order-of-magnitude increases in performance, such speedup can only be achieved by integrating the computer system and application code. Vectorization leads to faster manipulation of arrays by overlapping instruction CPU cycles. Discrete ordinates codes, which require the solving of large matrices, have proved to be major benefactors of vectorization. Monte Carlo transport, on the other hand, typically contains numerous logic statements and requires extensive redevelopment to benefit from vectorization.more » Multiprocessing and multitasking provide additional CPU cycles via multiple processors. Such systems are generally designed with either common memory access (multitasking) or distributed memory access. In both cases, theoretical speedup, as a function of the number of processors P and the fraction f of task time that multiprocesses, can be formulated using Amdahl's law: S(f, P) =1/(1-f+f/P). However, for most applications, this theoretical limit cannot be achieved because of additional terms (e.g., multitasking overhead, memory overlap, etc.) that are not included in Amdahl's law. Monte Carlo transport is a natural candidate for multiprocessing because the particle tracks are generally independent, and the precision of the result increases as the square Foot of the number of particles tracked.« less

Multiprocessing MCNP on an IBM RS/6000 cluster

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKinney, G.W.; West, J.T.

1993-03-01

The advent of high-performance computer systems has brought to maturity programming concepts like vectorization, multiprocessing, and multitasking. While there are many schools of thought as to the most significant factor in obtaining order-of-magnitude increases in performance, such speedup can only be achieved by integrating the computer system and application code. Vectorization leads to faster manipulation of arrays by overlapping instruction CPU cycles. Discrete ordinates codes, which require the solving of large matrices, have proved to be major benefactors of vectorization. Monte Carlo transport, on the other hand, typically contains numerous logic statements and requires extensive redevelopment to benefit from vectorization.more » Multiprocessing and multitasking provide additional CPU cycles via multiple processors. Such systems are generally designed with either common memory access (multitasking) or distributed memory access. In both cases, theoretical speedup, as a function of the number of processors (P) and the fraction of task time that multiprocesses (f), can be formulated using Amdahl`s Law S ((f,P) = 1 f + f/P). However, for most applications this theoretical limit cannot be achieved, due to additional terms not included in Amdahl`s Law. Monte Carlo transport is a natural candidate for multiprocessing, since the particle tracks are generally independent and the precision of the result increases as the square root of the number of particles tracked.« less

Five-way smoking status classification using text hot-spot identification and error-correcting output codes.

PubMed

Cohen, Aaron M

2008-01-01

We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2b2 task organizers, using micro- and macro-averaged F1 as the primary performance metric. Our best performing system achieved a micro-F1 of 0.9000 on the test collection, equivalent to the best performing system submitted to the i2b2 challenge. Hot-spot identification, zero-vector filtering, classifier weighting, and error correcting output coding contributed additively to increased performance, with hot-spot identification having by far the largest positive effect. High performance on automatic identification of patient smoking status from discharge summaries is achievable with the efficient and straightforward machine learning techniques studied here.

Comparative field trial of alternative vector control strategies for non-domiciliated Triatoma dimidiata.

PubMed

Ferral, Jhibran; Chavez-Nuñez, Leysi; Euan-Garcia, Maria; Ramirez-Sierra, Maria Jesus; Najera-Vazquez, M Rosario; Dumonteil, Eric

2010-01-01

Chagas disease is a major vector-borne disease, and regional initiatives based on insecticide spraying have successfully controlled domiciliated vectors in many regions. Non-domiciliated vectors remain responsible for a significant transmission risk, and their control is a challenge. We performed a proof-of-concept field trial to test alternative strategies in rural Yucatan, Mexico. Follow-up of house infestation for two seasons following the interventions confirmed that insecticide spraying should be performed annually for the effective control of Triatoma dimidiata; however, it also confirmed that insect screens or long-lasting impregnated curtains may represent good alternative strategies for the sustained control of these vectors. Ecosystemic peridomicile management would be an excellent complementary strategy to improve the cost-effectiveness of interventions. Because these strategies would also be effective against other vector-borne diseases, such as malaria or dengue, they could be integrated within a multi-disease control program.

A k-Vector Approach to Sampling, Interpolation, and Approximation

NASA Astrophysics Data System (ADS)

Mortari, Daniele; Rogers, Jonathan

2013-12-01

The k-vector search technique is a method designed to perform extremely fast range searching of large databases at computational cost independent of the size of the database. k-vector search algorithms have historically found application in satellite star-tracker navigation systems which index very large star catalogues repeatedly in the process of attitude estimation. Recently, the k-vector search algorithm has been applied to numerous other problem areas including non-uniform random variate sampling, interpolation of 1-D or 2-D tables, nonlinear function inversion, and solution of systems of nonlinear equations. This paper presents algorithms in which the k-vector search technique is used to solve each of these problems in a computationally-efficient manner. In instances where these tasks must be performed repeatedly on a static (or nearly-static) data set, the proposed k-vector-based algorithms offer an extremely fast solution technique that outperforms standard methods.

A C++11 implementation of arbitrary-rank tensors for high-performance computing

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.

2014-06-01

This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

A C++11 implementation of arbitrary-rank tensors for high-performance computing

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.

2014-11-01

This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

Hybrid modelling based on support vector regression with genetic algorithms in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain).

PubMed

García Nieto, P J; Alonso Fernández, J R; de Cos Juez, F J; Sánchez Lasheras, F; Díaz Muñiz, C

2013-04-01

Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational waters. As a result, anticipate its presence is a matter of importance to prevent risks. The aim of this study is to use a hybrid approach based on support vector regression (SVR) in combination with genetic algorithms (GAs), known as a genetic algorithm support vector regression (GA-SVR) model, in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain). The GA-SVR approach is aimed at highly nonlinear biological problems with sharp peaks and the tests carried out proved its high performance. Some physical-chemical parameters have been considered along with the biological ones. The results obtained are two-fold. In the first place, the significance of each biological and physical-chemical variable on the cyanotoxins presence in the reservoir is determined with success. Finally, a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained. Copyright © 2013 Elsevier Inc. All rights reserved.

Variable Selection for Support Vector Machines in Moderately High Dimensions

PubMed Central

Zhang, Xiang; Wu, Yichao; Wang, Lan; Li, Runze

2015-01-01

Summary The support vector machine (SVM) is a powerful binary classification tool with high accuracy and great flexibility. It has achieved great success, but its performance can be seriously impaired if many redundant covariates are included. Some efforts have been devoted to studying variable selection for SVMs, but asymptotic properties, such as variable selection consistency, are largely unknown when the number of predictors diverges to infinity. In this work, we establish a unified theory for a general class of nonconvex penalized SVMs. We first prove that in ultra-high dimensions, there exists one local minimizer to the objective function of nonconvex penalized SVMs possessing the desired oracle property. We further address the problem of nonunique local minimizers by showing that the local linear approximation algorithm is guaranteed to converge to the oracle estimator even in the ultra-high dimensional setting if an appropriate initial estimator is available. This condition on initial estimator is verified to be automatically valid as long as the dimensions are moderately high. Numerical examples provide supportive evidence. PMID:26778916

Recombinant poxviruses as mucosal vaccine vectors.

PubMed

Gherardi, M Magdalena; Esteban, Mariano

2005-11-01

The majority of infections initiate their departure from a mucosal surface, such as Human immunodeficiency virus (HIV), a sexually transmitted virus. Therefore, the induction of mucosal immunity is a high priority in the development of vaccines against mucosal pathogens. The selection of an appropriate antigen delivery system is necessary to induce an efficient mucosal immune response. Poxvirus vectors have been the most intensively studied live recombinant vector, and numerous studies have demonstrated their ability to induce mucosal immune responses against foreign expressed antigens. Previous studies have demonstrated that recombinants based on the attenuated modified vaccinia virus Ankara (MVA) vector were effective in inducing protective responses against different respiratory viruses, such as influenza and respiratory syncytial virus, following immunization via mucosal routes. Recent studies performed in the murine and macaque models have shown that recombinant MVA (rMVA) does not only stimulate HIV-specific immunity in the genital and rectal tracts following mucosal delivery, but can also control simian/human immunodeficiency viraemia and disease progression. In addition, a prime-boost vaccination approach against tuberculosis emphasized the importance of the intranasal rMVA antigen delivery to induce protective immunity against Mycobacterium tuberculosis. The aim of this review is to summarize the studies employing recombinant poxviruses, specifically rMVA as a mucosal delivery vector. The results demonstrate that rMVAs can activate specific immune responses at mucosal surfaces, and encourage further studies to characterize and improve the MVA mucosal immunogenicity of poxvirus vectors.

A parallel-vector algorithm for rapid structural analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1990-01-01

A fast, accurate Choleski method for the solution of symmetric systems of linear equations is presented. This direct method is based on a variable-band storage scheme and takes advantage of column heights to reduce the number of operations in the Choleski factorization. The method employs parallel computation in the outermost DO-loop and vector computation via the 'loop unrolling' technique in the innermost DO-loop. The method avoids computations with zeros outside the column heights, and as an option, zeros inside the band. The close relationship between Choleski and Gauss elimination methods is examined. The minor changes required to convert the Choleski code to a Gauss code to solve non-positive-definite symmetric systems of equations are identified. The results for two large-scale structural analyses performed on supercomputers, demonstrate the accuracy and speed of the method.

A parallel-vector algorithm for rapid structural analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1990-01-01

A fast, accurate Choleski method for the solution of symmetric systems of linear equations is presented. This direct method is based on a variable-band storage scheme and takes advantage of column heights to reduce the number of operations in the Choleski factorization. The method employs parallel computation in the outermost DO-loop and vector computation via the loop unrolling technique in the innermost DO-loop. The method avoids computations with zeros outside the column heights, and as an option, zeros inside the band. The close relationship between Choleski and Gauss elimination methods is examined. The minor changes required to convert the Choleski code to a Gauss code to solve non-positive-definite symmetric systems of equations are identified. The results for two large scale structural analyses performed on supercomputers, demonstrate the accuracy and speed of the method.

Modeling and Prediction of Solvent Effect on Human Skin Permeability using Support Vector Regression and Random Forest.

PubMed

Baba, Hiromi; Takahara, Jun-ichi; Yamashita, Fumiyoshi; Hashida, Mitsuru

2015-11-01

The solvent effect on skin permeability is important for assessing the effectiveness and toxicological risk of new dermatological formulations in pharmaceuticals and cosmetics development. The solvent effect occurs by diverse mechanisms, which could be elucidated by efficient and reliable prediction models. However, such prediction models have been hampered by the small variety of permeants and mixture components archived in databases and by low predictive performance. Here, we propose a solution to both problems. We first compiled a novel large database of 412 samples from 261 structurally diverse permeants and 31 solvents reported in the literature. The data were carefully screened to ensure their collection under consistent experimental conditions. To construct a high-performance predictive model, we then applied support vector regression (SVR) and random forest (RF) with greedy stepwise descriptor selection to our database. The models were internally and externally validated. The SVR achieved higher performance statistics than RF. The (externally validated) determination coefficient, root mean square error, and mean absolute error of SVR were 0.899, 0.351, and 0.268, respectively. Moreover, because all descriptors are fully computational, our method can predict as-yet unsynthesized compounds. Our high-performance prediction model offers an attractive alternative to permeability experiments for pharmaceutical and cosmetic candidate screening and optimizing skin-permeable topical formulations.

The role of computer-aided 3D surgery and stereolithographic modelling for vector orientation in premaxillary and trans-sinusoidal maxillary distraction osteogenesis.

PubMed

Varol, Altan; Basa, Selçuk

2009-06-01

Maxillary distraction osteogenesis is a challenging procedure when it is performed with internal submerged distractors due to obligation of setting accurate distraction vectors. Five patients with severe maxillary retrognathy were planned with Mimics 10.01 CMF and Simplant 10.01 software. Distraction vectors and rods of distractors were arranged in 3D environment and on STL models. All patients were operated under general anaesthesia and complete Le Fort I downfracture was performed. All distractions were performed according to orientated vectors. All patients achieved stable occlusion and satisfactory aesthetic outcome at the end of the treatment period. Preoperative bending of internal maxillary distractors prevents significant loss of operation time. 3D computer-aided surgical simulation and model surgery provide accurate orientation of distraction vectors for premaxillary and internal trans-sinusoidal maxillary distraction. Combination of virtual surgical simulation and stereolithographic models surgery can be validated as an effective method of preoperative planning for complicated maxillofacial surgery cases.

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.

PubMed

An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Fang, Yu-Hong; Zhao, Yu-Jun; Zhang, Ming

2016-01-01

We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

Prediction of Spirometric Forced Expiratory Volume (FEV1) Data Using Support Vector Regression

NASA Astrophysics Data System (ADS)

Kavitha, A.; Sujatha, C. M.; Ramakrishnan, S.

2010-01-01

In this work, prediction of forced expiratory volume in 1 second (FEV1) in pulmonary function test is carried out using the spirometer and support vector regression analysis. Pulmonary function data are measured with flow volume spirometer from volunteers (N=175) using a standard data acquisition protocol. The acquired data are then used to predict FEV1. Support vector machines with polynomial kernel function with four different orders were employed to predict the values of FEV1. The performance is evaluated by computing the average prediction accuracy for normal and abnormal cases. Results show that support vector machines are capable of predicting FEV1 in both normal and abnormal cases and the average prediction accuracy for normal subjects was higher than that of abnormal subjects. Accuracy in prediction was found to be high for a regularization constant of C=10. Since FEV1 is the most significant parameter in the analysis of spirometric data, it appears that this method of assessment is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording.

A Family of LIC Vectors for High-Throughput Cloning and Purification of Proteins1

PubMed Central

Eschenfeldt, William H.; Stols, Lucy; Millard, Cynthia Sanville; Joachimiak, Andrzej; Donnelly, Mark I.

2009-01-01

Summary Fifteen related ligation-independent cloning vectors were constructed for high-throughput cloning and purification of proteins. The vectors encode a TEV protease site for removal of tags that facilitate protein purification (his-tag) or improve solubility (MBP, GST). Specialized vectors allow coexpression and copurification of interacting proteins, or in vivo removal of MBP by TVMV protease to improve screening and purification. All target genes and vectors are processed by the same protocols, which we describe here. PMID:18988021

Learning atoms for materials discovery.

PubMed

Zhou, Quan; Tang, Peizhe; Liu, Shenxiu; Pan, Jinbo; Yan, Qimin; Zhang, Shou-Cheng

2018-06-26

Exciting advances have been made in artificial intelligence (AI) during recent decades. Among them, applications of machine learning (ML) and deep learning techniques brought human-competitive performances in various tasks of fields, including image recognition, speech recognition, and natural language understanding. Even in Go, the ancient game of profound complexity, the AI player has already beat human world champions convincingly with and without learning from the human. In this work, we show that our unsupervised machines (Atom2Vec) can learn the basic properties of atoms by themselves from the extensive database of known compounds and materials. These learned properties are represented in terms of high-dimensional vectors, and clustering of atoms in vector space classifies them into meaningful groups consistent with human knowledge. We use the atom vectors as basic input units for neural networks and other ML models designed and trained to predict materials properties, which demonstrate significant accuracy. Copyright © 2018 the Author(s). Published by PNAS.

Electromechanical actuation for thrust vector control applications

NASA Technical Reports Server (NTRS)

Roth, Mary Ellen

1990-01-01

The advanced launch system (ALS), is a launch vehicle that is designed to be cost-effective, highly reliable, and operationally efficient with a goal of reducing the cost per pound to orbit. An electromechanical actuation (EMA) system is being developed as an attractive alternative to the hydraulic systems. The controller will integrate 20 kHz resonant link power management and distribution (PMAD) technology and pulse population modulation (PPM) techniques to implement field-oriented vector control (FOVC) of a new advanced induction motor. The driver and the FOVC will be microprocessor controlled. For increased system reliability, a built-in test (BITE) capability will be included. This involves introducing testability into the design of a system such that testing is calibrated and exercised during the design, manufacturing, maintenance, and prelaunch activities. An actuator will be integrated with the motor controller for performance testing of the EMA thrust vector control (TVC) system. The EMA system and work proposed for the future are discussed.

Poynting Vector in High-Temperature Superconducting Transformers with a Separate Excitation Winding

NASA Astrophysics Data System (ADS)

Volkov, E. P.; Dzhafarov, E. A.

2017-12-01

The HTSC transformer with a separate winding for excitation of the mutual magnetic flux is considered; the windings of the transformer are performed of first- or second-generation HTSC wires. The article presents the design and the electrical circuit of the transformer, the equations of electromagnetic balance, and the total resistance of the primary and secondary power windings and the separate excitation winding. The transfer of the electromagnetic field energy is considered in a single-phase HTSC transformer with the separate excitation winding using the Poynting vector. The temporal change in the reactive and active components of the Poynting vector and the decrease in the leakage energy flux of the separate excitation winding are shown, which causes an increase in the critical current density of the HTSC power windings, a decrease in the energy losses in the latter, and an increase the in the specific power of the HTSC transformer.

Vectorization with SIMD extensions speeds up reconstruction in electron tomography.

PubMed

Agulleiro, J I; Garzón, E M; García, I; Fernández, J J

2010-06-01

Electron tomography allows structural studies of cellular structures at molecular detail. Large 3D reconstructions are needed to meet the resolution requirements. The processing time to compute these large volumes may be considerable and so, high performance computing techniques have been used traditionally. This work presents a vector approach to tomographic reconstruction that relies on the exploitation of the SIMD extensions available in modern processors in combination to other single processor optimization techniques. This approach succeeds in producing full resolution tomograms with an important reduction in processing time, as evaluated with the most common reconstruction algorithms, namely WBP and SIRT. The main advantage stems from the fact that this approach is to be run on standard computers without the need of specialized hardware, which facilitates the development, use and management of programs. Future trends in processor design open excellent opportunities for vector processing with processor's SIMD extensions in the field of 3D electron microscopy.

Internet-based biosurveillance methods for vector-borne diseases: Are they novel public health tools or just novelties?

PubMed

Pollett, Simon; Althouse, Benjamin M; Forshey, Brett; Rutherford, George W; Jarman, Richard G

2017-11-01

Internet-based surveillance methods for vector-borne diseases (VBDs) using "big data" sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such "digital disease detection" methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of "digital epidemiology." We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD.

Internet-based biosurveillance methods for vector-borne diseases: Are they novel public health tools or just novelties?

PubMed Central

Pollett, Simon; Althouse, Benjamin M.; Forshey, Brett; Rutherford, George W.; Jarman, Richard G.

2017-01-01

Internet-based surveillance methods for vector-borne diseases (VBDs) using “big data” sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such “digital disease detection” methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of “digital epidemiology.” We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD. PMID:29190281

Pseudo-Linear Attitude Determination of Spinning Spacecraft

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Harman, Richard R.

2004-01-01

This paper presents the overall mathematical model and results from pseudo linear recursive estimators of attitude and rate for a spinning spacecraft. The measurements considered are vector measurements obtained by sun-sensors, fixed head star trackers, horizon sensors, and three axis magnetometers. Two filters are proposed for estimating the attitude as well as the angular rate vector. One filter, called the q-Filter, yields the attitude estimate as a quaternion estimate, and the other filter, called the D-Filter, yields the estimated direction cosine matrix. Because the spacecraft is gyro-less, Euler s equation of angular motion of rigid bodies is used to enable the estimation of the angular velocity. A simpler Markov model is suggested as a replacement for Euler's equation in the case where the vector measurements are obtained at high rates relative to the spacecraft angular rate. The performance of the two filters is examined using simulated data.

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

NASA Astrophysics Data System (ADS)

Sheng, Hanlin; Zhang, Tianhong

2017-08-01

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

Using domain decomposition in the multigrid NAS parallel benchmark on the Fujitsu VPP500

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, J.C.H.; Lung, H.; Katsumata, Y.

1995-12-01

In this paper, we demonstrate how domain decomposition can be applied to the multigrid algorithm to convert the code for MPP architectures. We also discuss the performance and scalability of this implementation on the new product line of Fujitsu`s vector parallel computer, VPP500. This computer has Fujitsu`s well-known vector processor as the PE each rated at 1.6 C FLOPS. The high speed crossbar network rated at 800 MB/s provides the inter-PE communication. The results show that the physical domain decomposition is the best way to solve MG problems on VPP500.

Gallium Arsenide Pilot Line for High Performance Components

DTIC Science & Technology

1988-06-02

shown in Figure 4. A complete functional and timing verification was performed by GOALIE , MOTIS, and ADVICE tools. GOALIE was used to convert the...using LTX2 and was verified using GOALIE , and ADVICE. S The performance of the circuits was measured using 256 test-vectors on an Advantest T3340...cycling per MIL STD 883C, Method 1010.7 Condition C. No evidence of damage was found. A sample of fifteen leads were pull tested per MIL STD 883C. Method

Vector quantizer designs for joint compression and terrain categorization of multispectral imagery

NASA Technical Reports Server (NTRS)

Gorman, John D.; Lyons, Daniel F.

1994-01-01

Two vector quantizer designs for compression of multispectral imagery and their impact on terrain categorization performance are evaluated. The mean-squared error (MSE) and classification performance of the two quantizers are compared, and it is shown that a simple two-stage design minimizing MSE subject to a constraint on classification performance has a significantly better classification performance than a standard MSE-based tree-structured vector quantizer followed by maximum likelihood classification. This improvement in classification performance is obtained with minimal loss in MSE performance. The results show that it is advantageous to tailor compression algorithm designs to the required data exploitation tasks. Applications of joint compression/classification include compression for the archival or transmission of Landsat imagery that is later used for land utility surveys and/or radiometric analysis.

Development of a Multiple Input Integrated Pole-to-Pole Global CMORPH

NASA Astrophysics Data System (ADS)

Joyce, R.; Xie, P.

2013-12-01

A test system is being developed at NOAA Climate Prediction Center (CPC) to produce a passive microwave (PMW), IR-based, and model integrated high-resolution precipitation estimation on a 0.05olat/lon grid covering the entire globe from pole to pole. Experiments have been conducted for a summer Test Bed period using data for July and August of 2009. The pole-to-pole global CMORPH system is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). First, retrievals of instantaneous precipitation rates from PMW observations aboard nine low earth orbit (LEO) satellites are decoded and pole-to-pole mapped onto a 0.05olat/lon grid over the globe. Also precipitation estimates from LEO AVHRR retrievals are derived using a PDF matching of LEO IR with calibrated microwave combined (MWCOMB) precipitation retrievals. The motion vectors for the precipitating cloud systems are defined using information from both satellite IR observations and precipitation fields generated by the NCEP Climate Forecast System Reanalysis (CFSR). To this end, motion vectors are first computed for the CFSR hourly precipitation fields through cross-correlation analysis of consecutive hourly precipitation fields on the global T382 (~35 km) grid. In a similar manner, separate processing is also performed on satellite IR-based precipitation estimates to derive motion vectors from observations. A blended analysis of precipitating cloud motion vectors is then constructed through the combination of CFSR and satellite-derived vectors utilizing a two-dimensional optimal interpolation (2D-OI) method, in which CFSR-derived motion vectors are used as the first guess and subsequently satellite derived vectors modify the first guess. Weights used to generate the combinations are defined under the OI framework as a function of error statistics for the CFSR and satellite IR based motion vectors. The screened and calibrated PMW and AVHRR derived precipitation estimates are then separately spatially propagated forward and backward in time, using precipitating cloud motion vectors, from their observation time to the next PMW observation. The PMW estimates propagated in both the forward and backward directions are then combined with propagated IR-based precipitation estimates under the Kalman Filter framework, with weights defined based on previously determined error statistics dependent on latitude, season, surface type, and temporal distance from observation time. Performance of the pole-to-pole global CMORPH and its key components, including combined PMW (MWCOMB), IR-based, and model precipitation, as well as model-derived, IR-based, and blended precipitation motion vectors, will be examined against NSSL Q2 radar observed precipitation estimates over CONUS, Finland FMI radar precipitation, and a daily gauge-based analysis including daily Canadian surface reports over global land. Also an initial investigation will be performed over a January - February 2010 winter Test Bed period. Detailed results will be reported at the Fall 2013 AGU Meeting.

Performance Improvements of the Phoneme Recognition Algorithm.

DTIC Science & Technology

1984-06-01

VECTOR NUNDIRt"tIVECTj Beginning vector ; of speech to be extracted INDEX * MOD(IVECT,4) ICheck for vector being ; last vector in block 63 ILE u ((JUICT...1fIER0) ; Read header block. CALL CHECK(IERO) IHEADER(57) : ICOfP ; Change a of freq. components ICHECK : (IHEADER(56) - ([LENGTH - 1)) * ILENGTH...ICONT .Al. ICHECK ) GO TO 55 ; Check to make sure correct ;amount of vectors have been created# INCR u INCR + 32 ;Jump over last set of components

Impact of community-based vector control on house infestation and Trypanosoma cruzi infection in Triatoma infestans, dogs and cats in the Argentine Chaco.

PubMed

Cardinal, M V; Lauricella, M A; Marcet, P L; Orozco, M M; Kitron, U; Gürtler, R E

2007-09-01

The relative impact of two community-based vector control strategies on house infestation by Triatoma infestans and Trypanosoma cruzi infection in bugs, domestic dogs and cats was assessed in two neighboring rural areas comprising 40 small villages and 323 houses in one of the regions most endemic for Chagas disease in northern Argentina. The prevalence and abundance of domestic infestation were 1.5- and 6.5-fold higher, respectively, in the area under pulsed, non-supervised control actions operating under the guidelines of the National Vector Control Program (NCVP) than in the area under sustained, supervised surveillance carried out jointly by the UBA research team and NCVP. The prevalence of infestation and infection varied widely among village groups within each area. In the pulsed control area, the prevalence of infection in bugs, dogs and cats was two- to three-fold higher than in the area under sustained surveillance, most of the infected animals qualified as autochthonous cases, and evidence of recent transmission was observed. Infection was highly aggregated at the household level and fell close to the 80/20 rule. Using multiple logistic regression analysis clustered by household, infection in dogs was associated positively and significantly with variables reflecting local exposure to infected T. infestans, thus demonstrating weak performance of the vector surveillance system. For high-risk areas in the Gran Chaco region, interruption of vector-mediated domestic transmission of T. cruzi requires residual insecticide spraying that is more intense, of a higher quality and sustained in time, combined with community participation and environmental management measures.

A performance comparison of scalar, vector, and concurrent vector computers including supercomputers for modeling transport of reactive contaminants in groundwater

NASA Astrophysics Data System (ADS)

Tripathi, Vijay S.; Yeh, G. T.

1993-06-01

Sophisticated and highly computation-intensive models of transport of reactive contaminants in groundwater have been developed in recent years. Application of such models to real-world contaminant transport problems, e.g., simulation of groundwater transport of 10-15 chemically reactive elements (e.g., toxic metals) and relevant complexes and minerals in two and three dimensions over a distance of several hundred meters, requires high-performance computers including supercomputers. Although not widely recognized as such, the computational complexity and demand of these models compare with well-known computation-intensive applications including weather forecasting and quantum chemical calculations. A survey of the performance of a variety of available hardware, as measured by the run times for a reactive transport model HYDROGEOCHEM, showed that while supercomputers provide the fastest execution times for such problems, relatively low-cost reduced instruction set computer (RISC) based scalar computers provide the best performance-to-price ratio. Because supercomputers like the Cray X-MP are inherently multiuser resources, often the RISC computers also provide much better turnaround times. Furthermore, RISC-based workstations provide the best platforms for "visualization" of groundwater flow and contaminant plumes. The most notable result, however, is that current workstations costing less than $10,000 provide performance within a factor of 5 of a Cray X-MP.

Method for indexing and retrieving manufacturing-specific digital imagery based on image content

DOEpatents

Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

2004-06-15

A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

A Nearest Neighbor Classifier Employing Critical Boundary Vectors for Efficient On-Chip Template Reduction.

PubMed

Xia, Wenjun; Mita, Yoshio; Shibata, Tadashi

2016-05-01

Aiming at efficient data condensation and improving accuracy, this paper presents a hardware-friendly template reduction (TR) method for the nearest neighbor (NN) classifiers by introducing the concept of critical boundary vectors. A hardware system is also implemented to demonstrate the feasibility of using an field-programmable gate array (FPGA) to accelerate the proposed method. Initially, k -means centers are used as substitutes for the entire template set. Then, to enhance the classification performance, critical boundary vectors are selected by a novel learning algorithm, which is completed within a single iteration. Moreover, to remove noisy boundary vectors that can mislead the classification in a generalized manner, a global categorization scheme has been explored and applied to the algorithm. The global characterization automatically categorizes each classification problem and rapidly selects the boundary vectors according to the nature of the problem. Finally, only critical boundary vectors and k -means centers are used as the new template set for classification. Experimental results for 24 data sets show that the proposed algorithm can effectively reduce the number of template vectors for classification with a high learning speed. At the same time, it improves the accuracy by an average of 2.17% compared with the traditional NN classifiers and also shows greater accuracy than seven other TR methods. We have shown the feasibility of using a proof-of-concept FPGA system of 256 64-D vectors to accelerate the proposed method on hardware. At a 50-MHz clock frequency, the proposed system achieves a 3.86 times higher learning speed than on a 3.4-GHz PC, while consuming only 1% of the power of that used by the PC.

Anisotropic responses and initial decomposition of condensed-phase β-HMX under shock loadings via molecular dynamics simulations in conjunction with multiscale shock technique.

PubMed

Ge, Ni-Na; Wei, Yong-Kai; Song, Zhen-Fei; Chen, Xiang-Rong; Ji, Guang-Fu; Zhao, Feng; Wei, Dong-Qing

2014-07-24

Molecular dynamics simulations in conjunction with multiscale shock technique (MSST) are performed to study the initial chemical processes and the anisotropy of shock sensitivity of the condensed-phase HMX under shock loadings applied along the a, b, and c lattice vectors. A self-consistent charge density-functional tight-binding (SCC-DFTB) method was employed. Our results show that there is a difference between lattice vector a (or c) and lattice vector b in the response to a shock wave velocity of 11 km/s, which is investigated through reaction temperature and relative sliding rate between adjacent slipping planes. The response along lattice vectors a and c are similar to each other, whose reaction temperature is up to 7000 K, but quite different along lattice vector b, whose reaction temperature is only up to 4000 K. When compared with shock wave propagation along the lattice vectors a (18 Å/ps) and c (21 Å/ps), the relative sliding rate between adjacent slipping planes along lattice vector b is only 0.2 Å/ps. Thus, the small relative sliding rate between adjacent slipping planes results in the temperature and energy under shock loading increasing at a slower rate, which is the main reason leading to less sensitivity under shock wave compression along lattice vector b. In addition, the C-H bond dissociation is the primary pathway for HMX decomposition in early stages under high shock loading from various directions. Compared with the observation for shock velocities V(imp) = 10 and 11 km/s, the homolytic cleavage of N-NO2 bond was obviously suppressed with increasing pressure.

Novel Gyroscopic Mounting for Crystal Oscillators to Increase Short and Medium Term Stability under Highly Dynamic Conditions.

PubMed

Abedi, Maryam; Jin, Tian; Sun, Kewen

2015-06-17

In this paper, a gyroscopic mounting method for crystal oscillators to reduce the impact of dynamic loads on their output stability has been proposed. In order to prove the efficiency of this mounting approach, each dynamic load-induced instability has been analyzed in detail. A statistical study has been performed on the elevation angle of the g-sensitivity vector of Stress Compensated-cut (SC-cut) crystals. The analysis results show that the proposed gyroscopic mounting method gives good performance for host vehicle attitude changes. A phase noise improvement of 27 dB maximum and 5.7 dB on average can be achieved in the case of steady state loads, while under sinusoidal vibration conditions, the maximum and average phase noise improvement are as high as 24 dB and 7.5 dB respectively. With this gyroscopic mounting method, random vibration-induced phase noise instability is reduced 30 dB maximum and 8.7 dB on average. Good effects are apparent for crystal g-sensitivity vectors with low elevation angle φ and azimuthal angle β. under highly dynamic conditions, indicating the probability that crystal oscillator instability will be significantly reduced by using the proposed mounting approach.

Support-vector-based emergent self-organising approach for emotional understanding

NASA Astrophysics Data System (ADS)

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.

Enhanced gene transfection performance and biocompatibility of polyethylenimine through pseudopolyrotaxane formation with α-cyclodextrin.

PubMed

Hu, Li-Zhong; Wan, Ning; Ma, Xi-Xi; Jing, Zi-Wei; Zhang, Ya-Xuan; Li, Chen; Zhou, Si-Yuan; Zhang, Bang-Le

2017-03-24

Polyethylenimine (PEI), a commercially available gene transfection reagent, is a promising nonviral vector due to its inherent ability to efficiently condense genetic materials and its successful transfection performance in vitro. However, its low transfection efficiency in vivo, along with its high cytotoxicity, limit any further applications in gene therapy. To enhance the gene transfection performance and reduce the cytotoxicity of linear polyethylenimine, pseudopolyrotaxane PEI25k/CD and the polyrotaxanes PEI25k/CD-PA and PEI25k/CD-PB were prepared and their transfection efficiencies were then evaluated. The pseudopolyrotaxane PEI25k/CD exhibited better transfection efficiency and lower cytotoxicity than the transfection reagent linear PEI25k, even in the presence of serum. It also showed a remarkably higher cell viability, similar DNA protecting capability, and better DNA decondensation and release ability, and could be useful for the development of novel and safe nonviral gene delivery vectors for gene therapy.

Iterative-method performance evaluation for multiple vectors associated with a large-scale sparse matrix

NASA Astrophysics Data System (ADS)

Imamura, Seigo; Ono, Kenji; Yokokawa, Mitsuo

2016-07-01

Ensemble computing, which is an instance of capacity computing, is an effective computing scenario for exascale parallel supercomputers. In ensemble computing, there are multiple linear systems associated with a common coefficient matrix. We improve the performance of iterative solvers for multiple vectors by solving them at the same time, that is, by solving for the product of the matrices. We implemented several iterative methods and compared their performance. The maximum performance on Sparc VIIIfx was 7.6 times higher than that of a naïve implementation. Finally, to deal with the different convergence processes of linear systems, we introduced a control method to eliminate the calculation of already converged vectors.

Method and apparatus for optimized processing of sparse matrices

DOEpatents

Taylor, Valerie E.

1993-01-01

A computer architecture for processing a sparse matrix is disclosed. The apparatus stores a value-row vector corresponding to nonzero values of a sparse matrix. Each of the nonzero values is located at a defined row and column position in the matrix. The value-row vector includes a first vector including nonzero values and delimiting characters indicating a transition from one column to another. The value-row vector also includes a second vector which defines row position values in the matrix corresponding to the nonzero values in the first vector and column position values in the matrix corresponding to the column position of the nonzero values in the first vector. The architecture also includes a circuit for detecting a special character within the value-row vector. Matrix-vector multiplication is executed on the value-row vector. This multiplication is performed by multiplying an index value of the first vector value by a column value from a second matrix to form a matrix-vector product which is added to a previous matrix-vector product.

Static investigation of two STOL nozzle concepts with pitch thrust-vectoring capability

NASA Technical Reports Server (NTRS)

Mason, M. L.; Burley, J. R., II

1986-01-01

A static investigation of the internal performance of two short take-off and landing (STOL) nozzle concepts with pitch thrust-vectoring capability has been conducted. An axisymmetric nozzle concept and a nonaxisymmetric nozzle concept were tested at dry and afterburning power settings. The axisymmetric concept consisted of a circular approach duct with a convergent-divergent nozzle. Pitch thrust vectoring was accomplished by vectoring the approach duct without changing the nozzle geometry. The nonaxisymmetric concept consisted of a two dimensional convergent-divergent nozzle. Pitch thrust vectoring was implemented by blocking the nozzle exit and deflecting a door in the lower nozzle flap. The test nozzle pressure ratio was varied up to 10.0, depending on model geometry. Results indicate that both pitch vectoring concepts produced resultant pitch vector angles which were nearly equal to the geometric pitch deflection angles. The axisymmetric nozzle concept had only small thrust losses at the largest pitch deflection angle of 70 deg., but the two-dimensional convergent-divergent nozzle concept had large performance losses at both of the two pitch deflection angles tested, 60 deg. and 70 deg.

Simulation and Assessment of a Ku-Band Full-Polarized Radar Scatterometer for Ocean Surface Vector Wind Measurement

NASA Astrophysics Data System (ADS)

Dong, X.; Lin, W.; Zhu, D.; Song, Z.

2011-12-01

Spaceborne radar scatterometry is the most important tool for global ocean surface wind vector (OSVW) measurement. Performances under condition of high-wind speed and accuracy of wind direction retrievals are two very important concerns for the development of OSVW measurement techniques by radar scatterometry. Co-polarized sigma 0 measurements are employed, for all the spaceborne radar scatterometers developed in past, and future planned missions. The main disadvantages of co-polarized only radar scatterometers for OSVW measurement are: firstly, wind vector retrieval performances varies with the position of the wind vector cells (WVC) within the swath, where WVCs with small incident angels with weaker modulation effect between sigma0 and azimuth incident angle, and the WVCs located in the outer part of the swath with lower signal-to-noise ratio and lower radiometric accuracies, have worse retrieval performances; secondly, for co-polarization measurements, Sigma 0 is the even function of the azimuth incident angle with respect to the real wind direction, which can results in directional ambiguity, and more additional information is need for the ambiguity removal. Theoretical and experimental results show that the cross-polarization measurement can provide complementary directional information to the co-polarization measurements, which can provide useful improvement to the wind vector retrieval performances. In this paper, the simulation and performance assessment of a full-polarized Ku-band radar scatterometer are provided. Some important conclusions are obtained: (1) Compared with available dual co-polarized radar scatterometer, the introduction of cross-polarization information can significantly improve the OSVW retrieval accuracies, where a relatively identical performance can be obtained within the whole swath. Simulation show that without significantly power increase, system design based on rotating-pencil beam design has much better performances than rotation fan-beam system due to its higher antenna gain and signal-to-noise ratio; (2) The performances of the full-polarized measurement, where all the 9 element covariant coefficient elements will be measurement, only have a little improvement compared with the "dual-co-polarization+HVVV" design, which is because of the almost identical characteristics of HVVV and VHHH measurement due to reciprocity; (3) The propagation error of rotation pencil-beam system is obviously much smaller than that of the rotation fan-beam system, which is due to the significant difference of antenna gains and signal-to-noise ratios; (4) Introduction of cross-polarized HVVV measurement can lead to almost identical wind direction retrieval performance for both the rotation pencil-beam and rotation fan-beam systems, which show that the cross-polarization information can significantly improve the wind direction retrieval performances by increasing the number of look angles, compared with the available fixed-fan-beam systems.

Virulence Factors of Geminivirus Interact with MYC2 to Subvert Plant Resistance and Promote Vector Performance[C][W

PubMed Central

Li, Ran; Weldegergis, Berhane T.; Li, Jie; Jung, Choonkyun; Qu, Jing; Sun, Yanwei; Qian, Hongmei; Tee, ChuanSia; van Loon, Joop J.A.; Dicke, Marcel; Chua, Nam-Hai; Liu, Shu-Sheng

2014-01-01

A pathogen may cause infected plants to promote the performance of its transmitting vector, which accelerates the spread of the pathogen. This positive effect of a pathogen on its vector via their shared host plant is termed indirect mutualism. For example, terpene biosynthesis is suppressed in begomovirus-infected plants, leading to reduced plant resistance and enhanced performance of the whiteflies (Bemisia tabaci) that transmit these viruses. Although begomovirus-whitefly mutualism has been known, the underlying mechanism is still elusive. Here, we identified βC1 of Tomato yellow leaf curl China virus, a monopartite begomovirus, as the viral genetic factor that suppresses plant terpene biosynthesis. βC1 directly interacts with the basic helix-loop-helix transcription factor MYC2 to compromise the activation of MYC2-regulated terpene synthase genes, thereby reducing whitefly resistance. MYC2 associates with the bipartite begomoviral protein BV1, suggesting that MYC2 is an evolutionarily conserved target of begomoviruses for the suppression of terpene-based resistance and the promotion of vector performance. Our findings describe how this viral pathogen regulates host plant metabolism to establish mutualism with its insect vector. PMID:25490915

Static Thrust and Vectoring Performance of a Spherical Convergent Flap Nozzle with a Nonrectangular Divergent Duct

NASA Technical Reports Server (NTRS)

Wing, David J.

1998-01-01

The static internal performance of a multiaxis-thrust-vectoring, spherical convergent flap (SCF) nozzle with a non-rectangular divergent duct was obtained in the model preparation area of the Langley 16-Foot Transonic Tunnel. Duct cross sections of hexagonal and bowtie shapes were tested. Additional geometric parameters included throat area (power setting), pitch flap deflection angle, and yaw gimbal angle. Nozzle pressure ratio was varied from 2 to 12 for dry power configurations and from 2 to 6 for afterburning power configurations. Approximately a 1-percent loss in thrust efficiency from SCF nozzles with a rectangular divergent duct was incurred as a result of internal oblique shocks in the flow field. The internal oblique shocks were the result of cross flow generated by the vee-shaped geometric throat. The hexagonal and bowtie nozzles had mirror-imaged flow fields and therefore similar thrust performance. Thrust vectoring was not hampered by the three-dimensional internal geometry of the nozzles. Flow visualization indicates pitch thrust-vector angles larger than 10' may be achievable with minimal adverse effect on or a possible gain in resultant thrust efficiency as compared with the performance at a pitch thrust-vector angle of 10 deg.

Efficacy and safety of a clinically relevant foamy vector design in human hematopoietic repopulating cells.

PubMed

Everson, Elizabeth M; Hocum, Jonah D; Trobridge, Grant D

2018-06-23

Previous studies have shown that foamy viral (FV) vectors are a promising alternative to gammaretroviral and lentiviral vectors and insulators can improve FV vector safety. However, in a previous analysis of insulator effects on FV vector safety, strong viral promoters were used to elicit genotoxic events. Here we developed and analyzed the efficacy and safety of a high-titer, clinically relevant FV vector driven by the housekeeping promoter elongation factor-1α and insulated with an enhancer blocking A1 insulator (FV-EGW-A1). Human CD34 + cord blood cells were exposed to an enhanced green fluorescent protein expressing vector, FV-EGW-A1, at a multiplicity of infection of 10 and then maintained in vitro or transplanted into immunodeficient mice. Flow cytometry was used to measure engraftment and marking in vivo. FV vector integration sites were analyzed to assess safety. FV-EGW-A1 resulted in high-marking, multi-lineage engraftment of human repopulating cells with no evidence of silencing. Engraftment was highly polyclonal with no clonal dominance and a promising safety profile based on integration site analysis. An FV vector with an elongation factor-1α promoter and an A1 insulator is a promising vector design for use in the clinic. This article is protected by copyright. All rights reserved.

Experimental Evaluation of the High-Speed Motion Vector Measurement by Combining Synthetic Aperture Array Processing with Constrained Least Square Method

NASA Astrophysics Data System (ADS)

Yokoyama, Ryouta; Yagi, Shin-ichi; Tamura, Kiyoshi; Sato, Masakazu

2009-07-01

Ultrahigh speed dynamic elastography has promising potential capabilities in applying clinical diagnosis and therapy of living soft tissues. In order to realize the ultrahigh speed motion tracking at speeds of over thousand frames per second, synthetic aperture (SA) array signal processing technology must be introduced. Furthermore, the overall system performance should overcome the fine quantitative evaluation in accuracy and variance of echo phase changes distributed across a tissue medium. On spatial evaluation of local phase changes caused by pulsed excitation on a tissue phantom, investigation was made with the proposed SA signal system utilizing different virtual point sources that were generated by an array transducer to probe each component of local tissue displacement vectors. The final results derived from the cross-correlation method (CCM) brought about almost the same performance as obtained by the constrained least square method (LSM) extended to successive echo frames. These frames were reconstructed by SA processing after the real-time acquisition triggered by the pulsed irradiation from a point source. The continuous behavior of spatial motion vectors demonstrated the dynamic generation and traveling of the pulsed shear wave at a speed of one thousand frames per second.

An improved ternary vector system for Agrobacterium-mediated rapid maize transformation.

PubMed

Anand, Ajith; Bass, Steven H; Wu, Emily; Wang, Ning; McBride, Kevin E; Annaluru, Narayana; Miller, Michael; Hua, Mo; Jones, Todd J

2018-05-01

A simple and versatile ternary vector system that utilizes improved accessory plasmids for rapid maize transformation is described. This system facilitates high-throughput vector construction and plant transformation. The super binary plasmid pSB1 is a mainstay of maize transformation. However, the large size of the base vector makes it challenging to clone, the process of co-integration is cumbersome and inefficient, and some Agrobacterium strains are known to give rise to spontaneous mutants resistant to tetracycline. These limitations present substantial barriers to high throughput vector construction. Here we describe a smaller, simpler and versatile ternary vector system for maize transformation that utilizes improved accessory plasmids requiring no co-integration step. In addition, the newly described accessory plasmids have restored virulence genes found to be defective in pSB1, as well as added virulence genes. Testing of different configurations of the accessory plasmids in combination with T-DNA binary vector as ternary vectors nearly doubles both the raw transformation frequency and the number of transformation events of usable quality in difficult-to-transform maize inbreds. The newly described ternary vectors enabled the development of a rapid maize transformation method for elite inbreds. This vector system facilitated screening different origins of replication on the accessory plasmid and T-DNA vector, and four combinations were identified that have high (86-103%) raw transformation frequency in an elite maize inbred.

Cycles of Transient High-Dose Cyclophosphamide Administration and Oncolytic Adenovirus Vector Intratumoral Injection for Long Term Tumor Suppression in Syrian Hamsters

PubMed Central

Dhar, Debanjan; Toth, Karoly; Wold, William S.M.

2014-01-01

Immune responses against oncolytic adenovirus (Ad) vectors are thought to limit vector anti-tumor efficacy. In Syrian hamsters, which are immunocompetent and whose tumors and normal tissues are permissive for replication of Ad5-based oncolytic Ad vectors, treating with high-dose cyclophosphamide to suppress the immune system and exert chemotherapeutic effects enhances Ad vector anti-tumor efficacy. However, long term cyclophosphamide treatment and immunosuppression can lead to anemia and vector spread to normal tissues. Here we employed three cycles of transient high-dose cyclophosphamide administration plus intratumoral injection of the oncolytic Ad vector VRX-007 followed by withdrawal from cyclophosphamide. Each cycle lasted 4-6 weeks. This protocol allowed the hamsters to remain healthy so the study could be continued for ~100 days. The tumors were very well suppressed throughout the study. With immunocompetent hamsters, the vector retarded tumor growth initially, but after 3-4 weeks the tumors resumed rapid growth and further injections of vector were ineffective. Preimmunization of the hamsters with Ad5 prevented vector spillover from the tumor to the liver yet still allowed for effective long term anti-tumor efficacy. Our results suggest that a clinical protocol might be developed with cycles of transient chemotherapy plus intratumoral vector injection to achieve significant anti-tumor efficacy while minimizing the side effects of cytostatic treatment. PMID:24722357

Cycles of transient high-dose cyclophosphamide administration and intratumoral oncolytic adenovirus vector injection for long-term tumor suppression in Syrian hamsters.

PubMed

Dhar, D; Toth, K; Wold, W S M

2014-04-01

Immune responses against oncolytic adenovirus (Ad) vectors are thought to limit vector anti-tumor efficacy. With Syrian hamsters, which are immunocompetent and whose tumors and normal tissues are permissive for replication of Ad5-based oncolytic Ad vectors, treating with high-dose cyclophosphamide (CP) to suppress the immune system and exert chemotherapeutic effects enhances Ad vector anti-tumor efficacy. However, long-term CP treatment and immunosuppression can lead to anemia and vector spread to normal tissues. Here, we employed three cycles of transient high-dose CP administration plus intratumoral injection of the oncolytic Ad vector VRX-007 followed by withdrawal of CP. Each cycle lasted 4-6 weeks. This protocol allowed the hamsters to remain healthy so the study could be continued for ~100 days. The tumors were very well suppressed throughout the study. With immunocompetent hamsters, the vector retarded tumor growth initially, but after 3-4 weeks the tumors resumed rapid growth and further injections of vector were ineffective. Preimmunization of the hamsters with Ad5 prevented vector spillover from the tumor to the liver yet still allowed for effective long-term anti-tumor efficacy. Our results suggest that a clinical protocol might be developed with cycles of transient chemotherapy plus intratumoral vector injection to achieve significant anti-tumor efficacy while minimizing the side effects of cytostatic treatment.

An H-band Vector Vortex Coronagraph for the Subaru Coronagraphic Extreme-adaptive Optics System

NASA Astrophysics Data System (ADS)

Kühn, J.; Serabyn, E.; Lozi, J.; Jovanovic, N.; Currie, T.; Guyon, O.; Kudo, T.; Martinache, F.; Liewer, K.; Singh, G.; Tamura, M.; Mawet, D.; Hagelberg, J.; Defrere, D.

2018-03-01

The vector vortex is a coronagraphic imaging mode of the recently commissioned Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) platform on the 8 m Subaru Telescope. This multi-purpose high-contrast visible and near-infrared (R- to K-band) instrument is not only intended to serve as a VLT-class “planet-imager” instrument in the northern hemisphere, but also to operate as a technology demonstration testbed ahead of the ELTs-era, with a particular emphasis on small inner-working angle (IWA) coronagraphic capabilities. The given priority to small-IWA imaging led to the early design choice to incorporate focal-plane phase-mask coronagraphs. In this context, a test H-band vector vortex liquid crystal polymer waveplate was provided to SCExAO, to allow a one-to-one comparison of different small-IWA techniques on the same telescope instrument, before considering further steps. Here we present a detailed overview of the vector vortex coronagraph, from its installation and performances on the SCExAO optical bench, to the on-sky results in the extreme AO regime, as of late 2016/early 2017. To this purpose, we also provide a few recent on-sky imaging examples, notably high-contrast ADI detection of the planetary-mass companion κ Andromedae b, with a signal-to-noise ratio above 100 reached in less than 10 mn exposure time.

Feedback control laws for highly maneuverable aircraft

NASA Technical Reports Server (NTRS)

Garrard, William L.; Balas, Gary J.

1995-01-01

During this year, we concentrated our efforts on the design of controllers for lateral/directional control using mu synthesis. This proved to be a more difficult task than we anticipated and we are still working on the designs. In the lateral-directional control problem, the inputs are pilot lateral stick and pedal commands and the outputs are roll rate about the velocity vector and side slip angle. The control effectors are ailerons, rudder deflection, and directional thrust vectoring vane deflection which produces a yawing moment about the body axis. Our math model does not contain any provision for thrust vectoring of rolling moment. This has resulted in limitations of performance at high angles of attack. During 1994-95, the following tasks for the lateral-directional controllers were accomplished: (1) Designed both inner and outer loop dynamic inversion controllers. These controllers are implemented using accelerometer outputs rather than an a priori model of the vehicle aerodynamics; (2) Used classical techniques to design controllers for the system linearized by dynamics inversion. These controllers acted to control roll rate and Dutch roll response; (3) Implemented the inner loop dynamic inversion and classical controllers on the six DOF simulation; (4) Developed a lateral-directional control allocation scheme based on minimizing required control effort among the ailerons, rudder, and directional thrust vectoring; and (5) Developed mu outer loop controllers combined with classical inner loop controllers.

Measurement of aspheric mirror by nanoprofiler using normal vector tracing

NASA Astrophysics Data System (ADS)

Kitayama, Takao; Shiraji, Hiroki; Yamamura, Kazuya; Endo, Katsuyoshi

2016-09-01

Aspheric or free-form optics with high accuracy are necessary in many fields such as third-generation synchrotron radiation and extreme-ultraviolet lithography. Therefore the demand of measurement method for aspherical or free-form surface with nanometer accuracy increases. Purpose of our study is to develop a non-contact measurement technology for aspheric or free-form surfaces directly with high repeatability. To achieve this purpose we have developed threedimensional Nanoprofiler which detects normal vectors of sample surface. The measurement principle is based on the straightness of laser light and the accurate motion of rotational goniometers. This machine consists of four rotational stages, one translational stage and optical head which has the quadrant photodiode (QPD) and laser source. In this measurement method, we conform the incident light beam to reflect the beam by controlling five stages and determine the normal vectors and the coordinates of the surface from signal of goniometers, translational stage and QPD. We can obtain three-dimensional figure from the normal vectors and their coordinates by surface reconstruction algorithm. To evaluate performance of this machine we measure a concave aspheric mirror with diameter of 150 mm. As a result we achieve to measure large area of 150mm diameter. And we observe influence of systematic errors which the machine has. Then we simulated the influence and subtracted it from measurement result.

The effects of noise due to random undetected tilts and paleosecular variation on regional paleomagnetic directions

USGS Publications Warehouse

Calderone, G.J.; Butler, R.F.

1991-01-01

Random tilting of a single paleomagnetic vector produces a distribution of vectors which is not rotationally symmetric about the original vector and therefore not Fisherian. Monte Carlo simulations were performed on two types of vector distributions: 1) distributions of vectors formed by perturbing a single original vector with a Fisher distribution of bedding poles (each defining a tilt correction) and 2) standard Fisher distributions. These simulations demonstrate that inclinations of vectors drawn from both distributions are biased toward shallow inclinations. The Fisher mean direction of the distribution of vectors formed by perturbing a single vector with random undetected tilts is biased toward shallow inclinations, but this bias is insignificant for angular dispersions of bedding poles less than 20??. -from Authors

Acceleration of GPU-based Krylov solvers via data transfer reduction

DOE PAGES

Anzt, Hartwig; Tomov, Stanimire; Luszczek, Piotr; ...

2015-04-08

Krylov subspace iterative solvers are often the method of choice when solving large sparse linear systems. At the same time, hardware accelerators such as graphics processing units continue to offer significant floating point performance gains for matrix and vector computations through easy-to-use libraries of computational kernels. However, as these libraries are usually composed of a well optimized but limited set of linear algebra operations, applications that use them often fail to reduce certain data communications, and hence fail to leverage the full potential of the accelerator. In this study, we target the acceleration of Krylov subspace iterative methods for graphicsmore » processing units, and in particular the Biconjugate Gradient Stabilized solver that significant improvement can be achieved by reformulating the method to reduce data-communications through application-specific kernels instead of using the generic BLAS kernels, e.g. as provided by NVIDIA’s cuBLAS library, and by designing a graphics processing unit specific sparse matrix-vector product kernel that is able to more efficiently use the graphics processing unit’s computing power. Furthermore, we derive a model estimating the performance improvement, and use experimental data to validate the expected runtime savings. Finally, considering that the derived implementation achieves significantly higher performance, we assert that similar optimizations addressing algorithm structure, as well as sparse matrix-vector, are crucial for the subsequent development of high-performance graphics processing units accelerated Krylov subspace iterative methods.« less

Ecological Niche Modelling Predicts Southward Expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), Vector of Leishmania (Leishmania) amazonensis in South America, under Climate Change

PubMed Central

Carvalho, Bruno M.; Ready, Paul D.

2015-01-01

Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector’s climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: “stabilization” and “high increase”. Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region. PMID:26619186

Pyrethroid resistance persists after ten years without usage against Aedes aegypti in governmental campaigns: Lessons from São Paulo State, Brazil.

PubMed

Macoris, Maria de Lourdes; Martins, Ademir Jesus; Andrighetti, Maria Teresa Macoris; Lima, José Bento Pereira; Valle, Denise

2018-03-01

Aedes aegypti, vector of dengue, chikungunya and Zika viruses, is found at high densities in tropical urban areas. The dissemination of this vector is partially the consequence of failures in current vector control methods, still mainly relying upon insecticides. In the State of São Paulo (SP), Brazil, public health managers employed pyrethroids against Ae. aegypti adults from 1989 to 2000, when a robust insecticide resistance monitoring system detected resistance to pyrethroids in several Ae. aegypti populations. However, pyrethroids are also the preferred compounds engaged in household applications due to their rapid knockdown effect, lower toxicity to mammals and less irritating smell. We evaluated pyrethroid resistance in Ae. aegypti populations over the course of a decade, from 2004 to 2015, after interruption of pyrethroid public applications in SP. Qualitative bioassays with papers impregnated with a deltamethrin diagnostic dose (DD) performed with insects from seven SP municipalities and evaluated yearly from 2006 to 2014, detected resistance in most of the cases. Quantitative bioassays were also carried out with four populations in 2011, suggesting a positive correlation between resistance level and survivorship in the DD bioassays. Biochemical tests conducted with seven insect populations in 2006 and 2015, detected increasing metabolic alterations of all major classes of detoxifying enzymes, mostly of mixed function oxidases. Genotyping of the voltage-gated sodium channel (AaNaV, the pyrethroid target-site) with a TaqMan real time PCR based technique was performed from 2004 to 2014 in all seven localities. The two kdr mutations, Val1016Ile and Phe1534Cys, known to be spread throughout Brazil, were always present with a severe decrease of the susceptible allele over time. These results are discussed in the context of public and domestic insecticide use, the necessity of implementation of a strong integrated vector control strategy and the conceptual misunderstanding between 'vector control' and 'chemical control of vectors'.

Pyrethroid resistance persists after ten years without usage against Aedes aegypti in governmental campaigns: Lessons from São Paulo State, Brazil

PubMed Central

Andrighetti, Maria Teresa Macoris; Lima, José Bento Pereira; Valle, Denise

2018-01-01

Background Aedes aegypti, vector of dengue, chikungunya and Zika viruses, is found at high densities in tropical urban areas. The dissemination of this vector is partially the consequence of failures in current vector control methods, still mainly relying upon insecticides. In the State of São Paulo (SP), Brazil, public health managers employed pyrethroids against Ae. aegypti adults from 1989 to 2000, when a robust insecticide resistance monitoring system detected resistance to pyrethroids in several Ae. aegypti populations. However, pyrethroids are also the preferred compounds engaged in household applications due to their rapid knockdown effect, lower toxicity to mammals and less irritating smell. Methodology/Principal findings We evaluated pyrethroid resistance in Ae. aegypti populations over the course of a decade, from 2004 to 2015, after interruption of pyrethroid public applications in SP. Qualitative bioassays with papers impregnated with a deltamethrin diagnostic dose (DD) performed with insects from seven SP municipalities and evaluated yearly from 2006 to 2014, detected resistance in most of the cases. Quantitative bioassays were also carried out with four populations in 2011, suggesting a positive correlation between resistance level and survivorship in the DD bioassays. Biochemical tests conducted with seven insect populations in 2006 and 2015, detected increasing metabolic alterations of all major classes of detoxifying enzymes, mostly of mixed function oxidases. Genotyping of the voltage-gated sodium channel (AaNaV, the pyrethroid target-site) with a TaqMan real time PCR based technique was performed from 2004 to 2014 in all seven localities. The two kdr mutations, Val1016Ile and Phe1534Cys, known to be spread throughout Brazil, were always present with a severe decrease of the susceptible allele over time. Conclusions/Significance These results are discussed in the context of public and domestic insecticide use, the necessity of implementation of a strong integrated vector control strategy and the conceptual misunderstanding between 'vector control' and 'chemical control of vectors'. PMID:29601580

Development of Agrobacterium-Mediated Virus-Induced Gene Silencing and Performance Evaluation of Four Marker Genes in Gossypium barbadense

PubMed Central

Pang, Jinhuan; Zhu, Yue; Li, Qing; Liu, Jinzhi; Tian, Yingchuan; Liu, Yule; Wu, Jiahe

2013-01-01

Gossypium barbadense is a cultivated cotton species and possesses many desirable traits, including high fiber quality and resistance to pathogens, especially Verticilliumdahliae (a devastating pathogen of Gossypium hirsutum, the main cultivated species). These elite traits are difficult to be introduced into G. hirsutum through classical breeding methods. In addition, genetic transformation of G . barbadense has not been successfully performed. It is therefore important to develop methods for evaluating the function and molecular mechanism of genes in G . barbadense . In this study, we had successfully introduced a virus-induced gene silencing (VIGS) system into three cultivars of G . barbadense by inserting marker genes into the tobacco rattle virus (TRV) vector. After we optimized the VIGS conditions, including light intensity, photoperiod, seedling age and Agrobacterium strain, 100% of plants agroinfiltrated with the GaPDS silencing vector showed white colored leaves. Three other marker genes, GaCLA1, GaANS and GaANR, were employed to further test this VIGS system in G . barbadense . The transcript levels of the endogenous genes in the silenced plants were reduced by more than 99% compared to control plants; these plants presented phenotypic symptoms 2 weeks after inoculation. We introduced a fusing sequence fragment of GaPDS and GaANR gene silencing vectors into a single plant, which resulted in both photobleaching and brownish coloration. The extent of silencing in plants agroinfiltrated with fusing two-gene-silencing vector was consistent with plants harboring a single gene silencing vector. The development of this VIGS system should promote analysis of gene function in G . barbadense , and help to contribute desirable traits for breeding of G . barbadense and G. hirsutum. PMID:24023833

Interpreting linear support vector machine models with heat map molecule coloring

PubMed Central

2011-01-01

Background Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. Results We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor. Conclusions In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor. PMID:21439031

Assessing spatio-temporal trend of vector breeding and dengue fever incidence in association with meteorological conditions.

PubMed

Malik, Afifa; Yasar, Abdullah; Tabinda, Amtul Bari; Zaheer, Ihsan Elahi; Malik, Khalida; Batool, Adeeba; Mahfooz, Yusra

2017-04-01

Th aim of this study is to investigate spatio-temporal trends of dengue vector breeding and epidemic (disease incidence) influenced by climatic factors. The spatio-temporal (low-, medium-, and high-intensity periods) evaluation of entomological and epidemiological investigations along with climatic factors like rainfall (RF), temperature (T max ), relative humidity (RH), and larval indexing was conducted to develop correlations in the area of Lahore, Pakistan. The vector abundance and disease transmission trend was geo-tagged for spatial insight. The sufficient rainfall events and optimum temperature and relative humidity supported dengue vector breeding with high larval indices for water-related containers (27-37%). Among temporal analysis, the high-intensity period exponentially projected disease incidence followed by post-rainfall impacts. The high larval incidence that was observed in early high-intensity periods effected the dengue incidence. The disease incidence had a strong association with RF (r = 0.940, α = 0.01). The vector larva occurrence (r = 0.017, α = 0.05) influenced the disease incidence. Similarly, RH (r = 0.674, α = 0.05) and average T max (r = 0.307, α = 0.05) also induced impact on the disease incidence. In this study, the vulnerability to dengue fever highly correlates with meteorological factors during high-intensity period. It provides area-specific understanding of vector behavior, key containers, and seasonal patterns of dengue vector breeding and disease transmission which is essential for preparing an effective prevention plan against the vector.

[Effects of plant viruses on vector and non-vector herbivorous arthropods and their natural enemies: a mini review].

PubMed

He, Xiao-Chan; Xu, Hong-Xing; Zhou, Xiao-Jun; Zheng, Xu-Song; Sun, Yu-Jian; Yang, Ya-Jun; Tian, Jun-Ce; Lü, Zhong-Xian

2014-05-01

Plant viruses transmitted by arthropods, as an important biotic factor, may not only directly affect the yield and quality of host plants, and development, physiological characteristics and ecological performances of their vector arthropods, but also directly or indirectly affect the non-vector herbivorous arthropods and their natural enemies in the same ecosystem, thereby causing influences to the whole agro-ecosystem. This paper reviewed the progress on the effects of plant viruses on herbivorous arthropods, including vector and non-vector, and their natural enemies, and on their ecological mechanisms to provide a reference for optimizing the management of vector and non-vector arthropod populations and sustainable control of plant viruses in agro-ecosystem.

A hybrid structure for the storage and manipulation of very large spatial data sets

USGS Publications Warehouse

Peuquet, Donna J.

1982-01-01

The map data input and output problem for geographic information systems is rapidly diminishing with the increasing availability of mass digitizing, direct spatial data capture and graphics hardware based on raster technology. Although a large number of efficient raster-based algorithms exist for performing a wide variety of common tasks on these data, there are a number of procedures which are more efficiently performed in vector mode or for which raster mode equivalents of current vector-based techniques have not yet been developed. This paper presents a hybrid spatial data structure, named the ?vaster' structure, which can utilize the advantages of both raster and vector structures while potentially eliminating, or greatly reducing, the need for raster-to-vector and vector-to-raster conversion. Other advantages of the vaster structure are also discussed.

The diagnostic performance of recombinant Trypanosoma cruzi ribosomal P2beta protein is influenced by its expression system.

PubMed

Marcipar, Iván S; Olivares, María Laura; Robles, Lucía; Dekanty, Andrés; Marcipar, Alberto; Silber, Ariel M

2004-03-01

In the present work, we have determined the effect of expression vectors and their corresponding host bacteria on the antigenic performance of Trypanosoma cruzi P2beta (TcP2beta) full-length recombinant protein. The gene encoding the TcP2beta ribosomal protein was cloned in pMAL-c2 and pET-32a vectors that allow the expression of high levels of soluble fusion proteins. A panel of 32 positive and 32 negative sera was assayed with the purified proteins expressed using pMal-c2 (TcP2beta-MBP) and pET-32a (TcP2beta-TRX) vectors and with MBP and TRX purified from pMAL-c2 and pET-32a vectors, respectively. The antigenic behavior of each TcP2beta recombinant protein differed in the diagnostic performance in terms of DI(+) (93.7 for TcP2beta-MBP vs 100% for TcP2beta-TRX), in DI(-) (90.5 for TcP2beta-MBP vs 100% for TcP2beta-TRX) and in cross-reaction with negative sera. To determine if the higher reactivity of expressed pMAL-c2 protein was due to folding during protein expression or to a steric effect related to the protein adsorption at the titration plate, the reactivity of sera against soluble proteins was assessed by ELISA inhibition assays. As each soluble protein preserved its level of reactivity, we concluded that differences in reactivity were due to intrinsic characteristics of the proteins and not to differences in patterns of adsorption to the plates.

Highly efficient coupler for dielectric slot waveguides and hybrid plasmonic waveguides

NASA Astrophysics Data System (ADS)

Yu, Jiyao; Ohtera, Yasuo; Yamada, Hirohito

2018-05-01

A compact, highly efficient optical coupler for dielectric slot waveguides and hybrid plasmonic waveguides based on transition layers (air slot grooves) was investigated. The power-coupling efficiency of 75% for the direct coupling case increased to 90% following the insertion of an intermediate section. By performing time-averaged Poynting vector analysis, we successfully separated the factors of transmission, reflection, and radiation at the coupler interface. We found that the insertion of optimal air grooves into the coupler structure contributed to the improvement of coupling performance. The proposed compact structure is characterized by a high transmission efficiency, low reflection, small length, and broad-band spectrum response.

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Robust support vector regression networks for function approximation with outliers.

PubMed

Chuang, Chen-Chia; Su, Shun-Feng; Jeng, Jin-Tsong; Hsiao, Chih-Ching

2002-01-01

Support vector regression (SVR) employs the support vector machine (SVM) to tackle problems of function approximation and regression estimation. SVR has been shown to have good robust properties against noise. When the parameters used in SVR are improperly selected, overfitting phenomena may still occur. However, the selection of various parameters is not straightforward. Besides, in SVR, outliers may also possibly be taken as support vectors. Such an inclusion of outliers in support vectors may lead to seriously overfitting phenomena. In this paper, a novel regression approach, termed as the robust support vector regression (RSVR) network, is proposed to enhance the robust capability of SVR. In the approach, traditional robust learning approaches are employed to improve the learning performance for any selected parameters. From the simulation results, our RSVR can always improve the performance of the learned systems for all cases. Besides, it can be found that even the training lasted for a long period, the testing errors would not go up. In other words, the overfitting phenomenon is indeed suppressed.

Static internal performance of an axisymmetric nozzle with multiaxis thrust-vectoring capability

NASA Technical Reports Server (NTRS)

Carson, George T., Jr.; Capone, Francis J.

1991-01-01

An investigation was conducted in the static test facility of the Langley 16 Foot Transonic Tunnel in order to determine the internal performance characteristics of a multiaxis thrust vectoring axisymmetric nozzle. Thrust vectoring for this nozzle was achieved by deflection of only the divergent section of this nozzle. The effects of nozzle power setting and divergent flap length were studied at nozzle deflection angles of 0 to 30 at nozzle pressure ratios up to 8.0.

Production, concentration and titration of pseudotyped HIV-1-based lentiviral vectors.

PubMed

Kutner, Robert H; Zhang, Xian-Yang; Reiser, Jakob

2009-01-01

Over the past decade, lentiviral vectors have emerged as powerful tools for transgene delivery. The use of lentiviral vectors has become commonplace and applications in the fields of neuroscience, hematology, developmental biology, stem cell biology and transgenesis are rapidly emerging. Also, lentiviral vectors are at present being explored in the context of human clinical trials. Here we describe improved protocols to generate highly concentrated lentiviral vector pseudotypes involving different envelope glycoproteins. In this protocol, vector stocks are prepared by transient transfection using standard cell culture media or serum-free media. Such stocks are then concentrated by ultracentrifugation and/or ion exchange chromatography, or by precipitation using polyethylene glycol 6000, resulting in vector titers of up to 10(10) transducing units per milliliter and above. We also provide reliable real-time PCR protocols to titrate lentiviral vectors based on proviral DNA copies present in genomic DNA extracted from transduced cells or on vector RNA. These production/concentration methods result in high-titer vector preparations that show reduced toxicity compared with lentiviral vectors produced using standard protocols involving ultracentrifugation-based methods. The vector production and titration protocol described here can be completed within 8 d.

Low-rank separated representation surrogates of high-dimensional stochastic functions: Application in Bayesian inference

NASA Astrophysics Data System (ADS)

Validi, AbdoulAhad

2014-03-01

This study introduces a non-intrusive approach in the context of low-rank separated representation to construct a surrogate of high-dimensional stochastic functions, e.g., PDEs/ODEs, in order to decrease the computational cost of Markov Chain Monte Carlo simulations in Bayesian inference. The surrogate model is constructed via a regularized alternative least-square regression with Tikhonov regularization using a roughening matrix computing the gradient of the solution, in conjunction with a perturbation-based error indicator to detect optimal model complexities. The model approximates a vector of a continuous solution at discrete values of a physical variable. The required number of random realizations to achieve a successful approximation linearly depends on the function dimensionality. The computational cost of the model construction is quadratic in the number of random inputs, which potentially tackles the curse of dimensionality in high-dimensional stochastic functions. Furthermore, this vector-valued separated representation-based model, in comparison to the available scalar-valued case, leads to a significant reduction in the cost of approximation by an order of magnitude equal to the vector size. The performance of the method is studied through its application to three numerical examples including a 41-dimensional elliptic PDE and a 21-dimensional cavity flow.

Chemical modification of chitosan for efficient gene therapy.

PubMed

Jiang, Hu-Lin; Cui, Peng-Fei; Xie, Rong-Lin; Cho, Chong-Su

2014-01-01

Gene therapy involves the introduction of foreign genetic material into cells in order to exert a therapeutic effect. Successful gene therapy relies on effective vector system. Viral vectors are highly efficient in transfecting cells, but the undesirable complications limit their therapeutic applications. As a natural biopolymer, chitosan has been considered to be a good gene carrier candidate due to its ideal character which combines biocompatibility, low toxicity with high cationic density together. However, the low cell specificity and low transfection efficiency of chitosan as a gene carrier need to be overcome before undertaking clinical trials. This chapter is principally on those endeavors such as chemical modifications using cell-specific ligands and stimuli-response groups as well as penetrating modifications that have been done to increase the performances of chitosan in gene therapy. © 2014 Elsevier Inc. All rights reserved.

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amadio, G.; et al.

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physicsmore » models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.« less

Static internal performance of single expansion-ramp nozzles with thrust vectoring and reversing

NASA Technical Reports Server (NTRS)

Re, R. J.; Berrier, B. L.

1982-01-01

The effects of geometric design parameters on the internal performance of nonaxisymmetric single expansion-ramp nozzles were investigated at nozzle pressure ratios up to approximately 10. Forward-flight (cruise), vectored-thrust, and reversed-thrust nozzle operating modes were investigated.

High level over-expression of different NCX isoforms in HEK293 cell lines and primary neuronal cultures is protective following oxygen glucose deprivation.

PubMed

Cross, Jane L; Boulos, Sherif; Shepherd, Kate L; Craig, Amanda J; Lee, Sharon; Bakker, Anthony J; Knuckey, Neville W; Meloni, Bruno P

2012-07-01

In this study we have assessed sodium-calcium exchanger (NCX) protein over-expression on cell viability in primary rat cortical neuronal and HEK293 cell cultures when subjected to oxygen-glucose deprivation (OGD). In cortical neuronal cultures, NCX2 and NCX3 over-expression was achieved using adenoviral vectors, and following OGD increased neuronal survival from ≈20% for control vector treated cultures to ≈80% for both NCX isoforms. In addition, we demonstrated that NCX2 and NCX3 over-expression in cortical neuronal cultures enables neurons to maintain intracellular calcium at significantly lower levels than control vector treated cultures when exposed to high (9mM) extracellular calcium challenge. Further assessment of NCX activity during OGD was performed using HEK293 cell lines generated to over-express NCX1, NCX2 or NCX3 isoforms. While it was shown that NCX isoform expression differed considerably in the different HEK293 cell lines, high levels of NCX over-expression was associated with increased resistance to OGD. Taken together, our findings show that high levels of NCX over-expression increases neuronal and HEK293 cell survival following OGD, improves calcium management in neuronal cultures and provides additional support for NCX as a therapeutic target to reduce ischemic brain injury. Copyright © 2012 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Bioreducible Zinc(II)-Coordinative Polyethylenimine with Low Molecular Weight for Robust Gene Delivery of Primary and Stem Cells.

PubMed

Liu, Shuai; Zhou, Dezhong; Yang, Jixiang; Zhou, Hao; Chen, Jiatong; Guo, Tianying

2017-03-30

To transform common low-molecular-weight (LMW) cationic polymers, such as polyethylenimine (PEI), to highly efficient gene vectors would be of great significance but remains challenging. Because LMW cationic polymers perform far less efficiently than their high-molecular-weight counterparts, mainly due to weaker nucleic acid encapsulation, herein we report the design and synthesis of a dipicolylamine-based disulfide-containing zinc(II) coordinative module (Zn-DDAC), which is used to functionalize LMW PEI (M w ≈ 1800 Da) to give a non-viral vector (Zn-PD) with high efficiency and safety in primary and stem cells. Given its high phosphate binding affinity, Zn-DDAC can significantly promote the DNA packaging functionality of PEI 1.8k and improve the cellular uptake of formulated polyplexes, which is particularly critical for hard-to-transfect cell types. Furthermore, Zn-PD polymer can be cleaved by glutathione in cytoplasm to facilitate DNA release post internalization and diminish the cytotoxicity. Consequently, the optimal Zn-PD mediates 1-2 orders of magnitude higher gluciferase activity than commercial transfection reagents, Xfect and PEI 25k , across diverse cell types, including primary and stem cells. Our findings provide a valuable insight into the exploitation of LMW cationic polymers for gene delivery and demonstrate great promise for the development of next-generation non-viral vectors for clinically viable gene therapy.

A pair of new BAC and BIBAC vectors that facilitate BAC/BIBAC library construction and intact large genomic DNA insert exchange.

PubMed

Shi, Xue; Zeng, Haiyang; Xue, Yadong; Luo, Meizhong

2011-10-11

Large-insert BAC and BIBAC libraries are important tools for structural and functional genomics studies of eukaryotic genomes. To facilitate the construction of BAC and BIBAC libraries and the transfer of complete large BAC inserts into BIBAC vectors, which is desired in positional cloning, we developed a pair of new BAC and BIBAC vectors. The new BAC vector pIndigoBAC536-S and the new BIBAC vector BIBAC-S have the following features: 1) both contain two 18-bp non-palindromic I-SceI sites in an inverted orientation at positions that flank an identical DNA fragment containing the lacZ selection marker and the cloning site. Large DNA inserts can be excised from the vectors as single fragments by cutting with I-SceI, allowing the inserts to be easily sized. More importantly, because the two vectors contain different antibiotic resistance genes for transformant selection and produce the same non-complementary 3' protruding ATAA ends by I-SceI that suppress self- and inter-ligations, the exchange of intact large genomic DNA inserts between the BAC and BIBAC vectors is straightforward; 2) both were constructed as high-copy composite vectors. Reliable linearized and dephosphorylated original low-copy pIndigoBAC536-S and BIBAC-S vectors that are ready for library construction can be prepared from the high-copy composite vectors pHZAUBAC1 and pHZAUBIBAC1, respectively, without the need for additional preparation steps or special reagents, thus simplifying the construction of BAC and BIBAC libraries. BIBAC clones constructed with the new BIBAC-S vector are stable in both E. coli and Agrobacterium. The vectors can be accessed through our website http://GResource.hzau.edu.cn. The two new vectors and their respective high-copy composite vectors can largely facilitate the construction and characterization of BAC and BIBAC libraries. The transfer of complete large genomic DNA inserts from one vector to the other is made straightforward.

LASIK versus photorefractive keratectomy for high myopic (> 3 diopter) astigmatism.

PubMed

Katz, Toam; Wagenfeld, Lars; Galambos, Peter; Darrelmann, Benedikt Große; Richard, Gisbert; Linke, Stephan Johannes

2013-12-01

To compare the efficacy, safety, predictability, and vector analysis indices of LASIK and photorefractive keratectomy (PRK) for correction of high cylinder of greater than 3 diopters (D) in myopic eyes. The efficacy, safety, and predictability of LASIK or PRK performed in 114 consecutive randomly selected myopic eyes with an astigmatism of greater than 3 D were retrospectively analyzed at the 2- to 6-month follow-up visits. Vector analysis of the cylindrical correction was compared between the treatment groups. A total of 57 eyes receiving PRK and 57 eyes receiving LASIK of 114 refractive surgery candidates were enrolled in the study. No statistically significant difference in efficacy [efficacy index = 0.76 (±0.32) for PRK vs 0.74 (±0.19) for LASIK (P = .82)], safety [safety index = 1.10 (±0.26) for PRK vs 1.01 (±0.17) for LASIK (P = .121)], or predictability [achieved astigmatism < 1 D in 39% of PRK- and 54% of LASIK-treated eyes, and < 2 D in 88% of PRK- and 89% of LASIK-treated eyes (P = .218)] was demonstrated. Using Alpins vector analysis, the surgically induced astigmatism and difference vector were not significantly different between the surgery methods, whereas the correction index showed a slight and significant advantage of LASIK over PRK (1.25 for PRK and 1.06 for LASIK, P < .001). LASIK and PRK are comparably safe, effective, and predictable procedures for excimer laser correction of high astigmatism of greater than 3 D in myopic eyes. Predictability of the correction of the cylindrical component is lower than that of the spherical equivalent. Copyright 2013, SLACK Incorporated.

The identification of high potential archers based on fitness and motor ability variables: A Support Vector Machine approach.

PubMed

Taha, Zahari; Musa, Rabiu Muazu; P P Abdul Majeed, Anwar; Alim, Muhammad Muaz; Abdullah, Mohamad Razali

2018-02-01

Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. Standard fitness and ability measurements namely hand grip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were also recorded. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. The HACA clustered the archers into high-potential archers (HPA) and low-potential archers (LPA), respectively. The linear, quadratic, cubic, as well as the medium RBF kernel functions models, demonstrated reasonably excellent classification accuracy of 97.5% and 2.5% error rate for the prediction of the HPA and the LPA. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from a combination of the selected few measured fitness and motor ability performance variables examined which would consequently save cost, time and effort during talent identification programme. Copyright © 2017 Elsevier B.V. All rights reserved.

Cervical cancer survival prediction using hybrid of SMOTE, CART and smooth support vector machine

NASA Astrophysics Data System (ADS)

Purnami, S. W.; Khasanah, P. M.; Sumartini, S. H.; Chosuvivatwong, V.; Sriplung, H.

2016-04-01

According to the WHO, every two minutes there is one patient who died from cervical cancer. The high mortality rate is due to the lack of awareness of women for early detection. There are several factors that supposedly influence the survival of cervical cancer patients, including age, anemia status, stage, type of treatment, complications and secondary disease. This study wants to classify/predict cervical cancer survival based on those factors. Various classifications methods: classification and regression tree (CART), smooth support vector machine (SSVM), three order spline SSVM (TSSVM) were used. Since the data of cervical cancer are imbalanced, synthetic minority oversampling technique (SMOTE) is used for handling imbalanced dataset. Performances of these methods are evaluated using accuracy, sensitivity and specificity. Results of this study show that balancing data using SMOTE as preprocessing can improve performance of classification. The SMOTE-SSVM method provided better result than SMOTE-TSSVM and SMOTE-CART.

An RGD-Modified MRI-Visible Polymeric Vector for Targeted siRNA Delivery to Hepatocellular Carcinoma in Nude Mice

PubMed Central

Shen, Min; Zhu, Kangshun; Cheng, Du; Liu, Zhihao; Shan, Hong

2013-01-01

RNA interference (RNAi) has significant therapeutic promise for the genetic treatment of hepatocellular carcinoma (HCC). Targeted vectors are able to deliver small interfering RNA (siRNA) into HCC cells with high transfection efficiency and stability. The tripeptide arginine glycine aspartic acid (RGD)-modified non-viral vector, polyethylene glycol-grafted polyethylenimine functionalized with superparamagnetic iron oxide nanoparticles (RGD-PEG-g-PEI-SPION), was constructed as a magnetic resonance imaging (MRI)-visible nanocarrier for the delivery of Survivin siRNA targeting the human HCC cell line Bel-7402. The biophysical characterization of the RGD-PEG-g-PEI-SPION was performed. The RGD-modified complexes exhibited a higher transfection efficiency in transferring Survivin siRNA into Bel-7402 cells compared with a non-targeted delivery system, which resulted in more significant gene suppression at both the Survivin mRNA and protein expression levels. Then, the level of caspase-3 activation was significantly elevated, and a remarkable level of tumor cell apoptosis was induced. As a result, the tumor growth in the nude mice Bel-7402 hepatoma model was significantly inhibited. The targeting ability of the RGD-PEG-g-PEI-SPION was successfully imaged by MRI scans performed in vitro and in vivo. Our results strongly indicated that the RGD-PEG-g-PEI-SPION can potentially be used as a targeted non-viral vector for altering gene expression in the treatment of hepatocellular carcinoma and for detecting the tumor in vivo as an effective MRI probe. PMID:23922634

Radar target classification method with high accuracy and decision speed performance using MUSIC spectrum vectors and PCA projection

NASA Astrophysics Data System (ADS)

Secmen, Mustafa

2011-10-01

This paper introduces the performance of an electromagnetic target recognition method in resonance scattering region, which includes pseudo spectrum Multiple Signal Classification (MUSIC) algorithm and principal component analysis (PCA) technique. The aim of this method is to classify an "unknown" target as one of the "known" targets in an aspect-independent manner. The suggested method initially collects the late-time portion of noise-free time-scattered signals obtained from different reference aspect angles of known targets. Afterward, these signals are used to obtain MUSIC spectrums in real frequency domain having super-resolution ability and noise resistant feature. In the final step, PCA technique is applied to these spectrums in order to reduce dimensionality and obtain only one feature vector per known target. In the decision stage, noise-free or noisy scattered signal of an unknown (test) target from an unknown aspect angle is initially obtained. Subsequently, MUSIC algorithm is processed for this test signal and resulting test vector is compared with feature vectors of known targets one by one. Finally, the highest correlation gives the type of test target. The method is applied to wire models of airplane targets, and it is shown that it can tolerate considerable noise levels although it has a few different reference aspect angles. Besides, the runtime of the method for a test target is sufficiently low, which makes the method suitable for real-time applications.

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

PubMed Central

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

A global SOLIS vector spectromagnetograph (VSM) network

NASA Astrophysics Data System (ADS)

Streander, K. V.; Giampapa, M. S.; Harvey, J. W.; Henney, C. J.; Norton, A. A.

2008-07-01

Understanding the Sun's magnetic field related activity is far from complete as reflected in the limited ability to make accurate predictions of solar variability. To advance our understanding of solar magnetism, the National Solar Observatory (NSO) constructed the Synoptic Optical Long-term Investigations of the Sun (SOLIS) suite of instruments to conduct high precision optical measurements of processes on the Sun whose study requires sustained observations over long time periods. The Vector Spectromagnetograph (VSM), the principal SOLIS instrument, has been in operation since 2003 and obtains photospheric vector data, as well as photospheric and chromospheric longitudinal magnetic field measurements. Instrument performance is being enhanced by employing new, high-speed cameras that virtually freeze seeing, thus improving sensitivity to measure the solar magnetic field configuration. A major operational goal is to provide real-time and near-real-time data for forecasting space weather and increase scientific yield from shorter duration solar space missions and ground-based research projects. The National Solar Observatory proposes to build two near-duplicates of the VSM instrument and place them at international sites to form a three-site global VSM network. Current electronic industry practice of short lifetime cycles leads to improved performance and reduced acquisition costs but also to redesign costs and engineering impacts that must be minimized. The current VSM instrument status and experience gained from working on the original instrument is presented herein and used to demonstrate that one can dramatically reduce the estimated cost and fabrication time required to duplicate and commission two additional instruments.

Expected energy-based restricted Boltzmann machine for classification.

PubMed

Elfwing, S; Uchibe, E; Doya, K

2015-04-01

In classification tasks, restricted Boltzmann machines (RBMs) have predominantly been used in the first stage, either as feature extractors or to provide initialization of neural networks. In this study, we propose a discriminative learning approach to provide a self-contained RBM method for classification, inspired by free-energy based function approximation (FE-RBM), originally proposed for reinforcement learning. For classification, the FE-RBM method computes the output for an input vector and a class vector by the negative free energy of an RBM. Learning is achieved by stochastic gradient-descent using a mean-squared error training objective. In an earlier study, we demonstrated that the performance and the robustness of FE-RBM function approximation can be improved by scaling the free energy by a constant that is related to the size of network. In this study, we propose that the learning performance of RBM function approximation can be further improved by computing the output by the negative expected energy (EE-RBM), instead of the negative free energy. To create a deep learning architecture, we stack several RBMs on top of each other. We also connect the class nodes to all hidden layers to try to improve the performance even further. We validate the classification performance of EE-RBM using the MNIST data set and the NORB data set, achieving competitive performance compared with other classifiers such as standard neural networks, deep belief networks, classification RBMs, and support vector machines. The purpose of using the NORB data set is to demonstrate that EE-RBM with binary input nodes can achieve high performance in the continuous input domain. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Optoelectronic Inner-Product Neural Associative Memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1993-01-01

Optoelectronic apparatus acts as artificial neural network performing associative recall of binary images. Recall process is iterative one involving optical computation of inner products between binary input vector and one or more reference binary vectors in memory. Inner-product method requires far less memory space than matrix-vector method.

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

NASA Astrophysics Data System (ADS)

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.

Micropathogen Community Analysis in Hyalomma rufipes via High-Throughput Sequencing of Small RNAs

PubMed Central

Luo, Jin; Liu, Min-Xuan; Ren, Qiao-Yun; Chen, Ze; Tian, Zhan-Cheng; Hao, Jia-Wei; Wu, Feng; Liu, Xiao-Cui; Luo, Jian-Xun; Yin, Hong; Wang, Hui; Liu, Guang-Yuan

2017-01-01

Ticks are important vectors in the transmission of a broad range of micropathogens to vertebrates, including humans. Because of the role of ticks in disease transmission, identifying and characterizing the micropathogen profiles of tick populations have become increasingly important. The objective of this study was to survey the micropathogens of Hyalomma rufipes ticks. Illumina HiSeq2000 technology was utilized to perform deep sequencing of small RNAs (sRNAs) extracted from field-collected H. rufipes ticks in Gansu Province, China. The resultant sRNA library data revealed that the surveyed tick populations produced reads that were homologous to St. Croix River Virus (SCRV) sequences. We also observed many reads that were homologous to microbial and/or pathogenic isolates, including bacteria, protozoa, and fungi. As part of this analysis, a phylogenetic tree was constructed to display the relationships among the homologous sequences that were identified. The study offered a unique opportunity to gain insight into the micropathogens of H. rufipes ticks. The effective control of arthropod vectors in the future will require knowledge of the micropathogen composition of vectors harboring infectious agents. Understanding the ecological factors that regulate vector propagation in association with the prevalence and persistence of micropathogen lineages is also imperative. These interactions may affect the evolution of micropathogen lineages, especially if the micropathogens rely on the vector or host for dispersal. The sRNA deep-sequencing approach used in this analysis provides an intuitive method to survey micropathogen prevalence in ticks and other vector species. PMID:28861401

Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping

PubMed Central

2012-01-01

Background Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions and is now extending its range to temperate regions. The spread of the dengue viruses mainly depends on vector population (Aedes aegypti and Aedes albopictus), which is influenced by changing climatic conditions and various land-use/land-cover types. Spatial display of the relationship between dengue vector density and land-cover types is required to describe a near-future viral outbreak scenario. This study is aimed at exploring how land-cover types are linked to the behavior of dengue-transmitting mosquitoes. Methods Surveys were conducted in 92 villages of Phitsanulok Province Thailand. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson’s correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic. Results Results of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month of May, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively. Conclusions The study concluded that gasoline stations/workshops, rice paddy, marsh/swamp and deciduous forests played highly significant role in dengue vector growth. Thus, the spatio-temporal relationships of dengue vector larval density and land-use types may help to predict favorable dengue habitat, and thereby enables public healthcare managers to take precautionary measures to prevent impending dengue outbreak. PMID:23043443

Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping.

PubMed

Sarfraz, Muhammad Shahzad; Tripathi, Nitin K; Tipdecho, Taravudh; Thongbu, Thawisak; Kerdthong, Pornsuk; Souris, Marc

2012-10-09

Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions and is now extending its range to temperate regions. The spread of the dengue viruses mainly depends on vector population (Aedes aegypti and Aedes albopictus), which is influenced by changing climatic conditions and various land-use/land-cover types. Spatial display of the relationship between dengue vector density and land-cover types is required to describe a near-future viral outbreak scenario. This study is aimed at exploring how land-cover types are linked to the behavior of dengue-transmitting mosquitoes. Surveys were conducted in 92 villages of Phitsanulok Province Thailand. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson's correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic. Results of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month of May, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively. The study concluded that gasoline stations/workshops, rice paddy, marsh/swamp and deciduous forests played highly significant role in dengue vector growth. Thus, the spatio-temporal relationships of dengue vector larval density and land-use types may help to predict favorable dengue habitat, and thereby enables public healthcare managers to take precautionary measures to prevent impending dengue outbreak.

Global MHD simulation of magnetosphere using HPF

NASA Astrophysics Data System (ADS)

Ogino, T.

We have translated a 3-dimensional magnetohydrodynamic (MHD) simulation code of the Earth's magnetosphere from VPP Fortran to HPF/JA on the Fujitsu VPP5000/56 vector-parallel supercomputer and the MHD code was fully vectorized and fully parallelized in VPP Fortran. The entire performance and capability of the HPF MHD code could be shown to be almost comparable to that of VPP Fortran. A 3-dimensional global MHD simulation of the earth's magnetosphere was performed at a speed of over 400 Gflops with an efficiency of 76.5% using 56 PEs of Fujitsu VPP5000/56 in vector and parallel computation that permitted comparison with catalog values. We have concluded that fluid and MHD codes that are fully vectorized and fully parallelized in VPP Fortran can be translated with relative ease to HPF/JA, and a code in HPF/JA may be expected to perform comparably to the same code written in VPP Fortran.

A Metric to Quantify Shared Visual Attention in Two-Person Teams

NASA Technical Reports Server (NTRS)

Gontar, Patrick; Mulligan, Jeffrey B.

2015-01-01

Introduction: Critical tasks in high-risk environments are often performed by teams, the members of which must work together efficiently. In some situations, the team members may have to work together to solve a particular problem, while in others it may be better for them to divide the work into separate tasks that can be completed in parallel. We hypothesize that these two team strategies can be differentiated on the basis of shared visual attention, measured by gaze tracking. 2) Methods: Gaze recordings were obtained for two-person flight crews flying a high-fidelity simulator (Gontar, Hoermann, 2014). Gaze was categorized with respect to 12 areas of interest (AOIs). We used these data to construct time series of 12 dimensional vectors, with each vector component representing one of the AOIs. At each time step, each vector component was set to 0, except for the one corresponding to the currently fixated AOI, which was set to 1. This time series could then be averaged in time, with the averaging window time (t) as a variable parameter. For example, when we average with a t of one minute, each vector component represents the proportion of time that the corresponding AOI was fixated within the corresponding one minute interval. We then computed the Pearson product-moment correlation coefficient between the gaze proportion vectors for each of the two crew members, at each point in time, resulting in a signal representing the time-varying correlation between gaze behaviors. We determined criteria for concluding correlated gaze behavior using two methods: first, a permutation test was applied to the subjects' data. When one crew member's gaze proportion vector is correlated with a random time sample from the other crewmember's data, a distribution of correlation values is obtained that differs markedly from the distribution obtained from temporally aligned samples. In addition to validating that the gaze tracker was functioning reasonably well, this also allows us to compute probabilities of coordinated behavior for each value of the correlation. As an alternative, we also tabulated distributions of correlation coefficients for synthetic data sets, in which the behavior was modeled as a first-order Markov process, and compared correlation distributions for identical processes with those for disparate processes, allowing us to choose criteria and estimate error rates. 3) Discussion: Our method of gaze correlation is able to measure shared visual attention, and can distinguish between activities involving different instruments. We plan to analyze whether pilots strategies of sharing visual attention can predict performance. Possible measurements of performance include expert ratings from instructors, fuel consumption, total task time, and failure rate. While developed for two-person crews, our approach can be applied to larger groups, using intra-class correlation coefficients instead of the Pearson product-moment correlation.

Ensemble of sparse classifiers for high-dimensional biological data.

PubMed

Kim, Sunghan; Scalzo, Fabien; Telesca, Donatello; Hu, Xiao

2015-01-01

Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature selection method has been proposed utilising the sparsity of high-dimensional biological data where a small subset of features accounts for most variance of the dataset. In this study we propose a new classification method for high-dimensional biological data, which performs both feature selection and classification within a single framework. Our proposed method utilises a sparse linear solution technique and the bootstrap aggregating algorithm. We tested its performance on four public mass spectrometry cancer datasets along with two other conventional classification techniques such as Support Vector Machines and Adaptive Boosting. The results demonstrate that our proposed method performs more accurate classification across various cancer datasets than those conventional classification techniques.

VISPA2: a scalable pipeline for high-throughput identification and annotation of vector integration sites.

PubMed

Spinozzi, Giulio; Calabria, Andrea; Brasca, Stefano; Beretta, Stefano; Merelli, Ivan; Milanesi, Luciano; Montini, Eugenio

2017-11-25

Bioinformatics tools designed to identify lentiviral or retroviral vector insertion sites in the genome of host cells are used to address the safety and long-term efficacy of hematopoietic stem cell gene therapy applications and to study the clonal dynamics of hematopoietic reconstitution. The increasing number of gene therapy clinical trials combined with the increasing amount of Next Generation Sequencing data, aimed at identifying integration sites, require both highly accurate and efficient computational software able to correctly process "big data" in a reasonable computational time. Here we present VISPA2 (Vector Integration Site Parallel Analysis, version 2), the latest optimized computational pipeline for integration site identification and analysis with the following features: (1) the sequence analysis for the integration site processing is fully compliant with paired-end reads and includes a sequence quality filter before and after the alignment on the target genome; (2) an heuristic algorithm to reduce false positive integration sites at nucleotide level to reduce the impact of Polymerase Chain Reaction or trimming/alignment artifacts; (3) a classification and annotation module for integration sites; (4) a user friendly web interface as researcher front-end to perform integration site analyses without computational skills; (5) the time speedup of all steps through parallelization (Hadoop free). We tested VISPA2 performances using simulated and real datasets of lentiviral vector integration sites, previously obtained from patients enrolled in a hematopoietic stem cell gene therapy clinical trial and compared the results with other preexisting tools for integration site analysis. On the computational side, VISPA2 showed a > 6-fold speedup and improved precision and recall metrics (1 and 0.97 respectively) compared to previously developed computational pipelines. These performances indicate that VISPA2 is a fast, reliable and user-friendly tool for integration site analysis, which allows gene therapy integration data to be handled in a cost and time effective fashion. Moreover, the web access of VISPA2 ( http://openserver.itb.cnr.it/vispa/ ) ensures accessibility and ease of usage to researches of a complex analytical tool. We released the source code of VISPA2 in a public repository ( https://bitbucket.org/andreacalabria/vispa2 ).

Virus infection of a weed increases vector attraction to and vector fitness on the weed.

PubMed

Chen, Gong; Pan, Huipeng; Xie, Wen; Wang, Shaoli; Wu, Qingjun; Fang, Yong; Shi, Xiaobin; Zhang, Youjun

2013-01-01

Weeds are important in the ecology of field crops, and when crops are harvested, weeds often become the main hosts for plant viruses and their insect vectors. Few studies, however, have examined the relationships between plant viruses, vectors, and weeds. Here, we investigated how infection of the weed Datura stramonium L. by tomato yellow leaf curl virus (TYLCV) affects the host preference and performance of the TYLCV vector, Bemisia tabaci (Gennadius) Q. The results of a choice experiment indicated that B. tabaci Q preferentially settled and oviposited on TYLCV-infected plants rather than on healthy plants. In addition, B. tabaci Q performed better on TYLCV-infected plants than on healthy plants. These results demonstrate that TYLCV is indirectly mutualistic to B. tabaci Q. The mutually beneficial interaction between TYLCV and B. tabaci Q may help explain the concurrent outbreaks of TYLCV and B. tabaci Q in China.

High yield of functional metagenomic library from mangroves constructed in fosmid vector.

PubMed

Gonçalves, A C S; dos Santos, A C F; dos Santos, T F; Pessoa, T B A; Dias, J C T; Rezende, R P

2015-10-02

In the present study, metagenomic technique and fosmid vectors were used to construct a library of clones for exploring the biotechnological potential of mangrove soils by isolation of functional genes encoding hydrolytic enzymes. The library was built with genomic DNA from the soil samples of mangrove sediments and the functional screening of 1824 clones (~64 Mbp) was performed to detect the hydrolytic activity specific for cellulases, amylases (at acidic, neutral and basic pH), lipases/esterases, proteases, and nitrilases. Significant numbers of clones, positive for the tested enzyme activities were obtained. Our results indicate the importance and biotechnological potential of mangrove soils especially when compared to those obtained using other soil metagenomic libraries.

A vectorized Lanczos eigensolver for high-performance computers

NASA Technical Reports Server (NTRS)

Bostic, Susan W.

1990-01-01

The computational strategies used to implement a Lanczos-based-method eigensolver on the latest generation of supercomputers are described. Several examples of structural vibration and buckling problems are presented that show the effects of using optimization techniques to increase the vectorization of the computational steps. The data storage and access schemes and the tools and strategies that best exploit the computer resources are presented. The method is implemented on the Convex C220, the Cray 2, and the Cray Y-MP computers. Results show that very good computation rates are achieved for the most computationally intensive steps of the Lanczos algorithm and that the Lanczos algorithm is many times faster than other methods extensively used in the past.

An assessment of support vector machines for land cover classification

USGS Publications Warehouse

Huang, C.; Davis, L.S.; Townshend, J.R.G.

2002-01-01

The support vector machine (SVM) is a group of theoretically superior machine learning algorithms. It was found competitive with the best available machine learning algorithms in classifying high-dimensional data sets. This paper gives an introduction to the theoretical development of the SVM and an experimental evaluation of its accuracy, stability and training speed in deriving land cover classifications from satellite images. The SVM was compared to three other popular classifiers, including the maximum likelihood classifier (MLC), neural network classifiers (NNC) and decision tree classifiers (DTC). The impacts of kernel configuration on the performance of the SVM and of the selection of training data and input variables on the four classifiers were also evaluated in this experiment.

Controlling Malaria Using Livestock-Based Interventions: A One Health Approach

PubMed Central

Franco, Ana O.; Gomes, M. Gabriela M.; Rowland, Mark; Coleman, Paul G.

2014-01-01

Where malaria is transmitted by zoophilic vectors, two types of malaria control strategies have been proposed based on animals: using livestock to divert vector biting from people (zooprophylaxis) or as baits to attract vectors to insecticide sources (insecticide-treated livestock). Opposing findings have been obtained on malaria zooprophylaxis, and despite the success of an insecticide-treated livestock trial in Pakistan, where malaria vectors are highly zoophilic, its effectiveness is yet to be formally tested in Africa where vectors are more anthropophilic. This study aims to clarify the different effects of livestock on malaria and to understand under what circumstances livestock-based interventions could play a role in malaria control programmes. This was explored by developing a mathematical model and combining it with data from Pakistan and Ethiopia. Consistent with previous work, a zooprophylactic effect of untreated livestock is predicted in two situations: if vector population density does not increase with livestock introduction, or if livestock numbers and availability to vectors are sufficiently high such that the increase in vector density is counteracted by the diversion of bites from humans to animals. Although, as expected, insecticide-treatment of livestock is predicted to be more beneficial in settings with highly zoophilic vectors, like South Asia, we find that the intervention could also considerably decrease malaria transmission in regions with more anthropophilic vectors, like Anopheles arabiensis in Africa, under specific circumstances: high treatment coverage of the livestock population, using a product with stronger or longer lasting insecticidal effect than in the Pakistan trial, and with small (ideally null) repellency effect, or if increasing the attractiveness of treated livestock to malaria vectors. The results suggest these are the most appropriate conditions for field testing insecticide-treated livestock in an Africa region with moderately zoophilic vectors, where this intervention could contribute to the integrated control of malaria and livestock diseases. PMID:25050703

Knowledge, Attitude and Practices of Vector-Borne Disease Prevention during the Emergence of a New Arbovirus: Implications for the Control of Chikungunya Virus in French Guiana.

PubMed

Fritzell, Camille; Raude, Jocelyn; Adde, Antoine; Dusfour, Isabelle; Quenel, Philippe; Flamand, Claude

2016-11-01

During the last decade, French Guiana has been affected by major dengue fever outbreaks. Although this arbovirus has been a focus of many awareness campaigns, very little information is available about beliefs, attitudes and behaviors regarding vector-borne diseases among the population of French Guiana. During the first outbreak of the chikungunya virus, a quantitative survey was conducted among high school students to study experiences, practices and perceptions related to mosquito-borne diseases and to identify socio-demographic, cognitive and environmental factors that could be associated with the engagement in protective behaviors. A cross-sectional survey was administered in May 2014, with a total of 1462 students interviewed. Classrooms were randomly selected using a two-stage selection procedure with cluster samples. A multiple correspondence analysis (MCA) associated with a hierarchical cluster analysis and with an ordinal logistic regression was performed. Chikungunya was less understood and perceived as a more dreadful disease than dengue fever. The analysis identified three groups of individual protection levels against mosquito-borne diseases: "low" (30%), "moderate" (42%) and "high" (28%)". Protective health behaviors were found to be performed more frequently among students who were female, had a parent with a higher educational status, lived in an individual house, and had a better understanding of the disease. This study allowed us to estimate the level of protective practices against vector-borne diseases among students after the emergence of a new arbovirus. These results revealed that the adoption of protective behaviors is a multi-factorial process that depends on both sociocultural and cognitive factors. These findings may help public health authorities to strengthen communication and outreach strategies, thereby increasing the adoption of protective health behaviors, particularly in high-risk populations.

Ultra-Reliable Digital Avionics (URDA) processor

NASA Astrophysics Data System (ADS)

Branstetter, Reagan; Ruszczyk, William; Miville, Frank

1994-10-01

Texas Instruments Incorporated (TI) developed the URDA processor design under contract with the U.S. Air Force Wright Laboratory and the U.S. Army Night Vision and Electro-Sensors Directorate. TI's approach couples advanced packaging solutions with advanced integrated circuit (IC) technology to provide a high-performance (200 MIPS/800 MFLOPS) modular avionics processor module for a wide range of avionics applications. TI's processor design integrates two Ada-programmable, URDA basic processor modules (BPM's) with a JIAWG-compatible PiBus and TMBus on a single F-22 common integrated processor-compatible form-factor SEM-E avionics card. A separate, high-speed (25-MWord/second 32-bit word) input/output bus is provided for sensor data. Each BPM provides a peak throughput of 100 MIPS scalar concurrent with 400-MFLOPS vector processing in a removable multichip module (MCM) mounted to a liquid-flowthrough (LFT) core and interfacing to a processor interface module printed wiring board (PWB). Commercial RISC technology coupled with TI's advanced bipolar complementary metal oxide semiconductor (BiCMOS) application specific integrated circuit (ASIC) and silicon-on-silicon packaging technologies are used to achieve the high performance in a miniaturized package. A Mips R4000-family reduced instruction set computer (RISC) processor and a TI 100-MHz BiCMOS vector coprocessor (VCP) ASIC provide, respectively, the 100 MIPS of a scalar processor throughput and 400 MFLOPS of vector processing throughput for each BPM. The TI Aladdim ASIC chipset was developed on the TI Aladdin Program under contract with the U.S. Army Communications and Electronics Command and was sponsored by the Advanced Research Projects Agency with technical direction from the U.S. Army Night Vision and Electro-Sensors Directorate.

Prostate Cancer Evaluation: Design, Synthesis and Evaluation of Novel Enzyme-Activated Proton MRI Contrast Agents

DTIC Science & Technology

2009-10-01

NUMBER E -Mail: 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER...transcriptional activation, protein expression, and protein interaction, lacZ gene encoding E . coli β-gal has already been recognized as the most...1) Cell preparation (a) Stably transfected PC3 cell line: E . coli lacZ gene (from pSV-β-gal vector, Promega, Madison,WI) was inserted into high

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

NASA Technical Reports Server (NTRS)

Larson, J. W.; Guo, J.; Lyster, P. M.

1999-01-01

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines

PubMed Central

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-01-01

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately. PMID:27879843

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines.

PubMed

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-04-15

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately.

An economic evaluation of vector control in the age of a dengue vaccine.

PubMed

Fitzpatrick, Christopher; Haines, Alexander; Bangert, Mathieu; Farlow, Andrew; Hemingway, Janet; Velayudhan, Raman

2017-08-01

Dengue is a rapidly emerging vector-borne Neglected Tropical Disease, with a 30-fold increase in the number of cases reported since 1960. The economic cost of the illness is measured in the billions of dollars annually. Environmental change and unplanned urbanization are conspiring to raise the health and economic cost even further beyond the reach of health systems and households. The health-sector response has depended in large part on control of the Aedes aegypti and Ae. albopictus (mosquito) vectors. The cost-effectiveness of the first-ever dengue vaccine remains to be evaluated in the field. In this paper, we examine how it might affect the cost-effectiveness of sustained vector control. We employ a dynamic Markov model of the effects of vector control on dengue in both vectors and humans over a 15-year period, in six countries: Brazil, Columbia, Malaysia, Mexico, the Philippines, and Thailand. We evaluate the cost (direct medical costs and control programme costs) and cost-effectiveness of sustained vector control, outbreak response and/or medical case management, in the presence of a (hypothetical) highly targeted and low cost immunization strategy using a (non-hypothetical) medium-efficacy vaccine. Sustained vector control using existing technologies would cost little more than outbreak response, given the associated costs of medical case management. If sustained use of existing or upcoming technologies (of similar price) reduce vector populations by 70-90%, the cost per disability-adjusted life year averted is 2013 US$ 679-1331 (best estimates) relative to no intervention. Sustained vector control could be highly cost-effective even with less effective technologies (50-70% reduction in vector populations) and in the presence of a highly targeted and low cost immunization strategy using a medium-efficacy vaccine. Economic evaluation of the first-ever dengue vaccine is ongoing. However, even under very optimistic assumptions about a highly targeted and low cost immunization strategy, our results suggest that sustained vector control will continue to play an important role in mitigating the impact of environmental change and urbanization on human health. If additional benefits for the control of other Aedes borne diseases, such as Chikungunya, yellow fever and Zika fever are taken into account, the investment case is even stronger. High-burden endemic countries should proceed to map populations to be covered by sustained vector control.

An economic evaluation of vector control in the age of a dengue vaccine

PubMed Central

Haines, Alexander; Bangert, Mathieu; Farlow, Andrew; Hemingway, Janet; Velayudhan, Raman

2017-01-01

Introduction Dengue is a rapidly emerging vector-borne Neglected Tropical Disease, with a 30-fold increase in the number of cases reported since 1960. The economic cost of the illness is measured in the billions of dollars annually. Environmental change and unplanned urbanization are conspiring to raise the health and economic cost even further beyond the reach of health systems and households. The health-sector response has depended in large part on control of the Aedes aegypti and Ae. albopictus (mosquito) vectors. The cost-effectiveness of the first-ever dengue vaccine remains to be evaluated in the field. In this paper, we examine how it might affect the cost-effectiveness of sustained vector control. Methods We employ a dynamic Markov model of the effects of vector control on dengue in both vectors and humans over a 15-year period, in six countries: Brazil, Columbia, Malaysia, Mexico, the Philippines, and Thailand. We evaluate the cost (direct medical costs and control programme costs) and cost-effectiveness of sustained vector control, outbreak response and/or medical case management, in the presence of a (hypothetical) highly targeted and low cost immunization strategy using a (non-hypothetical) medium-efficacy vaccine. Results Sustained vector control using existing technologies would cost little more than outbreak response, given the associated costs of medical case management. If sustained use of existing or upcoming technologies (of similar price) reduce vector populations by 70–90%, the cost per disability-adjusted life year averted is 2013 US$ 679–1331 (best estimates) relative to no intervention. Sustained vector control could be highly cost-effective even with less effective technologies (50–70% reduction in vector populations) and in the presence of a highly targeted and low cost immunization strategy using a medium-efficacy vaccine. Discussion Economic evaluation of the first-ever dengue vaccine is ongoing. However, even under very optimistic assumptions about a highly targeted and low cost immunization strategy, our results suggest that sustained vector control will continue to play an important role in mitigating the impact of environmental change and urbanization on human health. If additional benefits for the control of other Aedes borne diseases, such as Chikungunya, yellow fever and Zika fever are taken into account, the investment case is even stronger. High-burden endemic countries should proceed to map populations to be covered by sustained vector control. PMID:28806786

A vectorized Poisson solver over a spherical shell and its application to the quasi-geostrophic omega-equation

NASA Technical Reports Server (NTRS)

Mullenmeister, Paul

1988-01-01

The quasi-geostrophic omega-equation in flux form is developed as an example of a Poisson problem over a spherical shell. Solutions of this equation are obtained by applying a two-parameter Chebyshev solver in vector layout for CDC 200 series computers. The performance of this vectorized algorithm greatly exceeds the performance of its scalar analog. The algorithm generates solutions of the omega-equation which are compared with the omega fields calculated with the aid of the mass continuity equation.

Chimeric Bovine/Human Parainfluenza Virus Type 3 Expressing Respiratory Syncytial Virus (RSV) F Glycoprotein: Effect of Insert Position on Expression, Replication, Immunogenicity, Stability, and Protection against RSV Infection

PubMed Central

Munir, Shirin; Amaro-Carambot, Emerito; Surman, Sonja; Mackow, Natalie; Yang, Lijuan; Buchholz, Ursula J.; Collins, Peter L.; Schaap-Nutt, Anne

2014-01-01

ABSTRACT A recombinant chimeric bovine/human parainfluenza type 3 virus (rB/HPIV3) vector expressing the respiratory syncytial virus (RSV) fusion F glycoprotein previously exhibited disappointing levels of RSV F immunogenicity and genetic stability in children (D. Bernstein et al., Pediatr. Infect. Dis. J. 31:109–114, 2012; C.-F. Yang et al., Vaccine 31:2822–2827, 2013). To investigate parameters that might affect vaccine performance and stability, we constructed and characterized rB/HPIV3 viruses expressing RSV F from the first (pre-N), second (N-P), third (P-M), and sixth (HN-L) genome positions. There was a 30- to 69-fold gradient in RSV F expression from the first to the sixth position. The inserts moderately attenuated vector replication in vitro and in the upper and lower respiratory tracts of hamsters: this was not influenced by the level of RSV F expression and syncytium formation. Surprisingly, inserts in the second, third, and sixth positions conferred increased temperature sensitivity: this was greatest for the third position and was the most attenuating in vivo. Each rB/HPIV3 vector induced a high titer of neutralizing antibodies in hamsters against RSV and HPIV3. Protection against RSV challenge was greater for position 2 than for position 6. Evaluation of insert stability suggested that RSV F is under selective pressure to be silenced during vector replication in vivo, but this was not exacerbated by a high level of RSV F expression and generally involved a small percentage of recovered vector. Vector passaged in vitro accumulated mutations in the HN open reading frame, causing a dramatic increase in plaque size that may have implications for vaccine production and immunogenicity. IMPORTANCE The research findings presented here will be instrumental for improving the design of a bivalent pediatric vaccine for respiratory syncytial virus and parainfluenza virus type 3, two major causes of severe respiratory tract infection in infants and young children. Moreover, this knowledge has general application to the development and clinical evaluation of other mononegavirus vectors and vaccines. PMID:24478424

Large Animal Models for Foamy Virus Vector Gene Therapy

PubMed Central

Trobridge, Grant D.; Horn, Peter A.; Beard, Brian C.; Kiem, Hans-Peter

2012-01-01

Foamy virus (FV) vectors have shown great promise for hematopoietic stem cell (HSC) gene therapy. Their ability to efficiently deliver transgenes to multi-lineage long-term repopulating cells in large animal models suggests they will be effective for several human hematopoietic diseases. Here, we review FV vector studies in large animal models, including the use of FV vectors with the mutant O6-methylguanine-DNA methyltransferase, MGMTP140K to increase the number of genetically modified cells after transplantation. In these studies, FV vectors have mediated efficient gene transfer to polyclonal repopulating cells using short ex vivo transduction protocols designed to minimize the negative effects of ex vivo culture on stem cell engraftment. In this regard, FV vectors appear superior to gammaretroviral vectors, which require longer ex vivo culture to effect efficient transduction. FV vectors have also compared favorably with lentiviral vectors when directly compared in the dog model. FV vectors have corrected leukocyte adhesion deficiency and pyruvate kinase deficiency in the dog large animal model. FV vectors also appear safer than gammaretroviral vectors based on a reduced frequency of integrants near promoters and also near proto-oncogenes in canine repopulating cells. Together, these studies suggest that FV vectors should be highly effective for several human hematopoietic diseases, including those that will require relatively high percentages of gene-modified cells to achieve clinical benefit. PMID:23223198

Generation and characterization of a novel candidate gene therapy and vaccination vector based on human species D adenovirus type 56.

PubMed

Duffy, Margaret R; Alonso-Padilla, Julio; John, Lijo; Chandra, Naresh; Khan, Selina; Ballmann, Monika Z; Lipiec, Agnieszka; Heemskerk, Evert; Custers, Jerome; Arnberg, Niklas; Havenga, Menzo; Baker, Andrew H; Lemckert, Angelique

2018-01-01

The vectorization of rare human adenovirus (HAdV) types will widen our knowledge of this family and their interaction with cells, tissues and organs. In this study we focus on HAdV-56, a member of human Ad species D, and create ease-of-use cloning systems to generate recombinant HAdV-56 vectors carrying foreign genes. We present in vitro transduction profiles for HAdV-56 in direct comparison to the most commonly used HAdV-5-based vector. In vivo characterizations demonstrate that when it is delivered intravenously (i.v.) HAdV-56 mainly targets the spleen and, to a lesser extent, the lungs, whilst largely bypassing liver transduction in mice. HAdV-56 triggered robust inflammatory and cellular immune responses, with higher induction of IFNγ, TNFα, IL5, IL6, IP10, MCP1 and MIG1 compared to HAdV-5 following i.v. administration. We also investigated its potential as a vaccine vector candidate by performing prime immunizations in mice with HAdV-56 encoding luciferase (HAdV-56-Luc). Direct comparisons were made to HAdV-26, a highly potent human vaccine vector currently in phase II clinical trials. HAdV-56-Luc induced luciferase 'antigen'-specific IFNγ-producing cells and anti-HAdV-56 neutralizing antibodies in Balb/c mice, demonstrating a near identical profile to that of HAdV-26. Taken together, the data presented provides further insight into human Ad receptor/co-receptor usage, and the first report on HAdV-56 vectors and their potential for gene therapy and vaccine applications.

Targeted Screening Strategies to Detect Trypanosoma cruzi Infection in Children

PubMed Central

Levy, Michael Z.; Kawai, Vivian; Bowman, Natalie M.; Waller, Lance A.; Cabrera, Lilia; Pinedo-Cancino, Viviana V.; Seitz, Amy E.; Steurer, Frank J.; Cornejo del Carpio, Juan G.; Cordova-Benzaquen, Eleazar; Maguire, James H.; Gilman, Robert H.; Bern, Caryn

2007-01-01

Background Millions of people are infected with Trypanosoma cruzi, the causative agent of Chagas disease in Latin America. Anti-trypanosomal drug therapy can cure infected individuals, but treatment efficacy is highest early in infection. Vector control campaigns disrupt transmission of T. cruzi, but without timely diagnosis, children infected prior to vector control often miss the window of opportunity for effective chemotherapy. Methods and Findings We performed a serological survey in children 2–18 years old living in a peri-urban community of Arequipa, Peru, and linked the results to entomologic, spatial and census data gathered during a vector control campaign. 23 of 433 (5.3% [95% CI 3.4–7.9]) children were confirmed seropositive for T. cruzi infection by two methods. Spatial analysis revealed that households with infected children were very tightly clustered within looser clusters of households with parasite-infected vectors. Bayesian hierarchical mixed models, which controlled for clustering of infection, showed that a child's risk of being seropositive increased by 20% per year of age and 4% per vector captured within the child's house. Receiver operator characteristic (ROC) plots of best-fit models suggest that more than 83% of infected children could be identified while testing only 22% of eligible children. Conclusions We found evidence of spatially-focal vector-borne T. cruzi transmission in peri-urban Arequipa. Ongoing vector control campaigns, in addition to preventing further parasite transmission, facilitate the collection of data essential to identifying children at high risk of T. cruzi infection. Targeted screening strategies could make integration of diagnosis and treatment of children into Chagas disease control programs feasible in lower-resource settings. PMID:18160979

Superconducting Quantum Interference Device Array Based High Frequency Direction Finding on an Airborne Platform

DTIC Science & Technology

is performed using the MUSIC algorithm on the signals received on the non-uniform phased array, and the ESPRIT algorithm is used on the signals...received on the non-colocated vector sensor. The simulation results show that the MUSIC algorithm using 2D Bi-SQUIDs is able to differentiate two signals

Insect cell transformation vectors that support high level expression and promoter assessment in insect cell culture

USDA-ARS?s Scientific Manuscript database

A somatic transformation vector, pDP9, was constructed that provides a simplified means of producing permanently transformed cultured insect cells that support high levels of protein expression of foreign genes. The pDP9 plasmid vector incorporates DNA sequences from the Junonia coenia densovirus th...

Intelligent Optimization of the Film-to-Fiber Ratio of a Degradable Braided Bicomponent Ureteral Stent

PubMed Central

Liu, Xiaoyan; Li, Feng; Ding, Yongsheng; Zou, Ting; Wang, Lu; Hao, Kuangrong

2015-01-01

A hierarchical support vector regression (SVR) model (HSVRM) was employed to correlate the compositions and mechanical properties of bicomponent stents composed of poly(lactic-co-glycolic acid) (PGLA) film and poly(glycolic acid) (PGA) fibers for urethral repair for the first time. PGLA film and PGA fibers could provide ureteral stents with good compressive and tensile properties, respectively. In bicomponent stents, high film content led to high stiffness, while high fiber content resulted in poor compressional properties. To simplify the procedures to optimize the ratio of PGLA film and PGA fiber in the stents, a hierarchical support vector regression model (HSVRM) and particle swarm optimization (PSO) algorithm were used to construct relationships between the film-to-fiber weight ratio and the measured compressional/tensile properties of the stents. The experimental data and simulated data fit well, proving that the HSVRM could closely reflect the relationship between the component ratio and performance properties of the ureteral stents. PMID:28793658

Effects of OCR Errors on Ranking and Feedback Using the Vector Space Model.

ERIC Educational Resources Information Center

Taghva, Kazem; And Others

1996-01-01

Reports on the performance of the vector space model in the presence of OCR (optical character recognition) errors in information retrieval. Highlights include precision and recall, a full-text test collection, smart vector representation, impact of weighting parameters, ranking variability, and the effect of relevance feedback. (Author/LRW)

Spin Chirality of Cu3 and V3 Nanomagnets. 1. Rotation Behavior of Vector Chirality, Scalar Chirality, and Magnetization in the Rotating Magnetic Field, Magnetochiral Correlations.

PubMed

Belinsky, Moisey I

2016-05-02

The rotation behavior of the vector chirality κ, scalar chirality χ, and magnetization M in the rotating magnetic field H1 is considered for the V3 and Cu3 nanomagnets, in which the Dzialoshinsky-Moriya coupling is active. The polar rotation of the field H1 of the given strength H1 results in the energy spectrum characterized by different vector and scalar chiralities in the ground and excited states. The magnetochiral correlations between the vector and scalar chiralities, energy, and magnetization in the rotating field were considered. Under the uniform polar rotation of the field H1, the ground-state chirality vector κI performs sawtooth oscillations and the magnetization vector MI performs the sawtooth oscillating rotation that is accompanied by the correlated transformation of the scalar chirality χI. This demonstrates the magnetochiral effect of the joint rotation behavior and simultaneous frustrations of the spin chiralities and magnetization in the rotating field, which are governed by the correlation between the chiralities and magnetization.

Harmonic reduction of Direct Torque Control of six-phase induction motor.

PubMed

Taheri, A

2016-07-01

In this paper, a new switching method in Direct Torque Control (DTC) of a six-phase induction machine for reduction of current harmonics is introduced. Selecting a suitable vector in each sampling period is an ordinal method in the ST-DTC drive of a six-phase induction machine. The six-phase induction machine has 64 voltage vectors and divided further into four groups. In the proposed DTC method, the suitable voltage vectors are selected from two vector groups. By a suitable selection of two vectors in each sampling period, the harmonic amplitude is decreased more, in and various comparison to that of the ST-DTC drive. The harmonics loss is greater reduced, while the electromechanical energy is decreased with switching loss showing a little increase. Spectrum analysis of the phase current in the standard and new switching table DTC of the six-phase induction machine and determination for the amplitude of each harmonics is proposed in this paper. The proposed method has a less sampling time in comparison to the ordinary method. The Harmonic analyses of the current in the low and high speed shows the performance of the presented method. The simplicity of the proposed method and its implementation without any extra hardware is other advantages of the proposed method. The simulation and experimental results show the preference of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A scalable method for the production of high-titer and high-quality adeno-associated type 9 vectors using the HSV platform

PubMed Central

Adamson-Small, Laura; Potter, Mark; Falk, Darin J; Cleaver, Brian; Byrne, Barry J; Clément, Nathalie

2016-01-01

Recombinant adeno-associated vectors based on serotype 9 (rAAV9) have demonstrated highly effective gene transfer in multiple animal models of muscular dystrophies and other neurological indications. Current limitations in vector production and purification have hampered widespread implementation of clinical candidate vectors, particularly when systemic administration is considered. In this study, we describe a complete herpes simplex virus (HSV)-based production and purification process capable of generating greater than 1 × 1014 rAAV9 vector genomes per 10-layer CellSTACK of HEK 293 producer cells, or greater than 1 × 105 vector genome per cell, in a final, fully purified product. This represents a 5- to 10-fold increase over transfection-based methods. In addition, rAAV vectors produced by this method demonstrated improved biological characteristics when compared to transfection-based production, including increased infectivity as shown by higher transducing unit-to-vector genome ratios and decreased total capsid protein amounts, shown by lower empty-to-full ratios. Together, this data establishes a significant improvement in both rAAV9 yields and vector quality. Further, the method can be readily adapted to large-scale good laboratory practice (GLP) and good manufacturing practice (GMP) production of rAAV9 vectors to enable preclinical and clinical studies and provide a platform to build on toward late-phases and commercial production. PMID:27222839

RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences.

PubMed

An, Ji-Yong; You, Zhu-Hong; Meng, Fan-Rong; Xu, Shu-Juan; Wang, Yin

2016-05-18

Protein-Protein Interactions (PPIs) play essential roles in most cellular processes. Knowledge of PPIs is becoming increasingly more important, which has prompted the development of technologies that are capable of discovering large-scale PPIs. Although many high-throughput biological technologies have been proposed to detect PPIs, there are unavoidable shortcomings, including cost, time intensity, and inherently high false positive and false negative rates. For the sake of these reasons, in silico methods are attracting much attention due to their good performances in predicting PPIs. In this paper, we propose a novel computational method known as RVM-AB that combines the Relevance Vector Machine (RVM) model and Average Blocks (AB) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the AB feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We performed five-fold cross-validation experiments on yeast and Helicobacter pylori datasets, and achieved very high accuracies of 92.98% and 95.58% respectively, which is significantly better than previous works. In addition, we also obtained good prediction accuracies of 88.31%, 89.46%, 91.08%, 91.55%, and 94.81% on other five independent datasets C. elegans, M. musculus, H. sapiens, H. pylori, and E. coli for cross-species prediction. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM-AB method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool. To facilitate extensive studies for future proteomics research, we developed a freely available web server called RVMAB-PPI in Hypertext Preprocessor (PHP) for predicting PPIs. The web server including source code and the datasets are available at http://219.219.62.123:8888/ppi_ab/.

Full Wave Analysis of RF Signal Attenuation in a Lossy Rough Surface Cave using a High Order Time Domain Vector Finite Element Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pingenot, J; Rieben, R; White, D

2005-10-31

We present a computational study of signal propagation and attenuation of a 200 MHz planar loop antenna in a cave environment. The cave is modeled as a straight and lossy random rough wall. To simulate a broad frequency band, the full wave Maxwell equations are solved directly in the time domain via a high order vector finite element discretization using the massively parallel CEM code EMSolve. The numerical technique is first verified against theoretical results for a planar loop antenna in a smooth lossy cave. The simulation is then performed for a series of random rough surface meshes in ordermore » to generate statistical data for the propagation and attenuation properties of the antenna in a cave environment. Results for the mean and variance of the power spectral density of the electric field are presented and discussed.« less

A survey of upwind methods for flows with equilibrium and non-equilibrium chemistry and thermodynamics

NASA Technical Reports Server (NTRS)

Grossman, B.; Garrett, J.; Cinnella, P.

1989-01-01

Several versions of flux-vector split and flux-difference split algorithms were compared with regard to general applicability and complexity. Test computations were performed using curve-fit equilibrium air chemistry for an M = 5 high-temperature inviscid flow over a wedge, and an M = 24.5 inviscid flow over a blunt cylinder for test computations; for these cases, little difference in accuracy was found among the versions of the same flux-split algorithm. For flows with nonequilibrium chemistry, the effects of the thermodynamic model on the development of flux-vector split and flux-difference split algorithms were investigated using an equilibrium model, a general nonequilibrium model, and a simplified model based on vibrational relaxation. Several numerical examples are presented, including nonequilibrium air chemistry in a high-temperature shock tube and nonequilibrium hydrogen-air chemistry in a supersonic diffuser.

Charge density wave properties of the quasi two-dimensional purple molybdenum bronze KMo 6O 17

NASA Astrophysics Data System (ADS)

Balaska, H.; Dumas, J.; Guyot, H.; Mallet, P.; Marcus, J.; Schlenker, C.; Veuillen, J. Y.; Vignolles, D.

2005-06-01

The purple molybdenum bronze KMo 6O 17 is a quasi-two-dimensional compound which shows a Peierls transition towards a commensurate metallic CDW state. Electron spectroscopy (ARUPS), Scanning Tunnelling Microscopy (STM) and spectroscopy (STS) as well as high magnetic field studies are reported. ARUPS studies corroborate the model of the hidden nesting and provide a value of the CDW vector in good agreement with other measurements. STM studies visualize the triple- q CDW in real space. This is consistent with other measurements of the CDW vector. STS studies provide a value of several 10 meV for the average CDW gap. High magnetic field measurements performed in pulsed fields up to 55 T establish that first order transitions to smaller gap states take place at low temperature. These transitions are ascribed to Pauli type coupling. A phase diagram summarizing all observed anomalies and transitions is presented.

Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome.

PubMed

Mallory, Emily K; Acharya, Ambika; Rensi, Stefano E; Turnbaugh, Peter J; Bright, Roselie A; Altman, Russ B

2018-01-01

Bacteria in the human gut have the ability to activate, inactivate, and reactivate drugs with both intended and unintended effects. For example, the drug digoxin is reduced to the inactive metabolite dihydrodigoxin by the gut Actinobacterium E. lenta, and patients colonized with high levels of drug metabolizing strains may have limited response to the drug. Understanding the complete space of drugs that are metabolized by the human gut microbiome is critical for predicting bacteria-drug relationships and their effects on individual patient response. Discovery and validation of drug metabolism via bacterial enzymes has yielded >50 drugs after nearly a century of experimental research. However, there are limited computational tools for screening drugs for potential metabolism by the gut microbiome. We developed a pipeline for comparing and characterizing chemical transformations using continuous vector representations of molecular structure learned using unsupervised representation learning. We applied this pipeline to chemical reaction data from MetaCyc to characterize the utility of vector representations for chemical reaction transformations. After clustering molecular and reaction vectors, we performed enrichment analyses and queries to characterize the space. We detected enriched enzyme names, Gene Ontology terms, and Enzyme Consortium (EC) classes within reaction clusters. In addition, we queried reactions against drug-metabolite transformations known to be metabolized by the human gut microbiome. The top results for these known drug transformations contained similar substructure modifications to the original drug pair. This work enables high throughput screening of drugs and their resulting metabolites against chemical reactions common to gut bacteria.

Selection vector filter framework

NASA Astrophysics Data System (ADS)

Lukac, Rastislav; Plataniotis, Konstantinos N.; Smolka, Bogdan; Venetsanopoulos, Anastasios N.

2003-10-01

We provide a unified framework of nonlinear vector techniques outputting the lowest ranked vector. The proposed framework constitutes a generalized filter class for multichannel signal processing. A new class of nonlinear selection filters are based on the robust order-statistic theory and the minimization of the weighted distance function to other input samples. The proposed method can be designed to perform a variety of filtering operations including previously developed filtering techniques such as vector median, basic vector directional filter, directional distance filter, weighted vector median filters and weighted directional filters. A wide range of filtering operations is guaranteed by the filter structure with two independent weight vectors for angular and distance domains of the vector space. In order to adapt the filter parameters to varying signal and noise statistics, we provide also the generalized optimization algorithms taking the advantage of the weighted median filters and the relationship between standard median filter and vector median filter. Thus, we can deal with both statistical and deterministic aspects of the filter design process. It will be shown that the proposed method holds the required properties such as the capability of modelling the underlying system in the application at hand, the robustness with respect to errors in the model of underlying system, the availability of the training procedure and finally, the simplicity of filter representation, analysis, design and implementation. Simulation studies also indicate that the new filters are computationally attractive and have excellent performance in environments corrupted by bit errors and impulsive noise.

A comparison of in situ measurements of vector-E and - vector-V x vector-B from Dynamics Explorer 2

NASA Technical Reports Server (NTRS)

Hanson, W. B.; Coley, W. R.; Heelis, R. A.; Maynard, N. C.; Aggson, T. L.

1993-01-01

Dynamics Explorer-2 provided the first opportunity to make a direct comparison of in situ measurements of the high-latitude convection electric field by two distinctly different techniques. The vector electric field instrument (VEFI) used antennae to measure the intrinsic electric fields and the ion drift meter (IDM) and retarding potential analyzer (RPA) measured the ion drift velocity vector, from which the convection electric field can be deduced. The data from three orbits having large electric fields at high latitude are presented, one at high, one at medium, and one at low altitudes. The general agreement between the two measurements of electric field is very good, with typical differences at high latitudes of the order of a few millivolts per meter, but there are some regions where the particle fluxes are extremely large (e.g., the cusp) and the disagreement is worse, probably because of IDM difficulties. The auroral zone potential patterns derived from the two devices are in excellent agreement for two of the cases, but not in the third, where bad attitude data may be the problem. At low latitudes there are persistent differences in the measurements of a few millivolts per meter, though these differences are quite constant from orbit to orbit. This problem seems to arise from some shortcoming in the VEFI measurments. Overall, however, these measurements confirm the concept of `frozen-in' plasma that drifts with velocity vector-E x vector-B/B(exp 2) within the measurement errors of the two techniques.

Quantitative evaluation of a thrust vector controlled transport at the conceptual design phase

NASA Astrophysics Data System (ADS)

Ricketts, Vincent Patrick

The impetus to innovate, to push the bounds and break the molds of evolutionary design trends, often comes from competition but sometimes requires catalytic political legislature. For this research endeavor, the 'catalyzing legislation' comes in response to the rise in cost of fossil fuels and the request put forth by NASA on aircraft manufacturers to show reduced aircraft fuel consumption of +60% within 30 years. This necessitates that novel technologies be considered to achieve these values of improved performance. One such technology is thrust vector control (TVC). The beneficial characteristic of thrust vector control technology applied to the traditional tail-aft configuration (TAC) commercial transport is its ability to retain the operational advantage of this highly evolved aircraft type like cabin evacuation, ground operation, safety, and certification. This study explores if the TVC transport concept offers improved flight performance due to synergistically reducing the traditional empennage size, overall resulting in reduced weight and drag, and therefore reduced aircraft fuel consumption. In particular, this study explores if the TVC technology in combination with the reduced empennage methodology enables the TAC aircraft to synergistically evolve while complying with current safety and certification regulation. This research utilizes the multi-disciplinary parametric sizing software, AVD Sizing, developed by the Aerospace Vehicle Design (AVD) Laboratory. The sizing software is responsible for visualizing the total system solution space via parametric trades and is capable of determining if the TVC technology can enable the TAC aircraft to synergistically evolve, showing marked improvements in performance and cost. This study indicates that the TVC plus reduced empennage methodology shows marked improvements in performance and cost.

The evolution of adenoviral vectors through genetic and chemical surface modifications.

PubMed

Capasso, Cristian; Garofalo, Mariangela; Hirvinen, Mari; Cerullo, Vincenzo

2014-02-17

A long time has passed since the first clinical trial with adenoviral (Ad) vectors. Despite being very promising, Ad vectors soon revealed their limitations in human clinical trials. The pre-existing immunity, the marked liver tropism and the high toxicity of first generation Ad (FG-Ad) vectors have been the main challenges for the development of new approaches. Significant effort toward the development of genetically and chemically modified adenoviral vectors has enabled researchers to create more sophisticated vectors for gene therapy, with an improved safety profile and a higher transduction ability of different tissues. In this review, we will describe the latest findings in the high-speed, evolving field of genetic and chemical modifications of adenoviral vectors, a field in which different disciplines, such as biomaterial research, virology and immunology, co-operate synergistically to create better gene therapy tools for modern challenges.

Internal Performance of a Fixed-Shroud Nonaxisymmetric Nozzle Equipped with an Aft-Hood Exhaust Deflector

NASA Technical Reports Server (NTRS)

Asbury, Scott C.

1997-01-01

An investigation was conducted in the model preparation area of the Langley 16-Foot Transonic Tunnel to determine the internal performance of a fixed-shroud nonaxisymmetric nozzle equipped with an aft-hood exhaust deflector. Model geometric parameters investigated included nozzle power setting, aft-hood deflector angle, throat area control with the aft-hood deflector deployed, and yaw vector angle. Results indicate that cruise configurations produced peak performance in the range consistent with previous investigations of nonaxisymmetric convergent-divergent nozzles. The aft-hood deflector produced resultant pitch vector angles that were always less than the geometric aft-hood deflector angle when the nozzle throat was positioned upstream of the deflector exit. Significant losses in resultant thrust ratio occurred when the aft-hood deflector was deployed with an upstream throat location. At each aft-hood deflector angle, repositioning the throat to the deflector exit improved pitch vectoring performance and, in some cases, substantially improved resultant thrust ratio performance. Transferring the throat to the deflector exit allowed the flow to be turned upstream of the throat at subsonic Mach numbers, thereby eliminating losses associated with turning supersonic flow. Internal throat panel deflections were largely unsuccessful in generating yaw vectoring.

Forces on intraocular lens haptics induced by capsular fibrosis. An experimental study.

PubMed

Guthoff, R; Abramo, F; Draeger, J; Chumbley, L C; Lang, G K; Neumann, W

1990-01-01

Electronic dynamometry measurements, performed upon intraocular lens (IOL) haptics of prototype one-piece three-loop silicone lenses, accurately defined the relationships between elastic force and haptic displacement. Lens implantations in the capsular bag of dogs (loop span equal to capsular bag diameter, loops underformed immediately after the operation) were evaluated macrophotographically 5-8 months postoperatively. The highly constant elastic property of silicon rubber permitted quantitative correlation of subsequent in vivo haptic displacement with the resultant force vectors responsible for tissue contraction. The lens optics were well centered in 17 (85%) and slightly offcenter in 3 (15%) of 20 implanted eyes. Of the 60 supporting loops, 28 could be visualized sufficiently well to permit reliable haptic measurement. Of these 28, 20 (71%) were clearly displaced, ranging from 0.45 mm away from to 1.4 mm towards the lens' optic center. These extremes represented resultant vector forces of 0.20 and 1.23 mN respectively. Quantitative vector analysis permits better understanding of IOL-capsular interactions.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

NASA Astrophysics Data System (ADS)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

Color image segmentation with support vector machines: applications to road signs detection.

PubMed

Cyganek, Bogusław

2008-08-01

In this paper we propose efficient color segmentation method which is based on the Support Vector Machine classifier operating in a one-class mode. The method has been developed especially for the road signs recognition system, although it can be used in other applications. The main advantage of the proposed method comes from the fact that the segmentation of characteristic colors is performed not in the original but in the higher dimensional feature space. By this a better data encapsulation with a linear hypersphere can be usually achieved. Moreover, the classifier does not try to capture the whole distribution of the input data which is often difficult to achieve. Instead, the characteristic data samples, called support vectors, are selected which allow construction of the tightest hypersphere that encloses majority of the input data. Then classification of a test data simply consists in a measurement of its distance to a centre of the found hypersphere. The experimental results show high accuracy and speed of the proposed method.

Decomposition of group-velocity-locked-vector-dissipative solitons and formation of the high-order soliton structure by the product of their recombination.

PubMed

Wang, Xuan; Li, Lei; Geng, Ying; Wang, Hanxiao; Su, Lei; Zhao, Luming

2018-02-01

By using a polarization manipulation and projection system, we numerically decomposed the group-velocity-locked-vector-dissipative solitons (GVLVDSs) from a normal dispersion fiber laser and studied the combination of the projections of the phase-modulated components of the GVLVDS through a polarization beam splitter. Pulses with a structure similar to a high-order vector soliton could be obtained, which could be considered as a pseudo-high-order GVLVDS. It is found that, although GVLVDSs are intrinsically different from group-velocity-locked-vector solitons generated in fiber lasers operated in the anomalous dispersion regime, similar characteristics for the generation of pseudo-high-order GVLVDS are obtained. However, pulse chirp plays a significant role on the generation of pseudo-high-order GVLVDS.

Application of a VLSI vector quantization processor to real-time speech coding

NASA Technical Reports Server (NTRS)

Davidson, G.; Gersho, A.

1986-01-01

Attention is given to a working vector quantization processor for speech coding that is based on a first-generation VLSI chip which efficiently performs the pattern-matching operation needed for the codebook search process (CPS). Using this chip, the CPS architecture has been successfully incorporated into a compact, single-board Vector PCM implementation operating at 7-18 kbits/sec. A real time Adaptive Vector Predictive Coder system using the CPS has also been implemented.

Walsh-Hadamard transform kernel-based feature vector for shot boundary detection.

PubMed

Lakshmi, Priya G G; Domnic, S

2014-12-01

Video shot boundary detection (SBD) is the first step of video analysis, summarization, indexing, and retrieval. In SBD process, videos are segmented into basic units called shots. In this paper, a new SBD method is proposed using color, edge, texture, and motion strength as vector of features (feature vector). Features are extracted by projecting the frames on selected basis vectors of Walsh-Hadamard transform (WHT) kernel and WHT matrix. After extracting the features, based on the significance of the features, weights are calculated. The weighted features are combined to form a single continuity signal, used as input for Procedure Based shot transition Identification process (PBI). Using the procedure, shot transitions are classified into abrupt and gradual transitions. Experimental results are examined using large-scale test sets provided by the TRECVID 2007, which has evaluated hard cut and gradual transition detection. To evaluate the robustness of the proposed method, the system evaluation is performed. The proposed method yields F1-Score of 97.4% for cut, 78% for gradual, and 96.1% for overall transitions. We have also evaluated the proposed feature vector with support vector machine classifier. The results show that WHT-based features can perform well than the other existing methods. In addition to this, few more video sequences are taken from the Openvideo project and the performance of the proposed method is compared with the recent existing SBD method.

Flow velocity vector fields by ultrasound particle imaging velocimetry: in vitro comparison with optical flow velocimetry.

PubMed

Westerdale, John; Belohlavek, Marek; McMahon, Eileen M; Jiamsripong, Panupong; Heys, Jeffrey J; Milano, Michele

2011-02-01

We performed an in vitro study to assess the precision and accuracy of particle imaging velocimetry (PIV) data acquired using a clinically available portable ultrasound system via comparison with stereo optical PIV. The performance of ultrasound PIV was compared with optical PIV on a benchmark problem involving vortical flow with a substantial out-of-plane velocity component. Optical PIV is capable of stereo image acquisition, thus measuring out-of-plane velocity components. This allowed us to quantify the accuracy of ultrasound PIV, which is limited to in-plane acquisition. The system performance was assessed by considering the instantaneous velocity fields without extracting velocity profiles by spatial averaging. Within the 2-dimensional correlation window, using 7 time-averaged frames, the vector fields were found to have correlations of 0.867 in the direction along the ultrasound beam and 0.738 in the perpendicular direction. Out-of-plane motion of greater than 20% of the in-plane vector magnitude was found to increase the SD by 11% for the vectors parallel to the ultrasound beam direction and 8.6% for the vectors perpendicular to the beam. The results show a close correlation and agreement of individual velocity vectors generated by ultrasound PIV compared with optical PIV. Most of the measurement distortions were caused by out-of-plane velocity components.

An affine projection algorithm using grouping selection of input vectors

NASA Astrophysics Data System (ADS)

Shin, JaeWook; Kong, NamWoong; Park, PooGyeon

2011-10-01

This paper present an affine projection algorithm (APA) using grouping selection of input vectors. To improve the performance of conventional APA, the proposed algorithm adjusts the number of the input vectors using two procedures: grouping procedure and selection procedure. In grouping procedure, the some input vectors that have overlapping information for update is grouped using normalized inner product. Then, few input vectors that have enough information for for coefficient update is selected using steady-state mean square error (MSE) in selection procedure. Finally, the filter coefficients update using selected input vectors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing with the existing algorithms.

Techniques utilized in the simulated altitude testing of a 2D-CD vectoring and reversing nozzle

NASA Technical Reports Server (NTRS)

Block, H. Bruce; Bryant, Lively; Dicus, John H.; Moore, Allan S.; Burns, Maureen E.; Solomon, Robert F.; Sheer, Irving

1988-01-01

Simulated altitude testing of a two-dimensional, convergent-divergent, thrust vectoring and reversing exhaust nozzle was accomplished. An important objective of this test was to develop test hardware and techniques to properly operate a vectoring and reversing nozzle within the confines of an altitude test facility. This report presents detailed information on the major test support systems utilized, the operational performance of the systems and the problems encountered, and test equipment improvements recommended for future tests. The most challenging support systems included the multi-axis thrust measurement system, vectored and reverse exhaust gas collection systems, and infrared temperature measurement systems used to evaluate and monitor the nozzle. The feasibility of testing a vectoring and reversing nozzle of this type in an altitude chamber was successfully demonstrated. Supporting systems performed as required. During reverser operation, engine exhaust gases were successfully captured and turned downstream. However, a small amount of exhaust gas spilled out the collector ducts' inlet openings when the reverser was opened more than 60 percent. The spillage did not affect engine or nozzle performance. The three infrared systems which viewed the nozzle through the exhaust collection system worked remarkably well considering the harsh environment.

Experimental Study of a Nozzle Using Fluidic Counterflow for Thrust Vectoring

NASA Technical Reports Server (NTRS)

Flamm, Jeffrey D.

1998-01-01

A static experimental investigation of a counterflow thrust vectoring nozzle concept was performed. The study was conducted in the NASA Langley Research Center Jet Exit Test Facility. Internal performance characteristics were defined over a nozzle pressure ratio (jet total to ambient) range of 3.5 to 10.0. The effects of suction collar geometry and suction slot height on nozzle performance were examined. In the counterflow concept, thrust vectoring is achieved by applying a vacuum to a slot adjacent to a primary jet that is shrouded by a suction collar. Two flow phenomena work to vector the primary jet depending upon the test conditions and configuration. In one case, the vacuum source creates a secondary reverse flowing stream near the primary jet. The shear layers between the two counterflowing streams mix and entrain mass from the surrounding fluid. The presence of the collar inhibits mass entrainment and the flow near the collar accelerates, causing a drop in pressure on the collar. The second case works similarly except that the vacuum is not powerful enough to create a counterflowing stream and instead a coflowing stream is present. The primary jet is vectored if suction is applied asymmetrically on the top or bottom of the jet.

Novel Gyroscopic Mounting for Crystal Oscillators to Increase Short and Medium Term Stability under Highly Dynamic Conditions

PubMed Central

Abedi, Maryam; Jin, Tian; Sun, Kewen

2015-01-01

In this paper, a gyroscopic mounting method for crystal oscillators to reduce the impact of dynamic loads on their output stability has been proposed. In order to prove the efficiency of this mounting approach, each dynamic load-induced instability has been analyzed in detail. A statistical study has been performed on the elevation angle of the g-sensitivity vector of Stress Compensated-cut (SC-cut) crystals. The analysis results show that the proposed gyroscopic mounting method gives good performance for host vehicle attitude changes. A phase noise improvement of 27 dB maximum and 5.7 dB on average can be achieved in the case of steady state loads, while under sinusoidal vibration conditions, the maximum and average phase noise improvement are as high as 24 dB and 7.5 dB respectively. With this gyroscopic mounting method, random vibration-induced phase noise instability is reduced 30 dB maximum and 8.7 dB on average. Good effects are apparent for crystal g-sensitivity vectors with low elevation angle φ and azimuthal angle β. under highly dynamic conditions, indicating the probability that crystal oscillator instability will be significantly reduced by using the proposed mounting approach. PMID:26091393

Tensor-decomposed vibrational coupled-cluster theory: Enabling large-scale, highly accurate vibrational-structure calculations

NASA Astrophysics Data System (ADS)

Madsen, Niels Kristian; Godtliebsen, Ian H.; Losilla, Sergio A.; Christiansen, Ove

2018-01-01

A new implementation of vibrational coupled-cluster (VCC) theory is presented, where all amplitude tensors are represented in the canonical polyadic (CP) format. The CP-VCC algorithm solves the non-linear VCC equations without ever constructing the amplitudes or error vectors in full dimension but still formally includes the full parameter space of the VCC[n] model in question resulting in the same vibrational energies as the conventional method. In a previous publication, we have described the non-linear-equation solver for CP-VCC calculations. In this work, we discuss the general algorithm for evaluating VCC error vectors in CP format including the rank-reduction methods used during the summation of the many terms in the VCC amplitude equations. Benchmark calculations for studying the computational scaling and memory usage of the CP-VCC algorithm are performed on a set of molecules including thiadiazole and an array of polycyclic aromatic hydrocarbons. The results show that the reduced scaling and memory requirements of the CP-VCC algorithm allows for performing high-order VCC calculations on systems with up to 66 vibrational modes (anthracene), which indeed are not possible using the conventional VCC method. This paves the way for obtaining highly accurate vibrational spectra and properties of larger molecules.

High Performance Distributed Computing in a Supercomputer Environment: Computational Services and Applications Issues

NASA Technical Reports Server (NTRS)

Kramer, Williams T. C.; Simon, Horst D.

1994-01-01

This tutorial proposes to be a practical guide for the uninitiated to the main topics and themes of high-performance computing (HPC), with particular emphasis to distributed computing. The intent is first to provide some guidance and directions in the rapidly increasing field of scientific computing using both massively parallel and traditional supercomputers. Because of their considerable potential computational power, loosely or tightly coupled clusters of workstations are increasingly considered as a third alternative to both the more conventional supercomputers based on a small number of powerful vector processors, as well as high massively parallel processors. Even though many research issues concerning the effective use of workstation clusters and their integration into a large scale production facility are still unresolved, such clusters are already used for production computing. In this tutorial we will utilize the unique experience made at the NAS facility at NASA Ames Research Center. Over the last five years at NAS massively parallel supercomputers such as the Connection Machines CM-2 and CM-5 from Thinking Machines Corporation and the iPSC/860 (Touchstone Gamma Machine) and Paragon Machines from Intel were used in a production supercomputer center alongside with traditional vector supercomputers such as the Cray Y-MP and C90.

A short-term and high-resolution distribution system load forecasting approach using support vector regression with hybrid parameters optimization

DOE PAGES

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard; ...

2016-01-01

This paper 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 themore » 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. The performance of the proposed approach is compared to some classic methods in later sections of the paper.« less

Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization.

PubMed

Karayiannis, N B; Pai, P I

1999-02-01

This paper evaluates a segmentation technique for magnetic resonance (MR) images of the brain based on fuzzy algorithms for learning vector quantization (FALVQ). These algorithms perform vector quantization by updating all prototypes of a competitive network through an unsupervised learning process. Segmentation of MR images is formulated as an unsupervised vector quantization process, where the local values of different relaxation parameters form the feature vectors which are represented by a relatively small set of prototypes. The experiments evaluate a variety of FALVQ algorithms in terms of their ability to identify different tissues and discriminate between normal tissues and abnormalities.

Symbolic computer vector analysis

NASA Technical Reports Server (NTRS)

Stoutemyer, D. R.

1977-01-01

A MACSYMA program is described which performs symbolic vector algebra and vector calculus. The program can combine and simplify symbolic expressions including dot products and cross products, together with the gradient, divergence, curl, and Laplacian operators. The distribution of these operators over sums or products is under user control, as are various other expansions, including expansion into components in any specific orthogonal coordinate system. There is also a capability for deriving the scalar or vector potential of a vector field. Examples include derivation of the partial differential equations describing fluid flow and magnetohydrodynamics, for 12 different classic orthogonal curvilinear coordinate systems.

Discrimination of soft tissues using laser-induced breakdown spectroscopy in combination with k nearest neighbors (kNN) and support vector machine (SVM) classifiers

NASA Astrophysics Data System (ADS)

Li, Xiaohui; Yang, Sibo; Fan, Rongwei; Yu, Xin; Chen, Deying

2018-06-01

In this paper, discrimination of soft tissues using laser-induced breakdown spectroscopy (LIBS) in combination with multivariate statistical methods is presented. Fresh pork fat, skin, ham, loin and tenderloin muscle tissues are manually cut into slices and ablated using a 1064 nm pulsed Nd:YAG laser. Discrimination analyses between fat, skin and muscle tissues, and further between highly similar ham, loin and tenderloin muscle tissues, are performed based on the LIBS spectra in combination with multivariate statistical methods, including principal component analysis (PCA), k nearest neighbors (kNN) classification, and support vector machine (SVM) classification. Performances of the discrimination models, including accuracy, sensitivity and specificity, are evaluated using 10-fold cross validation. The classification models are optimized to achieve best discrimination performances. The fat, skin and muscle tissues can be definitely discriminated using both kNN and SVM classifiers, with accuracy of over 99.83%, sensitivity of over 0.995 and specificity of over 0.998. The highly similar ham, loin and tenderloin muscle tissues can also be discriminated with acceptable performances. The best performances are achieved with SVM classifier using Gaussian kernel function, with accuracy of 76.84%, sensitivity of over 0.742 and specificity of over 0.869. The results show that the LIBS technique assisted with multivariate statistical methods could be a powerful tool for online discrimination of soft tissues, even for tissues of high similarity, such as muscles from different parts of the animal body. This technique could be used for discrimination of tissues suffering minor clinical changes, thus may advance the diagnosis of early lesions and abnormalities.

RRTMGP: A High-Performance Broadband Radiation Code for the Next Decade

DTIC Science & Technology

2014-09-30

Hardware counters were used to measure several performance metrics, including the number of double-precision (DP) floating- point operations ( FLOPs ...0.2 DP FLOPs per CPU cycle. Experience with production science code is that it is possible to achieve execution rates in the range of 0.5 to 1.0...DP FLOPs per cycle. Looking at the ratio of vectorized DP FLOPs to total DP FLOPs we see (Figure PROF) that for most of the execution time the

High performance magnetic bearing systems using high temperature superconductors

DOEpatents

Abboud, Robert G.

1998-01-01

A magnetic bearing apparatus and a method for providing at least one stabilizing force in a magnetic bearing structure with a superconducting magnetic assembly and a magnetic assembly, by providing a superconducting magnetic member in the superconducting magnetic assembly with a plurality of domains and arranging said superconducting magnetic member such that at least one domain has a domain C-axis vector alignment angularly disposed relative to a reference axis of the magnetic member in the magnetic assembly.

Optimizing modelling in iterative image reconstruction for preclinical pinhole PET

NASA Astrophysics Data System (ADS)

Goorden, Marlies C.; van Roosmalen, Jarno; van der Have, Frans; Beekman, Freek J.

2016-05-01

The recently developed versatile emission computed tomography (VECTor) technology enables high-energy SPECT and simultaneous SPECT and PET of small animals at sub-mm resolutions. VECTor uses dedicated clustered pinhole collimators mounted in a scanner with three stationary large-area NaI(Tl) gamma detectors. Here, we develop and validate dedicated image reconstruction methods that compensate for image degradation by incorporating accurate models for the transport of high-energy annihilation gamma photons. Ray tracing software was used to calculate photon transport through the collimator structures and into the gamma detector. Input to this code are several geometric parameters estimated from system calibration with a scanning 99mTc point source. Effects on reconstructed images of (i) modelling variable depth-of-interaction (DOI) in the detector, (ii) incorporating photon paths that go through multiple pinholes (‘multiple-pinhole paths’ (MPP)), and (iii) including various amounts of point spread function (PSF) tail were evaluated. Imaging 18F in resolution and uniformity phantoms showed that including large parts of PSFs is essential to obtain good contrast-noise characteristics and that DOI modelling is highly effective in removing deformations of small structures, together leading to 0.75 mm resolution PET images of a hot-rod Derenzo phantom. Moreover, MPP modelling reduced the level of background noise. These improvements were also clearly visible in mouse images. Performance of VECTor can thus be significantly improved by accurately modelling annihilation gamma photon transport.

Template protection and its implementation in 3D face recognition systems

NASA Astrophysics Data System (ADS)

Zhou, Xuebing

2007-04-01

As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

Molecular detection and antimicrobial resistance of Klebsiella pneumoniae from house flies (Musca domestica) in kitchens, farms, hospitals and slaughterhouses.

PubMed

Ranjbar, Reza; Izadi, Morteza; Hafshejani, Taghi T; Khamesipour, Faham

2016-01-01

Identifying disease vectors and pathogens is one of the key steps in controlling vector-borne diseases. This study investigated the possible role of house flies (Musca domestica) as vectors in the transmission of Klebsiella pneumoniae in Chaharmahal VA Bakhtiari and Isfahan provinces of Iran. House flies were captured from household kitchens, cattle farms, chicken farms, animal hospitals, human hospitals and slaughterhouses. Isolation of K. pneumoniae from external surfaces and guts of the flies was performed using MacConkey agar (MA) and thioglycollate broth (TGB). Identification of the isolates was performed with phenotypic techniques and polymerase chain reaction (PCR). A total of 600 house flies were sampled during the study period from different locations in four different seasons. Overall, 11.3% of the captured house flies were positive for K. pneumoniae. In Chaharmahal VA Bakhtiari province, the prevalence was 12.7%, while in Isfahan province, 10.0% of the sampled house flies were infected with K. pneumoniae. Season-wise, the highest prevalence of infections among the house flies was in summer. The organisms were highly resistant to ampicillin, amoxicillin, cefotaxime and piperacillin. A lowest level of resistance was observed for imipenem/cilastatin. The findings of this study demonstrated that house flies are potential vectors of antibiotic-resistant K. pneumoniae in Isfahan and Chaharmahal provinces, Iran. Control efforts for infections caused by this particular bacterium should take M. domestica into account. Copyright © 2016 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

New model for prediction binary mixture of antihistamine decongestant using artificial neural networks and least squares support vector machine by spectrophotometry method

NASA Astrophysics Data System (ADS)

Mofavvaz, Shirin; Sohrabi, Mahmoud Reza; Nezamzadeh-Ejhieh, Alireza

2017-07-01

In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM) as intelligent methods based on absorption spectra in the range of 230-300 nm have been used for determination of antihistamine decongestant contents. In the first step, one type of network (feed-forward back-propagation) from the artificial neural network with two different training algorithms, Levenberg-Marquardt (LM) and gradient descent with momentum and adaptive learning rate back-propagation (GDX) algorithm, were employed and their performance was evaluated. The performance of the LM algorithm was better than the GDX algorithm. In the second one, the radial basis network was utilized and results compared with the previous network. In the last one, the other intelligent method named least squares support vector machine was proposed to construct the antihistamine decongestant prediction model and the results were compared with two of the aforementioned networks. The values of the statistical parameters mean square error (MSE), Regression coefficient (R2), correlation coefficient (r) and also mean recovery (%), relative standard deviation (RSD) used for selecting the best model between these methods. Moreover, the proposed methods were compared to the high- performance liquid chromatography (HPLC) as a reference method. One way analysis of variance (ANOVA) test at the 95% confidence level applied to the comparison results of suggested and reference methods that there were no significant differences between them.

Equivalent Vectors

ERIC Educational Resources Information Center

Levine, Robert

2004-01-01

The cross-product is a mathematical operation that is performed between two 3-dimensional vectors. The result is a vector that is orthogonal or perpendicular to both of them. Learning about this for the first time while taking Calculus-III, the class was taught that if AxB = AxC, it does not necessarily follow that B = C. This seemed baffling. The…

Fuzzy support vector machine for microarray imbalanced data classification

NASA Astrophysics Data System (ADS)

Ladayya, Faroh; Purnami, Santi Wulan; Irhamah

2017-11-01

DNA microarrays are data containing gene expression with small sample sizes and high number of features. Furthermore, imbalanced classes is a common problem in microarray data. This occurs when a dataset is dominated by a class which have significantly more instances than the other minority classes. Therefore, it is needed a classification method that solve the problem of high dimensional and imbalanced data. Support Vector Machine (SVM) is one of the classification methods that is capable of handling large or small samples, nonlinear, high dimensional, over learning and local minimum issues. SVM has been widely applied to DNA microarray data classification and it has been shown that SVM provides the best performance among other machine learning methods. However, imbalanced data will be a problem because SVM treats all samples in the same importance thus the results is bias for minority class. To overcome the imbalanced data, Fuzzy SVM (FSVM) is proposed. This method apply a fuzzy membership to each input point and reformulate the SVM such that different input points provide different contributions to the classifier. The minority classes have large fuzzy membership so FSVM can pay more attention to the samples with larger fuzzy membership. Given DNA microarray data is a high dimensional data with a very large number of features, it is necessary to do feature selection first using Fast Correlation based Filter (FCBF). In this study will be analyzed by SVM, FSVM and both methods by applying FCBF and get the classification performance of them. Based on the overall results, FSVM on selected features has the best classification performance compared to SVM.

Vector magnetometer design study: Analysis of a triaxial fluxgate sensor design demonstrates that all MAGSAT Vector Magnetometer specifications can be met

NASA Technical Reports Server (NTRS)

Adams, D. F.; Hartmann, U. G.; Lazarow, L. L.; Maloy, J. O.; Mohler, G. W.

1976-01-01

The design of the vector magnetometer selected for analysis is capable of exceeding the required accuracy of 5 gamma per vector field component. The principal elements that assure this performance level are very low power dissipation triaxial feedback coils surrounding ring core flux-gates and temperature control of the critical components of two-loop feedback electronics. An analysis of the calibration problem points to the need for improved test facilities.

Direction-of-arrival estimation for a uniform circular acoustic vector-sensor array mounted around a cylindrical baffle

NASA Astrophysics Data System (ADS)

Yang, DeSen; Zhu, ZhongRui

2012-12-01

This work investigates the direction-of-arrival (DOA) estimation for a uniform circular acoustic Vector-Sensor Array (UCAVSA) mounted around a cylindrical baffle. The total pressure field and the total particle velocity field near the surface of the cylindrical baffle are analyzed theoretically by applying the method of spatial Fourier transform. Then the so-called modal vector-sensor array signal processing algorithm, which is based on the decomposed wavefield representations, for the UCAVSA mounted around the cylindrical baffle is proposed. Simulation and experimental results show that the UCAVSA mounted around the cylindrical baffle has distinct advantages over the same manifold of traditional uniform circular pressure-sensor array (UCPSA). It is pointed out that the acoustic Vector-Sensor (AVS) could be used under the condition of the cylindrical baffle and that the UCAVSA mounted around the cylindrical baffle could also combine the anti-noise performance of the AVS with spatial resolution performance of array system by means of modal vector-sensor array signal processing algorithms.

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

PubMed

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-02-20

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

Observation of Threading Dislocations in Ammonothermal Gallium Nitride Single Crystal Using Synchrotron X-ray Topography

NASA Astrophysics Data System (ADS)

Yao, Y.; Ishikawa, Y.; Sugawara, Y.; Takahashi, Y.; Hirano, K.

2018-04-01

Synchrotron monochromatic-beam x-ray topography observation has been performed on high-quality ammonothermal gallium nitride single crystal to evaluate threading dislocations (TD) in a nondestructive manner. Asymmetric diffractions with six equivalent g-vectors of 11-26, in addition to a symmetric diffraction with g = 0008, were applied to determine the Burgers vectors (b) of dislocations. It was found that pure edge-type TDs with \\varvec b = < {11 - 20} > /3 did not exist in the sample. A dominant proportion of TDs were of mixed type with \\varvec b = < {11 - 20} > /3 + < {0001} > , i.e., so-called c + a dislocations. Pure 1c screw dislocations with \\varvec b = < {0001} > and TDs with c-component larger than 1c were also observed.

Apparatus, systems, and methods for ultrasound synthetic aperature focusing

DOEpatents

Schuster, George J.; Crawford, Susan L.; Doctor, Steven R.; Harris, Robert V.

2005-04-12

One form of the present invention is a technique for interrogating a sample with ultrasound which includes: generating ultrasonic energy data corresponding to a volume of a sample and performing a synthetic aperture focusing technique on the ultrasonic energy data. The synthetic aperture focusing technique includes: defining a number of hyperbolic surfaces which extend through the volume at different depths and a corresponding number of multiple element accumulation vectors, performing a focused element calculation procedure for a group of vectors which are representative of the interior of a designated aperture, performing another focused element calculation procedure for vectors corresponding to the boundary of the aperture, and providing an image corresponding to features of the sample in accordance with the synthetic aperture focusing technique.

A method to determine fault vectors in 4H-SiC from stacking sequences observed on high resolution transmission electron microscopy images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Fangzhen; Wang, Huanhuan; Raghothamachar, Balaji

A new method has been developed to determine the fault vectors associated with stacking faults in 4H-SiC from their stacking sequences observed on high resolution TEM images. This method, analogous to the Burgers circuit technique for determination of dislocation Burgers vector, involves determination of the vectors required in the projection of the perfect lattice to correct the deviated path constructed in the faulted material. Results for several different stacking faults were compared with fault vectors determined from X-ray topographic contrast analysis and were found to be consistent. This technique is expected to applicable to all structures comprising corner shared tetrahedra.

Integrating an infectious disease programme into the primary health care service: a retrospective analysis of Chagas disease community-based surveillance in Honduras.

PubMed

Hashimoto, Ken; Zúniga, Concepción; Nakamura, Jiro; Hanada, Kyo

2015-03-24

Integration of disease-specific programmes into the primary health care (PHC) service has been attempted mostly in clinically oriented disease control such as HIV/AIDS and tuberculosis but rarely in vector control. Chagas disease is controlled principally by interventions against the triatomine vector. In Honduras, after successful reduction of household infestation by vertical approach, the Ministry of Health implemented community-based vector surveillance at the PHC services (health centres) to prevent the resurgence of infection. This paper retrospectively analyses the effects and process of integrating a Chagas disease vector surveillance system into health centres. We evaluated the effects of integration at six pilot sites in western Honduras during 2008-2011 on; surveillance performance; knowledge, attitude and practice in schoolchildren; reports of triatomine bug infestation and institutional response; and seroprevalence among children under 15 years of age. The process of integration of the surveillance system was analysed using the PRECEDE-PROCEED model for health programme planning. The model was employed to systematically determine influential and interactive factors which facilitated the integration process at different levels of the Ministry of Health and the community. Overall surveillance performance improved from 46 to 84 on a 100 point-scale. Schoolchildren's attitude (risk awareness) score significantly increased from 77 to 83 points. Seroprevalence declined from 3.4% to 0.4%. Health centres responded to the community bug reports by insecticide spraying. As key factors, the health centres had potential management capacity and influence over the inhabitants' behaviours and living environment directly and through community health volunteers. The National Chagas Programme played an essential role in facilitating changes with adequate distribution of responsibilities, participatory modelling, training and, evaluation and advocacy. We found that Chagas disease vector surveillance can be integrated into the PHC service. Health centres demonstrated capacity to manage vector surveillance and improve performance, children's awareness, vector report-response and seroprevalence, once tasks were simplified to be performed by trained non-specialists and distributed among the stakeholders. Health systems integration requires health workers to perform beyond their usual responsibilities and acquire management skills. Integration of vector control is feasible and can contribute to strengthening the preventive capacity of the PHC service.

Modified Newcastle disease virus vectors expressing the H5 hemagglutinin induce enhanced protection against highly pathogenic H5N1 avian influenza virus in chickens

PubMed Central

Kim, Shin-Hee; Paldurai, Anandan; Xiao, Sa; Collins, Peter L.; Samal, Siba K.

2016-01-01

Naturally-occurring attenuated strains of Newcastle disease virus (NDV) are being developed as vaccine vectors for use in poultry and humans. However, some NDV strains, such as Beaudette C (BC), may retain too much virulence in poultry for safe use, and more highly attenuated strains may be suboptimally immunogenic. We therefore modified the BC strain by changing the multibasic cleavage site sequence of the F protein to the dibasic sequence of avirulent strain LaSota. Additionally, the BC, F, and HN proteins were modified in several ways to enhance virus replication. These modified BC-derived vectors and the LaSota strain were engineered to express the hemagglutin (HA) protein of H5N1 highly pathogenic influenza virus (HPAIV). In general, the modified BC-based vectors expressing HA replicated better than LaSota/HA, and expressed higher levels of HA protein. Pathogenicity tests indicated that all the modified viruses were highly attenuated in chickens. Based on in vitro characterization, two of the modified BC vectors were chosen for evaluation in chickens as vaccine vectors against H5N1 HPAIV A/Vietnam/1203/04. Immunization of chickens with rNDV vector vaccines followed by challenge with HPAIV demonstrated high levels of protection against clinical disease and mortality. However, only those chickens immunized with modified BC/HA in which residues 271–330 from the F protein had been replaced with the corresponding sequence from the NDV AKO strain conferred complete protection against challenge virus shedding. Our findings suggest that this modified rNDV can be used safely as a vaccine vector with enhanced replication, expression, and protective efficacy in avian species, and potentially in humans. PMID:24968158

High-efficiency induction motor drives using type-2 fuzzy logic

NASA Astrophysics Data System (ADS)

Khemis, A.; Benlaloui, I.; Drid, S.; Chrifi-Alaoui, L.; Khamari, D.; Menacer, A.

2018-03-01

In this work we propose to develop an algorithm for improving the efficiency of an induction motor using type-2 fuzzy logic. Vector control is used to control this motor due to the high performances of this strategy. The type-2 fuzzy logic regulators are developed to obtain the optimal rotor flux for each torque load by minimizing the copper losses. We have compared the performances of our fuzzy type-2 algorithm with the type-1 fuzzy one proposed in the literature. The proposed algorithm is tested with success on the dSPACE DS1104 system even if there is parameters variance.

Economical Implementation of a Filter Engine in an FPGA

NASA Technical Reports Server (NTRS)

Kowalski, James E.

2009-01-01

A logic design has been conceived for a field-programmable gate array (FPGA) that would implement a complex system of multiple digital state-space filters. The main innovative aspect of this design lies in providing for reuse of parts of the FPGA hardware to perform different parts of the filter computations at different times, in such a manner as to enable the timely performance of all required computations in the face of limitations on available FPGA hardware resources. The implementation of the digital state-space filter involves matrix vector multiplications, which, in the absence of the present innovation, would ordinarily necessitate some multiplexing of vector elements and/or routing of data flows along multiple paths. The design concept calls for implementing vector registers as shift registers to simplify operand access to multipliers and accumulators, obviating both multiplexing and routing of data along multiple paths. Each vector register would be reused for different parts of a calculation. Outputs would always be drawn from the same register, and inputs would always be loaded into the same register. A simple state machine would control each filter. The output of a given filter would be passed to the next filter, accompanied by a "valid" signal, which would start the state machine of the next filter. Multiple filter modules would share a multiplication/accumulation arithmetic unit. The filter computations would be timed by use of a clock having a frequency high enough, relative to the input and output data rate, to provide enough cycles for matrix and vector arithmetic operations. This design concept could prove beneficial in numerous applications in which digital filters are used and/or vectors are multiplied by coefficient matrices. Examples of such applications include general signal processing, filtering of signals in control systems, processing of geophysical measurements, and medical imaging. For these and other applications, it could be advantageous to combine compact FPGA digital filter implementations with other application-specific logic implementations on single integrated-circuit chips. An FPGA could readily be tailored to implement a variety of filters because the filter coefficients would be loaded into memory at startup.

Construction of siRNA/miRNA expression vectors based on a one-step PCR process

PubMed Central

Xu, Jun; Zeng, Jie Qiong; Wan, Gang; Hu, Gui Bin; Yan, Hong; Ma, Li Xin

2009-01-01

Background RNA interference (RNAi) has become a powerful means for silencing target gene expression in mammalian cells and is envisioned to be useful in therapeutic approaches to human disease. In recent years, high-throughput, genome-wide screening of siRNA/miRNA libraries has emerged as a desirable approach. Current methods for constructing siRNA/miRNA expression vectors require the synthesis of long oligonucleotides, which is costly and suffers from mutation problems. Results Here we report an ingenious method to solve traditional problems associated with construction of siRNA/miRNA expression vectors. We synthesized shorter primers (< 50 nucleotides) to generate a linear expression structure by PCR. The PCR products were directly transformed into chemically competent E. coli and converted to functional vectors in vivo via homologous recombination. The positive clones could be easily screened under UV light. Using this method we successfully constructed over 500 functional siRNA/miRNA expression vectors. Sequencing of the vectors confirmed a high accuracy rate. Conclusion This novel, convenient, low-cost and highly efficient approach may be useful for high-throughput assays of RNAi libraries. PMID:19490634

Vector Magnetograph Design

NASA Technical Reports Server (NTRS)

Chipman, Russell A.

1996-01-01

This report covers work performed during the period of November 1994 through March 1996 on the design of a Space-borne Solar Vector Magnetograph. This work has been performed as part of a design team under the supervision of Dr. Mona Hagyard and Dr. Alan Gary of the Space Science Laboratory. Many tasks were performed and this report documents the results from some of those tasks, each contained in the corresponding appendix. Appendices are organized in chronological order.

Multiaxis Thrust-Vectoring Characteristics of a Model Representative of the F-18 High-Alpha Research Vehicle at Angles of Attack From 0 deg to 70 deg

NASA Technical Reports Server (NTRS)

Asbury, Scott C.; Capone, Francis J.

1995-01-01

An investigation was conducted in the Langley 16-Foot Transonic Tunnel to determine the multiaxis thrust-vectoring characteristics of the F-18 High-Alpha Research Vehicle (HARV). A wingtip supported, partially metric, 0.10-scale jet-effects model of an F-18 prototype aircraft was modified with hardware to simulate the thrust-vectoring control system of the HARV. Testing was conducted at free-stream Mach numbers ranging from 0.30 to 0.70, at angles of attack from O' to 70', and at nozzle pressure ratios from 1.0 to approximately 5.0. Results indicate that the thrust-vectoring control system of the HARV can successfully generate multiaxis thrust-vectoring forces and moments. During vectoring, resultant thrust vector angles were always less than the corresponding geometric vane deflection angle and were accompanied by large thrust losses. Significant external flow effects that were dependent on Mach number and angle of attack were noted during vectoring operation. Comparisons of the aerodynamic and propulsive control capabilities of the HARV configuration indicate that substantial gains in controllability are provided by the multiaxis thrust-vectoring control system.

Performance characteristics of a variable-area vane nozzle for vectoring an ASTOVL exhaust jet up to 45 deg

NASA Technical Reports Server (NTRS)

Mcardle, Jack G.; Esker, Barbara S.

1993-01-01

Many conceptual designs for advanced short-takeoff, vertical landing (ASTOVL) aircraft need exhaust nozzles that can vector the jet to provide forces and moments for controlling the aircraft's movement or attitude in flight near the ground. A type of nozzle that can both vector the jet and vary the jet flow area is called a vane nozzle. Basically, the nozzle consists of parallel, spaced-apart flow passages formed by pairs of vanes (vanesets) that can be rotated on axes perpendicular to the flow. Two important features of this type of nozzle are the abilities to vector the jet rearward up to 45 degrees and to produce less harsh pressure and velocity footprints during vertical landing than does an equivalent single jet. A one-third-scale model of a generic vane nozzle was tested with unheated air at the NASA Lewis Research Center's Powered Lift Facility. The model had three parallel flow passages. Each passage was formed by a vaneset consisting of a long and a short vane. The longer vanes controlled the jet vector angle, and the shorter controlled the flow area. Nozzle performance for three nominal flow areas (basic and plus or minus 21 percent of basic area), each at nominal jet vector angles from -20 deg (forward of vertical) to +45 deg (rearward of vertical) are presented. The tests were made with the nozzle mounted on a model tailpipe with a blind flange on the end to simulate a closed cruise nozzle, at tailpipe-to-ambient pressure ratios from 1.8 to 4.0. Also included are jet wake data, single-vaneset vector performance for long/short and equal-length vane designs, and pumping capability. The pumping capability arises from the subambient pressure developed in the cavities between the vanesets, which could be used to aspirate flow from a source such as the engine compartment. Some of the performance characteristics are compared with characteristics of a single-jet nozzle previously reported.

Vector excitation speech or audio coder for transmission or storage

NASA Technical Reports Server (NTRS)

Davidson, Grant (Inventor); Gersho, Allen (Inventor)

1989-01-01

A vector excitation coder compresses vectors by using an optimum codebook designed off line, using an initial arbitrary codebook and a set of speech training vectors exploiting codevector sparsity (i.e., by making zero all but a selected number of samples of lowest amplitude in each of N codebook vectors). A fast-search method selects a number N.sub.c of good excitation vectors from the codebook, where N.sub.c is much smaller tha ORIGIN OF INVENTION The invention described herein was made in the performance of work under a NASA contract, and is subject to the provisions of Public Law 96-517 (35 USC 202) under which the inventors were granted a request to retain title.

Vectorization of optically sectioned brain microvasculature: learning aids completion of vascular graphs by connecting gaps and deleting open-ended segments.

PubMed

Kaufhold, John P; Tsai, Philbert S; Blinder, Pablo; Kleinfeld, David

2012-08-01

A graph of tissue vasculature is an essential requirement to model the exchange of gasses and nutriments between the blood and cells in the brain. Such a graph is derived from a vectorized representation of anatomical data, provides a map of all vessels as vertices and segments, and may include the location of nonvascular components, such as neuronal and glial somata. Yet vectorized data sets typically contain erroneous gaps, spurious endpoints, and spuriously merged strands. Current methods to correct such defects only address the issue of connecting gaps and further require manual tuning of parameters in a high dimensional algorithm. To address these shortcomings, we introduce a supervised machine learning method that (1) connects vessel gaps by "learned threshold relaxation"; (2) removes spurious segments by "learning to eliminate deletion candidate strands"; and (3) enforces consistency in the joint space of learned vascular graph corrections through "consistency learning." Human operators are only required to label individual objects they recognize in a training set and are not burdened with tuning parameters. The supervised learning procedure examines the geometry and topology of features in the neighborhood of each vessel segment under consideration. We demonstrate the effectiveness of these methods on four sets of microvascular data, each with >800(3) voxels, obtained with all optical histology of mouse tissue and vectorization by state-of-the-art techniques in image segmentation. Through statistically validated sampling and analysis in terms of precision recall curves, we find that learning with bagged boosted decision trees reduces equal-error error rates for threshold relaxation by 5-21% and strand elimination performance by 18-57%. We benchmark generalization performance across datasets; while improvements vary between data sets, learning always leads to a useful reduction in error rates. Overall, learning is shown to more than halve the total error rate, and therefore, human time spent manually correcting such vectorizations. Copyright © 2012 Elsevier B.V. All rights reserved.

Vectorization of optically sectioned brain microvasculature: Learning aids completion of vascular graphs by connecting gaps and deleting open-ended segments

PubMed Central

Kaufhold, John P.; Tsai, Philbert S.; Blinder, Pablo; Kleinfeld, David

2012-01-01

A graph of tissue vasculature is an essential requirement to model the exchange of gasses and nutriments between the blood and cells in the brain. Such a graph is derived from a vectorized representation of anatomical data, provides a map of all vessels as vertices and segments, and may include the location of nonvascular components, such as neuronal and glial somata. Yet vectorized data sets typically contain erroneous gaps, spurious endpoints, and spuriously merged strands. Current methods to correct such defects only address the issue of connecting gaps and further require manual tuning of parameters in a high dimensional algorithm. To address these shortcomings, we introduce a supervised machine learning method that (1) connects vessel gaps by “learned threshold relaxation”; (2) removes spurious segments by “learning to eliminate deletion candidate strands”; and (3) enforces consistency in the joint space of learned vascular graph corrections through “consistency learning.” Human operators are only required to label individual objects they recognize in a training set and are not burdened with tuning parameters. The supervised learning procedure examines the geometry and topology of features in the neighborhood of each vessel segment under consideration. We demonstrate the effectiveness of these methods on four sets of microvascular data, each with > 8003 voxels, obtained with all optical histology of mouse tissue and vectorization by state-of-the-art techniques in image segmentation. Through statistically validated sampling and analysis in terms of precision recall curves, we find that learning with bagged boosted decision trees reduces equal-error error rates for threshold relaxation by 5 to 21 % and strand elimination performance by 18 to 57 %. We benchmark generalization performance across datasets; while improvements vary between data sets, learning always leads to a useful reduction in error rates. Overall, learning is shown to more than halve the total error rate, and therefore, human time spent manually correcting such vectorizations. PMID:22854035

HIV-1 vaccine strategies utilizing viral vectors including antigen- displayed inoviral vectors.

PubMed

Hassapis, Kyriakos A; Kostrikis, Leondios G

2013-12-01

Antigen-presenting viral vectors have been extensively used as vehicles for the presentation of antigens to the immune system in numerous vaccine strategies. Particularly in HIV vaccine development efforts, two main viral vectors have been used as antigen carriers: (a) live attenuated vectors and (b) virus-like particles (VLPs); the former, although highly effective in animal studies, cannot be clinically tested in humans due to safety concerns and the latter have failed to induce broadly neutralizing anti-HIV antibodies. For more than two decades, Inoviruses (non-lytic bacterial phages) have also been utilized as antigen carriers in several vaccine studies. Inoviral vectors are important antigen-carriers in vaccine development due to their ability to present an antigen on their outer architecture in many copies and to their natural high immunogenicity. Numerous fundamental studies have been conducted, which have established the unique properties of antigen-displayed inoviral vectors in HIV vaccine efforts. The recent isolation of new, potent anti-HIV broadly neutralizing monoclonal antibodies provides a new momentum in this emerging technology.

A novel system for the production of high levels of functional human therapeutic proteins in stable cells with a Semliki Forest virus noncytopathic vector.

PubMed

Casales, Erkuden; Aranda, Alejandro; Quetglas, Jose I; Ruiz-Guillen, Marta; Rodriguez-Madoz, Juan R; Prieto, Jesus; Smerdou, Cristian

2010-05-31

Semliki Forest virus (SFV) vectors lead to high protein expression in mammalian cells, but expression is transient due to vector cytopathic effects, inhibition of host cell proteins and RNA-based expression. We have used a noncytopathic SFV mutant (ncSFV) RNA vector to generate stable cell lines expressing two human therapeutic proteins: insulin-like growth factor I (IGF-I) and cardiotrophin-1 (CT-1). Therapeutic genes were fused at the carboxy-terminal end of Puromycin N-acetyl-transferase gene by using as a linker the sequence coding for foot-and-mouth disease virus (FMDV) 2A autoprotease. These cassettes were cloned into the ncSFV vector. Recombinant ncSFV vectors allowed rapid and efficient selection of stable BHK cell lines with puromycin. These cells expressed IGF-I and CT-1 in supernatants at levels reaching 1.4 and 8.6 microg/10(6)cells/24 hours, respectively. Two cell lines generated with each vector were passaged ten times during 30 days, showing constant levels of protein expression. Recombinant proteins expressed at different passages were functional by in vitro signaling assays. Stability at RNA level was unexpectedly high, showing a very low mutation rate in the CT-1 sequence, which did not increase at high passages. CT-1 was efficiently purified from supernatants of ncSFV cell lines, obtaining a yield of approximately 2mg/L/24 hours. These results indicate that the ncSFV vector has a great potential for the production of recombinant proteins in mammalian cells. 2010 Elsevier B.V. All rights reserved.

Geminivirus vectors for high-level expression of foreign proteins in plant cells.

PubMed

Mor, Tsafrir S; Moon, Yong-Sun; Palmer, Kenneth E; Mason, Hugh S

2003-02-20

Bean yellow dwarf virus (BeYDV) is a monopartite geminivirus that can infect dicotyledonous plants. We have developed a high-level expression system that utilizes elements of the replication machinery of this single-stranded DNA virus. The replication initiator protein (Rep) mediates release and replication of a replicon from a DNA construct ("LSL vector") that contains an expression cassette for a gene of interest flanked by cis-acting elements of the virus. We used tobacco NT1 cells and biolistic delivery of plasmid DNA for evaluation of replication and expression of reporter genes contained within an LSL vector. By codelivery of a GUS reporter-LSL vector and a Rep-supplying vector, we obtained up to 40-fold increase in expression levels compared to delivery of the reporter-LSL vectors alone. High-copy replication of the LSL vector was correlated with enhanced expression of GUS. Rep expression using a whole BeYDV clone, a cauliflower mosaic virus 35S promoter driving either genomic rep or an intron-deleted rep gene, or 35S-rep contained in the LSL vector all achieved efficient replication and enhancement of GUS expression. We anticipate that this system can be adapted for use in transgenic plants or plant cell cultures with appropriately regulated expression of Rep, with the potential to greatly increase yield of recombinant proteins. Copyright 2003 Wiley Periodicals, Inc. Biotechnol Bioeng 81: 430-437, 2003.

Attitude Determination Algorithm based on Relative Quaternion Geometry of Velocity Incremental Vectors for Cost Efficient AHRS Design

NASA Astrophysics Data System (ADS)

Lee, Byungjin; Lee, Young Jae; Sung, Sangkyung

2018-05-01

A novel attitude determination method is investigated that is computationally efficient and implementable in low cost sensor and embedded platform. Recent result on attitude reference system design is adapted to further develop a three-dimensional attitude determination algorithm through the relative velocity incremental measurements. For this, velocity incremental vectors, computed respectively from INS and GPS with different update rate, are compared to generate filter measurement for attitude estimation. In the quaternion-based Kalman filter configuration, an Euler-like attitude perturbation angle is uniquely introduced for reducing filter states and simplifying propagation processes. Furthermore, assuming a small angle approximation between attitude update periods, it is shown that the reduced order filter greatly simplifies the propagation processes. For performance verification, both simulation and experimental studies are completed. A low cost MEMS IMU and GPS receiver are employed for system integration, and comparison with the true trajectory or a high-grade navigation system demonstrates the performance of the proposed algorithm.

A Tensor Product Formulation of Strassen's Matrix Multiplication Algorithm with Memory Reduction

DOE PAGES

Kumar, B.; Huang, C. -H.; Sadayappan, P.; ...

1995-01-01

In this article, we present a program generation strategy of Strassen's matrix multiplication algorithm using a programming methodology based on tensor product formulas. In this methodology, block recursive programs such as the fast Fourier Transforms and Strassen's matrix multiplication algorithm are expressed as algebraic formulas involving tensor products and other matrix operations. Such formulas can be systematically translated to high-performance parallel/vector codes for various architectures. In this article, we present a nonrecursive implementation of Strassen's algorithm for shared memory vector processors such as the Cray Y-MP. A previous implementation of Strassen's algorithm synthesized from tensor product formulas required working storagemore » of size O(7 n ) for multiplying 2 n × 2 n matrices. We present a modified formulation in which the working storage requirement is reduced to O(4 n ). The modified formulation exhibits sufficient parallelism for efficient implementation on a shared memory multiprocessor. Performance results on a Cray Y-MP8/64 are presented.« less

Plane-wave transverse oscillation for high-frame-rate 2-D vector flow imaging.

PubMed

Lenge, Matteo; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Liebgott, Hervé

2015-12-01

Transverse oscillation (TO) methods introduce oscillations in the pulse-echo field (PEF) along the direction transverse to the ultrasound propagation direction. This may be exploited to extend flow investigations toward multidimensional estimates. In this paper, the TOs are coupled with the transmission of plane waves (PWs) to reconstruct high-framerate RF images with bidirectional oscillations in the pulse-echo field. Such RF images are then processed by a 2-D phase-based displacement estimator to produce 2-D vector flow maps at thousands of frames per second. First, the capability of generating TOs after PW transmissions was thoroughly investigated by varying the lateral wavelength, the burst length, and the transmission frequency. Over the entire region of interest, the generated lateral wavelengths, compared with the designed ones, presented bias and standard deviation of -3.3 ± 5.7% and 10.6 ± 7.4% in simulations and experiments, respectively. The performance of the ultrafast vector flow mapping method was also assessed by evaluating the differences between the estimated velocities and the expected ones. Both simulations and experiments show overall biases lower than 20% when varying the beam-to-flow angle, the peak velocity, and the depth of interest. In vivo applications of the method on the common carotid and the brachial arteries are also presented.

[Ecology of Glossina palpalis VANDERPLANK, 1949 (Diptera: Glossinidae) in mangrove area of Guinea: influence of tides on tsetse densities].

PubMed

Kagbadouno, S M; Salou, E; Rayaisse, J B; Courtin, F; Sanon, A; Solano, P; Camara, M

2016-05-01

The mangrove area on the Guinea littoral constitutes a favourable habitat for transmission of Trypanosoma brucei gambiens, the parasite causing sleeping sickness also called Human African Trypanosmosis (HAT), due the simultaneous presence of the vector (tsetse flies) and the human hosts. In order to assess the influence of the sea tides on the densities of Glossina palpalis gambiensis (Gpg), major vector of HAT in the mangrove, entomological surveys were performed using two transects, according to tides coefficient (great and small) and tide daily fluctuations (high and low). On each transect, 12 biconical traps were deployed through the mangrove to the continent. In total, up to 612 Gpg were caught, giving a density of 2.13 flies/trap/day (f/t/d). Highest captures were recorded during small tides and more tsetse were caught during the dry season than in the wet season. There were significant differences between captures when considering the different biotopes, and highest tsetse densities were recorded at the junction of the river and the channel of the mangrove (6.17±5.24); and in the channels of mangrove (3.50±3.76), during high tides of small coefficients. The results of this study may be used to improve vector control methods.

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Comparative and functional triatomine genomics reveals reductions and expansions in insecticide resistance-related gene families.

PubMed

Traverso, Lucila; Lavore, Andrés; Sierra, Ivana; Palacio, Victorio; Martinez-Barnetche, Jesús; Latorre-Estivalis, José Manuel; Mougabure-Cueto, Gaston; Francini, Flavio; Lorenzo, Marcelo G; Rodríguez, Mario Henry; Ons, Sheila; Rivera-Pomar, Rolando V

2017-02-01

Triatomine insects are vectors of Trypanosoma cruzi, a protozoan parasite that is the causative agent of Chagas' disease. This is a neglected disease affecting approximately 8 million people in Latin America. The existence of diverse pyrethroid resistant populations of at least two species demonstrates the potential of triatomines to develop high levels of insecticide resistance. Therefore, the incorporation of strategies for resistance management is a main concern for vector control programs. Three enzymatic superfamilies are thought to mediate xenobiotic detoxification and resistance: Glutathione Transferases (GSTs), Cytochromes P450 (CYPs) and Carboxyl/Cholinesterases (CCEs). Improving our knowledge of key triatomine detoxification enzymes will strengthen our understanding of insecticide resistance processes in vectors of Chagas' disease. The discovery and description of detoxification gene superfamilies in normalized transcriptomes of three triatomine species: Triatoma dimidiata, Triatoma infestans and Triatoma pallidipennis is presented. Furthermore, a comparative analysis of these superfamilies among the triatomine transcriptomes and the genome of Rhodnius prolixus, also a triatomine vector of Chagas' disease, and other well-studied insect genomes was performed. The expression pattern of detoxification genes in R. prolixus transcriptomes from key organs was analyzed. The comparisons reveal gene expansions in Sigma class GSTs, CYP3 in CYP superfamily and clade E in CCE superfamily. Moreover, several CYP families identified in these triatomines have not yet been described in other insects. Conversely, several groups of insecticide resistance related enzymes within each enzyme superfamily are reduced or lacking in triatomines. Furthermore, our qRT-PCR results showed an increase in the expression of a CYP4 gene in a T. infestans population resistant to pyrethroids. These results could point to an involvement of metabolic detoxification mechanisms on the high levels of pyrethroid resistance detected in triatomines from the Gran Chaco ecoregion. Our results help to elucidate the potential insecticide resistance mechanisms in vectors of Chagas' disease and provide new relevant information for this field. This study shows that metabolic resistance might be a contributing cause of the high pyrethroid resistance observed in wild T. infestans populations from the Gran Chaco ecoregion, area in which although subjected to intense pyrethroid treatments, vector control has failed. This study opens new avenues for further functional studies on triatomine detoxification mechanisms.

Comparative and functional triatomine genomics reveals reductions and expansions in insecticide resistance-related gene families

PubMed Central

Traverso, Lucila; Lavore, Andrés; Sierra, Ivana; Palacio, Victorio; Martinez-Barnetche, Jesús; Latorre-Estivalis, José Manuel; Mougabure-Cueto, Gaston; Francini, Flavio; Lorenzo, Marcelo G.; Rodríguez, Mario Henry; Ons, Sheila; Rivera-Pomar, Rolando V.

2017-01-01

Background Triatomine insects are vectors of Trypanosoma cruzi, a protozoan parasite that is the causative agent of Chagas’ disease. This is a neglected disease affecting approximately 8 million people in Latin America. The existence of diverse pyrethroid resistant populations of at least two species demonstrates the potential of triatomines to develop high levels of insecticide resistance. Therefore, the incorporation of strategies for resistance management is a main concern for vector control programs. Three enzymatic superfamilies are thought to mediate xenobiotic detoxification and resistance: Glutathione Transferases (GSTs), Cytochromes P450 (CYPs) and Carboxyl/Cholinesterases (CCEs). Improving our knowledge of key triatomine detoxification enzymes will strengthen our understanding of insecticide resistance processes in vectors of Chagas’ disease. Methods and findings The discovery and description of detoxification gene superfamilies in normalized transcriptomes of three triatomine species: Triatoma dimidiata, Triatoma infestans and Triatoma pallidipennis is presented. Furthermore, a comparative analysis of these superfamilies among the triatomine transcriptomes and the genome of Rhodnius prolixus, also a triatomine vector of Chagas’ disease, and other well-studied insect genomes was performed. The expression pattern of detoxification genes in R. prolixus transcriptomes from key organs was analyzed. The comparisons reveal gene expansions in Sigma class GSTs, CYP3 in CYP superfamily and clade E in CCE superfamily. Moreover, several CYP families identified in these triatomines have not yet been described in other insects. Conversely, several groups of insecticide resistance related enzymes within each enzyme superfamily are reduced or lacking in triatomines. Furthermore, our qRT-PCR results showed an increase in the expression of a CYP4 gene in a T. infestans population resistant to pyrethroids. These results could point to an involvement of metabolic detoxification mechanisms on the high levels of pyrethroid resistance detected in triatomines from the Gran Chaco ecoregion. Conclusions and significance Our results help to elucidate the potential insecticide resistance mechanisms in vectors of Chagas’ disease and provide new relevant information for this field. This study shows that metabolic resistance might be a contributing cause of the high pyrethroid resistance observed in wild T. infestans populations from the Gran Chaco ecoregion, area in which although subjected to intense pyrethroid treatments, vector control has failed. This study opens new avenues for further functional studies on triatomine detoxification mechanisms. PMID:28199333

High performance magnetic bearing systems using high temperature superconductors

DOEpatents

Abboud, R.G.

1998-05-05

Disclosed are a magnetic bearing apparatus and a method for providing at least one stabilizing force in a magnetic bearing structure with a superconducting magnetic assembly and a magnetic assembly, by providing a superconducting magnetic member in the superconducting magnetic assembly with a plurality of domains and arranging said superconducting magnetic member such that at least one domain has a domain C-axis vector alignment angularly disposed relative to a reference axis of the magnetic member in the magnetic assembly. 7 figs.

Development and Application of Modern Optimal Controllers for a Membrane Structure Using Vector Second Order Form

NASA Astrophysics Data System (ADS)

Ferhat, Ipar

With increasing advancement in material science and computational power of current computers that allows us to analyze high dimensional systems, very light and large structures are being designed and built for aerospace applications. One example is a reflector of a space telescope that is made of membrane structures. These reflectors are light and foldable which makes the shipment easy and cheaper unlike traditional reflectors made of glass or other heavy materials. However, one of the disadvantages of membranes is that they are very sensitive to external changes, such as thermal load or maneuvering of the space telescope. These effects create vibrations that dramatically affect the performance of the reflector. To overcome vibrations in membranes, in this work, piezoelectric actuators are used to develop distributed controllers for membranes. These actuators generate bending effects to suppress the vibration. The actuators attached to a membrane are relatively thick which makes the system heterogeneous; thus, an analytical solution cannot be obtained to solve the partial differential equation of the system. Therefore, the Finite Element Model is applied to obtain an approximate solution for the membrane actuator system. Another difficulty that arises with very flexible large structures is the dimension of the discretized system. To obtain an accurate result, the system needs to be discretized using smaller segments which makes the dimension of the system very high. This issue will persist as long as the improving technology will allow increasingly complex and large systems to be designed and built. To deal with this difficulty, the analysis of the system and controller development to suppress the vibration are carried out using vector second order form as an alternative to vector first order form. In vector second order form, the number of equations that need to be solved are half of the number equations in vector first order form. Analyzing the system for control characteristics such as stability, controllability and observability is a key step that needs to be carried out before developing a controller. This analysis determines what kind of system is being modeled and the appropriate approach for controller development. Therefore, accuracy of the system analysis is very crucial. The results of the system analysis using vector second order form and vector first order form show the computational advantages of using vector second order form. Using similar concepts, LQR and LQG controllers, that are developed to suppress the vibration, are derived using vector second order form. To develop a controller using vector second order form, two different approaches are used. One is reducing the size of the Algebraic Riccati Equation to half by partitioning the solution matrix. The other approach is using the Hamiltonian method directly in vector second order form. Controllers are developed using both approaches and compared to each other. Some simple solutions for special cases are derived for vector second order form using the reduced Algebraic Riccati Equation. The advantages and drawbacks of both approaches are explained through examples. System analysis and controller applications are carried out for a square membrane system with four actuators. Two different systems with different actuator locations are analyzed. One system has the actuators at the corners of the membrane, the other has the actuators away from the corners. The structural and control effect of actuator locations are demonstrated with mode shapes and simulations. The results of the controller applications and the comparison of the vector first order form with the vector second order form demonstrate the efficacy of the controllers.

Rapid high-yield expression of full-size IgG antibodies in plants coinfected with noncompeting viral vectors

PubMed Central

Giritch, Anatoli; Marillonnet, Sylvestre; Engler, Carola; van Eldik, Gerben; Botterman, Johan; Klimyuk, Victor; Gleba, Yuri

2006-01-01

Plant viral vectors allow expression of heterologous proteins at high yields, but so far, they have been unable to express heterooligomeric proteins efficiently. We describe here a rapid and indefinitely scalable process for high-level expression of functional full-size mAbs of the IgG class in plants. The process relies on synchronous coinfection and coreplication of two viral vectors, each expressing a separate antibody chain. The two vectors are derived from two different plant viruses that were found to be noncompeting. Unlike vectors derived from the same virus, noncompeting vectors effectively coexpress the heavy and light chains in the same cell throughout the plant body, resulting in yields of up to 0.5 g of assembled mAbs per kg of fresh-leaf biomass. This technology allows production of gram quantities of mAbs for research purposes in just several days, and the same protocol can be used on an industrial scale in situations requiring rapid response, such as pandemic or terrorism events. PMID:16973752

Training Extract, AFSC 113X0B, Flight Engineer, Helicopter Qualified.

DTIC Science & Technology

1982-12-01

TRAINING .................................................................. 1I0 SE. GENERAL rLIGHT RULES A 9 C t | 7. PeRFORM INSPECIIOIS 12 7A... TRAINING .................................................................. lIC 6E. GENERAL FLIGHT RULES A a C...ME"BERS PERFORMING I-A I PROGRAM GENERATED VECTOR IMEMBERS/ NO TYPE VECTOR MEAN - SC DESCRIPTION I TN. SEP J.6 2.J TRAINING EMPHASIS RATINSS I IIOS

Pilot study on the combination of an organophosphate-based insecticide paint and pyrethroid-treated long lasting nets against pyrethroid resistant malaria vectors in Burkina Faso.

PubMed

Mosqueira, Beatriz; Soma, Dieudonné D; Namountougou, Moussa; Poda, Serge; Diabaté, Abdoulaye; Ali, Ouari; Fournet, Florence; Baldet, Thierry; Carnevale, Pierre; Dabiré, Roch K; Mas-Coma, Santiago

2015-08-01

A pilot study to test the efficacy of combining an organophosphate-based insecticide paint and pyrethroid-treated Long Lasting Insecticide Treated Nets (LLINs) against pyrethroid-resistant malaria vector mosquitoes was performed in a real village setting in Burkina Faso. Paint Inesfly 5A IGR™, comprised of two organophosphates (OPs) and an Insect Growth Regulator (IGR), was tested in combination with pyrethroid-treated LLINs. Efficacy was assessed in terms of mortality for 12 months using Early Morning Collections of malaria vectors and 30-minute WHO bioassays. Resistance to pyrethroids and OPs was assessed by detecting the frequency of L1014F and L1014S kdr mutations and Ace-1(R)G119S mutation, respectively. Blood meal origin was identified using a direct enzyme-linked immunosorbent assay (ELISA). The combination of Inesfly 5A IGR™ and LLINs was effective in killing 99.9-100% of malaria vector populations for 6 months regardless of the dose and volume treated. After 12 months, mortality rates decreased to 69.5-82.2%. The highest mortality rates observed in houses treated with 2 layers of insecticide paint and a larger volume. WHO bioassays supported these results: mortalities were 98.8-100% for 6 months and decreased after 12 months to 81.7-97.0%. Mortality rates in control houses with LLINs were low. Collected malaria vectors consisted exclusively of Anopheles coluzzii and were resistant to pyrethroids, with a L1014 kdr mutation frequency ranging from 60 to 98% through the study. About 58% of An. coluzzii collected inside houses had bloodfed on non-human animals. Combining Inesfly 5A IGR™ and LLINs yielded a one year killing efficacy against An. coluzzii highly resistant to pyrethroids but susceptible to OPs that exhibited an anthropo-zoophilic behaviour in the study area. The results obtained in a real setting supported previous work performed in experimental huts and underscore the need to study the impact that this novel strategy may have on clinical malaria and malaria exposure in children in a similar area of high pyrethroid resistance in South-Western Burkina Faso. Copyright © 2015 Elsevier B.V. All rights reserved.

Live attenuated rubella vectors expressing SIV and HIV vaccine antigens replicate and elicit durable immune responses in rhesus macaques

PubMed Central

2013-01-01

Background Live attenuated viruses are among our most potent and effective vaccines. For human immunodeficiency virus, however, a live attenuated strain could present substantial safety concerns. We have used the live attenuated rubella vaccine strain RA27/3 as a vector to express SIV and HIV vaccine antigens because its safety and immunogenicity have been demonstrated in millions of children. One dose protects for life against rubella infection. In previous studies, rubella vectors replicated to high titers in cell culture while stably expressing SIV and HIV antigens. Their viability in vivo, however, as well as immunogenicity and antibody persistence, were unknown. Results This paper reports the first successful trial of rubella vectors in rhesus macaques, in combination with DNA vaccines in a prime and boost strategy. The vectors grew robustly in vivo, and the protein inserts were highly immunogenic. Antibody titers elicited by the SIV Gag vector were greater than or equal to those elicited by natural SIV infection. The antibodies were long lasting, and they were boosted by a second dose of replication-competent rubella vectors given six months later, indicating the induction of memory B cells. Conclusions Rubella vectors can serve as a vaccine platform for safe delivery and expression of SIV and HIV antigens. By presenting these antigens in the context of an acute infection, at a high level and for a prolonged duration, these vectors can stimulate a strong and persistent immune response, including maturation of memory B cells. Rhesus macaques will provide an ideal animal model for demonstrating immunogenicity of novel vectors and protection against SIV or SHIV challenge. PMID:24041113

Vector disparity sensor with vergence control for active vision systems.

PubMed

Barranco, Francisco; Diaz, Javier; Gibaldi, Agostino; Sabatini, Silvio P; Ros, Eduardo

2012-01-01

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.

Operations of the Far Ultraviolet Spectroscopic Explorer : A `Dynamic' Flux Calibration.

NASA Astrophysics Data System (ADS)

Ehrenreich, D.; Dupuis, J.; Dixon, W. V.; Sahnow, D. J.; Kruk, J. W.

2003-05-01

The FUSE flux calibration is based on model-atmosphere predictions of the spectra of well studied white-dwarf stars. Calibration operations, however, are a highly `dynamic' process consisting of repeatedly measuring these standard stars, deriving corrections, and integrating the results into CALFUSE, the FUSE science pipeline. With suitable scheduling, those calibration observation campaigns let us characterize short term and long term variations of the sensitivity. One particular issue addressed by these observations is monitoring possible degradation of the FUSE optical coatings by atomic oxygen present in the upper atmosphere. We have attempted to minimize this by avoiding pointing close to the instantaneous velocity vector of the spacecraft (the ram vector). Prior to Cycle 3, the minimum permitted angle between the line of sight and the ram vector was 20 degrees. This was reduced to 15 degrees during Cycle 3 to increase our sky coverage, and will be further reduced to 10 degrees for Cycle 4. This relaxation of ram constraints has been preceded by a tailored calibration program in which white dwarf measurements are obtained before and after observations performed for a limited time below the current ram vector constraint. This relaxation of the ram vector constraint will considerably expand the ability of FUSE to observe sources at low declination. This work is based on data obtained for the Guaranteed Time Team by the NASA-CNES-CSA FUSE mission operated by the Johns Hopkins University. Financial support to U.S. participants has been provided by NASA contract NAS5-32985.

Impact of drought on vector-borne diseases--how does one manage the risk?

PubMed

Brown, L; Medlock, J; Murray, V

2014-01-01

This article aimed to review all literature on drought and vector-borne disease to enable an assessment of the possible impact of drought on the changing risk of vector-borne diseases in the UK. A systematic literature review was performed. Using a search strategy developed from a combination of terms for drought and selected outcomes, the authors systematically reviewed all available literature from 1990 to 2012 on the impact of drought on vector-borne diseases. The following databases were searched: PubMed, Web of Science, and EMBASE. After reviewing the abstracts, 38 articles were found to fit the inclusion and exclusion criteria. Evidence found drought followed by re-wetting can have a substantial effect on water table levels, vegetation, and aquatic predators; all factors which influence mosquito populations. Several studies found an association between a drought during the previous year and West Nile virus incidence. Urban mosquito vectors of dengue virus and chikungunya virus are adaptable by nature and are able to exploit a multitude of additional aquatic habitats created as a response to drought (i.e. water storage containers). Tick populations are likely to be negatively affected by drought as they are dependent upon high levels of humidity and soil moisture. Further research is needed to identify public health interventions and environmental control measures for an invasive mosquito problem or arthropod-borne disease outbreak in the UK. Copyright © 2013 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Vector Disparity Sensor with Vergence Control for Active Vision Systems

PubMed Central

Barranco, Francisco; Diaz, Javier; Gibaldi, Agostino; Sabatini, Silvio P.; Ros, Eduardo

2012-01-01

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. PMID:22438737

Design of analytical failure detection using secondary observers

NASA Technical Reports Server (NTRS)

Sisar, M.

1982-01-01

The problem of designing analytical failure-detection systems (FDS) for sensors and actuators, using observers, is addressed. The use of observers in FDS is related to the examination of the n-dimensional observer error vector which carries the necessary information on possible failures. The problem is that in practical systems, in which only some of the components of the state vector are measured, one has access only to the m-dimensional observer-output error vector, with m or = to n. In order to cope with these cases, a secondary observer is synthesized to reconstruct the entire observer-error vector from the observer output error vector. This approach leads toward the design of highly sensitive and reliable FDS, with the possibility of obtaining a unique fingerprint for every possible failure. In order to keep the observer's (or Kalman filter) false-alarm rate under a certain specified value, it is necessary to have an acceptable matching between the observer (or Kalman filter) models and the system parameters. A previously developed adaptive observer algorithm is used to maintain the desired system-observer model matching, despite initial mismatching or system parameter variations. Conditions for convergence for the adaptive process are obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors, while accurate and fast parameter identification, in both deterministic and stochastic cases, is obtained.

The path toward HEP High Performance Computing

NASA Astrophysics Data System (ADS)

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

2014-06-01

High Energy Physics code has been known for making poor use of high performance computing architectures. Efforts in optimising HEP code on vector and RISC architectures have yield limited results and recent studies have shown that, on modern architectures, it achieves a performance between 10% and 50% of the peak one. Although several successful attempts have been made to port selected codes on GPUs, no major HEP code suite has a "High Performance" implementation. With LHC undergoing a major upgrade and a number of challenging experiments on the drawing board, HEP cannot any longer neglect the less-than-optimal performance of its code and it has to try making the best usage of the hardware. This activity is one of the foci of the SFT group at CERN, which hosts, among others, the Root and Geant4 project. The activity of the experiments is shared and coordinated via a Concurrency Forum, where the experience in optimising HEP code is presented and discussed. Another activity is the Geant-V project, centred on the development of a highperformance prototype for particle transport. Achieving a good concurrency level on the emerging parallel architectures without a complete redesign of the framework can only be done by parallelizing at event level, or with a much larger effort at track level. Apart the shareable data structures, this typically implies a multiplication factor in terms of memory consumption compared to the single threaded version, together with sub-optimal handling of event processing tails. Besides this, the low level instruction pipelining of modern processors cannot be used efficiently to speedup the program. We have implemented a framework that allows scheduling vectors of particles to an arbitrary number of computing resources in a fine grain parallel approach. The talk will review the current optimisation activities within the SFT group with a particular emphasis on the development perspectives towards a simulation framework able to profit best from the recent technology evolution in computing.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Overview and Performance

NASA Astrophysics Data System (ADS)

Hoeksema, J. Todd; Liu, Yang; Hayashi, Keiji; Sun, Xudong; Schou, Jesper; Couvidat, Sebastien; Norton, Aimee; Bobra, Monica; Centeno, Rebecca; Leka, K. D.; Barnes, Graham; Turmon, Michael

2014-09-01

The Helioseismic and Magnetic Imager (HMI) began near-continuous full-disk solar measurements on 1 May 2010 from the Solar Dynamics Observatory (SDO). An automated processing pipeline keeps pace with observations to produce observable quantities, including the photospheric vector magnetic field, from sequences of filtergrams. The basic vector-field frame list cadence is 135 seconds, but to reduce noise the filtergrams are combined to derive data products every 720 seconds. The primary 720 s observables were released in mid-2010, including Stokes polarization parameters measured at six wavelengths, as well as intensity, Doppler velocity, and the line-of-sight magnetic field. More advanced products, including the full vector magnetic field, are now available. Automatically identified HMI Active Region Patches (HARPs) track the location and shape of magnetic regions throughout their lifetime. The vector field is computed using the Very Fast Inversion of the Stokes Vector (VFISV) code optimized for the HMI pipeline; the remaining 180∘ azimuth ambiguity is resolved with the Minimum Energy (ME0) code. The Milne-Eddington inversion is performed on all full-disk HMI observations. The disambiguation, until recently run only on HARP regions, is now implemented for the full disk. Vector and scalar quantities in the patches are used to derive active region indices potentially useful for forecasting; the data maps and indices are collected in the SHARP data series, hmi.sharp_720s. Definitive SHARP processing is completed only after the region rotates off the visible disk; quick-look products are produced in near real time. Patches are provided in both CCD and heliographic coordinates. HMI provides continuous coverage of the vector field, but has modest spatial, spectral, and temporal resolution. Coupled with limitations of the analysis and interpretation techniques, effects of the orbital velocity, and instrument performance, the resulting measurements have a certain dynamic range and sensitivity and are subject to systematic errors and uncertainties that are characterized in this report.

An Energy Scaled and Expanded Vector-Based Forwarding Scheme for Industrial Underwater Acoustic Sensor Networks with Sink Mobility.

PubMed

Wadud, Zahid; Hussain, Sajjad; Javaid, Nadeem; Bouk, Safdar Hussain; Alrajeh, Nabil; Alabed, Mohamad Souheil; Guizani, Nadra

2017-09-30

Industrial Underwater Acoustic Sensor Networks (IUASNs) come with intrinsic challenges like long propagation delay, small bandwidth, large energy consumption, three-dimensional deployment, and high deployment and battery replacement cost. Any routing strategy proposed for IUASN must take into account these constraints. The vector based forwarding schemes in literature forward data packets to sink using holding time and location information of the sender, forwarder, and sink nodes. Holding time suppresses data broadcasts; however, it fails to keep energy and delay fairness in the network. To achieve this, we propose an Energy Scaled and Expanded Vector-Based Forwarding (ESEVBF) scheme. ESEVBF uses the residual energy of the node to scale and vector pipeline distance ratio to expand the holding time. Resulting scaled and expanded holding time of all forwarding nodes has a significant difference to avoid multiple forwarding, which reduces energy consumption and energy balancing in the network. If a node has a minimum holding time among its neighbors, it shrinks the holding time and quickly forwards the data packets upstream. The performance of ESEVBF is analyzed through in network scenario with and without node mobility to ensure its effectiveness. Simulation results show that ESEVBF has low energy consumption, reduces forwarded data copies, and less end-to-end delay.

In vitro and in vivo documentation of quantum dots labeled Trypanosoma cruzi--Rhodnius prolixus interaction using confocal microscopy.

PubMed

Feder, Denise; Gomes, Suzete A O; de Thomaz, André A; Almeida, Diogo B; Faustino, Wagner M; Fontes, Adriana; Stahl, Cecília V; Santos-Mallet, Jacenir R; Cesar, Carlos L

2009-12-01

Semiconductor quantum dots (QDs) are highly fluorescent nanocrystals markers that allow long photobleaching and do not destroy the parasites. In this paper, we used fluorescent core shell quantum dots to perform studies of live parasite-vector interaction processes without any observable effect on the vitality of parasites. These nanocrystals were synthesized in aqueous medium and physiological pH, which is very important for monitoring live cells activities, and conjugated with molecules such as lectins to label specific carbohydrates involved on the parasite-vector interaction. These QDs were successfully used for the study of in vitro and in vivo interaction of Trypanosoma cruzi and the triatomine Rhodnius prolixus. These QDs allowed us to acquire real time confocal images sequences of live T. cruzi-R. prolixus interactions for an extended period, causing no damage to the cells. By zooming to the region of interest, we have been able to acquire confocal images at the three to four frames per second rate. Our results show that QDs are physiological fluorescent markers capable to label living parasites and insect vector cells. QDs can be functionalized with lectins to specifically mark surface carbohydrates on perimicrovillar membrane of R. prolixus to follow, visualize, and understand interaction between vectors and its parasites in real-time.

High-quality and interactive animations of 3D time-varying vector fields.

PubMed

Helgeland, Anders; Elboth, Thomas

2006-01-01

In this paper, we present an interactive texture-based method for visualizing three-dimensional unsteady vector fields. The visualization method uses a sparse and global representation of the flow, such that it does not suffer from the same perceptual issues as is the case for visualizing dense representations. The animation is made by injecting a collection of particles evenly distributed throughout the physical domain. These particles are then tracked along their path lines. At each time step, these particles are used as seed points to generate field lines using any vector field such as the velocity field or vorticity field. In this way, the animation shows the advection of particles while each frame in the animation shows the instantaneous vector field. In order to maintain a coherent particle density and to avoid clustering as time passes, we have developed a novel particle advection strategy which produces approximately evenly-spaced field lines at each time step. To improve rendering performance, we decouple the rendering stage from the preceding stages of the visualization method. This allows interactive exploration of multiple fields simultaneously, which sets the stage for a more complete analysis of the flow field. The final display is rendered using texture-based direct volume rendering.

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.

1994-01-01

The unequal error protection capabilities of convolutional and trellis codes are studied. In certain environments, a discrepancy in the amount of error protection placed on different information bits is desirable. Examples of environments which have data of varying importance are a number of speech coding algorithms, packet switched networks, multi-user systems, embedded coding systems, and high definition television. Encoders which provide more than one level of error protection to information bits are called unequal error protection (UEP) codes. In this work, the effective free distance vector, d, is defined as an alternative to the free distance as a primary performance parameter for UEP convolutional and trellis encoders. For a given (n, k), convolutional encoder, G, the effective free distance vector is defined as the k-dimensional vector d = (d(sub 0), d(sub 1), ..., d(sub k-1)), where d(sub j), the j(exp th) effective free distance, is the lowest Hamming weight among all code sequences that are generated by input sequences with at least one '1' in the j(exp th) position. It is shown that, although the free distance for a code is unique to the code and independent of the encoder realization, the effective distance vector is dependent on the encoder realization.

An alternative subspace approach to EEG dipole source localization

NASA Astrophysics Data System (ADS)

Xu, Xiao-Liang; Xu, Bobby; He, Bin

2004-01-01

In the present study, we investigate a new approach to electroencephalography (EEG) three-dimensional (3D) dipole source localization by using a non-recursive subspace algorithm called FINES. In estimating source dipole locations, the present approach employs projections onto a subspace spanned by a small set of particular vectors (FINES vector set) in the estimated noise-only subspace instead of the entire estimated noise-only subspace in the case of classic MUSIC. The subspace spanned by this vector set is, in the sense of principal angle, closest to the subspace spanned by the array manifold associated with a particular brain region. By incorporating knowledge of the array manifold in identifying FINES vector sets in the estimated noise-only subspace for different brain regions, the present approach is able to estimate sources with enhanced accuracy and spatial resolution, thus enhancing the capability of resolving closely spaced sources and reducing estimation errors. The present computer simulations show, in EEG 3D dipole source localization, that compared to classic MUSIC, FINES has (1) better resolvability of two closely spaced dipolar sources and (2) better estimation accuracy of source locations. In comparison with RAP-MUSIC, FINES' performance is also better for the cases studied when the noise level is high and/or correlations among dipole sources exist.

Nonlinear stability and control study of highly maneuverable high performance aircraft

NASA Technical Reports Server (NTRS)

Mohler, R. R.

1993-01-01

This project is intended to research and develop new nonlinear methodologies for the control and stability analysis of high-performance, high angle-of-attack aircraft such as HARV (F18). Past research (reported in our Phase 1, 2, and 3 progress reports) is summarized and more details of final Phase 3 research is provided. While research emphasis is on nonlinear control, other tasks such as associated model development, system identification, stability analysis, and simulation are performed in some detail as well. An overview of various models that were investigated for different purposes such as an approximate model reference for control adaptation, as well as another model for accurate rigid-body longitudinal motion is provided. Only a very cursory analysis was made relative to type 8 (flexible body dynamics). Standard nonlinear longitudinal airframe dynamics (type 7) with the available modified F18 stability derivatives, thrust vectoring, actuator dynamics, and control constraints are utilized for simulated flight evaluation of derived controller performance in all cases studied.

Insertion of operation-and-indicate instructions for optimized SIMD code

DOEpatents

Eichenberger, Alexander E; Gara, Alan; Gschwind, Michael K

2013-06-04

Mechanisms are provided for inserting indicated instructions for tracking and indicating exceptions in the execution of vectorized code. A portion of first code is received for compilation. The portion of first code is analyzed to identify non-speculative instructions performing designated non-speculative operations in the first code that are candidates for replacement by replacement operation-and-indicate instructions that perform the designated non-speculative operations and further perform an indication operation for indicating any exception conditions corresponding to special exception values present in vector register inputs to the replacement operation-and-indicate instructions. The replacement is performed and second code is generated based on the replacement of the at least one non-speculative instruction. The data processing system executing the compiled code is configured to store special exception values in vector output registers, in response to a speculative instruction generating an exception condition, without initiating exception handling.

Safety profile, efficacy, and biodistribution of a bicistronic high-capacity adenovirus vector encoding a combined immunostimulation and cytotoxic gene therapy as a prelude to a phase I clinical trial for glioblastoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Puntel, Mariana; Department of Cell and Developmental Biology, The University of Michigan School of Medicine, MSRB II, RM 4570C, 1150 West Medical Center Drive, Ann Arbor, MI 48109-5689; Gene Therapeutics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048

2013-05-01

Adenoviral vectors (Ads) are promising gene delivery vehicles due to their high transduction efficiency; however, their clinical usefulness has been hampered by their immunogenicity and the presence of anti-Ad immunity in humans. We reported the efficacy of a gene therapy approach for glioma consisting of intratumoral injection of Ads encoding conditionally cytotoxic herpes simplex type 1 thymidine kinase (Ad-TK) and the immunostimulatory cytokine fms-like tyrosine kinase ligand 3 (Ad-Flt3L). Herein, we report the biodistribution, efficacy, and neurological and systemic effects of a bicistronic high-capacity Ad, i.e., HC-Ad-TK/TetOn-Flt3L. HC-Ads elicit sustained transgene expression, even in the presence of anti-Ad immunity, andmore » can encode large therapeutic cassettes, including regulatory elements to enable turning gene expression “on” or “off” according to clinical need. The inclusion of two therapeutic transgenes within a single vector enables a reduction of the total vector load without adversely impacting efficacy. Because clinically the vectors will be delivered into the surgical cavity, normal regions of the brain parenchyma are likely to be transduced. Thus, we assessed any potential toxicities elicited by escalating doses of HC-Ad-TK/TetOn-Flt3L (1 × 10{sup 8}, 1 × 10{sup 9}, or 1 × 10{sup 10} viral particles [vp]) delivered into the rat brain parenchyma. We assessed neuropathology, biodistribution, transgene expression, systemic toxicity, and behavioral impact at acute and chronic time points. The results indicate that doses up to 1 × 10{sup 9} vp of HC-Ad-TK/TetOn-Flt3L can be safely delivered into the normal rat brain and underpin further developments for its implementation in a phase I clinical trial for glioma. - Highlights: ► High capacity Ad vectors elicit sustained therapeutic gene expression in the brain. ► HC-Ad-TK/TetOn-Flt3L encodes two therapeutic genes and a transcriptional switch. ► We performed a dose escalation study at acute and chronic time points. ► Doses up to 1 × 10{sup 9} vp of HC-Ad-TK/TetOn-Flt3L can be safely delivered in the brain. ► Efficacy and safety of HC-Ad-TK/TetOn-Flt3L merits its use in a GBM Phase I trial.« less

Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

PubMed Central

Zhao, Yu-Xiang; Chou, Chien-Hsing

2016-01-01

In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. PMID:27314346

Manipulation of dielectric Rayleigh particles using highly focused elliptically polarized vector fields.

PubMed

Gu, Bing; Xu, Danfeng; Rui, Guanghao; Lian, Meng; Cui, Yiping; Zhan, Qiwen

2015-09-20

Generation of vectorial optical fields with arbitrary polarization distribution is of great interest in areas where exotic optical fields are desired. In this work, we experimentally demonstrate the versatile generation of linearly polarized vector fields, elliptically polarized vector fields, and circularly polarized vortex beams through introducing attenuators in a common-path interferometer. By means of Richards-Wolf vectorial diffraction method, the characteristics of the highly focused elliptically polarized vector fields are studied. The optical force and torque on a dielectric Rayleigh particle produced by these tightly focused vector fields are calculated and exploited for the stable trapping of dielectric Rayleigh particles. It is shown that the additional degree of freedom provided by the elliptically polarized vector field allows one to control the spatial structure of polarization, to engineer the focusing field, and to tailor the optical force and torque on a dielectric Rayleigh particle.

Kalman Filter Tracking on Parallel Architectures

NASA Astrophysics Data System (ADS)

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

2016-11-01

Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGPU, ARM and Intel MIC. In order to achieve the theoretical performance gains of these processors, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High-Luminosity Large Hadron Collider (HL-LHC), for example, this will be by far the dominant problem. The need for greater parallelism has driven investigations of very different track finding techniques such as Cellular Automata or Hough Transforms. The most common track finding techniques in use today, however, are those based on a Kalman filter approach. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. They are known to provide high physics performance, are robust, and are in use today at the LHC. Given the utility of the Kalman filter in track finding, we have begun to port these algorithms to parallel architectures, namely Intel Xeon and Xeon Phi. We report here on our progress towards an end-to-end track reconstruction algorithm fully exploiting vectorization and parallelization techniques in a simplified experimental environment.

Performance analysis of distributed symmetric sparse matrix vector multiplication algorithm for multi-core architectures

DOE PAGES

Oryspayev, Dossay; Aktulga, Hasan Metin; Sosonkina, Masha; ...

2015-07-14

In this article, sparse matrix vector multiply (SpMVM) is an important kernel that frequently arises in high performance computing applications. Due to its low arithmetic intensity, several approaches have been proposed in literature to improve its scalability and efficiency in large scale computations. In this paper, our target systems are high end multi-core architectures and we use messaging passing interface + open multiprocessing hybrid programming model for parallelism. We analyze the performance of recently proposed implementation of the distributed symmetric SpMVM, originally developed for large sparse symmetric matrices arising in ab initio nuclear structure calculations. We also study important featuresmore » of this implementation and compare with previously reported implementations that do not exploit underlying symmetry. Our SpMVM implementations leverage the hybrid paradigm to efficiently overlap expensive communications with computations. Our main comparison criterion is the "CPU core hours" metric, which is the main measure of resource usage on supercomputers. We analyze the effects of topology-aware mapping heuristic using simplified network load model. Furthermore, we have tested the different SpMVM implementations on two large clusters with 3D Torus and Dragonfly topology. Our results show that the distributed SpMVM implementation that exploits matrix symmetry and hides communication yields the best value for the "CPU core hours" metric and significantly reduces data movement overheads.« less

Study on Temperature and Synthetic Compensation of Piezo-Resistive Differential Pressure Sensors by Coupled Simulated Annealing and Simplex Optimized Kernel Extreme Learning Machine

PubMed Central

Li, Ji; Hu, Guoqing; Zhou, Yonghong; Zou, Chong; Peng, Wei; Alam SM, Jahangir

2017-01-01

As a high performance-cost ratio solution for differential pressure measurement, piezo-resistive differential pressure sensors are widely used in engineering processes. However, their performance is severely affected by the environmental temperature and the static pressure applied to them. In order to modify the non-linear measuring characteristics of the piezo-resistive differential pressure sensor, compensation actions should synthetically consider these two aspects. Advantages such as nonlinear approximation capability, highly desirable generalization ability and computational efficiency make the kernel extreme learning machine (KELM) a practical approach for this critical task. Since the KELM model is intrinsically sensitive to the regularization parameter and the kernel parameter, a searching scheme combining the coupled simulated annealing (CSA) algorithm and the Nelder-Mead simplex algorithm is adopted to find an optimal KLEM parameter set. A calibration experiment at different working pressure levels was conducted within the temperature range to assess the proposed method. In comparison with other compensation models such as the back-propagation neural network (BP), radius basis neural network (RBF), particle swarm optimization optimized support vector machine (PSO-SVM), particle swarm optimization optimized least squares support vector machine (PSO-LSSVM) and extreme learning machine (ELM), the compensation results show that the presented compensation algorithm exhibits a more satisfactory performance with respect to temperature compensation and synthetic compensation problems. PMID:28422080

Study on Temperature and Synthetic Compensation of Piezo-Resistive Differential Pressure Sensors by Coupled Simulated Annealing and Simplex Optimized Kernel Extreme Learning Machine.

PubMed

Li, Ji; Hu, Guoqing; Zhou, Yonghong; Zou, Chong; Peng, Wei; Alam Sm, Jahangir

2017-04-19

As a high performance-cost ratio solution for differential pressure measurement, piezo-resistive differential pressure sensors are widely used in engineering processes. However, their performance is severely affected by the environmental temperature and the static pressure applied to them. In order to modify the non-linear measuring characteristics of the piezo-resistive differential pressure sensor, compensation actions should synthetically consider these two aspects. Advantages such as nonlinear approximation capability, highly desirable generalization ability and computational efficiency make the kernel extreme learning machine (KELM) a practical approach for this critical task. Since the KELM model is intrinsically sensitive to the regularization parameter and the kernel parameter, a searching scheme combining the coupled simulated annealing (CSA) algorithm and the Nelder-Mead simplex algorithm is adopted to find an optimal KLEM parameter set. A calibration experiment at different working pressure levels was conducted within the temperature range to assess the proposed method. In comparison with other compensation models such as the back-propagation neural network (BP), radius basis neural network (RBF), particle swarm optimization optimized support vector machine (PSO-SVM), particle swarm optimization optimized least squares support vector machine (PSO-LSSVM) and extreme learning machine (ELM), the compensation results show that the presented compensation algorithm exhibits a more satisfactory performance with respect to temperature compensation and synthetic compensation problems.

A portable approach for PIC on emerging architectures

NASA Astrophysics Data System (ADS)

Decyk, Viktor

2016-03-01

A portable approach for designing Particle-in-Cell (PIC) algorithms on emerging exascale computers, is based on the recognition that 3 distinct programming paradigms are needed. They are: low level vector (SIMD) processing, middle level shared memory parallel programing, and high level distributed memory programming. In addition, there is a memory hierarchy associated with each level. Such algorithms can be initially developed using vectorizing compilers, OpenMP, and MPI. This is the approach recommended by Intel for the Phi processor. These algorithms can then be translated and possibly specialized to other programming models and languages, as needed. For example, the vector processing and shared memory programming might be done with CUDA instead of vectorizing compilers and OpenMP, but generally the algorithm itself is not greatly changed. The UCLA PICKSC web site at http://www.idre.ucla.edu/ contains example open source skeleton codes (mini-apps) illustrating each of these three programming models, individually and in combination. Fortran2003 now supports abstract data types, and design patterns can be used to support a variety of implementations within the same code base. Fortran2003 also supports interoperability with C so that implementations in C languages are also easy to use. Finally, main codes can be translated into dynamic environments such as Python, while still taking advantage of high performing compiled languages. Parallel languages are still evolving with interesting developments in co-Array Fortran, UPC, and OpenACC, among others, and these can also be supported within the same software architecture. Work supported by NSF and DOE Grants.

Insecticide resistance in the dengue vector Aedes aegypti from Martinique: distribution, mechanisms and relations with environmental factors.

PubMed

Marcombe, Sébastien; Mathieu, Romain Blanc; Pocquet, Nicolas; Riaz, Muhammad-Asam; Poupardin, Rodolphe; Sélior, Serge; Darriet, Frédéric; Reynaud, Stéphane; Yébakima, André; Corbel, Vincent; David, Jean-Philippe; Chandre, Fabrice

2012-01-01

Dengue is an important mosquito borne viral disease in Martinique Island (French West Indies). The viruses responsible for dengue are transmitted by Aedes aegypti, an indoor day-biting mosquito. The most effective proven method for disease prevention has been by vector control by various chemical or biological means. Unfortunately insecticide resistance has already been observed on the Island and recently showed to significantly reduce the efficacy of vector control interventions. In this study, we investigated the distribution of resistance and the underlying mechanisms in nine Ae. aegypti populations. Statistical multifactorial approach was used to investigate the correlations between insecticide resistance levels, associated mechanisms and environmental factors characterizing the mosquito populations. Bioassays revealed high levels of resistance to temephos and deltamethrin and susceptibility to Bti in the 9 populations tested. Biochemical assays showed elevated detoxification enzyme activities of monooxygenases, carboxylesterases and glutathione S-tranferases in most of the populations. Molecular screening for common insecticide target-site mutations, revealed the presence of the "knock-down resistance" V1016I Kdr mutation at high frequency (>87%). Real time quantitative RT-PCR showed the potential involvement of several candidate detoxification genes in insecticide resistance. Principal Component Analysis (PCA) performed with variables characterizing Ae. aegypti from Martinique permitted to underline potential links existing between resistance distribution and other variables such as agriculture practices, vector control interventions and urbanization. Insecticide resistance is widespread but not homogeneously distributed across Martinique. The influence of environmental and operational factors on the evolution of the resistance and mechanisms are discussed.

Insecticide Resistance in the Dengue Vector Aedes aegypti from Martinique: Distribution, Mechanisms and Relations with Environmental Factors

PubMed Central

Marcombe, Sébastien; Mathieu, Romain Blanc; Pocquet, Nicolas; Riaz, Muhammad-Asam; Poupardin, Rodolphe; Sélior, Serge; Darriet, Frédéric; Reynaud, Stéphane; Yébakima, André; Corbel, Vincent; David, Jean-Philippe; Chandre, Fabrice

2012-01-01

Dengue is an important mosquito borne viral disease in Martinique Island (French West Indies). The viruses responsible for dengue are transmitted by Aedes aegypti, an indoor day-biting mosquito. The most effective proven method for disease prevention has been by vector control by various chemical or biological means. Unfortunately insecticide resistance has already been observed on the Island and recently showed to significantly reduce the efficacy of vector control interventions. In this study, we investigated the distribution of resistance and the underlying mechanisms in nine Ae. aegypti populations. Statistical multifactorial approach was used to investigate the correlations between insecticide resistance levels, associated mechanisms and environmental factors characterizing the mosquito populations. Bioassays revealed high levels of resistance to temephos and deltamethrin and susceptibility to Bti in the 9 populations tested. Biochemical assays showed elevated detoxification enzyme activities of monooxygenases, carboxylesterases and glutathione S-tranferases in most of the populations. Molecular screening for common insecticide target-site mutations, revealed the presence of the “knock-down resistance” V1016I Kdr mutation at high frequency (>87%). Real time quantitative RT-PCR showed the potential involvement of several candidate detoxification genes in insecticide resistance. Principal Component Analysis (PCA) performed with variables characterizing Ae. aegypti from Martinique permitted to underline potential links existing between resistance distribution and other variables such as agriculture practices, vector control interventions and urbanization. Insecticide resistance is widespread but not homogeneously distributed across Martinique. The influence of environmental and operational factors on the evolution of the resistance and mechanisms are discussed. PMID:22363529

Enhancing Global Competitiveness: Benchmarking Airline Operational Performance in Highly Regulated Environments

NASA Technical Reports Server (NTRS)

Bowen, Brent D.; Headley, Dean E.; Kane, Karisa D.

1998-01-01

Enhancing competitiveness in the global airline industry is at the forefront of attention with airlines, government, and the flying public. The seemingly unchecked growth of major airline alliances is heralded as an enhancement to global competition. However, like many mega-conglomerates, mega-airlines will face complications driven by size regardless of the many recitations of enhanced efficiency. Outlined herein is a conceptual model to serve as a decision tool for policy-makers, managers, and consumers of airline services. This model is developed using public data for the United States (U.S.) major airline industry available from the U/S. Department of Transportation, Federal Aviation Administration, the National Aeronautics and Space Administration, the National Transportation Safety Board, and other public and private sector sources. Data points include number of accidents, pilot deviations, operational performance indicators, flight problems, and other factors. Data from these sources provide opportunity to develop a model based on a complex dot product equation of two vectors. A row vector is weighted for importance by a key informant panel of government, industry, and consumer experts, while a column vector is established with the factor value. The resulting equation, known as the national Airline Quality Rating (AQR), where Q is quality, C is weight, and V is the value of the variables, is stated Q=C[i1-19] x V[i1-19]. Looking at historical patterns of AQR results provides the basis for establishment of an industry benchmark for the purpose of enhancing airline operational performance. A 7 year average of overall operational performance provides the resulting benchmark indicator. Applications from this example can be applied to the many competitive environments of the global industry and assist policy-makers faced with rapidly changing regulatory challenges.

Classification of small lesions in dynamic breast MRI: Eliminating the need for precise lesion segmentation through spatio-temporal analysis of contrast enhancement over time.

PubMed

Nagarajan, Mahesh B; Huber, Markus B; Schlossbauer, Thomas; Leinsinger, Gerda; Krol, Andrzej; Wismüller, Axel

2013-10-01

Characterizing the dignity of breast lesions as benign or malignant is specifically difficult for small lesions; they don't exhibit typical characteristics of malignancy and are harder to segment since margins are harder to visualize. Previous attempts at using dynamic or morphologic criteria to classify small lesions (mean lesion diameter of about 1 cm) have not yielded satisfactory results. The goal of this work was to improve the classification performance in such small diagnostically challenging lesions while concurrently eliminating the need for precise lesion segmentation. To this end, we introduce a method for topological characterization of lesion enhancement patterns over time. Three Minkowski Functionals were extracted from all five post-contrast images of sixty annotated lesions on dynamic breast MRI exams. For each Minkowski Functional, topological features extracted from each post-contrast image of the lesions were combined into a high-dimensional texture feature vector. These feature vectors were classified in a machine learning task with support vector regression. For comparison, conventional Haralick texture features derived from gray-level co-occurrence matrices (GLCM) were also used. A new method for extracting thresholded GLCM features was also introduced and investigated here. The best classification performance was observed with Minkowski Functionals area and perimeter , thresholded GLCM features f8 and f9, and conventional GLCM features f4 and f6. However, both Minkowski Functionals and thresholded GLCM achieved such results without lesion segmentation while the performance of GLCM features significantly deteriorated when lesions were not segmented ( p < 0.05). This suggests that such advanced spatio-temporal characterization can improve the classification performance achieved in such small lesions, while simultaneously eliminating the need for precise segmentation.

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

PubMed

Xu, Beibei; Tan, Zhiying; Li, Kenli; Jiang, Taijiao; Peng, Yousong

2017-01-01

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.

Video Vectorization via Tetrahedral Remeshing.

PubMed

Wang, Chuan; Zhu, Jie; Guo, Yanwen; Wang, Wenping

2017-02-09

We present a video vectorization method that generates a video in vector representation from an input video in raster representation. A vector-based video representation offers the benefits of vector graphics, such as compactness and scalability. The vector video we generate is represented by a simplified tetrahedral control mesh over the spatial-temporal video volume, with color attributes defined at the mesh vertices. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. From an input raster video, our method is capable of generating a compact video in vector representation that allows a faithful reconstruction with low reconstruction errors.

New Term Weighting Formulas for the Vector Space Method in Information Retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chisholm, E.; Kolda, T.G.

The goal in information retrieval is to enable users to automatically and accurately find data relevant to their queries. One possible approach to this problem i use the vector space model, which models documents and queries as vectors in the term space. The components of the vectors are determined by the term weighting scheme, a function of the frequencies of the terms in the document or query as well as throughout the collection. We discuss popular term weighting schemes and present several new schemes that offer improved performance.

A selective-update affine projection algorithm with selective input vectors

NASA Astrophysics Data System (ADS)

Kong, NamWoong; Shin, JaeWook; Park, PooGyeon

2011-10-01

This paper proposes an affine projection algorithm (APA) with selective input vectors, which based on the concept of selective-update in order to reduce estimation errors and computations. The algorithm consists of two procedures: input- vector-selection and state-decision. The input-vector-selection procedure determines the number of input vectors by checking with mean square error (MSE) whether the input vectors have enough information for update. The state-decision procedure determines the current state of the adaptive filter by using the state-decision criterion. As the adaptive filter is in transient state, the algorithm updates the filter coefficients with the selected input vectors. On the other hand, as soon as the adaptive filter reaches the steady state, the update procedure is not performed. Through these two procedures, the proposed algorithm achieves small steady-state estimation errors, low computational complexity and low update complexity for colored input signals.

Approaches for Language Identification in Mismatched Environments

DTIC Science & Technology

2016-09-08

different i-vector systems are considered, which differ in their feature extraction mechanism. The first, which we refer to as the standard i-vector, or...both conversational telephone speech and narrowband broadcast speech. Multiple experiments are conducted to assess the performance of the system in...bottleneck features using i-vectors. The proposed system results in a 30% improvement over the baseline result. Index Terms: language identification

A two-model hydrologic ensemble prediction of hydrograph: case study from the upper Nysa Klodzka river basin (SW Poland)

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Mizinski, Bartlomiej

2016-04-01

The HydroProg system has been elaborated in frame of the research project no. 2011/01/D/ST10/04171 of the National Science Centre of Poland and is steadily producing multimodel ensemble predictions of hydrograph in real time. Although there are six ensemble members available at present, the longest record of predictions and their statistics is available for two data-based models (uni- and multivariate autoregressive models). Thus, we consider 3-hour predictions of water levels, with lead times ranging from 15 to 180 minutes, computed every 15 minutes since August 2013 for the Nysa Klodzka basin (SW Poland) using the two approaches and their two-model ensemble. Since the launch of the HydroProg system there have been 12 high flow episodes, and the objective of this work is to present the performance of the two-model ensemble in the process of forecasting these events. For a sake of brevity, we limit our investigation to a single gauge located at the Nysa Klodzka river in the town of Klodzko, which is centrally located in the studied basin. We identified certain regular scenarios of how the models perform in predicting the high flows in Klodzko. At the initial phase of the high flow, well before the rising limb of hydrograph, the two-model ensemble is found to provide the most skilful prognoses of water levels. However, while forecasting the rising limb of hydrograph, either the two-model solution or the vector autoregressive model offers the best predictive performance. In addition, it is hypothesized that along with the development of the rising limb phase, the vector autoregression becomes the most skilful approach amongst the scrutinized ones. Our simple two-model exercise confirms that multimodel hydrologic ensemble predictions cannot be treated as universal solutions suitable for forecasting the entire high flow event, but their superior performance may hold only for certain phases of a high flow.

Analysis of sandflies (Diptera: Psychodidae) in Barra do Garças, State of Mato Grosso, Brazil, and the influence of environmental variables on the vector density of Lutzomyia longipalpis (Lutz & Neiva, 1912).

PubMed

Queiroz, Mirian Francisca Martins; Varjão, Jane Ramos; Moraes, Sinara Cristina de; Salcedo, Gladys Elena

2012-06-01

Leishmaniasis is an infectious and parasitic zoonotic, non-contagious, vector-borne disease caused by protozoa of the genus Leishmania. In Brazil, the major vector of Leishmania (Leishmania) infantum chagasi (Cunha & Chagas, 1934) is Lutzomyia longipalpis. Barra do Garças, State of Mato Grosso, was designated as a priority area by the Brazilian Ministry of Health for american visceral leishmaniasis, and it is important to identify the vector species present in this municipality. Our objective was to raise sandflies and study the influence of environmental variables on the vector density of Lutzomyia longipalpis. We performed entomological monitoring in 3 districts using Centers for Disease Control and Prevention (CDC) light traps and recorded human cases of american visceral leishmaniasis in the city. We calculated the relative frequency and richness of sandflies and applied a transfer function model to the vector density correlate with relative humidity. The sandfly population was composed of 2 genera and 27 species, totaling 8,097 individuals. Monitoring identified Lutzomyia longipalpis (44%), followed by Lutzomyia lenti (18.9%), Lutzomyia whitmani (13.9%), Lutzomyia carmelinoi (9.1%), Lutzomyia evandroi (5.1%), Lutzomyia termitophila (3.3%), Lutzomyia sordellii (1.9%), and 20 other species (<4%). The male:female ratio was 3.5:1. We observed high species diversity (Dα = 6.65). Lutzomyia longipalpis showed occurrence peaks during the rainy season; there was a temporal correlation with humidity, but not with frequency or temperature. The presence of Lutzomyia longipalpis in the urban area of Barra do Garças underscores the changing disease profile, which was previously restricted to the wild environment.

Targeted Adenoviral Vector Demonstrates Enhanced Efficacy for In Vivo Gene Therapy of Uterine Leiomyoma

PubMed Central

Abdelaziz, Mohamed; Sherif, Lotfy; ElKhiary, Mostafa; Nair, Sanjeeta; Shalaby, Shahinaz; Mohamed, Sara; Eziba, Noura; El-Lakany, Mohamed; Curiel, David; Ismail, Nahed; Diamond, Michael P.; Al-Hendy, Ayman

2016-01-01

Background: Gene therapy is a potentially effective non-surgical approach for the treatment of uterine leiomyoma. We demonstrated that targeted adenovirus vector, Ad-SSTR-RGD-TK/GCV, was highly effective in selectively inducing apoptosis and inhibiting proliferation of human leiomyoma cells in vitro while sparing normal myometrial cells. Study design: An in-vivo study, to compare efficacy and safety of modified adenovirus vector Ad-SSTR-RGD-TK/GCV versus untargeted vector for treatment of leiomyoma. Materials and methods: Female nude mice were implanted with rat leiomyoma cells subcutaneously. Then mice were randomized into three groups. Group 1 received Ad-LacZ (marker gene), Group 2 received untargeted Ad-TK, and Group 3 received the targeted Ad-SSTR-RGD-TK. Tumors were measured weekly for 4 weeks. Then mice were sacrificed and tissue samples were collected. Evaluation of markers of apoptosis, proliferation, extracellular matrix, and angiogenesis was performed using Western Blot & Immunohistochemistry. Statistical analysis was done using ANOVA. Dissemination of adenovirus was assessed by PCR. Results: In comparison with the untargeted vector, the targeted adenoviral vector significantly shrank leiomyoma size (P < 0.05), reduced expression of proliferation marker (PCNA) (P < 0.05), induced expression of apoptotic protein, c-PARP-1, (P < 0.05) and inhibited expression of extracellular matrix-related genes (TGF beta 3) and angiogenesis-related genes (VEGF & IGF-1) (P < 0.01). There were no detectable adenovirus in tested tissues other than leiomyoma lesions with both targeted and untargeted adenovirus. Conclusion: Targeted adenovirus, effectively reduces tumor size in leiomyoma without dissemination to other organs. Further evaluation of this localized targeted strategy for gene therapy is needed in appropriate preclinical humanoid animal models in preparation for a future pilot human trial. PMID:26884457

Targeted Adenoviral Vector Demonstrates Enhanced Efficacy for In Vivo Gene Therapy of Uterine Leiomyoma.

PubMed

Abdelaziz, Mohamed; Sherif, Lotfy; ElKhiary, Mostafa; Nair, Sanjeeta; Shalaby, Shahinaz; Mohamed, Sara; Eziba, Noura; El-Lakany, Mohamed; Curiel, David; Ismail, Nahed; Diamond, Michael P; Al-Hendy, Ayman

2016-04-01

Gene therapy is a potentially effective non-surgical approach for the treatment of uterine leiomyoma. We demonstrated that targeted adenovirus vector, Ad-SSTR-RGD-TK/GCV, was highly effective in selectively inducing apoptosis and inhibiting proliferation of human leiomyoma cells in vitro while sparing normal myometrial cells. An in-vivo study, to compare efficacy and safety of modified adenovirus vector Ad-SSTR-RGD-TK/GCV versus untargeted vector for treatment of leiomyoma. Female nude mice were implanted with rat leiomyoma cells subcutaneously. Then mice were randomized into three groups. Group 1 received Ad-LacZ (marker gene), Group 2 received untargeted Ad-TK, and Group 3 received the targeted Ad-SSTR-RGD-TK. Tumors were measured weekly for 4 weeks. Then mice were sacrificed and tissue samples were collected. Evaluation of markers of apoptosis, proliferation, extracellular matrix, and angiogenesis was performed using Western Blot & Immunohistochemistry. Statistical analysis was done using ANOVA. Dissemination of adenovirus was assessed by PCR. In comparison with the untargeted vector, the targeted adenoviral vector significantly shrank leiomyoma size (P < 0.05), reduced expression of proliferation marker (PCNA) (P < 0.05), induced expression of apoptotic protein, c-PARP-1, (P < 0.05) and inhibited expression of extracellular matrix-related genes (TGF beta 3) and angiogenesis-related genes (VEGF & IGF-1) (P < 0.01). There were no detectable adenovirus in tested tissues other than leiomyoma lesions with both targeted and untargeted adenovirus. Targeted adenovirus, effectively reduces tumor size in leiomyoma without dissemination to other organs. Further evaluation of this localized targeted strategy for gene therapy is needed in appropriate preclinical humanoid animal models in preparation for a future pilot human trial. © The Author(s) 2016.

Geographic and ecological features of phlebotomine sand flies (Diptera: Psychodidae) as leishmaniasis in Central Iran.

PubMed

Vatandoost, Hassan; Nejati, Jalil; Saghafipour, Abedin; Zahraei-Ramazani, Alireza

2018-03-01

Phlebotomine sand flies occur throughout the tropics and subtropics, as well as in temperate regions of the world. They are vectors of human and canine leishmaniasis and sand fly fevers caused by phleboviruses. This study was aimed to determine the geographic and ecological characteristics of phlebotomine sand flies as vectors of leishmaniasis and to prepare a checklist of phlebotomine sand flies. The study was conducted in Qom province, central Iran, between April and November 2016. Qom is located in latitude 34.6399°N and longitude 50.8759°E with average annual minimum and maximum temperatures of 16.5 and 49 °C, annual rainfall of 150 mm and relative humidity of 84 and 28%, respectively. Sand flies were collected by sticky paper traps from Qom city and its six districts. The sand flies collected were separated from the sticky paper traps using an insulin syringe and kept in 70% ethanol for species identification using taxonomic keys. Also, a literature review was performed using all published reports on phlebotomine sand flies in this province during 1999-2015. A total of 28,410 sand flies from two genera and 14 species were collected. Phlebotomus papatasi, the main vector of zoonotic cutaneous leishmaniasis and arboviruses, and Phlebotomus sergenti , the vector of anthroponotic cutaneous leishmaniasis, were the predominant species followed by Phlebotomus kandelakii , P. major and P. alexandri . Fourteen species from two genera mostly from wet and mountainous areas were identified in the study area. Kahak and Markazi districts were identified as high-risk foci with numerous leishmaniasis vectors species; we recommend intensifying and strengthening of vector control programme in the area of study.

Irrigation in the arid regions of Tunisia impacts the abundance and apparent density of sand fly vectors of Leishmania infantum

PubMed Central

Barhoumi, Walid; Qualls, Whitney A.; Archer, Reginald; Fuller, Douglas O.; Chelbi, Ifhem; Cherni, Saifedine; Derbali, Mohamed; Arheart, Kristopher L.; Zhioua, Elyes; Beier, John C.

2015-01-01

The distribution expansion of important human visceral leishmaniasis (HVL) and sporadic cutaneous leishmaniasis (SCL) vector species, Phlebotomus perfiliewi and P. perniciosus, throughout central Tunisia is a major public health concern. This study was designed to investigate if the expansion of irrigation influences the abundance of sand fly species potentially involved in the transmission of HVL and SCL located in arid bioclimatic regions. Geographic and remote sensing approaches were used to predict the density of visceral leishmaniasis vectors in Tunisia. Entomological investigations were performed in the governorate of Sidi Bouzid, located in the arid bioclimatic region of Tunisia. In 2012, sand flies were collected by CDC light traps located at nine irrigated and nine non-irrigated sites to determine species abundance. Eight species in two genera were collected. Among sand flies of the subgenus Larroussius, P. perfiliewi was the only species collected significantly more in irrigated areas. Trap data were then used to develop Poisson regression models to map the apparent density of important sand fly species as a function of different environmental covariates including climate and vegetation density. The density of P. perfiliewi is predicted to be moderately high in the arid regions. These results highlight that the abundance of P. perfiliewi is associated with the development of irrigated areas and suggests that the expansion of this species will continue to more arid areas of the country as irrigation sites continue to be developed in the region. The continued increase in irrigated areas in the Middle East and North Africa region deserves attention, as it is associated with the spread of L. infantum vector P. perfiliewi. Integrated vector management strategies targeting irrigation structures to reduce sand fly vector populations should be evaluated in light of these findings. PMID:25447265

Bioengineering a non-genotoxic vector for genetic modification of mesenchymal stem cells.

PubMed

Chen, Xuguang; Nomani, Alireza; Patel, Niket; Nouri, Faranak S; Hatefi, Arash

2018-01-01

Vectors used for stem cell transfection must be non-genotoxic, in addition to possessing high efficiency, because they could potentially transform normal stem cells into cancer-initiating cells. The objective of this research was to bioengineer an efficient vector that can be used for genetic modification of stem cells without any negative somatic or genetic impact. Two types of multifunctional vectors, namely targeted and non-targeted were genetically engineered and purified from E. coli. The targeted vectors were designed to enter stem cells via overexpressed receptors. The non-targeted vectors were equipped with MPG and Pep1 cell penetrating peptides. A series of commercial synthetic non-viral vectors and an adenoviral vector were used as controls. All vectors were evaluated for their efficiency and impact on metabolic activity, cell membrane integrity, chromosomal aberrations (micronuclei formation), gene dysregulation, and differentiation ability of stem cells. The results of this study showed that the bioengineered vector utilizing VEGFR-1 receptors for cellular entry could transfect mesenchymal stem cells with high efficiency without inducing genotoxicity, negative impact on gene function, or ability to differentiate. Overall, the vectors that utilized receptors as ports for cellular entry (viral and non-viral) showed considerably better somato- and genosafety profiles in comparison to those that entered through electrostatic interaction with cellular membrane. The genetically engineered vector in this study demonstrated that it can be safely and efficiently used to genetically modify stem cells with potential applications in tissue engineering and cancer therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Newcastle Disease Virus as a Vaccine Vector for Development of Human and Veterinary Vaccines

PubMed Central

Kim, Shin-Hee; Samal, Siba K.

2016-01-01

Viral vaccine vectors have shown to be effective in inducing a robust immune response against the vaccine antigen. Newcastle disease virus (NDV), an avian paramyxovirus, is a promising vaccine vector against human and veterinary pathogens. Avirulent NDV strains LaSota and B1 have long track records of safety and efficacy. Therefore, use of these strains as vaccine vectors is highly safe in avian and non-avian species. NDV replicates efficiently in the respiratory track of the host and induces strong local and systemic immune responses against the foreign antigen. As a vaccine vector, NDV can accommodate foreign sequences with a good degree of stability and as a RNA virus, there is limited possibility for recombination with host cell DNA. Using NDV as a vaccine vector in humans offers several advantages over other viral vaccine vectors. NDV is safe in humans due to host range restriction and there is no pre-existing antibody to NDV in the human population. NDV is antigenically distinct from common human pathogens. NDV replicates to high titer in a cell line acceptable for human vaccine development. Therefore, NDV is an attractive vaccine vector for human pathogens for which vaccines are currently not available. NDV is also an attractive vaccine vector for animal pathogens. PMID:27384578

Newcastle Disease Virus as a Vaccine Vector for Development of Human and Veterinary Vaccines.

PubMed

Kim, Shin-Hee; Samal, Siba K

2016-07-04

Viral vaccine vectors have shown to be effective in inducing a robust immune response against the vaccine antigen. Newcastle disease virus (NDV), an avian paramyxovirus, is a promising vaccine vector against human and veterinary pathogens. Avirulent NDV strains LaSota and B1 have long track records of safety and efficacy. Therefore, use of these strains as vaccine vectors is highly safe in avian and non-avian species. NDV replicates efficiently in the respiratory track of the host and induces strong local and systemic immune responses against the foreign antigen. As a vaccine vector, NDV can accommodate foreign sequences with a good degree of stability and as a RNA virus, there is limited possibility for recombination with host cell DNA. Using NDV as a vaccine vector in humans offers several advantages over other viral vaccine vectors. NDV is safe in humans due to host range restriction and there is no pre-existing antibody to NDV in the human population. NDV is antigenically distinct from common human pathogens. NDV replicates to high titer in a cell line acceptable for human vaccine development. Therefore, NDV is an attractive vaccine vector for human pathogens for which vaccines are currently not available. NDV is also an attractive vaccine vector for animal pathogens.

Modelling the distributions and spatial coincidence of bluetongue vectors Culicoides imicola and the Culicoides obsoletus group throughout the Iberian peninsula.

PubMed

Calvete, C; Estrada, R; Miranda, M A; Borrás, D; Calvo, J H; Lucientes, J

2008-06-01

Data obtained by a Spanish national surveillance programme in 2005 were used to develop climatic models for predictions of the distribution of the bluetongue virus (BTV) vectors Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and the Culicoides obsoletus group Meigen throughout the Iberian peninsula. Models were generated using logistic regression to predict the probability of species occurrence at an 8-km spatial resolution. Predictor variables included the annual mean values and seasonalities of a remotely sensed normalized difference vegetation index (NDVI), a sun index, interpolated precipitation and temperature. Using an information-theoretic paradigm based on Akaike's criterion, a set of best models accounting for 95% of model selection certainty were selected and used to generate an average predictive model for each vector. The predictive performances (i.e. the discrimination capacity and calibration) of the average models were evaluated by both internal and external validation. External validation was achieved by comparing average model predictions with surveillance programme data obtained in 2004 and 2006. The discriminatory capacity of both models was found to be reasonably high. The estimated areas under the receiver operating characteristic (ROC) curve (AUC) were 0.78 and 0.70 for the C. imicola and C. obsoletus group models, respectively, in external validation, and 0.81 and 0.75, respectively, in internal validation. The predictions of both models were in close agreement with the observed distribution patterns of both vectors. Both models, however, showed a systematic bias in their predicted probability of occurrence: observed occurrence was systematically overestimated for C. imicola and underestimated for the C. obsoletus group. Average models were used to determine the areas of spatial coincidence of the two vectors. Although their spatial distributions were highly complementary, areas of spatial coincidence were identified, mainly in Portugal and in the southwest of peninsular Spain. In a hypothetical scenario in which both Culicoides members had similar vectorial capacity for a BTV strain, these areas should be considered of special epidemiological concern because any epizootic event could be intensified by consecutive vector activity developed for both species during the year; consequently, the probability of BTV spreading to remaining areas occupied by both vectors might also be higher.

A Neuro-Fuzzy Approach in the Classification of Students' Academic Performance

PubMed Central

2013-01-01

Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions. PMID:24302928

A neuro-fuzzy approach in the classification of students' academic performance.

PubMed

Do, Quang Hung; Chen, Jeng-Fung

2013-01-01

Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions.

Transmission of Rift Valley fever virus from European-breed lambs to Culex pipiens mosquitoes.

PubMed

Vloet, Rianka P M; Vogels, Chantal B F; Koenraadt, Constantianus J M; Pijlman, Gorben P; Eiden, Martin; Gonzales, Jose L; van Keulen, Lucien J M; Wichgers Schreur, Paul J; Kortekaas, Jeroen

2017-12-01

Rift Valley fever virus (RVFV) is a mosquito-borne bunyavirus of the genus Phlebovirus that is highly pathogenic to ruminants and humans. The disease is currently confined to Africa and the Arabian Peninsula, but globalization and climate change may facilitate introductions of the virus into currently unaffected areas via infected animals or mosquitoes. The consequences of such an introduction will depend on environmental factors, the availability of susceptible ruminants and the capacity of local mosquitoes to transmit the virus. We have previously demonstrated that lambs native to the Netherlands are highly susceptible to RVFV and we here report the vector competence of Culex (Cx.) pipiens, the most abundant and widespread mosquito species in the country. Vector competence was first determined after artificial blood feeding of laboratory-reared mosquitoes using the attenuated Clone 13 strain. Subsequently, experiments with wild-type RVFV and mosquitoes hatched from field-collected eggs were performed. Finally, the transmission of RVFV from viremic lambs to mosquitoes was studied. Artificial feeding experiments using Clone 13 demonstrated that indigenous, laboratory-reared Cx. pipiens mosquitoes are susceptible to RVFV and that the virus can be transmitted via their saliva. Experiments with wild-type RVFV and mosquitoes hatched from field-collected eggs confirmed the vector competence of Cx. pipiens mosquitoes from the Netherlands. To subsequently investigate transmission of the virus under more natural conditions, mosquitoes were allowed to feed on RVFV-infected lambs during the viremic period. We found that RVFV is efficiently transmitted from lambs to mosquitoes, although transmission was restricted to peak viremia. Interestingly, in the mosquito-exposed skin samples, replication of RVFV was detected in previously unrecognized target cells. We here report the vector competence of Cx. pipiens mosquitoes from the Netherlands for RVFV. Both laboratory-reared mosquitoes and well as those hatched from field-collected eggs were found to be competent vectors. Moreover, RVFV was transmitted efficiently from indigenous lambs to mosquitoes, although the duration of host infectivity was found to be shorter than previously assumed. Interestingly, analysis of mosquito-exposed skin samples revealed previously unidentified target cells of the virus. Our findings underscore the value of including natural target species in vector competence experiments.

Progressive Classification Using Support Vector Machines

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; Kocurek, Michael

2009-01-01

An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user can halt this reclassification process at any point, thereby obtaining the best possible result for a given amount of computation time. Alternatively, the results can be displayed as they are generated, providing the user with real-time feedback about the current accuracy of classification.

Soft-contact conductive carbon enabling depolarization of LiFePO4 cathodes to enhance both capacity and rate performances of lithium ion batteries

NASA Astrophysics Data System (ADS)

Ren, Wenju; Wang, Kai; Yang, Jinlong; Tan, Rui; Hu, Jiangtao; Guo, Hua; Duan, Yandong; Zheng, Jiaxin; Lin, Yuan; Pan, Feng

2016-11-01

Conductive nanocarbons generally are used as the electronic conductive additives to contact with active materials to generate conductive network for electrodes of commercial Li-ion batteries (LIBs). A typical of LiFePO4 (LFP), which has been widely used as cathode material for LIBs with low electronic conductivity, needs higher quantity of conductive nanocarbons to enhance the performance for cathode electrodes. In this work, we systematically studied three types of conductive nanocarbons and related performances in the LFP electrodes, and classify them as hard/soft-contact conductive carbon (named as H/SCC), respectively, according to their crystallite size, surface graphite-defect, specific surface area and porous structure, in which SCC can generate much larger contact area with active nano-particles of cathode materials than that of HCC. It is found that LFP nanocrystals wrapped in SCC networks perform significantly enhanced both capacity and rate performance than that in HCC. Combined experiments with multiphysics simulation, the mechanism is that LFP nanoparticles embedded in SCC with large contact area enable to generate higher depolarized effects with a relatively uniform current density vector (is) and lithium flux vector (NLi) than that in HCC. This discovery will guide us to how to design LIBs by selective using conductive carbon for high-performance LIBs.

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

PubMed Central

Tian, Yin; Zhang, Huiling; Xu, Wei; Zhang, Haiyong; Yang, Li; Zheng, Shuxing; Shi, Yupan

2017-01-01

Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed Residual Time (SRT) scores based on response speed and accuracy trade-off, 20 subjects were divided into two groups, namely high-performance and low-performance groups, to undertake working memory (WM) tasks. We found that spectral entropy derived from the retention period of WM on channel FC4 exhibited a high correlation with SRT scores. To this end, spectral entropy was used in support vector machine classifier with linear kernel to differentiate these two groups. Receiver operating characteristics analysis and leave-one out cross-validation (LOOCV) demonstrated that the averaged classification accuracy (CA) was 90.0 and 92.5% for intra-session and inter-session, respectively, indicating that spectral entropy could be used to distinguish these two different WM performance groups successfully. Furthermore, the support vector regression prediction model with radial basis function kernel and the root-mean-square error of prediction revealed that spectral entropy could be utilized to predict SRT scores on individual WM performance. After testing the changes in SRT scores and spectral entropy for each subject by short-time training, we found that 16 in 20 subjects’ SRT scores were clearly promoted after training and 15 in 20 subjects’ SRT scores showed consistent changes with spectral entropy before and after training. The findings revealed that spectral entropy could be a promising indicator to predict individual’s WM changes by training and further provide a novel application about WM for brain–computer interfaces. PMID:28912701

Data-Rate Performance and Coverage of the Sub-Band Vectoring for VDSL 35b Profile

NASA Astrophysics Data System (ADS)

Giuliano, Romeo; Mazzenga, Franco; Vatalaro, Francesco

2017-05-01

Vectoring, used in VDSL2 to counteract FEXT, becomes less effective, or even ineffective, when users belong to different vectoring groups. This situation is common when the Regulator imposes sub-loop unbundling and users of uncoordinated service providers cause alien-FEXT. The sub-band vectoring (SBV) technique introduced here, avoids this situation and retains the vectoring benefits. We show SBV allows achieving up to 150 Mbit/s per user in downstream at 200 m from cabinet for VDSL2 profile-35b, with two concurrent service providers. We also introduce the concept of data-rate coverage representing the users' percentage served at a given data-rate in the area.

A Two-Layer Least Squares Support Vector Machine Approach to Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Liu, Jingli; Li, Jianping; Xu, Weixuan; Shi, Yong

Least squares support vector machine (LS-SVM) is a revised version of support vector machine (SVM) and has been proved to be a useful tool for pattern recognition. LS-SVM had excellent generalization performance and low computational cost. In this paper, we propose a new method called two-layer least squares support vector machine which combines kernel principle component analysis (KPCA) and linear programming form of least square support vector machine. With this method sparseness and robustness is obtained while solving large dimensional and large scale database. A U.S. commercial credit card database is used to test the efficiency of our method and the result proved to be a satisfactory one.

A Real-Time Phase Vector Display for EEG Monitoring

NASA Technical Reports Server (NTRS)

Finger, Herbert J.; Anliker, James E.; Rimmer, Tamara

1973-01-01

A real-time, computer-based, phase vector display system has been developed which will output a vector whose phase is equal to the delay between a trigger and the peak of a function which is quasi-coherent with respect to the trigger. The system also contains a sliding averager which enables the operator to average successive trials before calculating the phase vector. Data collection, averaging and display generation are performed on a LINC-8 computer. Output displays appear on several X-Y CRT display units and on a kymograph camera/oscilloscope unit which is used to generate photographs of time-varying phase vectors or contourograms of time-varying averages of input functions.

Singer product apertures-A coded aperture system with a fast decoding algorithm

NASA Astrophysics Data System (ADS)

Byard, Kevin; Shutler, Paul M. E.

2017-06-01

A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.

Production of first generation adenoviral vectors for preclinical protocols: amplification, purification and functional titration.

PubMed

Armendáriz-Borunda, Juan; Bastidas-Ramírez, Blanca Estela; Sandoval-Rodríguez, Ana; González-Cuevas, Jaime; Gómez-Meda, Belinda; García-Bañuelos, Jesús

2011-11-01

Gene therapy represents a promising approach in the treatment of several diseases. Currently, the ideal vector has yet to be designed; though, adenoviral vectors (Ad-v) have provided the most utilized tool for gene transfer due principally to their simple production, among other specific characteristics. Ad-v viability represents a critical variable that may be affected by storage or shipping conditions and therefore it is advisable to be assessed previously to protocol performance. The present work is unique in this matter, as the complete detailed process to obtain Ad-v of preclinical grade is explained. Amplification in permissive HEK-293 cells, purification in CsCl gradients in a period of 10 h, spectrophotometric titration of viral particles (VP) and titration of infectious units (IU), yielding batches of AdβGal, AdGFP, AdHuPA and AdMMP8, of approximately 10¹³-10¹⁴ VP and 10¹²-10¹³ IU were carried out. In vivo functionality of therapeutic AdHuPA and AdMMP8 was evidenced in rats presenting CCl₄-induced fibrosis, as more than 60% of fibrosis was eliminated in livers after systemic delivery through iliac vein in comparison with irrelevant AdβGal. Time required to accomplish the whole Ad-v production steps, including IU titration was 20 to 30 days. We conclude that production of Ad-v following standard operating procedures assuring vector functionality and the possibility to effectively evaluate experimental gene therapy results, leaving aside the use of high-cost commercial kits or sophisticated instrumentation, can be performed in a conventional laboratory of cell culture. Copyright © 2011 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Reflectance Prediction Modelling for Residual-Based Hyperspectral Image Coding

PubMed Central

Xiao, Rui; Gao, Junbin; Bossomaier, Terry

2016-01-01

A Hyperspectral (HS) image provides observational powers beyond human vision capability but represents more than 100 times the data compared to a traditional image. To transmit and store the huge volume of an HS image, we argue that a fundamental shift is required from the existing “original pixel intensity”-based coding approaches using traditional image coders (e.g., JPEG2000) to the “residual”-based approaches using a video coder for better compression performance. A modified video coder is required to exploit spatial-spectral redundancy using pixel-level reflectance modelling due to the different characteristics of HS images in their spectral and shape domain of panchromatic imagery compared to traditional videos. In this paper a novel coding framework using Reflectance Prediction Modelling (RPM) in the latest video coding standard High Efficiency Video Coding (HEVC) for HS images is proposed. An HS image presents a wealth of data where every pixel is considered a vector for different spectral bands. By quantitative comparison and analysis of pixel vector distribution along spectral bands, we conclude that modelling can predict the distribution and correlation of the pixel vectors for different bands. To exploit distribution of the known pixel vector, we estimate a predicted current spectral band from the previous bands using Gaussian mixture-based modelling. The predicted band is used as the additional reference band together with the immediate previous band when we apply the HEVC. Every spectral band of an HS image is treated like it is an individual frame of a video. In this paper, we compare the proposed method with mainstream encoders. The experimental results are fully justified by three types of HS dataset with different wavelength ranges. The proposed method outperforms the existing mainstream HS encoders in terms of rate-distortion performance of HS image compression. PMID:27695102

Detection of anomaly in human retina using Laplacian Eigenmaps and vectorized matched filtering

NASA Astrophysics Data System (ADS)

Yacoubou Djima, Karamatou A.; Simonelli, Lucia D.; Cunningham, Denise; Czaja, Wojciech

2015-03-01

We present a novel method for automated anomaly detection on auto fluorescent data provided by the National Institute of Health (NIH). This is motivated by the need for new tools to improve the capability of diagnosing macular degeneration in its early stages, track the progression over time, and test the effectiveness of new treatment methods. In previous work, macular anomalies have been detected automatically through multiscale analysis procedures such as wavelet analysis or dimensionality reduction algorithms followed by a classification algorithm, e.g., Support Vector Machine. The method that we propose is a Vectorized Matched Filtering (VMF) algorithm combined with Laplacian Eigenmaps (LE), a nonlinear dimensionality reduction algorithm with locality preserving properties. By applying LE, we are able to represent the data in the form of eigenimages, some of which accentuate the visibility of anomalies. We pick significant eigenimages and proceed with the VMF algorithm that classifies anomalies across all of these eigenimages simultaneously. To evaluate our performance, we compare our method to two other schemes: a matched filtering algorithm based on anomaly detection on single images and a combination of PCA and VMF. LE combined with VMF algorithm performs best, yielding a high rate of accurate anomaly detection. This shows the advantage of using a nonlinear approach to represent the data and the effectiveness of VMF, which operates on the images as a data cube rather than individual images.

Factors Related to Aedes aegypti (Diptera: Culicidae) Populations and Temperature Determine Differences on Life-History Traits With Regional Implications in Disease Transmission.

PubMed

Muttis, Evangelina; Balsalobre, Agustin; Chuchuy, Ailen; Mangudo, Carolina; Ciota, Alexander T; Kramer, Laura D; Micieli, María Victoria

2018-04-11

Aedes aegypti (L.) (Diptera: Culicidae) is a vector of many medically significant viruses in the Americas, including dengue virus, chikungunya virus, and Zika virus. Traits such as longevity, fecundity, and feeding behavior contribute to the ability of Ae. aegypti to serve as a vector of these pathogens. Both local environmental factors and population genetics could contribute to variability in these traits. We performed a comparative study of Ae. aegypti populations from four geographically and environmentally distinct collection sites in Argentina in which the cohorts from each population were held at temperature values simulating a daily cycle, with an average of 25°C in order to identify the influence of population on life-history traits. In addition, we performed the study of the same populations held at a daily temperature cycle similar to that of the surveyed areas. According to the results, Aguaray is the most outstanding population, showing features that are important to achieve high fitness. Whereas La Plata gathers features consistent with low fitness. Iguazu was outstanding in blood-feeding rate while Posadas's population showed intermediate values. Our results also demonstrate that climate change could differentially affect unique populations, and that these differences have implications for the capacity for Ae. aegypti to act as vectors for medically important arboviruses.

Analysis of superconducting electromagnetic finite elements based on a magnetic vector potential variational principle

NASA Technical Reports Server (NTRS)

Schuler, James J.; Felippa, Carlos A.

1991-01-01

Electromagnetic finite elements are extended based on a variational principle that uses the electromagnetic four potential as primary variable. The variational principle is extended to include the ability to predict a nonlinear current distribution within a conductor. The extension of this theory is first done on a normal conductor and tested on two different problems. In both problems, the geometry remains the same, but the material properties are different. The geometry is that of a 1-D infinite wire. The first problem is merely a linear control case used to validate the new theory. The second problem is made up of linear conductors with varying conductivities. Both problems perform well and predict current densities that are accurate to within a few ten thousandths of a percent of the exact values. The fourth potential is then removed, leaving only the magnetic vector potential, and the variational principle is further extended to predict magnetic potentials, magnetic fields, the number of charge carriers, and the current densities within a superconductor. The new element produces good results for the mean magnetic field, the vector potential, and the number of superconducting charge carriers despite a relatively high system condition number. The element did not perform well in predicting the current density. Numerical problems inherent to this formulation are explored and possible remedies to produce better current predicting finite elements are presented.

T-ray relevant frequencies for osteosarcoma classification

NASA Astrophysics Data System (ADS)

Withayachumnankul, W.; Ferguson, B.; Rainsford, T.; Findlay, D.; Mickan, S. P.; Abbott, D.

2006-01-01

We investigate the classification of the T-ray response of normal human bone cells and human osteosarcoma cells, grown in culture. Given the magnitude and phase responses within a reliable spectral range as features for input vectors, a trained support vector machine can correctly classify the two cell types to some extent. Performance of the support vector machine is deteriorated by the curse of dimensionality, resulting from the comparatively large number of features in the input vectors. Feature subset selection methods are used to select only an optimal number of relevant features for inputs. As a result, an improvement in generalization performance is attainable, and the selected frequencies can be used for further describing different mechanisms of the cells, responding to T-rays. We demonstrate a consistent classification accuracy of 89.6%, while the only one fifth of the original features are retained in the data set.

[Transposition errors during learning to reproduce a sequence by the right- and the left-hand movements: simulation of positional and movement coding].

PubMed

Liakhovetskiĭ, V A; Bobrova, E V; Skopin, G N

2012-01-01

Transposition errors during the reproduction of a hand movement sequence make it possible to receive important information on the internal representation of this sequence in the motor working memory. Analysis of such errors showed that learning to reproduce sequences of the left-hand movements improves the system of positional coding (coding ofpositions), while learning of the right-hand movements improves the system of vector coding (coding of movements). Learning of the right-hand movements after the left-hand performance involved the system of positional coding "imposed" by the left hand. Learning of the left-hand movements after the right-hand performance activated the system of vector coding. Transposition errors during learning to reproduce movement sequences can be explained by neural network using either vector coding or both vector and positional coding.

Signal processing applications of massively parallel charge domain computing devices

NASA Technical Reports Server (NTRS)

Fijany, Amir (Inventor); Barhen, Jacob (Inventor); Toomarian, Nikzad (Inventor)

1999-01-01

The present invention is embodied in a charge coupled device (CCD)/charge injection device (CID) architecture capable of performing a Fourier transform by simultaneous matrix vector multiplication (MVM) operations in respective plural CCD/CID arrays in parallel in O(1) steps. For example, in one embodiment, a first CCD/CID array stores charge packets representing a first matrix operator based upon permutations of a Hartley transform and computes the Fourier transform of an incoming vector. A second CCD/CID array stores charge packets representing a second matrix operator based upon different permutations of a Hartley transform and computes the Fourier transform of an incoming vector. The incoming vector is applied to the inputs of the two CCD/CID arrays simultaneously, and the real and imaginary parts of the Fourier transform are produced simultaneously in the time required to perform a single MVM operation in a CCD/CID array.

Adaptive proxy map server for efficient vector spatial data rendering

NASA Astrophysics Data System (ADS)

Sayar, Ahmet

2013-01-01

The rapid transmission of vector map data over the Internet is becoming a bottleneck of spatial data delivery and visualization in web-based environment because of increasing data amount and limited network bandwidth. In order to improve both the transmission and rendering performances of vector spatial data over the Internet, we propose a proxy map server enabling parallel vector data fetching as well as caching to improve the performance of web-based map servers in a dynamic environment. Proxy map server is placed seamlessly anywhere between the client and the final services, intercepting users' requests. It employs an efficient parallelization technique based on spatial proximity and data density in case distributed replica exists for the same spatial data. The effectiveness of the proposed technique is proved at the end of the article by the application of creating map images enriched with earthquake seismic data records.

A Fast Reduced Kernel Extreme Learning Machine.

PubMed

Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

2016-04-01

In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

PubMed Central

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-01-01

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequency-domain and achieves computational complexity reduction. PMID:28230763

Angular velocity estimation based on star vector with improved current statistical model Kalman filter.

PubMed

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Zhang, He

2016-11-20

Angular velocity information is a requisite for a spacecraft guidance, navigation, and control system. In this paper, an approach for angular velocity estimation based merely on star vector measurement with an improved current statistical model Kalman filter is proposed. High-precision angular velocity estimation can be achieved under dynamic conditions. The amount of calculation is also reduced compared to a Kalman filter. Different trajectories are simulated to test this approach, and experiments with real starry sky observation are implemented for further confirmation. The estimation accuracy is proved to be better than 10^-4  rad/s under various conditions. Both the simulation and the experiment demonstrate that the described approach is effective and shows an excellent performance under both static and dynamic conditions.

Sound Processing Features for Speaker-Dependent and Phrase-Independent Emotion Recognition in Berlin Database

NASA Astrophysics Data System (ADS)

Anagnostopoulos, Christos Nikolaos; Vovoli, Eftichia

An emotion recognition framework based on sound processing could improve services in human-computer interaction. Various quantitative speech features obtained from sound processing of acting speech were tested, as to whether they are sufficient or not to discriminate between seven emotions. Multilayered perceptrons were trained to classify gender and emotions on the basis of a 24-input vector, which provide information about the prosody of the speaker over the entire sentence using statistics of sound features. Several experiments were performed and the results were presented analytically. Emotion recognition was successful when speakers and utterances were “known” to the classifier. However, severe misclassifications occurred during the utterance-independent framework. At least, the proposed feature vector achieved promising results for utterance-independent recognition of high- and low-arousal emotions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dayman, Ken J; Ade, Brian J; Weber, Charles F

High-dimensional, nonlinear function estimation using large datasets is a current area of interest in the machine learning community, and applications may be found throughout the analytical sciences, where ever-growing datasets are making more information available to the analyst. In this paper, we leverage the existing relevance vector machine, a sparse Bayesian version of the well-studied support vector machine, and expand the method to include integrated feature selection and automatic function shaping. These innovations produce an algorithm that is able to distinguish variables that are useful for making predictions of a response from variables that are unrelated or confusing. We testmore » the technology using synthetic data, conduct initial performance studies, and develop a model capable of making position-independent predictions of the coreaveraged burnup using a single specimen drawn randomly from a nuclear reactor core.« less

High-performance Chinese multiclass traffic sign detection via coarse-to-fine cascade and parallel support vector machine detectors

NASA Astrophysics Data System (ADS)

Chang, Faliang; Liu, Chunsheng

2017-09-01

The high variability of sign colors and shapes in uncontrolled environments has made the detection of traffic signs a challenging problem in computer vision. We propose a traffic sign detection (TSD) method based on coarse-to-fine cascade and parallel support vector machine (SVM) detectors to detect Chinese warning and danger traffic signs. First, a region of interest (ROI) extraction method is proposed to extract ROIs using color contrast features in local regions. The ROI extraction can reduce scanning regions and save detection time. For multiclass TSD, we propose a structure that combines a coarse-to-fine cascaded tree with a parallel structure of histogram of oriented gradients (HOG) + SVM detectors. The cascaded tree is designed to detect different types of traffic signs in a coarse-to-fine process. The parallel HOG + SVM detectors are designed to do fine detection of different types of traffic signs. The experiments demonstrate the proposed TSD method can rapidly detect multiclass traffic signs with different colors and shapes in high accuracy.

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Huaiguang

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 themore » 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.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, David H.

The NAS Parallel Benchmarks (NPB) are a suite of parallel computer performance benchmarks. They were originally developed at the NASA Ames Research Center in 1991 to assess high-end parallel supercomputers. Although they are no longer used as widely as they once were for comparing high-end system performance, they continue to be studied and analyzed a great deal in the high-performance computing community. The acronym 'NAS' originally stood for the Numerical Aeronautical Simulation Program at NASA Ames. The name of this organization was subsequently changed to the Numerical Aerospace Simulation Program, and more recently to the NASA Advanced Supercomputing Center, althoughmore » the acronym remains 'NAS.' The developers of the original NPB suite were David H. Bailey, Eric Barszcz, John Barton, David Browning, Russell Carter, LeoDagum, Rod Fatoohi, Samuel Fineberg, Paul Frederickson, Thomas Lasinski, Rob Schreiber, Horst Simon, V. Venkatakrishnan and Sisira Weeratunga. The original NAS Parallel Benchmarks consisted of eight individual benchmark problems, each of which focused on some aspect of scientific computing. The principal focus was in computational aerophysics, although most of these benchmarks have much broader relevance, since in a much larger sense they are typical of many real-world scientific computing applications. The NPB suite grew out of the need for a more rational procedure to select new supercomputers for acquisition by NASA. The emergence of commercially available highly parallel computer systems in the late 1980s offered an attractive alternative to parallel vector supercomputers that had been the mainstay of high-end scientific computing. However, the introduction of highly parallel systems was accompanied by a regrettable level of hype, not only on the part of the commercial vendors but even, in some cases, by scientists using the systems. As a result, it was difficult to discern whether the new systems offered any fundamental performance advantage over vector supercomputers, and, if so, which of the parallel offerings would be most useful in real-world scientific computation. In part to draw attention to some of the performance reporting abuses prevalent at the time, the present author wrote a humorous essay 'Twelve Ways to Fool the Masses,' which described in a light-hearted way a number of the questionable ways in which both vendor marketing people and scientists were inflating and distorting their performance results. All of this underscored the need for an objective and scientifically defensible measure to compare performance on these systems.« less

1988 IEEE Aerospace Applications Conference, Park City, UT, Feb. 7-12, 1988, Digest

NASA Astrophysics Data System (ADS)

The conference presents papers on microwave applications, data and signal processing applications, related aerospace applications, and advanced microelectronic products for the aerospace industry. Topics include a high-performance antenna measurement system, microwave power beaming from earth to space, the digital enhancement of microwave component performance, and a GaAs vector processor based on parallel RISC microprocessors. Consideration is also given to unique techniques for reliable SBNR architectures, a linear analysis subsystem for CSSL-IV, and a structured singular value approach to missile autopilot analysis.

sw-SVM: sensor weighting support vector machines for EEG-based brain-computer interfaces.

PubMed

Jrad, N; Congedo, M; Phlypo, R; Rousseau, S; Flamary, R; Yger, F; Rakotomamonjy, A

2011-10-01

In many machine learning applications, like brain-computer interfaces (BCI), high-dimensional sensor array data are available. Sensor measurements are often highly correlated and signal-to-noise ratio is not homogeneously spread across sensors. Thus, collected data are highly variable and discrimination tasks are challenging. In this work, we focus on sensor weighting as an efficient tool to improve the classification procedure. We present an approach integrating sensor weighting in the classification framework. Sensor weights are considered as hyper-parameters to be learned by a support vector machine (SVM). The resulting sensor weighting SVM (sw-SVM) is designed to satisfy a margin criterion, that is, the generalization error. Experimental studies on two data sets are presented, a P300 data set and an error-related potential (ErrP) data set. For the P300 data set (BCI competition III), for which a large number of trials is available, the sw-SVM proves to perform equivalently with respect to the ensemble SVM strategy that won the competition. For the ErrP data set, for which a small number of trials are available, the sw-SVM shows superior performances as compared to three state-of-the art approaches. Results suggest that the sw-SVM promises to be useful in event-related potentials classification, even with a small number of training trials.

An experimental investigation of thrust vectoring two-dimensional convergent-divergent nozzles installed in a twin-engine fighter model at high angles of attack

NASA Technical Reports Server (NTRS)

Capone, Francis J.; Mason, Mary L.; Leavitt, Laurence D.

1990-01-01

An investigation was conducted in the Langley 16-Foot Transonic Tunnel to determine thrust vectoring capability of subscale 2-D convergent-divergent exhaust nozzles installed on a twin engine general research fighter model. Pitch thrust vectoring was accomplished by downward rotation of nozzle upper and lower flaps. The effects of nozzle sidewall cutback were studied for both unvectored and pitch vectored nozzles. A single cutback sidewall was employed for yaw thrust vectoring. This investigation was conducted at Mach numbers ranging from 0 to 1.20 and at angles of attack from -2 to 35 deg. High pressure air was used to simulate jet exhaust and provide values of nozzle pressure ratio up to 9.

Reflections on the early development of poxvirus vectors.

PubMed

Moss, Bernard

2013-09-06

Poxvirus expression vectors were described in 1982 and quickly became widely used for vaccine development as well as research in numerous fields. Advantages of the vectors include simple construction, ability to accommodate large amounts of foreign DNA and high expression levels. Numerous poxvirus-based veterinary vaccines are currently in use and many others are in human clinical trials. The early reports of poxvirus vectors paved the way for and stimulated the development of other viral vectors and recombinant DNA vaccines. Published by Elsevier Ltd.

Vectorized algorithms for spiking neural network simulation.

PubMed

Brette, Romain; Goodman, Dan F M

2011-06-01

High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.

Measurement of surface shear stress vector beneath high-speed jet flow using liquid crystal coating

NASA Astrophysics Data System (ADS)

Wang, Cheng-Peng; Zhao, Ji-Song; Jiao, Yun; Cheng, Ke-Ming

2018-05-01

The shear-sensitive liquid crystal coating (SSLCC) technique is investigated in the high-speed jet flow of a micro-wind-tunnel. An approach to measure surface shear stress vector distribution using the SSLCC technique is established, where six synchronous cameras are used to record the coating color at different circumferential view angles. Spatial wall shear stress vector distributions on the test surface are obtained at different velocities. The results are encouraging and demonstrate the great potential of the SSLCC technique in high-speed wind-tunnel measurement.

Estimation of attitude sensor timetag biases

NASA Technical Reports Server (NTRS)

Sedlak, J.

1995-01-01

This paper presents an extended Kalman filter for estimating attitude sensor timing errors. Spacecraft attitude is determined by finding the mean rotation from a set of reference vectors in inertial space to the corresponding observed vectors in the body frame. Any timing errors in the observations can lead to attitude errors if either the spacecraft is rotating or the reference vectors themselves vary with time. The state vector here consists of the attitude quaternion, timetag biases, and, optionally, gyro drift rate biases. The filter models the timetags as random walk processes: their expectation values propagate as constants and white noise contributes to their covariance. Thus, this filter is applicable to cases where the true timing errors are constant or slowly varying. The observability of the state vector is studied first through an examination of the algebraic observability condition and then through several examples with simulated star tracker timing errors. The examples use both simulated and actual flight data from the Extreme Ultraviolet Explorer (EUVE). The flight data come from times when EUVE had a constant rotation rate, while the simulated data feature large angle attitude maneuvers. The tests include cases with timetag errors on one or two sensors, both constant and time-varying, and with and without gyro bias errors. Due to EUVE's sensor geometry, the observability of the state vector is severely limited when the spacecraft rotation rate is constant. In the absence of attitude maneuvers, the state elements are highly correlated, and the state estimate is unreliable. The estimates are particularly sensitive to filter mistuning in this case. The EUVE geometry, though, is a degenerate case having coplanar sensors and rotation vector. Observability is much improved and the filter performs well when the rate is either varying or noncoplanar with the sensors, as during a slew. Even with bad geometry and constant rates, if gyro biases are independently known, the timetag error for a single sensor can be accurately estimated as long as its boresight is not too close to the spacecraft rotation axis.

Deletion of Specific Immune-Modulatory Genes from Modified Vaccinia Virus Ankara-Based HIV Vaccines Engenders Improved Immunogenicity in Rhesus Macaques

PubMed Central

O'Mara, Leigh A.; Gangadhara, Sailaja; McQuoid, Monica; Zhang, Xiugen; Zheng, Rui; Gill, Kiran; Verma, Meena; Yu, Tianwei; Johnson, Brent; Li, Bing; Derdeyn, Cynthia A.; Ibegbu, Chris; Altman, John D.; Hunter, Eric; Feinberg, Mark B.

2012-01-01

Modified vaccinia virus Ankara (MVA) is a safe, attenuated orthopoxvirus that is being developed as a vaccine vector but has demonstrated limited immunogenicity in several early-phase clinical trials. Our objective was to rationally improve the immunogenicity of MVA-based HIV/AIDS vaccines via the targeted deletion of specific poxvirus immune-modulatory genes. Vaccines expressing codon-optimized HIV subtype C consensus Env and Gag antigens were generated from MVA vector backbones that (i) harbor simultaneous deletions of four viral immune-modulatory genes, encoding an interleukin-18 (IL-18) binding protein, an IL-1β receptor, a dominant negative Toll/IL-1 signaling adapter, and CC-chemokine binding protein (MVAΔ4-HIV); (ii) harbor a deletion of an additional (fifth) viral gene, encoding uracil-DNA glycosylase (MVAΔ5-HIV); or (iii) represent the parental MVA backbone as a control (MVA-HIV). We performed head-to-head comparisons of the cellular and humoral immune responses that were elicited by these vectors during homologous prime-boost immunization regimens utilizing either high-dose (2 × 108 PFU) or low-dose (1 × 107 PFU) intramuscular immunization of rhesus macaques. At all time points, a majority of the HIV-specific T cell responses, elicited by all vectors, were directed against Env, rather than Gag, determinants, as previously observed with other vector systems. Both modified vectors elicited up to 6-fold-higher frequencies of HIV-specific CD8 and CD4 T cell responses and up to 25-fold-higher titers of Env (gp120)-specific binding (nonneutralizing) antibody responses that were relatively transient in nature. While the correlates of protection against HIV infection remain incompletely defined, our results indicate that the rational deletion of specific genes from MVA vectors can positively alter their cellular and humoral immunogenicity profiles in nonhuman primates. PMID:22973033

Vector flow mapping in obstructive hypertrophic cardiomyopathy to assess the relationship of early systolic left ventricular flow and the mitral valve.

PubMed

Ro, Richard; Halpern, Dan; Sahn, David J; Homel, Peter; Arabadjian, Milla; Lopresto, Charles; Sherrid, Mark V

2014-11-11

The hydrodynamic cause of systolic anterior motion of the mitral valve (SAM) is unresolved. This study hypothesized that echocardiographic vector flow mapping, a new echocardiographic technique, would provide insights into the cause of early SAM in obstructive hypertrophic cardiomyopathy (HCM). We analyzed the spatial relationship of left ventricular (LV) flow and the mitral valve leaflets (MVL) on 3-chamber vector flow mapping frames, and performed mitral valve measurements on 2-dimensional frames in patients with obstructive and nonobstructive HCM and in normal patients. We compared 82 patients (22 obstructive HCM, 23 nonobstructive HCM, and 37 normal) by measuring 164 LV pre- and post-SAM velocity vector flow maps, 82 maximum isovolumic vortices, and 328 2-dimensional frames. We observed color flow and velocity vector flow posterior to the MVL impacting them in the early systolic frames of 95% of obstructive HCM, 22% of nonobstructive HCM, and 11% of normal patients (p < 0.001). In both pre- and post-SAM frames, we measured a high angle of attack >60° of local vector flow onto the posterior surface of the leaflets whether the flow was ejection (59%) or the early systolic isovolumic vortex (41%). Ricochet of vector flow, rebounding off the leaflet into the cul-de-sac, was noted in 82% of the obstructed HCM, 9% of nonobstructive HCM, and none (0%) of the control patients (p < 0.001). Flow velocities in the LV outflow tract on the pre-SAM frame 1 and 2 mm from the tip of the anterior leaflet were low: 39 and 43 cm/s, respectively. Early systolic flow impacts the posterior surfaces of protruding MVL initiating SAM in obstructive HCM. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.